FLUOROCARBONS AND HUMAN HEALTH:
STUDIES IN AN OCCUPATIONAL COHORT

A THESIS
SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL
OF THE UNIVERSITYY OF MINNESOTA

FRANK DAVIS GILLILAND

lN' PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE OF
DOCTOR OF PHILOSOPHYIENVIRONMENTAL HEALTH

OCTOBER, 1992



ACKNOWLEDGEMENTS

I am indebted to Dr. Jack Mandel whose competent research and career
advice were Invaluable. Not only did Dr Mandel guide me to this research
project: he directed me to the occupational medicine fellowship that
has enriched my clinical medicine knowledge and supported my research
efforts over the last three years. His generosity with his time and patience are
deeply appreciated. Dr. Timothy Church. Dr. William Toscano. Dr. ian
Greaves, and Dr. Thomas Sellers served on my committee. They deserve a
special thanks for their efforts.

i wish to thank the Division of Environmental and Occupational Health at the
University of Minnesota and the Occupational Medicine Section at St. Paul
Ramsey Medical Center for the superb training opportunities I have had over
the past three years. Dr. William bohman. Dr. Samuel Hall. and Paula Geiger
at St. Paul Ramsey Medical Center provided much appreciated support during
the arduous task of residency and dbctoral training. Several members of the
Division of Environmental and Occupational health staff were instrumental in
the successful completion of this research effort. Sarah Wolgamot and
Maralyn Zappia provided excellent administrative support. Gavin Watt. Mindy
Geisser. Richard Hoffbeck. and other members of Colon Cancer Control Study
provided outstanding computer and statistical support.

Dr. Larry Zobel and Dr. Jeffrey Mandel of the 3M Corporation's Medical
Department provided advice and support. Their help was an essential
element in the success of this project. Stan Sorenson. Dr. Roger Perkins. and
other 3M Medical Department members shared their invaluable experience
and knowledge. I would also like to acknowledge the support of the Dow
Chemical Corporation over the last two years of my training.

Last. but not least. this work could not have been accomplished without the

loving support of Susan, my wife. Her understanding and excellent editorial
comments are greatiy appreciated. 



ABSTRACT

Per?uorooctanoic acid (PFOA) has been reported to be a nongenotoxic
hepatocarcinogen and reproductive hormonal toxin in rats. Although PFOA is
the major component of total ?uorine in humans. little information is available
concerning human toxicities. The health effects of PFOA were assessed in two
studies conducted in occupationally exposed workers. The associations
between PFOA and reproduc?ve hormones. hepatic enzymes, lipoproteins.
hematology parameters, and leukocyte counts were studied int 15 male
employees. Serum PFOA was positively associated with estradiol and
negatively associated with free testosterone (TF) but was not signi?cantly
associated with luteinizing hormone. The negative association between TF and
PFOA was stronger in older men. Thyroid stimulating hormone and PFOA were
positively associated. PFOA and prolactln were positively associated in
moderate drinkers. The effect of adiposity on serum glutamyi oxaloacetic and
glutamyl pyluvic transaminase decreased as PFOA increased. The induction of
gamma glutamyl transferase by alcohol was decreased as PFOA increased.
The effect of alcohol on HDL was reduced as PFOA increased. A positive
association between hemoglobin. mean cellular volume. and leukocyte counts
with PFOA was observed. These results suggest that PFOA affects mas
reproductive hormones and that the liver is not a signi?cant site of toxicity in
humans at the PFOA levels observed in this study. However, PFOA appears to
modify hepatic and immune responses to xenobiotics. A retrospective cohort
mortality study of 2788 male and 749 females workers employed between
1947-1984 at a PFOA production plant was conducted. Overall, there were no
sig increased cause speci?c Among men. ten years of
employment in PFOA production was associated with a significant three fold
increase in prostate cancer mortality compared to no employment in production.
Given the small number of prostate cancer deaths and the natural history of the
disease, the association between production work and prost?e cancer must be
viewed as hypothesis generating and should not be over interpreted. It the
prostate cancer mortality excess is related to PFOA, the results of the two
studies suggest that PFOA may increase prostate cancer mortality through
endocrine alterations.



 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1. INTRODUCTION - 1
2. REVIEW OF THE LITERATURE 4
2.1 Introduction - - 
2 Organic Fluorochemicals .- 4
2. 3 Physical Properties -- Sources 01 Organm Fluoride Exposure 8
2. 6 Toxiooklnetios oi PFOA 11
2.7 'l'oximdynamlcs ot PFOA -- 16
2.7.1 Mala Reproductive Toxidties 16
2.7.2 Female Reproductive Toxicities 20
2. 7. 3 Thyroid Toxicities 20

2. 7.4 Hepatic Toxiclties 21
2. 7. 5 Nongenotoxic Carcinogenesis - 23
2. 7. 6 lmmunotoxicity -- 
2.7.7 Mechanisms of Action -- - 24
2.8 Occupational Fluorine Exposures At Chernolite- 26
2.9 Epidemiological Studies 
2.10 Summary -. -28
3. METHODS 29
3.1 Introduction - 29
3. 2 Retrospective Cohort Modality -- 30
3.2.1 Definition Of The Cohort - - 30

3. 2.2 Study Databases And 31

3.2.3 Data Editing 31
3.2.4 Validation Of The Historical Cohort Information 32

3.2.4.1 Assessment 01 Completeness Oi

Ascertainrnent 32

3.2.4.2 Validation OI Cohort information 33

3. 2.5 Vital Status Ascertainment-.. 33
3. 2. 6 Validation oi Vital Status Assertainment 34
3.2.7 Analysis 34

3. 3 Cross Sectional Study Oi PFOA Exposed Workers 36
3.3.1 Population Definition And Recmitment 36

3. 3. 2 Data Collection .37

3 ..3 2.1 Study Logs And Files 37

3. 3. 2. 2 Questionnaire - 37

3.3.2. 3 Laboratory Procedures 37
3.3. 2. 3. 1 Height and Weight - 37
3. 3. 2. 3. 2 Blood. -- 33

3.3.2.3.2.1 Drawing And Handling 38

3. 3.2. 3. 2.2 Assays - - 38

3.3.2.323 Quality Assurance 40

3.3.3 Analysis . -- -- 4o

4. RESULTS 43

 



4.1 Cross Sectional Perfluorocarbon Physiologic Etfects Study. 43

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

4.1.1 Participant Characteristics 43
4.1.2 Total Serum Fluorine 44
4.1.3 Hormone Assays 45
4.1.4 Hormone Ratios 49
41.5 Cholesterol Low Density Lipoprotein, High Density
Lipoproteln. And Triglycerides 51
4.1.6 Hepatic Parameters -. 52
4.1.7 Hematology Parameters - 54
4.1.8 Summary Of Results -- 56
4. 2 The 1990 Chernolite Retrospective Cohort Mortality Study 58
4.2.1 Standardized Mortality Ratios (SMRs) 59
4.2.1.1 SMRs For Women -- 59
4.2.1.2 SMRs For Men 59
4.2.2 Standardized Rate Ratios - 60
4. 2.3 Mantel- R?lative Risks (RRMHProportional Hazard Regression Model Relative
Risk -- 61
4.2.4.1 Proportional Hazard Models For Male
Workers - -- 61
4. 2.4. 2 Proportional Hazard Models For Female
Workers 63
4. 3 Physiologic Effects Tables -- -- 64
4. 4 Mortality Tables -- - - 
4. 5 Figures - 190
5. DISCUSSION - -- - 198
5.1 Physiologic Effects Study 198
5..1 1 -- -, - 198
512 --..198
5.1.3 Cholesterol, Triglycerides, and lipoproteins 202
5.1.4 Hepatic - 203
5.1.5 Hematology Counts and Parameters 206
5 1.6 Total FIuorlne? . 209
5 1.7 Methodological Considerations 210
5.1.7.1 Selection Bias -- 210
5.1.7.2 lnfonnation Bias - 211
5.1.7.3 Confounding Bias. - -214
5.1.7.4 Analytic Model Specification Bias: 216
5. 2 1990 Chemolite Mortality Study 217
5.2.1 7 217
5. 2.2 Participant Characteristics 217
5.2.3 Mortality Results 218
5. 2.4 Methodological Considerations 220
5. 2.4.1 Information Bias 220
5. 2. 4. 2 Confounding and Selection Bias 221
5. 2. 4. 4 Analytic Model Specification Bias 223
6. SUMMARY, CONCLUSIONS AND RECOMMENDATIONS 225
6.1 Cross-Sectional Study of the Physiologic Effects of PFOA 225
11



6. 2 Retrospective Cohort Mortality Study Of 1119 Chemolite

 

 

 

 

 

 

Workforce. 1947-1990 996
REFERENCES - 230
APPENDIX 1 - - 
APPENDIX 2 -- - - 259
APPENDIX 3 - - 281



 

LIST OF TABLES

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 4.1.1 Age Distribution In Five Year Age Groups- - 64
Table 4.1.2 Distribution Of Alcohol And Tobacco Use 65
Table 4.1.3 The Joint Distribution Oi Tobacco And Alcohol Use 66
Table 4.1.4 Distribution Of Age By Smoking And Drinking Status. 67
Table 4.1.5 Pearson Correlation Coef?cients Between Total Semm
Fluorine, Age, Body Mass index (Bmi), -. 68
Table 4.1.6 Body Mass index Distribution 69
Table 4.1.7 Body Mass index By Smoking-And Drinking Status 70
Table 4.1.8 The Distribution. Onge. Alcohol And Tobacco Use By 
Body Mass Index - -. - 71
Table 4.1.9 Total Serum Fluoride Distribution 72
Table 4.1.10 Total Serum Fluoride By Body Mass index. Age.
Smoking And Drinking Status. 73
Table 4.1.11 Age Distribution By Total Serum Fluorine Category. 74
Table 4.1.12 Distribution 01' Tobacco Use By Total Serum Fluoride
. Category. -- 75
Table 4.1.13 Distribution Of Alcohol Use By Total Semm Fluoride
Category- .. 76
Table 4.1.14 gody Mass index Distribution By Total Serum Fluorine
atego . 77
Table 4.1.15 Coef?cient 01? Variation For Seven Hormone Assays. 78
Table 4.1.16 The Observed Versus Expected Number 01 Workers
With Hormone Assays Outside The Assay Reference
Range. .. -- -- 79
Table 4.1.17 Pearson Correlation Coef?cients Between Serum
Hormones. - 80
Table 4.1.18 Pearson Co?elation Coef?cients Between Total Serum
. Fluoride, Age. Body Mass Daily Alcohol
Use. Daily Tobacco Consumption. And Semrn --
Hormones. -- -. 81
Table 4.1.19 Bound Testosterone (Tb) By Body Mass Index, Age,
Smoking, Drinking Status And Total Serum Fluoride 82
Table 4.1.20 Linear Multivarlate Regression Model 01 Factors
Pmdicting The Bound Testosterone (Nngi) Among 112
- Male Workers. -- -- 83
Table 4.1.21 Free Testosteronefl?i} By Body Mass index, Age,
Smoking And Drinking Status And Total-Serum . .
Fluoride. -- - 84
Table 4.1.22 Linear Multivariate Regression Model Of Factors
Predicting The Free Testosterone Value (Ng/Di) 85
Table 4.1.23 Participant Estradioi By Body Mass index, Age, Smoking
Drinking Status And Total Serum Fluoride. 86
Tabie 4.1.24 Linear Multivariate Regression Model 01 Factors
Predicting The Estradlol Value Among 113 Male
Workers. - -87

 



Table 4.1.25 Lutenizlng Hormone (Lh) By Body Mass Index. Age.
Smoking And Drinking Status. And Total Serum
Fluorine -- - - 88
Table 4.1.28 Linear Multivariate Regression Model #1 01 Factors
Predicting The Lutenizing Hormone" Value (Mu/Ml)
Among 113 Male Workers. 
Table 4.1.27 Follicle Stimulating Hormone (Fsh) By Body Mass Index.
Age, Smoking And Drinking Status. And Total Semm
Fluorine - 90
Table 4.1.28 Linear Multivariate Regression Model Of Factors
Predicting The Follicle Stimulating Hormone Value
(Mu/Ml) Among 113 Male Workers. - 91
1 Table 4.1.29 Thyroid Stimulating Hormone (T sh) By Body Mass
1 Index, Age. Smoking And Drinking Status. And Total
Serum Fluorine. - - 92
Table 4.1.30 Linear Multivariate Regression Model 01 Factors


 

 

 

 

 

 

Predicting The Thyroid Stimulating Hormone? Value

 

(MulMl) Among 113 Male Workers. 93
Table 4.1.31 Proiacun By Body Mass Index. Age. Smoking. Drinking
Status. And Total Serum Fluorine 94

 

Table 4.1.32 Linear Multivariate Regression Model Of Factors
Predicting The Proan Value (Mg/Mi) Among 113 Male
Workers. 95
Table 4.1.33 Pearson Correlation Coefficients Between Hormone
Ratios And Total Fluoride, Age, Body Mass index.
Alcohol And Tobacco Consumption 96
Table 4.1.34 Pearson Correlation Coefficients Between Prolactin
Hormone Ratios And Total Fluoride. Age, Body Mass
Index, Alcohol And Tobacco Consumption 97
Table 4.1.35 Pearson Correlation Coefficients Between Thyroid
Stimulating Hormone Ratios And Total Fluoride, Age,
Body Mass index. Alcohol And Tobacco Consumption 98
Table 4.1.38 Pearson Correlation Coefficients Between Follicle
Stimulating Hormone Ratios And Total Fluoride,Age.
Body Mass index, Alcohol And'Tobaoco Consumption 98
Table 4.1.37 Pearson Correlation Coefficients Between Pituitary
Glycoprotlen Hormone Rmios And Total Fluoride. Age,
Body Mass Index, Alcohol And Tobawo Consumption 99
5 Table 4.1.38 Linear Multivariate Regression Mode" 01 Factors
Predicting The Bound-Free Testosterone Ratio Among
112 Male Workers. 100
Table 4.1.39 Linear Multivariate Regression Model2 01 Factors
Predicting The Bound-Free Testosterone Ratio Among
112 Male Workers. .. 101
Table 4.1.40 Linear Multivariate Regression Model 01 Factors
Predicting The Estradiol-Bound Testosterone Ratio
Among 112 Male Workers. 102

 

 

 

 



Table 4.1.41 Linear Multivariate Regression Model 01 Factors

Predicting The Estradiol-Free Testosterone Ratio

Among 112 Male Workers. -- 103
Table 4.1.42 Linear Multivariate Regression Model 01 Factors

Predicting The Estradiol-Lh+ Ratio Among 112 Male

Workers. - - -
Table 4.1.43 Linear Multivariate Regression Model 01 Factors

Predicting The Bound Testosterone-Lh-l- Ratio Among

112 Male Workers. --105
Table 4.1.44 Linear Multivariate Regression Model 01 Factors

Predicting The Free Testosterone-LN- Ratio Among 112

Male Workers. 106
Table 4.1.45 Linear Multivariate Regression Model 01 Factors

Predicting The Bound Testosterone-Prolactin Ratio

Among 111 Male Workers. -107
Table 4.1.46 Linear Multivariate Regression Model 01 Factors

Predicting The Free Testosterone-Prolactin Ratio

Among 111 Male Workers. - --..108
Table 4.1.47 Linear Multivariate Regression Model 01 Factors

Predicting The Estradioi-Prolactin Ratio Among 111

 

 

-104

 

 

 

 

 

 

 

Male Workers. - - - 
Table 4.1.48 Unear Multivariate Regression Model 01 Factors

Predicting The Prolactin-Fsh@ Ratio Among 111 Male

Workers. -.-1 10

Table 4.1.49 Linear Multivariate Regression Model 01 Factors

Predicting The Proiactin-Lh? Ratio Among 111 Male

Workers. a 111
Table 4.1.50 linear Multivariate Regression Model 01 Factors

Predicting The Prolactin-Tsh+ Ratio Among 111 Male

Workers. ?112
Table 4.1.51 Linear Multivariate Regression Model 01 Factors

Predicting The Bound Testosterone-Tahi? Ratio Among

112 Male Workers. - 113
Table 4.1.52 Linear Multivariate Regression Model Of Factors

Predicting The Free Testosterone-Tem- Ratio Among

112 Male Workers. - .114
Table 4.1.53 Linear Multivariate Regression Model 01 Factors

Predicting The Estradiol-Tsh+ Ratio Among 112 Male

Workers. - 115
Table 4.1.54 Linear Multivariate Regression Model 01 Factors

Predicting The Bound Testosterone-Fetu- Ratio Among

112 Male Workers. 116
Table 4.1.55 Linear Multivariate Regression Model 01 Factors

Predicting The Free Testosterone-Fetu- Ra?o Amen

112MaleWorkers.- - - -- 117
Table 4.1.56 Linear Multivariate Regression Model 01 Factors

Predicting The Estradiol-Fsh+ Ratio Among 112 Male

Workers. -- 118

 

 

 

 

 

 

 



Table 4.1.57 Linear Multivariate Regression?Modei 01 Factors
Predicting The Bound Tsh-Fsh+ Ratio Among 112 Male
Workers. -



 

Table 4.1.58 Linear Multivariate Regression Model Of Factors
Preggting The Tsh-Lh+ Ratio Among 112 Male
We rs. 

- 120

 

Table 4.1.59 Linear Multivariate Regression meagre Factors
wedicting The Bound Lh-Fsh+ Ratio Among 112 Male
orkers. -



 

Table 4.1.60 Pearson Correlation Coef?cients Between Total Serum
Fluoride. Age. Body Mass index (Brni). Daily 

Use. Dally Tobacco Consumption. And Lipoproteins 

Table 4.1.61 Linear Multivariate Regression Model 01 Factors

Predicting The Cholesterol Among 111 Male Workers. ..

Table 4.1.62 Linear Multivariate Regression Model 01? Factors
Predicting The Low Density Lipoprotien Among 111
Male Workers.

122
123

124

 

Table 4.1.63 Linear Multivariate Regression Model 01 Factors
Predicting The High Density Lipoprotien (Hdi) Among
111 Male Workers. -- -

125

 

Table 4.1.64 Linear Multivariate Regression Model 01 Factors .
Predicting The Triglycerides Among 111 Male Workers.

Table 4.1.65 Pearson Correlation Coef?cients Between Total Serum
Fluoride. Age. Body Mass index (Bmi), Dally Alcohol
Use. Daily Tobacco Consumption. And Hepatic
Parameters 

126

127

 

Table 4.1.66 Pearson Correlation Coef?cients Between Hepa?c

Enzymes. Serum Hormones. And Lipoproteins 128

Table 4.1.67 Pearson Correlation Coefficients Between Hepatic

 

Parameters 
Table 4.1.68 Serum Giutamic Oxaloacetic Transarninase (Sgot 
Glutamic Pyruvic Transarninese. (Sgpt).Gamma
Glutamyi Transferase (691). And Alkaline Phosphatase
Akph) By Total Serum Fluorine

129



 

Table 4.1.69 Serum Glutamic Oxaloacetic Transaminase (390m --

Body Mass index. Age. Smoking And Drinking Status?

Table 4.1.70 Serum Glutamic Pyruvic Transaminase (Sgpt) By Body

Mass index. Age. Smoking And Drinking Status 

Table 4.1.71 Gamma Glutamyi Transferase (th) By Body Mass
index, Age. Smoking And Drinking Status

131
132
133

 

Table 4.1.72 Alkaline Phosphatase (Akph) By Body Mass index. Age.
Smoking And Drinking Status

134

 

Table 4.1.73a Linear Multivariate Regression Model 1 0f Factors
Predicting The Serum Glutamic Oxaloaoetic

Transaminase (Sgot) Ar'nong 111 Male Workers. 

Table 4.1.73b Linear Multivariate Regression Model 2 Of Factors
Predicting The Senim Glutamlc Oxaioacetic

Tramaminase (Sgot) Among 111 Male Workers. 



135

136



Table 4.1 .73c Linear Multivariate Regression Model 3 Of Factors
Predicting The Serum Glutamic Oxaloacetic
Transaminase (Sgot) Among 111 Male Workers. 137
Table 4.1.74a Linear Multivariate Regression Model 1 01 Factors
Predicting The Serum Glutamic Pyruvic Transaminase
(Sgpt) Among 111 Male Workers.-- -- 138
Table 4.1.74b Linear Multivariate Regression Model 2 0f Factors
Predicting The Serum Glutamic Pyruvio Transaminase
(Sgpt) Among 111 Male Workers. - 139
Table 4.1.74c Linear Multivariate Regression Model 3 01 Factors
Predicting The Serum Glutamlc Pyruvic Transamlnase
(Sgpt) Among-111 Male Workers. 140
Table 4.1.75a Linear Multivariate Regression Model 1 Of Factors
Predicting The Gamma Glutamyl Transferase (th)
Among 111 Male Workers. - -
Table 4.1.75b Linear Multivariate Regression Model 2 Of Factors
Predicting The Gamma Glutamyl Transferase (th)
Among 111 Male Workers. - - 142
Table 4.1.750 Linear Multivariate Regre?on Model 3 01 Factors
Predicting The Gamma Glutamyl Transierase (th)
Among 111 Male Workers. 143
Table 4.1.76 Unear Multivariate Regression Model 1 01 Factors
Predicting The Alkaline Phosphatase (Akph) Among 111
Male Workers. - - 
Table 4.1.77 Pearson Correlation Coef?cients Between Total Serum
Fluoride. Age. Body Mass Index (Bml). Daily Alcohol
Use, Daily Tobacco Consumption, And Hematology
Parameters -- - 
Table 4.1.78 Linear Multivariate Regression Model Of Factors
Predicting The Hemaglobin Among 111 Male 
Table 4.1.79 Linear Multivariate Regression Model Of Factors
Predicting The Mean Corpuscular Hemoblobin (Mch)

 

 

 

141

 

 

 



 

 

 

Among 111 Male Workers. - 147
Table 4.1.80 Linear Multivariate Regression Model Of Factors
. Mean Corpuscular Volume (Mcv) Among
111 Male Workers. - 148

 

Table 4.1.81 Unear Multivariate Regression Model Of Factors
Predicting The White Blood Cell Count (Wbc)* Among
111 Male Workers. 7 . - 149
Table 4.1.82 Unear ?Multivariate Regression Model Of Factors
Predicting The Polymorphonuclea?r Leukocute Count
(Poly) Among 111 Male Workers. 150
Table 4.1.83 Linear Multivariate Regression Model Of Factors
Predicting The Band Count (Band) Among 111 Male
Workers. - - 151
Table 4.1.84 Unear Multivariate Regression Model Of Factors
Predicting The Count Among 111
Male Workers. - - 

 

 

 

152

 



Table 4.1.85 Linear Multivariate Regression Model Of Factors
Predicting The Monocyte Count (Mono) Among 111

Male Workers. . 

Table 4.1.86 Linear Multivariate Regression Model 01? Factors

Predicting The Eosinophil Count (Eos) 

Table 4.1.87 Linear Multivariate Regression Model Of Factors
Predicting The Platelet Count (Plate) Among 111 Male

Workers. -- 

 

Table 4.1.88 Linear Multivariate Regression Model Of Factors
Predicting The Basophll Count (Base) Among 111
Male Workers. -

153

154

155

156

 

Table 4.21 Characteristics or 749 Female Employees, 1947-1 
Table 4.2.2 Characteristics Of 2788 Male Employees, 1947?1990 

Table 4.2.3 Vital Status And Cause Of Death Ascertainment Among
749 Female Employees. 19474 990.

157
158

..159

 

 

Table 4.2.4 Vital Status And Cause or Death Moertainment Among 

2788 Male Employees, 1947-1989.

--159

 

Table 4.2.5 Numbers 01 Deaths And Standardized Mortality Ratios

(Smrs) Among 749 Female Employees. 1947-1989.

Table 4.2.6 Numbers Of Deaths And Standardzed Mortality Ratios
(Smrs) By Duration 01? Employment Among Female

Employees, 

160

161

 

Table 4.2.7 Numbers 0f Deaths And Standardized Mortality Ratios
(Smrs) By Latency Among Female Employees. 1947-
1989.- - 

162

 

Table 4.2.3 Numbers or Deaths And Standardized Mortality Ratios
(Smrs) By Any Employment in The Chemical Division
Among Female Employees, 1947-1989.



 

Table 4.2.9 Numbers 01 Deaths And Standardzed Mortality Ratios
(Smrs). Based On US. White Male Rates,

164

 

Table 4.2.10 Numbers or Deaths And Standardized Mortality Fiatios
(Smrs). Based On Minnesota White Male Rates.

Among 2788 Male Employees, 1947-1989. 

Table 4.2.11 Numbers Of Deaths And Standardized Mortality Ratios
(Smrs) By Latency. Based On Minnesota White Male

Rates. Among Male Employees. 1947-1989. 

Table 4.2.12 Numbers Of Deaths And Standardized Mortality Ratios
(Smrs) By Latency, Based On Minnesota White Male

Rates, Among Male Employees. 1947-1989. 

Table 4.2.13 Numbers Of Deaths And Standardized Mortality Ratios
(Smrs) By Latency. Based On Minnesota White Male

Rates, Among Male Employees, 1947~1 989. 

Table 4.2.14 Numbers Oi Deaths And Standardized Mortallty Ratios
(Smrs) By Duration 01 Employment, Based On

165

166

167

168

Minnesota White Male Rates. Among Male Employees.

1947-1969. 

169

 

Table 4.215 Numbers or Deaths And Standardized Mortality Ratios
(Smrs) By Duration Oi Employment. Based On

ix



 

Minnesota White Male Rates, Among Male Employees. .

1947-1989. -- --.170
Table 4.2.16 Numbers Of Deaths And Standardized Mortality Ratios

(Smrs) By Duration 01 Employment. Based On

Minnesota White Male Rates. Among Male Employees.

1947-1989. . . 171
Table 4.2.17 Numbers 01 Deaths And Standardized Mortality Ratios

(Smrs). Based On Minnesota White Male Rates,

Among 1339 Male Employees Ever Employed in The

Chemical Division. 1947-1989. -- 172
Table 4.2.18 Numbers 01 Deaths And Standardized Mortality Ratios

(Smrs), Based On Minnesota White Male Rates,

Among 1449 Male Employees Never Employed In The

Chemical Division. 1947-1989. 173
Table 4.2.19 Numbers 01 Deaths And Standardized Mortality Ratios

{Smrs) By Latency. Based On Minnesota White Male

Rates, Among Male Employees Never Employed in

The Chemical Division. 1947-1989.
Table 4.2.20 Numbers 01 Deaths And Standardized Mortality Ratios

(Smis) By Latency, Based On Minnesota White Male

Rates. Among Male Employees Ever Employed in The

Chemical Division. 1947-1 989..- -- - - 175
Table 4.2.21 Numbers 01 Deaths Md Standardized Mortality Ratios

(Smrs) By Duration 01 Employment, Based On

Minnesota White Male Rates. Among Male Employees

Ever Employed in The Chemical Division. 1947-1989. 178
Table 4.2.22 Numbers Of Deaths And Standardized Mortality Ratios

(Smrs) By Duration 01 Employment. Based On

Minnesota White Male Rates. Among Male Employees

Ever Employed In The Chemical Division. 1947-1989. 177
Table 4.2.23 Numbers 01 Deaths And Standardized Mortality Ratios

(Smrs) By Duration Of Employment, Based On

Minnesota White Male Rates. Among Male Employees

Never Employed in The Chemical Division, 1947-1989. 178
Table 4.2.24 Numbers 01 Deaths And Standardized Mortality Ratios

(Smrs) By Duration 01 Employment, Based On

Mlnnesota White Male Rates. Among Male Employees

Never Employed In The Chemical Division, 1947-1989. 179
Table 4.2.25 Age Adjusted Standardized Rate Ratios (Srrs) For All

Cause, Cancer. And Cardiovascular Mortality By

Duration 01 Employment. Among Male Employees. 

1947-1989. -.?180
Table 4.2.26 Age Adjusted Standardized Rate Ratios (Srrs) For All

Cause. Cancer. Lung Cancer. Gi Cancer. And!

Cardiovascular Mortality'By Ever/Never Employed ln?

Division. Among Male Employees. 1947-

.- -- -- 

 

 

 

 

 

174

 

 

 

 

 



 

Table 4.2.27 Age Stratified, Years 01 Follow-Up Adjusted Rate Ratios
(erh) For All Cause, Cancer, And Cardiovascular
Mortality By Ever/Never Employed In The Chemical
Division, Among Male Employees. 1947-1989. 182
Table 4.2.28 Age Strati?ed. Years 01 Follow-Up Adjusted Rate
Ratios For All Cause. Cancer, And
Cardiovascular Mortality By Duration 01 Employment in
The Chemical Division. Among Male Employees. 1947-
1989 -- - 183
Table 4.2.29 Proportional Hazard Regression Model 01 Facto
Predicting The All Cause Mortality Among 2788 Male
Workers. - 
Table 4.2.30 Proportional Hazard Regression Model 01 Factors
Predicting The Cardiovascular Mortality Among 2788
Male Workers. -
Table 4.2.31 Proportional Hazard Regression Model 01 Factors
Predicting The Cancer Mortality Among 2788 Male
Workers. 185
Table 4.2.32 Proportional Hazard Regression Model Of Factors
Predicting The Lung Cancer Mortality Among 2788 Me
WorkersTable 4.2.33 Proportional Hazard Regression Model 01 Factors
Predicting The 61 Cancer Mortality Among 2788 Male
Workers. - 186
Table 4.2.34 Proportional Hazard Regression Model Oi Factors
Predicting The Prostate Cancer Mortality Among 2788

 

 

 

 

 

184

 

 

.185

 

 

 

 

Male Workers. .. - 186
Table 4.2.35 Proportional Hazard Regression Model 01 Factors

Predicting The Pancreatic Cancer Mortality Among 2788

Male Wcrkers. 187

 

Table 4.2.36 Proportional Hazard Regression Model Of Factors

Predicting The Diabetes Meliitus Mortality Among 2788

Male Workers. . - 187
Table 4.2.37 Proponional Hazard Regression Model 01 Factors

$93:an 1119 All Cause Mortality Among 749 Female

are. -- - - 

Table 4.2.38 Proportional Hazard Regression Model Of Factors 

Predicting The Cardiovascular Mortality Among 749

Female Workers. -- - 188
Table 4.2.39 Proportional Hazard Regression Model Of Factors 

Predicting The Cancer Mortality Among 749 Female

Workers. - 189

 

?-188

 

 

 



LIST OF TABLES 

 

Figure 1. Free Testosterone Versus Total Serum Fluorine 190
Figure 2. Bound Testosterone Versus Total Serum Fluorine 191
Figure 3. Estradiol Versus Total Serum Fluorine 192
Figure 4. Lutenlzing Hormone Versus Total Serum Fluorine 193
Figure 5. Follicle Stimulating Hormone Versus Total Serum Fluorine 194
Figure 6. Prolactin Versus Total Serum Fluorine 195
Figure 7. Thyroid Stimulating Hormone Versus Total Serum Fluorine 196
Figure 8. Bound Testosterone To Free Testosterone Ratio Versus

Total Serum Fluorine 197



 



Fluorine was first isolated as an element in 1880 by Moisser 1. Five years later
he the first fluorocarbons through uncontrolled reactions of carbon
with elemental ?uorine. It was not until the late 1930s that the controlled
of ?uorocarbons became possible. In the 1940s. Frigidaire and DuPont
developed chloro?uorocarbons, the first commercially available fluorocarbons. for
use in refrigeration 1. During the same period perfluorocarbons. a subclass of
perfluorinated organic fluorocarbons with unique properties. were first
to meet the special needs of the Manhattan project 2. The
electrochemical fluorination method for perfluorocamon production made
commercial production of perfluorocarbons possible and opened the doorto
widespread use of perfluorocarbons 3- 4.

Fluorocarbons are wide ranging in their structures and uses. Many commercial
applications have been developed for chlorofluorocarbon compounds Including
refrigeration, degreasing. aerosol dispensing. polymerization. polymer foam A
blowing. drugs, and reactive intermediates or Periluorocarbons (PFCs)
have extensive applications because of their unique physical and chemical
properties. These applications inciude use-as artificial blood substitutes,
computer coolants. polymers such as teflon, surfactants, lubricants. foaming

- agents. ski waxes. and in an extensive specialty chemical industry which

produces grease and oil repellent coatings for paper and cloth. polymers.
insecticides, and a variety of consumer products. Periluorocarbons are currently
being tested as replacements for chlorofluorocarbons in industrial processes and
products.

For many years fluorocarbons were generally thought to be nontoxic.
Periluorocarbons were considered to be particulariy nontoxic because they were
chemically and physically inert and showed low acute toxicity in animals 
Recent epidemiological and experimental studies have associated exposure to
chlorofluorocarbons. a subclass of fluorocarbons previously classified as
nontoxic. with direct and indirect adverse human health effects. Subsequently,
researchers and regulators turned their attention to the study of other
fluorocarbons. The discovery that one per?uorocarbon, perfluorooctanoic acid

1



(PFOA), was present in measurable quanti?es in residents of several U.S. cities
5'7. the recognition that some perfluorocarbons including PFOA have long half
lives in the humans a and the observations that PFOA produced toxic effects in
animals, including hepatotoxicity. endocrine toxicity. immunotoxicity. and
carcinogenesis 9. has led to a re-evaluation of the toxic potential of
perfiuorocarbons. particularly PFOA. in humans.

Despite widespread exposure to perfluorocarbons. little is known about their
effects on human health. It was apparent that additional studies designed to
explore their physiologic effects and potential adverse health outcomes and
conducted in an occupational cohort with high exposure to PFCs, were
necessary. The 3M Chemolite Plant located in Cottage Grove, Minnesota is one
of a few PFC production facilities in the world. Biological monitoring data from
studies of the Chemolite workforce showed that employees have had high levels
and long durations of exposure to PFOA 5-19.. This occupational cohort provided
the opportunity to study the effects of PFOA onhumans. The speci?c goals and
objectives of this study were:

QQALJJ To quantify the human effects of perfluorooctanoic acid on the
following physiologic parameters:

a) Hormones; free and bound testosterone, estradiol, lutenizlng
hormone, thyroid stimulating hon'none, prolactin. and follicle stimulating
hormone.

b) Serum lipids and lipoproteins: cholesterol, low density lipoprotein,
high density lipoprotein. and triglycerides.

c) Hematologic parameters: hemoglobin. mean corpuscular volume.
white blood cell count. polymorphonuclear leukocyte count. bandoount,
count, monocyte count. platelet count. eosinophil count, and
basophll count.



d) Hepatic enzymes: serum glutamic oxaloacetic transaminase, serum
glutamic pyruvic transarninase. gamma glutamyl transferase. and alkaline
phosphatase.

W: to conduct a cross-sectional study of production workers to
estimate the relationships between total serum ?uoride. a surrogate assay
for pre?uorooctanolc acid. and physiologic parameters.

GOAL 2)To quantity the mortality in an occupational cohort with long term
exposure to per?uorooctanoic acid production. .

9515911152: to conduct a retrospective cohort occupational study to
assess the mortality experience of workers using expected mortality based

on Minnesota mortality rates.

 




2.1mm

The presence of small amounts of ?uoride in human blood was recognized in
1856 More than 100 years later. Taves 5- 3 presented evidence that ?uorine
exists in two major forms in humans and animals; in a free ionic state and in a
covalently bound organic state. Priorto this report. it assumed that ?uorine
existed primarily as inorganic ionic ?uoride in biological systems. Taves'
observations have since been con?nned by several other investigators 12'15. The
discovery that organo?uorine compounds constitute the majority of ?uorine found
in humans focused research on characterizing these unde?ned compounds. Guy
identi?ed a per?uorlnated compound, per?uorooctanoic acid (PFOA). as a major
constituent of the serum organic ?uorine fraction 7. 17. Per?uorooctanoic acid
(PFOA) is the only organic ?uorine compound to be identified in human serum 
The recognition of human and animal toxicities associated with
per?uorcchernicals 9- has renewed interest in understanding the human health
effects of per?uorocarbons (PFC). particularly PFOA.

- WW

Organic ?uorochemicals, otherwise referred to as ?uorocarbons. are compounds
composed of ?uorine. carbon and other elements such as oxygen. nitrogen and
sulfur. Per?uorocmbons have structures analogous to hydrocarbons, except the
hydrogens are exhaustively replaced by ?uorine A limited number of organic
?uorochemicais occur in nature however no PFOs occur naturally 24' as.

The first report of the of a ?uorocarbon ?was published in 1890 when
Moissen claimed to have puri?ed carbon tetra?uoride. It is likely he isolated
?uorographite, however?. Pure carbon tetrafiuoride was not obtained until 1930
Work by Ru? and the Belgian chemise Swans. in the late 19th and early 20th
centuries laid the foundation of organic ?uoride chemistry. Midegly and Henna
extended Swarts' work and reported the of dichlorodl?uonnethane.

4



Gle2, in 1930 27. This chloro?uorocarbon with the trade name Freon 12 is an
inert, non-toxic refrigerant which was vastly superior to other refrigerants
available in the 19303. After commercial production of Freon 12 began in 1936, it
rapidly became a major industrial chemical 2- A number of
choloriluoromethanes and chloro?uoroethanes have been produced on a
commercial scale in many regions of the world. These chlorofluorocarbons have
been used in large amounts as aerosol propellants and degreasers. in addition to
their use as refrigerants. Currently. their production is being reduced asa result
of their ozone depleting properties 23' 29.

In 1937, Simone and Block developed a method to produce laboratory quantities
of perlluorocarbons. such as CaFa, cycloCsFto and cycloCsF12 2- 3. The
analysis of these compounds led to the understanding that many of the structures
of saturated hydrocarbons could be replicated in the form of perfluorocarbons.
Research in the area of periluorocarbons was stimulated by two developments.
First, Plunkett dsoovered the polymer. polytetra?uoroethylene, or Te?on 1.
Second, the development of periluoromrbon chemistry was stimulated by the
U.S. effort to develop atomic weapons during World War ll under the Manhattan
Project. The 235u isotope of uranium was required for the development of atomic
bombs. One method of uranium isotope separation was gaseous diffusion. The
only volatile uranium compound available for use in this diffusion process was

- uranium hexa?uoride. UFs. an extremely reactive gas. Materials were needed for
use as coolants, lubricants. sealers and buffer gases in equipment exposed to
this highly reactive gas 1. 2- 25. Perfluorocarbons prepared by Simone were found
to be inert to UFs. This discovery led to a research effort directed toward
understanding the properties of a variety of perfluorooarbons and developing
commercial methods for preparation of periluorocarbons. The development by
Simons of the fluorination (ECF) was a major milestone in the
fluorochemical industry. Since World War ii there has been much interest and
work in this new branch of organic chemistry based on per?uorocarbons.

The use of Simons' ECF method has allowed the production of a wide variety of
perfluorocarbons including per?uorinated alkanes, alkenes, others, esters,
amides, sulfonamides and compounds with cyclic and ring structures 2. The ?inort?
per?uorocarbons are compounds made up of only carbon and ?uorine. This class

5



of compounds ranges from carbon tetra?uoride to complex multiple ring
structures such as per?uorodecalin. Periiuorinated surfactants include can'ooxylic
acids. sulicnic acids. and their derivatives. These compounds form the basis of
an extensive fluorochemical industry. A variety of periluorinated polymers and
elasiomers exist. The most widely used are polytetra?uoroethylene and Kai-F. a
elastomer oi vinyldiene ?uoride and hexatluoropropylene.

2W

Per?uoroodanoic acid is a straight chain eight carbon carboxylic acid with a
molecular weight of 414.16. The melting point of POFA is 59-60?0. its boiling
point is 1891) at standard conditions Per?uorooctanoic acid is produced as a
complex mixture of branched chain isomers. In practice. all eightan
carboxylic acid isomers are refered to as PFOA. The ammonium salt of PFOA
(APFOA) is the common industrially used form of PFOA. it is a white 
powder that easily becomes airborne and sublimes at 130?0.

Periluorocarbons have unique chemical and physical properties 3" 32. The
importance of periluorination in producing these properties cannot be
cveremphasized. Per?uorocarbons are not just another hydrocarbonulike 
molecule. Chemically, periluorocarbons are remarkably inert. They are stable to

. boiling in strong acids and bases. Very few oxidizing or reducing agents'rew

appreciably with periluorocarbons. Periluorocarbons that contain other organic
molecules such as nitrogen. oxygen and sulfur Will participate in reaction at the
site of these molecules. For instance, periluoroctanoyl sulionic acid will react and
form the sulionamlde derivative. The amide portion of this molecule can then be
conjugated with many other organic compounds. The perll'uorinated portion of
these larger molecules remains non-reactive.

Per?uorocarbons are heat stable. They can be heated to greater than 250?0
without breakdown. At high temperatures. greater than some compounds
will breakdown. For example. PTFE, breaks down to per?uoroisobutylene (PFIB).
an extremely toxic gas 1. Because most periluorochemicals are heat stable they
are used ln'hlg'h temperature applications.



 

The inertperfiuorocarbons are excellent insulators. Polymers, such as PTFE,
and inerts PFCs. such as periluorohexane. are used in electrical applications
because oi their superior dielectric properties. Their heat stability and insulation
properties make per?uorocarbon materials the insulators of choice 
Per?uorinated surfaces are the most non-wettabie and non-adhesive surfaces
known 23. Fiuorochemical surfactants are some of the most potent surface
active agents yet discovered Very low concentrations of ?uorochemical
surfactants effectively reduce the surface tension at interphase boundaries.

Most periiuorocarbons are poorly soluble in both aqueous and organic solutions.
They form a group of fluorophllic compounds. however some perfiuorocarbons
with functional groups such as the salts of PFOA. are highly water soluble 3" 32.
Perfiirorocarbon liquids dissolve oxygen avidly. This unique property is the basis
for the use of perfluorocarbons as blood substitutes 33.

Periiuorinated carboxyiic and sulionic acids are some of the strongest organic
acids known The pKa of PFOA is 2.5 34. Thus. when in physiologic solutions,
they exist in primarily anionic iorrns. The anionic forms have a strong propersity
to form complex ion pairs' .

. In the past. some investigators have assumed that the chemical and physical
properties of many ?ucrocarbons is synonymous with lack of activity in biologic
systems 35- 35. However, abundant evidence exists that their chemical and
physical inertness does not imply biologic inertness 19. 37' 



of fluorocarbons has been accomplished using four major methods;
electrochemical ?ucrlnation (ECF), direct ?ucrination, teleomerization. and
catalytic methods using high valence heavy metals. The ECF was developed by
Simons in 1941 3. The Simone process is the oldest commercial technique and
remains a commercial method to obtain many per?uorocarbons. A solution of

 

personal commhication from James Johnson. 3M Corporation
7



 

 

organic substrate is electrolyzed in HF at a low voltage. high current,
nickel anode. The products of these electrolysis cell reactions are largely
perfluorinated. The spectrum of material produced by the ECF process is de?ned
by the starting material. Commercial products from this process include
per?uoroalkanes. perfluoroalkyl others, pertiuoroalkenes. periluoroalkyl esters,
per?uorotrlalkyl amines. perfluorocar?ooxylic acids and periluorosuifonic acids 2.
Products of ECF often include a signi?cant proportion of complex isomers and
fragmentation products. For example, ECF production of PFOA from straight
chain octanoic acid produces 30% complex branch chain isomers 39. The mixture
of products from each ECF run is unpredictably variable. These isomeric mixes
are dif?cult to separate and purify 33. Workers producing PFCs using ECF may
be exposed to a complex mixture that changes composition over time.

Direct ?uorination is another method used to produce perfluorocarbons. It is not
subjected to the impurity problems associated with the ECF process. Direct
fluorination reacts fluorine gas with hydrocarbon substrate. Because ?uorine gas
is extremely reactive. direct ?uorination is a technically dif?cult process and has
only recently been pilot tested for commercial production of ?uomcarbons.

World production of ?uorocarbons is limited to a handful of commercial plants.
The 3M Corporation operates PFC production plants in Minnesota, Illinois,

Alabama and Antwerp. Belgium. A plant in Italy owned by a Japanese and Italian
consortium produces limited amount of fluorocarbons. Periiuorocarbons are also
produced in Germany and have been produced. in the past, in the former Soviet
Union.

Guy ?7 presented possible candidates for the organic fluorine constituents of

human blood based on observation made during the bolation of PFOA from

?7 serum. The organic ?uorine was not likely to be a macromolecule such a a

protein or nucleic acid. because of its solubility in organic solvents such as other

or chloroform/methanol. It was not covalently bound to albumin since it was

.. removed on charcoal at pH 3 at room temperature. The solubility characteristics
suggested that multiple compounds existed with different polarities. The major

8

12200

 

compound was a polar lipid like molecule that was identi?ed as PFOA. Other
less polar compounds appeared to be present. This data suggests that
fluorocompounds other than PFOA were bound to albumin. These compounds
were not esters of C13 - 13 fatty acids and were less polar than PFOA.
Per?uorooctanyl sulfonamide (PFOS) and Its derivative compounds ?t this
description and may be constituents of the organic fluorine fraction. Although
exposure is probably low. the properties of PFOS suggest that it may accumulate
to measurable levels.

In contrast to ionic ?uoride, little has been reported concerning the organic
fluorine content of water and beverages. The ?uorine content of ground water is
essentially all in ionic form. Some ?uorochemicals. such as the per?uorinated
carboxylic acid surfactants and their salts, are soluble in water. Such water
soluble compounds may locally contaminate surface and ground water near
industrial plants that use these compounds. Other per?uorinated compounds
such as the alkanes. alkenes. and others are ?uorOphilic and are insoluble in
aqueous solutions. Although data on the oral organic fluorine intake is limited. it
is unlikely that water and beverages are significant sources of organic ?uorine in
humans. -

The diet as a source of the organic ?uorine found in human semm has been the
subject of speculation 5' 5' Non-perfluorinated ?uorocompounds have found
in biological systems. Marais showed that ?uoroacetate was the compound
responsible for toxicity from the poisonous plant Dichapefalum cyrnosum 
Other investigators have found plant species that ?uoroacetate,
?uorocitrate. and mono?uorinated fatty acids. Peters reported that a few toxic
plants produce ?uoroacetate 42. Flucroacetate and ?uorocitrate have been found
in beans grown in high ?uoride soil 23. Peters 2? and Lovelace et al. 22 have
reported the occurrence of ?uorocitrate in a few plants and foods. In animals. the
metabolic activation of ?uoroacetate into blocks the
transport of citrate into the mitochondria and citrate breakdown by aconitm 
Other omega-fatty acids with even numbers of carbon atoms are highly toxic
as a result of oxidation that produces ?uoroacetate. Fluorocitrate also undergoes
rapid de?uorina?on in rat liver in the presence of glutathione (GSH) Given the
low environmental levels, the infrequent occurrence, the toxicity, and the rapid



 

 

metabolism of these compounds in mammalian species. it is unlikely that these
mono?uorinated compounds contribute substantially to the organic fluorine
content in humans.

