title: Modeling energy expenditure in children and adolescents using quantile regression.
abstract: 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.
authors: Department of Epidemiology and Biostatistics, Drexel University, Philadelphia, Pennsylvania, USA.
authors: Yunwen
authors: Y
authors: Yang
authors: Anne L
authors: AL
authors: Adolph
authors: Maurice R
authors: MR
authors: Puyau
authors: Firoz A
authors: FA
authors: Vohra
authors: Nancy F
authors: NF
authors: Butte
authors: Issa F
authors: IF
authors: Zakeri
mesh_terms: D061725:Accelerometry / Q000379:methods; D000293:Adolescent; D001835:Body Weight / Q000502:physiology; D002153:Calorimetry, Indirect / Q000379:methods; D002648:Child; D002675:Child, Preschool; D003430:Cross-Sectional Studies; D004734:Energy Metabolism / Q000502:physiology*; D005260:Female; D006339:Heart Rate / Q000502:physiology; D006801:Humans; D008297:Male; D009043:Motor Activity / Q000502:physiology; D009765:Obesity / Q000503:physiopathology; D014851:Wakefulness / Q000502:physiology
keywords: accelerometry; childhood; energy expenditure; heart rate; obesity; physical activity; quantile regression
references: BMC Med Res Methodol. 2012 Dec 13;12:185
references: 23234603
references: J Nutr. 2006 May;136(5):1371-6
references: 16614432
references: J Appl Physiol (1985). 2008 Jun;104(6):1665-73
references: 18403453
references: Pediatrics. 1998 Mar;101(3 Pt 2):505-18
references: 12224657
references: Med Sci Sports Exerc. 2002 Feb;34(2):350-5
references: 11828247
references: Hum Nutr Clin Nutr. 1985;39 Suppl 1:42-91
references: 3900006
references: Med Sci Sports Exerc. 2012 Jan;44(1 Suppl 1):S5-12
references: 22157774
references: J Physiol. 1949 Aug;109(1-2):1-9
references: 15394301
references: J Clin Epidemiol. 2009 May;62(5):511-7.e1
references: 19135859
references: Am J Epidemiol. 2009 Jul 1;170(1):72-9
references: 19439580
references: Int J Obes Relat Metab Disord. 2003 Jul;27(7):834-9
references: 12821970
references: Adv Data. 2000 Jun 8;(314):1-27
references: 11183293
references: Epidemiology. 2011 Nov;22(6):859-66
references: 21968775