Association between Rainfall and Stroke Admissions: Based on Distributional Lag Nonlinear Modeling

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