Taves measured the organic and inorganic ?uorine in 93 food items No
significant organic ?uorine was found in the tested foods. (>ng and Singer
tested a market basket of food. They concluded that there was no signi?cant
organic ?uorine content in food. Although food and beverages generally do not
contain PFCs, it is possible that they may be contaminated by ?uorochemical
packaging materials. Water and grease repellent coatings in packaging material
could leach into food items in small quantities. This could cwur when materials
that are not designed for microwave use are used in microwave ovens. Studies
have not been reported that quantify human exposures from food packaging
sources.

Per?uorocarbons are contained in many consumer products. Fluorocarbon
surfactants such as PFOA. PFOS. and its derivatives are present in window
cleaning products, floor waxes and polishes, fabric and leather coatings and
carpet and upholstery treatments Additionally these compounds are used to
coat food wraps and are incorporated into plastic food storage bags.
Fluorocarbons are the basis for a new generation of cross country ski waxes.
fiction and Te?on related products are widely used as lubricants, electrical
insulators. heat and chemical stable gaskets and linings and in non-stick
cookware. Fluoroalkanes such as periluorohexane are being evaluated as CFO
replacements. if per?uorohexane or other ?uorocarbons are used as
replacements for CPU . consumer exposure from aerosols and other pmducts
will increase dramatically. PFC's have several experimental medical uses
including use as blood substitutes, x-ray and magnetic resonance imaging
contrast agents vitreous replacement and in liquid ventilation therapeutic
methods Recently. a potent ?uorocarbon insecticide has been marketed to
control ?re ants 

Periluorocarbons have a variety or industrial uses. Te?on and other polymers are
used whereheat stable and chemicdlyinert liners. gaskets and lubricants are
necessary. in addition. they are used as electrical insulators both in solid and

10

12202

i
I

i

 

 

.

liquid form and used as inert non~conductive liquid coolants in electrical devices
such as Cray supercomputers. Perfluorinated surfactants are important fire
suppression materials. Periiuorocarbons have been used to control the metal
vapors ln electroplating processes and to prevent the release of toxic gases\
from landfills?. Per?uorocarbons are being considered to replace CFC's in many
processes such as refrigeration, polymer foam blowing and building insulation.
New applications are being continually developed for these unique compounds,
making increased exposure to workers probable.

WW

Since Taves and Guy's observations. periluorocarboxylic acids. per?iiuorosultonic
acids and their derivatives have been the subject of numerous toxicokinetic and
studies in animals. These studies have focused primarily on two
compounds. PFOA. and per?uorodecanoic acid (PFDA).

Perfiuorooctanoic acid or its salts are well absorbed by ingestion, inhalation or
dermal exposure. Absorption has been studied primarily in rats. although a
number of other spades have been studied.

Five male and five female rats were exposed to airborne APFOA for one hour. In
this experiment the nominal air concentration of ammonium periluorcoctanoate
was 18.6 mgll. No animals died during the inhalation exposure or the 14 day post
exposure observation period. Pooled serum samples contained 42 of
organic fluorine for males and 2 for females. inorganic ?uoride content was
0.02 for males and 0.01 for females 9. Kennedy and Hall 33 studied the
inhalation toxicity in male rats of ammonium perfluorccton?e using both single
dose and repeated dose schedules. They found a L650 of 980 mglm3 for a 4
hour exposure placing PFOA in the moderately toxic by inhalation category.
Following ten repeated doses at levels of 1.0, 7.6,and 84 mg/m3 blood
ammonium PFOA levels were obtained. At the 1.0 mg/m3 level PFOA levels
were 13 ppm. at the 7.6 mg/m3 level PFOA levels were 47 and at 84 mglm3
level PFOA levels were 108 ppm. Therefore it appears that PFOA is well
absorbed by inhalation. it should be noted that the exposures were to APFOA
dust, the likely form for occupational exposure.

11

12203

 

.

Ammonium perfluorooctonoate in food and PFOA administered by gavage in
propylene glycol or corn oil vehicles are well absorbed in rats. In an acute oral
L050 study 9. rats displayed a dose dependent spectrum of toxicities indicating
that PFOA was absorbed after ingestion. PFOA levels were not measured in this
study. in a subacute oral toxicity study, rats were fed PFOA for 90 days 9.
Serum concentration of organic fluorine showed a dose response relationship in
both sexes. A marked gender difference in organic ?uorine levels was observed.
Males had organic ?uorine 50 times higher than females at each dose level.

Studies have since demonstrated excellent. oral absorption of PFOA in a variety
of species including rats, mice, guinea pigs, dogs,- hamsters and monkeys 9- 
Of most immediate. relevance to humans have been studies in a small number of
rhesus monkeys 9. in a 90 day oral toxicity study. monkeys were given 3. 10. and
30 mg/kg/day doses of APFOA. In monkeys at the 3 dose. mean
serum was 50 in males and 58 in females. At the same dose.
males had 3 and females 7 in liver samples. At 10 doses.
male monkeys had a mean serum PFOA of 63 and females 75 ppm. Liver
levels were 9 andfo for males and females, respectively. Because all but 1
monkey died at the 30 and 100 dose levels. only 1 serum sample from
a male monkey in the 30 mg/kglday dose group was available. In this monkey the

serum level of PFOA was 145 ppm. in the 30 and dangerous

mean liver levels were greater than 100 ppm. Thus; the oral route of absorption
may be a significant contributor to the body burden of PFOA lnexposed workers.

Dermal absorption of PFOA has been studied in rats and rabbits. Ammonium

perlluorooctanoate is a fine white powder that may come Into contact with skin

and be absorbed. In rats dermally exposed to ammonium perlluoroctonate at 4
dose levels, PFOA was absorbed in a dose dependent fashion 37. In single dose
dermal exposure experiments using rabbits. appeared to be absorbed.
Levels of ?uorine were not measured, but dose dependent toxic changes were
noted 9. In a mum-dose experiment. ten male and ten female rabbits were
injected derrnally with a 100 mg/kg dose of PFOA on a five day a week schedule
for two weeks. Total serum fluorine. levels were increased in a dose-dependent
fashion. Dose-dependent changes in weight were noted From these studies.

12

12204

 

 

. 

it appears that dermal exposure to the salts of PFOA are absorbed in animals. in
the past. Chemollte workers have been exposed to large dermal doses of
ammonium perfluoroctonate. It appears that dermal exposure may have played a
signi?cant role in the absorption of PFOA in these workers. Upon recognition that
PFOA could be absorbed dermally. work practices were changed and
engineering controls were adopted that reduced dermal exposures. The role that
dermal exposures currently play in PFOA absorption at Chemolite has not been
well studied.

Once absorbed, PFOA enters the plasma probably by diffusing as a neutral ion
pair. In plasma. PFOA is strongly bound to proteins in the serum with more than
97.5 percent in bound form It is likely that albumin is the major site for high
af?nity binding 5'7- There does not appear to be a sex difference in protein
binding Hanhijarvi at al. have suggested that protein binding is saturable in
rats 55. Using human serum. Ophaug and Singer 39 found that PFOA was 99%
protein bound at PFOA levels up to 16 total ?uorine, however. Guy
suggested that per?uorocarboxylic acids bind to albumin in a similar fashion to
fatty acids This hypothesis is consistent with the results of several studies.
Taves observed that the organic fraction of serum co-migrated with albumin
during electrophoresis 5. Dialysis and ultra?ltration studies observed the
retention of organic ?uorine during dialysis and ultra?ltration 7' 17- 53. Belisle and
Hagen reported that PFOA appeared to be strongly protein bound in human
serum Extraction of PFOA from acidi?ed water is quantitatively complete
using hexane. When PFOA is extracted from plasma. recovery is only 35
percent. Plasma appeared to complex PFOA and PFDA. The partitioning of the
bound into organic phase during extraction was more dif?cult and necessitated
the use of more polar solvents. Klevens 53 suggested that CF2 and CF3 groups
complex with polar groups that are present in the amino acids in proteins such as
albumin. in protein precipitation studies using bovine serum albumin, PFOA
bound to albumin at an estimated 28 binding sites per molecule Nordby and
Luck studied the precipitation of human albumin by PFOA. Under acidic pH
conditions, PFOA produced reversible precipitation of albumin 57 by binding to
high af?nity sites. These studies do not rule out signi?cant bindingto other
plasma proteins components. In studies using serum protein
electrophoresis, the protein bound organic ?uorine was distributed in a 

13

12205

 

pattern 3- ?7 suggesting that PFOA protein binding may be nonspeci?c. The large
amount bound to albumin may re?ect the abundance of albumin in plasma and
serum.

in rats, PFOA is distributed to all tissues studied except adipose tissue. The
highest concentrations of PFOA are in the serum, liver. and kidneys. Ylinen et al.
3? studied the disposition of PFOA in male and female rats after single and 28
day oral dosing. After a single dose of 50 mg/kg, PFOA was concentrated in the
serum. Twelve hours after dosing 40% of the PFOA dose was found in the

serum of males and 10% in females. Males retained 3.5% of the dose in serum

after 14 days. retained in the liver for much longer than in serum. in
females, the half-life of PFOA in liver was 60 hours compared to 24 hours in
serum. in males the half-life was 210 hours in liver and 105 hours in serum. it is
noteworthy that PFOA was not found in adipose tissue in detectable quantities.
Alter 28 days of PFOA treatment. PFOA was distributed to the following sites in
decending amounts: serum, liver, lung, spleen. brain, and testis. Again, no
PFOA was found in adipose tissue. The distribution of PFC from serum to the
tissues occumd in a dose dependent manner for females. In male rats. the
concentrations of PFOA in testis and spleen followed a dose dependent trend.
The levels in male rat?serum and liverwas the same for the 10 and 30
dose group. Johnson and Gibson 53- 59 studied the distribution of 140
labeledammonium periluorooctonoate after a single iv dose in rats. Their
findings?were similar to those of Ylinen at al. The primary sites of distribution
were the liver. kidneys. and plasma. Other sites, including adipose tissue. had
less than 1% of the administered dose. The level of PFOA In the testis of male
rats was not reported. As discussed previously, the 90 day oral toxicity study in
rhesus monkeys showed that the relative amounts of PFOA in serum and liver
was different in monkeys compared to rats. In the low dose group of monkeys (3
andio senim had 5 to 10 times the PFOA levels found in liver.
However, at higher dose levels, the PFOA levels were equally distributed.
Additionally. nosex differences were noted In the monkeys liver and serum
PFOA levels. 

There is no evidence that periluorinated compounds including PFOA are
biotransformed by living organisms. several studies have examined whether

14

'ri-i

12206

 

 

 

PFOA is conjugated or Incorporated into tissue constituents such as triglycerides
or lipids. Yiinen et al. found no evidence in Wlstar rats for metabolism or
incorporation of PFOA into lipids Although the lipid content in PFOA treated
rats was different than that in untreated rats. Pastoor et al. did not find evidence
for PFOA incorporation into lipids or of metabolism 5? Vander Heuval et al.
showed that PFOA was not incorporated into triacyiglycerols. phospholipids. or
cholesterol esters in the liver, kidney. heart. fat pet. or testis of male or female
rats No evidence has been found that PFOA is conjugated in phase ii
metabolism Kusilkis et al. studied the formation of activated coenzyme A
(00A) derivatives of PFOA using rat liver microsomes. They found no evidence
for the formation of a derivative.

Sex related differences in the toxicokinetics of PFOA have been reported for rate.
The mechanism of PFOA excretion appears to be species-dependent since these
gender differences are not seen in mice, monkeys. rabbits. or dogs 9 The
half-life of PFOA in female rats has been estimated to be less than one day"-9
whereas the haif-iife of PFOA in males is five to seven days 3" 33. it is of note
that PFDA does not exhibit this gender difference 33. it is hypothesized the
sex differences in sensitivity to the toxicities of PFOA are as a result of the slower
excretion of PFOA in male rats compared to female rats. investigators have
reported that rats have an estrogen-dependent active renal excretion mechanism
for PFOA which can be inhibited by probenecid As noted previously.
females have a much shorter half-life than male rats. The half-life in males can
be reduced by castration or estrogen administration. it can be reduced to the
female half-life by a combination of castration and estrogen treatment. Estrogen
administration alone is almost as effective as the combination of castration and
estradiol treatment in reducing the PFOA half-life. This treatment increased the
renal excretion of PFOA in male rats to those observed in female rats. Other
investigators have reported that the gender difference in half-life depends on a
testosterone mediated increase in PFOA tissue binding?. This hypothesis is
consistent with the gender difference in tissue half-life discussed previously 3?
Johnson has suggested that the primary method of excretion in intact males is
via the hepatobiliary route 59' 59. He reported that choiestyramine enhanced the
fecal elimination of carbon 14 labeled PFOA in male rats. These data suggest
there was biliary excretion with enterohepatic circulation of PFOA, particularly in

15



 

male rats. However, in a male worker with high serum PFOA levels who was

treated with cholestyramine, little if any change in excretion of PFOA was noted.

In this study PFOA was excreted slowly in the urine.

in humans. the half-life of PFOA appears to be extremely long and is not sex
dependent. Ubel and Griffith 9 reported kinetic data for one highly exposed
worker. At the time he was removed from exposure his serum organic ?uorine
was 66 ppm. 80 percent of which was PFOA. Over the next 18 months his
organic ?uorine level decreased to 39 ppm. Urinary excretion of PFOA tell from
387 micrograms/24 hours to 80 micrograms/24 hours. The decline in organic
?uorine levels was consistent with two compartment kinetics. with a calculated
half-life of 2 to 5 years. Additional unpublished biological monitoring data from
three Chemolite workers is consistent with the 2 to 5 year half-life. In the
Chemolite workforce. male and female workers employed in jobs with similar
PFOA exposure have increased PFOA levels. Since men and women with
similar exposures have similar levels, a large gender difference in PFOA
toxicokinetics is unlikely. Therefore, the relevance of the rat data in assessing
the effects of PFOA in humans is questionable.




Both PFOA and PFDA have been found to produce signi?cant toxicities in the
reproductive systems of male rodents 19* 63- The testis has been reported as
the target organ of toxicity for both PFOA and PFOA 19- 33. Additional evidence
exists suggesting that these compounds affect the function of the hypothalamlc-
pituitary-gonad axis (HPG) 19- 55.

Per?uorodecanoic acid;'but not PFOA. has been shown to produce degenerative
changes in rat seminiferous tubules that could progress to tubular necrosis. Van

Raielghem et al. reported that a single ipdose of 50 of PFOA. produced

degenerative changes in rat seminiferous tubules 8 days after injection 55; Similar

but lesser changes were noted in the seminiferous tubules of hamsters and
guinea pigs treated in the same manner. They reported no such change in

16

ear-? 

12208

 

 

treated mice. Bookstafl and Moore 35 did not observe similar changes in rats
treated with 20-80 mg/kg of PFDA. They used a different strain of rats in their
experiments which is less susceptible to testicular toxlcants than those used by
Van Hafelghem et al. Thus. the effects of perfluorocarboxylic acids on
seminlferous tubules may be limited to a speci?c compound. PFDA. in a specific
strain of rats. The effects observed by Van Flafelghem et al. in other species
were not consistent and c?d not demonstrate a dose-response relationship. In
monkeys treated orally with PFOA, no compound related histopathologic
changes in the seminiferous tubules were noted 3.

In a two year rat feeding study. PFOA treated animals were observed to have
increased numbers of Leydig cell tumors'. Male and female rats were fed PFOA
containing diets resulting in a mean intake of 1.5 and 15 A
statistically signi?cant increase in Leydig cell adenomas of and 14% in
the control, low dose. and high dose groups, respectively. was observed at the
end of the two year study. The result was statistically signi?cant as a result of the
unexpectedly low number of adenomes in control animals. Historically. CD rats
experience a lifetime mean Leydig cell incidence of 6.3 percent with a range of 2
to 12 percent. The high dose group incidence is outside the expected range and
may represent a compound related effect. Although the evidence was not
de?nitive. it suggested that PFOA may alter the histology as well as the function
of Leydig cells in rats. Periluorcoctanoic acid was not mutagenic in the standard
tests including the Ames assay using ?ve species of Salmonella typhirr?rurium and
in Seccharomyces cerevisiae 9. Mammalian cell transformation assays using
(33H 10T 112 cells were also negative 57. These data suggest that PFOA is not a
genotoxic xenobiotic. The increase in Leydig cell tumors may be the result of an
epigenetic mechanism.

The observation that rats fed PFOA for 2 years had an increasedincidence of
Leydig cell adenomes prompted researchers to examine the hormonal effects of
PFOA in male rats Adult male CD rats were treated orally with PFOA in doses
of 1 to 50 Serum estradiol levels were elevated in the rats treated with
more than 10 of PFOA. In the highest dose group estradiol was 2.7 times

 

Report: 3M Hiker Laboratories. Two Year Oral Study of F6143 In Flats
#281 080012.1983

17

12209

 

greater than the estradiol levels in pair ted control group rats. Serum testosterone
levels were signi?camly decreased in a dose dependent manner when compared
with ad Iibitum teed control animals. No signi?cant differences were observed
between the high dose rats and their pair fed controls, however. No signi?cant
differences were noted in serum luteinlzing hormone (LH) levels. Additionally. the
accessory sex organ relative weights of the highest group were signi?cantly less
than those of their pair-fed controls.

In order to clarify the site of PFOA action. Cook ?9 conducted a set of challenge
experiments in PFOA treated rats. The results of these experiments demonstrate
that the altered testosterone levels were PFOA related. Human chorionic
gonadotropin challenge can be used to identify abnormalities in the
steriodogenic pathway. Human chorionic gonadotropin binds to the LH receptors
on Leydig cells and stimulates sex steroid hormone 53. 
in Leydig cell function can be detectedby challenging Leydig cells with hce and
measuring steroid hormone production. Similarly, abnormalities in pituitary
secretion of gonadctropins can be identi?ed using a gonadotropin releasing
hormone challenge that stimulates LH release 59. Hypothalamic
dysfunction can be identified using a naloxone challenge to stimulate 
release in rats treated with PFOA for 14 days at the same dose level as the
initial experiment, the Leydig cell. production of testosterone was significantly
blunted after me challenge in the highest dose group compared to ad llbitum ted
controls. A small. non-significant blunting of the testosterone production in
response to GnRH?and naloxone was~observed. Following and naloxone
stimulation, LH levels were not significantly different in the treatment and control
animals. The ma challenge showed that the decrease in testosterone in PFOA
treated rats resulted from altered steroldogenesis in the Leydig cell. The results
from and naloxone stimulation were not definitive. The results were
compatible with an effect at the pituitary level as well as atthe Leydig cell level.
Cook et al. examined the site at which testosterone steroidcgenesis was affected
by PFOA. Progesterone. 17 alpha-hydroxyprogesterone and androstenedlone
were measured after me challenge. Progesterone and 17 alpha-
hydroxyprogesterone were unaffected. Ahdrostenedione levels were significantly
decreased in PFOA treated rats compared to controls. Given that the conversion
of 17 alpha-hydroxyprogesterone to androstenedione by C17120 lyase is

18

 



 

necessary for testosterone these results suggest that decreased
testosterone is the result of a block in this conversion step. In stimulated rat
Leydig cells. the 17 alpha hydroxylase/O-17I20 lyaSe is inhibited by estradiol.
Taken together. these data are consistent with the hypothesis that the elevated
estradiol levels associated with PFOA'treatment inhibit the 047/20 lyase enzyme
and thereby depress testosterone levels. Cook et al. suggested that the blunted
response of Ll-l to low testosterone may be mediated. in part. by elevated
estradiol levels. A subtle hypothalamic or pituitary effea may also be present.
however. The mechanism for the estradiol elevation was not studied.

Per?uorodecanoio acid alters reproductive hormones in male rats in a fashion
similar to PFDA. In male rats treated with doses of PFDA ranging from 20 to 80
mg/kg. given as a single ip dose. PFDA decreased plasma androgen levels in a
dose dependent fashion 55. Both plasma testosterone and 5-alpha
dihydrotestosterone were significantly reduced. Compared to ad Iibitum fed
control rat values. mean plasma testosterone was decreased by 88 percent in
PFDA treated animals and DHT was decreased by 82 percent. These changes
were reflected in accessory sex organ weight and histology. The changes in
accessory sex organs after PFDA administration were found to-be reversed by 
testosterone replacement. The PFDA decrease in androgens was the result of
decreased responsiveness of Leydig cells to LH. There was no eVidence' for
altered metabolism of testosterone. Additionally. plasma LH concentrations did
not increase appropriately in the face of low plasma testosterone concentrations.
This suggests that PF DA may alter the normal feedback mechanisms of the HPG
axis.

it is of interest to note that 2.3.7.8 tetrachlorodibenzo-p?dioxin (TODD). which,
like PFOA. is a nongenotoxic rat carcinogen. a peroxisome proliferators. and an
inducer of P-450 system. has been shown to produce hormonal effects in male
rats similar to those observed for PFOA and PFDA. Moore et al. 7? studied the
effect of TODD on steroidogenesis in rat Leydig cells. Exposure of cell to TODD
resulted in depression testosterone and 5-alpha-DHT concentrations without
altering LH concentration or testosterone metabolism. Moore concluded that
TODD treatment inhibits the early phase of the pathway and the
mobilization of cholesterol to cytochrome P4505cc. However. Moore et al.

19



 

observed decreased estradiol. TODD has been shown to increase the estrogen
mediated feedback inhibition of LH secretion 72 Additionally. in stuc?es using
MOP-7 breast tumor cells, the antiestrogenic effect of TODD was mediated by
alterations in the cytochrome P450 metabolism of estradiol 73. The decreased
testosterone in rats could be mediated by the effect of TODD on Leydig cells
directly, by alterations in testosterone metabolism. or through increased negative
feedback at the pituitary or hypothalamic level. Recently. reports from
omupational studies of TODD exposed workers have associated TODD exposure
with hormonal alterations in human males. Egeland et al. 74 reported that men
with high TODD levels had significantly depressed serum testosterone levels.
The changes in testosterone were not associated with altered LH values.
Estradiol values were not reported. They concluded that dioxin has a similar
effects in men and male rodents. The obvservations that PFOA. PFDA. and
TODD have overlapping spectrums of rodent toxicities suggests that peroxisome
proliferators, lnducers of the P-450 system and non-genotoxio carcinogens may
also alter the hypothalamic -pituitary-gonad function in male animas.

IE I 

In the two year rat leading study, female rats treated with PFOA were observed
to have an increased number of mammary fibroadenomas compared to control
animals. All mammary carcinomas occurred in control animals. Hyperplasla of
the ovarian stroma was observed, but specific histopathologicel studies were not
reported . No Information is available concerning the effect of PFOA and PFDA
on HPG axis in women or female animals.



Altered thyroid hormone dynamics have been observed in rats exposed to PFDA
75'7?. A single ip dose of PFDA in rats results in a rapid and persistent decrease
in thyroxin (T4) and T3 73. Gutshall reported that the decrease in thyroid
hormones occurred as early as eight hours after treatment and persistent for at 
least 90 days 79. These changes were associated with a hypothyroid-like state in

 

Report: 3M error Laboratories. Two Year Oral Toxrary/caromogonmy Study of F0143 in Rats
m1cnoo12,1sas.

2O



 

 

the treated rats. The alterations in serum thyroid levels occurred at dose levels
that did not produce a hypothyroid Animals with depressed T4
levels were found to be metabolically euthyroid 77. Replacement of T4 resulted in
normal food intake. but did not reverse the hypothyroid-like of
hypothermia and bradycardia 73. This suggests that PFDA has a marked effect
on cellular metabolism that is independent of its eitect on thyroid homeostasis.
The low T4 was thought to be a result of two mechanisms. First. PFDA readily
displaces T4 from albumin which results in increased metabolic turn over of the
hormone. Second. the response of the hypothalamic-pituitary?thyroid (HPT) axis
appeared to be depressed as assessed by thyrotropin releasing hormone
simulation testing 75. in these studies. the animals had increased levels of
thyroid responsive hepatic enzyme activities suggesting that the PFDA treated
rats were not functionally hypothyroid. The histological appearance of the thyroid
glands were unremarkable. although treated rats had signi?cantly lower thyroid
weights. TSH levels were not studied. No similar studies are available for
PFOA. PFOA has been noted to produce a transient weightless in treated rats
The hypothyroid-like observed in PFDA treated rat; has not been
studied in PFOA treated rats. however. Since the thyroid hormone effects of
PFDA do not cause the hypothyroid-like state in rats. PFOA may alter the HPT
axis without producing this 

l' I 'it'

The primary site of PFOA toxicity in rodents is the liver. Peroxisome proliferation
(PP), induction of enzymes involved in B-oxldation of fatty acids. and induction of
cytochrome P450 occur after a single PFOA dose. Marked hepatomegaly has
been noted coincident to the PP and enzyme induction. increased liver size was
the result of a combination of both hypertrophy and hyperplasia. Cell
hypertrophy predominated after an initial burst of cell proliferation. The initial
hyperplasia is evidenced by large hepatocytes and markers of DNA 
Areas of increased necrosis in the periportal regions have been observed 

The relationship between hepatic enlargement, peroxisome proliferation, and
increased B-oxidation is unclear. Xenobiotic induced changes in one speci?c
peroxlsomal enzyme are not necessarily linked to changes in other peroxisomal

21



 

enzymes or hepatic enlargement 32. Studies have suggested that xenobictic
induced hepatomegaly and PP may be related to the endocrine status of
experimental animals or to oxidative stress ?3'35. Adrenal and thyroid
hormones may play a role in peroxisomal proliferation. 35. Studies of
ciofibrate, a PP, have shown that endocrine manipulation can modify its hepatic
effects. in adrenaleciomized and thryoidectomized rats. clofibrate-lnduced
hepatomegaly was reduced compared to the effect in control rats 33- 
Conversely, in thyroidectomized or hypophysectomized rats. cloflbrate induced
peroxisomal B?oxidation enzymes were increased compared to normal rats 33.
Thottassery et al. compared the .PFOA-induced hepatomegaly in normal rats.
adrenaiectomized rats and adrenaiectomized rats with cortisol replacement 
They found that hepatomegaly was cortisol dependent and was primarily a result
of hepatocyte hypertrophy. Hyperplastic responses were also cortisol dependent
and were noted in periportal regions. of the liver. Peroxisomai proliferation did not
depend on cortisol and was observed in centriiobuiar regions. They concluded
that PFOA-indUced hepatomegaly and peroxisome proliferation were separate
processes.

In oral feeding studies. PFOA and other PP were reported to cause increased

hepatomegaly in males compared to females. This difference could be reduced
by exogenous estradiol administration or castration and eliminated by castration
and estradiol administration These observations may be explained by an
estrogen dependent renal excretion mechanism or a testosterone mediated
increase in tissue binding 35- 37. 3?

issemann and Green have cloned a mouse PP activated receptor. a
member of the nuclear hormone receptor superfamiiy of llgand-ac?vated
transcription factors that is activated by peroxisome proliferators 39. This
receptor directly mediates the effects of peroxisome proliferators (PPs).
Tugwood has shown that PPs activated recognizes a specific response
unit on the Acyi-CoA oxidase gene promoter in a manner simiiarto the steroid
hc'rrnone receptor 1119 action of PFOA and other PPs may be mediated by a
family of cytosolic receptors that regulate gene transcription in a manner similar
to other nuclear hormone receptors.



 

Weasel:

In initiation. selection. and promotion experiments in rats. PFOA produced an
increased number of hepatocellular carcinomas 91.92 Several mechanisms for
PFDA associated nongenotoxic carcinogenesis have been suggested.

Perfluorooctanoic acid is an archetypal member of a unique sub class of PPs that
are not metabolized. Raddy has argued that the structurally diverse peroxisome
proliferators (PP) are a distinct class of nongenotoxlc carcinogens 35. Roddy
proposed that PPs induce oxidative stress which results in increased tumor
formation. According to this theory. the observed increase in hydrogen peroxide
formation associated with increased B?oxidation is not associated with an
increase of similar magnitude in detoxifying catalase activity 35. Oxidative attack
by hydrogen peroxide and other reactive oxygen species on cell constituents and
membranes leads to DNA damage andincreased cell pmliferation. Increased
proliferation in concert with DNA damage produces increased cell transformation
and malignancies.

Studies testing the theory that PFOA induces HCC by increasing oxidative stress
have lead to con?icting results. Takagi et al. observed an increase in 8-
hydroxydeoxyguanosine in liver DNA from rats exposed to PFOA. They
concluded that rat hepatocytes were under increased oxidative stress 93.
Handler at al. found no increase in hydrogen peroxide production in intact litters
exposed to PFOA 94. Lake at al. failed to find an association between hepatic
tumor formation and peroxisome proliferation 95. Thottassery et al. observed that
the PFDA induction of B-oxidation was independent of adrenal hormone status.
A PFOA associated increase in catalase activity depended on cortisol 
Therefore, the hormonal status in animals used in experiments could confound
studies of oxidative stress and account for the con?icting results.



in the 90 day monkey feeding study. bone marrow and tissue were a
site of histopathology Treated monkeys In the highest two dose groups were
observed to have moderate hypocellularlty of the bone marrow. Specific

23



 

 

histopathological ?ndings were not reported. Atrophy of follicles in
nodes and the spleen were noted in the same treatment groups. No
follow-up studies of these observations have been reported. Studies in PFOA
treated rats have not shown histological changes in the immune system 9.



The mechanism of toxicity of perfluorinated surfactantsmay be mediated by their
effect on cell membranes. Olson and Anderson 3? suggested that PFOA may
alter membrane function through changes in fatty acid composition and oxidation
status. Levitt and Lies hypothesized that the effect of per?uorinated surfactants is
mediated by their alteration of membrane organization or fluidity 95' 97.

32 reported that miscibility of fluorocarbon and hydrocarbon surfactants
depends strongly on carbon chain length. A carbon chain length greater than
eight carbons is necessary for lmmiscibility. Perfluorocerbon surfactants with
eight or fewer carbon atoms are miscible with hydrocarbon surfactants with
carbon chain up to nine. These observations could have important
implications for biological systems that contain fluorocarbon surfactants. Cellular
membranes are a phase boundary. usually between a lipid phase and an

aqueous phase. Surfactants will segregate to this phase boundary. Two

surfactants may form two coexistent monolayers on the inside and
outside of the membrane whereas miscible surfactants will form only one such
monolayer. The presence of two monolayers will maximally reduce the surface
tension at the boundary. whereas a single monolayer will affect surface tension to
a lesser degree. Changes in surface tension may alter membrane fluidity and
affect its function in such processes as signal recognition and transduction. it is
interesting to note that the change in miscibility in Shindo?s experimental system
occurred for fluorocarbon surfactants with carbon chain greater than
eight. This change in miscibility dependedon hydrocarbon surfactant chain
length as well.

The effects of PFOA and PFDA on experimental membrane systems and cellular
membranes have been investigated. lnoue studied the differential effects of
octanoic acid and perfluorooctanoic acid on experimental cell membrane

24



 

 

properties 93. The phase transition temperature of 
vesicles decreased linearly as PFOA increased in concentration up to one mM
and then reach a plateau. This suggested that PFOA may form aggregates in
the membrane above a critical concentration. Such a phase separation is
observed to occur in micelles 32. The partition coefficient between water and the
membranes for PFOA, a 8910, was larger than the coefficient for ionized
octanoic acid. a 135, possibly because of the difference in hydrophobicity
between hydrocarbon and ?uorowrbon chains in aqueous solution. The
differences between the toxicokinetice and toxicodynamics of PFOA and PFDA
may be the result of their differing miscibilities with cell membrane surfactants.

Levitt and Lies investigated the effect of PFOA and PFDA on the plasma
membranes of cells from F4 human cell line using the dye
merocyanine 540 (M0540) 97. The dye binds to phospholiplds that are loosely
packed on the outer cell membrane. but does not bind to highly organized lipids
and does not penetrate the membrane of healthy cells 99. A large decrease in
M0540 cell surface binding was observed after treatment with sub-lethal
concentrations of PFOA and PFDA but not other nonoperfluorinated fatty acids.
Albumin or serum reduced the change in M0540 binding. This effect may be a
result of the strong protein binding of PFOA and PFDA by albumin These
observations suggest that PFOA and PFDA either interact directly with M0540
lipid binding sites or alter the structure of the lipids in the membranes.

In experiments examining functional changes in the cell lines.
Levitt and Lisa observed that PFOA and PFDA could cause direct damage to
cells resulting in the release of membrane bound cell proteins and
immunoglobulins in soluble form 93. PFDA was signi?cantly more potent than
PFOA in solublizing proteins and killing cells. This may be the result of different
miscibilitles in the cell membrane of these compounds. However. neither PFOA
nor PFDA reduces the ability of surface immunoglobulins to migrate and undergo 
capping after antigen recognition 97. In the PFOA concentration ranges that
decreased M0540 binding. PFOA did not affect immunoglobulln migration and
capping. Capping involves the cytoskeletal'mediated polar migration of
immunoglobulins within the plane of the membrane Apparently, the PFOA

25



 

and PFDA associated membrane changes do not affect membrane
characteristics that are important for receptor migration.

The membrane eliects of PFDA have been studied in greater detail. Pitcher et al.
reported that a single injection of PFDA in rats signi?cantly reduced the apparent
number of adrenergic receptors In cardiac cells This change in number of I
receptors was reflected In the diminished response of cyclase (AC) to
epinephrine in PFDA treated rat cardiac cells. The intrinsic properties of Ac were
not altered. The action of PFOA was on the epinephrine receptor. The fatty acid
composition of the treated rat cardiac cell membranes was signi?cantly altered
Palmitic (16:0) acid was elevated 13 percent. elcosotrienoic (20:3 we) was
elevated 71 percent, and docosahexaenolc acid (22:6 w3) was elevated 18
percent. Arachldonic acid (20:4) was reduced by 18 percent. Several other
investigators have reported changes In membrane tunctiontollowing PFDA
exposure. Wigler and Shaw demonstrated that PFDA inactivated a
membrane transport channel for 2?aminopurlne in 5178 mouse 
cells. In vitro experiments reported by Olson et al. 1? showed that 
exposed to PFDA exhibited decreased osmotic fragility and increased fluidity.
Taken together. these studies indicate that per?uorinaed surfactants exert their
sheets on cell membranes. The effects appear to be limited to the outer portion
of the membranes as the result of differential partitioning within the membrane or
binding to speci?c membrane constituents. Although PFOA and PFDA can be
cytotoxic as a result of their detergent action on membranes. their membrane
effects at lower doses are not related to their detergent action. From available
- data. it appears that functional membrane changes may be limited to speci?c
receptor mediated tunctions.



In workers employed in ?uorochemioal production plants. blood organic ?uorine
has tar outweighed ionic ?uoride 51. 55. More than 98 percent of the total
?uorine in these groups has been reported to be organic ?uorine. Therefore. the
use of total ?uoride levels, which consist predominantly of organic ?uorine
compounds. is a valid surrogate for organic ?uorine. in ocwpationally exposed
groups. In workers at the Chemolite plant, PFOA has been identi?ed in the semm

26



 

 

 

of these workers and was estimated to account for 90 percent of organic ?uorine
found in the serum samples 3. In this cohort of workers. total ?uorine is a good
surrogate measure for PFOA.

Industrial hygiene measurement of ?uorochemicals have been conducted at the
Chemolite plant since the 19703 a_ These measurements include area samples,
personal breathing samples and surface wipe samples. In 1977. a
comprehensive effort at evaluating ?uorochemical exposures was conducted at
the Chemolite plant. During certain operations breathing zone PFOA
concentrations were as high as 165 ppm. After extensive engineering control
alterations, the plant was serially re-surveyed. In general, alrbome exposures
were below the recommended limit of 0.1 mglma. However, there was evidence
of surface contamination in production buildings 3. In 1986, airborne PFOA. as
well as breathing zone samples were less than 0.1 mg/m3 based on a hour time
weighted averages. Levels as high as 1.5 rug/m3 were measured in breathing
zone samples during certain clean-up and maintenance zone samples.
Periluorobutyric acid was also found. but in much lower concentrations. Spray
dryer operators had consistemly higher exposures. even following extensive
equipment improvements. 

It appears that airborne exposure to PFOA was low for most workers. Spray dry
operators and workers involved in clean up and maintenance activities have
higher intermittent exposures. Although personal protection devices are required
in high exposure jobs, worker compliance has not been evaluated. The role that
surface contamination plays in worker exposure has not been de?ned? . The
route of PFOA exposure in worker has not been clearly identified.

'l 115'?

A retrospective cohort mortality study of employees at the Chemolite Plant in the
period of 1940-1978 was conducted by Mandel and Schuman 3. Of the 3,688
male employees who were employed tor at least 6 months. 159 deaths were
identi?ed. There was no excess mortality in the employees as compared to all

 

I persona conununlcatlon from Stan Sorenson, 3M Corporate Medical Department
personal communication from Stan Sorenson. 3M Corporate Medical Department

27



 

cause or cause speci?c mortality in the U.S. white male population. The
suboohort of all chemical division workers did not show any all cause or cause-
specific excess in mortality.

Starting in 1976 medical surveillance examinations were offered to Chemoiite
employees in the Chemical division 3. Approximately 90 percent of the workers
participated in the program. No health problems related to the exposure to
fluorocamons were encountered in participants. Serlaily conducted surveillance
examinations have failed to reveal any relationship between blood levels at
organic ?uorine and clinical pathology .



Animal studies have suggested that there are five areas of toxicity associated
with PFOA exposure. These include hepatotoxiclty. immune system alterations.
reproductive hormone alterations. Leydlg cell adenomas. and non-genotoxlc
hepatowrcinogenlcity. Toxicity studies have primarily used rodents. There is
considerable variability between strains of rats for some of the toxic endpoints
such as Leydig cell adenomas. Additionally. some oi the eitects seen in rats have
not been seen in other rodent species such as mice. hamsters or guinea pigs. .
The limited data available on PFOA exposed rhesus monkeys and ocwpa?onally
exposed workers suggests tha any extrapolation oi the results from rodent
experiments to humans requires more information about the mechanism of PFOA
toxicity. From this data it does not appear that the liver is a major site for PFOA
toxicity in humans. or greater human health concern are the potential attests on
the immune system and thereproductive hormones.

In the past. workers have Ibsen found to have significant blood levels of PFOA.
Many workers have levels above one ppm. These blood levels are 50-1000
times backgrotrnd levels in the general population. These levels may be high
enough to produce toxicities in occupationally exposed humans. A confident
estimate of risk cannot be made until further information on the adverse health
effects of PFOA exposure in humans is obtained.

 

personal acorn-ionisation from Larry Zobei: 3M Corporation Medical Department
28

1 



 

 

William

The effects of perfluorooctanoic acid (PFOA) exposure on human health were
studied in employees of the 3M Chemolite plant (hereafter referred to as
Chemolite) located in Cottage Grove. Minnesota. Two studies were conducted to
investigate of the human health effects associated with PFOA exposure. First,
mortality associated with occupational PFOA exposure was studied using a
retrospective cohort design. Second. a cross sectional study design was used to
estimate the relationships between PFOA exposure and selected physiologic
parameters.

A retrospective cohort study was designed to examine mortality among workers.
All workers ever employed at the Chemoiite plant for greater than six months were
included in the cohort. All causes and cause-specific mortality were compared to
expected mortality. Expected mortality was calculated by applying sex and race
speci?c quinquennial age, calendar period, and cause-specific mortality rates for
the United States and Wnnesota populations to the distribution of observed
person-time Age adjusted standardized rate ratios were calculated A
relative risk (HR) for PFOA exposed workers compared to unexposed werkers

was calculated using proportional hazard regression models 197. The FIR were

strati?ed by gender and adjusted for age at ?rst employment. duration of
employment and calendar period of ?rst employment. Any signi?cant differences
between observed and expected cause-speci?c mortality were to be explored
using nested case control studies. Case studies were completed for causes of
death with 5 or more deaths and standardized mortality rates greater than 1.5.
Each deceased individuals record was examined for commonaities in Jobhistory
information including age at first employment. calendar period of employment.
years in the Chemical Division. and duration of employment.

Selected physiologic effects of PFOA exposure were studied using a cross
sectional study design. The relationships between total serum ?uorine and
biochemical parameters including reproductive hormones, hepatic biochemical
parameters. lipid and lipoprotein parameters. and hematologic parameters, were

29



 

explored. A sample of the work force employed on November 1. 1990 was invited
to participate. All employees in high exposure jobs were asked to participate. A
sample of workers employed in low exposure jobs was frequency matched to the
age and sex distribution of the high exposure group. Each participant completed
a questionnaire which included medical history and information concemlng
alcohol. tobacco. and medication 'use. The questionnaire is provided in Appendix
3-1. Blood was drawn for determination ot hematologic and biochemical
parameters. Total semm ?uorine. free (FT) and bound testosterone (8T).
estradlol (E). thyroid stimulating hormone (TSH), follicle stimulating hormone
(FSH), prolactin (P) and luteinizing hormone (LH) were assayed. The PFOA-
hormone dose-response relationship for each hormone was estimated using
linear regression techniques to adjust for the effects of age. sex. body mass.
alcohol consumption, tobacco use. and other potential contounders. The PFOA-
hormone dose-response relationshipwas further explored by ?tting linear
multivariate models to hormone ratios. All unique ratios between the seven
hormones were de?ned . Twenty-one hormone ratios were calculated for each
participant The prevalence of hormone values outside the laboratory reference
range for men was compared to the expected prevalence assuming a normal
distribution for assay values.

Wm

WM

The?Chemolite facility opened in 1947. Individuals who were employed at the
Chemolite plant between January 1, 1947 and December 31. 1983 were identified
from company records. Workers with fewer than six months employment were
excluded. In October 1951 large scale commercial PFOA production facilities
became operational (Abe 1982). Because large scale PFOA production &d not
begin until 1951, a second cohort with potentially signi?cant PFOA exposure was
de?ned as those workers employed between October 1. 1951 and December 31 

1983. Subjects with greater than six months employment were included in this
second cohort.

30



 

The cohort was initially assembled in 1979. Subsequently, the cohort was
updmw to include new employees through 1983. Personnel records for
employees working prior to 1979 were coded for demographic items and work
history by trained abstractors. Computerized corporate personnel databases were
utilized to provideinfonnation for workers employed in the 1979 to 1983 period.
Abstracted work history included year of first employment, year of last
employment, years employed at Chemoiite. and months worked in the chemical
division. Individual job histories were not abstracted because job titles were
de?ned by wage grades and did not correspond to specific jobs or locations within
the plant.



A Chemolite cohort database was created on a VAX computer using lngres
software. Data stored on magnetic tape were transferred to the VAX. Duplicate
records were identified and removed. Missing data were identified. The ingress
update function was used for data editing. Final analytic files for the Monaco
program. SAS programs. and custom programs were constructed using the
ingress report writer.

relational database allowed extensive intemal consistency checks to
be made. All dates werechecked for plausibility. These records with implausible.
inconsistent, or improperly formatted dates were edited and comcted if
information was available. Records of workers with fewer than six months
employment were flagged and excluded from the analytic data set. A random
check of 50 of the 364 workers with fewer than six month employment found no
errors in classification of employment length. Extensive attempts were made to
obtain all missing data items. Sources of information included plant personnel
records, corporate personnel databases, benefit records, archived corporate
records. plant medical records. and death certificates. No individual employees or
next-of-kin were contacted. Four employees were excluded from the cohort as a
result of missing demographic data items.

31



 

 

The cohort was initially de?ned from personnel records stored at the Chemollte
plant. Complete records were maintained on all workers ever employed at the
plant. Hourly and salaried workers were included in these ?les. as were all
transferred. terminated and retired former employees. Records for workers first
employed in the 1947-1978 period were abstracted from documents. coded and
computerized. A corporate computerized database was used to update the cohort
through December 1. 1983. Since insufficient induction time had lapsed between
1983 and 1989. no new employees or work history information was added to the
cohort database for the post 1983 period for this study.

Verifying the ascertainment of all eligible cohort members was problematic. The
assumption that the personnel records represented a complete roster was dit?cult
to check because of a lack of independent information. Several sources were
used to exclude major errors in the enumeration of the cohort. The historical plant
hiring pattern based on seniority dates was compared with the distribution of

dates of first employment. Qualitativeiy. dates of major plant expansion
corresponded to peaks in the detribution of dates of ?rst employment and to
seniority dates. Large increases in hiring due to new plant openings were
reflected in peaks in the distribution of starting dates in the cohort. A sample of 25
annuity bene?ciaries retired from the Chemolite plant were obtained from the
corporate personnel of?ce. All 25 were found to be included in the enumerated
cohort.

Several plant personnel record systems were randomly sampled. Separate ?les
were maintained for active workers, retirees, transferred and terminated workers,
and workers whose employment at Chemolite ended priorto 1960. A sample of
records for current employees with start dates prior to December 31, 1983 was
compared to the cohort. All 12 records from the 1945-1960 period for start dates
were found in the cohort database. Of 30 records sampled from the 1981 -1 969,
28 were inclUded in the cohort. Fifty two records had starting dates in the
1970-1978 period. Of these 52 records. forty seven were found in the

32

12224

 

 

 

 

database. in the 1979-1980 period 18 of 44 records were in the database.
Lastly. in the 1981 through 1983 period. 36 of 37 records were in the database
The low ascertainment for workers ?rst employed in the 1979-1980 period
was further examined. Of the 34 workers not in the cohort database. 16 
were ?rst employed in the 7179-1180 period. These omissions occurred in the
transition period between document abstracting and electronic updating of the
cohort. Using seniority lists, 44 workers currently employed were hired between
1979 and 1980. They represent approximately 1% of the total number of
individuals in the workforce and less than 0.5% of the total person time at risk for
the cohort. Records for retired workers were sampled from tiles containing all
workers retired from Chemolite. Forty seven of the 48 sampled records
were present in the database. A sample of the ?les containing the personnel
records of employees completing employment before 1960 was randomly drawn.
Of the 67 selected records. 65 were in the database. Finally, ?les
containing records of all transferred. terminated. or disabled employees were
randomly sampled. 0f the 120 sampled records, 116 were present in the
cohort database.

