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

Objective: To develop new equations for the estimation of basal metabolic r ate in children aged 10-15 years, and to evaluate the impact of including p ubertal stage into the equations. Design: Mixed longitudinal. Setting: The children were recruited from schools in Oxford, and the measur ements were made in the schools. Subjects: 195 school children, aged 10-15 years, were recruited in three co horts. 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, bo dy breadths and skinfold measurements (biceps, triceps, subscapular, suprai liac and medial calf) were collected on each occasion. Fat and fat-free mas s was calculated from the skinfold measurements. Pubertal development was a lso assessed on annually by paediatricians. Pubic hair (PH) and gonad (G) d evelopment was assessed in boys and breast (B) development in girls. The gi rls were questioned about menarche. Stepwise multiple regression analysis w as used to develop and assess new formulae for BMR that also incorporate pu bertal development. Results: The mean BMR measured was 5.754 (s.d. 0.933) MJ/day (138 (s.d. 22) kJ/kg body wt/day) in the boys (n = 351) and 5.476 (s.d. 0.725) MJ/day (12 1 (s.d. 20) kJ/kg body wt/day) in the girls (n = 554). Weight was the most important facto; 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 a s 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 significantly (P < 0.05) improved BMR estimatio n in the pre-menarche girls. Boys, pubertal stage as assessed by Pubic Hair (PH) and Gonadal Stage (G) did not contribute to a significant improvement in BMR estimation, except for 11-year-olds. Conclusions: The inclusion of pubertal stage afforded only minor improvemen ts in the derivation of regression equations for the estimation of BMR of c hildren aged between 10 and 15 years. Sponsorship: Nestle Foundation, Lausanne, Switzerland.