Several studies have shown a positive relationship between local greenspace availability and residents' health, which may offer opportunities for health improvement. This study focuses on three ...mechanisms through which greenery might exert its positive effect on health: stress reduction, stimulating physical activity and facilitating social cohesion. Knowledge on mechanisms helps to identify which type of greenspace is most effective in generating health benefits. In eighty neighbourhoods in four Dutch cities data on quantity and quality of streetscape greenery were collected by observations. Data on self-reported health and proposed mediators were obtained for adults by mail questionnaires (N = 1641). Multilevel regression analyses, controlling for socio-demographic characteristics, revealed that both quantity and quality of streetscape greenery were related to perceived general health, acute health-related complaints, and mental health. Relationships were generally stronger for quality than for quantity. Stress and social cohesion were the strongest mediators. Total physical activity was not a mediator. Physical activity that could be undertaken in the public space (green activity) was, but less so than stress and social cohesion. With all three mediators included in the analysis, complete mediation could statistically be proven in five out of six cases. In these analyses the contribution of green activity was often not significant. The possibility that the effect of green activity is mediated by stress and social cohesion, rather than that it has a direct health effect, is discussed.
•Quality of streetscape greenery in neighbourhoods is especially related to health.•The greenery–health relationship is strongly mediated by stress and social cohesion.•Although no important mediator, physical activity may help exposure to greenery.•Results are first step towards identifying effective greenery for health promotion.
The 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 people's 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.
The 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.
No 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.
Our 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.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
This open access book is a practical introduction to multilevel modelling or multilevel analysis (MLA) – a statistical technique being increasingly used in public health and health services research. ...The authors begin with a compelling argument for the importance of researchers in these fields having an understanding of MLA to be able to judge not only the growing body of research that uses it, but also to recognise the limitations of research that did not use it. The volume also guides the analysis of real-life data sets by introducing and discussing the use of the multilevel modelling software MLwiN, the statistical package that is used with the example data sets. Importantly, the book also makes the training material accessible for download – not only the datasets analysed within the book, but also a freeware version of MLwiN to allow readers to work with these datasets. The book’s practical review of MLA comprises: Theoretical, conceptual, and methodological background Statistical background The modelling process and presentation of research Tutorials with example datasets Multilevel Modelling for Public Health and Health Services Research: Health in Context is a practical and timely resource for public health and health services researchers, statisticians interested in the relationships between contexts and behaviour, graduate students across these disciplines, and anyone interested in utilising multilevel modelling or multilevel analysis. “Leyland and Groenewegen’s wealth of teaching experience makes this book and its accompanying tutorials especially useful for a practical introduction to multilevel analysis.” ̶ Juan Merlo, Professor of Social Epidemiology, Lund University “Comprehensive and insightful. A must for anyone interested in the applications of multilevel modelling to population health”. ̶ S. (Subu) V. Subramanian, Professor of Population Health and Geography, Harvard University ; For researchers and students with a basic mastery of ordinary least squares and logistic regression Discusses multilevel analysis in context of public health, health services research, and epidemiology Includes an online component where users can download the datasets analyzed in the book, and also a freeware version of the multilevel modelling software MLwiN Can be used as part of a course on multilevel modelling, or as a self-training text
Neighborhood social capital is increasingly considered to be an important determinant of an individual’s health. Using data from the Netherlands we investigate the influence of neighborhood social ...capital on an individual’s self-reported health, while accounting for other conditions of health on both the level of the neighborhood and the individual. We use national representative data (‘The Housing and Living Survey’, 2006) on the Netherlands with 61,235 respondents in 3273 neighborhoods. The cross-sectional data were combined with information provided by Statistics Netherlands on neighborhoods, i.e., the percentage of residents in the highest income quintile per neighborhood and the municipality’s degree of urbanity. The association of neighborhood social capital with individual health was assessed by multilevel logistic regression analysis. Our results show that neighborhood social capital is positively associated with health. Interestingly, residents in urban neighborhoods benefit particularly from their neighborhood social capital.
► There is a noticeable clustering of self-rated health in Dutch neighborhoods. ► Ecometrics guarantees a reliable social capital measurement. ► Next to controls neighborhood social capital enhances self-rated health. ► This health improving effect is stronger in urban areas.
Even though there is general agreement that primary care is the linchpin of effective health care delivery, to date no efforts have been made to systematically review the scientific evidence ...supporting this supposition. The aim of this study was to examine the breadth of primary care by identifying its core dimensions and to assess the evidence for their interrelations and their relevance to outcomes at (primary) health system level.
A systematic review of the primary care literature was carried out, restricted to English language journals reporting original research or systematic reviews. Studies published between 2003 and July 2008 were searched in MEDLINE, Embase, Cochrane Library, CINAHL, King's Fund Database, IDEAS Database, and EconLit.