WW

Information in the edited database was compared to information in the personnel
records. A random sample of 25 records was drawn from the personnel ?les.
Database names. social security numbers (SSN), dates of birth (DOB). and dates
of employment were veri?ed against record information. The sole error occurred
in coding the last digit of one SSN. "All other information was correctly entered
into the database.

The reliability of ICD8 coding of death certi?cates for underlying cause oi death
was evaluated by resubmitting a sample of death certificates for coding by the
same nosologist. The sample consisted of 25 death certi?cates from 1970 -1 989.
No change in the major categories of cause of death was noted. All cancer
deaths were coded concordantly. Within cardiovascular causes of death. two
certificates were discordant.

Woman!
33



 

The vital status was ascertained from the Social Security Administration (SSA)
and the National Death Index (NDI). All individuals with unknown vital status were
traced successfully and vital status determined. Vital status determination in the
1979-1989 period was obtained through the NDI. Death certificates were
requested from the appropriate state health departments for those individuals
identified as. or presumed to be. deceased. A professional nosoiogist mded the
death certificates for underlying cause of death according to International
Classi?cation of Diseases. 8th revision (ICDB). information concerning the date
and cause of two deaths which occurred outside the United States was obtained
from family members or other available sources. Date of death and the 
code for the underlying cause of death were entered into the database.



The vital status determination procedures for the cohort was evaluated.

Corporate bene?t records were utilized as an independent source for vital status 
among the retirees. Vital status from the database was compared to vital status 
in corporate records. A list of all retirees in the 1947-1984 cohort was sent to 3M

bene?ts department. These individuals were matched to retirees who had

received 3M death benefits. 3M records were not complete for periods prior to

.1 975. In the pre-1983 period, 4 deaths in retirees were identified" by3Mi records. 1
Vital status was correctly ascertained by the SSA matching procedurefor only one

of these retirees. In the 1983-1989 period, 34 deaths in retirees were identi?ed in

3M records. The NDI matching procedure ascertained all 34 of these deaths.

The NDI was not available for 1990. 3M records indicate that 8 retirees died

during 1990. The incomplete SSA ascertainment in the period 1975 to 1983

resulted in extending the NDI search to include 1979 to 1983. All 3M identified

deaths were also identi?ed in the subsequent NDI search covering the 1979 to

1983 period.



Analytic methods employed in this?study were appropriate for cohort studies. The
relative risk was estimated by calculating an adjusted standardized mortality ratio

34



 

 

 

 

(SMR) 105. This study used both national and Minnesota mortality rates for
comparisons. Mortality for men in the Chemolite cohort was compared to
expected national and Minnesota mortality, adjusted for age, calendar period, sex
and race. The use of mortality rates in the rural counties surrounding the plant
were not considered to be stable for many causes of death and were not used.
Since less than one percent of plant employees are non-white, white male and
female rates were used for comparison. For women. only us. rates were used
because cause- and calendar period-speci?c Minnesota rates were not available.
were calculated for all cause, all cancer. and cause-speci?c mortality. The
effects of disease latency, duration of employment, duration of follow-up, and
work in the Chemical Division were examined using stratified analyses.

Three additional methods of analysis were used to assess the validity of the SMR
contrasts. The three methods were: standardized rate ratios (SRR) Mantel
Haenszel adjusted relative rates (RRMH) and proportional hazard regression

adjusted an 107.

Umited exposure data were available from plant records. Exposed workers were
de?ned as all workers who worked for 1 month or more in the chemical division.
Exposed and unexposed workers? all cause, all cancer, and cause-speci?c
mortality was compared using strati?ed and strati?ed Mantel
Haenszel analysis Additionally. the Same summary measures were
calculated contrasting the rates for workers with at least ten years duration of
employment and those with less than ten years employment.

The relative risk (anror deaths from all causes. cancer,
cardiovascular diseases. and selected specific causes were estimated using a
proportional hazard model (PH) 107. The time to event or censoring was
de?ned as time from ?rst employment to event or December 31 . 1989. In PH
models for specific causes of death, deaths from other causes were censored at
the time oi death. Exposure was quanti?ed by months of chemical division
employment. Covariates included in the models were age at ?rst employment.
year of ?rst employment. and duration of employment. The analyses were
strati?edby gender. The appropriateness of the proportional hazard assumptions
were tested using strati?ed models with graphical analysis of log 

35

 



 

 

 

 

versus follow-up time relationships and models that tested the signi?cance of a
product term between exposure and logifoliow-up time) 




Medical screening of workers employed at the Chemolite plant occurs every two
years. The general medical screening program included a medical questionnaire
(Appendix 3-1). measurement of height. weight and vital signs. pulmonary
function evaluation, urinalysis, semm assays. and hematology indices. This
screening program offered an opportunity to assess the physiologic effects of
PFOA exposure in workers engaged in commercial production of a limited
spectrum of PFCs. Of particular interest were the effects of PFOA. the primary
?uorochemical found in the serum ofChemolite workers. (Grif?th and Ubel, 1980).

Participation in the Physiologic Effects Study required the subjects' willingness to
undergo hormonal and biochemical testing and to have an additional 15 mi of
blood drawn for total ?uorine assay. in the cross-sectional study. exposure
classi?cation was based on the potential for PFOA exposure in a workers job and
plant location. All workers engaged In any facet of PFOA production in the
previous ?ve years were considered to have potentially high PFOA exposure.

The jobs considered to hays high exposure potential included all jobs in the
production buildings (bldg 6 and 15), all maintenance workers who were assigned
to the PFOA production areas. and all management jobs requiring physical
presence in the production building. Plant records and job history information was
used to assign exposure status to indvidual workers. A random sample of
workers in jobs with low exposure potential was frequency mashed to the age
and sex distribution of the high exposure workers. Workers with low exposure
potential were de?ned as those assigned to jobs not involved in the production of
PFCs for at least ?ve years. A meter of workers meeting the low exposure
potential was de?ned from plant records and knowledge of plant personnel about
the location of high exposure jobs. A gender strati?ed sample from the group of
workers in low exposure jobs with an age (5 year strata) distribu?on slmilarto the
exposed group was identi?ed and invited to participate. if a worker in a job with

36

MN03112228

 

 

low exposure declined to participate. another worker in the same age and sex
stratum was randomly selected and invited to participate. In all cases informed
consent was obtained. Participation in this study was voluntary.

Winn


A roster of participants was maintained by the plant occupational health nurses. A
log for biological sample information was completed by the laboratory technician.
The date and time of ample coolection was recorded. Quality assurance samples
were recorded on a separate log. Results reported on paper records were
maintained as medical records. Results for other tests were transmitted
electronically to a computerized database and coded as SAS detasets. All
records were stored with employee medical records or in the corporate medical
offices for con?dentiality purposes. Printed laboratory results and questionnaire
data were entered into a SAS dataset.



Each participant completed a medical questionnaire prior to reporting to the plant
medical of?ce. (Appendix 3-1) Items included demographic information.
illness history and diagnoses. and medication usage. Detailed
questions conoemlng tobacco use and alcohol use were included. Workers were
not re-contacled to obtain missing lnlonnatlon or to correct inconsistencies.
Responses were not validated. Two plant occupational health nurses collected
the questionnaires and returned them to the corporate medical department. in the
corporate medical office, data were coded and entered into a SAS data base.





37



 

 

 

Upon reporting to the plant medical of?ce. participants had their height and
weight determined by an occupational health nurse. Height and weight
were measured once on the same calibrated scale.




Four vacutainers of blood were drawn from a single venipuncture by a laboratory
technologist. Two 15 ml red top vacutainers of blood were drawn and allowed to
clot. One to ml purple top vacutainer was drawn tor hematology studies. A
specially prepared ?uorine tree 15 ml vacutainer was used to collect blood for total
serum fluorine deten'ninatlon. Venipunctures were scheduled to occur at the
same time of day and on the same shift lor each worker. All blood was drawn
between 6:30 and 8:00 am. Workers in the Chemical Division of the Chemolite
plant rotate shifts on a weekly basis. Blood was drawn alter a worker was
assigned to the day shift for at least 3 days.

All specimens were refrigerated at the plant prior to transport to the appropriate
laboratory. Clotted red top vacutainer specimens were centrifuged for 12 minutes
to separ?e serum from cells before transport to the contract laboratory. In order
to render the total serum fluorine specimens non-infectious, semm fortotal
?uorine assays was ether extracted in the corporate medical department prior to
earning the samples to the 3M Chemical Division analytic laboratories.

mm

Serum samples were analyzed for total serum ?uorine. hepatic biochemical
parameters, cholesterol. lipoproteins, and seven hormones. Assayed biochemical
parameters included serum glutamic oxaioacetic transaminase (SGOT). semm
glutamatic pyruvic transamlnase (SGPT), gamma glutamyl transferase 
and alkaline phospatase (AKPH). The following hormones were assayed: bound
testosterone. free testosterone, estradiol, prolactin, luteinizing hormone (LH),
follicle stimulating hormoneiFSH), and thyroid stimulating hormone (T SH). EDTA
preserved whole blood samples underwent routine hematologic analysis including

38

12230

 

complete blood count with indices and leukocyte differential cell count
(CBC). Analyses were done without knowledge of the subject status or purpose
of the study.

Total serum ?uorine was determined in 3M?s Chemical Division analytic laboratory
using the sodium biphenyl extraction method (Venkateswarlu. 1982). The
accurate determination of total ?uorine in the parts per million (ppm) range
required specialized equipment, procedures, and personnel. Assays were
completed in a dedicated laboratory following tested protocols.

Upon receipt of extracted serum samples divided aliquots were frozen at ~70
degrees centigrade. After all samples had been received. batches of 15 samples
were assayed on successive working days. Each batch included high and low
quality control samples. Each sample was assayed twice. if the difference in
assayed values was greater than 1 ppm.- the sample was re-assayed. The total
semm ?uorine value was reported as a mean value and a rounded integer value.

Serum glutamic oxaloacetic transaminase (SGOT). senrrn glutamatic pyruvic
transaminase (SGPT), gamma glutamyl transierase and alkaline
phospatase (AKPH) were assayed by the United Health Services Laboratory in
Apple Valley, Minnesota using clinical colorimetric assays. 0805 were
determined using automated Coulter counters. Light microscopy was utilized for
differential counts.

Estradloi. prolactin. thyroid stimulating hormone (TSH), luteinizing hormone (LH),
and follicle stimulating hormone (FSH) were assayed by the United Health
Services laboratory using radioimmunoassay (BIA) and enzyme linked
immunosorbent assay (ELISA). FSH. LH. and prolactln were assayed using
Abbott laboratories microparticle enzyme linked immunoassays. TSH was
assayed using London Diagnostics chemiluminescense immunometrlc assay.
Estradiol was determined using Diagnostic Products Corporation?s Coat-a-count
assay. 

39



 

Testosterone was assayed by the Mayo Clinic clinical laboratories. Total
testosterone was determined by RIA using proprietary immunoglobulins. Free
and bound testosterone was determined using equilibrium dialysis?.

WNW

Two methods were used to assess the accuracy and reliability of the laboratory
assays. The laboratories routinely followed quality assurance programs. Three
standards were mn with each batch. lithe control values were outside two
standard deviations of the intra assay mean value for each standard. the assay
was repeated. if 10 controls were outside 1 standard deviation of the mean. the
assay was flagged for review. The reliability of each of these asays was
assessed. For each assay, ?ve specimens were randomly selected and split into
two aliquots. The aliquots were labeled with different identifiers ensuring that the
assays were carried out in a blinded fashion. Both aliquots were submittedon the
same day to the laboratory. The coefficient of variation was calculated for each
hormone.



There were two analytic strategies. First, assay results were treated as
continuous parameters and modeled using regression methods. Models were fit
to assess the relationship between assay results and total fluorine. body mass
index, alcohol consumption, and smoking. Second. results were
dichotomized into those within. the reference range and those outside the
reference range. The hormone assay categories were based on published sex
speci?c normal reference values for each assay. The pumose of this
dichotomizatlon was to evaluate the possibility that highly susceptible individuals
may be affected at lower levels of exposure and not follow the adjusted dose-
response curve.

The relationships between total serum ?uorine and the assayed parameters were
estimated by fitting linear multivariate regression models to the data. The clinical
parameters and ratios of selected parameters were ?rst modeled as functions of
nominally categorized exposure and covarimes. Dependent variables that were

40

12232

 

 

not normally distributed were appropriately transformed. Total serum fluorine was
categorized into mutually distinct categories. Cutolt values for the categories
were chosen to assure adequate numbers in each category while maintaining the
fullest range of exposure values possible. Accordingly, total serum ?uorine level
categories were de?ned as the following: less than 1 ppm, greater than 1 
toless than 4 ppm, 4 to 10 ppm, greater than 10 to 15 ppm, and greater
than 15 ppm. If insuf?cient numbers of events occurred within individual
categories. the number of categories was reduced by combining adjacent
categories. Additionally, models were ?tted with total serum ?uorine entered as a
continuous variable using linear, square, square root transformations.

Age. body mass index (BMI). alcohol use and tobacco use were included in the
model as potential confounders. Age was included in the models as both a
categorical variable and a continuous variable. Age was grouped into four ten
year age categories. Age was treated as a continuous variable using linear.
square. square root, and log transformations. BMI was entered in the models as
a categorical variable and as a continuous variable. BMI categories were less
than 25 kg/m2, 25-30 kg/m2 . and greater than so kg/m2. Additionally. BMI was
into obese, greater than 28 kglma, and non-obese. less than or
equal to 28 kg/mz. The continuous variable was entered as linear, square. log,
and square transformations. Alcohol use was categorized into 3 categories: less
than 1 drink per day. greater than one to 3 drinks per day. and non response to
the questionnaire item. Smoking was categorized as current nonsmokers and
current smokers. A nonresponse category was not included since only two
individuals were in this category. These two individuals were excluded from
analyses that required smoking history. Smoking was quanti?ed as cigarettes
smoked per day. Linear. square and square root transformations of cigarettes per
day were used in regression models.

The choice of the final model was somewhat subjective. For each dependent
variable. other covariates were included in the final model if they were potential
confounders. Other potential confounding. hormones and biochemical parameters
were included in the models if they produced signi?cant changes in effect
estimates. i

41

12233

 

Total serum fluorine and confounding covariates were entered into models as
continuous variables. Signi?cant nonlinear dose-response relationships were
evaluated by comparing model ?t and parameter estimates using categorical
variables and continuous variables. Square, square root. exponential. and
logarithmic transformations were used if the transformed variables produced
models of superior predictive power as assessed by model All two way
interactions between total serum ?uorine and the included covarlates were
evaluated. interaction terms were included in the ?nal model if the parameter
estimate for the interaction term was signi?cant at the alpha level.

The potential for susceptibility to confound the relationship between PFOA
exposure and the assayed parameters was examined by comparing the
observed prevalence of assay results outside of the reference range with the
expected prevalence. The prevalence of abnormal assays based on
published reference values for the adult male Us population. Reference ranges
for test parameters were de?ned as being within 2 standard deviations above or
below the mean value for the parameter. The laboratory maintains laboratory
and assay specific reference range for each assay. Given that the distribution of
values is approximately normal. about 2.5% of individual values are expected to
fall above the upper limit and 2.5% below the lower limit. It follows that the
prevalence for a high test is .025. The prevalence for a low value is .025. Using
these prevalences. an expected number of tests outside of the reference range
can be de?ned. A priori hypotheses based upon animal and in vitro studies
de?ned the expected direction of the effect. The calculation of an observed to
expected ratio allowed the estimation of the relative prevalence for a test outside
of the normal range in the study subjects as compared to the general population.
The 95% Cl for the ratio was calculated assuming that the expected number is a
constant and the observed number is a random variable with a Poisson
distribution.

42

12234

as

 

 

 

 

in October 1990. at the time of the cross sectional study. the workforce at
Chemolite consisted of 880 salaried and hourly employees. There were 50 men
and 2 women in high exposure potential jobs. Since there were only 2 women in
this group, the study was restricted to males. Forty-eight ot the 50 male
workers in high exposure potential jobs agreed to participate. The exact number
of low exposure workers invited to participate in the study was not recorded.
However, few individuals in this group refused to participate. Thus, it is estimated
that over 80% of low exposure workers participated.

WW

Since frequency matching for age was used to select study participants. the

overall age distribution reflected the age distribution of workers in high exposure
potential jobs (Table 4.1.1). Ages ranged from 24 to 59 years. with a median age
of 37 years and a mean age of 89.2 years. 

Table 4.1.2 presents the alcohol and tobacco use profile of the study participants.
The light drinkers category included 22 participants who reported no alcohol use.
Consumptionoi one to three ounces of ethanol per day was reported by 20
participants. No participants reported drinking greater than three ounces
of ethanol per day. Eight workers did not complete this item of the
questionnaire. There were 28 smokers who smoked an average of 21.7
cigarettes per day. Smoking status was not available for two workers 
The association between smoking and alcohol consumption is presented in Table
4.1.3. Thirteen of 85 nonsmokersand seven of 23 smokers
reported moderate drinking Table 4.1.4 displays the age distribution for
alcohol and tobacco use categories. There were no signi?cant differences in
mean ages among smoking or drinking categories.

12235

 

Total ?uorine was not signi?cantly correlated with age. BMI. alcohol. or tobacco
use able 4.1.5). BMI and age were correlated pa.005). Alcohol use
and tobacco use were not signi?cantly consisted (r338: 

BMI ranged from 18.8 to 40.5 kg/mz with a median value of 26.3 and a
mean of 26.9 kg/mZ (Table 4.1.6). Half of all workers had between 25 and
30 kglm2 . The mean BMI in smokers was not signi?cantly different from that of
nonsmokers (Table 4.17). The mean BMI for moderate drinkers was not
signi?cantly different from the BMI of light drinkers. Smoking status and BMI were
not signi?cantly associated (T able 4.1.8). There was a signi?cant linear
relationship between BMI and age (ls-.10 This relationship was not'
substantially altered alter adjusting for smoking status. alcohol use, and total
senim ?uorine level.

llZIllS 

The total serum ?uorine values ranged from zero to 26 with a median value of
two ppm, a mean of 3.27 and a standard deviation of 4.68 (T able
4.1.9). The Inter-assay coefficient of variation was 66% calculated from repeated
essays on different days.

Twenty-three of 115 ?workers had total serum fiUorine values less than
one ppm. This group included eight workers values reported as zero (below
the limits of detection). Eighty-eight workers had levels less than or
equal to three ppm. Six of 115 workers had values between 10 and 15
and ?ve had values greater than 15 ppm. All workers with levels
greater than ten. had worked in Building 15, the primary PFC production area at
the Chemolite Plant.

There were no significant diferences in total serum fluoride mean values among
the BMI. age. alcohol use and tobacco use categories (T able 4.1.10). No
statistically signi?cant differences in mean age between total fluorine categories
were observed (Table 4.1.11). 

12236

 

 

 

Participants with less than one total ?uorine smoked the least (16.3) number
of cigarettes per day (Table 4.1.12). Those with one to three total
?uorine smoked the greatest number of cigarettes per day (24.5). This difference
was statistically signi?cant As estimmed in a regression model. the
linear relationship between total ?uorine and smoking status. adjusted for age
and BMI. was small in magnitude Smokers
average total serum ?uorine was estimated to be 0.1 higher than
nonsmokers. The number of cigarettes smoked per day was weakly correlated
with total serum ?uorine (Table 4.1.5).

Drinking status was not associated with total ?uorine (Table 4.1.13). Overall.
eight participants did not respond to this question. Four had less than one
total serum ?uorine.

Table 4.1.14 presents the distributibn of BMI in the total ?uorine categories
de?ned previously. BMI mean values were not significant differences among the
total semm ?uorine categories. The linear relationship between BMI and total
?uorine. adjusted for age, smoking. and alcohol use, was weak and not
significant (Ba-.016 



The infra-assay coefficient of variation (CV) for the bound and free testosterone.
estradioi, TSH. LH, prolactin. and FSH assays are provided in Table 4.1.15. The
estradioi assay had the highest CV. 18.3%. The prolactin assay had the lowest
CV of 

Table 4.1.16 presents the observed and expected number of hormone assays
out of the assay reference range. the observed to expected ratio . and the
95% confidence limits. The 015 ratio was signi?cantly greater than one for
estradioi. free testosterone. bound testosterone and prolactin. The OIE ratios for
LH. FSH. and TSH were not significantly different from one.

The Pearson correlation coefficients among the seven hormones assayed In
study participants are presented in Table 4.1.17. As expected. estradioi was

45



 

 

 

 

correlated with free testosterone p=.0001) and bound testosterone 
Bound testosterone was correlated with free testosterone (r=.74
LH p=.003) and FSH LH and FSH were
signi?cantly correlated FSH and TSH were signi?cantly
consisted pant).

As shown in Table 4.1.18, total ?uorine was signi?cantly correlated with proiactin

p=.045) and TSH Age was negatively correlated with 
estradioi (rs-.25. free testosterone (rs-.45. bound testosterone :9
?p.24. and prolactin (rs-.19. Age was positively consisted with
FSH As expected, BMI was negatively correlated with free and

bound testosterone( ran-.26. p-.005 and r-.36, p=.0001 respectively). BMI was

correlated positively with LH Alcohol consumption was

signi?cantly consisted with FSH (rs-.24 

Bound testosterone ranged from 141 to 1192 ng/dl with a mean of 572 and
a median of 561 (T able 4.1.19). The standard deviations were large. The
mean bound testosterone values were not signi?cantly different among the total
serum ?uorine groups. As expected, the mean bound testosterone decreased
signi?cantly as increased. The mean bound testosterone values were
signi?cantly different among the age categories 

There was a signi?cant nonlinear relationship between total serum fluorine and
bound testosterone in the ?nal regression model (Table 4.1.20). Bound 
testo?erone, which was positively associated with both LH and estradiol.

decreased as both age and BMI increased. Alcohol and cigarette use were

weakly associated with BT. There was a signi?cant interaction between age and

total serum fluorine. There was a negative association between bound

testoaerone and total serum ?uorine in young workers than in older workers. in

workers greater than 45 years of age. total serum ?uorine was associated with a

slight Increase in BT. The relationship between bound testosterone and total

serum fluorine is presented for tour different sets of covariate value (Figure 2 

Dose-response curves for bound testosterone were plotted for young. lean

individuals aged 30 with of 25. young obese individuals aged 30 with 

of 35. middle aged lean individuals aged 50 with of 25. and middle aged

46

12238

 

 

obese individuals aged 50 with of 35. Each of the relationships is for
nonsmoking, light drinking men with the sample mean LH value (5.4 mU/i) and
mean estradiol value (33.4 in 30 year old workers, bound testosterone
decreased as total serum ?uorine increased in both groups. The dose-
response relationship for 40 year old workers was approximately flat (not shown).
In workers greater than 50 year of age, BT increased as total serum ?uorine
increased.

Total serum ?uoride was not signi?cantly associated with free testosterone 
(Table 4.1.21). Within categories, free testosterone was highest in the less
than 25 lthm2 group and lowest in the greater than 30 category. The
difference in mean FT among categories was statistically significant 

There was a signi?cant nonlinear dose-response relationship between total
serum ?uorine and FT in the final?regression model (Table 4.1.22). As total
serum ?uorine increased. free testosterone decreased. There was a significant
interaction between age and total serum ?uorine. Figure 4.2 illustrates the
modifying effect of age on the total serum ?uorine tree testosterone relationship.
The covarlate vectors (nonsmoker. light drinker. mean LH and estradiol. age=30
and or 25. age==50 and or 35) were the same as used Figure-1.
Lean or obese 50 year old men had low free testosterone (less than 9 for

all values of total serum ?uorine. In 30 year olds. tree testosterone decreased

toward the 50 year old values. in this model. a 50 year old. obese,
moderate drinker with any total serum ?uorine level (the lower limit of assay
sensitivity was approximately 1 total serum ?uorine) had free testosterone
below nine .

As shown in Table 4.1.23. the estradiol means in the three groups were not
significantly different As the age of participants increased. mean
estradiol levels decreased. In the greater than 30 to 40 year age group. mean
estradiol was 36.8 compared to 25.9 in the greater than 50 to 60
year age group. The age group means were signi?cantly different (p.018).
There was a nonsignificant positive association between mean estradiol and total
serum ?uorine.

47

12239

 

 

As shown in Table 4.1.24, estradiol and total serum fluorine were positively
associated in the ?nal regression model. Total serum fluorine followed a
nonlinear relationship with estradiol. No interaction terms were statistically
signi?cant. As expected, tree testosterone and estradioi were positively
associated (ls-.85 The relationship between total serum ?uorine and
estradiol is illustrated in Figure 3. The plotted curves depict the relationship for
lean (25 and obese (as kg/m2) male workers who were so years old with
sample mean free testamerone and who were nonsmokers and light drinkers. As
total semm ?uorine increased over the observed range. estradol increased
quadratically. in obese men kg/m2 aged so, estradiol exceeded 44
when total serum ?uorine was between 15 and 20 ppm. The highest
estradiol levels were in young. obese smokers who consumed 1 to 8 ounces of
ethanol per day.

LH was not signi?cantly associated with senim ?uorine. but was negatively
associated with (p=.003) and positively associated with smoking 
age. and BT . There was no association between total semm ?uorine and FT.
(T able 4.1.25. Table 4.1.26, and Figure 4).

FSH was not signi?cantly related to total serum ?uorine levels but was positively
associated with age (p=.014) (Table 4.1.27. Table 4.1.28). The final regression

. model for FSH ls illustrated in Figure 5. The relationship was essentially ?at over
the total ?uorine range.

TSH was positively associated with total semm ?uorine in both univariate and
multivariate analyses (T able 4.1.29. Table 4.1.30 and Figure 7). TSH was not
significantly related to age. alcohol use. smoking. and other hormones.

Prolactin was positively associated with total. serum ?uorine and smoldng (Table
4.1.31. Table 4.1.32). Moderate drinkers had a different prolactln-total serum
?uorine relationship compared to light drinkers and nonrespondents. Figure 6
illustrates the relationship of prolactin with total serum fluorine and the modifying
effect of alcohol use. Total serum ?uorine was weakly associated with prolactin
in light and moderate drinkers. However, in moderate drinkers (1 ~3 ozlday).
there was a positive association between prolactin and total semm ?uorine.

48

12240

 



The univariate distributions of the 21 ratios are provided in Appendices 4.1 and
4.2. A table is presented for each of the 21 ratios showing the number of
participants, mean ratio value with the standard deviation. median ratio value.
and the range of ratio values in each of the previously de?ned categories of BMI.
age, alcohol use, tobacco use. and total serum ?uorine

Correlations between total serum ?uorine (ppm), age (years). BMI (kg/m2).
alcohol use (oz/day), and cigarette consumption (cigarettes/day) and all possible
ratios between E. free testosterone TF. TB. and LH are displayed in Table 4.1.33.
The estradiol to bound testosterone ratio (EH8) and estradiol to free testosterone
ratio (Efl?F) were significantly consisted with BMI p=.001 and r=.27.
p=.oo4 respectively). The estradiol to luteinlzing hormone ratio (EILH) was
negatively consisted with age (re-.26, and positively correlated with BMI
(ra.18, The bound testosterone to luteinizing hormone ratio (TBILH)
followed a different pattern as compared to EILH. The correlation coefficient
between TBILH and age was -.32 (p=.001) while the coef?cient between TBILH
and BMI was -.14. (pasta). The free testosterone to luteinizing hormone ratio
(TFILH) had the strongest correlation with age (rs-.40, p=.0001) but was not
significantly consisted with BMI. The bound testosterone to free testosterone
ratio followed a unique pattern. TBITF was positively correlated with age
and negatively correlated with BMI 

Prolactin ratios with bound testosterone free testosterone (TFIP).
estradiol (EIP), follicle stimulating hormone (FSHIP). luteinizing hormone (PILH).
and thyroid stimula?ng hormone (PITSH) are presented in Table 4.1.34. None of
the prolsctin-hormone ratios were significantly consisted with total serum fluorine
or BMI. All except were signi?cantly correlated with cigarette
consumption.

Table 4.1.35 presents the Pearson conelstion coefficients for the bound
testosterone to thyroid stimulating hormone (T BITSH) ratio, the free testosterone
to thyroid stimulating hormone (TFITSH), and the estradiol to thyroid stimulating .

49

 

12241

 

hormone Total serum ?uorine and were negatively correlated
All three ratios were signi?cantly and negatively consisted with
age. TBIT SH and TFIT SH were negatively correlated with Bil/ll, p=.01

and far-.23. p==01 respectively).

The Pearson correlation coef?cients for the bound testosterone to follicle
stimulating hormone (TBIFSH) ratio. the tree testosterone to follicle stimulating
hormone (TFIFSH). and the estradicl to follicle stimulating hormone (ElFSi-i) are
provided in Table 4.1.36. Age was the only covariate that significantly
correlated with the three ratios.

The correlation coefficients for selected ratios between pituitary glycoprctein
hormones. TSH, LH. and LH, are presented in Table 4.1.37. The thyroid
stimulating hormone to follicle stimulating hormone (T SHIFSH), the thyroid
stimulating hormone to luteinizing hormone (T SHILH). and the follicle stimulating
hormone to luteinizing hormone are provided. Age was signi?cantly
consisted with the FSHILH ratio and the TSHIFSH ratio. Alcohol consumption
was consisted with both and TSHILH.

As shown in the final regression models. the TBITF ratio increased as total semm

?uorine increased (Tables 4.38 and 4.39). Alcohol consumption. cigarette

. consumption, estradiol. proiaotin. and TSH were not significantly related to the

TBITF ratio in either model. These covariates do not substantially alter the 
estimated relationship between. total serum ?uorine and TBITF ratio when -
included in the regression model. The quadratic increase of the TBITF ratio over

the observed range of total serum ?uorine is illustrated in Figure 4.3. The

oovariates used were: nonsmoker, less than one ounce of alcohol consumed per

day. 30 years of age. and a BMI of 30 kg/m2.

Table 4.1.40 presents the full regression model for the estradlol to bound
testosterone ratio (EITB). Total serum fluorine was not significantly assodated
with the ENS ratio. was a ot the EITB ratio. Free testosterone
was negatively related to the Efi'B ratio.

12242

 

 

The full regression model for estradiol to tree testosterone ratio is
displayed in Table 4.1.41. There was a signi?cant positive dose-response
relationship between the EITF ratio and total serum ?uorine. Although the dose-
response relationship for tree testosterone was modi?ed by age. the dose-
response relationship for the ratio was not modified by age.

As shown in Tables 4.1.42, 4.1.43 and 4.1.44, total serum ?uorine was not
signi?cantly associated with and TBILH. but was positively association with
the ratio (Ba-.05. Bound testosterone and FSH were associated
with the TFILH ratio p=.0001) and (39.33, 

Cigarette consumption and free testosterone were strongly and significantly
related to the TBIP ratio and 8:3.93. p=.008 respectively) (Table
4.1.45). Cigarette consumption and bound testosterone were signi?cantly related
to the ratio p=.03 and p=.03 respectively) (Table 4.1.46).
Only cigarette consumption was signi?cantly related to the BF ratio 
p=.005) (T able 4.1.47).

Tables 4.48 through 4.50 present full regression models for the ratios of prolactin
to FSH (PIFSH). prolactin to LH (PILH). and prolactin to TSH (PIT SH). in each of
the three regression models total serum ?uorine was positively and signi?cantly

. associated with the prolactin-hormone ratio. Moderate drinkers had a

signi?cantly different ratio total serum fluorine dose-response relationship
compared to the relationships in light drinker and nonrespondents.

The full regression models for the glycoprotein hormone ratios are presented in
Table 4.1.51 to 4.1.59. As shown in table 4.1.52, total serum ?uorine was
related to (Ba-.28. p=.03) and bound testosterone and FSH
were signi?cantly related to the SH ratio (Ba. 01 pa. 006 and 812.68. p=.04
respectively). Total serum ?uorine was not signi?cantly associated with the other
glycoprotein hormone ratios.

 

51

12243

 

Table 4.1.60 provides the correlation coef?cients for serum lipids. speci?cally
cholesterol, low density Iipoprotein (LDL). and high density lipoprotein (HDL), with
total serum ?uorine. age, BMI, alcohol consumption. and cigarette consumption.
Total serum ?uorine was not signi?cantly correlated with cholesterol. LDL. HDL,
or triglycerides. Cholesterol and triglycerides were correlated with age r=.25,
p=.008 and r=.19, p=.04, respectively), and BMI p=.o4 and r=.27, 
respectively). Cigarette smoking was positively and signi?cantly correlated with
cholesterol LDL (rt-.28, pa.002), and triglycerides 
HDL was not signi?cantly correlated with any variable. although the correlation
with alcohol consumption was suggestive r-.18, 

Total ?uorine was not signi?cantly associated with cholesterol. LDL or
triglycerides ("Fables 4.1.61 Table 4.1.62. Table 4.1.64). Smoking, age, and
GGT were positively and signi?cantly associated with cholesterol. Smoking and
prolactin were positively and significantly associated with LDL Smoking and free
testosterone were positively associated and bound testosterone was negatively
associated with triglycerides.

The final regression model for HDL, displayed in Table 4.1.63. presents a
different picture. HDL decreased as total fluorine increased in moderate drinkers.
In light drinkers, there was a negligible change in HDL as total ?uorine increased.

?Self~reported moderate alcohol consumption was positively associated with HDL
Additionally, bound testosterone was positively associated with HDL. while tree
testosterone was negatively associated.

 

Table 4.1.65 presents the correlation coefficients between the hepatic
parameters, seer. seer. Ger, AKPH, and total serum ?uorine. age. BMI,
alcohol consumption. and cigarette consumption. The hepatic parameters were
not signi?cantly correlated with total serum ?uorine. SGOT was not signi?cantly
correlated with any of the participant characteristics. SGPT and GGT were 
correlated signi?cantly only with BMI p=.02 and r227. pa.004

52

 

 



12244

 

 

respectively). AKPH was signi?cantly correlated with age. BMI, alcohol
consumption, and cigarette consumption.

The correlation coef?cients between the hepatic parameters and cholesterol,
LDL. HDL. triglycerides. estradiol. TF, TB. and prolactln are displayed in Table
4.1.66. SGOT and AKPH were signi?cantly correlated with prolactln. SGPT was
correlated with cholesterol and triglycerides. GGT was correlated with
cholesterol. triglycerides. and free testosterone. As expected. SGOT. SGPT, and
GGT were highly correlated (Table 4.1.67). AKPH was only correlated with GGT.

The SGOT. SGPT, GGT, and AKPH mean values were not significantly different
among the five total serum fluorine categories (Table 4.1.68). SGOT and SGPT
mean values were not significantly different for BMI. age. alcohol use. and
smoking ables 4.1.69 to 4.1.72) . Mean GGT was significantly higher in the
greater than thirty BMI group (pace). As shown in Table 4.1.72. mean and
median AKPH values were significantly higher in smokers compared to
nonsmokers 

Tables 4.1.73 A. B. and 0 present three linear multiple regression models for
SGOT. In non-obese workers SGOT decreased as total ?uorine
increased. In obese workers (BMI: 35). the association between total serum

. fluorine and SGOT was in the opposite direction. Model 2 included GGT as a
covariate (Table 4.1.73 B). The association between total fluorine and SGOT, as
well as the effect modification by BMI, were present after adjusting for GGT.) .
When seer was included in the regression model (Table 4.1.73 0), the 
association between total fluorine and SGOT was weak and nonsigniflcant- The
effect modification by BMI was no longer present. AKPH had little effect on the
regression estimates when included in the model.

Three linear multiple regression models for SGPT are provided in Tables 4.1.74
A. B. and C. In non-obese workers (BMI-25), SGPT decreased as total fluorine
increased. However, in obese workers (BMI- 35), the association between total
serum fluorine and SGPT was in the opposite direction. Little change occurred in
the estimates after adjusting for GGT. As seen in Table 4.1.74 0, the association
was significant, although weaker in strength, after adjusting for SGOT. The effect

53

12245

 

modi?cation by BMI was present. When AKPH was included in the model. effect
estimates did not change signi?can?y.

The ?nal regression models for GGT. provided in Tables 4.75 A, B. and C.
present a different picture. GGT decreased as total ?uorine increased in
moderate drinkers. In light drinkers, GGT decreased less steeply as total ?uorine
increased. Controlling for SGOT and SGPT (model 2 and 3) did not signi?cantly
alter the relationship between total ?uorine and GGT. Moderate alcohol
consumption was positively associated with GGT.

Table 4.1.76 presents the ?nal regression model for AKPH. ln nonsmokers. total
serum ?uorine was negatively associated with AKPH. As the number of
cigarettes smoked per day increased to more than five per day. AKPH increased
as total serum ?uorine increased.

 

Table 4.1.77 presents the correlation coefficients between the nine hematology

parameters and total serum ?uorine, age, alcohol use. and cigarette

consumption. The only parameter that was signi?cantly correlated with total

serum ?uorine was count Monocyte count was a:
correlated with BMI p=.04) and alcohol consumption, pa.03).. All 
the parameters, except the basophil and band counts. were strongly associated -
with cigarette consumption. Alcohol consumption was correlated with ..
hemoglobin,? (ran-.20. pu.04). and band count 

The ?nal regression models for hemoglobin and the indices. mean
corpuscular hemoglobin (MCH) and mean corpuscular volume (MCV). are
presented in Tables 4.1.78. 4.1.79. and 4.1.80 respectively. Total serum ?uorine
was significantly asSociated with hemoglobin. The association hemoglobin and
MCV were modified by smoking. In smokers who smoked seven or more
cigarettes per day. hemaglobln and MCV increased signi?cantly as total ?uorine
increased. in nonsmokers. hemaglobln and MCVdecreased as total ?uorine

54

12246

 

 

 

increased . The association of total ?uorine with MCH was modi?ed by Smoking
and by alcohol use. The increase in MCH as total ?uorine Increased was
enhanced with Increased smoking. In light drinkers. total semm ?uorine had a
weak association with MCH. ln moderate drinkers. MCH Increased as total
fluorine Increased. There was a positive association of both MCH and MCV with
alcohol consumption. None of the estimated associations are of clinically
signi?cant magnitude over the range of total ?uorine values.

The white blood cell count (WBC) increased signi?cantly in nonrespondents as
total fluorine increased above 2ppm, increased less in moderate drinkers. and
increased the least in light drinkersi'l'able 4.1.81). As expected. cigarette
smoking intensity was positively associated with WBC. PMN Increased
signi?cantly in alcohol use nonrespondents as total ?uorine increased and
increased less steeply in moderate drinkers (Table 4.1.82). in light drinkers. total
serum ?uoride above 10 was associated with a decreased in PMN.
Cigarette smoking was positively associated with PMN. As shown in Table
4.1.83. the ?nal regression models for band count provides little evidence that
total fluorine was associated with band count. Moderate alcohol use was
estimated to reduce the band count. Smoking was positively associated with
band count.

.The negative association between total ?uorine and count was
modified by adiposity. alcohol consumption, and cigarette smoking (Table
4.1.84). The decrease in count was smaller as Bill" increased. The
decrease in count associated with total ?uorine above 3 was
greater in moderate drinkers compared to nonrespondents. As cigarette
consumption increased, the decrease in count increased.

The positive association between total ?uorine and monocyte count (MONO) was
modi?ed by adiposity (Table 4.1.85). As increased, the association with
MONO was weaker. Cigarette smoking and LH were positively associated with
MONO. Alcohol consumption was negatively associated with MONO. The
association between total ?uorine and eosinophil count (EOS) was negative for
nonsmokers. but was positive as more than ten cigarettes per day were smoked

55

12247

(fable 4.1.86). As smoking increased. the PFOA associated decrease in BASO
was smaller (Table 4.1.88).

The association between total ?uorine and platelet count (PLAT) was modified by
adiposity and cigarette smoking intensity (Table 4. ?l 8.7) in lean participants
PLAT increased as total fluorine increased. in obese participants
(BMle40), the PLAT decreased as total ?uorine increased. As smoking
increased the rate of increase in PLAT associated with total ?uorine above 10
decreased.



The serum ?uorine levels in Chemolite workers were 20-100 times higher than
expected in workers not directly involved in PFOA production. All workers with
levels above 10 ?uorine work in PFOA production areas. Smoking was
associated with a small increase in semm ?uorine. Age was not associated with
serum ?uorine levels. The two women employed in the PFOA production areas
had total serum ?uorine levels similarto men.

Alcohol use, smoking. age, BMI, and hormones had the expected associations
With peripheral leukocyte counts, hematology parameters. cholesterol. HDL. LDL,
"and hepatic enzymes.

The main hormone results are:

1. The number of male workers with hormone values outside of the
laboratory reference range was greater than expected for estradlol. free
testosterone, bound testosterone. and prolactin.

2. Total serum ?uorine was negatively associated with free testosterone
and positively associated with estradiol. No association was noted
between total serum ?uorine and LH.

3. EITF and TBITF, but not were positively with total
serum ?uorine.

4. EILH and were not associated with total semm fluorine. However,
the relationship between total sentm ?uorine and was suggestive.

56

12248

5. TSH was positively associated with total serum ?uorine. TFITSH was
negatively associated with total semm ?uorine; and EITSH were
not.

6. Prolactin and total semm ?uorine were positively associated In moderate
drinkers. but not in light drinkers.

7. PIFSH. PITSH were positively associated with total serum ?uorine.
TFIP, and EIP were not associated with total serum ?uorine

The main hepatic parameter results are:

1. The increase in SGOT and SGPT levels associated with adiposity was
enhanced by total serum ?uorine.

1 2. The induction of GGT by alcohol was decreased as total serum ?uorine

increased.

 

3. The induction of AKPH by smoking was increased by increasing levels of
total serum ?uorine.

The main cholesterol and lipoprotein results are:

1. Cholesterol and triglyceride levels were not associated with total serum
?uorine.

2. LDL not associated with total serum ?uorine.

3. The positive association between moderate alcohol use and HDL levels
was reduced as total serum fluorine increased.

The main hematology parameter and peripheral leukocyte count results are:

1. The effect of smoking on hemoglobin and MCV was enhanced by total
serum ?uorine.

2. Total serum ?uorine was negatively associated with all peripheral
leukocyte counts except PMNs and MONOs, which were positively
associated. 

3. The associations between cell counts and total serum ?uorine were
modified by smoking, drinking, and adiposity.

57

12249

 

A total of 3.537 Individualswho were employed at the Chemolite plant between
January 1. 1947 and December 81. 1983 were identi?ed from company records.
The cohort consisted of 2.788 male and 749 females employees
(Tables 4.2.1 and 4.2.2). The majority of women never worked in the
Chemical Division. Of the 19,309 person years (PY) observed for women. 68.8%
occurred in those who were never employed in the Chemical Division. The mean
follow-up for women was 25.8 years in the overall cohort, 24.6 years in the
Chemical Division (CD) cohort, and 26.4 years in the non-CD cohort. The
distribution of follow-up periods was similar in the women?s CD and non-CD
cohorts.

The women's mean age at first employment was 27.6 years. Sixty-eight percent

were less than 30 years old at employment: 9.7% were older than 40 at first

employment at Chemolite. The CD cohort was older than the non-CD

cohort. The CD and non-CD distributions of latency times were not statistically

different The mean duration of employment for women was 8.7 years

and ranged from six months to 41.4 years. The distribution of years of

employment was signi?cantly different for CD and non-CD women Of

non?CD women, 11.9% were employed for more than twenty years. Of 245
women in the CD cohort. 51 were employed for more than twenty years. it?

As shown in Table 4.2.2, the 2,788 men who were ever employed for more than
six months at Chemolite contributed a total of 71.1 17.7 PY?which was about
equally divided between the CD and non-CD cohorts. The mean follow-up for the
overall male cohort was 25.5 years. The distribution of follow-up periods and
distribution of year of first employment was similar in the male CD and non-CD
cohorts. The average age at death was higher in the male non-CD group, 58.1
years, compared to the CD group, 54.2 years. The duration of employment for
men (mean 13.6 years, median 9.8 years) Was longer than for women. The
distribution of years of employment was signi?cantly different for CD and non-CD
men Of non-CD men, 25.5% were employed for longer than twenty

58

12250

 

years. Of men in the CD cohort. 38.0% were employed for longer than twenty
years.

Vital status was obtained for 100% of the women?s cohort (Table 4.2.3). Among
the 749 women there were 50 deaths; 11 in the CD cohort and 39 in the non-CD
cohort. Vital status was obtained for 100% of the men's cohort. Among the 2788
men there were 348 deaths; 148 deaths in the CD group and 200 in the non-CD
group. Six individuals who had employment records that were missing
information were excluded from the cohort and their vital status was not
ascertained. Death certi?cates were obtained for 99.5% of deaths. Two deaths
occurred outside the U.S. and causes of death were ascertained by other means.

ll' 


The numbers of deaths. the SMHs and 95% confidence intervals (Cl) among
women in the 1947-198910llow-up period are shown in Table 4.2.5. The 
for all causes of death 95% CI 56-39). and cancer 95%
Cl .42-1.14) were signi?cantly lower than expected in comparison to national
rates. No association was found with duration of employment or latency for
deaths from all causes. cancer, and cardiovascular diseases (Tables 4.2.6 and
4.2.7). for CD women and non-CD women are displayed in Table 4.2.8.
The estimated SMR for the CD cohort of women were less than expected. in CD
women. the all causes SMR was .46 (95% Cl .23..86) and the cancer was
.31 (95% Cl The SMRs for the non-CD women were closer to unity.

mm

The number at male deaths. the expected number of male deaths based on us.
national white male rates, and age and calendar period adjusted SMRs with
associated 95% are presented in Table 4.2.9. The for all causes (.73.
95% Cl .66..81). for cardiovascular diseases (swear/1. 95% Cl 60..48), for all
gastrointestinal (GI) diseases (50.95% Cl .26..87) and for all respiratory
diseases (50.95% Cl .27..86) were significantly less than one. None of the

59



cause-speci?c SMRs were large nor were the estimates signi?cantly different
from one. As shown in Table 4.2.10. the results were similar when the expected
numbem of male deaths was based on Minnesota white male rates.

