Food Security and Leukocyte Telomere Length in Adult Americans
Bibliographic record
Abstract
Background and Purpose. Leukocyte telomere length (LTL) is a biomarker of biologic age. Whether food security status modulates LTL is still unknown. We investigated the association between food security and LTL in participants of the 1999–2002 US National Health and Nutrition Examination Survey (NHANES). Methods. Analysis of covariance (ANCOVA) was used to evaluate the association between food security categories and LTL controlling for sex, race, and education and accounting for the survey design and sample weights. Results. We included 10,888 participants with 5228 (48.0%) being men. They were aged on average 44.1 years. In all, 2362 (21.7%) had less than high school, 2787 (25.6%) had achieved high school, while 5705 (52.5%) had done more than high school. In sex‐, race‐, and education‐adjusted ANCOVA, average LTL (T/S ratio) for participants with high food security versus those with marginal, low, or very low food security was 1.32 versus 1.20 for the age group 25–35 years and 1.26 versus 1.11 for the 35–45 years, (p < 0.001). Conclusion. The association between food insecurity and LTL shortening in young adults suggest that some of the future effects of food insecurity on chronic disease risk in this population could be mediated by telomere shortening.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".