Data · dataset · 2022
AGK PhD Data File
Listed in Teesside University Research Data Repository
The dataset described in this paper emanated from a survey distributed to patients visiting or referred to a public hospital in Pretoria, South Africa between July to December 2021.
Description
The ultimate goal of the study was to develop a reasonably robust model meant to establish the risk factors of hypertension amongst adults in South Africa attributable to extreme systolic and diastolic blood pressure values. Hypertension is becoming a global public health issue leading to global burden of morbidity and mortality worldwide and In sub-Saharan Africa, South Africa is one of the countries experiencing dramatic increase in the burden of hypertension.
The high prevalence of hypertension in South African adults (17.1% to 25.9%) was found to be predicted by age, bmi, gender, highest education level, race, physical exercises, family history of hypertension, depression, diabetes, stress and marital status after fitting the Bayesian binary quantile regression models. Convergence was achieved using the Gelman-Rubin diagnostic as indicated by the estimated potential scale reduction factors of less than 1.1 for both systolic and diastolic blood pressure risk factors, suggesting the Bayesian binary's accuracy posterior estimated upper quantiles and the associated 95% credible intervals.
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Aggressive collaborative efforts between the general public, health authorities, non-governmental organisations, private sector and the government meant to minimise lifestyle causes of hypertension are a priority.
Links
Where it is published
- DOI doi.org/10.17632/9mgndk38dy.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Medicine & Health · Public health · Social Science
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/9mgndk38dy.1 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:group:4206 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Public Health'] |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |