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Ridesharing and Alcohol-Related Assaults in NYC: A Spatial Ecological Case-Crossover Study

Supporting Files
File Language:
English


Details

  • Alternative Title:
    Drug Alcohol Depend
  • Personal Author:
  • Description:
    Objective:

    Ridesharing has changed urban transportation and the distribution of some health outcomes, including alcohol consumption. Studies relating ridesharing to crime and violence at low space-time resolution (e.g., county-months) find mixed results. The aim of this study was to examine whether ridesharing was associated with increased incidence of alcohol-related assaults within highly resolved space-time units.

    Methods:

    This spatial ecological case-crossover study used rideshare and taxi trip data from the New York City (NYC) Taxi and Limousine Commission for 2017-2018 and assault data from the NYC Police Department, aggregated within taxi zone-hours. Conditional logistic regression models estimated the odds of observing an assault for case taxi zone-hours in which an assault occurred compared to two control units of the same taxi zone-hour one week before (−168 hours) and one week after (+168 hours) relative to the number of rideshare trips. Separate analyses assessed assaults occurring at bars and restaurants.

    Results:

    From 2017 to 2018, there were 47,124 nighttime assaults in the 262 taxi zones. There were 2,482 taxi zone-hours at a bar and 693 taxi zone-hours at a restaurant that contained at least one nighttime assault. Ridesharing was positively associated with nighttime assaults at bars (OR: 1.050; 95% CI: 1.002 to 1.100) but not at restaurants (OR: 1.049; 95% CI: 0.943 to 1.168).

    Conclusions:

    Additional ridesharing trips are associated with increased incidence of assaults at on-premise alcohol outlets in NYC at the precise hour and taxi zone of trip origins.

  • Keywords:
  • Source:
    Drug Alcohol Depend. 232:109321
  • Pubmed ID:
    35074695
  • Pubmed Central ID:
    PMC8885919
  • Document Type:
  • Funding:
  • Volume:
    232
  • Collection(s):
  • Main Document Checksum:
    urn:sha256:c13e84dd921177357fd549a259f31eefb1bdf49035d1757af414910eb80e39d1
  • Download URL:
  • File Type:
    Filetype[PDF - 386.41 KB ]
File Language:
English
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