4.5 Article

Are field measures of adiposity sufficient to establish fatness-related linkages with metabolic outcomes in adolescents?

Journal

EUROPEAN JOURNAL OF CLINICAL NUTRITION
Volume 68, Issue 6, Pages 671-676

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/ejcn.2014.14

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OBJECTIVE: To examine the associations between the adiposity-related information conveyed by field fatness measures: body mass index (BMI), waist circumference (WC) and sum of triceps and subscapular skinfolds (SUM SF) relative to dual-energy X-ray absorptiometry (DXA), beyond their common intercorrelations, with three important metabolic variables in US adolescents. METHODS: We analyzed data on adiposity and insulin resistance (HOMA-IR), serum triglycerides (TGs) and total cholesterol (IC) from three US national surveys. In two-stage least-square modeling, we first calculated the common adiposity variance, and then used multivariate linear and quantile regressions to access residual associations with each measure. RESULTS: Basic associations for each of the adiposity measures were similar but differences emerged in residual adiposity analyses scaled by s.d. units. While a 1 s.d. change in residual variance in DXA total fat beyond that accounted for by BMI (DXA(|BMI)) was strongly and significantly associated with all outcomes, associations with DXA accounting for SUM SF (DXA(|SUM) (SF)) and WC (DXA(|WC)) were weak or nonsignificant. Contrasted amongst themselves, the residual score association between BMI|SUM (SF) (beta = 0.06, P < 0.0001) and HOMA-IR was weaker, and half as strong as that for the converse, SUM SF|BMI (beta = 0.13, P = 0.020). SUM SF|WC was stronger than WC|SUM (SF) (beta = 0.08, P < 0.0001 vs SUM SF|WC beta = 0.13, P < 0.0001). Associations were similar for TGs and TC. CONCLUSIONS: Laboratory methods like DXA offer minimal explanatory advantage over field methods in assessing adiposity-related contributions to metabolic outcomes in adolescents. Among the simple fatness measures, skinfolds convey additional information beyond BM! and WC when estimating associations both at the population mean and at the upper extremes of metabolic factors.

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