Prevalence and factors associated with female genital mutilation among women of reproductive age in the Bawku municipality and Pusiga District of northern Ghana
Bibliographic record
Abstract
BACKGROUND: Globally, three million girls are at risk of female genital mutilation (FGM) and an estimated 200 million girls and women in the world have undergone FGM. While the overall prevalence of FGM in Ghana is 4%, studies have shown that the overall prevalence in the Upper East Region is 38%, with Bawku municipality recording the highest at 82%. METHODS: This study used a cross-sectional design with a quantitative approach: a survey with women of reproductive age (15-49). RESULTS: Among all respondents, 830 women who participated in the study, 61% reported having undergone FGM. Of those circumcised, 66% indicated their mothers influenced it. Three quarters of the women think FGM could be stopped through health education. Women who live in the Pusiga district (AOR: 1.66; 95% CI: 1.16-2.38), are aged 35-49 (AOR: 4.24; 95% CI: 2.62-6.85), and have no formal education (AOR: 2.78; 95% CI: 1.43-5.43) or primary education (AOR: 2.10; 95% CI: 1.03-4.31) were more likely to be circumcised relative to those who reside in Bawku Municipal, are aged 15-24, and had tertiary education. Likewise, married women (AOR: 3.82; 95% CI: 2.53-5.76) were more likely to have been circumcised compared with unmarried women. At a site-specific level, factors associated with FGM included age and marital status in Bawku, and age, marital status, and women's education in Pusiga. CONCLUSION: Female Genital Mutilation is still being practiced in the Bawku Municipality and the Pusiga District of northern Ghana, particularly among women with low socio-economic status. Implementing interventions that would provide health education to communities and promote girl-child education beyond the primary level could help end the practice.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".