Aprill Z Dawson1, Rebekah J Walker1, Jennifer A Campbell1, Joni S Williams1, Leonard E Egede2. 1. Division of General Internal Medicine, Department of Medicine, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, United States; Center for Advancing Population Science, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, United States. 2. Division of General Internal Medicine, Department of Medicine, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, United States; Center for Advancing Population Science, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, United States. Electronic address: legede@mcw.edu.
Abstract
OBJECTIVE: The aims of this study were to understand the prevalence and sociodemographic characteristics associated with diabetes among adults in Namibia and South Africa. METHODS: Data from the Demographic and Health Survey for Namibia (2013) and South Africa (2016) were analyzed. The dependent variable, diabetes, was defined using lab values for blood glucose≥ 126 for Namibia, and hemoglobin A1c (HbA1c) ≥ 6.5% for South Africa. Logistic regression was used to identify independent correlates of diabetes for each country. Demographic (age, sex, geographic location, number of children), economic (wealth index, education level), and cultural (religion - Namibia, ethnicity - South Africa) factors were added in blocks to the models. RESULTS: In Namibia, 4.6% had diabetes based on blood glucose, and 14.6% had diabetes based on HbA1c in South Africa. In Namibia, after adjustment, higher wealth was independently associated with diabetes (OR:1.67; 95% CI: 1.11, 2.50). In South Africa, after adjustment, those who were older (OR: 1.06; 95% CI: 1.04, 1.07), female (OR: 1.25; 95% CI: 1.03, 1.52), lived in a rural area (OR: 1.54; 95% CI: 1.20, 1.96), and Black (OR: 2.27; 95% CI: 1.17, 4.42) or Other (OR: 5.74; 95% CI: 2.50, 13.20) compared to White, had increased odds of diabetes. CONCLUSIONS: Prevalence of diabetes is high in South Africa and relatively low in Namibia using reliable laboratory diagnostic indices. Strategies to address the rising burden of non-communicable diseases like diabetes are needed in sub-Saharan Africa.
OBJECTIVE: The aims of this study were to understand the prevalence and sociodemographic characteristics associated with diabetes among adults in Namibia and South Africa. METHODS: Data from the Demographic and Health Survey for Namibia (2013) and South Africa (2016) were analyzed. The dependent variable, diabetes, was defined using lab values for blood glucose≥ 126 for Namibia, and hemoglobin A1c (HbA1c) ≥ 6.5% for South Africa. Logistic regression was used to identify independent correlates of diabetes for each country. Demographic (age, sex, geographic location, number of children), economic (wealth index, education level), and cultural (religion - Namibia, ethnicity - South Africa) factors were added in blocks to the models. RESULTS: In Namibia, 4.6% had diabetes based on blood glucose, and 14.6% had diabetes based on HbA1c in South Africa. In Namibia, after adjustment, higher wealth was independently associated with diabetes (OR:1.67; 95% CI: 1.11, 2.50). In South Africa, after adjustment, those who were older (OR: 1.06; 95% CI: 1.04, 1.07), female (OR: 1.25; 95% CI: 1.03, 1.52), lived in a rural area (OR: 1.54; 95% CI: 1.20, 1.96), and Black (OR: 2.27; 95% CI: 1.17, 4.42) or Other (OR: 5.74; 95% CI: 2.50, 13.20) compared to White, had increased odds of diabetes. CONCLUSIONS: Prevalence of diabetes is high in South Africa and relatively low in Namibia using reliable laboratory diagnostic indices. Strategies to address the rising burden of non-communicable diseases like diabetes are needed in sub-Saharan Africa.
Authors: Rifat Atun; Justine I Davies; Edwin A M Gale; Till Bärnighausen; David Beran; Andre Pascal Kengne; Naomi S Levitt; Florence W Mangugu; Moffat J Nyirenda; Graham D Ogle; Kaushik Ramaiya; Nelson K Sewankambo; Eugene Sobngwi; Solomon Tesfaye; John S Yudkin; Sanjay Basu; Christian Bommer; Esther Heesemann; Jennifer Manne-Goehler; Iryna Postolovska; Vera Sagalova; Sebastian Vollmer; Zulfiqarali G Abbas; Benjamin Ammon; Mulugeta Terekegn Angamo; Akhila Annamreddi; Ananya Awasthi; Stéphane Besançon; Sudhamayi Bhadriraju; Agnes Binagwaho; Philip I Burgess; Matthew J Burton; Jeanne Chai; Felix P Chilunga; Portia Chipendo; Anna Conn; Dipesalema R Joel; Arielle W Eagan; Crispin Gishoma; Julius Ho; Simcha Jong; Sujay S Kakarmath; Yasmin Khan; Ramu Kharel; Michael A Kyle; Seitetz C Lee; Amos Lichtman; Carl P Malm; Maïmouna N Mbaye; Marie A Muhimpundu; Beatrice M Mwagomba; Kibachio Joseph Mwangi; Mohit Nair; Simon P Niyonsenga; Benson Njuguna; Obiageli L O Okafor; Oluwakemi Okunade; Paul H Park; Sonak D Pastakia; Chelsea Pekny; Ahmed Reja; Charles N Rotimi; Samuel Rwunganira; David Sando; Gabriela Sarriera; Anshuman Sharma; Assa Sidibe; Elias S Siraj; Azhra S Syed; Kristien Van Acker; Mahmoud Werfalli Journal: Lancet Diabetes Endocrinol Date: 2017-07-05 Impact factor: 32.069
Authors: Melanie Y Bertram; Aneil V S Jaswal; Victoria Pillay Van Wyk; Naomi S Levitt; Karen J Hofman Journal: Glob Health Action Date: 2013-01-24 Impact factor: 2.640
Authors: Marília B Gomes; Fengming Tang; Hungta Chen; Javier Cid-Ruzafa; Peter Fenici; Kamlesh Khunti; Wolfgang Rathmann; Marina V Shestakova; Filip Surmont; Hirotaka Watada; Jesús Medina; Iichiro Shimomura; Gabriela Luporini Saraiva; Andrew Cooper; Antonio Nicolucci Journal: Front Endocrinol (Lausanne) Date: 2022-04-22 Impact factor: 6.055