This article was downloaded by: [The University of Texas at El Paso] On: 07 November 2014, At: 19:28 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

Traffic Injury Prevention Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/gcpi20

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

c

d

Mahmood Bakhtiyari , Ali Delpisheh , Ayad Bahadori Monfared , Mohammad Hassan Kazemib

e

a

f

Galougahi , Mohammad Reza Mehmandar , Mohammad Riahi , Masoud Salehi & Mohammad Ali Mansournia

b

a

Safety Promotion and Injury Prevention Research Centre, Shahid Beheshti University of Medical Sciences, Tehran, Iran b

Department of Epidemiology and Biostatistics, School of Public Health & Health Research Institute, Tehran University of Medical Sciences, Tehran, Iran

Click for updates

c

Department of Epidemiology, Prevention of Psychosocial Injuries Research Centre, Ilam University of Medical Sciences, Ilam, Iran d

Department of Health & Community Medicine, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran e

Police Science University, NAJA Traffic Police, Tehran, Iran

f

Health Management and Economics Research Center, Department of Statistics and Mathematics, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran Accepted author version posted online: 24 Apr 2014.Published online: 26 Sep 2014.

To cite this article: Mahmood Bakhtiyari, Ali Delpisheh, Ayad Bahadori Monfared, Mohammad Hassan Kazemi-Galougahi, Mohammad Reza Mehmandar, Mohammad Riahi, Masoud Salehi & Mohammad Ali Mansournia (2015) The Road Traffic Crashes as a Neglected Public Health Concern; An Observational Study From Iranian Population, Traffic Injury Prevention, 16:1, 36-41, DOI: 10.1080/15389588.2014.898182 To link to this article: http://dx.doi.org/10.1080/15389588.2014.898182

PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any

Downloaded by [The University of Texas at El Paso] at 19:28 07 November 2014

form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions

Traffic Injury Prevention (2015) 16, 36–41 C Taylor & Francis Group, LLC Copyright  ISSN: 1538-9588 print / 1538-957X online DOI: 10.1080/15389588.2014.898182

The Road Traffic Crashes as a Neglected Public Health Concern; An Observational Study From Iranian Population MAHMOOD BAKHTIYARI1,2, ALI DELPISHEH3, AYAD BAHADORI MONFARED4, MOHAMMAD HASSAN KAZEMI-GALOUGAHI2, MOHAMMAD REZA MEHMANDAR5, MOHAMMAD RIAHI1, MASOUD SALEHI6, and MOHAMMAD ALI MANSOURNIA2 1

Safety Promotion and Injury Prevention Research Centre, Shahid Beheshti University of Medical Sciences, Tehran, Iran Department of Epidemiology and Biostatistics, School of Public Health & Health Research Institute, Tehran University of Medical Sciences, Tehran, Iran 3 Department of Epidemiology, Prevention of Psychosocial Injuries Research Centre, Ilam University of Medical Sciences, Ilam, Iran 4 Department of Health & Community Medicine, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran 5 Police Science University, NAJA Traffic Police, Tehran, Iran 6 Health Management and Economics Research Center, Department of Statistics and Mathematics, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran

Downloaded by [The University of Texas at El Paso] at 19:28 07 November 2014

2

Received 17 November 2013, Accepted 22 February 2014

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. Keywords: public health, human factors, alcohol, crashes, Iran

Introduction Traffic crashes are multifactorial events caused by human factors, technical issues, and environmental conditions (Bakhtiyari et al. 2013). Road design, warning signs, and legislation concerning traffic and transportation structure affect the frequency and severity of road crashes (Al-Ghamdi 2002). Identifying the most likely human and non-human risk factors that influence the severity of traffic crashes is fundamental for preventative programs and policies (Rosman 2001). Lowand middle-income countries including Iran have the highest mortality rate due to road traffic crashes (21.5 and 19.5 cases

