The impact of diet diversity—defined as the number of different foods or food groups consumed over a given reference period—on child nutrition outcomes strongly interacts with agro-ecological, institutional, and socio-economic drivers of child food and nutrition security. Yet, the literature on the impact of diet diversity typically estimates average treatment effects, largely ignoring impact heterogeneity among different groups. In this paper, we introduce a new method of profiling to identify groups of treatment units that stand to gain the most from a given intervention. We start from the ‘polling approach’ which provides a fully flexible (non-parametric) method to profile vulnerability patterns (patterns in ‘needs’) across highly heterogeneous environments [35]. Here we combine this polling methodology with matching techniques to identify ‘impact profiles’ showing how impact varies across non-parametric profiles. We use this method to explore the potential for improving child nutrition outcomes, in particular stunting, through targeted improvements in dietary diversity in a physically and socio-economically diverse country, namely Zimbabwe. Complex interaction effects with agro-ecological, institutional and socio-economic conditions are accounted for. Finally, we analyze whether targeting interventions at the neediest (as identified by the polling approach) will also create the largest benefits. The dominant profile for stunted children is that they are young (6–12 months), live in poorer/poorest households, in rural areas characterized by significant sloping of the terrain and with one-sided emphasis on maize cultivation and medium dry conditions. When moving from “need” to “maximal impact”, we calculate both the coverage in “need” as well as the impact coverage, and find that targeting on need does not always provide the largest impact. Policy-makers need to remain alert that targeting on need is not always the same as targeting on impact. Estimation of heterogeneous treatment effects allows for more efficient targeting. It also enhances the external validity of the estimated impact findings, as the impact of child diet diversity on stunting depends on various agro-ecological variables, and policy-makers can relate these findings to areas outside our study area with similar agro-ecological conditions.

中文翻译：

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谁缺乏饮食多样性，谁受益于饮食多样性：来自津巴布韦儿童（影响）分析的证据

饮食多样性（定义为在给定参考期内消耗的不同食物或食物组的数量）对儿童营养结果的影响与儿童粮食和营养安全的农业生态、体制和社会经济驱动因素密切相关。然而，关于饮食多样性影响的文献通常估计平均治疗效果，很大程度上忽略了不同群体之间的影响异质性。在本文中，我们引入了一种新的分析方法，以识别能够从给定干预措施中获得最大收益的治疗单位组。我们从“轮询方法”开始，它提供了一种完全灵活的（非参数）方法来分析高度异构环境中的漏洞模式（“需求”模式）[35]。在这里，我们将这种民意调查方法与匹配技术相结合，以识别“影响概况”，显示影响在非参数概况中的变化情况。我们使用这种方法来探索通过在物质和社会经济多样化的国家（即津巴布韦）有针对性地改善饮食多样性来改善儿童营养结果（特别是发育迟缓）的潜力。考虑了与农业生态、体制和社会经济条件的复杂相互作用效应。最后，我们分析针对最需要的人（通过民意调查方法确定）的干预措施是否也会带来最大的效益。发育迟缓儿童的主要特征是他们年龄较小（6-12 个月），生活在较贫困/最贫困的家庭中，居住在地形明显倾斜的农村地区，并且片面强调玉米种植和中等干旱条件。当从“需要”转向“最大影响”时，我们计算了“需要”的覆盖范围以及影响覆盖范围，发现以需求为目标并不总是能产生最大的影响。政策制定者需要保持警惕，以需求为目标并不总是以影响为目标。异质治疗效果的估计可以实现更有效的靶向。它还增强了估计影响结果的外部有效性，因为儿童饮食多样性对发育迟缓的影响取决于各种农业生态变量，政策制定者可以将这些发现与我们研究区域以外具有类似农业生态条件的地区联系起来。