China, as well as many other populous countries in Asia, continues to face a dual burden of high pulmonary tuberculosis (PTB) incidence and severe air pollution, especially fine particulate matter with a diameter ≤ 2.5 μm (PM2.5). However, few studies have explored the effect of ambient PM2.5, especially its specific components, on the risk of developing PTB. We obtained active PTB cases from 37 prefectures in China over a 7-year period. Prefecture-level monthly PTB counts were analyzed in relation to population-weighted mean concentrations of PM2.5 and its major components. Exposure data were derived from the Tracking Air Pollution in China (TAP) dataset and spatiotemporally linked to each case by prefecture of residence and month of diagnosis. To investigate the lagged exposure-response relationship, we applied an integrated spatiotemporal Bayesian hierarchical model within a distributed lag non-linear modeling framework. We further evaluated potential effect modification by sex, age, local PTB transmission intensity, greenness level, and temperature to assess effect heterogeneity and provide preliminary insights into potential underlying pathways. Mixed-effects meta-regression models were used to evaluate potential effect modification, incorporating interaction terms between the pollutant and each potential modifier. 636,391 PTB cases were reported in our study area during the study period. We found positive associations between all components and PTB incidence and the effects are stronger and last longer at higher concentrations. At the 95th percentile of the concentrations the strongest effect occurring at a one-month lag and lasted for up to three months, the maximum incidence rate ratio were 1.069 (95% CI: 1.046–1.092 ) for PM2.5, 1.048 (95% CI: 1.029–1.068) for sulfate, 1.066 (95% CI: 1.040–1.092) for nitrate, 1.063 (95% CI: 1.039–1.087) for ammonium, 1.060 (95% CI: 1.038–1.083) for OM, and 1.065 (95% CI: 1.045–1.086) for BC. The peak incidence rate ratios (IRRs) per interquartile range (IQR) increase were comparable across components, although the cumulative effects of ammonium were slightly stronger than those of the other pollutants. Meta-regression analyses indicated that the effect sizes varied by sex, age group, PTB transmission intensity, greenness, and annual mean temperature. Stronger associations were observed among males, younger age groups, regions with lower transmission intensity and greenness, and those with higher annual mean temperature, although the magnitude and statistical significance of effect modification differed across components. Exposure to ambient PM2.5 and its components may be associated with an increased risk of PTB. The observed short peak lag times and consistently larger incidence rate ratios in settings with lower local transmission intensity suggest that the increased risk may be more strongly related to disease reactivation or progression from recently acquired infections than to enhanced transmission.
Wang et al. (2026) studied this question.