Managing Editor David Viano oversaw the review of this article Address correspondence to Mohammad Reza Mehmandar, NAJA Traffic Police, Police Sciences University, Tehran, Iran. E-mail: [email protected]

per 100,000 population, respectively) compared to developed countries, with an average of 15.6 cases per 100,000 population (Ameratunga et al. 2006; Kopits and Cropper 2005; Nantulya and Reich 2002). Road traffic crashes have significant effects on the field of public health and need to be recognized as a priority for prevention strategies. This issue has frequently been addressed by a number of Iranian studies (Akbari et al. 2006; Montazeri 2004). There are many risk factors for traffic crashes, which can be classified into drivers’ characteristics (human factors), vehicle status, and environmental features (Valent et al. 2002; Vorko-Jovic et al. 2006; Whitelegg 1987). Peden (2004) has shown the significant role of human (57%) and environmental factors (34%) in the occurrence of traffic crashes in the United States, where they are the most important cause of death and injury. There are some known human or human-related risk factors associated with road traffic crashes, including fatigued

A Neglected Public Health Concern

Downloaded by [The University of Texas at El Paso] at 19:28 07 November 2014

driving (Nikzad 2006; Sagberg 1999), gender, failure to use seat belts (Bendak 2005; Valent et al. 2002), certain days of the week and holidays, travel time, driving against traffic (Hijar et al. 2000), age, speeding (Abdel-Aty et al. 1998; Vorko-Jovic et al. 2006), smoking, cell phone use, and alcohol consumption (Grout et al. 1983; Kaul et al. 2005). Given the lack of reliable information on human factors and their influence on the occurrence and severity of road traffic injuries in Iran, the present study aimed to determine role of human factors in traffic crashes within and outsid of cities using a proportional odds regression model.

Methods The available documents of all Iranian drivers in 2010 (n = 592, 168) injured in traffic crashes by 2-wheel vehicles and vehicles with more than 2 wheels were investigated. To compare the sample with the population of the country according to the baseline characterstics, data from the Statistical Centre of Iran were used (Iran SCo 2011). The estimated population of Iran is about 75 million, of which 50.4 percent is male. Of the total population, 71.4 percent is urbanized. Recorded data on “COM114” forms (on which information about crashes and their causes is recorded) from police headquarters were available for analysis. The Iranian National Traffic and Driving Police (NAJA) traffic police have 2 separate branches in Iran. The first branch is in charge of implementation of traffic laws and regulations in urban areas. The second branch is responsible for intercity routes. In the present study, all available records on traffic crashes in both branches were investigated. The distinction between crash data for within cities and outside cities is made according to special codes (1 vs. 2) in the current study. Three Iranian organizations are in charge of recording traffic accident data, including the NAJA Traffic Police, the Legal Medical Centre, and the Ministry of Health. In the present study, the NAJA database was used because it is more comprehensive and included human and environmental information as well as vehicle factors (Nikzad 2006). Information regarding crashes was gathered in 4 different tables (accident, vehicle, passenger, and occupant characteristics) using Microsoft Office Access. Each crash was given 3 codes: a serial number, series number, and date of crash. In order to prepare the final data set, these 4 tables were linked to the codes. Data processing was conducted to examine repetitive codes by transferring the final table to SQL software. For example, a code was repeated 52 consecutive times for vehicle passengers. After identifying these cases, all of them were reduced to one code and the duplicates were eliminated. Thus, information about the accident was considered as a reference and other information was attached to them by considering the 3 mentioned codes. At this stage, some reference-free (no parents) records were recognized and stored to separate tables for separate analyses. It should be noted that some passengers might be injured in a single crash; therefore, their data were recorded separately and resulted in duplication in terms of age and other variables. Accordingly, the final table was produced and used for the final analyses. Human factors

