Correlates and Prevalence of Insufficient 25‐Hydroxyvitamin D Status in Black and White Older Adults: The Health, Aging and Body Composition Study
Bibliographic record
Abstract
OBJECTIVES: To determine the prevalence and correlates of vitamin D insufficiency in black and white older adults. DESIGN: Cross-sectional. SETTING: Health, Aging and Body Composition Study. PARTICIPANTS: Nine hundred seventy-seven black and 1,604 white adults aged 70 to 81. MEASUREMENTS: Logistic regression and classification and regression tree analysis were used to identify correlates of vitamin D insufficiency (25-hydroxyvitamin D (25(OH)D) <30 ng/mL) separately in blacks and whites. RESULTS: The prevalence of 25(OH)D insufficiency was 84% in blacks and 57% in whites. Seventy-six percent of blacks and 56% of whites did not take a multivitamin; those who did not take a multivitamin were more likely to be vitamin D insufficient (odds ratio (OR)=5.17 (95% confidence interval (CI)=3.47-7.70) for blacks; OR=2.56, 95% CI=2.05-3.19 for white). Additional risk factors for vitamin D insufficiency were vitamin D-containing supplement use, female sex, and obesity in blacks; and winter season, low dietary vitamin D intake, obesity, type 2 diabetes mellitus, and female sex in whites. CONCLUSION: Vitamin D insufficiency was more prevalent in blacks than whites. Not consuming a multivitamin increased the odds of vitamin D insufficiency in blacks and whites. Knowledge of additional risk factors such as dietary intake and comorbid conditions may help identify older adults who are likely to be vitamin D insufficient.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".