1. Quantifying energy expenditure in childhood: utility in managing pediatric metabolic disorders
- Author
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Carla Moran, Krishna Chatterjee, Carlo L. Acerini, Peter R. Murgatroyd, Laura Watson, Michelle C. Venables, Greta Lyons, Katherine S. Carr, Watson, Laura [0000-0002-2120-3531], Venables, Michelle [0000-0002-9380-0060], Chatterjee, Krishna [0000-0002-2654-8854], and Apollo - University of Cambridge Repository
- Subjects
Male ,Thyroid Hormone Resistance Syndrome ,medicine.medical_specialty ,Adolescent ,030309 nutrition & dietetics ,Population ,Medicine (miscellaneous) ,030209 endocrinology & metabolism ,Standard score ,resistance to thyroid hormone ,Prediabetic State ,03 medical and health sciences ,0302 clinical medicine ,Metabolic Diseases ,Internal medicine ,Linear regression ,Medicine ,Humans ,Resting energy expenditure ,education ,Child ,Dual-energy X-ray absorptiometry ,indirect calorimetry ,0303 health sciences ,education.field_of_study ,healthy boys and girls ,Nutrition and Dietetics ,medicine.diagnostic_test ,business.industry ,Metabolic disorder ,Thyroid ,medicine.disease ,Growth, Development, and Pediatrics ,Original Research Communications ,medicine.anatomical_structure ,resting energy expenditure prediction equations ,Cohort ,Body Composition ,Female ,Basal Metabolism ,business ,Energy Metabolism ,dual-energy X-ray absorptiometry - Abstract
Background Energy expenditure prediction equations are used to estimate energy intake based on general population measures. However, when using equations to compare with a disease cohort with known metabolic abnormalities, it is important to derive one's own equations based on measurement conditions matching the disease cohort. Objective We aimed to use newly developed prediction equations based on a healthy pediatric population to describe and predict resting energy expenditure (REE) in a cohort of pediatric patients with thyroid disorders. Methods Body composition was measured by DXA and REE was assessed by indirect calorimetry in 201 healthy participants. A prediction equation for REE was derived in 100 healthy participants using multiple linear regression and z scores were calculated. The equation was validated in 101 healthy participants. This method was applied to participants with resistance to thyroid hormone (RTH) disorders, due to mutations in either thyroid hormone receptor β or α (β: female n = 17, male n = 9; α: female n = 1, male n = 1), with deviation of REE in patients compared with the healthy population presented by the difference in z scores. Results The prediction equation for REE = 0.061 * Lean soft tissue (kg) − 0.138 * Sex (0 male, 1 female) + 2.41 (R2 = 0.816). The mean ± SD of the residuals is −0.02 ± 0.44 kJ/min. Mean ± SD REE z scores for RTHβ patients are −0.02 ± 1.26. z Scores of −1.69 and −2.05 were recorded in male (n = 1) and female ( n = 1) RTHα patients. Conclusions We have described methodology whereby differences in REE between patients with a metabolic disorder and healthy participants can be expressed as a z score. This approach also enables change in REE after a clinical intervention (e.g., thyroxine treatment of RTHα) to be monitored.
- Published
- 2019
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