World J Surg (2015) 39:776–781 DOI 10.1007/s00268-014-2853-z
ORIGINAL SCIENTIFIC REPORT
Pedestrian Injuries-Related Deaths: A Global Evaluation Hani O. Eid • Fikri M. Abu-Zidan
Published online: 6 November 2014 Ó Socie´te´ Internationale de Chirurgie 2014
Abstract Objective Pedestrians are vulnerable road users who are at risk of injuries and death on the roads. We aimed to define factors affecting pedestrian injuries-related deaths worldwide and to give recommendations regarding their prevention priorities. Methods Data on pedestrian injuries-related deaths for years 2007 and 2010 were retrieved from the WHO global status reports on road safety. These included the country population, gross national income (GNI), number of registered vehicles, estimated pedestrian deaths rate, effectiveness of enforcement of law, and the presence of policies to promote walking or cycling. Correlations between studied variables were done using Spearman rank correlation. General linear models were used to define factors affecting pedestrian injuries-related deaths. Results The median (range) pedestrian death rates of different countries per 100,000 population significantly decreased in year 2010 compared with year 2007 [3.9 (0–13.5) compared with 4.2 (0–23.6), (p = 0.004, Wilcoxon signed rank test)]. There was a reduction of 8.1 % of the global pedestrian death rate between 2007 and 2010. The estimated pedestrian lives saved annually worldwide of a population of 6.8 billion were 23,120 persons. A general linear model has shown that GNI (p = 0.001) and population density (p = 0.01) were the best predictors of pedestrian death rates in 2007, while national legislation (p = 0.03) was the best predictor of pedestrian death rates in 2010. Conclusions There is a change in the factors affecting pedestrian mortality worldwide over time. GNI and population density became less significant than national legislation enforcement. Legislation and its enforcement are important to achieve the UN mission of reducing road traffic deaths by 5 million over the next decade.
Introduction The World Health Organization (WHO) ranked road injuries as the ninth leading cause of death in 2011 and projected it to be the seventh in 2030 [1]. Furthermore, about 60 % of global road traffic deaths are among young people aged 15–44-years old [2]. Road traffic injuries jumped from the tenth to be the eighth cause of death over the last H. O. Eid F. M. Abu-Zidan (&) Department of Surgery, College of Medicine and Health Sciences, UAE University, PO Box 17666, Al Ain, UAE e-mail: [email protected]
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two decades (1990–2010). Furthermore, it is the eighth cause of years of life lost (YLL) [3]. The goal of the United Nations (UN) Decade of Action for Road Safety is to reduce road deaths by around five million lives during the period of 2011–2020 [4]. It is important for trauma surgeons to be part of this action by being actively involved in defining risk factors of injury, performing proper interventional studies on injury prevention, evaluating its effects, and having clear policies to promote road safety [5, 6]. Physicians treating pedestrian injured patients should support health-policy reform through personal expert opinion and proper research [7].
World J Surg (2015) 39:776–781
Walking is a popular daily activity for most of the people regardless of their primary method of transportation mainly in the low- and middle-income countries [8]. Furthermore, it has been promoted as a healthy and cheap alternative method by different countries so as to reduce the number of vehicles. Nevertheless, policies to improve pedestrian safety do not exist in many countries. Pedestrians are vulnerable road users who are at risk of injuries and death on the roads. More than 20 % of the world’s road traffic deaths occur among pedestrians [2]. Most pedestrian deaths occur in low- and middle-income countries with figures reaching up to 75 % [2, 9, 10]. We aimed to define factors affecting pedestrian injuries-related deaths worldwide and to give recommendations regarding their prevention priorities.
Materials and methods Data retrieval and entry Data on pedestrian injuries-related deaths for different countries were retrieved from the global status reports on road safety of years 2007 and 2010 [2, 11]. The data of year 2010 have been published at the end of 2013 [2] because it took almost 3 years for the World Health Organization to publish these data. These data included the country population, Gross National Income (GNI) per capita in United State dollars, number of registered vehicles, reported number of road traffic deaths, estimated road traffic deaths rate per 100,000 population, percentage of deaths of pedestrians, effectiveness of overall enforcement of national speed limits, and the presence of policies to promote walking or cycling. The 2007 report had data on 178 countries. Out of them, 136 (76 %) had available data on pedestrian mortality and were included [11]. The 2010 report had data on 181 countries. Out of them, 134 (74 %) had available data on pedestrian mortality and were included [2]. 114 countries had data of both years. Collective data of these countries were used to estimate the change of the global pedestrian death rates for years 2007 and 2010. The enforcement of speed limits was scored on a zero to ten effectiveness scale. This represented consensus based on professional opinion of respondents [11]. Data were entered into excel program and rechecked for accuracy of data entry.
