Childhood maltreatment as a risk factor for cancer: findings from a population-based survey of Canadian adults
Bibliographic record
Abstract
BACKGROUND: Childhood maltreatment (CM) is an established risk factor for various mental and substance use disorders. This study adds to existing evidence that CM may also be a risk factor for cancer. METHODS: Based on data from a sample of 9783 men and 12,132 women from the 2012 Canadian Community Health Survey - Mental Health (CCHS-MH), this analysis explores mediated associations between cancer in adulthood and different levels of exposure to three types of CM-childhood physical abuse (CPA), childhood sexual abuse (CSA), and childhood exposure to intimate partner violence (CEIPV). "Cancer" was defined as an affirmative response to either of these questions: "Do you have cancer?" or "Have you ever been diagnosed with cancer?" The potential mediators were: smoking, depression, alcohol abuse/dependence, life stress, obesity, and physical activity. RESULTS: For women, but not men, having experienced CM was significantly associated with a cancer diagnosis in adulthood, even when effects due to age and socio-demographic characteristics were controlled. Smoking, life stress, depression, and alcohol abuse/dependence reduced the strength of the association between CM and cancer in women. However, most associations remained statistically significant when controlling for effects due to these behavioural and other mediators. Evidence indicated a "dose-response" relationship, in that the likelihood of reporting cancer increased with the number of abuse types (CPA, CSA, CEIPV) reported, and with the severity of CPA. CONCLUSIONS: The analyses suggest an association between CM and cancer in women, even when the effects of known risk factors were taken into account. The association was graded, becoming stronger as CM exposure increased. Implications for the provision of cancer screening and other health care services to women with histories of CM to reduce health disparities are discussed.
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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) | 0.007 | 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".