If you haven't been
directly affected by diabetes mellitus, you probably know
someone who is or has been affected by it. Furthermore,
with the incidence of
diabetes in the United States skyrocketing, your
chances of getting the disease is higher than ever. Type
2 Diabetes, once referred to as "adult onset diabetes" because it
usually afflicts adults, can no longer be called that because it is now being
diagnosed in children as young as five years old. This is
thought to be a
result of increasing childhood obesity and sedentary lifestyle, both of
which are associated with the convenience and the poor quality of fast
food and its consumption.
Are YOU at risk?
|Jokes about and symbols of our nation's
obsession with fast food and sedentary lifestyle can be found in many
These clips may be funny, but the
truth behind them is anything but funny. Diabetes
mellitus Type 2,
which is more often a result of a poor diet and exercise, is costing
our nation billions of dollars in health care a year. If left
diabetes can lead its victims into a coma that can result in death.
- The Simpson's portrayal of the lazy, fat American
you have gathered your data, use it to answer the following questions.
Using Excel for graphical displays and analysis will be very helpful!
there a strong
statistical relationship) between the percent of Americans that are
obese and the number of Americans with diabetes? Given this
relationship in addition to each variable's relationship with time, can you predict the number of Americans
have diabetes in the year 2010, 2020, and 2030?
2. Is there a strong correlation between the prevalence
food outlets (i.e. the number of franchises) and diabetes prevalence in
the United States? Given this relationship in addition to each
variable's relationship with time, can you predict the number of
will have diabetes in the year 2010, 2020, and 2030? You will consider
the international food chain McDonald's as a representative symbol for
the fast food industry.
3. Describe your findings and any discrepancies that you've
found trying to predict future diabetes prevalence. What can you do to
lessen your chances of getting diabetes?
of Data | Investigation
Tools | Defining
Terms | Manipulating
|Types of Data
- Prevalence of Diabetes
and II) in the United States, 1980 to present
- Percent of the United
population (not discriminating by age) that is obese, 1980-present
- Growth of McDonald's
franchises over time, 1980-present
- Centers for Disease
(CDC) Health Statistics--Diabetes and Obesity
- McDonald's Franchise
- Excel Spreadsheets and
- Other Excel Tools:
Functions, Trend line/Correlation
- Diabetes mellitus
- The word diabetes means urine, and the word mellitus
means sweet. Diabetes is a
condition in which the patient urinates frequently due to a buildup of
solutes in their blood. Diabetes mellitus (which has two forms--Type 1
and Type 2) is a condition which causes the patient to urinate
frequently, but the urine is sweet because the solute present is glucose that
did not get broken down in the blood. This happens because of either a
resistance to insulin or the absence of insulin in
- Type 1 and Type
1 Diabetes occurs when the patient produces either ineffective
insulin or none at all. This condition is generally hereditary and is
developed from a young age. Therefore it is often referred to as juvenile-onset
2 Diabetes occurs when the patient's immune system develops a
resistance to its own insulin. Therefore, the insulin is present but
not used. The resistance often happens as a result to an overexposure
to glucose in the diet (i.e., overeating that often times leads
to obesity). Type 2 Diabetes is usually developed by adults (hence
"adult-onset"), but with the increasingly sedentary, food-centered
lifestyle that Americans have become accustomed to, it
is now being developed by children as young as five.
- A chemical produced by the pancreas that is
break to glucose in the blood.
- Prevalence and
- Prevalence refers to the total number of people who
- Incidence refers to how many new cases of a disease
reported in a certain time period (for example, in one year)
- A statistical relationship between two variables
between the prevalence of diabetes and obesity). A correlation is
measured as R².
- -1<R²<0 (negative
correlation) OR 0<R²<1
closer R² is to | 1 |, the stronger the
you will be plotting variables against time and then against one
another, fitting the resulting graphs with trend lines that generate a
correlation value and equation, and then using these tools to predict
future trends. Include
in your data sets statistics from 1980 on.
about which variable (i.e. obesity or diabetes) is
the dependent one, and which is the independent one.
- First graph
both variables as dependent on time. Add trend lines that show both the
equation of the lines and the correlation value (R²).
- Use the
diabetes vs. time graph to predict the prevalence of diabetes in the
years 2010, 2020 and 2030.
- Then graph both variables against one
another, and add a trend line as above.
- Use the values you just
predicted for diabetes prevalence in the future in your diabetes v.
obesity equation to predict the prevalence of diabetes in 2010, 2020
and 2030 as a function of obesity alone.
- Plot graphs that show the current rate of growth for
variables, and plot the two variables against each other as well.
McDonald's growth statistics are not extensively reported within the
United States, so it may be wise to use the worldwide statistics
the trend line for the McDonald's graph, predict the number of
McDonald's franchises that will be present in 2010, 2020, and 2030,
given the current rate of growth.
- Then use these extrapolated values in
you diabetes vs. fast food outlet equation to predict the prevalence of
diabetes in 2010, 2020, and 2030.
Question # 3
- Look at the difference between the sets of
future diabetes prevalence (from diabetes
v. time, diabetes v. obesity,
and diabetes v. McDonald's chains)
- You may want to go beyond simply describing the
in the numbers; graphing all three of the predicted trends (i.e., diabetes prevalence v. time)
through 2030 on the same graph may help.
- If the trends do not add up, what does this say? Is
diabetes still linked with obesity and fast food consumption? Hint: think about weaknesses in the data
collected, and think about the biological factors at hand (i.e., are
there multiple causes of diabetes, is there more than one type, etc.)
