Distractions and the risk of car crash injury: The effect of drivers age

Journal of Safety Research 33 (2002) 411 419 www.elsevier.com/locate/jsr Distractions and the risk of car crash injury: The effect of drivers age Lawrence T. Lam * Royal Alexandra Hospital for Children, Locked Bag 4001, Westmead, Sydney, NSW 2145, Australia Received 26 October 2001; accepted 3 April 2002 Abstract Problem: Motor-vehicle accidents are one of the major causes of injury in most motorized countries. Driver distractions have been suggested as a contributor to traffic accidents. Moreover, age of the driver seems to have a role in the relationship between distractions and car crashes. But very few studies have investigated the effect of driver s age on this relationship. This exploratory study investigated the association between distractions, both inside and outside the vehicle, and the increased risk of car crash injury among drivers across different ages. Method: This study used a case series design to analyze data routinely collected by the NSW police in Australia. A special focus of this study was on how drivers age affects the risk of car crash injury, which was determined by using a well-documented risk estimation methodology. Results: The results obtained indicated that drivers of all ages, on the whole, are more susceptible to distractions inside the vehicle than distractions coming from outside. Age was shown to affect the relationship between in-vehicle distraction and the risk of car crash injury. A separate analysis was also conducted on hand-held phone usage while driving with results supplementing previous findings reported in the literature. Impact to industry: Safety strategies to countermeasure in-vehicle distractions have been suggested and discussed. D 2002 National Safety Council and Elsevier Science Ltd. All rights reserved. Keywords: Distractions; Mobile phone; Car crash injury; Age factor; Risk estimation 1. Introduction Injury of any type poses a severe threat to all ages of the population in most developed countries (Murry & Lopez, 1997). Motor-vehicle accidents are one of the major causes of injury in most motorized countries (Evans, 1991). According to the Global Burden of * Tel.: +612-9845-3055; fax: +612-9845-3082. E-mail address: lawrencl@chw.edu.au (L.T. Lam). 0022-4375/02/$ - see front matter D 2002 National Safety Council and Elsevier Science Ltd. All rights reserved. PII: S0022-4375(02)00034-8

412 L.T. Lam / Journal of Safety Research 33 (2002) 411 419 Disease Study (Murry & Lopez, 1996), motor-vehicle-related injury was estimated as the fourth largest cause of disability-adjusted life years lost (DALYS) in prosperous countries in 1999. In Australia, car crash injuries are also the main cause of hospital presentations, admission, and fatalities among young people, in particular, young males aged 17 25 (NH & MRC, 1999). Over the past few decades, much effort has been devoted to researching risks and preventable factors of car crash injury, particularly among young drivers (Evans, 1993; Goldstein, 1962; McGwin & Brown, 1999; Norris, Matthews, & Riad, 2000). The aim of these efforts is to derive countermeasures, based on the evidence obtained from research, to the problem of motor vehicle-related mortality and morbidity. Amongst various factors studied, inattention of the driver has long been suggested as a contributor to traffic accidents (Treat et al., 1977). However, until recently, not much attention has been paid to the distraction of drivers as one of the important risk factors for car crash involvement and injuries. The refocussing of attention is mainly due to the widespread use of mobile cellular telephones, a significant component of distraction while driving (Min & Redelmeier, 1998). There is a growing body of literature on the effects of mobile phone usage on driving performance (Alm & Nilsson, 1994, 1995; Brookhuis, De Vries, & De Waard, 1991; Irwin, Fitzgerald, & Berg 2000; Lamble, Kauranen, Laakso, & Summala, 1999; McKnight & McKnight, 1993). In terms of the relationship between in-vehicle mobile phone use as a distraction and car crash involvement and injury, results obtained from epidemiological studies provide affirmative evidence (Parkes & Hooijmeijer, 2000; Redeleier & Tibshirani, 1997; Violanti, 1997, 1998; Violanti & Marshall, 1996). In general, these results indicate that there is a significant association between mobile phone use and the risk of car collision and injury. In a case-control study by Violanti and Marshall (1996), it was found that talking on the mobile phone while driving more than 50 min per month was associated with a nearly six-fold increase in the risk of traffic accident involvement when compared with those who talked less that 50 min. In another case-crossover study, using information obtained from self-reported questionnaires, police reports, and telephone records, results indicated that the risk of car collision was four times higher when a mobile phone was used as compared to not being used (Redeleier & Tibshirani, 1997). In the two other studies by Violanti (1997, 1998), the age of the driver was included in the analyses. The results suggested that there seemed to have been an interactive effect of age of driver and phone use on the risk of collision and injury. In terms of other forms of distraction, very few epidemiological studies have been conducted. Two studies investigated the association between lighting or smoking a cigarette while driving and car crash collision (Brison, 1990; Violanti & Marshall, 1996). Results obtained from both studies suggested that there is no significant relationship between distraction due to smoking or lighting cigarettes and car crash. Very few studies have actually investigated the effect of distraction as a whole on the risk of car crash collision or injury. Much less have studied the effect of drivers age on the relationship between distraction and car crash injury. The aim of this exploratory study is to further investigate the relationship between any distraction while driving and the risk of car crash injury, with particular focus on the age of drivers.

