Resting energy expenditure prediction using bioelectrical impedance analysis in patients with severe motor and intellectual disabilities

• Published in: Brain & development (Tokyo. 1979) Vol. 41; no. 4; pp. 352 - 358
• Main Authors: Hashizume, Naoki, Tanaka, Yoshiaki, Yoshida, Motomu, Fukahori, Suguru, Ishii, Shinji, Saikusa, Nobuyuki, Masui, Daisuke, Higashidate, Naruki, Sakamoto, Saki, Tsuruhisa, Shiori, Yuge, Kotaro, Ohya, Takashi, Yagi, Minoru, Yamashita, Yushiro
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.04.2019
• Subjects: Adult; Bioelectrical impedance analysis; Body Composition; Body Mass Index; Body Weight; Calorimetry, Indirect - methods; Electric Impedance; Energy Metabolism - physiology; Equation; Fat-free mass; Female; Forecasting - methods; Humans; Indirect calorimetry; Intellectual Disability - physiopathology; Linear Models; Male; Motor Activity - physiology; Predictive Value of Tests; Regression Analysis; Resting energy expenditure; Severe motor and intellectual disabilities; Young Adult; Fat-free mass; Equation; Bioelectrical impedance analysis; Severe motor and intellectual disabilities; Indirect calorimetry; Resting energy expenditure
• ISSN: 0387-7604; 1872-7131; 1872-7131
• DOI: 10.1016/j.braindev.2018.11.003

Resting energy expenditure (REE) is expected to be lower in with severe motor and intellectual disabilities (SMID) patients than in healthy subjects because of their relatively low fat-free mass (FFM). Therefore, an REE predictive equation for SMID patients may be required. The aim of this study was to validate existing REE predictive weight-based equations (Harris-Benedict, WHO, Mifflin, Owen, Schofield) and FFM-based REE equations (Mifflin, Owen and Cunningham) and to develop a new SMID patient-specific FFM-based REE equation. Twenty-eight (22 males, 6 females) SMID patients over 18 years of age were included. The REE was measured using indirect calorimetry. FFM were measured using bioelectrical impedance analysis. A multiple linear regression analysis was used to develop a new FFM-based REE predictive equation. The accurate predictions compared the measured REE and root mean square error. The median measured REE was 950 (25th,75th percentile:712.75, 1102.75) kcal/day. The new FFM-based equation was as follows: REE (kcal/day) = 550.62 + 16.62 FFM (kg). The new FFM-based REE resulted in the highest percentage of accurate predictions within 10% of measured REE (42.9%). The root mean square errors were the smallest for the new FFM-based REE and largest for Harris-Benedict (91.00 and 185.22 kcal/day). For SMID patients, the REE cannot accurately be predicted using the existing weight-based REE equations. Furthermore, the existing FFM-based REE equations are less accurate with regard to the measured REE than the new FFM-based REE equation. The new FFM-based equation is advised for use in SMID patients.