Classification of metabolic syndrome according to lipid alterations: analysis from the Mexican National Health and Nutrition Survey 2006.

Abstract

BackgroundThere are 16 possible Metabolic Syndrome (MS) combinations out of 5 conditions (glucose intolerance, low levels of high-density lipoprotein Cholesterol (HDL-C), high triglycerides, high blood pressure and abdominal obesity), when selecting those with at least three. Studies suggest that some combinations have different cardiovascular risk. However evaluation of all 16 combinations is complex and difficult to interpret. The purpose of this study is to describe and explore a classification of MS groups according to their lipid alterations.MethodsThis is a cross-sectional study with data from the Mexican National Health and Nutrition Survey 2006. Subjects (n = 5,306) were evaluated for the presence of MS; four mutually-exclusive MS groups were considered: mixed dyslipidemia (altered triglycerides and HDL-C), hypoalphalipoproteinemia: (normal triglycerides but low HDL-C), hypertriglyceridemia (elevated triglycerides and normal HDL-C) and without dyslipidemia (normal triglycerides and HDL-C). A multinomial logistic regression model was fitted in order to identify characteristics that were associated with the groups.ResultsThe most frequent MS group was hypoalphalipoproteinemia in females (51.3%) and mixed dyslipidemia in males (43.5%). The most prevalent combination of MS for both genders was low HDL-C + hypertension + abdominal obesity (20.4% females, 19.4% males). The hypoalphalipoproteinemia group was characteristic of women and less developed areas of the country. The group without dyslipidemia was more frequent in the highest socioeconomic level and less prevalent in the south of the country. The mixed dyslipidemia group was characteristic of men, and the Mexico City region.ConclusionsA simple system to classify MS based on lipid alterations was useful to evaluate prevalences by diverse biologic and sociodemographic characteristics. This system may allow prevention and early detection strategies with emphasis on population-specific components and may serve as a guide for future studies on MS and cardiovascular risk.