Abstract

BackgroundEvidence of causal relationship between mortality of older adults and low- concentration PM2.5 remains limited.ObjectivesThis study investigates the effects of low-concentration PM2.5 on the mortality of adults older than 65 using the closure of coal-fired power plants in the Eastern United States as a natural experiment.MethodsWe investigated power plants in the Eastern United States (US) that had production changes through unit shutdown or plant retirement between 1999 and 2013. We included only non-clustered power plants without scrubbers and with capacities greater than 50 MW. We used instrumental variable (IV) and difference-in-differences (DID) approaches to estimate the causal impact of PM2.5 concentrations on mortality among Medicare beneficiaries. We compared changes in monthly age-adjusted mortality before and after the retirement of coal-fired plants between the treated and control counties; we accounted for annual wind direction in our selection of treated and control counties. In the models, we initially included only county and monthly fixed effects, and then adjusted for covariates including: 1) only weather variables (temperature, dew point, pressure); and 2) weather variables and socio-economic variables (median household income and poverty rate).ResultsThe monthly age-adjusted mortality rate averaged across all plants was approximately 423 per 100,000 (SD = 69) and was higher for males than females. Mean PM2.5 concentrations across all counties were 12 μg/m3 (SD = 3.78). Using the IV method, we found that reductions in PM2.5 concentrations significantly decreased monthly mortality among older adults. IV results show that a 1-μg/m3 reduction in PM2.5 concentrations leads to 7.17 fewer deaths per 100,000 per month, or a 1.7% lower monthly mortality rate among people older than 65 years. Using the DID approach, we found that power plant retirement significantly decreased: 1) monthly PM2.5 levels by 2.1 μg/m3, and 2) monthly age-adjusted mortality by approximately 15 people per 100,000 (or 3.6%) in treated counties relative to control counties. The mortality effects were higher among males than females and its impact was the greatest among people older than 75 years.ConclusionThese findings provide evidence of the effectiveness of local, plant-level control measures in reducing near-plant PM2.5 and mortality among U.S. Medicare beneficiaries.

Highlights

  • Evidence of causal relationship between mortality of older adults and low- concentration PM2.5 remains limited

  • Using the instrumental variable (IV) approach, we found that the reduction of PM2.5 significantly decreased monthly age-adjusted mortality by 7 per 100,000 or 1.7% of the mortality rate

  • Using the most comprehensive IV estimate in Column (6) of Table 2, which reports that the reduction of PM2.5 significantly decreases monthly age-adjusted mortality by 7.17 people over 100,000, a back-of-envelope calculation shows that 3322 deaths per year could have been avoided among the US population older than 65 if PM2.5 concentrations decreased by 1 μg/m3

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Summary

Introduction

Evidence of causal relationship between mortality of older adults and low- concentration PM2.5 remains limited. A large number of observational epidemiological studies have established a positive association between shortterm (e.g. daily or monthly) exposure to fine particulate matter (PM2.5) and mortality in the past [1,2,3,4,5,6,7]. The observed association between PM2.5 and mortality may result from factors other than air pollution. Wealthy people, whose health status tends to be good for other reasons, can migrate to clean regions, while poor people may be confined to polluted areas. These observational/associational approaches tend to produce unreliable estimates due to endogeneity issues [10]. Overstating the impacts will lead to over-stringent environmental regulation and potentially hurt economic growth, while underestimating the impacts will provide less than optimal protection for vulnerable people (e.g. infants and the elderly) and result in significant welfare losses

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