COMMUNITY ENGAGEMENT, ACCESS INEQUITIES, AND BEHAVIORAL CONSTRAINTS IN ITN UTILIZATION: EVIDENCE FROM TWO MALARIA-ENDEMIC LOCAL GOVERNMENT AREAS IN NIGERIA

Abstract

Malaria remains a major public health burden in Nigeria, which accounts for the highest number of malaria cases and deaths globally. Despite widespread insecticide-treated net (ITN) distribution campaigns, utilisation rates remain suboptimal. This study examined community engagement, access inequities, and behavioural constraints influencing ITN utilisation in two malaria-endemic Local Government Areas (LGAs) in Adamawa State, northeastern Nigeria. A community-based cross-sectional analytical study was conducted between July and October 2025 among 400 household heads or adult representatives (≥18 years) selected through multistage probability sampling from Yola North (urban, n=267) and Fufore (rural, n=133) LGAs. Data were collected using a pre-tested, interviewer-administered semi-structured questionnaire. Descriptive statistics, Chi-square tests, binary logistic regression, and ordinal logistic regression were employed. Statistical significance was set at p < 0.05. Regular community education programmes on ITN care were reported by only 5.2% in Yola North and 8.3% in Fufore. Lack of information was the predominant maintenance challenge (38.9% in Yola North; 83.5% in Fufore). Significant rural–urban disparities were observed in awareness of ITN importance (p=0.030), ease of access (p<0.001), affordability (p<0.001), perceived malaria risk (p=0.020), and influence of cultural beliefs (p=0.010). Higher educational attainment independently predicted ITN use (Diploma: OR=2.10, 95% CI: 95%CI:1.12–3.93; Degree: OR=2.50, 95% 95%CI:1.40-4.30; MSc+: OR=2.85, 95% CI: 95%CI:1.32–6.14) and comfort (Degree: aOR=1.85, 95% 95%CI:1.15-2.98; MSc+: aOR=2.00, 95% CI: 1.05-3.80). Exposure to regular community programmes was the strongest predictor of both ITN use (OR=3.15, 95% 95%CI:1.40-7.09) and comfort (aOR=2.40, 95% 95%CI:1.35-4.27). Age and gender were not significant predictors.