ArticleFrontiers in public health2022
Association of extreme precipitation with hospitalizations for acute myocardial infarction in Beijing, China: A time-series study.
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Impact of autumn-winter wind speed and low temperatures on acute coronary syndrome: a 5-year single-center study in Beijing.Scientific reports · 2026Article
- Machine learning prediction of acute myocardial infarction incidence using regional meteorological data.Frontiers in cardiovascular medicine · 2026Article
- Rainfall events and daily mortality across 645 global locations: two stage time series analysis.BMJ (Clinical research ed.) · 2024Article
- Short-Term Changes in Weather Conditions and the Risk of Acute Coronary Syndrome Hospitalization with and without ST-Segment Elevation: A Focus on Vulnerable Subgroups.Medicina (Kaunas, Lithuania) · 2024Article
- Risk assessment and disease burden of extreme precipitation on hospitalizations for acute aortic dissection in a subtropical coastal Chinese city.Frontiers in public health · 2023Article
- Extreme temperature exposure and urolithiasis: A time series analysis in Ganzhou, China.Frontiers in public health · 2022Article
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Authors and funding
11 authors.
Funding
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Abstract
Background: In the context of global climate changes, increasing extreme weather events have aroused great public concern. Limited evidence has focused on the association between extreme precipitation and hospitalizations for acute myocardial infarction (AMI). Our study aimed to examine the effect of extreme precipitation on AMI hospitalizations. Methods: Daily AMI hospitalizations, weather variables and air pollution data in Beijing from 2013 to 2018 were obtained. We used a time-series analysis with a distributed lag model to evaluate the association of extreme precipitation (≥95th percentile of daily precipitation) with AMI hospitalizations. Subgroup analysis was conducted to identify the vulnerable subpopulations and further assessed the attributable burden. Results: Extreme precipitation increased the risk of AMI hospitalizations with significant single-day effects from Lag 4 to Lag 11, and the maximum cumulative effects at Lag 0-14 (CRR = 1.177, 95% CI: 1.045, 1.326). Older people (≥65 years) and females were more vulnerable to extreme precipitation. The attributable fraction and numbers of extreme precipitation on AMI hospitalizations were 0.68% (95% CI: 0.20%, 1.12%) and 854 (95% CI: 244, 1,395), respectively. Conclusion: Extreme precipitation is correlated with a higher risk of AMI hospitalizations. The elderly (≥65 years) and females are more susceptible to AMI triggered by extreme precipitation.
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