Article Text
PDF
Abstract
Objectives We investigated concordance between haemoglobin A1c (HbA1c)-defined diabetes and fasting plasma glucose (FPG)-defined diabetes in a black South African population with a high prevalence of obesity.
Design Cross-sectional study.
Setting Rural South African population-based cohort.
Participants 765 black individuals aged 40–70 years and with no history of diabetes.
Primary and secondary outcome measures The primary outcome measure was concordance between HbA1c-defined diabetes and FPG-defined diabetes. Secondary outcome measures were differences in anthropometric characteristics, fat distribution and insulin resistance (measured using Homoeostatic Model Assessment of Insulin Resistance (HOMA-IR)) between those with concordant and discordant HbA1c/FPG classifications and predictors of HbA1c variance.
Results The prevalence of HbA1c-defined diabetes was four times the prevalence of FPG-defined diabetes (17.5% vs 4.2%). Classification was discordant in 15.7% of participants, with 111 individuals (14.5%) having HbA1c-only diabetes (kappa 0.23; 95% CI 0.14 to 0.31). Median body mass index, waist and hip circumference, waist-to-hip ratio, subcutaneous adipose tissue and HOMA-IR in participants with HbA1c-only diabetes were similar to those in participants who were normoglycaemic by both biomarkers and significantly lower than in participants with diabetes by both biomarkers (p<0.05). HOMA-IR and fat distribution explained additional HbA1c variance beyond glucose and age only in women.
Conclusions Concordance was poor between HbA1c and FPG in diagnosis of diabetes in black South Africans, and participants with HbA1c-only diabetes phenotypically resembled normoglycaemic participants. Further work is necessary to determine which of these parameters better predicts diabetes-related morbidities in this population and whether a population-specific HbA1c threshold is necessary.
- general diabetes
- epidemiology
- international health services
- public health
Data availability statement
Data are available in a public, open access repository. Data are available on reasonable request. The HAALSI baseline data are publicly available at the Harvard Centre for Population and Development Studies (HCPDS) programme website (www.haalsi.org). Data are also accessible through the Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan (www.icpsr.umich.edu) and the INDEPTH Data Repository (http://www.indepth-ishare.org/index.php/catalog/113). Data from the AWI-Gen study is available on request to the AWI-Gen Data and Biospecimen Access Committee (michele.ramsay@wits.ac.za). Additional data are available on request from Alisha Wade (alisha.wade@wits.ac.za), the principal investigator of this nested study.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
Statistics from Altmetric.com
Data availability statement
Data are available in a public, open access repository. Data are available on reasonable request. The HAALSI baseline data are publicly available at the Harvard Centre for Population and Development Studies (HCPDS) programme website (www.haalsi.org). Data are also accessible through the Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan (www.icpsr.umich.edu) and the INDEPTH Data Repository (http://www.indepth-ishare.org/index.php/catalog/113). Data from the AWI-Gen study is available on request to the AWI-Gen Data and Biospecimen Access Committee (michele.ramsay@wits.ac.za). Additional data are available on request from Alisha Wade (alisha.wade@wits.ac.za), the principal investigator of this nested study.
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Footnotes
Twitter @George
Contributors ANW, NJC, SA-G, LB, FXG-O, JAS, RGW, TAG and SMT were involved in design and data collection for the HAALSI and AWI-Gen studies. ANW and ARC designed this analysis and ANW performed the statistical analysis. ANW and ARC wrote the first draft of the manuscript. ANW, NJC, SA-G, LB, JAG, FXG-O, JM-G, JAS, RGW, TAG, SMT and ARC critically revised the manuscript and approved the final version. ANW is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. ANW, NJC, SA-G, LB, JAG, FXG-O, JM-G, JAS, RGW, TAG, SMT and ARC have reviewed the final version of this manuscript and agree to be accountable for all aspects of the work.
Funding The AWI-Gen Collaborative Centre is funded by the National Human Genome Research Institute (NHGRI), Office of the Director (OD), the Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD), the National Institute of Environmental Health Sciences (NIEHS), the Office of AIDS Research (OAR) and the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) of the National Institutes of Health (NIH) under award number U54HG006938 and its supplements, as part of the H3Africa Consortium as well as by the Department of Science and Innovation, South Africa, award number DST/CON 0056/2014, and by the African Partnership for Chronic Disease Research. The HAALSI study was funded by the National Institute on Aging (P01 AG041710). The MRC/Wits Rural Public Health and Health Transitions Research Unit and Agincourt Health and Socio-Demographic Surveillance System, a node of the South African Population Research Infrastructure Network (SAPRIN), is supported by the Department of Science and Innovation, South Africa, the University of the Witwatersrand, and the Medical Research Council, South Africa, and previously the Wellcome Trust, UK (grants 058893/Z/99/A; 069683/Z/02/Z; 085477/Z/08/Z; 085477/B/08/Z). ANW is supported by the Fogarty International Centre, National Institutes of Health under award number K43TW010698 and ARC is supported by the National Institute on Ageing, National Institutes of Health under award K24AG042765. JM-G is supported by grant number T32 AI007433 from the National Institute of Allergy and Infectious Diseases.
Disclaimer This paper describes the views of the authors and does not necessarily represent the official views of the National Institutes of Health (USA), the South African Department of Science and Innovation or by the South African Medical Research Council who funded this research. The funders had no role in study design, data collection, analysis and interpretation, report writing or the decision to submit this article for publication.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.