Literature DB >> 10946797

Measurement of dietary intake in children.

M B Livingstone1, P J Robson.   

Abstract

When children and adolescents are the target population in dietary surveys many different respondent and observer considerations surface. The cognitive abilities required to self-report food intake include an adequately developed concept of time, a good memory and attention span, and a knowledge of the names of foods. From the age of 8 years there is a rapid increase in the ability of children to self-report food intake. However, while cognitive abilities should be fully developed by adolescence, issues of motivation and body image may hinder willingness to report. Ten validation studies of energy intake data have demonstrated that mis-reporting, usually in the direction of under-reporting, is likely. Patterns of under-reporting vary with age, and are influenced by weight status and the dietary survey method used. Furthermore, evidence for the existence of subject-specific responding in dietary assessment challenges the assumption that repeated measurements of dietary intake will eventually obtain valid data. Unfortunately, the ability to detect mis-reporters, by comparison with presumed energy requirements, is limited unless detailed activity information is available to allow the energy intake of each subject to be evaluated individually. In addition, high variability in nutrient intakes implies that, if intakes are valid, prolonged dietary recording will be required to rank children correctly for distribution analysis. Future research should focus on refining dietary survey methods to make them more sensitive to different ages and cognitive abilities. The development of improved techniques for identification of mis-reporters and investigation of the issue of differential reporting of foods should also be given priority.

Entities:  

Mesh:

Year:  2000        PMID: 10946797     DOI: 10.1017/s0029665100000318

Source DB:  PubMed          Journal:  Proc Nutr Soc        ISSN: 0029-6651            Impact factor:   6.297


  187 in total

1.  Contribution of beverages to energy, macronutrient and micronutrient intake of third- and fourth-grade schoolchildren in Quetzaltenango, Guatemala.

Authors:  Gabriela Montenegro-Bethancourt; Marieke Vossenaar; Colleen M Doak; Noel W Solomons
Journal:  Matern Child Nutr       Date:  2010-04       Impact factor: 3.092

2.  Beverage consumption among European adolescents in the HELENA study.

Authors:  K J Duffey; I Huybrechts; T Mouratidou; L Libuda; M Kersting; T De Vriendt; F Gottrand; K Widhalm; J Dallongeville; L Hallström; M González-Gross; S De Henauw; L A Moreno; B M Popkin
Journal:  Eur J Clin Nutr       Date:  2011-09-28       Impact factor: 4.016

3.  Self-reported vs. actual energy intake in youth with and without loss of control eating.

Authors:  Laura E Wolkoff; Marian Tanofsky-Kraff; Lauren B Shomaker; Merel Kozlosky; Kelli M Columbo; Camden A Elliott; Lisa M Ranzenhofer; Robyn L Osborn; Susan Z Yanovski; Jack A Yanovski
Journal:  Eat Behav       Date:  2010-09-18

Review 4.  How to engage children in self-administered dietary assessment programmes.

Authors:  A S Lu; J Baranowski; N Islam; T Baranowski
Journal:  J Hum Nutr Diet       Date:  2012-05-18       Impact factor: 3.089

5.  Banning all sugar-sweetened beverages in middle schools: reduction of in-school access and purchasing but not overall consumption.

Authors:  Daniel R Taber; Jamie F Chriqui; Lisa M Powell; Frank J Chaloupka
Journal:  Arch Pediatr Adolesc Med       Date:  2011-11-07

6.  Association of food parenting practice patterns with obesogenic dietary intake in Hispanic/Latino youth: Results from the Hispanic Community Children's Health Study/Study of Latino Youth (SOL Youth).

Authors:  Madison N LeCroy; Anna Maria Siega-Riz; Sandra S Albrecht; Dianne S Ward; Jianwen Cai; Krista M Perreira; Carmen R Isasi; Yasmin Mossavar-Rahmani; Linda C Gallo; Sheila F Castañeda; June Stevens
Journal:  Appetite       Date:  2019-05-04       Impact factor: 3.868

7.  Internet Based Obesity Prevention Program for Thai School Children- A Randomized Control Trial.

Authors:  Lakkana Rerksuppaphol; Sanguansak Rerksuppaphol
Journal:  J Clin Diagn Res       Date:  2017-03-01

8.  Three-year change in diet quality and associated changes in BMI among schoolchildren living in socio-economically disadvantaged neighbourhoods.

Authors:  Sandrine Lioret; Sarah A McNaughton; Adrian J Cameron; David Crawford; Karen J Campbell; Verity J Cleland; Kylie Ball
Journal:  Br J Nutr       Date:  2014-04-28       Impact factor: 3.718

9.  Water fluoridation and the association of sugar-sweetened beverage consumption and dental caries in Australian children.

Authors:  Jason M Armfield; A John Spencer; Kaye F Roberts-Thomson; Katrina Plastow
Journal:  Am J Public Health       Date:  2013-01-17       Impact factor: 9.308

10.  Tracking of dietary intakes in early childhood: the Melbourne InFANT Program.

Authors:  S Lioret; S A McNaughton; A C Spence; D Crawford; K J Campbell
Journal:  Eur J Clin Nutr       Date:  2013-01-16       Impact factor: 4.016

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.