APRIL 2019
Volume 26
Number 4

MSMR

M E D I C A L SU RV E I L L A N C E M O N T H LY R E P O RT

PAG E 2  

Modeling Lyme disease host animal habitat suitability, West Point,
New York
Sara L. Schubert, MPH; Vanessa R. Melanson, PhD

PAG E 7  

Incidence, timing, and seasonal patterns of heat illnesses during U.S.
Army basic combat training, 2014–2018
Stephen R. Barnes, MPH; John F. Ambrose PhD, MPH; Alexis L. Maule, PhD;
Julianna Kebisek, MPH; Ashleigh A. McCabe, MPH; Kiara Scatliffe, MPH;
Lanna J. Forrest, PhD, MPH; Ryan Steelman, MPH; Michael Superior, MD

PAG E 15  

Update: Heat illness, active component, U.S. Armed Forces, 2018

PAG E 21 

Update: Exertional rhabdomyolysis, active component, U.S. Armed
Forces, 2014–2018

CE/CME
PAG E 27  

Update: Exertional hyponatremia, active component, U.S. Armed
Forces, 2003–2018

A publication of the Armed Forces Health Surveillance Branch

 Modeling Lyme Disease Host Animal Habitat Suitability, West Point, New York
Sara L. Schubert, MPH (CPT, MSC, USA); Vanessa R. Melanson, PhD (LTC, MSC, USAR)

As the most frequently reported vector-borne disease among active component U.S. service members, with an incidence rate of 16 cases per 100,000
person-years in 2011, Lyme disease poses both a challenge to healthcare providers in the Military Health System and a threat to military readiness. Spread
through the bite of an infected blacklegged tick, infection with the bacterial
cause of Lyme disease can have lasting effects that may lead to medical discharge from the military. The U.S. Military Academy at West Point is situated in a highly endemic area in New York State. To identify probable areas
where West Point cadets as well as active duty service members stationed at
West Point and their families might contract Lyme disease, this study used
Geographic Information System mapping methods and remote sensing data
to replicate an established spatial model to identify the likely habitat of a key
host animal—the white-tailed deer.

L

yme disease (LD) is the most frequently reported vector-borne disease in the U.S., with over 36,429
confirmed and probable cases in 2016.1
The vast majority of LD cases are reported
from 14 states in the Northeast and Upper
Midwest.2 New York State alone accounted
for 11.4% and 10.0% of confirmed cases
nationally in 2015 and 2016, respectively.3
Moreover, Southeastern NY—an area
that includes the U.S. Military Academy
(USMA) at West Point that is home to over
4,400 cadets and 4,200 active duty service
members (ADSMs) and their families—has
the highest burden of LD (Figure 1). One
study reported that ticks in Southeastern
NY had infection rates as high as 55% for
the bacterial cause of LD.4
In the past few years, LD has resulted
in the removal of at least 2 cadets from
the USMA because of medical ineligibility
for commissioning. In addition, 2 recently
commissioned Second Lieutenants have
been discharged from the Army because
of medical issues as a result of chronic
LD. Further research on the prevalence
of LD at West Point as well as the diagnostic accuracy of techniques employed
there is ongoing. Results of these studies
may increase the need for identification of
 Page

2

high-risk areas within the reservation and
the surrounding area.
Cases of LD in humans are a result of
several factors (e.g., vectors and reservoir
hosts) that facilitate the transmission of the
causative bacterium (Borrelia burgdorferi)
to humans. The most common vector of B.
burgdorferi in the Northeastern U.S. is Ixodes
scapularis, commonly known as the blacklegged tick or deer tick.5 While Ixodes spp
larvae and nymphs prefer small mammalian hosts, including the white-footed mouse
(a competent reservoir for B. burgdorferi),6,7
adult ticks prefer white-tailed deer (a less
competent host of this bacterium).8,9
There are few methods to determine
tick density in a given area. One common
method, tick dragging, was used at West
Point in 2016 and showed that B. burgdorferiinfected ticks were found in both military
family housing neighborhoods and cadet
training areas. (The housing area for cadets
was not tested since it consisted of impervious surfaces and thus was not a likely tick
habitat).10 While tick dragging can locate B.
burgdorferi-infected ticks, this technique is
limited by its time intensive nature, the difficulty in finding and extracting the small tick
larvae and nymphs from the drag cloth, and
its susceptibility to weather and temperature

WHAT ARE THE NEW FINDINGS?
This study used an established spatial analysis method to determine likely high-risk areas
for contracting Lyme disease from ticks
(Ixodes scapularis) near West Point, NY.
Urban population centers in this area have
lower habitat suitability values for white-tailed
deer, the tick’s host, while rural areas and
military training grounds have higher suitability values.

WHAT IS THE IMPAC T ON
R E AD INE S S AND FO RC E HE ALTH
PROTECTION?
Lyme disease, if not diagnosed early, can
result in post-treatment Lyme disease
syndrome (PTLDS). The symptoms resulting
from Lyme disease and possible PTLDS may
render service members non-deployable and
may result in medical separations from service. Military bases in endemic areas need
to increase awareness of the local Lyme disease threat and facilitate the implementation
of superior tick bite prevention measures.

conditions.11 These limitations of tick dragging demonstrate the need for improved tick
habitat prediction.
To address these limitations, some studies have used spatial analysis and predictive
modeling for LD vectors and have focused
on a variety of variables including soil type,
vegetation, small mammal abundance, temperature, humidity, geology, and predator
abundance.8,12–16 However, these studies have
produced conflicting results, which may be
due to confounding effects of various geographic factors, including inconsistencies
such as a positive correlation between tick
abundance and precipitation in areas with
soils that drain quickly (such as sand) and
a negative correlation between tick abundance and precipitation in areas with soils
that drain slowly (such as clay).5 Studies of
tick tree preferences also have demonstrated
inconsistent findings.12,17 Thus, it is difficult
to pinpoint the environmental preferences of
I. scapularis without the implementation of
a control habitat and/or standardization of
data capture across multiple studies.
MSMR  Vol. 26  No. 04  April 2019

 Figure 1. Lyme disease cases by county, 2016a

F I G U R E 1 . Lyme disease cases by county, New York State, 2016a

points, lines, and polygons); these data
were publically available for the contiguous
U.S. at a scale of 1:24,000 or better.24 Data
needed to calculate the slope of the terrain were obtained from USGS’s National
Elevation Dataset in raster form (i.e., representation as a surface divided into a grid of
cells) with a resolution of approximately 10
meters (one-third arc-second).25

Data processing and analysis

Author: Sara Schubert, 30 September 2018 Coordinate System: GCS WGS 1984. Reference: Centers for Disease
Control and Prevention. Lyme Disease 2017, https://www.cdc.gov/lyme/stats/index.html.
a

a

Author: Sara Schubert, 30 September 2018 Coordinate System: GCS WGS 1984. Reference: Centers for Disease Control and Prevention.
Lyme Disease 2017, https://www.cdc.gov/lyme/stats/index.html.

Some studies also have focused on host
animal habitats in order to estimate the spatial
distribution of I. scapularis. Results of studies
regarding the importance of host animals in
LD and I. scapularis ecology are mixed.18,19
However, studies agree that deer are an
important part of the ecology and contribute
to the continued spread of this disease.17,20
In light of this, Chen et al. used Geographic
Information System (GIS) mapping methods
combined with spatial analysis techniques to
create a habitat suitability model for whitetailed deer in Ontario, Canada.9 The results
of this study demonstrated that high suitability areas for white-tailed deer corresponded
with high tick abundance.9
At the time of this report, no studies have examined white-tailed deer habitat
suitability at West Point. The current study
addresses this gap by using open data in a
model similar to that employed by Chen
et al. to identify the LD risk for West Point
cadets, ADSMs, and their families.

METHODS

Study area
The USMA at West Point is located in
Orange County, which is situated on the
April 2019   Vol. 26  No. 04  MSMR 

Hudson River in upstate NY. This area is
semi-rural, heavily wooded, and relatively
mountainous, with the highest peak rising
1,664 feet above the Hudson River.21

Data sources
To determine the most likely geographic distribution of blacklegged ticks
and the resulting areas of potentially high
LD prevalence, Chen and colleagues’ model
for deer habitat suitability was replicated
using open data for Orange County. The
model sought to determine where deer have
the best access to shelter (i.e., land cover and
terrain slope), food (i.e., vegetation type),
water, diversity of land cover, and proximity to urban areas and roads (i.e., suitability criteria). Data on vegetation and land
use patterns were obtained from the U.S.
Geological Survey’s (USGS’s) National Gap
Analysis Project (GAP) Land Cover dataset, which represents vegetation and land
use patterns for the continental U.S. derived
from 1999–2001 Landsat Thematic Mapper satellite imagery.22 Data on all roads
in Orange County were obtained from
the Orange County GIS Division.23 Water
body data were obtained from the USGS’s
National Hydrography Dataset in the form
of a vector dataset (i.e., representation using

To transform the 4 datasets outlined
above into a single habitat suitability layer,
each dataset was reclassified using a scale
from 1 (less suitable) to 5 (most suitable)
using ArcGIS Pro software, version 2.1.2
(2018, ESRI, Redlands, CA). The 7 suitability criteria used in the analysis are shown in
Table 1.
To determine the suitability of the vegetation for the shelter and food layers, the
original GAP land cover values were reclassified to the coordinating suitability values
from Chen and colleagues’ model.9 These
values are presented in Table 2. The terrain
slope also contributed to shelter suitability.
Relatively flat areas were classified as most
suitable, while steeper slopes were classified as less suitable. Chen and colleagues’
analysis used a maximum distance of 1 mile
to water for a suitability rating of 5; however, because of the abundance of water in
Orange County, a maximum distance of 1
mile from a water body covered over 95% of
the county. To better determine suitability,
distances of 0.5 miles, 1 mile, and 1.5 miles
were used to create the buffers. Similarly,
multiple ring buffers were used for roads
and urban areas. To determine the diversity
of the land cover, the ArcGIS Pro focal statistics tool was used to determine the variety
of cells within a circle with a 0.5 mile radius;
resulting values were reclassified to the 1 to
5 suitability values, with higher vegetative
diversity receiving a value of 5. Once each
dataset layer was reclassified to the appropriate suitability values, vector data were
converted to raster in order to calculate the
suitability layer. These layers were then combined using a weighted sum to create 1 layer
with an overall habitat suitability as follows:
habitat suitability = land cover (shelter) *
0.148 + terrain slope (shelter) * 0.074 + vegetation (food) * 0.220 + proximity to water
Page 3

 TA B L E 1 . Chen et al.9 model adapted for predicting deer habitat suitability in Orange

County, NY
Criterion
(weight)
Shelter/
land cover
(4/27)

Shelter/
terrain slope
(2/27)

Food
(2/9)
Proximity
to water
(2/9)

Diversity of
land cover
(1/6)

Proximity to
urban areas
(1/12)

Proximity to
roads (speed
limit >30 mph)
(1/12)

Measurement

Data source

GIS data
processing

Original value

Suitability
valuea

Type of
vegetation

GAP land
cover22

Reclassify

38–584

See Table 2

13.41–20.89

1

8.44–13.41

2

5.02–8.44

3

2.36–5.02

4

0–2.36

5

Degrees

National
Elevation
Dataset25

Reclassify

Type of
vegetation

GAP land
cover22

Reclassify

38–584

See Table 2

USGS
hydrography,
water body24

Reclassify,
multiple ring
buffer

1–1.5 miles

3

Miles

0.6–1 miles

4

0–0.5 miles

5

7

1

12

2

16

3

19

4

Variety of
vegetation

Miles

Miles

GAP land
cover22

GAP land
cover22

Reclassify,
focal statistics
(variety)

Reclassify,
extract urban
areas, buffer

Reclassify,
Orange County extract major
roads23
roads, multiple
ring buffer

27

5

0–0.8

1

0.8–1.6

2

1.6–2.4

3

2.4–3.1

4

>3.1

5

0–0.8

1

0.8–1.6

2

1.6–2.4

3

2.4–3.1

4

>3.1

5

Scale: 1 (less suitable) to 5 (most suitable)
GIS, Geographic Information System; GAP, Gap Analysis Project; USGS, U.S. Geological Survey; mph, miles per hour
a

* 0.220 + diversity of land cover (shelter) *
0.167 + proximity to urban areas * 0.083 +
proximity to roads * 0.083.
R E SULT S
Figure 2 shows the map resulting from
the final suitability analysis for white-tailed
deer habitats within Orange County. Areas
in shades of yellow and green are less suitable for deer and, as a result, are less likely
to be areas where humans will contract LD.
Conversely, areas in orange and red are more
suitable habitats for white-tailed deer and are
 Page

4

presumably areas where humans are more
likely to encounter the blacklegged tick and
contract LD. Areas around the cities of Newburgh, Middletown, and Monroe appear to
be primarily green (unsuitable deer habitat). Urban population centers with reduced
green space, increased density of roads, and
continuous vehicular traffic offer reduced
food and shelter for white-tailed deer, resulting in lower suitability values. Because water
is prevalent throughout Orange County,
its effect on habitat suitability was not pronounced. There were few areas further than
1.5 miles from a water body, which resulted
in the entire county having suitability values that ranged between 2 and 4. The large

uniform yellow area to the southwest of
Goshen stands out from the uneven texture of the rest of the county. This area contains the Wallkill River and large stretches of
cropland, which is only moderately suitable
for deer given the shelter suitability value of
3. Additionally, Highway 26 runs the length
of this section, keeping suitability values relatively low overall.
The pixel size for GAP land cover data
is 30 meters, which makes it difficult to look
specifically at West Point within Orange
County (Figure 2). However, zooming in on
this portion of the map reveals that the training areas, where cadets spend the majority
of their summers, contain several habitats
with medium to high suitability for whitetailed deer. The main garrison, located in
the northeast portion of the reservation, is
primarily green and yellow (low suitability).
This region is where cadets spend the majority of their time during the academic year
and also where ADSMs and family members reside.
EDITORIAL COMMENT

As the most frequently reported vectorborne disease in the U.S., with an incidence
rate of 16 cases per 100,000 person-years
among active component service members in 2011, LD poses both a challenge to
healthcare providers in the Military Health
System and a threat to military readiness.26
LD, if not diagnosed early, can result in
post-treatment LD syndrome (PTLDS). The
symptoms resulting from LD and possible
PTLDS may render service members nondeployable and may result in medical separations from service.
Research focused specifically on LD
among ADSMs and their families on military
reservations has found that family members
were affected at a higher rate than service
members.27 Analysis of the U.S. Army’s Public Health Command Human Tick Test Kit
Program data revealed a similar finding that
only 23% of the ticks submitted to the program were removed from ADSMs.28 Additionally, this study demonstrated that the
crude overall incidence of LD increased
with both age and rank. The positive correlation between LD incidence and age is also
MSMR  Vol. 26  No. 04  April 2019

 TA B L E 2 . Vegetation reclassification table for alignment with Chen et al.'s9 model
Original value
(GAP land cover)

