Chapter 12: Sexually Transmitted Infections: HIV/AIDS and Other Communicable Conditions Critical Thinking Exercise: Causes of Death Around the World

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You must read each slide, and complete any questions on the slide, in sequence.

Chapter 12: Sexually Transmitted Infections: HIV/AIDS and Other Communicable Conditions

Critical Thinking Exercise: Causes of Death Around the World

The Institute for Health Metrics and Evaluation reported that the topography of disease-related deaths has changed over many generations, and that different diseases, both communicable and noncommunicable, are starting to affect communities differently. Specifically, the researchers identify that the typical life expectancy has increased on a global scale, which means there are now different, previously unknown risks and causes of illness due to aging populations. Of specific interest the researchers mention that the “leading causes of death and disability have changed from communicable diseases in children to noncommunicable diseases in adults” (IME, 2013). The United States and other developed and industrialized nations have seen a stark reduction in maternal, nutritional, and premature child deaths. Third-world or underdeveloped nations, however, have seen a spike in communicable, maternal, nutritional and child related diseases. The Institute for Health Metrics and Evaluation implemented the Global Burden of Disease (GBD) study to systematically address health concerns related to a number of demographic characteristics. The GBD 2010 study found an increased life expectancy of 35 years since 1970 for many industrialized nations, but negligible improvement in life expectancy in developing nations such as sub-Saharan Africa.

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As part of this exercise, check out the data presented in Figure 12.1: Top 10 Causes of Death. Review the data presented and interpret the findings in answering the following questions. Why is it important to research and understand the causes of death in various economies across the world?

Research related to causes of death, as well as disease transmission and disease trends, is important in prevention. Understanding the evolution and transition of diseases in various areas of the world may provide more specific targets for vaccinations and health education.

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Compare and contrast the major causes of death for each of the four economic groups. What conclusions can you draw from this data?

Students should show critical analysis in interpreting the data in the graph and presenting it here by comparing and contrasting the different groups for the same disease, and across diseases. Be sure students do not simply list information for each group but compare and contrast them. Identify and explain some of the factors related to the various causes of death for these groups. For example, why are noncommunicable diseases more common in higher income groups, while communicable diseases are more common in lower income groups?

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Those with higher income are more likely to live in more sanitary conditions and are more likely to receive vaccines, leading them to be at lower risk of communicable diseases. However, greater access to food and alcohol, as well as higher stress levels, could result in higher income economies being at greater risk for lifestyle related diseases, such as heart disease. Students may present alternative hypotheses for the patterns observed in the data. How are the graphs misleading in the presentation of the data on these causes of death for the four economic groups? Consider the x-axis and y-axis, as well as the colors used in this analysis. How could we use this information to improve upon these graphs?

If one was to quickly glance at the graphs, they might assume the colors represent the same causes. For example, we might assume that dark blue always represents heart disease and is presented as the number one cause of death for all groups. In addition, we might believe that the causes for death are the same in all four groups, though the second through the tenth causes are more prevalent in the lower-income economies. This is an incorrect assumption since the disease names change along the y-axis, though the colors are in the same order. In addition, the ranges provided on the x-axis are different for each group, with the lowest income group having an exaggerated scale since the numbers are lower than in the other three groups. This would lead us to believe these numbers are higher when compared to the other three groups.

Changes to the graphs could include using different colors for different diseases, and making the x-axis consistent across all four graphs. Students may offer other suggestions in terms of how to combine the data in one larger graph or making sure data is provided for each of the economies on each of the causes listed.