OBJECTIVES: Several reports indicate that the body fat compartments, especially ip fat, predict metabolic risk better than total body fat. The objective of the study was to determine whether this can be confirmed and generalized throughout the population. PARTICIPANTS: A representative sample of 1934 Black and White women and men of the Dallas Heart Study participated in the study. DESIGN: We measured the fat in total body, trunk, and lower body with dual-energy x-ray absorptiometry and in abdominal compartments (sc, ip, and retroperitoneal) with magnetic resonance imaging. Other measurements included body mass index (BMI), waist circumference, blood pressure, plasma lipids, glucose, insulin (including homeostasis model), and C-reactive protein. RESULTS: In all groups, total body fat correlated positively with key metabolic risk factors, i.e. homeostasis model, triglyceride/high-density lipoprotein-cholesterol ratios, C-reactive protein, and blood pressure; however, it explained less than one third of the variability of all the risk factors. After adjustment for total body fat, truncal fat conferred additional positive correlation with risk factors. Furthermore, with multivariable regression analysis, ip fat conferred independent correlation with plasma lipids beyond a combination of other compartments including truncal fat. Still, except for insulin levels, all combinations including ip fat still explained less than one third of the variability in risk-factor levels. Conversely, lower body fat correlated negatively with risk factors; i.e. lower body fat appeared to offer some protection against risk factors. CONCLUSIONS: Body fat distribution has some influence on risk factors beyond total body fat content. Both waist circumference and BMI significantly predicted risk factors after adjustment for total body fat, and for clinical purposes, most of the predictive power for men was contained in waist circumference, whereas for women, BMI and waist circumference were similarly predictive. Finally, even though the correlations between combined body fat parameters and risk factors explained only a portion of the variation in the latter, the average number of categorical metabolic risk factors increased progressively with increasing obesity. Hence, obesity seemingly has more clinical impact than revealed in these correlative studies.
OBJECTIVES: Several reports indicate that the body fat compartments, especially ip fat, predict metabolic risk better than total body fat. The objective of the study was to determine whether this can be confirmed and generalized throughout the population. PARTICIPANTS: A representative sample of 1934 Black and White women and men of the Dallas Heart Study participated in the study. DESIGN: We measured the fat in total body, trunk, and lower body with dual-energy x-ray absorptiometry and in abdominal compartments (sc, ip, and retroperitoneal) with magnetic resonance imaging. Other measurements included body mass index (BMI), waist circumference, blood pressure, plasma lipids, glucose, insulin (including homeostasis model), and C-reactive protein. RESULTS: In all groups, total body fat correlated positively with key metabolic risk factors, i.e. homeostasis model, triglyceride/high-density lipoprotein-cholesterol ratios, C-reactive protein, and blood pressure; however, it explained less than one third of the variability of all the risk factors. After adjustment for total body fat, truncal fat conferred additional positive correlation with risk factors. Furthermore, with multivariable regression analysis, ip fat conferred independent correlation with plasma lipids beyond a combination of other compartments including truncal fat. Still, except for insulin levels, all combinations including ip fat still explained less than one third of the variability in risk-factor levels. Conversely, lower body fat correlated negatively with risk factors; i.e. lower body fat appeared to offer some protection against risk factors. CONCLUSIONS: Body fat distribution has some influence on risk factors beyond total body fat content. Both waist circumference and BMI significantly predicted risk factors after adjustment for total body fat, and for clinical purposes, most of the predictive power for men was contained in waist circumference, whereas for women, BMI and waist circumference were similarly predictive. Finally, even though the correlations between combined body fat parameters and risk factors explained only a portion of the variation in the latter, the average number of categorical metabolic risk factors increased progressively with increasing obesity. Hence, obesity seemingly has more clinical impact than revealed in these correlative studies.
Authors: M Sánchez-López; F B Ortega; P Moya-Martínez; S López-Martínez; I Ortiz-Galeano; M A Gómez-Marcos; M Sjöström; V Martínez-Vizcaíno Journal: Eur J Nutr Date: 2012-04-07 Impact factor: 5.614
Authors: Manthos G Giannoulis; Finbarr C Martin; K Sreekumaran Nair; A Margot Umpleby; Peter Sonksen Journal: Endocr Rev Date: 2012-03-20 Impact factor: 19.871
Authors: Yuichiro Yano; Wanpen Vongpatanasin; Colby Ayers; Aslan Turer; Alvin Chandra; Mercedes R Carnethon; Philip Greenland; James A de Lemos; Ian J Neeland Journal: Hypertension Date: 2016-07-18 Impact factor: 10.190
Authors: Jill A Young; Shih-Jen Hwang; Mark J Sarnak; Udo Hoffmann; Joseph M Massaro; Daniel Levy; Emelia J Benjamin; Martin G Larson; Ramachandran S Vasan; Christopher J O'Donnell; Caroline S Fox Journal: Clin J Am Soc Nephrol Date: 2008-09-24 Impact factor: 8.237