37 including fatigue; involved defects; generalized body weakness due to aging, drugs, and alcohol consumption; disregarding traffic rules and regulations; driver rushing; violation of right of way; unfamiliarity with the road; and deliberately violating traffic laws were investigated. The impact of each risk factor on outcomes of road traffic crashes within and outside of cities was estimated using a proportional odds regression model. The eligible crashes were included in the study after confirming data accuracy and reliability of the study by statisticians and epidemiologists. The present police database on traffic crashes in Iran was previously validated (Bahadorimonfared et al. 2013, Bakhtiyari et al. 2013). The inclusion criteria were based on road traffic injury classification. In the present study, land-based traffic crashes with at least one motor vehicle with 2 or more wheels (on road) were considered; therefore, other events lacking these conditions were excluded from the study. The most important risk factors leading to death and injuries were determined using an ordinal logistic regression model. It was based on an assumption that the effects of the covariates x1 , . . ., xp−1 are the same for all categories on a logarithmic scale. The proportional odds model will not be affected by reversing the labels of the categories and only the signs of the parameters will change (Dobson 2001). This model was reported as a good option to treat ordinal data in epidemiologic as well as medical studies (Bender and Grouven 1997). In this model, fatal or nonfatal outcomes were considered as dependent variables and no injury was the referent based on the previous reports showing lower burden of no injury compared to either fatal or nonfatal categories. The known risk factors were also considered as independent dichotomous variables. Using this model, a numerical value was given to each injury class. Evaluation of the importance of each risk factor was based on the odds ratios and confidence intervals. This model was used to calculate adjusted odds ratios by entering significant variables (P value< .2) in the univariate analysis including age; gender; fatigue and sleepiness; driver impairment; generalized body weakness due to aging, drug abuse, or alcohol consumption; neglect of regulations; driver rushing; violation of right of way; not being familiar with roads; and deliberately violating traffic laws. We use the modified Pearson’s chi-square and deviance tests that are suitable for evaluating goodnessof-fit in ordinal response models when both categorical and continuous covariates are present (Pulkstenis and Robinson 2004). Stata software (Ver. 11.3) was used for all analyses. The proposal for the present study was approved by the Shahid Beheshti University of Medical Sciences Ethical Committee.

Results In the current study, traffic crash documents for 537,688 males (90.8%) and 54,480 females (9.2%) were investigated. Mean age of drivers ± standard deviation was 34.1 ± 14.0 years. In terms of employment status, 18.8% of drivers were clerks, 24.2% were either service workers or shop sellers, 28.3% were unemployed, 11% were professionals, 8.3% were in elementary

38

Bakhtiyari et al.

Table 1. Frequency of death, injury, and damage outcomes in traffic crashes within and outside of cities Male

Total

Setting

Outcome

n

%

n

%

n

%

Within cities

Fatal Nonfatal No injury Total Fatal Nonfatal No injury Total

1392 137,142 325,867 464,401 2669 20,446 48,428 71,543

0.3 29.5 70.2 100 3.7 28.6 67.7 100

96 10,182 40526 50,804 96 620 4704 5420

0.2 20 79.8 100 1.8 11.4 86.8 100

1488 147,324 366,393 515,205 2765 21,066 53,132 76,963

0.3 28.6 71.1 100 3.6 27.4 69.0 100

Out of cities

Downloaded by [The University of Texas at El Paso] at 19:28 07 November 2014

Female

occupations, and the rest (9.4%) were working in military forces. The gender distribution in routes within and outside of cities is shown in Table 1. The fatal crash rate was lower in routes within cities compared to roads outside of cities. The distribution of human factors involved in road traffic crashes according to the type of the outcome is demonstrated in Appendix 1 (see online supplement). Disregarding traffic rules and regulations (69.9%) and driver rushing (21.1%) were the most prevalent risk factors of road traffic crashes outside of cities. The corresponding risk factors for traffic crashes within cities were also disregarding traffic rules and regulations (45%), driver rushing (31%), and alcohol consumption (12.3%). A significant difference was found between traffic crashes within and outside of cities (P < .001). There were significant differences between crash outcomes including fatal, nonfatal, and no injury within and outside of cities (P < 0.001). Table 2 provides the human risk factors associated with crashes. Alcohol consumption was the most important risk factor in terms of magnitude of association (odds ratio) for traffic crashes leading to fatal or nonfatal outcomes in both routes within (odds ratio [OR] = 6.5, 95% confidence interval [CI], 4.88–8.65) and outside of cities (OR = 1.73, 95% CI, 1.22–3.29). Independent factors such as age and gender also had significant effects on fatal and nonfatal crashes.

Discussion The present study is unique in terms of sources of data (police registry, which is the largest and most useful database for researchers) compared to the other sources of data in Iran, as discussed the Method section. In short, the main components of road traffic crashes causes including human, environmental, and vehicle-related risk factors were available through this database. The sufficient sample size also made the present study representative and free of random errors. The high mortality rate of 39 cases per 100,000 population indicates that traffic fatalities are an important public health issue in Iran. The mortality rate due to traffic crashes in Iran is 2 times higher than the highest rate in European countries, which makes this matter a priority for the public health system in Iran (Khorasani-Zavareh et al. 2009; Rasouli et al. 2008; Shahraz et al. 2009). Therefore, focused attention and ongoing investigations into factors that contribute to increase

