Income and Life Expectancy

Gapminder World (http://www(dot)gapminder(dot)org/world/) is a tool for viewing, presenting, and understanding a wide range of statistical data including health, population, and economics. This is the software that Hans Rosling has used to very effectively communicate the the information contained in a wide range of data sets about the countries of the world. The software, plus a very large number of data sets, are available online.
In this assignment, you will use Gapminder World, plus other information resources, to explore how a relationship of interest to you changes over time. You should compare at least one "high income" or "middle income" country to one or more "low income" countries. You should create an argument about the relationship and present your argument in an essay; this essay will be posted in the discussion forum. (As you recall from Module 4, an argument includes a claim supported by one or more reasons and their evidence, an acknowledgment and response, and a warrant.)
When you are on the Gapminder World page, you can access a video that shows how to use the chart application by clicking on the "How to Use" button or on the "Learn to select indicators and more" link. There is also a PDF Guide on how to use the chart application (http://www(dot)gapminder(dot)org/GapminderMedia/wp-uploads/tutorial/Gapminder_World_Guide.pdf).
You post should include the following components:
Your written essay of 250-1000 words.
Your essay should include at least one figure created with Gapminder World. To create this figure:
Select the two or more countries you are comparing so that the names of the countries are indicated on your chart.
Make sure "Trails" is selected; this will create a trail of your country data over time.
Click on "Play".
Once the animation has completed, take and save a screen shot of the graph; include the horizontal and vertical axes in this screen shot.
In the post editor, insert the screen shot into your post by clicking on the image icon (see Figure 1) or right clicking at the point where you want to insert the image and selecting image. Do not attached your figure as a file to your post. Do not create a word document and attach that to your post.
This figure should be integrated into your post:
Your essay should refer to ("cite") your figure in the text.
Your figure should have a caption.
Your essay should include a bibliography with at least one source that is cited in the essay. This source or sources should provide evidence to back up your argument.
Check that your chart for your figure is visible in your post. Do not attach the image! Do not attach a word document! Attachments will not be graded!
Reply
Reply to one classmate's post in the discussion forum. Your reply should evaluate their use of statistics as evidence in their argument. Identify at least one alternate explanation for the pattern they have graphed. Include a bibliography with at least one formally cited source to back up your alternate explanation.
Classmates post (graph attached)
It has long been debated whether income affects life expectancy. It is clear that it does. This is due in large part, to the lack of clean water due to low income. Typically most countries with greater than 90% of households with improved water have an average GDP per capita of more than $10,000-15,000. Those at lower incomes tend to have a larger share of the population without access. [1] This means that those countries with lower income would have a lower life expectancy as can be seen in Figure 1.
africasingaporepng.png
Figure 1
Comparing income to life expectancy in Singapore and the Central African Republic from 1800 to 2020 Source: Free material from www(dot)gapminder(dot)org
For those countries that can afford the infrastructure associated with clean water, the life expectancy is higher, as evidenced by Singapore in figure 1. One of the highest income nations as well as the most life expectancy. On the other end of the chart, the Central African Republic is one of the poorest countries in the world and has a corresponding low life expectancy.
Water is one of the contributing factors to the low life expectancy as there is less sanitation which leads to the greater prevalence of diseases. In particular, Diarrheal disease, one of the leading causes of death in sub-Saharan Africa, is exacerbated by a lack of clean water. Evidence shows that diarrhoeal diseases disproportionately affect locations with poor access to health care, safe water, and sanitation, and low-income or marginalized populations.[2]
Some might say that it is war or lack of food that is the reason behind low life expectancy in CAR but even those reasons are tied to water in some form, either in the control of existing infrastructure or in ways to sanitize and prepare foods.
[1] H. Ritchie and M. Roser, “Clean Water,” Our World in Data, 26-Sep-2019. [Online]. Available: https://ourworldindata(dot)org/water-access#access-to-improved-water-sources-increases-with-income. [Accessed: 07-Feb-2021].

[2] “Estimates of the global, regional, and national morbidity, mortality, and aetiologies of diarrhea in 195 countries: a systematic analysis for the Global Burden of Disease Study 2016,” 19-Sep-2018. [Online]. Available: https://www(dot)thelancet(dot)com/journals/laninf/article/PIIS1473-3099(18)30362-1/fulltext#back-bib2. [Accessed: 07-Feb-2021].