Genetic risk of type 2 diabetes in populations of the African continent: A systematic review and meta-analyses

Yako, Yandiswa Y; Guewo-Fokeng, Magellan; Balti, Eric Vounsia; Bouatia-Naji, Nabila; Matsha, Tandi E.; Sobngwi, Eugène; Erasmus, Rajiv T; Echouffo‐Tcheugui, Justin B.; Kengne, André Pascal

doi:10.1016/j.diabres.2016.01.003

Cited by 25 publications

(15 citation statements)

References 93 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Epigenetic changes have also been shown to have differential effects on diabetes incidence depending on the population studied, and such changes might be very important in African populations given early-life risks of undernutrition. 31 Studies 30,31 in sub-Saharan African populations suggest that natural selection has acted on several genomic regions associated with obesity and type 2 diabetes, and a study 32 that mapped the genetic risk of type 2 diabetes by measuring the allelic frequency of 16 diabetes-associated variants in 51 populations suggested that Africans face the greatest known genetic risk for type 2 diabetes of any ethnicity studied thus far.…”

Section: Genetics Of Type 2 Diabetes In Sub-saharan Africamentioning

confidence: 99%

Diabetes in sub-Saharan Africa: from clinical care to health policy

Atun

Davies

Gale

et al. 2017

The Lancet Diabetes & Endocrinology

Self Cite

366

432

View full text Add to dashboard Cite

Key message 2: diabetes and its consequences are costly to patients and economies We estimate that, in 2015, the overall cost of diabetes in sub-Saharan Africa was US$19•45 billion or 1•2% of cumulative gross domestic product (GDP). Around $10•81 billion (55•6%) of this cost arose from direct costs, which included expenditure on diabetes treatment (eg, medication, hospital stays, and treatment of complications), with out-of-pocket expenditure likely to exceed 50% of the overall health expenditure in many countries. We estimate that the total cost will increase to between $35•33 billion (1•1% of GDP) and $59•32 billion (1•8% of GDP) by 2030. Putting in place systems to prevent, detect, and manage hyperglycaemia and its consequences is therefore warranted from a health economics perspective. Key message 3: health systems in countries in sub-Saharan Africa are unable to cope with the current burden of diabetes and its complications By use of information from WHO Service Availability Readiness Assessment surveys and World Bank Service Delivery Indicator surveys and the local knowledge of Commissioners, we found inadequacies at all levels of the health system required to provide adequate management for diabetes and its associated risk factors and sequelae. We found inadequate availability of simple equipment for diagnosis and monitoring, a lack of sufficiently knowledgable health-care providers, insufficient availability of treatments, a dearth of locally appropriate guidelines, and few disease registries. These inadequacies result in a substantial dropoff of patients along the diabetes care cascade, with many patients going undiagnosed and with those who are diagnosed not receiving the advice and drugs they need. We also noted scarce facilities to manage the microvascular and macro vascular complications of diabetes. Additionally, despite calls for adding the care of diabetes and other cardiovascular risk factors onto existing infectious disease programmes (such as those for HIV), we found little evidence that such combined programmes are successful at improving outcomes.

show abstract

Section: Genetics Of Type 2 Diabetes In Sub-saharan Africamentioning

confidence: 99%

Diabetes in sub-Saharan Africa: from clinical care to health policy

Atun

Davies

Gale

et al. 2017

The Lancet Diabetes & Endocrinology

Self Cite

366

432

View full text Add to dashboard Cite

show abstract

“… 1 Furthermore, economic growth and accompanying rapid urbanization have led to a burgeoning wealthier middle class, possibly with shifts in diet and physical activity contributing to the development of obesity. This, with a genetic predisposition and epigenetic changes, 2 , 3 increases the risk of diabetes. 4…”

Section: Introductionmentioning

confidence: 99%

Trends in obesity and diabetes across Africa from 1980 to 2014: an analysis of pooled population-based studies

Kengne¹,

Bentham²,

Zeng³

et al. 2017

International Journal of Epidemiology

201

104

View full text Add to dashboard Cite

BackgroundThe 2016 Dar Es Salaam Call to Action on Diabetes and Other non-communicable diseases (NCDs) advocates national multi-sectoral NCD strategies and action plans based on available data and information from countries of sub-Saharan Africa and beyond. We estimated trends from 1980 to 2014 in age-standardized mean body mass index (BMI) and diabetes prevalence in these countries, in order to assess the co-progression and assist policy formulation.MethodsWe pooled data from African and worldwide population-based studies which measured height, weight and biomarkers to assess diabetes status in adults aged ≥ 18 years. A Bayesian hierarchical model was used to estimate trends by sex for 200 countries and territories including 53 countries across five African regions (central, eastern, northern, southern and western), in mean BMI and diabetes prevalence (defined as either fasting plasma glucose of ≥ 7.0 mmol/l, history of diabetes diagnosis, or use of insulin or oral glucose control agents).ResultsAfrican data came from 245 population-based surveys (1.2 million participants) for BMI and 76 surveys (182 000 participants) for diabetes prevalence estimates. Countries with the highest number of data sources for BMI were South Africa (n = 17), Nigeria (n = 15) and Egypt (n = 13); and for diabetes estimates, Tanzania (n = 8), Tunisia (n = 7), and Cameroon, Egypt and South Africa (all n = 6). The age-standardized mean BMI increased from 21.0 kg/m2 (95% credible interval: 20.3–21.7) to 23.0 kg/m2 (22.7–23.3) in men, and from 21.9 kg/m2 (21.3–22.5) to 24.9 kg/m2 (24.6–25.1) in women. The age-standardized prevalence of diabetes increased from 3.4% (1.5–6.3) to 8.5% (6.5–10.8) in men, and from 4.1% (2.0–7.5) to 8.9% (6.9–11.2) in women. Estimates in northern and southern regions were mostly higher than the global average; those in central, eastern and western regions were lower than global averages. A positive association (correlation coefficient ≃ 0.9) was observed between mean BMI and diabetes prevalence in both sexes in 1980 and 2014.ConclusionsThese estimates, based on limited data sources, confirm the rapidly increasing burden of diabetes in Africa. This rise is being driven, at least in part, by increasing adiposity, with regional variations in observed trends. African countries’ efforts to prevent and control diabetes and obesity should integrate the setting up of reliable monitoring systems, consistent with the World Health Organization’s Global Monitoring System Framework.

show abstract

“…MTHRF is the enzyme that catalyzes the conversion of 5,10-methylenetetrahydrofolate to 5-methyltetrahydrofolate whose deficiency increases plasmatic homocysteine concentrations. Both polymorphisms had been previously studied for the association to T2D with conflicting results in different ethnic groups (4,5). No association of these polymorphisms with T2D was found by Pirozzi and cols., in agreement with a previous study performed in Brazilian patients from the South region, which also did not find association of T2D with rs1799752 in the ACE gene (6).…”

Section: (Epi) Genetics and The Complexity Of Diabetes Mellitusmentioning

confidence: 99%

(Epi) Genetics and the complexity of diabetes mellitus

Corrêa-Giannella¹

2018

Archives of Endocrinology and Metabolism

View full text Add to dashboard Cite

Genetic risk of type 2 diabetes in populations of the African continent: A systematic review and meta-analyses

Cited by 25 publications

References 93 publications

Diabetes in sub-Saharan Africa: from clinical care to health policy

Diabetes in sub-Saharan Africa: from clinical care to health policy

Trends in obesity and diabetes across Africa from 1980 to 2014: an analysis of pooled population-based studies

(Epi) Genetics and the complexity of diabetes mellitus

Contact Info

Product

Resources

About