traffic crash injuries are warranted. Disregarding traffic rules and regulations accounted for the highest frequency among other human risk factors for road traffic crashes. Although alcohol consumption is banned due to religious consideration, it showed a significant effect in traffic crashes both within and outside of cities. The effect of alcohol consumption within cities was more prominent than that outside the cities. This difference could be in part due to more respect for traffic regulations and better control by traffic police within cities. The critical role of alcohol consumption as a significant risk factor in traffic crashes has already been revealed (Kaasik et al. 2007; Racioppi et al. 2004; Woratanarat et al. 2009). Driver age significantly affected traffic crashes both within and outside of cities. For example in traffic crashes outside of cities, with every one-year increase in age, the odds of being classified as either an injury or death was multiplied by 0.7%. This finding is consistent with other studies (Valent et al. 2002). Men have a higher risk of severe road traffic crashes than women and the odds of fatal or nonfatal crashes for men were 24% higher than for women. Drivers’ gender is also known as a risk factor in traffic crashes (Petridou et al. 1997). However, in traffic crashes within cities, being male was a protective factor for the occurrence of events. A potential reason for this observation may be due to the low number of female drivers outside of cities. Assessment of light condition showed that driving at sunset increased the odds of traffic crashes by 2.3-fold. Other risk factors such as older age and drug abuse showed a protective role in crashes resulting in fatal or nonfatal events outside of cities compared to crashes within cities. A rational look reveals that impaired, older, or addicted drivers drive less outside of cities than other groups. The lower odds ratio of other risk factors out of cities indicates both drivers’ respect for traffic regulations and police success in better control of road traffic crashes during recent years. Human factors were implicated in 23.8% of traffic crashes. The combined effects of human and road (8.43%), human and vehicle (4.3%), and human, vehicle, and road (6.25%) have also been reported. A similar study demonstrated a causative role of human factors in 97.5% of crashes in Iran (Nikzad 2006). A review of 33 American studies showed that regulations on fastening seat belts have decreased death and injury rates up to 9% and 2%, respectively (Shults et al. 2004). Badrinarayan and colleagues (2010) investigated factors related to traffic crashes including environmental and human factors, vehicle-related

A Neglected Public Health Concern

39

Table 2. Effect of human risk factors on traffic crashes in Iran, 2010 Within cities Variable

Category

OR

95% CI

OR

95% CI

Age Sex

Year Male Female Sunrisea Sunsetb Nightc Dayd Yes No Yes No Yes No Yes No Yes No Yes No Yes No Yes No Yes No Yes No

1.01 0.59 Reference 0.38 1.42 0.78 Reference 2.37 Reference 2.1 Reference 1.04 Reference 1.63 Reference 6.5 Reference 3.73 Reference 3.12 Reference 1.76 Reference 3 Reference 1.39 Reference

1.008–1.01 0.58–0.61

1.007 1.24 Reference 0.75 2.3 0.82 Reference 1.43 Reference 0.9 Reference 0.4 Reference 0.3 Reference 1.73 Reference 0.92 Reference 1.11 Reference 0.73 Reference 1.23 Reference 1.53 Reference

1.006–1.008 1.12–1.36

Light condition

Fatigue and sleepiness Driver impairment

Downloaded by [The University of Texas at El Paso] at 19:28 07 November 2014

Out of cities

Generalized body weakness due to aging Drug abuse Alcohol consumption Disregarding traffic rules and regulations Driver rushing Violation of right of way Unfamiliarity with the road Deliberately violating traffic laws

0.3–0.47 1.34–1.50 0.77–0.79 2.09–2.68 1.64–2.70 0.65–0.67 2.09–2.42 4.88–8.65 3.55–3.93 2.96–3.29 1.62–1.90 2.63–3.42 1.26–1.53

