» Articles » PMID: 28950847

The Extent and Determinants of Diabetes and Cardiovascular Disease Comorbidity in South Africa - Results from the South African National Health and Nutrition Examination Survey (SANHANES-1)

Overview
Publisher Biomed Central
Specialty Public Health
Date 2017 Sep 28
PMID 28950847
Citations 6
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Diabetes is a major health problem and cause of death worldwide. It is predicted that the prevalence of diabetes will increase from 415 million in 2015 to 642 million in 2040. However, the burden of diabetes in low- and middle-income countries is not clearly understood, particularly its interaction with other chronic illnesses. This study investigates the self-reported prevalence of and factors associated with diabetes and cardiovascular comorbidity in South Africa.

Methods: Data used in this study are from the 2012 South African National Health and Nutrition Examination Survey; a nationally representative cross-sectional household survey (N = 25,532). Diabetes and cardiovascular disease comorbidity was defined as the coexistence of diabetes plus one or more cardiovascular diseases reported at the time of the survey. This study makes use of multinomial logistic regression models to analyse the relationship between diabetes - cardiovascular disease comorbidity and several predictors including race, income, socio-economic status and obesity.

Results: According to the survey data we analysed, 5% of South Africans aged 15 and above had self-reported diabetes in 2011-2012. Among those with self-reported diabetes, 73% had at least one additional cardiovascular chronic illness. Diabetes and its cardiovascular disease comorbidity was more prevalent in Africans (66%), females (66%), those who lived in urban areas (75%), had secondary education (44%) and were unemployed (62%). Factors strongly associated with diabetes - cardiovascular disease comorbidity were older age (Odds ratio [OR] 1.09; 95% Confidence Interval [CI] 1.06-1.12), high household income (0.27; 0.10-0.76) versus low income, moderate (0.33; 0.11-0.96) and good self-rated health (0.24; 0.08-0.68) versus bad self-rated health, occasional (0.29; 0.10-0.88) and regular smokers (0.25; 0.12-0.53) versus non-smokers and physical activity (0.15; 0.03-0.68) versus no physical activity.

Conclusion: The study provides insight into the factors associated with cardiovascular disease comorbidity in diabetic individuals. The findings indicate that there are differences in the factors associated with diabetes and those associated with diabetes - cardiovascular disease comorbidity. This provides information, which can be used to design programmes that encourage healthy lifestyles in people living with diabetes.

Citing Articles

Determinants of cardiovascular disease among type 2 diabetic patients attending diabetic follow-up clinic in Arba Minch general hospital, southern Ethiopia: an unmatched case-control study.

Annose R, Asefa H, Gezahagn Y, Abebe G, Hailu Zewde T Ann Med Surg (Lond). 2024; 86(5):2467-2473.

PMID: 38694275 PMC: 11060215. DOI: 10.1097/MS9.0000000000001951.


Multimorbidity in African ancestry populations: a scoping review.

Kamp M, Achilonu O, Kisiangani I, Nderitu D, Mpangase P, Tadesse G BMJ Glob Health. 2023; 8(12).

PMID: 38084495 PMC: 10711865. DOI: 10.1136/bmjgh-2023-013509.


Multimorbidity of cardiometabolic diseases: a cross-sectional study of patterns, clusters and associated risk factors in sub-Saharan Africa.

Otieno P, Asiki G, Wekesah F, Wilunda C, Sanya R, Wami W BMJ Open. 2023; 13(2):e064275.

PMID: 36759029 PMC: 9923299. DOI: 10.1136/bmjopen-2022-064275.


Comparison of the Ability of Anthropometric Indices to Predict the Risk of Diabetes Mellitus in South African Males: SANHANES-1.

Sekgala M, Sewpaul R, Opperman M, Mchiza Z Int J Environ Res Public Health. 2022; 19(6).

PMID: 35328910 PMC: 8949079. DOI: 10.3390/ijerph19063224.


Demographic stratification of Type 2 diabetes and comorbidities in district healthcare in KwaZulu-Natal.

Chetty L, Govender N, Govender G, Reddy P S Afr Fam Pract (2004). 2021; 63(1):e1-e9.

PMID: 33881328 PMC: 8377998. DOI: 10.4102/safp.v63i1.5218.


References
1.
Pan X, Li G, Hu Y, Wang J, Yang W, An Z . Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance. The Da Qing IGT and Diabetes Study. Diabetes Care. 1997; 20(4):537-44. DOI: 10.2337/diacare.20.4.537. View

2.
Ording A, Sorensen H . Concepts of comorbidities, multiple morbidities, complications, and their clinical epidemiologic analogs. Clin Epidemiol. 2013; 5:199-203. PMC: 3704301. DOI: 10.2147/CLEP.S45305. View

3.
Agborsangaya C, Lau D, Lahtinen M, Cooke T, Johnson J . Multimorbidity prevalence and patterns across socioeconomic determinants: a cross-sectional survey. BMC Public Health. 2012; 12:201. PMC: 3353224. DOI: 10.1186/1471-2458-12-201. View

4.
Folb N, Timmerman V, Levitt N, Steyn K, Bachmann M, Lund C . Multimorbidity, control and treatment of noncommunicable diseases among primary healthcare attenders in the Western Cape, South Africa. S Afr Med J. 2015; 105(8):642-7. PMC: 4797628. DOI: 10.7196/samjnew.8794. View

5.
Egbujie B, Igumbor E, Puoane T . A cross-sectional study of socioeconomic status and cardiovascular disease risk among participants in the Prospective Urban Rural Epidemiological (PURE) Study. S Afr Med J. 2016; 106(9):900-6. DOI: 10.7196/SAMJ.2016.v106i9.10456. View