Chapter 19 : Urbanization, Population, and the Environment

Demographers who study population dynamics are interested in identifying factors associated with a society's life expectancy. Among those that play a part in determining life expectancy are illnesses, nutrition, and natural disasters. In this exercise we will also investigate whether there is an association between the level of national income and a society's overall life expectancy.

Before we begin, let's review the two concepts that we will be investigating. Life expectancy measures the average number of years a newborn infant can expect to live under the current mortality levels for a society or social group. The Gross National Income in Purchasing Power Parity (GNI PPP) per capita measures gross national income converted to "international" dollars, using a purchasing power parity conversion factor. International dollars indicate the amount of goods and services one could buy in the United States with a given amount of money. The GNI PPP per capita provides a realistic indication of the value generated by all of the resident producers plus the net receipts of primary income generated by the nation's residents doing business abroad.

Part I:

In this exercise, we will try to answer the question of whether income is related to life expectancy by conducting empirical research from twenty randomly picked countries. Table 1 lists the twenty countries selected. Up-to-date data on both life expectancy and gross national income is available at Population Reference Bureau website . Follow these steps to obtain data for the twenty randomly selected countries:

1. Using the "Select Country" option, scroll down the list of countries. You can select more than one nation by using the "control-mouse click."
2. After you have highlighted all twenty countries, then scroll through the "Population and Health Variables" to select the two variables.
3. Finally, click on the "Submit Query" button.
4. Write the numbers in the table below.

Writing Assignment 1:

After you complete the above table, look at the data carefully. Do you find a relationship? If so, is it positive or negative? It is probably difficult to determine by just looking at the above table:

Part II:

Another way to answer the question would be to do a scatterplot. A scatterplot allows you to visually examine the relationship between two variables. Below you will find a completed scatterplot for ten hypothetical countries. The X axis represents the GNI PPP per capita and the Y axis the life expectancy.

You will notice that there are ten data points on the scatterplot, one for each of the ten hypothetical countries. This graph suggests that there is a strong positive relationship between the two sets of hypothetical data. 

Part III:

Up-to-date data on infant mortality rates is also available at Population Reference Bureau website . Follow these steps to obtain data for the twenty randomly selected countries:

1. Using the "Select Country" option, scroll down the list of countries. You can select more than one nation by using the "control-mouse click."
2. After you have highlighted all twenty countries, then scroll through the "Population and Health Variables" to select the "Infant Mortality Rate (live births per 1000 deaths).
3. Finally, click on the "Submit Query" button.
4. After you have copied the life expectancy numbers from Table 1 into Table 2, fill in the information on infant mortality that you obtained through your research at the Population Reference Bureau.

Writing Assignment 2:

Based on the data from the table above and from discussion in the text, develop an explanation for the relationship between infant mortality and life expectancy. Do you think that infant mortality rates are related to the levels of national income?

Writing Assignment 3:

Why do you think life expectancy improves as a nation's gross national income rises and infant mortality falls? What benefits does rising income confer on individuals and on a society? Write a brief report for your professor about why these relationships between income level, infant mortality and life expectancy exist.