The Geography, Math and Science of Disease Roger Palmer Red River High School GISetc.

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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 see how closely the two data sets were correlated

While many county ag sale statistics were available the first 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 * * * * * * * * * * ** * * * * The model line helps predict normal trends.

How close your data lies to the line is called the correlation coefficient. The closer that the correlation is to 1.00 the data fit 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 once Entered 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! For ideas, trouble shooting, training events contact us at: Roger.gisetc@gmail.com

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