Mkulu-Statix/dhs-data-analysis-kenya

Analysis of child malnutrition and inequality in Kenya using DHS data and R. # DHS Child Malnutrition Analysis in Kenya ## Project Overview This project analyzes child malnutrition in Kenya using data from the Demographic and Health Surveys (DHS) Program. The study focuses on three key nutritional indicators among children under five years of age: - Stunting (height-for-age) - Wasting (weight-for-height) - Underweight (weight-for-age) The analysis was conducted using R and demonstrates data cleaning, indicator creation, prevalence estimation, and data visualization. ## Objectives - Measure the prevalence of child malnutrition in Kenya. - Create nutritional indicators using WHO z-score thresholds. - Visualize the prevalence of stunting, wasting, and underweight. - Demonstrate practical statistical programming skills using real-world survey data. ## Dataset - Source: Demographic and Health Surveys (DHS) Program - Country: Kenya - File: KEKR8AFL.DTA - Population: Children under five years of age ## Methodology 1. Import DHS data. 2. Select relevant anthropometric variables. 3. Recode WHO z-scores. 4. Create binary indicators using WHO thresholds (DHS stores z-scores multiplied by 100): - Stunted: hc70 < -200 (equivalent to height-for-age z-score < -2 SD) - Wasted: hw72 < -200 (equivalent to weight-for-height z-score < -2 SD) - Underweight: hw71 < -200 (equivalent to weight-for-age z-score < -2 SD) 5. Calculate prevalence percentages. 6. Produce summary tables and visualizations. ## Tools and Packages ### Software - R - RStudio - Git - GitHub ### R Packages - haven - dplyr - tidyr - ggplot2 ## Repository Structure dhs-data-analysis-kenya/ ├── README.md ├── Child_Malnutrition_Report.Rmd ├── data/ │ └── KEKR8AFL.DTA ├── scripts/ │ └── Child_Malnutrition_Analysis_Kenya.R └── outputs/ ├── prevalence_table.csv ├── stunting_plot.png ├── wasting_plot.png ├── underweight_plot.png └── child_malnutrition_report.pdf ## Key Findings The analysis estimates the prevalence of: - Stun …