777
Pedestrian death rates were calculated by multiplying the percentage of pedestrian deaths by the estimated road traffic death rates per 100,000 population for both years of 2007 and 2010. Vehicle per person ratio was calculated by dividing the number of vehicles over the total population for both years 2007 and 2010. Statistics Spearman rank correlation test was used to define the correlation between different variables. Wilcoxon signed rank test was used to compare two dependent groups with continuous data. Pedestrian death rate for years 2007 and 2010 was transformed to the best normal distribution to fulfill the assumptions of the general linear models (GLM) [13]. The logarithmic transformation of pedestrian death rate of 2007 and the power of 0.5 transformation of pedestrian death rate in 2010 had the best normal distribution. A general linear model was done to define factors affecting pedestrian death rates. Factors which showed significant Spearman rank correlations (\0.05) were entered into GLM models for years 2007 and 2010. We have used GLM model for studying the effect of multiple independent factors on a dependent factor. GLM needs only the outcome dependent variable to have a normal distribution, while the independent variables can be binomial, ordinal, or continuous and do not need to have a normal distribution. This would address the nonlinear relationship between different factors. Independent continuous data were changed into ordinal data of 10-15 ranks to help the GLM to converge by reducing its levels. This included GNI for years 2007 and 2010, vehicle/person ratio for years 2007 and 2010, and population density for 2007 year. We had to do this because the GLM did not converge when continuous variables having high number of levels were used as independent factors in the model. The general linear model included Type III sum of squares error because the data were unbalanced. The residuals of the model were tested for normality and homogeneity [14]. Data were analyzed with the PASW Statistics version 18, SPSS Inc, Chicago, Illinois, USA.
Results Calculations The population density was calculated by dividing the population over the country area (inhabitants/mile square). The country area was retrieved from infoplease.com [12].
Table 1 shows the correlation between the studied variables in 2007. Pedestrian death rate was highly correlated with GNI (p \ 0.0001, r =-0.63), promoting alternative transport (p = 0.01, r =-0.22), population density
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Table 1 Spearman rank correlations between studied variables of year 2007 GNI/ capita
National legislation
Promoting alternative transport
Population density
Vehicle/ person ratio
Pedestrian-related death rates r
-0.63
p \0.0001
-0.12
-0.22
0.18
0.01
-0.3
-0.6
\0.0001
\0.0001
Vehicle/person ratio r
0.91
0.34
p \0.0001 \0.0001
0.32
0.14
\0.0001
0.64
–
Population density r
0.13
0.07
0.01
p
0.09
0.39
0.84
–
–
Promoting alternative transport r
0.32
p \0.0001
0.06
–
0.45
National legislation r 0.29 p \0.0001
–
–
–
–
(p \ 0.0001, r =-0.3), and vehicle per person ratio (p \ 0.0001, r =-0.6). Figure 1 shows the correlation between the GNI and pedestrian death rate worldwide in 2007. There were two outliers, the Cook Islands (black arrow) and United Arab Emirates (white arrow). Otherwise there was a nice nonlinear negative exponential relationship between GNI and death rate (shown by the solid line). This justified the use of Spearman rank correlation and not the linear regression correlations because it correlates the ranks and not the crude data. Table 2 shows the correlation between the studied variables in 2010. Pedestrian death rate was highly correlated with GNI (p \ 0.0001, r =-0.65), national legislation (p \ 0.0001, r =-0.3), promoting alternative transport methods (p \ 0.0001, r =-0.37), and vehicle per person ratio (p \ 0.0001, r =-0.66). Table 3 shows the general linear model that included the studied variables for defining factors that affected the pedestrian death rate in 2007. Levene’s test of equality of error variances was nonsignificant (p = 0.37) indicating that the error variance of the dependent variable was equal across groups. The model was highly significant (p \ 0.0001, F = 4.85, R Squared = 0.67). GNI (p \ 0.0001) and population density (p = 0.01) were significant factors affecting pedestrian death rate. Table 4 shows the GLM that included the studied variables for defining the factors that affected the pedestrian death rate in 2010. Levene’s test of equality of error variances was nonsignificant (p = 0.71) indicating that the
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Fig. 1 The correlation between pedestrian death rates and gross national income (GNI) of year 2007 (r =-0.63, p \ 0.0001, Spearman rank correlation). There were two outliers, the Cook Islands (black arrow) and United Arab Emirates (white arrow). The nonlinear negative exponential relationship between GNI and death rate is shown by the solid line
error variance of the dependent variable was equal across groups. The model was highly significant (p \ 0.0001, F = 4.16, R Squared = 0.62). National legislation (p = 0.03) was the only significant factor affecting pedestrian death rate, while GNI had a trend to be a significant factor (p = 0.07). The assumptions of the GLM models were met. The residuals of the models had a normal distribution and reasonable homogeneity. The median (range) estimated road traffic death rates of different countries per 100,000 population significantly decreased in 2010 compared with 2007 [15.3 (0–68.3) compared with 16.6 (1.7–48.4), (p \ 0.0001, Wilcoxon signed rank test)]. Similarly, the median (range) pedestrian death rates of different countries per 100,000 population significantly decreased in 2010 compared with 2007 [3.9 (0–13.5) compared with 4.2 (0–23.6), (p = 0.004, Wilcoxon signed rank test)] Fig. 2. The exact calculated global pedestrian death rate for countries having data of both years (n = 114) was 4.22 deaths per 100,000 population for year 2007 (229563/5,443,780541) and 3.88 deaths per 100 000 population for year 2010 (220773/5,697,097284). There was a reduction of 8.1 % of the pedestrian death rate between 2007 and 2010. The estimated pedestrian lives saved annually worldwide of a population of 6.8 billion would be 23,120 persons. There was no change in the percentage of pedestrian deaths out of road users between 2007 and 2010 [median (range) 26.1 % (0–78) compared with 28.2 % (0–75), (p = 0.9, Wilcoxon signed rank test)].
