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 and/or higher 24-RQ than Caucasians.

Subjects and methods: 916 non-diabetic subjects, aged 31.5 +/- 11.9 y, body weight 90.5 +/- 26.1 kg (mean +/- 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 significant independent determinants of 24-EE (2258 +/- 422 kcal/d), explaining 85% of its variability (24-EE (kcal/d)=696 + 18.9 FFM (kg) + 10.O FM (kg) + 180 male -1.9 age (y) + 7.1 WTR (per decimal) + 44 Pima Indian). SMR (1623 +/- 315kcal/d) was determined (78% of variability) by FFM, FM, sex, age, WTR, and glucose tolerance (SMR (kcal/d) = 443 +/- 14.6 FFM (kg) + 6.9 FM (kg) + 79 male - 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 kcal/d and in SMR from 315 to 146kcal/d. 24-RQ (0.854 +/- 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 confirms the previous findings 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.