Measuring coverage in MNCH: determining and interpreting inequalities in coverage of maternal, newborn, and child health interventions.
Measuring coverage in MNCH: determining and interpreting inequalities in coverage of maternal, newborn, and child health interventions.
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DOI：
10.1371/journal.pmed.1001390
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发表时间：
2013
期刊：
影响因子：
15.8
通讯作者：
Victora CG
中科院分区：
文献类型：
--
作者：
Barros AJ;Victora CG
在《公共科学图书馆医学评论》中，巴罗斯和塞萨尔维多利亚提供了一个实用指南，利用大型家庭调查收集的数据来衡量和解释低收入和中等收入国家孕产妇、新生儿和儿童干预措施覆盖率的不平等。为了监测实现千年发展目标的进展情况，必须监测保健干预措施在人口亚群体中的覆盖情况，因为国家平均数可能掩盖重大的不平等现象。在本次审查中，我们根据在低收入和中等收入国家开展的调查，提供了一个衡量和解释不平等的实用指南，重点是母亲和儿童的健康。相关的分层变量包括城市/农村居住地、地理区域和教育水平，但按财富状况划分的细分越来越受欢迎。对于后者，基于资产指数的分类最适合于国家调查。干预措施覆盖率的衡量可以通过单一指标进行，但使用综合措施具有重要的优势，我们主张采用两种汇总措施（综合覆盖率指数和共同覆盖率指标）来研究时间趋势和进行跨国比较。我们强调需要考虑到整个社会经济分布的不平等计量，如相对集中指数和不平等斜率指数，尽管也可以为非技术受众提供更简单的计量，如最富有和最贫穷群体之间的比率和差异。最后，我们提出了一个框架的时间趋势不平等的分析，认为这是必不可少的研究绝对和相对指标，我们提供指导，这些结果的联合解释。
In a PLOS Medicine Review, Aluísio Barros and Cesar Victora provide a practical guide to measuring and interpreting inequalities in the coverage of maternal, newborn, and child interventions in low- and middle-income countries using data collected by large household surveys. 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.
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影响因子：
168.9
作者：
Boerma, J. Ties;Bryce, Jennifer;Victora, Cesar G.
通讯作者：
Victora, Cesar G.
影响因子：
8.1
作者：
Deaton, A
通讯作者：
Deaton, A
影响因子：
6.6
作者：
Harper, Sam;King, Nicholas B.;Lynch, John
通讯作者：
Lynch, John
影响因子：
12.7
作者：
Almeida-Filho, N;Kawachi, I;Dachs, JNW
通讯作者：
Dachs, JNW
影响因子：
168.9
作者：
Barros, Aluisio J. D.;Ronsmans, Carine;Victora, Cesar G.
通讯作者：
Victora, Cesar G.