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      Increased risk for type 2 diabetes in relation to adiposity in middle-aged Black South African men compared to women


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          Despite a higher prevalence of overweight/obesity in Black South African women compared to men, the prevalence of type 2 diabetes (T2D) does not differ. We explored if this could be due to sex differences in insulin sensitivity, clearance and/or beta-cell function and also sex-specific associations with total and regional adiposity.


          This cross-sectional study included 804 Black South African men ( n = 388) and women ( n = 416). Dual-energy X-ray absorptiometry was used to measure total and regional adiposity. Insulin sensitivity (Matsuda index), secretion (C-peptide index) and clearance (C-peptide/insulin ratio) were estimated from an oral glucose tolerance test.


          After adjusting for sex differences in the fat mass index, men were less insulin sensitive and had lower beta-cell function than women ( P  < 0.001), with the strength of the associations with measures of total and central adiposity being greater in men than women ( P  < 0.001 for interactions). Further, the association between total adiposity and T2D risk was also greater in men than women (relative risk ratio (95% CI): 2.05 (1.42–2.96), P  < 0.001 vs 1.38 (1.03–1.85), P = 0.031).


          With increasing adiposity, particularly increased centralisation of body fat linked to decreased insulin sensitivity and beta-cell function, Black African men are at greater risk for T2D than their female counterparts.

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          Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
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            Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man.

            The steady-state basal plasma glucose and insulin concentrations are determined by their interaction in a feedback loop. A computer-solved model has been used to predict the homeostatic concentrations which arise from varying degrees beta-cell deficiency and insulin resistance. Comparison of a patient's fasting values with the model's predictions allows a quantitative assessment of the contributions of insulin resistance and deficient beta-cell function to the fasting hyperglycaemia (homeostasis model assessment, HOMA). The accuracy and precision of the estimate have been determined by comparison with independent measures of insulin resistance and beta-cell function using hyperglycaemic and euglycaemic clamps and an intravenous glucose tolerance test. The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (Rs = 0.88, p less than 0.0001), the fasting insulin concentration (Rs = 0.81, p less than 0.0001), and the hyperglycaemic clamp, (Rs = 0.69, p less than 0.01). There was no correlation with any aspect of insulin-receptor binding. The estimate of deficient beta-cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (Rs = 0.61, p less than 0.01) and with the estimate from the intravenous glucose tolerance test (Rs = 0.64, p less than 0.05). The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for beta-cell deficit) limits its use, but the correlation of the model's estimates with patient data accords with the hypothesis that basal glucose and insulin interactions are largely determined by a simple feed back loop.
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              Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp.

              Several methods have been proposed to evaluate insulin sensitivity from the data obtained from the oral glucose tolerance test (OGTT). However, the validity of these indices has not been rigorously evaluated by comparing them with the direct measurement of insulin sensitivity obtained with the euglycemic insulin clamp technique. In this study, we compare various insulin sensitivity indices derived from the OGTT with whole-body insulin sensitivity measured by the euglycemic insulin clamp technique. In this study, 153 subjects (66 men and 87 women, aged 18-71 years, BMI 20-65 kg/m2) with varying degrees of glucose tolerance (62 subjects with normal glucose tolerance, 31 subjects with impaired glucose tolerance, and 60 subjects with type 2 diabetes) were studied. After a 10-h overnight fast, all subjects underwent, in random order, a 75-g OGTT and a euglycemic insulin clamp, which was performed with the infusion of [3-3H]glucose. The indices of insulin sensitivity derived from OGTT data and the euglycemic insulin clamp were compared by correlation analysis. The mean plasma glucose concentration divided by the mean plasma insulin concentration during the OGTT displayed no correlation with the rate of whole-body glucose disposal during the euglycemic insulin clamp (r = -0.02, NS). From the OGTT, we developed an index of whole-body insulin sensitivity (10,000/square root of [fasting glucose x fasting insulin] x [mean glucose x mean insulin during OGTT]), which is highly correlated (r = 0.73, P < 0.0001) with the rate of whole-body glucose disposal during the euglycemic insulin clamp. Previous methods used to derive an index of insulin sensitivity from the OGTT have relied on the ratio of plasma glucose to insulin concentration during the OGTT. Our results demonstrate the limitations of such an approach. We have derived a novel estimate of insulin sensitivity that is simple to calculate and provides a reasonable approximation of whole-body insulin sensitivity from the OGTT.

                Author and article information

                Eur J Endocrinol
                Eur J Endocrinol
                European Journal of Endocrinology
                Bioscientifica Ltd (Bristol )
                28 February 2022
                01 May 2022
                : 186
                : 5
                : 523-533
                [1 ]Department of Paediatrics, South African Medical Research Council (SAMRC) , WITS, Developmental Pathways for Health Research Unit (DPHRU), Faculty of Health Sciences, Department of Paediatrics, University of the Witwatersrand, Johannesburg, South Africa
                [2 ]Non-Communicable Diseases Research Unit , South African Medical Research Council, Cape Town, South Africa
                [3 ]Oxford Centre for Diabetes , Endocrinology and Metabolism, University of Oxford, Oxford, UK
                [4 ]National Institute for Health Research , Oxford Biomedical Research Centre, Oxford Radcliffe Hospitals Trust, OCDEM, Churchill Hospital, Oxford, UK
                [5 ]Global Health Research Institute , School of Human Development and Health, University of Southampton, Southampton, UK
                [6 ]Department of Chemical Pathology , National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
                [7 ]Department of Public Health and Clinical Medicine , Medicine, Umeå University, Umeå, Sweden
                Author notes
                Correspondence should be addressed to C Kufe; Email: klekufe@ 123456gmail.com
                Author information
                © The authors

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                : 17 May 2021
                : 28 February 2022
                Clinical Study

                Endocrinology & Diabetes
                Endocrinology & Diabetes


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