Daily mean temperature and HFMD: risk assessment and attributable fraction identification in Ningbo China

JOURNAL OF EXPOSURE SCIENCE AND ENVIRONMENTAL EPIDEMIOLOGY(2021)

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摘要
Background Hand, foot, and mouth disease (HFMD) remains a significant public health issue, especially in developing countries. Many studies have reported the association between environmental temperature and HFMD. However, the results are highly heterogeneous in different regions. In addition, there are few studies on the attributable risk of HFMD due to temperature. Objectives The study aimed to assess the association between temperature and HFMD incidence and to evaluate the attributable burden of HFMD due to temperature in Ningbo China. Methods The research used daily incidence of HFMD from 2014 to 2017 and distributed lag non-linear model (DLNM) to investigate the effects of daily mean temperature (Tmean) on HFMD incidence from lag 0 to 30 days, after controlling potential confounders. The lag effects and cumulative relative risk (CRR) were analyzed. Attributable fraction (AF) of HFMD incidence due to temperature was calculated. Stratified analysis by gender and age were also conducted. Results The significant associations between Tmean and HFMD incidence were observed in Ningbo for lag 0–30. Two peaks were observed at both low (5–11 °C) and high (16–29 °C) temperature scales. For low temperature scale, the highest CRR was 2.22 (95% CI: 1.61–3.07) at 7 °C on lag 0–30. For high temperature scale, the highest CRR was 3.54 (95% CI: 2.58–4.88) at 24 °C on lag 0–30. The AF due to low and high temperature was 5.23% (95% CI: 3.10–7.14%) and 39.55% (95% CI: 30.91–45.51%), respectively. There was no significant difference between gender- and age-specific AFs, even though the school-age and female children had slightly higher AF values. Conclusions The result indicates that both high and low temperatures were associated with daily incidence of HFMD, and more burdens were caused by heat in Ningbo.
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关键词
Hand, foot, and mouth disease (HFMD), Meteorological factors, Temperature, Distributed lag non-linear model (DLNM), Ningbo
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