More bike and pedestrian accidents near bars?

Researchers in New York City have found that the presence of alcohol-serving establishments can have a significant impact on bicycle and pedestrian accidents.

Regular blog readers may recall my interest in biking (recall); until recently I would frequently commute by bike. So I found the new study in Injury Epidemiology by researchers at New York City research hospitals tracking bicycle (and pedestrian) accidents by proximity to bars personally highly interesting. Especially because the route I used to take (I’ve recently taken to doing laps in Prospect Park instead) went right by a few watering holes on Vanderbilt Avenue in Brooklyn.

The presence of alcohol-serving establishments had critical importance on the probability of pedestrian and cyclist injury, even more so than factors like traffic density.

So I was naturally very interested in the article, “Spatial analysis of the association of alcohol outlets and alcohol-related pedestrian/bicyclist injuries in New York City” by Charles DiMaggio, Stephen Mooney, Spiros Frangos, and Stephen Wall. (Luckily for me, I would usually be biking at times—early morning and early afternoon—when the bars weren’t busy…)

In their statistical and probabilistic analysis, they found that the presence of alcohol-serving establishments had critical importance on the probability of pedestrian and cyclist injury, even more so than factors like traffic density. They write:

We found place, in particular the presence of alcohol outlets in a census tract, to be a critically important determinant of alcohol-related pedestrian and bicyclist injury risk beyond other perhaps, more immediately apparent factors such as traffic density. There were areas in each borough of New York City where the risk of alcohol-related pedestrian injury was higher than the city as whole throughout the 10-year study period. The use of exceedance probabilities refines this characterization of risk by placing explicit probabilities on the observed risk estimates to identify those areas for which the increased risk was highly unlikely to be due to chance.

You can read the entire article here.

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