Health conditions among women in prisons: a systematic review
Bibliographic record
Abstract
Despite rapidly rising incarceration rates, the health needs of women in custody are overlooked. This Review aims to summarise the current evidence on the health of women in prisons around the world. In this systematic review, we searched peer-reviewed and grey literature databases for quantitative studies published between Jan 1, 2003, and Jan 29, 2025. Our population of interest was people detained in carceral spaces designated for women as part of the criminal-legal system worldwide. We included studies that reported the prevalence of health conditions (based on the Global Burden of Disease Study, or in the International Classification of Disease 11th revision) among women in custody. We assessed risk of bias using the JBI Critical Appraisal Checklist for Studies Reporting Prevalence Data. We identified 18 008 unique records, 247 studies (including more than 452 261 women) were included for analysis. Nearly all studies had a high risk of bias in at least one domain. Communicable diseases and mental health conditions were the most frequently described topics. Prevalence of many conditions varied widely between studies and across geographical regions. We identified gaps in the literature, particularly around non-communicable conditions and in the geographical representation of data. Globally, women in custody experience a high burden of health conditions but there are substantial gaps in current evidence and a need for improved data collection and reporting. Additionally, limitations found in some studies included the exclusion of people with complex health-care needs and the use of measures such as self-reporting, which depend on previous access to health care, and it is likely that the true burden of health conditions among incarcerated women is even greater. The findings of this Review call the correctional, health, and research communities to act to reduce the health inequities faced by women in prison.
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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 | 0.007 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".