Evidence map›Paper›PMID 36227899›Full record

ArticlePloS one2022

Education and income-related inequalities in multimorbidity among older Brazilian adults.

Fabíola Bof de Andrade, Elaine Thumé, Luiz Augusto Facchini, Juliana Lustosa Torres, Bruno Pereira Nunes

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Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

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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

4 citing papers in PubMed.

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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.

Fabíola Bof de AndradeRené Rachou Institute, Oswaldo Cruz Foundation (FIOCRUZ), Belo Horizonte, MG, Brazil.ORCID 0000-0002-3467-3989
Elaine ThuméCollective Health Nursing Department, Federal University of Pelotas, Pelotas, RS, Brazil.ORCID 0000-0002-1169-8884
Luiz Augusto FacchiniSocial Medicine Department, Federal University of Pelotas, Pelotas, RS, Brazil.
Juliana Lustosa TorresPreventive and Social Medicine Department, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil.
Bruno Pereira NunesDepartment of Nursing, Federal University of Pelotas, Pelotas, RS, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study aimed to evaluate the existence of socioeconomic inequalities related to the prevalence of multimorbidity in the Brazilian population aged 60 and older.

methodsThis was a cross-sectional study with data from the last Brazilian National Health Survey (PNS) collected in 2019. Multimorbidity was the dependent variable and was defined as the presence of two or more chronic diseases. All the diseases were assessed based on a self-reported previous medical diagnosis. Education and per capita family income were the measures of socioeconomic position. Socioeconomic inequalities related to multimorbidity were assessed using two complex measures of inequality; the Slope Index of Inequality (SII) and the Concentration Index (CI).

resultsThe prevalence of multimorbidity in Brazil was 56.5% 95% CI (55.4; 57.6) and varied from 46.9% (44.3; 49.6) in the North region to 59.3% (57.0; 61.5) in the South region. In general, individuals with higher socioeconomic positions had a lower prevalence of multimorbidity. Significant absolute and relative income inequalities were observed in the South region [SII -9.0; CI -0.054], Southeast [SII -9.8; CI -0.06], and Middle-east [SII -10.4; CI -0.063]. Absolute and relative education inequalities were significant for the country and two of its regions (Southeast [SII -12.7; CI -0.079] and South [SII -19.0; CI -0.109]).

conclusionsThe prevalence of multimorbidity is high in Brazil and all of its macro-regions. The significant findings concerning the inequalities suggest that the distribution of this condition is more concentrated among those with lower education and income.

Indexed as

Health Status DisparitiesMultimorbidityAdultAgedBrazilCross-Sectional StudiesHumansMiddle AgedSocioeconomic Factors

Identifiers

PMID36227899
PMCPMC9560520

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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.