Effect of ambient temperature and other environmental factors on stroke emergency department visits in Beijing

A distributed lag non-linear model

Dados Bibliográficos

ID22074488
AutoresJinhua Zhao (0000-0002-1929-7583, Tianjin Medical University), Yongming Zhang (0000-0002-7312-2397, China-Japan Friendship Hospital), Ying Ni (0000-0003-4737-386X, Tianjin Medical University), Junyu He (0000-0003-1873-3125, Zhejiang Ocean University), Jianping Wang (0000-0002-1890-3238, Tianjin Medical University), Xuan Li (0000-0003-0366-872X, Tianjin Medical University), Yuming Guo (0000-0002-2351-4456, Monash University), Changping Li (0000-0001-7508-1907, Tianjin Medical University), Wenyi Zhang (0009-0003-8183-8189, autor correspondente), Zhuang Cui (0000-0001-6495-766X, Tianjin Medical University, autor correspondente)
Ano2022
Volume10
Páginas1034534-1034534
Data de publicação2022-11-16
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoFrontiers in Public Health (JOURNAL)
Identificadores do periódicoISSN: 2296-2565 • E-ISSN: 2296-2565
EditoraFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2022.1034534
PMID36466462
OpenAlexW4309309771
IdiomaEN
Citações recebidas2
Referências citadas53

Background: Most studies have focused on the relationship between ambient temperature and stroke mortality, but studies on the relationship between ambient temperature and stroke occurrence are still limited and inconsistent. Objective: This study aimed to analyze the effect of ambient temperature and other environmental factors on emergency stroke visits in Beijing. Methods: Our study utilized stroke visit data from the Beijing Red Cross Emergency Medical Center during 2017-2018, and applied a generalized additive model (GAM) as well as a distributed lag non-linear model (DLNM), respectively, regarding the direct, lagged, and cumulative effects of ambient temperature alone and with correction for other environmental factors on stroke occurrence. Results: With a total of 26,984 emergency stroke patients in 2017-2018, both cold and hot effects were observed and weakened after correction for other environmental factors. Compared to the reference temperature, in the multi-factor model, extreme cold (-10°C) reached a maximum relative risk (RR) of 1.20 [95% Confidence Interval (CI): 1.09, 1.32] at lag 14 days, and extreme hot (30°C) had a maximum RR of 1.07 (95% CI: 1.04, 1.11) at lag 6 days. The cumulative effect of extreme cold reached a maximum of 2.02 (95% CI: 1.11, 3.67) at lag 0-14 days, whereas the cumulative effect of extreme hot temperature is greatest at lag 0-10 days, but no statistically significant effect was found. In addition, ischemic stroke patients, the elderly, and males were more susceptible to the effects of cold temperature. Conclusions: There is a non-linear relationship between ambient temperature and stroke occurrence, with cold temperature having a greater and longer-lasting impact than hot temperature

Beijing · Biology · Confidence interval · Distributed lag · Emergency department · Geography · Lag · Lag time · Relative risk · Statistics · Climate Change and Health Impacts · Demography · Mathematics · Medicine · Thermal Regulation in Medicine · Thermoregulation and physiological responses · Emergency Medicine · Internal Medicine