Economic Development and Public Health - An Analysis of Income and Life Expectancy
STEP 1: Data Set Selection
I have chosen to work with the Gapminder dataset to explore global trends in health and economics.
STEP 2: Identify a Specific Topic of Interest
After looking through the codebook for the Gapminder dataset, I decided that I am particularly interested in public health, specifically life expectancy.
STEP 3: Prepare a Personal Codebook (First Topic)
Since Gapminder provides a clear, single indicator for this topic, I added the lifeexpectancy variable to my personal codebook:
Variable Name: lifeexpectancy
Description: 2011 life expectancy at birth (years). The average number of years a newborn child would live if current mortality patterns were to stay the same.
STEP 4: Identify a Second Topic
While life expectancy is a good starting point, I needed to determine what factors might influence how long people live across different countries. It strikes me that nations with higher economic resources generally seem to have better healthcare systems and living conditions. Therefore, I decided that I am most interested in exploring the association between a country's wealth and its life expectancy.
STEP 5: Add Second Topic to Personal Codebook
I added to my personal codebook the variable reflecting economic development (incomeperperson):
Variable Name: incomeperperson
Description: 2010 Gross Domestic Product per capita in constant 2000 US$. The inflation but not the differences in the cost of living between countries has been taken into account.
STEP 6: Literature Review
To understand the existing research on this topic, I conducted a brief literature review:
Search Terms Used: I used Google Scholar with the exact search terms: "GDP per capita and life expectancy", "economic development and mortality rates", and "income inequality and public health".
Summary of Findings: The literature consistently shows a strong, positive relationship between national income and life expectancy, a pattern famously known as the "Preston Curve". Researchers highlight that higher income per capita allows countries to invest more heavily in healthcare infrastructure, sanitation, and nutrition. Interestingly, studies also show that this relationship is non-linear: gains in life expectancy are massive when moving from extreme poverty to middle-income, but the curve flattens out among the wealthiest nations, where lifestyle factors play a larger role.
Preston, S. H. (1975). The changing relation between mortality and level of economic development. Population Studies, 29(2), 231-248.
Deaton, A. (2003). Health, inequality, and economic development. Journal of Economic Literature, 41(1), 113-158.
STEP 7: Research Question & Hypothesis
Research Question: Is there a direct and positive association between a country's income per person (incomeperperson) and the life expectancy of its inhabitants at birth (lifeexpectancy)?
Hypothesis: Based on the literature review, my hypothesis is that there is a positive association between a country's wealth and its health outcomes. Specifically, if a country has a higher incomeperperson, then its lifeexpectancy at birth will also be significantly higher, because greater economic resources provide better living conditions and medical care.