0.64–0.88 2.13–2.5 0.79–0.85 1.21–1.89 0.49–1.62 0.27–0.61 0.1–0.9 1.22–3.29 0.85–1.001 1.05–1.44 0.64–1.1 1.05–1.71 0.43–1.67

a5:15

a.m. to 7:20 a.m. p.m. to 20:50 p.m. c20:50 p.m. to 5:14 a.m. d7:21 a.m. to 16:31 p.m. b16:30

conditions, and time of the crash prospectively. There was a significant relationship between human risk factors and severe crashes leading to fatal events. The frequency of death among inexperienced drivers was also remarkable and included half of the population. They concluded that the most severe risk factors leading to death are preventable (Badrinarayan et al. 2010). Sleepiness while driving, which occurs more frequently in men than women, is reported to be the cause of 3.9% increase in road traffic crashes(Sagberg 1999). The present study and other reports (Leibowitz et al. 1998) have shown a significant relationship between fatigue (due to driving long distances) while driving and severe consequences of traffic crashes. Valent and colleagues (2002), who analyzed police-reported traffic crashes in 2002, suggested more pressure by legislation, more focus on people who break the rules, change in driver behaviors, and improvement of driving conditions as the best strategies to control traffic crashes. The World Health Organization has already introduced 5 basic factors to reduce traffic crashes: using a safe speed on roads outside of cities, which reduces up to 70% of accidents; using a safety belt, which can reduce 40% to 65% of mortality and injury due to traffic crashes; and use of helmets by motorcycle riders, which decreases mortality and injury rates up to 40% and 70%, respectively. Moreover, driver’s consciousness and ability to see and be seen can reduce traffic crashes within and outside of cities up to 35% (Peden 2004).

The risk of involvement in a traffic crash after consumption of alcohol has been investigated and well described elsewhere (Jones et al. 2009; Petridou and Moustaki 2000). A recent Iranian study reported that 64.5% of traffic crashes were due to disregarding traffic rules and regulations followed by alcohol consumption and drug abuse (24.3%) and only 3.9% were allocated to fatigue and sleepiness (Nikzad 2006). The present study showed drinking alcohol as a less frequent cause of fatal traffic crashes (overal responsible for 7.4%), but in terms of the measure of association (OR) it is one of the most prominent risk factors on urban and suburban roads. This is due to the use of an ordinal logistic regression model, which analyzes human risk factors closely and is a functional tool for researchers. Another reason could be related to using different sources of data or lack of appropriate attention to alcohol and drug use in our population, especially by young people, due to religious concerns. Consumption of alcohol is formally banned in Iran due to Islamic law and this habit is not common. Even so, according to studies in Iran, male youth and adolescents are at risk for alcohol consumption; therefore, these groups require special attention (Ahmadi and Hasani 2003, Mohammad Poorasl et al. 2007). Given the fact that in Iran studies have not been done regarding alcohol consumption by drivers, we lacked accurate information on this situation. Nevertheless, this study demonstrates the high impact of alcohol consumption on traffic fatalities and injuries to Iranian drivers.

Downloaded by [The University of Texas at El Paso] at 19:28 07 November 2014

40 Possible prevention measures for this risk factor include establishing driving while impaired courts, suspending or revoking driver’s licenses, locking away or confiscating vehicle plates, impounding or immobilizing vehicles, increasing penalties such as fines or jail for drunk driving, and mandating alcohol education. Nonmodifiable risk factors for the current study include age, gender, aging drivers, type of road user, and light condition. For these risk factors, implementing a systematic training program in the precrash stage for high-risk groups such as teenagers, older people, and females could be useful; for example, educational programs targeting traffic injury prevention in high school-aged children and improved knowledge about risks and risk avoidance in the target group. In addition, constant efforts to improve driving education among teenagers by implementing a graduated licensing system is recommended. A study by Rosenberg and Martinez (1996) showed that such efforts resulted in reduction of teen crashes by 5 to 16%. Older drivers, though, are usually capable of compensating for minor disfunction, but it is important to determine fitness to drive in light of a multidimensional assessment (Morgan and King 1995). For other modifiable risk factors in this study, enforcement of legislation, environmental modification such as implementing area-wide traffic calming measures (e.g., speed humps and speed cameras), and school crossing patrols are useful in reducing road traffic injuries. The present study is limited by possible errors in recording crash information by traffic police, which hopefully can be covered and minimized by the large sample size and our analysis method. Comprehensive information is needed to recognize what makes a difference and what has a direct impact on reducing deaths, injuries, injury severity, and costs. As mentioned previously, a linkage between our sources of data in the current design is impossible. However each data set has some application for stakeholders regarding prevention strategies in Iran. Data from police focus on human, environment, and vehicle factors; these data cannot be used to identify the factors contributing to road traffic mortality due to their incompleteness. Similarly, medico-legal data are used only for macrolevel policy making. To make these data more useful, there is an urgent need to merge these data. Nevertheless, the currently available data are crucial for identifying the current status and subsequent decisions for injury control and safety promotion. In addition, the new insights introduced by this large data set may bring valuable insights from unreported populations and offer a baseline for longitudinal studies. The increased mortality rate due to traffic crashes in Iran is of concern and needs to be considered seriously. The population-attributable fraction (PAF) is an important tool to assess the public health impact for a given exposure. PAF can be understood by considering that if the given population becomes completely unexposed to the risk factor of interest, what amount of reduction in incidence can be achieved. Two key components that drive PAF are frequency and measure of association (OR, relative risk) of an exposure. Thus, a high frequency and high measure of association will yield a high PAF, giving that risk factor a public health importance (Rockhill et al. 1998; Szklo and Nieto 2012). Considering this definition, we conclude that public health strategies and preventive policies should be fo-

