An end-to-end data analytics project exploring child nutrition inequalities in Nigeria using Excel, SQL Server and Power BI.
# Health Inequality in Nigeria: A Child Nutrition Analysis
An end-to-end data analytics project analyzing child nutrition inequalities in Nigeria using WHO Global Health Observatory (GHO) data. The project explores how wealth, educational attainment, and place of residence influence childhood nutrition outcomes through SQL analysis and an interactive Power BI dashboard.
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## Dashboard Preview
### Wealth Inequality
### Education Inequality
### Rural vs Urban
### Findings & Recommendations
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## Project Overview
Child malnutrition remains one of Nigeria's most significant public health challenges. While national averages provide useful information, they often conceal inequalities between socioeconomic groups.
This project investigates disparities in three major child nutrition indicators:
- Stunting
- Underweight
- Wasting
The analysis focuses on how these outcomes differ across:
- Wealth Quintiles
- Education Levels
- Rural vs Urban Residence
The objective is to transform raw WHO health indicator data into actionable insights that can support evidence-based decision-making.
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## Business Problem
Public health interventions are more effective when resources are targeted toward the populations with the greatest need.
This project answers questions such as:
- Which socioeconomic factor has the strongest association with child malnutrition?
- How large are nutrition disparities between the poorest and richest households?
- Does educational attainment influence nutrition outcomes?
- Are rural communities disproportionately affected?
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## Dataset
**Source**
World Health Organization (WHO) Global Health Observatory (GHO)
**Country**
Nigeria
**Years**
2018–2022
**Rows Imported**
25,909
Following data cleaning and filtering, only child nutrition indicators relevant to the project objectives were retained.
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## Tools Used
| Tool | Purpose |
|------|---------|
| Microsoft Excel | Data auditing and validation |
| SQL Server | D …