Roberts Jennifer D, Voss Jameson D, Knight Brandon
Department of Preventive Medicine and Biometrics, F. Edward Hebert School of Medicine, Uniformed Services University, Bethesda, Maryland, United States of America.
Department of Preventive Medicine and Biometrics, F. Edward Hebert School of Medicine, Uniformed Services University, Bethesda, Maryland, United States of America; Epidemiology Consult Service, United States Air Force School of Aerospace Medicine, Wright-Patterson Air Force Base, Ohio, United States of America.
PLoS One. 2014 Mar 5;9(3):e90143. doi: 10.1371/journal.pone.0090143. eCollection 2014.
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.
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.
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.
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.
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.
缺乏身体活动、环境空气污染和肥胖是非传染性疾病的可改变风险因素，其中缺乏身体活动在全球过早死亡原因中占10%。尽管社区层面的干预措施可能会同时针对这三者，但关于这些风险因素之间关系的研究却很缺乏。
在比较空间插值方法以确定美国各地细颗粒物（PM2.5；PM10）和臭氧（O3）暴露的最佳预测指标后，我们评估了环境空气污染与成年人休闲时间身体活动不足之间的横断面关联。
在这项横断面研究中，我们使用疾病控制和预防中心2011年行为风险因素监测系统的个人自我报告调查数据评估休闲时间身体活动不足情况。这些数据与美国环境保护局县级空气污染暴露估计值相结合，采用两种插值方法（反距离加权法和经验贝叶斯克里金法）。最后，我们通过进行逻辑回归评估空气污染水平较高者的活动是否较少，对人口统计学和行为风险因素进行了调整，并按体重类别进行分层。
对于经验贝叶斯克里金法得出的空气污染值，在完全调整模型中，我们估计正常体重受访者中，PM2.5每增加一个暴露等级，休闲时间身体活动不足的几率相对增加16% - 35%，具有统计学意义（p值<0.0001）。有证据表明PM2.5暴露剂量增加与身体活动不足几率增加之间存在关联。
在一个具有全国代表性的横断面样本中，社区层面空气污染增加与休闲时间身体活动减少有关，尤其是在正常体重人群中。虽然我们的设计无法进行因果推断，但这些结果提供了额外证据，表明空气污染应作为身体活动不足的一个环境决定因素进行研究。
