Assessing joint spatial autocorrelations between mortality rates due to cardiovascular conditions in South Africa

Submitted: 29 April 2019
Accepted: 18 October 2019
Published: 6 November 2019
Abstract Views: 1044
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South Africa is experiencing an increasing burden of noncommunicable diseases (NCDs). There is evidence of co-morbidity of several NCDs at small geographical areas in the country. However, the extent to which this applies to joint spatial autocorrections of NCDs is not known. The objective of this study was to derive and quantify multivariate spatial autocorrections for NCDrelated mortality in South Africa. The study used mortality attributable to cerebrovascular, ischaemic heart failure and hypertension captured by the country's Department of Home Affairs for the years 2001, 2007 and 2011. Both univariate and pairwise spatial clustering measures were derived using observed, empirical Bayes smoothed and age-adjusted standardised mortality rates. Cerebrovascular and ischaemic heart co-clustering was significant for the years 2001 and 2011. Cerebrovascular and hypertension co-clustering was significant for the years 2007 and 2011, while hypertension and ischaemic heart co-clustering was significant for the year 2011. Co-clusters of cerebrovascular-ischaemic heart disease are the most profound and located in the south-western part of the country. It was successfully demonstrated that bivariate spatial autocorrelations can be derived for spatially dependent mortality rates as exemplified by mortality rates attributed to three cardiovascular conditions. The identified co-clusters of spatially dependent health outcomes may be targeted for an integrated intervention and monitoring programme.

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Supporting Agencies

SAMRC-Biostatistics Capacity Development, no. 57042; Teaching development grant national collaborative project, no. APP-TDG-088; DST-NRF Centre of Excellence in Mathematical and Statistical Sciences (CoE-MASS); VLIR-UOS. Opinions expressed and conclusions arrived at are those of the authors and are not necessarily to be attributed to UL, SAMRC, CoE-MASS or VLIR-UOS.

How to Cite

Darikwa, T. B., Manda, S., & Lesaoana, ‘Maseka. (2019). Assessing joint spatial autocorrelations between mortality rates due to cardiovascular conditions in South Africa. Geospatial Health, 14(2). https://doi.org/10.4081/gh.2019.784

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