World J Surg (2015) 39:776–781
779
Table 2 Spearman rank correlations between studied variables of year 2010 GNI/ capita
National legislation
Promoting alternative transport
Population density
Vehicle/ person ratio
Pedestrian-related death rates r
-0.65
-0.3
p \0.0001 \0.0001
-0.37 \0.0001
-0.14
-0.66 \0.0001
0.12
Vehicle/person ratio r
0.86
0.45
p \0.0001 \0.0001
0.47
0.15
\0.0001
0.05
–
Population density r
0.14
0.13
0.12
p
0.05
0.09
0.11
–
–
–
–
–
–
–
–
Promoting alternative transport r
0.45
0.45
p \0.0001 \0.0001 National legislation r 0.49 p \0.0001
–
Table 3 The results of the general linear model showing factors affecting logarithmic transformation of pedestrian death rate of year 2007 Factor
Type III sum of squares
F value
p value
GNI
2.85
2.86
0.001
Promoting alternative transport
0.001
0.01
0.9
Population density
2.22
2.22
0.01
Vehicle/person ratio
0.53
0.82
0.6
Table 4 The results of the general linear model showing factors affecting the power of 0.5 transformation of pedestrian death rate of year 2010 Factor
Type III sum of squares
F value
p value
GNI
8.36
1.72
0.07
Promoting alternative transport
1.26
1.81
0.17
Vehicle/person ratio
2.83
0.81
0.62
National legislation
6.76
2.17
0.03
Discussion Our present study has shown that the factors affecting pedestrian death rate changed globally over time. While high GNI was important in reducing pedestrian death
Fig. 2 Box-and-whiskers plot of pedestrian death rate/100,000 population of years 2007 and 2010. The box resembles the interquartile range (IQR) where the box begins with the 25th percentile and ends with 75th percentile. The horizontal line within the box resembles the median. The whiskers lines represent the range of values that are not outliers. *** p = 0.004, Wilcoxon signed rank test
during 2007, enforcing national legislation of road safety became more important during 2010. The effect of wealth on pedestrian injuries has reduced and the importance of enforcing the law has increased. This study is unique because it represents the whole world population (global data from 181 countries, accounting for almost 99 % of the world’s population, covering 6.8 billion people) [2, 11]. Other detailed published studies from individual countries will help us to better understand our results but are not comparable. The rapid economic development since 2007 has increased the number of motorized vehicles by 15 % [15] with anticipated increased traffic flow and pedestrian death rates. Furthermore, increased population density worldwide would increase the pedestrian injury rates [16]. Despite these factors, pedestrian death rates were reduced between 2007 and 2010 years indicating that enforcement of the law played an important role in reducing pedestrian deaths in year 2010. This goes with the WHO resolution (64/255) of reducing the impact of road injuries [17]. Although an annual reduction of global pedestrian death rate of 8.1 % seems minor, this is a remarkable reduction for different reasons; first, this reduction occurred on a global level with large numbers worldwide (more than 23,000 were saved annually); second, this occurred within a relatively short period of time (3 years); and third, when compared with establishments of trauma systems, trauma systems reduced mortality of severe trauma by 25 % but they needed huge resources and longer time to achieve that [18].
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Different factors affect death rates in different countries. High GNI had a positive role in reducing pedestrian deaths in 2007. Increased GNI will initially be associated with improved road design interventions like signalized cross walks and humps which are associated with reduced mortality [19] but these developments will not be useful unless the pedestrian law is respected. Pedestrian deaths, in general, are higher in low- and middle-income countries compared with high-income countries (45 % of road deaths in low-income countries, 29 % in middle-income countries, and 18 % in highincome countries) [20]. The Eastern Mediterranean region is an exemption where high-income countries still have high pedestrian death rates [15]. For example, pedestrian deaths are high in the United Arab Emirates (UAE) despite the high income as shown by Fig. 1 and they cause 55 % of all hospitalized road traffic deaths [21]. The road infrastructure is of high quality and the population density is not high in UAE. This natural development highlights the need for strong and sustained law enforcement and adequate penalties to change the behavior of drivers so as to reduce pedestrian deaths at our setting [15]. Paulozzi et al. have suggested that poor countries transitioning to motorized transportation are likely to pass through a transitional period of increased road mortality before reaching the low rates of developed countries [22]. This may also explain the differences of the factors affecting pedestrian mortality in years 2007 and 2010. Reduction of the toll of pedestrian deaths, which constitute more than 20 % of road deaths at a global level, can be achieved by reducing their risk factors. The three e components of effective interventions to establish a safe pedestrian environment include engineering, enforcement, and education [23]. These interventions required a multidisciplinary approach involving legislators and different governmental sectors. Engineering measures toward pedestrian safety including roads separating pedestrians from motorized road users will help in decreasing pedestrian injuries and change the behavior of road users [23]. Reducing speed on roads is an important factor to reduce pedestrian deaths. The relationship between the speed and the severity of the crash is well established [24]. Energy transferred to the pedestrian during a collision increases with increased vehicle’s speed [25]. The relationship between the car impact speed and pedestrian death is exponential [26]. We have shown that reducing speed is more important than improving the vehicle design in reducing the severity of pedestrian injuries [27]. Presence of speed limit regulations, monitoring of speed on the roads, and strict enforcement of the law are very important in reducing pedestrian injuries [27, 28]. Despite that, speed limits in shared-space residential areas
