Robert Verheij

Green space, urbanity, and health: how strong is the relation?

Study objectives: To investigate the strength of the relation between the amount of green space in people’s living environment and their perceived general health. This relation is analysed for different age and socioeconomic groups. Furthermore, it is analysed separately for urban and more rural areas, because the strength of the relation was expected to vary with urbanity. Design: The study includes 250 782 people registered with 104 general practices who filled in a self administered form on sociodemographic background and perceived general health. The percentage of green space (urban green space, agricultural space, natural green space) within a one kilometre and three kilometre radius around the postal code coordinates was calculated for each household. Methods: Multilevel logistic regression analyses were performed at three levels—that is, individual level, family level, and practice level—controlled for sociodemographic characteristics. Main results: The percentage of green space inside a one kilometre and a three kilometre radius had a significant relation to perceived general health. The relation was generally present at all degrees of urbanity. The overall relation is somewhat stronger for lower socioeconomic groups. Elderly, youth, and secondary educated people in large cities seem to benefit more from presence of green areas in their living environment than other groups in large cities. Conclusions: This research shows that the percentage of green space in people’s living environment has a positive association with the perceived general health of residents. Green space seems to be more than just a luxury and consequently the development of green space should be allocated a more central position in spatial planning policy.

Natural Environments—Healthy Environments? An Exploratory Analysis of the Relationship between Greenspace and Health

Are people living in greener areas healthier than people living in less green areas? This hypothesis was empirically tested by combining Dutch data on the self-reported health of over 10 000 people with land-use data on the amount of greenspace in their living environment. In the multilevel analysis we controlled for socioeconomic and demographic characteristics, as well as urbanity. Living in a green environment was positively related to all three available health indicators, even stronger than urbanity at the municipal level. Analyses on subgroups showed that the relationship between greenspace and one of the health indicators was somewhat stronger for housewives and the elderly, two groups that are assumed to be more dependent on, and therefore exposed to, the local environment. Furthermore, for all three health indicators the relationship with greenspace was somewhat stronger for lower educated people. Implications for policymaking and spatial planning are discussed briefly.

Morbidity is related to a green living environment

Background: As a result of 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. The percentage of green space within a 1 km and 3 km 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 socioeconomic 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 socioeconomic groups.

Social contacts as a possible mechanism behind the relation between green space and health

This study explored whether social contacts are an underlying mechanism behind the relationship between green space and health. We measured social contacts and health in 10,089 residents of the Netherlands and calculated the percentage of green within 1 and a 3km radius around the postal code coordinates for each individuals address. After adjustment for socio-economic and demographic characteristics, less green space in peoples living environment coincided with feelings of loneliness and with perceived shortage of social support. Loneliness and perceived shortage of social support partly mediated the relation between green space and health.

Vitamin G: effects of green space on health, well-being, and social safety

BackgroundLooking out on and being in the green elements of the landscape around us seem to affect health, well-being and feelings of social safety. This article discusses the design of a research program on the effects of green space in the living environment on health, well-being and social safety.Methods/designThe program consists of three projects at three different scales: at a macro scale using data on the Netherlands as a whole, at an intermediate scale looking into the specific effect of green space in the urban environment, and at micro scale investigating the effects of allotment gardens. The projects are observational studies, combining existing data on land use and health interview survey data, and collecting new data through questionnaires and interviews. Multilevel analysis and GIS techniques will be used to analyze the data.DiscussionPrevious (experimental) research in environmental psychology has shown that a natural environment has a positive effect on well-being through restoration of stress and attentional fatigue. Descriptive epidemiological research has shown a positive relationship between the amount of green space in the living environment and physical and mental health and longevity.The program has three aims. First, to document the relationship between the amount and type of green space in peoples living environment and their health, well-being, and feelings of safety. Second, to investigate the mechanisms behind this relationship. Mechanisms relate to exposure (leading to stress reduction and attention restoration), healthy behavior and social integration, and selection. Third, to translate the results into policy on the crossroads of spatial planning, public health, and safety. Strong points of our program are: we study several interrelated dependent variables, in different ordinary settings (as opposed to experimental or extreme settings), focusing on different target groups, using appropriate multilevel methods.

