BACKGROUND: Accurate prediction equations for estimating body composition and total energy expenditure (TEE) in children with severe neurologic impairment and intellectual disability are currently lacking. OBJECTIVE: The objective was to develop group-specific equations to predict body composition by using skinfold-thickness measurements and bioelectrical impedance analysis (BIA) and to predict TEE by using data on mobility, epilepsy, and muscle tone. DESIGN: Measures of body composition with the use of skinfold-thickness measurements (percentage of body fat) and BIA (total body water) were compared with those from isotope dilution (reference method) by using intraclass correlation coefficients (ICCs) and Bland and Altman limits of agreement analyses. With the use of the same methods, the outcomes of cerebral palsy-specific TEE equations were compared with those of the doubly labeled water method (reference method). Group-specific regression equations were developed by using forward-stepwise-multiple-correlation-regression analyses. RESULTS: Sixty-one children with a mean (±SD) age of 10.1 ± 4.3 y (32 boys) were studied. A new equation based on the sum of 4 skinfold-thickness measurements did not improve agreement (n = 49; ICC = 0.61), whereas the newly developed BIA equation-which includes tibia length as an alternative for standing height-did improve agreement (n = 61; ICC = 0.96, SEE = 1.7 kg, R(2) = 0.92). The newly developed TEE equation, which uses body composition, performed better (n = 52; ICC = 0.87, SEE = 180 kcal, R(2) = 0.77) than did the equation of Schofield (n = 52; ICC = 0.82, SEE = 207 kcal, R(2) = 0.69). CONCLUSIONS: Current cerebral palsy-specific equations for measuring body composition and energy expenditure are inaccurate. BIA is more accurate at assessing nutritional status in this population than is the measurement of skinfold thickness. The newly developed TEE equation, which uses body composition, provides a reasonable estimate of energy expenditure in these children despite its variability.
BACKGROUND: Accurate prediction equations for estimating body composition and total energy expenditure (TEE) in children with severe neurologic impairment and intellectual disability are currently lacking. OBJECTIVE: The objective was to develop group-specific equations to predict body composition by using skinfold-thickness measurements and bioelectrical impedance analysis (BIA) and to predict TEE by using data on mobility, epilepsy, and muscle tone. DESIGN: Measures of body composition with the use of skinfold-thickness measurements (percentage of body fat) and BIA (total body water) were compared with those from isotope dilution (reference method) by using intraclass correlation coefficients (ICCs) and Bland and Altman limits of agreement analyses. With the use of the same methods, the outcomes of cerebral palsy-specific TEE equations were compared with those of the doubly labeled water method (reference method). Group-specific regression equations were developed by using forward-stepwise-multiple-correlation-regression analyses. RESULTS: Sixty-one children with a mean (±SD) age of 10.1 ± 4.3 y (32 boys) were studied. A new equation based on the sum of 4 skinfold-thickness measurements did not improve agreement (n = 49; ICC = 0.61), whereas the newly developed BIA equation-which includes tibia length as an alternative for standing height-did improve agreement (n = 61; ICC = 0.96, SEE = 1.7 kg, R(2) = 0.92). The newly developed TEE equation, which uses body composition, performed better (n = 52; ICC = 0.87, SEE = 180 kcal, R(2) = 0.77) than did the equation of Schofield (n = 52; ICC = 0.82, SEE = 207 kcal, R(2) = 0.69). CONCLUSIONS: Current cerebral palsy-specific equations for measuring body composition and energy expenditure are inaccurate. BIA is more accurate at assessing nutritional status in this population than is the measurement of skinfold thickness. The newly developed TEE equation, which uses body composition, provides a reasonable estimate of energy expenditure in these children despite its variability.
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