Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China.
Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, 81 Meishan Road, Hefei, Anhui, China.
Environ Sci Pollut Res Int. 2022 Feb;29(10):13797-13804. doi: 10.1007/s11356-021-16580-w. Epub 2021 Oct 1.
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.
先前的研究发现，非最佳温度会影响痛风的发展，但结果并不一致。本研究旨在探讨高温和高温变化对中国安庆市痛风住院的影响。我们收集了 2016 年 1 月 1 日至 2020 年 12 月 31 日期间安庆市每日的空气污染物、气象因素和痛风住院数据。我们使用泊松广义线性回归模型和分布式滞后非线性模型（DLNM）来探讨高温、日较差（DTR）和相邻日温度变化（TCN）与痛风住院的关系。按照性别（男性、女性）和年龄（<65 岁、≥65 岁）进行分层分析。还量化了归因于高温、高 DTR 和高 TCN 的痛风住院人数。在研究期间，共报告了 8675 例痛风住院患者。我们观察到，暴露于高温与痛风住院风险增加有关（滞后 0 时，RR：1.081，95%置信区间（CI）：1.011，1.155）。暴露于高 DTR 也与痛风住院风险增加有关（滞后 9 时，RR：1.017，95% CI：1.001，1.035）。相邻两天内温度大幅下降与痛风住院风险增加有关（滞后 0-2 天，RR：1.234，95% CI：1.017，1.493）。分层分析结果表明，高龄和男性对高水平 DTR 暴露比其同龄人更为敏感。近 15%的痛风住院可归因于高温（归因分数：14.93%，95% CI：5.99%，22.11%）。本研究表明，高温和高温变化可能引发痛风住院，提示痛风患者在面临非最佳温度时需要采取积极行动。
