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Spatial analysis of myocardial infarction in Iran: National report from the Iranian myocardial infarction registry.

Ahmadi A, Soori H, Mehrabi Y, Etemad K - J Res Med Sci (2015)

Bottom Line: Out of the associated factors with clustered MI in six provinces, temperature, humidity, hypertension, smoking, and body mass index (BMI) could be mentioned.Addressing the place-based pattern of incidence and clarifying their epidemiologic dimension, including spatial analysis, has not yet been implemented in Iran.Report on MI incidence rate by place and formal borders is useful and is used in the planning and prioritization in different levels of health system.

View Article: PubMed Central - PubMed

Affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Modeling in Health Research Center, Shahrekord University of Medical Sciences, Shahrekord, Iran.

ABSTRACT

Background: Myocardial infarction (MI) is a leading cause of mortality and morbidity in Iran. No spatial analysis of MI has been conducted to date. The present study was conducted to determine the pattern of MI incidence and to identify the associated factors in Iran by province.

Materials and methods: This study has two parts. One part is prospective and hospital-based, and the other part is an ecological study. In this study, the data of 20,750 new MI cases registered in Iranian Myocardial Infarction Registry in 2012 were used. For spatial analysis in global and local, spatial autocorrelation, Moran's I, Getis-Ord, and logistic regression models were used. Data were analyzed by Stata software and ArcGIS 9.3.

Results: Based on autocorrelation coefficient, a specific pattern was observed in the distribution of MI incidence in different provinces (Moran's I: 0.75, P < 0.001). Spatial pattern of incidence was approximately the same in men and women. MI incidence was clustering in six provinces (North Khorasan, Yazd, Kerman, Semnan, Golestan, and Mazandaran). Out of the associated factors with clustered MI in six provinces, temperature, humidity, hypertension, smoking, and body mass index (BMI) could be mentioned. Hypertension, smoking, and BMI contributed to clustering with, respectively, 2.36, 1.31, and 1.31 odds ratio.

Conclusion: Addressing the place-based pattern of incidence and clarifying their epidemiologic dimension, including spatial analysis, has not yet been implemented in Iran. Report on MI incidence rate by place and formal borders is useful and is used in the planning and prioritization in different levels of health system.

No MeSH data available.


Related in: MedlinePlus

Cluster analysis: Z Score of Moran's I for male, female and total patients with myocardial infarction in Iran; 2012
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Figure 1: Cluster analysis: Z Score of Moran's I for male, female and total patients with myocardial infarction in Iran; 2012

Mentions: Coefficient of global autocorrelation per sex is shown in Table 1. Figure 1 depicts spatial pattern of MI incidence by gender. MI incidence was clustering in six provinces (North Khorasan, Yazd, Kerman, Semnan, Golestan, and Mazandaran) Map A [Figure 1]. Spatial pattern of incidence was observed as clustering for men in six provinces (North Khorasan, Yazd, Kerman, Semnan, Quazvin, and Mazandaran) and for women in six provinces (North Khorasan, Yazd, Kerman, Semnan, Golestan, and Mazandaran) Maps B and C [Figure 1].


Spatial analysis of myocardial infarction in Iran: National report from the Iranian myocardial infarction registry.

Ahmadi A, Soori H, Mehrabi Y, Etemad K - J Res Med Sci (2015)

Cluster analysis: Z Score of Moran's I for male, female and total patients with myocardial infarction in Iran; 2012
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4590197&req=5

Figure 1: Cluster analysis: Z Score of Moran's I for male, female and total patients with myocardial infarction in Iran; 2012
Mentions: Coefficient of global autocorrelation per sex is shown in Table 1. Figure 1 depicts spatial pattern of MI incidence by gender. MI incidence was clustering in six provinces (North Khorasan, Yazd, Kerman, Semnan, Golestan, and Mazandaran) Map A [Figure 1]. Spatial pattern of incidence was observed as clustering for men in six provinces (North Khorasan, Yazd, Kerman, Semnan, Quazvin, and Mazandaran) and for women in six provinces (North Khorasan, Yazd, Kerman, Semnan, Golestan, and Mazandaran) Maps B and C [Figure 1].

Bottom Line: Out of the associated factors with clustered MI in six provinces, temperature, humidity, hypertension, smoking, and body mass index (BMI) could be mentioned.Addressing the place-based pattern of incidence and clarifying their epidemiologic dimension, including spatial analysis, has not yet been implemented in Iran.Report on MI incidence rate by place and formal borders is useful and is used in the planning and prioritization in different levels of health system.

View Article: PubMed Central - PubMed

Affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Modeling in Health Research Center, Shahrekord University of Medical Sciences, Shahrekord, Iran.

ABSTRACT

Background: Myocardial infarction (MI) is a leading cause of mortality and morbidity in Iran. No spatial analysis of MI has been conducted to date. The present study was conducted to determine the pattern of MI incidence and to identify the associated factors in Iran by province.

Materials and methods: This study has two parts. One part is prospective and hospital-based, and the other part is an ecological study. In this study, the data of 20,750 new MI cases registered in Iranian Myocardial Infarction Registry in 2012 were used. For spatial analysis in global and local, spatial autocorrelation, Moran's I, Getis-Ord, and logistic regression models were used. Data were analyzed by Stata software and ArcGIS 9.3.

Results: Based on autocorrelation coefficient, a specific pattern was observed in the distribution of MI incidence in different provinces (Moran's I: 0.75, P < 0.001). Spatial pattern of incidence was approximately the same in men and women. MI incidence was clustering in six provinces (North Khorasan, Yazd, Kerman, Semnan, Golestan, and Mazandaran). Out of the associated factors with clustered MI in six provinces, temperature, humidity, hypertension, smoking, and body mass index (BMI) could be mentioned. Hypertension, smoking, and BMI contributed to clustering with, respectively, 2.36, 1.31, and 1.31 odds ratio.

Conclusion: Addressing the place-based pattern of incidence and clarifying their epidemiologic dimension, including spatial analysis, has not yet been implemented in Iran. Report on MI incidence rate by place and formal borders is useful and is used in the planning and prioritization in different levels of health system.

No MeSH data available.


Related in: MedlinePlus