Abstract
BackgroundFine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) are major air pollutants that pose considerable threats to human health. However, what has been mostly missing in air pollution epidemiology is causal dose-response (D-R) relations between those exposures and mortality. Such causal D-R relations can provide profound implications in predicting health impact at a target level of air pollution concentration.MethodsUsing national Medicare cohort during 2000–2016, we simultaneously emulated causal D-R relations between chronic exposures to fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) and all-cause mortality. To relax the contentious assumptions of inverse probability weighting for continuous exposures, including distributional form of the exposure and heteroscedasticity, we proposed a decile binning approach which divided each exposure into ten equal-sized groups by deciles, treated the lowest decile group as reference, and estimated the effects for the other groups. Binning continuous exposures also makes the inverse probability weights robust against outliers.ResultsAssuming the causal framework was valid, we found that higher levels of PM2.5, O3, and NO2 were causally associated with greater risk of mortality and that PM2.5 posed the greatest risk. For PM2.5, the relative risk (RR) of mortality monotonically increased from the 2nd (RR, 1.022; 95% confidence interval [CI], 1.018–1.025) to the 10th decile group (RR, 1.207; 95% CI, 1.203–1.210); for O3, the RR increased from the 2nd (RR, 1.050; 95% CI, 1.047–1.053) to the 9th decile group (RR, 1.107; 95% CI, 1.104–1.110); for NO2, the DR curve wiggled at low levels and started rising from the 6th (RR, 1.005; 95% CI, 1.002–1.018) till the highest decile group (RR, 1.024; 95% CI, 1.021–1.027).ConclusionsThis study provided more robust evidence of the causal relations between air pollution exposures and mortality. The emulated causal D-R relations provided significant implications for reviewing the national air quality standards, as they inferred the number of potential early deaths prevented if air pollutants were reduced to specific levels; for example, lowering each air pollutant concentration from the 70th to 60th percentiles would prevent 65,935 early deaths per year.
Highlights
Fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) are major air pollutants that pose considerable threats to human health [1, 2]
We proposed a decile binning approach to emulate the causal D-R relations between chronic air pollution exposures and mortality by dividing each exposure into ten equal-sized groups by deciles, treating the lowest decile group (i.e., 10% of the study population with the lowest exposure levels) as the reference, and estimating the effects for the other groups compared to the reference
For O3, the risk of mortality monotonically increased from the 2nd (RR, 1.050; 95% confidence interval (CI), 1.047–1.053) to the 9th decile group (RR, 1.107; 95% CI, 1.104–1.110), and dropped at the highest decile group (RR, 1.044; 95% CI, 1.041–1.048)
Summary
Fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) are major air pollutants that pose considerable threats to human health [1, 2]. Chronic exposure to NO2 has been associated with mortality, the evidence is relatively scarce [10, 11] These findings provide important implications for understanding the health burden attributable to poor air quality. A growing literature has examined the long-term effect of PM2.5 on mortality using the formal causal modeling techniques, there is so far little evidence for O3 and NO2 [16,17,18]. What has been mostly missing in air pollution epidemiology is causal dose-response (D-R) relations between those exposures and mortality. Such causal D-R relations can provide profound implications in predicting health impact at a target level of air pollution concentration
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