Assessment of vitamin D and its association with cardiovascular disease risk factors in an adult migrant population: an audit of patient records at a Community Health Centre in Kensington, Melbourne, Australia
Bibliographic record
Abstract
BACKGROUND: Vitamin D deficiency is a global public health problem associated with increased risk of cardio-metabolic diseases and osteoarthritis. Migrants with dark skin settled in temperate climates are at greater risk of both vitamin D deficiency and cardiovascular diseases. This study aims to identify the risk of vitamin D deficiency and associations with cardiovascular disease in a migrant population in Australia. METHODS: An audit was carried out at a Community Health Service in Kensington, Melbourne which, services a large migrant population. Data from the clinical records of all adults who visited the medical centre at least once during the period from 1st January 2010 to 31st December 2012 was extracted. The future (10 year) coronary heart disease risk was estimated using Framingham Risk Score. RESULTS: The centre has given higher priority to vitamin D testing in migrants, those middle-aged, females and those with diabetes and osteoarthritis. Migrants from countries located in lower latitude regions (Latitude N230 to S230) were 1.48 (95% C.I. 1.32-1.65) times more likely to develop vitamin D deficiency post migration and 0.44 (95% C.I. 0.31-0.62) times less likely to have a >15% 10-year risk of coronary heart disease when compared to their Australian-born counterparts. CONCLUSIONS: Adherence to a high risk strategy for vitamin D testing was observed in the centre. Pre-migration latitude is an important factor for vitamin D deficiency (lower the latitude higher the risk) and in predicting future risk of cardiovascular disease in migrants. These findings suggest that a targeted approach for vitamin D testing, including zone of origin might better identify individuals at higher risk of both vitamin D deficiency and cardiovascular disease.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".