TY - JOUR
T1 - Nutritional Blood Concentration Biomarkers in the Hispanic Community Health Study/Study of Latinos
T2 - Measurement Characteristics and Power
AU - Boe, Lillian A.
AU - Mossavar-Rahmani, Yasmin
AU - Sotres-Alvarez, Daniela
AU - Daviglus, Martha L.
AU - Durazo-Arvizu, Ramon A.
AU - Thyagarajan, Bharat
AU - Kaplan, Robert C.
AU - Shaw, Pamela A.
N1 - Publisher Copyright:
© The Author(s) 2023. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved.
PY - 2023/8/1
Y1 - 2023/8/1
N2 - 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-reporting. As part of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) baseline visit (2008–2011), self-reported information on diet was collected from all participants (n = 16,415). The HCHS/SOL also included annual telephone follow-up, as well as a second (2014–2017) and third (2020–2023) clinic visit. Blood concentration biomarkers for carotenoids, tocopherols, retinol, vitamin B12, and folate were measured in a subset of participants (n = 476) as part of the Study of Latinos: Nutrition and Physical Activity Assessment Study (SOLNAS) (2010–2012). We examined the relationships among biomarker levels, self-reported intake, Hispanic/Latino background (Central American, Cuban, Dominican, Mexican, Puerto Rican, or South American), and other participant characteristics in this diverse cohort. We built regression calibration–based prediction equations for 10 nutritional biomarkers and used a simulation to study the power of detecting a diet-disease association in a multivariable Cox model using a predicted concentration level. Good statistical 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 inf luence of the measurement characteristics on the power to detect associations with health outcomes.
AB - 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-reporting. As part of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) baseline visit (2008–2011), self-reported information on diet was collected from all participants (n = 16,415). The HCHS/SOL also included annual telephone follow-up, as well as a second (2014–2017) and third (2020–2023) clinic visit. Blood concentration biomarkers for carotenoids, tocopherols, retinol, vitamin B12, and folate were measured in a subset of participants (n = 476) as part of the Study of Latinos: Nutrition and Physical Activity Assessment Study (SOLNAS) (2010–2012). We examined the relationships among biomarker levels, self-reported intake, Hispanic/Latino background (Central American, Cuban, Dominican, Mexican, Puerto Rican, or South American), and other participant characteristics in this diverse cohort. We built regression calibration–based prediction equations for 10 nutritional biomarkers and used a simulation to study the power of detecting a diet-disease association in a multivariable Cox model using a predicted concentration level. Good statistical 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 inf luence of the measurement characteristics on the power to detect associations with health outcomes.
KW - biomarkers
KW - diet
KW - measurement error
KW - prediction
KW - regression calibration
KW - study design
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U2 - 10.1093/aje/kwad109
DO - 10.1093/aje/kwad109
M3 - Article
C2 - 37116075
AN - SCOPUS:85166701545
SN - 0002-9262
VL - 192
SP - 1288
EP - 1303
JO - American journal of epidemiology
JF - American journal of epidemiology
IS - 8
ER -