Sultan Qaboos University Med J, May 2015, Vol. 15, Iss. 2, pp. e191–201, Epub. 28 May 15
Submitted 1 Aug 14
Revision Req. 22 Sep 14; Revision Recd. 26 Nov 14
Accepted 18 Dec 14

1Centre for Accident Research & Road Safety–Queensland, Queensland University of Technology, Brisbane, Australia; 2Department of Occupational & 
Environmental Health, Directorate General of Disease Control, Ministry of Health, Muscat, Oman; 3Department of Epidemiology, College of Medicine & 
Health Sciences, Sultan Qaboos University; 4Department of Civil Engineering, College of Engineering, Sultan Qaboos University, Muscat, Oman
*Corresponding Author e-mail: jason.edwards@qut.edu.au

خصائص حوادث املركبات الثقيلة يف عمان
2009-2011

اإ�سالم البلو�سي، جي�سن اأدواردز، جريمي ديفي، كريي اأرم�سرتوجن، حمد الريي�سي، خالد ال�سام�سي

abstract: In recent years, Oman has seen a shift in the burden of diseases towards road accidents. The main 
objective of this paper, therefore, is to describe key characteristics of heavy vehicle crashes in Oman and identify 
the key driving behaviours that influence fatality risks. Crash data from January 2009 to December 2011 were 
examined and it was found that, of the 22,543 traffic accidents that occurred within this timeframe, 3,114 involved 
heavy vehicles. While the majority of these crashes were attributed to driver behaviours, a small proportion 
was attributed to other factors. The results of the study indicate that there is a need for a more thorough crash 
investigation process in Oman. Future research should explore the reporting processes used by the Royal Oman 
Police, cultural influences on heavy vehicle operations in Oman and improvements to the current licensing system. 

Keywords: Traffic Accidents; Accident Prevention; Automobile Driving; Safety; Oman.

امللخ�ص: يف ال�سنوات االأخرية، �سهدت عمان تغري يف اأعباء االأمرا�ض نحو حوادث الطرق. الهدف من هذة الورقة هو و�سف اخل�سائ�ض 
الرئي�سية حلوادث املركبات الثقيلة يف عمان وحتديد �سلوكيات القيادة التى توؤثر على خماطر الوفاة. ثم فح�ض بيانات احلوادث من يناير 
2009 اإىل دي�سمرب 2011 والتى اأظهرت وقوع 22,543 حادثًا على الطرق يف هذة الفرتة الزمنية �سمل منها 3,114 مركبات ثقيلة. على 
الرغم من اأن معظم هذة احلوادث كانت ب�سبب �سلوكيات القيادة، كانت هناك ن�سبة �سغرية ب�سبب عوامل اأخرى. اأظهرت نتائج هذة الدرا�سة 
اإىل اأنه هناك حاجة اإىل حتقيق �سامل للحوادث يف عمان. البحوث امل�ستقبلية يجب اأن تفح�ض عمليات اإعداد تقارير احلوادث امل�ستخدمة 

من قبل �رشطة عمان ال�سلطانية، والثاأثريات الثقافية لعمل املركبات الثقيلة يف عمان وحت�سني نظام تراخي�ض املركبات احلايل.
مفتاح الكلمات: حوادث الطرق؛ الوقاية من احلوادث؛ قيادة املركبات؛ ال�سالمة؛ عمان.

special contribution

Heavy Vehicle Crash Characteristics 
in Oman
2009–2011

Islam Al-Bulushi,1,2 *Jason Edwards,1 Jeremy Davey,1 Kerry Armstrong,1 Hamed Al-Reesi,3 Khalid Al-Shamsi4

Oman, along with other Gulf Cooperation Council (GCC) countries— the United Arab Emirates (UAE), Saudi 
Arabia (KSA), Kuwait, Bahrain and Qatar—has 
experienced substantial social and economic 
development as a result of the discovery of oil. 
With targeted effort from governing bodies, this 
development has contributed to a reduction in the 
burden of many life-threatening infectious diseases. 
As a result, the burden of disease has now shifted 
towards non-communicable diseases.1 In particular, 
the prevalence of road traffic injuries in Oman is 
very high; in 2007, road traffic injuries accounted 
for 73.3% of total hospital deaths due to external 
causes.2 Moreover, a significant number of those who 
sustain injuries as a result of traffic accidents live with 
pervasive and debilitating physical, emotional and 
behavioural impairments.3

