Identifying developmental trajectories of worldwide road traffic accident death rates using a latent growth mixture modeling approach

Road Traffic Accidents (RTA) are a major worldwide public health problem. The aim of this study was to use the growth mixture model for clustering countries on the basis of the mortality rate patterns of RTAs from 2007 to 2013. We obtained the data on RTA death rates from World Health Organization reports and Human Development Index (HDI) of United Nations Development Programme reports for the years 2007, 2010 and 2013. Simple Latent Growth Models (LGM) in 181 countries were applied to estimate overall RTA mortality rate growth trajectories and the latent growth mixture modeling utilized to cluster them. According to non-linear LGM, the overall mortality rate of RTAs showed a decrease from 2007 to 2010 followed by an increase from 2010 to 2013. The HDI covariate had a significant negative and positive effect on intercept and slope of the LGM, respectively. The extracted mixture model appeared to have seven classes with different trends in RTA mortality rates. The worldwide countries were clustered into seven classes. Further studies on each of the seven classes are suggested to provide recommendations for reducing the mortality rate of the RTAs. Additionally, increasing HDI in some countries could have a significant effect on reducing the RTA death rates. © 2019 Salehi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

An epidemiological survey on road traffic crashes in Iran: application of the two logistic regression models

Risk factors of human-related traffic crashes are the most important and preventable challenges for community health due to their noteworthy burden in developing countries in particular. The present study aims to investigate the role of human risk factors of road traffic crashes in Iran. Through a cross-sectional study using the COM 114 data collection forms, the police records of almost 600,000 crashes occurred in 2010 are investigated. The binary logistic regression and proportional odds regression models are used. The odds ratio for each risk factor is calculated. These models are adjusted for known confounding factors including age, sex and driving time. The traffic crash reports of 537,688 men (90.8) and 54,480 women (9.2) are analysed. The mean age is 34.1 +/- 14 years. Not maintaining eyes on the road (53.7) and losing control of the vehicle (21.4) are the main causes of drivers' deaths in traffic crashes within cities. Not maintaining eyes on the road is also the most frequent human risk factor for road traffic crashes out of cities. Sudden lane excursion (OR = 9.9, 95 CI: 8.2-11.9) and seat belt non-compliance (OR = 8.7, CI: 6.7-10.1), exceeding authorised speed (OR = 17.9, CI: 12.7-25.1) and exceeding safe speed (OR = 9.7, CI: 7.2-13.2) are the most significant human risk factors for traffic crashes in Iran. The high mortality rate of 39 people for every 100,000 population emphasises on the importance of traffic crashes in Iran. Considering the important role of human risk factors in traffic crashes, struggling efforts are required to control dangerous driving behaviours such as exceeding speed, illegal overtaking and not maintaining eyes on the road

The Road Traffic Crashes as a Neglected Public Health Concern; An Observational Study From Iranian Population

Objective: Traffic crashes are multifactorial events caused by human factors, technical issues, and environmental conditions. The present study aimed to determine the role of human factors in traffic crashes in Iran using the proportional odds regression model. Methods: The database of all traffic crashes in Iran in 2010 (n = 592, 168) registered through the "COM.114" police forms was investigated. Human risk factors leading to traffic crashes were determined and the odds ratio (OR) of each risk factor was estimated using an ordinal regression model and adjusted for potential confounding factors such as age, gender, and lighting status within and outside of cities. Results: The drivers' mean age +/- standard deviation was 34.1 +/- 14.0years. The most prevalent risk factors leading to death within cities were disregarding traffic rules and regulations (45), driver rushing (31), and alcohol consumption (12.3). Using the proportional odds regression model, alcohol consumption was the most significant human risk factor in traffic crashes within cities (OR = 6.5, 95 confidence interval CI, 4.88-8.65) and outside of cities (OR = 1.73, 95% CI, 1.22-3.29). Conclusions: Public health strategies and preventive policies should be focused on more common human risk factors such as disregarding traffic rules and regulations, drivers' rushing, and alcohol consumption due to their greater population attributable fraction and more intuitive impacts on society

Study of Road Traffic Injuries Risk Factors by Geographic Information System (GIS) in 2009

