Association between short-term exposure to meteorological factors on hospital admissions for hemorrhagic stroke: an individual-level, case-crossover study in Ganzhou, China.

Kailun PAN; Fen LIN; Kai HUANG; Songbing ZENG; Mingwei GUO; Jie CAO; Haifa DONG; Jianing WEI; Qiujiang XI

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Association between short-term exposure to meteorological factors on hospital admissions for hemorrhagic stroke: an individual-level, case-crossover study in Ganzhou, China.

Author: Kailun PAN ¹ ; Fen LIN ² ; Kai HUANG ³ ; Songbing ZENG ³ ; Mingwei GUO ¹ ; Jie CAO ¹ ; Haifa DONG ¹ ; Jianing WEI ³ ; Qiujiang XI ¹
Author Information

1. Department of Neurology, First Affiliated Hospital of Gannan Medical University.
2. School of Public Health and Health Management, Gannan Medical University.
3. School of the Frist Clinical Medicine, Gannan Medical University.
Publication Type:Journal Article
Keywords: Airborne particulate matter; Case-crossover design; Distributional lag nonlinear models; Hemorrhagic stroke; Meteorological factors
MeSH: China/epidemiology*; Humans; Female; Male; Aged; Middle Aged; Cross-Over Studies; Hospitalization/statistics & numerical data*; Adult; Hemorrhagic Stroke/etiology*; Meteorological Concepts; Weather; Particulate Matter/analysis*; Air Pollution/adverse effects*; Environmental Exposure/adverse effects*; Aged, 80 and over; Young Adult
From:Environmental Health and Preventive Medicine 2025;30():12-12
CountryJapan
Language:English
Abstract: BACKGROUND:Hemorrhagic stroke (HS) is associated with significant disability and mortality. However, the relationship between meteorological factors and hemorrhagic stroke, as well as the potential moderating role of these factors, remains unclear.
METHODS:Daily data on HS, air pollution, and meteorological conditions were collected from January 2015 to December 2021 in Ganzhou to analyze the relationship between meteorological factors and HS admissions. This analysis employed a time-stratified case-crossover design in conjunction with a distributional lag nonlinear model. Additionally, a bivariate response surface modelling was utilized to further investigate the interaction between meteorological factors and particulate matter. The study also stratified the analyses by gender and age. To investigate the potential impact of extreme weather conditions on HS, this study defined the 97.5th percentile as representing extremely high weather conditions, while the 2.5th percentile was classified as extremely low.
RESULTS:In single-day lags, the risk of admissions for HS was significantly associated with extremely low temperature (lag 1-2 and lag 13-14), extremely low humidity (lag 1 and lag 9-12), and extremely high precipitation (lag 2-7). Females exhibited greater susceptibility to extremely low temperature than males within the single-day lag pattern in the subcomponent layer, with a maximum relative risk (RR) that was 7% higher. In the cumulative lag analysis, the risk of HS admissions was significantly associated with extremely high temperature (lag 0-8∼lag 0-14), extremely low humidity (lag 0-2∼lag 0-14), and extremely high precipitation (lag 0-4∼lag 0-14). Within the cumulative lag day structure of the subcomponent layer, both extremely low and extremely high temperature had a more pronounced effect on females and aged ≥65 years. The risk of HS admissions was positively associated with extremely high barometric pressure in the female subgroups (lag 0-1 and lag 0-2). The highest number of HS admissions occurred when high PM_2.5 concentrations coexisted with low precipitation.
CONCLUSIONS:Meteorological factors were significantly associated with the risk of hospital admissions for HS. Individuals who were female and aged ≥65 years were found to be more susceptible to these meteorological influences. Additionally, an interaction was observed between airborne particulate matter and meteorological factors. These findings contributed new evidence to the association between meteorological factors and HS.