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 sub-sample 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 R2 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.