Application of a Repeat-Measure Biomarker Measurement Error Model to 2 Validation Studies: Examination of the Effect of Within-Person Variation in Biomarker Measurements

摘要

Repeat-biomarker measurement error models accounting for systematic correlated within-person error can benused to estimate the correlation coefficient (q) and deattenuation factor (k), used in measurement error correction.nThese models account for correlated errors in the food frequency questionnaire (FFQ) and the 24-hour diet recallnand random within-person variation in the biomarkers. Failure to account for within-person variation in biomarkersncan exaggerate correlated errors between FFQs and 24-hour diet recalls. For 2 validation studies, q and k werencalculated for total energy and protein density. In the Automated Multiple-Pass Method Validation Study (n ¼ 471),ndoubly labeled water (DLW) and urinary nitrogen (UN) were measured twice in 52 adults approximately 16 monthsnapart (2002–2003), yielding intraclass correlation coefficients of 0.43 for energy (DLW) and 0.54 for protein densityn(UN/DLW). The deattenuated correlation coefficient for protein density was 0.51 for correlation between the FFQnand the 24-hour diet recall and 0.49 for correlation between the FFQ and the biomarker. Use of repeat-biomarkernmeasurement error models resulted in a q of 0.42. These models were similarly applied to the Observing Proteinnand Energy Nutrition Study (1999–2000). In conclusion, within-person variation in biomarkers can be substantial,nand to adequately assess the impact of correlated subject-specific error, this variation should be assessed innvalidation studies of FFQs.