Table 4.2.11. Table 4.2.12. and Table 4.2.13 present adjusted and 95% Cl

for males based on Minnesota mortality rates for three latency intervals 10. 15.

and 20 years respectively. The three latency intervals the all causes SMR

ranged from .75 to .77. For all cancers. SMRs ranged from 1.06 to 1.12 and

were nonsigni?cant. Among men there was no association between any cause 
of death and duration of employment (Table 4.2.14. Table 4.2.15. and Table 2
4.2.16).

Table 4.2.17 and 4.2.18 display the SMRs and 95% CI for CD and non-CD male
workers. The all causes SMRs were .69 (.59..79) for the non CD group and .86
(12.1.01) for the CD group. The for prostate cancer. based on a
comparison with Minnesota population rates. were 2.03 (95% Cl .55.4.59) in the
CD group and .58 (95% Cl .07.2.09) in the non-CD cohort. There were 4
observed deaths from prostate cancer compared to 2 expected in the CD group.
The latency analysis tor non-CD and CD men are presented in Tables 4.2.19 and
4.2.20. There was no associations between any cause of death and latency In
either group.

As shown in Table 4.2.21 and 4.2.22. male CD cohort members with more than
10 or more than 20 years of employment had that were less than one for
all causes of death. all malignancy. cardiovascular diseases and all respiratory
diseases. Among male non-CD cohort members with more than ten years of
employment or more 20 years of employment. the for all causes.
cardiovascular disease and all respiratory diseases were signi?cantly less than
expected (T able 4.2.23 and 4.2.24). There was no association of any cause of
death with duration of employment at Chemollte in either CD or nonch groups.

W51

Age adjusted standardized rate ratios (SFiFts) were calculated for all causes. all
cancer. and cardiovascular diseases mortality comparing men employed at the

60

12252

 

plant for ten years or more to men employed for less than ten years. The SRRs
are presented in Table 4.2.25. The 95% for all causes. all cancer. and all
cardiovascular diseases were wide and include one. Confounding variables such
as year at ?rst employment and length of follow-up were not controlled in this
analysis due to small numbers and unstable rates within the large number of

strata.

Table 4.226 presents the age adjusted SRRs for all causes. all cancers. lung
cancer. GI cancer. and all cardiovascular diseases mortality comparing men ever
employed in the CD with men never employed in the CD. All SFle were 
greater than one, however. none was statistically signi?cant.

WEISS. (RRMH)

Age strati?ed RRMH. contrasting the rates in men over employed in the CD
compared to the rates in men never employed in the CD. were calculated for all
causes. all cancer. and all cardiovascular diseases mortality and are displayed in
Table 4.2.27. The estimated RH for CD employment versus non-CD employment
did not follow a monotonic pattern and the 95% include one for each of the
three endpoints.

- Table 4.2.28 presents the RRMH for men employed for less than ten years to
those employed for more than ten years. The all causes RRMH (2.16, 95% Cl
1.52, 2.70) in the 30 to 39 year age at ?rst employment strata was re?ected in
both the for all cancers (1.75, 95% Cl.95.3.21) and cardiovascular
diseases (3.53 . 95% Cl 1.68.62?. The RRMH were not adjusted for important
time oovariates such as the year of first employment.

 

Table 4.2.29 to 4.2.36 show the ?nal proportional hazard (PH) model for death
from all causes, cardiovascular diseases. all cancers. lung cancer. Gl cancer,
prostate cancer. pancreatic cancer, and diabetes among the 2788 male workers

61

12253

 

ever employed at Chemolite for greater than six months. There was no evidence
for violation of the PH assumptions or for signi?cant nonlinear associations
between the independent variables and mortality. As expected. age at ?rst
employment was positively associated with all causes of death. The RH for a
one year increase in age at ?rst employment was 1.082 (95% Cl 
Year of ?rst employment and duration of employment were negatively associated
with all causes mortality. The risk of death associated with months in the
Chemical Division was small and nonsigni?cant.

For cardiovascular diseases mortality, the HR for a one year increase in age at
?rst employment was 1.126 (95% Cl 1.069.1.094). Year of ?rst employment was
negatively associated with cardiovascular diseases mortality. Time in the CD
was not associated with death from cardiovascular diseases.

Age at ?rst employment was positively associated with cancer mortality. The HR
for a one year increase in age of employment was 1.08 (95% Cl 1.06.1.10).
Duration of employment was negatively associated with cancer. The HR was
.972 95% Cl.96..99)1or a one year increase in employment. There was no
association of cancer mortality with employment time in the CD.

The ?nal prostate cancer mortality proportional hazard model for male cohort
members is shown in Table 4.2.34. Time in the Chemical Division was positively
and significantly associated with prostate cancer mortality. The relative risk for a
one year increase in CD employment time was 1.13 (95% Cl 1.01.1.43). Age at
?rst employment was positively associated with prostate cancer mortality risk. A
one year increase in age at ?rst employment was associated with a HR of 1.09
(95% Cl 99.1.19). The HR tor lung cancer mortality was 1.07 (95% Cl .03.1.12)
tor a one year increase in age of employment. Months in the chemical division
was not signi?cantly associated with lung cancer mortality. Table 4.2.33 shows
the ?nal proportional hazard (PH) model for all (31 cancer mortality. The
estimated HR for a one year increase in age at ?rst employment was 1.14 (95%
CI 1.09.1.19). Year of ?rst employment. duration at employment and time
employed in the co were not associated with Gl cancer risk. Age at ?rst
employment was positively associated with pancreatic cancer mortality. The
other covariates were weakly associated with pancreatic cancer risk and were

62

12254

 

 

not signi?cantly different from one. A one year increase in age at first
employment was positIVely associated with diabetes mortality (an a: 1.10. 95%




Table 4.2.37, 4.2.38 and 4.2.39 show the ?nal PH model for death from all
causes. cardiovascular diseases and all cancers among the 749 female cohort
members. Age at ?rst employment was positively associated with all causes
mortality. The HR for all causes of death among women employed fortwo to ten
years (3.72) and among women employed for greater than ten years (2.33) were
signi?camly greater than the all causes mortality in women employed for less
than two years. Time in the CD was not related to mortality. The RH for death
from cardiovascular diseases associated with a one year increase in age at first
employment was 1.13 (1 .07.1.18). The year at first employment. duration of
employment, and time in the CD were not signi?cantly associated with female
cardiovascular diseases mortality. The HR for death from cancer was associated
with age at first employment. A one year increase in age at ?rst employment
increase the HR for death from cancer (1.09 (1 .04,1 .14). The year at ?rst
employment. duration of employment, and time in the chemical division were

. weakly and non-significantly associated with female cancer mortality.

63

12255

WW

TABLE 4.1.1 AGE DISTRIBUTION IN FIVE YEAR AGE GROUPS
3M CHEMOLITE PLANT, COTTAGE GROVE. MINNESOTA

 

 

 

AGE NUMBER PERCENT
21-25 3 2.6
26-30 18 15.7
31 -35 26 22.6
36-40 22 1 9.1
41-45 1 8 1 5.7
46-50 9 7.8
51-55 13 11.3
56-60 6 5.2
TOTAL 115 100.0
MEAN 39.2
SD 8.91
MEDIAN 37
RANGE 24-59
64

 

12256

 

 

TABLE 4.1 .2 DISTRIBUTION OF ALCOHOL AND TOBACCO USE
3M CH EMOLITE PLANT, COTTAGE GROVE. MINNESOTA

 

 

 

USE STATUS NUMBER PERCENT
TOBACCO USE
CURRENT SMOKER 28 24.3
NONSMOKER 85 73.9
MISSING VALUES 2 1.8
TOTAL 115 100.0
ALCOHOL USE
<1 oz 87 75.6
1-302 20 17.4
MISSING VALUES 8 7.0
TOTAL 115 100.0
?Includes 22 nondrinkers

65



 

TABLE 4.1.3 THE JOINT DISTRIBUTION OF TOBACCO AND ALCOHOL USE
3M CHEMOLITE PLANT . COTTAGE GROVE. MINNESOTA

 

         

TOBACCO USE

ALCOHOL
use
<1ozlday 19 57 1 37 
1-3onday 7 13 0 20 
missing 2 5 0 
TOTAL 28 (100%) 05 (100%) 2 (100%) 115 (100%)

 

66

12258

TABLE 4.1.4 DISTRIBUTION OF AGE BY SMOKING AND DRINKING STATUS.
3M CHEMOLITE PLANT. COTTAGE GROVE, MINNESOTA

 

 

AG-ETyaars)
MEAN SD MEDIAN RANGE 

Alcohol
<1ozld 87 39.9 9.31 37 24-59
13071:! 20 37.5 6.95 37 27-51 'p-.29
missing 9 36.6 9.70 35 27-54 ?p-.17
Tobacco
smoker 28 40.4 7.59 39 28-54
nonsmokor 85 39.0 9.35 37 24?59 'p-.47
missing 2 325 3.53 32 30-35
TOTAL 1 15 39.2 8.91 37 24-59

 

 

?Student test. Prob>T. reference groups <1 oz/day, smoker

67

 

12259

 

TABLE 4.1.5 PEARSON CORRELATION COEFFICIENTS BETWEEN TOTAL
SERUM FLUORINE. AGE. BODY MASS INDEX (BMI).
DAILY ALCOHOL USE. AND DAILY TOBACCOCONSUMPTION.
3M CHEMOLITE PLANT, COTTAGE GROVE. MINNESOTA

 

(years) am TOBACCO
FLUORINE (ozldav) (clumsy)

 
 



   

 

 

 

 

 

 

 

 

 

 

 

1 004 .0002 - 007 006
FLUORINE
- 1 .26 15
ACE 9-.005
- . .08
ALCOHOL
- - - - ?1
TOBACCO
I

I

68

12260

TABLE 4.1.6 BODY MASS INDEX DISTRIBUTION
3M CHEMOLITE PLANT. COTTAGE GROVE, MINNESOTA

 

 

 

 

BMI NUMBER PERCENT

-1

40
?25-30 57 49.5
>30-35 15 13.0
?35-45 2 1.8
TOTAL 115 100.0
MEAN 26.9
SD 3.4
MEDIAN Bl? 26.3
RANGE 18.8-40.5

69



 

TABLE 4.1.7 BODY MASS INDEX BY SMOKING AND DRINKING STATUS.
3M CHEMOLITE PLANT, COTTAGE GROVE. MINNESOTA

 

smog/mi)

MEDIAN RAGE 

   

<1ozfd 87 28.9 3.54 26.1 18.8-40.5

13021:! 20 27.2 3.10 27.0 22.8-33.7 ?p-.71
missing 8 25.9 3.64 26.1 21.3-30.4

Tobacco

smoker 28 26.6 3.63 28.3 18.8-28.2

nonsmoker 85 27.0 2.99 26.6 21 .4-33.7 'p-.57
missing 2 26.2 2.87 28.2 24.1-28.2

Total 115 26.8 3.45 28.3 18.8-40.5

 

'Student test. ttest p-value. reference groups <1ozlday, smoker

7O

12262

TABLE 4.1.8 THE DISTRIBUTION OF AGE. ALCOHOL AND TOBACCO USE BY

 

 

   
 

 

 

BODY MASS INDEX
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA
BMI nag/kg2


SMOKER 11 15 2 
NONSMOKER 41 15 
MISSING 1 1 0 
TOTAL 41 (100%) a (100%) 17 (100%)
ALCOHOL USE
<1 ozlday 31 43 13 
1-3 07109)! 6 11 3 
MISSING 4 a 1 
TOTAL 41 (100%) a (100%) 17 (100%)
AGE
<40 was 31 
>49 years 10 29 11 
TOTAL 41 (100%) 57 (100%) 17 (100%)
't test p=.005

71

12263

 

TABLE 4.1 .9 TOTAL SERUM FLUOFIIDE DISTRIBUTION
3M CHEMOLITE PLANT. COTTAGE GROVE, MINNESOTA

 

TOTAL FLUORINE NUMBER PERCENT

SPPMI 

d1 23 20.0
1-3 85 56.5
>340 16 13.9
:10-15 0 5.2
?5-20 5 4.4
TOTAL 115 100.0
TF 3.3
SD 7 4.7
MEDIANTF 2
RANGE 0-26

 

72

12264

 

 

TABLE 4.1.10 TOTAL SERUM FLUORIDE BY BODY MASS INDEX, AGE.
SMOKING AND DRINKING STATUS.
3M CHEMOLITE PLANT, COTTAGE GROVE, MINNESOTA

 

 

 

 

<25 41 (35.7) 2.8 3.74 2 0-19 51.471!
25-30 57(49.6) 4.0 5.47 2 0-26 13.24
>30 17(14.8) 2.1 3.51 1 0-14
AGE
<31 21(183) 3.7 4.95 2 0-20 H.103
31-40 48011.7) 3.2 4.08 2 0-14 P-.96
41-50 27(235) 3.3 4.26 2 0-19
51-60 19(1 6.5) 3.0 6.42 1 0-26
Alcohol
<1ozld 6705.6) 3.4 5.15 2 0-26 p.331
1-3021d 2007.4) 3.2 2.67 2 0-12
missing (80.0) 2.1 2.53 1 0-6
Tobacco
smoker 26(243) 3.6 4.36 2 0-20 pa.68?
nonsmoker 85(752) 3.2 4.13 2 0-28
missing 2(1.7) 3.0 4.24 3 0-6
TOTAL 115 3.3 4.67 2 0-26
#univariate Anova
.?Student test. Prob>T

73

12265

 

TABLE 4.1.11 AGE TOTAL SERUM FLUORINE
3M CHEMOLITE PLANT, COTTAGE GROVE. MINNESOTA

TOTAL SERUM FLUORINE (ppm)

 

 

 

15-25

 

 

 

AGE
20-25 1 (4.4) 1 (1.5) 0 (0) 1 (15.7) 0 (0)
25-30 3 (13.0) 10 (15.4) 4 (25.0) 0 (0) 1 (20.0)
31-35 5 (25.1) 13 (20.0) 4 (25.0) 2 (332) 1 (20.0)
35-40 4 (17.4) 12 (13.5) 5 (31.2) 0 (0) 1 (20.0)
41-45 2 (5.7) 13 (20.0) 2 (12.5) 1 (15.7) 0 (0)
45-50 0 (0) 7 (10.7) 0 (0) 1(15.7) 1 (20.0)
51-55 5(25.1) 5 (3.3) 0 (0) 1(15.7) 0 (0)
55-50 1 (43) 3 (4.5) 1 (5.3) 0 (0) 1 (20.0)
TOTAL 23 (100) 55 (100) 15 (100) 5 (100) 5 (100)
new AGE so 33.9 33.5 35.0 39.3 41.5
10.2 35 7.5 11.1 10.5
MEDIAN AGE 37 35 355 37.5 40
AGE RANGE 25-53 24-55 27-57 25-54 30-57
74

12266

 

TABLE 4.1.12 DISTRIBUTION OF TOBACCO USE BY TOTAL SERUM
FLUORIDE CATEGORY.

3M CHEMOLITE PLANT. COTTAGE GROVE, MINNESOTA
TOTAL SERUM FLUORINE (Rpm)

 

Tobacco
use

Smoker 3 (13.0)
Nonsmoker 19 (82.7)
Missing 1 (4.3)
Total 23 (100)
Cigaretteslday
(among smokers)
MEAN 16.3
so 14.0
M-IAN 17
RANGE 2-30

         

16 (24.6)
49 (75.4)
(0)

65 (100)

245?
8.8
20
7-40



6 (37.5)
9 (562)

1 (6.3)
16 (100)

1 8.0
9.9
20
3-30

2 (33.3)
4 (66.7)

(0)
6 (1 on)

83:38

L515,

1 (20.0)
4 (80.0)

0 (0)
5 (100)

88

28 (24.3)
85 (73.9)

2 (1.7)
115 (100)

21 .5
10.1

2-40

 

 

*signi?oantly different from <1 mean (p<.005)

75



 

 

TABLE 4.1.13 DISTRIBUTION OF ALCOHOL USE BY TOTAL SERUM
FLUORIDE CATEGORY.
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

TOTAL SERUM FLUOFIINE (ppm)

 

 

 

<1 1-3 >3-10 >10-15 315-26
ALCOHOL NUMBER (PERCENT)
USE
<1 ozlday 17 (73.9) 51 (78.5) 9 (55.3) 5 (83.3) 5 (100)
1-3 ozlday 2 (8.7) 13 (20.0) 4 (25.0) 1 (16.7) 0 (0)
MISSING 4 (17.4) 1 (1.5) a (18.7) (0)
TOTAL 23 (100) 65 (100) 18 (100) 6 (100) 5 (100)
76

12268

 

.TABLE 4.1.14 BODY MASS INDEX DISTRIBUTION BY TOTAL SERUM
7 FLUORINE CATEGORY.
3M CHEMOLITE PLANT. COTTAGE GROVE, MINNESOTA

TOTAL SERUM FLUORINE (ppm)

   
 

    

   

NUMBER (venom .

315-20 1 (4.(33.1) 21 (32.3) 3 (50.0) 1 (13.7) 1 (200)
.2530 (21.7) 39 (30.0) 5 (31 2) 4 (33.3) 4 (30.0)
.3335 7 (30.4) 3 (7.7) a (13.3) 0 (0) 0(0)
.3540 0 (0) 0(0) 0 (0) 1 (13.7) 0(0)
.4045 1 (4.(0)
TOTAL 23 (100) 33 (100) 13 (100) 3 (100) (100)
MEAN 3311 27.3 23.3 23.3 29.4 23.0
30 3.3 2.3 3.3 3.7 1.4
11-1?: 27 23.3 23.7 23.3 25.3

RANGE 18.8-40.5 22.5-33.7 21.4-32.5 24.5-35.5 24.1-27.6

 

12269

 

TABLE 4.1.15 COEFFICIENT FOR SEVEN HORMONE
3M CHEMOLITE PLANT. GROVE, MINNESOTA

 

HORMONE ch

 

 

BOUND TESTOSTERONE 10.6%
FREE TESTOSTERONE 12.1 
ESTRADIOL 1 8.3%
TSH 10.0%
LH 8.6%
PROLACTIN 3.1%
FSH 5.6%
78

12270

 

TABLE 4.1.16 THE OBSERVED VERSUS EXPECTED NUMBER OF WORKERS
WITH HORMONE ASSAYS OUTSIDE THE ASSAY REFERENCE RANGE
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

   

OBSERVED EXPECTED 85% Cl?
Estradiol 17 2.8 6.0 (3.6.9.8)
>=44 
Testosterone 13 2.8 4.5 (2.6.8.1)
bound
<=800 
Testosterone 11 2.8 8.9 (2.0.7.1)
free

Prolactin 10 2.8 8.5 (1.8.6.7)
>=15 
LH 3 2.8 1.1 (0.3.3.3)
212 mUIml
FSH 1 2.8 .4 (0.1 .2.0)
1-12 mUlrnl
TSH 1 2.8 .4 (0.1 .2.0)


 

- OBSERVED TO EXPECTED RATIO
?Cl 65% CONFIDENCE INTERVAL

79



3M 

3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA.



TABLE 4.1.17 PEARSON CORRELATION COEFFICIENTS BETWEEN SERUM HORMONES.

 

 

 

 

minnow

earn?mm. FREE amounts 



 

TEST. TEST.


1 .40 .32 .18 .06 ?.14
p-.0001 [b.0006 9-.08 p-.15

 

.05

 

FREE

3510315110?:-

1 :74 .13 .10 4:5
p-mm

.07

 

BOUND

TESTOSTERONE

- 1 .21 .28 .16
p.03 9-.003 9-.04

-.02

 

 

momenta

- - 1 .15 .004

.11

 



- - - 1 .63
13-3001

?.15
pa.?

 



.23


 

@mlml


 

 

 

 

 

 

??06 LUTENIZING HORMONE (mUIml)
FOLLICLE srmmua HORMONE (mUlmD
THYFIOID 3110me HORMONE (mUlml)

 

 

 

 

TABLE 4.1.18 PEARSON CORRELATION COEFFICIENTS BETWEEN TOTAL
SERUM FLUORIDE. AGE, BODY MASS INDEX (BMI), DAILY ALCOHOL USE,
DAILY TOBACCO CONSUMPTION. AND SERUM HORMON ES.

3M CHEMOLITE PLANT, COTTAGE GROVE. MINNESOTA

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

AGE (years) AW
FLUORINE (kg/m2) (ozlday) (agelday)

ssmmou? .13 -25 -.01 .05 .12
p-.16 p-.01 p-.2
FREE .00 -.45 ~26 -.08 .05
?0001 ?5005
BOUND .08 -.24 -.36 -.16 .11
TESTOSTERONE 9-.01 {.0001 9-.11
.19 -.19 ~08 .03 ?.18
p-.045 9-.01 p.09
.04 .11 .20 -.14 .18
p-.03 pun-.06
FSHT -.03 .33 ~.08 -.24 .17
9-.0003 p-.01 pan-.06
.26 .09 .04 .15 -.03
p-.005 p.15
@Psiml 
'ng/dl


LUIENIZING HORMONE (meI)
FOLLICLE STIMULATING HORMONE 
THYROID STIOMULATING HORMONE 

81

12273

TABLE 4.1.19 BOUND TESTOSTERONE (TB) BY BODY MASS INDEX, AGE,
SMOKING. DRINKING STATUS AND TOTAL SERUM FLUORIDE

3M CHEMOLITE PLANT, COTTAGE GROVE, MINNESOTA.

 

 

 

 

 



MEAN SD MEDIAN RANGE 
Mm?)
<25 4005.4) 841 7242.8 592 275-1182 F-5.84
25-30 56(49.6) 585 198.8 580 141-854 p.005
>30 1705.0) 436 172.7 438 210-803
Age
<31 2007.7) 598 232.8 873 278-1182 F-3.80
31-40 48(425) 634 214.1 805 275-1188 p.018
4150 28(23.0) 512 185.8 488 141-847
51-80 1808.8) 470 228.1 408 210-854
Alcohol
<1ozld 66(76.1) 581 212.5 574 -210-1192 F-1.23
1352/11 1808.8) 484 215.1 417 141-1038 p-.27
missing 60.1) 690 272.6 602 409-1101
Tobacco
smoker 27(23.3) 622 177.7 817 378-1038 F-1.88 
nonsmokor 8404.3) 559 233.0 556 141 -1192 p.20 
missing 20.8) 432 97.8 432 383-501
Total
Fluorlne
<1 2300.4) 584 285.4 436 275-1182 5039
1-3 .7 :64(56.6) 567 202.9 572 141-1039 pan-.82
>3-10 1503.3) 530 188.3 574 210-818
>10-15 65.3) 600 234.6 563 244-047
>15-26 50.4) 882 148.8 858 517-880
Total 113000) 572 220.7 581 141-1182
#univariate Anova

82

12274

TABLE 4.120 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE BOUND AMONG 112 MALE
3M CHEMOLITE PLANT, GROVE. MINNESOTA

 

 

   

Var?abe

   

 

Intercept 1027 190.7 .0001
Tota  Fluorine (ppm)' -148 67.2. .05
Age (years) -9 3.3 .009
Age Total Fluoride' 3 1.6 .04
BMI (kg/m2) -16 . 5.4 .003
Smoker" 74 45.0 .28
Alcohol (<1ozlday)# 09 47.5 .11
Estradiol (pg/ml) 2 1.0 .02
LH (mUlml) 116 - 0.1 .004
Prolactin (rug/ml) 8 4.1 .04
R21: .39

.?Square root transformation of total serum ?uoride measured In ppm.
?Reference category is nonsmokers.
#Reterence category is moderate drinkers who consume 1-3 oz ethanollday.

83

12275

 

 

TABLE 4.1.21 FREE TESTOSTERONE (TF) BY BODY MASS INDEX. AGE,
SMOKING AND DRINKING STATUS AND TOTAL SERUM FLUORIDE.

3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

  

 

 

   

mm

  

  

 

BMI 11911112
425 40(35.4) 17.4 6.22 16.7 7.4453 15.3.56
25-30 56(49.6) 15.1 4.13 15.6 32-232 p.03
:30 17115.0) 13.7 6.06 13.5 5.6305
Age years
231) 2007.7) 16.7 7.64 16.7 9345.3 5.9.14
31-40 460125) 17.0 3.75 17.1 7.4-2937 p-.0001
41-50 23(23.0) 14.1 4.73 14.3 32-233
51-60 19(16.8) 11.5 3.76 11.5 5,649.0
Alcohol
<1-ozld 6606.1) 15.6 5.36 15.6 5.6453 51.45
1-3 0210 19(16.6) 142 4.79 15.3 32-233 0-23
missing 8(7.1) 16.1 6.40 172 11.0-29.7
Tobacco
smoker 27(23.9) 16.6 3.71 17.1 64-243 F985
nonsmokor 6404.3) 15.4 5.64 15.3 32-453 p.33
missing 2(1.6) 15.9 4.45 15.9 12.7-19.0
Total
Fluorlno
<1 23(20.4) 16.4 6.4 13.9 6.4453 5.0.13

13 15.6 45 15.8 3230.5 p.37
53-10 15113.3) 152 3.6 15.3 7.1-16.7
>10-15 6 '5 3) 15.9 52 17.6 5.6493
>15-26 514.4) 153 22 14.1 13.3-18.2
Total 113(100) 15.7 5.4 16 32-453
#univariate Anova?

84

12276

 

 

TABLE 4.1.22 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE FREE TESTOSTERONE VALUE (rig/d1)

AMONG 111 MALE WORKERS.

3M CHEMOLITE PLANT. COTTAGE GROVE, MINNESOTA

 

 

 

 

 

Variable
Intercept 29.72 4.57 .0001
Total Fluorine (pprn)?I ~3.56 1.62 .03
Age (years) -.34 .08 .0001
Age Total Fluoride' .07 .04 05
BM (kg/m2) -.21 .13 .11
Sm oker" 1.46 1.03 .1 6
Alcohol ozldayEstradiol .10 .03 .003
LH (mU/ml) .18 .15 .20
R2: .39

'Square root transformation of total serum 11

?Reference category is nonsmokers.
. #Rsference category is moderate drinkers who consume 1-3 oz ethanol/day.

85

uorlde measured in ppm. 



 

 

 

 

 

 

TABLE 4.1.23 PARTICIPANT ESTRADIOL BY BODY MASS INDEX. AGE,
SMOKING DRINKING STATUS AND TOTAL SERUM FLUOFHDE.
3M CHEMOLITE PLANT, COTTAGE GROVE. MINNESOTA
(ngmIT
N196) FMEAN SD MEDIAN RANGE 
BMI 691m?)
<25 40135.4) 34.1 12.91 40 6-69 F..13
25-30 56149.6) 332 13.69 33 6-63 11-33
>30 17115.0) 322 12.36 27 16-57
AGE
<30 20117.7) 34.4 10.15 34 19-56 5360
31-40 46142.5) 36.6 11.54 36 12-69 p.016
41-50 26123.0) 31.6 13.46 26 6-63
51-60 19116.6) 25.6 7.93 24 15-47
Alcohol
<1 ozld 66176.1) 33.0 11.76 33 6-66 F..14
1-3 0210! 19116.6) 31.6 16.61 30 6-69 11-171
missing 617.1) 41.1 16.20 40 23-63
Tobacco
smoker 27123.9) 36.3 17.40 34 14-63 F..13
nonsmokar 64174.3) 32.5 11.63 32 6-66 11-66
missing 211.6) 30.5 13.44 30 21-40 1
Total
Fluorine
<1 23120.4) 36.2 13.1 34 14-60 5127
5-1-3 64156.6) 31.4 13.6 30 6-33 13-29
53-10 15113.3) 32.3 10.6 34 10-56
510-15 615.3) 36.2 15.2 35.5 22-66
>15-26 514.4) 41.2 11.4 42 26-56
Total 1131100) 33.4 13.2 33 6-63
#univariate Anova
86


1
12278

 

TABLE 4.1.24 LINEAR MULTIVARIATE HEGFIESSION MODEL OE FACTORS
PREDICTING THE ESTRADIOL VALUE AMONG 113 MALE WORKERS.
3M CHEMOLITE PLANT. GROVE, MINNESOTA

 

 
      

 

Intercept 12.89 12.13 .29
Total Fluorine (ppm)' .03 .01 .03
Age (years) ~22 .15 .14
(kg/m2) .51 .34 .14
Cigarettes/day .16 .11 .15
Alcohol .09 .11 .98
Free Testosterone .05 .24 .0007
R2: .24

?Square transformation of total serum ?uoride measured in ppm.
#Reference category is moderate drinkers who consume 1-3 oz ethanol/day.

87

 

12279

TABLE 4.25 LUTENIZING HORMONE (LH) BY BODY MASS INDEX, AGE,
SMOKING AND DRINKING STATUS, AND TOTAL SERUM FLUOFIINE
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

 

 

 

LH (mUlml)

<25 40635.4) 5.43 3.06 4.60 . 2.6-21.7 F-6.13

25-30 56(49.6) 5.64 3.25 5.15 1.7-23.0 p.003

>30 17115.0) 3.72 121 3.60 2.0-7.2

Age years

<30 20(17.7) 4.81 2.26 4.45 1.7-10.1 F-.69

31-40 48(425) 5.43 3.14 4.75 2421.7 p-.56

41-50 26(23.0) 5.33 1.64 5.15 2.5-9.6

51-60 13(165) 5.30 4.73 4 10 20-230

Alcohol 

<1ozld 66(76.1) 5.60 3.34 4.70 1.7.23.0 F-124

1-3oz/d 19(165) 4.69 1.60 4.21 2310.1 p-.27

missing 80.1) 4.86 1.00 4.05 3.4-0.2

Tobacco

smoker 27(23.9) 8.30 3.78 5.30 22.6-21.7 F-5.16

nonsmokar 6404.3) 5.05 2.71 4.52 1.7-23.0 0-.025

missing 2(1.6) 7.45 2.47 7.45 5.7-3.2

Total

Fluorlne .

<1 23(20.2.5-0.3 F-0.16
. 6466.6) 5.6 3.6 4.6 1 .7-23.0 p- 03

>3-10 15113.3) 5.1 2.7 4.9 2.0-13.9

>10-15 65.3) 5.4 0.3 4 9 3.7-75

>15-26 5(4.4) 5.3 1.3 5.5 3.7-7.2

Total 113(100) 5.4 3.0 4.7 1.7-23.0

#univariate Anova

88



 

TABLE 4.1.26 LINEAR MULTIVARIATE REGRESSION MODEL #1 OF
FACTORS PREDICTING THE LUTENIZING VALUE (mU/ml)

 

 

 

 

AMONG 113 MALE WORKERS.
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

Intercept 1.26 .40 .002
Total Fluorine (ppm)' .001 .008 .93
Age (years) .01 .005 .03
(kg/m2) -.02 .01 .15
Smokers? .24 .23 .29
Alcohol (<1ozlday)# .06 .10 .60
(810933;)! Testosterone .001 .0002 .008
82: .28

transformation of lutenlzing hormone (LH).
Reference category is nonsmokers.
#Reference category is moderate drinkers who consume 1-3 oz ethanol/day.

89



 

TABLE 4.1.27 FOLLICLE STIMULATING HORMONE (FSH) BY BODY MASS
INDEX. AGE. SMOKING AND DRINKING STATUS, AND TOTAL SERUM

FLUOHINE

3M CHEMOLITE PLANT, COTTAGE GROVE. MINNESOTA

 

 

Em?vrsw?W
NW.) MEAN 0 A 

 

 

 

BMIWM2
<25 40135.4) 5.02 2.39 43 1310.3 13.1.27 1
2530 53019.3) 5.39 2.71 4.5 1.4143 0.29
>30 17(15.0) 4.31 1.75 3.3 1.3-3.3 
Age years I
<30 20(17.7) 3.33 1.33 3.3 1.4-9.3 F-3.72
3140 43142.5) 4.33 2.24 4.3 1310.3 p-.014
41-50 23(23.0) 5.35 2.55 4.3 21-143
5130 19(133) 322 3.01 5.0 2.7-143 

Alcohol
<1ozld 33(73.1) 5.37 . 2.32 4.3 1.4-14.3 53.47
13cm 13(133) 4.13 1.92 3.9 2.0-9.3 p.035
missing 317.1) 4.33 1.49 4.3 2.3-3.4
Tobacco 1
smoker 27123.9) 5.77 2.43 4.9 2311.9 3.2.30 1
nonsmokor 84(743) 4.85 4.49 4.2 1.4443 p.09
missing 2(13) 3.10 0.42 3.1 5.3-3.4
Tom!
Fluorine
<1 23(20.4) 4.4 1.35 4.4 1310.3 50.75
1.3 3453.3) 5.4 2.75 4.3 1414.3 0.53
>3-10 15(133) 4.3 2.23 4.9 2.1-9.7
>10-15 315.3) 5.4 2.14 4.4 3.5-3.9
s1523 5(4.4) 4.9 2.33 3.7 2.3-7.7
Total 113(100) 5.1 2.49 4.5 1.4-143 
#univariate Anova
1
i
90 



 

TABLE 4.1.28 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE FOLUCLE STIMULATING HORMONE VALUE (mU/ml)

 

 

 

AMONG 113 MALE WORKERS.
13M CHEMOLITE PLANT . COTTAGE GROVE, MINNESOTA
Variable m) p-value
Intercept 1.20 1.62 .46
Total Fluorine(ppm)" .004 .04 .91
Age (years) .08 .02 .0006
SW (kg/m2) -.04 .05 .41
Cigarettes/day .02 .02 .29
.45 .48 .34
TSH (mUlml)@ -.4o 22 .05
LH (mU/ml)? .44 .05 .0001

 

48

?logarithmic transformation of follicle stimulating hormone (FSH).
#Reference category is moderate drinkers who consume 1-3 oz emanollday.
@Thyroid Stimulating Hormone

##Lutienizing Hormone

91



TABLE 4.1.29 THYROID HORMONE (T SH) BY BODY MASS
INDEX, AGE, SMOKING AND STATUS, AND TOTAL SERUM

 

 

 

 

FLUORINE. .
3M CHEMOLITE PLANT, COTTAGE GROVE, MINNESOTA
Wuhan 
NE) MEAN SD MEDIAN RANGE 
an: m2 i
<25 40135.4) 1.55 0.66 1.04 0.67-3.14 F-.35 i 
25-30 56(46.6) 1.64 1.01 1066 0.45-6.60 p-.70 .
230 17115.0) 1.72 0.71 1.55 0.62-323
Age you:
<30 20(17.7) 1.43 0.56 1.42 0.36-2.36 5.47
31-40 46012.5) 1.66 1.04 1.46 0.37-6.60 p.70
41-50 26(23.0) 1.64 0.75 1.34 0.75-3.56
51-60 19(18.8) 1.70 0.74 1.53 0.62-3.06 
Alcohol
<1ozld 6606.1) 1.57 0.70 1.40 0.38-3.56 F-1.23
1-3oz/d 1606.6) 1.63 1.36 1.55 0.60-6.60 p.27
missing 60.1) 1.46 0.63 1.61 037-222
Tobacco
smoker 27(23.9) 153 0.61 1.37 0.61-3.03 . F-.09 
nonsmokor 8404.3) 1.88 0.92 1.49 0.37-6.80 p.76 1
missing 2(1.6) 1.26 0.42 1.26 0.6645 1
Total
?uo?ne
<1 23120.4) 1.5 0.64 1.5 0.3-3.3 16-230
>6 -3 64(56.6) 1.6 0.64 1.3 0.4-6.6 p.06
>3-10 15(133) 1.6 0.67 1.4-- 0.63.0
510-15 6(53) 2.4 0.67 2.5 0.63-3.5 
>15-26 5(4.4) 2.2 1.66 2.1 1.735 
Total 113(100) 1.6 0.65 1.4 0.3-6.6 
#univarlate Anova


92 i

12284

 

TABLE 4.1.30 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE THYROID STIMULATING VALUE (mU/ml)

 

 

 

 

 

 

AMONG 113 MALE WORKERS.
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

Intercept -.190 .465 .68
Total Fluorine (ppm)* .027 .009 .004
Age (years) .006 .005 .29
BMI (kg/m2) -.002 .013 .89
Cigaretteslday -.001 .004 .74
Alcohol -.140 .194 .26
Free Testosterone" .020 .009 .04
.060 .019 .003
.30

?logarithmic transformation of thyroid stimulating hormone SH).

#Reference category is moderate drinkers who consume 3 oz ethanol/day.

it 
##Foliicle stimulating hormone mU/ml

'93



 

 

TABLE 41.31 PROLACTIN BY BODY MASS INDEX, AGE, SMOKING
DRINKING STATUS AND TOTAL SERUM FLUORINE
3M CHEMOLITE PLANT, COTTAGE GROVE. MINNESOTA

_Pnoumu 

 

 

    

 

 

(11911112)
<25 40(854) 9.10 5.18 8.4 27-248 F-.69
25-80 58(48.8) 8.71 5.18 7.8 1 2-88.? [3-51
>30 1765.0) 7.45 3.08 7.2 2513.6
Age
<30 20( 17.7) 9 .63 4.20 8.5 3.9-18.3 F-.98
81-40 48(425) 8 .01 5.80 8.7 1288.7 p.51
41-50 28(28.0) . 8.88 5.52 8.2 2828.5
51-80 18(188) 7.18 8.87 8.8 2515.1
Alcohol
<1ozld 8808.1) 8.81 457 7.8 - 1224.8 5.44
188218 19(16.8) 8.48 - 8.87 8.7 28-88.? 9-50
missing 80.1) 7.25 2.33 8.8 48-105
Tobacco
smoker 27428.8) 8.87 8.14 8.8 1.2-128 5.4.18
nomolm 84174.3) 8.18 5.18 8.5 25-88 .7 p.848
missing 2(1.8) 11.85 8.40 11.7 5. 0-188
Total
Fluorine
<1 mm 28(20.4) 7.8 8.18 7.5 25-188 F-8.02
?1-3 84(588) 8.5 4.84 8.1 1224.8 p.02
>810 15(188) 4 .8 1.15 8.8 1.4-18.1
>10-15 8(5.8) 15.1 11.01 8.4 8.8-88.7
>15-26 5(4.4) 8.3 4.18 7.7 8.8-15.1
Total 118(100) 8.7 4.80 7.7 1288.7
#univariate Anova

g4



TABLE 4.1.32 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE PROLACTIN VALUE AMONG 113 MALE WORKERS.
3M OHEMOLITE PLANT. GROVE, MINNESOTA

 

 

 

 

 

Variable 8 SETS value
Intercept 7.41 4.14 .07
Total Fluorine (ppm) 1.43 .36 .0002
Age (years) -.04 .05 .41
SW (kg/m2) -.08 .13 .53
Cigarettes/dew -.08 .04 .08
Estradiol (pg/ml) .06 .03 .07
Alcohol Use##

Light ozlday) 3.21 1.65 .05
Nonresponsa (NR) 2.14 2.69 .43
Light total ?uoride -1.67 .77 .03
NR total fluoride -1 .34 .37 .0006
R2: .22

##Reference category is moderate drinkers who consume 1-3 oz ethanollday.
Nonrespondants (N Fl) failed to complete the alcohol use questionnaire items.
Light total ?uoride and NR total fluoride are interac?on terms for alcohol
categories and total semrn ?uoride.

95



TABLE 4.1.33 PEARSON CORRELATION COEFFICIENTS BETWEEN

 

HORMONE RATIOS AND TOTAL FLUORIDE. AGE, BODY MASS INDEX,
ALCOHOL AND TOBACCO CONSUMPTION
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

 

       

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Wm. ASE (rm) am Mm!) ALOOHOL TO"a?Acco
FLUORINE (nude!) (?nality)
.004 .05
mm p.201
.1 1 .15 .27 .01 .01
2.15 2.004
.001 - .18 .05 .04
_qu-I? 93.005 9.03
.002 -.32 ~34 -.01 -.01
0-.001 0-.13
-.09 -.4o -.02 .03 .03
WW p-.0001
.16 .24 -.16 -.12 .09
p.09 9-.01 p.08
TO BOUND TESTOSTERONE RATIO
TO FREE TESTOSTERONE
TO LUTENIZINS HORMONE RATIO
TESTOSTERONE TO LUTENIZINS HORMONE RATIO
TESTOSTERONE TO LUTENING HORMONE RATIO
TESTOSTERONE TO FREE TESTOSTERONE RATIO
I
96




TABLE 4.1.34 PEARSON CORRELATION COEFFICIENTS BETWEEN
PBOLACTIN HORMONE RATIOS AND TOTAL FLUORIDE, AGE. BODY MASS
INDEX, ALCOHOL AND TOBACCO CONSUMPTION
3M CHEMOLITE PLANT. COTTAGE GROVE, MINNESOTA

 

 

 

4?1011?. (years) om noon-101.

TOBACCO

  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

?Follicle stimulating homono to proIaoth-I ratio
?Prolaottn to Iutoniztng hormone ratio
?Protectin to thyroid stimulating hormone ratio

97

FLUO NE (ozldav) (6081*?)
p.001
08 - 11 -.00 .06 .22
3.02
- 00 .03 .25
p-.008
- 09 .37 .004 -.13 .21
mount 2.16 2.02
.11 ?:33 09 .15 -22
E- 2.11 2.02
.07 . 7 .07 .17 .09
man? 9-.07 p.07
@Frao testosterone to prolaottn Mo
*Froe testosterone to prolaottn ratio
+Estradiot to protactin ratio



TABLE 4.1.35 PEARSON CORRELATION COEFFICIENTS BETWEEN
THYROID STIMULATING HORMONE RATIOS AND TOTAL FLUORIDE. AGE.

BODY MASS INDEX, ALCOHOL AND TOBACCO CONSUMPTION
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

    

 

TEAL Toe (years) out m2, 

 

 
 

 
   

 

FLUORINE (oz/day) (cinsldey)
TBfl'Sl-ie 0-.01 0-.01 0-.09
-.1B -.34 -.23 -.13 .01
2.05 2.0002 95.01
-.13 -.24 ?.05 -.05 .04
errsI-i" ion-v.01

 

 

 

 

 

 

 

 

#Bound testosterone to thyroid stimulating hormone ratio
*Free testosterone to thyroid stimulating hormone ratio
+Estrediol to thyroid stimuhting hormone ratio

TABLE 4.1.36 PEARSON CORRELATION COEFFICIENTS BETWEEN

FOLLICLE STIMULATING HORMONE RATIOS AND TOTAL FLUORIDEAGE.

BODY MASS INDEX, ALCOHOL AND TOBACCO CONSUMPTION
3M CHEMOLITE PLANT, COTTAGE GROVE. MINNESOTA

 

 

 

 

TOTAL AGE (years) out mi) "foe" A'o' co"
FLuoniNE (02min (steamy)
A -
.07 ?.4a -.10 .00 -.00 
p..0001 p.00
-.01 5477 .04 .00 '51?
p-.0001
.04 -.as .04 -.02
pa.0001

 

 

 

 

 

 

 

 

#Bound testosterone to follicle stimulating hormone ratio
*Free testosterone to follicle stimulating hormone ratio
+Estredioi to stimulating hormone ratio

1
12290

TABLE 4.1.37 PEARSON CORRELATION COEFFICIENTS BETWEEN
PITUITARY GLYCOPROTIEN HORMONE RATIOS AND TOTAL FLUORIDE,
AGE. BODY MASS INDEX. ALCOHOL AND TOBACCO CONSUMPTION
3M CHEMOLITE PLANT, GROVE, MINNESOTA

 

 

 

 

Tom. am ALCOHOL TOBACCO 

FLUOBINE (oz/day) (oigelday)
-.1a .04 24 ..14 
p-.08 p-.o1

.09 -.oz .15 21 -.14

ou.03 
-.os .23 .13 -.14 .05
It!? 9-303

 

 

 

 

 

 

 

@Thyroid stimulating hormone to follicle stimulating hormone ratio

'Thyroid stimulating hormone to lutenizing hormone ratio
+Foilicle stimulating hormone to Iutenizing hormone ratio

99



 

TABLE 4.1.38 LINEAR MULTIVARIATE REGRESSION MODEL1 OF FACTORS
PREDICTING THE BOUND-FREE TESTOSTERONE RATIO AMONG 112 MALE

 

 

 

 

WORKERS.

3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA
Intercept 36.60 6.87 .0001
Total Fluorine (ppm)" .02 .008 .02
Age (years) .19 .101 .07
am (kg/m2) -.48 244 .05
[Ht .12 - .337 .73
.92 .440 .04
R2: .21

'square transformation of total serum ?uoride
+lutienizing hormone mU/ml
follicle stimulating hormone mU/ml

100

12292

TABLE 4.1.39 LINEAR MULTIVARIATE HEGRESSION MODEL2 OF FACTORS
PREDICTING THE RATIO AMONG 112 MALE
3M CHEMOLITE PLANT. COTTAGE GROVE, MINNESOTA

- Variable T3 Evolve

 

 

intercept 37.3 6.97 .0001
Total Fluorine (ppm)* .02 .009 .03
Age (years) .25 .097 .009
(kg/m2) -.52 .250 .03
.55 .271 .05
82: .17

'square transfonnation of total serum ?uoride

+luteinizing hormone mU/ml

follicle stimulating hormone mU/ml

101

12293

TABLE 4.1.40 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE ESTRADIOL-BOUND TESTOSTERONE RATIO AMONG 112

 

 

   

 

 

3M CHEMOLITE MINNESOTA
Intercept .05 .027 .05
Total Fluorine (ppm) .00001 .00001 .74
Age years)? -.0004 .0004 .29
BM: (kg/m2) .002 .0007 .006
Cigarettes/day -.00001 .00002 .96
Alcohol ozlday)# .003 .007 .63
Free Testosterone' -.001 .0006 .008
01+ .0001 .0006 .94
-.002 .001 .12
-.003 .003 .30
Proiaciin? .0001 .0005 .78
F12: 21 -
figs/iglrence category is moderate drinkers who consume 1-3 oz ethanol/day.

