The seasonality of acute coronary syndrome and its relations with climatic parameters

Am J Emerg Med. 2011 Sep;29(7):768-74. doi: 10.1016/j.ajem.2010.02.027. Epub 2010 May 1.

Abstract

Background: Most research on the seasonality of acute coronary syndrome (ACS) has been were reported from hospital-based data. We aimed to investigate the seasonal distribution of ACS in Beijing and to elucidate the relations between ACS occurrence and climatic parameters in a prehospital setting.

Methods: We retrospectively reviewed the electronic prehospital medical records from the Beijing's emergency medical service system spanning August 1, 2005, to July 31, 2007. Case data were analyzed by month and season with χ² test. The effects of climatic factors on the occurrence of ACS were analyzed by Poisson regression with generalized linear model.

Results: During the 2-year study period, a total of 7037 ACS events were identified, including 4135 male patients (58.8%) and 2902 female patients (41.2%). Significant variations were observed in the monthly (P < .001) and seasonal (P < .001) distribution of ACS. The highest seasonal incidence occurred in winter and lowest in autumn. Significant negative correlations were noticed between the number of ACS events and daily mean temperature (P < .001) and between the number of ACS events and barometric pressure (P < .001). Comparing to the baseline level (temperature of 25°C to approximately 31°C; barometric pressure of 1026 to approximately 1048 hectopascal (hPa)), an increase of 41.3% of daily ACS incidence was associated with temperature lower than 2°C (-10.0°C to approximately 2.0°C), and an increase of 19.8% was associated with barometric pressure under 1006 hPa (991.0 to approximately 1006 hPa).

Conclusions: There are clear monthly and seasonal rhythms of ACS in Beijing metropolitan area. Temperature and barometric pressure are negatively related with the occurrence of ACS.

MeSH terms

  • Acute Coronary Syndrome / epidemiology*
  • Acute Coronary Syndrome / etiology
  • Adult
  • Age Factors
  • Aged
  • Chi-Square Distribution
  • China / epidemiology
  • Emergency Service, Hospital / statistics & numerical data
  • Female
  • Humans
  • Male
  • Middle Aged
  • Poisson Distribution
  • Retrospective Studies
  • Seasons*
  • Temperature
  • Weather*