Maas, J., Verheij, R.A., Vries, S. de, Spreeuwenberg, P., Groenewegen, P.P., Schellevis, F.G. Morbidity is
related to a green living environment. Journal of Epidemiology & Community Health: 2009, 63(12), 967-973

Postprint Version
1.0
Journal website
http://jech.bmj.com/cgi/content/abstract/jech.2008.079038v1
Pubmed link
http://www.ncbi.nlm.nih.gov/pubmed/19833605
DOI
10.1136/jech.2008.079038
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Morbidity is related to a green living environment
JOLANDA MAAS M.SC. (1), ROBERT A. VERHEIJ PHD (1), SJERP DE VRIES PHD (3), PETER SPREEUWENBERG
(1)
, FRANCOIS G. SCHELLEVIS MD, PHD (1) (4), PETER P. GROENEWEGEN PHD (1) (2)
1)

NIVEL (Netherlands Institute for Health Services Research), Utrecht, the Netherlands
) Utrecht University, Department of Human Geography, Department of Sociology, P.O. Box 80115, NL3508 TC Utrecht, The Netherlands
3)
Alterra, Green World Research, P.O. Box 47 NL-6700 AA Wageningen, The Netherlands
4)
Department of General Practice/ EMGO Institute VU University Medical Centre, Amsterdam, The
Netherlands
Correspondence to: J. Maas MSc.,
NIVEL, Netherlands Institute for Health Services Research
P.O Box 1568 3500 BN Utrecht the Netherlands
Tel: +31-30-2729846
Fax: +31-30-2729729
e-mail address: j.maas@nivel.nl
2

ABSTRACT
Background Due to increasing urbanisation people face the prospect of living in environments
with few green spaces. There is increasing evidence for a positive relation between green space
in people's living environment and self-reported indicators of physical and mental health. This
study investigates whether physician assessed morbidity is also related to green space in
people’s living environment.
Methods Morbidity data were derived from electronic medical records of 195 general
practitioners in 96 Dutch practices, serving a population of 345,143 people. Morbidity was
classified by the general practitioners according to the International Classification of Primary
Care (ICPC). The percentage of green space within a one kilometre and three kilometre radius
around the postal code coordinates was derived from an existing database and was calculated
for each household. Multilevel logistic regression analyses were performed controlling for
demographic and socio-economic characteristics.
Results The annual prevalence rate of 15 of the 24 disease clusters was lower in living
environments with more green space in a 1 km radius. The relation was strongest for anxiety
disorder and depression. The relation was stronger for children and people with a lower
socioeconomic status. Furthermore, the relation was strongest in slightly urban areas and not
apparent in very strongly urban areas.
Conclusion This study indicates that the previously established relation between green space
and a number of self-reported general indicators of physical and mental health can also be
found for clusters of specific physician assessed morbidity. The study stresses the importance
of green space close to home for children and lower socio-economic groups.

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 Maas, J., Verheij, R.A., Vries, S. de, Spreeuwenberg, P., Groenewegen, P.P., Schellevis, F.G. Morbidity is
related to a green living environment. Journal of Epidemiology & Community Health: 2009, 63(12), 967-973

