Intimate partner violence and cardiovascular risk: is there a link?
Bibliographic record
Abstract
AIM: This paper is a report of a study of the relationship between stress associated with intimate partner violence and smoking and cardiovascular risk. BACKGROUND: Stress related to intimate partner violence persists after a woman leaves an abusive relationship. Persistent stress is associated with cardiovascular disease, the leading single cause of death among women. Smoking, an established risk factor for cardiovascular disease, is a coping mechanism commonly used to decrease the anxiety and stress of intimate partner violence. However, cardiovascular health is poorly understood in abused women. METHOD: Secondary analysis of data collected between 2004 and 2005 with a community sample of 309 women who had separated from an abusive partner 3 months to 3 years previously was conducted to create a descriptive profile of cardiovascular risk. Bivariate tests of association and logistic regression analysis were used to test relationships among variables. RESULTS: Of the women, 44.1% were smokers; 53.2% had body mass indices classified as overweight or obese; 54.7% had blood pressures above normal range; and 50.8% reported cardiovascular symptoms. Neither severity of intimate partner violence nor smoking behaviours were statistically significant in explaining the presence of cardiovascular symptoms. CONCLUSION: The prevalence of hypertension, obesity and smoking suggests that survivors of intimate partner violence may be at heightened risk for cardiovascular disease and warrant clinical attention. Because cardiac symptoms develop as women get older, the mean age of 39 years in this sample may explain why intimate partner violence severity and smoking did not sufficiently explain the presence of cardiac symptoms.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".