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Comparability of total cardiovascular disease risk estimates using laboratory and non-laboratory based assessments in urban-dwelling South Africans: The CRIBSA study

Nasheeta Peer, Carl Lombard, Krisela Steyn, Thomas Gaziano, Naomi Levitt

Abstract


Objectives. To establish the prevalence and determinants of the 10-year risk of a cardiovascular disease (CVD) event in 25 - 74-year-old black Africans in Cape Town, South Africa, using Framingham laboratory- and non-laboratory-based and National Health and Nutrition Examination Survey (NHANES) I non-laboratory-based equations.

Methods.  CVD risk factors were determined by questionnaires, clinical measurements and biochemical analyses. Survey logistic regression analyses assessed the sociodemographic determinants of CVD risk ≥20%.

Results. There were 1 025 participants, 369 men and 656 women. Mean 10-year risk for a CVD event by Framingham laboratory- and non-laboratory-based and NHANES I non-laboratory-based equations for men was 9.0% (95% confidence interval 7.7 - 10.3), 11.1% (9.6 - 12.6) and 9.0% (7.6 - 10.3), and for women 5.4% (4.7 - 6.1), 6.8% (5.9 - 7.7) and 8.7% (7.6 - 9.8). Correlations between laboratory- and non-laboratory-based scores were high (0.915 - 0.963). The prevalence of laboratory-based CVD risk ≥20% was 13.0% in men and 6.1% in women. In the logistic model for men, ≤7 years of education (odds ratio 3.09; 95% CI 1.67 - 5.71) and being unemployed (3.44; 1.21 - 9.81) compared with employed were associated with laboratory-based high risk. In women, high risk was associated with ≤7 years of education (4.20; 1.96 - 9.01), living in formal v. informal housing (2.74; 1.24 - 6.06) and being poor (middle v. lowest tertile 0.29; 0.13 - 0.66). In the Framingham non-laboratory-based logistic models there were no changes in the direction or significance of the variables except for housing, which was no longer significant in women.

Conclusions. Comparability of laboratory- and non-laboratory-based CVD risk estimates illustrates the utility of the latter in resource-constrained settings.


Authors' affiliations

Nasheeta Peer, Non-communicable Diseases Research Unit, Medical Research Council, Durban, South Africa

Carl Lombard, Biostatistics Unit, Medical Research Council, Cape Town, South Africa

Krisela Steyn, Chronic Disease Initiative for Africa, Department of Medicine, Faculty of Health Sciences, University of Cape Town, South Africa

Thomas Gaziano, Division of Cardiovascular Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA

Naomi Levitt, Chronic Disease Initiative for Africa, Department of Medicine, Faculty of Health Sciences, University of Cape Town, South Africa; Division of Diabetic Medicine and Endocrinology, Department of Medicine, Faculty of Health Sciences, University of Cape Town, South Africa

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Keywords

South Africa; Black; Epidemiology; Cardiovascular disease risk; Urban; Risk equations

Cite this article

South African Medical Journal 2014;104(10):691-696. DOI:10.7196/SAMJ.8125

Article History

Date submitted: 2014-02-27
Date published: 2014-08-13

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