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Prevalence and predictors for being unscreened for diabetic retinopathy: a population-based study over a decade
Tina Felfeli1, Glen Katsnelson2, Alex Kiss3
1Department of Ophthalmology and Vision Sciences, University of Toronto, Toronto, ON; Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON; ICES, Toronto, ON.
Objective:
To determine the population-level predictors for being unscreened for diabetic retinopathy (DR) among individuals with diabetes in a developed country.
Design:
A retrospective population-based repeated-cross-sectional study.
Participants:
All individuals with diabetes (types 1 and 2) aged ≥20 years in the universal health care system in Ontario were identified in the 2011-2013 and 2017-2019 time periods.
Methods:
The Mantel-Haenszel test was used for the relative risk (RR) comparison of subcategories stratified by the 2 cross-sectional time periods.
Results:
A total of 1 145 645 and 1 346 578 individuals with diabetes were identified in 2011-2013 and 2017-2019, respectively. The proportion of patients unscreened for DR declined very slightly from 35% (n = 405 967) in 2011-2013 to 34% (n = 455 027) in 2017-2019 of the population with diabetes (RR = 0.967; 95% CI, 0.964-0.9693; p < 0.0001). Young adults aged 20-39 years of age had the highest proportion of unscreened patients (62% and 58% in 2011-2013 and 2017-2019, respectively). Additionally, those who had a lower income quintile (RR = 1.039; 95% CI, 1.036-1.044; p < 0.0001), were recent immigrants (RR = 1.286; 95% CI, 1.280-1.293; p < 0.0001), lived in urban areas (RR = 1.149; 95% CI, 1.145-1.154; p < 0.0001), had a mental health history (RR = 1.117; 95% CI, 1.112-1.122; p < 0.0001), or lacked a connection to a primary care provider (RR = 1.656; 95% CI, 1.644-1.668; p < 0.0001) had a higher risk of being unscreened.
Conclusions:
This population-based study suggests that over 1 decade, 33% of individuals with diabetes are unscreened for DR, and young age, low income, immigration, residing in a large city, mental health illness, and no primary care access are the main predictors.
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