ArticleBMJ open2025
Understanding road accident injury dynamics in Iran: a growth mixture modelling perspective.
Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Defensive Driving and Iran's "No to Road Accidents" Campaign: The Pivotal Role of Occupational Health and Safety Professionals in Reducing Fatalities.Iranian journal of medical sciences · 2025Article
- Modeling Time Series of Mortality Cases Due to Traffic and Non-Traffic Accidents in Northwestern Iran from 2013 to 2022.Iranian journal of nursing and midwifery researchArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesRoad traffic injuries represent a significant public health concern globally. In Iran, road accidents have become a leading cause of death and disability, necessitating urgent attention to injury prevention strategies. This study aims to analyse the trends in injuries resulting from road accidents over a decade. Understanding these trends is crucial for informing targeted interventions and resource allocation, ultimately contributing to the reduction of road traffic injuries.
designEcological study.
settingThe data were obtained from the official database of the Iranian Legal Medicine Organization, which includes the injury rates of all provinces due to road accidents, from 2012 to 2021.
participantsAll records registered with injuries due to road traffic accidents across Iranian provinces. OUTCOME MEASURES: The incidence and average annual percentage of injury rates across provinces were illustrated using a map. A piecewise linear mixed-effects model was employed to estimate trends in injury rates, by gender. To identify distinct clusters of provinces exhibiting similar trends in injury rates, a growth mixture model was used over the 10 years.
resultsAmong provinces, Qom (95% CI 18.99 to 37.21) and Sistan and Baluchestan (95% CI 5.41 to 7.66) had the highest and lowest injury rates over the decade, respectively. The annual rate of injuries in Iran increased by 0.52% from 2012 to 2018 and then gradually decreased by 1.16% after 2018. Four distinct classes were identified for the trend of injury rates over the decade: one cluster exhibited a significant decline, two clusters showed sharp increases and the last one had a steady trend.
conclusionsThese results contribute valuable insights into the dynamics of road accident-related injuries in Iran, offering a nuanced understanding of both overarching national trends and the unique patterns observed across provinces. Such knowledge can serve as a foundation for targeted interventions and policy formulations aimed at mitigating the impact of road accidents on public health and safety.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.