Childhood maltreatment and leukocyte telomere length in men and women with chronic illness: an evaluation of moderating and mediating influences
Bibliographic record
Abstract
Abstract Background Childhood maltreatment can result in lifelong psychological and physical sequelae, including coronary artery disease (CAD). Mechanisms leading to increased risk of illness may involve emotional dysregulation and shortened leukocyte telomere length (LTL). Methods To evaluate whether (1) childhood maltreatment is associated with shorter LTL among older adults with CAD or other chronic illnesses; (2) sex and/or CAD status influence these results; and (3) symptoms of anxiety, depression, and stress moderate or mediate the association between childhood maltreatment and LTL, men and women (N = 1247; aged 65 ± 7.2 years) with and without CAD completed validated questionnaires on childhood maltreatment, symptoms of depression, anxiety, and perceived stress. LTL was measured using quantitative polymerase chain reaction. Analyses included bivariate correlations, hierarchical regressions, and moderation/mediation analyses, controlling for sociodemographic and lifestyle variables. Results Childhood maltreatment was associated with significantly shorter LTL (r = −0.059, p = 0.038, b = −0.016, p = 0.005). This relation was not moderated by depression, anxiety, nor perceived stress, though there was mitigated evidence for absence of a maltreatment-LTL relation in men with CAD. Stress perception (but not anxiety or depression) partially mediated the relation between childhood maltreatment and LTL [Indirect effect, b = −0.0041, s.e. = 0.002, 95% CI (−0.0085 to −0.0002)]. Conclusions Childhood maltreatment was associated with accelerated biological aging independently of patient characteristics. Emotional dysregulation resulting in chronic stress may contribute to this process. Whether stress management or other interventions may help prevent or slow premature aging in those who have suffered maltreatment requires study.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".