Land cover description

Shelter suitability
valuea

Food suitability
valuea

38

Ruderal forest

5

3

64

Oak/chestnut forest

5

3

78

Hickory forest & woodland

5

3

90

Managed tree plantation

4

3

91

Northern native ruderal forest

4

3

95

Hemlock—hardwood forest

5

4

98

Northern hardwoods forest

5

4

99

Oak forest

5

4

100

White pine forest

5

4

Silver maple forest

3

3

204

Silver maple forest—green ash

2

3

207

Alkaline swamp systems

2

2

208

Swamp forests

2

2

341

Pitch pine barrens

5

2

553

Barren

2

2

556

Cultivated cropland

3

5

557

Pasture & hay field crop

3

5

558

Annual grassland

3

4

561

Shrub

3

5

562

Wetland vegetation

2

2

563

Upland vegetation—treed

4

4

567

Grass/forb regeneration

3

4

568

Shrub regeneration

3

5

575

Disturbed shrub regeneration

3

4

579

Open water

1

1

Developed & urban

1

2

High-intensity developed & urban

1

1

197–199

581–583
584

Scale 1 (less suitable) to 5 (most suitable)
GAP, Gap Analysis Project
a

seen in the civilian population.29 However,
the association of higher incidence with
higher rank seems contrary to the assumption that spending greater amounts of time
outdoors escalates the risk for LD and other
tick-borne diseases.20 This discrepancy may
be due, at least in part, to an assumption that
LD is primarily contracted peridomestically
(around human habitations). This assumption is not unique to military-specific studies and is generally difficult to confirm
without additional data from patients.5,20,30
Socio-cultural factors also may explain this
discrepancy. ADSMs are provided a uniform
treated with permethrin and are ordinarily
instructed on vector-control measures, such
as tucking pants into boots and conducting
tick checks.7,27,31 These public health prevention measures may assist in decreasing LD
cases among ADSMs; however, additional
April 2019   Vol. 26  No. 04  MSMR 

data are needed to determine the effectiveness of these measures.
The finding of low suitability around
the main garrison is contradictory to the
assumption that LD is primarily contracted
near domestic areas; however, as noted in
other peridomestic studies, further research
examining human behavior in conjunction
with ecologic risk is warranted.20 Higher resolution land cover data for the entire West
Point reservation could increase the accuracy of predicting deer habitat and allow for
improved identification of areas where the
risk of exposure to LD-infected ticks is high.
There are important limitations to consider when interpreting the results of the
current study. First, because the cell resolution (30 meters) of the dataset employed in
the analysis was so much greater than the
minimum mapping unit area (1 acre), some

generalization of land cover was required,
which may have created bias within the
analysis where vegetation patches were too
small to be properly coded. However, this
bias is most likely non-differential since
both suitable and non-suitable deer habitats
were equally likely to be missed during the
aggregation. Second, the current study did
not incorporate information on deer density
or density of B. burgdorferi-positive I. scapularis on the military reservation. Identifying an association between the deer habitat
suitability values and deer and/or tick density would have suggested that the habitat
and environmental conditions of the whitetailed deer may also impact the abundance
of the tick.
While the current spatial analysis did
not provide a high-resolution mapping of
habitat suitability for deer within the West
Point reservation, the lower resolution map
did provide some insight into variations in
habitat suitability for deer (the I. scapularis
host) within and around the reservation, an
area of high LD prevalence. Further analysis of where LD cases acquire their tick bites
could enhance the spatial analysis method
used here. Moreover, the analysis method
could be used to generate maps of deer habitat suitability in other counties or parts of
the country. All of the data for this study
were publicly accessible, with the majority available on a national level, making this
type of suitability map easy to generate for
various areas within the U.S. These maps
may then be used to increase awareness of
LD, the factors leading to this disease, and
the proper prevention techniques, including vector control and preventive measures.
When combined with higher spatial resolution data, this mapping method could
provide the more detailed spatial analysis
necessary for better implementation of vector control programs and targeted promotion of LD awareness and prevention.
Author affiliations: Keller Army Community
Hospital, West Point, NY (CPT Schubert);
Keck School of Medicine, University of Southern California (CPT Schubert); U.S. Military
Academy, West Point, NY (LTC Melanson);
U.S. Army Medical Research Institute of
Infectious Diseases, Fort Detrick, MD (LTC
Melanson)
Page 5

 F I G U R E 2 . White-tailed deer habitat suitability map, Orange County, NY

Ackowledgment: The authors thank Jennifer
Moore Bernstein (PhD), Lecturer, Spatial Sciences Institute, University of Southern California Dornsife College of Letters, Arts and
Sciences for her review of the initial spatial
analysis. They also thank LTC Jason Barnhill,
Academy Professor in the Chemistry and Life
Science Department of U.S. Military Academy, West Point, for introducing and inspiring them to pursue tick-related research.
Disclaimer: The contents, views, or opinions
expressed in this publication are those of the
author(s) and do not necessarily reflect the
official policy or position of the Department of
Defense (DoD) or the Department of the Army.
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2006;31(2):364–370.
31. Connally NP, Durante AJ, Yousey-Hindes
KM, Meek JI, Nelson RS, Heimer R. Peridomestic Lyme disease prevention: results of a population-based case–control study. Am J Prev Med.
2009;37(3):201–206.

MSMR  Vol. 26  No. 04  April 2019

 Incidence, Timing, and Seasonal Patterns of Heat Illnesses During U.S. Army Basic
Combat Training, 2014–2018
Stephen R. Barnes, MPH; John F. Ambrose PhD, MPH; Alexis L. Maule, PhD; Julianna Kebisek, MPH; Ashleigh A. McCabe, MPH; Kiara
Scatliffe, MPH; Lanna J. Forrest, PhD, MPH; Ryan Steelman, MPH; Michael Superior, MD (LTC, MC, USA)

Risk factors for heat illnesses (HIs) among new soldiers include exercise
intensity, environmental conditions at the time of exercise, a high body mass
index, and conducting initial entry training during hot and humid weather
when recruits are not yet acclimated to physical exertion in heat. This study
used data from the Defense Health Agency’s–Weather-Related Injury Repository to calculate rates and to describe the incidence, timing, and geographic
distribution of HIs among soldiers during U.S. Army basic combat training
(BCT). From 2014 through 2018, HI events occurred in 1,210 trainees during
BCT, resulting in an overall rate of 3.6 per 10,000 BCT person-weeks (p-wks)
(95% CI: 3.4–3.8). HI rates (cases per 10,000 BCT p-wks) varied among the
4 Army BCT sites: Fort Benning, GA (6.8); Fort Jackson, SC (4.4); Fort Sill,
OK (1.8); and Fort Leonard Wood, MO (1.7). Although the highest rates of
HIs occurred at Fort Benning, recruits in all geographic areas were at risk.
The highest rates of HI occurred during the peak training months of June
through September, and over half of all HI cases affected soldiers during the
first 3 weeks of BCT. Prevention of HI among BCT soldiers requires relevant
training of both recruits and cadre as well as the implementation of effective
preventive measures.

U

.S. military training activities in
hot and humid environments
pose competing demands from
a public health perspective because of the
military’s obligation to perform realistic
training to develop operational capability
and readiness while also needing to protect
service members against heat-related illness. For example, a recent study examining the risk and timing of heat illness (HI)
in the U.S. active duty (AD) Army population demonstrated that the peak incidence
of HI occurs during the first 2 months of
duty.1 This period is when soldiers are
engaged in initial entry training (IET). IET
encompasses a variety of courses, each with
unique exposures that may affect the risk
of HI.
IET consists of 2 phases: basic combat
training (BCT) and advanced individual
training (AIT). BCT, which lasts 10 weeks,
April 2019   Vol. 26  No. 04  MSMR 

is followed by AIT, which varies from 5
to over 20 weeks, depending on military
occupational specialty.2 In one station unit
training (OSUT), BCT and AIT take place
at the same installation. The 10-week BCT
course is conducted at 4 locations: Fort
Benning, GA; Fort Jackson, SC; Fort Leonard Wood, MO; and Fort Sill, OK. Figure 1
provides a summary timeline view of the
IET process. This study only includes the
10-week period of BCT (i.e., recruits participating in BCT as a part of OSUT were
excluded).
No recently published studies have
reported HI rates during BCT. The current study assessed the incidence, timing,
and geographic distribution of HI during
BCT. Information about the timing and
geographic location of HI in this population could inform efforts to reduce the burden of HI during the conduct of training

WHAT ARE THE NEW FINDINGS?
During 2014–2018 BCT classes, the greatest number of HIs occurred in week 2. The
highest overall rate of HI was at Fort Benning
(6.8 cases per 10,000 p-wks), followed by
Fort Jackson (4.5 per 10,000 p-wks), Fort
Sill (1.8 per 10,000 p-wks), and Fort Leonard
Wood (1.7 per 10,000 p-wks).

WHAT IS THE IMPAC T ON
R E AD INE S S AND FO RC E HE ALTH
PROTECTION?
Service members experience the highest
rates of HIs during the first phase of BCT.
Entry month should be considered as a
modifiable factor to reduce HI rates during
training. The findings of this analysis may
inform Commanders at each training location
about the time of year that targeted mitigation strategies could be most effective.

essential to the development of individual
skills needed for operational capability and
readiness of the U.S. Army.

METHODS

Study design
The current study employed a retrospective cohort design using data from the
Defense Health Agency’s (DHA)–WeatherRelated Injury Repository (WRIR). The
WRIR utilizes many available data sources
with the goal of being the most complete
record system possible for weather-related
injuries in Army soldiers. The WRIR
enables researchers to review prior years’
data and provides contextual perspective
to emerging trends. The WRIR includes
Page 7

 Globalview
viewofofthe
theU.S.
U.S.
Army
initial
entry
training
process
F I GFigure
U R E 1 .1.Global
Army
initial
entry
training
process
Advanced individual
training

Basic combat
training

5−20 weeks

10 weeks

New
recruits

Reception
battalion

First duty
station

3−7 days

One station unit training
13−20+ weeks

6 main data sources: hospital admissions
(from the Standard Inpatient Data Record
[SIDR] and from TRICARE Encounter
Data–Institutional [TED-I]), in-theater
medical records (from the Theater Medical
Data Store [TMDS]), reportable medical
events (RMEs), and outpatient encounters
(from the Comprehensive Ambulatory/
Professional Encounter Record  [CAPER]
and from TRICARE Encounter Data–NonInstitutional [TED-NI]). The WRIR began
collecting data in 2014, so it includes International Classification of Diseases (ICD)
codes from both the 9th and 10th revisions.

Study population
All U.S. Army enlisted soldiers who
began BCT for the first time at any of the
4 BCT sites from January 2014 through
December 2018 were included in the analysis. In order to better compare variables of
interest in the training population, recruits
conducting BCT as part of OSUT were
excluded from the analysis. BCT rosters
from 2014–2018 were downloaded from
the Army Training Requirements and
Resources System (ATRRS). Each BCT site
has a unique school code, which was used
to pull the data from ATRRS.

Outcome
The outcome of interest was the occurrence of any HI. For this analysis, the identification of a case of HI was based on the
 Page

8

Armed Forces Health Surveillance Branch
(AFHSB) surveillance case definition and
included heat exhaustion (HE) and heat
stroke (HS).3 The AFHSB case definition
defines a case of HI as 1 hospitalization or
outpatient medical encounter with selected
diagnoses of HI (Table 1) in the primary or
secondary diagnostic position or 1 record
of an RME of HI reported to the Disease
Reporting System internet.4
The incidence date was the date of the
first hospitalization, outpatient encounter,
or RME associated with an HI. For individuals with more than 1 type of HI medical encounter during BCT, HS is prioritized
over HE. Outcome data extracted from the
WRIR were matched to ATRRS BCT roster
data by social security number. Cases were
included in the analysis only if the first
encounter date fell between a recruit’s first
and last day of class in BCT.

Basic combat training exposure time and
seasonality
Army BCT is conducted throughout
the year and includes the following 3 phases:
Red phase (phase 1; weeks 1–3): The
red phase consists of an environment
where recruits must demonstrate that they
possess the foundation for physical fitness,
resiliency, and a level of adaptability to
military life. Strenuous outdoor activities
with an overlapping risk of heat exposure
include 2.5- and 5-mile foot marches.

White phase (phase 2; weeks 4–6): The
white phase is centered on the development
of basic combat skills, with special emphasis on weapons qualification and physical readiness training. Strenuous outdoor
activities with an overlapping risk of heat
exposure include a 7.5-mile foot march,
land navigation exercises, and time spent at
rifle ranges.
Blue phase (phase 3; weeks 7–10): The
blue phase includes a 10-mile foot march
and concentrates on tactical training,
increased soldier responsibilities, and demonstration of teamwork and self-discipline.
Recruits are evaluated in basic soldiering
skills and prepared for AIT. The blue phase
culminates in a field training exercise and
the demonstration of proficiency in warrior
tasks and battle drills.
Recruit exposure time was measured
using a time-to-event approach (measured in weeks). For each recruit, exposure
time began at the BCT class starting date
and continued until censored because of
an outcome event (an HI), attrition from
BCT, or the end of the BCT class, whichever occurred first. Censoring due to attrition was identified by the graduation status
variable from ATRRS.
Because BCT classes begin throughout the calendar year, each BCT class experiences unique month-to-month variation
in weather-related exposures due to interannual seasonal variation. In order to control for the effect of this variation, data were
MSMR  Vol. 26  No. 04  April 2019

 TA B L E 1. ICD-9/ICD-10 codes used in the heat illness case definition
Condition

ICD-9

ICD-10a

Heat stroke

992.0 (heat stroke and sunstroke)

T67.0 (heatstroke and sunstroke)
T67.0* [A,D,S] (initial, subsequent, or
sequela encounter)

Heat exhaustion 992.3 (heat exhaustion, anhydrotic)

T67.3* [A,D,S] (initial, subsequent, or
sequela encounter)

Statistical analysis

992.4 (salt depletion)

R E SULT S

A total of 352,739 recruits entered BCT
for the first time during 2014–2018 and
were included in the current study (Table 2).
Although total annual recruit arrivals varied from year-to-year, the distribution of
recruit arrivals by month remained consistent, with an average low of approximately
4,500 recruit arrivals in January to an average high of 9,000 recruit arrivals in June
(data not shown). As a result of high school
graduation, there is a predictable surge of
new and younger recruits entering BCT
during the summer months (Figure 2). The
BCT population was observed for a total
of 3,362,271 p-wks. The mean observed
time per recruit was 9.5 weeks (median,
9.7; standard deviation, 0.95; range, 0–10
April 2019   Vol. 26  No. 04  MSMR 

T67.4 (heat exhaustion due to salt
depletion)
T67.4* [A,D,S] (initial, subsequent, or
sequela encounter)

992.5 (heat exhaustion, unspecified)

T67.5 (heat exhaustion, unspecified)

An asterisk (*) indicates that any subsequent digit/character is included.
ICD, International Classification of Diseases
a

F I G U R E 2. Cumulative numbers and mean ages, by entry month of basic combat training,
U.S. Army recruits, 2014–2018
50,000
No. new recruits starting basic combat training (solid line)

Descriptive analyses included chisquare tests for differences in the outcome
frequency distributions by BCT entrymonth and site. For BCT site and phasespecific rates, the frequency distribution
of outcomes was reported by entry-month
and site. Site- and phase-specific incidence
rates of HI were calculated as the number of HI cases per 10,000 person-weeks
(p-wks) with associated 95% confidence
interval (CIs). Rate ratios (RRs) were computed by BCT site and entry-month using
Fort Leonard Wood as the reference group
because of its northernmost location.
Because of low case counts at Fort Leonard
Wood during the fall and winter months,
RRs are reported for spring and summer
months only. P values less than .05 were
considered statistically significant. Exact
RR estimates, 95% CIs, and mid-p values
were calculated using OpenEpi v3.01.5

T67.3 (heat exhaustion, anhydrotic)

26

45,000

25

40,000
24

35,000
30,000

23

25,000
22

20,000
15,000

21

Mean age of recruits (dotted line)

analyzed by BCT phase and grouped by the
month in which recruits started BCT. A
recruit was considered to have entered BCT
in a given month if their class start date
fell within the first 20 days of the month.
Recruits whose BCT started on or after the
21st day of a given month were considered
to have entered training in the following
month.