INTRODUCTION
Due to increasing urbanisation, combined with a planning policy of spatial densification, more people face
the prospect of living in residential environments with little green space. At the same time, increasing
evidence shows that green space has beneficial effects on people’s health. Evidence has been found for a
positive relation between green space and self perceived health, [1-4], longevity, [5], number of symptoms
and the risk of psychiatric morbidity.[1] Access to a garden and shorter distances to green areas from the
dwelling were associated with less stress and a lower likelihood of obesity. [6] Experimental studies
showed that there is a positive relation between green space and restoration from stress and mental fatigue.
More specific, exposure to nature has been found to have a positive effect on mood, concentration, selfdiscipline, and physiological stress. [7-11] These studies indicate that there is a relation between green
space and self reported general indicators of physical and mental health. Thus, people living in greener
environments report a better physical and mental health.
The decrease of green space could therefore have health consequences. However, it remains unknown
whether living in residential environments with little green space also has negative consequences for
objective health. In this explorative study we will go one step further than other studies and investigate
whether the prevalence of several physician assessed morbidity clusters is also related to the amount of
green space in people’s living environment. This is the first study to investigate the relation between green
space and prevalence of physician assessed morbidity. This study has an explorative character and takes
into account a broad number of diseases highly prevalent in society.
To gain more insight into the relation between green space and physician assessed morbidity we analysed
this relation separately for different age groups and different socio-economic groups. We hypothesise that
the relation is stronger for elderly people and children (as compared to adults) because, as a result of their
lower mobility, they spend more time in the vicinity of their home, resulting in higher exposure to green
space in their living environment.
The same applies to people with a lower socio-economic status, whose activities and social contacts are
situated close to their homes. [12,13] Therefore we also hypothesise that people with a lower socioeconomic status are more exposed to the green space in their living environment. Finally, the relation was
analysed for different levels of urbanicity to investigate whether the relation varies between urban and rural
areas.
METHODS
For this study data from two different datasets were combined. Morbidity data were collected within the
framework of the second Dutch National Survey in General Practice (DNSGP-2), which included a
nationwide, representative sample of 104 general practices with 195 GPs and a practice population of
approximately 400 000 enlisted people, who were representative for the Dutch population in terms of age,
gender and type of health insurance.[14] For this study data from 96 practices that recorded morbidity for a
full period of 12 months or more were used. This selection had no significant effect on the
representativeness of the data, because after the selection the sample was still representative for the Dutch
population. [14] Only people who had been registered with their current GP for longer than 12 months prior
to the study (n = 345 143) were included, because we assumed that people will have to live for at least 12
months in the same living environment before any effect of it would be noticeable.
Environmental data were derived from the National Land Cover Classification database (LGN4) in 2001,
which contains the dominant type of land use of each 25 x 25 metre grid cell of the Netherlands.[15] The
two datasets were matched on the basis of the x and y coordinates of the respondent’s six character postal
code (on average about 15 to 20 households have the same six character postal code). The dataset included
50187 postal codes and on average 6.9 respondents resided in each postal code area.
Morbidity data
Morbidity data were derived from routine primary care electronical medical records. In the Netherlands
morbidity presented in general practice is a good indicator of morbidity in the population [16]. Basically all
non-institutionalized people are registered with a GP.
Furthermore, GPs have a gate keeping role for secondary care and are usually the first point of contact
with the health care system. The data have been validated for obtaining prevalence estimates [17] During a
of 12 months period, data on all GP consultations with patients were extracted from the electronic medical
records. These data included contact diagnoses and indications (diagnoses) for medication and referral to
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 Maas, J., Verheij, R.A., Vries, S. de, Spreeuwenberg, P., Groenewegen, P.P., Schellevis, F.G. Morbidity is
related to a green living environment. Journal of Epidemiology & Community Health: 2009, 63(12), 967-973

