Dietary staple type, protein quality and child wasting and stunting across 127 LMICs: an ecological cross-sectional study — data and code

This repository contains the analytical datasets, master food balance sheet dataset, and R code required to reproduce the primary analysis, sensitivity analyses, secondary cross-reference analyses, post-hoc maternal anthropometry analysis, and choropleth maps reported in the manuscript "Dietary staple type, protein quality and child wasting and stunting across 127 LMICs - an ecological cross-sectional study" (medRxiv preprint: https://doi.org/10.64898/2026.07.13.26357913). Data are de-identified, country-level aggregates drawn from publicly available sources: the Joint Malnutrition Estimates (JME, March 2025) for child wasting and stunting prevalence, the Global Burden of Disease study (GBD 2023) for disease and care covariates, and FAOSTAT (2019-2023 five-year means) for staple protein, animal protein, and caloric supply. No individual-level or identifiable data are included. The package includes: primary analytical dataset (n=127 LMICs for wasting, 126 for stunting); population-weighted dataset (used for sensitivity analysis S5); master food balance sheet dataset used for choropleth map generation (138 countries); secondary cross-reference datasets (Grellety & Golden WHZ-MUAC discordance data, n=46, and Kerac et al wasting-and-stunting in infants under 6 months, n=56); post-hoc maternal anthropometry cross-reference dataset (DHS StatCompiler, n=57); and nine R scripts covering data correction, primary robust MM-estimation and quantile regression analyses, five pre-specified sensitivity analyses, secondary cross-reference analyses, and choropleth map generation. Full documentation of file contents, column definitions, data corrections applied prior to analysis, and step-by-step instructions for reproducing all reported results is provided in README.txt and DATA_DICTIONARY.md within this repository.本仓库包含复现论文"Dietary staple type, protein quality and child wasting and stunting across 127 LMICs - an ecological cross-sectional study"（medRxiv预印本：https://doi.org/10.64898/2026.07.13.26357913）中报告的主要分析、敏感性分析、二次交叉参照分析、事后母体人体测量分析及等值区域图（choropleth maps）所需的分析数据集、主食物平衡表数据集与R代码。 本数据集均为去标识化的国家级汇总数据，来源于公开可获取的数据源：儿童消瘦与发育迟缓患病率数据来自联合营养不良估计报告（Joint Malnutrition Estimates, JME，2025年3月），疾病与照护协变量数据来自全球疾病负担研究2023（Global Burden of Disease study, GBD 2023），主食蛋白质、动物蛋白质与热量供给数据来自FAOSTAT（2019-2023年五年均值）。本数据集未包含任何个体级或可标识化数据。 本数据包包含：用于主要分析的数据集（针对儿童消瘦研究纳入127个中低收入国家（Low- and Middle-Income Countries, LMICs），儿童发育迟缓研究纳入126个）；用于敏感性分析S5的人口加权数据集；用于生成等值区域图的主食物平衡表数据集（覆盖138个国家）；二次交叉参照数据集（包括Grellety与Golden的WHZ-MUAC不一致性数据，n=46，以及Kerac等人关于6个月以下婴儿消瘦与发育迟缓的研究数据，n=56）；事后母体人体测量交叉参照数据集（来源于DHS StatCompiler，n=57）；以及9个R脚本，涵盖数据校正、主要稳健MM估计与分位数回归分析、5项预设敏感性分析、二次交叉参照分析及等值区域图生成。 本仓库内的README.txt与DATA_DICTIONARY.md文件提供了完整的文档说明，涵盖文件内容、字段定义、分析前实施的数据校正方法，以及复现所有报告结果的分步操作指南。