The association of ambient air pollution and physical inactivity in the United States.
<h4>Background</h4>Physical inactivity, ambient air pollution and obesity are modifiable risk factors for non-communicable diseases, with the first accounting for 10% of premature deaths worldwide. Although community level interventions may target each simultaneously, research on the rel...
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2014
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oai:doaj.org-article:ad7cb026ceef47bca5c5ebff1c149fb82021-11-18T08:29:41ZThe association of ambient air pollution and physical inactivity in the United States.1932-620310.1371/journal.pone.0090143https://doaj.org/article/ad7cb026ceef47bca5c5ebff1c149fb82014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24598907/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>Physical inactivity, ambient air pollution and obesity are modifiable risk factors for non-communicable diseases, with the first accounting for 10% of premature deaths worldwide. Although community level interventions may target each simultaneously, research on the relationship between these risk factors is lacking.<h4>Objectives</h4>After comparing spatial interpolation methods to determine the best predictor for particulate matter (PM2.5; PM10) and ozone (O3) exposures throughout the U.S., we evaluated the cross-sectional association of ambient air pollution with leisure-time physical inactivity among adults.<h4>Methods</h4>In this cross-sectional study, we assessed leisure-time physical inactivity using individual self-reported survey data from the Centers for Disease Control and Prevention's 2011 Behavioral Risk Factor Surveillance System. These data were combined with county-level U.S. Environmental Protection Agency air pollution exposure estimates using two interpolation methods (Inverse Distance Weighting and Empirical Bayesian Kriging). Finally, we evaluated whether those exposed to higher levels of air pollution were less active by performing logistic regression, adjusting for demographic and behavioral risk factors, and after stratifying by body weight category.<h4>Results</h4>With Empirical Bayesian Kriging air pollution values, we estimated a statistically significant 16-35% relative increase in the odds of leisure-time physical inactivity per exposure class increase of PM2.5 in the fully adjusted model across the normal weight respondents (p-value<0.0001). Evidence suggested a relationship between the increasing dose of PM2.5 exposure and the increasing odds of physical inactivity.<h4>Conclusions</h4>In a nationally representative, cross-sectional sample, increased community level air pollution is associated with reduced leisure-time physical activity particularly among the normal weight. Although our design precludes a causal inference, these results provide additional evidence that air pollution should be investigated as an environmental determinant of inactivity.Jennifer D RobertsJameson D VossBrandon KnightPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 3, p e90143 (2014) |
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Medicine R Science Q Jennifer D Roberts Jameson D Voss Brandon Knight The association of ambient air pollution and physical inactivity in the United States. |
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<h4>Background</h4>Physical inactivity, ambient air pollution and obesity are modifiable risk factors for non-communicable diseases, with the first accounting for 10% of premature deaths worldwide. Although community level interventions may target each simultaneously, research on the relationship between these risk factors is lacking.<h4>Objectives</h4>After comparing spatial interpolation methods to determine the best predictor for particulate matter (PM2.5; PM10) and ozone (O3) exposures throughout the U.S., we evaluated the cross-sectional association of ambient air pollution with leisure-time physical inactivity among adults.<h4>Methods</h4>In this cross-sectional study, we assessed leisure-time physical inactivity using individual self-reported survey data from the Centers for Disease Control and Prevention's 2011 Behavioral Risk Factor Surveillance System. These data were combined with county-level U.S. Environmental Protection Agency air pollution exposure estimates using two interpolation methods (Inverse Distance Weighting and Empirical Bayesian Kriging). Finally, we evaluated whether those exposed to higher levels of air pollution were less active by performing logistic regression, adjusting for demographic and behavioral risk factors, and after stratifying by body weight category.<h4>Results</h4>With Empirical Bayesian Kriging air pollution values, we estimated a statistically significant 16-35% relative increase in the odds of leisure-time physical inactivity per exposure class increase of PM2.5 in the fully adjusted model across the normal weight respondents (p-value<0.0001). Evidence suggested a relationship between the increasing dose of PM2.5 exposure and the increasing odds of physical inactivity.<h4>Conclusions</h4>In a nationally representative, cross-sectional sample, increased community level air pollution is associated with reduced leisure-time physical activity particularly among the normal weight. Although our design precludes a causal inference, these results provide additional evidence that air pollution should be investigated as an environmental determinant of inactivity. |
format |
article |
author |
Jennifer D Roberts Jameson D Voss Brandon Knight |
author_facet |
Jennifer D Roberts Jameson D Voss Brandon Knight |
author_sort |
Jennifer D Roberts |
title |
The association of ambient air pollution and physical inactivity in the United States. |
title_short |
The association of ambient air pollution and physical inactivity in the United States. |
title_full |
The association of ambient air pollution and physical inactivity in the United States. |
title_fullStr |
The association of ambient air pollution and physical inactivity in the United States. |
title_full_unstemmed |
The association of ambient air pollution and physical inactivity in the United States. |
title_sort |
association of ambient air pollution and physical inactivity in the united states. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2014 |
url |
https://doaj.org/article/ad7cb026ceef47bca5c5ebff1c149fb8 |
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