Literature DB >> 25656531

Invited commentary: Dietary misreporting as a potential source of bias in diet-disease associations: future directions in nutritional epidemiology research.

Michelle A Mendez.   

Abstract

Error and bias in self-reported intakes make estimating relationships among dietary factors, obesity, and related health outcomes a complex challenge in observational studies. In the absence of measures that can be applied in calibration adjustments of dietary data, simple methods to identify persons who misreport their intakes have been used to assess the impact of screening out reports characterized by energy intakes that are implausible when compared with estimated energy needs. Sensitivity analyses in cross-sectional studies have shown these methods to yield more plausible associations between diet and obesity, but few longitudinal studies have evaluated this approach. In this issue of the Journal, findings reported by Rhee et al. (Am J Epidemiol. 2015;181(4):237) underscore the need for caution in drawing conclusions on how self-reported diet may influence such outcomes based on cross-sectional associations but suggest that this approach might have little impact on the more credible associations derived from prospective analyses. However, other prospective studies have found that diet-disease relationships emerge or are substantially strengthened with the use of calibration adjustments using recovery biomarkers. To better understand the influence of diet on obesity-related health outcomes, efforts to reduce dietary measurement error through improved collection, evaluation, and analysis of consumption data are still urgently needed.
© The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  body mass index; energy intake; implausible reporting; measurement error

Mesh:

Substances:

Year:  2015        PMID: 25656531     DOI: 10.1093/aje/kwu306

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  6 in total

1.  Rhee and Willett respond to "dietary misreporting".

Authors:  Jinnie J Rhee; Walter C Willett
Journal:  Am J Epidemiol       Date:  2015-02-05       Impact factor: 4.897

2.  Dietary underreporting in women affected by polycystic ovary syndrome: A pilot study.

Authors:  Rachele De Giuseppe; Valentina Braschi; David Bosoni; Ginevra Biino; Fatima C Stanford; Rossella E Nappi; Hellas Cena
Journal:  Nutr Diet       Date:  2018-08-05       Impact factor: 2.333

3.  Objective Biomarkers for Total Added Sugar Intake - Are We on a Wild Goose Chase?

Authors:  Jimmy Chun Yu Louie
Journal:  Adv Nutr       Date:  2020-11-16       Impact factor: 8.701

4.  Comparison of Methods Used to Correct Self-Reported Protein Intake for Systematic Variation in Reported Energy Intake Using Quantitative Biomarkers of Dietary Intake.

Authors:  Amy L Korth; Surabhi Bhutani; Marian L Neuhouser; Shirley A Beresford; Linda Snetselaar; Lesley F Tinker; Dale A Schoeller
Journal:  J Nutr       Date:  2020-05-01       Impact factor: 4.798

5.  Assessments of risk of bias in systematic reviews of observational nutritional epidemiologic studies are often not appropriate or comprehensive: a methodological study.

Authors:  Dena Zeraatkar; Alana Kohut; Arrti Bhasin; Rita E Morassut; Isabella Churchill; Arnav Gupta; Daeria Lawson; Anna Miroshnychenko; Emily Sirotich; Komal Aryal; Maria Azab; Joseph Beyene; Russell J de Souza
Journal:  BMJ Nutr Prev Health       Date:  2021-12-07

Review 6.  Mobile Ecological Momentary Diet Assessment Methods for Behavioral Research: Systematic Review.

Authors:  Susan M Schembre; Yue Liao; Sydney G O'Connor; Melanie D Hingle; Shu-En Shen; Katarina G Hamoy; Jimi Huh; Genevieve F Dunton; Rick Weiss; Cynthia A Thomson; Carol J Boushey
Journal:  JMIR Mhealth Uhealth       Date:  2018-11-20       Impact factor: 4.773

  6 in total

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