L.T. Lam / Journal of Safety Research 33 (2002) 411 419 413 2. Methods Data used in this study were made available from the Traffic Accident Database System (TADS) by the Roads and Traffic Authority of New South Wales (NSW), Australia for the period between 1996 and 2000. The TADS is used to collate information on all road traffic accidents that occur on the roads in NSW. Data were derived from the traffic incidents reported by the NSW police. According to the law in NSW, police are required to attend a serious accident if a person was killed or injured, or a minor accident when there was property damage over A$500 or one or more of the vehicles was required to be towed away. The data collected are very similar to the Fatality Analysis Reporting System (FARS) in the United States. The database records details on the drivers of the crash vehicles and the circumstances surrounding the traffic accident. They include details on the physical environment of the crash sites, and situational and behavioral information on the drivers and passengers that might contribute to the accident. Distraction is defined in the dictionary as an act of distracting, drawing apart, or separating; an action that diverts attention (Webster s Dictionary, 1998). Thus, it followed that distraction to the driver could broadly be defined as any movement, activity, and/or happening initiated by the driver or someone else inside or outside the vehicle that might have caused a diversion of the driver s attention. In this study, distractions while driving were classified into three categories: (a) distraction within the vehicle; (b) distraction outside the vehicle; and (c) no distraction at all. Distraction within the vehicle was defined as any activities, actioned by the driver or passenger(s), which might cause a diversion of attention of the driver from his/her driving task. These included using a hand-held telephone, attending to passengers, adjusting radio or CD/cassette player, lighting and smoking a cigarette, and other activities in the vehicle. Distraction outside the vehicle was defined as any circumstances on the road that constitutes a distraction to the driving task. These included a wide range of sudden happenings such as an accident, emergency vehicle warning, and even pursued by police. The distraction status and types of distraction were assessed by investigating police officers at the crash scenes. In most cases, information was gathered from the injured drivers, passenger(s), and/or other witness(es). The outcomes of the study were car crash-related fatalities and injuries to the drivers. The aim of the study is to investigate associations between distraction as a whole, both inside and outside vehicle, and car crash injury to the driver with a special focus on the age of drivers. Data were analyzed by stratifying the outcome by distraction types and age groups. Hand-held phone usage was considered as a separate distraction type in this study. Injury rates and crash rates per 10,000 population for each age group were calculated. The population estimations for each year between 1996 and 2000 were obtained from the Australian Bureau of Statistics (1998, 2000). The deaths and injuries per 1,000 crashes were used as a measure of crash outcome. As noted by Chen, Baker, Braver, and Li (2000), this represented crash outcome rather than actual incidence, and reflected the relationship between the consequence of the crash and some variables, such as cognitive processing while driving, that might have been affected by distractions. Relative risks and their 95% CI were estimated for each age group and distraction type. The relative risk was defined as death/injury rate ratio, calculated by dividing the death/injury rate of the target

414 L.T. Lam / Journal of Safety Research 33 (2002) 411 419 group by that of the reference group. The 95% confidence intervals for relative risks were calculated by adopting the standardized rate ratio confidence intervals method detailed in Rothman and Greenland (1998). 