secondary care. Prevalence rates are based on contacts that were classified by the GP according to the
International Classification of Primary Care (ICPC) and subsequently clustered into episodes of disease.
[18] The most prevalent episodes were combined into 24 disease clusters. These disease clusters have been
used in several other studies [19, 20] and include the most prevalent diseases in general practice (prevalence
> 10 per 1000) (see table 1). The 24 disease clusters have been distributed over disease categories, namely
cardiovascular diseases, musculoskeletal diseases, mental diseases, respiratory diseases, neurological
diseases, digestive diseases and miscellaneous.
Not all disease clusters were relevant for all age groups, therefore the epidemiological denominator varied
(table 1). A prevalence rate for each cluster was calculated by dividing the number of patients with at least
one disease episode in 2001 belonging to the cluster by the population at risk. The population at risk was
based on age groups in which the diseases occurred. Some disease clusters, like for instance high blood
pressure, were only present in the older age-groups. Therefore, for high blood pressure the prevalence rate
was calculated by dividing the number of patients with at least one high blood pressure episode in 2001 by
the older age-groups and not for the population as a whole.
[TABLE 1]
Characteristics of the respondents’ living environment
The LGN4 database discriminates 39 land use classes including crop types, forest types, water, various
urban classes and semi-natural classes and has been proven to be valid and accurate. [15, 21] The total
percentage of green space in the respondents’ living environment was measured within a 1-km radius and
within a 3-km radius around the postcode centroid of a respondent’s home, to see whether there is a
stronger relation for green space close by than green space further away. Only green spaces that dominate
the land use in the 25 by 25 meter grid cell (more than 50% of the grid cell is green) have been classified as
green space in the dataset. Small-scale green spaces, such as street trees and roadside vegetation were only
included as green space if they were dominant in the grid cell.
Urbanicity
Another environmental characteristic is urbanicity. This variable consists of five categories ranging from
very strongly urban (1) to non-urban (5); it was measured at municipal level and was derived from Statistics
Netherlands. The indicator is based on the number of households per square km and is commonly used in
the Netherlands. [22]
Demographic and socioeconomic characteristics
Part of the relation between green space and health may be the result of direct or indirect selection. Direct
selection would take place when people’s health is related to their chances of living in a green environment.
Indirect selection takes place when people with certain characteristics related to wellbeing (such as income)
tend to live in a green environment [23].
As migration flows are related to such socio-demographic characteristics as age, income and education
[24], we decided to rule out indirect selection effects as far as possible by controlling statistically for
demographic and socio-economic characteristics.
The demographic characteristics taken into account were gender (female = 1) and age (which was taken
into account as polynomial till the third order because there was no linear relation between the disease
clusters and age) and were derived from the patient lists of the participating practices. To find out whether
the relation between green space and morbidity differed between age groups, age was divided into six
categories (viz. children (aged <12 year), adolescent (aged 13-17 year), youth (aged 18-25 year), young
adults (aged 26-45 year), older adults (aged 46-65 year) and elderly (aged 65+)).
Socio-economic characteristics were collected by a registration form that was sent by mail to all people
listed in the participating practices in the DNSGP-2 (n= 380 000, response 76,5%) [14] and included
education, work status, and health care insurance type. For a number of people these socio-economic
characteristics were unknown. To reduce the number of missings we included a category unknown in the
analyses. Education was measured as the highest level of completed education (unknown, no education
completed, primary education, secondary education, higher education). Work situation was categorised as:
work situation unknown, paid job, attending school/ studying, housewife/ houseman, retired, disability
pension, unemployed. Socio-economic status was additionally implicitly measured by type of health care
insurance (unknown, public or private). The type of health care insurance can be regarded as an indicator of

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 Maas, J., Verheij, R.A., Vries, S. de, Spreeuwenberg, P., Groenewegen, P.P., Schellevis, F.G. Morbidity is
related to a green living environment. Journal of Epidemiology & Community Health: 2009, 63(12), 967-973

