Anthropometrically predicted visceral adipose tissue and blood-based biomarkers: a cross-sectional analysis.
OBJECTIVE
We hypothesized that anthropometrically predicted visceral adipose tissue (apVAT) accounts for more variance in blood-based biomarkers of glucose homeostasis, inflammation, and lipid metabolism than body mass index (BMI), waist circumference (WC), and the combination of BMI and WC (BMI + WC).


METHODS
This was a cross-sectional analysis of 10,624 males and females who participated in the Third National Health and Nutrition Examination Survey (NHANES III; 1988-1994). apVAT was predicted from a validated regression equation that included age, height, weight, waist, and thigh circumferences. Bootstrapped linear regression models were used to compare the proportion of variance (R2) in biomarkers explained by apVAT, BMI, WC, and BMI + WC.


RESULTS
apVAT accounted for more variance in biomarkers of glucose homeostasis than BMI (∆R2= 8.4-11.8 %; P < 0.001), WC (∆R2= 5.5-8.4 %; P < 0.001), and BMI + WC (∆R2= 5.1-7.7 %; P < 0.001). apVAT accounted for more variance in biomarkers of inflammation than BMI (ΔR2= 3.8 %; P < 0.001), WC (ΔR2= 3.1 %; P < 0.001), and BMI + WC (ΔR2= 2.9 %; P < 0.001). apVAT accounted for more variance in biomarkers of lipid metabolism than BMI (ΔR2= 2.9-9.2 %; P < 0.001), WC (ΔR2= 2.9-5.2 %; P < 0.001), and BMI + WC (ΔR2= 2.4-4.1 %; P ≤ 0.01).


CONCLUSIONS
apVAT, estimated with simple and widely used anthropometric measures, accounts for more variance in blood-based biomarkers than BMI, WC, and BMI + WC. Clinicians and researchers may consider utilizing apVAT to characterize cardio-metabolic health, particularly in settings with limited availability of imaging and laboratory data.
Division of Population Sciences, Department of Medical Oncology, Dana-Farber Cancer Institute, 450 Brookline Ave, Boston, MA, 02215, USA. justinc_brown@dfci.harvard.edu.|Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA. justinc_brown@dfci.harvard.edu.
Justin C
http://orcid.org/0000-0001-7540-4913
JC
Brown
Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA.
Michael O
MO
Harhay
Division of Nephrology, Department of Medicine, Drexel University College of Medicine, Philadelphia, PA, USA.
Meera N
MN
Harhay
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000886:Anthropometry / Q000379:methods*; D015415:Biomarkers / Q000097:blood*; D001786:Blood Glucose / Q000032:analysis; D001823:Body Composition; D001827:Body Height; D015992:Body Mass Index; D001835:Body Weight; D003430:Cross-Sectional Studies; D005215:Fasting; D005260:Female; D006706:Homeostasis; D006801:Humans; D007249:Inflammation / Q000097:blood; D050152:Intra-Abdominal Fat; D050356:Lipid Metabolism / Q000502:physiology; D008297:Male; D024821:Metabolic Syndrome / Q000175:diagnosis; D008875:Middle Aged; D009749:Nutrition Surveys; D013848:Thigh / Q000033:anatomy & histology; D055105:Waist Circumference
D015415:Biomarkers; D001786:Blood Glucose
Adiposity; Body composition; Population-based; Waist–hip ratio