The Value of Anthropometric Measures in Nutrition and Metabolism: Comment on Anthropometrically Predicted Visceral Adipose Tissue and Blood-Based Biomarkers: A Cross-Sectional Analysis. (February 2019)

• Record Type: Journal Article
• Authors: Brown, Justin C; Harhay, Michael O; Harhay, Meera N
• Is Part Of: Nutrition and metabolic insights. Volume 12(2019)
• Publication Date: 2019-02
• Subjects: Obesity -- insulin resistance -- inflammation -- body composition -- cohort study; Nutrition -- Periodicals; Metabolism -- Periodicals; Nutritional Physiological Phenomena -- Periodicals; Metabolism -- Periodicals; Metabolism; Nutrition; Electronic journals; Periodicals; 572.405
• DOI: 10.1177/1178638819831712
• Languages: English
• ISSNs: 1178-6388

Abstract

Visceral adipose tissue (VAT)—fat stored deep in the abdominal cavity that surrounds vital organs—is associated with a variety of chronic health conditions. Computed tomography and magnetic resonance imaging are the gold standards to quantify VAT. However, the high cost, limited accessibility, and potential exposure to radiation limit the use of these imaging modalities. In this commentary, we review the application of a previously validated regression equation that estimates anthropometrically predicted VAT (apVAT) to explain variance in blood-based biomarkers and predict mortality in a large sample of adults. In our first study (Brown et al. 2018 Eur J Nutr ; doi:10.1007/s00394-016-1308-8), apVAT accounted for more variance in biomarkers of glucose homeostasis, inflammation, and lipid metabolism, than body mass index (BMI), waist circumference (WC), or the combination of BMI + WC. In our second study (Brown et al. 2017 Am J Hum Biol ; doi:10.1002/ajhb.22898), compared with BMI, WC, and BMI + WC, apVAT more accurately predicted mortality from all causes, cardiovascular disease, and cancer. These studies demonstrate that apVAT can be used in clinical practice and in clinical nutrition and metabolism research when imaging modalities to quantify VAT may not be feasible.