Advanced mathematical models have the potential to capture the complex metabolic and physiological processes that result in energy expenditure (EE). Study objective is to apply quantile regression (QR) to predict EE and determine quantile-dependent variation in covariate effects in nonobese and obese children. First, QR models will be developed to predict minute-by-minute awake EE at different quantile levels based on heart rate (HR) and physical activity (PA) accelerometry counts, and child characteristics of age, sex, weight, and height. Second, the QR models will be used to evaluate the covariate effects of weight, PA, and HR across the conditional EE distribution. QR and ordinary least squares (OLS) regressions are estimated in 109 children, aged 5–18 yr. QR modeling of EE outperformed OLS regression for both nonobese and obese populations. Average prediction errors for QR compared with OLS were not only smaller at the median τ = 0.5 (18.6 vs. 21.4%), but also substantially smaller at the tails of the distribution (10.2 vs. 39.2% at τ = 0.1 and 8.7 vs. 19.8% at τ = 0.9). Covariate effects of weight, PA, and HR on EE for the nonobese and obese children differed across quantiles (P < 0.05). The associations (linear and quadratic) between PA and HR with EE were stronger for the obese than nonobese population (P < 0.05). In conclusion, QR provided more accurate predictions of EE compared with conventional OLS regression, especially at the tails of the distribution, and revealed substantially different covariate effects of weight, PA, and HR on EE in nonobese and obese children.

Direct Link: https://doi.org/10.1152/japplphysiol.00295.2013

Journal: Journal of Applied Physiology. 2013 Jul 15;115(2):251-9

Keywords: children, energy expenditure, Heart Rate, obesity, Physical Activity, quantile regression,

Applications: Energy Expenditure,

CamNtech Reference: AH13041

Back to Search Results

UK & International customers

CamNtech Ltd.
Manor Farm
Fenstanton
Cambridgeshire
PE28 9JD, UK

US customers

CamNtech Inc.
630 Boerne Stage Airfield,
Boerne,
Texas 78006,
USA

Copyright

© 2021 CamNtech Ltd and CamNtech Inc

Company information

Registered in England No. 2221302
VAT No: GB486 3019 34


Privacy Policy