Beijing Institute of Tuberculosis Control, Beijing Center for Disease Prevention and Control, Beijing, China.
Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China.
Environ Res. 2023 Jan 1;216(Pt 2):114581. doi: 10.1016/j.envres.2022.114581. Epub 2022 Oct 13.
Tuberculosis (TB) is a severe public health problem globally. Previous studies have revealed insufficient and inconsistent associations between air pollutants, meteorological factors and TB cases. Yet few studies have examined the associations between air pollutants, meteorological factors and TB cases in Beijing.
The purpose of this study was to explore the impact of air pollutants and meteorological factors on TB in Beijing, and to provide novel insights into public health managers to formulate control strategies of TB.
Data on the daily case of TB in Beijing during 2014-2020 were obtained from Chinese tuberculosis information management system. Concurrent data on the daily PM, PM, SO, NO, CO and O, were obtained from the online publication platform of the Chinese National Environmental Monitoring Center. Daily average temperature, average wind speed, relative humidity, sunshine duration and total precipitation were collected from the China Meteorological Science Data Sharing Service System. A distributed lag non-linear model was fitted to identify the non-linear exposure-response relationship and the lag effects between air pollutions, meteorological factors and TB cases in Beijing.
In the single-factor model, the excess risk (ER) of TB was significantly positively associated with every 10 μg/m increase in NO in lag 1 week (ER: 1.3%; 95% confidence interval [CI]: 0.4%, 2.3%) and every 0.1 m/s increase in average wind speed in lag 5 weeks (ER: 0.3%; 95% CI: 0.1%, 0.5%), and was negatively associated with every 10 μg/m increase in O in lag 1 week (ER: -1.2%; 95% CI: -1.8%, -0.5%), every 5 °C increase in average temperature (ER: -1.7%; 95% CI: -2.9%, -0.4%) and every 10% increase in average relative humidity (ER: -0.4%; 95% CI: -0.8%, -0.1%) in lag 10 weeks, respectively. In the multi-factor model, the lag effects between TB cases and air pollutants, meteorological factors were similar. The subgroup analysis suggests that the effects of NO, O, average wind speed and relative humidity on TB were greater in male or labor age subgroup, while the effect of CO was greater in the elderly. In addition, no significant associations were found between PM, SO sunshine duration and TB cases.
Our findings provide a better understanding of air pollutants and meteorological factors driving tuberculosis occurrence in Beijing, which enhances the capacity of public health manager to target early warning and disease control policy-making.
结核病(TB)是全球严重的公共卫生问题。先前的研究表明,空气污染物和气象因素与结核病病例之间的关联不足且不一致。然而,很少有研究探讨北京地区空气污染物、气象因素与结核病病例之间的关系。
本研究旨在探讨空气污染物和气象因素对北京结核病的影响,为公共卫生管理者制定结核病控制策略提供新的思路。
从中国结核病信息管理系统获取 2014-2020 年北京市结核病日病例数据。从中国国家环境监测中心在线发布平台获取同期每日 PM、PM、SO、NO、CO 和 O 数据。从中国气象科学数据共享服务系统收集每日平均气温、平均风速、相对湿度、日照时间和总降水量数据。使用分布式滞后非线性模型来识别北京地区空气污染物、气象因素与结核病病例之间的非线性暴露-反应关系和滞后效应。
在单因素模型中,NO 每增加 10μg/m(滞后 1 周的超额风险 [ER]:1.3%;95%置信区间 [CI]:0.4%,2.3%)和平均风速每增加 0.1m/s(滞后 5 周的 ER:0.3%;95% CI:0.1%,0.5%),TB 的超额风险呈显著正相关;O 每增加 10μg/m(滞后 1 周的 ER:-1.2%;95% CI:-1.8%,-0.5%),平均温度每升高 5°C(滞后 10 周的 ER:-1.7%;95% CI:-2.9%,-0.4%)和平均相对湿度每增加 10%(滞后 10 周的 ER:-0.4%;95% CI:-0.8%,-0.1%),TB 的超额风险呈显著负相关。在多因素模型中,TB 病例与空气污染物和气象因素之间的滞后效应相似。亚组分析表明,NO、O、平均风速和相对湿度对男性或劳动年龄组的 TB 影响更大,而 CO 对老年人的影响更大。此外,PM、SO 和日照时间与 TB 病例之间没有明显关联。
本研究结果更好地了解了北京地区空气污染物和气象因素对结核病发病的驱动作用,增强了公共卫生管理者进行早期预警和疾病控制政策制定的能力。