Determinants of vitamin D supplement use in Canadians
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence of vitamin D supplement use in Canadian adults and associations with demographic and socio-economic variables. DESIGN: Data from the Healthy Aging module of the Canadian Community Health Survey were used to investigate the prevalence of vitamin D supplement use in Canadians aged 45 years and over. The prevalence of supplement use stratified by various behavioural and demographic characteristics was calculated and adjusted models were used to find associations with those factors. SETTING: The ten provinces of Canada. SUBJECTS: Canadians aged 45 years and over who participated in the Healthy Aging module of the Canadian Community Health Survey from 2008-2009. RESULTS: The highest observed prevalence for women was 48·0 % in the 65-69 years age group and the highest prevalence for men was 25·3 % in the 70-74 years age group. Women had higher odds of vitamin D supplement use than men in all age groups. Not using supplements was more common in smokers, those who did not engage in leisure-time physical activities and who were either overweight or obese. Vitamin D supplement use increased with household income and level of education, and decreased with self-perceived health. Supplement use was higher in those with chronic conditions. CONCLUSIONS: The inverse association with self-perceived health could be partly explained by age, chronic conditions and increased use of health-care services. Associations with higher income and education suggest a strong socio-economic influence and that individuals may not have the expendable income to purchase vitamin D supplements or knowledge of their health benefits.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".