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利用 MANUSH 评估印度儿童营养结果的不平等和地区差异——一个更敏感的衡量标准。

Assessing inequalities and regional disparities in child nutrition outcomes in India using MANUSH - a more sensitive yardstick.

机构信息

Centre for Technology Alternatives for Rural Areas (CTARA), Indian Institute of Technology, Bombay, Maharashtra, 400076, India.

出版信息

Int J Equity Health. 2020 Aug 13;19(1):138. doi: 10.1186/s12939-020-01249-6.

Abstract

BACKGROUND

India is strongly committed to reducing the burden of child malnutrition, which has remained a persistent concern. Findings from recent surveys indicate co-existence of child undernutrition, micronutrient deficiency and overweight/obesity, i.e. the triple burden of malnutrition among children below 5 years. While considerable efforts are being made to address this challenge, and several composite indices are being explored to inform policy actions, the methodology used for creating such indices, i.e., linear averaging, has its limitations. Briefly put, it could mask the uneven improvement across different indicators by discounting the 'lagging' indicators, and hence not incentivising a balanced improvement. Signifying negative implications on policy discourse for improved nutrition. To address this gap, we attempt to develop a composite index for estimating the triple burden of malnutrition in India, using a more sensitive measure, MANUSH.

METHODOLOGY

Data from publicly available nation-wide surveys - National Family Health Survey (NFHS) and Comprehensive National Nutrition Survey (CNNS), was used for this study. First, we addressed the robustness of MANUSH method of composite indexing over conventional aggregation methods. Second, using MANUSH scores, we assessed the triple burden of malnutrition at the subnational level over different periods NHFS- 3(2005-06), NFHS-4 (2015-16) and CNNS (2106-18). Using mapping and spatial analysis tools, we assessed neighbourhood dependency and formation of clusters, within and across states.

RESULT

MANUSH method scores over other aggregation measures that use linear aggregation or geometric mean. It does so by fulfilling additional conditions of Shortfall and Hiatus Sensitivity, implicitly penalising cases where the improvement in worst-off dimension is lesser than the improvement in best-off dimension, or where, even with an overall improvement in the composite index, the gap between different dimensions does not reduce. MANUSH scores helped in revealing the gaps in the improvement of nutrition outcomes among different indicators and, the rising inequalities within and across states and districts in India. Significant clusters (p < 0.05) of high burden and low burden districts were found, revealing geographical heterogeneities and sharp regional disparities. A MANUSH based index is useful in context-specific planning and prioritising different interventions, an approach advocated by the newly launched National Nutrition Mission in India.

CONCLUSION

MANUSH based index emphasises balanced development in nutritional outcomes and is hence relevant for diverse and unevenly developing economy like India.

摘要

背景

印度一直致力于减轻儿童营养不良的负担,这一问题仍然是一个持续关注的问题。最近的调查结果表明,5 岁以下儿童同时存在营养不足、微量营养素缺乏和超重/肥胖问题,即存在三重营养不良负担。尽管正在做出相当大的努力来应对这一挑战,并且正在探索几个综合指标来为政策行动提供信息,但用于创建这些指标的方法,即线性平均法,存在其局限性。简而言之,它可能会通过折扣“滞后”指标来掩盖不同指标的不均衡改善,从而不会激励平衡的改善。这对改善营养的政策讨论产生了负面影响。为了解决这一差距,我们试图使用更敏感的指标 MANUSH 来开发一个评估印度三重营养不良负担的综合指数。

方法

本研究使用来自公开的全国性调查——国家家庭健康调查(NFHS)和综合国家营养调查(CNNS)的数据。首先,我们解决了 MANUSH 综合索引方法相对于传统聚合方法的稳健性问题。其次,使用 MANUSH 得分,我们评估了不同时期 NFHS-3(2005-06 年)、NFHS-4(2015-16 年)和 CNNS(2106-18 年)的次国家层面的三重营养不良负担。使用映射和空间分析工具,我们评估了州内和州际之间的邻里依赖关系和集群的形成。

结果

MANUSH 方法的分数优于使用线性聚合或几何平均值的其他聚合措施。它通过满足短差和差距敏感的附加条件来实现这一点,这隐含地惩罚了在最差维度的改善小于最佳维度的改善的情况,或者即使复合指数整体有所改善,不同维度之间的差距也没有缩小的情况。MANUSH 分数有助于揭示不同指标之间营养结果改善的差距,以及印度州内和州际之间的不平等程度不断上升。发现了高负担和低负担地区的显著集群(p<0.05),揭示了地理异质性和明显的区域差异。基于 MANUSH 的指数在特定于上下文的规划和优先考虑不同干预措施方面很有用,这是印度新启动的国家营养使命所倡导的方法。

结论

基于 MANUSH 的指数强调营养结果的平衡发展,因此与印度这样多样化和不均衡发展的经济体相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87fa/7427294/ced02f7e031d/12939_2020_1249_Fig1_HTML.jpg

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