Browsing by Author "Erasmus, Rajiv T"

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    Open Access
    Assessment of the association between plant-based dietary exposures and cardiovascular disease risk profile in sub-Saharan Africa: a systematic review
    (2022-02-19) Lopes, Tatum; Zemlin, Annalise E; Erasmus, Rajiv T; Madlala, Samukelisiwe S; Faber, Mieke; Kengne, Andre P
    Background Studies have investigated dietary attributes associated with cardiovascular disease (CVD) risk in Africa. However, there has been no effort to critically assess the existing evidence. This systematic review examined available evidence on the association between plant-based dietary exposures and CVD risk profile in Africa. PROSPERO registration number: CRD42020159862. Methods We conducted a literature search for observational studies reporting on plant-based dietary exposures in relation to CVD risk profile in African populations. PubMed-Medline, Scopus, EBSCOhost, and African Journals Online platforms were searched up to 19 March 2021. Titles and abstracts of the identified records were screened independently by two investigators. The quality of the studies was also assessed independently. Results Of 458 entries identified, 15 studies published between 2002 and 2020 were included in this review. These studies originated from 12 sub-Saharan Africa (SSA) countries. Sample sizes ranged from 110 to 2362, age from 18 to 80 years; and majority of participants were females (66.0%). In all, four plant-based dietary exposures were identified across SSA. Sixty percent of the studies reported a significant association between a plant-based dietary exposure with at least one CVD risk factor such as hypertension, diabetes mellitus, dyslipidaemia, overweight/obesity, and metabolic syndrome. Conclusions The few available studies suggest that there may be a protective effect of plant-based dietary exposures on CVD risk profile in the African setting. Nonetheless, more elaborated studies are still needed to address plant-based diet (PBD) adherence in relation with CVD risk in African populations.
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    Open Access
    Effects of different missing data imputation techniques on the performance of undiagnosed diabetes risk prediction models in a mixed-ancestry population of South Africa
    (Public Library of Science, 2015) Masconi, Katya L; Matsha, Tandi E; Erasmus, Rajiv T; Kengne, Andre P
    BACKGROUND: Imputation techniques used to handle missing data are based on the principle of replacement. It is widely advocated that multiple imputation is superior to other imputation methods, however studies have suggested that simple methods for filling missing data can be just as accurate as complex methods. The objective of this study was to implement a number of simple and more complex imputation methods, and assess the effect of these techniques on the performance of undiagnosed diabetes risk prediction models during external validation. METHODS: Data from the Cape Town Bellville-South cohort served as the basis for this study. Imputation methods and models were identified via recent systematic reviews. Models’ discrimination was assessed and compared using C-statistic and non-parametric methods, before and after recalibration through simple intercept adjustment. RESULTS: The study sample consisted of 1256 individuals, of whom 173 were excluded due to previously diagnosed diabetes. Of the final 1083 individuals, 329 (30.4%) had missing data. Family history had the highest proportion of missing data (25%). Imputation of the outcome, undiagnosed diabetes, was highest in stochastic regression imputation (163 individuals). Overall, deletion resulted in the lowest model performances while simple imputation yielded the highest C-statistic for the Cambridge Diabetes Risk model, Kuwaiti Risk model, Omani Diabetes Risk model and Rotterdam Predictive model. Multiple imputation only yielded the highest C-statistic for the Rotterdam Predictive model, which were matched by simpler imputation methods. CONCLUSIONS: Deletion was confirmed as a poor technique for handling missing data. However, despite the emphasized disadvantages of simpler imputation methods, this study showed that implementing these methods results in similar predictive utility for undiagnosed diabetes when compared to multiple imputation.
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    Optimal waist-to-height ratio values for cardiometabolic risk screening in an ethnically diverse sample of South African urban and rural school boys and girls
    (Public Library of Science, 2013) Matsha, Tandi E; Kengne, Andre-Pascal; Yako, Yandiswa Y; Hon, Gloudina M; Hassan, Mogamat S; Erasmus, Rajiv T
    BACKGROUND: The proposed waist-to-height ratio (WHtR) cut-off of 0.5 is less optimal for cardiometabolic risk screening in children in many settings. The purpose of this study was to determine the optimal WHtR for children from South Africa, and investigate variations by gender, ethnicity and residence in the achieved value. METHODS: Metabolic syndrome (MetS) components were measured in 1272 randomly selected learners, aged 10-16 years, comprising of 446 black Africans, 696 mixed-ancestry and 130 Caucasians. The Youden's index and the closest-top-left (CTL) point approaches were used to derive WHtR cut-offs for diagnosing any two MetS components, excluding the waist circumference. RESULTS: The two approaches yielded similar cut-off in girls, 0.465 (sensitivity 50.0, specificity 69.5), but two different values in boys, 0.455 (42.9, 88.4) and 0.425 (60.3, 67.7) based on the Youden's index and the CTL point, respectively. Furthermore, WHtR cut-off values derived differed substantially amongst the regions and ethnic groups investigated, whereby the highest cut-off was observed in semi-rural and white children, respectively, Youden's index0.505 (31.6, 87.1) and CTL point 0.475 (44.4, 75.9). CONCLUSION: The WHtR cut-off of 0.5 is less accurate for screening cardiovascular risk in South African children. The optimal value in this setting is likely gender and ethnicity-specific and sensitive to urbanization.
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    The agreement between fasting glucose and markers of chronic glycaemic exposure in individuals with and without chronic kidney disease: a cross-sectional study
    (2020-01-30) George, Cindy; Matsha, Tandi E; Korf, Marizna; Zemlin, Annalise E; Erasmus, Rajiv T; Kengne, Andre P
    Abstract Background To assess whether the agreement between fasting glucose and glycated proteins is affected by chronic kidney disease (CKD) in a community-based sample of 1621 mixed-ancestry South Africans. Methods CKD was defined as an estimated glomerular filtration rate < 60 ml/min/1.73 m2. Fasting plasma glucose and haemoglobin A1c (HbA1c) concentrations were measured by enzymatic hexokinase method and high-performance liquid chromatography, respectively, with fructosamine and glycated albumin measured by immunoturbidimetry and enzymatic method, respectively. Results Of those with CKD (n = 96), 79, 16 and 5% where in stages 3, 4 and 5, respectively. Those with CKD had higher levels of HbA1c (6.2 vs. 5.7%; p < 0.0001), glycated albumin (15.0 vs. 13.0%; p < 0.0001) and fructosamine levels (269.7 vs. 236.4 μmol/l; p < 0.0001), compared to those without CKD. Higher fasting glucose levels were associated with higher HbA1c, glycated albumin and fructosamine, independent of age, gender, and CKD. However, the association with HbA1c and glycated albumin differed by CKD status, at the upper concentrations of the respective markers (interaction term for both: p ≤ 0.095). Conclusion Our results suggest that although HbA1c and glycated albumin perform acceptably under conditions of normoglycaemia, these markers correlate less well with blood glucose levels in people with CKD who are not on dialysis.