+luteinizing hormone mU/ml

follicle stimulating hormone mU/ml

Thyroid stimulating hormone (mU/ml)

prolactin rig/ml 

102

12294

TABLE 4.1.41 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE ESTRADIOL-FREE TESTOSTERONE RATIO AMONG 112
MALE WORKERS.
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

 

   

 

 

intercept 1.81 .880 .15
Total Fluorine (ppm) .002 .001 .03
Age (years) .012 .011 .34
BMI (kg/m2) .048 .028 .07
Cigarettes/day .005 .008 .51
Alcohol ozlday)# .090 .730 .70
Bound Testosterone' -.001 .0004 .01
L111- .012 .035 .73
-.059 .046 .21
-.204 .110 .05
Prolactln? .027 .018 .15
R2: .22

f?gjgrence category is moderate drinkers who consume 1-3 oz ethanol/day.
+lutienizing hormone 

follicle stimulating hormone mUlml

Thyroid stimulating hormone (mUlmI)

prolactin 

103

12295

TABLE 4.1.42 LINEAR MULTIVARIATE

 

 

 

 

   

REGRESSION MODEL OF FACTORS

 

 

PREDICTING THE RATIO AMONG 112 MALE WOBKERS.
3M CHEMOLITE PLANT. COTTAGE GROVE, 

Intercept 3.07 3.58 .39
Total Fluorine (ppm) .02 .07 .80
Age (years) -.03 .05 .39
.27 .10 .008
Cigarettes/day .009 .03 .77
Alcohol .37 .90 .68
Free Testosterone' .13 .10 .21
Bound Testosterone? .001 .002 .71
-.75 - .15 .0001
-.39 .42 .35 
Prolactin" -.03 .07 .72
[32: .34
+estraoiol to lutenizing hormone (mU/ml) ratio
#Refglrence category is moderate drinkers who consume 1-3 oz ethanol/day.
ng/
@fcllicle stimulating hormone mU/ml
Thyroid stimulating hormone (mU/ml)
prolactin ng/ml

 

 

104


12296

TABLE 4.1.43 LINEAR MULTIVARIATE REGRESSION MODEL OF FACT OHS
PREDICTING THE SOUND RATIO AMONG 112 MALE
3M COTTAGE GROVE. MINNESOTA

 

 

 

 

 

Intercept 74.46 48.53 .13
Total Fluorine (ppm) .27 .98 .79
Age (years) 29 .62 .64
(kg/m2) -.43 1.35 .75
Cigarettes/day -.15 .44 .73
Alcohol onday)# 7.55 12.1 .54
Free Testosterone' 5.96 1.01 .0001
aetradiol@ -.28 .38 .45
-8.65 2.03 .0001
-.23 5.69 .97
Prolactin? .11 .95 .90
R2: .43

+bound testosterone to lutenizing hormone (mU/ml) ratio

#Fleferenoe category is moderate drinkers who consume 1-3 oz ethanol/day.

ng/dl

pg/rnl

stimulating hormone mUlml
Thyroid stimulating hormone (mUIml)
prolactin 

105



TABLE 4.1.44 LINEAR MULTIVAFIIATE REGRESSION MODEL OF FACTORS
PREDICTING THE FREE RATIO AMONG 112 MALE

 

 

 

 

WORKERS.
3M CHEMOLITE PLANT. CO1TAGE GROVE, MINNESOTA
Variable Ti value

Intercept 3.00 1.38 .03
Total Fluorine (ppm) -.05 .03 .09
Age (years) .001 .01 .91
BMI (kg/m2) .07 .04 .08
Cigarettes/day -.007 .01 .58
Alcohol .30 .36 .41
Bound Testosterone' .003 .0007 .0001
Estradiol@ .001 .01 .91
-.33 .06 .0001
.16 .17- .30
Prolao?n? -.05 .03 .08
F12: .46

+free testosterone to lutenizing hormone (m Ulml) ratio
#Referenoe category is moderate drinkers who consume 1-3 oz ethanol/day.

ng/dl
pg/rnl

@@follioie stimulating hormone mU/ml

Thyroid stimulating hormone (mU/ml)

prolaotin ng/ml

106

12298

 

TABLE 4.1.45 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE BOUND RATIO AMONG 111

 

   

 

MALE WORKERS.

13M CHEMOLITE PLANT. CO1TAGE GROVE. MINNESOTA
intercept 60.05 68.04 .38
Total Fluorine (ppm) -.15 1.38 .91
Age (years) .84 .88 34
SW (kg/n12) -1 .54 1.92 42
Cigarettes/day ,1 .49 .62 .02
Alcohol ozlday)# 13.9 17.2 42
Estradiol'? -.22 .53 68
Free Testosterone 3.93 1.45 .008
2.23 2.63 .40
~2.55 3.50 .47
-.95 .80 .24
R2: .17
Mpg/ml

#joglrence category is moderate drinkers who consume 1-3 oz ethanol/day.
lutenizing hormone mU/rnl

follicle stimulating hormone mUIml

Thyroid stimulating hormone mU/ml

107

12299

TABLE 4.1.46 LINEAR MULTIVARIATE REGRESSION
PREDICTING THE FREE TESTOSTERONE-PROMO

 

 

MODEL OF FACTORS
TIN RATIO AMONG 111

 

 

 

MALE WORKERS.
3M CHEMOLITE PLANT, COTTAGE GROVE. MINNESOTA

Variable p-value 4
Intercept 2.41 1.76 .17
Total Fluorine (ppm) -.03 .04 .35
Age (years) -.004 .02 .95
BMI (kg/m2) ?.004 .05 .93
Cigarettes/day .04 .02 .03
Alcohol oz/day)# -.03 .76 .97
Estradiol? -.0001 .01 .99
Bound Testosterone .002 .0001 .03
-.08 .07 .24
-.12 .09 .21
-.1a 21 .40
.15
category is moderate drinkers who consume 1 -3 oz ethanol/day.

ng/dl 

lutenizing humane mU/ml

follicle stimulating hormone mU/ml
Thyroid stimulating hormone mel

108

 


12300

 

 

TABLE 4.1.47 LINEAR MULTIVARIATE HEGRESSION MODEL OF FACTORS
PREDICTING THE EST RATIO AMONG 111 MALE

 

 

 
      

 

WORKERS.
3M PLANT. CO1TAGE GROVE, MINNESOTA


Intercept 2.65 4.01 .51
Total Fluorine (ppm) .005 .081 .95
Age (years) .01 .05 .30
(kg/m2) .07 .116 53
Cigarettes/day .10 .036 .005
Alcohol ozlday)# .86 1.01 .40
Bound Testosterone? -.001 .003 .95
Free Testosterone .12 .12 .31
-.13 .15 .39
-.29 .21 .17
-.67 .47 .16
R2: .16

category is moderate drinkers who consume 1-3 oz ethanol/day.


lutenizing hormone mU/ml

follicle stimulating hormone mU/ml

Thyroid stimulating hormone mU/ml

109

12301

I?sw.


 

TABLE 4.1.43 LINEAR MULTIVARIATE MODEL OF morons 
PREDICTING THE RATIO AMONG 111 MALE WORKERS.
3M cur-moms PLANT, comes enovs, MINNESOTA

 

 

       

 

Intercept 2.56 1.52 .09 
Total Fluorine (ppm) .31 .11 .008
Alcohol 
low oz/day) .81 .52 .13
nonresponse (N R) .19 .85 .82 1
low Fluoride -.31 .12 .01 1
NR Fluoride -.08 .29 .78
Age (years) -.05 .02 .01 
BMI (kg/m2) .01 .04 .86
Cigarettes/day -.03 .01 .03
EstracliolM .02 .01 .06 1
Bound Testosterone' -.001 .001 .92
Free Testosterone .01 .04 .75 7 7
?.07 .05 .15
.31 .17 .07
82- .31
Fang/pages category to moderate drinkers who consume 1-8 oz ethanonay. 
Thyrold mandating humane mUIrnl

11o

12302

 

TABLE 4.1.49 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE RATIO AMONG 111 MALE WORKERS.

3M CHEMOLITE PLANT. COTFAGE GROVE. MINNESOTA

 

 

 

 

 

Intercept 1 .07 1 .27 38
Total Fluorine (ppm) .34 09 .0003
Alcohol 
low ozlday) .68 .43 11
nonresponse (NR) .41 .69 .55
low Fluoride -.35 09 .0004
Fluoride -.39 .20 05
Age (years) -.02 .01 .12
(kg/m2) .05 .04 1 7
Cigarettes/day -.02 .01 .09
Estradlol++ .003 .009 .76
Bound Testosterone? .001 .0008 1 7
Free Testosterone -.04 .03 .30
-.1 1 .05 .03
.15 .14 .29
B?zuia?lgng hormone


#Haferenoe category is moderate drinkers who consume 1-3 oz emanollday.

d!


Me stimulating hormone mUIrnl
Thyroid stimulating hormone mUIml

111

12303

TABLE 4.1.50 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS

PREDICTING THE RATIO AMONG 111 MALE WORKERS.

3M CHEMOLITE PLANT, COTTAGE GROVE, MINNESOTA

Variable 1 Evalue

 

 

 

Intercept 5.06 4.83 .30
Total Fluorine (ppm) 1.61 .37 .0001
Alcohol 
low (<1ozlday) 4.16 1.67 .01
nonresponse (NR) 3.85 2.72 .16
Iowx Fluoride -1.76 .38 .0001
NR Fluoride -2.11 .77 .008
Age (years) -.19 .06 .003
(kg/m2) .11 .14 .43
Cigarettes/day -.06 .04 .14
EstradiclH' .037 .04 .46
Bound Testosterone' .008 .003 .02
Free Teetostercnecategory is drinkers who consume 1-3 02 ethanol/day.
$911133; 3.133132% 2m. 2233'.


112

 

12304

TABLE 4.1.51 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE BOUND RATIO AMONG 112 MALE

 

 

 

WORKERS.

3M CHEMOLITE PLANT, COTTAGE GROVE, MINNESOTA
Intercept 559.5 360.7 .12
Total Fluorine (ppm) 37.7 109.8 .73
Age (years) -1.1 6.2 .85
BMI (kg/n12) ~9.8 8.9 .27
Cigarettes/day -.66 2.9 .82
Alcohol ozlday)# 74.9 78.3 .34
Free Testosterone? 12.5 6.6 .06
Estradiol@ -1 .6 2.5 .51
47.1 . 15.9 .004
5.7 122 .64
Prolactin"? -1 .1 6.2 .85
Ba; .29

+bound testosterone to thyroid stimulating hormone (mU/ml) ratio

#Reference oategory is moderate drinkers who consume 1-3 oz ethanol/day.

ng/dl

pg/ml

@@follicle stimulating hormone mU/ml
Thyroid stimulating hormone (mU/ml)
prolactin 

113

 

12305

 

TABLE 4.1.52 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE FREE RATIO AMONG 112 MALE

 

WORKERS.
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA i
Variable 0 ?g 1 Eveline I
Intercept 15.65 6.34 .02
Total Fluorine (ppm) -.28 .13 .03
Age (years) -.29 .08 .003
(kg/m2) -.01 .19 .94
Cigarettes/day -.03 .06 .65
Alcohol ozlday)# 1.50 1.64 .36
Bound Testosterone" .01 .003 .006
Estradioi? -.01 .05 .80
FSi-l@@ .68 .33 .04
-.001 . .25 .99
Prolactin? -.16 .13 .17

 

32:: .37

+free testosterone to thyroid stimulating hormone (mU/ml) ratio

#Rg?glrence category is moderate drinkers who consume 1-3 oz ethanol/day.





@@follicle stimulating hormone mUlm++ Thyroid stimulating hormone (mU/ml)
prolactin 

114

12306

 

TABLE 4.1.53 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE RATIO AMONG 112 MALE WORKERS.
3M CHEMOLITE PLANT, GROVE, MINNESOTA

 

 

 

 

83b? 7 7, 7 
Intercept 30.80 16.10 .06
Total Fluorine (ppm) -.425 .31 .18
Age (years) -.53 .20 .01
(kg/m2) .32 .46 .50
Cigaretteslday .06 .14 .70
Alcohol 2.36 4.00 .55
Free Testosterone" -.28 .46 .55
Bound Testosterone' .009 .01 .42
.31 .81 .31
.20 .62 .75
Prolactin? -.07 .32 .83
R2: .15

+estradiol to thyroid s?mulating hormone (mU/ml) ratio

#Refglrenoe category is moderate drinkers who consume 1-3 oz ethanol/day.
"w

@follicle stimulating hormone mU/ml

thyrold stimulating hormone (mU/ml)

prolactin 

115

12307

TABLE 4.1.54 LINEAR MULTIVARIATE MODEL OF FACTORS
PREDICTING THE BOUND Esrasgg?ganse-st AMONG 112 MALE
3M CHEMOLITE PLANT. COTTAGE GROVE, MINNESOTA

 

 

Intercept 101.89 61 .25 .10

 

Total Fluorine (ppm) .66 1.24 .60
Age (years) -.13 .75 .14
(kg/m2) -1 .08 1 .70 .53
Cigarettes/day -.37 .55 .50
.29 15.30 . .96
Free Testosterone" 6.87 1.28 .0001
-7.61 1.93 .0002
-Eslradiol@ .77 .47 .1 1
8.90 7.03 .21
Prolactin? -.03 1.20 .97
R2: .50

+bound testosterone to follicle stimulating hormone (mU/ml) ratio
#Refglrence category is moderate drinkers who consume 1-3 oz ethanol/day.


@luteinizlng hormone mU/ml

@@estradiol pg/ml

Thyroid stimulating hormone (mU/ml)

prolactin 

116

12308

 

TABLE 4.1.55 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE FREE RATIO AMONG 112 MALE

 

 

   

 

WORKERS.
3M CHEMOLITE PLANT. GROVE. MINNESOTA
arilabe . a 

Intercept 4.31 2.01 .03
Total Fluorine (ppm) -.04 .04 .27
Age (years) -.10 .02 .0001
SW (kg/m2) .06 .06 .28
Cigarettes/day -.02 .02 .31
Alcohol ozlday}# .18 .52 .74
Bound Testosterone' .003 .001 .02
~25 .07 .0003
Estradiol? .03 .04 .27
A .49 .24 .04
Prolac?n? ?.05 .04 .23
Fla: .43

+free testosterone to follicle stimulating hormone (mU/ml) ratio

#joceirence category is moderate drinkers who consume 1-3 oz ethanol/day.


@luteinizing hormone mU/ml

@@estraaiol pg/ml

Thyroid stimulating hormone (mU/ml)

prolactin 

117

12309

TABLE 4.1.56 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE RATIO AMONG 112 MALE WORKERS.
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

 

   

Intercept 6.91 5.69 .23

Total Fluorine (ppm) .006 .006 .34

Age (years) -.19 .07 .008

BMI (kg/m2) .27 .16 .1o

Cigarettes/day .03 .05 .57

Alcohol .52 1.42 .71

Free Testosterone' .26 .16 .1 1

Bound Testosterone? -.002 .004 .62

-.49 .18 .609
.08 .65 .90 1
Prolactin+estradiol to follicle stimulating hormone (mU/rnl) ratio 1
#Rgliglrenoe category is moderate drinkers who consume 1-3 oz ethanol/day.

i
@Iuteinizing hormone rnU/mi 1
Thyroid stimulating hormone (mU/ml)

prolaotin ng/ml

118

 



TABLE 4.1.57 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE BOUND RATIO AMONG 112 MALE WORKERS.
3M CHEMOLITE PLANT, COTTAGE GROVE. MINNESOTA

 

 

 

 

 

 

 

Intercept .72 .33 .03
Total Fluorine (ppm) .01 .006 .14
Age (years) .002 .004 .59
(kg/m2) .0000? .01 .94
Cigarettes/day -.003 .003 .37
Alcohol 021de -.16 .08 .05
Estradi0l++ -.001 .003 .56
Bound Testosterone' ?.0002 .0002 .28
Free Testosterone? -.01 .009 .15
Prolaclin" .002 .007 .73
-.03 .01 .005
R2: .26

++pglm 

category is moderate drinkers who consume 1-3 oz ethanol/day.
prolaciin 

lutenizing hormone mU/ml

thyroid stimulating hormone (mU/mi) t0 follicle stimulating hormone

(mU/ml) ratio

119



 

 

TABLE 4.1.58 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE RATIO AMONG 112 MALE WORKERS.
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

 

 
      

 

Intercept .32 .25 .21
Total Fluorine (ppm) .006 .005 .21
Age (years) .004 .003 .26
BMI (kg/m2) .000 .007 27
Cigarettes/day -.001 .002 .53
Alcohol oz/day)# -.07 .06 .26
Estradiol? -.004 .002 .07
Bound Testosterone? -.0001 .001 .84
Free Testosterone? .007 .007 .32
Prolaatin" .001 .005 .91
-.05 .01 .0001
R2: .26



#joglrence category ls moderate drinkers who consume 1-3 oz ethanol/day.
I 

prolactin 

follicle stimulating hormone mUlml

Thyroid stimulating hormone (mU/ml) to lutenizing hormone (mU/ml) ratio

120



TABLE 4.1.59 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE BOUND RATIO AMONG 112 MALE WORKERS.
3M CHEMOLIT PLANT. COTTAGE GROVE, MINNESOTA

 

 

 

 

 

 

 

 

Variable .. 7 7, value
Intercept .60 .43 .17
Total Fluorine (ppm) ~.0001 .009 .98
Age (years) .009 .005 .09
(kg/m2) .01 .01 .40
Cigarettes/day .0001 .004 .82
Alcohol oz/day)# .04 .11 .71
Estradiol++ .004 .003 .18
Bound Testosterone? .0001 .0002 .18
Free Testosterone? -.004 .01 .78
Prolactln" -.oos .009 .57
?.05 .05 .29
R2: .12
?Mpg/ml

#jogfenoe category is moderate drinkers who consume 1-3 oz e?wanoI/dey.

prolaotin 
thyroid stimulating hormone mU/ml
lutenizing hormone (mU/ml) to follicle stimulating hormone
(mU/ml) ratio

121



 

TABLE 4.1.60 PEARSON CORRELATION COEFFICIENTS BETWEEN TOTAL
SERUM FLUORIDE. AGE. BODY MASS INDEX (BMI). DAILY ALCOHOL USE.
DAILY TOBACCO CONSUMPTION. AND LIPOPROTEINS
3M CHEMOLITE PLANT, COTTAGE GROVE, MINNESOTA

g'f'ro AL (?05 wits)" am ?mi??j ALCOHOL TOBACCO

FLUOFIIDE (way) (eta-rum

. .07 .25 .19 .09 .35

p.008 9-.05 b.0001
.02 .13 .03 -.003 .28

 

 

 

-.01 .03 -.13 18 ~09

 

 

 

 

.09 .19 .27 .07 .19
p-.004 . 

 

 

 

 

'mg/dl -
"low do upoprotoi
thigh Iboprotelg

 

 

122 I



TABLE 4.1.61 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE CHOLESTEROL AMONG 111 MALE WORKERS.
3M CHEMOLITE PLANT, COTTAGE GROVE, MINNESOTA

 

 

 

 

Variable

Intercept 107.30 33.00 .002
Total Fluoride (ppm) .52 .67 .44
Cigarettes/day 1.12 .31 .0005
BMI (kg/m2) 1.44 1.01 .16
Age (years) .77 .38 .05
Alcohol 

low (<1oz/day) -5.50 8.71 .53

nonresponse (NR) -13.53 14.75 .35
GGT (lU/dl)? .41 .12 .001
Bound Testosterone" .03 .02 .07

 

 

I12. 29

#Referenoe category ls moderate drinkers who consume 1-3 oz ethanollday.

'gamma glutanryl transferee


123



 

TABLE 4.1.62 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTINGTHE LOW DENSITY LIPOPHOTIEN AMONG ?1 11 MALE WORKERS.
3M CHEMOLITE PLANT GROVE. MINNESOTA

 

   

 

Intercept 73.93 32.00 .03
Total Fluoride (ppm) .22 .65 .73
Cigarettes/day .69 .30 .02
(kg/m2) 1.26 .95 .19
Age (years) .37 .37 .32
Alcohol 
low ozlday) -3.02 8.33 .71
nonresponse (NR) -1 0.85 13.93 .43
Proan (119/111!) -1 .59 .66 .02
Bound .04 .02 .0071
Ta!- .19

#Referenoo category is moderate drinkers who consume 1-3 oz chattel/day.

124



 

TABLE 4.1.63 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE HIGH DENSITY LIPOPROTIEN (HDL) AMONG 111 MALE

 

 

 

WORKERS.
3M CHEMOLITE PLANT. CO1TAGE GROVE, MINNESOTA
Variable
Intercept
Total Fluoride (ppm) -1.61 .77 .04
Alcohol 
low (<1oz/day) -9.92 3.51 .006
nonresponse (NB) -6.7 5.73 .24
low Fluoride 1.62 .80 .04
Fluoride' 2.05 1.63 .21
Age (years) -.004 .12 .97
(kg/m2) -.a1 .29 . 2s
Cigarettes/day . -.12 .09 .. .18
Bound Testosterone" .018 .007 .009
"Free Testosterone? ..77 23 .008

 

Hz. .17
#Referenoe category is moderate drinkers who consume 1-3 oz ethanol/day.
terms between total ?uoride and alcohol category

125



 

 

TABLE 4.1.64 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE TRIGLYCERIDES AMONG 111 MALE WORKERS.
3M CHEMOLITE PLANT. CO1TAGE GROVE. MINNESOTA

 

 

 

 

Intercept 4114.50 117.20 .33
Total Fluoride (ppm) 2.38 2.31 .15
Cigarettes/day 2.28 1.05 .03
BMI (kg/m2) 6.07 3.39 .08
Age (years) 2.32 1.44 .11
Alcohol 

low oz/day) -1 1 .48 29.4 .70

nonresponse (NR) -19.94 49.03 .69
Free Testosterone? 7.34 3.37 .03
Bound Testosterone' ~21 .08 .009
category is moderate drinkerswhocemume 1-3 ozemanelldey.

126



TABLE 4.1.65 PEARSON CORRELATION COEFFICIENTS BETWEEN TOTAL
SERUM FLUORIDE, AGE. BODY MASS INDEX (BMI). DAILY ALCOHOL USE,
DAILY TOBACCO CONSUMPTION. AND HEPATIC PARAMETERS
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

TTML ACE (years) an: Mimi) newonm TOBACCO

     

(?9968!)

 

 

 

 

 

 

 

 

.01 ~.10 .09 .12 -.11

.01 '.01 .20 .03 -.11
n- cg

-.04 .12 .27 .15 .03
93.004

-.03 . 27 19 -.19 .26
p.004 9- 04 p.05 3-906

 

 

 

GLUTAMIC OXALOACETIC TRANSAMINASE 
GLUTAMIC PYRUVIC TRANSAMINASE 
GLUTAMYL TRANSFERASE IUldl

PHOSPHATASE 

127



 

TABLE 4.1.66 PEARSON CORRELATION
ENZYMES, SERUM HORMO

COEFFICIENTS BETWEEN HEPATIC
NES, AND LIPOPROTEINS

3M CH EMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

-.01 .03 ?.13 .18
2.08
09 .19 .27 .07
0-434 D-.OO4
-.18 -.04 .03 . -.003
9-.09
FREE TESTOSTERONE ~12 -.14 -.23 -.03
J31
BOUND -.18 -.1o -.12 -.12
mos
-.20 -.15 -.16 -.20 
p.03 p.09 p-.q3
?mg/6 
"low density bin
4?th density loin
Wm!

128

12320

 

TABLE 4.1.67 PEARSON CORRELATION COEFFICIENTS 

 

 

 

 

 

 

HEPATIC PARAMETERS
3M PLANT. COWAGE GROVE, MINNESOTA
855T $55? 55'? AKFI-I
1 .68 .43 .04
5607. 9.9001
We - 1 .30 .09
P411001 21

- - - 1

 

 

 

 

 

 

 

GLUTAMIG OXALOAOETIO TMNSAMINASE 
GLUTAMIC PYRUVIC TRANSAMINASE lUIdl

GLUTAMYL TRANSFERASE lUldI .,

PHOSPHATASE 

129

12321

TABLE 4.1.68 SERUM GLUTAMIC OXALOACETIC TRANSAMINASE (SGOT 
GLUTAMIC PYRUVIC TRANSAMINASE GLUTAMY 
TRANSFERASE (SGT). AND ALKALINE PHOSPHATASE (AKPH) BY TOTAL
SERUM FLUORINE
3M CHEMOLITE PLANT, COTTAGE GROVE. MINNESOTA

 

 

75375

 

 

 

TOTAL
FLUORINE :32:
<1 23 22.5 4.1 22 13-28 F-o.41
?1.3 65 24.1 8.6 23 10-74 9-50
>3-10 16 25.8 14.5 22.5 17-77
>10-15 6 25.7 11.3 22.5 17-47
>15-26 5 22.2 5.1 22 14-27
TOTAL 115 24.0 8.8 23 10-77
SGPT
(Ill/d!)
<1 23 47.7 10.7 46 30-68 F-1.19
?1.3 85 513 30.2 45 4-263 p.32
>3-10 16 53.0 14.0 50.5 28-40
>10-15 6 73.2 532 52.5 38-177
>15-26 5 44.6 8.8 42 34-54
TOTAL 115 51.7 26.8 47 4-263
Alkallne Phosphatase
(ll-lid!)
<1 23 86.1 25.6 85 43-153 F-0.43
-3 65 85.9 19.9 80 35-137 gnu-.78
>340 16 77.8 20.3 71.5 54-123
>10-15 6 87.2 34.0 75.5 81-153
>15-26 5 88.0 42.1 64 41-153
TOTAL 11566.3 22.8 88 38-153
GGT
(lU/dl)
<1 23 37.2 28.4 27 6-117 M39
66 324 26.7 25 5174 p.31
>3-10 16 35.4 35.4 26 10-156
>10-15. 6 38.3 16.7 36.5 18-80
>15-26 5 22.2 11.5 20 1137
TOTAL 115 33.7 27.6 26 5-174
#univariate Anova
130

12322

 

 

TABLE 4.1.69 SERUM GLUTAMIC OXALOACETIC THANSAMINASE (SGOT)
BY BODY MASS INDEX, AGE. SMOKING AND DRINKING STATUS

3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

 

 

 

 

 

ilU/dl)

?25 41 (35.7) 24 12.4 22 13-77 5.92
25-30 57019.6) 23 5.8 23 10-42 p-.40
>30 17(14.8) 27 3.1 26 17-47
AGE
230 21(13.3) 25 12.7 23 17-77 F..78
31-40 48(41.7) 24 9.1 23 10-74 p.51
41-50 27(235) 22 5.4 23 13-40
51-50 19(165) 26 7.8 23 14-47
Alcohol
210210 87(813) 26 13.5 22 10-77 1-1-51
13cm 20(13.7) 24 3.0 35 10-74 p.44
missing a 23 4.3 21 19-31
Tobacco
maker 28(243) 24 8.4 23 13-77 F-.02
nonsmokar 3505.2) 24 11.0 22 10-42 31-33
missing 2 20 3.5 20 17-47
TOTAL 115
Waivadate Anova
1 31

12323

TABLE 4.1.70 SERUM GLUTAMIC PYRUVIC TRANSAMINASE (SGPT) BY
BODY MASS INDEX. AGE. SMOKING AND DRINKING STATUS
3M CHEMOLITE PLANT, COTTAGE GROVE. MINNESOTA

 

 

 

 

 



MEAN SD MEDIAN RANGE TEST

<25 41 (35.7) 49 35.4 41 29-263 5-2.1
25-39 57149.9) 50 14.2 49 4-95 p-.12
>30 17114.9) 94 32.9 55 39-177
AGE
?39 21119.3) 49 11.5 45 91-99 5-.91
91-49 49141.7) 59 99.9 47 29-293 p-..91
41-50 27123.5) 47 15.2 49 4-99
51-99 19119.5) 57 92.9 so 34-177
Alcohol
<1ozld 97191.3) 53 2935 47 29-293 F-.99
1.99219 20119.7) 47 19.9 49 4-99 
missing 9 51 19.9 52 35-97
Tobacco
smoker 29124.9) 49 15.2 47 4-99 F379
nonmokor M2) 53 29.6 48 30-283 p-..39
missing 2 49 29.5 49 31-97
TOTAL 119
#univariate Anova

132

12324

 

TABLE 4.1.71 GAMMA GLUTAMYL TRANSFERASE (GGT) BY BODY MASS
INDEX, AGE, SMOKING AND DRINKING STATUS
8M CHEMOLITE PLANT . COTTAGE GROVE. MINNESOTA

 

 

r1 (lUIdl)

 

 

<25 41(3517) 28 31.1 17 5-174 F-3.54
25-30 57019.8) 34 23.1 19 8-158 p.03
>30 17(143) 48 28.6 44 19-117
AGE .
<30 21(183) 32 23.4 25 11-111 - F-1.58
3140 48(41.7) 31 32.7 22 5-174 [1-38
41-50 27(235) 33 17.2 29 8-72
51-60 19(185) 44 29.3 35 11-117
Alcohol
<1ozld 87(813) 40 25.5 35 889 Fan-1.64
1302/11 20(18.7) 32 25.3 23 8?174 p.36
missing 8 41 50.4 23 12-158
Tobacco
smoker 36 21.3 as 5-89 Fuss
nonsmokar 8505.2) 32 28.3 25 8-174 p.48
missing 2 85 103.2 as 12-153
TOTAL 115
'iiunivariate Anova

133

12325

 

 

TABLE 4.1.72 ALKALINE PHOSPHATASE (AKPH) MASS INDEX,
AGE, SMOKING AND DRINKING STATUS

3M CHEMOLITE PLANT, GROVE, MINNESOTA

 

 

 

A I

MEAN SD M-IAN RANGE 
BMI
225 41(35.7) 78 22.1 75 38-153 F-1.53
25-30 51649.3) 84 21.9 81 41-153 p.22
>30 17(143) 00 7_ 27.1 80 43-153
AGE
<30 21 (18.3) 78 22.2 76 38-153 F-2.78
31-40 48011.7) 80 20.3 78 50-15. p.45
41-50 27(23.5) 86 24.1 83 48-153
51-60 18(155) 85 24.1 84 41-130
Alcohol
<10?d 87(813) 85 24.0 2 38-153 52.05
1302/0 2008.7) 77 16.8 75 51-124 p-.15
missing 8 82 22.5 70 80-115
Tobacco
smoker 28(24.8) 85 23.8 85 61-153 F-6.48
000311101187 8505.2) T7 22.0 77 38-153 p.012
missing 2 85 24.8 88 58-103
TOTAL 115
_#univariate Anova 

134

12326

 

 

. 

 

TABLE 4.1 .73A LINEAR MULTIVARIATE REGRESSION MODEL 1 OF
FACTORS PREDICTING THE SERUM GLUTAMIC OXALOACETIC
TRANSAMINASE (SGOT) AMONG 111 MALE WORKERS.
3M CHEMOLITE PLANT . COTTAGE GROVE. MINNESOTA

 

 

 

 

Intercept 26.71 7.1 .0003
Total Fluorine (ppm) -3.23 1.31 .02
(kg/m2) 23 .99
T. Fluorine' .12 .05 .015
Age (years) ?.003 .08 .97
Alcohol 

low ozlday) .70 1.85 .71

nonresponse -1.10 3.10 .72
Cigarettes/day -.09 .07 .16
Prolactin -.37 .15 .01
32. .17

#Flaforenoa category ls" consume 1~3 oz ammollday.
interaction tarm between total semi: and BMI.

135

12327

TABLE 4.1.733 LINEAR MULTIVARIATE REGRESSION MODEL 2 OF
FACTORS PREDICTING THE SERUM GLUTAMIC 
TRANSAMINASE AMONG 111 MALE WORKERS.
3M CHEMOLITE PLANT, COTTAGE GROVE. MINNESOTA

 

 

 

Variable 5 W) p-value
Intercept 27.71 6.22 .0001
Total Fluorine (ppm) ~2.70 1.23 .02
BMI (kg/m2) -.oo .06 .11
BMI T. Fluorine' .10 .04 .02
Age (years) I -.02 .07 .74
Cigarettes/day -.1 1 .06 .1 1
Alcohol 

low ozlday) 1.84 1.61 .28

nonresponse (NR) -1.3 2.7 .64
Prolactin (rug/ml) -.27 .13 .04
GGT (lUIdl)" .1 3 .02 .0001

 

 

32- .35

#Fleforonoo category to moderate drinkers who consume 1-3 oz ammollday.
Interaction term between total serum ?uo?de and 

Gamma glutamyl transfema 

136

12328

 

TABLE 4.1.730 LINEAR MULTIVAFIIATE REGRESSION MODEL 3 OF
FACTORS PREDICTING THE SERUM GLUTAMIC OXALOACETIC
TRANSAMINASE (SGOT) AMONG 111 MALE WORKERS.
3M CHEMOLITE PLANT. GROVE. MINNESOTA

 

 

 

 

 

Intercept 120.60 4.0 .002
Total Fluorine (ppm) .63 .78 .42
(kg/m2) -.07 .13 .50
T. Fluorine' -.03 .03 .34
Age (years) .06 .05 23
Cigarettes/day -.02 .04 .45
Alcohol 

. low ozlday) -.65 1.03 .53

nonresponse (N R) -1 .40 1.72 .42

Prolactin -.09 .00 .29
SGPT (lU/dl)? .24 .01 .0001
HZ. .74

#Roferonoo category is moderate (trinkets who consume 1-3 oz ethanol/day.
Interaction term between total 83mm ?uoride, and -

Serum glutamic pymvic transmittal:

137

12329

 

TABLE 4.1 .74A LINEAR MULTIVARIATE REGRESSION MODEL 1 OF
FACTORS PREDICTING THE SERUM GLUTAMIC PYRUVIO TRANSAMINASE

(SGPT) AMONG 111 MALE WORKERS.

3M CHEMOLITE PLANT. GROVE, MINNESOTA

 

Variable 5 value

Intercept 58.13 24.26 .02
Total Fluorine (ppm) -1 5.80 4.58 .0008
(kg/m2) .30 .82 .72
T. Fluorine? .62 .17 .0004
Age (years) -.24 .28 .39
Alcohol 

low (<1ozlday) 5.54 6.36 .39

nonresponse (NR) 1.31 10.63 .90 
Cigarettes/day -.27 .23 .24 
Prolactln (rig/ml) -1.18 .51 .02

 

755-21

#Referenoe category is moderate drinkem who consume 1-3 oz ethanollday.
interaction term between total serum ?uoride and 

138

12330

 

TABLE 4.1.743 LINEAR MULTIVARIATE REGRESSION MODEL 2 OF
FACTORS PREDICTING THE SERUM GLUTAMIC PYRUVIC TRANSAMINASE

(SGPT) AMONG 111 MALE WORKERS.

3M CHEMOLITE PLANT. COWAGE GROVE, MINNESOTA

 

 

 

 

 

Variable 75 W6) parami?
lnteroept 62.09 19.63 .002
Total Fluoride (ppm) -1 3.70 3.64 .0003
(kg/m2) -.70 .66 .30
T. Fluorine? .54 .14 .0001
Age (years) -.33 .22 .1 4
Cigarettes/day -.027 .18 .14
Alcohol 

low (<1ozlday) 10.02 5.09 .05
nonresponse (NR) .48 8.44 .95
Prolactln -.74 .41 .07
GGT (lU/dl)? .56 .07 .0001
51

#Fleforenoe category is moderate drinkers who consume 1-3 oz manollday.
Interaction term between total serum fluoride and BMI

Gamma glulamyl transferase

139

12331

TABLE 4.1.740 LINEAR MULTIVARIATE HEGRESSION MODEL 3 OF
FACTORS PREDICTING THE SERUM GLUTAMIC PYRUVIC TRANSAMINASE

(SGPT) AMONG 111 MALE WORKERS.

3M CHEMOLITE PLANT. COWAGE GROVE, MINNESOTA

 

 

Variable Evalue

 

Intercept -1 825 14.36 .21
Total Fluorine (ppm) -6.65 2.61 .01
BMI (kg/m2) .30 .45 .51
BMI T. Fluorine? .27 .10 .007
Age (years) -.23 .16 .14
Cigarettes/day -.001 .13 .99
Alcohol 

low ozlday) 3.55 3.53 .32

nonresponse (NR) 4.39 5.91 .46
Prolactin (noun!) -.11 29 .72
SGOT (lUIdl)? 2.85 .1 9 .0001
category is moderate drinkers who consume 1-3 oz emanouday.

Interaction term between total serum ?uoride and BMI

serum glutamio oxeloaootic transom

140

12332

TABLE 4.1.75A LINEAR MULTIVARIATE REGRESSION MODEL 1 OF
FACTORS PREDICTING THE GAMMA GLUTAMYL TRANSFERASE (GGT)
AMONG 111 MALE WORKERS.
3M CHEMOLITE PLANT. COTTAGE GROVE, MINNESOTA

 

 

         

 

Intercept -1 2.59 22.62 .58
Total Fluorine (ppm) -1.93 2.11 .36
Alcohol #7
low (<1oz/day) -1 2.37 9.50 .20
nonresponse (NR) 28.13 15.46 .07
low Fluorine? 1.59 2.18 .47
NR Fluorine? 13.90 4.48 .003
Age (years) 29 .30 .33
(kg/m2) 1.71 .76 .03
Cigarettes/day .09 .24 .72
1:12- .18

Reference category is moderate drinkers who consume 1-3 oz ethmollday.
'lnteracllon terms between total ?uoride and aioohoi category

 

 

141

12333

TABLE 4.1.758 LINEAR MULTIVARIATE REGHESSION MODEL 2 OF
FACTORS PREDICTING THE GAMMA GLUTAMYL TRANSFERASE (GGT)
AMONG 111 MALE WORKERS.
3M CHEMOLITE PLANT. COTTAGE GROVE, MINNESOTA

 

 

 

 

Intercept -56.78 21 .55 .008
'rllotal Fluoride (ppm) -1.79 1.83 .33
Alcohol 
low (<1ozlday) -9.04 8.25 .28
nonresponse (N Fl) -20.06 13.49 .14
low Fluorine' 1.39 1.90 .47
NR Fluorine" 12.18 3.91 .002
Age (years) .15 .26 .57
BMI (kg/m2) 1.30 .66 .05
Cigarettes/day .01 .23 .96
Cholesterol (mg/d1) .15 .06 .02
SGOT (lU/dl) 1.16 .24 .0001
Hz: .35

#Fleforanoe category ls moderate drinkers who 1-3 oz a?aanollday.
'interao?on terms between total fluoride and alcohol category

142

12334

 

TABLE 4.1.750 LINEAR MULTIVARIATE REGRESSION MODEL 3 OF
FACTORS PREDICTING THE GAMMA GLUTAMYL TRANSFERASE (GGT)
AMONG 11 1 MALE WORKERS.
3M CHEMOLIT PLANT. COTTAGE GROVE. MINNESOTA

 

 

   

Intercept -32.39 18.47 .08
Total Fluorine (ppm) -1.63 1.60 .31
Alcohol 
low czlday) -1 3.56 7.17 .06
(NR) 2668 11.75 .025
low Fluorine? .92 1.66 .58
NR Fluorine' 12.04 3.41 .0006
Age (yearsClgaretteslday .09 .20 .65
Cholesterol (mg/d1) .12 .06 .04
SGPT (lU/dl)? .59 .07 .0001
Ti- 53

 

#Reference category is moderate drinkers who consume 14! oz ethanol/day.
'lnteractlon terms between total ?uoride and alcohol category
serum glutamlc pyruvlc transaminase

'143

12335

 

TABLE 4.1.76 LINEAR MULTIVARIATE REGRESSION MODEL 1 OF FACTORS
PREDICTING THE ALKALINE PHOSPHATASE (AKPH) AMONG 111 MALE

 

 

 

WORKERS.
3M CHEMOLITE PLANT, COTTAGE GROVE. MINNESOTA

Intercept 24.50 15.69 .09
Total Fluorine (ppm) -1.03 .43 .02
Cigarettes/day -.06 .22 .79
Cigarettes/day Fluorine? .22 .05 .0001
BMI (kg/m2) 1.10 .55 .05
Age (years) .54 .22 .02
Alcohol 

low ozlday) 5.78 4.90 .24

nonresponse (NR) 8.12 8.13 .32
32- .31 

 

#Referenco category is moderate dnnkete who consume 1-3 oz emanollday.
Interaction term between total serum fluoride and cigarettes/day.

144

12336

 

 

TABLE 4.1.77 PEARSON CORRELATION COEFFICIENTS BETWEEN TOTAL
SERUM FLUORIDE. AGE, BODY MASS INDEX (BMI), DAILY ALCOHOL USE.
DAILY TOBACCO CONSUMPTION, AND HEMATOLOGY PARAMETERS
3M CHEMOLITE PLANT, COTTAGE GROVE. MINNESOTA

 

TOTAL AGE (years) 3m (kg/m5) ALCOHOL TOBACCO

FLUOBINE (oz/day) (cicada!)

    
 

    

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

"201.00?
2.04 2.008
Tee'- .10 .07 .07 -.07 .70
2.0001
pun ooum+ .05 .03 09 -.10 .64
2.0001
-.10 .13 *Ts 02 23
2.003 
Twp? Hocvr'ss .19 -.05 .04 is 23
p-.04 9-.002
woof-res .05 .04 -22 -.21 .32
03.02 5.03 2-0004
.10 -.13 T1 1 .05 '29
P..002
.04 -.03 -.02 -.14 
.26 -.14
mom
9/0:
?white blood can count
polymorphonuclear leukocyta count
145

12337

TABLE 4.1.78 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE HEMAGLOBIN AMONG 111 MALE WORKERS.
3M CHEMOLITE PLANT, COTTAGE GROVE, MINNESOTA

 

 

 

 

Variable 75 $13) Evalue
intercept I 14.51 .67 .0001
Total Fluorine (ppm)* -.002 .0009 .02
Alcohol 

low ozlday) .22 .20 .27

nonresponse (NR) .56 .33 .09
Age (years) .001 .009 .88
(kg/m2) .01 .02 . .65
Cigaretteslday .01 .007 .20
Gigs/day Fluorine?? .0000 .0001 .0005
Estradiol (pg/ml) .01 .006 .07

'07-'23

'0quara transformation of total ?uoride
inoforonoo oatogoly is moderate drinkers who consume 1-3 oz othmollday.
?mtomc?ontonnbetwoon 

146

 

12338

TABLE 4.1.79 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE MEAN CORPUSCULAFI HEMOBLOBIN (MCH) AMONG 111

 

 

 

MALE WORKERS.
3M CHEMOLITE PLANT, GROVE, MINNESOTA
Variable p-value 
,lntercept 31.65 .95 .0001
Total Fluorine (ppm) .15 .09 .10
Alcohol 
low ozlday) 1 -.29 .65 .65
nonresponse (NR) .03 .01 .02
low Fluorine -.16 .09 .08
NR Fluorine -.04 .19 .80
Age (years) .03 .01 .02
BMI (kg/m2) -.07 .03 .01
Cigmetteslday' .02 .01 .13
Gigs/day .?uo?ne? .006 .003 .03

 

32.24

#Rafarenoo category is moderate drinkers who consume 1 4-1 oz ethan

?1nteraction terms: alcohol category by total ?uoride. cigamttes per day by tau: ?uoride?

147

12339

TABLE 4.1.1.80 LINEAR MULTIVAFIIATE REGRESSION MODEL OF FACTORS
PREDICTING THE MEAN (MCV) AMONG 111 MALE
3M CHEMOLITE PLANT. COTTAGE GROVE, MINNESOTA

 

 

 

 

Intercept 8.74 250 .0001
Total Fluorine (ppm) -.04 .07 .52
Alcohol 

low (<1czlday) -.61 .78 .43

nonresponse (NH) -.95 1.27 .46
Age (years) .1 1 .03 .002
BMI (kg/m2) -.06 .08 .05
Cigarettes/day - .04 .03 .21
Gigs/day Flucrine' .02 .007 .004
TSH (mU/ml) .38 .35 .29
R2- .23

#Reference category ls moderate drinkers who consume 1-3 oz amend/day.
term; cigarettes per day by total lluorlde

148

12340

 

 

TABLE 4.1.81 LINEAR MULTIVAFIIATE REGRESSION MODEL OF FACTORS
PREDICTING THE WHITE BLOOD CELL COUNT (WBCY AMONG '111 MALE

 

 

 

 

3M CHEMOLITE PLAN?Igvgoa'fTEng GROVE. MINNESOTA

Intercept 2.87 1.32 .03
Total Fluorine-(ppm) .07 .10 .49
Alcohol 

low (<1ozlday) .44 .46 .33

nonresponse (NR) ?1.08 .74 .15

low Fluorine -.04 .10 .68

NR Fluorine .59 .21 .006
Age (years) -.007 .02 .64
BMI (kg/m2) .07 .04 .05
Cigarettes/day .13 .01 .0001
Free .04 .03 .13
.10 .04 .02


#Referenoe category ls moderate drinkers who consume 1-3 oz ethanollday.
lutenizing hormone mUIml

149

12341

TABLE 4.1.82 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE POLYMORPHONUCLEAFI LEUKOCUTE COUNT (POLY)
AMONG 111 MALE WORKERS.
3M CHEMOLITE PLANT, GROVE, MINNESOTA

 

 

 

 

 

Intercept 368 1151 .75
Total Fluorine (ppm) 165 88 .06
Alcohol 

low ozlday) 746 399. .06

nonresponse (NR) -49 651 .94

low Fluorine ?461 90 .08

NR Fluorine 370 185 .05
Age (years) 6 14 .66
(kg/m2) 45 33 .17
Cigarettes/day 95 10 .0001
Ll-l (mUlml)++ 79 36 .03
Bound Testosterone' ?1.62 .8 -04
Free Testosterone moderate drinkers who consume 1-3 oz 

150

 

12342

 

TABLE 4.1.83 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE BAND COUNT (BAND) AMONG 111 MALE WORKERS.
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

 

 

Intercept -1 1.4 - 129.6 .93
Total Fluorine (ppm) ?3.4 3.2 .30
Alcohol 

low ozlday) 78.2 40.3 .05

nonresponse (N R) 14.9 67.8 .83
Age (years) 1.0 1 .8 .56
BMI (kg/m2) 2.2 4.6 .63
Cigaretteslday 4.2 1 .5 .005
H2: .12

#Referanoo category is moderate drinkers who comm 1-3 oz ahanollday.

