Determinants of plasma 25-hydroxyvitamin D and development of prediction models in three US cohorts

Abstract

Epidemiologic and other evidence suggests that vitamin D may be protective against several chronic diseases. Assessing vitamin D status in epidemiologic studies, however, is challenging given finite resources and limitations of commonly used approaches. Using multivariable linear regression, we derived predicted 25-hydroxyvitamin D [25(OH)D] scores based on known determinants of circulating 25(OH)D, including age, race, ultraviolet-B radiation flux at residence, dietary and supplementary vitamin D intakes, body mass index, physical activity, alcohol intake, postmenopausal hormone use (women only), and season of blood draw, in three nationwide cohorts: the Nurses' Health Study (NHS), NHSII, and the Health Professionals Follow-up Study. The model r2 for each cohort ranged from 0.25 to 0.33. We validated the prediction models in independent samples of participants from these studies. Mean measured 25(OH)D levels rose with increasing decile of predicted 25(OH)D score, such that differences in mean measured 25(OH)D between extreme deciles of predicted 25(OH)D were 8.7–12.3 ng/mL. Substituting predicted 25(OH)D scores for measured 25(OH)D in a previously published case-control analysis of colorectal cancer yielded similar effect estimates with odds ratios of approximately 0.8 for a 10-ng/mL difference in either plasma or predicted 25(OH)D. We conclude that these data provide reasonable evidence that a predicted 25(OH)D score is an acceptable marker for ranking individuals by long-term vitamin D status and may be particularly useful in research settings where biomarkers are not available for a majority of a study population.

Physical activity and the incidence of multiple sclerosis

“…In 25(OH)D prediction models developed in NHS and NHS II, physical activity quintiles were associated with higher predicted 25 (OH)D levels (p , 0.0001). 33 Though we did not adjust for 25(OH)D levels, we adjusted for supplemental vitamin D intake, which is associated with higher predicted 25(OH)D levels 33 and MS risk. 16 It remains unclear how much of the association between physical activity and MS might have been due to more active women having more sunlight exposure, a major vitamin D source, 34 than less active women.…”

Relative importance of summer sun exposure, vitamin D intake, and genes to vitamin D status in Dutch older adults: The B-PROOF study

“…On the other hand Gilbert et al did consider taking genetic information into account, but concluded that this information did not improve the fit of the prediction score in their data, which explained 28% of the variation in 25(OH)D when sun exposure, vitamin D intake, anthropometrics, clinical factors, demographics, age, season, study center, and batch assay were included in the model [42]. Other previous studies that included vitamin D intake, a measure of UV-B exposure, demographic, and environmental factors have explained between 21 and 33% of the variation in 25(OH)D status [33,43,44]. Studies considering vitamin D intake, demographic and environmental factors and season of blood sampling have shown an explained variation in 25(OH)D ranging from 19 to 28% [45][46][47].…”

Vitamin D levels in a large Mediterranean cohort: reconsidering normal cut-off values

“…16,124 We can assume that calcium intake is adequate in our population due to high availability and consumption of dairy products. 125,126 Regarding adiposity indices, a negative association between levels of 25-(OH)D and overweight/obesity is well established 44,67,[127][128][129][130][131] and more pronounced with percentage of body fat rather than body mass index (BMI). Underweight, though not as extensively explored, may also be negatively related to VitD status.…”

“…139 Excessive alcohol consumption is linked to lower 25-(OH)D concentrations, 140 but moderate intake is consistently reported to relate to better VitD status. 30,67,131,141,142 Strengths of our study include the large number of subjects for whom 25-(OH)D measurements were available and the wide age distribution, which lead us to consider our cohort as being representative of the general population of a Mediterranean island. The inherent limitations of our work lie in its retrospective design and the mixed population studied (in-and outpatients), although no significant differences between the two groups were found.…”