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World J Surg (2015) 39:776–781
do not exist in many countries worldwide [9]. Furthermore, Safety education, especially for children, combined with community safety promotion activities will improve the knowledge of children and change their behavior when crossing roads [29], improve traffic control at child pedestrian sites, and reduce pedestrian injuries [30]. Limitations of the study Our study depended on the WHO-reported data. These official data are submitted by legal authorities worldwide. Pedestrian injuries and fatalities can be underreported in many countries due to limitations in data collection or political considerations [9]. It is expected that the actual number of pedestrian fatalities is higher than those reported. There are missing data from certain countries and most probably that this is not random because poorer countries do not have well-established data collection systems due to economical restrictions. Furthermore, we have to note that there are other important factors with possible effects on pedestrian death rates that we did not study. This includes level of pedestrian safety education especially for children [29, 30], using visibility aids including fluorescent material during the day, and lights/reflective materials at night [31], and the presence of pedestrian friendly vehicles [32]. Nevertheless, both of our GLM models had R Square higher than 0.6. This indicates that our models explained more than 60 % of the variation in the pedestrian death rates and that we have studied important factors. Furthermore, the level of GNI may reflect other hidden factors like regulations, education, behaviors of pedestrians and drivers, and perception of danger of the population. The fixed parameters model that we have used assumes that the effects of explanatory variables are the same within each country and does not account for unobserved heterogeneity [33]. For example, pedestrian deaths are more in the elderly [34, 35] because of their reduced vision, hearing, and perception of dangers when crossing roads [36]. Increased GNI is usually associated with increased elderly population which may dilute the positive effect of GNI on reducing pedestrian deaths.
Conclusions There is a change in the factors affecting pedestrian mortality worldwide over time. GNI and population density became less significant than national legislation enforcement. Legislation and its enforcement are important to achieve the UN mission of reducing road traffic deaths by 5 million over the next decade.
World J Surg (2015) 39:776–781 Conflict of interest All authors declare that there are no conflicts of interest.
References 1. World Health Organization (2013) Global burden of disease. Geneva, World Health Organization. Available at: (http://www. who.int/healthinfo/global_burden_disease/projections/en/. Accessed 10 April 2014 2. World Health Organization (2013) Global status report on road safety: supporting a decade of action. Geneva, World Health Organization. Available at: www.who.int/violence_injury_pre vention/road_safety_status/2013. Accessed 8 April 2014 3. Lozano R, Naghavi M, Foreman K et al (2012) Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 380:2095–2128 4. World Health Organization (2011) Decade of Action for Road Safety 2011–2020: saving millions of lives. Geneva, World Health Organization. Available at: http://www.who.int/violence_ injury_prevention/publications/road_traffic/decade_booboob/en/. Accessed 10 April 2014 5. American College of Surgeons, Injury Prevention and Control, https://www.facs.org/quality-programs/trauma/ipc. Accessed on 4 Sep 2014) 6. Royal Australasian College of Surgeons (2004) Appendix to Policy on Trauma (injury) 2004, Royal Australasian College of Surgeons p. 7 7. Chakravarthy B, Lotfipour S, Vaca FE (2007) Pedestrian injuries: emergency care considerations. Cal J Emerg Med 8:15–21 8. Zegeer CV, Bushell M (2012) Pedestrian crash trends and potential countermeasures from around the world. Accid Anal Prev 44:3–11 9. World Health Organization (2004) World report on road traffic injury prevention. Geneva, World Health Organization. Available at: http://www.who.int/violence_injury_prevention/publications/ road_traffic/world_reporr/en/. Accessed 10 April 2014 10. Nantulya VM, Reich MR (2002) The neglected epidemic: road traffic injuries in developing countries. BMJ 324:1139–1141 11. World Health Organization (2009) Global status report on road safety: time for action. Geneva, World Health Organization. Available at: www.who.int/violence_injury_prevention/road_ safety_status/2009. Accessed 8 April 2014 12. Area and Population of Countries. Available at: http://www. infoplease.com/ipa/A0004379.HTML. Accessed 8 April 2014 13. Miller J, Haden P (2006) Statistical analysis with the general linear model. University of Otago, Dunedin, New Zealand. http:// www.uv.es/*friasnav/librofactorial.pdf. Accessed 18 Sept 2014 14. Berry G (1998) Generalized linear models. In: Kerr C, Taylor R, Heard G (eds) Handbook of Public Health Methods. McGrawHill, Sydney, pp 340–343 15. Toroyan T, Khayesi M, Peden M (2013) Time to prioritise safe walking. Int J Inj Contr Saf Promot 20:197–202 16. Lascala EA, Gerber D, Gruenewald PJ (2000) Demographic and environmental correlates of pedestrian injury collisions: a spatial analysis. Accid Anal Prev 32:651–658 17. World Health Organization (2010) Improving global road safety, A/RES/64/255. Resolution of the United Nations General