Within the Arab world, Oman has one of the 
highest rates of road traffic fatalities.4 Between 
1985 and 2009, 13,722 men, women and children 
lost their lives in car crashes in Oman and 165,757 
were injured.5,6 In 2011, more than 7,700 road traffic 
crashes were recorded in Oman, averaging close to 
one crash every hour and one fatality every 10 hours.4 
Definitions of fatalities resulting from traffic crashes 
vary from country to country. Internationally, the 
World Health Organization (WHO) defines a road 
traffic fatality as a death occurring within 30 days of 
involvement in a traffic crash.7 However, in Oman, 
this definition is not applied as the Royal Oman Police 
(ROP) define road traffic fatalities as those in which 
death related to a crash occurs between the time of 
the crash and the closure of the case file in January 
of the next year;6 thus, it is difficult to determine the 
accuracy of a direct comparison with other countries 
using the WHO definition.



Heavy Vehicle Crash Characteristics in Oman 
2009-2011

e192 | SQU Medical Journal, May 2015, Volume 15, Issue 2

Recently, there has been a growing effort within 
Oman to reduce the impact of traffic incidents. A 
number of policy changes have been made, such as the 
introduction of seatbelt and mobile phone laws as well 
as fixed and mobile speed detection devices. However, 
significant effort is still required across a number of 
organisations, government departments and the wider 
population to stem the increasing number of road 
traffic accidents in Oman. 

One area which may require specific attention is 
that of heavy vehicle safety. As countries, including 
Oman, witness economic development, the use of 
heavy vehicles becomes crucial for the transportation 
of goods and with increased use comes an increase in 
the number of heavily vehicle crashes. In 2010, heavy 
vehicles represented 12.5% of registered vehicles 
in Oman.7 However, research from other countries 
suggests that mortality and morbidity as a result 
of heavy vehicle crashes are proportionally higher 
than their percentage of registrations.8 In Finland, 
between 1990 and 1997, heavy vehicles represented 
approximately 6% of registered vehicles yet accounted 
for 16% of crashes.8 Research to date has yet to explore 
heavy vehicle crashes within Oman. The purpose of 
the current research, therefore, was to analyse road 
traffic crash data pertaining to heavy vehicles in Oman 
in order to identify the key characteristics of these 
crashes and the factors that influence the likelihood 
of fatalities. This analysis will aid in identifying road 
traffic accident trends in order to enable future efforts 
to be directed towards improving heavy vehicle safety 
in Oman. 

Methods

Crash data were obtained from the ROP Directorate 
General of Traffic and included details on all ROP-
attended heavy vehicle crashes occurring from January 
2009 until December 2011, including all serious 
crashes but omitting minor crashes. In the ROP data, 
serious crashes were defined as those where there is 
either an injury, public property damage or an 
inability for the involved drivers to determine, among 
themselves, who was at fault. This definition is a result 
of the 2006 ROP policy which states that minor crashes 
(where the three aforementioned criteria do not 
apply) are to be resolved between drivers’ insurance 
companies without police involvement.6,9

As the original ROP crash database is in Arabic, 
translation into English was performed according to 
the published bilingual statistical report of the ROP (for 
the purpose of this research). In some cases, translation 
was based on terms or definitions used by three Omani 
academics familiar with road safety literature. 

The data collected were predominantly concerned 
with the at-fault vehicle and driver and in labelling 
crash causes; thus, the data were divided into three 
sub-datasets—crash, person and vehicle. For the 
purpose of this analysis, a new combined dataset was 
developed in order to enable characterisation of at-fault 
crashes, and to differentiate between fatal and non-
fatal crashes in relation to characteristics of drivers, 
vehicles and crashes. Driver-related data included age, 
gender, nationality, seatbelt usage and licence status 
of the driver. Vehicle-related data included the type of 
vehicle. Crash-related data included the time, place, 
reason and severity of the crash, including whether a 
fatality occurred before file closure.

