Experiences of violence across life course and its effects on mobility among participants in the International Mobility in Aging Study
Bibliographic record
Abstract
BACKGROUND: Life course exposure to violence may lead to disability in old age. We examine associations and pathways between life course violence and mobility disability in older participants of the International Mobility in Aging Study (IMIAS). METHODS: A cross-sectional study using IMIAS 2012 baseline. Men and women aged 65-74 years were recruited at 5 cities (n=1995): Kingston and Saint-Hyacinthe (Canada), Tirana (Albania), Manizales (Colombia) and Natal (Brazil). Mobility was assessed by the Short Physical Performance Battery (SPPB) and by 2 questions on difficulty in walking and climbing stairs. Childhood physical abuse history and the HITS instrument were used to gather information on childhood exposure to violence and violence by intimate partners or family members. Multivariate logistic regression and mediation analysis models were constructed to explore the significance of direct and indirect effects of violence on mobility. Interaction effects of gender on violence and on each of the mediators were tested. RESULTS: Experiences of physical violence at any point of life were associated with mobility disability (defined as SPPB<8 or limitation in walking/climbing stairs) while psychological violence was not. Chronic conditions, C reactive protein, physical activity and depression mediated the effect of childhood exposure to violence on both mobility outcomes. Chronic conditions and depression were pathways between family and partner violence and both mobility outcomes. Physical activity was a significant pathway linking family violence to mobility. Gender interactions were not significant. CONCLUSIONS: Our results provide evidence for the detrimental effects of life course exposure to violence on mobility in later life.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 | 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".