Ian Crandell1, Michelle Rockwell2,3, Phyllis Whitehead4,5, Kimberly Ferren Carter6, Alexandra Hanlon1. 1. Center for Biostatistics and Health Data Sciences, Virginia Polytechnic Institute and State University, Roanoke, Virginia, USA. 2. Family and Community Medicine, Carilion Clinic and Virginia Tech Carilion School of Medicine, Roanoke, Virginia, USA. 3. Fralin Life Sciences Institute, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA. 4. Department of Ethics and Palliative Medicine, Carilion Clinic, Roanoke, Virginia, USA. 5. Department of Medicine, Virginia Tech Carilion School of Medicine, Roanoke, Virginia, USA. 6. Department of Nursing Research and Evidence-based practice, Carilion Clinic, Roanoke, Virginia, USA.
Abstract
INTRODUCTION: With a well-established role in inflammation and immune function, vitamin D status has emerged as a potential factor for coronavirus disease-2019 (COVID-19). OBJECTIVE: The purpose of this study was to evaluate the moderating effect of race on the relationship between vitamin D status and the risk of COVID-19 test positivity, and to compare propensity score (PS) model results to those obtained from classical bivariate and multivariable models, which have primarily comprised the literature to date. METHODS: Electronic health record (EHR) data from TriNetX (unmatched n = 21,629; matched n = 16,602) were used to investigate the effect of vitamin D status, as measured by 25-hydroxyvitamin D [25(OH)D], on the odds of experiencing a positive COVID-19 test using multivariable logistic regression models with and without PS methodology. RESULTS: Having normal (≥ 30 ng/mL) versus inadequate 25(OH)D (< 30 ng/mL) was not associated with COVID-19 positivity overall (OR = 0.913, p = 0.18), in White individuals (OR = 0.920, p = 0.31), or in Black individuals (OR = 1.006, p = 0.96). When 25(OH)D was analyzed on a continuum, a 10 ng/mL increase in 25(OH)D lowered the odds of having a positive COVID-19 test overall (OR = 0.949, p = 0.003) and among White (OR = 0.935, p = 0.003), but not Black individuals (OR = 0.994, p = 0.75). CONCLUSIONS: Models which use weighting and matching methods resulted in smaller estimated effect sizes than models which do not use weighting or matching. These findings suggest a minimal protective effect of vitamin D status on COVID-19 test positivity in White individuals and no protective effect in Black individuals.
INTRODUCTION: With a well-established role in inflammation and immune function, vitamin D status has emerged as a potential factor for coronavirus disease-2019 (COVID-19). OBJECTIVE: The purpose of this study was to evaluate the moderating effect of race on the relationship between vitamin D status and the risk of COVID-19 test positivity, and to compare propensity score (PS) model results to those obtained from classical bivariate and multivariable models, which have primarily comprised the literature to date. METHODS: Electronic health record (EHR) data from TriNetX (unmatched n = 21,629; matched n = 16,602) were used to investigate the effect of vitamin D status, as measured by 25-hydroxyvitamin D [25(OH)D], on the odds of experiencing a positive COVID-19 test using multivariable logistic regression models with and without PS methodology. RESULTS: Having normal (≥ 30 ng/mL) versus inadequate 25(OH)D (< 30 ng/mL) was not associated with COVID-19 positivity overall (OR = 0.913, p = 0.18), in White individuals (OR = 0.920, p = 0.31), or in Black individuals (OR = 1.006, p = 0.96). When 25(OH)D was analyzed on a continuum, a 10 ng/mL increase in 25(OH)D lowered the odds of having a positive COVID-19 test overall (OR = 0.949, p = 0.003) and among White (OR = 0.935, p = 0.003), but not Black individuals (OR = 0.994, p = 0.75). CONCLUSIONS: Models which use weighting and matching methods resulted in smaller estimated effect sizes than models which do not use weighting or matching. These findings suggest a minimal protective effect of vitamin D status on COVID-19 test positivity in White individuals and no protective effect in Black individuals.
Authors: Jennifer E Meng; Kathleen M Hovey; Jean Wactawski-Wende; Christopher A Andrews; Michael J Lamonte; Ronald L Horst; Robert J Genco; Amy E Millen Journal: Cancer Epidemiol Biomarkers Prev Date: 2012-04-20 Impact factor: 4.254
Authors: Sreedhar Subramanian; George Griffin; Martin Hewison; Julian Hopkin; Rose Anne Kenny; Eamon Laird; Richard Quinton; David Thickett; Jonathan M Rhodes Journal: J Intern Med Date: 2022-07-15 Impact factor: 13.068