Evaluating Obstructive Sleep Apnea Risk in Pregnancy: Insights from the STOP-BANG Questionnaire in Sar-e-pol, Afghanistan
Year: 2025
Type: article
Study design: Observational Study
Abstract: Objectives: Obstructive Sleep Apnea (OSA) causes recurrent airway obstruction during sleep, affecting 9–38% globally, with higher rates in obesity and chronic conditions. This study aimed to evaluate the risk of OSA among pregnant women in Kabul, Afghanistan, using the STOP-BANG questionnaire and to analyze associations between risk factors and adverse pregnancy outcomes. Methods: A descriptive cross-sectional study was conducted on 425 pregnant women in 2023–2024. Demographic, medical history, and OSA risk data were collected using the STOP-BANG questionnaire. Scores were categorized as low (0–2), moderate (3–4), or high (5–8). Statistical analysis assessed associations between OSA risk and variables such as body mass index (BMI), hypertension, and diabetes. Results: Most participants (91.8%) had low OSA risk, while 4.2% and 4.0% were classified as moderate and high risk, respectively. Hypertension was significantly associated with high OSA risk, with 55.0% of hypertensive participants in the high-risk category (p<0.001). Diabetes was also linked to moderate-to-high OSA risk (p=0.006). Elevated BMI (≥30) and older age (≥35 years) were strong predictors of higher OSA risk (p<0.001). Among participants with three or more miscarriages, OSA risk was notably elevated (p<0.05). Conclusion: OSA risk among pregnant women is associated with key factors including hypertension, diabetes, elevated BMI, and advanced maternal age. The STOP-BANG questionnaire proves to be an effective screening tool. Integrating OSA screening into antenatal care can help identify high-risk individuals, improve maternal health outcomes, and reduce complications associated with untreated OSA.
Authors: Sediqa Masoudi, Mohammad Shafiq Poya
Institution: Jami University
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4407573577