@article{WANG2026, 
author = {Chuan WANG and Xiaohan LIU and Jun YANG and Mali WU and Yunli ZHENG and Qiumei ZHANG and Jun SONG and Bihua GAO and Feng LONG and Dan JU and Guozhong HE},
title = {Climate and female tuberculosis incidence: heterogeneity drivers and precision control strategies in China’s 6 major climate zones},
year = {2026},
journal = {Journal of Army Medical University},
volume = {48},
number = {8},
pages = {1110-1118},
keywords = {tuberculosis, female, climatic zones, heterogeneity, precision prevention},
url = {https://www.sciopen.com/article/10.16016/j.2097-0927.202602054},
doi = {10.16016/j.2097-0927.202602054},
abstract = {ObjectiveChina has achieved remarkable progress in tuberculosis (TB) control, with the incidence rates declining continuously; however, the disease burden among females remained substantial with pronounced regional heterogeneity. The differential impacts of climatic factors on TB onset and their driving mechanisms remains poorly understood, particularly lacking zone-specific evidence based on climatic gradients. This study aims to analyze the heterogeneous effects of climatic factors and air pollutants on female TB incidence across 6 climatic zones and identify key driving pathways, thereby providing evidence-based support for developing gender-sensitive, climate-adapted precision prevention and control strategies.MethodsA retrospective descriptive study design was adopted. Based on China’s climate zoning standards and typical climate characteristics, 6 representative regions were selected, corresponding to the 6 major climate zones: Cold-Dry Zone, Hot-Humid Zone, Warm-Humid Zone, Temperate Continental Zone, Alpine Zone, and Temperate Monsoon Zone. Sample representativeness was evaluated across 3 dimensions: geographic coverage (encompassing northern, southern, eastern, western, and central China), climate consistency (consistent with the core climate characteristics of the corresponding regions), and population epidemiological representativeness. A total of 9570 female patients with newly diagnosed TB in 6 regions from 2017 to 2024, along with official meteorological and pollutant monitoring data during the same period, were collected. Two categories of measurement indicators were established for cases and meteorological pollution variables. After preprocessing such as imputation of missing values and construction of lagged 1 to 3 period variables, a panel data set was formed. With female TB case counts as the dependent variable, stepwise regression analysis was applied, and model performance was evaluated using R2, VIF, and F/t tests.ResultsThe overall demographic and clinical characteristics of female TB patients exhibited highly significant heterogeneity across the 6 climatic zones (P<0.001). The TB incidence in the females increased with advancing age, showing a fluctuating downward trend across all regions with significant inter-zone differences. The alpine zone demonstrated high incidence rates, initially declining then rising, decreasing from 155/100000 in 2017 to 36/100000 in 2022, subsequently increasing to 91/100000 in 2024. Regression models for all climatic zones passed multicollinearity tests (VIF<10) and demonstrated extremely significant statistical significance (P<0.001): R2=0.452 for the Cold-Dry Zone, R2=0.589 for the Hot-Humid Zone, R2=0.610 for the Warm-Humid Zone, R2=0.626 for the Temperate Continental Zone, R2=0.641 for the Alpine Zone, and R2=0.580 for the Temperate Monsoon Zone. The combined model yielded R2=0.584 (F=71.548, P<0.001). Lag effects of 2 to 3 periods were present across all regions. Core driving factors were zone-specific, with lag 1 period PM10 identified as the core positive driver of female TB onset.ConclusionClimatic conditions and air pollutants exert significantly heterogeneous effects on female TB incidence across China’s 6 climatic zones. The 2 to 3 period lag effects essentially align with the incubation period of Mycobacterium tuberculosis infection. Regional differences in the incidence are closely associated with climatic characteristics, population behavioral patterns, and pollutant exposure profiles.CountermeasuresBuilding upon the existing technical guidance system for TB prevention and control, it is recommended to incorporate early warning rules tailored to local climatic conditions and pollutant lag-based screening window standards. Screening resources and health education efforts at the primary care level should be reallocated based on core pollutant drivers in each region. Data interfaces among meteorological, environmental, and TB surveillance systems should be integrated to establish linked assessment mechanisms, enabling zone-specific, time-specific precision early warning and targeted interventions.}
}