Poor and non-poor gap in under-five child nutrition: a case from Nepal using Blinder-Oaxaca decomposition approach.
Poor and non-poor gap in under-five child nutrition: a case from Nepal using Blinder-Oaxaca decomposition approach.
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DOI：
10.1186/s12913-022-08643-6
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发表时间：
2022-10-12
影响因子：
2.8
通讯作者：
中科院分区：
文献类型：
--
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许多低收入和中等收入国家在过去几十年中改善了健康指标，但社会经济群体之间的结果存在差异。对非贫困群体和贫困群体之间儿童营养差距的驱动因素进行系统分析，对于尼泊尔和其他国家在实现全民健康覆盖方面取得进展具有政策意义。本文的目的是估计属于非贫困和贫困群体的5岁以下儿童之间的平均身高年龄z分数（HAZ）的差距，划分差距到组件（禀赋，系数和交互作用），并确定每个组件的贡献最大的因素。有关6277名五岁以下儿童的信息摘自最新的全国代表性尼泊尔多指标聚类调查（MICS）2019。HAZ用于评估儿童的营养状况。财富指数用于将儿童分为非贫困和贫困。使用Blinder-Oaxaca技术将组间平均HAZ差距分解为以下组成部分：禀赋（预测因子水平的组差异）、系数（预测因子效应的组差异）和相互作用（由于预测因子水平和效应之间的相互作用而导致的组差异）。进行了详细的分解，以确定对每个组成部分贡献最大的因素。在尼泊尔五岁以下儿童中，HAZ（0.447; p < 0.001）测量的非贫困和贫困儿童营养结果存在显著差距。研究参与者（捐赠）预测因素的组间平均差异对差距的贡献为0.210（47%）。同样，预测因子（系数）效应的组间差异对差距的贡献为0.308（68.8%）。相互作用对最小化差距的贡献为-0.071（15.8%）。对差距贡献最大的预测因素/变量是：（一）禀赋：母亲教育、省份（Karnali、Sudurpaschim、Madhesh）、居住地（农村/城市）、厕所设施类型和族裔群体（达利特人和穆斯林）;（二）系数：家庭中五岁以下儿童人数、族裔群体（达利特人和穆斯林）、厕所设施类型、母亲年龄和教育。对儿童营养差距的分解表明，缩小财富群体之间的不平等不仅取决于提高贫困群体的预测因子（禀赋）水平，而且还取决于减少预测因子（系数）的差异效应。在线版本包含补充材料，可通过10.1186/s12913-022-08643-6获得。
Many low-and middle-income countries (LMICs) have improved health indicators in the past decades, however, there is a differential in outcomes between socioeconomic groups. Systematic analysis of drivers of child nutrition gap between non-poor and poor groups has a policy relevance in Nepal and other countries to make progress towards universal health coverage (UHC). The objective of this paper was to estimate the mean height-for-age z scores (HAZ) gap between under-five children belonging to non-poor and poor groups, divide the gap into components (endowments, coefficients and interaction), and identify the factors that contributed most to each of the component. Information about 6277 under-five children was extracted from the most recent nationally representative Nepal Multiple Indicator Cluster Survey (MICS) 2019. HAZ was used to assess nutritional status of children. Wealth index was used to categorize children into non-poor and poor. Mean HAZ gap between groups was decomposed using Blinder-Oaxaca technique into components: endowments (group difference in levels of predictors), coefficients (group difference in effects of predictors), and interaction (group difference due to interaction between levels and effects of predictors). Detailed decomposition was carried out to identify the factors that contributed most to each component. There was a significant non-poor and poor gap in nutrition outcome measured in HAZ (0.447; p < 0.001) among under-five children in Nepal. The between-group mean differences in the predictors of study participants (endowments) contributed 0.210 (47%) to the gap. Similarly, the between-group differences in effects of the predictors (coefficients) contributed 0.308 (68.8%) towards the gap. The interaction contributed -0.071 (15.8%) towards minimizing the gap. The predictors/variables that contributed most towards the gap due to (i) endowments were: maternal education, province (Karnali, Sudurpaschim, Madhesh), residence (rural/urban), type of toilet facility and ethnic group (Dalit and Muslim); (ii) coefficients were: number of under-five children in family, ethnic group (Dalit and Muslim), type of toilet facility, maternal age and education. Decomposition of the child nutrition gap revealed that narrowing the inequality between wealth groups depends not only on improving the level of the predictors (endowments) in the poor group but also on reducing differential effects of the predictors (coefficients). The online version contains supplementary material available at 10.1186/s12913-022-08643-6.
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4.8
作者：
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