【摘要】 目的 分析安徽省食源性疾病与气温的关系，探讨滞后效应及识别易感人群。方法 收集2016―2019年安徽省各市食源性疾病监测数据以及同期气象数据。采用类Poisson回归的广义线性模型分析各市日均气温和食源性疾病的关系，然后采用Meta分析合并效应值。结果 研究期间，安徽省共填报348 958例食源性疾病病例，年均发病率0.13%。日均气温与食源性疾病发病呈线性关系，且存在一定的滞后效应。单日滞后中，其效应在当天(lag0)最大，效应值为1.009 6(95%CI:1.004 7～1.019 0),即日均气温每增加1℃,当日食源性疾病发生风险增加1.009 6倍。到滞后第3天及以后其效应无统计学意义。累积滞后中，lag05对应的RR值最大，为1.019 9(95%CI:1.012 6～1.027 2)。亚组分析结果显示，<65岁年龄组较≥65岁年龄组更易受到影响。结论 气温升高会增加食源性疾病的发病风险，且存在滞后效应，应加强对易感人群的预防。更多还原

【Abstract】 Objective To examine the effect of ambient temperature on foodborne diseases in Anhui Province, identify lag effects, and pinpoint vulnerable populations. Methods Foodborne disease surveillance data and meteorological data from all Cities in Anhui Province from 2016 to 2019 were collected. A generalized linear model based on quasi-Poisson regression was used to analyze the potential association between mean temperature and foodborne diseases in each city. Meta-analysis was then applied to pool the estimated city-specific effects. Results Between 2016 and 2019, 348 958 cases of foodborne diseases were reported in Anhui Province, with an annual incidence rate of 0.13%. Mean ambient temperature exhibited a linear effect on foodborne diseases incidence and revealed a delayed effect. In single lag effect, the maximum effect occurred at lag0 with a corresponding RR of 1.009 6(95% CI: 1.004 7-1.019 0), indicating that a 1 ℃ temperature increase would raise the risk of foodborne diseases by 1.009 6-time on the current day. As the lag day lengthened, the effect diminished gradually, becoming statistically insignificant on the third lag day. For cumulative lag effects, the maximum effect was at lag05 1.019 9(95% CI: 1.012 6-1.027 2). Subgroup analysis showed that individuals less than 65 years old were more susceptible than those aged 65 or older. Conclusions Ambient temperature can increase the risk of foodborne disease, with a lag effect observed. Prevention program on foodborne disease should be focusing on susceptible individuals.更多还原