梁敏仪, 张敏怡, 范顺昌, 吴若君, 陈宏标, 陈清. 2016—2019年深圳市龙华区气温与14岁及以下人群流感发病的关联研究[J]. 环境与职业医学, 2023, 40(12): 1431-1436. DOI: 10.11836/JEOM23130
引用本文: 梁敏仪, 张敏怡, 范顺昌, 吴若君, 陈宏标, 陈清. 2016—2019年深圳市龙华区气温与14岁及以下人群流感发病的关联研究[J]. 环境与职业医学, 2023, 40(12): 1431-1436. DOI: 10.11836/JEOM23130
LIANG Minyi, ZHANG Minyi, FAN Shunchang, WU Ruojun, CHEN Hongbiao, CHEN Qing. Association between temperature and influenza in children 14 years of age and below in Longhua District of Shenzhen, 2016—2019[J]. Journal of Environmental and Occupational Medicine, 2023, 40(12): 1431-1436. DOI: 10.11836/JEOM23130
Citation: LIANG Minyi, ZHANG Minyi, FAN Shunchang, WU Ruojun, CHEN Hongbiao, CHEN Qing. Association between temperature and influenza in children 14 years of age and below in Longhua District of Shenzhen, 2016—2019[J]. Journal of Environmental and Occupational Medicine, 2023, 40(12): 1431-1436. DOI: 10.11836/JEOM23130

2016—2019年深圳市龙华区气温与14岁及以下人群流感发病的关联研究

Association between temperature and influenza in children 14 years of age and below in Longhua District of Shenzhen, 2016—2019

  • 摘要: 背景

    流行性感冒(简称流感)是全球关注的重要公共卫生问题。气象因素是影响流感发病的重要因素之一,探讨气温与流感的关联性可对地区流感防控工作提供科学依据。

    目的

    探讨深圳市龙华区气温与0~14岁人群流感发病的关联性及归因风险。

    方法

    收集2016年1月—2019年12月深圳市龙华区来源于气象局的气象观测资料,以及同时期来源于中国疾病预防控制信息系统0~14岁人群流感临床诊断与实验室确诊病例资料,共计19657例。采用Spearman等级相关分析探讨流感日发病数与各气象因素之间的相关性,利用分布滞后非线性模型分析气温对不同性别与年龄分组人群流感发病的关联及滞后效应,并在此模型基础上探讨气温对流感发病带来的归因风险。

    结果

    该地区2016年1月—2019年12月流感日均发病13.45例,男女性别比为1.36∶1,<5岁及5~14岁组病例占比分别为50.05%、49.95%。Spearman相关分析得到各气象因素中以日均气温对流感日发病人数影响最为显著,呈现负相关关系(r=−0.1541)。日均气温与流感日发病在不同的滞后天数呈非线性暴露效应关系,累积滞后14 d日均气温对流感带来的发病风险存在两个高峰,在11 ℃时达到最大(RR=8.15,95%CI:5.73~11.60)。此外,日均气温对女性、5~14岁人群带来的归因风险相比男性和<5岁年龄组更大。低温与高温对流感均有影响,但归因于低温的效应(44.58%)远大于高温效应(4.92%)。低温对不同性别和年龄组人群均带来风险效应,其中对5~14岁人群影响最大,当滞后14 d累积风险最大(RR=12.80,95%CI:8.29~18.93)。高温表现为在5~14岁人群中出现滞后效应,滞后14 d累积风险最大。

    结论

    气温影响深圳市龙华区14岁及以下人群的流感发病;尤其对女性和5~14岁人群的影响更大,低温带来发病风险比高温大。

     

    Abstract: Background

    Influenza is an important public health issue of global concern. Meteorological factors are one of the important factors affecting the incidence of influenza. Exploring the correlation between temperature and influenza can provide a scientific basis for the prevention and control of influenza in specific regions.

    Objective

    To explore the association and attributable risk between temperature and influenza incidence in residents aged 0-14 years in Longhua District of Shenzhen.

    Methods

    Meteorological observation data were collected from the Meteorological Bureau of Longhua District, Shenzhen City from January 2016 to December 2019. A total of 19657 influenza cases among children of 0-14 years old were identified from the China Information System for Disease Control and Prevention during the same period. Spearman rank correlation was used to analyze the correlation between daily incidence of influenza and meteorological factors. Distributed lag non-linear model was used to quantify the association and lag effect of temperature on influenza incidence in different gender and age groups, and to estimate the attributable risk of temperature on influenza incidence.

    Results

    From January 2016 to December 2019, the average daily incidence of influenza in this area was 13.45 cases, and the male to female ratio was 1.36∶1. The proportion of cases in <5 years old and 5-14 years old groups was 50.05% and 49.95%, respectively. The results of Spearman correlation analysis showed that among all meteorological factors, the daily mean temperature had the most significant impact on the daily incidence of influenza, showing a negative correlation r=−0.1541. There was a non-linear exposure-effect relationship between daily mean temperature and influenza incidence in different lag days. There were two peaks in the risk of influenza incidence caused by daily mean temperature at a cumulative lag of 14 d, and the maximum risk was at 11 ℃ (RR=8.15, 95%CI: 5.73, 11.60). In addition, the attributable risks of daily mean temperature on females and residents aged 5-14 years were greater than those on males and other age groups respectively. Both low and high temperatures had effects on influenza, but the proportion of low temperature effect (44.58%) was much greater than that of high temperature effect (4.92%). Low temperature had risk effects on residents of both genders and all age groups, with the greatest effect on residents aged 5-14 years old, and the cumulative risk was the highest at lag 14 d (RR=12.80, 95%CI: 8.29, 18.93). The lag effect of high temperature appeared in residents aged 5-14 years, with the highest cumulative risk at lag 14 d.

    Conclusion

    Temperature significantly influences influenza incidence among children 14 years and under in Longhua District of Shenzhen. In particular, it has a greater impact on girls and people aged 5-14 years old, and low temperature poses a higher risk than high temperature.

     

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