An examination of sex and racial/ethnic differences in the metabolic syndrome among adults: a confirmatory factor analysis and a resulting continuous severity score

Metabolism. 2014 Feb;63(2):218-25. doi: 10.1016/j.metabol.2013.10.006. Epub 2013 Oct 24.

Abstract

Objective: The metabolic syndrome (MetS) is typically diagnosed based on abnormalities in specific clustered clinical measures that are associated with increased risk for coronary heart disease (CHD) and Type 2 diabetes mellitus (T2DM). However, current MetS criteria result in racial/ethnic discrepancies. Our goals were to use confirmatory factor analysis (CFA) to delineate differential contributions to MetS by sub-group, and if contributions were discovered, develop sex and racial/ethnic-specific equations to calculate MetS severity.

Research design and methods: Using data on adults from the National Health and Nutrition Examination Survey 1999-2010, we performed a CFA of a single MetS factor that allowed differential loadings across groups, resulting in a sex and race/ethnicity-specific continuous MetS severity score.

Results: Loadings to the single MetS factor differed by sub-group for each MetS component (p<0.001), with lower factor loadings among non-Hispanic-blacks for triglycerides and among Hispanics for waist circumference. Systolic blood pressure exhibited low factor loadings among all groups. MetS severity scores were correlated with biomarkers of future disease (high-sensitivity C-reactive-protein, uric acid, insulin resistance). Non-Hispanic-black-males with diabetics had a low prevalence of MetS but high MetS severity scores that were not significantly different from other racial/ethnic groups.

Conclusions: This analysis among adults uniquely demonstrated differences between sexes and racial/ethnic groups regarding contributions of traditional MetS components to an assumed single factor. The resulting equations provide a clinically-accessible and interpretable continuous measure of MetS for potential use in identifying adults at higher risk for MetS-related diseases and following changes within individuals over time. These equations hold potential to be a powerful new outcome for use in MetS-focused research and interventions.

Keywords: AIC; ATP-III; AUC; Adult Treatment Panel III; Akaike’s Information Criteria; Area under the curve; Bentler–Bonett Normed Fit Index; CDC; CFA; CHD; CHF; CVD; Cardiovascular disease; Centers for Disease Control; Clinical studies; Confirmatory Factor Analysis; Congestive heart failure; Coronary heart disease; Epidemiology; GFI; Goodness of Fit Index; HOMA-IR; High-sensitivity C-reactive protein; Hisp; Hispanic; Homeostasis model of insulin resistance; MI; MetS; Metabolic syndrome; Myocardial infarction; NFI; NHANES; NHB; NHW; National Health and Nutrition Examination Survey; Non-Hispanic Black; Non-Hispanic White; Obesity; RMSEA; ROC; Racial/ethnic differences; Receiver operating characteristic; Root Mean Square Error of Approximation; SBP; SRMR; Standardized Root Mean Square Residual; Systolic blood pressure; T2DM; Type 2 diabetes mellitus; WC; Waist circumference; hsCRP.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • African Americans / statistics & numerical data*
  • European Continental Ancestry Group / statistics & numerical data*
  • Factor Analysis, Statistical
  • Female
  • Hispanic Americans / statistics & numerical data*
  • Humans
  • Insulin Resistance
  • Male
  • Metabolic Syndrome / blood
  • Metabolic Syndrome / diagnosis*
  • Metabolic Syndrome / ethnology*
  • Middle Aged
  • Nutrition Surveys
  • Severity of Illness Index*
  • Sex Factors
  • Triglycerides / blood
  • United States / epidemiology
  • Waist Circumference

Substances

  • Triglycerides