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.
University, the Netherlands.
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.  and by Nightingale and Gorgey  were validated. New equations for predicting REE were developed using multivariate regression analysis.
Prediction equations by Chun et al.  and by Nightingale and Gorgey  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%).
Prediction equations by Chun et al.  and by Nightingale and Gorgey  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.
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The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.
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We thank Amsterdam University of Applied Sciences (Amsterdam Nutritional Assessment Center, DR. MEURERHUIS) and the rehabilitation center Reade in Amsterdam which has contributed to the organization of measurements. We thank China Scholarship Council (CSC) which has supported the PhD career of the corresponding author. We appreciate the cooperation of all the participants, the master students who helped with the measurements and Drs. Robert G. Memelink for providing DXA training and guidance.
The authors declare no competing interests.
This study was approved by the Medical Ethical Committee of Slotervaart hospital and Reade (NL64704.048.18).
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Ma, Y., de Groot, S., Hoevenaars, D. et al. Predicting resting energy expenditure in people with chronic spinal cord injury. Spinal Cord (2022). https://doi.org/10.1038/s41393-022-00827-5