10,000
20

5,000
0

No., number

Jan Feb Mar Apr May Jun

Jul Aug Sep Oct Nov Dec

19

Entry month

weeks) (data not shown). A total of 9,159 HIs
were reported in the WRIR during the study
period among all AD Army service members, of which 13.2% (n=1,210) occurred
during BCT. The proportion of recruits
without any HI who successfully graduated

BCT was 90.0% (n=316,205/351,529) compared to 66.9% (n=809/1,210) of those who
were diagnosed with an HI (data not shown).
During the 5-year surveillance period, July
had the highest total number (n=327) and
proportion (27.0%) of HI cases (Figure 3).
Page 9

 TA B L E 2 . Demographic characteristics of basic combat training population (n=352,739)

with results of chi-square tests comparing those with and without a heat illness, U.S.
Army recruits, 2014–2018
Heat illness (%)

All recruits
(n=352,739)
Sex

Yes
(n=1,210)

No
(n=351,625)

N

%

N

%

N

%

263,891

74.8

674

55.7

263,217

74.9

88,848

25.2

536

44.3

88,312

25.1

Non-Hispanic white

232,499

65.9

721

59.6

231,753

65.9

Non-Hispanic black

94,582

26.8

416

34.4

94,159

26.8

Hispanic

22,001

6.2

62

5.1

21,932

6.2

2,824

0.8

8

0.7

2,816

0.8

833

0.2

3

0.2

869

0.2

17–19

46,286

13.1

242

20.0

46,044

13.1

20–22

137,624

39.0

585

48.3

137,039

39.0

23–25

90,777

25.7

234

19.3

90,543

25.8

25+

78,052

22.1

149

12.3

77,903

22.2

Male
Female

p-value

<.001

Race/ethnicity

Asian/Pacific Islander
Other/unknown

<.001

Age group (years)

Mean age
(SD)

23.2
(3.9)

22.0
(3.3)

<.001

23.3
(3.9)

Basic combat training phase

Service
Active duty

201,839

57.2

654

54.0

201,185

57.2

National Guard

100,380

28.5

372

30.7

100,008

28.4

50,520

14.3

184

15.2

50,336

14.3

E1

201,897

57.2

752

62.1

201,145

57.2

E2

82,164

23.3

326

26.9

81,838

23.3

E3

39,303

11.1

91

7.5

39,212

11.2

E4

28,662

8.1

41

3.4

28,621

8.1

713

0.2

0

-

713

0.2

Reserve

<.001

Rank

>E5

<.001

Training location
Fort Jackson

185,196

52.5

780

64.5

184,416

52.5

Fort Sill

77,093

21.9

131

10.8

76,962

21.9

Fort Leonard Wood

59,124

16.8

94

7.8

59,030

16.8

Fort Benning

31,326

8.9

205

16.9

31,121

8.9

<.001

SD, standard deviation

The demographic characteristics of
all recruits and those affected by an HI are
shown in Table 2. The rates of HI events
were significantly higher among several
demographic groups (Table 3). The HI rate
was higher among women than men (RR:
2.3) and higher among non-Hispanic black
recruits than those in all other race/ethnicity groups. Recruits aged 20 years or older
 Page

10

sites, with the highest rate at Fort Benning (6.8 per 10,000 p-wks), followed by
Fort Jackson (4.5 per 10,000 p-wks), Fort
Sill (1.8 per 10,000 p-wks), and Fort Leonard Wood (1.7 per 10,000 p-wks) (Table 4).
Further, recruits who received BCT at Fort
Benning had 4.1 (95% CI: 3.2–5.2) times
the rate of HI events compared to recruits
who received BCT at Fort Leonard Wood.
The rate of HI events among Fort Jackson
recruits was 2.7 times the rate among Fort
Leonard Wood recruits. After controlling
for the entry month of BCT, recruits at both
Fort Benning and Fort Jackson experienced
HI rates that were between 1.9 and 10.3
times the rates among recruits at Fort Leonard Wood for the months of May–August
(Table 5). For example, among recruits who
started in August, those at Fort Benning
experienced 5.9 (95% CI: 3.4–11.2) times
the rate of HI events compared to recruits
at Fort Leonard Wood.

were less likely than those aged 17–19 years
to be affected by an HI. Soldiers in the
National Guard had slightly increased rates
(RR: 1.1) compared to soldiers in the AD
component.

Basic combat training location
Incident HIs were disproportionately
distributed among the individual BCT

Of the 1,210 total HIs that occurred
during BCT, 686 (56.8%) occurred during
phase 1 of training, 277 (22.9%) occurred
during phase 2, and 247 (20.4%) occurred
during phase 3 (data not shown). The greatest number of incident HI cases occurred
in the second week of training (Figure 4),
when 23.0% of all HI events occurred (data
not shown). In unadjusted analyses, phase 1
of BCT had the highest HI rates at all BCT
sites, with 6.5 cases per 10,000 p-wks, followed by phases 2 and 3 with 2.0 and 1.8
cases per 10,000 p-wks, respectively (data
not shown). Entering BCT after May was
associated with a substantial increase in
phase 1 rates and a small reduction in
phase 3 rates (Figure 5). After controlling
for location, phase, and entry-month, rates
varied widely (Table 6). The highest phase
1 rate was 27.1 HIs per 10,000 p-wks for
recruits who entered BCT in June at Fort
Benning. At Fort Leonard Wood, the highest phase 1 rates were also seen among
recruits who entered BCT in June (10.8 per
10,000 p-wks). On the other hand, phase 1
rates at Fort Sill peaked at 9.7 per 10,000
p-wks for those who entered in August, and
phase 1 rates at Fort Jackson peaked at 17.7
per 10,000 p-wks for those who entered in
July (Table 6).
MSMR  Vol. 26  No. 04  April 2019

 F I G U R E 3 . Basic combat training heat illnesses, by month and location, U.S. Army recruits,
2014–2018

EDITORIAL COMMENT

350
300

No. cases

250
200
150
100
50
0

Fort Leonard Wood
Fort Sill
Fort Benning
Fort Jackson

Jan
0
0
0
3

Feb
1
1
1
4

Mar
0
2
5
5

Apr
0
2
4
27

May
1
7
23
66

Jun
38
15
42
161

Jul
27
46
39
215

Aug
23
45
50
189

Sep
3
12
31
83

Oct
1
1
6
23

Nov
0
0
4
3

Dec
0
0
0
1

No., number

TA B L E 3 . Heat illness rates and rate ratios, by demographic and military characteristics,
U.S. Army recruits, 2014–2018
Crude HI ratea

Rate ratio

95% CI

p-value

Sex
Male

2.7

ref

-

-

Female

6.4

2.3

(2.1–2.6)

<.001

Race/ethnicity
Non-Hispanic white

3.3

ref

-

-

Non-Hispanic black

4.6

1.4

(1.2–1.6)

<.001

Hispanic

2.9

0.8

(0.6–1.1)

.425

Asian/Pacific Islander

3.0

0.9

(0.4–1.8)

.799

Other/unknown

3.8

1.1

(0.3–3.5)

.802

Age group (years)
17–19

5.5

ref

-

-

20–22

4.5

0.8

(0.6–0.9)

.007

23–25

2.7

0.4

(0.4–0.5)

<.001

25+

2.0

0.3

(0.2–0.4)

<.001

Service
Active duty

3.4

ref

-

-

National Guard

3.9

1.1

(1.0–1.2)

.046

Reserve

3.8

1.1

(0.9–1.3)

.173

Rank
E1

3.9

ref

-

-

E2

4.2

1.0

(0.9–1.2)

.382

E3

2.4

0.6

(0.4–0.7)

<.001

E4

1.5

0.3

(0.2–0.5)

<.001

>E5

0.0

n/a

-

-

Fort Benning

6.8

4.1

(3.2–5.2)

<.001

Fort Jackson

4.5

2.7

(2.2–3.3)

<.001

Fort Sill

1.8

1.1

(0.8–1.4)

.327

Fort Leonard Wood

1.7

ref

-

-

Training location

Number of cases per 10,000 basic combat training person-weeks
HI, heat illness; CI, confidence interval; ref, referent group; n/a, not applicable
a

April 2019   Vol. 26  No. 04  MSMR 

This study examined the timing of
HI events among recruits during BCT by
month of entry into training and phase of
training at each of the 4 BCT locations. HI
events occurred at all BCT locations and
during all phases of BCT. However, variability in the rates, measured in numbers
of HI events per 10,000 p-wks, was seen
across BCT sites, BCT entry-month, and
BCT training phase. When location was
examined, the southernmost locations
(Fort Benning and Fort Jackson) had the
highest rates of HI events, and rates were
significantly higher when compared to
the northernmost BCT site (Fort Leonard
Wood). This is consistent with the results of
a study of active component service members between 2013 and 2017, where Fort
Benning and Fort Jackson were among
the top 5 Army locations with the highest
numbers of HI events.6
Despite being located in the southeastern U.S., Fort Benning and Fort Jackson had significantly different HI rates.
The quantifiable factors examined in this
study did not fully explain this difference.
The recruits at these 2 BCT sites experience
similar weather environments and training
schedules; however, there are many individual risk factors for HI that could not
be controlled for in this study. For example, other studies have found that physical
fitness, body composition, sex, individual motivation, medication, and prior illness are associated with an increased risk
of HI.1,6–8 While differences in the overall
HI injury risk by BCT location have been
reported in the past, future investigations
into the causes of these differences may
benefit from inclusion of environmental
and/or local climatological data, factors
related to the delivery of training, and careseeking behavior.9,10 Another factor that is
difficult to control for between BCT sites
is diagnostic consistency among medical providers and access to medical care.
For example, Fort Benning has an emergency department on the installation; Fort
Jackson does not. This may result in considerable and systemic variations in HI
diagnosis.
Page 11

 TA B L E 4 . Heat illness rates and rate ratios, by basic combat training location, U.S. Army

recruits, 2014–2018
Location

Crude HI ratea

Rate ratio

95% CI

p-value

Fort Benning

6.8

4.1

(3.2–5.2)

<.0001

Fort Jackson

4.5

2.7

(2.2–3.3)

<.0001

Fort Sill

1.8

1.1

(0.8–1.4)

.327

Fort Leonard Wood

1.7

ref

-

-

Number of cases per 10,000 basic combat training person-weeks
HI, heat illness; CI, confidence interval; ref, referent group
a

TA B L E 5 . Rate ratios, by basic combat training location and entry month, U.S. Army recruits, 2014–2018
 Entry month

Rate ratioa

95% CI

p-value

Fort Benning
April

3.2

(0.9–13.0)

.078

May

10.3

(4.3–29.5)

<.001

June

3.3

(2.1–5.1)

<.001

July

1.9

(1.2–3.2)

.010

August

5.9

(3.4–11.2)

<.001

April

3.1

(1.2–10.0)

.015

May

7.1

(3.1–19.6)

<.001

June

2.1

(1.5–3.1)

<.001

July

2.4

(1.6–3.7)

<.001

August

3.3

(2.0–6.0)

<.001

April

0.6

(0.1–2.5)

.426

May

1.4

(0.5–4.6)

.521

June

0.6

(0.3–0.9)

.018

July

1.1

(0.6–1.8)

.831

August

2.1

(1.2–4.1)

.012

Fort Jackson

Fort Sill

Fort Leonard Wood used as reference
CI, confidence interval
a

If a recruit entered BCT between May
and November, rates of HIs were highest during phase 1. In the later BCT training phases, HI rates were highest among
recruits who entered training in May. Each
phase is approximately 3 weeks long, so for
a recruit entering BCT in May, the later
phases of BCT would coincide with the
peak summer months of July and August. It
is possible that these recruits have adapted
to the physical intensity of BCT, but have
not been fully acclimatized to hot and
humid conditions.
At the time of this report, this was
the only study that examined the rate of
HI during Army BCT controlling for BCT
entry-month and training phase. However,
the studies that have been conducted tend
to support the results of the current analysis. For example, a study of Army enlisted
soldiers found that the highest rates of mild
and severe HI occurred within the first
2 months of service; however, this study
did not specifically examine the time the
enlistees spent in BCT.1 Moreover, a study
of Marine Corps recruits found that the
highest number of HI cases occurred during the first 2 weeks of a 12-week recruit
training, with a second peak of HI events
towards the end of training in weeks 8 and
9,8 supporting the current report’s finding
of higher rates of HI during the first few
weeks of BCT (phase 1). However, unlike
the current study, the Marine study did not
consider how seasonal variations in temperature affected the number of HI events.
HI events occurred during each month
of the year, but as expected, the majority

F I G U R E 4 . Daily heat illness case counts, by week and phase of basic combat training, U.S. Army recruits, 2014–2018
60

Week 1

Week 2

Week 3

Week 4

Week 5

Week 6

Week 7

Week 8

Week 9

Week 10

No. heat illness cases

50
40
30
20
10
0
No., number

 Page

12

Phase 1

Phase 2

Phase 3

MSMR  Vol. 26  No. 04  April 2019

 F I G U R E 5. Heat illness rate, by basic combat training phase and entry month, U.S. Army
recruits, 2014–2018
16.0

Rate per 10,000 basic combat training p-wks

of HI events at BCT occurred during the
summer months (June–August). This is
a common finding across the HI literature describing military populations.1,11,12
Approximately 70,000 recruits entered
BCT per calendar year from 2014–2018.
The surge of new and younger recruits
entering BCT during the hottest months
leads to a larger number of recruits completing phase 1 of their training during the
period when they are most at risk for an HI.
The findings of this analysis should
be interpreted in light of several important limitations. The first potential limitation is the use of U.S. Army administrative
data that is not collected or maintained for
research purposes to identify the first-time
BCT recruits. Despite potential data quality issues with pertinent variables of interest (e.g., training dates) previous research
suggests that data sources like the ones

Phase 1 (weeks 1–3)
Phase 2 (weeks 4–6)

14.0

Phase 3 (weeks 7–10)

12.0
10.0

8.0
6.0
4.0

2.0
0.0

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Entry month
P-wks, person-weeks

TA B L E 6 . Heat illness ratesa, by location, phase, and entry month, U.S. Army recruits, 2014–2018b
Month of entry into basic combat training
Location

Phase

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

1 (weeks 1–3)

0.0

0.0

4.9

9.5

18.7

27.1

15.1

24.1

22.7

4.8

4.3

0.0

2 (weeks 4–6)

0.0

1.4

0.0

1.8

6.0

8.7

5.1

8.4

1.7

0.0

0.0

0.0

3 (weeks 7–10)

0.0

0.7

3.7

1.8

16.8

9.7

3.6

3.4

1.7

0.7

0.0

0.0

1 (weeks 1–3)

0.5

0.5

0.5

4.7

10.6

15.5

17.7

16.3

7.0

4.1

0.7

0.0

2 (weeks 4–6)

0.0

0.0

0.4

2.9

7.2

5.1

5.8

3.0

1.2

0.0

0.2

0.0

3 (weeks 7–10)

0.2

0.5

0.8

3.5

9.7

3.1

5.9

1.3

0.5

0.0

0.2

0.5

1 (weeks 1–3)

0.0

0.0

0.0

0.0

0.9

10.8

9.7

6.6

0.5

0.0

0.0

0.0

2 (weeks 4–6)

0.0

0.0

0.0

0.0

2.1

1.1

0.8

0.0

0.4

0.0

0.0

0.0

3 (weeks 7–10)

0.0

0.0

0.0

3.3

0.7

2.5

2.4

0.0

0.0

0.0

0.0

0.9

1 (weeks 1–3)

0.0

0.5

0.0

0.0

2.5

2.4

8.4

9.7

4.0

0.0

0.0

0.0

2 (weeks 4–6)

0.0

0.0

0.4

0.5

1.9

3.4

3.7

3.2

0.3

0.0

0.0

0.0

3 (weeks 7–10)

0.5

0.4

0.0

1.4

1.4

1.3

1.1

0.3

0.3

0.0

0.0

0.0

Fort Benning

Fort Jackson

Fort Leonard Wood

Fort Sill

a
b

Rates are reported per 10,000 basic combat training person-weeks.
Bolded numbers represent peak rates by phase and location.

used to identify this cohort of likely firsttime BCT recruits are valid and consistent
with other estimates of the BCT population.13 The second potential limitation is
that while the ICD-9/ICD-10 coding was
April 2019   Vol. 26  No. 04  MSMR 

largely used to define outcomes, a single
ICD code may not represent a true or final
diagnosis. Moreover, diagnosis coding can
be subject to clinician- or site-specific bias
and ultimately lead to a potential source of

misclassification bias. In order to reduce
this bias, the current analysis included only
medical records with a code of interest in
the first 2 diagnostic code positions. Third,
recruits in OSUT, AIT, or basic officer
Page 13

 leadership courses were excluded from this
analysis. Although roughly 70% of all new
trainees receive BCT as part of their overall
IET, the results of this analysis do not represent the complete burden of HI for all service members as evidenced by the fact that
the 1,210 HI cases in this study accounted
for only 13% (n=1,210/9,159) of all HI cases
in Army service members (active component, National Guard, Reserve) during the
study period. Fourth, this study did not
incorporate climate data (e.g., temperature,
humidity, or wind speed) into the analysis.
The goal of this study was to identify the
differences in HI rates by the timing of BCT
entry and BCT phase. The use of climate
data in a future analysis could account for
short-term (e.g., daily) and long-term (e.g.,
interannual) variability in local climate
and build upon the findings in the current
study. Despite these limitations, use of the
comprehensive DHA–WRIR data combined with U.S. Army administrative data
allowed for a novel level of granularity and
insight into the timing and incidence of HI
during BCT.
The results of the current study indicate that Fort Benning had the highest rates
of HI events, particularly among recruits
entering phase 1 training in the summer
months (June–August). The rates of HI
were lower in the later phases of BCT; however, HI rates increased during BCT phases
2 and 3 among recruits who entered BCT
in the spring months (April and May). The
identification of periods during the calendar year and within the 10-week training

 Page

14

period when rates of HI events are higher
could facilitate the targeted implementation of interventions or prevention strategies to mitigate the risk of HI during BCT.
Examination of such results by BCT location could inform each site about the time
of year when targeted mitigation strategies
could be most effective.
Author affiliations: Armed Forces Health
Surveillance Branch, Silver Spring, MD
(Mr. Barnes, Dr. Ambrose, Ms. Kebisek, Ms.
McCabe, Dr. Forrest, and Mr. Steelman);
United States Army Public Health Center
Clinical Public Health and Epidemiology
Directorate, Disease Epidemiology Division
(Dr. Maule, Ms. Scatliffe, and LTC Superior).
Disclaimer: The contents, views, or opin­
ions expressed in this publication are those of
the author(s) and do not necessarily reflect
the official policy or position of the Defense
Health Agency, the Department of Defense
(DoD), or the Department of the Army.
REFERENCES
1.  Nelson DA, Deuster PA, O’Connor FG, Kurina
LM. Timing and predictors of mild and severe heat
illness among new military enlistees. Med Sci Sport
Exer. 2018;50(8):1603–1612.
2.  Headquarters, Department of the Army, Training and Doctrine Command. TRADOC Regulation
350-6. Enlisted Initial Entry Training Policies and
Administration. Washington, DC: Department of
the Army; 2018. https://adminpubs.tradoc.army.mil/
regulations/TR350-6withChange1.pdf. Accessed
08 March 2019.
3.  Armed Forces Health Surveillance Branch.

