Contribution of intra-abdominal fat accumulation to the impairment of glucose and lipid metabolism in human obesity

Fujioka, S; Matsuzawa, Yūji; Tokunaga, Katsuto; Tarui, Seiichiro

doi:10.1016/0026-0495(87)90063-1

Cited by 1,118 publications

(666 citation statements)

References 27 publications

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“…Some studies emphasising visceral fat as a risk factor for metabolic disease have specified threshold values to identify subjects at risk, e.g. a visceral fat area of ≥100 cm 2 has been used to identify MONW Japanese individuals [41]. However, there have been discrepancies between studies that have used such values, and the differences are not completely explained by ethnic-or sex-related confounders across investigations.…”

Section: What Do We Learn From Body Fat Distribution?mentioning

confidence: 99%

Adipose tissue distribution and risk of metabolic disease: does thiazolidinedione-induced adipose tissue redistribution provide a clue to the answer?

2007

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The relative effect of visceral and subcutaneous obesity on the risk of chronic metabolic disease has been a matter of long-term dispute. While ample data support either of the fat depots being causative or associative, valid argument for one depot often automatically belittles the other. Paradigms such as the visceral/portal hypothesis and the acquired lipodystrophy/ectopic fat storage and endocrine hypothesis have been proposed. Nevertheless, neither hypothesis alone explains the entire pathophysiological setting. Treatment of diabetes with thiazolidinediones selectively increases fat partitioning to the subcutaneous adipose depot but does not change visceral fat accumulation. This is in contrast to the preferential visceral fat mobilisation by diet and exercise. Surgical removal of visceral or subcutaneous adipose tissue yields relatively long-lasting metabolic improvement only when combined with procedures that ameliorate adipose tissue cell composition. These studies illustrate that human adipose tissue in different anatomic locations does not work in isolation, and that there is a best-fit relationship in terms of volume and function among different fat depots that needs to be met to maintain the systemic energy balance and to prevent the complications related to obesity.

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Section: What Do We Learn From Body Fat Distribution?mentioning

confidence: 99%

Adipose tissue distribution and risk of metabolic disease: does thiazolidinedione-induced adipose tissue redistribution provide a clue to the answer?

2007

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“…Android body fat distribution is associated with insulin resistance more than is a gynoid body fat distribution [5], with the site of abdominal fat distribution being an additional determinant of insulin sensitivity [6,7,8,9,10,11]. We found in both lean and obese subjects that the intraabdominal fat (IAF) depot is a stronger determinant of insulin sensitivity than the subcutaneous fat (SCF) depot [11], while SCF is the main determinant of the plasma concentration of leptin [11], an adipocyte-derived hormone regulating energy metabolism [12,13].…”

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confidence: 99%

Relationship of adiponectin to body fat distribution, insulin sensitivity and plasma lipoproteins: evidence for independent roles of age and sex

et al. 2003

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Aims/hypothesis. Increased intra-abdominal fat is associated with insulin resistance and an atherogenic lipoprotein profile. Circulating concentrations of adiponectin, an adipocyte-derived protein, are decreased with insulin resistance. We investigated the relationships between adiponectin and leptin, body fat distribution, insulin sensitivity and lipoproteins. Methods. We measured plasma adiponectin, leptin and lipid concentrations, intra-abdominal and subcutaneous fat areas by CT scan, and insulin sensitivity index (S I ) in 182 subjects (76 M/106F). Results. Adiponectin concentrations were higher in women than in men (7.4±2.9 vs 5.4±2.3 µg/ml, p<0.0001) as were leptin concentrations (19.1±13.7 vs 6.9±5.1 ng/ml, p<0.0001). Women were more insulin sensitive (S I : 6.8±3.9 vs 5.9±4.4×10 −5 min −1 /(pmol/l), p<0.01) and had more subcutaneous (240±133 vs 187±90 cm 2 , p<0.01), but less intra-abdominal fat (82±57 vs 124±68 cm 2 , p<0.0001). By simple regression, adiponectin was positively correlated with age (r=0.227, p<0.01) and S I (r=0.375, p<0.0001), and negatively correlated with BMI (r=−0.333, p<0.0001), subcutaneous (r=−0.168, p<0.05) and intra-abdominal fat (r=−0.35, p<0.0001). Adiponectin was negatively correlated with triglycerides (r=−0.281, p<0.001) and positively correlated with HDL cholesterol (r=0.605, p<0.0001) and Rf, a measure of LDL particle buoyancy (r=0.474, p<0.0001). By multiple regression analysis, adiponectin was related to age (p<0.0001), sex (p<0.005) and intra-abdominal fat (p<0.01). S I was related to intraabdominal fat (p<0.0001) and adiponectin (p<0.0005). Both intra-abdominal fat and adiponectin contributed independently to triglycerides, HDL cholesterol and Rf. Conclusion/interpretation. These data suggest that adiponectin concentrations are determined by intra-abdominal fat mass, with additional independent effects of age and sex. Adiponectin could link intra-abdominal fat with insulin resistance and an atherogenic lipoprotein profile. [Diabetologia (2003) 46:459-469] Keywords Adiponectin, Acrp30, adipoQ, central obesity, subcutaneous fat, intra-abdominal fat, insulin sensitivity, lipids, hepatic lipase, cardiovascular disease, leptin. It is well recognized that obesity and insulin resistance are closely related [1,2,3,4]. Android body fat distribution is associated with insulin resistance more than is a gynoid body fat distribution [5], with the site of abdominal fat distribution being an additional determinant of insulin sensitivity [6,7,8,9,10,11]. We found in both lean and obese subjects that the intraabdominal fat (IAF) depot is a stronger determinant of insulin sensitivity than the subcutaneous fat (SCF) depot [11], while SCF is the main determinant of the plasma concentration of leptin [11], an adipocyte-derived hormone regulating energy metabolism [12,13].

