Evidence map›Paper›PMID 29564357›Full record

ArticleSafety (Basel, Switzerland)2016

The Effect of Sharrows, Painted Bicycle Lanes and Physically Protected Paths on the Severity of Bicycle Injuries Caused by Motor Vehicles.

Stephen P Wall, David C Lee, Spiros G Frangos, Monica Sethi, Jessica H Heyer, Patricia Ayoung-Chee, Charles J DiMaggio

Abstract read
In one paragraph

Article in Safety (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Bicycle Facilities That Address Safety, Crime, and Economic Development: Perceptions from Morelia, Mexico.International journal of environmental research and public health · 2017
    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

7 authors.

Stephen P WallRonald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York, NY 10016, USA.
David C LeeRonald O. Perelman Department of Emergency Medicine, New York University School of Medicine, New York, NY 10016, USA.
Spiros G FrangosDivision of Trauma and Surgical Critical Care, Department of Surgery, Bellevue Hospital Center, New York University School of Medicine, New York, NY 10016, USA.
Monica SethiDivision of Trauma and Surgical Critical Care, Department of Surgery, Bellevue Hospital Center, New York University School of Medicine, New York, NY 10016, USA.
Jessica H HeyerDivision of Trauma and Surgical Critical Care, Department of Surgery, Bellevue Hospital Center, New York University School of Medicine, New York, NY 10016, USA.
Patricia Ayoung-CheeDivision of Trauma and Surgical Critical Care, Department of Surgery, Bellevue Hospital Center, New York University School of Medicine, New York, NY 10016, USA.
Charles J DiMaggioDepartment of Population Health, New York University School of Medicine, New York, NY 10016, USA.

Funding

Data Integration and Advanced Statistical Modeling to Describe and Control Pediatric Pedestrian Injuries in The United StatesR01HD087460 · NICHD · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI DIMAGGIO, CHARLES · 2016 to 2018
$984k
NICHD NIH HHS R01 HD087460
6 · The paper itself

Abstract

We conducted individual and ecologic analyses of prospectively collected data from 839 injured bicyclists who collided with motorized vehicles and presented to Bellevue Hospital, an urban Level-1 trauma center in New York City, from December 2008 to August 2014. Variables included demographics, scene information, rider behaviors, bicycle route availability, and whether the collision occurred before the road segment was converted to a bicycle route. We used negative binomial modeling to assess the risk of injury occurrence following bicycle path or lane implementation. We dichotomized U.S. National Trauma Data Bank Injury Severity Scores (ISS) into none/mild (0-8) versus moderate, severe, or critical (>8) and used adjusted multivariable logistic regression to model the association of ISS with collision proximity to sharrows (i.e., bicycle lanes designated for sharing with cars), painted bicycle lanes, or physically protected paths. Negative binomial modeling of monthly counts, while adjusting for pedestrian activity, revealed that physically protected paths were associated with 23% fewer injuries. Painted bicycle lanes reduced injury risk by nearly 90% (IDR 0.09, 95% CI 0.02-0.33). Holding all else equal, compared to no bicycle route, a bicycle injury nearby sharrows was nearly twice as likely to be moderate, severe, or critical (adjusted odds ratio 1.94; 95% confidence interval (CI) 0.91-4.15). Painted bicycle lanes and physically protected paths were 1.52 (95% CI 0.85-2.71) and 1.66 (95% CI 0.85-3.22) times as likely to be associated with more than mild injury respectively.

Indexed as

bicycle lanesbicyclistsgeographic analysisinjury severitytrauma

Identifiers

PMID29564357
PMCPMC5858726

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.