Surveillance Case Definition. Heat Illness. March
2018.
https://www.health.mil/Reference-Center/
Publications/2017/03/01/Heat-Injuries. Accessed 8
March 2019.
4.  Armed Forces Health Surveillance Branch.
Armed Forces Reportable Medical Events: Guidelines and Case Definitions. https://health.mil/Reference-Center/Publications/2017/07/17/ArmedForces-Reportable-Medical-Events-Guidelines.
Accessed 08 March 2019.
5.  Sullivan KM, Dean A, Soe MM. OpenEpi:
a web-based epidemiologic and statistical calculator for public health. Public Health Rep.
2009;124(3):471–474.
6.  Armed Forces Health Surveillance Branch. Update: Heat illness, active component, U.S. Armed
Forces, 2017. MSMR. 2018;25(4):6–10.
7.  Gardner JW, Kark JA, Karnei K, et al. Risk
factors predicting exertional heat illness in male
Marine Corps recruits. Med Sci Sport Exer.
1996;28(8):939–944.
8.  Wallace RF, Kriebel D, Punnett L, et al. Risk
factors for recruit exertional heat illness by gender and training period. Aviat Space Environ Med.
2006;77(4):415–421.
9.  Swedler DI, Knapik JJ, Williams KW, Grier TL,
Jones BH. Risk factors for medical discharge from
United States Army Basic Combat Training. Mil
Med. 2011;176(10):1104–1110.
10. Grier TL, Knapik JJ, Canada S, CanhamChervak M, Jones BH. Risk factors associated with
self-reported training-related injury before arrival
at the U.S. Army Ordnance School. Public Health.
2011;124(7):417–423.
11.  Kark, JA, Burr PQ, Wenger CB, Gastaldo
E, Gardner JW. Exertional heat illness in Marine
Corps recruit training. Aviat Space Environ Med.
1996;67(4):354–360.
12. Stacey MJ, Brett S, Woods D, Jackson S,
Ross D. Case ascertainment of illness in the British
Army: evidence of under-reporting from analysis of
Medical and Command notifications, 2009–2013. J
R Army Med Corps. 2016;162(2):428–433.
13. Sulsky SL, Karlsson LH, Bulzacchelli MT, et al.
Methodological challenges of using U.S. Army administrative data to identify a cohort of basic combat
trainees and descriptive analysis of trends in characteristics that are potential risk factors for trainingrelated injury. Mil Med. 2014;179(12):1487–1496.

MSMR  Vol. 26  No. 04  April 2019

 Update: Heat Illness, Active Component, U.S. Armed Forces, 2018

In 2018, there were 578 incident diagnoses of heat stroke and 2,214 incident
diagnoses of heat exhaustion among active component service members. The
overall crude incidence rates of heat stroke and heat exhaustion diagnoses
were 0.45 cases and 1.71 cases per 1,000 person-years, respectively. In 2018,
subgroup-specific rates of incident heat stroke diagnoses were highest among
males and service members less than 20 years old, Asian/Pacific Islanders,
Marine Corps and Army members, recruit trainees, and those in combatspecific occupations. Subgroup-specific incidence rates of heat exhaustion
diagnoses in 2018 were notably higher among service members less than 20
years old, Asian/Pacific Islanders, Army and Marine Corps members, recruit
trainees, and service members in combat-specific occupations. During 2014–
2018, a total of 325 heat illnesses were documented among service members
in Iraq and Afghanistan; 8.6% (n=28) were diagnosed as heat stroke. Commanders, small unit leaders, training cadre, and supporting medical personnel must ensure that the military members whom they supervise and support
are informed about the risks, preventive countermeasures, early signs and
symptoms, and first-responder actions related to heat illnesses.

H

eat illness refers to a group of disorders that occur when the elevation of core body temperature
surpasses the compensatory limits of thermoregulation.1 Heat illness is the result of
environmental heat stress and/or exertion
and represents a set of conditions that exist
along a continuum from less severe (heat
exhaustion) to potentially life threatening
(heat stroke).
Heat exhaustion is caused by the inability to maintain adequate cardiac output
because of strenuous physical exertion and
environmental heat stress.1,2 Acute dehydration often accompanies heat exhaustion
but is not required for the diagnosis.3 The
clinical criteria for heat exhaustion include
a core body temperature greater than
100.5ºF/38ºC and less than 104ºF/40ºC at
the time of or immediately after exertion
and/or heat exposure, physical collapse at
the time of or shortly after physical exertion, and no significant dysfunction of the
central nervous system. If any central nervous system dysfunction develops with heat
exhaustion (e.g., dizziness or headache), it
April 2019   Vol. 26  No. 04  MSMR 

is mild and rapidly resolves with rest and
cooling measures (e.g., removal of unnecessary clothing, relocation to a cooled environment, and oral hydration with cooled,
slightly hypotonic solutions).1–4
Heat stroke is a debilitating illness
characterized clinically by severe hyperthermia (i.e., a core body temperature of
104ºF/40ºC or greater), profound central
nervous system dysfunction (e.g., delirium,
seizures, or coma), and additional organ
and tissue damage.1,4,5 The onset of heat
stroke requires aggressive clinical treatments, including rapid cooling and supportive therapies such as fluid resuscitation
to stabilize organ function.1,5 The observed
pathologic changes in several organ systems are thought to occur through a
complex interaction between heat cytotoxicity, coagulopathies, and a severe systemic
inflammatory response.1,5 Multi-organ system failure is the ultimate cause of mortality due to heat stroke.5
Timely medical intervention can prevent milder cases of heat illness (e.g., heat
exhaustion) from becoming severe (e.g.,

WHAT ARE THE NEW FINDINGS?
Annual rates of incident heat stroke diagnoses increased steadily between 2014 and
2018. During the same period, the annual
incidence rate of heat exhaustion diagnoses
peaked in 2018. A sizable proportion of heat
stroke and heat exhaustion cases identified through records of ambulatory visits did
not prompt mandatory reports through the
Reportable Medical Events System.

WHAT IS THE IMPAC T ON
R E AD INE S S AND FO RC E HE ALTH
PROTECTION?
Heat illnesses can degrade U.S. military
effectiveness by causing considerable morbidity, particularly during training of recruits
and of soldiers and Marines in combat arms
specialties. Complete and timely submission
of mandatory reports of heat illness events
ensures that local public health and command leaders have ready access to real-time
surveillance data to identify trends and to
guide preventive measures.

heat stroke) and potentially life threatening. However, even with medical intervention, heat stroke may have lasting effects,
including damage to the nervous system
and other vital organs and decreased heat
tolerance, making an individual more susceptible to subsequent episodes of heat
illness.6–8 Furthermore, the continued manifestation of multi-organ system dysfunction after heat stroke increases patients’ risk
of mortality during the ensuing months
and years.9,10
Strenuous physical activity for
extended durations in occupational settings
as well as during military operational and
training exercises exposes service members
to considerable heat stress because of high
environmental heat and/or a high rate of
metabolic heat production.11 In some military settings, wearing needed protective
clothing or equipment may make it biophysically difficult to dissipate body heat.
The resulting body heat burden and associated cardiovascular strain reduce exercise
performance and increase the risk of heatrelated illness.11,12
Page 15

 Over many decades, lessons learned
during military training and operations
in hot environments as well as a substantial body of literature have resulted in doctrine, equipment, and preventive measures
that can significantly reduce the adverse
health effects of military activities in hot
weather.13–19 Although numerous effective countermeasures are available, heatrelated illness remains a significant threat
to the health and operational effectiveness
of military members and their units and
accounts for considerable morbidity, particularly during recruit training in the U.S.
military.11,20
In the U.S. Military Health System
(MHS), the most serious types of heatrelated illness are considered notifiable
medical events. Notifiable cases of heat
illness include heat exhaustion and heat
stroke. All cases of heat illness that require
medical intervention or result in change of
duty status are reportable.4
This report summarizes reportable
medical events of heat illness as well as heat
illness-related hospitalizations and ambulatory visits among active component service members during 2018 and compares
them to the previous 4 years. Episodes of
heat stroke and heat exhaustion are summarized separately.

METHODS

The surveillance period was 1 January
2014 through 31 December 2018. The surveillance population included all individuals who served in the active component of
the Army, Navy, Air Force, or Marine Corps
at any time during the surveillance period.
All data used to determine incident heat illness diagnoses were derived from records
routinely maintained in the Defense
Medical Surveillance System (DMSS).
These records document both ambulatory encounters and hospitalizations of
active component service members of the
U.S. Armed Forces in fixed military and
civilian (if reimbursed through the MHS)
treatment facilities worldwide. In-theater
diagnoses of heat illness were identified
from medical records of service members
deployed to Southwest Asia or the Middle
 Page

16

East and whose healthcare encounters were
documented in the Theater Medical Data
Store (TMDS). Because heat illnesses represent a threat to the health of individual
service members and to military training
and operations, the Armed Forces require
expeditious reporting of these reportable
medical events through any of the service-specific electronic reporting systems;
these reports are routinely transmitted and
incorporated into the DMSS.
For this analysis, a case of heat illness was defined as an individual with 1)
a hospitalization or outpatient medical
encounter with a primary (first-listed) or
secondary (second-listed) diagnosis of heat
stroke (International Classification of Diseases, 9th Revision [ICD-9]: 992.0; International Classification of Diseases, 10th
Revision [ICD-10]: T67.0*) or heat exhaustion (ICD-9: 992.3–992.5; ICD-10: T67.3*–
T67.5*) or 2) a reportable medical event
record of heat exhaustion or heat stroke.21
Because of an update to the Disease Reporting System internet (DRSi) medical event
reporting system in July 2017, the type of
reportable medical events for heat illness
(i.e., heat stroke or heat exhaustion) could
not be distinguished using reportable medical event records in DMSS data. Instead,
information on the type of reportable
medical event for heat illness during the
entire 2014–2018 surveillance period was
extracted from the DRSi by the Defense
Health Agency (DHA) Army Satellite and
Army Public Health Center Staff.
It is important to note that previous
MSMR analyses included diagnosis codes
for other and unspecified effects of heat
and light (ICD-9: 992.8 and 992.9; ICD10: T67.8* and T67.9*) within the heat illness category “other heat illnesses.” These
codes were excluded from the current analysis and the April 2018 MSMR analysis. If
an individual had a diagnosis for both heat
stroke and heat exhaustion during a given
year, only 1 diagnosis was selected, prioritizing heat stroke over heat exhaustion.
Encounters for each individual within each
calendar year then were prioritized in terms
of record source, with hospitalizations prioritized over reportable events, which were
prioritized over ambulatory visits.
For surveillance purposes, a “recruit
trainee” was defined as an active component

service member (grades E1–E4) who was
assigned to 1 of the services’ 9 recruit training locations (per the individual’s initial
military personnel record). For this report,
each service member was considered a
recruit trainee for the period corresponding to the usual length of recruit training
in his or her service. Recruit trainees were
considered a separate category of enlisted
service members in summaries of heat illnesses by military grade overall.
Records of medical evacuations from
the U.S. Central Command (CENTCOM)
area of responsibility (AOR) (e.g., Iraq or
Afghanistan) to a medical treatment facility outside the CENTCOM AOR were
analyzed separately. Evacuations were considered case defining if affected service
members had at least 1 inpatient or outpatient heat illness medical encounter in a
permanent military medical facility in the
U.S. or Europe from 5 days before to 10
days after their evacuation dates.
Medical data from military treatment
facilities that are using MHS GENESIS
are not available in the DMSS, which was
implemented at different sites throughout
2017. These sites include Naval Hospital
Oak Harbor, Naval Hospital Bremerton,
Air Force Medical Services Fairchild, and
Madigan Army Medical Center. Therefore,
medical encounter data for individuals
seeking care at any of these facilities during 2017–2018 were not included in this
analysis.
R E SULT S

In 2018, there were 578 incident cases
of heat stroke and 2,214 incident cases of
heat exhaustion among active component
service members (Table 1). The crude overall incidence rates of heat stroke and heat
exhaustion diagnoses were 0.45 cases and
1.71 cases per 1,000 person-years (p-yrs),
respectively. In 2018, subgroup-specific
incidence rates of heat stroke diagnoses were highest among males, those less
than 20 years old, Asian/Pacific Islanders,
Marine Corps and Army members, recruit
trainees, and those in combat-specific
occupations (Table 1). The rate of incident
heat stroke diagnoses was 20.9% higher
MSMR  Vol. 26  No. 04  April 2019

 among service members in the Marine
Corps than among those in the Army; the
Army rate was more than 7-fold the Navy
rate and 9-fold the Air Force rate; and the
rate among females was 26.5% lower than
the rate among males. There were only 37
cases of heat stroke reported among recruit
trainees, but their incidence rate was more
than 3 times that of other enlisted members
and officers.
Similar to the heat stroke findings, the
crude overall incidence rate of heat exhaustion diagnoses among males was slightly
higher than among females (Table 1). In
2018, subgroup-specific rates of incident
heat exhaustion diagnoses were notably
higher among service members less than
20 years old, Asian/Pacific Islanders, Army
and Marine Corps members, recruit trainees, and service members in combat-specific occupations.
Crude (unadjusted) annual incidence
rates of heat stroke diagnoses increased
steadily from 0.26 cases per 1,000 p-yrs in
2014 to 0.45 cases per 1,000 p-yrs in 2018
(Figure 1). In 2018, there were more heat
stroke-related hospitalizations and reportable medical events than in 2017 but similar
numbers of ambulatory visits. Crude annual
rates of incident heat exhaustion diagnoses
increased steadily during the first 3 years of
the surveillance period and ranged from a
low of 1.12 cases per 1,000 p-yrs in 2014 to
1.42 cases per 1,000 p-yrs in 2016 (Figure
2). Annual rates were stable during 2016–
2017 and then increased 18.7% to a peak of
1.71 cases per 1,000 p-yrs in 2018. During
the 5-year surveillance period, the numbers of heat exhaustion-related hospitalizations and the proportions they represented
remained relatively stable (range: 49–65;
2.7%–3.4%). However, the proportions of
of total heat exhaustion cases from reportable medical events increased from 29.5%
in 2014 to 40.1% in 2018, while the proportions from ambulatory visits decreased
from 66.3% to 57.0% during this period.

Heat illnesses by location
During the 5-year surveillance period,
a total of 11,452 heat-related illnesses were
diagnosed at more than 250 military installations and geographic locations worldwide (Table 2). Less than 8% of the total
April 2019   Vol. 26  No. 04  MSMR 

TA B L E 1. Incident casesa and incidence ratesb of heat illness, active component service

members, U.S. Army, Navy, Air Force, and Marine Corps, 2018
Heat stroke

Total
Sex
Male
Female
Age group (years)
<20
20–24
25–29
30–34
35–39
40+
Race/ethnicity
Non-Hispanic white
Non-Hispanic black
Hispanic
Asian/Pacific Islander
Other/unknown
Service
Army
Navy
Air Force
Marine Corps
Military status
Recruit
Enlisted
Officer
Military occupation
Combat-specificc
Motor transport
Pilot/air crew
Repair/engineering
Communications/intelligence
Healthcare
Other/unknown
Home of recordd
Midwest
Northeast
South
West
Other/unknown

Heat exhaustion

Total heat illness
diagnoses

No.

Rateb

No.

Rateb

No.