781 Assembly, 64th session, 10 May 2010. Available at: http://www. who.int/roadsafety/about/resolutions/download/en/ 18. Celso B, Tepas J, Langland-Orban B et al (2006) A systematic review and meta-analysis comparing outcome of severely injured patients treated in trauma centers following the establishment of trauma systems. J Trauma 60:371–378 19. Kudryavtsev AV, Nilssen O, Lund J et al (2012) Explaining reduction of pedestrian-motor vehicle crashes in Arkhangelsk, Russia, in 2005–2010. Int J Circumpolar Health 71:19107 20. Naci H, Chisholm D, Baker TD (2009) Distribution of road traffic deaths by road user group: a global comparison. Inj Prev 15:55–59 21. Hefny AF, Eid HO, Abu-Zidan FM (2014) Pedestrian injuries in the United Arab Emirates. Int J Inj Contr Saf Promot 10(1080/ 17457300):884143 22. Paulozzi LJ, Ryan GW, Espitia-Hardeman VE et al (2007) Economic development’s effect on road transport-related mortality among different types of road users: a cross-sectional international study. Accid Anal Prev 39:606–617 23. World Health Organization (2013) Pedestrian safety: a road safety manual for decision-makers and practitioners. Geneva, World Health Organization. Available at: http://www.who.int/ roadsafety/projects/manuals/pedestrian/en/. Accessed 10 April 2014 24. Ga˚rder PE (2004) The impact of speed and other variables on pedestrian safety in Maine. Accid Anal Prev 36:533–542 25. Eid HO, Abu-Zidan FM (2007) Biomechanics of road traffic collision injuries: a clinician’s perspective. Singapore Med J 48:693–700 26. Rose´n E, Stigson H, Sander U (2011) Literature review of pedestrian fatality risk as a function of car impact speed. Accid Anal Prev 43:25–33 27. Aleassa EM, Eid HO, Abu-Zidan FM (2013) Effects of Vehicle size on pedestrian injury pattern and severity: prospective study. World J Surg 37:136–140. doi:10.1007/s00268-012-1797-4 28. Damsere-Derry J, Ebel BE, Mock CN et al (2010) Pedestrians’ injury patterns in Ghana. Accid Anal Prev 42:1080–1088 29. Duperrex O, Bunn F, Roberts I (2002) Safety education of pedestrians for injury prevention: a systematic review of randomised controlled trials. BMJ 324(7346):1129 30. Turner C, McClure R, Nixon J et al (2004) Community-based programmes to prevent pedestrian injuries in children 0–14 years: a systematic review. Inj Control Saf Promot 11:231–237 31. Kwan I, Mapstone J (2006) Interventions for increasing pedestrian and cyclist visibility for the prevention of death and injuries. Cochrane Database Syst Rev 4:CD003438 32. Crandall JR, Bhalla KS, Madeley NJ (2002) Designing road vehicles for pedestrian protection. BMJ 324(7346):1145–1148 33. Savolainen PT, Mannering FL, Lord D et al (2011) The statistical analysis of highway crash-injury severities: a review and assessment of methodological alternatives. Accid Anal Prev 43:1666–1676 34. Adam SH, Eid HO, Barss P et al (2008) Epidemiology of geriatric trauma in United Arab Emirates. Arch Gerontol Geriatr 47:377–382 35. Tefft BC (2013) Impact speed and a pedestrian’s risk of severe injury or death. Accid Anal Prev 50:871–878 36. Sparrow WA, Bradshaw EJ, Lamoureux E et al (2002) Ageing effects on the attention demands of walking. Hum Mov Sci 21:961–972
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ORIGINAL SCIENTIFIC REPORT
Pedestrian Injuries-Related Deaths: A Global Evaluation Hani O. Eid • Fikri M. Abu-Zidan
Published online: 6 November 2014 Ó Socie´te´ Internationale de Chirurgie 2014
Abstract Objective Pedestrians are vulnerable road users who are at risk of injuries and death on the roads. We aimed to define factors affecting pedestrian injuries-related deaths worldwide and to give recommendations regarding their prevention priorities. Methods Data on pedestrian injuries-related deaths for years 2007 and 2010 were retrieved from the WHO global status reports on road safety. These included the country population, gross national income (GNI), number of registered vehicles, estimated pedestrian deaths rate, effectiveness of enforcement of law, and the presence of policies to promote walking or cycling. Correlations between studied variables were done using Spearman rank correlation. General linear models were used to define factors affecting pedestrian injuries-related deaths. Results The median (range) pedestrian death rates of different countries per 100,000 population significantly decreased in year 2010 compared with year 2007 [3.9 (0–13.5) compared with 4.2 (0–23.6), (p = 0.004, Wilcoxon signed rank test)]. There was a reduction of 8.1 % of the global pedestrian death rate between 2007 and 2010. The estimated pedestrian lives saved annually worldwide of a population of 6.8 billion were 23,120 persons. A general linear model has shown that GNI (p = 0.001) and population density (p = 0.01) were the best predictors of pedestrian death rates in 2007, while national legislation (p = 0.03) was the best predictor of pedestrian death rates in 2010. Conclusions There is a change in the factors affecting pedestrian mortality worldwide over time. GNI and population density became less significant than national legislation enforcement. Legislation and its enforcement are important to achieve the UN mission of reducing road traffic deaths by 5 million over the next decade.
