Gender difference in the effect of body composition on energy metabolism

Dionne, Isabelle J.; Jp, Després; Bouchard, Claude; Tremblay, Angelo

doi:10.1038/sj.ijo.0800820

Cited by 44 publications

(30 citation statements)

References 23 publications

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“…The relationship of age and gender with metabolic rates disappeared after adjustment for fat mass and fat-free mass, except for SMR-8h. Similar results have been reported showing that the effect of age and gender on metabolic rates is mainly due to fat-free mass (Ravussin et al, 1986;Astrup et al, 1990;Cunningham, 1991;Nelson et al, 1992) and fat mass (Dionne et al, 1999).…”

Section: Discussionsupporting

confidence: 89%

Interindividual variability in sleeping metabolic rate in Japanese subjects

et al. 2007

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Introduction: Basal metabolic rate (BMR) or sleeping metabolic rate (SMR) is the largest component of total energy expenditure (EE). An accurate prediction of BMR or SMR is needed to accurately predict total EE or physical activity EE for each individual. However, large variability in BMR and SMR has been reported. Objectives: This study was designed to develop prediction equations using body size measurements for the estimation of both SMR and BMR and to compare the prediction errors with those in previous reports. Methods: We measured body size, height, weight and body composition (fat mass and fat-free mass) from skinfold thickness in adult Japanese men (n ¼ 71) and women (n ¼ 66). SMR was determined as the sum of EE during 8 h of sleep (SMR-8h) and minimum EE during 3 consecutive hours of sleep (SMR-3h) measured using two open-circuit indirect human calorimeters. BMR was determined using a human calorimeter or a mask and Douglas bag. Results: The study population ranged widely in age. The SMR/BMR ratio was 1.0170.09 (range 0.82-1.42) for SMR-8h and 0.9470.07 (range 0.77-1.23) for SMR-3h. The prediction equations for SMR accounted for a 3À5% larger variance with 2-3% smaller standard error of estimate (SEE) than the prediction equations for BMR. Discussion: SMR can be predicted more accurately than previously reported, which indicates that SMR interindividual variability is smaller than expected, at least for Japanese subjects. The prediction equations for SMR are preferable to those for BMR because the former exhibits a smaller prediction error than the latter.

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Section: Discussionsupporting

confidence: 89%

Interindividual variability in sleeping metabolic rate in Japanese subjects

et al. 2007

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“…Other studies report that FM is a more important contributor to REE in men. 21 In our ®nal model including FFM, FM and age the percentage of the variability in REE explained by these parameters was moderate (56% and 45% in women and men, respectively) and in the low range of what has been reported previously by others. 1 It should be noted that the range of FFM included in our population is less than that reported by other investigators, 9,26 which may have reduced the correlation coef®cient between FFM and REE.…”

Section: Discussionmentioning

confidence: 65%

Body composition and resting energy expenditure in humans: role of fat, fat-free mass and extracellular fluid

et al. 2000

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OBJECTIVE: The objective of this study was to determine whether there are independent effects of extracellular¯uid volume (ECF) and fat mass (FM) on resting energy expenditure (REE) relative to fat-free mass (FFM) in adult men and women. METHODS: Multiple linear regression analysis was used to relate REE, as determined by indirect calorimetry, to FFM and FM (measured using dual energy X-ray absorptiometry) and ECF (measured using bromide space andaor the radiosulfate washout space) in 153 women and 100 men with varying amounts of body fat. RESULTS: REE correlated signi®cantly with FFM and FM in women (r 0.65 and r 0.63, both P`0.001) and men (r 0.62 and r 0.48, both P`0.001, FFM and FM, respectively). In a multiple linear regression analysis FFM, FM and age signi®cantly contributed to the ability to predict REE in both genders. The models that were derived were not signi®cantly different between women and men. In women the contribution to REE from FM was easier to detect when FM was greater. Adjustment of FFM for ECF did not improve the relationship between FFM and REE. CONCLUSIONS: FFM, FM and age are signi®cant, independent predictors of REE in both men and women. Adjustment of FFM for ECF does not improve the ability of FFM to predict REE, which suggests that ECF is a highly integrated component of FFM in healthy adults. Expressing REE relative to FFM alone will introduce errors when lean and obese populations are compared.

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“…Other studies failed to demonstrate such a sex difference in the composition of weight loss (Ballor & Poehlman, 1994;Garrow & Summerbell, 1995;Dionne et al, 1999;Doucet et al, 2002), since changes in fat-free mass associated to diet and/or exercise were comparable between men and women. These conflicting findings are mainly attributable to the heterogeneity in experimental subjects, study design, exercise intensity and type, as well as intervention length between the present and the above-cited studies.…”

Section: Discussionmentioning

confidence: 96%

Changes in body composition, physical performance and cardiovascular risk factors after a 3-week integrated body weight reduction program and after 1-y follow-up in severely obese men and women

et al. 2005

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Objective: To investigate the short-and medium-term (ie, at 1-y follow-up) effects of a hospital-based body weight reduction (BWR) program lasting 3 weeks in severely obese individuals. Design: Longitudinal, clinical intervention study entailing energy-restricted diet, tailored aerobic-strength exercise, psychological counselling and nutritional education during a 3-week period followed by 49 weeks of indirect supervision at home. Subjects: In all, 45 women and 19 men aged 30.277.2 y (mean7s.d.) with severe obesity (BMI: 41.374.3 kg/m 2 ), classified as weight losers (finaloinitial weight) and regainers (finalZinitial weight). Interventions: Body composition, physical performance and cardiovascular risk factors before and after the BWR program and at follow-up. Results: The large majority of the experimental subjects obtained a clinical success after the 1-y period, and the rate was higher in females (n ¼ 37/45, ie, 82.2%) than in males (n ¼ 11/19, ie, 57.9%). At follow-up, weight losers had higher percent fat-free mass, muscle strength, HDL-cholesterol and self-reported physical activity level and lower total cholesterol and glucose levels than weight regainers (Po0.05-0.01). Males displayed significantly larger fat-free mass losses than females at post-BWR and at follow-up. Conclusions: A 3-week hospital-based integrated BWR program resulted in a high rate of clinical success in severely obese individuals at 1-y follow-up (particularly in females), that was associated with increased levels of self-reported physical activity and improved muscle strength and lipid profile. Further research is needed to establish the long-term effects (ie, at 2-5 y) associated to this treatment.

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Gender difference in the effect of body composition on energy metabolism

Cited by 44 publications

References 23 publications

Interindividual variability in sleeping metabolic rate in Japanese subjects

Interindividual variability in sleeping metabolic rate in Japanese subjects

Body composition and resting energy expenditure in humans: role of fat, fat-free mass and extracellular fluid

Changes in body composition, physical performance and cardiovascular risk factors after a 3-week integrated body weight reduction program and after 1-y follow-up in severely obese men and women

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