Internationally, there are several definitions related 
to heavy vehicles. However, within this dataset, the 
ROP’s Traffic Safety Institute’s definition was used. 
According to this definition, a heavy vehicle is a 
motor vehicle with a weight of >4,000 kg (4 tonnes) 
when unladen, as recorded by the ROP at the time 
of registration.10

The combined dataset was explored and analysed 
using the Statistical Package for the Social Sciences 
(SPSS), Version 16 (IBM, Corp., Chicago, Illinois, 
USA). The severity of the heavy vehicle crashes 
(fatal versus non-fatal) was explored and then linked 
to characteristics related to the driver, vehicle and 
crash. Due to the policy that minor crashes are to be 
handled by insurance companies, property damage-
only crashes in the dataset represented only serious 
accidents. In light of this, it was decided to group injury 
and property damage crashes and compare them with 
fatal crashes to determine the factors most associated 
with loss of life. Due to the small number of crashes in 
some categories, Fisher’s exact tests were conducted 
(using r) to identify whether the occurrence of a 
fatality was independent of certain factors. Further, the 
adjusted standardised residuals for each variable and 
the effect size (Cramér’s V)were calculated.11 

The factors that were significantly related to 
the likelihood of fatality were then included in a 
multiple logistic regression model to further indicate 
important predictors for fatalities within at-fault heavy 
vehicle crashes. 

Results

Over the three-year sample period, there were 2,543 
police-reported road traffic crashes in Oman. As 
a result of these crashes, 2,829 people were killed 
and a further 31,313 were injured. Close to 50% of 
the crashes were reported to involve more than one 
vehicle. Of the total number of crashes in Oman 
during this timeframe, 3,114 incidents involved heavy 



Islam Al-Bulushi, Jason Edwards, Jeremy Davey, Kerry Armstrong, Hamed Al-Reesi and Khalid Al-Shamsi

Special Contribution | e193

vehicles (13.8%). Of these heavy vehicle crashes, 11.7% 
involved a fatality, 62.6% involved an injury and 25.7% 
resulted in no physical harm to those affected. The 
crashes resulted in 268 deaths and 2,134 individuals 
being injured. There were limited data available on heavy 
vehicle crashes in which the heavy vehicle driver was not 
at fault. Of the 3,114 heavy vehicle crashes, 59.7% (n = 
1,859) were deemed the fault of the driver. The at-fault 
crashes were the focus of the remaining analysis. 

As shown in Table 1, within at-fault heavy vehicle 
crashes, almost half of the drivers were aged 21–30 
years (46.2%), the vast majority were male (99.3%) 
and over 40% were expatriates. The majority of 
drivers were reported to be wearing a seatbelt (97.7%) 
and approximately two-thirds of the drivers were 
unlicensed (65.2%). Of the unlicensed drivers, 94.4% 
held either an Omani light vehicle licence or one from 
another GCC country and 2.2% held no driving licence 
at all. In terms of crash characteristics, 70% of these 
crashes occurred during the daytime and around half 
involved other vehicles. With regards to the principal 
reason identified for the crash, the majority were the 
result of common unsafe driving behaviours such as 
speeding, incorrect vehicle manoeuvres, inattention 
and not keeping a safe distance from the preceding car.

Only a small number of heavy vehicle crashes were 
deemed to be the result of fatigue (0.5%) or alcohol 
(1.8%). Furthermore, the ROP attributed a small 
number of the crashes (8.8%) to factors other than 
driver behaviour, such as vehicle or road conditions 
or the climate [Table 1]. The majority of the heavy 
vehicles involved in these crashes were standard 
‘trucks’, meaning they were rigid and articulated trucks 
not including tankers and heavy equipment vehicles.

fata l a n d n o n-fata l c r a s h e s
Univariate Analysis

A number of factors were significantly associated 
with fatalities [Table 1]. These included the age and 
nationality of the driver, whether the driver was 
wearing a seatbelt, their licence status, the type of 
crash that occurred and the reasons for the crash.

There was a small effect (V = 0.10) of age on 
the likelihood of a fatality, with crashes involving 
drivers aged 21–30 years less likely, and crashes with 
drivers aged 41–50 years more likely to result in a 
fatality. Nationality also had a small effect (V = 0.06) 
on the likelihood of a fatality with crashes involving 
non-Omani drivers more likely to lead to a fatality. 
Increased reported use of seatbelts also had a small 
effect (V = 0.18) in lessening the likelihood of fatality. 
Surprisingly, licenced drivers were slightly more likely 
to be involved in a fatal crash (V = 0.09). 