Bakhtiyari et al. cused on more common human risk factors such as disregarding traffic rules and regulations, driver rushing, and alcohol consumption due to their greater PAF and more intuitive impacts on society.

Funding Financial support by the Iranian National Traffic and Driving Police (NAJA) is appreciated.

Supplemental Material Supplemental data for this article can be accessed on the publisher’s website.

References Abdel-Aty MA, Chen CL, Schott JR. An assessment of the effect of driver age on traffic accident involvement using log-linear models. Accid Anal Prev. 1998;30:851–861. Ahmadi J, Hasani M. Prevalence of substance use among Iranian high school students. Addict Behav. 2003;28:375–379. Akbari M, Naghavi M, Soori H. Epidemiology of deaths from injuries in the Islamic Republic of Iran. East Mediterr Health J. 2006;12:382– 390. Al-Ghamdi AS. Pedestrian–vehicle crashes and analytical techniques for stratified contingency tables. Accid Anal Prev. 2002;34:205–214. Ameratunga S, Hijar M, Norton R. Road-traffic injuries: confronting disparities to address a global-health problem. Lancet. 2006;367:1533–1540. Badrinarayan M, Nidhi S, Sukhla S, Sinha A. Epidemiological study of road traffic accident cases from western Nepal. Indian J Community Med. 2010;35(1):115–121. Bahadorimonfared A, Soori H, Mehrabi Y, et al. Trends of fatal road traffic injuries in Iran (2004–2011). PLoS One. 2013;8:e65198. Bakhtiyari M, Mehmandar MR, Mirbagheri B, et al. An epidemiological survey on road traffic crashes in Iran: application of the two logistic regression models. Int J Inj Contr Saf Promot. 2013;21:1–7. Bendak S. Seat belt utilization in Saudi Arabia and its impact on road accident injuries. Accid Anal Prev. 2005;37:367–371. Bender R, Grouven U. Ordinal logistic regression in medical research. J R Coll Physicians Lond. 1997;31:546–551. Dobson AJ. An Introduction to Generalized Linear Models. Boca Raton, FL: Chapman & Hall/CRC; 2001. Grout P, Cliff DKS, Harman M, Machin D. Cigarette smoking, road traffic accidents and seat belt usage. Public Health. 1983;97(2):95– 101. Hijar M, Carrillo C, Flores M, Anaya R, Lopez V. Risk factors in highway traffic accidents: a case control study. Accid Anal Prev. 2000;32:703–709. Iran S C o. Selected Findings of the 2011 National Population and Housing Census. Tehran, Iran: Statistical Centre of Iran; 2011. Jones AW, Kugelberg FC, Holmgren A, Ahlner J. Five-year update on the occurrence of alcohol and other drugs in blood samples from drivers killed in road-traffic crashes in Sweden. Forensic Sci Int. 2009;186(1):56–62. Kaasik T, V¨ali M, Saar I. Road traffic mortality in Estonia: alcohol as the main contributing factor. Int J Inj Contr Saf Promot. 2007;14(3):163–170. Kaul A, Sinha U, Kapoor A, et al. An epidemiological study of fatal road traffic accidents in Allahabad region. Indian Internet J Forensic Med Toxicol. 2005;3(1):36–45.

