Childhood Maltreatment and Mental-Physical Multimorbidity: An Analysis of Canadian Survey Data Using Entropy Balancing
Bibliographic record
Abstract
ABSTRACT Objectives To explore childhood maltreatment as a risk factor for mental-physical multimorbidity and examine gender as an effect modifier. Methods We analyzed data from the 2022 Mental Health and Access to Care Survey. We described sample characteristics with unweighted counts, survey-weighted percentages, and weighted chi-square tests. Missing data were addressed via multiple imputation. Entropy balancing adjusted for age, gender, LGBTQ2+ identity, visible minority group, and immigration status and multinomial logistic regression was used to estimate associations between the number of childhood maltreatment subtypes (physical abuse, sexual abuse, and exposure to domestic violence) reported and physical (≥ 2 physical conditions but no mental), mental (≥ 2 mental conditions but no physical), and mental-physical (≥ 1 mental and physical condition) multimorbidity. Survey weights were applied during both entropy balancing and regression modeling. Effect modification by gender was examined and sub-analyses of mental- cardiometabolic, mental-inflammatory, mental-somatic multimorbidity, and subtype-specific exposures were conducted. Results 8,967 respondents were included. Mental-physical multimorbidity increased with maltreatment: 3.4% (none, n=4647), 6.3% (1 type, n=2804), 10.1% (2 types, n=1208), and 18.2% (3 types, n=308). Adjusted odds ratios for mental-physical multimorbidity ranged from 2.15 (95% CI:1.90-2.44) for 1 type to 8.72 (95% CI:7.01-10.85) for 3 types compared to physical (aOR=1.31-2.00) and mental (aOR=1.90-3.63) multimorbidity. Men showed higher odds of mental-physical multimorbidity at high exposure (aOR=6.14, 95% CI:4.90-7.70 in women; aOR=13.96, 95% CI:9.58-20.34 in men) with varying effect sizes across disease areas. Conclusion Childhood maltreatment shows a strong dose-response association with mental- physical multimorbidity. Further research is needed to clarify gender-specific pathways.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.006 | 0.016 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".