With regards to the type of crash, there was again 
a small effect (V = 0.21), with fatalities less likely 
in overturns and collisions with fixed objects and 
more likely when a person or animal was run over. 
In addition, when the reasons for the crash were 
attributed to driver fatigue (increased risk), overtaking 
(increased risk) and incorrect vehicle manoeuvres 
(decreased risk), there was a small effect (V = 0.20) on 
the likelihood of a fatality occurring.

Multivariate Analysis

The results were further examined through a 
multivariate logistic regression model including only 
the significant univariate predictors (age, nationality, 
seatbelt, licence status, crash type and reason) [Table 
2]. The Hosmer-Lemeshow test (5.741; P = 0.676) 
indicated a good level of fit and the model explained 
20.8% of the variance in occurrence of fatal crashes 
(Nagelkerke’s R2 = 0.208).11 For each predictor, the 
most numerous category was selected as the referent 
group to calculate the odds ratios (OR). The results of 
the logistic regression are shown in Table 2.

Age group was a significant predictor for fatal 
crashes, with drivers aged 41–50 years being 2.09 
times as likely to have a fatal crash than those aged 21–
30 years (P <0.01). No other age groups significantly 
differed from the referent category. Not wearing a 
seatbelt increased the likelihood of fatality by 6.58 
(P <0.01). Licence status was also found to be 
associated significantly with the likelihood of a fatality, 
with licenced drivers 1.64 times more likely to be 
involved in fatal crashes compared to drivers who 
were not licenced (P = 0.01). 

Both crash type and the reason for the crashes 
were significantly associated with the likelihood of 
a fatality occurring. Compared to vehicle collisions, 
crashes involving a person or animal being run-over 
were 2.38 times more likely to lead to a fatality (P 
<0.01), while overturned vehicles (P <0.01) and fixed-
object collisions (P <0.01) were 0.26 and 0.30 times as 
likely, respectively. When compared to crashes caused 
by speeding, fatigue (OR = 10.65; P <0.01), overtaking 
(OR = 2.77; P <0.01) and vehicle defect-related crashes 
(OR = 3.06; P <0.01) were at an increased likelihood 
of fatality, while failure to keep a safe distance 
(OR = 0.27; P = 0.01) and incorrect vehicle manoeuvres 
(OR = 0.42; P <0.01) decreased the likelihood of fatality.

Discussion

The purpose of the current study was to analyse crash 
data pertaining to heavy vehicle accidents in Oman in 
order to identify trends and enable future efforts to 



Heavy Vehicle Crash Characteristics in Oman 
2009-2011

e194 | SQU Medical Journal, May 2015, Volume 15, Issue 2

improve heavy vehicle safety. Prior to discussing the 
findings of this analysis, it is important to recognise the 
limitations inherent to the nature of the data source. 
While the data should only include serious crashes, 
due to the potential for confusion as to the  nature 
of minor or serious crashes, there is still a possibility 
that minor crashes have been recorded incorrectly as 
serious crashes by the police. Furthermore, crashes 
are investigated by police officers at the scene, who 
then complete a crash report and send it later to the 

Table 1: Heavy vehicle crashes by fatality in 2009–2011

Variable Total
n (%)

Fatal
n (%)

Non-fatal
n (%)

% Fatal

Age group in years*

≤20 118 
(6.3)

13 
(6.0)

105 
(6.4)

11.0

21–30 859 
(46.2)

78 
(35.8)

781 
(47.6)

9.1

31–40 523 
(28.1)

64 
(29.4)

459 
(28.0)

12.2

41–50 231 
(12.4)

45 
(20.6)

186 
(11.3)

19.5

≥51 128 
(6.9)

18 
(8.3)

110 
(6.7)

14.1

Gender

Male 1,846 
(99.3)

218 
(100.0)

1,628 
(99.2)

11.8

Female 13 
(0.7)

0 
(0.0)

13 
(0.8)

0.0

Nationality*

Omani 1,071 
(57.6)

106 
(48.6)

965 
(58.8)

9.9)

Non-Omani 788 
(42.4)

112 
(51.4)

676 
(41.2)

14.2

Seat belt use*

Yes 1,817 
(97.7)

197 
(90.4)

1,620 
(98.7)

10.8

No 42 
(2.3)

21 
(9.6)

21 
(1.3)

50.0

Licence status*

Licensed 647 
(34.8)

101 
(46.3)

