New equations to estimate basal metabolic rate in children aged 10–15 years

Abstract

Objective: To develop new equations for the estimation of basal metabolic rate in children aged 10 ± 15 years, and to evaluate the impact of including pubertal stage into the equations. Design: Mixed longitudinal. Setting: The children were recruited from schools in Oxford, and the measurements were made in the schools. Subjects: 195 school children, aged 10 ± 15 years, were recruited in three cohorts. The gender distribution of the subjects was 40% boys and 60% girls. Methods: Basal metabolic rate (BMR) was measured, by indirect calorimetry, at 6-monthly intervals for 3 years. Anthropometric data, height, weight, body breadths and skinfold measurements (biceps, triceps, subscapular, suprailiac and medial calf) were collected on each occasion. Fat and fat-free mass was calculated from the skinfold measurements. Pubertal development was also assessed on annually by paediatricians. Pubic hair (PH) and gonad (G) development was assessed in boys and breast (B) development in girls. The girls were questioned about menarche. Stepwise multiple regression analysis was used to develop and assess new formulae for BMR that also incorporate pubertal development. 554). Weight was the most important factor in developing the regression equations for the calculation of BMR in both sexes (R 2 0.61 and 0.52 for boys and girls, respectively). Stepwise multiple regression analyses, with independent variables such as gender, weight, height, puberty stage and skinfolds, allowed several BMR regression equations to be developed. The inclusion of the menarche status in the regression equations signi®cantly (P`0.05) improved BMR estimation in the pre-menarche girls. Boys, pubertal stage as assessed by Pubic Hair (PH) and Gonadal Stage (G) did not contribute to a signi®cant improvement in BMR estimation, except for 11-year-olds. Conclusions: The inclusion of pubertal stage afforded only minor improvements in the derivation of regression equations for the estimation of BMR of children aged between 10 and 15 years.

Dietary intakes assessed by 24-h recalls in peri-urban African adolescents: validity of energy intake compared with estimated energy expenditure

“…In 1985, Schofield et al noted that the inclusion of height had little effect on the estimation of BMR. This conclusion has been confirmed more recently and specifically for normal weight adolescents (Tverskaya et al, 1998;Henry et al, 1999;Rodriguez et al, 2000) and supports the use of the simpler BMR estimation equations, as has been carried out in other studies among adolescents (Vance et al, 2008). One known factor to affect BMR, but which is not accounted for by any of the published equations, is that of climate (Rodriguez et al, 2000).…”

“…The estimation of EE using published equations to calculate BMR (Henry et al, 1999) and physical activity factors (PAFs; Brooks et al, 2004) derived from simple physical activity questionnaires such as the Previous Day Physical Activity Recall (PDPAR; Trost et al, 1999) offers a feasible approach to validate reported EI in populations in resource-poor settings. The use of BMR estimation equations, however, is limited by the fact that equations derived for one population may not be applicable to a target population in a different environment (Tverskaya et al, 1998;Rodriguez et al, 2000).…”

“…This comparative approach may, however, merely show similar errors in both methods rather than relative validity. Another approach uses biomarkers such as plasma or serum levels of vitamins B6 and C and folate (Flood et al, 2004), 24-h urinary nitrogen excretion and EE (Gibson, 2005) to determine the validity of reported intakes, using specialised and expensive equipment (Henry et al, 1999). Although the determination of basal metabolic rate (BMR) and EE to calculate total daily EE by doubly labelled water is considered the most accurate method of validating reported EI (Schoeller, 1995), this method is costly and not always available in a field setting, especially in a resourcepoor country such as South Africa.…”

Mechanisms of changes in basal metabolism during ageing

“…Taken together these results illustrate à stable' BMR in homeotherms after they reach maturity. Holliday et al (1967) and Henry et al (1999).…”

The conceptual framework for estimating food energy requirement

“…The BMR of Indian men and women were found to be correctly predicted by the Schofield equations, independently of their nutritional status 33 . A later analysis found that Chinese children's BMR is correctly predicted 34 . The same is true for adult Ethiopian men and women 35,36 , and for Mexican men 37 .…”