Determinants of energy expenditure and fuel utilization in man: effects of body composition, age, sex, ethnicity and glucose tolerance in 916 subjects

Abstract

BACKGROUND: 24-h energy expenditure (24-EE) and 24-h respiratory quotient (24-RQ) are important measurements in obesity research, but their accurate assessment is limited to few specialized laboratories. OBJECTIVES: 1) To provide comprehensive prediction equations for 24-EE, sleeping metabolic rate (SMR) and 24-RQ, based on a large number of Caucasian and Pima Indian subjects, covering a wide range of body weight and composition, body fat distribution, and age and 2) to test whether Pima Indians have lower metabolic rate andaor higher 24-RQ than Caucasians. SUBJECTS AND METHODS: 916 non-diabetic subjects, aged 31.5 AE 11.9 y, body weight 90.5 AE 26.1 kg (mean AE s.d.), (561 males, 355 females; 416 Caucasians, 500 Pima Indians; 720 with normal (NGT) and 196 with impaired (IGT) glucose tolerance) spent 24 h in a respiratory chamber for measurements of 24-EE, SMR and 24-RQ. Fat-free mass (FFM) and fat mass (FM) were assessed by either hydrodensitometry or DEXA. Waist circumference and waist-to-thigh ratio (WTR) were determined as measures of body fat distribution. RESULTS: In a stepwise multiple regression analysis, FFM, FM, sex, age, WTR, and ethnicity were signi®cant independent determinants of 24-EE (2258 AE 422 kcalad), explaining 85% of its variability (24-EE (kcalad) 696 18.9 FFM (kg) 10.0 FM (kg) 180 male 7 1.9 age (y) 7.1 WTR (per decimal) 44 Pima Indian). SMR (1623 AE 315 kcalad) was determined (78% of variability) by FFM, FM, sex, age, WTR, and glucose tolerance (SMR (kcalad) 443 14.6 FFM (kg) 6.9 FM (kg) 79 male 7 1.0 age (y) 5.8 WTR (per decimal) 38 IGT), but not by ethnicity. Adjustment for the respective variables reduced the variance in 24-EE from 422 to 162 kcalad and in SMR from 315 to 146 kcalad. 24-RQ (0.854 AE 0.026) was determined by waist circumference and energy balance (24-RQ 0.88429 ± 0.00175 waist circumference (cm) 0.00004 energy balance (%)), but not by sex, ethnicity or glucose tolerance. With this equation only 13% of the variability in 24-RQ could be explained (residual variance 0.024). Compared to Caucasians, Pima Indians had higher 24-EE, but similar SMR and 24-RQ. CONCLUSIONS: This analysis provides comprehensive prediction equations for 24-EE, SMR and 24-RQ from their major known determinants. It con®rms the previous ®ndings that, even after adjustment for body composition, age, sex, ethnicity, and glucose tolerance, there is still considerable variability in energy expenditure and substrate oxidation that may, in part, be genetically determined. In adult Pima Indians, we found no evidence for lower metabolic rate or impaired fat oxidation that could explain the propensity towards obesity in this ethnic group.

Interindividual variability in sleeping metabolic rate in Japanese subjects

“…Anthropometry, a relatively simpler technique used to predict RMR, has an accuracy rate similar to that of more complicated techniques (Van der Ploeg et al, 2001). In our equations, fatfree mass (measured using skinfold thickness) accounted for 84À89% of the variation in SMR, which is better than previously reported (Ravussin et al, 1990;Toubro et al, 1996;Weyer et al, 1999). In addition, results for the BMR equations are in good agreement with those of others (Cunningham, 1991;Ravussin and Bogardus, 1989;Tataranni and Ravussin, 1995).…”

“…In general, the reported interindividual CV is about 8À13% (Shetty et al, 1996, Muller et al, 2004. For our SMR equations, the SEE was much lower than the SEE reported by Weyer et al (1999), which was based on fat-free mass measured using sophisticated methods. In Weyer's equation, age, impaired glucose tolerance and waist-to-thigh ratio were additional predictors.…”

“…This study was performed to develop predictive equations for SMR-3h and SMR-8h that predict SMR with much lower prediction errors than previously reported (Tataranni and Ravussin, 1995;Weyer et al, 1999;Nielsen et al, 2000;Henry, 2005). The findings indicate that interindividual variability in SMR after adjustment for body size or body composition is much smaller than expected, at least in healthy Japanese adults.…”

“…These variations were much lower than reported in other studies. For example, although Weyer et al (1999) worked with subjects with a smaller age range than in this study, the s.d. values of their weights were 25.9 kg (male subjects) and 26.3 kg (female subjects).…”

Concept of fat balance in human obesity revisited with particular reference to de novo lipogenesis

“…In typical nutritional studies, fat balance is evaluated over 24 h (or more) using a respiration chamber to continuously measure energy expenditure and substrate oxidation. [1][2][3][4] Fat balance is closely linked to energy balance when considered over weeks and months. This means that continuous positive energy balance is essential to gain fat.…”