  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.
