UV and vitamin D: what are we aiming for and what are we achieving?
Bibliographic record
Abstract
Vitamin D is important for bone health, is linked to many other health benefits including protection against a range of malignancies and autoimmune disorders, and is known to modulate many biological responses including cell differentiation. It is therefore important to evaluate the vitamin D status of the general population in the context of recommended target levels and public health advice on vitamin D acquisition. The accepted best indicator of vitamin D status is the circulating level of 25-hydroxyvitamin D (25OHD). The Institute of Medicine for the USA and Canada advises a target 25OHD level of ≥20 ng/ml (50 nmol/L) based on parameters of bone health, and recommends oral intake of ≥600 IU daily. The target is currently under review in the UK, where most adults are not advised of any oral vitamin D requirement as adequate intake has been assumed to occur from cutaneous synthesis following regular brief UV exposures. Through a series of intervention studies, we demonstrated that a 6 week course of low dose (1.3 SED) UV radiation exposures (3 times a week to 35% skin surface area), simulating a summer’s casual sunlight exposures, could produce 25OHD ≥20 ng/ml in 90% of the white Caucasian adult (phototype I-IV, aged 20-60 years) population. However, no adults of South Asian ethnicity (phototype V) reached sufficiency following an identical course of exposures. Increased UV exposure, up to 3 times that given to white Caucasians, raised 25OHD levels in South Asians enough to avoid deficiency i.e.25OHD ≥10 ng/ml but the majority could not reach 20 ng/ml.. Our observation studies have shown that 77% of white Caucasian adults aged 20-60 years actually achieve 20 ng/ml at summer end (September) in the UK, falling to 40% at the winter trough in February. In contrast, 25OHD levels in a cohort of South Asian adults in the same age range were startlingly low, with only 7% ever achieving 20 ng/ml. Due to the diverse roles of vitamin D, suboptimal status may impact on responses to therapy, as well as on various health outcomes. Considering our observation and intervention studies in tandem, more effectively targeted guidance on sunlight exposure and oral vitamin D acquisition could assist those at risk of low levels.
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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 | 0.024 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.012 | 0.018 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.011 | 0.016 |
| Insufficient payload (model declined to judge) | 0.014 | 0.007 |
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".