the geography, math and science of disease roger palmer red river high school gisetc
TRANSCRIPT
The Geography, Math and Science
of Disease
Roger Palmer
Red River High School
GISetc
Student question: Are there really regions of the country that have much
higher rates of cancer than others, what other variables follow the same trend?
How would students answer this question?
What data is available?,
What areas do these data cover?
How can we compare data that cover different extents?
How will we know when two factors have similar trends?
What data is available?
How do you get it?
Can you use a type available then convert it?
What cancer type is most interesting?
Many sites have GIS data if you look for it
After downloading the separate cancer type files, they were appended together
along with their locational information. They were then joined with the county
shape files using the FIPS code like we did last class with the historic population
data. The abbreviations mean, all cancer deaths from 1950 to 1970 for white
females or all prostate cancer deaths from 1970 - 1994.
Total female cancer fatalities ‘70-94
A look at the all Female Cancer deaths from ‘70-’94
using natural breaks; breaks are placed at places
where the data set has fewer values. The histogram of
the data is given above..
Quantile; breaks are
placed so that the map
is colored equally. Notice
the breaks are not spaced
evenly.
Students proposed several reasons for the patterns in the quantile graph.
It was time to find data to back these hypothesis up. The leading thought
was that the bread basket area of the US exposed people to agri-chemicals.
While we were able to find a great report of agri-chemicals sold by county
in 1994, we didn’t understand the impact various chemicals had on human
health. Fertilizer amounts were finally chosen even though these have
minimum health impacts it was reasoned that farms fertilizing intensively
must also be using other chemicals that are used to kill bugs or weeds
(herbicides and insecticides).
A second set of information was sought to seehow closely the two data sets were correlated
While many county ag sale statistics were available thefirst round choices were to compare to fertilizer use
Cancer Rates: are shown here after
determining the rate of mortality instead
of raw numbers using quantile classes
Fertilizer Sales: while
fertilizer is not cancerous,
other imputs used in
intensive farming can be..
In the Midwest these rates appear
highly correlated! When comparing
the values in just the central part of the
U.S. The correlation coefficient calculate
out to r = 0.84
How do we show that 2 trends change in the same way
I.e. one increases as the other increases
In the simplest cases there is a general trend for the data to follow a line when plotted against each other.
Income
Age
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The model line helps predict normal trends.
How close your data lies to the line is called the correlationcoefficient. The closer that the correlation is to 1.00 the datafit better on the line. A correlation of -1.00 is an inverse relationship
So what other data might be available to compare as possible
sources of cancer causing substances in our environment?
Air quality toxic releases,
Water releases,
Natural release of Radon from soil,
….
We were able to find some great data of corporate toxic gas releases as self
reported to the EPA as part of certain allowed or fined agreements with
these companies.
Toxic release inventories are easily accessible for areas
Area searches narrowed the data down to state levels
Toxic releases are lists of quantities of known irritants released from fixed sites under a permitted process.
Since there are many such sites, narrowing down data to a state helps focus students interest
Copy the whole
page but paste it
into excel to clean
up the formatting
before creating a
point theme..
Data is listed by standard longitude and latitude and onceEntered into ArcGIS can be summarized by county
r = 0.12
In Texas, most monitored releases of toxic airborne substances
occur in cities. These substances when properly diluted in air are
claimed to be effectively rendered harmless. In this state, cancer
mortalities do not raise near areas that have high air polutant releases.
Does this mean that these releases are completely harmless?
No, what it does mean is that when considering all the toxic releases
combined that can possibly be released in Texas, that cancer rates do not
fluctuate in the same way these releases do.
Possible other alternative explainations students proposed were that
rates increase downwind, That certain releases are worse than others
so we should separate out the different kinds gasses and do the same
correlation studies.….
The important thing is that students can look at actual data to test their
hypothesis about what influences our health when it comes to cancer.
Like all good science this is the type of data that is necessary to make the first
steps toward changing our practices so that we may all live healthier lives!
Web Sites Used:
*www3.cancer.gov/cancer/
Cancer rates by counties since 1950
*http://water.usgs.gov/pubs/wri944176/
Fertilizer use, Herbicide use, Ag Data
*Www.rtk.net
Right to know data of toxic release data
Thank you for your attention, questions,
and discussion!
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