Using Cumulative Distribution Functions to Analyze Environmental Exposure in School Children
Author Information
Author(s): Paul A. Zandbergen, Jayajit Chakraborty
Primary Institution: Department of Geography, University of South Florida
Hypothesis
Are school-aged children more likely to be exposed to environmental pollution and related health risks at home or at school?
Conclusion
The study found that using cumulative distribution functions (CDFs) provides more reliable results in assessing environmental exposure than traditional discrete buffer distances.
Supporting Evidence
- The use of CDFs provided a more meaningful representation of exposure potential than discrete buffer distances.
- Different buffer distances yielded different results, indicating the sensitivity of exposure assessments to chosen methods.
- The study demonstrated that individual geocoding can reduce bias introduced by aggregated demographic data.
Takeaway
This study shows that looking at how far kids live from pollution sources helps us understand where they might be more at risk, whether at home or school.
Methodology
The study used cumulative distribution functions (CDFs) and individual geocoding to analyze the exposure of school children to environmental pollution from various sources.
Potential Biases
There are known biases in street geocoding, such as variable match rates and positional error.
Limitations
The study's findings are limited by the availability of individual addresses for geocoding and potential biases in street address geocoding.
Participant Demographics
The study focused on school-aged children in Orange County, Florida.
Statistical Information
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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