Assessing short-term impact of PM10 on mortality using a semiparametric generalized propensity score approach

Abstract

Background: The shape of the exposure-response curve describing the effects of air pollution on population health has crucial regulatory implications, and it is important in assessing causal impacts of hypothetical policies of air pollution reduction. Methods: After having reformulated the problem of assessing the short-term impact of air pollution on health within the potential outcome approach to causal inference, we developed a method based on the generalized propensity score (GPS) to estimate the average dose-response function (aDRF) and quantify attributable deaths under different counterfactual scenarios of air pollution reduction. We applied the proposed approach to assess the impact of airborne particles with a diameter less than or equal to 10 μm (PM 10) on deaths from natural, cardiovascular and respiratory causes in the city of Milan, Italy (2003-2006). Results: As opposed to what is commonly assumed, the estimated aDRFs were not linear, being steeper for low-moderate values of exposure. In the case of natural mortality, the curve became flatter for higher levels; this behavior was less pronounced for cause-specific mortality. The effect was larger in days characterized by higher temperature. According to the curves, we estimated that a hypothetical intervention able to set the daily exposure levels exceeding 40 μg/m 3 to exactly 40 would have avoided 1157 deaths (90%CI: 689, 1645) in the whole study period, 312 of which for respiratory causes and 771 for cardiovascular causes. These impacts were higher than those obtained previously from regression-based methods. Conclusion: This novel method based on the GPS allowed estimating the average dose-response function and calculating attributable deaths, without requiring strong assumptions about the shape of the relationship. Its potential as a tool for investigating effect modification by temperature and its use in other environmental epidemiology contexts deserve further investigation.

Long-term exposure to particulate matter and risk of dementia in Korea: A national population-based cohort study

“…The shape of the exposureresponse could play an important role in determining disease burden by suggesting whether a safe threshold exists (Roberts and Martin 2006). Some studies have suggested a violation of the log-linearity assumption for particulate matter effects on population mortality and morbidity (Forastiere et al 2020;Li et al 2019b;Liu et al 2019). In our vascular dementia model, the risk of dementia tended to increase when PM 10 concentration increased by 53.4 µg/m 3 (Q3) and remained constant thereafter.…”

Long-term exposure to particulate matter and risk of Alzheimer’s disease and vascular dementia in Korea: a national population-based Cohort Study

“…In our curves, the slope for PM 10 -vascular dementia was steeper at concentrations lower than 50 µg/m 3 , and the slopes seed to flatter at high ranges. Some previous studies also have suggested a violation of the log-linearity assumption for particulate matter effects on population mortality and morbidity [ 17 , 36 , 37 ]. One possible explanation could be that populations living in areas with high exposure to PM may develop an adaptive response, resulting in smaller estimates of exposure changes per unit [ 37 ].…”

Improving the design stage of air pollution studies based on wind patterns

“…Further research is therefore needed to better understand if improving the design stage of instrument variable studies with matching methods is feasible given the small sample size it entails 48 – 51 . If it is the case, could matching methods actually lead to different results 52 – 54 ?…”