Exposure to neighborhood green space and mental health: evidence from the survey of the health of Wisconsin.
ABSTRACT: Green space is now widely viewed as a health-promoting characteristic of residential environments, and has been linked to mental health benefits such as recovery from mental fatigue and reduced stress, particularly through experimental work in environmental psychology. Few population level studies have examined the relationships between green space and mental health. Further, few studies have considered the role of green space in non-urban settings. This study contributes a population-level perspective from the United States to examine the relationship between environmental green space and mental health outcomes in a study area that includes a spectrum of urban to rural environments. Multivariate survey regression analyses examine the association between green space and mental health using the unique, population-based Survey of the Health of Wisconsin database. Analyses were adjusted for length of residence in the neighborhood to reduce the impact of neighborhood selection bias. Higher levels of neighborhood green space were associated with significantly lower levels of symptomology for depression, anxiety and stress, after controlling for a wide range of confounding factors. Results suggest that "greening" could be a potential population mental health improvement strategy in the United States.
Project description:Urban residence is associated with a higher risk of some psychiatric disorders, but the underlying drivers remain unknown. There is increasing evidence that the level of exposure to natural environments impacts mental health, but few large-scale epidemiological studies have assessed the general existence and importance of such associations. Here, we investigate the prospective association between green space and mental health in the Danish population. Green space presence was assessed at the individual level using high-resolution satellite data to calculate the normalized difference vegetation index within a 210 × 210 m square around each person's place of residence (∼1 million people) from birth to the age of 10. We show that high levels of green space presence during childhood are associated with lower risk of a wide spectrum of psychiatric disorders later in life. Risk for subsequent mental illness for those who lived with the lowest level of green space during childhood was up to 55% higher across various disorders compared with those who lived with the highest level of green space. The association remained even after adjusting for urbanization, socioeconomic factors, parental history of mental illness, and parental age. Stronger association of cumulative green space presence during childhood compared with single-year green space presence suggests that presence throughout childhood is important. Our results show that green space during childhood is associated with better mental health, supporting efforts to better integrate natural environments into urban planning and childhood life.
Project description:More than half of the world's population lives in urban environments. Due to urban related factors (e.g. higher air pollution), urban residents may face higher risk of adverse health outcomes, while access to green space could benefit health.We explored associations between urban and green land-use and birth weight.Connecticut, U.S., birth certificate data (2000-2006) were acquired (n=239,811), and land-use data were obtained from the National Land Cover Database. We focused on three land-uses; urban space, urban open space, and green space (i.e. forest, shrub, herbaceous, and cultivated land). We estimated fractions of greenness and urbanicity within 250 m from residence. A linear mixed effects model was conducted for birth weight and a logistic mixed effects model for low birth weight (LBW) and small for gestational age (SGA).An interquartile range (IQR) increment in the fraction of green space within 250 m of residence was associated with 3.2g (95% Confidence Interval [0.4, 6.0]) higher birth weight. Similarly, an IQR increase in green space was associated with 7.6% [2.6, 12.4] decreased risk of LBW. Exposure to urban space was negatively correlated with green space (Pearson correlation=-0.88), and it showed negative association with birth outcomes. Results were generally robust with different buffer sizes and controlling for fine particles (PM2.5) and traffic.We found protective associations by green space on birth outcomes. Increasing green space and/or reducing urban space (e.g. the greening of city environments) may reduce the risk of adverse birth outcomes such as LBW and SGA. Populations living in urban environments will grow in the next half century, and allocation of green space among urban areas may play a critical role for public health in urban planning.
Project description:BACKGROUND:Previous studies reported positive associations between perceived neighborhood greenness and mental health. There has been a focus on perceived neighborhood greenness at people's home environment or in general, but data are lacking on greenness at working places or other locations where they actually spend most of their time during their day. METHODS:This study investigated the perceived greenness of college students' home and study environments and its relation to mental health. An online survey collected data from 601 participants with a mean age of 24?years, living in or around and studying in the city of Graz, Austria. The perceived greenness at home and at university was assessed using questions on quality of and access to green space; mental health was measured with the WHO-5 well-being index. Uni- and multivariate regression analyses were used to analyze the data. RESULTS:The analyses revealed positive associations between perceived greenness at home and mental health as well as perceived greenness at university and mental health. This adds more evidence to the existing literature that perceiving the environment as green is positively related to better mental health. CONCLUSIONS:Future research will have to incorporate objective greenness measures as a means of controlling for the reliability of the measurements and investigate the effects of different environments people are exposed to over the course of a day.
