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 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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".