This study models nitrate occurrence in private wells in Iowa for the purpose of exposure assessment. Like other epidemiology studies it heads down the limited pathway of an ecologic study design. Modeled nitrate occurrence in wells does not represent actual exposure to N-nitroso compounds or even to nitrate. Application of this work in a cancer cohort assessment can at best only generate hypotheses. As an aside, an r-square = 0.77 still generates a very large confidence interval at any level of significance.
Wheeler DC, Nolan BT, Flory AR, DellaValle CT, Ward MH. Modeling groundwater nitrate concentrations in private wells in Iowa. The Science of the Total Environment. 2015 Jul 29;536:481-488. doi: 10.1016/j.scitotenv.2015.07.080.
Contamination of drinking water by nitrate is a growing problem in many agricultural areas of the country. Ingested nitrate can lead to the endogenous formation of N-nitroso compounds, potent carcinogens. We developed a predictive model for nitrate concentrations in private wells in Iowa. Using 34,084 measurements of nitrate in private wells, we trained and tested random forest models to predict log nitrate levels by systematically assessing the predictive performance of 179 variables in 36 thematic groups (well depth, distance to sinkholes, location, land use, soil characteristics, nitrogen inputs, meteorology, and other factors). The final model contained 66 variables in 17 groups. Some of the most important variables were well depth, slope length within 1km of the well, year of sample, and distance to nearest animal feeding operation. The correlation between observed and estimated nitrate concentrations was excellent in the training set (r-square=0.77) and was acceptable in the testing set (r-square=0.38). The random forest model had substantially better predictive performance than a traditional linear regression model or a regression tree. Our model will be used to investigate the association between nitrate levels in drinking water and cancer risk in the Iowa participants of the Agricultural Health Study cohort.