Evidence map›Paper›PMID 31730469›Full record

ArticleInternational journal for equity in health2019

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.

Olfa Saidi, Nada Zoghlami, Kathleen E Bennett, Paola Andrea Mosquera, Dhafer Malouche, Simon Capewell, Habiba Ben Romdhane, Martin O'Flaherty

Abstract readComparative Study
In one paragraph

Article in International journal for equity in health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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6citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Olfa SaidiCardiovascular Epidemiology and Prevention Research Laboratory -Faculty of medicine of Tunis, University Tunis El Manar, Tunis, Tunisia. olfa.saidi@yahoo.fr.ORCID 0000-0001-5206-5736
Nada ZoghlamiCardiovascular Epidemiology and Prevention Research Laboratory -Faculty of medicine of Tunis, University Tunis El Manar, Tunis, Tunisia.
Kathleen E BennettPopulation and Health Sciences, Royal College of Surgeons in Ireland, Dublin, Ireland.
Paola Andrea MosqueraDepartment of Epidemiology and Global Health, Umeå University, Umeå, Sweden.
Dhafer MaloucheCardiovascular Epidemiology and Prevention Research Laboratory -Faculty of medicine of Tunis, University Tunis El Manar, Tunis, Tunisia.
Simon CapewellDepartment of Public Health and Policy, University of Liverpool, Liverpool, UK.
Habiba Ben RomdhaneCardiovascular Epidemiology and Prevention Research Laboratory -Faculty of medicine of Tunis, University Tunis El Manar, Tunis, Tunisia.
Martin O'FlahertyDepartment of Public Health and Policy, University of Liverpool, Liverpool, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIt 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.

methodsWe 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.

resultsResults 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.

conclusionsThe 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.

Indexed as

Health Status DisparitiesSocioeconomic FactorsAdultAgedCardiovascular DiseasesFemaleHumansLogistic ModelsMaleMiddle AgedRisk FactorsSocial ClassTunisiaCardiovascular risk factorsDiabetesGlobal sensitivity analysis (GSA)Logistic regressionSocial inequalitiesTunisiaWagstaff-type decomposition analysis

Identifiers

PMID31730469
PMCPMC6858762

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