Evidence map›Paper›PMID 26822991›Full record

ArticleInternational journal for equity in health2016

Monitoring subnational regional inequalities in health: measurement approaches and challenges.

Ahmad Reza Hosseinpoor, Nicole Bergen, Aluisio J D Barros, Kerry L M Wong, Ties Boerma, Cesar G Victora

Open access · goldAbstract read
In one paragraph

Article in International journal for equity in health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 2 pooled it
19.0field-weighted citation impact, top 1% of its field
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

51 citing papers in PubMed, 2 syntheses or guidelines pooled it, 104 citations in OpenAlex.

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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 at 2 institutions in 2 countries.

Ahmad Reza HosseinpoorDepartment of Information, Evidence and Research, World Health Organization, Geneva, Switzerland. hosseinpoora@who.int.
Nicole BergenDepartment of Information, Evidence and Research, World Health Organization, Geneva, Switzerland. bergenn@who.int.
Aluisio J D BarrosInternational Center for Equity in Health, Federal University of Pelotas, Pelotas, Brazil. abarros@equidade.org.
Kerry L M WongInternational Center for Equity in Health, Federal University of Pelotas, Pelotas, Brazil. kwong@equidade.org.
Ties BoermaDepartment of Information, Evidence and Research, World Health Organization, Geneva, Switzerland. boermat@who.int.
Cesar G VictoraInternational Center for Equity in Health, Federal University of Pelotas, Pelotas, Brazil. cvictora@equidade.org.
Universidade Federal de Pelotas · BRWorld Health Organization · CH

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundMonitoring inequalities based on subnational regions is a useful practice to unmask geographical differences in health, and deploy targeted, equity-oriented interventions. Our objective is to describe, compare and contrast current methods of measuring subnational regional inequality. We apply a selection of summary measures to empirical data from four low- or middle-income countries to highlight the characteristics and overall performance of the different measures.

methodsWe use data from Demographic and Health Surveys conducted in Bangladesh, Egypt, Ghana and Zimbabwe to calculate subnational regional inequality estimates for reproductive, maternal, newborn, and child health services generated from 11 summary measures: pairwise measures included high to low absolute difference, high to low relative difference, and high to low ratio; complex measures included population attributable risk, weighted variance, absolute weighted mean difference from overall mean, index of dissimilarity, Theil index, population attributable risk percentage, coefficient of variation, and relative weighted mean difference from overall mean. Four of these summary measures (high to low absolute difference, high to low ratio, absolute weighted mean difference from overall mean, and relative weighted mean difference from overall mean) were selected to compare their performance in measuring trend over time in inequality for one health indicator.

resultsOverall, the 11 different measures were more remarkable for their similarities than for their differences. Pairwise measures tended to support the same conclusions as complex summary measures-that is, by identifying same best and worst coverage indicators in each country and indicating similar time trends. Complex measures may be useful to illustrate more nuanced results in countries with a great number of subnational regions.

conclusionsWhen pairwise and complex measures lead to the same conclusions about the state of subnational regional inequality, pairwise measures may be sufficient for reporting inequality. In cases where complex measures are required, mean difference from mean measures can be easily communicated to non-technical audiences.

Indexed as

BenchmarkingEpidemiologic MeasurementsHealth Status DisparitiesBangladeshChild Health ServicesDeveloping CountriesEgyptGhanaHealth SurveysHumansIncomeInfantInfant MortalityMaternal Health ServicesSocioeconomic FactorsZimbabwe

Identifiers

PMID26822991
PMCPMC4730638
OpenAlexW2275486550

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.