The Association between Meteorological Factors and the Prevalence of Acute-on-chronic Liver Failure: A Population-based Study, 2007–2016

Background and Aims: The aim of this study was to investigate the effect(s) of meteorological factors on the prevalence of acute-on-chronic liver failure (ACLF) based on 10-years’ worth of population data. Methods: We retrospectively collected ACLF case data from January 2007 to December 2016 from three major hospitals in Fuzhou City, China. Climatic data, including rainfall, mean temperature, differences in temperature (delta temperature) and mean humidity for each month were downloaded from the China Climatic Data Service Center. Following data collection, Poisson regression analysis was used to estimate the effect(s) of climatic factors on the risk of the prevalence of ACLF. Results: The population consisted of a total of 3510 cases, with a mean age of 44.7 ± 14.8 years-old and with 79.8% being male. Upon analyzing the population data, we found a growing trend and seasonal pattern of monthly counts of ACLF-related hospitalization throughout the past decade. Specifically, the primary peak of ACLF prevalence was in January and the secondary peak was in July. Poisson regression showed mean temperature (risk ratio = 0.991, 95%CI = 0.986–0.996) and mean humidity (risk ratio = 1.011, 95%CI = 1.006–1.017) to be independently correlated with the monthly cases of ACLF. The results suggest that every unit increase of mean temperature (1°C) and mean humidity (1%) are associated with 0.991- and 1.011-fold changes of ACLF cases, respectively. Rainfall and delta temperature did not appear to affect the prevalence of this disease. Conclusions: The hospitalization for ACLF peaks in January and July. Low temperature and high humidity appear to function as factors contributing to this seasonal pattern.