  Backgrounds and Aims: Using Geographical Information System (GIS) can decreases the burden of road traffic injuries effectively by identification of hot spot to modification in hazardous areas. The aim of the study was determining geographical distribution of human risk factors associated with road traffic injuries by using Geographical Information System (GIS) in Iran. Materials and Methods: The national database of road traffic injuries registered by the Iranian traffic Police (Rahvar NAJA) was used. The human risk factors were investigated by recognition of the hazardous points and geographical distribution of associated risk factors. The Hot Spot Analysis and Map clustering approaches were employed to meet the objectives.  Results: The mean age of injured subjects was 34 years and the most affected age group was 20-39 years. Death and injury occurrence within out of cities ways were 0.3 % and 28% respectively. Geographical distribution of risk factors also showed that roads of Northern provinces i.e. (Gilaan and Mazandaran) were the hazardous rising as well as Qazvin to Rasht and Qom to Tehran roads. Sistan and Balochestan Provinces and Tehran had the highest (4.8%) and the lowest (0.1%) rates of road traffic injuries leading to death in the country. Conclusions: Northern provinces and its leading axes by hazardous rising and Sistan and Balochestan province with fatal injuries need to identify the cause of injuries’ and, if necessary, more tighten regulations and more controls by the traffic police must be applied. REFERENCESPeden M, Scurfield R, Sleet D, Mohan D Hyder A A, Jarawan E . (2004).World report on road traffic injury prevention: World Health Organization Geneva. 2004.Kopits E, Cropper M. Traffic fatalities and economic growth. Accid Anal Prev 2005;37(1): 169-78.Channa R, Jaffrani H A, Khan A J, Hasan T, Razzak J A. Transport time to trauma facilities in Karachi: an exploratory study. Int J Emerg Med  2008; 1(3): 201–4. Soori H, Hussain S, Razzak J. Road safety in the Eastern Mediterranean Region–findings from the Global Road Safety Status Report. East Mediterr Health J 2011;17(10):770-6.Soori H.  Descriptive study (Chapter 8) in Basic applied epidemiology. Percian text book 2nd edition.Tehran: Arjmand publisher; 2008.Gesler W. The uses of spatial analysis in medical geography: a review. Social Science & Medicine 1986; 23(10): 963-73.Ameratunga S, Hijar M, Norton R. Road-traffic injuries: confronting disparities to address a global-health problem. The Lancet 2006;367(9521): 1533-40.Akbari M, Naghavi M, Soori H. Epidemiology of deaths from injuries in the Islamic Republic of Iran. East Mediterr health J 2006;12(3/4): 382-90.Rasouli M R, Nouri M, Zarei M R. Saadat S, Rahimi-Movaghar V. Comparison of road traffic fatalities and injuries in Iran with other countries. Chin J Traumatol 2008;11(3): 131-4.Ainy E, Soori H, Mahfozphoor S, Movahedinejad AA. Presenting a practical model for governmental political mapping on road traffic injuries in Iran in 2008: a qualitative study. J R Soc Med Sh Rep 2011; 2(10):79.Khorasani-Zavareh D, Mohammadi R., Khankeh H R, Laflamme L, Bikmoradi A, Haglund B J A. The requirements and challenges in preventing of road traffic injury in Iran. A qualitative study. BMC Public Health 2009; 23(9): 486-91.Nantulya V M, Reich M R. The neglected epidemic: road traffic injuries in developing countries. BMJ 2002; 324(7346): 1139-41. Elvik R. Road safety management by objectives: A critical analysis of the Norwegian approach. Accid Anal Prev 2008;40(3): 1115-22.Liang L Y, Mo’soem D, Hua L T. Traffic accident application using geographic information system. Journal of the Eastern Asia Society for Transportation Studies 2005;6(1): 3574–89.Braddock M, Lapidus G, Cromley E, Cromley R., Burke G, Banco L. Using a geographic information system to understand child pedestrian injury. Am J Public Health. 1994;84(7): 1158-61. Lascala E A, Gerbe D, Gruenewald P J. Demographic and environmental correlates of pedestrian injury collisions: a spatial analysis. Accid Anal Prev 2000;32(5): 651-8.Lightstone A, Dhillon P, Peek-Asa C, Kraus J. A geographic analysis of motor vehicle collisions with child pedestrians in Long Beach, California: comparing intersection and midblock incident locations. Inj Prev  2001;7(2): 155-60.Daum M L, Dorsch W R. Managing Land Use and Institutional Controls with GIS .  Journal of Map & Geography Libraries: Advances in Geospatial Information, Collections & Archives2008 ;4(1): 163-73.Erdogan, S, Yilmaz I, Baybura T, Gullu, M. Geographical information systems aided traffic accident analysis system case study: city of Afyonkarahisar. Accid Anal Prev 1998; 40(1): 174-81.Al-Kharusi W. Update on Road Traffic Crashes. Clinical Orthopaedics and Related Research. 2008;466(10): 2457-64.Fars news. Saturday 5th October 2012.Mwatelah J. Application of Geographical Information Systems (GIS) to Analyze causes of Road traffic Accidents (RTAs)–case Study of Kenya. International Conference on Spatial Information for Sustainable Development Nairobi, Kenya. 2–5 October 2001.Cusimano MD, Chipman M., Glazier R. H, Rinner C, Marshall S P. Geomatics in injury prevention: the science, the potential and the limitations. Inj Prev 2007;13(1): 51-6.Rezaeian M, Dunn G, St Leger S, Appleby L. Geographical epidemiology, spatial analysis and geographical information systems: a multidisciplinary glossary. J Epidemiol Community Health 2005;61(2): 98-102

The Road Traffic Crashes as a Neglected Public Health Concern; An Observational Study From Iranian Population

Objective: Traffic crashes are multifactorial events caused by human factors, technical issues, and environmental conditions. The present study aimed to determine the role of human factors in traffic crashes in Iran using the proportional odds regression model. Methods: The database of all traffic crashes in Iran in 2010 (n = 592, 168) registered through the �COM.114� police forms was investigated. Human risk factors leading to traffic crashes were determined and the odds ratio (OR) of each risk factor was estimated using an ordinal regression model and adjusted for potential confounding factors such as age, gender, and lighting status within and outside of cities. Results: The drivers� mean age ± standard deviation was 34.1 ± 14.0 years. The most prevalent risk factors leading to death within cities were disregarding traffic rules and regulations (45), driver rushing (31), and alcohol consumption (12.3). Using the proportional odds regression model, alcohol consumption was the most significant human risk factor in traffic crashes within cities (OR = 6.5, 95 confidence interval CI, 4.88�8.65) and outside of cities (OR = 1.73, 95% CI, 1.22�3.29). Conclusions: Public health strategies and preventive policies should be focused on more common human risk factors such as disregarding traffic rules and regulations, drivers� rushing, and alcohol consumption due to their greater population attributable fraction and more intuitive impacts on society. © 2015, Copyright © Taylor & Francis Group, LLC