Date of Award
Master of Public Health (MPH)
School of Public Health
Current literature suggests PFAS carbon chain length is a predicative variable of toxicity. If so, statistical modeling may be used to predict toxicity, thus improving efficiency of PFAS regulations. Data containing clinical chemistry health outcomes of rats exposed to various PFAS compound obtained from the National Toxicology Program were analyzed using one-way ANOVAs, Tukey’s HSD post hoc tests, and simple linear regressions. A dataset was predicted using modeling from this data. Analysis indicated that 13 of 15 health outcomes showed significant differences in mean values. Results of simple linear regressions were statistically significant in five of 15 health outcomes. After predicative modeling generated a theoretical dataset, unpaired t-tests comparing results of an actual dataset, indicating no significant differences among the mean values of two of five health outcomes. Therefore, predictive statistical modeling may be used to predict health outcomes.
Bellia, Giselle Rita Maria, "Regulation Of Pfas Chemicals Using Predictive Statistical Modeling" (2022). Public Health Theses. 2132.