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苏雪梅, 刘晓萌, 王利, 刘坦, 张荣娜, 刘海博. 应用分布滞后非线性模型评估环境温度对北京市大兴区手足口病发病的影响及归因疾病负担[J]. 疾病监测. DOI: 10.3784/jbjc.202307100330
引用本文: 苏雪梅, 刘晓萌, 王利, 刘坦, 张荣娜, 刘海博. 应用分布滞后非线性模型评估环境温度对北京市大兴区手足口病发病的影响及归因疾病负担[J]. 疾病监测. DOI: 10.3784/jbjc.202307100330
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Su Xuemei, Liu Xiaomeng, Wang Li, Liu Tan, Zhang Rongna, Liu Haibo. Evaluation of effect of ambient temperature on incidence of hand foot and mouth disease and attributable disease burden in Daxing, Beijing by distributed lag non-linear model[J]. Disease Surveillance. DOI: 10.3784/jbjc.202307100330
Citation: Su Xuemei, Liu Xiaomeng, Wang Li, Liu Tan, Zhang Rongna, Liu Haibo. Evaluation of effect of ambient temperature on incidence of hand foot and mouth disease and attributable disease burden in Daxing, Beijing by distributed lag non-linear model[J]. Disease Surveillance. DOI: 10.3784/jbjc.202307100330
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应用分布滞后非线性模型评估环境温度对北京市大兴区手足口病发病的影响及归因疾病负担

Evaluation of effect of ambient temperature on incidence of hand foot and mouth disease and attributable disease burden in Daxing, Beijing by distributed lag non-linear model

    摘要
  • 摘要:
    目的 通过计算2016—2019年北京市大兴区环境温度与手足口病发病的累积相对风险值（CRR）和归因分值（AFs），评估北京市大兴区极端气温对手足口病发病的影响及归因疾病负担。
    方法 收集2016—2019年北京市逐日气象数据和大兴区手足口病个案数据，应用分布滞后非线性模型定量分析极端气温对手足口病发病的累积相对风险值，并通过计算AFs评估环境温度对手足口病发病所造成的归因疾病负担。
    结果 极端高温（P75：24 ℃）和极端低温（P25：3 ℃）均会对手足口病的发病产生影响且存在一定的滞后效应，其中，极端高温滞后效应可持续到第6 d，极端低温滞后效应持续到第3天。 极端高温和极端低温所造成的CRR分别为1.823［95%置信区间（confidence interval, CI）：1.231～2.701］和1.327（95%CI： 1.108～1.589）；归因于高温（10～32 ℃）和低温（−5～10 ℃）的疾病负担分别为36.860%（95%CI：18.430%～50.456%）和2.873%（95%CI：1.226%～4.323%），按年龄别和性别进行分层分析，发现4岁及以上年龄组和女性人群归因于环境温度（−5～32 ℃）的疾病负担较大，分别为40.872%（95%CI：13.313%～56.493%）和45.932%（95%CI：21.086%～60.268%）。
    结论 高温和低温环境均会对北京市大兴区手足口病的发病产生影响，且高温所造成的归因疾病负担更大。 其中4岁及以上年龄组和女性人群归因于环境温度的疾病负担较大。

     

    Abstract:
    Objective To evaluate the effect of extreme ambient temperature on the incidence of hand, foot and mouth disease (HFMD) and attributable disease burden in Daxing district, Beijing by calculate the cumulative relative risk (CRR) and attributable fraction (AF) of ambient temperature and HFMD during 2016−2019.
    Methods The daily meteorological data of Beijing from 2016 to 2019 and the incidence data of HFMD in Daxing from 2016 to 2019 were collected, the distributed lag nonlinear model (DLNM) was used to quantitatively analyze the CRR of extreme ambient temperature on the incidence of HFMD; the attributable disease burden of HFMD caused by ambient temperature was assessed by calculating the AF.
    Results The impact of extreme high ambient temperature (P75, 24 ℃) and extreme low ambient temperature (P25, 3 ℃) had lag effect on the incidence of HFMD, the lag effect of extreme high ambient temperature lasted to the 6th day, and the lag effect of extreme low ambient temperature lasted to the 3rd day. The CRR caused by extreme high and low ambient temperatures were 1.823 (95%CI: 1.231–2.701) and 1.327 (95%CI: 1.108–1.589), respectively; the AF of high temperature 10–32 ℃ and low temperature −5–10 ℃ was 36.860% (95%CI: 18.430%–50.456%) and 2.873% (95%CI: 1.226%–4.323%), respectively, stratified analysis by age and gender found that the disease burden attributed to ambient temperature –5–32 ℃ was higher in age group ≥4 years and in the female population, with AFs of 40.872% (95%CI: 13.313%–56.493%) and 45.932% (95%CI: 21.086%–60.268%), respectively.
    Conclusion Both high temperature and low temperature would affect the incidence of HFMD in Daxing. The disease burden caused by high temperature was greater, and the disease burden attributed to ambient temperature was greater in age group ≥4 years and in female population.

     

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