Background Rapid epidemiological health transitions occurring in vulnerable populations in Africa that have an existing burden of infectious and non-communicable diseases predict an increased risk and consequent prevalence of kidney disease. However, few studies have characterised the true burden of kidney damage and associated risk factors in Africans. We investigated the prevalence of markers for kidney damage and known risk factors in rural and urban settings in sub-Saharan Africa. Methods In this cross-sectional population study (Africa Wits-International Network for the Demographic Evaluation of Populations and their Health Partnership for Genomic Studies [AWI-Gen]), we recruited unrelated adult participants aged 40-60 years from four rural community research sites (Nanoro, Burkina Faso; Navrongo, Ghana; Agincourt and Dikgale, South Africa), and two urban community research sites (Nairobi, Kenya; and Soweto, South Africa). Participants were identified and selected using random sampling frames already in use at each site. Participants completed a lifestyle and medical history questionnaire, had anthropometric and blood pressure measurements taken, and blood and urine samples were collected. Markers of kidney damage were defined as low estimated glomerular filtration rate (eGFR; <60 mL/min per 1·73 m²), presence of albuminuria (urine albumin creatinine ratio >3 mg/mmol); or chronic kidney disease (low eGFR or albuminuria, or both). We calculated ageadjusted prevalence of chronic kidney disease, low eGFR, and albuminuria by site and sex and used logistic regression models to assess risk factors of kidney damage.Findings Between August, 2013, and August, 2016, we recruited 10 702 participants, of whom 8110 were analysable. 4120 (50·8%) of analysable participants were male, with a mean age of 49·9 years (SD 5·8). Age-standardised population prevalence was 2·4% (95% CI 2·1-2·8) for low eGFR, 9·2% (8·4-10·0) for albuminuria, and 10·7% (9·9-11·7) for chronic kidney disease, with higher prevalences in South African sites than in west African sites (14·0% [11·9-16·4] in Agincourt vs 6·6% [5·5-7·9] in Nanoro). Women had a higher prevalence of chronic kidney disease (12·0% [10·8-13·2] vs 9·5% [8·3-10·8]) and low eGFR (3·0% [2·6-3·6] vs 1·7% [1·3-2·3]) than did men, with no sex-specific differences for albuminuria (9·9% [8·8-11·0] vs 8·4% [7·3-9·7]). Risk factors for kidney damage were older age (relative risk 1·04, 95% CI 1·03-1·05; p<0·0001), hypertension (1·97, 1·68-2·30; p<0·0001), diabetes (2·22, 1·76-2·78; p<0·0001), and HIV (1·65, 1·36-1·99; p<0·0001); whereas male sex was protective (0·85, 0·73-0·98; p=0·02).Interpretation Regional differences in prevalence and risks of chronic kidney disease in sub-Saharan Africa relate in part to varying stages of sociodemographic and epidemiological health transitions across the area. Public health policy should focus on integrated strategies for screening, prevention, and risk factor management in the broader non-communicable disease and infectious diseases framework.

South Africa is experiencing a steep rise in postgraduate candidature and a backlog in research training and supervision. Co-supervision is a means to address such challenges. This study investigated how co-supervision could effectively and efficiently be implemented within a Faculty of Health Sciences. Supervisors and postgraduates brainstormed co-supervisory practice to identify: (1) the reasons for co-supervision, (2) what co-supervisors should discuss to facilitate their interactions and (3) how best to initiate the novice supervisor into supervisory practice. Co-supervisors are formally appointed for different reasons and all co-supervisory activities should be directed towards meeting the purpose of that appointment. Points to consider in facilitating a co-supervisor memorandum of understanding and novice supervisor training were discussed. Our findings provide suggestions to develop accountable co-supervisory practices, enhance novice supervisor training and to design discipline-specific best practice policy at institutional level to enable a common understanding of co-supervisory roles and responsibilities. Threats to effective co-supervision identified were the implications of co-supervision in staff promotion, inequitable workload recognition and no official acknowledgement of informal supervisory activities. Unless these issues are addressed, the full potential of co-supervision will remain unrealised. Supervision pedagogy and research teaching is a sophisticated skill worthy of professionalisation.

Summary:Immunoenzymometric assays (lEMAs) for human insulin and intact proinsulin were developed using the amplification system developed by Johannsson et al. (Clin. Chim. Acta 148 (1985) 119 -124) for the detection of the enzyme alkaline phosphatase. The detection limit of the assays was 0.8 pmol/1 for proinsulin and 0.8 pmol/1 for insulin whereas it was 1.8 pmol/1 and 2.3 pmol/1 respectively for the homologous immunoradiometric assays (IRMA). These assays are superior to immunoradiometric assays in terms of sensitivity, shelf-life of the labelled antibody and suitability for automation.

Genetic associations for lipid traits have identified hundreds of variants with clear differences across European, Asian and African studies. Based on a sub-Saharan-African GWAS for lipid traits in the population cross-sectional AWI-Gen cohort (N = 10,603) we report a novel LDL-C association in the GATB region (P-value=1.56 × 10−8). Meta-analysis with four other African cohorts (N = 23,718) provides supporting evidence for the LDL-C association with the GATB/FHIP1A region and identifies a novel triglyceride association signal close to the FHIT gene (P-value =2.66 × 10−8). Our data enable fine-mapping of several well-known lipid-trait loci including LDLR, PMFBP1 and LPA. The transferability of signals detected in two large global studies (GLGC and PAGE) consistently improves with an increase in the size of the African replication cohort. Polygenic risk score analysis shows increased predictive accuracy for LDL-C levels with the narrowing of genetic distance between the discovery dataset and our cohort. Novel discovery is enhanced with the inclusion of African data.