Next, the study stratified the population sample based on region, education, household income and insurance status, and again, only mammogram utilization was statistically significant between rural and urban residents. Finally, a logistical model was conducted for the statistically significant results from the first chi-square test and other explanatory variables that could possibly impact the relationship between utilization of mammograms between rural and urban residents. These results were presented as odds ratios with 95% confidence intervals. After adjusting for confounding factors, the relationship between rural and urban did not remain significant. This suggests that these confounding variables have an association with utilization of preventative medical services, however this relationship is not explored further (Zhang et al.,
Next, the study stratified the population sample based on region, education, household income and insurance status, and again, only mammogram utilization was statistically significant between rural and urban residents. Finally, a logistical model was conducted for the statistically significant results from the first chi-square test and other explanatory variables that could possibly impact the relationship between utilization of mammograms between rural and urban residents. These results were presented as odds ratios with 95% confidence intervals. After adjusting for confounding factors, the relationship between rural and urban did not remain significant. This suggests that these confounding variables have an association with utilization of preventative medical services, however this relationship is not explored further (Zhang et al.,