Evidence map›Paper›PMID 31773498›Full record

ReviewCurrent environmental health reports2019

Built Environment Interventions to Increase Active Travel: a Critical Review and Discussion.

Rachel Aldred

Abstract readReview
In one paragraph

Review in Current environmental health reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Bikeability and the induced demand for cycling.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  5. Article
  6. Article
  7. In this Together: International Collaborations for Environmental and Human Health.The Journal of law, medicine & ethics : a journal of the American Society of Law, Medicine & Ethics · 2023
    Article
  8. Neighborhood Makes or Breaks Active Ageing? Findings from Cross-Sectional Path Analysis.International journal of environmental research and public health · 2022
    Article
  9. Provisional COVID-19 infrastructure induces large, rapid increases in cycling.Proceedings of the National Academy of Sciences of the United States of America · 2021
    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

1 author.

Rachel AldredUniversity of Westminster, Westminster, UK. r.aldred@westminster.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewTo review the literature on built environment interventions to increase active travel, focusing on work since 2000 and on methodological choices and challenges affecting studies. RECENT

findingsIncreasingly, there is evidence that built environment interventions can lead to more walking or cycling. Evidence is stronger for cycling than for walking interventions, and there is a relative lack of evidence around differential impacts of interventions. Some of the evidence remains methodologically weak, with much work in the 'grey' literature. While evidence in the area continues to grow, data gaps remain. Greater use of quasi-experimental techniques, improvements in routine monitoring of smaller schemes, and the use of new big data sources are promising. More qualitative research could help develop a more sophisticated understanding of behaviour change.

Indexed as

BicyclingBuilt EnvironmentEnvironment DesignHumansResearch DesignTransportationWalkingActive travelBuilt environmentCyclingInfrastructurePhysical activityWalking

Identifiers

PMID31773498
PMCPMC6920230

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.