Chang Qinxue, Wang Keyun, Zhang Honglu, Li Changping, Wang Yong, Jing Huaiqi, Li Shanshan, Guo Yuming, Cui Zhuang, Zhang Wenyi
Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University.
Chinese PLA Center for Disease Control and Prevention.
Environ Health Prev Med. 2022;27:13. doi: 10.1265/ehpm.21-00005.
Although previous studies have shown that meteorological factors such as temperature are related to the incidence of bacillary dysentery (BD), researches about the non-linear and interaction effect among meteorological variables remain limited. The objective of this study was to analyze the effects of temperature and other meteorological variables on BD in Beijing-Tianjin-Hebei region, which is a high-risk area for BD distribution.
Our study was based on the daily-scale data of BD cases and meteorological variables from 2014 to 2019, using generalized additive model (GAM) to explore the relationship between meteorological variables and BD cases and distributed lag non-linear model (DLNM) to analyze the lag and cumulative effects. The interaction effects and stratified analysis were developed by the GAM.
A total of 147,001 cases were reported from 2014 to 2019. The relationship between temperature and BD was approximately liner above 0 °C, but the turning point of total temperature effect was 10 °C. Results of DLNM indicated that the effect of high temperature was significant on lag 5d and lag 6d, and the lag effect showed that each 5 °C rise caused a 3% [Relative risk (RR) = 1.03, 95% Confidence interval (CI): 1.02-1.05] increase in BD cases. The cumulative BD cases delayed by 7 days increased by 31% for each 5 °C rise in temperature above 10 °C (RR = 1.31, 95% CI: 1.30-1.33). The interaction effects and stratified analysis manifested that the incidence of BD was highest in hot and humid climates.
This study suggests that temperature can significantly affect the incidence of BD, and its effect can be enhanced by humidity and precipitation, which means that the hot and humid environment positively increases the incidence of BD.
尽管先前的研究表明温度等气象因素与细菌性痢疾(BD)的发病率有关,但关于气象变量之间的非线性和交互作用的研究仍然有限。本研究的目的是分析温度和其他气象变量对京津冀地区BD的影响,该地区是BD分布的高风险区域。
我们的研究基于2014年至2019年BD病例和气象变量的日尺度数据,使用广义相加模型(GAM)探索气象变量与BD病例之间的关系,并使用分布滞后非线性模型(DLNM)分析滞后和累积效应。通过GAM进行交互效应和分层分析。
2014年至2019年共报告了147,001例病例。温度与BD之间的关系在0℃以上近似呈线性,但总温度效应的转折点为10℃。DLNM的结果表明,高温在滞后5天和滞后6天的影响显著,滞后效应表明每升高5℃,BD病例增加3%[相对风险(RR)=1.03,95%置信区间(CI):1.02-1.05]。在10℃以上,温度每升高5℃,延迟7天的累积BD病例增加31%(RR=1.31,95%CI:1.30-1.33)。交互效应和分层分析表明,在炎热潮湿的气候中BD的发病率最高。
本研究表明温度可显著影响BD的发病率,湿度和降水可增强其影响,这意味着炎热潮湿的环境会增加BD的发病率。