Stroke is a chronic condition that seriously impairs human health. The correlation between rainfall and onset of stroke remains unclear.

To analyze the correlation between rainfall and stroke admissions in Nanchang City, and to provide scientific references for developing a comprehensive prevention and treatment strategy for stroke.

Stroke admission data from Nanchang City (2015-2019) from the digital-related group (DRG) system of the Jiangxi Provincial Health Commission Information Center were collected. In addition, atmospheric pollutant data from the national urban air quality real-time release platform and meteorological data from the Nanchang meteorological base station were collected. Basic characteristics of stroke admission patients, air pollutants, and meteorological factors were analyzed. Spearman rank correlation analysis was performed to identify the correlation of case number of stroke admissions with air pollutants and atmospheric factors. Distributional lag nonlinear model was used to explore the linkage between rainfall and stroke admissions. Stratified analysis was conducted based on gender and age (<65 years old and ≥65 years old), and lag represented the lagging days.

From 2015 to 2019, there were 79 523 hospitalized patients with stroke in Nanchang City, of which 49 072 (61.71%) were males and 48 092 (60.48%) were ≥65 years old, accounting for a large proportion. The number of stroke admissions in winter (December to February) and spring (March to May) were 20 065 (25.23%) and 20 358 (25.60%), respectively. There was a nonlinear relationship between rainfall and stroke admission, and there was a certain lag effect. The RR values of lag1 and lag2 for the effect of rainfall on stroke admission was both 1.009, and 95%CI were 1.000-1.019 and 1.001-1.016, respectively. Stratified analysis showed that the main effect of higher rainfall on the number of male stroke admissions was lag6, RR value was 1.003; the main effect on the number of hospital admissions for female stroke was lag1 and lag2, with RR values of 1.018 (95%CI=1.004-1.031) and 1.020 (95%CI=1.009-1.031), respectively. The main effects on the number of hospitalizations for ischemic stroke under 65 years of age were lag1 (RR=1.016, 95%CI=1.003-1.030), and lag2 (RR=1.018, 95%CI=1.007-1.029) .

Short-term exposure to higher rainfall can increase the risk of stroke hospitalization, and women and people under 65 years of age are more sensitive to rainfall exposure, and protection should be strengthened for this group of people.

脑卒中是严重危害人类健康的主要慢性病，降雨量与脑卒中发病的关系尚未明确。

分析南昌市降雨量与脑卒中入院的关联性，为制定脑卒中综合防治策略和措施提供科学依据。

收集江西省卫生健康委员会信息中心DRGs管理系统中南昌市2015—2019年脑卒中入院数据及全国城市空气质量实时发布平台大气污染物和南昌市气象基站数据，分析脑卒中入院患者、大气污染物及气象因素的基本特征。采用Spearman秩相关分析探究脑卒中入院例数与大气污染物和气象因素的相关性，利用分布滞后非线性模型分析降雨量与脑卒中入院的关系，并按照性别、年龄（<65岁和≥65岁）进行分层分析，lag代表滞后天数。

2015—2019年南昌市脑卒中入院患者79 523例，其中男性（49 072例，61.71%）、年龄≥65岁（48 092例，60.48%）的患者所占比例较大，冬（12月~次年2月）、春（3~5月）季脑卒中入院例数分别为20 065例（25.23%）、20 358例（25.60%）。降雨量与脑卒中入院呈非线性关系，并存在一定的滞后效应。降雨量对脑卒中入院的效应在lag1、lag2的RR值均为1.009，95%CI分别为1.000~1.019、1.001~1.016。分层分析显示：较高降雨量对男性脑卒中入院例数的主要效应为lag6，RR值为1.003；对女性脑卒中入院例数的主要效应为lag1和lag2，RR值分别为1.018（95%CI=1.004~1.031）、1.020（95%CI=1.009~1.031）；对65岁以下缺血性脑卒中入院例数的主要效应为lag1（RR=1.016，95%CI=1.003~1.030）、lag2（RR=1.018，95%CI=1.007~1.029）。

短期暴露于较高降雨量可增加脑卒中入院风险，女性、65岁以下人群对降雨暴露更为敏感，应加强对该人群的防护。