Evidence map›Paper›PMID 33502328›Full record

ArticleJournal of medical Internet research2021

Ride-Hailing Services and Alcohol Consumption: Longitudinal Analysis.

Gordon Burtch, Brad N Greenwood, Jeffrey S McCullough

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Gordon Burtch *Carlson School, University of Minnesota, Minneapolis, MN, United States.ORCID 0000-0001-9798-1113
Brad N Greenwood *Department of Information Systems and Operations Management, George Mason University, Fairfax, VA, United States.ORCID 0000-0002-0772-7814
Jeffrey S McCullough *Department of Health Management and Policy, University of Michigan, Ann Arbor, MI, United States.ORCID 0000-0001-6155-980X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlcohol 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.

objectiveThe 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.

methodsWe 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.

resultsRide-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.

conclusionsRide-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.

Indexed as

Alcohol DrinkingAutomobilesFemaleHumansLongitudinal StudiesMaleTransportationalcohol consumptionbinge drinkingdifference in differencesdrunk drivingride-hailingroad traffic safetyUber

Identifiers

PMID33502328
PMCPMC7875688

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.