Assessment of prevalence and risk factors of diabetes and pre-diabetes in South Africa

Abstract

Background: Diabetes prevalence, as well as that of pre-diabetes, is rapidly increasing in South Africa. Individuals with pre-diabetes have a high risk of developing type 2 diabetes, which is reversible with a change in lifestyle. If left untreated, diabetes can lead to serious health complications. Our objective was to assess the prevalence of diabetes and pre-diabetes, and to investigate the associated risk factors of each in the South African population.

Method: This study made use of the South African Demographic Health Survey 2016 data. The study participants included 6442 individuals aged 15 years and older. A generalized additive mixed model was employed to account for the complex survey design of the study as well as well spatial autocorrelation in the data.

Results: The observed prevalence of pre-diabetes and diabetes was 67% and 22%, respectively. Among those who had never been tested for diabetes prior to the survey, 10% of females and 6% of males were found to be diabetic, and 67% of both males and females were found to be pre-diabetic. Thus, a large proportion of the South African population remains undiagnosed. The model revealed both common and uncommon factors significantly associated with pre-diabetes and diabetes. This highlights the importance of considering diabetic status as a three-level categorical outcome, rather than binary. In addition, significant interactions between some of the lifestyle factors, demographic factors and anthropometric measures were revealed, which indicates that the effects each these factors have on the likelihood of an individual being pre-diabetic or diabetic is confounded by other factors.

Conclusion: The risk factors for diabetes and pre-diabetes are many and complicated. Individuals need to be aware of their diabetic status before health complications arise. It is therefore important for all stakeholders in government and the private sector of South Africa to get involved in providing education and creating awareness about diabetes. Regular testing of diabetes, as well as leading a healthy lifestyle, should be encouraged.

Keywords: Generalized additive mixed models; Spatial autocorrelation; Survey logistic regression.

Fig. 1

Conceptual framework of variables of interest for diabetes

Fig. 2

Diabetic status across different age groups

Fig. 3

Boxplots for the continuous covariates by diabetic status

Fig. 4

Interaction plot of waist-to-height ratio and salt consumption

Fig. 5

Interaction plot of waist-to-height ratio and body mass index category

Fig. 6

Interaction plot of approach towards salt consumption and consumption of fruit juice

Fig. 7

Interaction plot of perception of health and consumption of fruit juice

Fig. 8

Interaction plot of age and education level