TY - JOUR
T1 - Influence of body fat content and distribution on variation in metabolic risk
AU - Vega, Gloria L
AU - Huet, Beverley A
AU - Peshock, Ronald M
AU - Willett, Duwayne L
AU - Shah, Brijen
AU - Grundy, Scott M
N1 - Funding Information:
This work was supported by the Donald W. Reynolds Cardiovascular Clinical Research Center at Dallas and General Clinical Research Center Grant MO1-RR0633, the Moss Heart Foundation, and a Veterans Affairs Merit grant.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2006/11
Y1 - 2006/11
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=33751542483&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33751542483&partnerID=8YFLogxK
U2 - 10.1210/jc.2006-0814
DO - 10.1210/jc.2006-0814
M3 - Article
C2 - 16926254
AN - SCOPUS:33751542483
SN - 0021-972X
VL - 91
SP - 4459
EP - 4466
JO - Journal of Clinical Endocrinology and Metabolism
JF - Journal of Clinical Endocrinology and Metabolism
IS - 11
ER -