Effect of adiposity on leukocyte telomere length in US adults by race/ethnicity: The National Health and Nutrition Examination Survey
Bibliographic record
Abstract
Abstract Objective Obesity is associated with telomere attrition – a marker of cellular and biological aging. The US has the highest proportion of obesity and is comprised of a racially/ethnic diverse population. Little is known about the relationship between obesity and telomere attrition according to race/ethnicity in the US. Our objective is to examine the differential association. Design and setting The effect of body mass index (BMI), % total body fat (TBF) and waist circumference (WC) on leukocyte telomere length (LTL) were examined as adiposity measures according to race/ethnicity and sex specific race/ethnicity using separate adjusted linear regressions on a sample of 4,919 respondents aged 20-84 years from cross-sectional 1999-2002 data using the US National Health and Nutrition Examination Survey. Mediation analyses assessed health behaviors associated with relationship between adiposity measures and LTL. Main outcome measure LTL Results African Americans (AA) experienced a 28% and 11% decrease in LTL associated with increasing BMI and WC, ( p =.02 and .03) respectively. Mexican Americans (MA) experienced a 33% decrease in LTL associated with increasing %TBF ( p =.04). Whites experienced a 19%, 23%, and .08% decrease in LTL associated with increasing BMI, %TBF, and WC, ( p =.05, .003, .02) respectively. White men experienced a 26% decrease in LTL due to increasing BMI ( p =.05). AA women experienced a 41%, 44%, and 16% decrease in LTL due to increasing BMI, %TBF, and WC, respectively ( p =.007, .02, .04). White women experienced a 29% decrease in LTL associated with increasing %TBF ( p =.006). Selected health behaviors were associated with the relationship between adiposity measures and LTL. Conclusion Overall, AA and Whites have worse cellular and biological aging related to collective adiposity measures. According to sex, AA women experienced more deleterious cellular and biological aging. Findings suggest tailored interventions to improve adverse behaviors that contribute to obesity may improve telomere attrition in US adults.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".