ORIGINAL ARTICLE

Injuries to 15–19-year olds in road traffic crashes: a crosssectional analysis of police crash data

Jamie R. V. Thomas & Sarah J. Jones

Received: 4 November 2013 /Accepted: 12 March 2014 /Published online: 4 April 2014# Springer-Verlag Berlin Heidelberg 2014

AbstractAim To describe the circumstances in which 15–19-year-oldvehicle occupants are injured in road traffic crashes, comparedwith older casualties.Subjects and methods Regression analysis of UK STATS19police road traffic casualty data from 2008–2010. Odds ratiosused to compare circumstances between 15 to 19 and 25 to 59-year-old passenger and driver casualty groups.Results Amongst 15–19-year olds, there were 27,552 carpassenger casualties and 28,322 car driver casualties. 15–19-year olds were at greatest risk of being injured as passengerswhen being driven by a 17–19-year old (adjusted OR 25.4,95 %CI 23.95–26.91) or between 9 pm and 5.59 am (adjustedOR 1.9, 95 %CI 1.83–2.01). Motorway driving was associat-ed with a significantly reduced risk (adjusted OR 0.55,95 %CI 0.49–0.61).

For driver casualties, 15–19 year olds were at greatest riskwhen carrying a 15–19-year-old passenger (adjusted OR 12.1,95 %CI 11.55–12.70) and between 9 pm and 5.59 am (adjustedOR 2.3, 9 %CI 2.22–2.39). Motorway travel again saw a signif-icantly reduced risk (adjusted OR 0.37, 95 %CI 0.34–0.41).Conclusion The main risk factors for road traffic injury to 15–19-year olds are travelling with occupants of a similar age orbetween 9 pm and 5.59 am. Other countries have implementedan intervention, graduated driver licensing (GDL), to tackleprecisely these risk factors. The UK Government needs toreview the case for GDL as a matter of urgency.

Keywords Youngpeople . Road traffic crash risk . Graduateddriver licensing

Introduction

Amongst 15–19-year olds in the UK, road traffic injuries arethe leading cause of mortality accounting for a quarter of allfatalities (ONS 2011; DfT 2011). The risk factors for adoles-cent road traffic casualties in the UK are not clear, althoughseveral risk factors for adolescent road traffic crashes (RTCs)have been identified internationally. RTCs can injure all roadusers, but of key concern in this age group are the risks topassengers and drivers.

Newly qualified young drivers are at high risk of crashing.In the UK, where the age at which learning can begin is 17,17–20-year-old male driver fatalities are 20 times higher thanthose of 50–59-year olds (Mindell and Leslie 2012). Forfemale drivers, 17–20-year-old rates were 11 times those of30–39 year olds (Mindell and Leslie 2012). In terms of hos-pital admissions, male 17–20-year-old rates were 13.7 times50–59 year olds, with females 6.6 times higher than 40–49 year olds (Mindell and Leslie 2012). These findings areneither new, nor specific to the UK. Twisk and Stacey (2007)found that in the Netherlands, self reported RTC rates of 18-year olds were 12 times higher than 45-year olds. Chen et al.(2000) showed that the US fatal RTC rate per million miles for16-year-old drivers was seven times 30–59-year-old drivers.Also in the USA, 16–19-year-old drivers are involved in twiceas many RTCs as drivers in their early 20s, but four timesmore than drivers aged 40–44 years (Williams 1999). Driversaged under 20 are also 12 times more likely to have caused afatal RTC than been innocently involved (Clarke et al. 2010).

This RTC risk is influenced by a number of key factors;teenaged passengers have been well documented to increaserisk, with 16 and 17-year-old drivers carrying similar aged

J. R. V. ThomasCardiff University, Cardiff, UK

S. J. Jones (*)Environmental Health Protection, Public Health Wales and CardiffUniversity, Temple of Peace and Health, King Edward VII Avenue,Cathays Park, Cardiff CF10 3NW, UKe-mail: jonessj3@cf.ac.uk

J Public Health (2014) 22:245–255DOI 10.1007/s10389-014-0617-8

passengers having an RTC risk five times that of 30–59 yearolds (Chen et al. 2000; Buckley and Foss 2012). Amongst 18to 19 year drivers, the risk was 3 times that of 30–59 year oldsand young male passengers were found to increase risk morethan young female passengers (Buckley and Foss 2012). It hasalso been shown that 67–85 % of teens are killed in vehiclesbeing driven by other teens (Williams and Well 1995;Cvijanovich et al. 2001). Night-time driving is also associatedwith increased risk (Williams and Preusser 1997; Lam et al.2003; Mayhew et al. 2003), as is driving after consuming anyalcohol (Peck et al. 2008; Bingham et al. 2009; Williams et al.2012). It is also suggested that rural roads are more dangerousthan urban roads (Clarke et al. 2010), whilst policy makers inthe UK often call for learner drivers to receive more tuition onmotorways.

