Guo Mengen, Qi Jinlei, He Guanhao, Liu Jiangmei, Hu Jianxiong, Yin Peng, Liu Tao, Lin Ziqiang, Jing Fengrui, You Jinling, Ma Wenjun, Liu Fanna, Zhou Maigeng
Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, 510632, China.
The National Center for Chronic and Noncommunicable Disease Control and Prevention, Beijing, 100050, China.
Environ Res. 2025 Aug 15;279(Pt 1):121696. doi: 10.1016/j.envres.2025.121696. Epub 2025 May 2.
Many studies have investigated the association of temperature with non-accidental mortality, but there is limited evidence on the temperature-related mortality burden of kidney diseases. This study aims to assess the mortality impact of temperatures on cause-specific kidney in China.
We conducted a time-stratified case-crossover study using mortality data from kidney diseases across 2790 counties/districts in China from 2003 to 2022. We used conditional logistic regression in conjunction with distribution lag nonlinear model (DLNM) to examine the association between temperature and kidney disease mortality. Furthermore, we projected the mortality burden of kidney diseases attributed to temperature under diverse climate change scenarios in China in the future.
The study included 914,177 kidney disease fatalities, revealing an inversely J-shaped association between temperature and kidney disease mortality across various subgroups. Both extreme cold (Odds ratios [OR] = 1.34, 95 % CI: 1.27-1.41) and extreme heat (1.06, 95 % CI: 1.02-1.10) were linked to increased kidney mortality, with a more pronounced effect in females [1.08(95 % CI: 1.02-1.14) for extreme heat, 1.34(95 % CI: 1.24-1.46) for extreme cold], the elderly [1.07(95 % CI: 1.03-1.12) for extreme heat, 1.35(95 % CI: 1.26-1.45) for extreme cold ] and those with acute kidney disease [1.10(95 % CI: 0.96-1.26)] for extreme heat, 1.43(95 % CI: 1.19-1.73) for extreme cold]. Nationwide, temperatures accounted for 9.28 % (95 % CI: 9.17 %-9.40 %) of kidney disease mortality, with 9.15 % (95 % CI: 9.03 %-9.26 %) for cold and 0.13 % (95 % CI: 0.12 %-0.14 %) for heat, and temperature-related AF of acute kidney disease was the greatest (attributable fraction [AF] = 11.00 %,95 %CI:10.71 %-11.31 %). Projections suggest that temperature-related AFs would rise from 11.39 % (95 % CI: 8.19 %-13.89 %) in the 2050s to 15.26 % (95 % CI: 10.30 %-18.68 %) in the 2090s under SSP5-8.5, with heat-related AFs increasing from 2.82 % (95 % CI: 1.8 %-4.20 %) to 7.12 % (95 % CI: 4.23 %-10.09 %) and cold-related AFs decreasing from 8.57 % (95 % CI: 5.71 %-9.89 %) to 8.14 % (95 % CI: 5.22 %-8.81 %).
Our study indicates that temperatures are significantly associated with the mortality risk and burden of kidney diseases in China, and temperature-related mortality is expected to increase in the future, particularly from heat. Our findings indicate that kidney diseases are vulnerable to ambient temperature in the context of climate change.
许多研究调查了温度与非意外死亡率之间的关联,但关于温度与肾脏疾病死亡率负担的证据有限。本研究旨在评估温度对中国特定病因肾脏疾病死亡率的影响。
我们利用2003年至2022年中国2790个县/区的肾脏疾病死亡率数据进行了一项时间分层病例交叉研究。我们使用条件逻辑回归结合分布滞后非线性模型(DLNM)来检验温度与肾脏疾病死亡率之间的关联。此外,我们预测了未来中国在不同气候变化情景下温度导致的肾脏疾病死亡率负担。
该研究纳入了914,177例肾脏疾病死亡病例,揭示了温度与各亚组肾脏疾病死亡率之间呈倒J形关联。极端寒冷(优势比[OR]=1.34,95%置信区间:1.27-1.41)和极端炎热(1.06,95%置信区间:1.02-1.10)均与肾脏疾病死亡率增加有关,在女性中影响更为明显[极端炎热时为1.08(95%置信区间:1.02-1.14),极端寒冷时为1.34(95%置信区间:1.24-1.46)],老年人[极端炎热时为1.07(95%置信区间:1.03-1.12),极端寒冷时为1.35(95%置信区间:1.26-1.45)]以及急性肾脏疾病患者[极端炎热时为1.10(95%置信区间:0.96-1.26),极端寒冷时为1.43(95%置信区间:1.19-1.73)]也是如此。在全国范围内,温度占肾脏疾病死亡率的9.28%(95%置信区间:9.17%-9.40%),其中寒冷占9.15%(95%置信区间:9.03%-9.26%),炎热占0.13%(95%置信区间:0.12%-0.14%),且温度相关的急性肾脏疾病归因分数最高(归因分数[AF]=11.00%,95%置信区间:10.71%-11.31%)。预测表明,在共享社会经济路径5-8.5情景下,温度相关的归因分数将从21世纪50年代的11.39%(95%置信区间:8.19%-13.89%)上升到21世纪90年代的15.26%(95%置信区间:10.30%-18.68%),其中炎热相关的归因分数从2.82%(95%置信区间:1.8%-4.20%)增加到7.12%(95%置信区间:4.23%-10.09%),寒冷相关的归因分数从8.57%(95%置信区间:5.71%-9.89%)下降到8.14%(95%置信区间:5.22%-8.81%)。
我们的研究表明,温度与中国肾脏疾病的死亡风险和负担显著相关,且未来与温度相关的死亡率预计会增加,尤其是炎热导致的死亡率。我们的研究结果表明,在气候变化背景下,肾脏疾病易受环境温度影响。