Profiling of cardio‐metabolic risk factors and medication utilisation among Type II diabetes patients in Ghana: a prospective cohort study. Issue 1 (7th September 2017)

• Record Type: Journal Article
• Authors: Adua, Eric; Roberts, Peter; Sakyi, Samuel Asamoah; Yeboah, Francis Agyemang; Dompreh, Albert; Frimpong, Kwasi; Anto, Enoch Odame; Wang, Wei
• Is Part Of: Clinical and translational medicine. Volume 6:Issue 1(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-09-07
• Subjects: Type II diabetes mellitus -- Hypertension -- Anti‐diabetic medications -- Risk factors -- Ghana; Clinical medicine -- Periodicals; Medicine, Experimental -- Periodicals; Medical innovations -- Periodicals; Molecular biology -- Periodicals; Pathology, Molecular -- Periodicals; 616.027
• DOI: 10.1186/s40169-017-0162-5
• Languages: English
• ISSNs: 2001-1326

Abstract

Abstract: Background: Type II diabetes mellitus (T2DM) is complicated by multiple cardio‐metabolic risk factors. Controlling these factors requires lifestyle modifications alongside utilisation of anti‐diabetic medications. Different glucose lowering [(biguanides (BIGs), sulfonylureas (SUAs), thiazolidinediones (TNZ)], lipid lowering (statins), and anti‐hypertensive medicines [angiotensin converting enzyme inhibitors (ACEIs), calcium channel blockers (CCBs), angiotensin II receptor blockers (ARBs) and central acting drugs (CADs)] have been approved for controlling hyperglycaemia, dyslipidaemia and hypertension respectively. Here, we examined factors that characterise T2DM and explored the response to medication therapy among T2DM patients. Methods: This prospective cohort study recruited 241 T2DM patients reporting at a clinic in Ghana, from January through to August, 2016. Each patient's demographic, medications and anthropometric data was obtained while information on medication adherence was captured using Morisky adherence scale‐8 (MMAS‐8). Fasting blood samples were collected for biochemical analysis. Results: The mean age of participants was 57.82 years for baseline and six‐month follow‐up. Physical activity differed at baseline and follow up (p < 0.05) but not body mass index (BMI). BIG alone, or in combination with SUA and TNZ did not improve glycaemic status at follow up (p > 0.05). Many participants using either ACEI or ARB were able to control their blood pressures. Among dyslipidaemia patients under statin treatment, there was an improved lipid profile at follow‐up. Conclusions: Statin medications are effective for reducing dyslipidaemia in T2DM patients. However, control of modifiable risk factors, particularly blood glucose and to a lesser degree blood pressure is suboptimal. Addressing these will require concomitant interventions including education on medication adherence and correct dietary plans, lifestyle modifications and physical activity.