Dataset Information

Particulate matter air pollution and national and county life expectancy loss in the USA: A spatiotemporal analysis.

ABSTRACT:

Background

Exposure to fine particulate matter pollution (PM2.5) is hazardous to health. Our aim was to directly estimate the health and longevity impacts of current PM2.5 concentrations and the benefits of reductions from 1999 to 2015, nationally and at county level, for the entire contemporary population of the contiguous United States.

Methods and findings

We used vital registration and population data with information on sex, age, cause of death, and county of residence. We used four Bayesian spatiotemporal models, with different adjustments for other determinants of mortality, to directly estimate mortality and life expectancy loss due to current PM2.5 pollution and the benefits of reductions since 1999, nationally and by county. The covariates included in the adjusted models were per capita income; percentage of population whose family income is below the poverty threshold, who are of Black or African American race, who have graduated from high school, who live in urban areas, and who are unemployed; cumulative smoking; and mean temperature and relative humidity. In the main model, which adjusted for these covariates and for unobserved county characteristics through the use of county-specific random intercepts, PM2.5 pollution in excess of the lowest observed concentration (2.8 ?g/m3) was responsible for an estimated 15,612 deaths (95% credible interval 13,248-17,945) in females and 14,757 deaths (12,617-16,919) in males. These deaths would lower national life expectancy by an estimated 0.15 years (0.13-0.17) for women and 0.13 years (0.11-0.15) for men. The life expectancy loss due to PM2.5 was largest around Los Angeles and in some southern states such as Arkansas, Oklahoma, and Alabama. At any PM2.5 concentration, life expectancy loss was, on average, larger in counties with lower income and higher poverty rate than in wealthier counties. Reductions in PM2.5 since 1999 have lowered mortality in all but 14 counties where PM2.5 increased slightly. The main limitation of our study, similar to other observational studies, is that it is not guaranteed for the observed associations to be causal. We did not have annual county-level data on other important determinants of mortality, such as healthcare access and quality and diet, but these factors were adjusted for with use of county-specific random intercepts.

Conclusions

According to our estimates, recent reductions in particulate matter pollution in the USA have resulted in public health benefits. Nonetheless, we estimate that current concentrations are associated with mortality impacts and loss of life expectancy, with larger impacts in counties with lower income and higher poverty rate.

SUBMITTER: Bennett JE

PROVIDER: S-EPMC6650052 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Particulate matter air pollution and national and county life expectancy loss in the USA: A spatiotemporal analysis.

Bennett James E JE Tamura-Wicks Helen H Parks Robbie M RM Burnett Richard T RT Pope C Arden CA Bechle Matthew J MJ Marshall Julian D JD Danaei Goodarz G Ezzati Majid M

PLoS medicine 20190723 7

<h4>Background</h4>Exposure to fine particulate matter pollution (PM2.5) is hazardous to health. Our aim was to directly estimate the health and longevity impacts of current PM2.5 concentrations and the benefits of reductions from 1999 to 2015, nationally and at county level, for the entire contemporary population of the contiguous United States.<h4>Methods and findings</h4>We used vital registration and population data with information on sex, age, cause of death, and county of residence. We us ...[more]

PMID: 31335874

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Dataset Information

Particulate matter air pollution and national and county life expectancy loss in the USA: A spatiotemporal analysis.

Background

Methods and findings

Conclusions

Publications

Particulate matter air pollution and national and county life expectancy loss in the USA: A spatiotemporal analysis.

Similar Datasets

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