Determinants of resting energy expenditure in obese non-diabetic caucasian women

Karhunen, Leila; Franssila-Kallunki, Anja; Rissanen, Aila; Kervinen, Kari; Ya, Kesäniemi; Uusitupa, M

doi:10.1038/sj.ijo.0800387

Cited by 35 publications

(34 citation statements)

References 32 publications

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“…The latter may have reflected a lower REE in women who were characterized by greater hip circumferences and lower fat-free mass. Others have shown, but only in women, that there is an association between visceral fat and REE 37 and waist-to-hip ratio and REE, 29 indicating greater REE with greater abdominal obesity. These findings support the negative effect of hip circumference (gluteo femoral obesity) on REE that we found.…”

Section: Discussionmentioning

confidence: 96%

“…Our obese population was characterized by upper body obesity and equal proportions of whole-body fat mass and fat-free mass such that weight was a better predictor of REE than fat-free mass. Fatfree mass has been identified as the strongest determinant of REE, accounting for 49 29 to 90% 34 of the variation in REE, depending upon the heterogeneity of the cohorts studied. In our subjects, weight was largely contributed to by the upper body as indicated by elevated waist circumferences and waist-to-hip ratios, which is the area where organ mass with high metabolic activity is located.…”

Section: Discussionmentioning

confidence: 99%

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The prediction of resting energy expenditure in type 2 diabetes mellitus is improved by factoring for glycemia

et al. 2002

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BACKGROUND: Predictive equations have been reported to overestimate resting energy expenditure (REE) for obese persons. The presence of hyperglycemia results in elevated REE in obese persons with type 2 diabetes, and its effect on the validity of these equations is unknown. OBJECTIVE: We tested whether (1) indicators of diabetes control were independent associates of REE in type 2 diabetes and (2) their inclusion would improve predictive equations. DESIGN: A cross-sectional study of 65 (25 men, 40 women) obese type 2 diabetic subjects. Variables measured were: REE by ventilated-hood indirect calorimetry, body composition by bioimpedance analysis, body circumferences, fasting plasma glucose (FPG) and hemoglobin A 1c . Data were analyzed using stepwise multiple linear regression. RESULTS: REE, corrected for weight, fat-free mass, age and gender, was significantly greater with FPG > 10 mmol=l (P ¼ 0.017) and correlated with FPG (P ¼ 0.013) and hemoglobin A 1c as percentage upper limit of normal (P ¼ 0.02). Weight was the main determinant of REE. Together with hip circumference and FPG, it explained 81% of the variation. FPG improved the predictability of the equation by > 3%. With poor glycemic control, it can represent an increase in REE of up to 8%. CONCLUSION: Our data indicate that in a population of obese subjects with type 2 diabetes mellitus, REE is better predicted when fasting plasma glucose is included as a variable.

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Section: Discussionmentioning

confidence: 96%

Section: Discussionmentioning

confidence: 99%

The prediction of resting energy expenditure in type 2 diabetes mellitus is improved by factoring for glycemia

et al. 2002

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“…Because estrogens may independently influence CHD risk factors. 30 These factors might partly preclude our definitive conclusions. It is well known that menopause is associated with a body fat redistribution toward an increase in the accumulation of visceral adipose tissue, resulting in increase in risks for CHD.…”

Section: Regional Lean Soft Tissue and Chd Risk Factorsmentioning

confidence: 94%

“…However, because LST is the strongest determinant of resting metabolic rates, which is closely associated with lipid and glucose metabolism, 30 it can be hypothesized that an increase in LST may improve some CHD-related metabolic variables. Resistance training has the potential to increase LST, 31 which results in normalized blood pressure in those with high normal values, 32 and improved glucose tolerance and insulin sensitivity.…”

Section: Regional Lean Soft Tissue and Chd Risk Factorsmentioning

confidence: 99%

Regional Body Composition Changes Exhibit Opposing Effects on Coronary Heart Disease Risk Factors

