Environmental Influences on Leisure-Time Physical Inactivity in the U.S.: An Exploration of Spatial Non-Stationarity
Considerable research has been conducted to advance our understanding of how environmental factors influence people’s health behaviors (e.g., leisure-time physical inactivity) at the neighborhood level. However, different environmental factors may operate differently at different geographic location...
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doaj-d83378443bbe42fe9deb286aa0f79a622020-11-24T20:58:59ZengMDPI AGISPRS International Journal of Geo-Information2220-99642018-04-017414310.3390/ijgi7040143ijgi7040143Environmental Influences on Leisure-Time Physical Inactivity in the U.S.: An Exploration of Spatial Non-StationarityJue Wang0Kangjae Lee1Mei-Po Kwan2Department of Geography and Geographic Information Science, University of Illinois at Urbana-Champaign, Natural History Building, MC-150, 1301 W Green Street, Urbana, IL 61801, USAIllinois Informatics Institute, University of Illinois at Urbana-Champaign, National Center for Supercomputing Applications, MC-257, 1205 W Clark St., Urbana, IL 61801, USADepartment of Geography and Geographic Information Science, University of Illinois at Urbana-Champaign, Natural History Building, MC-150, 1301 W Green Street, Urbana, IL 61801, USAConsiderable research has been conducted to advance our understanding of how environmental factors influence people’s health behaviors (e.g., leisure-time physical inactivity) at the neighborhood level. However, different environmental factors may operate differently at different geographic locations. This study explores the inconsistent findings regarding the associations between environmental exposures and physical inactivity. To address spatial autocorrelation and explore the impact of spatial non-stationarity on research results which may lead to biased estimators, this study uses spatial regression models to examine the associations between leisure-time physical inactivity and different social and physical environmental factors for all counties in the conterminous U.S. By comparing the results with the conventional ordinary least squares regression and spatial lag model, the geographically weighted regression model adequately addresses the problem of spatial autocorrelation (Moran’s I of the residual = 0.0293) and highlights the spatial non-stationarity of the associations. The existence of spatial non-stationarity that leads to biased estimators, which were often ignored in past research, may be another reason for the inconsistent findings in previous studies besides the modifiable areal unit problem and the uncertain geographic context problem. Also, the observed associations between environmental variables and leisure-time physical inactivity are helpful for developing location-based policies and interventions to encourage people to undertake more physical activity.http://www.mdpi.com/2220-9964/7/4/143physical activityspatial regressionspatial autocorrelationspatial non-stationarityenvironmental healthGIS |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jue Wang Kangjae Lee Mei-Po Kwan |
spellingShingle |
Jue Wang Kangjae Lee Mei-Po Kwan Environmental Influences on Leisure-Time Physical Inactivity in the U.S.: An Exploration of Spatial Non-Stationarity ISPRS International Journal of Geo-Information physical activity spatial regression spatial autocorrelation spatial non-stationarity environmental health GIS |
author_facet |
Jue Wang Kangjae Lee Mei-Po Kwan |
author_sort |
Jue Wang |
title |
Environmental Influences on Leisure-Time Physical Inactivity in the U.S.: An Exploration of Spatial Non-Stationarity |
title_short |
Environmental Influences on Leisure-Time Physical Inactivity in the U.S.: An Exploration of Spatial Non-Stationarity |
title_full |
Environmental Influences on Leisure-Time Physical Inactivity in the U.S.: An Exploration of Spatial Non-Stationarity |
title_fullStr |
Environmental Influences on Leisure-Time Physical Inactivity in the U.S.: An Exploration of Spatial Non-Stationarity |
title_full_unstemmed |
Environmental Influences on Leisure-Time Physical Inactivity in the U.S.: An Exploration of Spatial Non-Stationarity |
title_sort |
environmental influences on leisure-time physical inactivity in the u.s.: an exploration of spatial non-stationarity |
publisher |
MDPI AG |
series |
ISPRS International Journal of Geo-Information |
issn |
2220-9964 |
publishDate |
2018-04-01 |
description |
Considerable research has been conducted to advance our understanding of how environmental factors influence people’s health behaviors (e.g., leisure-time physical inactivity) at the neighborhood level. However, different environmental factors may operate differently at different geographic locations. This study explores the inconsistent findings regarding the associations between environmental exposures and physical inactivity. To address spatial autocorrelation and explore the impact of spatial non-stationarity on research results which may lead to biased estimators, this study uses spatial regression models to examine the associations between leisure-time physical inactivity and different social and physical environmental factors for all counties in the conterminous U.S. By comparing the results with the conventional ordinary least squares regression and spatial lag model, the geographically weighted regression model adequately addresses the problem of spatial autocorrelation (Moran’s I of the residual = 0.0293) and highlights the spatial non-stationarity of the associations. The existence of spatial non-stationarity that leads to biased estimators, which were often ignored in past research, may be another reason for the inconsistent findings in previous studies besides the modifiable areal unit problem and the uncertain geographic context problem. Also, the observed associations between environmental variables and leisure-time physical inactivity are helpful for developing location-based policies and interventions to encourage people to undertake more physical activity. |
topic |
physical activity spatial regression spatial autocorrelation spatial non-stationarity environmental health GIS |
url |
http://www.mdpi.com/2220-9964/7/4/143 |
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