Evidence map›Paper›PMID 11003193›Full record

ArticleInjury prevention : journal of the International Society for Child and Adolescent Injury Prevention2000

Population preventable fraction of bicycle related head injuries.

B Kopjar

Open access · greenAbstract read
In one paragraph

Article in Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention, 2000. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.7field-weighted citation impact, top 14% of its field
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

2 citing papers in PubMed, 16 citations in OpenAlex.

  1. Explaining regional disparities in traffic mortality by decomposing conditional probabilities.Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention · 2011
    Article
  2. Audit of an intervention to decrease cycle related head injuries in primary school children.Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention · 2006
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

B KopjarDepartment of Population Health Sciences, National Institute of Public Health, Oslo, Norway. branko.kopjar@samfunnsmed.uio.no

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study analyzes the population attributable fraction (PAF) of bicycle head injuries due to non-helmet use.

methodsThe concept of the PAF and Levin's formula for its calculation were used to develop mathematical models for estimation of: (i) attributable fraction of bicycle related head injuries in the population due to non-helmet use, (ii) expected proportion of helmeted cases among all head injuries, and (iii) estimate of the helmet use rate in the population based on patient case information. The PAF was calculated for a sample of injuries from Stavanger, Norway.

resultsLevin's formula was used to calculate the PAF. Two additional mathematical models were developed for calculating the expected proportion of helmeted cases and the estimation of the helmet use rate in the population. The P calculation examples for all models were is shown. It was estimated that 133 out of 210 injuries could have been avoided in Stavanger between 1990 and 1996 if all children aged 0-14 had used helmets.

conclusionsIf applied correctly, the PAF is a valid and useful indicator for the population effects of bicycle helmets. The models developed in this study may help to better interpret and predict the population effects of helmet promotion interventions.

Indexed as

Population SurveillanceAdolescentAthletic InjuriesBicyclingChildChild, PreschoolChild WelfareHead Protective DevicesHumansIncidenceInfantModels, StatisticalNorwayOdds RatioProspective StudiesRegistries

Identifiers

PMID11003193
PMCPMC1730631
OpenAlexW2083177910

What OpenQuestion holds

Textmetadata
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.