Patterns of clustering of the metabolic syndrome components and its association with coronary heart disease in the Multi-Ethnic Study of Atherosclerosis (MESA): A Latent Class Analysis
سال انتشار: 1397
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 492
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شناسه ملی سند علمی:
IHSC11_650
تاریخ نمایه سازی: 5 آذر 1397
چکیده مقاله:
Background: The Metabolic syndrome (MetS), refer to one of the most challenging public health issues across the world. The aim of this study was to explore the latent classes of participants in a study on the basis of MetS components. Methods: This study used the information from Multi-Ethnic Study of Atherosclerosis (MESA). MESA was performed at 6 US sites and was a population-based cohort study of 6776 adults (3576 females; 3200 males), aged 45 to 84 years. The participants were free of clinical cardiovascular disease at baseline. Latent class analysis (LCA) was conducted to achieve the study’s objectives. The outcome variable was coronary heart disease (CHD) during the study period (2000-2012). Analyses were performed by using proc LCA in SAS 9.2 and stata12 software. Results: The prevalence of all components (except triglyceride (TG) and fasting blood glucose (FBS)) is more common in females than in males. Three latent classes were recognized: (1) Non-MetS, (2) low risk, and (3) MetS. Notably, MetS latent class included 29.88% and 35.38% in females and males, respectively. After adjustment for covariates, only MetS latent class showed a positive association with CHD events in both genders. Conclusions: Results showed that clustering pattern of the MetS components, as well as the association between latent classes and risk of incident CHD events, are different in females and males. Notable percentages of individuals are in the MetS class, which emphasizes the necessity of implementing preventive interventions for this sub-group of the population.
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نویسندگان
Seyed Mohammad Riahi
Department of Epidemiology, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran. Department of Public health, School of Health, Birjand University of Medical Sciences, Birjand, Iran.
Soraya Moamer
Department of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Mahshid Namdari
Community Oral Health Department, School of Dentistry, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Yaser Mokhayeri
Department of Epidemiology, School of Public Health, Lorestan University of Medical Sciences, Khorramabad, Iran