Determinants of Health Education Utilization Among Afghan Immigrants in Southeast Iran: An Application of Anderson’s Model

This study examines the factors that determine the use of educational services as part of primary healthcare for immigrants in Sistan and Balochistan Province, Iran.

A cross-sectional study selected 1,000 Afghan immigrants (≥18 years) via multi-stage sampling. Anderson's behavioral model of health service utilization was employed to assess the effects of predisposing and enabling variables, health behaviors, and needs on the use of health education services. Multivariable logistic regression was used to predict key determinants.

The study revealed that 60% of immigrants received health education in the past year, but only 24.33% found it comprehensible. There were variations in utilization and needs across different ages and genders. While 57.5% of respondents preferred online health education, 88.92% favored receiving health information from their peers, highlighting the value of peer-led education. Health education priorities included prevention/treatment of noncommunicable diseases (32%) and children’s healthcare (49.04%). Chi-square tests identified factors such as age, gender, marital status, religion, having children, employment, working hours, health knowledge, and general health status as significant determinants. Logistic regression analysis showed that male immigrants were less likely to utilize four types of health education (communicable and non-communicable diseases, prenatal care, and childcare) compared to females.

Our findings reveal a critical disconnect between health education access and comprehension, underscoring urgent needs for culturally/linguistically adapted materials. A pronounced gender disparity emerged, with men significantly underutilizing services across all domains due to occupational barriers and time constraints. Crucially, migrants expressed strong preferences for peer-delivered education and digital platforms, highlighting systemic gaps in current standardized approaches and opportunities for technology-mediated solutions.

Policymakers should focus on removing structural barriers by offering culturally sensitive programs and using AI-driven tools to improve access to health education for immigrants.