socio-economic status in the Dutch context in 2001, as only people with a higher income had private health
insurance, whereas people with a lower income had obligatory public health insurance.
When testing the effect of green space for different SES groups, SES was operationalised as the level of
education divided into three categories, viz. higher education (university or higher vocational education),
secondary education and primary or no education. Characteristics of the study population are displayed in
table 2.
[TABLE 2]
Statistical analysis
The relation between percentage of green space in people’s living environment and morbidity was
assessed using multilevel logistic regression analyses, controlling for demographic and socio-economic
characteristics and urbanicity. We included two levels: individuals and practices, because of the hierarchical
structure of the data within DNSGP-2. The multilevel logistic regression analyses were performed with
MLwiN. The independent variables, including the percentage of green space, were centred around their
average. The results thus represent morbidity of the average population living in an area with an average
amount of green space. We used interaction effects between respective age groups, SES groups and
urbanicity and the green space indicator to investigate the relation for different age groups, SES groups and
in different levels of urbanicity. Because of the large dataset we adopted a strict type 1 error criterion of
alpha = .01.
RESULTS
On average there is 42.4% of green space in a 1 km radius and 60.8% of green space in a 3km radius
around people’s home. Table 3 presents the odds ratios for the annual prevalence rate of the 24 disease
clusters for people who have 10 percent more green space than average. In general, a significant relation
between the percentage of green space and the annual prevalence rate was only present for green space in a
1 km radius. Only for anxiety disorders, infectious diseases of the digestive system and Medically
Unexplained Physical Symptoms (MUPS) the annual prevalence rate was lower in environments with more
green space in a 3 km radius.
For fifteen of the twenty-four disease clusters the annual prevalence rate was lower in living environments
with a higher percentage of green space in a 1km radius. This relation is apparent for diseases in all seven
disease categories. It is strongest for anxiety disorders and depression. For none of the disease clusters the
relationship is negative.
[TABLE 3]
Strength of the relation
An indication of the strength of the relation is given in table 4 which shows the annual prevalence per
1000 for people with average characteristics on the control variables with respectively 10% and 90% green
space in a 1 km radius around their home. For anxiety disorders, the annual prevalence for people with
average characteristics with 10% green space in a 1 km radius was 26 per 1000 people and for those with
90% green space in a 1 km radius 18 per 1000 people. For depression these figures are respectively 32 and
24 per 1000.
Generally the found relation between green space and physician assessed morbidity is comparable with the
relation between age and morbidity. An increase of one percentage of green space on physician assessed
morbidity equals the effect of one year lower age.
[TABLE 4]
Relation in different age groups
Further analysis showed that the relation was strongest for children younger than 12 and people between
46 and 65 (not in table). For children the relation was not only apparent for the percentage of green space in
a 1 km radius, but also for the percentage of green space in a 14 3 km radius. For a few disease clusters the
relation for children was especially strong, for example for vertigo (1 km: OR = 0.81 (95% C. I = 0.74 0.90) / 3km: OR 0.85 (95% C. I = 0.77 -0.94)) and severe intestinal complaints (1km: 0.85 (95% C. I = 0.80
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 Maas, J., Verheij, R.A., Vries, S. de, Spreeuwenberg, P., Groenewegen, P.P., Schellevis, F.G. Morbidity is
related to a green living environment. Journal of Epidemiology & Community Health: 2009, 63(12), 967-973

