31. Lifetime prevalence of anal intercourse among sexually active female youth and young female sex workers: a comparative systematic review and meta-analysis
Bibliographic record
Abstract
Background Anal cancer incidence has increased over the past twenty years. Heterosexual anal intercourse (AI) is a risk factor for HPV and HIV infection but is under-researched and ill-understood. We compare AI practices among young, sexually active general population females and female sex workers (FSW). Methods: We searched PubMed for heterosexual AI studies among young females, including FSWs (mean age <25 years), to December 2012. Study estimates were pooled using a random-effects model. Results: Fifty-four studies (42 average-risk, 6 higher-risk, 6 FSWs) were included. Most studies among general population youth were conducted in North America using self-administered questionnaires. All FSW studies were conducted in Africa and Asia using face-to-face interviews (FTFI). Pooled estimates of lifetime AI prevalence were larger among average-risk (23.6%, 95% CI 20.4–26.7) and higher-risk youth (25.5%, 95% CI 11.7–39.2) than FSWs (12.8%, 95% CI 8.4–17.3), but highly heterogeneous (I2 >90%). However, pooled AI estimates by continent of average-risk youth (Asia = 13.9%, 95% CI = 1.7–29.5; Africa = 18.4%, 95% CI 0.9–35.8) were more similar to those of FSWs (Asia = 16.0%, 95% CI 10.3–21.6; Africa = 9.7%, 95% CI 3.8–15.7). Estimates of average-risk youth reporting via FTFI (12.1%, 95% CI 0.7–23.5) were likewise similar to those among FSWs (12.8%, 95% CI 8.4–17.3). Pooled AI prevalence estimates among FSWs were higher in studies conducted after 2001 than in earlier studies. Conclusions: AI is common among sexually active females and may be increasing; it could therefore be an important determinant of HPV transmission and anal cancers. AI is as or more common among the general population youth than young FSWs but this may be confounded by continent, interview method and other unmeasured variables.
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 | 0.013 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.043 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".