Department of Neurology, Dongtai People's Hospital, Yancheng, 224200, Jiangsu, China.
Department of Respiratory Medicine, The First People's Hospital of Yancheng, Affiliated Hospital of Nanjing University Medical School, Yancheng, 224006, Jiangsu Province, China.
BMC Public Health. 2024 Jul 15;24(1):1879. doi: 10.1186/s12889-024-19423-8.
Acute ischemic stroke (AIS) is a major global public health issue. There is limited research on the relationship between ambient temperature and AIS hospital admissions, and the results are controversial. Our objective is to assess the short-term impact of ambient temperature on the risk of AIS hospital admissions in Yancheng, China.
We collected data on daily AIS hospital admissions, meteorological factors, and air quality in Yancheng from 2014 to 2019. We used Poisson regression to fit generalized linear models and distributed lag non-linear models to explore the association between ambient temperature and AIS hospital admissions. The effects of these associations were evaluated by stratified analysis by sex and age.
From 2014 to 2019, we identified a total of 13,391 AIS hospital admissions. We observed that the influence of extreme cold and heat on admissions for AIS manifests immediately on the day of exposure and continues for a duration of 3-5 days. Compared to the optimal temperature (24.4 °C), the cumulative relative risk under extreme cold temperature (-1.3 °C) conditions with a lag of 0-5 days was 1.88 (95%CI: 1.28, 2.78), and under extreme heat temperature (30.5 °C) conditions with a lag of 0-5 days was 1.48 (95%CI: 1.26, 1.73).
There is a non-linear association between ambient temperature and AIS hospital admission risk in Yancheng, China. Women and older patients are more vulnerable to non-optimal temperatures. Our findings may reveal the potential impact of climate change on the risk of AIS hospital admissions.
急性缺血性脑卒中(AIS)是一个重大的全球公共卫生问题。有关环境温度与 AIS 住院人数之间关系的研究有限,且结果存在争议。我们的目的是评估环境温度对中国盐城 AIS 住院风险的短期影响。
我们收集了 2014 年至 2019 年盐城每日 AIS 住院人数、气象因素和空气质量数据。我们使用泊松回归拟合广义线性模型和分布滞后非线性模型,以探讨环境温度与 AIS 住院人数之间的关系。通过按性别和年龄分层分析来评估这些关联的影响。
2014 年至 2019 年,我们共确定了 13391 例 AIS 住院病例。我们观察到,极冷和极热天气对 AIS 住院人数的影响在暴露当天立即显现,并持续 3-5 天。与最佳温度(24.4°C)相比,在滞后 0-5 天的极冷温度(-1.3°C)条件下,累积相对风险为 1.88(95%CI:1.28,2.78),在滞后 0-5 天的极热温度(30.5°C)条件下,累积相对风险为 1.48(95%CI:1.26,1.73)。
中国盐城的环境温度与 AIS 住院风险之间存在非线性关联。女性和老年患者对非最佳温度更为敏感。我们的研究结果可能揭示了气候变化对 AIS 住院风险的潜在影响。