Given the lack of information on the circumstances inwhich 15–19-year olds are casualties in RTCs in the UK, thisstudy aims to analyse police casualty data to understand moreabout these factors, as in Cvijanovich et al. (2001) in Utah.This information will inform the debate on how to deal withthe burden of RTCs amongst young people in the UK andsupport the identification of interventions with which to ad-dress this problem.

Methods

STATS19 police RTC data from 2008–2010 were obtainedfrom the UK Data Archive (UK Data Archive). STATS19details the circumstances of injury RTCs in England,Scotland and Wales and consists of an accident record (1 perRTC), vehicle record (1 per vehicle involved in the RTC) andcasualty record (1 per casualty in the RTC; DfT 2004). Thecasualty record was the basis for these analyses.

Driver and passenger casualties aged 15–19 years werecompared with 25–59-year olds (Williams et al. 2010). Datafor other age groups, including under 15 year olds and 60 plusyear olds, were removed from the dataset and not included inthese analyses. This comparison is consistent with approachesused previously. The 15–19-year olds were the key group ofinterest because of their high morbidity and mortality rates;RTCs are the leading cause of death amongst 15–24-year olds.

Drivers were grouped to age 17–19 (young driver, YD) andover 20 (older driver, OD; Chen et al. 2006; Jones et al. 2012).The casualty dataset was reduced to casualties injured in carsonly.

The dataset was reduced to the variables casualty class (driver,passenger), casualty sex (male, female), and casualty severity(fatal, serious or slight). The accident variables included wereyear of RTC (2008, 2009, 2010), country in which RTC oc-curred, day of week, month, road class (including motorway, A,B, C), speed limit, light conditions (daylight or darkness), weath-er (fine, rain, other), road surface conditions (dry, damp, other),

urban or rural area, and deprivation fifth in which the RTCoccurred (based on the Index of Multiple Deprivation (IMD) inEngland, the Scottish IMD (SIMD) in Scotland and the WelshIMD (WIMD) in Wales). The accident record was also used todetermine whether the RTC occurred between 9 pm and 5.59 am(Lam et al. 2003); this time frame was selected after reviewinginternational data on young driver RTCs.

Analysis

Simple comparisons of the descriptive statistics were carriedout using difference in proportions (DiP) tests (Newcombe1998). The 15–19-year groups was compared with the 25–59-year group. Where there were only two variables in a field,DiP was only calculated for one of the variables. DiP was notcalculated for “not knowns”.

Multiple logistic regression was used to study the associa-tion between various environmental factors and casualty agefor passenger and driver casualties separately (Cvijanovichet al. 2001). For passengers, 15–19-year olds were comparedwith 25–59-year olds using the explanatory variables listed inthe previous in univariate and multivariate models analysedusing SPSS 16.0. For driver casualties, the presence of anypassenger casualties in the driver’s vehicle was also includedin the analysis, with passengers classified as “present and aged15–19”, “present and not aged 15–19” and “not present”.STATS19 only records casualties, rather than individuals in-volved in RTCs, therefore, other un-injured passengers ordrivers may have been involved in the RTC.

Results

Descriptive analysis

Between 2008 and 2010, 27,552 15–19-year olds were injuredas passengers on UK roads, with a further 28,322 injured asdrivers (Tables 1 and 2). In the 25–59-year casualty group,there were 174,431 drivers and 45,990 passengers.Comparedwith car occupants of all ages, 15–19-year olds account for13.5 % of casualties (Table 3), but just 6.3 % of the UKpopulation (ONS 2011).

Of the passenger casualties, significantly more 15–19-yearolds were male (45.7 % vs. 36.7 %, DiP 9.0 %, 8.2–9.7 %)compared with 25–59-year olds. A similar finding, also signif-icant, was seen for driver casualties (DiP 6.1 %, 95 %CI 5.5–6.8 %). Of the driver casualties, significantly more 15–19-yearolds were carrying a passenger when injured (DiP 15–19 vs.25–59-year-old drivers, any passenger, 14.5 %, 95 %CI 13.9–15.0 %). Passengers and drivers aged 15–19 were significantlymore likely to be injured between 9 pm and 5.59 am than thoseaged 25–59 (passengers, DiP 19.2 %, 95 %CI 18.5–19.8 %);drivers; DiP 15.3 %, 95 %CI 14.7–15.8 %).