Project description:Environment-health research has shown significant relationships between the quantity of green space in deprived urban neighbourhoods and people's stress levels. The focus of this paper is the nature of access to green space (i.e., its quantity or use) necessary before any health benefit is found. It draws on a cross-sectional survey of 406 adults in four communities of high urban deprivation in Scotland, United Kingdom. Self-reported measures of stress and general health were primary outcomes; physical activity and social wellbeing were also measured. A comprehensive, objective measure of green space quantity around each participant's home was also used, alongside self-report measures of use of local green space. Correlated Component Regression identified the optimal predictors for primary outcome variables in the different communities surveyed. Social isolation and place belonging were the strongest predictors of stress in three out of four communities sampled, and of poor general health in the fourth, least healthy, community. The amount of green space in the neighbourhood, and in particular access to a garden or allotment, were significant predictors of stress. Physical activity, frequency of visits to green space in winter months, and views from the home were predictors of general health. The findings have implications for public health and for planning of green infrastructure, gardens and public open space in urban environments.
Project description:A growing body of literature shows that neighborhood characteristics influence older adults' mental health. Therefore, the aim of this study was to examine the association between structural and social characteristics of the neighborhood, and depression in Mexican older adults. A longitudinal study was conducted based on waves 1 (2009-2010) and 2 (2014) of the Mexican sample from the Study on global AGEing and adult health (SAGE). A street-network buffer around each participant's household was used to define neighborhood, so that built environment and social characteristics were assessed within it. Depression was ascertained by using an algorithm based on the Composite International Diagnostic Interview. In the analysis, multilevel logistic regression models were constructed separately for each built and social environments measurement, adjusted for socioeconomic, demographic and health-related covariates, and stratified by area of residence (urban versus rural). The results showed that a length of space between 15-45 meters restricted to vehicles was significantly associated with a lower risk of depression in older adults from the urban area (OR: 0.44; IC 95% 0.23-0.83) and the protective association appeared to be larger with increasing space with this restriction, although it lacked significance. Contrarily, the built environment measures were not predictive of depression in the rural setting. On the other hand, none of the variables from the social environment had a significant association, although safety appeared to behave as a risk factor in the overall (OR: 1.48; CI 95% 0.96-2.30; p = 0.08) and rural (OR: 3.44; CI 95% 0.95-12.45; p = 0.06) samples, as it reached marginal significance. Research about neighborhood effects on older adults' mental health is an emergent field that has shown that depression might be treated not only from the individual-level, but also from the neighborhood-level. Additionally, further research is needed, especially in low- and middle-income countries, to help guide neighborhood policies.
Project description:BACKGROUND:There is a growing body of literature supporting positive associations between natural environments and better health. The type, quality and quantity of green and blue space ('green-space') in proximity to the home might be particularly important for less mobile populations, such as for some older people. However, considerations of measurement and definition of green-space, beyond single aggregated metrics, are rare. This constitutes a major source of uncertainty in current understanding of public health benefits derived from natural environments. We aimed to improve our understanding of how such benefits are conferred to different demographic groups through a comprehensive evaluation of the physical and spatial characteristics of urban green infrastructure. METHODS:We employed a green infrastructure (GI) approach combining a high-resolution spatial dataset of land-cover and function with area-level demographic and socio-economic data. This allowed for a comprehensive characterization of a densely populated, polycentric city-region. We produced multiple GI attributes including, for example, urban vegetation health. We used a series of step-wise multi-level regression analyses to test associations between population chronic morbidity and the functional, physical and spatial components of GI across an urban socio-demographic gradient. RESULTS:GI attributes demonstrated associations with health in all socio-demographic contexts even where associations between health and overall green cover were non-significant. Associations varied by urban socio-demographic group. For areas characterised by having higher proportions of older people ('older neighbourhoods'), associations with better health were exhibited by land-cover diversity, informal greenery and patch size in high income areas and by proximity to public parks and recreation land in low income areas. Quality of GI was a significant predictor of good health in areas of low income and low GI cover. Proximity of publicly accessible GI was also significant. CONCLUSIONS:The influence of urban GI on population health is mediated by green-space form, quantity, accessibility, and vegetation health. People in urban neighbourhoods that are characterised by lower income and older age populations are disproportionately healthy if their neighbourhoods contain accessible, good quality public green-space. This has implications for strategies to decrease health inequalities and inform international initiatives, such as the World Health Organisation's Age-Friendly Cities programme.
Project description:This study follows previous research showing how green space quantity and contact with nature (via access to gardens/allotments) helps mitigate stress in people living in deprived urban environments (Ward Thompson et al., 2016). However, little is known about how these environments aid stress mitigation nor how stress levels vary in a population experiencing higher than average stress. This study used Latent Class Analysis (LCA) to, first, identify latent health clusters in the same population (n = 406) and, second, to relate health cluster membership to variables of interest, including four hypothetical stress coping scenarios. Results showed a three-cluster model best fit the data, with membership to health clusters differentiated by age, perceived stress, general health, and subjective well-being. The clusters were labeled by the primary health outcome (i.e., perceived stress) and age group (1) Low-stress Youth characterized by ages 16-24; (2) Low-stress Seniors characterized by ages 65+ and (3) High-stress Mid-Age characterized by ages 25-44. Next, LCA identified that health membership was significantly related to four hypothetical stress coping scenarios set in people's current residential context: "staying at home" and three scenarios set outwith the home, "seeking peace and quiet," "going for a walk" or "seeking company." Stress coping in Low stress Youth is characterized by "seeking company" and "going for a walk"; stress coping in Low-stress Seniors and High stress Mid-Age is characterized by "staying at home." Finally, LCA identified significant relationships between health cluster membership and a range of demographic, other individual and environmental variables including access to, use of and perceptions of local green space. Our study found that the opportunities in the immediate neighborhood for stress reduction vary by age. Stress coping in youth is likely supported by being social and keeping physically active outdoors, including local green space visits. By contrast, local green space appears not to support stress regulation in young-middle aged and older adults, who choose to stay at home. We conclude that it is important to understand the complexities of stress management and the opportunities offered by local green space for stress mitigation by age and other demographic variables, such as gender.