151

12343

TABLE 4.1.84 LINEAR MULTIVAFIIATE REGRESSION MODEL OF FACTORS
PREDICTING THE AMONG 111 MALE
8M CHEMOLITE PLANT. OOTTAOE GROVE. MINNESOTA

 

 

 

Intercept 2205.8 811.1 .0005 i

 

Total Fluorine (ppm) 642.7 125.3 .007
Alcohol 
low (<1ozlday) -526.6 222.7 .02
nonrasponse (NR) 9771 855.7 .007
lowX Fluorine 189.0 52.3 - .0005 5
NR Fluorine 247.9 108.9 .02 
Cigarettes/day 34.0 8.9 .0001
Cigslday Fluorine? -3.3 1.45 .02
SW (kg/m2) 1.58 19.6 .94
BM: Fluorine' 7.15 4.1 .08
Age (years) -18.1 8.8 .08 
Prolactin (ng/ml) 38.5 14.2 .008
TSH (mU/ml)+ 170.4 772 .08 
.35

#Roforonoo Mary is moderate drinkers who consume 1-3 oz otlmnollday.
'intoraction terms abohol category by total ?uoride: olgarottoslday by total ?uoride.

by total ?uoride. I
4 thyroid stimulating homono mUIml i

152

12344

 

TABLE 4.1.85 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE MONOCYTE COUNT (MONO) AMONG 111 MALE

 

 

 

WORKERS.
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA
Variable T513) Evalue

Intercept 397.4 198.9 .05
Total Fluorine (ppm) 110.4 88.6 .005
#0001101 

10w (<1ozlday) 132.1 53.3 .02

nonresponse (NR) 40.1 89.1 .66
Age (years) -.37 2.4 .88
(kg/m2) -2.66 7.0 .70
BMI Fluorine? -4.0 1.42 .006
Cigarettes/day 7.0 1.9 .0004
13.9 6.8 .04

113- 30 

#Rafaranoe category is moderate drinkers who consume 1.3 oz ehanollday.
'intaraction term. 0511010! ?uoride.
Iutenizing hormone mUIml

153

12345

TABLE 4.1.86 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE EOSINOPHIL COUNT (EOS)
AMONG 111 MALE WORKERS.
3M CHEMOLITE PLANT, COTTAGE GROVE, MINNESOTA

 

 

 

 

Intercept 50.45 122.30 .68
Total Fluorine (ppm) -7.31 3.35 .03
Alcohol 

low ezlday) ~12.1 0 37.91 .75

nonresponse (NR) 21.79 62.25 .73
Age (years) 1.56 1.67 .35
(kg/m2) 2.10 4.13 .61
Cigaretteslday 3.04 1.59 .08
Gigs/day Fluorine? .62 .35 .08
30.1 17.1 .08

In
154

 

12346

 

TABLE 4.1.87 LINEAR MULTIVARIATE REGRESSION MODEL OF FACTORS
PREDICTING THE PLATELET COUNT (PLATE) AMONG 111 MALE

 

 

    

WORKERS.
3M CHEMOLITE PLANT, COTTAGE GHOVE. MINNESOTA

    

 

Intercept 264.7 54.8 .0001
Total ?uorine (ppm) 29.8 9.5 .002
Alcohol 

low ozlday) 8.2 . 13.3 .54

nonresponse (NR) .9 22.5 .97
Age (yearS) ~1.3 .6 .04
BMI (kg/m2) 1 .1 1 .7 .53
Fluorine? -1.0 .4 .004
Cigarettes/day 2.7 .6 .0001
Gigs/day Fluorine? -.3 .1 .04
Proan 2.6 .03 .09
Bound Testosterone?t0 -.04 .03 .10
32.28

#Referanca category is moderate (trinkets who comma 1-3 oz athanollday.
'interaction terms, BMI by total ?uowe. dgarottos per day by total ?uoride.



155

12347

TABLE 4.1.88 LINEAR MULTIVARIATE HEGRESSION MODEL OF FACTORS

PREDICTING THE BASOPHIL COUNT (BASO) AMONG 111 MALE WORKERS.

3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

 

   

Intercept 44.35 54.19 .42

 

 

Total Fluorine (ppm)* -.03 .06 .61
Alcohol 

low ozlday) -1.73 13.61 .90

nonresponse (NR) -.56 22.54 .81
Age (years) -.07 .68 .92
BMI (kg/m2) -.61 1.58 .70
Gigeretleslday -.80 .52 .12
Gigs/day Fluorine?" .02 .007 .007
Bound Testosterone? -.07 .04 .06
Free Testosterone!? 2.5 1.6 .11
5.5 1.8 .002
Fiz- .17

?square transfonna?on of total eenrm ?uoride
#Relerenoe category ls moderate drinkers who consume 14% oz amend/day.
'lnterao?on term. cigarettes per day by total fluoride.


lutenlzing hormone mUIml

156

12348

 

WW

TABLE 4.2.1 CHARACTERISTICS OF 749 FEMALE EMPLOYEES, 1947-1989.

 

Chemical Non chemical Total
Division Division

number of workers 245 504 749
person years of 6029.0 13280.4 19309.4
observation
mean follow-up 24.6 26.4 25.8
(years)
mean age at 28.8 26.9 27.6
employment
wears}
mean year of 1965.0 1962.8 1963.5
employment
(years)
mean year of 1981.3 1979.2 1979.6
death (years)
mean age at death 58.7 54.4 55.4
lyears}

 

 

157

12349

TABLE 4.2.2 CHARACTERISTICS OF 2788 MALE EMPLOYEES. 1947-1990.

 

 

 

 

Chemical Non chemical Total
number of workers 1339 1449 2788
person years of 33385.3 37732.4 71117.7
observation
mean follow-up 24.8 26.0 25.5
(yeaIS)
mean age at 25.6 28.9 27.3
employment
(years)
mean year of 1963.8 1962.3 1963.0
employment
Wears}
mean year of 1978.3 1978.1 1978.2
death (years)
mean age at death 54.2 58.1 56.4
(yearS)

 

 

158

12350

TABLE 4.2.3 VITALSTATUS AND CAUSE OF DEATH ASCERTAINMENT
AMONG 749 FEMALE EMPLOYEES, 1947-1990.

 

 

Vital status Chemical Non chemical Total
Alive 234 95.3 465 91 .6 699 93.3
Dead6.7
Total 245 100.0 504 1 00.0 749 1 00

 

?two deaths occurred outslde the US. with cause of death ascertained from
sources other than death certi?mtes.

1! TABLE 4.2.4 VITAL STATUS AND CAUSE OF DEATH ASCERTAINMENT
AMONG 2788 MALE EMPLOYEES, 1947-1989.

'V?Ital status mammal Non chemical I?Fetal

  

             

No.

0. No.
Alive 1 1 91 88.9 1249 86.2 2440 87.5
Dead3.8 348 12.5
Total 1339 100.0 1449 100.0 2788 100.0

 

'two deaths occurred outside the with cause of death ascertained from
sources other thanth certi?cates.

 

159

12351

TABLE 4.2.5 NUMBERS OF DEATHS AND ST ANDARDIZED MORTALITY
RATIOS (SMHs) AMONG 749 FEMALE EMPLOYEES. 1947-1989.

 

 

 

 

All causes 50 66.74 .75 .56-.99
Cancer 17 23.04 .71 .424 .14
Gastrointestinal 2 4.54 .44 .05-1.59
Respiratory 4 4.72 .95 .26-2.43
Breast 3 5.87 .51 .10?1.49
Genital 2 3.37 .59 .07-2 14
3 2.04 1.47 .30-429
Heart disease 10 12.39 .81 .49-129
Cerebrovasoular 3 3.51 .86 .01-4 80
Gastrointestinal 3 3.41 .88 .18-2 57
Injuries 4 6.23 .64 .17-1 64
Suicide 1 1.12352

TABLE 4.2.6 NUMBERS OF DEATHS AND ST ANDARDIZED MORTALITY
RATIOS (SMRS) BY DURATION OF EMPLOYMENT AMONG FEMALE

 

  

  

     

EMPLOYEES.
1947-1989.

ml Bath -, w, 95? 51
Duration 510 years

All causes 50 66.74 .75 56-.99
Cancer 17 23.04 .71 .42-1.14
Cardiovascular 18 22.00 .82 .48-129
Duration >10 years

All causes 20 26.62 .75 .46-1.16
Cancer 6 9.42 .64 23-1 .39
Cardiovascular 8 10.27 .78 .34-1.54

 

Ibbrevietions used are: Obs, observed; Exp. expected; CI, con?dence interval.

161

12353

 

TABLE 4.2.7 NUMBERS OF DEATHS AND ST ANDARDIZED MORTALITY
RATIOS (SMRS) BY LATENCY AMONG FEMALE EMPLOYEES, 1947-1989.

 

          

Latency>10 years

All causes 41 56.94 .72 52-98

Cancer 16 20.93 .76 .44-1.24

Cardiovascular 13 19.66 .65 .35-1.12

Latenoy>15 years 
All causes 37 49.37 .75 .53-1.03 
Cancer 14 1 8.25 .77 .42-129

Cardiovascular 13 17.79 .73 .39-125

Latency>20 years

All causes 29 39.20 .74 .49-1.06

Cancer - 11 14.47 .76 .38-1.36

Cardiovascular 10 14.67 .68 .33-125

 

Abbreviations used are: Obs, observed?xp. expected; CI. confidence interval.

162

12354

 

TABLE 4.2.8 NUMBERS OF DEATHS AND STANDARDIZED MORTALITY
RATIOS (SMRS) BY ANY EMPLOYMENT IN THE CHEMICAL DIVISION
AMONG FEMALE EMPLOYEES, 1947-1989.

_0 ,7 ,7 A 

Not employed in
CD

 

   

All causes 39 43.05 .91 .64-124
Cancer 14 15.46 .91 .49-1.52
Cardiovascular 13 13.82 .94 .50-1.61
Heart disease 8 7.69 1.04 .45-2.05
AJI GI 2 2.23 .90 .10-323
AII respiratory 2 2.23 .90 .10-323
Injuries 3 1.48 2.02 .41 -5.90
employed in CD
All causes 11 23.69 .46 23-.83
Cancer 3 8.38 .36 .07-1.05
Cardiovascular 5 8.19 .61 .20-1.43
Heart disease 2 4.69 .43 .05-1.54
All GI 1 1.18 .85 .01-4.73
AII respiratory 1 1.28 .78 .01-4.81
Injuries 1 1.98 ?.51 .51 ?2.81

 

Abbreviations used are?bs, oMerveT?xp. expectedET, comdence interval;
CD. Chemical Division.

16.3

12355

 

TABLE 4.2.9 NUMBERS OF DEATHS AND ST ANDAFIDIZED MORTALITY

RATIOS (SMRs), BASED ON U.S. WHITE MALE RATES,
AMONG 2788 MALE EMPLOYEES, 1947-1989.

 

 

wuss of basal? ?es Exp 95%. l_
All causes 347 473.56 .73 .66- .81
Cancer 103 107.80 .95 .77-1.15
Gastrointestinal 24 25.94 .93 .59-1.38
Colon 9 9.11 .99 .45-1.88
Pancreas 3 5.33 1.50 .65-2.96
Respiratory 31 40.53 .76 521.09
Lung 29 38.72 .75 .50-1.08
Prostate 6 5.10 1.18 .43-2.56
Testis 1 .62 1.22 .02-6.60
Bladder 3 2.20 1.36 .27-3.98
13 11.42 1.14 .54-1.84
Cardiovascular 145 203.31 .71 .60-.84
Cl-lD 110 147.04 .75 .61 -.90
Cerebrovasmlar 10 19.92 .50 24-.92
All Gastrointestinal 12 23.99 .50 26?37
All respiratory 13 25.89 .50 27-.36
Diabetes 8 6.53 1.23 .53~2.42
Injuries 38 46.56 .82 .58-1 .12
Suicide 12 17.10 .70 .32-123

 

Abbreviations used are: (The. observed; "Exp, expected; CI. con?dence interval;
CHD. coronary and atherosclerotlc heart disease.

164

12356

 

TABLE 4.2.10 NUMBERS OF DEATHS AND ST ANDARDIZED MORTALITY
RATIOS (SMRS). BASED ON MINNESOTA WHITE MALE RATES. AMONG
2788 MALE EMPLOYEES, 1947-1989.

 

 
    

Cause of Deafi'T Obs SMR 
All causes 347 450.79 77 .69-.86
Cancer 103 9729 1.05 36-12?
Gastrointestinal 24 26.78 .90 571.33
Colon 9 9.42 .96 .44-1.81
Pancreas 8 5.58 1.43 .62-2.83
Respiratory 31 30.42 1.02 .69-1.45
Lung 29 28.94 1.00 .67-1.44
Prostate 6 6.07 .99 .36-2.15
Testis 1 .92 1.09 .01 -6.05
Bladder 3 2.18 1.37 284.01
13 12.07 1.09 .57-1.84
Cardiovascular 145 212.19 .63 .58-.80
CHD 110 159.09 .69 57-.83
Cerebrovascular 10 24.66 .60 .32-1 .02
All Gastrointestinal 12 21.13 .57 29-.99
All respiratory 13 21.75 .60 .32-1.06
Diabetes 8 6.52 1.23 .53?2.42
Injuries 38 47.74 .80 .56-1 .08
Suicide 12 15.09 .79 .41 -1 .39

 

Abbreviations used areTOFs. observed; Exp, interval;
CHD, coronary and atherosclerotic heart disease.

165

12357

TABLE 4.2.11 NUMBERS OF DEATHS AND ST ANDARDIZED MORTALITY
RATIOS (SMRs) BY LATENCY, BASED ON MINNESOTA WHITE MALE
RATES, AMONG MALE EMPLOYEES. 1947-1989.

.LATENCY 2 10 YEARS

?ause ?Obsw

        

 

All muses 299 398.27 .77 .68-.86
Cancer 98 88.71 1.10 .90-1.35 1
Gastrointestinal 24 24.78 .97 ?24.44 
Pancreas 5.20 1.54 era-3.03 
Respiratory 29 28.81 1.01 .67-1.45
Lung 27 27.44 .98 .65-1.43
Skin 3 1.53 1.96 .39-5.73
Prostate 6 5.94 1.01 .37-220
Bladder 3 1.75 1.72 .34~5.01
11 10.03 1.10 .55-1.96
Cardiovascular 130 195.91 .66 . 55-.79
All Gastrointestinal 8 18.58 .43 .1986
All respiratory 11 20.16 .55 .27-.98
Diabetes 8 5.37 1.49 .64?294
injuries 21 27.61 .76 .47-1.16
Suicide 11 10.19 1.08 .544 .93

 

Abbreviations used are: Che. observed; Exp, expected; CI, con?dence interval;
CHD, coronary and atherosclerotic heart disease.

166

 

12358

 

TABLE 4.2.12 NUMBERS OF DEATHS AND STANDARDIZED 
RATIOS (SMRs) BY LATENCY. BASED ON MINNESOTA WHITE MALE
RATES, AMONG MALE EMPLOYEES, 1947-1989.

 

LATENCY 2 15 YEARS

Tause of ?eath rifts EB emf We.
All causes 266 344 .77 .6837
Cancer 90 80.64 1.12 .90-1.37
Gastrointestinal 24 22.63 1.06 .68-1.51
Pancreas 8 4.72 1.69 .73-3.32
Respiratory 27 26.71 1.01 .67-1.47
Lung 25 25.45 .98 .64-1.45
Skin 3 1.29 2.33 .47?6.80
Prostate 5 5.73 .87 .28-2.04
Bladder 3 1.96 1.53 .37-4.47
9 8.68 1.04 .47-1 .97
Cardiovaswlar 119 178.25 .67 .55-.80
All Gastrointestinal 8 16.17 .49 21-97
All respiratory 9 18.60 .48 22-.92
Diabetes 7 4.54 1.54 .82~3.18
injuries 23 29.21 .79 .50-1.16
Suicide 9 7.47 1.21 .55-229

 

Abbreviations used are: Obs. observed; Exp. expected; OWdence interval;
CHD, coronary and ati'Ierosdero?c heart disease.

167

12359

 

TABLE 4.2.13 NUMBERS OF DEATHS AND STANDARDIZED MORTALITY
RATIOS (SM Rs) BY LATENCY, BASED ON MINNESOTA WHITE MALE
RATES, AMONG MALE EMPLOYEES. 1947-1989.

LATENCY 2 20 YEARS

   

     

All arises 216 286.9 .75 .86-.86
Cancer 73 68.74 1.06 .83-1.34
Gastrointestinal 15 19.33 .77 .43-128

7 Pancreas 4 4.06 .99 27-252
Respiratory 25 23.06 1.08 .70-1.60
Lung 23 21.06 1.05 .66-1.57
Skin 2 .98 2.02 .23-7.34
Prostate 5 5.29 .95 .30-221
Bladder 3 1.75 1.72 .34-5.01
7 7.01 .99 39-203
Cardiovascular 99 151.80 1.06 .83-1.34
All Gastrointestinal 8 12.90 .62 27-121
All respiratory 9 16.3 .55 .25-1.05
Diabetes 7 3.65 1.92 .77-3.95
Injuries 13 19.47 .67 .36-1.14
Suicide 7 5.01 1.40 .56-2.80

 

Abbreviations used are: Obs. observed; Eip, expected?l. con?dence interval;
CHD, coronary and atherosderotic heart disease.

168 

12360

 

TABLE 4.2.14 NUMBERS OF DEATHS AND ST ANDAFIDIZED MORTALITY

RATIOS (SMFIs) BY DURATION OF EMPLOYMENT. BASED ON MINNESOTA

WHITE MALE RATES. AMONG MALE EMPLOYEES, 1947-1989.
DURATION 2 5 YEARS

Cause of Bath TObs FE 95% DI

All causes
Cancer
Gastrointestinal
Colon
Pancreas
Respiratory
Lung
Prostate
Bladder
Brain

Cardiovascular
CHD
Cerebrovasoular
All Gastrointestinal
All respiratory
Diabetes
Injuries
Suicide

assess?

A


321 .20
72.21
20.21

7.1 0
4.22
23.72
22.1 0
4.47
1 .68
2.51
8.41

1 59.50

120.20
1 8.44
1 5.20
16.30

4.53
36.60
8.81



.55
1 .77
.79
1 .02

.70-.90
.88-1 .38
068.1 .65
.49-222
.66-3.42
.70-1 .59
.66-1 .56
.23-2.1 5
?134.29
.24-1 .50
.26-1 .55

.59-.86

.60-.92

.1 2-.71

.1 8-.95
.25-1 .05
.76-3.48
.53-1 .14
.47-1 .94

 

Abbreviations used are: Obs. observed
CHD. coronary and atherosclerotic he

169

Exp. expectedm??denee interval;
an dsease.

12361

 

TABLE 4.2.15 NUMBERS OF DEATHS AND STANDARDIZED MORTALITY
RATIOS (SMRs) BY DURATION OF EMPLOYMENT, BASED ON MINNESOTA
WHITE MALE RATES, AMONG MALE EMPLOYEES, 1947-1989.

 

DURATION 2 10 YEARS

'EEuse oF?eath 66s Exp 95% I

All muses 203 257.30 .79 .68-.91
Cancer 67 59.36 1.13 .67-1.43
Gastrointestinal 20 16.75 1.19 .73-1.84
Colon 7 5.92 1.16 .47-2.44
Pancreas 6 3.50 1.71 .63-3.71
Respiratory 22 19.38 1.13 .71 -1 .72
Lung 20 18.47 1.08 .66-1.67
Prostate 4 4.20 .95 26-244
Bladder 1 1.44 .69 .01 ~3.65
Brain 3 1.89 1.59 .32-4.64
5 6.58 .76 .24-1 .77
Cardiovascular 92 132.1 3 .70 56-85
CHD 75 99.75 .73 57-92
Cerebrovascular 5 15.49 .32 .10-.75
All Gastrointestinal 4 11.96 .33 .09-.86
All respiratory 7 13.80 .51 .20-1.05
Diabetes 8 3.49 2.29 .99-4.51
Injuries 19 23.46 .68 .34-122
Suicide 8 5.68 1.36 .59?2.66

 

 

um .uu-v-

we.?

170

Abbreviations used are: Obs. observed?xp. expected; 51. con?dence interval;
OHD, coronary and atherosclerotio heart disease.

12362

 

TABLE 4.2.16 NUMBERS OF DEATHS AND STANDARDIZED MORTALITY
RATIOS (SMRs) BY DURATION OF EMPLOYMENT. BASED ON MINNESOTA

WHITE MALE RATES, AMONG MALE EMPLOYEES. 1947-1989.

 

 

DURATION 2 20 
'Cause of Beath Obs 8MB 95% 5  
Ali causes 104 152.36 .68 .56-.83
Cancer 35 37.31 .94 .65-1.30
Gastrointes?nal 10 10.52 .95 .46-1.75
Colon 5 3.77 1.33 .43-3.09
Pancreas 1 2.21 .45 .01-2.52
Respiratory 11 12.69 .87 .43-1.55
Lung 10 12.10 .83 .40-1.52
Prostate 2 2.83 .71 .08-2.55
Bladder 1 .94 1.08 . .01 -5.91
Brain 1 1.03 .97 .01-5.40
4 3.82 1.05 .28-6.02
Cardiovascular 48 80.6 .58 .19-1.36

CHD 39 81.25 .64 .45-.87

Cerebrovascular 1 9.13 .11 .00-.61
All Gastrointestinal 2 6.87 .29 .03-1.05
All respiratory 5 8.61 .58 .19-1 .36
Diabetes 5 1.94 2.58 .83-6.02
Injuries 2 6.61 .30 .03-1.09
Suicide 3 2.54 1.18 .24-3.45

 

Abbreviations used are: Obs, observed; Exp. expected; CI. con?dence interval;

CHD. coronary and atherosclerotio heart dsease.

171

12363

 

 

 

TABLE 4.2.17 NUMBERS OF DEATHS AND STANDARDIZED 
RATIOS (SMRs), BASED ON MINNESOTA WHITE MALE RATES. AMONG
1339' MALE EMPLOYEES IN THE CHEMICAL DIVISION.

 

     

tause of?eath Obs 7 7 95% CI
All causes 146 172.96 .86 .72-1.01
Cancer 40 36.31 1.10 .79-1.50
Gastrointestinal 9 9.77 .92 .42-1 .75
Colon 4 3.46 1.15 .31 -4.01
Pancreas 4 2.04 1.96 .53-5.01
Respiratory 12 11.26 1.07 .55-1.86
Lung 11 10.70 1.03 .51 -1 .34
Prostate 4 1.97 2.03 .55-4.59
Testis 1 .44 2.28 .03-1266
Bladder 1 .75 1.33 .02-7.40
5 4.76 1.05 .34?2.45
Cardiovascular 54 76.65 .70 .53-.92
CHD 43 57.74 .74 .54?1.00
Cerebrovasouiar 4 8.53 .47 .13-1 .20
All Gastrointestinal 8 8.27 .97 .42-1.91
All respiratory 7, 7.770 .91 .36-1.87
Diabetes 3 2.55 1.18 24-344
Injuries 31 31.72 .96 .66-1.39
Suicide 10 6.99 1.43 .68-2.63

 

Abbreviations used are: Obs, observed; Exp, expected; Ci. con?dence interval:
CHD, coronary and atherosclerotic heart disease.

172

12364

 

 

TABLE 4.2.18 NUMBERS OF DEATHS AND ST ANDARDIZED MORTALITY
RATIOS (SMRS). BASED ON MALE RATES. AMONG
1449 MALE EMPLOYEES NEVER EMPLOYED IN THE CHEMICAL DIVISION,

 

 

 

1 947-1 989.

Time o?'aeath Obs Exp 
All causes 200 291.25 .69 .59-.79
Cancer 63 67.56 .93 .72-1.19
Gastrointestinal 15 16.46 .91 .51 ?1.50
Colon 5 5.79 .89 .28-2.01
Pancreas 4 3.37 1.19 .32-3.04
Respiratory 19 25.58 .74 .45-1.16
Lung 18 24.44 .74 .44-1.16
Prostate 2 3.45 .58 .07-2.09
Testis 0 .43 .00 .00-8.45
Bladder 2 1.45 1.38 .16-4.99
8 6.89 1.16 .50-229
Cardiovascular 91 129.77 .70 .56-.86
CHD 67 93.84 .71 .55-.91
Cerebrovascular 6 12.93 .46 .17-1.01
All Gastrointestinal 4 14.56 .27 .07-.70
All respiratory 6 16.77 .36 .13-.78
Diabetes 5 4.05 1.24 .40-2.88
Injuries 23 38.28 .60 .38-.98
Suicide 2 9.26 .60 .02-.78

 

Abbreviations used are: Obs. observed; Eitp, expected; CI. con?dence interval;

CHD, coronary and heart disease.

173

12365

 

TABLE 4.2.19 NUMBERS OF DEATHS AND STANDARDIZED MORTALITY
RATIOS (SMRs) BY LATENCY, BASED ON MINNESOTA WHITE MALE

RATES. AMONG MALE EMPLOYEES NEVER EMPLOYED IN THE CHEMICAL

 

 

DIVISION, 1947-1989.

LATENCY 2 15 YEARS
'Cause of Beath Obs Exp 95% CI
All causes 161 216.10 .75 .63-.87
Cancer 56 50.70 1.10 .83-1.43
Gastrointestinal 15 14.37 1.05 .59-1.73
Colon 5 5.13 .98 .31 2.28
Pancreas 4 2.99 1.34 .36-3.43
Respiratory 17 16.73 1.02 .59-1.67
Luna 16 15.94 1.00 574.63
Prostate 2 3.86 .52 .06-1 .87
5 5.40 .93 .30-2.16
Cardiovascular 75 113.60 .66 .52-.83
All Gastrointestinal 4 9.80 .41 .11-1 .05
All respiratory 4 12.14 .33 .09-.84
Diabetes 5 2.82 1.77 .57-4.14
injuries 7 1 1.17 .63 .25-1 .29

 

Abbreviations used are: Obs, observed; Exp, expected; CI, con?dence interval;
CHD. coronary and atherosclerotic heart disease; CD. Chemical Division.

174

 

 

12366

 

TABLE 4.2.20 NUMBERS OF DEATHS AND STANDARDIZED MORTALITY

RATIOS (SMRs) BY LATENCY. BASED ON MINNESOTA WHITE MALE

RATES, AMONG MALE EMPLOYEES EVER EMPLOYED IN THE CHEMICAL

DIVISION. 1947-1 989.

 

 

LATENCY 2 15 YEARS

Cause of ?eath Obs SMFI 955/70
All causes 105 128.4 .82 .67-.99
Cancer 34 29.95 1.14 .79-1.59
Gastrointestinal 9 8.30 1.08 .49-2.06
Colon 7 3.00 1.33 .36-3.42
Pancreas 4 1.75 2. .61-5.85
Respiratory 10 9.98 1.00 .48-1.94
Lung 9 9.50 .95 .43-1.80
Prostate 3 1.87 1.61 .32-4.70
4 3.28 1.72 .33-3.12
Cardiovascular 44 64.67 .68 .49-.91
All Gastrointestinal 4 6.37 .63 .17-1.61
All respiratory 5 6.49 .77 .25-1 .80
Diabetes 2 1.72 1.17 .43421
Injuries 6 8.54 .70 .26-1 .53

 

Abbreviations. used are: Obs. observed; Exp. expected; CI. con?dence interval;

CHD, coronary and atherosclerotio heart disease; CD. Chemical Division.

175

12367

 

TABLE 4.221 NUMBERS DEATHS ANO STANDARDIZED MORTALITY
RATIOS (SMRS) av DURATION OF EMPLOYMENT, BASED ON MINNESOTA I

WHITE MALE RATES. AMONG MALE EMPLOYEES EVER EMPLOYED IN THE 
CHEMICAL DIVISION. 1947-1999. 

 

 

DURATION 2 10YEARS
?case of Beam Obs Exp SW 
All causes 90 108.7 .83 .67-1.02
Cancer 27 24.4 1.08 171-1 .58 
Gastrointestinal 6 6.92 .87 .22-1 .89
Colon 3 2.47 1.22 243.55
Pancreas 2 1.46 1.37 .75-4.86
Respiratory 8 8.16 .98 .42-1.93
Lung 7 7.78 .90 .36-1.86
Prostate 3 1.55 1.94 .39-5.66
4 2.84 1.41 .38-3.61
Cardiovascular 38 54.60 .70 50-.97
All respiratory 3 5.42 .55 .11-1.62
Diabetes 3 1.51 1.99 .40-5.80
Injuries 7 8.11 .86 .35-1.78

 

Abbreviations used are: Obs. observed; Exp. expected?l. confidence interval;
CHD, coronary and atherosclerotic heart disease; CD.-Chemical Division.

 

176

12368

 

 

 

 

 

TABLE 4.2.22 NUMBERS OF DEATHS AND STANDARDIZED MORTALITY
RATIOS (SMRS) BY DURATION OF EMPLOYMENT. BASED ON MINNESOTA
WHITE MALE RATES, AMONG MALE EMPLOYEES EVER EMPLOYED IN THE

CHEMICAL DIVISION. 1947-1989.

 

 

      

DURATION 2 20YEARS

?Cause of Death Obs Ex SMR Ev. Cl

All causes 45 66.29 .68 .50-.91
Cancer 16 16.21 .99 .56-120
Gastrointestinal 3 4.53 .66 .13?1.94
Colon 3 1 61 1.84 .37-5.38

Pancreas 0 96 .00 0-384
Respiratory 5 5 57 .90 29-209
Lung 4 5 31 .75 .20-1.93
Prostate 2 1 10 1.82 .20-6.58
3 1.67 1.79 .36-524
Cardiovascular 18 34.48 .52 .31 -.83
All respiratory 2 3 52 .57 .06-2.52
Diabetes 2 .84 2.37 .27-8.56
Injuries 2 .27 .61 .07-221

 

Abbreviations used are: Obs, omerved?xp. expecterfCT, con?dence interval;

CHO. coronary and atherosderotic heart disease; CD, Chemical Division.

177

12369

 

TABLE 4.2.23 NUMBERS OF DEATHS AND STANDARDIZED MORTALITY
RATIOS (SMFIS) BY DURATION OF EMPLOYMENT . BASED ON MINNESOTA
WHITE MALE RATES. AMONG MALE EMPLOYEES NEVER EMPLOYED IN
THE CHEMICAL DIVISION. 1 941-1989.

 

 

 

DURATION 2 10YEARS 
cause of Wreath Obs Exp 95% cu__

All causes 1 13 148.60 .76 .63-.91 
Cancer 40 34.43 1.16 .83-1.58
Gastrointestinal 14 9.82 1.43 .78-2.39
Colon 4 3.45 1.16 .31-2.97
Pancreas 4 2.04 1.96 .53-5.01
Respiratory 14 11.22 1.25 .68-2.09
Lung 13 10.69 1.22 .65-2.08
Prostate . 1 2.65 .38 .01 -2.10
1 3.47 .27 .01-1.49

Cardiovascular 54 78.31 .69 - .52-.90
All respiratory 4 8.35 .48 .13-127
Diabetes 5 1.98 2.52 .81 -3.87
Injuries 4 7.98 .50 0.14-1.29

 

Abbreviations used are: Obs, observed; Eip. expecteECl, con?dence interval;
CHD. coronary and atherosclerotic heart disease; CD. Chemical Division.

178

12370

 

TABLE 4.2.24 NUMBERS OF DEATHS AND STANDARDIZED MORTALITY
RATIOS (SMRS) BY DURATION OF EMPLOYMENT. BASED ON MINNESOTA
WHITE MALE RATES, AMONG MALE EMPLOYEES NEVER EMPLOYED IN
THE CHEMICAL DIVISION. 1947-1989.

 

 

 

DURATION 2 20YEARS 

CauseoTDeath Obs Ex- SMFI 95% CI

All causes 59 86.1 .69 .52-.88
Cancer 19 21.09 .90 .54-1.41
Gastrointestinal 7 5.99 1.17 .47-2.41
Colon 2 2.15 .93 .103.32
Pancreas 1 1.25 .80 .01-4.45
Respiratory 6 7.12 .84 .31 -1 .83
Lung 6 6.79 .88 .32-1.92

Prostate 0 1.73 .00 .0-2.12
1 2.15 .46 .01 -2.58

Cardiovascular 30 46.14 .65 .44-.93
All respiratory 3 5.43 .59 .12-1.72?
Diabetes 3 1.10 2.74 .55-8.00
Injuries 0 3.34 .00 .00-1.14

   

 

Abbreviations used areT?bs, observed?xp, expected; 51, con?dence interval;

CHD. coronary and atherosclerotic heart disease; CD. Chemical Division.

179



 

TABLE 4.2.25 AGE ADJUSTED ST ANDARDIZED RATE RATIOS (SRRs) FOR
ALL CAUSE, CANCER, AND CARDIOVASCULAR MORTALITY BY DURATION
OF EMPLOYMENT. AMONG MALE EMPLOYEES. 1947-1989.

 

 

Cause of death 95%Cl

all causes .81 .63-1 .03
all cancers 1.04 .67-1.61

all cardiovascular .91 .62-1 .34

 

Abbreviations used are: SRR, amndardized rate ratio CI. confidence interval.
less than 10 years of employment as referent category

180

12372

TABLE 4.2.26 AGE ADJUSTED ST ANDARDIZED RATE RATIOS (SRRS) FOR

ALL CAUSE, CANCER. LUNG CANCER. GI CANCER. AND

CARDIOVASCULAR MORTALITY BY EMPLOYED IN THE

CHEMICAL DIVISION. AMONG MALE EMPLOYEES. 19474 989.

 

 

 

Cause of death 
all causes 1.18

all cancers 1.10

lung cancer 1.09

GI cancer 1.16

all cardiovascular 1.05

95%Cl

(95.1.47)
(74.1.65)
(67.2.31)
(50.2.89)
(76.1.48)

 

Abbreviations used are: standardized rate ratio CI. con?dence interval; GI.

gastrointestinal.

Never employed in the Chemical Division as referent category

181

12373

 

TABLE 4.2.27 AGE STRATIFIED. YEARS OF FOLLOW-UP ADJUSTED RATE

RATIOS (RRMH) FOR ALL CAUSE, CANCER, AND CARDIOVASCULAR
MORTALITY BY EMPLOYED IN THE CHEMICAL DIVISION.

AMONG MALE EMPLOYEES. 1947-1989.

 

 

Age at employment R?w? 95%0!
All causes
15?19 years 1.22 (.62. 2.40)
20-29 years .95 (.68. 1.32)
30-39 years .95 (.61 1.50)
40-65 years 1.02 1.72-1.44)
All mocers
15-19 years .95 (.21 4.34)
20-29 years .72 (.38, 1.35)
30-39 years 1.10 (52.1.90)
40-65 years .66 (.27, 1.60)
All oardiovaswlar
15-19 years 1.40 (.3 . 5.03)
20-29 years .85 (.44. 1.67)
30-39 years .78 (.44. 1 .29)
'40-65 years 1.11 (.73. 1.82)

 

Abbreviations used are: RRMH, Mantel-Haenszel age a?us?d rate ratio :0l.

con?dence interval.

Adjusted for years at follow-up and stratified by four age categories.
Never employed in the Chemical Division as referent category

182

 

12374

TABLE 4.2.28 AGE STRATIFIED. YEARS OF FOLLOW-UP ADJUSTED RATE
RATIOS (RRMH) FOR ALL CAUSE. CANCER, AND CARDIOVASCULAR
MORTALITY BY DURATION OF EMPLOYMENT IN THE CHEMICAL DIVISION,
AMONG MALE EMPLOYEES. 17947-1939.

 

 

at em 0 ment 95%Cl
All causes
15-19 years 1 .30 (.58, 3.28)
20-29 years 1.16 (.81. 1.65)
30-39 years 2.16 (1 .52, 2.70)
40-65 years 1.69 (1.07. 2.60)
All cancers
15-19years 2.17 (40.11.61)
20-29'ye'ar's .84 (44.1.51)
30-39 years 1.75 (.95. 3.21)
40-65 years 2.67 (.995.7.14)
All cardiovascular
15-19 years .88 (.25. 3.33)
20-29 years 1.38 (.73. 2.60)
30-39 years 3.53 (1.68. 6.21)
40-65 years 1.50 - (.81, 2.79)

 

Abbreviations used are: RRMH, Mantel-Haenszel age adjusted rate ratio 
con?dence interval.
Adjusted for years of follow-up and stratified by four age categories.

less than 10 years employment as referent category

183

12375

 

TABLE 4.2.29 PROPORTIONN. HAZARD REGRESSION MODEL OF
FACTORS PREDICTING THE ALL CAUSE MORTALITY AMONG 2788 MALE

 

 

 

WORKERS.

1 Variable 0 SEE) p-value 
Year 01 ?rst employment -.55 .009 .0001 .946
Age at first em ployment? .079 .006 .0001 1.082
Duration of employment' -.34 .001 .0001 .907
Months in chemical .001 .001 .24 1.001

division

 

 

Abbrevi?ons used are: E, regression parameter; SE10), standard error of the
slope parameter; RFI. relative risk.
relative risk for one unit change in independent variable

TABLE 4.2.30 PROPORTIONAL HAZARD REGRESSION MODEL OF
FACTORS PREDICTING THE CARDIOVASCULAR MORTALITY AMONG 2788

 

     

MALE WORKERS.
Year of ?rst employment -.075 .016 .001 .928
Age at ?rst employment? .119 .009 .0001 1.126
Duration of employment? .230 .294 .45 .852
33g: in chemical .0002 .001 .85 1.00

 

Abbrevia?ons used are: E. regression parameter: standard error 01 the
slope parameter; RR. relative risk.

relative risk for one unit change in independent variable

years

184

12376

TABLE 4.2.31 PROPORTIONAL HAZARD REGRESSION MODEL OF
FACTORS PREDICTING THE CANCER MORTALITY AMONG 2788 MALE

 

 

 

 

WORKERS.
Variable 5 SEE) p-value 33*
Year of ?rst employment -.031 .019 .11 .969
Age at ?rst employment? .078 .011 .0001 1.081
Duration of employment? -.028 .009 .002 .972
Months in chemical .002 .001 .20 1.002

division

 

Abbreviations used are: 3. regression parameter; 85(3). standard error of the
slope parameter; RR, relative risk.

relative risk for one unit change in independent variable

years

TABLE 4.2.32 PROPORTIONAL HAZARD REGRESSION MODEL OF
FACTORS PREDICTING THE LUNG CANCER MORTALITY AMONG 2788

 

 

 

MALE WORKERS.
Variable SEE) p-value an!
Year of first employment -.019 .042 .65 .981
Age at first employment' .070 .021 .001 1.072
Duration of employment? -.062 .133 .64 .940
Months in chemical -.026 .016 .11 .975

division

 

 

 

Abbreviations used areFE, regression parameter; SW3). standard error of the
slope parameter; HR, relative risk.

relative risk for one unit change in independent variable

years

185



 i

TABLE 4.2.33 PROPORTIONAL HAZARD REGRESSION MODEL OF
FACTORS PREDICTING THE GI CANCER MORTALITY AMONG 2788 MALE

 

 

 

WORKERS. .
Variable i see) p-value ear
Year of ?rst employment .015 .038 .71 1.015
Age at ?rst employment? .130 .021 .001 1.139
Duration of employment? .005 .020 .82 1.005
Months In chemical .001 .002 .58 1.001

division

 

Abbreviations used are: GI. Gastrointes?nal?, regression parameter; SEE).
standard error of the slope parameter; RR. relative risk.

relative risk for one unit change in independent variable

years

TABLE 4.2.34 PROPORTIONAL HAZARD REGRESSION MODEL OF
FACTORS PREDICTING THE PROSTATE CANCER MORTALITY AMONG 2788
MALE WORKERS.

 

 

    
    

 

 

 

Year of ?rst employment .010 .081 .90 1.011
Age at first employment? .082 .045 .06 1.085
Duration of employment? -.oro .052 .18 .932
Months in chemical .010 .005 .03 1.010
division
Abbreviations used are: 5, regression parameter; SEE-B). standard error oijt'he
slope parameter; RR, relative risk.
relative risk for one unit change in independent variable
years

1 86

12378



 

TABLE 4.2.35 PROPORTIONAL HAZARD REGRESSION MODEL OF
FACTORS PREDICTING THE PANCREATIC CANCER MORTALITY AMONG

 

 

 

2788 MALE WORKERS.
Variable i SEE) p-vaiue 1 
Year of first employment .046 .066 .48 1.047
Age at first. em ployment' .136 .034 .0001 1.146
Duration of employment' -.012 .035 .73 .988
Months in chemical -.002 .006 .73 .998

division

 

 

Abbreviations used are: E, regression parameter; standard error of the
slope parameter; RR. relmive risk.

relative risk for one unit change In independent variable

i even

TABLE 4.2.36 PROPORTIONAL HAZARD REGRESSION MODEL OF
FACTORS PREDICTING MELLITUS MORTALITY AMONG

 

 

 

2788 MALE WORKERS.
Variable 5 STETB) - p-value Fi?! 
Year of first employment -.405 .221 .06 .667
Age at ?rst employment? .092 .044 .04 1.096
Duration of employment' .009 .030 .75 1.009
Months in chemical -.001 .004 .76 .999

division

 

 

Abbreviations used are: 6. regression parameter; standard error of the
slope parameter; RR, relative risk.

relative risk for one unit change in independent variable

a oyears

187

12379



TABLE 4.2.37 PROPORTIONAL HAZARD REGRESSION MODEL OF
FACTORS PREDICTING THE ALL CAUSE MORTALITY AMONG 749 FEMALE

 

 

WORKERS.

Variable 8 p-vaiue 
Year of first employment -.02 .03 .41 .977
Age at first employment? .08 .02 .0001 1.03
Duration of employment?
2-10 years 1.31 .54 .01 3.72
>10 years .05 .57 .14 2.33
Months in chemical ~.003 .004 .48 .997

division

 

Abbreviations used aref?, regression parameter; . standard error of the

slope parameter; RR. relative risk.
relative risk for one unit change In independent variable

years

TABLE 4.2.38 PROPORTIONAL HAZARD REGRESSION MODEL OF
FACTORS PREDICTING THE CARDIOVASCULAR MORTALITY AMONG 749

 

 

 

 

FEMALE WORKERS.
Variable i8 p-value 
Year of first employment -.034 .048 .48 .966
Age at ?rst employment? .119 .024 .0001 1.126
Duration of employment" -.011 .025 .67 .986
mg: in chemical -.015 .017 .37 .985

 

 

 

Abbreviations used are: E, regression parameter; standard error of the

slope parameter; RR, relative risk.
relative risk for one unit change in independent variable

years

188

12380

 

TABLE 4.2.39 PROPORTIONAL HAZARD REGRESSION MODEL OF
FACTORS PREDICTING THE AMONG 749 FEMALE

 

 

       

Year of ?rst employment -.043 .053 .42 .958
Age at first employment' .085 .025 .001 1.089
Duration of employment' -.021 .025 .65 .980
Months in chemical .001 .005 .87 1.001
division

 

 

Thbreviations used are: E. regression parameter; Em. standard error of the
slope parameter; RR, relative risk.
relative risk for one unit change in independent variable
years

189

12381

 

FREE TESTOSTERONE
(ngidl)

 

FIGURE 1. Free testosterone and total serum ?uorine
1990 3M Chemome study

 

 

AGE-30 Bill-35
AGE-50 ?-25
AGE-50 Nil-TOTAL FLUORINE (ppm)
1 90

1
12382

 

 

BOUND TESTOSTERONE


Figure 2. Bound testosterone and total serum fluorine
1990 am Chemollte study

100

 

 

 

AGE-30 sums

 

AGE-30 

AGE-50 Bill-25



 

TOTAL FLUORINE (ppm)

191

12383

 

ESTRADIOL 

 

Figure 3. Estradlol and total serum ?uorine
1990 am Chemllte study

 

 

. so -
so -.
4o -

AGE-30 sun-25
3? - AGE-TOTAL FLUORINE (ppm). .

12384

 

 

(9me

Figure 4. hormone and total somm ?uorine

1990 3M Chemollte study

 

 

 

_l I 

1 0 20 30

TOTAL FLUORINE (ppm)

193

12385

 

(pg/ml)

Figum 5. Follicle stimulating hormone and total serum ?uorine

 

1990 am Chemolito study

 



TOTAL FLUORINE (ppm - 



194 

12386

 

PRQLACTIN 

50"

 

Figure 6. Prolactln and total serum ?uorine
1990 am Chemllte study

Moderate drinkers

Light dm?s
Nonreapondants

 

 

 

 

TOTAL FLUORINE (ppm)

195

12387

?Wm

 

TSH 

Figure 7. Thyroid stimulating hormone and total serum ?uorine
1990 3M Chemoiite study

FLUOBINE (ppm)

196

i
12388

 

 

BOUND 
TESTOSTERONE RATIO

Figure 8. Bound to tree testosterone ratio and total serum ?uorine

45.4

40.

1990 am Chemollte study

30?

TOTAL FLUORINE (ppm)

197

12389

 

. 0 on?

El 'l'EiiISll
mm

This was a cross-sectional study of the relationship between selected physiologic
parameters and PFOA exposure which was assessed using total semm ?uorine.
Participants were recruited from workers employed during November, 1990 in the
Chemical Division of the 3M Chemolite Plant in Cottage Grove. Minnesota. All
current workers who had worked in high exposure jobs at any time in the ?ve
previous years were invited to participde. A sample of workers employed in low
exposure jobs was frequency matched to the age distribution of workers in high
exposrue jobs.

Participants completed a corporate medical history questionnaire and had vital
parameters measured by an occupational health nurse. Blood was drawn for
assays of total serum ?uorine. seven hormones involved in the hypothalamic-
pituitary~gonadal axis. serum lipids, iipoproteins. hepatic function parameters.
and hematology indices. Blood was drawn in the morning after workers were
assigned to the day shift for at least three days.