246 J Public Health (2014) 22:245–255

Table 1 Drivers: casualty age by crash circumstances and outcomes

15–19 years 25–59 years Difference in proportions(95 %CI)

Sex n % n %

Male 16,500 58.3 % 90,931 52.1 % 6.1 %a

(5.5–6.8 %)a

Female 11,820 41.7 % 83,466 47.9 % -

Not known 2 0.0 % 34 0.0 % -

Total 28,322a 100.0 %a 174,431a 100.0 %a -

Severity n % n %

Fatal 268 0.9 % 1,020 0.6 % 2.30 %a

Serious 2,255 8.0 % 10,467 6.0 % (2.0–2.7 %)a

Slight 25,799 91.1 % 162,944 93.4 % -

Country n % n %

England 24,507 86.5 % 154,352 88.5 % −2.0 % (−2.4 to −1.5 %)a

Scotland 1,966 6.9 % 11,374 6.5 % 0.4 % (0.1–0.7 %)a

Wales 1,849 6.5 % 8,705 5.0 % 1.5 % (1.2–1.9 %)a

Passenger n % n %

15–19 year passenger 6,022 21.3 % 3,265 1.9 % 14.50 %a

(13.9–15.0 %)a

Other age passenger 2,139 7.6 % 21,782 12.5 % (any passenger)

No passenger 20,161 71.2 % 149,384 85.6 % -

Time of day n % n %

9 pm to 5.59 am 7,677 27.1 % 20,648 11.8 % 15.30 %a

(14.7–15.8 %)a

6 am to 8.59 pm 20,645 72.9 % 153,783 88.2 % -

Day of week n % n %

Thursday to Saturday 12,670 44.7 % 77,227 44.3 % 4.6 % (−0.2–1.1 %)

Sunday to Wednesday 15,652 55.3 % 97,204 55.7 % -

Month n % n %

Jan to Mar 7,043 24.9 % 43,810 25.1 % −0.3 % (−0.8–0.3 %)

Apr to June 7,018 24.8 % 41,098 23.6 % 1.2 % (0.7–1.8 %)a

July to Sept 6,861 24.2 % 42,113 24.1 % 0.1 % (−0.5–0.6 %)

Oct to Dec 7,400 26.1 % 47,410 27.2 % −1.1 % (−1.6 to −0.5 %)a

Road class n % n %

Mway 842 3.0 % 11,864 6.8 % −3.8 % (−4.0 to −3.6 %)a

A (M) 82 0.3 % 869 0.5 % −0.2 % ( −0.3 to −0.1 %)a

A 11,922 42.1 % 85,644 49.1 % −7.0 % (−7.6 to −6.4 %)a

B 4,590 16.2 % 22,184 12.7 % 3.5 % (3.0–4.0 %)a

C 3,190 11.3 % 15,099 8.7 % 2.6 % (2.2–3.0 %)a

Unclassified 7,696 27.2 % 38,771 22.2 % 5.0 % (4.4–5.5 %)a

Speed limit n % n %

20 104 0.4 % 693 0.4 % 0.0 % (−0.1–0.1 %)

30 13,383 47.3 % 89,971 51.6 % −4.3 % (−5.0 to −3.7 %)a

40 2,940 10.4 % 18,089 10.4 % 0.0 % (−0.3–0.3 %)

50 1,194 4.2 % 7,991 4.6 % −0.4 % (−0.6 to −0.1 %)a

60 8,662 30.6 % 36,697 21.0 % 9.6 % (9.0–10.1 %)a

70 2,037 7.2 % 20,989 12.0 % −4.8 % (−5.2 to −4.5 %)a

Not known 2 0.0 % 1 0.0 % -

Light n % n %

Darkness 4,778 16.9 % 14,688 8.4 % 8.50 %a

(8.0–8.9 %)a

Daylight 23,544 83.1 % 159,743 91.6 %

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In most areas of injury prevention, injuries amongst themost deprived people and in the most deprived areas areconsiderably higher than the least deprived. Based on areasin which RTCs occurred, 15–19-year-old casualties show thereverse trend, with a smaller proportion in the most deprivedareas (Fig. 1).

In terms of outcomes, significantly higher proportions of 15–19-year olds suffered either fatal or serious injuries (9.7 % pas-sengers vs. 7.0 % for 25–59 year olds, DiP 9.2 %, 95 %CI 8.8–9.6 %; 8.9 % drivers vs. 6.6 %, DiP 2.3 %, 95 %CI 2.0–2.7 %).

Regression analysis: passengers

Univariate regression analysis of the passenger casualtiesfound that there were significant variations in risk of RTCbetween 15–19-year olds and 25–59-year olds for all of thevariables (Table 4). The most notable crude finding was thatpassengers aged 15–19 were at 30.14 times (95 %CI 28.48–31.90, p<.001) higher risk of injury than 25–59 year oldswhen driven by a YD compared with an OD. In the adjustedmodel, this dropped to 25.38 (95 %CI 23.95–26.91, p<.001).Night time was also high risk for 15–19-year-old passengers,with their risk of injury 92% higher than 25–59 year olds (OR1.92, 95 %CI 1.83–2.01, p<.001). Protective factors werebeing in England (OR 0.89, 95 %CI 0.82–.96, p=0.004) orScotland (OR 0.82, 95 %CI 0.74–0.91, p<.001) compared to

Wales and travelling on a motorway (OR 0.55, 95 %CI 0.49–0.61, p<.001), A(M) (OR 0.47, 95 %CI 0.34–0.64, p<.001),or A road (OR 0.73, 95 %CI 0.69–0.77, p<.001) compared toan unclassified road.The adjusted analysis also showed thatdeprivation was protective, with 16 % fewer casualties in themost deprived areas (OR 0.84, 95 %CI 0.78–0.89, p<.001).

