Life Expectancy Is On The Rise. How Does GDP Affect Longevity?

Data from six different countries (Chile, China, Germany, Mexico, U.S., and Zimbabwe) was analyzed to draw conclusions about a country’s gross domestic product and life expectancy of the population.

In this study, data obtained from the World Health Organization and the World Bank provided information on the annual gross domestic product (GDP) and annual life expectancy of six countries from 2000 to 2015. These six countries included Chile, China, Germany, Mexico, United States of America, and Zimbabwe.

From the entirety of the data, life expectancy across these countries appears fill out a left skewed distribution while GDP forms a right skewed distribution. This is shown in Figure 1 below.

Figure 1: Distribution of Life Expectancy and GDP

This illustrates a majority life expectancy existing in the range of 70 to 80 years old while most GDP figures are found in the low to sub trillions. The life expectancy graph, however, contains a relatively large bin at the lowest limit. This will be explained by the next couple figures.

The distribution of GDP tends towards right skewed. This is due, in part, to the outliers in the data as well as the variety of the economies in the study.

Figure 2: Development of GDP’s over 15 year period

As shown in Figure 2 there are some recesses, but an overall trend upward for each country. The GDP scales from each country range from millions to trillions, creating a very diverse collection of economies. This helps to explain the right skew mentioned above, but how does life expectancy come into play?

Life expectancy plotted as a time series portrays a similar trend to gross domestic product (Figure 3). It too has small recesses encompassed by an overall positive trend, and like GDP there are large scaling differences. This is most notably apparent in Zimbabwe where the average life expectancy is approximately 50 while the remaining countries see averages larger than or equal to 74. This also helps to explain the age distribution in Figure 1.

Figure 3: Development of life expectancy over 15 year period

The relationship between GDP and life expectancy growth produces a Pearson correlation near for each country (greater than .9). This quantifies that the relationship between these two variables (GDP and life expectancy) is linear and an increase in one is associated with an increase in the other. This is further demonstrated by Figure 4 which shows the life expectancy data plotted as a function of GDP. The graph explicitly shows the strength of the correlation between the two variables.

Figure 4: Scatter plot of life expectancy vs GDP

GDP’s relation to life expectancy is not absolute and cannot be used to predict or explain life expectancy of one country relative to another. This is evident when comparing the mean values of each variable.

Figure 5: Life expectancy box plot and variable averages

Figure 5 represents data summaries for each country. As shown, the mean life expectancy does not influence the relative GDP or vice versa. This alludes to other variables affecting the relative life expectancy that are outside of the scope of this study.

In conclusion, the data suggests a strong tie between the development of a country’s economic output and the livelihood of its people. As a country creates more goods and services, its people see benefits which include longer lives. This study is limited in scope, however, and only contained data from 2000 to 2015. There is much more to be found out about the secret of longevity.