- 0.90)/ 3km: 0.89 (95% C. I = 0.84 - 0.94)). The strongest relation for children was found for depression
(1km: OR = 0.79 (95% C. I = 0.72 - 0.88) / 3 km: OR = 0.84 (95% C. I = 0.78 - 0.91)).
The relations for the other age groups were similar to the overall relations shown in table 3.
Relation for different socio-economic groups
Especially the lower educated groups had a lower annual prevalence rate when they had more green space
in a 1 km radius around their home. For example, the odds for COPD were smaller for the lower educated (
1 km: OR = .97 (95% C.I.= .95 - .99)) than for higher educated (OR = .98 (95% C.I.= .96 – 1.00).
Relation for different levels of urbanicity
Concerning the level of urbanicity our analyses show that urbanicity influences the relation between green
space and the annual prevalence of disease clusters (not in table). There is often no relation between green
space and the annual prevalence of disease clusters in the very strongly urban areas. At all other levels of
urbanicity people with more green space in a 1 km radius around their home had a lower annual prevalence
rate. The relations between green space and annual prevalence rates were strongest in slightly urban areas.
DISCUSSION
Principal findings
This explorative study shows that the previously established relation between green space and a number of
self-reported general indicators of physical and mental health can also be found for specific, doctorassessed disease categories. The annual prevalence rates for 15 of the 24 investigated disease clusters is
lower in living environments with more green space in a 1 km radius. Green space close to home appeared
to be more important than green space further away. This is in contrast with our previous studies [1, 2]
which found the relation between self-perceived health and the amount of green space in a 1km and a 3km
radius around people’s home to be equally strong. It appears that for the prevalence of these more specific
diseases green space close to home is more important. This study differs from other studies which mainly
focussed on the relation between green space and self-perceived measures of physical and mental health
[1,2,3,4,6]. This is the first study to assess the relation between green space and specific diseases which
were derived from electronical medical records of GP’s. This dataset helps better establish the relation
between green space and health, because it used physician assessed morbidity as outcome, because there
was no single source bias in the data, and because we used a large dataset which was representative for the
Netherlands.
In line with our hypothesis the relation was strongest for people who were expected to spend more time in
the vicinity of their homes, namely children and people with a lower socioeconomic status. However,
contrary to our expectations the relation appeared to be stronger for people aged between 46 and 65 than for
elderly. Concerning urbanicity, the relation appeared to be strongest in slightly urban areas. In very strongly
urban areas there was no relation with the annual prevalence of disease clusters. This may be related to the
fact that green spaces in highly urban areas are more often found to evoke feelings of insecurity [25], and
thereby inhibiting their use. This study only gives some indications for the relation between green space
and morbidity for different subgroups. Further research should focus specifically on one of the subgroups to
investigate the relation for subgroups more thoroughly.
Underlying mechanisms
The results of this study give some indications for the possible mechanism behind the relation between
green space and health. Several mechanisms could be responsible for the relation between green space and
health, of which the following are most commonly mentioned: recovery from stress and attention fatigue,
encouragement of physical activity, facilitation of social contact and better air quality. [7, 26] What do the
results tell us about the mechanism at work? The strong relation we particularly found for anxiety disorder
and depression suggests that recovery from stress and attention fatigue might be the most likely mechanism
behind the relation between green space and health, though facilitation of social contacts might also
contribute. However, there is no reason to discard any of the other possible mechanisms. In living
environments with more green space, the prevalence of most respiratory illnesses was lower, indicating that
air quality could also be a possible mechanism behind the relation between green space and health. For
diseases related to physical activity (diabetes, high blood pressure, musculoskeletal diseases) somewhat less
strong relations were found. But as the associations were present, physical activity could also be a possible
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 Maas, J., Verheij, R.A., Vries, S. de, Spreeuwenberg, P., Groenewegen, P.P., Schellevis, F.G. Morbidity is
related to a green living environment. Journal of Epidemiology & Community Health: 2009, 63(12), 967-973

