Abstract
BACKGROUND: Seasonal variation has been observed in the occurrence of pulmonary tuberculosis (PTB). However, whether this variation can be attributed to suboptimal ambient temperatures remains unclear. METHODS: In this study, 30,898 PTB events were identified in Beijing, China, from 2019 to 2023. A distributed-lag non-linear model (DLNM) was utilized to assess the association of daily ambient mean temperature with PTB risk and population-attributable risks, adjusting for potential time-varying confounders. RESULTS: The reference was the minimum morbidity temperature (MMT) of 1.1 °C. The risk of PTB associated with extremely (27.7 °C), sub-extremely (25.2 °C) and moderately (22.0 °C) high temperature occurred on the concurrent day, attenuated on lag 1 day and thereafter became insignificant. The relative risks of PTB at extremely (27.7 °C), sub-extremely (25.2 °C) and moderately (22.0 °C) high temperature cumulated over lag 0-7 days were 1.92 [95% confidence interval (CI): 1.17, 3.13], 1.79 (95% CI: 1.16, 2.76), and 1.66 (95% CI: 1.12, 2.47), respectively, compared to the referent temperature (1.1 °C). Stronger associations were observed for patients who were aged ≥60 years and female. The attributable fraction (AF) of PTB due to temperatures exceeding the MMT (1.1 °C) and physiologically optimal temperature (22 °C) were 11.60 and 10.73%, respectively. CONCLUSION: Our study provides evidence that short-term exposure to high ambient temperature is associated with an increased risk of PTB, with effects being more pronounced in females and the older adults. These findings suggest that rising temperatures could pose a substantial public health challenge for PTB control. Integrating temperature-based early warnings into public health strategies may help mitigate the impact of heat on PTB transmission.