3. Results There were 414,136 crashes reported to the police within the period of 1996 2000 in NSW, Australia. Among these, 63,779 (15.3%) crashes resulted in a driver being killed or injured. As summarized in Table 1, there was a slight increase in the average injury and total crash rates from the 16 19 age group (43.93/10,000 pop) to the 20 24 (45.13/10,000 pop) age group, then a general decline in both rates as the age of drivers increased. As shown, the injury rate and total crash rate increased again in the oldest (70 or above) age group. This was consistent with the well-reported bimodal pattern of frequency distributions by age of injury statistics. Distraction was identified as a contributing factor of the crash in 2,400 incidents resulting in the drivers being killed or injured. These included both distractions inside and outside the vehicle, representing 3.8% of the total injurious crashes. Over the 5-year period, a total of 30 drivers were killed or injured with hand-held phone usage while driving as a contributing factor, and 120 crashes were attributed to the same reason. Drivers in the 25 29 age group had the highest frequency of phone use-related injurious crashes, as well as total crashes. In terms of other types of distractions, there was a general decline in the frequencies of injurious crashes as the age of drivers increased, with the exception of the 30 39 age group. Table 2 details the results on death rates and the relative risks calculated as the rate ratio between the target group and the reference group for each age stratum, and type of distraction. The results suggested that there are significant associations between distractions inside the vehicle and an increased risk of car crash injury across all age groups. On the other hand, outside vehicle distractions tended to have no effect on increasing the risk of car crash injury for drivers of all ages (Table 2). As shown, there appeared to be an age effect on the association between hand-held phone usage while driving and the risk of car crash injury. There was no significant increase in the risk of being killed or injured in a crash for drivers using a hand-held phone in most age groups, except 25 29- year-old drivers, when compared with those crashed drivers without any distraction. The Table 1 Average injury and total crash rates per 10,000 population in NSW, Australia, 1996 2000 Age group Killed/injured Total car crash 16 19 43.93 (39.74 48.11) a 248.02 (166.74 329.30) 20 24 45.13 (42.23 48.02) 256.35 (168.96 343.74) 25 29 32.93 (30.47 35.38) 185.52 (122.29 248.76) 30 39 25.53 (23.03 28.03) 143.93 (94.89 192.96) 40 49 20.88 (18.77 22.98) 118.21 (77.24 159.19) 50 69 15.80 (14.81 16.78) 73.38 (66.81 79.96) 70 + 22.69 (17.43 27.95) 147.49 (122.40 172.57) a 95% CI.

L.T. Lam / Journal of Safety Research 33 (2002) 411 419 415 Table 2 Distraction-related death and injury per 1000 crashes by distraction type and age of driver Distraction type No distraction a Hand held phone Other inside vehicle Outside vehicle Deaths/injury b 16 19 7,164 4 242 213 20 24 9,759 2 195 222 25 29 7,735 11 133 181 30 39 12,108 7 214 233 40 49 9,247 5 83 163 50 69 9,127 0 84 179 70 + 6,239 1 89 139 Total crashes b 16 19 46,573 23 1,010 1,470 20 24 63,323 26 916 1,740 25 29 49,908 30 593 1,253 30 39 78,143 27 884 1,822 40 49 59,354 19 494 1,417 50 69 56,235 9 333 1,367 70 + 45,541 16 357 1,253 Death rate c 16 19 153.82 173.91 239.60 144.90 20 24 154.11 76.92 212.88 127.59 25 29 154.99 366.67 224.28 144.45 30 39 154.95 259.26 242.08 127.88 40 49 155.79 263.16 168.02 115.03 50 69 162.30 0.00 252.25 130.94 70 + 137.00 52.50 249.30 110.93 Relative risk (95% CI) 16 19 1.00 1.13 (0.42 3.01) 1.56 (1.37 1.77) 0.94 (0.76 1.16) 20 24 1.00 0.50 (0.12 2.00) 1.38 (1.20 1.59) 0.83 (0.65 1.05) 25 29 1.00 2.37 (1.31 4.27) 1.45 (1.22 1.72) 0.93 (0.72 1.21) 30 39 1.00 1.67 (0.80 3.51) 1.56 (1.36 1.79) 0.83 (0.64 1.06) 40 49 1.00 1.69 (0.70 4.06) 1.08 (0.87 1.34) 0.74 (0.54 1.01) 50 69 1.00 1.55 (1.25 1.93) 0.81 (0.53 1.22) 70 + 1.00 0.46 (0.06 3.24) 1.82 (1.48 2.24) 0.81 (0.51 1.29) a References group. b Frequencies. c Deaths or injury per 1000 crashes. risk of car crash injury for 25 29-year-old drivers who used a hand-held phone was estimated to be 2.4 times higher than those not being distracted (RR = 2.37, 95% CI 1.31 4.27). Contrary to the hand-held phone, other in-vehicle distractions increased the risk of crash injury for drivers of nearly all age groups, except 40 49-year-olds (Table 2). As depicted in Fig. 1, the relative risks of inside vehicle distraction-related fatality and injury increased generally as the age of drivers increased from the 20 24 age group (aside from