Rateb

578

0.45

2,214

1.71

2,792

2.15

505
73

0.47
0.34

1,890
324

1.74
1.52

2,395
397

2.21
1.86

102
246
130
60
26
14

1.00
0.59
0.44
0.29
0.17
0.11

543
1,004
385
165
72
45

5.34
2.41
1.29
0.80
0.48
0.36

645
1,250
515
225
98
59

6.34
3.00
1.73
1.10
0.65
0.47

330
98
89
41
20

0.45
0.47
0.43
0.76
0.21

1,295
396
339
116
68

1.77
1.90
1.64
2.14
0.73

1,625
494
428
157
88

2.22
2.36
2.07
2.89
0.94

351
33
26
168

0.75
0.10
0.08
0.91

1,361
121
200
532

2.91
0.37
0.62
2.88

1,712
154
226
700

3.67
0.48
0.71
3.79

37
447
94

1.32
0.43
0.41

316
1,723
175

11.23
1.66
0.76

353
2,170
269

12.55
2.09
1.17

228
25
2
72
80
31
140

1.29
0.66
0.04
0.19
0.29
0.27
0.54

741
58
7
343
382
128
555

4.20
1.53
0.15
0.89
1.38
1.12
2.14

969
83
9
415
462
159
695

5.50
2.19
0.19
1.08
1.66
1.39
2.68

108
90
238
136
6

0.47
0.55
0.43
0.44
0.15

408
265
1,004
506
31

1.77
1.61
1.82
1.65
0.75

516
355
1,242
642
37

2.23
2.15
2.25
2.10
0.90

One case per person per year
Number of cases per 1,000 person-years
c
Infantry/artillery/combat engineering/armor
d
As self-reported at time of entry into service
No., number
a
b

heat illness cases occurred outside of the
U.S. (n=831). Four Army installations
accounted for slightly more than one-third
(34.2%) of all heat illnesses during the
period (Fort Benning, GA [n=1,504]; Fort
Bragg, NC [n=1,108]; Fort Campbell, KY
[n=694]; and Fort Polk, LA [n=610]). Six
other locations accounted for an additional

one-quarter (24.8%) of heat illness events
(Marine Corps Base Camp Lejeune/Cherry
Point, NC [n=738]; Marine Corps Recruit
Depot Parris Island/Beaufort, SC [n=580];
Marine Corps Base Camp Pendleton, CA
[n=496]); Naval Medical Center San Diego,
CA [n=429]; Okinawa, Japan [n=299]; and
Fort Jackson, SC [n=298]). Of these 10
Page 17

 rates of heat stroke by source of report and
year of diagnosis, active component, U.S.
Armed Forces, 2014–2018
Hospitalizations
Reportable events
Ambulatory visits
Rate

650

600

166

0.26
95

0.30

99

81

93

134

166

0.20

250
200

83

0.15

247

262

242

246

167

50

0

1,400
1,200

49

887

1.12
64

520
507

1.2
656
1.0

444
0.8

1,000
800

0.6

998

0.10

1.6

1.4

61

59

600

150
100

0.25

1,600
No. of cases (bars)

115

400

1.32

0.35

141

0.33

1.71

1.8

1.42 1.44

1,800

1,148

1,265

1,130

1,262

0.4

400

0.05

0.2

200

Fort Bragg, NC

2014 2015 2016 2017 2018

2014 2015 2016 2017 2018

a

locations with the most heat illness events,
7 are located in the southeastern U.S. The
19 locations with more than 100 cases of
heat illness accounted for nearly threequarters (73.0%) of all active component
cases during 2014–2018.

old (n=176; 54.2%); in the Army (n=173;
53.2%); enlisted (n=315; 96.9%); and in
repair/engineering (n=109; 33.5%) or
combat-specific (n=98; 30.2%) occupations (data not shown). During the surveillance period, 4 service members were
medically evacuated for heat illnesses
from Iraq or Afghanistan; all of the evacuations took place in the summer months
(May–September).

Heat illnesses in Iraq and Afghanistan
During the 5-year surveillance period,
a total of 325 heat illnesses were diagnosed and treated in Iraq and Afghanistan
(Figure 3). Of the total cases of heat illness, 8.6% (n=28) were diagnosed as heat
stroke. Deployed service members who
were affected by heat illnesses were most
frequently male (n=270; 83.1%); non-Hispanic white (n=196; 60.3%); 20–24 years

No.

1,108

9.7

MCB Camp Lejeune/Cherry
Point, NC

738

6.4

Fort Campbell, KY

694

6.1

Fort Polk, LA

610

5.3

MCRD Parris Island/ Beaufort, SC

580

5.1

MCB Camp Pendleton, CA

496

4.3

NMC San Diego, CA

429

3.7

Okinawa, Japan

299

2.6

Fort Jackson, SC

298

2.6

Fort Hood, TX

272

2.4

Fort Stewart, GA

265

2.3

MCB Quantico, VA

236

2.1

Lackland AFB, TX

198

1.7

Fort Shafter, HI

165

1.4

Fort Leonard Wood, MO

150

1.3

Fort Irwin, CA

111

1.0

Fort Bliss, TX

104

0.9

Fort Sill, OK

103

0.9

All other locations

3,092 27.0
11,452 100.0

0.0

Diagnosis codes were prioritized by severity and
record source (heat stroke > heat exhaustion; hospitalizations > reportable events > ambulatory visits)
No., number; p-yrs, person-years

18

Fort Benning, GA

%
total
1,504 13.1

Total
0

0.00

a

 Page

TA B L E 2. Heat injury eventsa by location
of diagnosis/report (with at least 100
cases during the period), active component, U.S. Armed Forces, 2014–2018
Location of diagnosis

65

2,000

Incidence rate per 1,000 p-yrs (line)

No. of cases (bars)

450

300

2,200

0.45
0.40

0.36

Hospitalizations
Reportable events
Ambulatory visits
Rate

2,400

0.40

500

350

rates of heat exhaustion, by source of report and year of diagnosis, active component, U.S. Armed Forces, 2014–2018

0.50

0.45

550

F I G U R E 2. Incident casesa and incidence

Incidence rate per 1,000 p-yrs (line)

F I G U R E 1 . Incident casesa and incidence

Diagnosis codes were prioritized by severity and
record source (heat stroke > heat exhaustion; hospitalizations > reportable events > ambulatory visits)
No., number; p-yrs, person-years

EDITORIAL COMMENT

This annual update of heat illnesses
among service members in the active component documented that the unadjusted

One heat injury per person per year
No., number; MCB, Marine Corps Base; MCRD,
Marine Corps Recruit Depot; NMC, Naval Medical
Center; AFB, Air Force Base

a

annual rates of incident heat stroke diagnoses increased steadily between 2014 and
2018. The crude annual incidence rate of
heat exhaustion diagnoses in 2018 represents an 18.7% increase over the 2017 rate.
There are significant limitations to
this update that should be considered
when interpreting the results. Similar heatrelated clinical illnesses are likely managed
differently and reported with different diagnostic codes at different locations and in
different clinical settings. Such differences
undermine the validity of direct comparisons of rates of nominal heat stroke and
heat exhaustion events across locations and
settings. Also, heat illnesses during training
exercises and deployments that are treated
MSMR  Vol. 26  No. 04  April 2019

 F I G U R E 3 . Numbers of heat illnesses diagnosed in Iraq/Afghanistan, active component, U.S. Armed Forces, 2014–2018
100

Heat stroke
Heat exhaustion

90

80
70

11

7

4

60
No. of events

3

50

3

40
30

60

64

68

60

45

20

10
0

2014 2015 2016 2017 2018

No., number

in field medical facilities may not be captured in this report. In addition, it should
be noted that the guidelines for mandatory
reporting of heat illnesses were modified
in the 2017 revision of the Armed Forces
guidelines and case definitions for reportable medical events.4 In this updated version of the guidelines and case definitions,
the heat injury category was removed, leaving only case classifications for heat stroke
and heat exhaustion. To compensate for
such possible variation in reporting, the
analysis for this update, as in previous
years, included cases identified in DMSS
records of ambulatory care and hospitalizations using a consistent set of ICD-9/ICD10 codes for the entire surveillance period.
However, it also is important to note that
the exclusion of diagnosis codes for other
and unspecified effects of heat and light
(formerly included within the heat illness
category “other heat illnesses”) in the current analysis precludes the direct comparison of numbers and rates of cases of heat
April 2019   Vol. 26  No. 04  MSMR 

exhaustion to the numbers and rates of
“other heat illnesses” reported in MSMR
updates prior to 2017.
As has been noted in previous MSMR
heat illness updates, results indicate that
a sizable proportion of cases identified
through DMSS records of ambulatory
visits did not prompt mandatory reports
through the reporting system.20 However, this study did not directly ascertain
the overlap between hospitalizations and
reportable events and the overlap between
reportable events and outpatient encounters. It is possible that cases of heat illness,
whether diagnosed during an inpatient
or outpatient encounter, were not documented as reportable medical events
because treatment providers were not
attentive to the criteria for reporting or
because of ambiguity in interpreting the
criteria (e.g., the heat illness did not result
in a change in duty status or the core body
temperature measured during/immediately after exertion or heat exposure was
not available). Underreporting is especially
concerning for cases of heat stroke because
it may reflect insufficient attentiveness to
the need for prompt recognition of cases of
this dangerous illness and for timely intervention at the local level to prevent additional cases.
In spite of its limitations, this report
documents that heat illnesses are a significant and persistent threat to both the
health of U.S. military members and the
effectiveness of military operations. Of all
military members, the youngest and most
inexperienced Marines and soldiers (particularly those training at installations in
the southeastern U.S.) are at highest risk of
heat illnesses, including heat stroke, exertional hyponatremia, and exertional rhabdomyolysis (see the other articles in this
issue of the MSMR).
Commanders, small unit leaders,
training cadre, and supporting medical
personnel—particularly at recruit training
centers and installations with large combat troop populations—must ensure that
the military members whom they supervise and support are informed regarding the risks, preventive countermeasures
(e.g., water consumption), early signs and
symptoms, and first-responder actions
related to heat illnesses.13–19,22 Leaders

should be aware of the dangers of insufficient hydration on the one hand and excessive water intake on the other; they must
have detailed knowledge of, and rigidly
enforce countermeasures against, all types
of heat illnesses.
Policies, guidance, and other information related to heat illness prevention and
treatment among U.S. military members
are available online at https://phc.amedd.
army.mil/topics/discond/hipss/Pages/
Heat-Related-Illness-Prevention.aspx.
Acknowledgment: The authors thank the
Army Public Health Center, Aberdeen, MD,
for providing data on reportable medical
events of heat illnesses.
REFERENCES
1. Atha WF. Heat-related illness. Emerg Med Clin
North Am. 2013;31(4):1097–1108.
2. Simon HB. Hyperthermia. N Engl J Med.
1993;329(7):483–487.
3. O’Connor FG, Sawka MN, Deuster P. Disorders due to heat and cold. In: Goldman L, Schafer
AI, eds. Goldman-Cecil Medicine. 25th ed. Philadelphia, PA: Elsevier Saunders; 2016:692–693.
4. Armed Forces Health Surveillance Branch in
collaboration with U.S. Air Force School of Aerospace Medicine, Army Public Health Center, and
Navy and Marine Corps Public Health Center.
Armed Forces Reportable Medical Events: Guidelines and Case Definitions. https://health.mil/Reference-Center/Publications/2017/07/17/ArmedForces-Reportable-Medical-Events-Guidelines.
Published 17 July 2017. Accessed 11 March 2019.
5. Leon LR, Bouchama A. Heat stroke. Compr
Physiol. 2015;5(2):611–647.
6. Epstein Y. Heat intolerance: predisposing
factor or residual injury? Med Sci Sports Exerc.
1990;22(1):29–35.
7. O’Connor FG, Casa DJ, Bergeron MF, et al.
American College of Sports Medicine roundtable
on exertional heat stroke—return to duty/return to
play: conference proceedings. Curr Sports Med
Rep. 2010;9(5):314–321.
8. Shapiro Y, Magazanik A, Udassin R, Ben-Baruch G, Shvartz E, Shoenfeld Y. Heat intolerance
in former heatstroke patients. Ann Intern Med.
1979;90(6):913–916.
9. Dematte JE, O’Mara K, Buescher J, et al. Nearfatal heat stroke during the 1995 heat wave in Chicago. Ann Intern Med. 1998;129(3):173–181.
10. Wallace RF, Kriebel D, Punnett L, Wegman DH,
Amoroso PJ. Prior heat illness hospitalization and
risk of early death. Environ Res. 2007;104(2):290–
295.
11. Carter R 3rd, Cheuvront SN, Williams JO, et
al. Epidemiology of hospitalizations and deaths
from heat illness in soldiers. Med Sci Sports Exerc.
2005;37(8):1338–1344.
12. Sawka MN, Cheuvront SN, Kenefick RW. High
skin temperature and hypohydration impair aerobic

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 performance. Exp Physiol. 2012;97(3):327–332.
13. Goldman RF. Introduction to heat-related
problems in military operations. In Lounsbury DE,
Bellamy RF, Zajtchuk R, eds. Textbook of Military
Medicine: Medical Aspects of Harsh Environments,
Volume 1. Washinton, DC: Office of the Surgeon
General, Borden Institute; 2001:3–49.
14. Sonna LA. Practical medical aspects of military
operations in the heat. In Lounsbury DE, Bellamy
RF, Zajtchuk R, eds. Textbook of Military Medicine:
Medical Aspects of Harsh Environments, Volume
1. Washington, DC: Office of the Surgeon General,
Borden Institute; 2001:293–309.
15. Headquarters, Department of the Army and Air
Force. Technical Bulletin, Medical, 507, Air Force
Pamphlet 48-152: Heat Stress Control and Heat
Casualty Management. Washington, DC: Department of the Army and Air Force; 2003. https://www.
dir.ca.gov/oshsb/documents/Heat_illness_preven-

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tion_tbmed507.pdf. Accessed 11 March 2019.
16. Headquarters, United States Marine Corps,
Department of the Navy. Marine Corps Order
6200.1E: Marine Corps Heat Injury Prevention Program. Washington DC: Department of the Navy;
2002. http://www.marines.mil/Portals/59/Publications/MCO%206200.1E%20W%20CH%201.pdf.
Accessed 11 March 2019.
17. Navy Environmental Health Center. NEHCTM-OEM 6260.6A: Prevention and Treatment of
Heat and Cold Stress Injuries. http://www.med.
navy.mil/sites/nmcphc/Documents/nepmu-6/Environmental-Health/Disease-Prevention/TechnicalManual-NEHC-TM-OEM-6260-6A.pdf. Published
June 2007. Accessed 11 March 2019.
18. Webber BJ, Casa DJ, Beutler AI, Nye NS,
Trueblood WE, O'Connor FG. Preventing exertional death in military trainees: recommendations and
treatment algorithms from a multidisciplinary work-

ing group. Mil Med. 2016;181(4):311–318.
19. Lee JK, Kenefick RW, Cheuvront SN. Novel
cooling strategies for military training and operations. J Strength Cond Res. 2015;29(suppl
11):S77–S81.
20. Armed Forces Health Surveillance Branch.
Update: Heat injuries, active component, U.S.
Armed Forces, 2017. MSMR. 2018;25(4):6–10.
21. Armed Forces Health Surveillance Branch.
Surveillance Case Definition. Heat Illness. March
2018. https://health.mil/Reference-Center/Publications/2017/03/01/Heat-Injuries. Accessed 11
March 2019.
22. Headquarters, Department of the Army, Training and Doctrine Command. Memorandum. TRADOC Heat Illness Prevention Program 2018. 8
January 2018.

MSMR  Vol. 26  No. 04  April 2019

 Update: Exertional Rhabdomyolysis, Active Component, U.S. Armed Forces, 2014–2018
This article provides continuing education (CE) and continuing medical education (CME) credit.

CE/CME Please see information at the end of the article.

WHAT ARE THE NEW FINDINGS?

Among active component service members in 2018, there were 545 incident
diagnoses of rhabdomyolysis likely due to exertional rhabdomyolysis, for an
unadjusted incidence rate of 42.0 cases per 100,000 person-years. Subgroupspecific rates in 2018 were highest among males, those less than 20 years old,
Asian/Pacific Islander service members, Marine Corps and Army members,
and those in combat-specific or “other/unknown” occupations. During 2014–
2018, crude rates of exertional rhabdomyolysis increased steadily from 2014
through 2016 after which rates declined slightly in 2017 before increasing
again in 2018. Compared to service members in other race/ethnicity groups,
the overall rate of exertional rhabdomyolysis was highest among non-Hispanic blacks in every year except 2018. Overall and annual rates were highest among Marine Corps members, intermediate among those in the Army,
and lowest among those in the Air Force and Navy. Most cases of exertional
rhabdomyolysis were diagnosed at installations that support basic combat/
recruit training or major ground combat units of the Army or the Marine
Corps. Medical care providers should consider exertional rhabdomyolysis in
the differential diagnosis when service members (particularly recruits) present with muscular pain or swelling, limited range of motion, or the excretion
of dark urine (possibly due to myoglobinuria) after strenuous physical activity, particularly in hot, humid weather.

