Shape of the concentration–response association between fine particulate matter pollution and human mortality in Beijing, China, and its implications for health impact assessment, The

Abstract

Background: Studies found approximately linear short-term associations between particulate matter (PM) and mortality in Western communities. However, in China, where the urban PM levels are typically considerably higher than in Western communities, some studies suggest nonlinearity in this association. Health impact assessments (HIA) of PM in China have generally not incorporated nonlinearity in the concentration–response (C-R) association, which could result in large discrepancies in estimates of excess deaths if the true association is nonlinear. Objectives: We investigated nonlinearity in the C-R associations between with PM with aerodynamic diameter ≤2.5μm (PM2.5) and mortality in Beijing, China, and the sensitivity of HIA to linearity assumptions. Methods: We modeled the C-R association between PM2.5 and cause-specific mortality in Beijing, China (2009–2012), using generalized linear models (GLM). PM2.5 was included through either linear, piecewise-linear, or spline functions to investigate evidence of nonlinearity. To determine the sensitivity of HIA to linearity assumptions, we estimated PM2.5-attributable deaths using both linear- and nonlinear-based C-R associations between PM2.5 and mortality. Results: We found some evidence that, for nonaccidental and circulatory mortality, the shape of the C-R association was relatively flat at lower concentrations of PM2.5, but then had a positive slope at higher concentrations, indicating nonlinearity. Conversely, the shape for respiratory mortality was positive and linear at lower concentrations of PM2.5, but then leveled off at the higher concentrations. Estimates of excess deaths attributable to short-term PM2.5 exposure were, in some cases, very sensitive to the linearity assumption in the association, but in other cases robust to this assumption. Conclusions: Our results demonstrate some evidence of nonlinearity in PM2.5–mortality associations and that an assumption of linearity in this association can influence HIAs, highlighting the importance of understanding potential nonlinearity in the PM2.5–mortality association at the high concentrations of PM2.5 in developing megacities like Beijing. https://doi.org/10.1289/EHP4464