phancykemunto/kenya-child-nutrition-analysis

# 🌍 Kenya Child Nutrition Analysis: From Data to Policy Action > **Transforming survey data into actionable nutrition policy recommendations using advanced statistical methods and interactive visualizations** ## 📊 Project Overview This project analyzes **17,280 children** from the Kenya Demographic and Health Survey (KDHS) to identify critical drivers of child malnutrition and provide evidence-based policy recommendations. By combining **survey-weighted logistic regression**, **geographic analysis**, and **interactive visualizations**, the analysis reveals actionable insights for resource allocation and intervention design. The analysis covers the three core WHO malnutrition indicators: | Indicator | Definition | Reflects | |-----------|-----------|----------| | **Stunting** | Height-for-Age Z-score (HAZ) The pipeline moves from raw KDHS survey data through cleaning and standardization in Stata, survey-weighted prevalence estimation, stratified subgroup analysis, and finally to policy-ready dashboards and evidence-based recommendations. --- ## 🗃️ Data Description **Source:** Kenya Demographic and Health Survey (KDHS) The dataset includes the following key variables: | Variable Category | Variables | |-------------------|-----------| | **Child Anthropometry** | Height (cm), Weight (kg) | | **WHO Z-scores** | HAZ (height-for-age), WAZ (weight-for-age), WHZ (weight-for-height), BMIZ | | **Demographics** | Age in months, sex, date of birth | | **Household Characteristics** | Wealth index quintile, maternal education level | | **Survey Design** | Cluster, strata, sample weights | --- ## 📊 Key Findings ### National Prevalence | Indicator | National Prevalence | |-----------|-------------------| | Stunting | ~22% | | Wasting | ~12% | | Underweight | ~16% | --- ### Stunting by Region — Top Hotspots > Regions above the 25% WHO threshold (red dashed line) require priority intervention: | Region | Stunting Prevalence | |--------|-------------------| | …