T J Cole1, C J K Henry. 1. Centre for Paediatric Epidemiology and Biostatistics, Institute of Child Health, London, UK. tim.cole@ich.ucl.ac.uk
Abstract
OBJECTIVE: To produce prediction equations for basal metabolic rate (BMR) derived from weight and height covering the age range from birth to old age. DESIGN: Cross-sectional data on BMR, sex, age, weight, height, ethnicity and measurement technique from the Oxford Brookes BMR database. SETTING: Worldwide. SUBJECTS: Data for 13,910 men, women and children from 174 papers published between 1914 and 2001. RESULTS: Absolute and proportional regression models were developed for each sex, showing a steep rise in predicted BMR with age until 15 years, more pronounced in males than females, then a gradual fall through adulthood. Predicted BMR increased by 6% and 1.4%, respectively, per standard deviation increase in weight and height. Predicted BMR in Caucasians was 4% higher than in non-Caucasians, though the effect size was sensitive to the inclusion or exclusion of data from certain influential publications. The effect of measurement technique on BMR, closed-circuit versus open-circuit, was small, near 1%. CONCLUSIONS: It is possible to develop prediction equations that avoid splitting the data into arbitrary age groups. Heterogeneity between publications is greater than might be expected by chance, probably due to undocumented differences in technique.
OBJECTIVE: To produce prediction equations for basal metabolic rate (BMR) derived from weight and height covering the age range from birth to old age. DESIGN: Cross-sectional data on BMR, sex, age, weight, height, ethnicity and measurement technique from the Oxford Brookes BMR database. SETTING: Worldwide. SUBJECTS: Data for 13,910 men, women and children from 174 papers published between 1914 and 2001. RESULTS: Absolute and proportional regression models were developed for each sex, showing a steep rise in predicted BMR with age until 15 years, more pronounced in males than females, then a gradual fall through adulthood. Predicted BMR increased by 6% and 1.4%, respectively, per standard deviation increase in weight and height. Predicted BMR in Caucasians was 4% higher than in non-Caucasians, though the effect size was sensitive to the inclusion or exclusion of data from certain influential publications. The effect of measurement technique on BMR, closed-circuit versus open-circuit, was small, near 1%. CONCLUSIONS: It is possible to develop prediction equations that avoid splitting the data into arbitrary age groups. Heterogeneity between publications is greater than might be expected by chance, probably due to undocumented differences in technique.
Authors: Amy L Korth; Surabhi Bhutani; Marian L Neuhouser; Shirley A Beresford; Linda Snetselaar; Lesley F Tinker; Dale A Schoeller Journal: J Nutr Date: 2020-05-01 Impact factor: 4.798
Authors: Nurshad Ali; Shakil Mahmood; M Manirujjaman; Rasheda Perveen; Abdullah Al Nahid; Shamim Ahmed; Farida Adib Khanum; Mustafizur Rahman Journal: BMC Public Health Date: 2017-07-25 Impact factor: 3.295