Introduction The World Health Organization (WHO) ranked road injuries as the ninth leading cause of death in 2011 and projected it to be the seventh in 2030 [1]. Furthermore, about 60 % of global road traffic deaths are among young people aged 15–44-years old [2]. Road traffic injuries jumped from the tenth to be the eighth cause of death over the last H. O. Eid F. M. Abu-Zidan (&) Department of Surgery, College of Medicine and Health Sciences, UAE University, PO Box 17666, Al Ain, UAE e-mail: [email protected]
123
two decades (1990–2010). Furthermore, it is the eighth cause of years of life lost (YLL) [3]. The goal of the United Nations (UN) Decade of Action for Road Safety is to reduce road deaths by around five million lives during the period of 2011–2020 [4]. It is important for trauma surgeons to be part of this action by being actively involved in defining risk factors of injury, performing proper interventional studies on injury prevention, evaluating its effects, and having clear policies to promote road safety [5, 6]. Physicians treating pedestrian injured patients should support health-policy reform through personal expert opinion and proper research [7].
World J Surg (2015) 39:776–781
Walking is a popular daily activity for most of the people regardless of their primary method of transportation mainly in the low- and middle-income countries [8]. Furthermore, it has been promoted as a healthy and cheap alternative method by different countries so as to reduce the number of vehicles. Nevertheless, policies to improve pedestrian safety do not exist in many countries. Pedestrians are vulnerable road users who are at risk of injuries and death on the roads. More than 20 % of the world’s road traffic deaths occur among pedestrians [2]. Most pedestrian deaths occur in low- and middle-income countries with figures reaching up to 75 % [2, 9, 10]. We aimed to define factors affecting pedestrian injuries-related deaths worldwide and to give recommendations regarding their prevention priorities.
Materials and methods Data retrieval and entry Data on pedestrian injuries-related deaths for different countries were retrieved from the global status reports on road safety of years 2007 and 2010 [2, 11]. The data of year 2010 have been published at the end of 2013 [2] because it took almost 3 years for the World Health Organization to publish these data. These data included the country population, Gross National Income (GNI) per capita in United State dollars, number of registered vehicles, reported number of road traffic deaths, estimated road traffic deaths rate per 100,000 population, percentage of deaths of pedestrians, effectiveness of overall enforcement of national speed limits, and the presence of policies to promote walking or cycling. The 2007 report had data on 178 countries. Out of them, 136 (76 %) had available data on pedestrian mortality and were included [11]. The 2010 report had data on 181 countries. Out of them, 134 (74 %) had available data on pedestrian mortality and were included [2]. 114 countries had data of both years. Collective data of these countries were used to estimate the change of the global pedestrian death rates for years 2007 and 2010. The enforcement of speed limits was scored on a zero to ten effectiveness scale. This represented consensus based on professional opinion of respondents [11]. Data were entered into excel program and rechecked for accuracy of data entry.
777
Pedestrian death rates were calculated by multiplying the percentage of pedestrian deaths by the estimated road traffic death rates per 100,000 population for both years of 2007 and 2010. Vehicle per person ratio was calculated by dividing the number of vehicles over the total population for both years 2007 and 2010. Statistics Spearman rank correlation test was used to define the correlation between different variables. Wilcoxon signed rank test was used to compare two dependent groups with continuous data. Pedestrian death rate for years 2007 and 2010 was transformed to the best normal distribution to fulfill the assumptions of the general linear models (GLM) [13]. The logarithmic transformation of pedestrian death rate of 2007 and the power of 0.5 transformation of pedestrian death rate in 2010 had the best normal distribution. A general linear model was done to define factors affecting pedestrian death rates. Factors which showed significant Spearman rank correlations (\0.05) were entered into GLM models for years 2007 and 2010. We have used GLM model for studying the effect of multiple independent factors on a dependent factor. GLM needs only the outcome dependent variable to have a normal distribution, while the independent variables can be binomial, ordinal, or continuous and do not need to have a normal distribution. This would address the nonlinear relationship between different factors. Independent continuous data were changed into ordinal data of 10-15 ranks to help the GLM to converge by reducing its levels. This included GNI for years 2007 and 2010, vehicle/person ratio for years 2007 and 2010, and population density for 2007 year. We had to do this because the GLM did not converge when continuous variables having high number of levels were used as independent factors in the model. The general linear model included Type III sum of squares error because the data were unbalanced. The residuals of the model were tested for normality and homogeneity [14]. Data were analyzed with the PASW Statistics version 18, SPSS Inc, Chicago, Illinois, USA.
Results Calculations The population density was calculated by dividing the population over the country area (inhabitants/mile square). The country area was retrieved from infoplease.com [12].
