Abstract
Application of a New Statistical Model for Measurement Error to the Evaluation of Dietary Self-report Instruments
Highlights
An extensive literature exists on statistical methods for dealing with dietary measurement error
We describe our model within a meta-analysis framework, so as to apply it to data that come from the Validation Studies Pooling Project (VSPP),[6,7] comprising five large dietary validation studies that used recovery biomarkers.[7]
We have described a time-varying usual intake model for analyzing dietary validation data that incorporates different types of instrument and accounts for the relative timing of biomarker measurements to self-report instruments and the time between repeated measurements
Summary
An extensive literature exists on statistical methods for dealing with dietary measurement error. Most methods specify a model linking an individual’s self-reported intake to his/her true usual intake, which is treated as a fixed quantity.[1]. Consider the correlation with true usual intake of reported intakes from multiple 24-hour recalls (24HRs) taken over 2 weeks This correlation may vary according to whether usual intake is defined as the average over the month, 3 months, year, or several years that are proximal to the time of the recalls. The longer the usual intake period, the lower the expected correlation is between the report and usual intake This is because dietary intakes on any 2 days tend to be closer, the closer are the 2 days in time[2] (cyclical variations between weekdays and weekends and between seasons excepted). In the “Discussion” section, we discuss the implications of our results
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