Environmental Pollution & Public Health

Alanna Lecher, Lynn University

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Environmental health is a field of study within public health that is concerned with human-environment interactions, and specifically, how the environment influences public well-being. In this module, students will explore how environmental pollution impacts public health through comparing cancer rates of areas with known environmental pollutants to the national average through a t-test. Students can further their knowledge by comparing the concentrations of atmospheric pollutants in areas with known sources to control sites without such sources. Project EDDIE modules are designed with an A-B-C structure to make them flexible and adaptable to a range of student levels and course structures.

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Learning Goals

By the end of this module students will be able to:

  • Calculate a cancer mortality rate
  • Describe how environmental pollutants influence cancer mortality rates
  • Create a bar graph in Excel
  • Execute a comparison of means t-test in Excel
  • Determine if the means of two sets of data are statistically significant

Context for Use

This module was taught in a sophomore-level science and society course for non-science majors. The course had approximately 25 students in which all students were provided a tablet to complete the assignment on, and students worked in pairs or small groups. It occurred in a single 2.5 hour lecture period.  Students did not necessarily have an experience previously in environmental health or statistics.  Students had previous experience using Microsoft Excel and knew how to complete basic Excel functions like copying and pasting, creating graphs, etc.

Strengths of the Module

This module uses data to show why taking care of the environment is important in a way that even the most anthropocentric student can identify with (not wanting to have their health harmed by pollutants).  It also introduces hypothesis testing and p-values at a very low-level, so that students who haven't taken a statistics class can complete some basic interpretation.  As the term "significant" is often misused in everyday life when referring to data, this arms the student with knowledge of what that term actually entails in science.

Why This Matters

A healthy community begins with a healthy environment.  Other health measures such as diet, exercise, and vaccination can all be undermined by polluted air and water.  In conjunction with a strong public health system, an emphasis on environmental quality can reduce disease and increase well-being.  Since the beginning of the industrial revolution, certain industries and practices have polluted the environment with carcinogens, endocrine disruptors, airway and skin irritants, and other toxicants.  The presence of these pollutants has serious implications for human health, a conclusion supported by analysis of large population data sets, as will be demonstrated in this module.

How Instructors Have Used This Module

Using Project EDDIE modules in DSL 200: Scientific Literacy
Alanna Lecher, Lynn University
This module will convince even the most anthropocentric student why they should care about environmental pollution. It's also a great way to shows students a practical application of hypothesis testing.

Description and Teaching Materials

Quick overview of the activities in this module

  • Activity A: Students calculate the average cancer mortality rate for each state in the US and the national average. Students plot these rates as a bar plot.
  • Activity B: Students learn about Louisiana's Cancer Alley and use a comparison of means t-test to determine if there is a significant difference between the cancer mortality rate of Louisiana and the national average.
  • Activity C: Students learn about mountain top removal coal mining and PM 2.5 pollution from such coal mining and use a comparison of means t-test to determine if there is a significant difference between the PM 2.5 atmospheric concentration near mountain top removal sites and control sites, both in the Appalachian Mountains.  Then, students revisit the cancer mortality data by comparing cancer mortality rates of a state with mountain top removal coal mines and an Appalachian state with no mountain top removal coal mines.

Workflow of this module:

  1. Assign any pre-class readings (pick from the readings section below)
  2. Give students their handout when they arrive to class
  3. Instructor gives brief PowerPoint presentation with background material. Discussion of the readings can be integrated into this presentation or done before.
  4. Students can then work through the module activities.

Teaching Materials

  • Student Handout (Microsoft Word 2007 (.docx) 437kB Aug12 22) 
  • Data (Excel 2007 (.xlsx) 39kB Jul5 22)
  • PowerPoint (PowerPoint 2007 (.pptx) 384kB Aug12 22) 

Teaching Notes and Tips

The screen shots of the module were taken in the iPad version of Excel, which is slightly different from Mac/PC/online versions of Excel. It may look slightly different than the version of Excel students are using. It can easily be adapted to Google Sheets, which has an identical =t.test() formula.

This is a very low level explanation and application of a t-test, and was meant for a class where it was assumed students had no previous experience with hypothesis testing.  If this module is meant to be used with a class where hypothesis testing is more commonly used, consider adding more information about the t-test, like null and alternative hypothesis, etc.

Extension activities are suggested in the Instructor Notes document, provided above.


A good place to check for formative assessment is after part B. Check what p-values students calculated and ask them what the p-value tells you.

In the course this module was piloted in, for the summative assessment, students turned in a copy of their worksheet (which was checked for completeness) and then took an open note quiz on the module. The quiz was launched through the learning management system and included an assortment of multiple choice and true or false questions that were graded automatically by the learning management system and a few open response questions that were graded by the instructor.

References and Resources

Below is a list of suggested pre or post reads for the module

Hendryx, M., Wolfe, L., Luo, J., & Webb, B. (2012). Self-reported cancer rates in two rural areas of West Virginia with and without mountaintop coal mining. Journal of community health, 37(2), 320-327.

  • This reference is similar to the analysis the students do of the cancer rates in mountain top removal and non-mountain top removal areas.

Aneja, V. P., Pillai, P. R., Isherwood, A., Morgan, P., & Aneja, S. P. (2017). Particulate matter pollution in the coal-producing regions of the Appalachian Mountains: Integrated ground-based measurements and satellite analysis. Journal of the Air & Waste Management Association, 67(4), 421-430.

Nichols, C. E., Shepherd, D. L., Knuckles, T. L., Thapa, D., Stricker, J. C., Stapleton, P. A., ... & Hollander, J. M. (2015). Cardiac and mitochondrial dysfunction following acute pulmonary exposure to mountaintop removal mining particulate matter. American Journal of Physiology-Heart and Circulatory Physiology, 309(12), H2017-H2030.

  • These two references are about the health effects of PM pollution in mountain top removal areas.

Castellón, I. G. (2021). Cancer Alley and the Fight Against Environmental Racism. Vill. Envtl. LJ, 32, 15.

  • This reference gives an overview of cancer ally, and introduces environmental justice/racism.

EPA Website on Particulate Matter Basics

Primer on T-testing

Excel and Google Sheets documentation on t.test()