mechanism. Further research will have to shed more light on the mechanisms behind the relation between
green space and health.
This study shows that the role of green space in the living environment for health should not be
underestimated. Most of the diseases which were found to be related to the percentage of green space in the
living environment are highly prevalent in society and in many countries they are subject of large scale
prevention programs. Furthermore, in many countries, diseases of the circulatory system, mental disorders
and diseases of digestive system are among the most expensive diseases with respect to health care costs.
[27] Our study contributes to the evidence that green space can help fight some major public health threats
in western societies and should be allocated a more central position in spatial planning. Healthy planning
should include a place for green space and policy makers should take the amount of green space in the
living environment into account when endeavouring to improve the health situation of children and lower
socio-economic groups.
Strength and limitations
This is the first large epidemiological study investigating the relation between the amount of green space
in the living environment of people and the prevalence of physician assessed morbidity. Morbidity data
were derived from a different database than the data on green space; consequently, there is no single source
or method bias. On the other hand, we don’t have information an exposure time.
The morbidity data are accurate because they were extracted from routine electronic medical records of
general practices, and the inter-observer reliability of grouping contacts into episodes was high. [16] The
registration covered a 12-month period for each practice in order to eliminate seasonal influences.
Considering the representativeness of the participating GPs and their patients – and the high validity of the
data – the results of the present study can be assumed to validly represent morbidity in Dutch general
practice.
Furthermore, because general practice in the Netherlands is usually the first point of contact with the
health care system, and because the GP has a gatekeeping role for specialist care, and because there are no
large geographic [28] or social differences in access to general practice, morbidity presented in general
practice can be regarded as a very close approximation of morbidity present in the open population.
The data used for this study also have some shortcomings. First, our data on green space, although
assessed on a small scale, does not take small green spaces in the living environment into account. A 25 by
25 meter grid cell was only regarded as green space when green space dominates in the grid cell. Gardens
and small-scale green spaces, such as street trees and green verges which could also influence people’s
health, are not regarded as green space in our study. Consequently the effect of green space might be
slightly underestimated.
Second, because of the cross-sectional design of the study, it is not possible to make strong inferences
about the causality of the relations that were found. The observed effects of green space on health may
partly be caused by selection. We tried to rule out this possibility by taking socio-economic and
demographic characteristics into account, but the effects of selection cannot be ruled out completely. The
results from the subgroup analyses by SES groups, however, make it rather unlikely that selection is the
responsible mechanism. The relationship observed between green space and morbidity was stronger for the
less welleducated group and this is exactly the subgroup that has fewer options in their choice of
neighbourhood of residence. Our results may be influenced by selective migration based on people’s health
(direct selection). However, longitudinal studies on health related migration show that direct selection can
not be held responsible for geographical differences that remain if socioeconomic and demographic factors
are taken into account.[29, 30] Third, we tried to control as much as possible for individual socio-economic
status. However, we did not have any information on the income of the respondents, which is a relevant
indicator for socio-economic status. Furthermore, we did not control for other confounders at
neighbourhood level, although different studies have shown that for example neighbourhood SES could
also influence health [31, 32] . Because this was an explorative study we chose to keep the design
somewhat easy. Further research should try to find out whether a relation can also be found when
neighbourhood SES is controlled for.
ACKNOWLEDGEMENT
This study was supported by a grant from the Netherlands Organisation for Scientific Research.

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 Maas, J., Verheij, R.A., Vries, S. de, Spreeuwenberg, P., Groenewegen, P.P., Schellevis, F.G. Morbidity is
related to a green living environment. Journal of Epidemiology & Community Health: 2009, 63(12), 967-973

COMPETING INTEREST
No conflicts of interest are reported by any of the authors.
LICENSE FOR PUBLICATION STATEMENT
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authors, an exclusive licence (or non exclusive for government employees) on a worldwide basis to the
BMJ Publishing Group Ltd to permit this article (if accepted) to be published in JECH and any other
BMJPGL products and sublicences such use and exploit all subsidiary rights, as set out in our licence
(http://jech.bmj.com/ifora/licence.pdf).
What is already known on this subject?
There is increasing evidence for a positive relation between green space in the living environment and a
number of self-reported indicators of physical and mental health. Smallscale psychological research showed
that exposure to green space has a positive effect on stress reduction and attention restoration. Several
epidemiological studies have shown that green space is positively correlated with self-perceived health,
number of symptoms experienced and mortality.
What does this study add?
This study uses large scale representative medical record data to investigate whether the prevalence of a
number of disease clusters is related to the amount of green space in people’s living environment. The
annual prevalence rates for 15 of the 24 investigated disease clusters is lower in living environments with
more green space in a 1km radius around people’s homes. The study stresses the importance of green space
close to people’s home. The relationship is particularly strong for children and lower socio-economic
groups.
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related to a green living environment. Journal of Epidemiology & Community Health: 2009, 63(12), 967-973
TABLES

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 Maas, J., Verheij, R.A., Vries, S. de, Spreeuwenberg, P., Groenewegen, P.P., Schellevis, F.G. Morbidity is
related to a green living environment. Journal of Epidemiology & Community Health: 2009, 63(12), 967-973

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 Maas, J., Verheij, R.A., Vries, S. de, Spreeuwenberg, P., Groenewegen, P.P., Schellevis, F.G. Morbidity is
related to a green living environment. Journal of Epidemiology & Community Health: 2009, 63(12), 967-973

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