In 93% of participants serum ?uorine levels were at least 10 times the
background levels in the general population and in 3M workers not employed at
Chemothe. Many workers who lacked PFOA exposure by job history had
elevated PFOA levels. The sources of the unexpected PFOA exposure are
unknown.

immense

The findings trom this study are consistent with the hypothesis that
periluorooctancic acid (PFOA) attests the human hypothalamtc-pitultary-gonadal
axis. This study showed that relatively low levels of serum PFOA (20pm
depressed free testosterone and elevated estradiol but did no effect LH or FSH -
levels. The association between free testosterone and PFOA was different in

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4., - .4

older men than in younger men. In older men. free testosterone (FT) was
depressed below 10 at semm ?uoride levels below one part per million
(estimated PFOA levels below 1 M). In younger men. FT decreased toward 1O
at serum fluoride levels above 15 (estimated PFOA levels below 15
uM). Increasing age may increase men's susceptibility to the testosterone
lowering effects of PFOA. The associations between PFOA and the hormone
levels may re?ect a true causal relationship. or may be a result of chance, bias.
or uncontrolled confounding. There are no human studies of PFOA associated
reproductive toxicity available for comparison. Studies of the effects of PFOA in
rodents have demonstrated a similar decrease in testosterone. increase in
estradiol. and little change in LH 

The association between PFOA and free testosterone may have been mediated
by elevated estradiol and prolactin. Elevated estradiol decreases testosterone
and other steroid hormone in Leydig cells. LH response to low
testosterone is attenuated by estradiol through negative feedback mechanisms at
the pituitary and hypothalamic levels Elevated prolactin sensitizes the
hypothalamus and pituitary to estrogens feedback. The combined effect of
elevated estradiol and prolactin could have reduced the secretion of LH and the
subsequent Leydig cell response. Estradiol has direct effects on Leydig cell
testosterone in rats, PFOA decreased androstenedione and
testosterone, but not 17 alpha-hydroxyprogesterone The metabolism of 17
alpha-hydrexyprogesterone to androstenedione was inhibited at the step of the
0-17.20 iyase. The activity of the rate limiting 0-17, 20 lyase has been reported
to be under estradiol regulation in rat Leydig cells Thus, in PFOA treated
rats, elevated levels of estradiol may inhibit the 6-17.20 lyase and thereby
reduce testosterone The increase in the estradiol-testosterone ratio
observed' in workers rs compatible with this mechanism for decreased free
testosterone.

The primary source of estradiol in males is the P450 (P450 19) mediated
aromatization of testosterone Additional estradiol is secreted directly
from Leydig cells. The observed increase in estradiol may be the result of
increased production from one of these two. sources or may be the result of
inhibition of P450 mediated estradiol metabolism Perfluorooctanoic acid, a

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prototype peroxisome proliferator, may regulate steroidogenesis by binding to a
member of a new family of cytosolic receptors (PPAR) belonging to the nuclear
hormone receptor superiamily and transactivating the transcription of genes
involved in steroid "942?.

PFOA was positively associated with the TBITF and EITF ratios. PFOA binding
to sex hormone bindinf globulin (SHBG) may have produced changes in the
bound to free testosterone ratio. However, this would result in a change in the
that is in the opposite direction to the observed association between
PFOA and TBITF. The associations of PFOA with these ratios are consistent
with a mechanism that involves decreased production of testosterone and
increased production of estradiol.

The HPG axis of older men appeared to be more susceptible to PFOA compared
to that of younger man. No animal data has=been reported concerning age'
related sensitivity to the effects of PFOA. However, the onset of Leydig cell
tumors has been reported to occur late in two year rat feeding studies ?22. This
finding may represent increased susceptibility tor hormonal alterations in aged
rats. Further animal research is needed to de?ne any age related susceptibility
factors.

Prolactin levels were positively associated with total serum fluoride in participants
who reported moderate drinking (1-3 drinks/day). Since the function of prolactin
in men is uncertain. the clinical signi?cance of such an association is unclear.
Alcohol ingestion is a stimulus for prolactin secretion. The mechanism at this
effect appears to be mediated by alterations in calcium mediated signal
transduction pathways ?23. This suggests that the elevation at prelactin
associated with PFOA and alcohol may bemediated by alterations in caldum
mediated events such as transmembrane signal transduction pathways.

Thyroid stimulating hormone was positively associated with total semm ?uoride.
Animal studies have shown that pertluorodecanoic acid depressed peripheral
thyroid hormone levels without producing a hypothyroid response 75' 7" In
the-presentstudy. peripheral thyroid horrnoneileveis were not assayed.
Therefore. it is not possible to assess whether the observed association between

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. an an" 

PFOA and TSH could be a direct hypothalamic effect, a pituitary regulatory
effect. or an effect mec?ated by changes in peripheral thyroid hormone levels.

in summary, this is the first report of hormonal changes associated with PFOA in
humans. The present ?ndings in humans are consistent with those previously
reported in animal studies 19.. The consistent ?ndings include low free
testosterone. increased estradiol. and unchanged Rodent and human
reproductive endocrine systems differ greatly, yet the suggested effects of PFOA
are similar. In light of the observed similarities in effect, it is tempting to
speculate that PFOA may effect the humans and rodents reproductive endocrine
system through the same mechanism. A hypothesis that PFOA alters a calcium
mediated cellular signd transduction pathway. such as the or lnosltol
triphosphate mediated second messenger response, may provide a unified
mechanism for the multiple loci of putative effects.

No adverse health effects have been observed in exposed a. The present study
did not examine adverse health effects, although several adverse outcomes
associated with hormonal alterations are possible. The etiology of a number of
cancers including adenocarcinomas of the prostate, endometrium, colon. rectum,
pancreas and breast, have been linked to changes in endogenous hormones'm.
Cancers in this etiologic category include.

Perfluorooctanoic acid is not a genotoxic carcinogen in standard assays 9.
However, PFOA is a nongenotoxic rodent carcinogen. In rats exposured to 
PFOA over a two year period, there was associated increase in Leydlg cell
tumors ?25. Leydig cell tumbrs have been observed in association with other
peroxisome proliferators in rats m_ it has been hypothesized that chronically
elevated LH produced testicular neoplasms 19-122. However, in PFOA treated
rats, LH was not elevated. This may be due to estrogens feedback inhibition as
discussed previously. or due to insuf?cient experimental induction time 
Alternatively, another mechanism may have been operative ln producing Leydlg
cell tumors. Exogenous estradiol produces Leydlg cell tumors in mice High
estradiol levels are associated with Leydig cell tumors in both rats and humans
?27' ?23. The tissue smrounding the Leydlg cell adenomas also produces
increased estrogens 127. High estradiol may be a stimulus for Leydg cell

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proliferation and tumor formation. This hypothesis is supported by the
observation that estradiol stimulates secretion in Leydig cells 
binds to EGF receptors expressed on Leydig cells ?29 and stimulates cell
proliferation. The honnonm changes associated with PFOA may be a
mechaniSm for nongenotoxic carcinogenesis. The role of PFOA in human
nongenotoxic carcinogenesis needs to be clarified.

Adequate androgen levels are necessary for maintenance of potency.
spermatcgenesls, libido and male reproductive organs. Lowtestosterone and
high estrogens may decrease libido. and fertility in males 13". Decreased male
fertility may be one potential adverse outcome of PFOA. The reproductive
toxicity of PFOA has not been extensively studied. No studies have been
conducted in hemans. PFOA was not teratogenic in rats 9' 131. ?32 . No adveme
effects on fertility were noted for female rats in a teratogenesis study 9. Male rats
were not studied. No other reprodudive studies in animals have been reported.
Studies of human reproductive function are needed since human reproductive
processes are thought to be more sensitive to xenobiotic insults compared to
other animal species 

Wm

Cholesterol, triglycerides. and LDL were not signi?cantly associated with 
The lack of association of PFOA with cholesterol or triglycerides is consistent
with observations in experimental animal models. No animd studies of PFOA's
effect on LDL are available The are no studies in humans
concerning the relationship of PFOA with LDL. cholesterol, or triglycerides.

. In light drinkers. PFOA had little effect on HDL levels. in moderate drinkers.

increasing PFOA reduced HDL The putative effects of PFOA and alcohol may
be mediated by alteration of a common HDL regulatory process. The findings
are limited by the small number of exposed workers. the limited range of total
fluoride values, and the limitations of the study design. The conclusion and
suggested mechanism must be considered preliminary.

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The mechanism by which PFOA modi?es the alcohol-HDL relationship could be
mediated by alterations in fatty acid metabolism or fatty acid binding. Alcohol
intake induces speci?c P450 metabolic enzymes including 2E1 and alters lipid
metabolism 134. PFOA induces a speci?c P450 A1 family of metabolic enzymes
and alters lipid metabolism in rodents. The joint effect of alcohol and PFOA on
P450 mediated lipid metabolism could alter HDL dynamics. The primary
structure of PFOA suggests that PFOA could affect the ligand binding of fatty
acid in hepatocytes and HDLs. The competition for NEFA binding sites could
reduce the e?ect of alcohol on HDL levels. Studies of the joint eltect of PFOA
and alcohol on HDL may clarify the regulatory mechanisms for HDL.

The decrease in HDL associated with increasing PFOA levels may be clinically
significant. In meta-analysis oi 12 prospective studies oi the relationship
between HDL levels and coronary heart disease (CHD). Gordon estimated that
the change in CHD risk associated with a one change in HDL level is
approximately the same as the change in risk associated with a 2-4 change
in LDL level ?35. The predicted drOp in HDL tor a moderate drinking participant
with a total ?uoride of 20 is .30 A change of this order of magnitude
may have a measurable impact on the occurrence of cardiovascular disease. In
the retrospective mortality study. there was no increase in mortality from
cardiovascular disease. However. there are a limited number of workers with
total serum fluorine levels of 20 of more. Any Increase in risk for
cardiovascular diseases among a small group of highly exposed workers may not
be readily apparentin a study of all Chemolite or CD employees. Further.
research is needed to confirm and clarify the association between PFOA and
HDL level. Future studies could test the hypothesis that PFOA and alcohol jointly
alter NEFA metabolism resulting in a decrease in HDL and an increase in
cardiovascular morbidity and mortality risks for exposed workers who drink
alcohol.

Changes in SGOT (AST) and SGPT (ALT) appear to be associated with total
serum ?uoride through an interaction with adiposity. ln obese participants, both
SGOT and SGPT increased with increasing PFOA. However, there did not

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.c

appear to be an independent effect of PFOA on SGOT after adjusting for SGPT.
The findings are limited by the small number of exposed workers. the limited
range of total ?uoride values. and the previously discussed limitations of the
study design. The conclusion and suggested mechanisms must be considered

preliminary.

Compared to SGOT. SGPT is a relatively spedtic marker for hepatocyte
disruption ?35. The lack of association of SGOT with PFOA after adjusting for
SGPT suggests that the liver is the primary source for the small PFOA
associated changes in transaminases. Since SGPT is a enzyme associated with
the ER membrane. the increase in SGPT may have been the result of PFOA
associated ER proliferation. It may indicate a disruption in the integrity of
hepatocyte membranes which allows increased release of cytosolic hepatic
enzymes. The tissue specific eiiect suggested for hepatocyte membranes could
be due to a higher hepatic concentration of PFOA. .-

Liver injury is generally considered to be a multifactorial process. There is
evidence that interactions between endogenous and exogenous factors play a
role in hepatotoxidty observed in workers ?37. The modi?cation of the capacity-
SGPT association by PFOA suggests that the mechanisms of transaminase
elevation may be linked. Obesity has been associated with elevation of
transaminases as well as clinically important hepatitis 138. ?39. The observation
that some obese individuals evidence little adiposity effect while other obese
individuals develop hepatic ?brosis has not been explained. It has been
hypothesized that metabolic polymorphisms or other hepatotoxin exposure may
play a role 14?. Animal studies and limited human data suggest that xenobiotics.
such as certain solvents and alcohol, may potentiate the effects of other
hepatotoxins ?41-?42. Following=this model, PFOA may directly or indirectly
potentiate the hepatotoxic effect of obesity.

A mitochondrial site of PFOA action may?occur. The mitochondria plays an
essential role in fat metabolism. Disruption of-rnitochondriai function can produce
impairment of mitochondrial oxidation of long chain and medium chain fatty acids.
Studies of fatty acid metabolism in PFOA exposed humans have not been carried
out. Valproic acid, an eight carbon branched chain fatty acid (2 propyi-pentanoic

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an.

acid) that impairs mitochondrial function and fatty acid metabolism, is an example
of a hepatotoxic xenobiotic of similar carbon structure to PFOA 143. Commercial
grade PFOA contains isomers with carbon backbones identical to valproic acids
structure 39. The valprcate-iike isomers of PFOA could produce toxicity similar
to that of valproate. The modification of the association between PFOA and the
transaminases by adiposity could be mediated by disturbances of mitochondrial
fatty acid metabolism in humans.

GGT increased as alcohol use increased. The increase in GGT was smaller as
PFOA increased. This association was independent of changes in SGOT,
SGPT, and AKPH. Perfluorocctanoic acid may inhibit the hepatotoxic effects of
alcohol. The (SGT-alcohol dose response relationship is thought to be smndary
to the induction and increased release of GGT. increased serum GGT levels
indicate proliferation of the endoplasmic reticulum and induction of cytochrome
P450 system, leakage from hepatocytes. or injury to other tissues 
Periluorooctanoic acid may decrease serum GGT by altering cell membrane
permeability. by reducing the alcohol mediated induction of GGT. or by changing
alcohol oxidation pathways and reducing the pmduction ct toxic intermediates
such as acetaldehyde.

Periluorooctanoic acid was negatively associated with AKPH in non-smokers. in
workers whosmoke greater than five cigarettes per day, PFOA was positively
associated with AKPH. The association of AKPH with PFOA was independent of
GGT. transaminases, and hormones. Smoking has been reported to elevate
AKPH Themechanism of this effect is thought to be the result of AKPH
induction by compounds in cigarette smoke. The joint effect of smoking and
PFOA could increase the induction of AKPH.

in summary, the associations between PFOA and hepatic enzymes are weak and
are not clinically significant. In the retrospective mortality study. there was no
increased in mortalltyassocaited with liver disease. Future studies of the effects
of PFOA may elucidate possible mechanisms of action of nongenotoxic hepatic
carcinogens. The hepmic enzyme results are illustrative of the problem of
extrapolating findings observed in rodent animal models to other species.
including humans in humans. PFOA does not cause the dramatic hepatic

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effects observed in rodents. Instead, the observed associations may result from
PFOA modi?cation of the hepatic effects of obesity. alcohol consumption, and
smoking. Each of these factors are independently associated with hepatotoxicity.
Further studies of the joint effects of PFOA and BMI, alcohol, and smoking on
hepatic enzymes are needed.



PFOA was weakly. but signi?cantly associated with hemoglobin levels. MCV. and
MCH. The associations between PFOA and indices appeared to be
mediated through interactions with smoking. and perhaps alcohol consumption.
The ?ndings in animal studies 9- 15? are consistent with a decrease in red cell
volume and alarger decrease in red cell number. Together. these changes
produce an increase in cellular hemoglobin concentration. The estimated
changes in indices are not of clinical significance over the range of
total serum ?uoride. However. these ?ndings suggest that further sttides oi the
effect of PFOA on red cell regulation and function are needed. The ?ndings are
limited by the small number of exposed workers, the limited range of total ?uoride
values. and the previously discussed limitations of the study design.

Pharmacological doses of androgens increase number and mass but
produce little change in MCV or MCH ?51 ?52 .The mechanisms by which
androgens increase hemoglobin appear to mediated by modulating the
responsiveness of mum-potential stem cells and by stimulating
prodUCtion' ?53'155. in physiologic closes, the effect of
testosterone on indices is controversial. Palacios et al. and
Cunningham et al. reperted that testosterone is associated with a small increase
in hemoglobin. but no change in MCV or MCH ?53- ?57. Mauss et al. reported no
change in red cell lndices for physiologic levels ot'testo?erone ?53. In the
present study. the testosterone level was not strongly or significantly related to
the red cell indices. Estradiol was weakly association with HGB but not MCV or
MCH. The effect of physiologic estradiol levels on the male hematological
system is poorly understood. Tell et al. reported that the effect of smoking on red
cell indices was different in male than in female adolescents 159. This suggests
that estrogen levels may play a role in the effect of xenoblotios on red cell

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i
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indlces. Taken together. the evidence suggests that the association between
PFOA and indlces was not mediated by the PFOA associated
changes in testosterone. but may have been mediated in part by changes in
esttadiol.

Thyroid hormone was associated with changes in H68 and MCV. A decreased
availability of (T4) to myxedma levels produces a mild 
anemia in humans. The increased cell volume is due to alterations in lipid
deposition in membranes that occurs during ineffective 
16?. TSH confounded the association between PFOA and MCV. Decrease in T4
could explain some of the increase in and TSH. However. PFOA appeamd
to have an independent and opposite effect on MCV. Therefore. the association
between PFOA and changes in red cell indices was probably not related to
changes in thyroid function.

The immune system effects associated with PFOA present a complex picture.
As expected, smoking had a strong effect on leukocyte counts. Smoking
modi?ed the association between cell count and PFOA for 
eosinophils. platelets and basophils. However, smoking did not modify the
estimated PFOA effect on WBC, PMN. band count, ormonocyte count. Alcohol
modi?ed the association between PFOA and cell count for WBC. PMN, and
count. Adiposity modi?ed the association between PFOA and
count, monocyte count, and platelet count. Taken together. this
preliminary data suggests that PFOA is associated with changes in peripheraly
leukocyte counts. The negative association with count is consistent
with the effects observed in primate studies. PFOA could mdulate
cell counts by altering the effects of smoking, alcohol consumption, and adipcsity
on peripheral leukocyte counts.

The magnitude of the WBC and PMN assodations were not clinically signi?cant
from an infectious disease perspective. Increased WBC is positively associated
with mortality from all causes. cardiovascular diseases, cancer and myocardial
infarction It is unclear lithe alteration in WBC is a consequence of. or the
cause of. ongoing pathological processes. Judgment as to the clinical relevance
of the PFOA associated changes in WBC must await funher study.

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Adiposity modi?ed the association between cell count and PFOA for monocytes.

Alcohol and cigarette consumption were independent determinants In the present i
study. Monocyte counts have been reported to be low in massively obese

individuals ?59. The biological basis for these effects are not clear. The

univariate and joint effects of adiposity and PFOA on monocyte count may a

fruitful area for future research.

In the present study. the complex relationships between count,
PFOA, alcohol use. cigarette use, and body mass may have been the result of
the differential effect on cell subsets. In order to clarify these assodations.
speci?c subsets need to be measured. The association of subsets
with disease endpoints have yet to be clarified. The interpretation of the
observed association requires further research.

Smoking was negatively associated with basophil count. As PFOA level
increased. the smoking effect was diminished. Taylor et al. reported an increase
in blood basophils In smokers compared to nonsmokers 17?. Walter et al. studied
smokers and nonsmokers and found that acute smoking causes degranuiation
and loss of basophiis. However. chronic smoking Is associated with an elevated
basophil count. 17?4?. No attempt was made to prohibit subjects from smoking
prior to the time of blood sampling. The negative association observed in this
study may re?ect recent smoking by participants prior to blood drawing. The
apparent reduction In the degranulating effect of smoking suggests that PFOA
may interact with the basophil degranuialtion process.

Exposure to PFOA may be associated with changes in immune function beyond
simple changes in cell number. The avid oxygen binding by PFCs may alter the
effectiveness of peroxidatic killing by PMNs. Cytokine signaling is Important in
immune function and could be altered by PFOA exposure ?75. The response to
antigen binding depends upon rearrangement of membrane proteins. Changes
in the membrane physical characteristics produced by the patent surfactant
action of PFOA could alter immune responses. More research is needed in the
area of PFOA immunotoxiclty. The findings of the present study need to be
confirmed. could be immunophenotyped using well established flow

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cytometry methods ?75- ?77. The standard immunotoxicoiogic assessment de?ned
by the National Toxicology Program 17? should be carried out for PFOA.

Smoking has been observed to increase platelet number. survival. adhesiveness,
activation. and aggregation when exposed to ADP Adhesiveness may
change as a result of the effects of smoking on nonesterified fatty acids (NEFA).
Smoking increases NEFA which may compete with PFOA for platelet membrane
binding sites. Such competition could alter the smoking associatedincrease in
platelet count. This hypothesized mechanism could be tested by in vitro 
modeling of platelet function in the presence of NEFA and PFOA. The
relationship between obesity and platelet count has not been well studied. am
has been reported to be negatively associated with platelet count ?35. The
mechanism for this effect is not clear. but may be related to changes in NEFA
associated with obesity. Thus, the effect modi?cation of the PFOA effect by
smoking and obesity may have resulted from a common effect on NEFA.
Changes in platelet count have been associated with risk for cadovascular
disease 133-187. Direct and indirect mechanisms have been hypothesized for the
observed increase in disease occurrence. Thus, PFOA associated changes in
platelet count may be a marker for increased cardiovascular disease risk.
Further study of potential effects of PFOA on platelet count and function are
needed. .

MW

Smoking and total serum ?uorine were weakly associated in participants. The
adjusted estimate for the difference in mean fluorine between smokers and
nonsmokers was smell (0.1 ppm) and probably not of biological significance.
Smoking intensity was not significantly consisted with total serum fluorine levels.
It is unlikely that smoking affects the pharmacokinetics of serum ?uorine or~
PFOA. it is unlikely that smoking was a primary route for absorption of PFOA.

Exposure reduction does not need to await the results of future studies. In
rodents. removal from exposure results in the reversal of the marked hepatic
responses to PFOA Intervention to reduce the PFOA body burdens of
employees would prevent any potential adverse effects in the future. The
reduction of exposure is especially important since PFOA has an unusually long

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biological half-life. A signi?cant reduction in body burden will require years of
reduced exposure.

We:

5.11.1.Selectlon?as

Given the occupational study setting, the voluntary participation, and the
requirements for blood sample collection, the overall participation was
unexpectedly high. Past medical screening programs at Chemolite had
participation rates of 60% to 70%. The present study's participation rate
exceeded 80%. Given the high participation. non-response bias is likely to be
small.

Selection bias is an important validity lssuetor sectional studies ?39. Only
active Chemical Division workers were included in this study. Workers not
included may have had a different response pattern than those who were
included. it continued employment depended on response to exposure and the
exposure was associated with the endpoint of interest, then selection bias may.
have occurred. A finding of the present study was PFOA was associated
with decreased free testosterone and incensed estradiol. if workers who had
high susceptibility to the cited of PFOA changed jobs,~then the overall slope of
the dose response curve could be underestimated. Conversely, if workers with
low testosterone associated with PFOA changed jobs less often. than the overall
dose response curve may be overestimated. Migration out of the high exposure
jobs is unlikely to be the result of subclinical changes in hormone levels. All
current Chemical Division employees who worked in high exposure jobs over the
last five years were included in the sample. Many workers who had been
employed in the high exposure jobs, but who changed jobs were included as 

participants. 111a vast majority of workers who had significant exposure over the 7

previous ?ve years would be included in the study sample as the tum-over rate in
Chemolite employees was low (three percent per year) and the study induded all
current employees with appropriate job histories. Selection bias is not a likely
explanation for the findings in this study.

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No worker was unexposed. The lowest potential exposure group had significantly
elevated levels of total serum ?uorine. in view of this. the observed effects may
represent an underestimate of the true effect.

Total senim ?uorine was used as a surrogate variable for PFOA exposure. The
use of total serum ?uorine has been validated in past biological monitoring in the
Chemolite Plant and other plants using PFOA a. Direct measurement of PFOA
using gas chromatographic techniques have been highly correlated with total
serum ?uorine in Chemolite workers. Approximately 90% of total serum ?uorine
in Chemolite workers was reported to be in the form of PFOA 3-12. The validity of
using this surrogate measure was not directly assessed in the current study due
to cost. Small amounts of PFCs other than PFOA may have been present in
serum. The half-life of PFC commands is directly related to molecular weight.
Compounds with six or less carbon backbones are likely to be rapidly excreted by
exhalation 19?. Short chain PFCs are unlikely to contribute appreciably to total
serum ?uorine. Longer chain PFC. such as per?uorodecanoic acid (PFDA). are
not produced at Chemolite. The high toxicity of PFDA excludes it from
commercial applications?. '77. 79' 101. Longer chain PFC are unlikely to be a.
significant component of total serum ?uorine. Other organic ?uorine containing
compounds exist in biol'ogical's'yste?ms and the environment. However, the small
amounts absorbed from the environment in the form of drugs or plant products
are rapidly metabolized and excreted inorganic ?uorine was not a large
constituent of the total ?uorine levels. Serum ionic ?uorine levels in the 1-5 
range are associated with death in unintentional occupational exposures ?92.
Total serum ?uorine is a good surrogate measure for PFOA in this cohort.

The coef?cient of variation for total serum ?uorine was 66%. The repeatability of
the assay was-better at total serum fluorine levels above five pprn. At the low
end of the spectrum 1 ppm), where the assay is limited by sensitivity, the total
serum ?uorine values may overestimate the true value. These measurement
encrs are likely to lead to an underestimate of the effect of PFOA on the
physiologic endpoints.

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Commercial PFOA Is a complex mixture of isomers and related compounds 39. .
it is clear that structurally related compounds, such as valprolc acid. exhibit 1
toxicity for certain isomeric tonne, but not others ?93. it is widely recognized
that different enantomers have different pharmacokfnetio and
pharmacodynamic properties Thus, different isomers of PFOA may have
different toxicities. if one isomer of PFOA is associated with toxicity. then the use
of total serum ?uorine or total PFOA levels could have pmduoed an under-
estimate oi the true strength oi assodation. However. in animal studies using
straight chain PFOA. the spectrum of toxicities is similarto those observed in
studies using mixed isomer of PFOA 37. 33- as. Further research is needed to
clarifythe role of PFOA isomers.

The toxicokir?retics of PFOA in humans are different from those observed in
rodents. Extrapolating the tissue distribution of PEOA from animals to humans
may not be valid. No data exist on the relationship between serum and tissue
PFOA distribution or body burden in humans. The use of serum levels to
extrapolate to the concentrations at the site of PFOA action may have been
inappropriate. Obtaining pharmacokinetic data in humans or appropriate animal
models is an important area for future research efforts.

The temporal variability of physiologic parameters is recognized. The ultraridan.
cimdian, and circennualvariability oi the study endpoints was not assessed
directly. Instead, blood samples were drawn at the same time of day. on the
same shift for all participants. One sample was drawn to estimate mean
parameter values. Considerable measurement error is inherent in this procedure
for hormones with Short pulsatiie intervals such as LH, FSH. and testosterone.
However, studies have shown that one sample is as good as three samples in
estimating mean values ?95. The use of a single sample to estimate mean
hormone level produced random measurement error and would be expected to
attenuate the observed relationships. Mean serum values of the assayed
hormones may not represent the biologically important quantities at the site of
action.

Validation studies of self-reported smoking status, using biochemical. markers
such as exhaled carbon monoxide, serum and urine thiocyanate. and serum

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thiocyanate. have shown that smokers underreport their smoking ?93. Smoking is
associated with changes in physiologic parameters such as hematological counts
197499. cholesterol lipoproteins 2?13?, and hepatic enzymes ?43. The
strength and direction of the assodation between self-reported smoking
information and these parameters can be used to indirectly assess the validity of
the smoking information 203.

In this study. smoking status and intensity was strongly and signi?cantly
associated with leukocyte count, band count, eosinophil count, platelet count,
and monocyte count. As expected. smoking intensity was negatively associated
with basophil count.

No participant reported drinking more than 3 ounces of alcohol per day. This
may reflect the company's success in discouraging heavy alcohol consumption in
employees, a reporting bias, or the fact that heavy drinkers may not be able to
continue employment due to the demands of Chemical Division jobs.

Alcohol consumption is associated with changes in physiologic parameters such
as hepatic enzymes mean corpuscular volume. triglycerides, and
high density lipoprotein 144. As with smoking. the strength and direction of the
association between self-reported alcohol consumption information and these
parameters can be used to indirectly assess the validity of the alcohol
information. increased serum HDL is associated with moderate alcohol intake
144.205.1208. The expected relationship between alcohol intake and HDL was
observed in this study in individuals with low PFOA levels. As expected, there
was a positive association between alcohol intake and triglycerides. Alcohol has
a direct toxic effect upon size, maturation. andnumber 207. The
speci?city of MCV is 90% in identifying alcoholics from social drinkers with a
positive predictive value of 96% In the present study alcohol consumption of
1 to 3 drinks per day was associated with an increase in MCV of the same order
as reported previously Alcohol induces GGT. The sensitivity of 
detecting alcohol use varies from 52% to 94%. GGT is highly non-specific for
alcohol consumption or for hepatic abnormalities A Heavy drinking of two
to ?ve drinks per day everyone week or more are necessary to induce GGT 
GGT may be the only commonly assayed hepatic enzyme to increase with

213

12405

 

heavy drinking. A significant positive association between GGT and self-reported
alcohol use was observed. The presence of these associations Indicates that the
misclassi?ca?on of alcohol use was unlikely to produce a bias large enough to
explain the observed associations.

Alcohol use was weakly associated with hepatic transamlnases. SGOT and
SGPT are less sensitive indicators of alcohol use than GGT. in alcohol induced
liver disease, SGOT may be elevated and SGPT little changed. SGPT
has been shown to decrease in some cases at alcohol lndumd liver disease 
Considering the relationship known to exist between alcohol use. SGOT and
SGPT, little alcohol associated change in transaminases would be expected.
The observed weak association is not an unexpected ?nding and therefore
probably ones not re?ect misclassi?cation of alcohol use.

Nonrespondents to the alcohol item were different than respondents. They were
treated as a separate group In the analysis since the difference could not be
explained by measured covariates. Although the power of the study is
diminished by treating alcohol information as a nominal categorical variable. the
potential for bias was reduced.

Wm

Information on the duration of employment In exposed Jobs was not collected. 
Plant records did not contain sufficient information to reconstruct exposures more

than five years in the past. The duration of exp?dSure may be an important

determinant of PFOA effect. Duration of employment may be related to PFOA

level since PFOA has the potential for bioaccumulation. The duration of

exposure may have been a confounder for peptide hormonal endpoints in this

study. in rodents steroid hormonal and hepatic enzyme effects of PFOA

exposure occur after two weeks of exposure, whereas peptide honnonal effects

may require longer emosures ?9 Leydig cell tumors may require a considerable

length of exposure or latency to develop ?22.

There are many compounds in complex androgen-estrogen system. The'present
study measured only a few of them. Other?biologicaily important steroid

214

12406

 

hormones include cortisol. androstenedlone, dihydroeplandrostenedione sulfate
(DHEAS), estrone. estrioi, estrogenic catechols. and dihydrotestosterone (DHT).
A total estrogen index or estrogen to testosterone ratio (511') may be more
important than assays of individual compounds 2?2. Sex hormone binding
globulin (SHBG), a major determinant of the estrogen to testosterone balance at
the tissue level 2?3. was not assayed. More research is needed to clarify the
potential role of these hormones as confounders of the observed associations.

The relationship for bound testosterone may have been confounded by steroid
hormone binding globulin (SHBG). Sex hormone binding globulin is an important
determinant of testosterone and estradiol levels in different tissues as well as
their metabolism 2?3. Plasma SHGB levels are positively associated with
estrogens'and negatively associated with androgens Thyroid hormone levels
aired SHBG 215. The ratios of estradiol to testosterone and testosterone to DHT
may be regulated by SHBG levels 213. The association between PFOA and
bound testosterone may have been, in part. related to estradiol and thyroid
hormone changes in SHBG levels. Adult rats do not express SHBG 213. The
decline in total testosterone observed in rats is not the result of changes in the
amount or binding characteristic of SHBG. The observed depression of free
testosterone in men is analogous to changes in total testosterone in rats and is
probably not significantly related to changes in SHGB binding. 

Major stresses, such as surgicd procedures, have been shown to markedly
affect hormones in men 2?7. it is unlikely that major physical stresses were
associated with PFOA. Therefore, stress Was not a significant confounder in the
present study. 

Shiftwork has been shown to attest a variety of physiologic endpoints including
biochemical parameters. hematologic indices, and hormones Study
participants rotated weekly through three shifts. All samples were collected on
the day shift atleast three days post shift change. Given the rotating shifts and
Standard day shift sampling, hit is unlikely that shlfiwork and PFOA were
associated. did not appear to be a significant confounder ot the
estimated dose response relationships. -

215

12407

 

Several dietary factors are determinants of the endpoints considered in this
study. The effects of dietary fat and cholesterol on serum Iipoproteins and lipids
is widely appreciated Dietary calories. fat, and carbohydrates affect steroid
hormones 219' 22?. Diet can also affect the metabolism of steroid hormones 22"
222. Since it is unlikely that diet is associated with PFOA. it is probably not a
confounding covariate in this study.

Physical activity affects many physiologic parameters including hormones 223.

enzymes 23?, iipoproteins and hematologic indioes. For hormones. only

maximal exercise produced an effect. No effect was noted for submaxlmal 
physical activity. it is unlikely that many partidparrts engaged In maximal 
physical activity. Therefore, in this group. it is unlikelythat physical activity is a

determinant of the hormonal endpoints under study. Physical activity may effect

HDL levels. but It is unlikely that physical activity was associated with PFOA.

Therefore. physical activity was unlikely to be a significant oonfounder in this

study.

Medication usage and diseases such as diabetes meilitus are important
determinants for some of the physiologic parameters measured in this study 
?95. Questionnaire items concerning mediwdion use and medicat history were
incomplete and were not validated. PFOA exposure has not been associated
with any medical conditions 3. if the use of medication or the diagnosis of a
medical condition that affects one of the physiologic endpoints is assodated with

exposure. then confounding may occur. However, no such relationships

have been described.

In?ammatory processes which are major determinants "of WBC. were not
assessed in this study. There is no evidence that inflammatory processes are
related to total semm fluorine or serum PFOA. Therefore, these determinants of

leukocyte count are unlikely to confound the estimated relationships.

The analytic multivariate approach used in this study assumed that a linear
model with additive effects was an adequate model with which to summarize the

216

12408

 

data. A normal error term was used. Similar models of physiologic variables
have been extensively used in the past and their assumptions tested 225. The
model form was partially de?ned a priori based on a biological hypothesis. The
choice of a ?nal model was based on biological knowledge plus best predictive
power. The variable transformations used were not based on a Specific
biological mechanism, but instead reflect the basic form of dose response
relationships observed in nature.

5W
Win

This was a retrospective cohort study of mortality in workers employed in a
PFOA production plant for greater than six months during the period from
January 1, 1947 to December 31 . 1989. Completeness of the cohort was
assessed from independent sources. Demographic and work history data were
collected from plant records and veri?ed from independent sources where
possible. Cohort members were not individually contacted for additional
information on confounding variables such as smoking. Vital status was
con?rmed for 100% of the cohort. Cause of death was obtained from death
certi?cates for 99.6% of deaths and other sources for 0.4% of deaths. Cause of
death was coded by IOU-8 categories by a nosologist. Reliability of death
certi?cate coding was assessed by random of death cem?cates for
recoding. The concordance was 100% for three digit codes.



The 749 women were observed tor19.309 person-years, had a mean age at ?rst
employment of 27 years and mean follow-up of 26 years. The number of
expected events given the age and size of the cohort was small. The study had
limited power to dated moderate increases in cause-speci?c mortaltiy.

The 2788 men were observed for over 70,000 person years. The mean age at
?rst employment was 27 years.the mean length of follow-up was 25 years and a
the mean age of death was 56 years. men were older on average than

217

12409

 

CD men and had more person-years in the older age groups where mortality was
the highest. .lnternalcornparisons were confounded by age as well as other tlme
correlated factors such as length of follow-up.



In females, 6.7% were deceased compared to 12.5% In the males. Given that
the mean age at first employment and mean length of follow-up was similar for
males and females. this reflects the expected survival advantage of women. For
both males and females the proportion or deaths was smaller In the co cohort.
Employment in the Chemical Division did not produce a large survival
disadvantage.

The all causes. all cancer. and all cardiovascular mortality among women was
less than expected in the overall cohort. The were remarkably stable
when stratified on ten year exposure groups. and ten. ?fteen. and twenty year
latency periods. The all causes was .75 in the total cohort. .75 in those
employed for at least ten years or for those employed longer than ten years. and

.75 in all three latency periods. Cardiovascular diseases and cancer mortality
followed a similar pattern.

In males. the all causes. cardiovascular diseases. all gastrointestinal. and all
respiratory diseases were signi?cantly less than one. The all causes SMR
was .77 using Minnesota mortality rates and .73 using national rates. The low
are most likely a result of the healthy worker effect (HWE). As expected.
the cancer SMR is less affected by the HWE. The all-causes were .75 for
all three latency groups. Latency did not have a strong relationship with the
HWE. The all causes SMR was .80 in the greater than five year employment
duration group and .68 in the greater than 20 year employment group. The low 
all causes sum in the greater than 20 year duration group suggests that working
for 20 or more years was associated with continued selection based on good
health. The all causes decreased with duration of employment in one
meta-analysis of retrospective cohort studies 25 .but increased in the meta-
analysis by Fox and Collier 227.

218



 

The SRRs for all causes. all cancer. and all cardiovascular diseases for less that
ten years employment to more than ten years employment were not signi?cantly
different from one. Because the rates were based on small numbers of events.
the 95% Cl were wide. Due to the small number of events in the females. SRRs
were not calculated. The SFiFls are slmilarto the for the less than ten year
employment and greater than ten year employment groups.

The for CD versus non-CD male workers for all causes, all cancer, and all
cardiovascular diseases were not significant and were similar to the 
Working in the CD did not substantially alter the rates of death. The small
number of events observed for rare causes of death or speci?c causes of death
make it unlikely that moderate increases in rates could be detected in this cohort
for the follow-up period'through 1989. More follow-up time will be needed to

allow sufficient power to detect moderate increases in rates for speci?c causes of
death.

The results from the adjusted contrasting the mortality rates for all
causes, all cancer. and all cardiovascular diseases between CD and non-OD
male workers were similar to those for the SFlFis and None of RRMH
point estimates were statistically different from one. The contrast of rates
between less than ten years of employment and greater than ten years of
employment presented a different picture. All cause were signi?cantly
elevated in the oldest two age groups. while the RRMH for cardiovascular
diseases was signi?cantly elevated in the 30 to less than 40 year age group. The
all cancer displayed a trend toward a statistically significant elevation in
the oldest two groups. The RRMH were not adjusted for year of ?rst
employment. They may have been substantially confounded by changes of
exposure over time since year of first employment. As seen in several PH
regression models, year of first employment was signi?cantly associated with the
mortatilty. After age and length of follow-up. calendar time is the strongest time
factor associated with mortality ?39. Hence. it is likely that the elevated for
composite categories of cause of death in the oldest groups were a result of
uncontrolled confounding by calendar period. Given the small number of events

in strata. it was not feasible to further stratify the data on year of ?rst
employment

219



 

 

In the PH regression analysis. prostate cancer mortality was positively and

significantly related to time in the Chemical Division. Ten years of employment in

the CD was associated with a 3 fold increase in prostate cancer mortality

compared to men never employed in the CD. This trend was evident in the SMR

analysis stratified by CD and non-CD employment. This association was

independent of duration of employment and year at first employment. As

expected. ageat ?rst employment was positively related to prostate cancer

mortality rate. The interpretation of this estimated relative rate is tempered by a

number of factors. The estimates were based on six prostate cancer deaths. tour .
in the CD cohort and two in the non-CD cohort. A change of one case could
significantly alter the estimates. Ascettainment oi all prostate cancer deaths may

have been incomplete. Diagnosis may have been more complete in the CD

cohort. Given that death certificate cause of death information is known to be

imperfect. mlsciassitication of one or more deaths could occur. The use of

mortality as the event of interest for etiologic studies of prostate cancer is not the

best study endpoint because of the long natural history and low mortality of

prostate cancer. The majority of incident prostate cancers do not progress and

cause death 229' For localized disease. an 80% ten year survival in untreated

patients have been reported 23?. Studies of prostate cancer incidence in this

workforce are needed to clarify the suggested increase in prostate cancer risk.

The ?ndings of hormonal alterations in PFOA exposed men suggests a possible

biologic mechanism for the increase in prostate cancer mortality incidence
studies of other diseases that are horrnonaily mediated may be indicated if the

PFOA associated hormonal changes are con?rmed.


Was

The use of death certi?cates to categorize cause of death imperfect 232-235. The
size of the potential bias depends on the cause of death. in one study cancer as
a cause of death was under-reported by 13% m. Leukemias and 
were underreported in 19% of autopsy continued cases. Colorectai cancers
were underreported in 12% of cases. Therefore, it appears that cancer deaths
were not severely misclassified. All cardiovascular diseases as a group may

220



 

 

have been inaccurate. individual disease with the whole may be severely
misclassi?cated and may produce large biases. For example, specific-causes of
death in the cardiovascular group, such as cerebrovascular disease. are
inaccurately designated on death certi?cates.

Three measures of PFOA exposure based on job history were used in this study.
First, the cohort was diohotomlzed into those who ever worked in the CD and
those who never worked in the CD. Second, the number of months worked in the
CD until 1985 was used as a continuous parameter for PFOA exposure. Third,
the total duration of Chemolite employment was used as a continuous parameter
for the effect of work in a plant producing PFOA among a large number of
products. Each of these surrogate variables may produce a different spectrum of
misclassitication. Categoriza?on of workers into ever versus never employed in
the CD may not re?ect the biological effective dose of PFOA. Many CD jobs do
not entail PFOA exposure. A number of workers were employed in the CD for
short periods in the distant past. Their exposure may not have been significant.
This categorization may misclassify unexposed workers as exposed.

Conversely, PFOA exposure was widespread among Chemical Division (CD)
employees working in jobs with no exposure to PFOA. No exposure
measurements have been done in non-CD employees. It is possible that non-CD
employees had significant body burdens of PFOA. If this was the case. exposed
workers would have been classi?ed as unexposed. Such misclassifioation would
be expected to bias the effect estimates toward the null. The months of
employment in the CD was the best available estimate of PFOA dose. Not all CD
jobs have PFOA exposure. The misclassification produced by 
unexposed workers as exposed could have biased the estimate toward the null.
The use of duration of employment at Chemolite as a continuous exposure
parameter is less speci?c for PFOA than time In the CD. If another xenobiotic
exposure in the plant has modulated disease occurrence rates. the use of
duration may produce less than use of duration in the CD.

 

The healthy worker effect strongly effects the validity of many oocrrpatlonal
studies ?39- 33". It is a complex bias that results, in part. from the selection of

221



 

individuals for employment who are healthier than those in the comparison
population. The HWE is usually stronger for cardiovascular diseases and
respiratory diseases. Because cardiovascular diseases mortality amounts for a
signi?cant portion of all causes mortality. the HWE usually reduces the all causes
The age at ?rst employment. age at risk. length of follow-up, and duration
of employment are four time factors that are associated with changes in the HWE
139. Generally. the HWE diminishes with age and time.

Collection of confounder information for individuals is dif?cult in retrospective
cohort mortality studies. The present study included workers followed for more
than 40 years. it was not feasible to coiled individual information on such
covariates as smoking, health status. medical history. or dietary habits. The
proportion of workers at Chemolite who smoke has been lower than in other
facilities owned by the same corporation. In recent health maintenance studies.
the self-reported smoking prevalence is lower than the statewide smoking
prevalence. The observation that all respiratory diseases and lung cancer rates
are lower than expected may be the result of historically low smoking prevalence.
The low smoking prevalence may depress the all causes SMR. all cancer SMR.
and all respiratory disease The use of internal comparison groups may
reduce this smoking related bias 237.

Time factors such as age at risk. age at ?rst employment, year of ?rst
employment. and duration of employment are associated with the occurrence of
many diseases ?39. The use of an internal comparison group may reduce certain
selection effects, but may not control confounding if the exposure de?ned internal
comparison groups have different distributions of these time factors. Although
the mean age at ?rst employment and mean year of ?rst employment are similar
in the CD and non-CD cohorts of men and women, the comparisons of the rates
of disease are confounded by differences in the distribution of age at risk. These
time factors are strongly consisted. with some being exact linear combinations of
others. The relationship between measures of exposure and disease occurrence
may be complex functions of these inter-related time factors. Adjustment for time
factors may reduce the effects of confounding. but may not control confounding
233. if the disease occurrence relationship is de?nedin terms of cumulative

222



 

exposure, the true effect of exposure may be biased toward the null by
uncontrolled confounding doe to the complex time factors ?99.

Some workers were exposed to many other potentially disease causing
xencbiotics, such as benzene and asbestos. during their employment at
Chemolite. Adjustment for their effects was not possible in this study. Even if
information was available, exposures are cfien highly correlated making the
separation of individual effects impossible.

IE 5'

Comparison of and between exposure groups may not be strictly
valid. However, if the distribution of the person time in the comparison groups is
not strongly discordant. then such a comparison may be useful. In the current
study, the person-time distributions are different in the exposed groups. However,
the differences appear to be of a magnitude that makes useful comparisons of
possible. 

Although the proportional hazard (PH) model has been used frequently for cohort
studies and clinical trials, it has not been widely used in occupational studies. In
the past. it has been suggested that Poisson regression was the analytic strategy
of choice because computational costs were less and the conceptualization of
the model straight forward ?99. However, PH models are now easily run with
standard computer packages Their wide application in clinical trials and
cohort studies has fostered the understanding of the PH models. Poisson
models appear less frequently in the literature and may not be as well
understood. Poison regression and PH models have theoretical links and have
been shown to give similar results when usedto analyze the same data set 
Cox PH regression was chosen as the multivariate model to employ In this study.
The validity of the proportional hazards assumptions was examined using the
two standard techniques. The assumptions did not appear to be grossly violated.
However, in analyses involving a small number of events. the assessment of the
validity of assumptions may be limited. The use of the factors as continuous
variables was based on lack of statistical evidence for a significant nonlinear

223



effect. Although this strate y has been widely used for control of confounding, it
has not been extensively validated in simulation studies.

