Evidence map›Paper›PMID 23083429›Full record

ArticleBMC public health2012

Comparing the impact of socio-demographic factors associated with traffic injury among older road users and the general population in Japan.

Takashi Nagata, Ayako Takamori, Hans-Yngve Berg, Marie Hasselberg

Abstract readComparative Study
In one paragraph

Article in BMC public health, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

4 authors.

Takashi NagataKarolinska Institute, Department of Public Health Sciences, Division of Global Health, Stockholm, Sweden. nagata.takashi@gmail.com
Ayako Takamori
Hans-Yngve Berg
Marie Hasselberg

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe increasing number of older road users represents a public health issue because older individuals are more susceptible to traffic injury and mortality than the general population. This study investigated the association between socio-demographic factors and traffic injury and traffic mortality for the general population and among older road users in Japan.

methodsAn ecological study was conducted using national data in Japan. Multivariate regression methods were applied to investigate the association of traffic injury and traffic mortality for the general population and among older road users with significant demographic, economic, road traffic, and medical/cultural factors.

resultsIncome per capita, total road length, and alcohol consumption per person were significantly associated with traffic injury and traffic mortality both for the general population and among older road users in Japan. Income per capita and alcohol consumption per person were negatively associated with traffic mortality for both groups. Meanwhile, for both groups, income per capita was positively associated with traffic injury, while total road length and alcohol consumption per person were negatively associated with traffic injury.

conclusionsThe effects of socio-demographic factors on traffic injury and traffic mortality in Japan were similar for both the general population and older road users. The study results suggest that injury preventive measures designed for the general population will be beneficial also for older road users in Japan.

Indexed as

Accidents, TrafficAgedAlcohol DrinkingDatabases, FactualEnvironment DesignHumansJapanRisk FactorsSocioeconomic FactorsWounds and Injuries

Identifiers

PMID23083429
PMCPMC3508935

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.