Countervailing effects of income, air pollution, smoking, and obesity on aging and life expectancy: population-based study of US Counties

被引:14
|
作者
Allen, Ryan T. [1 ]
Hales, Nicholas M. [1 ]
Baccarelli, Andrea [2 ]
Jerrett, Michael [3 ]
Ezzati, Majid [4 ]
Dockery, Douglas W. [2 ]
Pope, C. Arden, III [1 ]
机构
[1] Brigham Young Univ, Dept Econ, 142 FOB, Provo, UT 84602 USA
[2] Harvard TH Chan Sch Publ Hlth, Dept Environm Hlth, 665 Huntington Ave, Boston, MA 02115 USA
[3] Univ Calif Los Angeles, Fielding Sch Publ Hlth, 650Charles E Young Dr South,56-070B CHS, Los Angeles, CA 90095 USA
[4] Imperial Coll London, Sch Publ Hlth, MRC PHE Ctr Environm & Hlth, London, England
来源
ENVIRONMENTAL HEALTH | 2016年 / 15卷
关键词
Air pollution; Life expectancy; Income; Smoking; Obesity; Economic tradeoffs; UNITED-STATES; HEALTH; MORTALITY; EXPOSURE; INEQUALITIES; ASSOCIATION; COUNTRIES; CANCER; COHORT; ADULTS;
D O I
10.1186/s12940-016-0168-2
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Background: Income, air pollution, obesity, and smoking are primary factors associated with human health and longevity in population-based studies. These four factors may have countervailing impacts on longevity. This analysis investigates longevity trade-offs between air pollution and income, and explores how relative effects of income and air pollution on human longevity are potentially influenced by accounting for smoking and obesity. Methods: County-level data from 2,996 U.S. counties were analyzed in a cross-sectional analysis to investigate relationships between longevity and the four factors of interest: air pollution (mean 1999-2008 PM2.5), median income, smoking, and obesity. Two longevity measures were used: life expectancy (LE) and an exceptional aging (EA) index. Linear regression, generalized additive regression models, and bivariate thin-plate smoothing splines were used to estimate the benefits of living in counties with higher incomes or lower PM2.5. Models were estimated with and without controls for smoking, obesity, and other factors. Results: Models which account for smoking and obesity result in substantially smaller estimates of the effects of income and pollution on longevity. Linear regression models without these two variables estimate that a $1,000 increase in median income (1 mu g/m(3) decrease in PM2.5) corresponds to a 27.39 (33.68) increase in EA and a 0.14 (0.12) increase in LE, whereas models that control for smoking and obesity estimate only a 12.32 (20.22) increase in EA and a 0.07 (0.05) increase in LE. Nonlinear models and thin-plate smoothing splines also illustrate that, at higher levels of income, the relative benefits of the income-pollution tradeoff changed-the benefit of higher incomes diminished relative to the benefit of lower air pollution exposure. Conclusions: Higher incomes and lower levels of air pollution both correspond with increased human longevity. Adjusting for smoking and obesity reduces estimates of the benefits of higher income and lower air pollution exposure. This adjustment also alters the tradeoff between income and pollution: increases in income become less beneficial relative to a fixed reduction in air pollution-especially at higher levels of income.
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页数:10
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