A Comparison of Commonly Used Prediction Equations for Estimating Resting Metabolic Rate in Adults With Down Syndrome.
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| Title: | A Comparison of Commonly Used Prediction Equations for Estimating Resting Metabolic Rate in Adults With Down Syndrome. |
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| Authors: | Helsel, Brian C., Sherman, Joseph R., Bodde, Amy E., Washburn, Richard A., Ptomey, Lauren T. |
| Source: | Journal of Intellectual Disability Research. May2025, Vol. 69 Issue 5, p428-436. 9p. |
| Subjects: | Basal metabolism, Pearson correlation (Statistics), Down syndrome, Prediction models, Research funding, Academic medical centers, T-test (Statistics), Descriptive statistics, Lean body mass, Comparative studies, Regression analysis |
| Geographic Terms: | United States |
| Abstract: | Background: Resting metabolic rate (RMR), the energy required by the body at rest, is the largest part of total daily energy expenditure. Commonly used prediction equations may overestimate RMR in adults with Down syndrome (DS). The purpose of this study was to assess the equivalency of prediction equations for estimating RMR in adults with DS. Methods: Twenty‐five adults with DS (24 ± 5 years of age, 64% female) completed RMR assessments at an academic medical centre in the United States between November 2021 and July 2023. Measured RMR (kilocalories per day) was compared to estimated RMR from eight prediction equations using a null hypothesis significance (i.e., a paired t‐test) and equivalence (i.e., a two one‐sided test) tests. Bland–Altman plots, Pearson correlations and linear regressions were used to evaluate the bias between the measured and predicted RMR values. Results: Measured RMR in adults with DS was 1090 ± 136 kcal/day. Prediction equations overestimated RMR by 8 ± 16% (76 ± 165 kcal/day) to 45 ± 16% (488 ± 165 kcal/day) except for the Bernstein fat‐free mass equation which underestimated RMR by 0.2 ± 11.5% (8 ± 123 kcal/day) and was statistically equivalent to measured RMR in our sample (p = 0.027). Conclusions: The Bernstein fat‐free mass equation offers better accuracy in adults with DS than other RMR prediction equations, but the equation needs to be evaluated in larger, more diverse samples of adults with DS. [ABSTRACT FROM AUTHOR] |
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| Database: | Psychology and Behavioral Sciences Collection |
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