Qiu Beibei, Xu Zhengyuan, Miao Ruifen
Department of Chronic Communicable Disease, Nanjing Municipal Center for Disease Control and Prevention Affiliated to Nanjing Medical University, Nanjing, People's Republic of China.
School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China.
Infect Drug Resist. 2025 Jun 10;18:2951-2961. doi: 10.2147/IDR.S523064. eCollection 2025.
The associations between meteorological factors, air pollutant indicators, and latent tuberculosis infection (LTBI) have not yet been confirmed. This study aimed to assess the association of meteorological factors, air pollutant indicators, and other factors with LTBI among college students.
We selected 5,193 freshmen randomly who originated from key tuberculosis areas in nine colleges in Nanjing. We ranked the importance of independent variables using Least Absolute Shrinkage and Selection Operator (LASSO) regression and random forest models. We then conducted a multi-model analysis after incorporating them into the prediction model. In addition, we adopted a calibration curve to determine the quality of the model. A nomogram was used to evaluate the possibility of using multiple models to predict LTBI risk.
We found that higher outdoor PM concentrations (OR: 1.35; 95% CI: 1.10-1.65) was associated with LTBI. A history of allergies (OR: 1.37; 95% CI: 1.16-1.62) and coal-based fuels (OR: 1.44; 95% CI: 1.11-1.87) had a positive correlation with the occurrence of LTBI. Taking vitamin D supplements (OR: 0.82; 95% CI: 0.69-0.98) could reduce the risk of LTBI. Besides, age (OR: 1.11; 95% CI: 1.00-1.22) were significantly associated with strong positive populations.
Higher outdoor PM concentration, history of allergies, and use of coal-based fuels were positively correlated with the occurrence of LTBI. Vitamin D supplementation might reduce the risk of LTBI. Besides, older people were more likely to contribute to strong positive results.
气象因素、空气污染物指标与潜伏性结核感染(LTBI)之间的关联尚未得到证实。本研究旨在评估气象因素、空气污染物指标及其他因素与大学生LTBI之间的关联。
我们随机选取了来自南京9所高校重点结核病地区的5193名新生。我们使用最小绝对收缩和选择算子(LASSO)回归和随机森林模型对自变量的重要性进行排序。然后将它们纳入预测模型后进行多模型分析。此外,我们采用校准曲线来确定模型的质量。使用列线图来评估使用多个模型预测LTBI风险的可能性。
我们发现较高的室外PM浓度(OR:1.35;95%CI:1.10 - 1.65)与LTBI相关。过敏史(OR:1.37;95%CI:1.16 - 1.62)和以煤为基础的燃料(OR:1.44;95%CI:1.11 - 1.87)与LTBI的发生呈正相关。服用维生素D补充剂(OR:0.82;95%CI:0.69 - 0.98)可降低LTBI风险。此外,年龄(OR:1.11;95%CI:1.00 - 1.22)与强阳性人群显著相关。
较高的室外PM浓度、过敏史和使用以煤为基础的燃料与LTBI的发生呈正相关。补充维生素D可能会降低LTBI风险。此外,老年人更有可能导致强阳性结果。