Publication:
Ranking Predictors of Child Dietary Diversity in Nepal Using a Decision Tree

creativeworkseries.issn3059-9547
dc.contributor.authorBaral, Dipesh
dc.contributor.authorLama, Dindu
dc.contributor.authorDangal, Archana
dc.contributor.authorBaral, Dinesh
dc.contributor.authorKharel, Jiban
dc.contributor.authorThapa, Abhishek
dc.contributor.authorDahal, Pragati
dc.contributor.authorBaral, Swastika
dc.date.accessioned2026-07-08T06:53:21Z
dc.date.available2026-07-08T06:53:21Z
dc.date.issued2025
dc.descriptionDipesh Baral Department of Mathematics and Statistics, Washington State University, Washington, USA Dindu Lama Department of Business and Economics, Wittenberg University, Ohio, USA Archana Dangal Paradise Creek Health and Rehabilitation of Cascadia, Idaho, USA Dinesh Baral Independent Researcher, USA Jiban Kharel Independent Researcher, USA Abhishek Thapa Independent Researcher, USA Pragati Dahal Department of Agricultural and Applied Economics, Virginia Polytechnic Institute and State University, Virginia, USA Swastika Baral Independent Researcher, USA
dc.description.abstractAbstract: Introduction: Minimum dietary diversity among children (MDD-C) remains low in Nepal, contributing to persistent malnutrition. This study aimed to rank and characterize the association of dietary, socioeconomic, and health-related predictors of MDD-C among children aged 6–59 months in Madhyapur Thimi Municipality of Nepal. Method: A secondary analysis of survey data from 375 children was conducted. Chi-squared tests were used to identify baseline associations of the predictors with MDD-C. A Chi-squared Automatic Interaction Detection (CHAID) decision tree was then fitted to identify key split variables and interaction structures. A CHAID-based sensitivity analysis was used to estimate food groups’ contributions to predicted dietary adequacy by toggling individual food groups from absent to present. Bootstrap resampling was used to quantify the internal variability of these estimates. Result: Overall, 73.6% of children were predicted to achieve MDD-C. The decision tree placed other fruits and vegetables (Group G) at the root level, followed by splits on eggs (Group E), legumes and nuts (Group B), and vitamin A–rich foods (Group F). Sensitivity analysis suggested that enabling consumption of Group G or Group E was associated with the largest expected improvements in predicted dietary adequacy, and bootstrap resampling indicated that this ranking was relatively stable across resamples. Conclusion: This model-based analysis indicates that Group G and Group E foods are strong positive predictors of adequate dietary diversity and offer the largest expected gains among diet-deficient children. Hence, access to Group G and Group E foods could be prioritized as dietary interventions to improve child nutrition.
dc.identifierhttps://doi.org/10.63455/jew8tz06
dc.identifier.urihttps://hdl.handle.net/20.500.14572/6879
dc.language.isoen_US
dc.publisherPublic Health Concern Trust-Nepal (phect-NEPAL)
dc.subjectBootstrap
dc.subjectChildren
dc.subjectDecision Tree
dc.subjectNutrition
dc.subjectSensitivity Analysis
dc.titleRanking Predictors of Child Dietary Diversity in Nepal Using a Decision Tree
dc.typeArticle
dspace.entity.typePublication
local.article.typeOriginal Article
oaire.citation.endPage6
oaire.citation.startPage1
relation.isJournalIssueOfPublicationfa2742db-eab9-441f-aa1f-ef81654e2340
relation.isJournalIssueOfPublication.latestForDiscoveryfa2742db-eab9-441f-aa1f-ef81654e2340
relation.isJournalOfPublication56ecabdf-56c9-4caa-af6a-1fce9c15c360

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