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

dc.contributor.authorDarikwa, Timotheus B.
dc.contributor.authorManda, S.O.M. (Samuel)
dc.contributor.authorLesaoana, Maseka
dc.date.accessioned2020-08-21T13:29:12Z
dc.date.available2020-08-21T13:29:12Z
dc.date.issued2019
dc.description.abstractSouth 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 NCD-related 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.en_ZA
dc.description.departmentStatisticsen_ZA
dc.description.librarianam2020en_ZA
dc.description.sponsorshipSAMRC-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.en_ZA
dc.description.urihttp://www.geospatialhealth.net/index.php/ghen_ZA
dc.identifier.citationDarikwa, T.B., Manda, S. & Lesaoana, M. 2019, 'Assessing joint spatial autocorrelations between mortality rates due to cardiovascular conditions in South Africa', Geospatial Health, vol. 14, art. 784, pp. 293-305.en_ZA
dc.identifier.issn1827-1987 (print)
dc.identifier.issn1970-7096 (online)
dc.identifier.other10.4081/gh.2019.784
dc.identifier.urihttp://hdl.handle.net/2263/75852
dc.language.isoenen_ZA
dc.publisherPAGEpressen_ZA
dc.rights© the Author(s), 2019. Licensee PAGEPress, Italy. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.en_ZA
dc.subjectBivariate spatial autocorrelationen_ZA
dc.subjectIndirect standardised mortality rateen_ZA
dc.subjectCardiovascular mortalityen_ZA
dc.subjectEmpirical Bayes smoothingen_ZA
dc.subjectSouth Africa (SA)en_ZA
dc.subjectNon-communicable diseases (NCDs)en_ZA
dc.titleAssessing joint spatial autocorrelations between mortality rates due to cardiovascular conditions in South Africaen_ZA
dc.typeArticleen_ZA

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