Predicting resting energy expenditure in people with chronic spinal cord injury

Study design Cross-sectional study. Objectives: The aims of this study were (1) to validate the two recently developed SCI-specific REE equations; (2) to develop new prediction equations to predict REE in a general population with SCI. Setting: University, the Netherlands. Methods: Forty-eight community-dwelling men and women with SCI were recruited (age: 18–75 years, time since injury: ≥12 months). Body composition was measured by dual-energy X-ray absorptiometry (DXA), single-frequency bioelectrical impedance analysis (SF-BIA) and skinfold thickness. REE was measured by indirect calorimetry. Personal and lesion characteristics were collected. SCI-specific REE equations by Chun et al. [1] and by Nightingale and Gorgey [2] were validated. New equations for predicting REE were developed using multivariate regression analysis. Results: Prediction equations by Chun et al. [1] and by Nightingale and Gorgey [2] significantly underestimated REE (Chun et al.: −11%; Nightingale and Gorgey: −11%). New equations were developed for predicting REE in the general population of people with SCI using FFM measured by SF-BIA and Goosey-Tolfrey et al. skinfold equation (R2 = 0.45–0.47; SEE = 200 kcal/day). The new equations showed proportional bias (p < 0.001) and wide limits of agreement (LoA, ±23%). Conclusions: Prediction equations by Chun et al. [1] and by Nightingale and Gorgey [2] significantly underestimated REE and showed large individual variations in a general population with SCI. The newly developed REE equations showed proportional bias and a wide LoA (±23%) which limit the predictive power and accuracy to predict REE in the general population with SCI. Alternative methods for measuring REE need to be investigated.