Data analysis was performed with the Statistical Package for the Social Sciences, IBM – SPSS Statistics V20.0 [13]. Descriptive statistics (frequencies, percentage and cross-tabulation) were used to describe the main features of the data and to study the bivariate relationships between the variables. Bivariate Chi-square tests were used to identify the significance (α=0.05) of the associations between each of the covariates of interest and the dichotomous dependent variable (contamination or no contamination). Logistic regression (for binary outcome) was used to model the association between living area (residence) and the dichotomous dependent variable (contamination or no contamination). The associations between categories of the predictor variables and the outcome are expressed as odds ratios with 95% confidence intervals (CI).