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dc.contributor.authorGlory Chidumwaen_US
dc.contributor.authorInnocent Maposaen_US
dc.contributor.authorPaul Kowalen_US
dc.contributor.authorLisa K. Micklesfielden_US
dc.contributor.authorLisa J. Wareen_US
dc.date.accessioned2021-01-27T04:17:43Z-
dc.date.available2021-01-27T04:17:43Z-
dc.date.issued2021-01-01en_US
dc.identifier.issn16604601en_US
dc.identifier.issn16617827en_US
dc.identifier.other2-s2.0-85099061725en_US
dc.identifier.other10.3390/ijerph18010359en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85099061725&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/71921-
dc.description.abstract© 2021 by the authors. Licensee MDPI, Basel, Switzerland. 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.en_US
dc.subjectEnvironmental Scienceen_US
dc.subjectMedicineen_US
dc.titleBivariate joint spatial modeling to identify shared risk patterns of hypertension and diabetes in south africa: Evidence from who sage South Africa wave 2en_US
dc.typeJournalen_US
article.title.sourcetitleInternational Journal of Environmental Research and Public Healthen_US
article.volume18en_US
article.stream.affiliationsOrganisation Mondiale de la Santéen_US
article.stream.affiliationsUniversity of Witwatersranden_US
article.stream.affiliationsChiang Mai Universityen_US
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