Regression analysis: drivers

The outcomes of both the crude and adjusted analyses ofdriver casualties were broadly similar to those of the passengercasualties (Table 5). Driver casualties amongst 15–19-yearolds were 12.11 times more likely (95 %CI 11.55–12.70,p<.001) than 25 –59-year olds when carrying teenaged pas-sengers. Driving between 9 pm and 5.59 am was associatedwith an increased risk of 2.30 times for 15–19-year-old drivers(95 %CI 2.22–2.39, p<.001). Protective factors were, again,driving in England or Scotland, driving on a motorway anddriving in more deprived areas.

Discussion

Young people aged 15–19 years are at a disproportionatelyhigh risk of being injured in a car and this risk is increasedsignificantly when travelling with another young person or

Table 1 (continued)

15–19 years 25–59 years Difference in proportions(95 %CI)

Urban or rural n % n %

Urban 12,832 45.3 % 92,492 53.0 % −7.7 % (−8.3 to −7.1 %)a

Rural 15,240 53.8 % 80,191 46.0 % -

Not known 250 0.9 % 1,748 1.0 %

Crash IMD n % n %

Most deprived 3,910 13.8 % 33,698 19.3 % −5.5 % (−6.0 to −5.1 %)a

Next most deprived 4,516 15.9 % 31,227 17.9 % −2.0 % (−2.4 to −1.5 %)a

Median 6,668 23.5 % 37,976 21.8 % 1.8 % (1.2–2.3 %)a

Next least deprived 7,631 26.9 % 41,380 23.7 % 3.2 % (2.7–3.8 %)a

Least deprived 5,304 18.7 % 28,134 16.1 % 2.6 % (2.1–3.1 %)a

Not known 293 1.0 % 2,016 1.2 %

Weather n % n %

Rain 5,075 17.9 % 26,533 15.2 % 2.7 % (2.2–3.2 %)a

Other 1,645 5.8 % 10,060 5.8 % -

Fine 21,124 74.6 % 134,505 77.1 % −2.5 % (−3.1 to −2.0 %)a

Not known 478 1.7 % 3,333 1.9 % -

Road surface n % n %

Wet/damp 10,880 38.4 % 55,518 31.8 % 6.6 % (6.0–7.2 %)a

Other 1,571 5.5 % 11,325 6.5 % -

Dry 15,841 55.9 % 107,445 61.6 % −5.7 % (−6.3 to −5.0 %)a

Not known 30 0.1 % 143 0.1 % -

aDenotes significant differences

248 J Public Health (2014) 22:245–255

Table 2 Passengers: casualty age by crash circumstances and outcomes

15–19 years 25–59 years Difference in proportions(95 %CI)

Sex n % n %

Male 12,593 45.7 % 16,896 36.7 % 9.00 %a

(8.2–9.7 %)a

Female 14,952 54.3 % 29,077 63.2 % -

Not known 7 0.0 % 17 0.0 % -

Total 27,552a 100.0 %a 45,990a 100.0 %a

Severity n % n %

Fatal 278 1.0 % 257 0.6 % 2.80 %a

Serious 2,408 8.7 % 2,923 6.4 % (2.4–3.3 %)a

Slight 24,866 90.3 % 42,810 93.1 % -

Country n % n %

England 23,696 86.0 % 40,200 87.4 % −1.4 % (−1.9 to −0.9 %)a

Scotland 1,979 7.2 % 3,291 7.2 % 0.0 % (−0.4–0.4 %)a

Wales 1,877 6.8 % 2,499 5.4 % 1.4 % (1.0–1.7 %)a

Driver n % n %

Young driver 13,873 50.4 % 1,497 3.3 % 4.70 %a

4.6–4.8 %a

Older driver 13,679 49.6 % 44,493 96.7 % -

Time of day n % n %

9 pm to 5.59 am 9,832 35.7 % 7,605 16.5 % 19.2 %a

(18.5–19.8 %)a

6 am to 8.59 pm 17,720 64.3 % 38,385 83.5 % -

Day of week n % n %

Thursday to Saturday 12,568 45.6 % 21,354 46.4 % −0.9 % (−1.6 to −0.1 %)a

Sunday to Wednesday 14,984 54.4 % 24,636 53.6 % -

Month n % n %

Jan to Mar 6,473 23.5 % 10,635 23.1 % 0.4 % (−0.3–1.0 %)

