Individual and joint associations of PM2.5 components with the mumps incidence: based on quantile g-computation and Bayesian kernel machine regression.

Total PM2.5 mass has been shown to be associated with mumps. However, the individual and joint associations of PM2.5 components with mumps and the importance of each PM2.5 component remain unclear. To our knowledge, this ecological study is the first to investigate the associations of PM2.5 components with mumps. We collected the monthly mumps incidence in Northwest China from 2013 to 2019 to investigate the individual and joint effects of PM2.5 components on mumps using geographical probes, quantile g-computation (qgcomp), and Bayesian kernel-machine regression (BKMR) models. We found that sulfate (SO42-) and black carbon (BC) were associated with mumps, and SO42- (weight: 0.143) and organic matter (OM) (weight: 0.857) were positively correlated to mumps according to the qgcomp results. BKMR revealed that BC and OM were the dominant factors for the increasing monthly mumps incidence. The joint associations of PM2.5 components with mumps were positive at the high concentrations, and the single-pollutant models suggested that the individual associations of BC and OM with mumps were positive. Our evidence emphasizes that targeted control of anthropogenic sources of PM2.5 components (especially BC and OM) can help mitigate the monthly mumps incidence.