Eighty-five studies were identified. This review was able to provide insight in the complexity of primary care as a multidimensional system, by identifying ten core dimensions that constitute a primary care system. The structure of a primary care system consists of three dimensions: 1. governance; 2. economic conditions; and 3. workforce development. The primary care process is determined by four dimensions: 4. access; 5. continuity of care; 6. coordination of care; and 7. comprehensiveness of care. The outcome of a primary care system includes three dimensions: 8. quality of care; 9. efficiency care; and 10. equity in health. There is a considerable evidence base showing that primary care contributes through its dimensions to overall health system performance and health.
A primary care system can be defined and approached as a multidimensional system contributing to overall health system performance and health.
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Dostopno za:
CEKLJ, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
This study investigates whether the presence of green space can attenuate negative health impacts of stressful life events. Individual-level data on health and socio-demographic characteristics were ...drawn from a representative two-stage sample of 4529 Dutch respondents to the second Dutch National Survey of General Practice (DNSGP-2), conducted in 2000–2002. Health measures included: (1) the number of health complaints in the last 14 days; (2) perceived mental health (measured by the GHQ-12); and (3) a single item measure of perceived general health ranging from ‘excellent’ to ‘poor’. Percentages of green space in a 1-km and 3-km radius around the home were derived from the 2001 National Land cover Classification database (LGN4). Data were analysed using multilevel regression analysis, with GP practices as the group-level units. All analyses were controlled for age, gender, income, education level, and level of urbanity. The results show that the relationships of stressful life events with number of health complaints and perceived general health were significantly moderated by amount of green space in a 3-km radius. Respondents with a high amount of green space in a 3-km radius were less affected by experiencing a stressful life event than respondents with a low amount of green space in this radius. The same pattern was observed for perceived mental health, although it was marginally significant. The moderating effects of green space were found only for green space within 3 km, and not for green space within 1 km of residents' homes, presumably because the 3-km indicator is more affected by the presence of larger areas of green space, that are supposed to sustain deeper forms of restoration. These results support the notion that green space can provide a buffer against the negative health impact of stressful life events.
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 individual's address. After adjustment for socio-economic and demographic characteristics, less green space in people's 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.
BackgroundPrevious research shows a positive link between the amount of green area in one's residential neighbourhood and self-reported health. However, little research has been done on the quality ...of the green area, as well as on quantity and quality of smaller natural elements in the streetscape. This study investigates the link between the objectively assessed quantity and quality of (1) green areas and (2) streetscape greenery on the one hand and three self-reported health indicators on the other.Methods80 Dutch urban neighbourhoods were selected, varying in the amount of nearby green area per dwelling, as determined by Geographic Information System analysis. The quality of green areas, as well as the quantity and quality of streetscape greenery, was assessed by observers using an audit tool. Residents of each neighbourhood were asked to complete a questionnaire on their own health (N=1641). In multilevel regression analyses, we examined the relationship between greenspace indicators and three health indicators, controlling for socio-demographic and socioeconomic characteristics.ResultsBoth indicators for the quantity of greenspace were positively related to all three health indicators. Quantity and quality indicators were substantially correlated in the case of streetscape greenery. Nevertheless, the quality indicators tended to have added predictive value for the health indicators, given that the quantity information was already included in the model.ConclusionsThe quantity and also the quality of greenspace in one's neighbourhood seem relevant with regard to health. Furthermore, streetscape greenery is at least as strongly related to self-reported health as green areas.
Looking 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.
The 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.
Previous (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 people's 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.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Exposure to green space seems to be beneficial for self-reported mental health. In this study we used an objective health indicator, namely antidepressant prescription rates. Current studies rely ...exclusively upon mean regression models assuming linear associations. It is, however, plausible that the presence of green space is non-linearly related with different quantiles of the outcome antidepressant prescription rates. These restrictions may contribute to inconsistent findings.
Our aim was: a) to assess antidepressant prescription rates in relation to green space, and b) to analyze how the relationship varies non-linearly across different quantiles of antidepressant prescription rates.
We used cross-sectional data for the year 2014 at a municipality level in the Netherlands. Ecological Bayesian geoadditive quantile regressions were fitted for the 15%, 50%, and 85% quantiles to estimate green space–prescription rate correlations, controlling for physical activity levels, socio-demographics, urbanicity, etc.
The results suggested that green space was overall inversely and non-linearly associated with antidepressant prescription rates. More important, the associations differed across the quantiles, although the variation was modest. Significant non-linearities were apparent: The associations were slightly positive in the lower quantile and strongly negative in the upper one.
Our findings imply that an increased availability of green space within a municipality may contribute to a reduction in the number of antidepressant prescriptions dispensed. Green space is thus a central health and community asset, whilst a minimum level of 28% needs to be established for health gains. The highest effectiveness occurred at a municipality surface percentage higher than 79%. This inverse dose-dependent relation has important implications for setting future community-level health and planning policies.
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•Green space was inversely correlated with antidepressant prescription rates.•Bayesian geoadditive quantile regression showed non-linear dose-response functions.•The shape of the associations showed moderate variations across quantiles.•For health gains, communities should have at least one quarter green space; the most health gains occur when the proportion exceeds three quarters.
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