Nutritional blood concentration biomarkers in the Hispanic Community Health Study/Study of Latinos: Measurement characteristics and power

TL;DR

This study evaluates the measurement properties of nutritional blood biomarkers in a diverse Hispanic/Latino cohort and assesses their potential to improve diet-disease association detection compared to self-reported data.

Contribution

It introduces regression calibration models for multiple nutritional biomarkers and analyzes their effectiveness in detecting diet-disease relationships.

Findings

High prediction accuracy for some nutrients with strong biomarkers

Power to detect diet-disease links varies by biomarker prediction quality

Blood biomarkers can mitigate self-report bias in dietary studies

Abstract

Measurement error is a major issue in self-reported diet that can distort diet-disease relationships. Use of blood concentration biomarkers has the potential to mitigate the subjective bias inherent in self-report. As part of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) baseline visit (2008-2011), self-reported diet was collected on all participants (N=16,415). Blood concentration biomarkers for carotenoids, tocopherols, retinol, vitamin B12 and folate were collected on a subset (N=476), as part of the Study of Latinos: Nutrition and Physical Activity Assessment Study (SOLNAS). We examine the relationship between biomarker levels, self-reported intake, Hispanic/Latino background, and other participant characteristics in this diverse cohort. We build regression calibration-based prediction equations for ten nutritional biomarkers and use a simulation to study the power of detecting a diet-disease association in a multivariable Cox model using a predicted concentration level. Good power was observed for some nutrients with high prediction model R2 values, but further research is needed to understand how best to realize the potential of these dietary biomarkers. This study provides a comprehensive examination of several nutritional biomarkers within the HCHS/SOL, characterizing their associations with subject characteristics and the influence of the measurement characteristics on the power to detect associations with health outcomes.