Prevalence of Acute Myocardial Infarction and Changing Meteorological Conditions in Iran: Fuzzy Clustering Approach

Sharif Nia H 1 , Gorgulu O 2 , Pahlevan Sharif S 3 , Froelicher ES 4 , Haghdoost AA 5 , Golshani S 6 Show all authors , Yaghoobzadeh A 7 , Noble JH 8 , Nazari R 1 , Goudarzian AH 9 , Arefinia F 10

Affiliations 

  • 1 Department of Nursing, Amol School of Nursing and Midwifery, Mazandaran University of Medical Sciences, Sari, Iran
  • 2 Department of Biostatistics and Medical Informatics, Faculty of Medicine, Ahi Evran University, Kırşehir, Turkey
  • 3 Taylor's Business School, Taylor's University Malaysia, Subang Jaya, Malaysia
  • 4 Department of Physiological Nursing, School of Nursing, University of California San Francisco, San Francisco, California, USA
  • 5 Research Center for Modeling in Health, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
  • 6 Department of Cardiology, Cardiovascular Research Center, Mazandaran University of Medical Sciences, Sari, Iran
  • 7 Department of Nursing, School of Nursing and Midwifery, Tehran University of Medical Sciences, Tehran, Iran
  • 8 Board of Directors Alliance for Human Research Protection (AHRP), New York, NY, USA
  • 9 Student Research Committee, Mazandaran University of Medical Sciences, Sari, Iran
  • 10 Amol School of Nursing and Midwifery, Mazandaran University of Medical Sciences, Sari, Iran
Iran J Public Health, 2020 May;49(5):923-930.
PMID: 32953680

Abstract

Background: The prevalence of Acute Myocardial Infarction (AMI) varies from region to region caused by seasonal climate changes and temperature variation. This study aimed to assess the relationship between changing meteorological conditions and incidence of AMI in Iran.

Methods: This retrospective prevalence study was based on medical records of the heart center of Mazandaran Province on all patients diagnosed with AMI in Mazandaran, northern Iran between 2013 and 2015. Patients' sex and the day, month, year and time of hospital admission were extracted from patients' records. Moreover, the meteorological reports were gathered.

Results: A statistically significant difference was found between the distributions of AMI cases across 12 months of the year (P < 0.01). Fuzzy clustering analysis using 16 different climatic variables showed that March, April, and May were in the same cluster together. The other 9 months were in different clusters.

Conclusion: Significant increase in AMI was seen in March, April and May (cold to hot weather).

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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