Dietary creatine intake and all-cause mortality among U.S. adults: a linked mortality analysis from the NHANES study
Bibliographic record
Abstract
Evidence linking dietary creatine intake with mortality remains scarce and inconclusive. This study aimed to investigate the relationship between creatine consumption and all-cause mortality, as well as to evaluate the potential impact of meeting the recommended dietary creatine intake of ≥1 g per day in a nationally representative sample of U.S. adults. We evaluated creatine intake, estimated from a single 24 h dietary recall in the 1999–2000 National Health and Nutrition Examination Survey, with mortality follow-up extending through 2019. Of the 4041 participants enrolled at baseline, 858 deaths were recorded over a median follow-up period of 19.8 years. Creatine as a continuous variable (grams per day) had inverse association with all-cause mortality ( B = −0.094; P = 0.04). The hazard ratio for all-cause mortality was 0.85 (95% CI: 0.72–1.00) for participants consuming at least 1 g of creatine per day, compared to those consuming less than 1 g/day ( P = 0.05), suggesting that individuals meeting the recommended creatine intake had a significantly lower risk of early mortality compared to those with suboptimal intake. Proportional hazards regression analysis indicated that this association remained robust after adjusting for certain covariates, such as dietary macronutrients ( B = −0.234; P = 0.01) and physical examination measures ( B = −0.206; P = 0.02); however, it weakened when demographic and lifestyle factors were included in the model. In this sample of U.S. adults, higher creatine intake was inversely associated with all-cause mortality; however, this relationship may be influenced by other contributing factors. These findings underscore the need for further research on the relationship between dietary creatine intake and mortality outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".