Multi-ethnic differences in HbA1c, blood pressure, and low-density-lipid cholesterol control among South Africans living with type 2 diabetes after a 4-year follow-up

Abstract

PurposeOur study set out to examine if disparities in control of glycated hemoglobin (HbA1c), blood pressure (BP), and low-density-lipoprotein cholesterol (LDL-C) existed among an urban multi-ethnic cohort of South Africans, living with type 2 diabetes mellitus (T2DM).Patients and methodsThis longitudinal, retrospective study consisted of 261 men and women with previously diagnosed T2DM who attended Charlotte Maxeke Johannesburg Academic Hospital, South Africa across two time periods 2009 and 2013. Demographic and clinical data were extracted from consecutive medical records. The primary outcome was to determine achievements in HbA1c, BP, and LDL-C among ethnic groups using evidence-based goals.ResultsThe mean age of the cohort was 64 (±10.6) years, females represented 55%, and the self-reported diabetes duration was 16 (±10.6) years as at 2013. Black Africans (42.9%, n=112 of 261) were more likely to reach the HbA1c target (<7%) and less likely to have had retinopathy, nephropathy, or cardiovascular disease. Over two-thirds of mixed-ancestry patients attained the BP target (<140/80 mmHg), while 90.2% of Caucasians achieved LDL-C goals (<2.5 mmol/L). Overall, across the ethnic groups studied, we found that HbA1c control deteriorated over time, although BP levels remained the same and LDL-C levels drastically improved.ConclusionThere was poor control of HbA1c, BP, and LDL-C across all ethnic groups. Although a minority achieved recommended targets, some ethnic groups appeared to have worse control than others. Timely aggressive actions in particularly high-risk ethnic groups will prevent/delay the complications commonly associated with T2DM.

The prevalence and risk factors for diabetes mellitus in healthcare workers at Tygerberg hospital, Cape Town, South Africa: a retrospective study

“…Ethnicity is not considered as an independent risk factor for T2DM in this analysis, although individuals with either a mixed or black African ancestry have a greater risk due to their genetic predisposition. [22][23][24] The predicted T2DM risk of this study population may thus be an underestimation.…”

“…It is, however, well known that individuals with either a mixed or black African ancestry have a greater risk of developing T2DM due to a presumed genetic predisposition. [22][23][24][25] It is thus noteworthy that the predicted T2DM risk of this study population is likely to be an underestimation. Despite this limitation, the current study identified an opportunity for interventional strategies towards T2DM risk reduction by targeting specific modifiable risk factors.…”

Identifying gaps in the continuum of care for cardiovascular disease and diabetes in two communities in South Africa: Baseline findings from the HealthRise project

“…Low rates of control were notable among those with hypertension, hypercholesterolemia and diabetes, and comparable to prior estimates in South Africa. [ 39 , 40 ] The fact that such a small percentage of patients have well-controlled disease is not a surprise given that the study was performed in districts that are historically underserved. These findings further support the importance of the future HealthRise demonstration projects.…”

Poor blood pressure control and its associated factors among peoples living with Diabetes Mellitus in sub-Saharan Africa: A Systematic Review and Meta-analysis

“…Of the 21 studies, 5 were from South Africa(42)(43)(44)(45)(46), 5 from Ethiopia(11,(47)(48)(49)(50), 3 from Kenya (51-53), 2 from Tanzania (54, 55), 2 from Nigeria (56, 57), and 1 from Cameron (58), Uganda (59), Botswana(60), and Ghana(61). All studies were institution based cross-sectional studies.…”

“…All studies were institution based cross-sectional studies. To de ne poor blood pressure control, BP cut point of ≥140/90 was used by 11 studies(11,43,47,48,50,53,(62)(63)(64)(65)(66), ≥140/80 by 3 studies(45,59,67) and ≥130/80 by 7 studies (44, 52, 54-56, 58) (Table 1).…”