Application of a new statistical model for measurement error to the evaluation of dietary self-report instruments

Freedman, LS; Midthune, D; Carroll, RJ; Commins, JM; Arab, L; Baer, DJ; Moler, JE; Moshfegh, AJ; Neuhouser, ML; Prentice, RL; Rhodes, D; Spiegelman, D; Subar, AF; Tinker, LF; Willett, W; Kipnis, V

Application of a new statistical model for measurement error to the evaluation of dietary self-report instruments

Freedman, LS Midthune, D Carroll, RJ

Commins, JM Arab, L Baer, DJ Moler, JE Moshfegh, AJ Neuhouser, ML Prentice, RL Rhodes, D Spiegelman, D Subar, AF Tinker, LF Willett, W Kipnis, V

Permalink

Publication Type:: Journal Article
Citation:: Epidemiology, 2015, 26 (6), pp. 925 - 933
Issue Date:: 2015-10-01

Closed Access

	Filename	Description	Size
	\\utsfs.adsroot.uts.edu.au\homes\staff\108848\Desktop\nihms789907.pdf	Published Version	705.18 kB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Freedman, LS	en_US
dc.contributor.author	Midthune, D	en_US
dc.contributor.author	Carroll, RJ https://orcid.org/0000-0002-5465-9682	en_US
dc.contributor.author	Commins, JM	en_US
dc.contributor.author	Arab, L	en_US
dc.contributor.author	Baer, DJ	en_US
dc.contributor.author	Moler, JE	en_US
dc.contributor.author	Moshfegh, AJ	en_US
dc.contributor.author	Neuhouser, ML	en_US
dc.contributor.author	Prentice, RL	en_US
dc.contributor.author	Rhodes, D	en_US
dc.contributor.author	Spiegelman, D	en_US
dc.contributor.author	Subar, AF	en_US
dc.contributor.author	Tinker, LF	en_US
dc.contributor.author	Willett, W	en_US
dc.contributor.author	Kipnis, V	en_US
dc.date.issued	2015-10-01	en_US
dc.identifier.citation	Epidemiology, 2015, 26 (6), pp. 925 - 933	en_US
dc.identifier.issn	1044-3983	en_US
dc.identifier.uri	http://hdl.handle.net/10453/118354
dc.description.abstract	Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved. Most statistical methods that adjust analyses for dietary measurement error treat an individual's usual intake as a fixed quantity. However, usual intake, if defined as average intake over a few months, varies over time. We describe a model that accounts for such variation and for the proximity of biomarker measurements to self-reports within the framework of a meta-analysis, and apply it to the analysis of data on energy, protein, potassium, and sodium from a set of five large validation studies of dietary self-report instruments using recovery biomarkers as reference instruments. We show that this time-varying usual intake model fits the data better than the fixed usual intake assumption. Using this model, we estimated attenuation factors and correlations with true longer-term usual intake for single and multiple 24-hour dietary recalls (24HRs) and food frequency questionnaires (FFQs) and compared them with those obtained under the "fixed" method. Compared with the fixed method, the estimates using the time-varying model showed slightly larger values of the attenuation factor and correlation coefficient for FFQs and smaller values for 24HRs. In some cases, the difference between the fixed method estimate and the new estimate for multiple 24HRs was substantial. With the new method, while four 24HRs had higher estimated correlations with truth than a single FFQ for absolute intakes of protein, potassium, and sodium, for densities the correlations were approximately equal. Accounting for the time element in dietary validation is potentially important, and points toward the need for longer-term validation studies.	en_US
dc.relation.ispartof	Epidemiology	en_US
dc.relation.isbasedon	10.1097/EDE.0000000000000377	en_US
dc.subject.classification	Epidemiology	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Diet	en_US
dc.subject.mesh	Diet Surveys	en_US
dc.subject.mesh	Models, Statistical	en_US
dc.subject.mesh	Self Report	en_US
dc.subject.mesh	Biomarkers	en_US
dc.subject.mesh	Surveys and Questionnaires	en_US
dc.title	Application of a new statistical model for measurement error to the evaluation of dietary self-report instruments	en_US
dc.type	Journal Article
utslib.citation.volume	6	en_US
utslib.citation.volume	26	en_US
utslib.for	0104 Statistics	en_US
utslib.for	1117 Public Health and Health Services	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	closed_access
pubs.issue	6	en_US
pubs.publication-status	Published	en_US
pubs.volume	26	en_US

Abstract:

Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved. Most statistical methods that adjust analyses for dietary measurement error treat an individual's usual intake as a fixed quantity. However, usual intake, if defined as average intake over a few months, varies over time. We describe a model that accounts for such variation and for the proximity of biomarker measurements to self-reports within the framework of a meta-analysis, and apply it to the analysis of data on energy, protein, potassium, and sodium from a set of five large validation studies of dietary self-report instruments using recovery biomarkers as reference instruments. We show that this time-varying usual intake model fits the data better than the fixed usual intake assumption. Using this model, we estimated attenuation factors and correlations with true longer-term usual intake for single and multiple 24-hour dietary recalls (24HRs) and food frequency questionnaires (FFQs) and compared them with those obtained under the "fixed" method. Compared with the fixed method, the estimates using the time-varying model showed slightly larger values of the attenuation factor and correlation coefficient for FFQs and smaller values for 24HRs. In some cases, the difference between the fixed method estimate and the new estimate for multiple 24HRs was substantial. With the new method, while four 24HRs had higher estimated correlations with truth than a single FFQ for absolute intakes of protein, potassium, and sodium, for densities the correlations were approximately equal. Accounting for the time element in dietary validation is potentially important, and points toward the need for longer-term validation studies.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/118354