Apr to June 6,929 25.1 % 11,130 24.2 % 1.0 % (0.3–1.6 %)a

July to Sept 7,045 25.6 % 11,856 25.8 % 1.5 % (0.9–2.2 %)a

Oct to Dec 7,105 25.8 % 12,369 26.9 % −1.1 % (−1.8 to −0.5 %)a

Road class n % n %

Mway 1,150 4.2 % 3,982 8.7 % −4.5 % (−4.8 to −4.1 %)a

A (M) 70 0.3 % 260 0.6 % −0.3 % (−0.4 to −0.2 %)a

A 11,669 42.4 % 23,109 50.2 % −7.9 % (−8.6 to −7.2 %)a

B 4,207 15.3 % 5,328 11.6 % 3.6 % (3.1–4.1 %)a

C 2,922 10.6 % 3,475 7.6 % 3.1 % (2.6–3.5 %)a

Unclassified 7,534 27.3 % 9,836 21.4 % 6.0 % (5.3–6.6 %)a

Speed limit n % n %

20 115 0.4 % 200 0.4 % 0.0 % (−0.1–0.1 %)

30 13,325 48.4 % 23,363 50.8 % −2.4 % (−3.2 to −1.7 %)a

40 2,872 10.4 % 4,731 10.3 % 0.1 % (−0.3–0.6 %)

50 1,118 4.1 % 2,090 4.5 % −0.5 % (−0.8 to −0.2 %)a

60 7,786 28.3 % 9,147 19.9 % 8.4 % (7.7–9.0 %)a

70 2,335 8.5 % 6,459 14.0 % −5.6 % (−6.0 to −5.1 %)a

99999 1 0.0 % -

Light n % n %

Darkness 5,326 19.3 % 4,041 8.8 % 10.50 %a

(10.0–11.1 %)a

Daylight 22,226 80.7 % 41,949 91.2 % -

Urban or rural n % n %

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late at night. There were also a number of other significant riskfactors for RTC, including road type, speed and weatherconditions.

The identification of these risk factors is not unexpected.The findings are consistent with many previous internationalanalyses of risk factors for RTCs involving young people(Chen et al. 2000; Williams and Wells 1995; Cvijanovichet al. 2001; Lam et al. 2003; Williams 2003). The results ofthese analyses have contributed to the development and im-plementation of Graduated Driver Licensing (GDL) schemesin New Zealand, Australia, the USA and Canada (Russellet al. 2011). GDL aims to reduce high RTC and casualty ratesamongst young people by limiting exposure of young driversto the high-risk driving conditions identified by these analy-ses; travelling with another young person, travelling late atnight, and driving having consumed any alcohol. The differentlegislative contexts in which these programmes operate meanthat an overall estimate of effect is impossible, but Cochrane

reviews have shown that GDL has only positive effects andthat the size of this effect is up to 60 % reduction in RTC andcasualty rates (Russell et al. 2011).

The findings of this study would therefore appear to pro-vide further support for the introduction of GDL in the UK.However, there are limitations to these analyses.

Limitations

Most notably in relation to GDL schemes implemented else-where, these analyses were unable to account for the contri-bution of alcohol to RTC risk. STATS19 data were used forthe analyses, but only aggregate data on breath tests is rou-tinely reported and the driver level data were not availablethrough the Data Archive. However, it is well documentedthat young drivers are more susceptible to the presence ofalcohol in their systems than older drivers (Twisk and Stacey2007; Peck et al. 2008; Bingham et al. 2009), therefore of

Table 2 (continued)

15–19 years 25–59 years Difference in proportions(95 %CI)

Urban 12,973 47.1 % 24,419 53.1 % 16.0 % (15.2–16.7 %)

Rural 14,314 52.0 % 21,031 45.7 % -

Not known 265 1.0 % 540 1.2 % -

Crash IMD n % n %

Most deprived 4,624 16.8 % 10,128 22.0 % −5.2 % (−5.8 to −4.7 %)a

Next most deprived 4,695 17.0 % 8,477 18.4 % −1.3 % (−1.9 to −0.8 %)a

Median 6,352 23.1 % 9,954 21.6 % 1.4 % (0.8–2.0 %)a

Next least deprived 6,833 24.8 % 10,453 22.7 % 2.1 % (1.4–2.7 %)a

Least deprived 4,722 17.1 % 6,377 13.9 % 3.3 % (2.7–3.8 %)a

Not known 326 1.2 % 601 1.3 % -

Weather n % n %

Rain 4,827 17.5 % 6,920 15.0 % 2.5 % (1.9–3.0 %)a

Other 1,558 5.7 % 2,499 5.4 % 0.2 % (−0.1–0.6 %)

Fine 20,777 75.4 % 35,756 77.7 % −2.3 % (−3.0 to −1.7 %)a

Not known 390 1.4 % 815 1.8 %

Road surface n % n %

Wet/damp 10,308 37.4 % 14,291 31.1 % 6.3 % (5.6–7.1 %)a

Other 1,526 5.5 % 2,684 5.8 % −0.3 % (−0.6–0.1 %)

Dry 15,696 57.0 % 28,972 63.0 % −6.0 % (−6.8 to −5.3 %)a

Not known 22 0.1 % 43 0.1 %

aDenotes significant differences

Table 3 Car occupant casualtytype; all ages and 15–19-year olds All ages All ages (car travel) 15–19 years (car travel) %

Driver 415,812 281,897 28,322 10.0 %

Passenger 164,673 132,571 27,552 20.8 %

All 580,485 414,468 55,874 13.5 %

250 J Public Health (2014) 22:245–255

more value in understanding RTC risk would be actual breathalcohol content, rather than just a positive or negative breathtest result.

