Evidence map›Paper›PMID 32133180›Full record

ArticleBMJ global health2020

Are the poorest poor being left behind? Estimating global inequalities in reproductive, maternal, newborn and child health.

Aluisio J D Barros, Fernando C Wehrmeister, Leonardo Zanini Ferreira, Luis Paulo Vidaletti, Ahmad Reza Hosseinpoor, Cesar G Victora

Abstract read
In one paragraph

Article in BMJ global health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 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

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  18. Wealth and Education Inequities in Maternal and Child Health Services Utilization in Rural Ethiopia.International journal of environmental research and public health · 2022
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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

6 authors.

Aluisio J D BarrosDepartment of Data and Analytics, WHO, Geneve, Switzerland.ORCID 0000-0002-2022-8729
Fernando C WehrmeisterInternational Center for Equity in Health, Universidade Federal de Pelotas, Pelotas, Brazil.ORCID 0000-0001-7137-1747
Leonardo Zanini FerreiraDepartment of Data and Analytics, WHO, Geneve, Switzerland.ORCID 0000-0001-7843-9345
Luis Paulo VidalettiDepartment of Data and Analytics, WHO, Geneve, Switzerland.ORCID 0000-0002-2840-6841
Ahmad Reza HosseinpoorPost-Graduate Programme in Epidemiology, Universidade Federal de Pelotas, Pelotas, Brazil.ORCID 0000-0001-7322-672X
Cesar G VictoraDepartment of Data and Analytics, WHO, Geneve, Switzerland.ORCID 0000-0002-2465-2180

Funding

Wellcome Trust 101815/Z/13/ZWorld Health Organization 001
6 · The paper itself

Abstract

Introduction: Wealth-related inequalities in reproductive, maternal, neonatal and child health have been widely studied by dividing the population into quintiles. We present a comprehensive analysis of wealth inequalities for the composite coverage index (CCI) using national health surveys carried out since 2010, using wealth deciles and absolute income estimates as stratification variables, and show how these new approaches expand on traditional equity analyses. Methods: 83 low-income and middle-income countries were studied. The CCI is a combined measure of coverage with eight key reproductive, maternal, newborn and child health interventions. It was disaggregated by wealth deciles for visual inspection of inequalities, and the slope index of inequality (SII) was estimated. The correlation between coverage in the extreme deciles and SII was assessed. Finally, we used multilevel models to examine how the CCI varies according to the estimated absolute income for each wealth quintile in the surveys. Results: The analyses of coverage by wealth deciles and by absolute income show that inequality is mostly driven by coverage among the poor, which is much more variable than coverage among the rich across countries. Regardless of national coverage, in 61 of the countries, the wealthiest decile achieved 70% or higher CCI coverage. Well-performing countries were particularly effective in achieving high coverage among the poor. In contrast, underperforming countries failed to reach the poorest, despite reaching the better-off. Conclusion: There are huge inequalities between the richest and the poorest women and children in most countries. These inequalities are strongly driven by low coverage among the poorest given the wealthiest groups achieve high coverage irrespective of where they live, overcoming any barriers that are an impediment to others. Countries that 'punched above their weight' in coverage, given their level of absolute wealth, were those that best managed to reach their poorest women and children.

Indexed as

Child HealthDeveloping CountriesHealthcare DisparitiesMaternal HealthPovertyChildFemaleHealth SurveysHumansInfant, NewbornPregnancychild healthmaternal health

Identifiers

PMID32133180
PMCPMC7042578

What OpenQuestion holds

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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.