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Predictive equations for estimating resting energy expenditure in women with overweight and obesity at three postpartum stages.

Authors :
Halland Nesse S
Ottestad I
Winkvist A
Bertz F
Ellegård L
Brekke HK
Source :
Journal of nutritional science [J Nutr Sci] 2020 Aug 07; Vol. 9, pp. e31. Date of Electronic Publication: 2020 Aug 07 (Print Publication: 2020).
Publication Year :
2020

Abstract

The objective was to investigate which predictive equations provide the best estimates of resting energy expenditure (REE) in postpartum women with overweight and obesity. Lactating women with overweight or obesity underwent REE measurement by indirect calorimetry, and fat-free mass (FFM) was assessed by dual-energy X-ray absorptiometry at three postpartum stages. Predictive equations based on body weight and FFM were obtained from the literature. Performance of the predictive equations were analysed as the percentage of women whose REE was accurately predicted, defined as a predicted REE within ±10 % of measured REE. REE data were available for women at 10 weeks ( n 71), 24 weeks ( n 64) and 15 months ( n 57) postpartum. Thirty-six predictive equations (twenty-five weight-based and eleven FFM-based) were validated. REE was accurately predicted in ≥80 % of women at all postpartum visits by six predictive equations (two weight-based and four FFM-based). The weight-based equation with the highest performance was that of Henry (weight, height, age 30-60 years) (Henry <subscript>WH30-60</subscript> ), with an overall mean of 83 % accurate predictions. The Henry <subscript>WH30-60</subscript> equation was highly suitable for predicting REE at all postpartum visits (irrespective of the women's actual age), and the performance was sustained across changes in weight and lactation status. No FFM-based equation was remarkably superior to Henry <subscript>WH30-60</subscript> for the total postpartum period.<br /> (© The Author(s) 2020.)

Details

Language :
English
ISSN :
2048-6790
Volume :
9
Database :
MEDLINE
Journal :
Journal of nutritional science
Publication Type :
Academic Journal
Accession number :
32913643
Full Text :
https://doi.org/10.1017/jns.2020.16