Association between Adverse Childhood Experiences and Muscle Strength in Older Age
Bibliographic record
Abstract
BACKGROUND: Muscle weakness - a biomarker of health - may have its origins in early life and be related to factors such as adverse childhood experiences (ACE), which refer to a set of early-life traumatic and stressful psychosocial events out of the child's control. To date, evidence of an association between ACE and muscle strength in older age is lacking. -Objective: Here, we assessed the associations between ACE during the first 15 years of life and the risk of low muscle strength (LMS) later in life. We also examined whether adult-life socioeconomic circumstances (i.e., educational attainment, main occupational position, and satisfaction with household financial situation) and unhealthy behaviors (i.e., physical inactivity, unhealthy eating, smoking, and high level of alcohol consumption) explained this association. METHODS: We used data from the Survey of Health, Ageing, and Retirement in Europe, a 12-year cohort study with 6 -repeated measurements between 2004 and 2015. Muscle strength was measured using a handheld dynamometer. Confounder-adjusted logistic mixed-effect models were used to examine the associations between ACE (child in care, parental death, parental mental illness, parental drinking, period of hunger, or property taken away) and the risk of LMS in older age. -Results: 24,179 participants (96,372 observations; 13,477 women; aged 50-96 years) living in 14 countries were included. LMS increased with age for both genders. For women, there was a gradual increase in the risk of LMS with the number of experienced ACE (ORs = 1.22 for 1 ACE, 1.74 for ≥2 ACE compared to no ACE). However, there was no significant association among men. This association was only slightly attenuated when adjusting for socioeconomic circumstances and unhealthy behaviors in adulthood. CONCLUSIONS: ACE are associated with later-life muscle weakness among women. These associations were not compensated by the adoption of healthy behaviors or an improvement in socioeconomic circumstances in adulthood. These results suggest that tackling these early-life risk factors in women could promote long-term grip strength, a biomarker of aging.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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 teacher head, 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".