416 L.T. Lam / Journal of Safety Research 33 (2002) 411 419 Fig. 1. Relative risk of inside vehicle distraction-related car crash fatality and injury by age group. the 40 49 age group). In fact, this particular age group seemed to be less susceptible to any type of distraction, both inside and outside the vehicle. 4. Discussion This study investigated the association between distraction while driving and the risk of car crash fatality and injury, with a special focus on the age of drivers. Distraction, as defined in this study, covers a wide range of activities, situations, and circumstances that a driver may be exposed to while performing a driving task. Some distractions are initiated by the driver, and others are acute situations that demand a quick response from the driver. Most in-vehicle distractions belong to the former, whereas all outside vehicle distractions are of the latter. The reason for the separated consideration of hand-held phone use is two-fold. First, the police have collected specific information on phone use during crashes as separate data. Second, and more importantly, are the legislative and preventive uses of the results obtained. While there is a growing body of literature suggesting that in-vehicle distraction, in particular cellular phone use, is a significant risk factor of car crash injury and non-casualty collision, the results in the study indicated that age is also an important factor to be considered in such relation. This result is consistent with that obtained by Violanti (1997, 1998) who used police report data similar to this study. The significant interactive effect of the age variable and in-vehicle distractions on the outcome, as reported by Violanti (1998), is further demonstrated in this study. Differential risk estimates have been obtained for the association between in-vehicle distraction and crash fatality and injury across different age

L.T. Lam / Journal of Safety Research 33 (2002) 411 419 417 groups (Table 2). Moreover, it is also shown that a significant increase in the risk of crash injury due to hand-held phone usage occurred only to 24 29-year-old drivers. The results of this study provided supportive evidence to the findings of previous studies indicating that the ability to share attention between tasks performed while driving tends to decrease as age increases (McKnight & McKnight, 1993). This is probably because as drivers are distracted there is an increase in the load of their cognitive functioning and processing speed. As reported by Lamble et al. (1999) an increase in cognitive load impairs the ability of drivers to detect changes in the environment, thus increasing the chance of collision. Research in the area of cognitive psychology has provided evidence that age is an important factor in the development of mental capacity, which allows an individual to have better cognitive functioning (Kail & Salthous, 1994). There seems to be a developmental relationship between cognitive maturation and age where younger people require time to grow to full maturation, which then deteriorates in older age; if this was plotted as cognitive ability against ages, an inverted U-shape curve would be obtained. This, to a certain degree, corresponds to the general decreased and then increased relative risk of in-vehicle distraction-related crash fatality and injury as age increased (Fig. 1). The insignificant results obtained on the outside vehicle distractions across all ages does not necessarily mean that outside vehicle distractions have less effect on accident likelihood. It may be because outside vehicle distractions have been under reported by the police; self-generated internal distractions are easily identified as inattention-due-todistraction, whereas responding to stimuli outside the vehicle can be considered as part of the normal driving tasks and would less likely be identified as inattention. Although it is not the main focus of this report, it is worth noting the significant increase in the risk of crash injury due to the use of a hand-held phone while driving for the 25 29 age group, but not for other ages. This age difference in the relative risks of crash fatality and injury has not been reported before. The reason for such a phenomenon may be related to the differential exposure of mobile phone usage in cars. Unfortunately, no detailed information on phone use while driving, such as the kind obtained by Redeleier and Tibshirani (1997) in their study, is available in NSW. The suggested reason remains an educated conjecture. The significance of the results obtained in this study is in their application to road safety. Drivers on the whole are affected by distractions inside the vehicle more than distractions coming from outside of the vehicle. In-vehicle distractions, apart from handheld phone usage, affect drivers of nearly all ages, although to different extents. As is shown, age of the driver has a significant effect in