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Bivariate Joint Spatial Modeling to Identify Shared Risk Patterns of Hypertension and Diabetes in South Africa: Evidence from WHO SAGE South Africa Wave 2

Author

Listed:
  • Glory Chidumwa

    (Division of Epidemiology and Biostatistics, School of Public Health, University of the Witwatersrand, Johannesburg 2198, South Africa)

  • Innocent Maposa

    (Division of Epidemiology and Biostatistics, School of Public Health, University of the Witwatersrand, Johannesburg 2198, South Africa)

  • Paul Kowal

    (World Health Organization SAGE, CH-1211 Geneva, Switzerland
    Research Institute for Health Sciences, Chiang Mai University, Chiang Mai 50200, Thailand)

  • Lisa K. Micklesfield

    (South African Medical Research Council/Wits Developmental Pathways for Health Research Unit, School of Clinical Medicine, University of the Witwatersrand, Johannesburg 2198, South Africa)

  • Lisa J. Ware

    (South African Medical Research Council/Wits Developmental Pathways for Health Research Unit, School of Clinical Medicine, University of the Witwatersrand, Johannesburg 2198, South Africa
    DSI-NRF Centre of Excellence in Human Development, University of the Witwatersrand, Johannesburg 2198, South Africa)

Abstract

Recent studies have suggested the common co-occurrence of hypertension and diabetes in South Africa. Given that hypertension and diabetes are known to share common socio-demographic, anthropometric and lifestyle risk factors, the aim of this study was to jointly model the shared and disease-specific geographical variation of hypertension and diabetes. The current analysis used the Study on Global Ageing and Adult Health (SAGE) South Africa Wave 2 (2014/15) data collected from 2761 participants. Of the 2761 adults (median age = 56 years), 641 (23.2%) had high blood pressure on measurement and 338 (12.3%) reported being diagnosed with diabetes. The shared component has distinct spatial patterns with higher values of odds in the eastern districts of Kwa-Zulu Natal and central Gauteng province. The shared component may represent unmeasured health behavior characteristics or the social determinants of health in our population. Our study further showed how a shared component (latent and unmeasured health behavior characteristics or the social determinants of health) is distributed across South Africa among the older adult population. Further research using similar shared joint models may focus on extending these models for multiple diseases with ecological factors and also incorporating sampling weights in the spatial analyses.

Suggested Citation

  • Glory Chidumwa & Innocent Maposa & Paul Kowal & Lisa K. Micklesfield & Lisa J. Ware, 2021. "Bivariate Joint Spatial Modeling to Identify Shared Risk Patterns of Hypertension and Diabetes in South Africa: Evidence from WHO SAGE South Africa Wave 2," IJERPH, MDPI, vol. 18(1), pages 1-12, January.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:1:p:359-:d:475265
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    References listed on IDEAS

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