Physical activity as a possible mechanism behind the relationship between green space and health: A multilevel analysis

BackgroundThe aim of this study was to investigate whether physical activity (in general, and more specifically, walking and cycling during leisure time and for commuting purposes, sports and gardening) is an underlying mechanism in the relationship between the amount of green space in peoples direct living environment and self-perceived health. To study this, we first investigated whether the amount of green space in the living environment is related to the level of physical activity. When an association between green space and physical activity was found, we analysed whether this could explain the relationship between green space and health.MethodsThe study includes 4.899 Dutch people who were interviewed about physical activity, self-perceived health and demographic and socioeconomic background. The amount of green space within a one-kilometre and a three-kilometre radius around the postal code coordinates was calculated for each individual. Multivariate multilevel analyses and multilevel logistic regression analyses were performed at two levels and with controls for socio-demographic characteristics and urbanicity.ResultsNo relationship was found between the amount of green space in the living environment and whether or not people meet the Dutch public health recommendations for physical activity, sports and walking for commuting purposes. People with more green space in their living environment walked and cycled less often and fewer minutes during leisure time; people with more green space garden more often and spend more time on gardening. Furthermore, if people cycle for commuting purposes they spend more time on this if they live in a greener living environment. Whether or not people garden, the time spent on gardening and time spent on cycling for commuting purposes did not explain the relationship between green space and health.ConclusionOur study indicates that the amount of green space in the living environment is scarcely related to the level of physical activity. Furthermore, the amount of physical activity undertaken in greener living environments does not explain the relationship between green space and health.

Explaining urban-rural variations in health: A review of interactions between individual and environment

In order to gain insight into the relation between health and peoples environment, literature published between 1985 and 1994 was gathered from several international databases. An introduction into existing theory regarding geographic disparities is presented: geographical drift and breeder hypotheses are discussed. This is followed by a critical review focusing on interaction effects of urbanicity and individual characteristics on health. This leads to two major conclusions. First, emphasis in past research has been primarily on urban constraints rather than opportunities. Positive aspects of urban living are often insufficiently appreciated. Second, positive and negative environmental aspects have an effect on health that is often dependent on individual characteristics. The extent to which the environment exerts influence on a persons health is dependent on that persons individual characteristics. These conclusions are relevant only for further developing the breeder hypothesis, however. Large scale individual based longitudinal data should be studied in order to gain more insight into the relative importance of the geographical drift hypothesis.

Multimorbidity and comorbidity in the Dutch population - data from general practices.

BackgroundMultimorbidity is increasingly recognized as a major public health challenge of modern societies. However, knowledge about the size of the population suffering from multimorbidity and the type of multimorbidity is scarce. The objective of this study was to present an overview of the prevalence of multimorbidity and comorbidity of chronic diseases in the Dutch population and to explore disease clustering and common comorbidities.MethodsWe used 7 years data (2002–2008) of a large Dutch representative network of general practices (212,902 patients). Multimorbidity was defined as having two or more out of 29 chronic diseases. The prevalence of multimorbidity was calculated for the total population and by sex and age group. For 10 prevalent diseases among patients of 55 years and older (N = 52,014) logistic regressions analyses were used to study disease clustering and descriptive analyses to explore common comorbid diseases.ResultsMultimorbidity of chronic diseases was found among 13% of the Dutch population and in 37% of those older than 55 years. Among patients over 55 years with a specific chronic disease more than two-thirds also had one or more other chronic diseases. Most disease pairs occurred more frequently than would be expected if diseases had been independent. Comorbidity was not limited to specific combinations of diseases; about 70% of those with a disease had one or more extra chronic diseases recorded which were not included in the top five of most common diseases.ConclusionMultimorbidity is common at all ages though increasing with age, with over two-thirds of those with chronic diseases and aged 55 years and older being recorded with multimorbidity. Comorbidity encompassed many different combinations of chronic diseases. Given the ageing population, multimorbidity and its consequences should be taken into account in the organization of care in order to avoid fragmented care, in medical research and healthcare policy.