influencing the association between invehicle distractions and the risk of crash injury. Younger drivers, due to their developing cognitive capacity, may find it difficult to cope with distractions that add to the already heavy-loaded cognitive processing in handling the driving task. This also applies to older drivers where their deteriorating cognitive functioning, which has already been loaded with driving task, will further be jeopardized when being distracted. Distraction, unlike speeding or alcohol consumption, is a not totally self-initiated behavior that can easily be targeted in most of the road safety programs. There is no obvious single countermeasure to this problem. Safety education, such as media campaigns, that targets at increasing the awareness of the effect of distraction on the risk of car collision and injury would be

418 L.T. Lam / Journal of Safety Research 33 (2002) 411 419 helpful. This has been demonstrated in the area of drivers fatigue and road safety. In particular, drivers should be advised of useful strategies to handle some common invehicle distractions. For example, parents who are driving with young children who require urgent attention should be advised to slow down immediately and stop somewhere safe before attending their children. As for hand-held phone use, though there is a debate on whether safety education or legislative prohibition of in-vehicle usage is more effective in reducing the risk of crash injury (Redeleier & Tibshirani, 2001; Tsevat, 1999), it is unlikely that a single strategy would be sufficient to address such a problem. Further studies designed to investigate the effectiveness of both strategies are necessary in order to achieve an evidence-based policy-making decision. Some limitations have been identified in this study. Due to the design of the study and nature of data collected, this can only be considered as an exploratory study. Studies of this type serve the purpose of generating research hypothesis, but lack the ability for hypothesis testing. To achieve that, a cohort or case-control study design is warranted. There might also be biases involving reporting and information gathering. Data used in this study are based on all car crashes reported to the NSW police. Among these are crashes with drivers killed or injured, or incidents where the involved vehicle(s) was damaged and required towing. Minor crashes that did not require towing were not included, neither were cases with minimal injury that did not require hospital admission or presentation. Thus, the data represent the more severe end of total crashes experienced on the roads in NSW. Information bias is common in studies using routinely collected data. This happens mainly in the way that information is gathered. In this study, the information collected by the reporting police is largely based on circumstantial evidence gathered by police officers at scenes or reported by the passenger or witness. In cases of non-casualty crashes, information is mainly gathered by self-report of drivers. Another point worth noting is that non-casualty crashes are used for comparison in the calculation of risk estimates. This represents a group of drivers who are more at risk than any drivers in the population. The estimated risks could probably be higher, if a noncrash and noncasualty group was used for the comparison. References Alm, H., & Nilsson, L. (1994). Changes in driver behaviour as a function of handsfree mobile phones a simulator study. Accident Analysis and Prevention, 26, 441 451. Alm, H., & Nilsson, L. (1995). The effects of a mobile telephone task on driver behaviour in a car following situation. Accident Analysis and Prevention, 27, 707 715. Australian Bureau of Statistics. (1998). Population by Age and Sex Australian States and Territories. Report 3201.0. Canberra: Commonwealth Government. Australian Bureau of Statistics. (2000). Population by Age and Sex New South Wales. Report 3235.1 Canberra: Commonwealth Government. Brison, R. J. (1990). Risk of automobile accidents in cigarette smokers. Canadian Journal of Public Health, 81, 102 106. Brookhuis, K. A., De Vries, G., & De Waard, D. (1991). The effects of mobile telephoning on driving performance. Accident Analysis and Prevention, 23, 309 316. Chen, L., Baker, S. P., Braver, E. R., & Li, G. (2000). Carrying passengers as a risk factor for crashes fatal to 16- and 17-year old drivers. Journal of America Medical Association, 283, 1578 1582. Evans, L. (1991). Traffic safety and the driver. New York: Van Nostrand Reinhold.

