Literature DB >> 12197995

Predicting total energy expenditure from self-reported dietary records and physical characteristics in adult and elderly men and women.

James L Seale1.   

Abstract

BACKGROUND: Energy requirements and nutrient intakes are commonly estimated from self-reported dietary records, but such estimation has proven to be unreliable. When energy intakes determined from dietary records are compared with energy expenditures measured with the use of doubly labeled water, the former consistently underestimate energy requirements and have a high degree of variability.
OBJECTIVE: The objective of this study was to reduce the bias and variability of self-reported dietary records through the use of stepwise multiple regression analysis to develop models that relate energy expenditure measured with the use of doubly labeled water to energy intake from dietary records, sex, and fat-free mass (or weight and height).
DESIGN: Data from 54 healthy adult men and women were used to develop these models.
RESULTS: Fat-free mass, energy intake, and sex accounted for 86% of the variability in energy expenditure, whereas energy intake, sex, height, and weight accounted for 83%. When the model relating fat-free mass, energy intake, and sex to energy expenditure was tested on published data, it reduced the bias and variability of self-reported dietary records from -17 +/- 27% to 3 +/- 16%. When the model relating energy intake, sex, weight, and height to energy expenditure was tested on published data, it reduced the bias and variability of self-reported dietary records from -19 +/- 25% to -0.3 +/- 19%.
CONCLUSION: Results from this study indicate that a simple relation can be used to correct self-reported dietary records to estimated energy requirements.

Entities:  

Mesh:

Year:  2002        PMID: 12197995     DOI: 10.1093/ajcn/76.3.529

Source DB:  PubMed          Journal:  Am J Clin Nutr        ISSN: 0002-9165            Impact factor:   7.045


  5 in total

1.  [Basal metabolic rate and energy expenditure in the elderly].

Authors:  P Platte; J Hellhammer; J Zimmer; K M Pirke
Journal:  Z Gerontol Geriatr       Date:  2004-10       Impact factor: 1.281

2.  Investigating sex differences in the accuracy of dietary assessment methods to measure energy intake in adults: a systematic review and meta-analysis.

Authors:  Briar L McKenzie; Daisy H Coyle; Joseph Alvin Santos; Tracy Burrows; Emalie Rosewarne; Sanne A E Peters; Cheryl Carcel; Lindsay M Jaacks; Robyn Norton; Clare E Collins; Mark Woodward; Jacqui Webster
Journal:  Am J Clin Nutr       Date:  2021-05-08       Impact factor: 7.045

3.  The usefulness of an accelerometer for monitoring total energy expenditure and its clinical application for predicting body weight changes in type 2 diabetic korean women.

Authors:  Ji Yeon Jung; Kyung Ah Han; Hwi Ryun Kwon; Hee Jung Ahn; Jae Hyuk Lee; Kang Seo Park; Kyung Wan Min
Journal:  Korean Diabetes J       Date:  2010-12-31

4.  An easy approach to calculating estimated energy requirements.

Authors:  Shirley Gerrior; Wenyen Juan; Peter Basiotis
Journal:  Prev Chronic Dis       Date:  2006-09-15       Impact factor: 2.830

5.  Development and Validation of the General Dietary Behavior Inventory (GDBI) in Scope of International Nutrition Guidelines.

Authors:  Gerrit Engelmann; Matthias Marsall; Eva-Maria Skoda; Nadja Knoll-Pientka; Laura Bäuerle; Nanette Stroebele-Benschop; Martin Teufel; Alexander Bäuerle
Journal:  Nutrients       Date:  2021-04-17       Impact factor: 5.717

  5 in total

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