Biomarker-Based Methods and Study Designs to Calibrate Dietary Intake for Assessing Diet–Disease Associations. Issue 3 (14th December 2021)

• Record Type: Journal Article
• Authors: Huang, Ying; Zheng, Cheng; Tinker, Lesley F; Neuhouser, Marian L; Prentice, Ross L
• Is Part Of: Journal of nutrition. Volume 152:Issue 3(2022)
• Page Start: 899
• Page End: 906
• Publication Date: 2021-12-14
• Subjects: biomarker -- cardiovascular disease -- diet -- measurement error -- regression calibration -- study design; Nutrition -- Periodicals; Diet -- Periodicals; 613.205
• DOI: 10.1093/jn/nxab420
• Languages: English
• ISSNs: 0022-3166

Abstract

ABSTRACT: Background: Dietary biomarkers measured in biospecimens can play an important role in correcting for random and systematic measurement error in self-reported nutrient intake when assessing diet–disease associations. To date, high-quality biomarkers for calibrating self-reported dietary intake have only been developed for a few nutrients. Objectives: To investigate new study designs and regression calibration approaches for calibrating self-reported nutrient intake for use in disease association analyses. Methods: We studied 3 regression calibration approaches: 1 ) an existing approach built on a calibration cohort assuming the existence of an objective biomarker (i.e., biomarker with random independent measurement error), 2 ) a proposed approach using a biomarker development cohort, and 3 ) a proposed 2-stage approach using both cohorts. We conducted simulation studies to compare the performance of different study designs/methods for estimating diet–disease associations and applied suitable methods to examine the association of sodium and potassium intake with cardiovascular disease (CVD) risk in Women's Health Initiative cohorts. Results: Simulation studies showed that the first approach can lead to biased association estimation when the objective biomarker assumption is violated; the second and third proposed approaches obviate the need for such an objective biomarker. Precision for estimating the association depends critically on sample size of the biomarker development cohort and the strength of the self-reported nutrient intake. Analyses based on the second and third approaches support previously reported significant findings using the first approach about associations of the ratio of sodium to potassium intake with CVD risk while providing efficiency gain for some outcomes. Conclusions: Self-reported dietary intake needs to be calibrated for measurement error correction in diet–disease association analyses. When there are no existing objective biomarkers that can be used for calibration purpose, controlled feeding studies can be used to develop new biomarkers for use in calibration or can be used to calibrate self-reported dietary intake directly.