L.T. Lam / Journal of Safety Research 33 (2002) 411 419 419 Evans, L. (1993). Comments on driver behavior and its role in traffic crashes. Alcohol, Drugs, and Driving, 9, 185 195. Goldstein, L. G. (1962). Human variables in traffic accidents: a digest of research and selected bibliography. Washington, DC: Highway Research Board. Irwin, M., Fitzgerald, C., & Berg, W. P. (2000). Effect of the intensity of wireless telephone conversation on reaction time in a breaking response. Perceptual and Motor Skills, 90, 1130 1134. Kail, R., & Salthous, T. A. (1994). Processing speed as a mental capacity. Acta Psychologia, 86, 199 225. Lamble, D., Kauranen, T., Laakso, M., & Summala, H. (1999). Cognitive load and detection thresholds in car following situations: safety implication for using mobile (cellular) telephones whole driving. Accident Analysis and Prevention, 31, 617 623. McGwin, G., & Brown, D. B. (1999). Characteristics of traffic crashes among young, middle-aged, and older drivers. Accident Analysis and Prevention, 31, 181 198. McKnight, A. J., & McKnight, A. S. (1993). The effect of cellular phone use upon driver attention. Accident Analysis and Prevention, 25, 259 265. Min, S. T., & Redelmeier, D. A. (1998). Car phone and car crashes: an ecologic analysis. Canadian Journal of Public Health, 89, 157 161. Murry, C. C., & Lopez, A. D. (1996). The global burden of disease (Vol. 1). Global burden of disease and injury series. Boston: Harvard School of Public Health. Murry, C. C., & Lopez, A. D. (1997). Global mortality, disability, and the contribution of risk factors: global burden of disease study. Lancet, 349, 1436 1442. NH & MRC (1999). Paradigm shift. Injury: from problem to solution. New research directions. Strategic. Canberra: Commonwealth of Australia. Norris, F. H., Matthews, B. A., & Riad, J. K. (2000). Characterological, situational, and behavioral risk factors for motor vehicle accidents: a prospective examination. Accident Analysis and Prevention, 32, 505 515. Parkes, A., & Hooijmeijer, V. (2000). The influence of the use of mobile phones on driver situation awareness. Available at: http://www-nrd.nhtsa.dot.gov/departments/nrd-13/driver-distraction/topics011000000.htm. Accessed 25th May 2001. Redeleier, D. A., & Tibshirani, R. J. (1997). Association between cellular-telephone calls and motor vehicle collisions. The New England Journal of Medicine, 336, 453 458. Redeleier, D. A., & Tibshirani, R. J. (2001). Car phones and car crashes: some popular misconceptions. Canadian Medical Association Journal, 164, 1581 1582. Rothman, K. J., & Greenland, S. (1998). Modern epidemiology. (2nd ed.). Philadelphia, PA: Lipponcott Williams & Wilkins. Treat, J. R., Tumbas, N. S., McDonald, S. T., et al. (1977). Tri-level study of the causes of traffic accidents. Final report on U.S. Department of Transportation Contract. Indiana University, Institute for Research in Public Safety. Washington, DC: Government Printing Office. Tsevat, J. (1999). Calling while driving: laws, economics, and commandments. Medical Decision Making, 19 (Jan Mar). Violanti, J. M. (1997). Cellular phone and traffic accidents. Public Health, 111, 423 428. Violanti, J. M. (1998). Cellular phones and fatal traffic collisions. Accident Analysis and Prevention, 30, 519 524. Violanti, J. M., & Marshall, J. R. (1996). Cellular phones and traffic accidents: an epidemiological approach. Accident Analysis and Prevention, 28, 265 270. Webster s revised unabridged dictionary. (1998). MICRA. Lawrence Lam is an epidemiologist working at the Royal Alexandra Hospital for Children, Sydney, Australia. His primary research interests are in injury, trauma, and emergency medicine in children and adolescents.