Associations of Adverse Childhood Experiences with Frailty in Older Adults: A Cross-Sectional Analysis of Data from the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
INTRODUCTION: Frailty in older adults, characterized by a decline in multiple physiological systems and increasing vulnerability to loss of independence, disability, and death, is a public health priority in developed countries. Etiology of frailty extends across the lifespan and may begin in early life, but empirical evidence for this association is scarce. In this study, we examined whether adverse childhood experiences (ACEs) are associated with frailty in later life. METHODS: We conducted a cross-sectional analysis of data for a population-based sample of 27,748 adults aged 45-85 years from the Canadian Longitudinal Study on Aging. The frailty index (FI) was computed with 76 health-related characteristics of physical and cognitive performance, self-rated health, chronic conditions, visual and hearing ability, activities of daily living, and well-being. Self-reported exposure to ACEs included physical, emotional, and sexual abuse, neglect, and witnessing intimate partner violence prior age of 16 and parental death, divorce, and living with a family member with mental illness prior age of 18. Generalized linear regression models with gamma error distribution and identity link function, adjusted for age and sex, were used to examine associations of each ACE type and the number of ACE types (0, 1, 2, or 3+) reported by an individual with FI. All models were adjusted for income, education, smoking, and alcohol consumption in sensitivity analysis. RESULTS: Individuals exposed to ACEs had elevated levels of FI (mean = 0.13, SD = 0.09) than those unexposed, with the largest difference observed for neglect (B [95% CI]: 0.05 [0.04, 0.06]) and the smallest for parental death and divorce (0.015 [0.01,0.02]). The ACE count was associated with frailty in a graded manner, with the FI difference reaching 0.04 [0.037, 0.044] for participants exposed to 3+ ACE types. The association between ACEs and frailty tended to be stronger for women than men and for men aged 45-64 years than older men. CONCLUSIONS: Our study supports previous studies showing that exposure to ACEs is associated with frailty in adults. Our findings suggest that screening for ACEs involving childhood maltreatment may be useful for identifying individuals at risk of frailty and prevention of ACEs may have long-term benefits for healthy aging.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".