Analysis of healthcare access inequality in Kenya using DHS data (Python, data cleaning, visualization)
Kenya Healthcare Inequality Analysis (DHS Data)
Project Overview
This project analyzes healthcare inequality in Kenya using data from the Demographic and Health Survey (DHS). The goal is to examine disparities in healthcare access and utilization across different socioeconomic and demographic groups.
Healthcare inequality remains a significant challenge in Kenya, particularly across wealth levels, education categories, and rural versus urban populations. This analysis explores the extent and patterns of these disparities using nationally representative survey data.
Research Objectives
To examine whether wealth index affects access to healthcare services.
To analyze disparities in maternal healthcare utilization.
To compare healthcare access between rural and urban populations.
To investigate the role of education level in healthcare outcomes.
📊 Dataset
The analysis uses data from the Kenya DHS dataset:
File format: .DTA (Stata format)
Source: Demographic and Health Surveys (DHS) Program
Population: Women aged 15–49
Geographic coverage: National (Kenya)
Note: The raw DHS dataset is not included in this repository due to size and data usage restrictions.
Methodology
The project includes:
Data cleaning and preprocessing
Descriptive statistics
Cross-tabulation analysis
Visualization of inequality patterns
Regression analysis to assess determinants of healthcare access
Tools and Libraries
Python
Pandas
NumPy
Matplotlib
Seaborn
Statsmodels
Pyreadstat
📁 Project Structure
Kenya-healthcare-inequality-dhs/
│
├── data/ # Local DHS dataset
├── scripts/ # Python analysis scripts
├── outputs/ # Generated results
├── requirements.txt # Project dependencies
└── README.md
👩🏽💻 Author
Wanjala Diana
Statistics & Data Science Enthusiast
Kenya