Listed below you will find links to key
data that you are to manipulate in order to solve the questions.
If you would like to know more about diabetes, your chances of getting
diabetes, or how you can prevent getting diabetes in your lifetime, you
may want to visit a few of the sites linked below.
the top of the page
the top of the page
- Students should use statistics for "Number of Persons Diagnosed with Diabetes,
1980-2000" for their diabetes
prevalence raw data. On the CDC Diabetes Statistics Index his is
found under "Prevalence of Diabetes, U.S. Population." After getting to
this page, students need to click on "Data for Figure" to get to the
raw data. The students should copy and paste this data into an
- Students will then need to
plot a graph of Diabetes Prevalence vs.
Time (years). They can then fit the resulting curve with a trend
line that will automatically generate an equation for the line as well
as a correlation (R²) value.
- Students will then need to retrieve the raw
data for the U.S. obesity statistics. From the CDC's Obesity
Statistics Index, this page can be found by clicking on "Prevalence of Diabetes Among U.S. Adults,
by Characteristics, 1991-2001." The data table presented
displays obesity statistics for various characteristics (gender,
ethnicity, age, etc.) as percentages of the U.S. adult population.
Students should extract the "total" data from the table and paste the
data in a new column in their existing Excel spreadsheet. (You may
notice that this data is not ideal because it only goes back to 1991,
it doesn't give data for each consecutive year, and it only includes
adults in its estimate).
- Students should graph both Obesity Prevalence vs. Time (on the
same graph as Diabetes vs. Time)
and Diabetes Prevalence vs. Obesity
Prevalence (individual plot). Again, fits with line equations
and correlation values should be shown.
- Students can answer how strong of a correlation there
between diabetes (dependent) and obesity (independent) by using the
correlation value they found for their Diabetes Prevalence v. Obesity Prevalence
- Students can use the equation from the Diabetes
v. Time plot to predict the prevelence (in millions of people) of
diabetes in the years 2010, 2020, and 2030. These numbers represent
the prediction based solely on the current rate, with no other
contributing factors (such as obesity or
fast food prevalence) affecting the rate of increase. If they'd
like, they can graph this extension.
- Students should use the Obesity Prevalence vs. Time
equation to predict the future prevalence of obesity in 2010, 2020, and
2030 given the current trend. Students can then plug these values for
obesity into their equation for Diabetes Prevalence v. Obesity
Prevalence to predict the prevalence of diabetes in 2010, 2020, and
2030 based on obesity as the sole
- Students will already have the diabetes statistics
needs in spreadsheet form. To this spreadsheet, they will need to add
data for the number of McDonald's worldwide (this is only necessary to
retrieve for the years 1980 and beyond. This data will have to be
manually picked out from the text of the McDonald's
- Students can express the rate of growth of McDonald's
franchises (used in this project to represent the fast food industry)
in graph form (i.e., Number of
McDonald's Outlets vs. Time). They should then fit this line and
display the automated equation and correlation value.
- Students should also graph Diabetes Prevalence vs. Number of
McDonald's Outlets, and they should derive the equations and the
correlation as above.
- Students should use the equation from the McDonald's vs. Time graph to
predict the number of franchises that will be present, given the
current rate of growth, in the years 2010, 2020, and 2030. Students
will then put these values into the equation for the Diabetes Prevalence vs. Number of
McDonald's Outlets graph in order to predict the prevalence of
diabetes in the future as solely dependent on size of McDonald's (fast
the top of the page
the top of the page
- Students should graph the three different predictions
diabetes prevalence vs. time.
- The three sets of prevalence of diabetes predicted by
independent variable should look similar, but not the same. The
students should use their graph (and the slopes of the lines) to
explain which set they think is closest to accuracy.
- In their analysis, the students should also consider
factors as data limitations (e.g., limited amount of data, compared
data from inconsistent or incompatible sources, etc.) as well as the
biological factors involved (e.g., the different types of diabetes and
their causes, the various factors involved in getting diabetes of both
Students are expected to present their
findings in the following ways:
- Present raw data in a single
Excel spreadsheet. Create the
appropriate plots (as shown in the Analysis
above) and display the equations and correlation values for each line.
- Give a definitive answer to the
first portion of both
and Question 2: Is there a correlation (determined
by how close R²
is to | 1 | ) between diabetes prevalence and obesity
between diabetes prevalence and the growth of the fast food industry?
- Use the appropriate equations to
predict the prevalence of
diabetes in 2010, 2020, and 2030. Students should present this data in
an Excel spreadsheet; by entering the equations into the table, the
students should not have to do any calculations by hand.
- Provide a written explanation as
to why the predictions of
diabetes differ when the independent variable changes. In their
analysis, students should include numerical evidence and should explain
discrepancies by both data and biology.
Some new questions one might consider:
- What other nationwide health epidemics (e.g., heart
colon cancer, etc.) are correlated to the fast food industry?
- Has the health food craze in the last decade benefited our
- Would the findings of this project be any different if the
McDonald's statistics represented American franchises only?
- Is the Americanization of European and other countries
world leading to an increase in diabetes in these places?
- Type 2 Diabetes has been shown to have a much higher
certain ethnic groups in the United States such as American Indian,
African American, and Hispanic. Is the increasing proportion of these
minorities in our population affecting the diabetes statistics
presented by the CDC?