Association between extreme temperature and acute myocardial infarction hospital admissions in Beijing, China: 2013-2016

PLoS One. 2018 Oct 17;13(10):e0204706. doi: 10.1371/journal.pone.0204706. eCollection 2018.

Abstract

Over the past few decades, a growing body of epidemiological studies found the effects of temperature on cardiovascular disease, including the risk for acute myocardial infarction (AMI). Our study aimed to investigate whether there is an association between extremely temperature and acute myocardial infarction hospital admission in Beijng, China. We obtained 81029 AMI cases and daily temperature data from January 1, 2013 to December 31, 2016. We employed a time series design and modeled distributed lag nonlinear model (DLNM) to analyze effects of temperature on daily AMI cases. Compared with the 10th percentile temperature measured by daily mean temperature (Tmean), daily minimum temperature (Tmin) and daily minimum apparent temperature (ATmin), the cumulative relative risks (CRR) at 1st percentile of Tmean, Tmin and ATmin for AMI hospitalization were 1.15(95% CI: 1.02, 1.30), 1.24(95% CI: 1.11, 1.38) and 1.41(95% CI: 1.18, 1.68), respectively. Moderate low temperature (10th vs 25th) also had adverse impact on AMI events. The susceptive groups were males and people 65 years and older. No associations were found between high temperature and AMI risk. The main limitation of the study is temperature exposure was not individualized. These findings on cold-associated AMI hospitalization helps characterize the public health burden of cold and target interventions to reduce temperature induced AMI occurrence.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Beijing / epidemiology
  • Cold Temperature / adverse effects*
  • Female
  • Hospitalization / statistics & numerical data
  • Hot Temperature / adverse effects*
  • Humans
  • Male
  • Middle Aged
  • Myocardial Infarction / epidemiology*
  • Myocardial Infarction / etiology*
  • Nonlinear Dynamics
  • Risk Factors
  • Weather

Grants and funding

This work was supported by The National Environmental Protection Non-profit Project [201509062], National Natural Science Foundation [41450006, 91643208], Beijing Medical Health Science and Technology Key-support Project [2014-1-4016], Chinese Academy of Medical Sciences (CAMS) Initiative for Innovative Medicine [2017-I2M-2-001, CAMS 2016ZX310181-4/5], National Key Research and Development Plan [2017YFC0211703], National 973 Project [2015CB553400], and Beijing Municipal Science and Technology Commission [Z131107002213176]. Zhongjie Fan received all the fundings.