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Measuring the Influence of Residential Exposure to Natural Environments on Mental Health and Well-being
Citation:
Silva, R., W. Tsai, F. Cochran, S. Prince, D. Rosenbaum, M. Nash, A. D'Aloisio, L. Jackson, M. Mehaffey, A. Neale, D. Sandler, AND T. Buckley. Measuring the Influence of Residential Exposure to Natural Environments on Mental Health and Well-being. A Community on Ecosystem Services (ACES) 2018 meeting, Washington, DC, December 03 - 06, 2018.
Impact/Purpose:
This research will yield a more complete assessment of environmental influences on human health and well-being in support of EPA’s mission to protect public health and the environment.
Description:
There is compelling evidence that exposure to natural environments has a beneficial effect on human health and well-being, however there are few nationwide studies in the U.S. that have explored this issue. Much of the existing research comprises small, spatially-limited samples or is based on aggregate spatial scales, leading to imprecision in effects estimation and risk for erroneous conclusions. Also, many studies have access to only limited measures of exposure to the natural environment (e.g. percent greenery) and are unable to consider more robust metrics (e.g. distance to green or blue space, views of trees, views of water, etc.). In this study, we evaluate the influence of residential exposure to natural environments on individual well-being outcomes in the NIEHS Sister Study cohort. The cohort is comprised of 50,884 women, aged 35-74 years, living across the U. S. and Puerto Rico, who were enrolled from 2003 to 2009. The multifaceted measures collected by the Sister Study and the broad coverage of participants’ geographic distribution, as well as the diverse demographics within the cohort, help us develop a more comprehensive understanding of linkages and potential mechanisms for how exposure to natural environments influences selected health outcomes. Specifically, we focus on participants who live in the conterminous US and did not change primary residential address during the follow-up period up to 2015. We assess both presence of and access (physical distance) to natural environments based on EPA’s state-of-the-art geospatial ecosystem services tool, EnviroAtlas, using different sized spatial buffers (e.g. 250-m, 3000-m radii) around each individual residential address. We apply mixed effects logistic and linear regression to quantify the associations between several metrics of residential exposure (e.g. population near roadways with little or no tree buffer, access to outdoor recreational resources, percentage of natural land cover, percentage of forest) and outcomes of self-reported health, quality of life, perceived stress, and depressive symptoms. We control for a variety of covariates including individual-level demographic variables (e.g. age, income, education, race/ethnicity, marital status and employment status) and lifestyle factors (e.g. physical activity, dog ownership, perceived social support, smoking and alcohol consumption), an environmental stressor (air pollution), and level of urbanicity. Considering social, spatial, and temporal perspectives, we discuss the impact of using different metrics for assessment of exposure to natural environments. This research will yield a more complete assessment of environmental influences on human health and well-being in support of EPA’s mission to protect public health and the environment.
