Maternal, prenatal and postnatal risk factors for early child physical abuse: a French nationwide cohort study
Bibliographic record
Abstract
Background: Identifying risk factors for early child physical abuse (CPA) is crucial for understanding its mechanisms and defining effective preventive interventions. We aimed to identify maternal, prenatal and postnatal factors associated with early CPA. Methods: This cohort study was based on comprehensive data from the Mother-Child EPI-MERES nationwide register and included all infants born alive in France between 2010 and 2019. Factors associated with early CPA (before age 1) were identified with a multilevel Cox regression model with random intercepts at the regional level. Findings: Among the 6,897,384 included infants, 2994 (40/100,000) had a diagnosis of early CPA, at a median age of 4 months. Independent factors most strongly associated with early CPA were maternal low financial resources (adjusted hazard ratio [aHR] 1.91; 95% confidence interval [95% CI] 1.67-2.18), maternal age <20 years versus 35-40 years (aHR 7.06; 95% CI 6.00-8.31), maternal alcohol use disorder (aHR 1.85; 95% CI 1.48-2.31), opioid use disorder (aHR 1.90; 95% CI 1.41-2.56), intimate partner violence (aHR 3.33; 95% CI 2.76-4.01), diagnosis of a chronic mental disorder (aHR 1.50; 95% CI 1.14-1.97) or somatic disorder (aHR 1.55; 95% CI 1.32-1.83), hospitalisation for a mental disorder (aHR 1.88; 95% CI 1.49-2.36), very preterm birth (aHR 2.15; 95% CI 1.68-2.75), and diagnosis of a chronic severe neurocognitive disorder in the infant (aHR 14.37; 95% CI 11.85-17.44). Interpretation: Independent risk factors of early CPA identified at the national level in France may help in understanding CPA mechanisms and developing effective prevention programs including risk-stratification tools to optimise the allocation of parenting interventions to parents who could most benefit from them. Funding: Ile-de-France regional council, L'Oréal-UNESCO For Women In Science France Young Talent Award, French National Observatory for Child Protection [ONPE], French Association of Ambulatory Paediatrics [AFPA], HUGO university hospitals network, Mustela Foundation and Sauver la Vie prizes.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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".