UV and dietary predictors of serum 25-hydroxyvitamin D concentrations among young shift-working nurses and implications for bone density and skin cancer
Bibliographic record
Abstract
OBJECTIVE: In 2011, the U.S. Institute of Medicine updated the definition of vitamin D inadequacy to serum 25-hydroxyvitamin D (25(OH)D) concentration of 30-<50 nmol/l and of deficiency to serum 25(OH)D < 30 nmol/l. We describe the prevalence of these conditions according to these definitions, seasonal variation in 25(OH)D and predictors of serum 25(OH)D concentrations among working, white women. DESIGN: Participants recorded lifestyle factors and dietary intake and provided fasting blood samples for measurement of serum 25(OH)D in both summer and winter. Predictors of serum 25(OH)D variation were analysed using linear regression and generalized linear mixed models. SETTING: Kingston General Hospital in Kingston, Ontario, Canada, from April 2008 to July 2009. SUBJECTS: Female premenopausal nurses (n 83) working full-time rotating shifts. RESULTS: Deficient or inadequate vitamin D status was observed in 9% of participants following summer/autumn and in 13% following winter/spring. Predictors of serum 25(OH)D concentration were vitamin D supplement use, tanning bed use and season. Tanning bed use increased serum 25(OH)D by 23.24 nmol/l (95% CI 8.78, 37.69 nmol/l, P = 0.002) on average. CONCLUSIONS: According to the 2011 Institute of Medicine bone health guidelines, over 10% of nurses had deficient or inadequate vitamin D status following winter. Higher serum concentrations were associated with use of tanning beds and vitamin D supplements. As health promotion campaigns and legal restrictions are successful in reducing tanning bed use among women, our data suggest that increased prevalence of vitamin D inadequacy and deficiency may be a consequence, and that low vitamin D status will need to be countered with supplementation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".