Relationship of anthropometric measurements of body fat distribution to metabolic profile in premenopausal women

Acta Med Scand Suppl. 1988:723:179-88. doi: 10.1111/j.0954-6820.1987.tb05942.x.

Abstract

Regional fat distribution has emerged as an independent predictor of metabolic aberrations including glucose intolerance, hyperinsulinemia, insulin resistance, hyperlipidemia and hypertension. We investigated the comparative efficacy of various body fat distribution indices in predicting these aberrations. The relationship of circumferential ratios, skinfold measurements, and computerized tomography (CT)-derived indices of intra- and extra-abdominal fat distribution to the metabolic variables and blood pressure was examined in a cohort of healthy premenopausal women. All indices denoting preponderance of fat in the central, upper body or abdominal region were predictive of the metabolic profile. The subscapular skinfold, subscapular-triceps ratio, waist-hip ratio (WHR), and the CT derived intra-abdominal fat area (CT-IFA) were closely related to alterations in glucose and insulin concentrations independent of age and obesity. The WHR and CT-IFA were better predictors of plasma triglyceride levels and blood pressure profile and thus the overall aberrations than skinfold measurements. Despite a high degree of intercorrelation between the anthropometric indices measured, only the relationship of WHR to CT-IFA remained significant after adjusting for the effects of age and degree of adiposity, suggesting that WHR indexes not only the relative distribution of truncal to gluteofemoral subcutaneous fat but also the abundance of intra-abdominal or visceral fat depots. The greater reproducibility of CT-IFA and WHR also suggests that these measurements are the most useful in predicting the regional obesity-associated metabolic abnormalities with their morbidity and mortality risks.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adipose Tissue / anatomy & histology*
  • Adult
  • Anthropometry / methods*
  • Female
  • Forecasting
  • Humans
  • Menopause
  • Metabolic Diseases / metabolism*
  • Regression Analysis
  • Skinfold Thickness