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“…8,[12][13][14][15] The prevalence of a body mass index (BMI) X25 kg m -2 (overweight) or a BMI X30 kg m -2 (obesity) in patients with established CHD is over 80 and 40%, respectively. 16,17 Furthermore, obesity and insulin resistance are associated with greater inflammatory tone, as reflected by elevated measures of C-reactive protein 9,18 as well as abnormalities of coagulation, platelet function and fibrinolysis.…”

Section: Introductionmentioning

confidence: 99%

“…20 For these reasons, we determined insulin responsiveness using the euglycemic-hyperinsulinemic clamp technique as a criterion approach to measure modulators of other risk factors, such as hyperlipidemia, inflammation and coagulation abnormalities. [12][13][14][15][16][17] …”

Section: Introductionmentioning

confidence: 99%

The influence of obesity and consequent insulin resistance on coronary risk factors in medically treated patients with coronary disease

et al. 2008

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Objective: Obesity promotes the development and progression of coronary heart disease (CHD), in part, through its association with hyperlipidemia, hypertension, clotting abnormalities and insulin resistance. We assessed whether these relationships persist in patients with established CHD treated with evidence-based preventive pharmacologic therapies. Design and subjects: We performed a cross-sectional study of 74 adults with CHD and a body mass index (BMI) of 427 kg m -2 (mean 32±4). The mean age of subjects was 64±9 years (range 44-84 years). Measurements: Obesity measures included weight, BMI, waist, fat mass, intra-abdominal fat and subcutaneous fat. Risk factor measures included insulin sensitivity, fasting insulin level, lipid profiles, blood pressure, C-reactive protein (hs-CRP), plasminogen activator inhibitor (PAI-1) and platelet reactivity. Medication use included aspirin (99%), statin (84%), b-blocker (71%), ACE inhibitor or blocker (37%) and clopidogrel (28%). Results: There was no direct relationship between obesity parameters and risk factor measures of lipid concentrations, blood pressure, clotting abnormalities or platelet reactivity except for a modest relationship between visceral fat and hs-CRP (r ¼ 0.30, P ¼ 0.02). However, increased BMI, waist circumference, fat mass, total abdominal fat and abdominal subcutaneous fat all correlated with insulin sensitivity (r-values À0.30 to À0.45, P-values 0.01 to o0.001) and insulin concentrations. Insulin sensitivity, in turn, was the best predictor of PAI-1, triglycerides, high-density lipoprotein (HDL) levels, cholesterol/HDL levels (all Po0.01) and platelet reactivity (R ¼ 0.34, P ¼ 0.02). Conclusions: Use of preventive pharmacologic therapies obviated the expected relationship between adiposity and CHD risk factors. However, a residual effect of insulin resistance is left untreated. Total adiposity and central adiposity were strong predictors of insulin sensitivity, which in turn predicted cardiac risk factors such as lipid concentrations, PAI-1 and platelet reactivity. Thus, while evidence-based pharmacologic treatments may diminish the statistical relationship between obesity and many cardiac risk factors, adiposity negatively impacts CHD risk by reducing tissue insulin sensitivity.

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Contribution of intra-abdominal fat accumulation to the impairment of glucose and lipid metabolism in human obesity

Cited by 1,118 publications

References 27 publications

Adipose tissue distribution and risk of metabolic disease: does thiazolidinedione-induced adipose tissue redistribution provide a clue to the answer?

Adipose tissue distribution and risk of metabolic disease: does thiazolidinedione-induced adipose tissue redistribution provide a clue to the answer?

Relationship of adiponectin to body fat distribution, insulin sensitivity and plasma lipoproteins: evidence for independent roles of age and sex

The influence of obesity and consequent insulin resistance on coronary risk factors in medically treated patients with coronary disease

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