Female genital mutilation and sexual behaviour by marital status among a nationally representative sample of Nigerian women
Bibliographic record
Abstract
BACKGROUND: Female Genital Mutilation (FGM) is believed to have a negative effect on sexual and reproductive health but the evidence from nationally representative sample in high-burdened countries like Nigeria is scarce. This study explored the association between FGM and sexual behaviour in a nationally representative sample of Nigerian women. METHODS: A secondary data analysis was conducted using the Nigeria Demographic Health Survey conducted in 2013 and 2018 among women aged 15-49 years. The descriptive summaries of respondent characteristics by marital status were presented using frequencies and percentages. The proportion and 95% Confidence Interval (CI) of circumcision by sexual behaviour characteristics were computed. A multivariable log-binomial logistic regression was used to determine the association between sexual behaviour and female circumcision while adjusting for other covariates. All analyses were performed using Stata 15.1 (StataCorp, College Station, TX, USA) at the 0.05 level of significance. RESULTS: The proportion of circumcised women was 38.6% among those who were ever-married and 32.4% among those unmarried. There were no statistically significant relationship between circumcision status and sexual behaviour among women who were unmarried. However, circumcised women who were ever married had 18% higher risk of having contracted sexually transmitted disease in the last 12 months preceeding the survey and 10% higher risk of engaging in pre-marital sex compared to ever married women who were uncircumcised after adjusting for other covariates. However, the risk of having multiple sexual partners in the last 12 month among uncircumcised ever married women was lower (aRR = 0.80; 95% CI: 0.66-0.97) in the adjusted model. CONCLUSION: Circumcision is not associated with positive sexual behavioural outcomes including delay in sexual debut, virginity and marital fidelity, although there exists some perception behind increasing FGM in Nigeria including prevention of premarital sex and ensuring marital fidelity. While we strongly discourage FGM in all its form, we assert the need for alternative health promoting community measures to address these inherent sexual perceptions toward eliminating FGM and improving sexual and reproductive health across population groups.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".