Table 1 shows the correlation between the studied variables in 2007. Pedestrian death rate was highly correlated with GNI (p \ 0.0001, r =-0.63), promoting alternative transport (p = 0.01, r =-0.22), population density
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World J Surg (2015) 39:776–781
Table 1 Spearman rank correlations between studied variables of year 2007 GNI/ capita
National legislation
Promoting alternative transport
Population density
Vehicle/ person ratio
Pedestrian-related death rates r
-0.63
p \0.0001
-0.12
-0.22
0.18
0.01
-0.3
-0.6
\0.0001
\0.0001
Vehicle/person ratio r
0.91
0.34
p \0.0001 \0.0001
0.32
0.14
\0.0001
0.64
–
Population density r
0.13
0.07
0.01
p
0.09
0.39
0.84
–
–
Promoting alternative transport r
0.32
p \0.0001
0.06
–
0.45
National legislation r 0.29 p \0.0001
–
–
–
–
(p \ 0.0001, r =-0.3), and vehicle per person ratio (p \ 0.0001, r =-0.6). Figure 1 shows the correlation between the GNI and pedestrian death rate worldwide in 2007. There were two outliers, the Cook Islands (black arrow) and United Arab Emirates (white arrow). Otherwise there was a nice nonlinear negative exponential relationship between GNI and death rate (shown by the solid line). This justified the use of Spearman rank correlation and not the linear regression correlations because it correlates the ranks and not the crude data. Table 2 shows the correlation between the studied variables in 2010. Pedestrian death rate was highly correlated with GNI (p \ 0.0001, r =-0.65), national legislation (p \ 0.0001, r =-0.3), promoting alternative transport methods (p \ 0.0001, r =-0.37), and vehicle per person ratio (p \ 0.0001, r =-0.66). Table 3 shows the general linear model that included the studied variables for defining factors that affected the pedestrian death rate in 2007. Levene’s test of equality of error variances was nonsignificant (p = 0.37) indicating that the error variance of the dependent variable was equal across groups. The model was highly significant (p \ 0.0001, F = 4.85, R Squared = 0.67). GNI (p \ 0.0001) and population density (p = 0.01) were significant factors affecting pedestrian death rate. Table 4 shows the GLM that included the studied variables for defining the factors that affected the pedestrian death rate in 2010. Levene’s test of equality of error variances was nonsignificant (p = 0.71) indicating that the
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Fig. 1 The correlation between pedestrian death rates and gross national income (GNI) of year 2007 (r =-0.63, p \ 0.0001, Spearman rank correlation). There were two outliers, the Cook Islands (black arrow) and United Arab Emirates (white arrow). The nonlinear negative exponential relationship between GNI and death rate is shown by the solid line
error variance of the dependent variable was equal across groups. The model was highly significant (p \ 0.0001, F = 4.16, R Squared = 0.62). National legislation (p = 0.03) was the only significant factor affecting pedestrian death rate, while GNI had a trend to be a significant factor (p = 0.07). The assumptions of the GLM models were met. The residuals of the models had a normal distribution and reasonable homogeneity. The median (range) estimated road traffic death rates of different countries per 100,000 population significantly decreased in 2010 compared with 2007 [15.3 (0–68.3) compared with 16.6 (1.7–48.4), (p \ 0.0001, Wilcoxon signed rank test)]. Similarly, the median (range) pedestrian death rates of different countries per 100,000 population significantly decreased in 2010 compared with 2007 [3.9 (0–13.5) compared with 4.2 (0–23.6), (p = 0.004, Wilcoxon signed rank test)] Fig. 2. The exact calculated global pedestrian death rate for countries having data of both years (n = 114) was 4.22 deaths per 100,000 population for year 2007 (229563/5,443,780541) and 3.88 deaths per 100 000 population for year 2010 (220773/5,697,097284). There was a reduction of 8.1 % of the pedestrian death rate between 2007 and 2010. The estimated pedestrian lives saved annually worldwide of a population of 6.8 billion would be 23,120 persons. There was no change in the percentage of pedestrian deaths out of road users between 2007 and 2010 [median (range) 26.1 % (0–78) compared with 28.2 % (0–75), (p = 0.9, Wilcoxon signed rank test)].
World J Surg (2015) 39:776–781
779
Table 2 Spearman rank correlations between studied variables of year 2010 GNI/ capita
National legislation
Promoting alternative transport
Population density
Vehicle/ person ratio
Pedestrian-related death rates r
-0.65
-0.3
p \0.0001 \0.0001
-0.37 \0.0001
-0.14
-0.66 \0.0001
0.12
Vehicle/person ratio r
0.86
0.45
p \0.0001 \0.0001
0.47
0.15
\0.0001
0.05
–
Population density r
0.14
0.13
0.12
p
0.05
0.09
0.11
–
–
–
–
–
–
–
–
Promoting alternative transport r
0.45
0.45
p \0.0001 \0.0001 National legislation r 0.49 p \0.0001
–
Table 3 The results of the general linear model showing factors affecting logarithmic transformation of pedestrian death rate of year 2007 Factor
Type III sum of squares
F value
p value
GNI
2.85
2.86
0.001
Promoting alternative transport
0.001
0.01
0.9
Population density
2.22
2.22
0.01
Vehicle/person ratio
0.53
0.82
0.6
Table 4 The results of the general linear model showing factors affecting the power of 0.5 transformation of pedestrian death rate of year 2010 Factor
Type III sum of squares
F value
p value
GNI
8.36
1.72
0.07
Promoting alternative transport
1.26
1.81
0.17
Vehicle/person ratio
2.83
0.81
0.62
National legislation
6.76
2.17
0.03
Discussion Our present study has shown that the factors affecting pedestrian death rate changed globally over time. While high GNI was important in reducing pedestrian death
Fig. 2 Box-and-whiskers plot of pedestrian death rate/100,000 population of years 2007 and 2010. The box resembles the interquartile range (IQR) where the box begins with the 25th percentile and ends with 75th percentile. The horizontal line within the box resembles the median. The whiskers lines represent the range of values that are not outliers. *** p = 0.004, Wilcoxon signed rank test
during 2007, enforcing national legislation of road safety became more important during 2010. The effect of wealth on pedestrian injuries has reduced and the importance of enforcing the law has increased. This study is unique because it represents the whole world population (global data from 181 countries, accounting for almost 99 % of the world’s population, covering 6.8 billion people) [2, 11]. Other detailed published studies from individual countries will help us to better understand our results but are not comparable. The rapid economic development since 2007 has increased the number of motorized vehicles by 15 % [15] with anticipated increased traffic flow and pedestrian death rates. Furthermore, increased population density worldwide would increase the pedestrian injury rates [16]. Despite these factors, pedestrian death rates were reduced between 2007 and 2010 years indicating that enforcement of the law played an important role in reducing pedestrian deaths in year 2010. This goes with the WHO resolution (64/255) of reducing the impact of road injuries [17]. Although an annual reduction of global pedestrian death rate of 8.1 % seems minor, this is a remarkable reduction for different reasons; first, this reduction occurred on a global level with large numbers worldwide (more than 23,000 were saved annually); second, this occurred within a relatively short period of time (3 years); and third, when compared with establishments of trauma systems, trauma systems reduced mortality of severe trauma by 25 % but they needed huge resources and longer time to achieve that [18].
