Department of Tuberculosis Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, 3399 Binsheng Road BinJiang District, Hangzhou, 310000, Zhejiang, China.
Sci Rep. 2024 Oct 25;14(1):25430. doi: 10.1038/s41598-024-76785-0.
Although some studies have explored the role of meteorological factors in the development of tuberculosis (TB), the majority have been confined to single regions, leading to inconsistent findings. Consequently, we conducted a multi-city study not only to determine whether meteorological factors significantly influence the risk of developing TB but also to assess the magnitude of these effects and explore potential modifying factors. Data on daily reported TB cases and meteorological factors were collected from January 1, 2013, to December 31, 2022, across 11 cities in Zhejiang Province. A distributed lag non-linear model using a quasi-Poisson distribution was employed. Multivariate meta-regression was used to obtain overall pooled estimates and assess heterogeneity. From 2013 to 2022, 267,932 TB cases were reported in Zhejiang Province. Notably, a nonlinear relationship was observed between temperature and TB, with the relative risk (RR) peaking at 1.0 °C (RR = 1.882, 95% CI 1.173-3.020). The effect of low temperature was immediate and significant for a 13-day lag period, with the maximum effect at lag0 (RR = 1.014, 95% CI 1.008-1.021). The exposure-response curve between relative humidity (RH) and TB exhibited an M-shape, with the RR peaking at 47.7% (RR = 1.642, 95% CI 1.044-2.582). The lag effect of low RH was significant at lag 25-59, with the highest RR observed at lag 32 (RR = 1.011, 95% CI 1.001-1.022). Gross domestic product (GDP) per person, population density, and latitude demonstrated significant modification effects. Our study showed that low temperature and RH were associated with an increased risk of TB. Additionally, GDP per person, population density, and latitude may play important roles in explaining the association between RH and TB. These findings provide scientific evidence for the development of geographically specific public health policies.
尽管一些研究探讨了气象因素在结核病(TB)发展中的作用,但大多数研究仅限于单一地区,导致结果不一致。因此,我们进行了一项多城市研究,不仅旨在确定气象因素是否显著影响 TB 发病风险,还旨在评估这些影响的程度,并探讨潜在的调节因素。我们收集了 2013 年 1 月 1 日至 2022 年 12 月 31 日期间浙江省 11 个城市的每日报告 TB 病例和气象因素数据。采用分布式滞后非线性模型和拟泊松分布。使用多变量荟萃回归获得总体汇总估计值并评估异质性。2013 年至 2022 年期间,浙江省报告了 267932 例 TB 病例。值得注意的是,温度与 TB 之间存在非线性关系,相对风险(RR)在 1.0°C 时达到峰值(RR=1.882,95%CI 1.173-3.020)。低温的影响是即时且显著的,在滞后 13 天期间达到最大值,在滞后 0 时最大(RR=1.014,95%CI 1.008-1.021)。相对湿度(RH)与 TB 之间的暴露-反应曲线呈 M 形,RR 在 47.7%时达到峰值(RR=1.642,95%CI 1.044-2.582)。低 RH 的滞后效应在滞后 25-59 天内显著,在滞后 32 天达到最高 RR(RR=1.011,95%CI 1.001-1.022)。人均国内生产总值(GDP)、人口密度和纬度显示出显著的调节作用。我们的研究表明,低温和 RH 与 TB 发病风险增加有关。此外,人均 GDP、人口密度和纬度可能在解释 RH 与 TB 之间的关联方面发挥重要作用。这些发现为制定具有地域特色的公共卫生政策提供了科学依据。