Prevalence of Diabetes, Prediabetes, and Associated Risk Factors Among Agricultural Village Residents in the Dominican Republic.

This study examined the prevalence and risk factors of prediabetes and type 2 diabetes among residents of agricultural settlement villages (bateyes) in the Dominican Republic. From March to April 2016, a cross-sectional, multi-stage cluster survey was conducted across the country's three agricultural regions (southwest, east, and north). At selected households, an adult completed a questionnaire to assess demographics, diabetes knowledge, and care, and two household residents of any age provided finger-prick blood samples that were analyzed for hemoglobin A1c (HbA1c). HbA1c was categorized as normal (< 5.7%), prediabetic (5.7-6.4%), or diabetic (≥ 6.5%). The prevalence rates of diabetes and prediabetes were 8.6% (95% confidence interval [CI], 6.2-11.8%) and 20.4% (95% CI, 17.9-23.2%), respectively, among all participants (N = 1293; median age, 35 years; range, 2-96 years), and 10.0% (95% CI, 7.2-13.8%) and 20.0% (95% CI, 17.4-23.0%), respectively, among adults 18 years or older (N = 730). The average age of participants with diabetes was 47.2 years. The average age of participants with prediabetes was 40.7 years. Among adult questionnaire respondents, 64.8% of all participants and 39.4% of patients with diabetes had not been tested for diabetes previously. Among patients with diabetes, 28.4% were previously diagnosed; 1.2% of prediabetes patients were previously diagnosed. Half (50.7%) of the respondents had heard of diabetes. The majority (94.1%) of patients previously diagnosed with diabetes reported using diabetes medication. Among both undiagnosed and previously diagnosed patients with diabetes, diabetes knowledge, previous diabetes testing, and diabetes care-seeking were lowest among Haitian-born participants. A high burden of undiagnosed diabetes and deficiencies in diabetes knowledge, access to care, and diagnosis exist among all batey inhabitants, but most acutely among Haitians. Improvements will require a multi-sectoral approach.