Evidence map›Paper›PMID 41268126›Full record

ArticleInternational journal of population data science2025

A small area deprivation index for monitoring and evaluating health inequalities in a diverse, low and middle income country: the Índice Brasileiro de Privação (IBP).

Mirjam Allik, Elzo Pereira Pinto-Júnior, Dandara Ramos, Andrêa J F Ferreira, Flavia Jose Alves, Camila Teixeira, Marilyn Agranonik, Renzo Flores-Ortiz, Poliana Rebouças, Rita de Cássia Ribeiro-Silva and 6 more

Abstract read
In one paragraph

Article in International journal of population data science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

2 citing papers in PubMed.

  1. 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

16 authors.

Mirjam AllikMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Clarice Pears Building, 90 Byres Road, Glasgow G12 8TB.
Elzo Pereira Pinto-JúniorCentre for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation (FIOCRUZ), Parque Tecnológico da Bahia, Edf. Tecnocentro, sala 315, Rua Mundo, n° 121, CEP 41745-715, Salvador-Bahia, Brazil.
Dandara RamosCentre for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation (FIOCRUZ), Parque Tecnológico da Bahia, Edf. Tecnocentro, sala 315, Rua Mundo, n° 121, CEP 41745-715, Salvador-Bahia, Brazil.
Andrêa J F FerreiraCentre for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation (FIOCRUZ), Parque Tecnológico da Bahia, Edf. Tecnocentro, sala 315, Rua Mundo, n° 121, CEP 41745-715, Salvador-Bahia, Brazil.
Flavia Jose AlvesCentre for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation (FIOCRUZ), Parque Tecnológico da Bahia, Edf. Tecnocentro, sala 315, Rua Mundo, n° 121, CEP 41745-715, Salvador-Bahia, Brazil.
Camila TeixeiraCentre for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation (FIOCRUZ), Parque Tecnológico da Bahia, Edf. Tecnocentro, sala 315, Rua Mundo, n° 121, CEP 41745-715, Salvador-Bahia, Brazil.
Marilyn AgranonikUniversity of Vale do Rio dos Sinos, Av. Unisinos, 950, CEP 93022-750, Cristo Rei, São Leopoldo - RS.
Renzo Flores-OrtizCentre for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation (FIOCRUZ), Parque Tecnológico da Bahia, Edf. Tecnocentro, sala 315, Rua Mundo, n° 121, CEP 41745-715, Salvador-Bahia, Brazil.
Poliana RebouçasCentre for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation (FIOCRUZ), Parque Tecnológico da Bahia, Edf. Tecnocentro, sala 315, Rua Mundo, n° 121, CEP 41745-715, Salvador-Bahia, Brazil.
Rita de Cássia Ribeiro-SilvaCentre for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation (FIOCRUZ), Parque Tecnológico da Bahia, Edf. Tecnocentro, sala 315, Rua Mundo, n° 121, CEP 41745-715, Salvador-Bahia, Brazil.
Mauro SanchezCentre for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation (FIOCRUZ), Parque Tecnológico da Bahia, Edf. Tecnocentro, sala 315, Rua Mundo, n° 121, CEP 41745-715, Salvador-Bahia, Brazil.
Srinivasa Vittal KatikireddiMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Clarice Pears Building, 90 Byres Road, Glasgow G12 8TB.
Mauricio L BarretoCentre for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation (FIOCRUZ), Parque Tecnológico da Bahia, Edf. Tecnocentro, sala 315, Rua Mundo, n° 121, CEP 41745-715, Salvador-Bahia, Brazil.
Alastair H LeylandMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Clarice Pears Building, 90 Byres Road, Glasgow G12 8TB.
Maria Yury IchiharaCentre for Data and Knowledge Integration for Health (CIDACS), Oswaldo Cruz Foundation (FIOCRUZ), Parque Tecnológico da Bahia, Edf. Tecnocentro, sala 315, Rua Mundo, n° 121, CEP 41745-715, Salvador-Bahia, Brazil.
Ruth DundasMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Clarice Pears Building, 90 Byres Road, Glasgow G12 8TB.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Monitoring and addressing health inequalities is important. However, socioeconomic variables are usually unavailable within health datasets. Area deprivation measures provide access to open-source reliable socioeconomic data within low/middle-income countries and can contribute to the monitoring of the Sustainable Development Goals and assessing the growing burden of health inequalities. Objective: To create a small-area deprivation measure for the whole of Brazil - the Brazilian Deprivation Index (Índice Brasileiro de Privação - IBP). Methods: Using Census Sector data (mean population size=615) from the most recently available Brazilian Demographic Census (2010), variables measuring literacy, household income and housing conditions were standardised using z-scores and summed into a single measure. The IBP was validated using regional small-area measures of vulnerability: Belo Horizonte's Health Vulnerability Index (IVS) and São Paulo's Social Vulnerability Index (IPVS). Mortality data from Minas Gerais were used to estimate age-standardised mortality rates (ASMR) by ill-defined causes across IBP deprivation quintiles. Results: The IBP was created for 303,218 (97.8%) census sectors (99.7% population). Substantial regional variation in deprivation was found using the IBP measure, with higher deprivation in rural than urban areas. The IBP was correlated with the other indicators used for validation: the IVS (r = 0.96) and the IPVS (r = 0.68). We found gradients across the ill-defined causes ASMR, in Minas Gerais mortality was 2.6 higher in the most deprived quintile of IBP, compared with the least deprived. Main challenges in creating a deprivation measure for LMICs and possible solutions are demonstrated. Conclusion: A small area deprivation index was created for Brazil, a large and highly diverse middle-income country. The IBP improves our understanding and monitoring of inequalities, serving as a valuable tool for informing targeted public policies. Although the index is based on Brazil's specific context, the challenges faced, and the strategies implemented to tackle them are relevant for other low- and middle-income countries aiming to develop similar tools.

Indexed as

Health Status DisparitiesAdultBrazilCensusesDeveloping CountriesFemaleHumansMaleMiddle AgedMortalitySmall-Area AnalysisSocioeconomic Factorsdeprivation indexhealth policyinequalitiesmortality monitoring

Identifiers

PMID41268126
PMCPMC12629185

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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.