Lung cancer symptoms awareness among Ethiopian adults: A latent class analysis

Background: There is limited evidence regarding lung cancer awareness in developing countries. In Ethiopia, 92.2% of lung cancer patients present at facilities with late stages, leading to poor treatment outcomes. This emphasizes the importance of early detection. Symptom awareness is crucial for reducing delays. This study aimed to identify latent classes of lung cancer symptom awareness and their predictors, guiding class-specific interventions. Methods: A population-based cross-sectional survey was conducted from October to December 2023 among a randomly selected 2388 adults in Addis Ababa, Ethiopia. A face-to-face interview was conducted using the validated Lung Cancer Awareness Measure (Lung CAM). Latent class analysis and latent class multinomial logistic regression were used to identify classes and predictors of class membership. Results: Three distinct classes of participants were identified: “poor awareness” (Class 1: 38%), “fair awareness” (Class 2: 37.5%), and “good awareness” (Class 3: 24.5%). The average symptom awareness score was 7.8 out of 14. The most commonly recognized symptom was coughing up blood (72%), while changes in the shape of fingers were the least recognized (20%). Being male, employed, having a higher education level, using out-of-pocket money for health expenses, and knowing someone with cancer significantly increased the odds of belonging to the “good awareness” class, with adjusted odds ratios ranging from 1.66 to 12.60. Conclusion: Only one-fourth of participants were classified as class 3, denoted as “good awareness,” indicating a significant gap in symptom awareness. Respiratory symptoms were mostly well-known. Class membership varied across sociodemographic and related characteristics. Hence, there is a need for class-specific educational intervention and a focus on non-respiratory symptoms.