Background: Infectious diarrhea (ID) has exerted a severe disease burden on the world. The seasonal ID patterns suggest that meteorological factors (MFs) may influence ID incidence. The aim of this study was to evaluate the effect of MFs on ID, and to provide scientific evidence to the relevant health authorities for disease control and prevention.
Methods: Data from ID cases and daily MFs (including mean temperature, diurnal temperature range, relative humidity, precipitation, atmospheric pressure, and wind velocity) in Guangzhou, Southern China from 2006 to 2017 were collected. Using a distributed lag non-linear model approach, we assessed the relationship between MFs and ID incidence.
Results: Compared with the lowest ID risk values, low mean temperature, relative humidity, and precipitation were associated with an increased risk for ID, while higher diurnal temperature range and atmospheric pressure were also associated with increased risk. Maximum atmospheric pressure and minimum relative humidity had larger cumulative effects within 21 lag days, yielding relative risks of 133.11 (95% CI: 61.29-289.09) and 18.17 (14.42-22.89), respectively. The cumulative effect within 21 lag days of minimum temperature was higher than that from maximum temperature in all sub-populations. The cumulative effects of minimum temperature for men, teenagers, and young adults (10-29 years) were higher than those for other populations.
Conclusions: MFs should be considered when developing prevention and surveillance programs for ID. Special attention should be paid to vulnerable populations, such as teenagers and young adults.
Keywords: Distributed lag non-linear model; Infectious diarrhea disease; Meteorological factors.
Copyright © 2019 Elsevier B.V. All rights reserved.