Abstract
Previous studies have found that non-optimal temperature influences the development of gout, but the results have been inconsistent. The present study aimed to explore the effects of high temperature and high temperature variation on hospitalizations for gout in Anqing, China. We collected daily data on air pollutants, meteorological factors, and hospitalizations for gout between 1January 2016 and 31 December 2020 in Anqing City, China. We used Poisson generalized linear regression model and a distributed lag non-linear model (DLNM) to explore the relationship of high temperature, diurnal temperature range (DTR), and temperature change between neighboring days (TCN) with hospitalizations for gout. Stratified analysis by gender (male, female) and age (<65 years, ≥65 years) was conducted. Hospitalizations for gout attributed to high temperature, high DTR, and high TCN were also quantified. A total of 8675 hospitalized patients with gout were reported during the study period. We observed that exposure to high temperature was linked with an increased risk of hospitalizations for gout (lag 0, RR: 1.081, 95% confidence interval (CI): 1.011, 1.155). Exposure to high DTR was also associated with increased risk of hospitalizations for gout (lag9, RR: 1.017, 95% CI: 1.001,1.035). A large drop in temperature between neighboring days was associated an increased risk of hospitalizations for gout (lag 0-2 days, RR: 1.234, 95% CI: 1.017, 1.493). Stratified analysis results revealed that older adults and men were more sensitive to high-level DTR exposure than their counterparts. Nearly 15% of hospitalizations for gout could be attributable to high temperature (attributable fraction: 14.93%, 95% CI: 5.99%, 22.11%). This study suggests that high temperature and high temperature variation may trigger hospitalizations for gout, indicating that patients with gout need to take proactive actions in the face of days with non-optimal temperature.
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