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A Time-Series Prediction Model of Acute Myocardial Infarction in Northern of Iran: The Risk of Climate Change and Religious Mourning Publisher Pubmed



Sharif Nia H1 ; Gorgulu O2 ; Naghavi N3 ; Froelicher ES4, 5 ; Fomani FK6 ; Goudarzian AH7 ; Sharif SP8 ; Pourkia R9 ; Haghdoost AA10
Authors
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Authors Affiliations
  1. 1. Cardiovascular Research Center, Mazandaran University of Medical Sciences, Sari, Iran
  2. 2. Department of Biostatistics and Medical Informatics, Faculty of Medicine, Ahi Evran University, Kirsehir, Turkey
  3. 3. Faculty of Business and Law, Taylor’s University, Subang Jaya, Selangor, Malaysia
  4. 4. Department of Physiological Nursing, School of Nursing, University of California Sand Francisco, San Francisco, CA, United States
  5. 5. Department of Epidemiology and Biostatistics, School of Medicine, University of California Sand Francisco, San Francisco, CA, United States
  6. 6. School of Nursing and Midwifery, Tehran University of Medical Sciences, Tehran, Iran
  7. 7. Student Research Committee, Mazandaran University of Medical Sciences, Sari, Iran
  8. 8. Faculty of Business and Law, Taylor’s University Malaysia, Subang Jaya, Malaysia
  9. 9. Department of Cardiology, Cardiovascular Research Center, Babol University of Medical Sciences, Babol, Iran
  10. 10. Research Center for Modeling in Health, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran

Source: BMC Cardiovascular Disorders Published:2021


Abstract

Background: Although various studies have been conducted on the effects of seasonal climate changes or emotional variables on the risk of AMI, many of them have limitations to determine the predictable model. The currents study is conducted to assess the effects of meteorological and emotional variables on the incidence and epidemiological occurrence of acute myocardial infarction (AMI) in Sari (capital of Mazandaran, Iran) during 2011–2018. Methods: In this study, a time series analysis was used to determine the variation of variables over time. All series were seasonally adjusted and Poisson regression analysis was performed. In the analysis of meteorological data and emotional distress due to religious mourning events, the best results were obtained by autoregressive moving average (ARMA) (5,5) model. Results: It was determined that average temperature, sunshine, and rain variables had a significant effect on death. A total of 2375 AMI’s were enrolled. Average temperate (°C) and sunshine hours a day (h/day) had a statistically significant relationship with the number of AMI’s (β = 0.011, P = 0.014). For every extra degree of temperature increase, the risk of AMI rose [OR = 1.011 (95%CI 1.00, 1.02)]. For every extra hour of sunshine, a day a statistically significant increase [OR = 1.02 (95% CI 1.01, 1.04)] in AMI risk occurred (β = 0.025, P = 0.001). Religious mourning events increase the risk of AMI 1.05 times more. The other independent variables have no significant effects on AMI’s (P > 0.05). Conclusion: Results demonstrate that sunshine hours and the average temperature had a significant effect on the risk of AMI. Moreover, emotional distress due to religious morning events increases AMI. More specific research on this topic is recommended. © 2021, The Author(s).
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