Introduction

Focus

Main Variables of Interest

Cleaning and Recoding

Descriptive Analysis

Race
Age
Gender
Education
Unemployment
Income
Illness

Discussion

Paige M. Smyth
M.P.P./M.P.H. Candidate 2007
Gerald R. Ford School of Public Policy
University of Michigan, Ann Arbor
December 2006

Introduction

According to the World Health Organization, the life expectancy in South Africa is a mere 47 years of age for males; 48 years for females1. The country ranks in the lowest quartile in terms of infant mortality2, and with 18.8% of its adult population infected, has one of the highest prevalences of HIV/AIDS in the world3. The current health workforce is inadequte to meet all of the needs of the population. In 2004, for every 1,000 South Africans, there were only 0.77 physicians, 4.08 nurses, and 0.20 community health workers4. And in the wake of apartheid, racial disparities in terms of income, education, and employment add to the difficulty supporting a healthy population. It is safe to say that South Africa faces numerous challenges in improving the health of its nation.

The goal of this project is to provide a descriptive analysis of the sick population in South Africa as well as to identify how the sick population has changed over several demographic and economic characteristics from 1994 to 2004. Information is crucial to identifying the populations most in need to efficiently allocate time and resources in addressing health issues in South Africa.

Focus and Data

We want to characterize the sick population based on several demographic, economic, and social factors.  For example, we want to know what the average household income was of the sick population.  We also want to know what the gender and age distributions looked like 1994 and how they have changed since.  To accomplish these goals we will use two datasets, the Southern Africa Labour Development Research Unit data, or Saldru data, taken from the South Africa Integrated Household Survey given in 1994 and data from the Statistics South Africa (SSA) General Household Survey given in 2004.  All variables of interest will be analyzed in both sets of data and compared.

The variables looked at in this project can be found in Figure 1.

 

A NOTE ON RACE:

For purposes of clarity and interpretation, I will be using the data's terminology for population groups. These are Africans, Coloureds, Indians, and Whites.