Frontiers in pediatrics · 2026
Lag effects of meteorological factors on the risk of daily outpatient visits for herpangina in Guangzhou (2014-2023).
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Yan Feifei, Xu Rong, Dong Yi, Li Yuqing, Yang Xiaohan, Li Hui, Situ Minyi, Wang Kaicai, Yang Wanting, Liu Wangkai
Аннотация
OBJECTIVE: Herpangina (HA) is a common acute infectious disease in children that may exhibit epidemiological patterns associated with meteorological factors. This study investigated the short-term and lagged associations of temperature and relative humidity with daily outpatient visits for HA in Guangzhou and explored patterns across sex and age groups.
METHODS: Daily outpatient visits for HA, daily mean temperature, relative humidity, and particulate matter with an aerodynamic diameter of 2.5 micrometers or less (PM2.5) were collected from January 1, 2014 to December 31, 2023. A quasi-Poisson generalized linear model combined with distributed lag nonlinear models was used to estimate exposure-lag-response associations. Temperature, relative humidity, and PM2.5 cross-basis terms were included simultaneously, with adjustment for long-term trends, seasonality, day of week, public holidays, and the COVID-19 period.
RESULTS: During the study period, 83,146 HA outpatient visits were recorded, 56.4% of which were among male patients. Daily outpatient visits showed clear seasonal variation, with larger peaks generally occurring during summer and autumn. Compared with the median temperature (24.38 °C), the cumulative RR was 0.482 (95% CI: 0.353-0.657) at the 2.5th percentile (10.77 °C) and 1.966 (95% CI: 1.714-2.254) at the 97.5th percentile (30.63 °C) over lags 0-14 days. Compared with the median relative humidity (79.15%), the cumulative RR was 0.878 (95% CI: 0.795-0.970) at the 10th percentile (62.21%) and 1.477 (95% CI: 1.297-1.682) at the 97.5th percentile (93.21%) over lags 0-20 days. High-temperature and high-humidity associations were observed across sex and age strata. The lower-humidity association was less robust in sensitivity analyses.
CONCLUSION: High temperature and high relative humidity were associated with increased daily outpatient visits for HA in Guangzhou, whereas low temperature and lower relative humidity were associated with fewer visits in the main model. The lower-humidity estimate was less stable across alternative temporal-control settings. These findings support incorporating lagged meteorological information into HA surveillance and preparedness.
METHODS: Daily outpatient visits for HA, daily mean temperature, relative humidity, and particulate matter with an aerodynamic diameter of 2.5 micrometers or less (PM2.5) were collected from January 1, 2014 to December 31, 2023. A quasi-Poisson generalized linear model combined with distributed lag nonlinear models was used to estimate exposure-lag-response associations. Temperature, relative humidity, and PM2.5 cross-basis terms were included simultaneously, with adjustment for long-term trends, seasonality, day of week, public holidays, and the COVID-19 period.
RESULTS: During the study period, 83,146 HA outpatient visits were recorded, 56.4% of which were among male patients. Daily outpatient visits showed clear seasonal variation, with larger peaks generally occurring during summer and autumn. Compared with the median temperature (24.38 °C), the cumulative RR was 0.482 (95% CI: 0.353-0.657) at the 2.5th percentile (10.77 °C) and 1.966 (95% CI: 1.714-2.254) at the 97.5th percentile (30.63 °C) over lags 0-14 days. Compared with the median relative humidity (79.15%), the cumulative RR was 0.878 (95% CI: 0.795-0.970) at the 10th percentile (62.21%) and 1.477 (95% CI: 1.297-1.682) at the 97.5th percentile (93.21%) over lags 0-20 days. High-temperature and high-humidity associations were observed across sex and age strata. The lower-humidity association was less robust in sensitivity analyses.
CONCLUSION: High temperature and high relative humidity were associated with increased daily outpatient visits for HA in Guangzhou, whereas low temperature and lower relative humidity were associated with fewer visits in the main model. The lower-humidity estimate was less stable across alternative temporal-control settings. These findings support incorporating lagged meteorological information into HA surveillance and preparedness.