Abstract
Non-optimal ambient temperatures are risk factors for myocardial infarction (MI) and urban-rural temperature differences in the context of climate change may have caused and will lead to differential association between temperature and MI. We collected daily mean temperature and daily MI deaths from 1 January 2016 to 31 December 2020 in Anhui Province, China. A distributed lag nonlinear model was performed to estimate the area-specific association of heat and cold (defined as the 2.5th and 97.5th percentile of the daily mean temperature) with MI mortality; the random-effects meta-analysis was then used to pool the effects of cold and heat. We found the risk of MI death due to cold was higher in rural areas [relative risk (RR): 1.13, 95% confidence interval (CI): 1.02-1.26, lag0) than in urban areas (RR: 0.99, 95% CI: 0.80-1.21, lag0), whereas the risk of MI death associated with heat was higher in urban areas (RR: 1.14, 95% CI: 1.03-1.27, lag0) than in rural areas (RR: 1.04, 95% CI: 0.99-1.10, lag0). Our findings may help to develop targeted protective strategies to reduce the adverse effects of cold and heat on cardiovascular disease.
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