A two-year survey on the effect of temperature changes on the incidence of myocardial infarction in patients referred to the Ali-ibn Abi Talib Hospital, Rafsanjan, Iran, in 2013-2014

Abstract

Received: August 2015, Accepted: December 2015 Background: The role of temperature changes, as an environmental risk factor, in the human health status has been investigated in recent studies. Accordingly, the present two-year study was conducted to evaluate the incidence of myocardial infarction (MI) in warm and cold seasons in Ali-ibn Abi Talib Hospital, Rafsanjan, Iran. Materials and Methods:In this descriptive and cross-sectional study, 264 patients hospitalized with MI during a two-year period (2013-2014) were included. Data on the participants were obtained from their electronic medical files and on the weather from the official Rafsanjan Weather Bureau station. The collected data was then analyzed using statistical tests including chi-squared test, Fisher's exact test, and logistic regression model in SPSS software. Results: Data showed that 41.80% of MI occurred in hot weather, 14% in cold, and the remaining 37.12% in mild weather. According to the type of MI, 49.47% of non-ST elevation myocardial infarction (NSTEMI) and 44.44% of ST-segment elevation myocardial infarction (STEMI) occurred in very hot weather while 13.54% of NSTEMI and 18% of STEMI occurred in very cold weather. This difference was not significant. Conclusions: Based on our data, MI had occurred mostly in hot weather and more than half of the cases were NSTEMI.

Investigating artificial neural networks versus regression models in predicting Myocardial Infarction (MI) mortality based on climatic elements in Sanandaj city, Iran

“…Mohammadpur (2010) Using the regression method, studied the relationship between climatic elements, asthma, and MI and concluded that in Sanandaj, climatic elements have a great effect on asthma and MI and also concluded that among the climatic elements, minimum temperature, air pressure, and wind plays a greater role in the rate of hospitalization and mortality. Esmaeili-Nadimi et al (2014) showed that temperature changes has more effects on MI. Kojori et al (2015) showed that ANNs model performs well in predicting acute MI.…”