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Quantifying energy expenditure in childhood: utility in managing pediatric metabolic disorders

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 cond...

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Autores principales: Watson, Laura P E, Carr, Katherine S, Venables, Michelle C, Acerini, Carlo L, Lyons, Greta, Moran, Carla, Murgatroyd, Peter R, Chatterjee, Krishna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6821543/
https://www.ncbi.nlm.nih.gov/pubmed/31410443
http://dx.doi.org/10.1093/ajcn/nqz177
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author Watson, Laura P E
Carr, Katherine S
Venables, Michelle C
Acerini, Carlo L
Lyons, Greta
Moran, Carla
Murgatroyd, Peter R
Chatterjee, Krishna
author_facet Watson, Laura P E
Carr, Katherine S
Venables, Michelle C
Acerini, Carlo L
Lyons, Greta
Moran, Carla
Murgatroyd, Peter R
Chatterjee, Krishna
author_sort Watson, Laura P E
collection PubMed
description 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 (R(2) = 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.
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spelling pubmed-68215432019-11-06 Quantifying energy expenditure in childhood: utility in managing pediatric metabolic disorders Watson, Laura P E Carr, Katherine S Venables, Michelle C Acerini, Carlo L Lyons, Greta Moran, Carla Murgatroyd, Peter R Chatterjee, Krishna Am J Clin Nutr Original Research Communications 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 (R(2) = 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. Oxford University Press 2019-11 2019-08-13 /pmc/articles/PMC6821543/ /pubmed/31410443 http://dx.doi.org/10.1093/ajcn/nqz177 Text en Copyright © American Society for Nutrition 2019. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research Communications
Watson, Laura P E
Carr, Katherine S
Venables, Michelle C
Acerini, Carlo L
Lyons, Greta
Moran, Carla
Murgatroyd, Peter R
Chatterjee, Krishna
Quantifying energy expenditure in childhood: utility in managing pediatric metabolic disorders
title Quantifying energy expenditure in childhood: utility in managing pediatric metabolic disorders
title_full Quantifying energy expenditure in childhood: utility in managing pediatric metabolic disorders
title_fullStr Quantifying energy expenditure in childhood: utility in managing pediatric metabolic disorders
title_full_unstemmed Quantifying energy expenditure in childhood: utility in managing pediatric metabolic disorders
title_short Quantifying energy expenditure in childhood: utility in managing pediatric metabolic disorders
title_sort quantifying energy expenditure in childhood: utility in managing pediatric metabolic disorders
topic Original Research Communications
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6821543/
https://www.ncbi.nlm.nih.gov/pubmed/31410443
http://dx.doi.org/10.1093/ajcn/nqz177
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