Male circumcision: global trends and determinants of prevalence, safety and acceptability
Bibliographic record
Abstract
Male circumcision is one of the oldest and most common surgical procedures worldwide, and is undertaken for many reasons: religious, cultural, social and medical. There is conclusive evidence from observational data and three randomized controlled trials that circumcised men have a significantly lower risk of becoming infected with the human immunodeficiency virus (HIV). Demand for safe, affordable male circumcision is expected to increase rapidly, and country-level decision-makers need information about the sociocultural and medical determinants of circumcision, as well as risks of the procedure, in the context of comprehensive HIV prevention programming. Scope of the review: The aim of this report is to review the determinants, prevalence, safety and acceptability of male circumcision, focusing on sub-Saharan Africa. In the first section, we review the religious, cultural and social determinants of male circumcision and estimate the global and regional prevalences. In the second section, we summarize medical aspects of the procedure, including medical indications for circumcision, surgical methods used and the complications of circumcision carried out in clinical and non-clinical settings. The third section focuses on the public health implications of the fact that male circumcision reduces risk of HIV infection, including a summary of the acceptability of adult male circumcision in currently non-circumcising populations in sub-Saharan Africa with high incidence of HIV. Results: Approximately 30% of males are estimated to be circumcised globally, of whom an estimated two thirds are Muslim. Other common determinants of male circumcision are ethnicity, perceived health and sexual benefits, and the desire to conform to social norms. Neonatal circumcision is common in Israel, the United States of America, Canada, Australia and New Zealand, and in much of the Middle East, Central Asia and West Africa, but is uncommon in East and southern Africa, where median age at circumcision varies from boyhood to the late teens or twenties. In several countries, prevalence of non-religious circumcision has undergone rapid increases and decreases, reflecting cultural mixing and changing perceptions of health and sexual benefits. [...]
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".