Evidence map›Paper›PMID 39697383›Full record

ArticleBulletin of emergency and trauma2024

Road Traffic Injuries in Iran: Epidemiology and Equitable Distribution of Emergency Services.

Pirhossein Kolivand, Peyman Saberian, Samad Azari, Peyman Namdar, Fereshte Karimi, Arash Parvari, Seyed Jafar Ehsanzadeh, Behzad Raei, Mehdi Raadabadi, Soheila Rajaie

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Bulletin of emergency and trauma, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Pirhossein KolivandDepartment of Health Economics, Faculty of Medicine, Shahed University, Tehran, Iran.
Peyman SaberianDepartment of Anesthesiology, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran.
Samad AzariHospital Management Research Center, Health Management Research Institute, Iran University of Medical Sciences, Tehran, Iran.
Peyman NamdarDepartment of Emergency Medicine, Metabolic Disease Research Center, Qazvin University of Medical Sciences, Qazvin, Iran.
Fereshte KarimiResearch Center for Emergency and Disaster Resilience, Red Crescent Society of the Islamic Republic of Iran, Tehran, Iran.
Arash ParvariDepartment of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Seyed Jafar EhsanzadehEnglish Language Department, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran.
Behzad RaeiRazi Educational and Therapeutic Center, Tabriz University of Medical Science, Tabriz, Iran.
Mehdi RaadabadiSchool of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Soheila RajaieResearch Center for Emergency and Disaster Resilience, Red Crescent Society of the Islamic Republic of Iran, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study emphasized the importance of providing equal access to rescue and emergency services for all individuals involved in road accidents, regardless of their geographical location or socioeconomic status. Methods: This study involved gathering data on the number of Iranian Red Crescent Society (IRCS) and Emergency Medical Services (EMS) stations in 31 provinces of Iran. It entailed calculating the Gini coefficient and creating the Lorenz curve to assess the station distribution. To present road traffic injuries (RTIs) mortality, Disability-Adjusted Life Years (DALYs), and prevalence in Iran from 1990 to 2019, the Global Burden of Disease (GBD) 2019 estimates were utilized. Results: The findings revealed that Tehran, Khorasan Razavi, Isfahan, Fars, and Khuzestan provinces were equipped with the most stations; whereas, Ilam, Semnan, and Kohgiluyeh and Boyer Ahmad had the fewest. The Gini coefficient for the distribution of RCS and EMS stations was found to be 0.23 and 0.38, respectively. Additionally, the study examined the prevalence, DALYs, and mortalities caused by road injuries across the 31 provinces and presented the findings in the form of a geographical representation. Conclusion: The results of this study highlighted the importance of ongoing efforts to ensure the equitable allocation of RCS and emergency services, with a particular emphasis on road accidents and disaster management scenarios.

Indexed as

EquityGini coefficientLorenz curveRed crescent society

Identifiers

PMID39697383
PMCPMC11651247

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Registered trials

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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.