Weather and gastrointestinal disease in Spain: A retrospective time series regression study

Abstract

Background: A few studies in high-income countries have investigated the relationship between ambient temperature and/or precipitation and the occurrence of gastroenteritis. In most of the cases, hot temperatures and heavy precipitation events have been related to increases in infections. This is of concern as climate change predictions indicate an increase of those extreme events. Our aim was to evaluate the association between meteorological variables and daily gastroenteritis hospitalizations in Spain for the period 1997-2013.

Methods: We obtained data on all hospitalizations which occurred in Spain for the study period from administrative databases and selected those with gastroenteritis as the main diagnosis. Meteorological data was obtained from the European Climate Assessment & Dataset. Daily counts of hospitalizations were linked to meteorological variables in a retrospective ecological time series study using quasi-Poisson regression models with overdispersion and applying the Distributed Lag Non-linear Model (DLNM) framework.

Results: Both high and cold temperatures increased the risk of gastroenteritis hospitalizations (relative risk (RR) = 1.21, 95% confidence interval (CI): 1.09, 1.34; and RR = 1.07, 95% CI: 1.00, 1.15, respectively), whereas heavy precipitation was found protective for those hospitalizations (RR = 0.74, 95% CI: 0.63, 0.86). Hot temperatures increased hospitalizations for gastroenteritis classified as foodborne or idiopathic but not those in the group of Others, which were composed mainly of infections by rotavirus and were associated with cold temperatures.

Conclusions: Our findings suggest an important role of ambient temperatures, especially hot temperatures, in increasing gastroenteritis hospitalizations, while the exposure to heavy precipitation events pose opposite and unexpected effects on these infections.

Keywords: Climate change; Extreme temperatures; Gastroenteritis; Hospitalizations; Precipitation; Rainfall.