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Objective: To identify criteria that affect uptake of diabetes retinal screening in a community screening program using mobile retinal digital photography units.Research Design and Methods: Data from the regional diabetes population-based retinal screening program and regional ophthalmology laser database were linked to patient postal code (zip code) data. We used distance from retinal screening event, social deprivation scores, and demographic information to identify risk factors for nonattendance at a diabetes retinal screening event. Patients were subdivided into urban (>125,000 population), other urban (3,000-125,000 population), or rural (<3,000 population) depending on where they lived. Data were collected from 2004 to 2006 inclusive and included 15,150 patients and 32,621 eye screening records.Results: The mean +/- SD age of patients was 63 +/- 15 years, and 54% were male. Mean travel time to retinal screening event varied from 7.1 to 17.0 min. For 12% of missed appointments, patients were more likely to be younger, to have longer diabetes duration, to have poor A1C and blood pressure control, to be smokers, and to live in deprived areas. Poor attendance was not associated with sex or distance to retinal screening event.Conclusions: Social deprivation is strongly associated with poor attendance at retinal screening events. Time traveled to screening event was not associated with attendance in this study of a mobile retinal screening service, which visited general practitioner surgeries. This data can help inform population-based diabetes retinal screening programs about improving patient uptake. [ABSTRACT FROM AUTHOR]

OBJECTIVE: We aim to correlate the incidence of diabetic retinopathy and maculopathy requiring laser treatment with the control of risk factors in the diabetic population of Tayside, Scotland, for the years 2001-2006. RESEARCH DESIGN AND METHODS: Retinal laser treatment, retinal screening, and diabetes care databases were linked for calendar years 2001-2006. Primary end points were the numbers of patients undergoing first or any laser treatment for diabetic retinopathy or maculopathy. Mean A1C and blood pressure and retinal screening rates were followed over the study period. RESULTS: Over 6 years, the number of patients with diabetes in Tayside increased from 9,694 to 15,207 (57% increase). The number of patients receiving laser treatment decreased from 222 to 138 and first laser treatments decreased from 100 (1.03% of diabetic population) to 56 (0.37%). The number of patients with type 2 diabetes treated for maculopathy decreased from 180 in 2001 to 103 in 2006 (43% reduction, P = 0.03). Mean A1C decreased for type 1 and type 2 diabetic populations (P < 0.01) and a reduction in blood pressure was observed in type 2 diabetic patients (P < 0.01). The number of patients attending annual digital photographic retinopathy screening increased from 3,012 to 11,932. CONCLUSIONS: Laser treatment for diabetic maculopathy in type 2 diabetic patients has decreased in Tayside over a six-year period, despite an increased prevalence of diabetes and increased screening effort. We propose that earlier identification of type 2 diabetes and improved risk factor control has reduced the incidence of maculopathy severe enough to require laser treatment. [ABSTRACT FROM AUTHOR]