R

habdomyolysis is characterized by
the breakdown of skeletal muscle
cells and the subsequent release of
intracellular muscle contents into the circulation. The characteristic triad of rhabdomyolysis includes weakness, myalgias,
and red to brown urine (due to myoglobinuria) accompanied by an elevated serum
concentration of creatine kinase.1,2 In exertional rhabdomyolysis, damage to skeletal
muscle is generally caused by high-intensity, protracted, or repetitive physical activity, usually after engaging in unaccustomed
strenuous exercise (especially with eccentric
and/or muscle-lengthening contractions).3
Even athletes who are used to intense training and who are being carefully monitored
April 2019   Vol. 26  No. 04  MSMR 

are at risk of this condition,4 especially if
new overexertion-inducing exercises are
being introduced.5 Illness severity ranges
from elevated serum muscle enzyme levels
without clinical symptoms to life-threatening disease associated with extreme enzyme
elevations, electrolyte imbalances, and kidney failure.1–3,6
Risk factors for exertional rhabdomyolysis include younger age, male sex, a
lower level of physical fitness, a prior heat
illness, a lower level of education, and exertion during the warmer months of the
year.1,3,7–10 Acute kidney injury, due to an
excessive concentration of free myoglobin
in the urine accompanied by volume depletion, renal tubular obstruction, and renal

The annual numbers and rates of diagnoses
of exertional rhabdomyolysis among active
component U.S. military members during the
2014–2018 period peaked in 2018. In 2018,
for the first time, the annual rate of exertional
rhabdomyolysis among Asian/Pacific Islanders was higher than the rate in any other
race/ethnicity group.

WHAT IS THE IMPAC T ON
R E AD INE S S AND FO RC E HE ALTH
PROTECTION?
The net increase in annual rates of exertional
rhabdomyolysis suggests that Commanders,
supervisors, and trainers at recruit training
camps and at installations with large ground
combat units need to be more aggressive
in preventing cases of this and other types
of heat injury and in detecting early signs of
such serious heat-associated injuries.

ischemia, represents a serious complication of rhabdomyolysis.6,11 Severly affected
patients can also develop compartment
syndrome, fever, dysrhythmias, metabolic
acidosis, and altered mental status.
In U.S. military members, rhabdomyolysis is a significant threat during
physical exertion, particularly under heat
stress.7,9,12–14 Moreover, although rhabdomyolysis can affect any service member,
new recruits, who are not yet accustomed
to the physical exertion required of basic
training, may be at particular risk.9 Each
year, the MSMR summarizes the numbers,
rates, trends, risk factors, and locations
of occurrences of exertional heat injuries,
including exertional rhabdomyolysis. This
report includes the data for 2014–2018.
Additional information about the definition, causes, and prevention of exertional
rhabdomyolysis can be found in previous
issues of the MSMR.12,13,15
Page 21

 METHODS

The surveillance period was 1 January
2014 through 31 December 2018. The surveillance population included all individuals who served in the active component
of the Army, Navy, Air Force, or Marine
Corps at any time during the surveillance
period. All data used to determine incident exertional rhabdomyolysis diagnoses
were derived from records routinely maintained in the Defense Medical Surveillance
System (DMSS). These records document
both ambulatory encounters and hospitalizations of active component members
of the U.S. Armed Forces in fixed military
and civilian (if reimbursed through the
Military Health System [MHS]) treatment
facilities worldwide. In-theater diagnoses
of exertional rhabdomyolysis were identified from medical records of service members deployed to Southwest Asia/Middle
East and whose healthcare encounters were
documented in the Theater Medical Data
Store (TMDS).
For this analysis, a case of exertional
rhabdomyolysis was defined as an individual with 1) a hospitalization or outpatient medical encounter with a diagnosis
in any position of either “rhabdomyolysis”
(International Classification of Diseases,
9th Revision [ICD-9]: 728.88; International
Classification of Diseases, 10th Revision
[ICD-10]: M62.82) or “myoglobinuria”
(ICD-9: 791.3; ICD-10: R82.1) plus a diagnosis in any position of 1 of the following:
“volume depletion (dehydration)” (ICD9: 276.5*; ICD-10: E86.0, E86.1, E86.9),
“effects of heat” (ICD-9: 992.0–992.9; ICD10: T67.0–T67.9), “effects of thirst (deprivation of water)” (ICD-9: 994.3; ICD-10:
T73.1), “exhaustion due to exposure” (ICD9: 994.4; ICD-10: T73.2), or “exhaustion
due to excessive exertion (overexertion)”
(ICD-9: 994.5; ICD-10: T73.3).13 Each individual could be considered an incident case
of exertional rhabdomyolysis only once per
calendar year.
To exclude cases of rhabdomyolysis
that were secondary to traumatic injuries,
intoxications, or adverse drug reactions,
medical encounters with diagnoses in any
position of “injury, poisoning, toxic effects”
(ICD-9: 800–999; ICD-10: S00–T88, except
 Page

22

the codes specific for “sprains and strains
of joints and adjacent muscles” and “effects
of heat, thirst, and exhaustion”) were
not considered indicative of exertional
rhabdomyolysis.13
For surveillance purposes, a “recruit
trainee” was defined as an active component member in an enlisted grade (E1–
E4) who was assigned to 1 of the services’
recruit training locations (per the individual’s initial military personnel record).
For this report, each service member was
considered a recruit trainee for the period
of time corresponding to the usual length
of recruit training in his or her service.
Recruit trainees were considered a separate category of enlisted service members
in summaries of rhabdomyolysis cases by
military grade overall.
In-theater diagnoses of exertional
rhabdomyolysis were analyzed separately;
however, the same case-defining criteria
and incidence rules were applied to identify incident cases. Records of medical
evacuations from the U.S. Central Command (CENTCOM) area of responsibility (AOR) (e.g., Iraq and Afghanistan) to
a medical treatment facility outside the
CENTCOM AOR also were analyzed separately. Evacuations were considered case
defining if affected service members met
the above criteria in a permanent military
medical facility in the U.S. or Europe from
5 days before to 10 days after their evacuation dates.
The new electronic health record for the
MHS, MHS GENESIS, was implemented at
several military treatment facilities during 2017. Medical data from sites that are
using MHS GENESIS are not available in
the DMSS. These sites include Naval Hospital Oak Harbor, Naval Hospital Bremerton,
Air Force Medical Services Fairchild, and
Madigan Army Medical Center. Therefore,
medical encounters for individuals seeking
care at any of these facilities during 2017–
2018 were not included in this analysis.
R E SULT S

In 2018, there were 545 incident diagnoses of rhabdomyolysis likely associated with physical exertion and/or heat

stress (exertional rhabdomyolysis) (Table
1). The crude (unadjusted) incidence rate
was 42.0 cases per 100,000 person-years
(p-yrs). Subgroup-specific incidence rates
of exertional rhabdomyolysis diagnoses were highest among males (45.9 per
100,000 p-yrs), those less than 20 years
old (86.1 per 100,000 p-yrs), Asian/Pacific
Islander service members (73.8 per 100,000
p-yrs), Marine Corps and Army members (99.0 per 100,000 p-yrs and 54.8 per
100,000 p-yrs, respectively), and those in
combat-specific or “other/unknown” occupations (76.0 per 100,000 p-yrs and 72.9
per 100,000 p-yrs, respectively) (Table 1).
Of note, the incidence rate among recruit
trainees was more than 6 times that among
other enlisted members and officers, even
though cases among this group accounted
for only 13.0% of all cases in 2018.
During the surveillance period, crude
annual rates of incident diagnoses of exertional rhabdomyolysis increased steadily
from 30.0 per 100,000 p-yrs in 2014 to 40.8
per 100,000 p-yrs in 2016 after which rates
declined slightly to 39.0 per 100,000 p-yrs
in 2017 before increasing again to 42.0
per 100,000 p-yrs in 2018 (Figure 1). During 2014–2018, the annual incidence rates
of exertional rhabdomyolysis diagnoses
were highest among non-Hispanic blacks
in every year except 2018, when the highest
rate occurred among Asian/Pacific Islanders (data not shown). Overall and annual
rates of incident exertional rhabdomyolysis diagnoses were highest among service
members in the Marine Corps, intermediate among those in the Army, and lowest among those in the Air Force and Navy
(Table 1, Figure 2). The most pronounced
increases in annual incidence rates were
observed among Marine Corps members
and Army members during 2014–2016
(35.5% and 46.2%, respectively); however,
rates among service members in the Air
Force and Navy remained relatively stable
(Figure 2). During the surveillance period,
approximately three-quarters (75.6%) of
the cases occurred during May–October
(Figure 3).

Rhabdomyolysis by location
During the 5-year surveillance period,
the medical treatment facilities at 11
MSMR  Vol. 26  No. 04  April 2019

 TA B L E 1 . Incident diagnoses and incidence ratesa of exertional rhabdomyolysis, active

component, U.S. Armed Forces, 2018

Hospitalizations
Total

Ambulatory visits

No.

Rate

No.

Rate

260

20.1

285

234

21.6

26

12.2

a

Total
No.

Ratea

22.0

545

42.0

263

24.3

497

45.9

22

10.3

48

22.5

a

Sex
Male
Female
Age group (years)
<20

66

35.7

93

50.3

159

86.1

20–24

86

25.8

68

20.4

154

46.2

25–29

47

15.8

75

25.1

122

40.9

30–34

38

18.5

29

14.1

67

32.7

35–39

17

11.3

11

7.3

28

18.7

6

4.8

9

7.2

15

12.0

Non-Hispanic white

114

15.6

135

18.4

249

34.0

Non-Hispanic black

67

32.1

70

33.5

137

65.6

Hispanic

42

20.3

47

22.7

89

43.0

Asian/Pacific Islander

22

40.6

18

33.2

40

73.8

Other/unknown

15

16.1

15

16.1

30

32.1
54.8

40+
Race/ethnicity

Service
Army

109

23.3

147

31.5

256

Navy

31

9.6

17

5.2

48

14.8

Air Force

37

11.5

21

6.6

58

18.1

Marine Corps

83

44.9

100

54.1

183

99.0
38.6

Military status
Enlisted

192

18.5

209

20.1

401

Officer

37

16.1

36

15.7

73

31.7

Recruit

31

108.5

40

140.0

71

248.5

Combat-specificb

51

28.9

83

47.1

134

76.0

Motor transport

10

26.3

9

23.7

19

50.0

3

6.5

0

0.0

3

6.5

Repair/engineering

53

13.8

42

10.9

95

24.7

Communications/intelligence

29

10.4

44

15.8

73

26.3

Healthcare

22

19.3

10

8.8

32

28.1

Other/unknown

92

35.5

97

37.4

189

72.9

Midwest

35

15.2

44

19.1

79

34.2

Northeast

44

26.7

40

24.3

84

50.9

South

116

21.0

135

24.4

251

45.4

West

61

19.9

56

18.3

117

38.2

4

9.7

10

24.2

14

33.8

MCB Camp Lejeune/Cherry Point, NC;
Fort Shafter, HI; Fort Hood, TX; and Fort
Campbell, KY). The most cases overall were
diagnosed at Fort Bragg, NC (n=272) and
MCRD Parris Island/Beaufort, SC (n=250),
which together accounted for more than
one-fifth (22.5%) of all cases (Table 2).

Rhabdomyolysis in Iraq and Afghanistan
There were 6 incident cases of exertional rhabdomyolysis diagnosed and
treated in Iraq/Afghanistan (data not
shown) during the 5-year surveillance
period. Deployed service members who
were affected by exertional rhabdomyolysis were more often non-Hispanic black
or non-Hispanic white (n=4; 66.7% and
n=2; 33.3%, respectively), male (n=6), aged
20–24 years (n=2; 33.3%), in the Army
(n=6), enlisted (n=6), and in communication/intelligence occupations (n=2; 33.3%).
One active component service member was
medically evacuated from Iraq/Afghanistan for exertional rhabdomyolysis; this
medical evacuation occurred in September
2015 (data not shown).
EDITORIAL COMMENT

Military occupation

Pilot/air crew

Home of record

Other/unknown
a

Rate per 100,000 person-years

b

Infantry/artillery/combat engineering/armor

c

As self-reported at time of entry into service

No., number

installations diagnosed at least 50 cases
each; when combined, these installations
diagnosed almost half (47.7%) of all cases
(Table 2). Of these 11 installations, 4 provide support to recruit/basic combat training centers (Marine Corps Recruit Depot
April 2019   Vol. 26  No. 04  MSMR 

Parris Island/Beaufort, SC; Fort Benning,
GA; Joint Base San Antonio–Lackland, TX;
and Fort Leonard Wood, MO). In addition, 6 installations support large combat
troop populations (Fort Bragg, NC; Marine
Corps Base [MCB] Camp Pendleton, CA;

This report documents an increase in
the crude annual incidence rates of diagnoses of exertional rhabdomyolysis among
active component U.S. military members
from 2014 through 2016 after which rates
declined slightly in 2017 before increasing
again in 2018. Exertional rhabdomyolysis
continued to occur most frequently from
late spring through early fall at installations
that support basic combat/recruit training
or major Army or Marine Corps combat
units.
The risks of heat injuries, including
exertional rhabdomyolysis, are increased
among individuals who suddenly increase
overall levels of physical activity, recruits
who are not physically fit when they begin
training, and recruits from relatively cool
and dry climates who may not be acclimated to the high heat and humidity at
training camps in the summer.1,2,9 Soldiers and Marines in combat units often
conduct rigorous unit physical training,
Page 23

 F I G U R E 1 . Incident cases of exertional
rhabdomyolysis by year, active component,
U.S. Armed Forces, 2014–2018

500

35.2

No. of incident cases (bars)

285

400
304

40.0

30.0

262

25.0

259
300

100.0

35.0

30.0

216

20.0

15.0

200

100

186

199

222

239

260

10.0

5.0

0

2014 2015 2016 2017 2018

Marine Corps
Army
Air Force
Navy

45.0

Incidence rate per 100,000 person-years (line)

600

120.0

0.0

Incident cases per 100,000 p-yrs

Hospitalizations
Ambulatory visits
Rates
42.0
40.8
39.0

F I G U R E 2. Annual incidence rates of exertional rhabdomyolysis by service, active component, U.S. Armed Forces, 2014–2018

99.0
88.7

87.6

52.0

50.8

21.5

20.9

74.9

80.0
65.4
60.0

45.1
35.6

40.0

20.0

20.2

10.3

11.8

2014

2015

0.0

15.8
2016

2017

2018

F I G U R E 3. Distribution of exertional rhabdomyolosis cases by month, 2014–2018
Figure 3. Distribution of exertional rhabdomyolosis cases by month, 2014-2018

450
372

401

386

No. of cases

350

24

14.8

11.9

P-yrs, person-years

400

 Page

18.1

20.0

No., number; p-yrs, person-years

personal fitness training, and field training
exercises regardless of weather conditions.
Thus, it is not surprising that recruit camps
and installations with large ground combat
units account for most of the cases of exertional rhabdomyolysis.
The annual incidence rates among
non-Hispanic black service members
were higher than the rates among members of other race/ethnicity groups in 4 of
the 5 previous years, with the exception
of 2018. This observation has been attributed, at least in part, to an increased risk
of exertional rhabdomyolysis among individuals with sickle cell trait16–19 and is supported by at least 1 other study among
U.S. service members.9 However, in 2018,
the rate among Asian/Pacific Islanders was the highest of all race/ethnicity
groups. Although the annual incidence
rates of exertional rhabdomyolysis for
service members in this group have been

54.8

302

300
250

198

200
150
100

180

152
76

85

Jan

Feb

111

105

64

50
0

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

No., number

increasing since 2009, the reasons for such
a trend are unknown. Supervisors at all levels should ensure that guidelines to prevent
heat injuries are consistently implemented
and should be vigilant for early signs of
exertional heat injuries, including rhabdomyolysis, among all service members.

The findings of this report should be
interpreted with consideration of its limitations. A diagnosis of “rhabdomyolysis”
alone does not indicate the cause. Ascertainment of the probable causes of cases of
exertional rhabdomyolysis was attempted
by using a combination of ICD-9/ICD-10
MSMR  Vol. 26  No. 04  April 2019

 TA B L E 2 . Incident cases of exertional

rhabdomyolysis by installation (with at
least 30 cases during the period), active component, U.S. Armed Forces,
2014–2018
Location of diagnosis

No.

