A Time series analysis of the impact of daily temperature and daily relative humidity on the number of foodborne diarrhea visits in Beijing,China
Objective To explore the health effects of daily temperature and daily relative humidity on the incidence of foodborne diarrhea in Beijing.Methods Based on daily data on visit number of foodborne diarrhea and meteorological factors in Beijing from 2018 to 2023,a distributed lag nonlinear model was used to establish the expose-response relationship between daily temperature,daily relative humidity and the visit number of foodborne diarrhea,while controlling for the time trend,day of the week effect,holiday effect,and the confounding effects of other meteorological factors.The lagged effects and cumulative lagged effects of daily temperature and daily relative humidity on the incidence of foodborne diarrhea were analyzed.Results The relationships between daily tempera-ture,daily relative humidity and the visit number of foodborne diarrhea were non-linear.The daily temperature and daily relative hu-midity corresponding to the lowest risk of foodborne diarrhea were-5.7 ℃ and 38.4％,respectively.The health effects were mainly due to high temperature and high relative humidity.The lagged effect of high temperature(P95:29.2 ℃)on the risk of foodborne di-arrhea reached its maximum on the day of exposure,with a relative risk of 3.45(95％CI:1.12-10.67),while no statistically signifi-cant lag effect of high relative humidity(P95:83.5％)was observed.Cumulative lagged effects of high temperature and high relative humidity reached the maximum at 0-5 d,and cumulative relative risk were 10.10(95％CI:2.23-45.71)and 1.59(95％CI:1.06～2.40),respectively.Conclusion Both of high temperature and high relative humidity can increase the risk of foodborne diarrhea visits in Beijing,with the presence of lag effects.
daily temperaturedaily relative humidityfoodborne diarrheadistributed lag nonlinear model
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