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The association between high temperature and hospitalisations for cardiovascular diseases under climate change scenarios in Ho Chi Minh City
Author(s) -
Phung Duc Nhat,
Duong Thi Minh Tam,
Đặng Văn Chính,
Phu Le Vo,
Trần Ngọc Đăng,
Mai Tien Thanh
Publication year - 2022
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/964/1/012018
Subject(s) - poisson regression , distributed lag , heat wave , climate change , global warming , medicine , climatology , poisson distribution , public health , lag , environmental science , environmental health , statistics , mathematics , population , computer science , ecology , computer network , nursing , biology , geology
Global warming is anticipated to induce an increase in the frequency and intensity of hot days and heatwaves, which ultimately have effects on public health. The study aimed to identify the impacts of high temperature and developing climate forecasting projections focused on cardiovascular causes in Ho Chi Minh city (HCMC). The projections were built up based on updated climate scenarios in HCMC. Poisson regression model combined with a distributed lag non-linear model (DLNM) was applied. The forecasting model for cardiovascular causes was performed by using the Global Climate Model (GCM) and Yasushi Honda model. Result showed that the average daily temperature induces an increase in the risk of hospitalisation, in which temperature below 25.7°C reduced number of patients due to cardiovascular disease, meanwhile temperature above 25.7°C has increased hospitalisations. Heat waves over 31°C had the strongest impact on the > 60 years old elderly people after 5 days lag and decreased its impact consecutively to age groups of 41 to 60, 16 to 40, and less than 15 years old. The incremental prediction for the hospitalised cardiovascular disease cases based on the RCP4.5 scenario was 79,713 cases and based on the RCP8.5 scenario was 81,362 cases, respectively.

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