scholarly journals Executive functioning in prenatally alcohol exposed children in a South African population: Baseline findings from an RCT of a computer-based cognitive training program (Preprint)

10.2196/20658 ◽  
2020 ◽  
Author(s):  
Jacobus Louw ◽  
Alastair van Heerden ◽  
Leana Olivier ◽  
Tersius Lambrechts ◽  
Mandi Broodryk ◽  
...  
Keyword(s):  
Executive Functioning ◽  
Training Program ◽  
South African ◽  
Cognitive Training ◽  
African Population ◽  
South African Population ◽  
Computer Based

Violence in Male Patients with Schizophrenia: Risk Markers in a South African Population

2004 ◽  
Vol 38 (4) ◽  
pp. 254-259 ◽  
Author(s):  
L. Koen ◽  
C. J. Kinnear ◽  
V. A. Corfield ◽  
R. A. Emsley ◽  
E. Jordaan ◽  
...  
Keyword(s):  
South African ◽  
African Population ◽  
Risk Markers ◽  
South African Population ◽  
Male Patients

scholarly journals A pharmacogenetic study of CD4 recovery in response to HIV antiretroviral therapy in two South African population groups

2009 ◽  
Vol 54 (5) ◽  
pp. 261-265 ◽  
Author(s):  
John Parathyras ◽  
Stefan Gebhardt ◽  
Renate Hillermann-Rebello ◽  
Nelis Grobbelaar ◽  
Mauritz Venter ◽  
...  
Keyword(s):  
Antiretroviral Therapy ◽  
South African ◽  
African Population ◽  
South African Population ◽  
Pharmacogenetic Study ◽  
Population Groups ◽  
Hiv Antiretroviral Therapy

scholarly journals Differences in the Nature of Stroke in a Multiethnic Urban South African Population

Stroke ◽  
2009 ◽  
Vol 40 (2) ◽  
pp. 355-362 ◽  
Author(s):  
Myles D. Connor ◽  
Girish Modi ◽  
Charles P. Warlow
Keyword(s):  
South African ◽  
African Population ◽  
South African Population ◽  
Urban South

scholarly journals Genetic factors influencing bone mineral content in a black South African population

2013 ◽  
Vol 31 (6) ◽  
pp. 708-716 ◽  
Author(s):  
Andrew May ◽  
John M. Pettifor ◽  
Shane A. Norris ◽  
Michèle Ramsay ◽  
Zané Lombard
Keyword(s):  
Bone Mineral Content ◽  
South African ◽  
Bone Mineral ◽  
Mineral Content ◽  
Genetic Factors ◽  
African Population ◽  
South African Population ◽  
Black South African ◽  
Factors Influencing

scholarly journals Degenerative trends of the palmaris longus muscle in a South African population

2013 ◽  
Vol 27 (2) ◽  
pp. 222-226 ◽  
Author(s):  
G. Venter ◽  
A.N. Van Schoor ◽  
M.C. Bosman
Keyword(s):  
South African ◽  
African Population ◽  
South African Population ◽  
Palmaris Longus ◽  
Longus Muscle ◽  
Palmaris Longus Muscle

Environmental Manganese Exposure and Cognitive Control in a South African Population

2022 ◽  
Author(s):  
Brad A. Racette ◽  
Gill Nelson ◽  
Wendy W. Dlamini ◽  
Tamara Hershey ◽  
Pradeep Prathibha ◽  
...  
Keyword(s):  
Cognitive Control ◽  
South African ◽  
African Population ◽  
South African Population ◽  
Manganese Exposure

scholarly journals Acromial Morphology and Subacromial Architecture in a South African Population

2015 ◽  
Vol 33 (3) ◽  
pp. 817-825 ◽  
Author(s):  
N Naidoo ◽  
L Lazarus ◽  
S. A Osman ◽  
K. S Satyapal
Keyword(s):  
South African ◽  
African Population ◽  
South African Population

scholarly journals SUN-616 Poor Diagnostic Concordance Between Fasting Plasma Glucose and Glycosylated Hemoglobin in a Black South African Population

2020 ◽  
Vol 4 (Supplement_1) ◽  
Author(s):  
Alisha N Wade ◽  
Nigel Crowther ◽  
F Xavier Gomez-Olive ◽  
Ryan G Wagner ◽  
Jennifer Manne-Goehler ◽  
...  
Keyword(s):  
South African ◽  
Plasma Glucose ◽  
Fasting Plasma Glucose ◽  
Glycosylated Hemoglobin ◽  
Kappa Statistic ◽  
African Population ◽  
South African Population ◽  
Black South African ◽  
Fasting Plasma ◽  
History Of