Inappropriateness of medication prescriptions to elderly patients in the primary care setting: a systematic review

Background Inappropriate medication prescription is a common cause of preventable adverse drug events among elderly persons in the primary care setting. Objective The aim of this systematic review is to quantify the extent of inappropriate prescription to elderly persons in the primary care setting. Methods We systematically searched Ovid-Medline and Ovid-EMBASE from 1950 and 1980 respectively to March 2012. Two independent reviewers screened and selected primary studies published in English that measured (in)appropriate medication prescription among elderly persons (>65 years) in the primary care setting. We extracted data sources, instruments for assessing medication prescription appropriateness, and the rate of inappropriate medication prescriptions. We grouped the reported individual medications according to the Anatomical Therapeutic and Chemical (ATC) classification and compared the median rate of inappropriate medication prescription and its range within each therapeutic class. Results We included 19 studies, 14 of which used the Beers criteria as the instrument for assessing appropriateness of prescriptions. The median rate of inappropriate medication prescriptions (IMP) was 20.5% [IQR 18.1 to 25.6%.]. Medications with largest median rate of inappropriate medication prescriptions were propoxyphene 4.52(0.10–23.30)%, doxazosin 3.96 (0.32 15.70)%, diphenhydramine 3.30(0.02–4.40)% and amitriptiline 3.20 (0.05–20.5)% in a decreasing order of IMP rate. Available studies described unequal sets of medications and different measurement tools to estimate the overall prevalence of inappropriate prescription. Conclusions Approximately one in five prescriptions to elderly persons in primary care is inappropropriate despite the attention that has been directed to quality of prescription. Diphenhydramine and amitriptiline are the most common inappropriately prescribed medications with high risk adverse events while propoxyphene and doxazoxin are the most commonly prescribed medications with low risk adverse events. These medications are good candidates for being targeted for improvement e.g. by computerized clinical decision support.

Urban-rural variations in health in The Netherlands: does selective migration play a part?

STUDY OBJECTIVE: Urban-rural health differences are observed in many countries, even when socioeconomic and demographic characteristics are controlled for. People living in urban areas are often found to be less healthy. One of the possible causes for these differences is selective migration with respect to health or health risk factors. This hypothesis is hardly ever empirically tested. This paper tries to assess the existence of selective urban-rural migration. DESIGN: Health indicators and health risk factors were measured in a 1991 population sample. Moves were registered between 1991 and 1995. Using logistic regression analyses, comparisons were made between, firstly, urban to rural movers and rural to urban movers and secondly, between movers and stayers. SETTING: Region surrounding the city of Eindhoven in south eastern part of the Netherlands. SUBJECTS: Data were used of 15,895 respondents aged 20-74 in 1991. By 1995 613 subjects had moved from urban to rural and 191 subjects from rural to urban. MAIN RESULTS: Bivariate nor multivariate analyses show hardly and differences between movers into urban and movers into rural areas. Bivariate analyses on movers and stayers show that movers are healthier than stayers. However, when socioeconomic and demographic variables are controlled for, movers appear to be less healthy, with the exception of the younger age groups. CONCLUSIONS: Areas that attract many migrants from and lose few migrants to other degrees of urbanicity will in the long run obtain healthier populations, because of demographic and socioeconomic characteristics. However, if these characteristics are accounted for, the opposite is true, with the exception of younger age groups. In extreme cases this may cause spurious findings in cross sectional research into the relation between urbanicity and health. Absolute numbers of migrants need to be very high, however, to make this noticeable at the aggregate level.