Okura

Nakata

Yamabuki

et al. 2004

ATVB

119

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Objective-We investigated how regional body composition measured by dual-energy X-ray absorptiometry (DXA) is associated with risk factors for coronary heart disease (CHD) during weight reduction in obese women. Methods and Results-Data were gathered from 128 overweight and obese women, aged 34 to 66 years, during a 14-week intervention study with diet and exercise. Key Words: obesity Ⅲ risk factors Ⅲ exercise Ⅲ diet A ccording to several epidemiological studies, obesity is closely associated with some major health risk factors, 1,2 and the prevalence of obesity continues to increase in developed countries. 3 It is well known that individuals with android-type obesity are at greater risk for coronary heart disease (CHD) and several metabolic disorders. 4 Waist circumference and waist-to-hip ratio (WHR) are widely used anthropometric indices for determining central fat obesity. [5][6][7] Intra-abdominal fat measured by computerized tomography (CT) is also an index for evaluating abdominal adiposity and is strongly associated with metabolic disorders independent of whole-body adiposity, including high blood pressure and triglycerides as well as increased incidence of diabetes mellitus. 8 -10 There are also several cross-sectional studies showing an association between regional body composition, especially truncal adiposity measured by dual-energy X-ray absorptiometry (DXA), and several CHD risk factors. [11][12][13][14][15][16][17] Interestingly, some investigators have reported that peripheral fat may confer a negative association against metabolic dysfunction in postmenopausal 17 and elderly women. 12,13 However, very little information is available on the relationship between changes in regional body composition and CHD risk factors in response to weight reduction.Based on these studies, we hypothesized that changes in regional body composition during weight reduction would See page 795affect or improve CHD risk factors. In this study, we investigate how changes in anthropometric and CT variables and regional body composition measured by DXA are associated with improvement in CHD risk factors in overweight and obese women in response to weight reduction through diet and exercise. We focused on which body region as measured by DXA is most strongly related to the improvement in CHD risk factors. MethodsOne hundred sixty-three sedentary women were recruited through advertisements in local newspapers. Of them, 154 sedentary (exercise-induced energy expenditure Ͻ60 minutes/wk) women, aged 34 to 66 years, were chosen as subjects after they met the following criteria for high-risk obesity phenotype: (1) BMI Ն25 kg/m 2 with CHD risk factors that require weight reduction for their improvement or (2) high-risk obesity as specified by an excess of intra-abdominal fat, in which intra-abdominal fat area of 100 cm 2 was used as a cut-point for high-risk obesity by using a CT scan. 18 We excluded 15 subjects who smoked, had concomitant renal, hepatic, or cardiac disease or diabetes (defined as a 2-hour postload glycemia Ն200...

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“…Resting energy expenditure (REE) was measured by indirect calorimetry (Deltratrac, Datex, Helsinki, Finland). 10 Blood samples were taken from an antecubital vein, and leptin assay was performed by a commercial radioimmunoassay (Linco Research, St Louis, MO). 11 Preferences for sugar and fat were determined by three consecutively performed hedonic tests.…”

Section: Methodsmentioning

confidence: 99%

Serum leptin, food intake and preferences for sugar and fat in obese women

et al. 1998

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OBJECTIVE: To examine the association of leptin with food intake and preferences for sugar and fat in obese humans. METHOD: Food intake and preferences for sugar and fat were measured in 35 obese women by a four-day food record and three hedonic tests, respectively. RESULTS: High fasting serum leptin concentration adjusted for body fat mass and dietary underreporting was associated with low dietary energy and fat intakes. In addition, trends towards lower preference for chocolate as well as for the taste of high-fat, low-sugar mixture were observed in those with higher leptin concentration. CONCLUSION: High serum leptin concentration could be associated in obese women with lower dietary energy and fat intakes, and possibly with the lower preference for fat. These ®ndings need to be veri®ed in further human studies.

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Determinants of resting energy expenditure in obese non-diabetic caucasian women

Cited by 35 publications

References 32 publications

The prediction of resting energy expenditure in type 2 diabetes mellitus is improved by factoring for glycemia

The prediction of resting energy expenditure in type 2 diabetes mellitus is improved by factoring for glycemia

Regional Body Composition Changes Exhibit Opposing Effects on Coronary Heart Disease Risk Factors

Serum leptin, food intake and preferences for sugar and fat in obese women

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