Associations between exposure to adverse childhood experiences and biological aging: Evidence from the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
People exposed to adverse childhood experiences (ACEs) suffer from an increased risk of chronic disease and shorter lifespan. These individuals also tend to exhibit accelerated reproductive development and show signs of advanced cellular aging as early as childhood. These observations suggest that ACEs may accelerate biological processes of aging through direct or indirect mechanisms; however, few population-based studies have data to test this hypothesis. We analysed ACEs and biological aging data from the Canadian Longitudinal Study on Aging (CLSA; n = 23,354 adults aged 45-85) and used the BioAge R package to compute three indices of biological aging from blood-chemistry and organ-function data: Klemera-Doubal method (KDM) biological age, phenotypic age (PA), and homeostatic dysregulation (HD). Adults with ACEs tended to be biologically older than those with no ACEs, although the observed effect-sizes were small (Cohen's d<0.15), with the exception of neglect (d=0.35 for KDM and PA). Associations were similar for men and women and tended to be smaller for older as compared to midlife participants. Subtypes of ACEs perceived as being more severe (e.g., being pushed or kicked, experiencing forced sexual activity, witnessing physical violence) and more frequent and diverse exposures were associated with relatively larger effect-sizes. These findings support the hypothesis that ACEs contribute to accelerated biological aging, although replication is needed in studies with access to prospective records of ACEs and cellular-level measurements of biological aging. Furthermore, future work to better understand the degree to which associations between ACEs and biological aging are moderated by specific life-course pathways, and mediated by lifestyle and socioeconomic factors is warranted.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".