Serum 25-hydroxyvitamin D level, chronic diseases and all-cause mortality in a population-based prospective cohort: the HUNT Study, Norway
Bibliographic record
Abstract
OBJECTIVE: To investigate the association of vitamin D status with all-cause mortality in a Norwegian population and the potential influences of existing chronic diseases on the association. DESIGN: A population-based prospective cohort study. SETTING: Nord-Trøndelag County, Norway. PARTICIPANTS: A random sample (n=6613) of adults aged 20 years or older in a cohort. METHODS: Serum 25-hydroxyvitamin D (25(OH)D) levels were measured in blood samples collected at baseline (n=6377). Mortality was ascertained from the Norwegian National Registry. Cox regression models were applied to estimate the HRs with 95% CIs for all-cause mortality in association with serum 25(OH)D levels after adjustment for a wide spectrum of confounding factors as well as chronic diseases at baseline. RESULTS: The median follow-up time was 18.5 years, during which 1539 subjects died. The HRs for all-cause mortality associated with the first quartile level of 25(OH)D (<34.5 nmol/L) as compared with the fourth quartile (≥58.1 nmol/L) before and after adjustment for chronic diseases at baseline were 1.30 (95% CI 1.11 to 1.51) and 1.27 (95% CI 1.09 to 1.48), respectively. In the subjects without chronic diseases at baseline and with further exclusion of the first 3 years of follow-up, the corresponding adjusted HR was 1.34 (95% CI 1.09 to 1.66). CONCLUSIONS: Low serum 25(OH)D level was associated with increased all-cause mortality in a general Norwegian population. The association was not notably influenced by existing chronic diseases.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".