Comparison of analytical techniques to explain variability in stored drinking water quality and microbial hand contamination of female caregivers in Tanzania.

Abstract

Exposure to fecal contamination continues to be a major public health concern for low-income households in sub-Saharan Africa. Drinking water and hands are known transmission routes for pathogens in household environments. In an effort to identify explanatory variables of water and hand contamination, a variety of analytical approaches have been employed that model variation in E. coli contamination as a function of behaviors and household characteristics. Using data collected from 1217 households in Bagamoyo, Tanzania, this investigation compares the explanatory variables identified in the three different modeling methods to explain hand and water contamination: ordinary least squares regression, logistic regression, and classification tree. Although the modeling approaches varied, there were some similarities in the results, with certain explanatory variables being consistently identified as being related to hand and water contamination (e.g., water source type for the water models and activity prior to sampling for the hand models). At the same time, there were also marked differences across the models. In sum, these results suggest there are benefits to using multiple analysis methods to assess relationships in complex systems. The models were also characterized by low explanatory power, suggesting that variation in hand and water contamination is difficult to capture when analyzing one-time water and hand rinse samples. For improved model performance, future studies could explore modeling of repeat measures of water quality and hand contamination.