Downloaded by [The University of Texas at El Paso] at 19:28 07 November 2014

A Neglected Public Health Concern Khorasani-Zavareh D, Mohammadi R, Khankeh HR, et al. The requirements and challenges in preventing of road traffic injury in Iran. A qualitative study. BMC Public Health. 2009;9:486–495. Kopits E, Cropper M. Traffic fatalities and economic growth. Accid Anal Prev. 2005;37(1):169–178. Leibowitz HW, Owens DA, Tyrrell RA. The assured clear distance ahead rule: implications for nighttime traffic safety and the law. Accid Anal Prev. 1998;30(1):93–99. Mohammad Poorasl A, Vahidi R, Fakhari A, Rostami F, Dastghiri S. Substance abuse in Iranian high school students. Addict Behav. 2007;32:622–627. Montazeri A. Road-traffic-related mortality in Iran: a descriptive study. Public Health. 2004;118(2):110–113. Morgan R, King D. The older driver—a review. Postgrad Med J. 1995;71:525–528. Nantulya VM, Reich MR. The neglected epidemic: road traffic injuries in developing countries. BMJ. 2002;32:1139–1141. Nikzad M. The Rate of Road Traffic Injuries and Its Damge in Iran. 2nd ed. Tehran, Iran; Rahvar Research Center of NAJA; 2006. Peden M. World Report on Road Traffic Injury Prevention. Geneva, Switzerland: World Health Organization; 2004. Petridou E, Askitopoulou H, Vourvahakis D, Skalkidis Y, Trichopoulos D. Epidemiology of road traffic accidents during pleasure travelling: the evidence from the island of Crete. Accid Anal Prev. 1997;29:687–693. Petridou E, Moustaki M. Human factors in the causation of road traffic crashes. Eur J Epidemiol. 2000;16:819–826. Pulkstenis E, Robinson TJ. Goodness-of-fit tests for ordinal response regression models. Stat Med. 2004;23:999–1014. Racioppi F, Eriksson L, Tingvall C, Villaveces A. Preventing Road Traffic Injury: A Public Health Perspective for Europe. Citeseer; 2004.

41 Rasouli MR, Nouri M, Zarei MR, Saadat S, Rahimi-Movaghar V. Comparison of road traffic fatalities and injuries in Iran with other countries. Chin J Traumatol. 2008;11(3):131–134. Rockhill B, Newman B, Weinberg C. Use and misuse of population attributable fractions. Am J Public Health. 1998;88(1):15–19. Rosenberg ML, Martinez R. Graduated licensure: a win–win proposition for teen drivers and parents. Pediatrics. 1996;98:959–960. Rosman DL. The Western Australian Road Injury Database (1987–1996): ten years of linked police, hospital and death records of road crashes and injuries. Accid Anal Prev. 2001;33(1): 81–88. Sagberg F. Road accidents caused by drivers falling asleep. Accid Anal Prev. 1999;31:639–649. Shahraz S, Bartels D, Puthenpurakal JA, Motlagh ME. Adverse health outcomes of road traffic injuries in Iran after rapid motorization. Arch Iran Med. 2009;12:284–294. Shults RA, Nichols JL, Dinh-Zarr TB, Sleet DA, Elder RW. Effectiveness of primary enforcement safety belt laws and enhanced enforcement of safety belt laws: a summary of the Guide to Community Preventive Services systematic reviews. J Safety Res. 2004;35(2): 189–196. Szklo M, Nieto FJ. Epidemiology. Jones & Bartlett Publishers; 2012. Valent F, Schiava F, Savonitto C, et al. Risk factors for fatal road traffic accidents in Udine, Italy. Accid Anal Prev. 2002;4(1):71–84. Vorko-Jovic A, Kern J, Biloglav Z. Risk factors in urban road traffic accidents. J Safety Res. 2006;37(1):93–98. Whitelegg J. A geography of road traffic accidents. Trans Inst Br Geogr. 1987;12(2):161–176. Woratanarat P, Ingsathit A, Suriyawongpaisal P, et al. Alcohol, illicit and non-illicit psychoactive drug use and road traffic injury in Thailand: a case-control study. Accid Anal Prev. 2009;41:651–657.

The road traffic crashes as a neglected public health concern; an observational study from Iranian population.

Traffic crashes are multifactorial events caused by human factors, technical issues, and environmental conditions. The present study aimed to determin...
103KB Sizes 0 Downloads 3 Views