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

被引:4
|
作者
Chidumwa, Glory [1 ]
Maposa, Innocent [1 ]
Kowal, Paul [2 ,3 ]
Micklesfield, Lisa K. [4 ]
Ware, Lisa J. [4 ,5 ]
机构
[1] Univ Witwatersrand, Sch Publ Hlth, Div Epidemiol & Biostat, ZA-2198 Johannesburg, South Africa
[2] WHO, SAGE, CH-1211 Geneva, Switzerland
[3] Chiang Mai Univ, Res Inst Hlth Sci, Chiang Mai 50200, Thailand
[4] Univ Witwatersrand, Sch Clin Med, South African Med Res Council, Wits Dev Pathways Hlth Res Unit, ZA-2198 Johannesburg, South Africa
[5] Univ Witwatersrand, DSI NRF Ctr Excellence Human Dev, ZA-2198 Johannesburg, South Africa
基金
美国国家卫生研究院;
关键词
hypertension; diabetes; joint shared spatial model; NONCOMMUNICABLE DISEASES; BLOOD-PRESSURE; PREVALENCE; BURDEN;
D O I
10.3390/ijerph18010359
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页码:1 / 12
页数:12
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