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The disability adjusted life years due to stroke in South Africa in 2008

Authors

  • Melanie Y. Bertram,

    Corresponding author
    1. MRC/Wits Rural Public Health, Health Transitions Research Unit (Agincourt), Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa
    2. Health and Population Division of Public Health, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa
    • Correspondence: Melanie Bertram, MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of Witwatersrand, Parktown 2193, Johannesburg, South Africa.

      E-mail: mel.bertram@wits.ac.za

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  • Judith Katzenellenbogen,

    1. Centre for International Health, Curtin Health Innovation, Research Institute, Curtin University of Technology, Perth, WA, Australia
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  • Theo Vos,

    1. Centre for Burden of Disease and Cost Effectiveness, School of Population Health, The University of Queensland, Brisbane, QLD, Australia
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  • Debbie Bradshaw,

    1. Burden of Disease Research Unit, Medical Research Council of South Africa, Tygerberg, Western Cape, South Africa
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  • Karen J. Hofman

    1. MRC/Wits Rural Public Health, Health Transitions Research Unit (Agincourt), Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa
    2. Health and Population Division of Public Health, Faculty of Health Sciences, University of Witwatersrand, Johannesburg, South Africa
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  • Conflicts of interest: None declared.

Abstract

Background

South Africa is experiencing epidemiological transition, with the burden of chronic diseases increasing. Stroke is currently the second leading cause of death in South Africa; however, limited data are available on incidence, prevalence and resulting disability. Quantifying the epidemiological parameters and disease burden is important in the planning of health services.

Aims

To synthesize the data surrounding stroke in South Africa and calculate disability adjusted life years attributable to stroke in South Africa in 2008.

Methods

We undertook a systematic review to identify studies on the prevalence and mortality of stroke in South Africa. We used the DisMod program to calculate missing epidemiological parameters, in particular incidence and duration. Using these values, we calculated the burden of disease in years of life lost (YLL), years lived with disability (YLD) and disability adjusted life years (DALY).

Results

Data on prevalence and mortality of stroke in South Africa are scarce. We estimate there are 75 000 strokes in South Africa each year, with 25 000 of these fatal within the first month. The burden of disease due to stroke in South Africa was 564 000 DALYs. Of this, 17% is contributed by YLD (14–20% in sensitivity analysis).

Conclusions

This study provides information on prevalence, incidence and disease burden of stroke at the national level in South Africa. The results of this analysis will enable further work on priority setting and health service planning for primary and secondary prevention of stroke in South Africa.

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