ArticleJournal of public health research2026
Oral contraceptive safety in humanitarian settings: A WHO-based assessment among syrian refugee women.
Article in Journal of public health research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Women with elevated cardiovascular and systemic risks face major contraindications to combined hormonal contraceptives (CHCs). In humanitarian settings, limited healthcare access may lead to overreliance on CHCs. This study assessed the prevalence and predictors of CHC ineligibility among Syrian refugee women in Lebanon. Methods: A cross-sectional survey was conducted with 105 current CHC users aged 18-50 years, extracted from a larger cohort. Sociodemographic, clinical, and reproductive data were analyzed using the WHO Medical Eligibility Criteria (MEC). Univariate and multivariable logistic regression identified predictors of MEC Category 3-4 ineligibility. Results: Nearly half of the women (44.8%) were classified as MEC Category 3-4, indicating substantial risk. Migraine with aura was the most frequent comorbidity (25.7%), followed by migraine without aura (6.7%) and gallbladder disease (6.7%). In univariate analysis, age ≥ 35 years (UOR = 2.77, p = 0.01), residence in Mount Lebanon (UOR = 4.88, p = 0.001) or North Lebanon (UOR = 4.15, p = 0.001), and specific comorbidities were significantly associated with ineligibility. In multivariable analysis, only migraines with aura remained an independent predictor (AOR = 4.684, p = 0.04), suggesting high-risk clinical indicators are often overlooked during provision. Conclusion: High ineligibility highlights deficiencies in contraceptive screening in humanitarian contexts. Routine MEC-based assessments, and safer alternatives are urgently needed. Innovation and limitations: This study uniquely applies the WHO safety framework to a displaced population, revealing migraine with aura as a major safety barrier. Limitations include a cross-sectional design and reliance on self-reported medical data.
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