Measuring coverage in MNCH: determining and interpreting inequalities in coverage of maternal, newborn, and child health interventions.

To monitor progress towards the Millennium Development Goals, it is essential to monitor the coverage of health interventions in subgroups of the population, because national averages can hide important inequalities. In this review, we provide a practical guide to measuring and interpreting inequali...

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Main Authors: Aluísio J D Barros, Cesar G Victora
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2013-01-01
Series:PLoS Medicine
Online Access:http://europepmc.org/articles/PMC3646214?pdf=render
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spelling doaj-baf4150782d241adaa51d5c44af5f2f52020-11-25T02:43:14ZengPublic Library of Science (PLoS)PLoS Medicine1549-12771549-16762013-01-01105e100139010.1371/journal.pmed.1001390Measuring coverage in MNCH: determining and interpreting inequalities in coverage of maternal, newborn, and child health interventions.Aluísio J D BarrosCesar G VictoraTo monitor progress towards the Millennium Development Goals, it is essential to monitor the coverage of health interventions in subgroups of the population, because national averages can hide important inequalities. In this review, we provide a practical guide to measuring and interpreting inequalities based on surveys carried out in low- and middle-income countries, with a focus on the health of mothers and children. Relevant stratification variables include urban/rural residence, geographic region, and educational level, but breakdowns by wealth status are increasingly popular. For the latter, a classification based on an asset index is the most appropriate for national surveys. The measurement of intervention coverage can be made by single indicators, but the use of combined measures has important advantages, and we advocate two summary measures (the composite coverage index and the co-coverage indicator) for the study of time trends and for cross-country comparisons. We highlight the need for inequality measures that take the whole socioeconomic distribution into account, such as the relative concentration index and the slope index of inequality, although simpler measures such as the ratio and difference between the richest and poorest groups may also be presented for non-technical audiences. Finally, we present a framework for the analysis of time trends in inequalities, arguing that it is essential to study both absolute and relative indicators, and we provide guidance to the joint interpretation of these results.http://europepmc.org/articles/PMC3646214?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Aluísio J D Barros
Cesar G Victora
spellingShingle Aluísio J D Barros
Cesar G Victora
Measuring coverage in MNCH: determining and interpreting inequalities in coverage of maternal, newborn, and child health interventions.
PLoS Medicine
author_facet Aluísio J D Barros
Cesar G Victora
author_sort Aluísio J D Barros
title Measuring coverage in MNCH: determining and interpreting inequalities in coverage of maternal, newborn, and child health interventions.
title_short Measuring coverage in MNCH: determining and interpreting inequalities in coverage of maternal, newborn, and child health interventions.
title_full Measuring coverage in MNCH: determining and interpreting inequalities in coverage of maternal, newborn, and child health interventions.
title_fullStr Measuring coverage in MNCH: determining and interpreting inequalities in coverage of maternal, newborn, and child health interventions.
title_full_unstemmed Measuring coverage in MNCH: determining and interpreting inequalities in coverage of maternal, newborn, and child health interventions.
title_sort measuring coverage in mnch: determining and interpreting inequalities in coverage of maternal, newborn, and child health interventions.
publisher Public Library of Science (PLoS)
series PLoS Medicine
issn 1549-1277
1549-1676
publishDate 2013-01-01
description To monitor progress towards the Millennium Development Goals, it is essential to monitor the coverage of health interventions in subgroups of the population, because national averages can hide important inequalities. In this review, we provide a practical guide to measuring and interpreting inequalities based on surveys carried out in low- and middle-income countries, with a focus on the health of mothers and children. Relevant stratification variables include urban/rural residence, geographic region, and educational level, but breakdowns by wealth status are increasingly popular. For the latter, a classification based on an asset index is the most appropriate for national surveys. The measurement of intervention coverage can be made by single indicators, but the use of combined measures has important advantages, and we advocate two summary measures (the composite coverage index and the co-coverage indicator) for the study of time trends and for cross-country comparisons. We highlight the need for inequality measures that take the whole socioeconomic distribution into account, such as the relative concentration index and the slope index of inequality, although simpler measures such as the ratio and difference between the richest and poorest groups may also be presented for non-technical audiences. Finally, we present a framework for the analysis of time trends in inequalities, arguing that it is essential to study both absolute and relative indicators, and we provide guidance to the joint interpretation of these results.
url http://europepmc.org/articles/PMC3646214?pdf=render
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