Prevalence and Associated Factors of Self‐Reported Myopia Among Undergraduate Students in the Northern Region of Bangladesh: A Cross‐Sectional Study

Background and Aims: Myopia is an increasingly important public health concern worldwide, particularly among young adults. While previous research has applied machine learning techniques to identify myopia-related risk factors, evidence based on traditional statistical models using the same datasets remains limited. This study aimed to estimate the prevalence of self-reported myopia and examine its associated factors among undergraduate students in the northern region of Bangladesh. Methods: < 0.05. Results: The prevalence of self-reported myopia among the participants was 43.2%. Factors significantly associated with myopia included a family history of myopia (OR: 5.12; 95% CI: 3.22-8.13), premature birth (OR: 2.52; 95% CI: 1.25-6.03), visual stress (OR: 3.65; 95% CI: 2.37-5.12), uncertain response to visual stress (OR: 4.15; 95% CI: 2.25-6.76) and steroid use (OR: 2.11; 95% CI: 1.13-4.33). The logistic regression model demonstrated good discriminative ability, with an area under the receiver operating characteristic curve (AUC) of 0.836. Conclusion: This secondary data analysis indicates a high prevalence of myopia among undergraduate students in the northern region of Bangladesh. Several modifiable and non-modifiable factors, particularly family history, visual stress, and steroid use, were significantly associated with myopia. These findings underscore the importance of targeted public health strategies and support the use of traditional regression models as a transparent and interpretable alternative to machine learning approaches in epidemiological research.