Seasonal variations in vitamin D status in Bangladesh: a preliminary look at the potential role of aerosol pollution
Bibliographic record
Abstract
Vitamin D deficiency is common in South Asia, but the causes are unclear. Particulate air pollution interferes with ultraviolet (UV) irradiation of the earth surface, but the effect of UV‐absorbing aerosols on vitamin D status is unknown. Associations among vitamin D status (serum 25‐hydroxyvitamin D, [25(OH)D]), UV radiation exposure and UV‐absorbing aerosols in Dhaka were explored based on observations of 34 non‐pregnant and 13 pregnant women in July‐Oct 2009, and 28 pregnant women in Feb 2010 (N=75). Average [25(OH)D] was lower in winter vs. summer/fall; among the pregnant women, mean [25(OH)D] was 12 nmol/L lower in Feb vs. Aug‐Oct (95% CI, 1 – 22 nmol/L). Seasonal differences in [25(OH)D] could be largely explained by variations in personal UV exposure estimated using polysulphone (PS) badges worn on the shoulder, averaged over 2–3 days within ~2 months of [25(OH)D] assessment (N=72). UV exposure by PS dosimetry and [25(OH)D] were both inversely associated with the estimated UV aerosol index (UVAI) for Dhaka, based on satellite‐generated data downloaded from an on‐line NASA database (OMI/Aura). The UVAI peaked in early spring (before the monsoon season), when average UV exposures by PS dosimetry were lowest. These preliminary observations suggest that UV‐absorbing aerosols may have important effects on UV‐induced cutaneous vitamin D synthesis in South Asia and merit further research. Grant Funding Source : Center for Global Health, Johns Hopkins University; Department of International Health, Johns Hopkins Bloomberg School of Public Health
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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 | 0.002 |
| 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".