Dataset Information

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

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.

SUBMITTER: Chidumwa G

PROVIDER: S-EPMC7796507 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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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.

Chidumwa Glory G Maposa Innocent I Kowal Paul P Micklesfield Lisa K LK Ware Lisa J LJ

International journal of environmental research and public health 20210105 1

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. ...[more]

PMID: 33466566

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Project description:Background. The bacterial foodborne pathogen Campylobacter jejuni is a common cause of acute gastroenteritis and is also associated with the postinfectious neuropathies, Guillain-Barré and Miller Fisher syndromes. This study described the use of multilocus sequence typing and DNA microarrays to examine the genetic content of a collection of South African C. jejuni strains, recovered from patients with enteritis, Guillain-Barré or Miller Fisher syndromes. Methodology/Principal Findings. The comparative genomic analysis by using multilocus sequence typing and DNA microarrays demonstrated that the South African strains with Penner heat-stable (HS) serotype HS:41 were clearly distinct from the other South African strains. Further analysis of the DNA microarray data demonstrated that the serotype HS:41 strains from South African GBS and enteritis patients are highly similar in gene content. Interestingly, the South African HS:41 strains were distinct in gene content when compared to serotype HS:41 strains from other geographical locations due to the presence of genomic islands, referred to as Campylobacter jejuni integrated elements. Only the genomic integrated element CJIE1, a Campylobacter Mu-like prophage, was present in the South African HS:41 strains whereas absent in the closely-related HS:41 strains from Mexico. A more distantly-related HS:41 strain from Canada possessed both genomic integrated elements CJIE1 and CJIE2. Conclusion/Significance. These findings demonstrated that these C. jejuni integrated elements may contribute to the differentiation of closely-related C. jejuni strains. In addition, the presence of bacteriophage-related genes in CJIE1 may probably contribute to increasing the genomic diversity of these C. jejuni strains. This comparative genomic analysis of the foodborne pathogen C. jejuni provides fundamental information that potentially could lead to improved methods for analyzing the epidemiology of disease outbreaks and their sources. Keywords: comparative genomic indexing analysis

Dataset Information

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

Publications

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

Similar Datasets

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