Correlations between Educational Struggle, Toxic Sites by School District and Demographic Variables, with Geographical Information System Projections

Junu Shrestha, Raihan K. Khan, Shane McClintock, John DeGroote and Catherine L. Zeman ()
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Junu Shrestha: School of Integrated Sciences, Sustainability, and Public Health, University of Illinois, Springfield, IL 62703, USA
Raihan K. Khan: Department of Health Sciences, College of Health and Behavioral Studies, James Madison University, Harrisonburg, VA 22801, USA
Shane McClintock: Clinton County Environmental Health Department, Clinton County, DeWitt, IA 52742, USA
John DeGroote: Department of Geography, College of Social & Behavioral Sciences, University of Northern Iowa, Cedar Falls, IA 50614, USA
Catherine L. Zeman: Department of Health Sciences, College of Health and Behavioral Studies, James Madison University, Harrisonburg, VA 22801, USA

IJERPH, 2023, vol. 20, issue 24, 1-16

Abstract: This correlational study associated data on children enrolled in individualized educational plans in their K-12 schools (IEP) and an algorithm-calculated score of neurotoxins at contaminated sites located in each school district. The study also mapped and projected the correlations using Geographical Information System (GIS) technology. These data were populated in ArcMap 10.5 (a GIS software) for generating maps and data to conduct geospatial analysis. A total of 1 Superfund site and 39 CERCLA sites were identified as contaminated sites for this analysis. The majority of contaminants were heavy metals such as lead, arsenic, mercury, and cadmium. The mean toxic score of all contaminated sites combined was 13.4 (SD 14.4). Correlational analysis between the IEP numbers from each school district and toxic scores from the contaminated school district sites exhibited a positive relationship (F = 23.7, p < 0.0001). Correlations were also seen among higher toxics scores, IEP numbers, and children under the age of 10 ( p < 0.00052) as well as higher proportions of black students in areas with high toxics scores ( p = 0.0032). Black students were also far more likely to be enrolled in an IEP ( p < 0.0001). Household income and poverty percentage in contaminated areas were also correlated ( p = 0.0002). Individuals without college degrees were overrepresented in high toxic score school districts ( p < 0.0001). The important low socio-economic status indicator of free and reduced lunch programs also correlated with increasing toxic scores ( p = 0.0012) and IEP numbers ( p = 0.0416). This study emphasizes the need to account for multiple exposures to wholistically appreciate environmental factors contributing to negative health outcomes.

Keywords: toxic score; individualized education plan; geographic information systems; correlation; environmental factors; multiple exposure (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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