24



 

This was a cross-sectional study of selected physiologic effects of PFOA, as
quantified by total serum ?uorine. Participants were recruited from workers
employed during November 1990 In the Chemical Division of the 3M Chemolite
Plant in Cottage Grove. Minnesota. All current workers who were employed in
high exposure jobs at any time during the previous five years and an age
matched sample of workers employed in low exposure jobs were Invited to
participate.

Participants completed a corporate medical history questionnaire and had vital
parameters measured by an occupational health nurse. Blood was drawn for
assays of total serum ?uorine, seven hormones Involved in the hypothalamic-
pitultary-gonadal axis, serum lipids. lipcprotelns, hepatic function parameters.
and hematology indlces. Blood was drawn in the morning after workers were
assigned to the day shift for at least three days.

In past studies. the majority of total semm ?uorine found in Chemolite workers
was in the form of PFOA. Thus. total semrn ?uorine is a valid surrogate measure
of PFOA in Chemolite employees. For 93% of workers. total serum ?uorine
levels were 20 times greater than community and corporate background levels. 
Findings in the current study are consistent with other data suggesting that PFOA
has along biological half-life in both men and women. The long half-life of PFOA
may result In signi?cant bioaccumulation from small frequent doses or large,
infrequent doses.

The hormonal findings from this study are consistent with the hypothesis that
PFOA depresses the human hypothalamic-pituitarygonadal axis. The results
show that low levels of serum PFOA (zouM) depressed free testosterone and
elevated estradiol with little observed change in LH levels. In older men, free
testosterone was depressed below 9 at serum fluorine levels below one
(estimated PFOA levels below 1 pill).

225



 

Mean prolactin levels were positively associated with PFOA in moderate drinkers.
but not in light drinkers. Since the function of prolactin in men is uncertain. the
clinical significance of this finding is unclear.

Mean thyroid stimulating hormone was positively associated with PFOA. Since
hormone levels were not assayed. it was not possible to
assess whether the observed association between PFOA and TSH was the result
of a direct effect on the hypothalamus, pituitary. thyroid gland. or peripheral
thyroid hormone metabolism.

Cholesterol. triglycerides. and LDL were not significantly associated with PFOA.
PFOA was negatively associated with HDL in moderate drinkers.

PFOA was not associated with the marked hepatic changes in humans that have
been observed in rodents. PFOA appeared to alter the hepatic response to
endogenous factors and xenobiotics.

PFOA was signi?cantly associated with hemoglobin levels, MCV, and MCH. The
estimated changes in are not of clinical significance over the range
of observed total serum ?uorine.

The changes in leukocyte. counts associated with PFOA exposure presented a
complex picture. For example, the negative association between PFOA and
was increased by smoking more than to cigarettes per day and
decreased by alcohol use and adiposity. The magnitude of these associations
are not clinically signi?cant from an infectious disease perspective. However.
elevated WHO has been associated with increased all causes, cardiovascular
diseases, and cancer mortality as well as increased incidence of myocardial

infarction.

 

This was a retrospective cohort study of mortality in workers employed in a PFOA
production plant. All causes mortality in both male and female Chemolite
employees were significantly less than expected based on comparisons to the

226



 

aw.

mortality experience of the Minnesota and United States population. The SMRs
for several other causes of death including all respiratory diseases were less than
expected. Since the healthy worker effect was apparently strong In the
Chemoiite cohort, internal comparisons of were made between Chemical
Division (CD) and non-Chemical Division (non-CD) employees. These
comparisons did not suggest any significant excesses in mortality in CD or non-

CD employees.

Generally, the findings from this study provide no evidence that employment at
Chemoiite results in elevated mortality rates from any cause. However. pro?ate
cancer mortality. may be associated with length of employment in the Chemical
Division. Ten years of employment in the CD was associated with a significant
three fold increase in prostate cancer mortality. There was no association
between prostate cancer mortality and employment (ever/never) in the Chemical
Division. Given the small number of deaths from prostate cancer in this study
and the natural history of the disease, the association between employment in
the CD and prostate cancer must be viewed as hypothesis generating and should
not be over interpreted. However. the biological plausibility for any association
between CD employment and prostate cancer is increased by animal and human
toxicological data suggesting an association between PFOA and steroid sex
hormone changes.-



Periluorooctanoic acid was associated with reproductive hormonal changes in
exposed workers. The clinical significance of these findings are unknown. The
associations of PFOA with hormones, HDL. hematology parameters. prostate
cancer mortality in men indicates the need for further research.

Research is needed in ?ve areas.

227



 

1. An assessment of the hormonal effect of PFOA in women is needed. A cross-
sectlonai study should be conducted using speci?c assays for PFOA and
accounting for temporal hormonal variations.

2. The clinical significance of the associations of PFOA with the physiologic

parameters need clarification. Since morbidity from diseases such as prostate
cancer is reflected in mortality. an update of the retrospective mortality study is
needed in five years. Morbidity studies should be conducted of endpoints 

- may be produced by hormonal changes. Since exposed workers are relatively

young and are limited in number. the feasible endpoints tor a short term morbidity
study are limited. Pooling of workers from a number of plants could increase the
number of exposed workers and allow endpoints with lower incidence to be
studied. The?morbidity study should be a long term which would allow the study
of endpoints that occur at higher frequency in older age groups. in men.
endpoints should include the incidence of benign prostatic hypertrophy and
prostate cancer. The feasibility of including inflammatory bowel disease and
colorectal cancer as endpoints should also be evaluated. In women. endpoints
should include the age of menopause, the incidence of osteoporosis and related
fractures, uterine fibroids, and cholelithiasis. if there are a suf?cient number of
events. endometrial cancer and in?ammatory bowel disease should be
evaluated. If the cross-sectional hormonal study in women ?nds no association
between PFOA and hormones, then the morbidity study can be limited to men.

3. Studies of reproductive outcomes in both men and women are needed. Libido.
potency. and fertility are directly associated with steroid hormones levels. The
feasibility of a retrospective study of reproductive endpoints or a prospective
study of time-to-pregnancy needs to be explored.

4. The mechanisms of action of PFOA need to be studied concurrently with
morbidity. Mechanistic studies are needed to define the relevance of animal
studies for humans and provide a firm biological basis for the ?ndings of the
mortality. morbidity. and reproduction studies.

In vitro and cell line studies could ciariiy the mechanisms of action of PFOA on
the pituitary secretion of LH. FSH, TSH. and prolactin. Pituicyte cultures may be

228

12420

helpful in evaluating the direct effect of PFOA pituitary function. The effect of
PFOA on other autocrine or paracrlne factors such as TGF-B, FGF, and
TNF could also be evaluated. Human adiptocyte cultures could be used to study
the effect of PFOA on arometase activity. Additionally. studies are needed to
clarify the relationship between PFOA and the temporal variability of reproductive
hormones.

5. Studes are needed to better define the PFOA exposure pro?le of all workers
employed at Chemoiite, to ascertain the source of their PFOA exposure and

route of continued absorption and to darliy the toxicokinetics and toxicodynamics
of PFOA in humans.

229

12421

 



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12446

PHYSIOLOGIC EFFECTS STUDY QUESTIONNAIRE

12447

Medical History Questionnaire

256_

12448

mg? 

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258



12450

TABLES OF HORMONE RATIOS BY BODY MASS INDEX, AGE. SMOKING
STATUS, AND ALCOHOL CONSUMPTION

259

12451

TABLE A4.1.1 BOUND TESTOSTERONE TO FREE TESTOSTERONE RATIO
BY. BODY MASS INDEX. AGE.
SMOKING AND DRINKING STATUS
1990 PERFLUOROCHEMICAL EFFECTS STUDY.
3M CHEMOLITE PLANT, COTTAGE GROVE, MINNESOTA

 

 

   

 

.
MEAN SD MEDIAN RANGE TEST 

BMI I
425 40 37.2 9.06 37.1 22.3-62.5 F-1 47

25-30 55 378 9.31 37.1 19.3-62.4 53-23

.30 17 33.3 9.18 31.2 19 7-524

.AGE

<31 20 32.4 6.92 31.2 20.0-43.6 F-.2.39

31-40 49 37.3 9.37 37.1 19.3-62.6 p-.07

41-50 26 37.1 9.30 38.8 19.7-88.8

51-60 19 39.9 9.90 39.9 22.3-62.4

Alcohol -

{102/0 66 37.4 9.90 37.2 19.3-62.6 F-2.06

1-3ozld 19 33 9 6.70 32.2 22.7-44.1 p.315

missing a as 5 70 38.6 23.4435

Tobacco 
maker 27 37.9 7.96 37.2 25.0-58.8 F-.32 I
nonsmoket 64 36.7 9.64 36.3 19.3-62.6 p-.57

missing 2 27.5 1.57 27.5 26.4-28.8

113
Tunivariate Anova

260

12452

TABLE A4.1.2 ESTRADIOL TO FREE TESTOSTERONE RATIO 
BY BODY MASS INDEX, AGE. SMOKING AND DRINKING STATUS
1990 PERFLUOROCHEMICAL EFFECTS STUDY.
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

       

 

EITF


:25 40 207 0.00 1.04 073-00 
25.30 50 2.20 0.02 2.17 0.70530 >30m-00
.30 17 2.50 0.00 242 1.44.531 7-230

p.02
AGE
?31 20 1.04 0.00 1.01 1.44327 5.1.10
31-40 40 2.20 0.01 2.17 0.77-4.10 0-32
41-50 20 2.31 1.20 2.04 0.77-5.30
51-60 10 2.40 1.05 2.42 1.07-5.31
Alcohol
010270 06 2.23 0.02 2.10 0.745.111 F001
1-302/0 10 2.21 0.70 2.21 0.70410 0-02
missing 0 2.40 1.00 2.00 1.41-0.30
Tobacco
smoker 27 2.10 0.00 2.00 0.74.530 F-.15
nonsmoker 84 2.27 0.02 2.10 0.73-5.31 0-.70
2 1.03 0.32 1.00 1.05-2.11
TOTAL 113

"30051130310 Anova
*Student test, Prob>T
261

12453

TABLE A4.?l.3 ESTRADIOL TO BOUND TESTOSTERONE RATIO 
BY BODY MASS INDEX. AGE, SMOKING AND DRINKING STATUS
1990 PEFIFLUOROCHEMICAL EFFECTS STUDY,

3M CHEMOLITE PLANT COTTAGE GROVE, MINNESOTA

 

 

   
 

11100

  

W. RANGE 

   

3

 

MI
.25 40 5.0 2.05 5.7 11.5-13.5 F-3.70
25-30 55 5.3 2.73 5.5 2243.4 p.03
1 7 80? 2091 708 3.7-1 4.4
AGE 
31.40 45 5.4 2.75 5.5 11.5-13.5 p.95
41.50 25 5.5 3.53 5.0 1.7-14.4
51-50 19 5.4 2.75 5.0 2.3-11.5
Alcohol
40211! 88 6.3 2.90 5.7 1.2-1 4.4 F200
1.30m 19 5.5 1.95 5.5 3,040.5 p-.95
missing 5 5.5 3.45 5.4 3,943.5
Tobacco
smoker 27 5.9 2.73 5.1 11.5-13.5 F-1.01
nonsmoker . 84 5.5 2.84 5.0 2243.4 p.32
missing 2 5.9 1.55 5.9 3.7.14.4
TOTAL 113
'?univariate Anova

262

12454

 

TABLE A4.1.4 ESTRADIOL TO LUTENIZING HORMONE FIATIO 
BY BODY MASS INDEX. AGE. SMOKING AND DRINKING STATUS

1990 PERFLUOROCHEMICAL EFFECTS STUDY,

3M CHEMOLITE PLANT, COTTAGE GROVE, MINNESOTA

 

   

 



. ?"55
BMI
.25 40 7.0 3.11 7.3 2.0-15.4 5-255
25.30 55 7.0 423 5.5 1020.5 p.05
.30 17 3.3 3.92 3.5 3315.4
AGE
.31 20 3.7 4.55 7.5 2.3.20.5 5.2.51
31-40 45 7.3 3.35 7.5 1545.4 p.05
41.50 25 5.4 455 5.1 1510.5
51-50 19 5.3 233 5.2 13-115
Alcohol
41021:! 55 7.2 395 7.0 1.0.20.5 504
1-302111 10 7.4 4.15 5.7 1545.4 
missing a 3.5 3.13 3.7 4315.4
Tobacco
smoker 7 27 7.0 4.42 5.2 1515.4 5-.34
nonsmoker 54 7.5 3.77 7.1 1020.5 p.55
2 4.7 3.35 4.7 2.3-7.0
TOTAL 113
_#univariate Anova

263

12455

TABLE A4.1.5 FREE TESTOSTERONE TO LUTENIZING HORMONE RATIO
(TFILH) BY BODY MASS INDEX, AGE. SMOKING AND DRINKING STATUS
1990 PERFLUOROCHEMICAL EFFECTS STUDY,
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

 

       

 

TFILH
1
BMI
<25 49 3.5 1.74 3.3 1.1-113 5.1.47
25.39 59 3.2 1.74 2.9 9.7-9.1 p.24
.30 17 3.9 1.75 34 1.4-71
AGE
2311 29 4.9 2.55 3.9 39 5-721
31-40 49 3.9 1.43 3.3 3.3 111-5992
41-50 29 2.9 1.39 2.7 2.7
51-60 19 2.5 1.14 2.5 2.5
Alcohol
?192/9 99 34 1.95 3.2 9.7.11.3 5.39 
1-33213 19 3.3 1.44 3.2 9.7-5.4 p.31 
3.8 1.43 3.6 2.1-8.2 I
Tobacco
911191191- 27 3.2 1.34 3.2 1.1-9.9 5-129
1191191119391 94 3.9 1.97 3.2 11.7-11.3 11-29
missing . 2 2.4 1.38 2.3 1.46.3
TOTAL "3
"innivan'ate Anova
I
264

12456

TABLE A4.1.6 BOUND TESTOSTERONE LUTENIZING HORMONE RATIO
BY BODY MASS INDEX. AGE. SMOKING AND DRINKING STATUS

1990 PERFLUOROCHEMICAL EFFECTS STUDY,
3M CHEMOLITE PLANT . COTTAGE GROVE. MINNESOTA

 

 

 


MEAN SD MEDIAN RANGE 
BMI
.25 40 131 67.9 126 39-296 F-.79
26-30 66 116 60.6 107 24-299 p.46
>30 17 122 43.4 121 66-199
AGE
231 20 147 69.7 136 39-2911 54.72
31-40 49 133 69.0 131 36-299 6.004
41.50 26 101 96.7 93 29-163
51-60 19 96 47.6 96 24-209
Alcohol
4102111 96 122 67.1 121 24-296 F-.32
1-30216 19 114 56.1 92 29-202 p-.57
missing 9 147 63.2 142 77-234
Tobacco
smoker 27 116 52.4 114 41-299 F-.54
nonsmoker 84 125 58.8 121 24-298 p.48
1111961110 2 94 34.3 64 39-66
TOTAL 113
#univariate Anova
265?

12457

TABLE A4.1.7 THYROID STIMULATING HORMONE TO
LUTENIZING HORMONE RATIO (T SHILH)
BY BODY MASS INDEX, AGE, SMOKING AND DRINKING STATUS
1990 PEHFLUOROCHEMICAL EFFECTS STUDY.
3M CHEMOLITE PLANT. COTTAGE GROVE, MINNESOTA

 

 

  
 

      

 

:1.73 3.2 9.3?3.3 5.3.43
25.30 53 3.5 2.30 3.9 9417.9 9-.92
.30 17 5.3 3.34 4.4 1.7-13.5
AGE
231 29 3.7 2.43 3.1 1.9-9.9 F-.14 1
31.40 49 3.3 3.13 3.2 9.4.17.9 p.33 1
41-159 23 3.4 1.99 2.9 9.3-9.3 1
51-30 19 3.3 2.43 3.3 11.4-11.9
Alcohol
?132141 33 3.5 2.29 3.1 11.4-11.9 7.2.92
1-33213 19 4.7 4.93 3.2 1317.3 9-.09
missing 3 3.3 1.74 3.3 9.3-3.3
Tobacco - 
311191137 27 3.9 1.33 2.3 9.4-7.3 7.2.33 
nonsmoker 84 4.0 2.89 3.3 0.4-17.0 9-.09
1111931119 2 1.7 3.31 1.7 1.7.1.7
TOTAL 113 i
#univariata Anova



I
El
266 

12458

 

TABLE A4.1.8 FOLLICLE STIMULATING HORMONE TO

LUTENIZING HORMONE RATIO (FSHILH) BY BODY MASS INDEX, AGE,

SMOKING AND DRINKING STATUS

1990 PERFLUOROCHEMICAL EFFECTS STUDY.

3M CHEMOLITE PLANT. COTTAGE GROVE, MINNESOTA

 

 

 

 

 

 

 

FSHILH
BMI
?25 40 1.0 0.42 0.0 0.4-2.3 F-2.54
25-30 50 1.0 037 0.0 0.4-1.0 p.00
.30 17 1.2 0.40 1.1 0.4-2.0
AGE
231 20 0.0 0.4 0.0 0.5-1.0 53.00
31-40 43 0.0 0.40 0.0 0.4-1.0 p.03
41-50 20 1.1 0.45 1.0 0.4-1.0
51-50 10 12 0.40 1.1 0.5-2.3
Alcohol
as 1.0 0.42 0.0 0.4-2.3
130210 19 0.0 0.41 0.0 0.4-1.7 F-.48
0.0 024 0.0 0.0-1.3 p.49
Tobacco
011101401- 27 1.0 0.40 0.0 .04-1.0
nonsmokor a4 1.0 0.42 0.0 0.4-2.3 F-0.0
2 0.0 0.43 0.0 0.7-1.0 p.00
TOTAL 113
#uniVariate Anova

267

12459

TABLE A4.1.9 PROLACTIN TO LUTENIZING HORMONE (PILH)
BY BODY MASS INDEX. AGE, SMOKING AND DRINKING STATUS
1990 PERFLUOROCHEMICAL EFFECTS STUDY.
3M CHEMOLITE PLANT, COTTAGE GROVE, MINNESOTA

 

 

       

 

- FILH
am
a 40 1.34 1.14 1.33 0.30-3.33 F-.73
25-30 53 1.73 1.40 1.43 0.33-3.11 p-.43
.30 17 2.21 1.20 1.33 1.13-4.31
AGE
.31 20 2.23 1.70 1.33 1.13-4.31 3.133
31-40 43 1.35 1.33 1.37 0.33-3.11 p.21
41.50 23 1 31 0.33 1.13 0.33-3.70
51-33 13 1.54 0.37 1.33 0.35-3.37
Alcohol
210210 33 1.73 1.04 1.31 0.35-3.33 53.13
1-30210 13 2.37 2.14 1.70 0.33-3.11 p.03
missing 3 1.57 0.71 1.47 0.33-3.00
Tobacco
31110113: 27 1.27 0.73 1.12 0.33-2.74 3.3.23
1303311101133 34 2.07 1.33 1.72 0.35-3.11 02003
missing 2 1.43 0.73 1.43 0.33-2.00
TOTAL 113
7univarfate Anova

1
268

12460

1

TABLE A4.1.10 BOUND TESTOSTERONE TO THYROID ST IMULATING

HORMONE RATIO



BY BODY MASS INDEX. AGE, SMOKING AND DRINKING STATUS
1990 PERFLUOROCHEMICAL EFFECTS STUDY.

3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

 

 


MEAN SD MEDIAN RANGE TESW

BMI
d5 40 500 331 413 1m1682 52.42
25-30 58 461 364 329 51-2102 ran-.00
.30 17 296 152 297 87689
AGE
<31 20 522 387 416 122-1882 F464
31-40 48 521 388 421 51-2102 9-.05
41-50 26 359 203 345 131-1035
51-60 19 328 231 286 87-1122
Alcohol
?am 86 488 352 353 87-2102 F-2.74
1-30216 19 329 210 278 51-900 pun-.10
??33an a 553 328 456 184-1154
Tobacco
27 488 232 403 184-1185 F-.07
nonsmoker 84 448 364 321 51-2102 p.80
missing 2 371 199 371 231-511
TOTAL 113
#univariate Anova

. 269

12461

TABLE A4.1.11 FREE TESTOSTERONE TO THYROID STIMULATING
HORMONE RATIO (TFITSH)
BY BODY MASS INDEX, AGE, SMOKING AND DRINKING STATUS
1990 PERFLUOFIOCHEMICAL EFFECTS STUDY,
3M CHEMOLITE PLANT COTTAGE GROVE, MINNESOTA

 

 

       

 



W, WW BANG 
BMI
<25 40 19.9 9.92 10.9 11.9-49.7 5.2.49
25.30 59 11.7 7.01 9.7 1.7099 p-.09
.30 17 9.9 5.05 9.0 2.0-1915.9 9.97 10.9 9143.7 F-5.36
31.40 49 19.4 7.92 11.9 1.7999 9.2002
41-50 29 9.7 4.59 9.7 11.7-22.0
51-90 19 9.1 4.49 . 7.9 2021.9
Alcohol
<10ch 99 12.4 1.99 10.0 2049.7 F-2.48
1-3ozld 19 95 5.10 9.7 17-20.? p-.12
missing 9 15.3 9.35 12.3 5.0-33.5
Tobacco 7
smoker 27 12.5 5.59 11.9 9.0-27.2 9-.12
nonsmoker 94 11.9 909 9.9 1.7497 p.79
missing 2 13.7 7.99 13.7 9.1-19.4
TOTAL 119 W-
#univariate Anova
270

12462

TABLE A4.1.12 ESTRADIOL TO THYROID STIMULATING HORMONE RATIO
BY BODY MASS INDEX. AGE. SMOKING AND DRINKING STATUS
1990 PERFLUOROCHEMICAL EFFECTS STUDY,

3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

 

 

 

WH 
MEAN SD MEDIAN RANGE TEST 

BMI
?25 43 20.7 17.73 23.1 33409.1 5.27
25.30 56 25.4 14.04 213 13-390 - p.76
,30 17 23.4 13.79 19.4 7.7343
AGE
?31 20 27.3 12.00 24.3 9.7-30.0 F-3.21
31.40 49 29.3 13.40 23 13409.1 p-.03
41.50 26 21.3 13.06 19.0 3352.2
51.50 19 19.2 10.30 16.9 7334.3
Alcohol
([0211! 90 23.1 13.09 21.5 11.3-39.0 F-.57
1530210 19 22.4 15.30 13.0 1354.2 p-.45
missing a 37.3 31.31 23.5 10.44031
Tobacco
smoker 27 23.7 15.13 23.4 10.3-59.0 F-.20
Mr 34 25.1 15.35 20.7 13408.1 pan-.65
111199an . 2 27.1 19.40 27.1 13.4-40.3
TOTAL 113
#univariate-Anova?
271

 

12463

TABLE A4.1.13 THYHOID STIMULATING HORMONE TO 1
STIMULATING HORMONE RATIO (T SHIFSH) 
BY BODY MASS INDEX, AGE, SMOKING AND DRINKING STATUS 
1990 PERFLUOFIOCHEMICAL EFFECTS STUDY. 
3M CHEMOLITE PLANT, COTTAGE GROVE, MINNESOTA

 

 

 
 

   

 

 

5

?25 40 0.30 0.20 0.34 0.00-1.00 0.30
25.30 00 0.41 0.30 0.31 0.00-2.34 0.30
,30 17 0.40 120 0.43 0.15-1.20
AGE
<31 20 0.40 0.31 0.44 0.12-1.20 F..03
31.40 40 0.40 0.40 0.35 0.00-2.34 p-.43
41.50 20 0.37 0.20 0.30 0.03-1.21
51-00 10 0.33 0.10 031 0.00-0.75
Alcohol
?102/0 00 0.30 0.20 032 .00-120 0.5.30
1.30210 10 0.50 0.54 0.30 0.15-2.34 p.02 1
missing 8 0.40 0.24 0.39 0.00-0.70 1
Tobacco
smoker . 27 0.34 1.04 0.20 0.00-0.02 F-2.30
nonsmoker 04 0.43 2.20 0.40 0.00-2.34 p-.12
missing 2 0.21 0.00 0.21 0.17020 
7. TOTAL 113 
'aTunivariate Anova
1
272 1 I

12464

TABLE A4.1.14 TESTOSTERONE T0 FOLLICLE STIMULATING
HORMONE RATIO 
BY BODY MASS INDEX. AGE. SMOKING AND DRINKING STATUS
1990 PERFLUOROCHEMICAL EFFECTS STUDY,
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

 

       

 

TFIFSH

- TESW
BMI
?25 40 4.3 255 3.5 1315.5 5.1.03
25.30 55 35 2.15 3.0 0.7-11.1 p.35
.30 17 4.0 2.55 3.1 0.5.11.3
AGE
?31 20 5.5 3.34 5.0 1.7-15.5 5.10.35
31.40 45 42 215 3.7 1.7-11.3 11-0001
41.50 25 30 1.52 2.5 0.7-5.5
51-50 13 2.2 1.37 2.0 0.7-5.3
Alcohol
410270 35 2.3 250 3.1 0.7-15.5 F..01
1.35m 19 3.5 215 3.7 1310.1 p-.91
missing 5 4.4 1.57 4.7 2.2-7.3
Tobacco
smoker 27 3.5 1.75 3.0 0.7-7.5 F.1.14
1100311101151 34 4.1 2.57 3.5 11.7-15.5 p-28
1111531119 2 2.5 0.51 2.5 22-73
TOTAL 113
#univariato Anova

273

12465

TABLE A4.1.15 BOUND TESTOSTERONE TO FOLLICLE STIMULATING
HORMONE RATIO 
BY BODY MASS INDEX. AGE. SMOKING AND DRINKING STATUS
1999 PERFLUOROCHEMICAL EFFECTS STUDY.
3M CHEMOLITE PLANT, COTTAGE GROVE, MINNESOTA

 

 

   

 

TFIF -

MEAN SD MEDIAN RANGE TEST

?25 49 155 37.3 133 39-411 F-2.99
2530 53 125 37.3 113 23-297 p-.14
.30 17 122 75.7 115 34-393
AGE .
?31 29 132 99.3 134 39-411 F-3.75
31-40 43 154 74.5 141 45-343 .
41.59 23 191 529 91 39-227
51-50 19 37 53.2 73 23-234
.Alcohol
21cm 33 133 73.5 129 23-411 5-9.9
1-3ozld 19 133 73.3 112 39-325 p.33
missing 3 173 39.3 199 32-393
Tobacco
smoker 27 130 74.4 106 39-325 ?Pu-.28
nonsmokcr 34 139 73.5 131 23-411 15-139
missing 2 72 79.9 72 57-99

1
TOTAL "3
#univariate Anova
?274

12466

TABLE A4.1.16 ESTFIADIOL TO FOLLICLE ST IMULATING HORMONE RATIO
BY BODY MASS INDEX, AGE, SMOKING AND DRINKING STATUS
1990 PEHFLUOROCHEMICAL EFFECTS STUDY.
3M CHEMOLITE PLANT COTTAGE GROVE, MINNESOTA

EIFSH

 

 

       

 

BMI
?5 4o 97 9.91 9.9 13-233 9.59
25.30 99 7.9 9.79 9.9 1.4-29.9 'p-.61
>90 17 9.3 7.94 7.9 ass-33.1
AGE
?31 29 19.9 5.99 9.9 3.1.29.9 mm
31-40 49 9.9 9.91 7.3 1433.1 9-.003
41.50 29 9.9 9.13 4.9 1929.9
51.99 19 4.9 2.27 4.9 1.9-9.3
Alcohol
419279 99 91 5.93 9.9 13-391 F-.01
1-3999 19 93 4.99 7.1 3.1-19.1 p.91
9 19.9 7.94 93 4.9.29.9
Tobacco
smoker 27 9.1 9.92 4.7 1.4.29.9 9.49
nonsmoker 94 9.5 5.99 7.9 1333.1 p-.72
missing 2 5.1 2.59 9.1 3.2-9.9
TOTAL 113
'Ttunivariate Anova

275

12467

TABLE A4.1.17 THYROID STIMULATING HORMONE TO PROLACTIN RATIO
(T SHIP) BY BODY MASS INDEX, AGE, SMOKING AND DRINKING STATUS
1990 PERFLUOROCHEMICAL EFFECTS STUDY,
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

 

 

 



MEAN SD MEDIAN RANGE TEST 
BMI
as 40 0.22 0.17 0.10 0.06-0.03 5.71
25.30 50 025 022 0.10 0.02-1.21 p.20
,30 17 0a 0.10 0.20 0.07-0.01
AGE
?31 20 0.17 0.00 0.15 0.05-0.30 5.1.30
31-40 48 0.25 023 0.17 0.02-1.21 p.25
41.50 26 020 0.10 022 0.06-0.03
51-60 10 020 0.20 0.20 0.07-0.01
Alcohol
010210 06 024 0.10 0.10 0.04-1.21 F-2.15
1-302ch 10 020 024 0.17 0.02-1.00 p-.15
missing a 021 0.00 020 0.00-0.30
Tobacco
smoker 27 0.20 0.25 021 000-121 F.1.00
nonsmoker 84 023 0.10 0.10 0.02-1.00 p.22
missing 2 0.14 0.00 0.14 0.00-0.30
TOTAL 113
#univariate Anova

276

12468

TABLE A4.1.18 FREE TESTOSTERONE TO PROLACTIN RATIO 
BY BODY MASS INDEX, AGE, SMOKING AND DRINKING STATUS
1990 PERFLUOROCHEMICAL EFFECTS STUDY.
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

 

  

  

         

 

. 519-1:

V- 5? 
BMI
225 40 2.5 1.47 2.2 0.5-7.9 5.19
25.30 59 2.9 2.13 1.9 05-150 0-.99
.30 17 21 1.12 20 0.9-4.9
AGE
?31 20 2.4 1.57 2.0 0.7-7.9 5.72
31.40 49 25 2.27 2.1 0,545.0 p.54
41.50 29 2.1 1.05 20 07-42
51-60 19 2.0 1.19 1.9 0.9-5.5
Alcohol
210210 56 2.4 1.94 2.0 0.5150 54.19
1-902/0 19 2.0 1.20 1.5 0.5-5.1 p-.37
missing a 2.9 0.75 2.7 1.5-9.9
Tobacco 
smoker 27 3.2 2.91 2.4 1.1-15.0 5.9.59
0011911101197 94 2.1 1.19 1.9 0.5-7.8 p-.003
missing. 2 2.2 2.20 2.2 0.7-3.8
TOTAL 113
Tunivan?ate Anova

277

12469

TABLE A4.1.19 BOUND TESTOSTERONE TO PROLAOTIN RATIO

BY BODY MASS INDEX. AGE. SMOKING AND DRINKING STATUS
1990 PEHFLUOFIOCHEMICAL EFFECTS STUDY,

3M OHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

 

 

 

 


MEAN SD MEDIAN RANGE 
BMI
45 40 37 43.4 82 20-221 F450
25.30 53 37 35.0 64 22-324 p.55
.30 17 33 30.1 37 23-153
AGE
d1 20 75 47.1 33 20-203 5.33
31.40 43 93 31.0 79 22-624 p.43
41.50 26 73 41.3 72 23-163
51.50 19 73 34.4 34-158
Alcohol
?0210 as 37 73.0 72 20-324 51.23
1-302/0 19 68 49.9 43 22-221 p.27
missing 8 95 20.8 100 55-117
Tobacco
smoker 27 121 122.0 04 27-024 5.11.31
nonsmoker 64 73 38.7 66 22-208 p-.001
missing 2 60 56.3 00 20-100
TOTAL "3
iunivariate Anova
278

12470

TABLE A4.1.20 ESTRADIOL TO PROLACTIN FIATIO (EIP)
BY BODY MASS INDEX, AGE. SMOKING AND DRINKING STATUS
1990 PERFLUOFIOCHEMICAL EFFECTS STUDY.
3M CHEMOLITE PLANT . COTTAGE GROVE. MINNESOTA

 

       

 

EIP
., 
BMI
<25 43 4.7 2.33 4.4 1.1-13.3 5.19
25.30 53 5.1 4.93 3.9 1.1-32.5 9-.82
.30 17 5.1 2.33 4.3 1.9-9.7
AGE
?31 23 4.2 2.23 4.1 1.1.9.3 F.1.39
31-43; 43 5.7 5.13 4.3 1.1-32.5 p.33
41.50 23 4.7 3.22 4.3 1.1-15.1
51-33 19 4.3 2.33 3.7 2.2.9.3
Alcohol
21cm 33 3.3 4.11 4.1 1.1325 5.59
1-33213 19 4.2 2.34 3.1 1.1-13.3 p-.45
missing 3 3.5 4.15 4.3 3315.1
Tobacco
smoker 27 72 3.37 5.2 1.1-325 13.12.21
nonsmoker 34 43 213 4.3 1.1-13.2 
missing 2 4.3 4.34 4.3 1.1.3.3
TOTAL 113
#univariate Anova
279



 

 

 

TABLE A4.1 .21 FOLLICLE ST IMULATING HORMONE TO PROLACTIN RATIO
(FSHIP) BY BODY MASS INDEX, AGE. SMOKING AND DRINKING STATUS
1990 PERFLUOROCHEMICAL EFFECTS STUDY.
3M CHEMOLITE PLANT, COTTAGE GROVE, MINNESOTA

 

 

 
   

    

 

- .. 

?25 40 0.72 0.51 0.57 0.2-2.1 5.22
25.30 55 0.79 0.52 0.55 0.1-2.5 .50
.30 17 0.74 0.53 0.57 02-25
AGE
?31 20 0.45 025 0.45 0.2-1.0 5541
31-40 45 0.71 0.51 0.54 0.1-2.5 p.002
41.50 25 0.55 0.50 0.73 0.2-2.1
51.50 10 1.05 0.52 051 0.2-2.5
Alcohol
<1ozld 55 0.51 0.57 0.55 02-21 15-515
1-302/0 19 0.57 0.22 0.50 0.125 p.05
8 0.06 0.31 0.60 0.2-2.6
Tobacco
smoker 27 1.00 0.57 0.75 0.3-2.5 15.7.50
nonsmokar 84 0.55 0.49 051 0.1-2.5 p.005
missing 2 0.75 0.57 0.82 0.3-1.2
TOTAL 113
#unw? ariate Anova

280

12472

TABLES OF HORMONE RATIOS BY TOTAL SERUM FLUOHIDE

281

12473

TABLE A4.2.1 HORMONE RATIOS BY TOTAL SERUM FLUORIDE:
ESTRADIOLIFREE TESTOSTERONE 
ESTRADIOLIBOUND TESTOSTRONE (EITB)

STIMULATING HORMONE (EITSH)
1990 PERFLUOROCHEMICAL EFFECTS STUDY,
3M CHEMOLITE PLANT. COTTAGE GROVE. MINNESOTA

 

 

TOTAL EITF

 

FLUORIDE

<1 23 25 1.2 2.2 3.7-5.3 5.1.35
?1-3 34 21 3.3 1.3 3.3-5.4 p..13
53-13 15 2.2 3.3 2.2 33-32
313.15 3 23 1.1 2.1 1.3-4.3
515-23 5 2.7 3.7 3 1.33.3
TOTAL 113 2.35 .32 2.1 3.7-5.4
EITB
(X100) 1.
<1 23 7.3 3.5 3.3 1.1-14.4 3.1.17 1
551-3 34 5.3 2.3 5.5 17-133 p.33
53-13 15 3.7 23 5.3 23-123
513-15 3 3.3 2.3 5.3 4311.7
515-23 5 3.3 1.3 53 4.3-3.4
TOTAL 113 3.4 2.3 5.3 1.2-14.4
arrsn
21 23 23.2 21.3 21.3 13.4-133.1 F-0.75
531-3 34 24.3 132 23.3 1.3522 3.53
53-13. 15., 23.7 13.7 21.1 33-533
513-15 3 13.3 1.3 15.3 7.3453
515-23 5 13.3 3.3 13.3 152-315
TOTAL 113 255 15.3 21.3 1.73.1331
#univariate Anova
282

12474

TABLE A4.2.2 HORMONE RATIOS BY TOTAL SERUM FLUOHIDE:
BOUND TESTOSTRONE 
BOUND STIMULATING HORMONE (TBIFSH)
BOUND (T 

FREE (TFIP)

1990 PERFLUOROCHEMICAL EFFECTS STUDY.
3M CHEMOLITE PLANT, COTTAGE GROVE, MINNESOTA

 

     

 

MEAN SD MEDIAN RANGE TEST 
TOTAL
FLUORIDE Tarn:
<1 23 36.7 6.6 37.1 16.7-62.6 64.64
?1.3 64 36.6 6.6 35.6 16.2-56.6 P-AS
53-16 15 34.5 7.6 33.3 25 6-436
?10-15 6 663 7.6 36.6 26.3-47.6
.1526 5 43.6 10.6 36.6 366-624 3.16176 >10
TOTAL 113 36.6 62 37.6 16.7-62.6 1.2.116
In. 5
TBIFSH
21 23 146.3 65.6 126.4 56.7-411.6 5.46
?1.3 64 136.6 76.3 1142 23.16477 6.61
,346 15 135.3 61.4 66.6 46.63633
.1645 6 1227 46.3 135.6 34.4.1666
615-26 5 1626 764 1435 67.1.3535
Tom. 113 136.1 77.1 126.6 23.1-411.6
TBIP
21 23 62.1 43.2 67.5 16.62655 F-.4O
?1.3 64 67.5 61.2 63.3 236-6242 9.31
.3-16 15 86.4 51.6 76.6 28.1-2242
.1645 6 51.5 27.6 52.1 22.2-89.3
?5.26 5 66.3 36.6 63.4 5133-1267
TOTAL 113 64.5 67.3 76.7 16.66242
TFIP
<1 23 2.34 1.46 2.01 .7-7.6 5.52
?1.3 64 2.36 1.67 1.66 .6156 9.72
53-10 15 2.64 1.64 2.46 66.1
>10-15 6 1.46 6.62 1.35 52.3
?15-25 5 2.26 6.61 2.16 .6-3.5
TOTAL 113 2.35 1.76 1.65 .5-15.6
#univariate Anova 
283

12475

TABLE A4.2.3 HORMONE RATIOS BY TOTAL SERUM FLUORIDE:
ESTRADIOUPROLACTIN 

THYROID STIMULATING 
FOLLICLLE STIMULATING 
HORMONE (PILH)

1990 PERFLUOROCHEMICAL EFFECTS STUDY.
3M CHEMOLITE PLANT. COTTAGE GROVE, MINNESOTA

 

 
  

    

 
 

 
 

 

TOTAL
FLUORIDE 35
1

21 23 5.34 277 4.51 145-1022 55.54 .
?1.3 54 4.75 435 3.77 109-3250 55.53 1
53-10 15 5.57 4.55 4.75 137-1759
510.15 5 3.13 1.05 3.45 1.13-4.07
515.25 5 5.55 1.50 5.17 3.11-7.09
TOTAL 113 4.57 3.94 4.05 109-3250


21 23 0.22 0.11 021 0.07?0.49 55.40
551-3 54 0.24 0.21 0.17 0.04120 p.31
53.10 15 025 0.75 0.20 0.07-0.55
510-15 5 024 0.14 0.25 0.02-0.41
515.25 5 0.29 5.03 027 020-044
Tom 113 024 020 0.19 0.02-1.20

PSI-UP
<1 23 0.55 0.47 0.50 0.15-2.55 55.59
551-3 04 0.90 0.52 0.55 0.15-2.17 p.47
53-10 15 0.57 0.55 0.57 0.15-2.55
510.15 5 0.52 0.35 0.47 0.13-1.04
515.25 5 0.55 0.35 0.47 9.33-1.13
TOTAL 113 0.75 0.52 0.50 0.13-2.55

PILH
51 23 1.71 0.55 1.54 . 0.35-3.02 5.1.72
551-3 53 1.55 1.75 1577 0.41-5.39 5.45
53-10 15 - 1.75 1.20 1.45 0.33-4.00 -
510-15 5 3.14 3.00 1.53 1.19-9.11
515-25 5 1.5 0.44 1.33 1.03-2.10
TOTAL. 112 1.57 1.25 1.52 0.35-5.11
#univariate Anova

284

12476

TABLE A4.2.4 HORMONE RATIOS BY TOTAL SERUM FLUORIDE:
HORMONE (EILH)
STIMULATING 
FOLLICLLE STIMULATING HORMONE 
1990 PERFLUOROOHEMICAL EFFECTS STUDY.

3M CHEMOLITE PLANT, COTTAGE GROVE, MINNESOTA

 

 

MEAN SD MEDIAN RANGE TEST 
TOTAL
FLUORIDE EILH
PPM 
?1 23 6.64 4.73 6.26 1.51 -1 6.61 5.32
?1.3 63 6.65 4.01 6.13 11.35-20.53 p-.45
.340 15 7.24 2.74 7.55 136-1152
.10-15 6 721 2.15 7.03 433-1027
,1 5.25 5 7.33 2.71 7.03 13.03-12.70
TOTAL 112 7.34 3.31 7.01 ass-20.53

<1 23 10.27 6.65 3.63 13633.12 5.1.00
?1.3 64 7.71 5.36 6.10 Lao-23.60 p.041
.3411 15 7.74 3.26 6.63 3.71 -1 2.42
510-15 6 6.04 4.24 6.27 30345.30
515-26 5 10.32 6.60 7.03 54621.50
TOTAL 113 3.37 5.31 6.35 Lao-33.12
FSHILH
?1 23 0.31 0.30 0.63 0.42-1.46 5.41
?1.3 63 1.04 0.44 0.34 .. 0.37-2.25 p-.73
.3-10 15 0.33 0.43 0.31 0.41-1.35
>10-15 6 1.06 0.50 1.03 0.53-1.76
315-26 5 0.91 0.35 0.99 0.55-1.40
TOTAL 112 1.00 0.41 0.34 0.37-2.25
#univariate Anova
285



 

TABLE A4.2.5 HORMONE RATIOS BY TOTAL SERUM FLUORIDE:
FREE STIMULATING HORMONE (T Ffl' SH)
BOUND STIMULATING HORMONE (T SH)
FREE HORMONE 
BOUND HORMONE 

_1 990 PERFLUOROCHEMICAL EFFECTS STUDY,
3M CHEMOLITE PLANT, COTTAGE GROVE, MINNESOTA

 

       

 

MEAN SD MEDIAN BANG 
TOTAL
FLUORIDE . TFIT SH

<1 23 12.6 8.5 9.5 41.5-35.1 F..93
5:1-3 64 12.7 75 11.1 1.7-43.7 p..45
>34 0 15 11.9 6.8 1 0.4 32-272
,1o.15 6 8.5 1.7 7.5 12.0-20.7
$15.25 5 7.5 1.9 7.9 4.6-9.6
TOTAL 113 12.1 7.5 9.9 1.7-43.7
TBIT SH
<1 23 456 330 320 170-1367 F..54
?1.3 64 479 363 370 51-2102 p-.7D
>3-1 0 15 416 270 401 95-1185
1.10.1 5 6 . 334 296 226 87-900
3.15.23 5 314 49 317 247-370
TOTAL 113 451 333 353 51-2102

<1 23 3.7 2.3 3.3 12-1 1.3 F..28
64 3.5 1.8 3.2 0.6-9.1 p-.89
53.1 15 3.3 1.0 3.3 1.2-5.6
51 0-15 5 3.1 1.33 2.89 1.4-4.6
,1 5.26 5 3.0 0.8 3.4 1.9?3.9
TOTAL 113 3.4 1.7 3.2 0.6-11.3

<1 23 127 66 125 39-298 
5:1-3 64 121 58 1 14 24-286 p-.93
,3-1 a 15 115 51 105 52-234
5:10-15 6 118 56 105 61-201
>1 5-26. 5 127 21 125 122-149
TOTAL 1 13 122.1 57.3 1 18 243-298
#univariata Anova
286

12478

TABLE A4.2.6 HORMONE RATIOS BY TOTAL SERUM FLUORIDE:
THYROID STIMULATING STIMULATING HORMONE (T 
THYROID STIMULATING HORMONE (T 
1990 PERFLUOROCHEMICAL EFFECTS STUDY,
3M CHEMOLITE PLANT, COTTAGE GROVE, MINNESOTA

 

 

 

MEAN SD MEDIAN RANGE 

TOTAL
FLUORIDE - .

mm
21 23 0.42 0.24 0.40 0.03-0.39 F-0.23
?1.3 64 0.40 0.33 029 0.06-2.34 p-.92
>3-1o 15 0.44 0.33 035 0.06?1.20 .
>10-15 6 0.49 0.26 0.49 0.19-0.30
$15.25 6 0.49 0.17 0.45 0.27-0.63
TOTAL 113 0.42 0.33 0.35 0.06-2.34



<1 23 0.36 0.22 0.33 0.03-1.00 50.23
?1.3 64 0.36 0.30 0.23 0.04-1.70 p-.92
>3-10 15 0.33 0.27 0.31 0041.1
now 6 0.46 0.19 0.43 0.22070
9.15-25 5 0.40 0.37 0.40 0.36-0.45
TOTAL 113 0.37 0.26 0.31 0.04-1.70

,1 .
<1 23 4.40 3.27 3.7 1545.6 F-.34
?1-3 64 3.77 233 3.1 .7-11.1 p.35
>3-1o 15 3.73 1.64 32 1.7-7.3
>10.15 6 3.42 1.63 3.9 .3-5.3
.1525 3.93 215 3.6 1.3-6.6
TOTAL 113 
#univariate Anova

287

.47, .

12479

 

TABLE 4.1.78 LINEAR MULTIVARIATE REGHESSION MODEL OF FACTORS
PREDICTING THE HEMAGLOBIN AMONG 111 MALE WORKERS.
3M CHEMOLITE PLANT COTTAGE GROVE, MINNESOTA

Varlaebl 6 SE 

       

 

Intercept 14.51 .67 .0001
Total Fluorine (ppm)* -.002 .0009 .02
Alcohol 
low ozlday) .22 .20 .27
nonresponse (NR) .56 .33 .09
Age (years) .001 .009 .88
(kg/m2) .01 .02 .65
Cigarettes/day .01 .007 .20
Gigs/day Fluorinez? .0003 .0001 .0005
Estradiol (pg/ml) .01 .006 .07
7:15-23 -
?square transformation oi total Meade

#Reterence category is moderate drinkers who consume 1-3 oz ethanol/day.
Interaction term between cigarettes per day and square transtonnatton of total ?uoride

 

 

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