A Law Enforcement Database Was Used to Collect the Number

A law enforcement database was used to collect the number of driving under the influence (DUI) and alcohol-related incidents as well as the number of motor vehicle crashes for each county in the region. Counties were ranked according to alcohol experiences (none/sparse, low, moderate, high). A Poisson regression was used to investigate the relationship between the number of motor vehicle crashes and the alcohol ranking. The results of a Poisson regression indicated that counties in the high alcohol ranking had a 40% increase in the rate of motor vehicle crashes. However, when the analysis was repeated and additional variables (rural/urban, percentage of population between 16 and 25) were included in the model, the difference in the rate of crashes was no longer significant. What could explain this scenario?