STATS19 data are the primary source of UK road casualtydata and should include all RTCs on public highways andresulting in death or personal injury (DfT 2004). However,STATS19 is known to underreport casualties; in one study,45 % of hospital admissions following an RTC were notrecorded by STATS19 (Jeffrey et al. 2009). What is not clearis whether injuries to either of the age groups in this study areaccurately reported or suffer under or over reporting. If theyare, this could have significant implications for theconclusions.

In addition, STATS19 documents RTCs, not exposure torisk—i.e. distances or time travelled. Although the NationalTravel Survey (DfT 2013) is carried out annually, there is alack of comprehensive information on distances travelled bypeople of different ages as car drivers and car occupants.Research suggests that young people travel fewer miles thanolder people, travel less often and do so for leisure; furtherinflating their already high RTC risk (Twisk and Stacey 2007;Ward et al. 2007; Kweon and Kockelman 2003) and it isdifficult to see how such data could be collected on a routinebasis to support analyses such as these. This meant thatadjusting for different behaviours by drivers of different agesin terms of, for example, miles driven at night or on motor-ways, was not possible. Such a lack of exposure data is notuncommon in the injury prevention literature and is acknowl-edged by researchers throughout the discipline as an issue.However, the collection of the data on the injuries themselvesis exceptionally difficult and time consuming. Much work ison-going to try to address these issues.

Associated with this are problems with adequately express-ing how risk varies with passenger age. STATS19 only carriesinformation on passengers who are injured in crashes; there is

no information on uninjured passengers. As stated above, wealso lack adequate exposure data for passengers and driversof all ages. It is therefore possible that these findings inrelation to teenaged passengers are just the consequence ofdifferences in exposure; teen drivers are more likely tocarry teen passengers, older drivers are more likely to carrypassengers of a similar age. As stated above, it is difficultto see how this issue can be resolved in a truly satisfactorymanner.

In terms of the deprivation profiles, the data are limited inthat there is no denominator available and the findings mayjust be a reflection of trends in car ownership. In addition, thedata are merely indicative of where an RTC occurred, ratherthanwhere the car occupants live; such data were not availablefor these analyses. The analyses also show that RTC risk isincreased on 60 mph roads and that urban areas are ‘protec-tive’ against RTCs. Young drivers are known to drive forleisure purposes and seek out roads on which to test theirdriving skills (Clarke et al. 2010). Such roads are more likelyto be found in less deprived areas. This finding should there-fore be considered only in the entire context of the driver,passengers and driving environment.

That roads with higher speed limits are associated withincreased risk, but motorways are protective may seemcounter-intuitive; but there are a number of good reasons forthis finding. Motorways, particularly in the UK, are very safe.Traffic travels only in one direction (dual carriageway withrobust central reservation) and at similar speeds. There are nopedestrians or cyclists and the junctions are very wide andclearly marked. They are very ‘tolerant’ of errors. In addition,young drivers are believed to have low levels of exposure tomotorway travel. However, there are a group of roads, typi-cally in the UK labelled as A-roads, on which the speed limitis 60 mph. These are often single carriageway roads in rural orsemi rural areas. They are characterised by tight or blindbends, a range of different types of traffic, including horsesand tractors and are rarely lit at night. They appeal to youngdrivers as a place to “test” their driving skills. For thesereasons, the greater risk associated with the higher speed limitis mainly linked to these 60 mph or A-roads, rather thanmotorways.

It would also have been useful to be able to assess thecontribution of distractions including loud music and mobiletelephone use to RTCs. However, these analyses used routine-ly collected data which does not cover these types of contrib-utory factors.

It may also be argued that assessment of regional or urban:rural variations in RTCs may have been of value. However,given that the intervention for which there is strongest andmost consistent evidence of effect is the legislative approachthat is GDL, and that this would need to be applieduniversally, it is difficult to see that this would be ofuse to policy makers.

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ed

Leas

t dep

rived

Not

kno

wn

Mos

t dep

rived

Nex

t mos

t dep

rived

Med

ian

Nex

t lea

st d

epriv

ed

Leas

t dep

rived

Not

kno

wn

15 to 19 years 25 to 59 years

Passenger Driver

Fig. 1 Distribution of crashes by deprivation fifth

J Public Health (2014) 22:245–255 251

Table 4 Outcomes of regression modelling; crude and adjusted, for passenger casualties

Univariate/crude Multivariate/adjusted

Passengers OR 95 % CI for OR Sig. OR 95 % CI for OR Sig.