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Different factors affect death rates in different countries. High GNI had a positive role in reducing pedestrian deaths in 2007. Increased GNI will initially be associated with improved road design interventions like signalized cross walks and humps which are associated with reduced mortality [19] but these developments will not be useful unless the pedestrian law is respected. Pedestrian deaths, in general, are higher in low- and middle-income countries compared with high-income countries (45 % of road deaths in low-income countries, 29 % in middle-income countries, and 18 % in highincome countries) [20]. The Eastern Mediterranean region is an exemption where high-income countries still have high pedestrian death rates [15]. For example, pedestrian deaths are high in the United Arab Emirates (UAE) despite the high income as shown by Fig. 1 and they cause 55 % of all hospitalized road traffic deaths [21]. The road infrastructure is of high quality and the population density is not high in UAE. This natural development highlights the need for strong and sustained law enforcement and adequate penalties to change the behavior of drivers so as to reduce pedestrian deaths at our setting [15]. Paulozzi et al. have suggested that poor countries transitioning to motorized transportation are likely to pass through a transitional period of increased road mortality before reaching the low rates of developed countries [22]. This may also explain the differences of the factors affecting pedestrian mortality in years 2007 and 2010. Reduction of the toll of pedestrian deaths, which constitute more than 20 % of road deaths at a global level, can be achieved by reducing their risk factors. The three e components of effective interventions to establish a safe pedestrian environment include engineering, enforcement, and education [23]. These interventions required a multidisciplinary approach involving legislators and different governmental sectors. Engineering measures toward pedestrian safety including roads separating pedestrians from motorized road users will help in decreasing pedestrian injuries and change the behavior of road users [23]. Reducing speed on roads is an important factor to reduce pedestrian deaths. The relationship between the speed and the severity of the crash is well established [24]. Energy transferred to the pedestrian during a collision increases with increased vehicle’s speed [25]. The relationship between the car impact speed and pedestrian death is exponential [26]. We have shown that reducing speed is more important than improving the vehicle design in reducing the severity of pedestrian injuries [27]. Presence of speed limit regulations, monitoring of speed on the roads, and strict enforcement of the law are very important in reducing pedestrian injuries [27, 28]. Despite that, speed limits in shared-space residential areas
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do not exist in many countries worldwide [9]. Furthermore, Safety education, especially for children, combined with community safety promotion activities will improve the knowledge of children and change their behavior when crossing roads [29], improve traffic control at child pedestrian sites, and reduce pedestrian injuries [30]. Limitations of the study Our study depended on the WHO-reported data. These official data are submitted by legal authorities worldwide. Pedestrian injuries and fatalities can be underreported in many countries due to limitations in data collection or political considerations [9]. It is expected that the actual number of pedestrian fatalities is higher than those reported. There are missing data from certain countries and most probably that this is not random because poorer countries do not have well-established data collection systems due to economical restrictions. Furthermore, we have to note that there are other important factors with possible effects on pedestrian death rates that we did not study. This includes level of pedestrian safety education especially for children [29, 30], using visibility aids including fluorescent material during the day, and lights/reflective materials at night [31], and the presence of pedestrian friendly vehicles [32]. Nevertheless, both of our GLM models had R Square higher than 0.6. This indicates that our models explained more than 60 % of the variation in the pedestrian death rates and that we have studied important factors. Furthermore, the level of GNI may reflect other hidden factors like regulations, education, behaviors of pedestrians and drivers, and perception of danger of the population. The fixed parameters model that we have used assumes that the effects of explanatory variables are the same within each country and does not account for unobserved heterogeneity [33]. For example, pedestrian deaths are more in the elderly [34, 35] because of their reduced vision, hearing, and perception of dangers when crossing roads [36]. Increased GNI is usually associated with increased elderly population which may dilute the positive effect of GNI on reducing pedestrian deaths.
Conclusions There is a change in the factors affecting pedestrian mortality worldwide over time. GNI and population density became less significant than national legislation enforcement. Legislation and its enforcement are important to achieve the UN mission of reducing road traffic deaths by 5 million over the next decade.
World J Surg (2015) 39:776–781 Conflict of interest All authors declare that there are no conflicts of interest.
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