The Prevalence of Consanguineous Marriages in an Underserved Area in Lebanon and Its Association with Congenital Anomalies
Bibliographic record
Abstract
BACKGROUND: Consanguinity is a recognized common practice among marriages in the Middle East. Many studies have suggested a strong association between first cousin marriages and the incidence of autosomal recessive diseases and congenital anomalies. The objectives of this study were to study the prevalence of consanguinity among the marriages of Bekaa (a region in Lebanon) with its sociodemographic correlates, and to assess the prevalence of congenital anomalies associated with these marriages. METHODS: This study was a cross-sectional study done in three of the major areas of the Bekaa region. The sample size consisted of 552 households chosen based on proportionate random sampling according to population size in each area. The survey was conducted based on face-to-face interview with a member of the couples of each household. RESULTS: The overall prevalence of consanguineous marriages was reported to be 42% with first cousin marriage constituting around 31% of the total marriages. No association was found between different socioeconomic status (SES) correlates and first cousin marriages. Results showed a significant association between first cousin marriage and mental retardation, physical retardation, bilateral cleft lip +/- cleft palate, cystic fibrosis, and congenital blindness. CONCLUSION: In a population with a high degree of inbreeding, the formulation of a public health program with multiapproach strategy, including education about the anticipated genetic consequences, prenatal diagnosis, neonatal screening, and genetic counseling, is a necessity.
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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 | 0.001 | 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".