Fort Bragg, NC

272

%
total
11.2

MCRD Parris Island/
Beaufort, SC

250

10.3

MCB Camp Pendleton, CA

133

5.5

Fort Benning, GA

128

5.3

MCB Camp Lejeune/
Cherry Point, NC

112

4.6

Fort Shafter, HI

83

3.4

JBSA-Lackland AFB, TX

70

2.9

Fort Hood, TX

67

2.8

Fort Campbell, KY

61

2.5

Fort Leonard Wood, MO

57

2.3

Fort Carson, CO

54

2.2

NMC San Diego, CA

49

2.0

Fort Gordon, GA

46

1.9

Fort Bliss, TX

38

1.6

Fort Belvoir, VA

38

1.6

Fort Stewart, GA

36

1.5

Fort Jackson, SC

35

1.4

Okinawa, Japan

34

1.4

Fort Polk, LA

31

1.3

NMC Portsmouth, VA

31

1.3

807

33.2

Other/unknown locations
Total

2,432 100.0

No., number; MCRD, Marine Corps Recruit Depot;
MCB, Marine Corps Base; JBSA, Joint Base San
Antonio; AFB, Air Force Base; NMC, Naval Medical
Center

diagnostic codes related to rhabdomyolysis with additional codes indicative of
the effects of exertion, heat, or dehydration. Furthermore, other ICD-9/ICD-10
codes were used to exclude cases of rhabdomyolysis that may have been secondary
to trauma, intoxication, or adverse drug
reactions.
The measures that are effective at preventing exertional heat injuries in general apply to the prevention of exertional
rhabdomyolysis. In the military training setting, the risk of exertional rhabdomyolysis can be reduced by emphasizing
graded, individual preconditioning before

April 2019   Vol. 26  No. 04  MSMR 

starting a more strenuous exercise program and by adhering to recommended
work/rest and hydration schedules, especially in hot weather. The physical activities
of overweight and/or previously sedentary
new recruits should be closely monitored.
Strenuous activities during relatively cool
mornings following days of high heat stress
should be particularly closely monitored; in
the past, such situations have been associated with increased risk of exertional heat
injuries (including rhabdomyolysis).8
Management after treatment for exertional rhabdomyolysis, including the decision to return to physical activity and duty,
is a persistent challenge among athletes
and military members.9,10,20 It is recommended that those who have had a clinically confirmed exertional rhabdomyolysis
event be further evaluated and risk stratified for recurrence before return to activity/
duty.10,21,22 Low-risk patients may gradually
return to normal activity levels, while those
deemed high risk for recurrence will require
further evaluative testing (e.g., genetic testing for myopathic disorders).20,21
Commanders and supervisors at
all levels should watch for early signs of
exertional heat injuries and should intervene aggressively when dangerous conditions, activities, or suspicious illnesses are
detected. Finally, medical care providers
should consider exertional rhabdomyolysis
in the differential diagnosis when service
members (particularly recruits) present
with muscular pain or swelling, limited
range of motion, or the excretion of dark
urine (possibly due to myoglobinuria) after
strenuous physical activity, particularly in
hot, humid weather.

REFERENCES
1. Zutt R, van der Kooi AJ, Linthorst GE, Wanders
RJ, de Visser M. Rhabdomyolysis: review of the
literature. Neuromuscul Disord. 2014;24(8):651–
659.
2. Giannoglou GD, Chatzizisis YS, Misirli G. The
syndrome of rhabdomyolysis: pathophysiology and
diagnosis. Eur J Intern Med. 2007;18(2):90–100.
3. Rawson ES, Clarkson PM, Tarnopolsky MA.
Perspectives on exertional rhabdomyolysis. Sports
Med. 2017;47(Suppl 1):33–49.

4. McKewon S. Two Nebraska football players hospitalized, treated after offseason workout.
Omaha World-Herald. 20 January 2019. https://
www.omaha.com/huskers/football/two-nebraskafootball-players-hospitalized-treated-after-offseason-workout/article_d5929674-53a7-5d90-803e6b4e9205ee60.html. Accessed 06 March 2019.
5. Raleigh MF, Barrett JP, Jones BD, Beutler AI,
Deuster PA, O'Connor FG. A cluster of exertional
rhabdomyolysis cases in a ROTC program engaged in an extreme exercise program. Mil Med.
2018;183(suppl 1):516–521.
6. Bosch X, Poch E, Grau JM. Rhabdomyolysis and acute kidney injury. N Engl J Med.
2009;361(1):62–72.
7. Hill OT, Wahi MM, Carter R, Kay AB, McKinnon
CJ, Wallace RE. Rhabdomyolysis in the U.S. active duty Army, 2004–2006. Med Sci Sports Exerc.
2012;44(3):442–449.
8. Lee G. Exercise-induced rhabdomyolysis. R I
Med J (2013). 2014;97(11):22–24.
9. Hill OT, Scofield DE, Usedom J, et al. Risk factors for rhabdomyolysis in the U.S. Army. Mil Med.
2017;182(7):e1836–e1841.
10. Knapik JJ, O’Connor FG. Exertional rhabdomyolysis: epidemiology, diagnosis, treatment, and
prevention. J Spec Oper Med. 2016;15(3):65–71.
11. Holt S, Moore K. Pathogenesis of renal failure in rhabdomyolysis: the role of myoglobin. Exp
Nephrol. 2000;8(2):72–76.
12. Armed Forces Health Surveillance Branch.
Update: Exertional rhabdomyolysis, active component, U.S. Army, Navy, Air Force, and Marine
Corps, 2011–2015. MSMR. 2016;23(3):21–24.
13. Armed Forces Health Surveillance Branch.
Update: Exertional rhabdomyolysis among active
component members, U.S. Armed Forces, 2012–
2016. MSMR. 2017;24(3):14–18.
14. Armed Forces Health Surveillance Branch.
Update: Exertional rhabdomyolysis among active
component members, U.S. Armed Forces, 2013–
2017. MSMR. 2018;25(4):13–17.
15. Armed Forces Health Surveillance Branch.
Surveillance Case Definition. Exertional Rhabdomyolysis. April 2017. https://www.health.mil/Reference-Center/Publications/2017/03/01/Rhabdomyolysis-Exertional. Accessed 05 March 2019.
16. Gardner JW, Kark JA. Fatal rhabdomyolysis
presenting as mild heat illness in military training.
Mil Med. 1994;159(2):160–163.
17. Makaryus JN, Catanzaro JN, Katona KC. Exertional rhabdomyolysis and renal failure in patients with sickle cell trait: is it time to change our
approach? Hematology. 2007;12(4):349–352.
18. Ferster K, Eichner ER. Exertional sickling
deaths in Army recruits with sickle cell trait. Mil
Med. 2012;177(1):56–59.
19. Nelson DA, Deuster PA, Kurina LM. Sickle cell
trait and rhabdomyolysis among U.S. Army soldiers. N Engl J Med. 2016;375(17):1696.
20. O’Connor FG, Brennan FH Jr, Campbell W,
Heled Y, Deuster P. Return to physical activity after
exertional rhabdomyolysis. Curr Sports Med Rep.
2008;7(6):328–331.
21. Atias D, Druyan A, Heled Y. Recurrent exertional rhabdomyolysis: coincidence, syndrome,
or acquired myopathy? Curr Sports Med Rep.
2013;12(6):365–369.

Page 25

 CE/CME
This activity offers continuing education (CE) and continuing medical education (CME) to qualified professionals as well as a certificate of participation to those desiring documentation. For more information, go to www.health.mil/msmrce.

Key points
• The unadjusted overall incidence rate of exertional rhabdomyolysis diagnoses among active component service members in 2018
was 42.0 cases per 100,000 person-years. Subgroup-specific overall rates in 2018 were highest among males, those less than 20
years old, Asian/Pacific Islander service members, Marine Corps and Army members, and those in combat-specific or “other/
unknown” occupations.
• During 2014–2018, crude annual rates of incident exertional rhabdomyolysis diagnoses increased steadily from 2014 through
2016 after which rates declined slightly in 2017 before increasing again in 2018; compared to service members in other race/ethnicity groups, the annual rates of exertional rhabdomyolysis were highest among non-Hispanic blacks in every year except 2018.
• Overall and annual rates of incident exertional rhabdomyolysis were highest among Marine Corps members, intermediate among
those in the Army, and lowest among those in the Air Force and Navy.

Learning objectives
1. The reader will analyze recent trends in the rates of incident exertional rhabdomyolysis diagnoses among active component service members.
2. The reader will explain how incidence rates of exertional rhabdomyolysis diagnoses among active component service members of
different race/ethnicities compare over the surveillance period.
3. The reader will identify risk factors for and signs of exertional rhabdomyolysis as well as ways to reduce the risk of rhabdomyolysis among service members.
Disclosures: MSMR editorial staff engage in a monthly collaboration with the DHA J7 Continuing Education Program Office (CEPO) to provide this CE/CME activity. MSMR staff authors, the DHA J7 CEPO, as well as the planners and reviewers of this activity have no financial or
nonfinancial interest to disclose.

 Page

26

MSMR  Vol. 26  No. 04  April 2019

 Update: Exertional Hyponatremia, Active Component, U.S. Armed Forces, 2003–2018

From 2003 through 2018, there were 1,579 incident diagnoses of exertional
hyponatremia among active component service members, for a crude overall incidence rate of 7.2 cases per 100,000 person-years (p-yrs). Compared
to their respective counterparts, females, those less than 20 years old, and
recruit trainees had higher overall incidence rates of exertional hyponatremia diagnoses. The overall incidence rate during the 16-year period was
highest in the Marine Corps, intermediate in the Army and Air Force, and
lowest in the Navy. Overall rates during the surveillance period were highest among Asian/Pacific Islander and non-Hispanic white service members
and lowest among non-Hispanic black service members. Between 2003 and
2018, crude annual incidence rates of exertional hyponatremia peaked in
2010 (12.7 per 100,000 p-yrs) and then decreased to 5.3 cases per 100,000
p-yrs in 2013 before increasing in 2014 and 2015. The crude annual rate in
2018 (6.3 per 100,000 p-yrs) represented a decrease of 26.5% from 2015. Service members and their supervisors must be knowledgeable of the dangers of
excessive water consumption and the prescribed limits for water intake during prolonged physical activity (e.g., field training exercises, personal fitness
training, and recreational activities) in hot, humid weather.

E

xertional (or exercise-associated)
hyponatremia refers to a low serum,
plasma, or blood sodium concentration (below 135 milliequivalents/liter)
that develops during or up to 24 hours following prolonged physical activity.1 Acute
hyponatremia creates an osmotic imbalance between fluids outside and inside of
cells. This osmotic gradient causes water to
flow from outside to inside the cells of various organs, including the lungs (which can
cause pulmonary edema) and brain (which
can cause cerebral edema), producing serious and sometimes fatal clinical effects.1,2
Swelling of the brain increases intracranial
pressure, which can decrease cerebral blood
flow and disrupt brain function, potentially
causing hypotonic encephalopathy, seizures,
or coma. Rapid and definitive treatment is
needed to relieve increasing intracranial
pressure and prevent brain stem herniation,
which can result in respiratory arrest.2–4
Serum sodium concentration is determined mainly by the total content of
April 2019   Vol. 26  No. 04  MSMR 

exchangeable body sodium and potassium
relative to total body water. Thus, exertional
hyponatremia can result from loss of sodium
and/or potassium, a relative excess of body
water, or a combination of both.5,6 However,
overconsumption of fluids and the resultant excess of total body water are the primary driving factors in the development of
exertional hyponatremia.1,7,8 Other important factors include the persistent secretion
of antidiuretic hormone (arginine vasopressin), excessive sodium losses in sweat,
and inadequate sodium intake during prolonged physical exertion, particularly during
heat stress.2–4,9 The importance of sodium
losses through sweat in the development of
exertional hyponatremia is influenced by
the fitness level of the individual. Less fit
individuals generally have a higher sweat
sodium concentration, a higher rate of sweat
production, and an earlier onset of sweating
during exercise.10–12
This report uses a surveillance case
definition for exertional hyponatremia to

WHAT ARE THE NEW FINDINGS?
During 2003–2018, annual numbers and
rates of diagnoses of exertional hyponatremia among active component U.S. military
members were relatively stable from year
to year with the exception of 2009–2011
when rates were dramatically higher. Overall
incidence rates of exertional hyponatremia
by subgroups of demographic and military
characteristics were generally similar to
those reported in previous MSMR updates.

WHAT IS THE IMPAC T ON
R E AD INE S S AND FO RC E HE ALTH
PROTECTION?
Exertional hyponatremia continues to pose a
health risk to U.S. military members and can
significantly impair performance and reduce
combat effectiveness. Military members
(particularly recruit trainees and women) and
their supervisors must be vigilant for early
signs of heat-related illnesses, intervene immediately and appropriately (but not excessively) in such cases, and heed the recently
validated guidance on fluid intake.

estimate the frequencies, rates, trends, geographic locations, and demographic and
military characteristics of exertional hyponatremia cases among U.S. military members from 2003 through 2018.13

METHODS

The surveillance period was 1 January
2003 through 31 December 2018. The surveillance population included all individuals who served in an active component of
the U.S. Army, Navy, Air Force, or Marine
Corps at any time during the surveillance
period. All data used to determine incident
exertional hyponatremia diagnoses were
derived from records routinely maintained
in the Defense Medical Surveillance System (DMSS). These records document both
ambulatory encounters and hospitalizations
of active component service members of
the U.S. Armed Forces in fixed military and
Page 27

 civilian (if reimbursed through the Military
Health System [MHS]) treatment facilities
worldwide. In-theater diagnoses of hyponatremia were identified from medical records
of service members deployed to Southwest
Asia/Middle East and whose healthcare
encounters were documented in the Theater
Medical Data Store (TMDS). TMDS records
became available in the DMSS beginning in
2008.
For this analysis, a case of exertional
hyponatremia was defined as 1) a hospitalization or ambulatory visit with a primary
(first-listed) diagnosis of “hypo-osmolality
and/or hyponatremia” (International Classification of Diseases, 9th Revision [ICD-9]:
276.1; International Classification of Diseases, 10th Revision [ICD-10]: E87.1) and
no other illness or injury-specific diagnoses
(ICD-9: 001–999) in any diagnostic position or 2) both a diagnosis of “hypo-osmolality and/or hyponatremia” (ICD-9: 276.1;
ICD-10: E87.1) and at least 1 of the following within the first 3 diagnostic positions:
“fluid overload” (ICD-9: 276.9; ICD-10:
E87.70, E87.79), “alteration of consciousness” (ICD-9: 780.0*; ICD-10: R40.*), “convulsions” (ICD-9: 780.39; ICD-10: R56.9),
“altered mental status” (ICD-9: 780.97; ICD10: R41.82), “effects of heat/light” (ICD-9:
992.0–992.9; ICD-10: T67.0*–T67.9*), or
“rhabdomyolysis” (ICD-9: 728.88; ICD-10:
M62.82).13
Medical encounters were not considered case-defining events if the associated
records included the following diagnoses in
any diagnostic position: alcohol/illicit drug
abuse; psychosis, depression, or other major
mental disorders; endocrine (e.g., pituitary
or adrenal) disorders; kidney diseases; intestinal infectious diseases; cancers; major traumatic injuries; or complications of medical
care. Each individual could be considered
an incident case of exertional hyponatremia
only once per calendar year.
For surveillance purposes, a “recruit
trainee” was defined as an active component member in an enlisted grade (E1–E4)
who was assigned to 1 of the services’ recruit
training locations (per the individual’s initial
military personnel record). For this report,
each service member was considered a
recruit trainee for the period corresponding
to the usual length of recruit training in his/
her service. Recruit trainees were considered
 Page

28

a separate category of enlisted service members in summaries of exertional hyponatremia by military grade overall.
In-theater diagnoses of exertional
hyponatremia were analyzed separately
using the same case-defining criteria and
incidence rules that were applied to identify incident cases at fixed treatment facilities. Records of medical evacuations from
the U.S. Central Command (CENTCOM)
area of responsibility (AOR) (e.g., Iraq and
Afghanistan) to a medical treatment facility
outside the CENTCOM AOR were analyzed
separately. Evacuations were considered case
defining if the affected service members met
the above criteria in a permanent military
medical facility in the U.S. or Europe from 5
days before to 10 days after their evacuation
dates.
The new electronic health record for the
MHS, MHS GENESIS, was implemented
at several military treatment facilities during 2017. Medical data from sites that are
using MHS GENESIS are not available in
the DMSS. These sites include Naval Hospital Oak Harbor, Naval Hospital Bremerton,
Air Force Medical Services Fairchild, and
Madigan Army Medical Center. Therefore,
medical encounter data for individuals seeking care at any of these facilities during 2017–
2018 were not included in this analysis.

