Literature DB >> 26220569

Plausible self-reported dietary intakes in a residential facility are not necessarily reliable.

S Whybrow1, R J Stubbs1,2, A M Johnstone1, L M O'Reilly1, Z Fuller1, M B E Livingstone3, G W Horgan4.   

Abstract

BACKGROUND/
OBJECTIVES: Comparing reported energy intakes with estimated energy requirements as multiples of basal metabolic rate (Ein:BMR) is an established method of identifying implausible food intake records. The present study aimed to examine the validity of self-reported food intakes believed to be plausible. SUBJECTS/
METHODS: One hundred and eighty men and women were provided with all food and beverages for two consecutive days in a residential laboratory setting. Subjects self-reported their food and beverage intakes using the weighed food diary method (WDR). Investigators covertly measured subjects' actual consumption over the same period. Subjects also reported intakes over four consecutive days at home. BMR was measured by indirect calorimetry.
RESULTS: Average reported energy intakes were significantly lower than actual intakes (11.2 and 11.8 MJ/d, respectively, P<0.001). Two-thirds (121) of the WDR were under-reported to varying degrees. Only five of these were considered as implausible using an Ein:BMR cut-off value of 1.03*BMR. Under-reporting of food and beverage intakes, as measured by the difference between reported and actual intake, was evident at all levels of Ein;BMR. Reported energy intakes were lower still (10.2 MJ/d) while subjects were at home.
CONCLUSIONS: Under-recording of self-reported food intake records was extensive but very few under-reported food intake records were identified as implausible using energy intake to BMR ratios. Under-recording was evident at all levels of energy intake.

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Year:  2015        PMID: 26220569     DOI: 10.1038/ejcn.2015.124

Source DB:  PubMed          Journal:  Eur J Clin Nutr        ISSN: 0954-3007            Impact factor:   4.016


  23 in total

1.  Critical evaluation of energy intake using the Goldberg cut-off for energy intake:basal metabolic rate. A practical guide to its calculation, use and limitations.

Authors:  A E Black
Journal:  Int J Obes Relat Metab Disord       Date:  2000-09

Review 2.  Critical evaluation of energy intake data using fundamental principles of energy physiology: 1. Derivation of cut-off limits to identify under-recording.

Authors:  G R Goldberg; A E Black; S A Jebb; T J Cole; P R Murgatroyd; W A Coward; A M Prentice
Journal:  Eur J Clin Nutr       Date:  1991-12       Impact factor: 4.016

3.  Assessment of selective under-reporting of food intake by both obese and non-obese women in a metabolic facility.

Authors:  S D Poppitt; D Swann; A E Black; A M Prentice
Journal:  Int J Obes Relat Metab Disord       Date:  1998-04

4.  Repeated measurement of habitual food intake increases under-reporting and induces selective under-reporting.

Authors:  A H Goris; E P Meijer; K R Westerterp
Journal:  Br J Nutr       Date:  2001-05       Impact factor: 3.718

5.  Predicting basal metabolic rate in the obese is difficult.

Authors:  G W Horgan; J Stubbs
Journal:  Eur J Clin Nutr       Date:  2003-02       Impact factor: 4.016

6.  Assessing dietary intake: Who, what and why of under-reporting.

Authors:  J Macdiarmid; J Blundell
Journal:  Nutr Res Rev       Date:  1998-12       Impact factor: 7.800

7.  Measurements of total energy expenditure provide insights into the validity of dietary measurements of energy intake.

Authors:  A E Black; A M Prentice; G R Goldberg; S A Jebb; S A Bingham; M B Livingstone; W A Coward
Journal:  J Am Diet Assoc       Date:  1993-05

8.  Urine nitrogen as an independent validatory measure of dietary intake: a study of nitrogen balance in individuals consuming their normal diet.

Authors:  S A Bingham; J H Cummings
Journal:  Am J Clin Nutr       Date:  1985-12       Impact factor: 7.045

9.  Estimating under-reporting of energy intake in dietary surveys using an individualised method.

Authors:  Kirsten L Rennie; Andy Coward; Susan A Jebb
Journal:  Br J Nutr       Date:  2007-04-16       Impact factor: 3.718

10.  Validity of U.S. nutritional surveillance:National Health and Nutrition Examination Survey caloric energy intake data, 1971-2010.

Authors:  Edward Archer; Gregory A Hand; Steven N Blair
Journal:  PLoS One       Date:  2013-10-09       Impact factor: 3.240

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  1 in total

1.  Statistical models for meal-level estimation of mass and energy intake using features derived from video observation and a chewing sensor.

Authors:  Xin Yang; Abul Doulah; Muhammad Farooq; Jason Parton; Megan A McCrory; Janine A Higgins; Edward Sazonov
Journal:  Sci Rep       Date:  2019-01-10       Impact factor: 4.379

  1 in total

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