Factors Associated with Risky Sexual Practices among Female Sex Workers in Karnataka, India
Bibliographic record
Abstract
INTRODUCTION: The objectives of this study are to develop a summary measure of risky sexual practice and examine the factors associated with this among female sex workers (FSWs) in Karnataka, India. MATERIALS AND METHODS: Data were drawn from special behavioral surveys (SBS) conducted in 2007 among 577 FSWs in two districts of Karnataka, India: Belgaum and Bangalore. FSWs were recruited using the two-stage probability sampling design. FSWs' sexual practice was considered risky if they reported inconsistent condom use with any sexual partner and reported experience of one of the following vulnerabilities to HIV risk: anal sex, alcohol consumption prior to sex and concurrent sexual relationships. RESULTS: About 51% of FSWs had engaged in risky sexual practice. The odds of engaging in risky sex were higher among FSWs who were older (35+ years) than younger (18-25 years) (58% vs. 45%, Adjusted Odds Ratio (AOR): 2.0, 95% confidence interval (CI): 1.2-3.4), who were currently married than never married (61% vs. 51%, AOR: 4.8, 95% CI: 2.5-9.3), who were in sex work for 10+ years than those who were in sex work for less than five years (66% vs. 39%, AOR: 2.6, 95% CI: 1.6-4.2), and who had sex with 3+ clients/day than those who had sex with fewer clients (67% vs. 38%, AOR: 3.7, 95% CI:2.5-5.5). CONCLUSION: FSWs who are older, currently married, practicing sex work for longer duration and with higher clientele were more likely to engage in risky sexual practices. HIV prevention programs should develop strategies to reach these most-at risk group of FSWs to optimize the effectiveness of such programs.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".