Evidence map›Paper›PMID 26513729›Full record

ArticlePloS one2015

Socio-Economic Differences in Cardiovascular Health: Findings from a Cross-Sectional Study in a Middle-Income Country.

Janko Janković, Miloš Erić, Dragana Stojisavljević, Jelena Marinković, Slavenka Janković

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  7. Article
  8. Influence of the Social Environment on Ideal Cardiovascular Health.Journal of the American Heart Association · 2023
    Article
  9. Cardiovascular Risk Factors and Social Development Index.Frontiers in cardiovascular medicine · 2021
    Article
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  16. Association Between Living in Food Deserts and Cardiovascular Risk.Circulation. Cardiovascular quality and outcomes · 2017
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Janko JankovićInstitute of Social Medicine, Faculty of Medicine, University of Belgrade, Belgrade, Serbia.
Miloš ErićCenter for European Integration and Public Management, Faculty of Economics, Finance and Administration, Singidunum University, Belgrade, Serbia.
Dragana StojisavljevićInstitute of Public Health, Banja Luka, Republic of Srpska, Bosnia and Herzegovina.
Jelena MarinkovićInstitute of Medical Statistics and Informatics, Faculty of Medicine, University of Belgrade, Belgrade, Serbia.
Slavenka JankovićInstitute of Epidemiology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA relatively consistent body of literature, mainly from high-income countries, supports an inverse association between socio-economic status (SES) and risk of cardiovascular disease (CVD). Data from low- and middle-income countries are scarce. This study explores SES differences in cardiovascular health (CVH) in the Republic of Srpska (RS), Bosnia and Herzegovina, a middle-income country.

methodsWe collected information on SES (education, employment status and household's relative economic status, i.e. household wealth) and the 7 ideal CVH components (smoking status, body mass index, physical activity, diet, blood pressure, total cholesterol, and fasting blood glucose) among 3601 participants 25 years of age and older, from the 2010 National Health Survey in the RS. Based on the sum of all 7 CVH components an overall CVH score (CVHS) was calculated ranging from 0 (all CVH components at poor levels) to 14 (all CVH components at ideal levels). To assess the differences between groups the chi-square test, t-test and ANOVA were used where appropriate. The association between SES and CVHS was analysed with multivariate linear regression analyses. The dependent variable was CVHS, while independent variables were educational level, employment status and wealth index.

resultsAccording to multiple linear regression analysis CVHS was independently associated with education attainment and employment status. Participants with higher educational attainment and those economically active had higher CVHS (b = 0.57; CI = 0.29-0.85 and b = 0.27; CI = 0.10-0.44 respectively) after adjustment for sex, age group, type of settlement, and marital status. We failed to find any statistically significant difference between the wealth index and CVHS.

conclusionThis study presents the novel information, since CVHS generated from the individual CVH components was not compared by socio-economic status till now. Our finding that the higher overall CVHS was independently associated with a higher education attainment and those economically active supports the importance of reducing socio-economic inequalities in CVH in RS.

Indexed as

Health StatusAdultAgedAged, 80 and overCardiovascular DiseasesCross-Sectional StudiesDeveloping CountriesFemaleHealth SurveysHumansMaleMiddle AgedPrevalenceSocioeconomic FactorsYoung Adult

Identifiers

PMID26513729
PMCPMC4626110

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.