Dataset Information

Ride-Hailing Services and Alcohol Consumption: Longitudinal Analysis.

ABSTRACT:

Background

Alcohol consumption is associated with a wide range of adverse health consequences and a leading cause of preventable deaths. Ride-hailing services such as Uber have been found to prevent alcohol-related motor vehicle fatalities. These services may, however, facilitate alcohol consumption generally and binge drinking in particular.

Objective

The goal of the research is to measure the impact of ride-hailing services on the extent and intensity of alcohol consumption. We allow these associations to depend on population density as the use of ride-hailing services varies across markets.

Methods

We exploit the phased rollout of the ride-hailing platform Uber using a difference-in-differences approach. We use this variation to measure changes in alcohol consumption among a local population following Uber's entry. Data are drawn from Uber press releases to capture platform entry and the Behavioral Risk Factor Surveillance Systems (BRFSS) Annual Survey to measure alcohol consumption in 113 metropolitan areas. Models are estimated using fixed-effects Poisson regression. Pre- and postentry trends are used to validate this approach.

Results

Ride-hailing has no association with the extent of alcohol consumption in high (0.61 [95% CI -0.05% to 1.28%]) or low (0.61 [95% CI -0.05% to 1.28%]) density markets, but is associated with increases in the binge drinking rate in high-density markets (0.71 [95% CI 0.13% to 1.29%]). This corresponds to a 4% increase in binge drinking within a Metropolitan Statistical Area.

Conclusions

Ride-hailing services are associated with an increase in binge drinking, which has been associated with a wide array of adverse health outcomes. Drunk driving rates have fallen for more than a decade, while binge drinking continues to climb. Both trends may be accelerated by ride-hailing services. This suggests that health information messaging should increase emphasis on the direct dangers of alcohol consumption and binge drinking.

SUBMITTER: Burtch G

PROVIDER: S-EPMC7875688 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Ride-Hailing Services and Alcohol Consumption: Longitudinal Analysis.

Burtch Gordon G Greenwood Brad N BN McCullough Jeffrey S JS

Journal of medical Internet research 20210127 1

<h4>Background</h4>Alcohol consumption is associated with a wide range of adverse health consequences and a leading cause of preventable deaths. Ride-hailing services such as Uber have been found to prevent alcohol-related motor vehicle fatalities. These services may, however, facilitate alcohol consumption generally and binge drinking in particular.<h4>Objective</h4>The goal of the research is to measure the impact of ride-hailing services on the extent and intensity of alcohol consumption. We ...[more]

PMID: 33502328

Similar Datasets

Project description:BackgroundOnline ride-hailing is a fast-developing new travel mode. However, tobacco control policies on its drivers remain underdeveloped. This study aims to reveal the status and determine the influencing factors of ride-hailing drivers' smoking behaviour to provide a basis for the formulation of tobacco control policies.MethodsWe derived our cross-sectional data from an online survey of full-time ride-hailing drivers in China. We used a survey questionnaire to collect variables, including sociodemographic and work-related characteristics, health status, health behaviour, health literacy and smoking status. Finally, we analysed the influencing factors of current smoking by conducting chi-square test and multivariate logistic regression.ResultsA total of 8990 ride-hailing drivers have participated in the survey, in which 5024 were current smokers, accounting to 55.9%. Nearly one-third of smokers smoked in their cars (32.2%). The logistic regression analysis results were as follows: male drivers (OR = 0.519, 95% CI [0.416, 0.647]), central regions (OR = 1.172, 95% CI [1.049, 1.309]) and eastern regions (OR = 1.330, 95% CI [1.194, 1.480]), working at both daytime and night (OR = 1.287, 95% CI [1.164, 1.424]) and non-fixed time (OR = 0.847, 95% CI [0.718, 0.999]), ages of 35-54 years (OR = 0.585, 95% CI [0.408, 0.829]), current drinker (OR = 1.663, 95% CI [1.526, 1.813]), irregular eating habits (OR = 1.370, 95% CI [1.233, 1.523]), the number of days in a week of engaging in at least 10 min of moderate or vigorous exercise ≥3 (OR = 0.752, 95% CI [0.646, 0.875]), taking the initiative to acquire health knowledge occasionally (OR = 0.882, 95% CI [0.783, 0.992]) or frequently (OR = 0.675, 95% CI [0.591, 0.770]) and underweight (OR = 1.249, 95% CI [1.001, 1.559]) and overweight (OR = 0.846, 95% CI [0.775, 0.924]) have association with the prevalence of current smoking amongst online ride-hailing drivers.ConclusionThe smoking rate of ride-hailing drivers was high. Sociodemographic and work-related characteristics and health-related factors affected their smoking behaviour. Psychological and behavioural interventions can promote smoking control management and encourage drivers to quit or limit smoking. Online car-hailing companies can also establish a complaint mechanism combined with personal credit.

Project description:ObjectiveNightclub patrons who consume alcohol and drugs in these venues would appear to be an important population to target with on-demand ride hailing app (RHA) services to reduce drunk/drugged driving (DUI). The present study is an exploratory examination of RHA use to avoid DUI behavior, as well as the perceived barriers and benefits of such RHA use, among young adult nightclub patrons in Miami who use drugs.MethodsCompleters of a 2011-2015 randomized controlled trial of brief interventions to reduce health risk behaviors among young adult nightclub patrons were recruited to participate in a single self-administered computer-assisted interview about health risks, driving behaviors, and RHA perceptions and use. Recruitment (N = 123) began in June 2016 and ended in July 2017. Bivariable logistic regression and ANOVA models examined group differences between: (a) those who had used an RHA to avoid DUI vs. not; and (b) those who used RHAs as their primary mode of transportation to nightclubs vs. not.ResultsAbout half were female (52.8%); median age was 29; 59.4% Hispanic, 31.7% Black, 8.1% white, 0.8% other race/ethnicity. Recent alcohol and marijuana use were almost universally endorsed, and more than half reported recent use/misuse of cocaine (72.4%), MDMA (63.4%), and prescription benzodiazepines (62.6%) and opioids (56.9%). More than 80% reported driving under the influence of alcohol and/or drugs in the past 12 months, and 17.1% experienced a DUI arrest in the prior two years. Almost two-thirds (65.9%) of participants had used an on-demand RHA to avoid DUI, but self-driving or riding in another's car were the most common (76.4%) primary modes of transportation to clubs. RHAs were the primary mode of travel to clubs for 21 (17.1%) respondents. Participants whose friends strongly disapproved of DUI were more than twice as likely to have used RHAs for this reason compared to those who had not done so. Those reporting RHA use to avoid DUI were less likely than others to have driven under the influence in the past 12 months and were somewhat more likely to endorse DUI-related risks. Those who used alternate modes of transportation were more likely than those who used RHAs as their primary mode of transportation to clubs to endorse the expense of RHAs and the lack of RHA drivers near their favorite clubs as barriers to RHA use to travel to nightclubs.ConclusionsThis novel study among a high-risk population points to the potential for on-demand RHAs to reduce DUI behaviors and arrests among young adult nightclub patrons who consume alcohol and/or drugs in the context of the club experience. Our findings point to key educational, peer support, and structural targets for intervention to increase the use of RHAs among this population, specifically, club-based incentives for increasing RHA availability and affordability. Research is needed to fully elucidate the findings of this exploratory study, including potential differences in intervention approaches depending on the location-specific public transportation options.

Dataset Information

Ride-Hailing Services and Alcohol Consumption: Longitudinal Analysis.

Background

Objective

Methods

Results

Conclusions

Publications

Ride-Hailing Services and Alcohol Consumption: Longitudinal Analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets