Validation of Anthropometric Indices of Adiposity against Whole-Body Magnetic Resonance Imaging – A Study within the German European Prospective Investigation into Cancer and Nutrition (EPIC) Cohorts

Abstract

BackgroundIn epidemiological studies, measures of body fat generally are obtained through anthropometric indices such as the body mass index (BMI), waist (WC), and hip circumferences (HC). Such indices, however, can only provide estimates of a person’s true body fat content, overall or by adipose compartment, and may have limited accuracy, especially for the visceral adipose compartment (VAT).ObjectiveTo determine the extent to which different body adipose tissue compartments are adequately predicted by anthropometry, and to identify anthropometric measures alone, or in combination to predict overall adiposity and specific adipose tissue compartments, independently of age and body size (height).MethodsIn a sub-study of 1,192 participants of the German EPIC (European Prospective Investigation into Cancer and Nutrition) cohorts, whole-body MRI was performed to determine adipose and muscle tissue compartments. Additional anthropometric measurements of BMI, WC and HC were taken.ResultsAfter adjusting for age and height, BMI, WC and HC were better predictors of total body volume (TBV), total adipose tissue (TAT) and subcutaneous adipose tissue (SAT) than for VAT, coronary adipose tissue (CAT) and skeletal muscle tissue (SMT). In both sexes, BMI was the best predictor for TBV (men: r = 0.72 [0.68–0.76], women: r = 0.80 [0.77–0.83]) and SMT (men: r = 0.52 [0.45–0.57], women: r = 0.48 [0.41–0.54]). WC was the best predictor variable for TAT (r = 0.48 [0.41–0.54]), VAT (r = 0.44 [0.37–0.50]) and CAT (r = 0.34 [0.26–0.41]) (men), and for VAT (r = 0.42 [0.35–0.49]) and CAT (r = 0.29 [0.22–0.37]) (women). BMI was the best predictor for TAT (r = 0.49 [0.43–0.55]) (women). HC was the best predictor for SAT (men (r = 0.39 [0.32–0.45]) and women (r = 0.52 [0.46–0.58])).ConclusionsEspecially the volumes of internal body fat compartments are poorly predicted by anthropometry. A possible implication may be that associations of chronic disease risks with the sizes of internal body fat as measured by BMI, WC and HC may be strongly underestimated.

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“…Finally, we found that BMI in either cohort did not moderate the increased leptin among schizophrenia participants in our results. Although the leptin profile is intimately linked to various parameters of adiposity (total body fat, percentage body fat and fat distribution), these are not necessarily directly reflected in parameters such as BMI (Neamat-Allah et al, 2014).…”

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“…These include subcutaneous adipose tissue, which is located under the skin and stores $80% of total body fat with the major stores found in the upper (abdominal, subscapular fat) and lower body (gluteal-femoral fat). Intraabdominal adipose tissues include the visceral adipose tissue located around the digestive organs (mesenteric and omental) and the retroperitoneal depot (kidney), which together account for $20% of total body fat 6,7 (Fig. 1A).…”

Can the use of blood-based biomarkers in addition to anthropometric indices substantially improve the prediction of visceral fat volume as measured by magnetic resonance imaging?

“…Notwithstanding the fact that anthropometric indices strongly correlate with total and subcutaneous body fat volumes, we [8] and others have previously demonstrated that single or combined anthropometric measures only inadequately reflect visceral fat volume as objectively determined by MRI [9][10][11][12][13][14][15]. Thus, the underestimation of disease risks associated with visceral adiposity in epidemiological studies relying on anthropometry remains crucial, while the use of anthropometric indices only for individual risk assessment in clinical practice may lack sensitivity.…”

“…For the present analyses on circulating markers and visceral fat, MRI parameters and blood samples were available for 592 subjects. Further details about the background of this sub-study have been described previously [8]. In brief, the sub-sample was recruited according to a rectangular sampling scheme by age group, and sex, with the participation rate being 47 %.…”