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Spatially modelling the association between access to recreational facilities and exercise: the 'Multi-ethnic study of atherosclerosis'
Journal article   Open access

Spatially modelling the association between access to recreational facilities and exercise: the 'Multi-ethnic study of atherosclerosis'

Samuel I. Berchuck, Joshua L. Warren, Amy H. Herring, Kelly R. Evenson, Kari A. B. Moore, Yamini K. Ranchod and Ana V. Diez-Roux
Journal of the Royal Statistical Society. Series A, Statistics in society, v 179(1), pp 293-310
01 Jan 2016
PMID: 26877598
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://europepmc.org/articles/pmc4751045View
Accepted (AM)Open Access (License Unspecified) Open
url
https://doi.org/10.1111/rssa.12119View
Published, Version of Record (VoR) Open

Abstract

Mathematical Methods In Social Sciences Mathematics Physical Sciences Science & Technology Social Sciences Social Sciences, Mathematical Methods Statistics & Probability
Numerous studies have investigated the relationship between the built environment and physical activity. However, these studies assume that these relationships are invariant over space. In this study, we introduce a novel method to analyse the association between access to recreational facilities and exercise allowing for spatial heterogeneity. In addition, this association is studied before and after controlling for crime, which is a variable that could explain spatial heterogeneity of associations. We use data from the Chicago site of the Multi-ethnic study of atherosclerosis' of 781 adults aged 46 years and over. A spatially varying coefficient tobit regression model is implemented in the Bayesian setting to allow for the association of interest to vary over space. The relationship is shown to vary over Chicago, being positive in the south but negative or null in the north. Controlling for crime weakens the association in the south with little change observed in northern Chicago. The results of this study indicate that spatial heterogeneity in associations of environmental factors with health may vary over space and deserve further exploration.

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7 citations in Scopus

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UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

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Collaboration types
Domestic collaboration
Web of Science research areas
Social Sciences, Mathematical Methods
Statistics & Probability
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