Literature DB >> 12612176

Markers of the validity of reported energy intake.

M Barbara E Livingstone1, Alison E Black.   

Abstract

Energy intake (EI) is the foundation of the diet, because all other nutrients must be provided within the quantity of food needed to fulfill the energy requirement. Thus if total EI is underestimated, it is probable that the intakes of other nutrients are also underestimated. Under conditions of weight stability, EI equals energy expenditure (EE). Because at the group level weight may be regarded as stable in the timescale of a dietary assessment, the validity of reported EI can be evaluated by comparing it with either measured EE or an estimate of the energy requirement of the population. This paper provides the first comprehensive review of studies in which EI was reported and EE was measured using the doubly labeled water technique. These conclusively demonstrate widespread bias to the underestimation of EI. Because energy requirements of populations or individuals can be conveniently expressed as multiples of the basal metabolic rate (BMR), EE:BMR, reported EI may also be expressed as EI:BMR for comparison. Values of EI:BMR falling below the 95% confidence limit of agreement between these two measures signify the presence of underreporting. A formula for calculating the lower 95% confidence limit was proposed by Goldberg et al. (the Goldberg cutoff). It has been used by numerous authors to identify individual underreporters in different dietary databases to explore the variables associated with underreporting. These studies are also comprehensively reviewed. They explore the characteristics of underreporters and the biases in estimating nutrient intake and in describing meal patterns associated with underreporting. This review also examines some of the problems for the interpretation of data introduced by underreporting and particularly by variable underreporting across subjects. Future directions for research are identified.

Entities:  

Mesh:

Substances:

Year:  2003        PMID: 12612176     DOI: 10.1093/jn/133.3.895S

Source DB:  PubMed          Journal:  J Nutr        ISSN: 0022-3166            Impact factor:   4.798


  265 in total

Review 1.  The control of food intake of free-living humans: putting the pieces back together.

Authors:  John M de Castro
Journal:  Physiol Behav       Date:  2010-05-05

2.  A Sensor System for Automatic Detection of Food Intake Through Non-Invasive Monitoring of Chewing.

Authors:  Edward S Sazonov; Juan M Fontana
Journal:  IEEE Sens J       Date:  2012       Impact factor: 3.301

3.  Prospective association between body composition, physical activity and energy intake in young adults.

Authors:  C Drenowatz; B Cai; G A Hand; P T Katzmarzyk; R P Shook; S N Blair
Journal:  Eur J Clin Nutr       Date:  2015-08-19       Impact factor: 4.016

4.  Accuracy of self-reported energy intake in weight-restored patients with anorexia nervosa compared with obese and normal weight individuals.

Authors:  Janet E Schebendach; Kathleen J Porter; Carla Wolper; B Timothy Walsh; Laurel E S Mayer
Journal:  Int J Eat Disord       Date:  2012-01-23       Impact factor: 4.861

5.  Secular trends in regional differences in nutritional biomarkers and self-reported dietary intakes among American adults: National Health and Nutrition Examination Survey (NHANES) 1988-1994 to 2009-2010.

Authors:  Ashima K Kant; Barry I Graubard
Journal:  Public Health Nutr       Date:  2018-01-10       Impact factor: 4.022

6.  Associations between a posteriori defined dietary patterns and bone mineral density in adolescents.

Authors:  Teresa Monjardino; Raquel Lucas; Elisabete Ramos; Carla Lopes; Rita Gaio; Henrique Barros
Journal:  Eur J Nutr       Date:  2014-05-08       Impact factor: 5.614

7.  Diet quality and feelings of worry, sadness or unhappiness in Canadian children.

Authors:  Seanna E McMartin; Noreen D Willows; Ian Colman; Arto Ohinmaa; Kate Storey; Paul J Veugelers
Journal:  Can J Public Health       Date:  2013-07-25

Review 8.  The neuropathology of obesity: insights from human disease.

Authors:  Edward B Lee; Mark P Mattson
Journal:  Acta Neuropathol       Date:  2013-10-06       Impact factor: 17.088

9.  Carbon and nitrogen stable isotope ratios predict intake of sweeteners in a Yup'ik study population.

Authors:  Sarah H Nash; Alan R Kristal; Andrea Bersamin; Scarlett E Hopkins; Bert B Boyer; Diane M O'Brien
Journal:  J Nutr       Date:  2012-12-19       Impact factor: 4.798

10.  Adherence and weight loss outcomes associated with food-exercise diary preference in a military weight management program.

Authors:  Laura E Shay; Diane Seibert; Dorraine Watts; Tracy Sbrocco; Claire Pagliara
Journal:  Eat Behav       Date:  2009-07-16
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.