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Explaining income-related inequalities in cardiovascular risk factors in Tunisian adults during the last decade: comparison of sensitivity analysis of logistic regression and Wagstaff decomposition analysis
Umeå University, Faculty of Medicine, Department of Epidemiology and Global Health.ORCID iD: 0000-0001-7134-8256
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2019 (English)In: International Journal for Equity in Health, ISSN 1475-9276, E-ISSN 1475-9276, Vol. 18, article id 177Article in journal (Refereed) Published
Abstract [en]

BACKGROUND: It is important to quantify inequality, explain the contribution of underlying social determinants and to provide evidence to guide health policy. The aim of the study is to explain the income-related inequalities in cardiovascular risk factors in the last decade among Tunisian adults aged between 35 and 70 years old.

METHODS: We performed the analysis by applying two approaches and compared the results provided by the two methods. The methods were global sensitivity analysis (GSA) using logistic regression models and the Wagstaff decomposition analysis.

RESULTS: Results provided by the two methods found a higher risk of cardiovascular diseases and diabetes in those with high socio-economic status in 2005. Similar results were observed in 2016. In 2016, the GSA showed that education level occupied the first place on the explanatory list of factors explaining 36.1% of the adult social inequality in high cardiovascular risk, followed by the area of residence (26.2%) and income (15.1%). Based on the Wagstaff decomposition analysis, the area of residence occupied the first place and explained 40.3% followed by income and education level explaining 19.2 and 14.0% respectively. Thus, both methods found similar factors explaining inequalities (income, educational level and regional conditions) but with different rankings of importance.

CONCLUSIONS: The present study showed substantial income-related inequalities in cardiovascular risk factors and diabetes in Tunisia and provided explanations for this. Results based on two different methods similarly showed that structural disparities on income, educational level and regional conditions should be addressed in order to reduce inequalities.

Place, publisher, year, edition, pages
BioMed Central, 2019. Vol. 18, article id 177
Keywords [en]
Cardiovascular risk factors, Diabetes, Global sensitivity analysis (GSA), Logistic regression, Social inequalities, Tunisia, Wagstaff-type decomposition analysis
National Category
Public Health, Global Health, Social Medicine and Epidemiology
Research subject
Public health
Identifiers
URN: urn:nbn:se:umu:diva-165270DOI: 10.1186/s12939-019-1047-6PubMedID: 31730469OAI: oai:DiVA.org:umu-165270DiVA, id: diva2:1371045
Available from: 2019-11-19 Created: 2019-11-19 Last updated: 2019-11-19Bibliographically approved

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