Lower Upper Lower Upper

2008 1.18a 1.13a 1.22a <.001a 1.07a 1.02a 1.12a .004a

2009 1.14a 1.10a 1.19a <.001a 1.05a 1.00a 1.10a .035a

2010 Ref

Male 1.45a 1.41a 1.49a <.001a 1.07a 1.03a 1.11a .001a

Female Ref

Fatal 1.86a 1.57a 2.21a <.001a

Serious 1.42a 1.34a 1.50a <.001a

Slight Ref

England 0.78a 0.74a 0.83a <.001a 0.89a 0.82a 0.96a .004a

Scotland 0.80a 0.74a 0.87a <.001a 0.82a 0.74a 0.91a <.001a

Wales Ref

Young driver 30.14a 28.48a 31.90a <.001a 25.38a 23.95a 26.91a <.001a

Older driver Ref

9 pm to 5.59 am 2.80a 2.70a 2.90a <.001a 1.92a 1.83a 2.01a <.001a

6 am to 8.59 pm Ref

Thursday to Saturday 0.97a 0.94a 1.00a .032a 0.98 0.94 1.02 .244

Sunday to Wednesday Ref

January to March 1.06a 1.02a 1.11a .008a 1.01 0.95 1.06 .827

April to June 1.08a 1.04a 1.13a <.001a 1.06a 1.00a 1.12a .042a

July to September 1.03 0.99 1.08 .109 1.08a 1.02a 1.14a .005a

October to December Ref

Mway 0.38a 0.35a 0.41a <.001a 0.55a 0.49a 0.61a <.001a

A(M) 0.35a 0.27a 0.46a <.001a 0.47a 0.34a 0.64a <.001a

A 0.66a 0.64a 0.68a <.001a 0.73a 0.69a 0.77a <.001a

B 1.03 0.98 1.08 .237 0.99 0.93 1.06 .804

C 1.10a 1.04a 1.16a .002a 0.96 0.89 1.03 .278

Unclassified Ref

20 1.59a 1.26a 2.01a <.001a 1.13 0.84 1.51 .423

30 1.58a 1.50a 1.66a <.001a 1.10 1.00 1.21 .055

40 1.68a 1.57a 1.79a <.001a 1.15a 1.04a 1.27a .007a

50 1.48a 1.36a 1.61a <.001a 1.02 0.91 1.15 .716

60 2.35a 2.23a 2.49a <.001a 1.14a 1.04a 1.25a .005a

70 Ref

Darkness 2.49a 2.38a 2.60a <.001a 1.28a 1.20a 1.37a <.001a

Daylight Ref

Urban 0.78a 0.76a 0.80a <.001a 0.94a 0.89a 0.99a .029a

Rural Ref

Most deprived 0.62a 0.59a 0.65a <.001a 0.84a 0.78a 0.89a <.001a

Next most deprived 0.75a 0.71a 0.79a <.001a 0.89a 0.84a 0.95a .001a

Median 0.86a 0.82a 0.91a <.001a 0.94a 0.88a 1.00a .035a

Next least deprived 0.88a 0.84a 0.93a <.001a 0.91a 0.86a 0.97a .004a

Least deprived Ref

Rain 1.20a 1.15a 1.25a <.001a 1.01 0.95 1.08 .705

Other 1.07a 1.00a 1.15a .035a 0.94 0.86 1.04 .232

Fine Ref

Wet/damp 1.33a 1.29a 1.37a <.001a 1.15a 1.09a 1.22a <.001a

Other 1.05 0.98 1.12 .150 1.01 0.92 1.11 .864

Dry Ref

a Denotes significant differences

252 J Public Health (2014) 22:245–255

Table 5 Outcomes of regression modelling; crude and adjusted, for driver casualties

Univariate/crude Multivariate/adjusted

OR 95 % CI for OR Sig. OR 95 % CI for OR Sig.

