Evidence map›Paper›PMID 29470118›Full record

ArticleAmerican journal of public health2018

The Inverse Equity Hypothesis: Analyses of Institutional Deliveries in 286 National Surveys.

Cesar Gomes Victora, Gary Joseph, Inacio C M Silva, Fatima S Maia, J Patrick Vaughan, Fernando C Barros, Aluisio J D Barros

Abstract read
In one paragraph

Article in American journal of public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 91 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
91citing 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

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

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31 more citing papers are in PubMed but not listed here.

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

7 authors.

Cesar Gomes VictoraCesar Gomes Victora, Gary Joseph, Inacio C. M. Silva, and Aluisio J. D. Barros are with the International Center for Equity in Health, Federal University of Pelotas, Pelotas, Brazil. Fatima S. Maia is with the Federal University of Rio Grande (FURG), Rio Grande, Brazil. J. Patrick Vaughan is with the Health Policy Unit, London School of Hygiene and Tropical Medicine, London, United Kingdom. Fernando C. Barros is with Post Graduate Course in Health and Behavior, Catholic University of Pelotas, Pelotas.
Gary JosephCesar Gomes Victora, Gary Joseph, Inacio C. M. Silva, and Aluisio J. D. Barros are with the International Center for Equity in Health, Federal University of Pelotas, Pelotas, Brazil. Fatima S. Maia is with the Federal University of Rio Grande (FURG), Rio Grande, Brazil. J. Patrick Vaughan is with the Health Policy Unit, London School of Hygiene and Tropical Medicine, London, United Kingdom. Fernando C. Barros is with Post Graduate Course in Health and Behavior, Catholic University of Pelotas, Pelotas.
Inacio C M SilvaCesar Gomes Victora, Gary Joseph, Inacio C. M. Silva, and Aluisio J. D. Barros are with the International Center for Equity in Health, Federal University of Pelotas, Pelotas, Brazil. Fatima S. Maia is with the Federal University of Rio Grande (FURG), Rio Grande, Brazil. J. Patrick Vaughan is with the Health Policy Unit, London School of Hygiene and Tropical Medicine, London, United Kingdom. Fernando C. Barros is with Post Graduate Course in Health and Behavior, Catholic University of Pelotas, Pelotas.
Fatima S MaiaCesar Gomes Victora, Gary Joseph, Inacio C. M. Silva, and Aluisio J. D. Barros are with the International Center for Equity in Health, Federal University of Pelotas, Pelotas, Brazil. Fatima S. Maia is with the Federal University of Rio Grande (FURG), Rio Grande, Brazil. J. Patrick Vaughan is with the Health Policy Unit, London School of Hygiene and Tropical Medicine, London, United Kingdom. Fernando C. Barros is with Post Graduate Course in Health and Behavior, Catholic University of Pelotas, Pelotas.
J Patrick VaughanCesar Gomes Victora, Gary Joseph, Inacio C. M. Silva, and Aluisio J. D. Barros are with the International Center for Equity in Health, Federal University of Pelotas, Pelotas, Brazil. Fatima S. Maia is with the Federal University of Rio Grande (FURG), Rio Grande, Brazil. J. Patrick Vaughan is with the Health Policy Unit, London School of Hygiene and Tropical Medicine, London, United Kingdom. Fernando C. Barros is with Post Graduate Course in Health and Behavior, Catholic University of Pelotas, Pelotas.
Fernando C BarrosCesar Gomes Victora, Gary Joseph, Inacio C. M. Silva, and Aluisio J. D. Barros are with the International Center for Equity in Health, Federal University of Pelotas, Pelotas, Brazil. Fatima S. Maia is with the Federal University of Rio Grande (FURG), Rio Grande, Brazil. J. Patrick Vaughan is with the Health Policy Unit, London School of Hygiene and Tropical Medicine, London, United Kingdom. Fernando C. Barros is with Post Graduate Course in Health and Behavior, Catholic University of Pelotas, Pelotas.
Aluisio J D BarrosCesar Gomes Victora, Gary Joseph, Inacio C. M. Silva, and Aluisio J. D. Barros are with the International Center for Equity in Health, Federal University of Pelotas, Pelotas, Brazil. Fatima S. Maia is with the Federal University of Rio Grande (FURG), Rio Grande, Brazil. J. Patrick Vaughan is with the Health Policy Unit, London School of Hygiene and Tropical Medicine, London, United Kingdom. Fernando C. Barros is with Post Graduate Course in Health and Behavior, Catholic University of Pelotas, Pelotas.

Funding

Wellcome Trust
6 · The paper itself

Abstract

objectivesTo test the inverse equity hypothesis, which postulates that new health interventions are initially adopted by the wealthy and thus increase inequalities-as population coverage increases, only the poorest will lag behind all other groups.

methodsWe analyzed the proportion of births occurring in a health facility by wealth quintile in 286 surveys from 89 low- and middle-income countries (1993-2015) and developed an inequality pattern index. Positive values indicate that inequality is driven by early adoption by the wealthy (top inequality), whereas negative values signal bottom inequality.

resultsAbsolute inequalities were widest when national coverage was around 50%. At low national coverage levels, top inequality was evident with coverage in the wealthiest quintile taking off rapidly; at 60% or higher national coverage, bottom inequality became the predominant pattern, with the poorest quintile lagging behind.

conclusionsPolicies need to be tailored to inequality patterns. When top inequalities are present, barriers that limit uptake by most of the population must be identified and addressed. When bottom inequalities exist, interventions must be targeted at specific subgroups that are left behind.

Indexed as

Delivery, ObstetricDeveloped CountriesDeveloping CountriesHealthcare DisparitiesHealth Care SurveysHumansModels, TheoreticalSocioeconomic Factors

Identifiers

PMID29470118
PMCPMC5844402

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.