The robust association between childhood physical abuse and osteoarthritis in adulthood: Findings from a representative community sample
Bibliographic record
Abstract
OBJECTIVE: Research suggests a role of early-life trauma in the development of arthritis. This study investigated the relationship between childhood physical abuse and osteoarthritis (OA) while controlling for age, sex, race, and socioeconomic status (SES), in addition to the following types of risk factors for OA: 1) concurrent childhood stressors, 2) adult health behaviors, and 3) depression. METHODS: Data from the provinces of Manitoba and Saskatchewan were selected from the 2005 Canadian Community Health Survey (n = 13,093). Respondents with missing arthritis data or with arthritis types other than OA were excluded (n = 1,985). Of the 11,108 remaining respondents, 6.9% (n = 854) reported childhood physical abuse by someone close to them, and 10.1% (n = 1,452) reported that they had been diagnosed with OA by a health professional. The regional-level response rate was 84%. RESULTS: When adjusting for all 3 types of risk factors, a significant association between childhood physical abuse and OA was found (odds ratio [OR] 1.56, 95% confidence interval [95% CI] 1.21-2.00). In contrast, when adjusting for age, sex, race, and SES only, the OR was 1.99 (95% CI 1.57-2.52). CONCLUSION: The association between childhood physical abuse and OA remained significant, even after controlling for many risk factors that may mediate the relationship. Further research is needed to investigate potential pathways through which arthritis develops as a consequence of childhood physical abuse.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".