摘要
Abstract
[Background]Other infectious diarrhea(OID)refers to infectious diarrhea other than cholera,dysentery,and typhoid/paratyphoid fever.In the global climate change context,frequent extreme temperature events pose a significant threat to population health,yet the association between extreme temperatures and OID remains unclear.
[Objective]To understand the impact of extreme temperature events on the incidence of OID in Taizhou region,and provide a scientific basis for formulating targeted public health intervention strategies.
[Methods]Case data of OID from 2016 to 2024 and meteorological and pollutant data of Taizhou,Zhejiang during the same period were collected.The case data were derived from National Notifiable Infectious Diseases Reporting System,while the meteorological data and pollutant data were obtained from National Meteorological Science Data Center and Taizhou Ecology and Environment Bureau,respec-tively.An extreme heat event is defined as a period of two or more consecutive days in the warm season during which the daily mean temperature exceeds the 90th percentile value for that season.Similarly,an extreme cold event is defined as a period of two or more consecutive days in the cold season during which the daily mean temperature falls below the 10th percentile value.A distributed lag nonlinear model based on Poisson regression was used to assess the impact of extreme temperatures on OID incidence.Furthermore,subgroup analyses were conducted by gender and age.
[Results]From 2016 to 2024,a total of 108 670 OID cases were reported in Taizhou,with higher incidence in males(61 253 cases)than females(47 417 cases).In terms of single-day lag effect,exposure to extreme cold presented an inverted U-shaped risk pattern:a significant risk effect began to emerge on the 4th day after exposure,continued to rise,and reached a peak on the 7th day(RR=1.044,95%CI:1.029,1.058),whereas extreme heat had no significant impact.In terms of cumulative lag effect,exposure to extreme cold presented a J-shaped cumulative effect curve:short-term exposure(0-2 days)showed no risk effect,but as time extended(0-9 days),a risk effect emerged and reached the maximum risk value during the 0-12 d cumulative period(RR=1.243,95%CI:1.057,1.461).In contrast,extreme heat had no cumulative lag effect.The subgroup analysis revealed that under extreme cold exposure,the single-day lag effects for both males and females exhibited an inverted U-shaped curve,with the risk peaking on day 7 for males(RR=1.045,95%CI:1.026,1.065)and day 8 for females(RR=1.041,95%CI:1.019,1.064).The risk pattern in the 1-5 years age group was similar to that of the overall population but with a higher effect size(RR=1.063,95%CI:1.041,1.085).In terms of the cumulative lag effects,the cumulative risk curves for both males and females under extreme cold exposure showed a J-shaped pattern with varied risk profiles.Significant variations in risk patterns were observed across different age groups.No significant cumulative lag effects were observed for extreme heat exposure in any sub-group.
[Conclusion]Extreme cold can increase the incidence of OID in Taizhou,and the risk effects are heterogeneous among different groups.No risk effect is observed for extreme heat.关键词
极端温度/其他感染性腹泻/风险/滞后效应/分布滞后非线性模型Key words
extreme temperature/other infectious diarrhea/risk/lag effect/distributed lag nonlinear model分类
医药卫生