Project description:BACKGROUND:Residential green and blue spaces may be therapeutic for the mental health. However, solid evidence on the linkage between exposure to green and blue spaces and mental health among the elderly in non-Western countries is scarce and limited to exposure metrics based on remote sensing images (i.e., land cover and vegetation indices). Such overhead-view measures may fail to capture how people perceive the environment on the site. OBJECTIVE:This study aimed to compare streetscape metrics derived from street view images with satellite-derived ones for the assessment of green and blue space; and to examine associations between exposure to green and blue spaces as well as geriatric depression in Beijing, China. METHODS:Questionnaire data on 1190 participants aged 60 or above were analyzed cross-sectionally. Depressive symptoms were assessed through the shortened Geriatric Depression Scale (GDS-15). Streetscape green and blue spaces were extracted from Tencent Street View data by a fully convolutional neural network. Indicators derived from street view images were compared with a satellite-based normalized difference vegetation index (NDVI), a normalized difference water index (NDWI), and those derived from GlobeLand30 land cover data on a neighborhood level. Multilevel regressions with neighborhood-level random effects were fitted to assess correlations between GDS-15 scores and these green and blue spaces exposure metrics. RESULTS:The average cumulative GDS-15 score was 3.4 (i.e., no depressive symptoms). Metrics of green and blue space derived from street view images were not correlated with satellite-based ones. While NDVI was highly correlated with GlobeLand30 green space, NDWI was moderately correlated with GlobeLand30 blue space. Multilevel regressions showed that both street view green and blue spaces were inversely associated with GDS-15 scores and achieved the highest model goodness-of-fit. No significant associations were found with NDVI, NDWI, and GlobeLand30 green and blue space. Our results passed robustness tests. CONCLUSION:Our findings provide support that street view green and blue spaces are protective against depression for the elderly in China, yet longitudinal confirmation to infer causality is necessary. Street view and satellite-derived green and blue space measures represent different aspects of natural environments. Both street view data and deep learning are valuable tools for automated environmental exposure assessments for health-related studies.
Project description:Adolescent mental health problems are associated with poor health and well-being in adulthood. We used data from a cohort of 2,264 children born in large US cities in 1998-2000 to examine whether neighborhood collective efficacy (a combination of social cohesion and control) is associated with improvements in adolescent mental health. We found that children who grew up in neighborhoods with high collective efficacy experienced fewer depressive and anxiety symptoms during adolescence than similar children from neighborhoods with low collective efficacy. The magnitude of this neighborhood effect is comparable to the protective effects of depression prevention programs aimed at general or at-risk adolescent populations. Our findings did not vary by family or neighborhood income, which indicates that neighborhood collective efficacy supports adolescent mental health across diverse populations and urban settings. We recommend a greater emphasis on neighborhood environments in individual mental health risk assessments and greater investment in community-based initiatives that strengthen neighborhood social cohesion and control.
Project description:Neighborhood attributes have been shown to influence health, but advances in neighborhood research has been constrained by the lack of neighborhood data for many geographical areas and few neighborhood studies examine features of nonmetropolitan locations. We leveraged a massive source of Google Street View (GSV) images and computer vision to automatically characterize national neighborhood built environments. Using road network data and Google Street View API, from December 15, 2017-May 14, 2018 we retrieved over 16 million GSV images of street intersections across the United States. Computer vision was applied to label each image. We implemented regression models to estimate associations between built environments and county health outcomes, controlling for county-level demographics, economics, and population density. At the county level, greater presence of highways was related to lower chronic diseases and premature mortality. Areas characterized by street view images as 'rural' (having limited infrastructure) had higher obesity, diabetes, fair/poor self-rated health, premature mortality, physical distress, physical inactivity and teen birth rates but lower rates of excessive drinking. Analyses at the census tract level for 500 cities revealed similar adverse associations as was seen at the county level for neighborhood indicators of less urban development. Possible mechanisms include the greater abundance of services and facilities found in more developed areas with roads, enabling access to places and resources for promoting health. GSV images represents an underutilized resource for building national data on neighborhoods and examining the influence of built environments on community health outcomes across the United States.