This repository contains all the R code used to produce the Global Health Estimates of Stunting and Overweight, as developed by the UNICEF-WHO-World Bank Joint Child Malnutrition working group.
The R scripts in this repository are organized into several folders, each serving a specific purpose in the data processing and modeling workflow. Each folder contains a README file with more details about its contents and specific instructions.
To understand the technical details of the modeling procedure and the methods used to estimate confidence and prediction intervals, please refer to:
- McLain et al. (2019)
- An application of the methods published in Saraswati et al. (2022), and a corresponding editorial by Finaret (2022).
This folder contains R code to perform multiple imputation of the covariate data.
This folder includes programs to:
- Impute missing standard error (SE) information.
- Integration of data sources that were originally collected using different (non-standard) age ranges.
- Merge survey data with covariate data.
- Generates approximate sex-specific prevalence rates for specific years and countries (solely for use in visual figures).
This folder contains scripts for performing a multiply imputed analysis of the data for stunting or overweight.
In this folder, you will find code for:
- Pooling imputed estimates.
- Plotting results.
- Comparing estimates with past data.
- Data: Contains survey prevalence estimates, raw covariate data, country-level classifications, and outputted analysis files.
- Figures: Contains outputted figures displaying the results.
- Utils: Contains various programs and functions required to run the analyses.
All the programs in the folders Preparing Primary Data, Model, and
Results need to be run separately for both Stunting and Overweight.
Ensure that you read each file carefully to verify that the files are
named and stored correctly.
For further reading on the technical details and applications, please refer to the McLain et al. (2019).
This project is licensed under the MIT License. See the LICENSE file for details.
For questions or issues, please contact the repository maintainer.
Finaret, Amelia B. 2022. “Advancing Nutritional Epidemiology by Linking Datasets and Addressing Data Quality.” The Journal of Nutrition 152 (7): 1595–96. doi.org/10.1093/jn/nxac092
McLain, Alexander C, Edward A Frongillo, Juan Feng, and Elaine Borghi. 2019. “Prediction Intervals for Penalized Longitudinal Models with Multisource Summary Measures: An Application to Childhood Malnutrition.” Statistics in Medicine 38 (6): 1002–12. doi.org/10.1002/sim.8024
Saraswati, Chitra M, Elaine Borghi, João JR da Silva Breda, Monica C Flores-Urrutia, Julianne Williams, Chika Hayashi, Edward A Frongillo, and Alexander C McLain. 2022. “Estimating Childhood Stunting and Overweight Trends in the European Region from Sparse Longitudinal Data.” The Journal of Nutrition 152 (7): 1773–82. doi.org/10.1093/jn/nxac072