Impacts of confounding roadway characteristics on estimates of associations between alcohol outlet densities and alcohol-related motor vehicle crashes

Micro-temporal analyses of crime related to alcohol outlets: A comparison of outcomes over weekday, weekend, daytime and nighttime hours

INTRODUCTION

Causal relationships between alcohol outlets and crime are inferred from their statistical associations across neighbourhoods. However, many unobserved covariates may confound these effects. Recognising that outlet sales vary by time of day and day of week, we assess whether areas with more bars/pubs, restaurants or off-premise outlets have more crime during days and times when alcohol sales are greatest.

METHODS

Annual administrative crime counts, sociodemographic data and other area characteristics of 336 Census block groups in Oakland, California, USA, were related to outlet densities from 2000 to 2015. Bayesian space-time Poisson models were used to measure associations between outlet densities and crime during: (i) weekday daytime; (ii) weekday nighttime; (iii) weekend daytime; and (iv) weekend nighttime periods (four seemingly unrelated equations). Comparisons of parameter estimates across equations provided an assessment of outlet effects on crime across days and times within the same analysis units using the same constellation of confounding covariates.

RESULTS

Assault and driving under the influence crime incidents during weekend evening hours were more frequent in Census block group areas with greater numbers of bar/pubs. Burglaries were consistently greater in areas with greater densities of restaurants.

DISCUSSION AND CONCLUSIONS

The spatiotemporal signature relating densities of bars/pubs over weekend evening hours to assault and driving under the influence incidents suggests that these outlets are a critical source of these crimes across neighbourhoods. Prevention programs and policies that focus upon specific drinking establishments, days and times may be most effective in reducing assault and impaired driving incidents in neighbourhoods.

Rideshare Trips and Alcohol-Involved Motor Vehicle Crashes in Chicago

OBJECTIVE

Rideshare companies such as Uber and Lyft have substantially changed transportation markets in the United States and globally. The aim of this study was to examine whether ridesharing is associated with reductions in alcohol-involved crashes.

METHOD

This case-series study used highly spatially and temporally resolved trip-level rideshare data and motor vehicle crash data from the Chicago Data Portal from November 2018 to December 2019. The units of analysis were motor vehicle crashes in Chicago. Events of interest were 962 crashes that police indicated were alcohol involved. The comparison group was 962 non-alcohol-involved crashes that occurred in the same census tract, matched 1:1. The exposure of interest was the density per square mile of rideshare trips that were in progress at the time of the crash, calculated using a kernel density function around the estimated route paths of active trips. A conditional logistic regression compared alcohol involvement to rideshare trip density while adjusting for matching and relevant time-varying covariates (taxi trips, precipitation, temperature, holidays).

RESULTS

Mean rideshare trip density was 69.0 per square mile (SD = 129.7) at the time and location of alcohol-involved crashes and 105.7 per square mile (SD = 192.6) at the time and location of non-alcohol-involved crashes. After controlling for covariates, the conditional logistic regression model identified that a standard deviation increase in rideshare trips per square mile at the crash location was associated with 23% decreased odds that the crash location was alcohol involved (odds ratio = 0.771; 95% confidence interval [0.594, 0.878]).

CONCLUSIONS

Ridesharing may replace motor vehicle trips by alcohol-impaired drivers.

Proximity to the Southern Border and Sociodemographic Correlates of Drinking and Driving Arrests in California

BACKGROUND

About 30% of all motor vehicle fatalities in the United States are associated with alcohol-impaired motor vehicle crashes. Arrests for drinking and driving (Driving under the influence [DUI]) are 1 of the most important deterrence actions to minimize DUI. This paper examines trends and population-level correlates of drinking driving arrests (DUI) from 2005 to 2017 in California.

METHODS

Arrest data come from the Monthly Arrest and Citation Register compiled by the California Department of Justice. Sociodemographic and community characteristic data from the U.S. Census, alcohol outlet density, and distance to the U.S.-Mexico border from Law Enforcement Reporting Areas (LERA) centroids were aggregated at the level of 499 LERA contributing to the report. Reported arrest rates were related to area sociodemographic characteristics using hierarchical Bayesian Poisson space-time models.

RESULTS

Both among men and women rates showed an upward trend until 2008, decreasing after that year. DUI arrest rates were greater among Hispanics than Whites for the 2 younger age groups, 18 to 29 (p < 0.001) and 30 to 39 years (p < 0.001). DUI arrest rates in LERA areas are positively related to proximity to the California/Mexico border; a higher percent of bar/pub outlets; a higher percent of Hispanic population; a higher percent of population 18 to 29, 30 to 39, and 40 to 49 years of age; a higher percent of US-born population; a higher percent of population with annual income of $100,000 or more; a higher percent of population 150% below the federal poverty line; and a higher level of law-enforcement activities.

CONCLUSIONS

Results of this analysis of spatial correlates of DUI arrests overlap well with the literature on individual-level data and arrest rates. The decrease in arrest rates as distance to the California/Mexico border increases is potentially associated with the greater availability of alcohol in the border area.