Abstract
OBJECTIVE: To develop algorithms predicting serum 25 hydroxyvitamin D [s25(OH)D] for a large epidemiological study whose subjects come from large geographic areas, are racially diverse and have a wide range in age, skin types, and month of blood sample collection. This will allow a regression calibration approach to determine s25(OH)D levels replacing the more costly method of collection and analysis of blood samples. STUDY DESIGN AND SETTING: Questionnaire data from a subsample of 236 non-Hispanic whites (whites) and 209 blacks from the widely dispersed Adventist Health Study-2 (n = 96,000) were used to develop prediction algorithms for races separately and combined. A single blood sample was collected from each subject, at different times throughout the year. RESULTS: Models with independent variables age, sex, BMI, skin type, UV season, erythemal zone, total dietary vitamin D intake, and sun exposure factor explained 22 and 31% of the variance of s25(OH)D levels in white and black populations, respectively (42% when combined). UV season and erythemal zone determined from measured UV radiation produced models with higher R (2) than season and latitude. CONCLUSION: Combining races with a term for race and using variables with measured UV radiation capture the variance in s25(OH)D levels better than analyzing races separately.