TA B L E 1. Incident casesa and ratesb of
hyponatremia/overhydration diagnoses,
active component, U.S. Armed Forces,
January 2003–December 2018
2018

Total
2003–2018

No. Rateb No. Rateb
Total

82

6.3 1,579

7.2

Male

70

6.5 1,317

7.1

Female

12

5.6

8.1

<20

14

13.8

20–24

22

5.3

498

7.0

25–29

14

4.7

282

5.6

30–34

16

7.8

177

5.4

35–39

7

4.7

181

7.0

40+

9

7.2

237 10.4

Sex
262

Age group (years)
204 13.6

Race/ethnicity
Non-Hispanic
white

44

6.0 1,070

8.1

Non-Hispanic
black

16

7.7

195

5.4

Hispanic

13

6.3

157

5.8

Asian/Pacific
Islander

5

9.2

68

8.3

Other/unknown

4

4.3

89

6.2

Army

29

6.2

553

6.8

Navy

21

6.5

254

4.8

Air Force

12

3.7

315

5.9

Marine Corps

20

10.8

457 15.2

Recruit

11

39.1

143 31.9

Enlisted

56

5.4 1,110

6.3

Officer

15

6.5

326

8.9

Service

Military status

R E SULT S

During 2003–2018, permanent medical facilities recorded 1,579 incident diagnoses of exertional hyponatremia among
active component service members, for a
crude overall incidence rate of 7.2 cases per
100,000 person-years (p-yrs) (Table 1). In
2018, there were 82 incident diagnoses of
exertional hyponatremia (incidence rate: 6.3
per 100,000 p-yrs) among active component
service members. During this year, males
represented 85.4% of exertional hyponatremia cases (n=70); the annual incidence rate
was slightly higher among males (6.5 per
100,000 p-yrs) than females (5.6 per 100,000
p-yrs) (Table 1). The highest age group-specific annual incidence rates in 2018 were
among the youngest (less than 20 years
old) service members. Although the Army
had the most cases during 2018 (n=29), the

Military occupation
Combat-specificc

20

11.3

264

8.5

Motor transport

3

7.9

33

5.1

Pilot/air crew

3

6.5

48

5.8

Repair/
engineering

13

3.4

286

4.5

Communications/intelligence

17

6.1

278

5.7
6.4

Healthcare

4

3.5

119

22

8.5

551 13.4

15

6.5

299

7.4

8

4.9

232

8.2

South

39

7.1

668

7.4

West

19

6.2

302

6.2

1

2.4

78

7.8

Other/unknown
Home of recordd
Midwest
Northeast

Other/unknown

One case per person per year
b
Number of cases per 100,000 person-years
c
Infantry/artillery/combat engineering/armor
d
As self-reported at time of entry into service
No., number
a

MSMR  Vol. 26  No. 04  April 2019

 Exertional hyponatremia by location
During the 16-year surveillance
period, exertional hyponatremia cases were
diagnosed at the medical treatment facilities of more than 150 U.S. military installations and geographic locations worldwide;
April 2019   Vol. 26  No. 04  MSMR 

F I G U R E 1. Annual incident cases and rates of incident diagnoses of exertional hyponatremia, active component, U.S. Armed Forces, 2003–2018
12.7

Hospitalizations
Ambulatory visits
Rate

180

12.0
10.5

120
6.4

100

5.5
4.3

51

12

5.3
155
134

66

75

64

14

6.1

10

12

18

131

67

6.7

14
18

10

88

86

8.0

7.2

6.9 7.1
8

9.0

83

6.0

13

6.3

6.0
12

5.0

4.0

98

3.0
68

62

7.0

64

70

2.0

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

1.0

2003

0

11

5.5

8.6

16

10

40
20

11.0

10.4

10.0

140

60

25

14

2004

No. of incident diagnoses (bars)

160

80

13.0

Rate of incident diagnoses per 100,000 p-yrs (line)

200

0.0

No., number; p-yrs, person-years

F I G U R E 2. Annual incidence rates of exertional hyponatremia, by service, active component,
U.S. Armed Forces, 2003–2018
30.0

Marine Corps
Army
Navy
Air Force

25.0

20.0

15.0

10.0

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

0.0

2004

5.0

2003

Incidence rate per 100,000 p-yrs

highest incidence rate was among members
of the Marine Corps (10.8 per 100,000 p-yrs).
In 2018, there were only 11 cases of exertional hyponatremia among recruit trainees,
but their incidence rate was 6 times that of
officers and more than 7 times that of other
enlisted members (Table 1).
During the 16-year surveillance period,
females had a slightly higher overall incidence
rate of exertional hyponatremia diagnoses
than males (Table 1). The overall incidence
rate was highest in the Marine Corps (15.2
per 100,000 p-yrs) and lowest in the Navy
(4.8 per 100,000 p-yrs). Overall rates during
the surveillance period were highest among
Asian/Pacific Islander (8.3 per 100,000 p-yrs)
and non-Hispanic white service members
(8.1 per 100,000 p-yrs) and lowest among
non-Hispanic black service members (5.4
per 100,000 p-yrs). Although recruit trainees
accounted for less than one-tenth (9.1%) of
all exertional hyponatremia cases, their overall crude incidence rate was 5.1 and 3.6 times
the rates among other enlisted members and
officers, respectively (Table 1). During the
16-year period, 86.3% (n=1,362) of all cases
were diagnosed and treated without having
to be hospitalized (data not shown).
Between 2003 and 2018, crude annual
rates of incident exertional hyponatremia
diagnoses peaked in 2010 (12.7 per 100,000
p-yrs) and then decreased to 5.3 cases per
100,000 p-yrs in 2013 before increasing in
2014 and 2015. The crude annual incidence
rate in 2018 (6.3 per 100,000 p-yrs) represented a decrease of 26.5% from 2015 (Figure 1). During 2003–2018, annual incidence
rates of exertional hyponatremia diagnoses were consistently higher among those
in the Marine Corps compared to those in
the other services, with the overall trend
in rates primarily influenced by the trend
among Marine Corps members (Figure 2).
Between 2017 and 2018, annual incidence
rates decreased among Marine Corps members, increased among members of the Navy,
and remained relatively stable among members of the Army and the Air Force (Figure 2).

P-yrs, person-years

however, 14 U.S. installations contributed
20 or more cases each and accounted for
47.6% of the total cases (Table 2). The installation with the most exertional hyponatremia cases overall was the Marine Corps
Recruit Depot (MCRD) Parris Island/
Beaufort, SC (n=205).

Exertional hyponatremia in Iraq and Afghanistan
From 2008 through 2018, a total of
18 cases of exertional hyponatremia were
diagnosed and treated in Iraq and Afghanistan. Deployed service members who were
affected by exertional hyponatremia were
Page 29

 TA B L E 2 . Incident cases of exertional

hyponatremia, by installation (with at
least 20 cases during the period), active component, U.S. Armed Forces,
2003–2018
Location of diagnosis

No.

MCRD Parris Island/
Beaufort, SC

%
total

205

13.0

Fort Benning, GA

107

6.8

JBSA-Lackland AFB, TX

64

4.1

Fort Bragg, NC

51

3.2

MCB Camp Lejeune/Cherry
Point, NC

48

3.0

Walter Reed NMMC, MDa

46

2.9

MCB Camp Pendleton, CA

37

2.3

MCB Quantico, VA

36

2.3

NMC San Diego, CA

34

2.2

NMC Portsmouth, VA

32

2.0

Fort Jackson, SC

25

1.6

Fort Shafter, HI

23

1.5

Fort Campbell, KY

22

1.4

Fort Leonard Wood, MO

22

1.4

Other/unknown locations

827

52.4

Total

1,579 100.0

Walter Reed National Military Medical Center
(NMMC) is a consolidation of National Naval Medical Center (Bethesda, MD) and Walter Reed Army
Medical Center (Washington, DC). This number
represents the sum of the 2 sites prior to the
consolidation (November 2011) and the number
reported at the consolidated location.

a

No., number; MCRD, Marine Corps Recruit Depot;
JBSA, Joint Base San Antonio; AFB, Air Force
Base; MCB, Marine Corps Base; NMC, Naval
Medical Center

most frequently male (n=16; 88.9%), nonHispanic white (n=14; 77.8%), aged 20–24
years (n=8; 44.4%), in the Army (n=13;
72.2%), enlisted (n=15; 83.3%), and in
combat-specific (n=7; 38.9%) or communications/intelligence (n=4; 22.2%) occupations (data not shown). During the entire
surveillance period, 9 service members
were medically evacuated from Iraq or
Afghanistan for exertional hyponatremia
(data not shown).
 Page

30

EDITORIAL COMMENT

This report documents that after a
2-year period (2014–2015) of elevated
numbers and rates of exertional hyponatremia among active component U.S. military
members, numbers and rates of diagnoses
decreased slightly during 2016–2018. Subgroup-specific patterns of overall incidence
rates of exertional hyponatremia (e.g., sex,
age, race/ethnicity, service, and military status) were generally similar to those reported
in previous MSMR updates.14,15 It is important to note that in MSMR analyses prior to
April 2018, in-theater cases were included
if there was a diagnosis of hypo-osmolality and/or hyponatremia in any diagnostic position. Beginning last year, the same
case-defining criteria that were applied to
inpatient and outpatient encounters were
applied to the in-theater encounters. Therefore, the results of the in-theater analysis are
not comparable to those presented in earlier
MSMR updates.
Several important limitations should
be considered when interpreting the results
of this analysis. First, there is no diagnostic
code specific for exertional hyponatremia.
Thus, for surveillance purposes, cases of presumed exertional hyponatremia were ascertained from records of medical encounters
that included diagnoses of hypo-osmolality and/or hyponatremia but not of other
conditions (e.g., metabolic, renal, psychiatric, or iatrogenic disorders) that increase
the risk of hyponatremia in the absence of
physical exertion or heat stress. As such,
exertional hyponatremia cases here likely
include hyponatremia from both exerciseand non–exercise-related conditions. Consequently, the results of this analysis should
be considered estimates of the actual incidence of symptomatic exertional hyponatremia from excessive water consumption
among U.S. military members. In addition,
the accuracy of estimated numbers, rates,
trends, and correlates of risk depends on
the completeness and accuracy of diagnoses that are documented in standardized
records of relevant medical encounters. As
a result, an increase in recorded diagnoses
indicative of exertional hyponatremia may
reflect, at least in part, increasing awareness of, concern regarding, and aggressive

management of incipient cases by military supervisors and primary healthcare
providers.
In the past, concerns about hyponatremia resulting from excessive water
consumption were focused at training—
particularly recruit training—installations.
In this analysis, rates were relatively high
among the youngest, and hence the most
junior service members, and the highest
numbers of cases tended to be diagnosed at
medical facilities that support large recruit
training centers (e.g., MCRD Parris Island/
Beaufort, SC; Fort Benning, GA; and Joint
Base San Antonio–Lackland Air Force Base,
TX) and large Army and Marine Corps
combat units (e.g., Fort Bragg, NC, and
Marine Corps Base Camp Lejeune/Cherry
Point, NC).
In response to previous historical cases
of exertional hyponatremia in the U.S. military, the guidelines for fluid replacement
during military training in hot weather
were revised and promulgated in 1998.16–19
The revised guidelines were designed to
protect service members from not only heat
injury but also hyponatremia due to excessive water consumption by limiting fluid
intake regardless of heat category or work
level to no more than 1.5 quarts hourly and
12 quarts daily.17,18 There were fewer hospitalizations of soldiers for hyponatremia
due to excessive water consumption during
the year after (vs. the year before) implementation of the new guidelines.20 In 2003,
the revised guidelines were included in the
multi-service Technical Medical Bulletin
507, Heat Stress Control and Heat Casualty Management that provides guidance to
military and civilian healthcare providers,
allied medical personnel, and military leadership.21 A recent study found that this military fluid intake guidance remains valid for
preventing excessive dehydration as well as
overhydration and can be used by military
health professionals and leadership to adequately maintain a normal level of hydration in service members working in the 5
designated flag conditions (levels of heat/
humidity stress) while wearing contemporary uniform configurations (including
protective gear/equipment) across a range
of metabolic rates.22
During endurance events, a “drink-tothirst” or a programmed fluid intake plan
MSMR  Vol. 26  No. 04  April 2019

 of 400–800 mL per estimated hour of activity has been suggested to limit the risk of
exertional hyponatremia, although this rate
should be customized to the individual’s
tolerance and experience.4,8,18,20 In addition
to these guidelines, reducing the availability of fluids may help prevent exertional
hyponatremia during endurance events.23,24
Carrying a maximum fluid load of 1 quart
of fluid per estimated hour of activity and
encouraging a “drink-to-thirst” approach
to hydration may help prevent both severe
exertional hyponatremia and dehydration
during military training exercises and recreational hikes that exceed 2–3 hours.4,8,23,24
Women had relatively high rates of
hyponatremia during the entire surveillance period; women may be at greater risk
because of lower fluid requirements and
longer periods of exposure to risk during
some training exercises (e.g., land navigation courses or load-bearing marches).9 The
finding that the overall incidence of women
experiencing exertional hyponatremia was
greater than that of men in this analysis is
similar to results found among samples of
marathon runners in the general population. However, a large study of marathon
runners suggested that the apparent sex difference did not remain after adjustment for
body mass index and racing times.25–27
In many circumstances (e.g., recruit
training and Ranger School), military
trainees rigorously adhere to standardized
training schedules regardless of weather
conditions. In hot and humid weather,
commanders, supervisors, instructors, and
medical support staff must be aware of and
enforce guidelines for work–rest cycles and
water consumption. The finding in this
report that most cases of hyponatremia were
treated in outpatient settings suggests that
monitoring by supervisors and medical staff
identified most cases during the early and
less severe manifestations of hyponatremia.
In general, service members and their
supervisors must be knowledgeable of the
dangers of excessive water consumption
as well as the prescribed limits for water
intake during prolonged physical activity (e.g., field training exercises, personal

April 2019   Vol. 26  No. 04  MSMR 

fitness training, and recreational activities)
in hot, humid weather. Military members
(particularly recruit trainees and women)
and their supervisors must be vigilant for
early signs of heat-related illnesses and
intervene immediately and appropriately
(but not excessively) in such cases. Finally,
the recent validation of the current fluid
intake guidance highlights its importance as
a resource to leadership in sustaining military readiness.22
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3. Chorley J, Cianca J, Divine J. Risk factors for
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477.
4. Hew-Butler T, Loi V, Pani A, Rosner MH. Exercise-associated hyponatremia: 2017 update. Front
Med (Lausanne). 2017;4:21
5. Edelman IS, Leibman J, O’Meara MP, Birkenfeld LW. Interrelations between serum sodium concentration, serum osmolarity and total exchangeable sodium, total exchangeable potassium and
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7. Noakes TD, Sharwood K, Speedy D, et al.
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Surveillance-Case-Definitions. Accessed 6 March
2019.
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GA; Fort Leonard Wood, MO; Fort Jackson, SC,
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weather. Mil Med. 1999;164(7):502–508.
19. O’Brien KK, Montain SJ, Corr WP, Sawka MN,
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Page 31

 Medical Surveillance Monthly Report (MSMR)
Armed Forces Health Surveillance Branch
11800 Tech Road, Suite 220
Silver Spring, MD 20904

Chief, Armed Forces Health Surveillance Branch
 COL Douglas A. Badzik, MD, MPH (USA)
Editor
Francis L. O’Donnell, MD, MPH
Contributing Editors
Leslie L. Clark, PhD, MS
Shauna Stahlman, PhD, MPH
Writer/Editor
Valerie F. Williams, MA, MS
Managing/Production Editor
Donna K. Lormand, MPH
Data Analysis
Alexis A. Oetting, MPH
Gi-Taik Oh, MS
Layout/Design
Darrell Olson
Editorial Oversight
COL James D. Mancuso, MD, MPH, DrPH (USA)
CDR Shawn S. Clausen, MD, MPH (USN)
Mark V. Rubertone, MD, MPH

MEDICAL SURVEILLANCE MONTHLY REPORT (MSMR), in continuous publication
since 1995, is produced by the Armed Forces Health Surveillance Branch (AFHSB).
AFHSB is a designated public health authority within the Defense Health Agency. The
MSMR provides evidence-based estimates of the incidence, distribution, impact, and
trends of illness and injuries among U.S. military members and associated populations.
Most reports in the MSMR are based on summaries of medical administrative data
that are routinely provided to the AFHSB and integrated into the Defense Medical
Surveillance System for health surveillance purposes.
Archive: Past issues of the MSMR are available as downloadable PDF files at www.
health.mil/MSMRArchives.
Online Subscriptions: Submit subscription requests at www.health.mil/MSMRSubscribe. 
Editorial Inquiries: Call (301) 319-3240 or email dha.ncr.health-surv.mbx.msmr@
mail.mil.
Instructions for Authors:  Information about article submissions is provided at www.
health.mil/MSMRInstructions.
All material in the MSMR is in the public domain and may be used and reprinted
without permission. Citation formats are available  at  www.health.mil/MSMR.
Opinions and assertions expressed in the MSMR should not be construed as reflecting
official views, policies, or positions of the Department of Defense or the United States
Government.

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ISSN 2158-0111 (print)
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