Literature DB >> 31389721

Worldwide prevalence of alcohol in fatally injured motorcyclists: A meta-analysis.

Fatemeh Sadat Asgarian1, Mahshid Namdari2,3, Hamid Soori1.   

Abstract

Objective: The aim of this study was to estimate the prevalence of alcohol in fatally injured motorcyclists and to determine the factors that are related to the prevalence worldwide.
Methods: A systematic review was conducted using PubMed/Medline, ISI Web of Knowledge, and Google Scholar until 2018. Point prevalence with 95% confidence intervals was estimated. The variances of each study were calculated using by binomial distribution formula. Heterogeneity among the studies was tested using Cochran's Q test with a significance level less than .1. The index of changes attributed to heterogeneity (I2) was assessed. Regarding the heterogeneity of the studies, a random effects model was employed to combine the results of the studies. All statistical analyses were performed using STATA Ver. 11 using the meta-analysis commands.
Results: Of 916 articles from 2011 to 2018, 12 studies were examined and analyzed based on inclusion criteria. The prevalence of alcohol in fatally injured motorcyclists was 0.30 (95% confidence interval [CI], 0.25-0.35). Subgroup analysis based on the type of country showed that the prevalence of alcohol in fatally injured motorcyclists in developing countries was 34% (95% CI, 0.18-0.49), which was higher than that in developed countries (29%; 95% CI, 0.24-0.33). In addition, the prevalence of alcohol among fatally injured motorcyclists aged 25-35 years was greater than that of other age groups (0.34; 95% CI, 0. 27-0.4). Conclusions: Motorcyclists dominated the picture of fatal crashes and deserve more attention by the public and government. With the proper planning and adoption of health policies, increasing prevalence and complications of the disease will be prevented.

Entities:  

Keywords:  Alcoholic; meta-analysis; mortality; motorcyclists; prevalence; worldwide

Mesh:

Year:  2019        PMID: 31389721     DOI: 10.1080/15389588.2019.1637519

Source DB:  PubMed          Journal:  Traffic Inj Prev        ISSN: 1538-9588            Impact factor:   1.491


  1 in total

1.  A systematic review of statistical models and outcomes of predicting fatal and serious injury crashes from driver crash and offense history data.

Authors:  Reneta Slikboer; Samuel D Muir; S S M Silva; Denny Meyer
Journal:  Syst Rev       Date:  2020-09-28
  1 in total

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