Predictors of poor glycemic control among adults attending a peri-urban diabetic clinic in Wakiso district, Uganda: A cross-sectional study using modified Poisson regression analysis.

Background: Poor glycemic control, a contributor to the development of diabetes related complications among patients with diabetes mellitus, remains a public health challenge in low- and middle-income countries. In Uganda, limited evidence exists on predictors of poor glycemic control among diabetic patients attending peri-urban primary healthcare facilities. The study assessed predictors of poor glycemic control among adults attending the diabetic clinic at Kasangati Health Centre IV in Wakiso district. Methods: We conducted cross-sectional study among 283 diabetic patients attending Kasangati Health Centre IV between March and April 2025. Data were collected using interviewer-administered structured questionnaires and data abstraction tools. Poor glycemic control was defined as glycated hemoglobin (HbA1c) levels [≥]7%. Modified Poisson regression with robust standard errors was used to determine factors associated with poor glycemic control. Adjusted prevalence ratios (aPRs) with 95% confidence intervals (CIs) were reported. Results: Overall, 67.8% of the participants had poor glycemic control. Poor glycemic control was significantly associated with older age, low income status (aPR: 1.4, 95%CI: 1.24-1.58), use of multiple anti-diabetic medications, non-adherence to regular follow-up (aPR: 1.5, 95%CI: 1.33-1.65), medication side effects (aPR: 1.2, 95%CI: 1.01-1.32), physical inactivity (aPR: 1.1, 95%CI: 1.05-1.21), non-adherence to recommended dietary plans (aPR: 1.1, 95%CI: 1.02-1.22), perceived treatment regimen complexity (aPR: 1.2, 95%CI: 1.12-1.34), stress (aPR: 1.1, 95%CI: 1.08-1.20), lack of peer support groups (aPR: 1.2, 95%CI: 1.08-1.23), and high costs of accessing care (aPR: 1.2, 95%CI: 1.17-1.33). Conclusion: Almost two-thirds of the diabetic patients suffered from poor glycemic control which was determined by various socio-economic, behavioral, clinical and health system factors. Enhancing adherence counseling, encouraging healthy lifestyles, adopting age-based supportive healthcare approaches, better psychosocial support and reduction of cost barriers in accessing diabetic healthcare could improve the glycemic status of diabetic patients in peri-urban primary healthcare settings.