SihleNala-byte/UNICEF-Child-Malnutrition-Analysis-Southern-Africa
Domaine:
healthcareType de record:
project
Créateur:
Sih
Hôte:
Exploratory analysis of child malnutrition across Southern Africa using UNICEF's global nutrition dataset (1970–2023, 27,893 rows). Investigates stunting trends, gender gaps, and country-level burden using R and ggplot2. Highlights persistent inequalities across Mozambique, Madagascar, Malawi, and beyond.
# UNICEF Child Malnutrition Analysis - Southern Africa
An exploratory data analysis of child malnutrition indicators across Southern Africa, using UNICEF's global nutrition dataset spanning 1970-2023. The analysis investigates stunting trends, gender gaps, and the regional burden of malnutrition across 200 countries, with a focused lens on the Southern African region.
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## Background & Motivation
Child malnutrition remains one of the most persistent development challenges in Sub-Saharan Africa. Stunting, a marker of chronic undernutrition, affects millions of children under five and has lifelong consequences for cognitive development, educational outcomes, and economic productivity.
This project uses publicly available UNICEF data to answer four targeted questions about the state of child malnutrition in Southern Africa, comparing the region to global benchmarks, tracking progress over time, examining gender disparities, and identifying which countries carry the highest burden.
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## Research Questions
| # | Question |
|---|---|
| Q1 | How does stunting in Southern Africa compare to global averages? |
| Q2 | Has stunting improved over time in Southern Africa? |
| Q3 | Is there a gender gap in stunting rates across Southern Africa? |
| Q4 | Which Southern African countries have the highest burden of child malnutrition? |
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## Data Source
**UNICEF Data Warehouse (DW)**
Accessed at data.unicef.org
> UNICEF Data Warehouse (2025). *Child nutrition indicators, global dataset.* Retrieved from data.unicef.org
- **Coverage:** 200 countries | 16 indicators | 1970–2023
- **Format:** Single CSV export | 27,893 rows
- **Access:** Publicly available, no login required
### Variables Used
| Variable | Column Name | Description |
|---|---|---|
| Country | `country` | Country name |
| Country code | `country_code` | ISO 3-letter code (e.g. ZWE) |
| Indicator | `indicator_code` | Which nutrition measure |
| Sex | `sex` | Male / Female / Total |
| Age …