Analysis of influencing factors of atmospheric pollution on pulmonary tuberculosis incidence in China from 2014 to 2020

ObjectiveTo investigate the spatiotemporal heterogeneity in the associations between ambient air pollutants (PM2.5, SO2, NO2, CO, O3) and pulmonary tuberculosis (TB) incidence in China from 2014 to 2020, and to provide evidence for region-specific prevention and control strategies.MethodsBased on panel data from 31 provincial-level regions, spatial autocorrelation analysis, spatiotemporal scanning, and a Geographically and Temporally Weighted Regression (GTWR) model were employed. An exposure-window robustness analysis using 1- to 5-year moving averages was further conducted.ResultsThe overall TB incidence declined, yet high-burden clustering remained significant in Xinjiang, Xizang, and Qinghai (RR = 3.56). The GTWR model showed good fit (R2 = 0.889). PM2.5 coefficients exhibited an “east-negative, west-positive” gradient; SO2, NO2, and CO showed synergistic positive associations in Northeast China; O3 was negatively associated in most provinces and attenuated as the exposure window lengthened, suggesting predominantly short-term associations; and GDP coefficients reversed from positive in the east to negative in the west. The moving-average analysis confirmed that these spatial patterns were temporally robust.ConclusionThe associations between air pollution and pulmonary TB exhibit marked spatiotemporal non-stationarity, supporting region-specific prevention and control strategies prioritizing high-burden western regions. As an ecological study, this investigation identifies associations rather than causal relationships.