G K Raja1, M A Sarzynski2, P T Katzmarzyk3, W D Johnson4, Y Tchoukalova5, S R Smith6, C Bouchard2. 1. 1] Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA [2] Department of Biochemistry, Pir Mehr Ali Shah Arid Agriculture University Rawalpindi, Punjab, Pakistan. 2. Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA. 3. Preventive Medicine and Healthy Aging, Pennington Biomedical Research Center, Baton Rouge, LA, USA. 4. Biostatistics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA. 5. Biology of Adipose Tissue Depots Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA. 6. Translational Research Institute for Metabolism and Diabetes, Florida Hospital, Orlando, FL, USA.
Abstract
BACKGROUND: Many adiposity traits have been related to health complications and premature death. These adiposity traits are intercorrelated but their underlying structure has not been extensively investigated. We report on the degree of commonality and specificity among multiple adiposity traits in normal-weight and moderately overweight adult males and females (mean body mass index (BMI)=22.9 kg m(-2), s.d.=2.4). METHODS: A total of 75 healthy participants were assessed for a panel of adiposity traits including leg, arm, trunk, total fat masses and visceral adipose tissue (VAT) derived from dual energy X-ray absorptiometry (DXA), hepatic and muscle lipids from proton magnetic resonance spectroscopy, fat cell volume from an abdominal subcutaneous adipose tissue biopsy (n=36) and conventional anthropometry (BMI and waist girth). Spearman's correlations were calculated and were subjected to factor analysis. RESULTS: Arm, leg, trunk and total fat masses correlated positively (r=0.78-0.95) with each other. VAT correlated weakly with fat mass indicators (r=0.24-0.31). Intrahepatic lipids (IHL) correlated weakly with all fat mass traits (r=0.09-0.34), whereas correlations between DXA depots and intramyocellular lipids (IMCL) were inconsequential. The four DXA fat mass measures, VAT, IHL and IMCL depots segregated as four independent factors that accounted for 96% of the overall adiposity variance. BMI and waist girth were moderately correlated with the arm, leg, trunk and total fat and weakly with VAT, IHL and IMCL. CONCLUSION: Adiposity traits share a substantial degree of commonality, but there is considerable specificity across the adiposity variance space. For instance, VAT, IHL and IMCL are typically poorly correlated with each other and are poorly to weakly associated with the other adiposity traits. The same is true for BMI and waist girth, commonly used anthropometric indicators of adiposity. These results do not support the view that it will be possible to identify adequate anthropometric indicators of visceral, hepatic and muscle lipid content in normal-weight and moderately overweight individuals.
BACKGROUND: Many adiposity traits have been related to health complications and premature death. These adiposity traits are intercorrelated but their underlying structure has not been extensively investigated. We report on the degree of commonality and specificity among multiple adiposity traits in normal-weight and moderately overweight adult males and females (mean body mass index (BMI)=22.9 kg m(-2), s.d.=2.4). METHODS: A total of 75 healthy participants were assessed for a panel of adiposity traits including leg, arm, trunk, total fat masses and visceral adipose tissue (VAT) derived from dual energy X-ray absorptiometry (DXA), hepatic and muscle lipids from proton magnetic resonance spectroscopy, fat cell volume from an abdominal subcutaneous adipose tissue biopsy (n=36) and conventional anthropometry (BMI and waist girth). Spearman's correlations were calculated and were subjected to factor analysis. RESULTS: Arm, leg, trunk and total fat masses correlated positively (r=0.78-0.95) with each other. VAT correlated weakly with fat mass indicators (r=0.24-0.31). Intrahepatic lipids (IHL) correlated weakly with all fat mass traits (r=0.09-0.34), whereas correlations between DXA depots and intramyocellular lipids (IMCL) were inconsequential. The four DXA fat mass measures, VAT, IHL and IMCL depots segregated as four independent factors that accounted for 96% of the overall adiposity variance. BMI and waist girth were moderately correlated with the arm, leg, trunk and total fat and weakly with VAT, IHL and IMCL. CONCLUSION: Adiposity traits share a substantial degree of commonality, but there is considerable specificity across the adiposity variance space. For instance, VAT, IHL and IMCL are typically poorly correlated with each other and are poorly to weakly associated with the other adiposity traits. The same is true for BMI and waist girth, commonly used anthropometric indicators of adiposity. These results do not support the view that it will be possible to identify adequate anthropometric indicators of visceral, hepatic and muscle lipid content in normal-weight and moderately overweight individuals.
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