Lower Upper Lower Upper

2008 1.21a 1.17a 1.25a <.001a 1.21a 1.17a 1.25a <.001a

2009 1.18a 1.15a 1.22a <.001a 1.19a 1.15a 1.23a <.001a

2010

Male 1.28a 1.25a 1.31a <.001a 1.13a 1.10a 1.16a <.001a

Female

Fatal 1.66a 1.45a 1.90a <.001a

Serious 1.36a 1.30a 1.43a <.001a

Slight

England 0.75a 0.71a 0.79a <.001a 0.83a 0.79a 0.88a <.001a

Scotland 0.81a 0.76a 0.87a <.001a 0.82a 0.76a 0.89a <.001a

Wales

9 pm to 5.59 am 2.77a 2.69a 2.85a <.001a 2.30a 2.22a 2.39a <.001as

6 am to 8.59 pm

Thursday to Saturday 1.02 0.99 1.04 .147 1.00 0.97 1.02 .773

Sunday to Wednesday

January to March 1.03 0.99 1.07 .099 1.05 1.01 1.10 .007

April to June 1.09a 1.06a 1.13a <.001a 1.15a 1.11a 1.20a <.001a

July to September 1.04a 1.01a 1.08a .018a 1.07a 1.03a 1.12a .001a

October to December

Mway 0.36a 0.33a 0.39a <.001a 0.37a 0.34a 0.41a <.001a

A(M) 0.48a 0.38a 0.60a <.001a 0.49a 0.39a 0.63a <.001a

A 0.70a 0.68a 0.72a <.001a 0.65a 0.62a 0.67a <.001a

B 1.04a 1.00a 1.09a .043a 0.89a 0.85a 0.93a <.001a

C 1.06a 1.02a 1.11a .007a 0.94a 0.89a 0.98a .010a

Unclassified

20 1.55a 1.25a 1.91a <.001a 1.15 0.91 1.46 .232

30 1.53a 1.46a 1.61a <.001a 1.15a 1.07a 1.24a <.001a

40 1.67a 1.58a 1.78a <.001a 1.27a 1.18a 1.37a <.001a

50 1.54a 1.43a 1.66a <.001a 1.17a 1.07a 1.28a <.001a

60 2.43a 2.31a 2.56a <.001a 1.41a 1.32a 1.51a <.001a

70

Darkness 2.21a 2.13a 2.29a <.001a 1.22a 1.17a 1.28a <.001a

Daylight

Urban 0.73a 0.71a 0.75a <.001a 0.85a 0.82a 0.89a <.001a

Rural

Most deprived 0.62a 0.59a 0.64a <.001a 0.69a 0.66a 0.73a <.001a

Next most deprived 0.77a 0.73a 0.80a <.001a 0.83a 0.79a 0.87a <.001a

Median 0.93a 0.90a 0.97a <.001a 0.93a 0.89a 0.97a <.001a

Next least deprived 0.98 0.94 1.02 .257 0.97 0.93 1.01 .204

Least deprived

Rain 1.22a 1.18a 1.26a <.001a 1.00 0.96 1.05 .841

Other 1.04 0.99 1.10 .144 1.01 0.94 1.08 .822

Fine

Wet/damp 1.33a 1.29a 1.36a <.001a 1.23a 1.18a 1.27a <.001a

Other 0.94a 0.89a 0.99a .031a 0.80a 0.74a 0.86a <.001a

Dry

Teen pass - Yes 13.67a 13.06a 14.30a <.001a 12.11a 11.55a 12.70a <.001a

Teen pass - No 0.73a 0.694a 0.762a <.001a 0.69a 0.66a 0.73a <.001a

No pass

a Denotes significant differences

J Public Health (2014) 22:245–255 253

Policy context

STATS19 data have previously been used to argue thatadopting GDL in the UK could reduce RTC, casualties andfatalities (Jones et al. 2012). To date, there has been littleenthusiasm for GDL amongst policy makers in the UK, buta Green Paper covering the safety of young people is dueautumn 2013. It is hoped that this paper will include morepositive reference to the possible implementation of GDL.

One of the key barriers cited by policy makers is that GDLwould undermine the driving test and its ability to producecompetent drivers (UK Parliament 2012). However, driving isa complex task; the driving test is a test of skills and whilstthese are necessary for proficiency, they are not an indicator ofability to drive safely, not least because experience is neededto learn when to apply the skills appropriately (Williams 1999;Beanland et al. 2012; Foss 2007).

It has also been suggested that the driving test would bemore effective if competency in driving in high-risk condi-tions such as at night or on a motorway was also tested.However, as these results show, motorway driving is saferthan any other road type for young drivers. Obviously, thismay be linked to miles driven, but the absence of pedestriansand the fact that all vehicles are travelling in the same directionat similar speeds make UK motorways relatively safe drivingenvironments. In addition, large sections of the UK populationlive many hours drive from a motorway, meaning that manypeople will never have reason to drive on a motorway and itwould be impractical to ever include such an element in thetest.

In terms of the night time risk, whilst it is clear that it exists,it is again difficult to see how test conditions could reasonablyreplicate the conditions a young driver finds themselves in.The presence of an adult passenger is a risk moderator (Riceet al. 2003) and driving a full car unsupervised is very differ-ent to the learning situation which is often in a small car withonly an instructor present.

The biggest obstacle for UK GDL may be that responsibil-ity for the implementation and enforcement of GDL fall to theDepartment for Transport and Home Office respectively, butthe benefits of GDL would be experienced by the Departmentof Health. Moreover, whilst Health is devolved in the UK,Transport is a centrally reserved power.

Conclusions

The main risk factors for road traffic injury to 15–19-year oldsare travelling with a similar aged passenger or driver andtravelling between 9 pm and 5:59 am. These are not newfindings; other countries have implemented GDL to tackleprecisely these risk factors. The UK Government needs toreview the case for GDL as a matter of urgency.

What is known about this topic

Young drivers and passengers are at high risk of RTC.Internationally, high-risk circumstances for young driversand passengers have been identified, but no analysis of UKdata has previously been carried out.

What this study adds

In the UK, young drivers and their passengers are at high riskof injury when travelling late at night or are in a car withanother young person. Although many policy makers call foryoung people to have more experience of motorway driving,these roads are associated with low risk of RTC.

Conflicts of interest We have no conflicts of interests to declare.

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