Cumulative Lifetime Violence, Gender Role Conflict, and Cardiovascular Disease Risk in Eastern Canadian Men
Bibliographic record
Abstract
Despite violence being a chronic stressor that negatively affects health through allostatic overload and potentially harmful coping behaviors, the relationship between cumulative lifetime violence severity (CLVS) and cardiovascular disease (CVD) risk in men has received little attention and the role of gender has not been considered. Using survey and health assessment data from a community sample of 177 of eastern Canadian men with CLVS as target and/or perpetrator, we developed a profile of CVD risk measured by the Framingham 30-year risk score. We tested the hypothesis that CLVS measured by the CLVS-44 scale has direct and specific indirect effects through gender role conflict (GRC) on 30-year CVD risk using parallel multiple mediation analysis. Overall, the full sample had 30-year risk scores 1.5 times higher than their age-based Framingham reference normal risk scores. Men classified as having elevated 30-year CVD risk ( n = 77) had risk scores 1.7 times higher than reference normal. Although the direct effects of CLVS on 30-year CVD risk were not significant, indirect effects of CLVS through GRC, specifically Restrictive Affectionate Behavior Between Men, were significant. These novel results reinforce the critical role of chronic toxic stress, particularly from CLVS but also from GRC, in influencing CVD risk. Our findings highlight the need for providers to consider CLVS and GRC as potential antecedents to CVD and to routinely use trauma- and violence-informed approaches in the care of men.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".