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Abstract Background Over 80% of blindness in Kenya is due to curable or preventable causes and 7.5 m Kenyans currently need eye services. Embedding sociodemographic data collection into screening programmes could help identify the groups facing systematic barriers to care. We aimed to determine the sociodemographic characteristics that were associated with access among patients diagnosed with an eye problem and referred for treatment in the Vision Impact Programme, currently operating in Meru County. Method We used an embedded, pragmatic, cross-sectional design. A list of sociodemographic questions was developed with input from key stakeholders. The final question set included the following domains: age, gender, religion, marital status, disability, education, occupation, income, housing, assets, and health insurance. These were integrated into an app that is used to screen, refer, and check-in (register) participants within a major eye screening programme. We gathered data from 4,240 people who screened positive and were referred to their local outreach treatment clinic. We used logistic regression to identify which groups were facing the greatest barriers to accessing care. Results A quarter of those screened between April – July 2023 were found to have an eye problem and were referred, however only 46% of these people were able to access care. In our fully adjusted model, at the 0.05 level there were no statistically significant differences in the odds of attendance within the domains of disability, health insurance, housing, income, or religion. Strong evidence (p |
