Identifying Optimal level of characteristics of risk group subsets minimizing adverse nutritional outcome in India: A CART based Regression Tree Approach

Identifying Optimal level of characteristics of risk group subsets minimizing adverse nutritional outcome in India: A CART based Regression Tree Approach | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Identifying Optimal level of characteristics of risk group subsets minimizing adverse nutritional outcome in India: A CART based Regression Tree Approach Mukesh Ranjan, Laxmi Kant Dwivedi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7713523/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Child stunting remains a major public health challenge in India, reflecting persistent inequities in nutrition, health, and living conditions. This study applies a Classification and Regression Tree (CART) methodology to identify risk group subsets of children under five years, guided by the Sustainable Development Goal (SDG) principle of “Leave No One Behind (LNOB)” Using nationally representative NFHS-5 data (2019–21, n=208,657), we examine three sets of “circumstances” beyond a child’s control—standard (wealth, maternal education, sex, residence), extended (adding caste and religion), and reduced (excluding wealth)—to uncover intersectional vulnerabilities. CART regression trees reveal that maternal education is the most consistent protective factor, reducing stunting by 10–15 percentage points across contexts. Poverty, caste disadvantage, and rural residence compound risk, with Scheduled Castes, Scheduled Tribes, and Muslims disproportionately affected. At the national level, the Dissimilarity Index (D=0.2747) shows that nearly 27% of stunting inequality is attributable to unequal circumstances, with states such as Bihar, Uttar Pradesh, Gujarat, and Meghalaya recording the highest inequities. By contrast, Kerala, Punjab, and Sikkim show lower risks and more equitable outcomes. These findings demonstrate that stunting in India is shaped not only by economic deprivation but also by structural inequalities, underscoring the need for equity-focused, state-specific interventions. Stunting SDGs Circumstances LNOB Dissimilarity Index intersectional vulnerabilities NFHS-5 Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7713523","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":520602415,"identity":"32a19ce9-9b75-46b3-a8e4-bee3edab730f","order_by":0,"name":"Mukesh 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