Abstract Background: While elevations in fasting plasma glucose (FPG) and glycosylated hemoglobin (HbA1c) are both recognized by the American Diabetes Association (ADA) as diagnostic of hyperglycemia, previous comparisons of these tests have demonstrated discordant individual classifications and population estimates. This may be due to additional postprandial glycemia reflected by HbA1c and, in African-descent populations, to non-glycemic factors that contribute to higher HbA1c at any given level of glycemia. We hypothesized that glycemic classifications based on FPG or HbA1c would differ in a Black South African population and investigated factors associated with discordance. Methods: 889 Black adults with previously undiagnosed diabetes, aged 40-79 years, from the population-based Health and Ageing in Africa: a Longitudinal Study of an INDEPTH Community in South Africa (HAALSI) cohort were included. Concordance between ADA FPG (normoglycemia [NG] <100 mg/dl, prediabetes [pre-DM] 100-125 mg/dl, diabetes [DM] ≥ 126 mg/dl) and HbA1c (NG <5.7%, pre-DM 5.7-6.4%, DM ≥ 6.5%) classifications was assessed using Cohen’s kappa statistic and logistic regression models were used to identify predictors of discordance. Results: Median age was 55 years (IQR 49-62) and 49.3% of the sample was male. Median glucose was 86.4 mg/dl and median HbA1c was 5.4%. Pre-DM, as defined by HbA1c, was present in 204 participants (22.9%), while FPG-defined pre-DM was present in 122 (13.7%). DM defined by HbA1c was present in 146 (16.4%), while FPG-defined DM was present in 36 (4.0%). Concordance between the two tests was poor (kappa statistic 0.18; 95%CI 0.13-0.24). Self-reported history of tuberculosis (OR 1.90, p=0.026) and higher HbA1c (OR 4.70, p<0.001) were associated with increased likelihood of discordance, whereas higher fasting glucose was associated with decreased likelihood of discordance (OR 0.58, p<0.001). There was no association between discordance and hemoglobin, HIV status, BMI, waist circumference or hip circumference. Conclusion: FPG and HbA1c exhibit poor concordance in classifying hyperglycemia in this Black South African population, with HbA1c-based definitions identifying higher prevalences of pre-DM and DM. Further work is needed to confirm whether these discrepancies are due solely to elevations in postprandial glucose. In the interim, clinicians should consider confirming elevated HbA1c concentrations with oral glucose tolerance testing, particularly in those with a history of tuberculosis, prior to making a diagnosis of DM in this population.

scholarly journals A comparison of the visual status of dyslexic and non-dyslexic schoolchildren in Durban, South Africa

2011 ◽  
Vol 70 (1) ◽  
Author(s):  
S. O. Wajuihian ◽  
K. S. Naidoo
Keyword(s):  
South African ◽  
Educational Achievement ◽  
Economic Status ◽  
African Population ◽  
South African Population ◽  
Research Perspective ◽  
Black South African ◽  
Visual Status ◽  
Lag Of Accommodation ◽  
Vision Defects

Background:   Reading difficulties constitute an impediment to the learning process and in the educational achievement of a child. Consequently, several studies examined the visual status of dyslexic children in the Caucasian populations. Such studies are lacking in the African populations.Aim: To determine the prevalence of vision defects and investigate if there is an association between dyslexia and vision in a South African population of dyslexic school children.  Methods:  This comparative study assessed the visual function of 62 children (31 dyslexic and 31 normally-reading children), mean age 13 ± 1.42 years and 11.90 ± 0.93 years respectively. The participants were matched for gender, race and socio-economic status. The visual functions evaluated and the techniques used were: visual acuity (LogMAR acuity chart), refraction (static retinos-copy), ocular alignment (cover test) near point of convergence (RAF rule), accommodation facility (± 2 D flipper lenses), amplitude of accommodation (push-up method) relative accommodation(trial lenses) accommodation posture (monocular estimation technique) and vergence reserves (prism bars). Results:   In the following, results are  provided for the dyslexic versus control:  Refractive errors: (hyperopia 6.5% vs 3%,) (myopia 6.5% vs 6.5%), (astigmatism 10% vs 13%), (anisometropia 6.5% vs 6.5%) (amblyopia 6.5% vs 0%), (remote NPC 33% vs 48%) (esophoria at near 3%  vs 0%) (exophoria at near 9.5% vs 0%), (accommodative infacility at near  54% vs 33%), lag of accommodation 39.28% vs 41,93%,  (poor positive fusional amplitude at near, 25% vs 16%). Only the binocular accommodative facility at near was significantly associated with dyslexia (p=0.027). Conclusion: The prevalence of vision defects was similar between the dyslexic and non-dyslexic participants, which suggest that an association between dyslexia and vision variables investigated, cannot be inferred.  This study provides a research perspective on the prevalence of vision defects in a Black South African population of dyslexic children and has clinical relevance and implications for the assessment, detection and management of vision anomalies in dyslexic schoolchildren. (S Afr Optom 2011 70(1) 29-43) 

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