Sun Exposure Score and Vitamin D Levels in Moroccan Women of Childbearing Age
Bibliographic record
Abstract
Sunlight exposure is an essential source of vitamin D for many humans. However, hypovitaminosis D is a global public health problem. This study aimed to develop and validate a sun exposure score (SES) and correlate it with serum 25-hydroxyvitamin D levels in women of childbearing age. One hundred and sixty women aged 18 to 45 years residing in Meknes, Morocco, were included. A questionnaire estimating the sun exposure score and blood analysis of serum 25-OHD concentration were performed. The questionnaire’s reliability and construct validity were evaluated using Cronbach’s alpha and factor analysis. Spearman’s test was used to assess the correlation between SES and 25-OHD levels. The score’s reliability and construct validity were good, with Cronbach’s alpha values >0.70 and factorial saturation ranging from 0.696 to 0.948. Serum 25-OHD levels were significantly associated with the total sun exposure score, and all SES domains (Rho was 0.615 (p < 0.0001), 0.307 (p < 0.0001), 0.605 (p < 0.0001), and 0.424 (p < 0.0001) for total SES, indoor exposure domain, outdoor exposure domain, and sun protection practice domain, respectively). In addition, median 25-OHD levels increased significantly when sun exposure was changed from insufficient to sufficient (p < 0.0001). The results suggest that the sun exposure score could be used as a clinical tool to assess vitamin D levels in women of childbearing age.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".