546 
(33.3)

15.6

Unlicensed 1,212 
(65.2)

117 
(53.7)

1,095 
(66.7)

9.7

Crash time†

Early 
morning 

175 
(9.4)

22 
(10.1)

153 
(9.3)

12.6

Morning 733 
(39.4)

82 
(37.6)

651 
(39.7)

11.2

Evening 543 
(29.2)

59 
(27.1)

484 
(29.5)

10.9

Night 408 
(21.9)

55 
(25.2)

353 
(21.5)

13.5

Crash type*

Vehicle 
collision

874 
(47.0)

106 
(48.6)

768 
(46.8)

12.1

Person or 
animal run 
over

176 
(9.5)

54 
(24.8)

122 
(7.4)

30.7

Overturned 
vehicle

402 
(21.6)

28 
(12.8)

374 
(22.8)

7.0

Fixed-object 
collision

393 
(21.1)

26 
(11.9)

367 
(22.4)

6.6

Motorcycle/
bicycle

14 
(0.8)

4 
(1.8)

10 
(0.6)

28.6

Reasons for crash*‡

Speed 835 
(44.9)

90 
(41.3)

745 
(45.4)

10.8

Inattention 182 
(9.8)

28 
(12.8)

154 
(9.4)

15.4

Fatigue 9 
(0.5)

4 
(1.8)

5 
(0.3)

44.4

Alcohol 33 
(1.8)

2 
(0.9)

31 
(1.9)

6.1

Overtaking 83 
(4.5)

27 
(12.4)

56 
(3.4)

32.5

Climatic 
conditions

20 
(1.1)

4 
(1.8)

16 
(1.0)

20.0

Sudden 
stopping

19 
(1.0)

0 
(0.0)

19 
(1.2)

0.0

Lack of safe 
distance

100 
(5.4)

4 
(1.8)

96 
(5.9)

4.0

Incorrect 
manoeuvre

434 
(23.4)

31 
(14.2)

403 
(24.6)

7.1

Vehicle 
failure

108 
(5.8)

21 
(9.6)

87 
(5.3)

19.4

Road 
conditions

35 
(1.9)

7 
(3.2)

28 
(1.7)

20.0

Heavy vehicle type

Truck 1,618 
(87.0)

183 
(83.9)

1,435 
(87.4)

11.3

Heavy 
equipment

63 
(3.4)

10 
(1.5)

53 
(4.4)

15.9

Water tanker 164 
(8.8)

22 
(3.4)

142 
(11.7)

13.4

Sewage 
tanker

12 
(0.6)

3 
(0.5)

9 
(0.7)

25.0

Oil tanker 2 
(0.1)

0 
(0.0)

2 
(0.2)

0.0

*Significant (P <0.01) difference between licensed and unlicensed crashes. 
Bold = Figures with adjusted standardised residuals greater than +2.58 
(P <0.01). †Crash times were classified as early morning (1:00 am to 5:59 
am), morning (6:00 am to 12:59 pm), evening (1:00 pm to 5:59 pm) or 
night (6:00 pm to12:59 am). ‡Total dataset for crash reasons was 1,858 
due to one missing data point.



Islam Al-Bulushi, Jason Edwards, Jeremy Davey, Kerry Armstrong, Hamed Al-Reesi and Khalid Al-Shamsi

Special Contribution | e195

Directorate General of Traffic to be entered into the 
database.6,9 Thus, all crash data is manually handled, 
leading to the potential for errors while transcribing 
crash reports to the database or to investigator bias.

With these limitations in mind, this paper focused 

on the characteristics of at-fault serious heavy vehicle 
crashes; these findings therefore may not reflect 
prevalence within Oman’s general heavy vehicle driving 
population. As there was a lack of previous  research 
on the prevalence of various risk factors, for example 

Table 2: Logistic model estimation and odds ratios for significant independent variables for heavy vehicle fatal 
crashes in 2009–2011

Variable B SE Significance Odds ratio 95% CI

Age group in years

≤20 0.120 0.350 0.732 1.127 0.568 2.237

21–30 - - - 1.000 - -

31–40 0.131 0.204 0.520 1.140 0.764 1.702

41–50 0.739 0.234 0.002 2.094 1.324 3.314

≥51 0.322 0.308 0.295 1.380 0.755 2.523

Nationality

Omani - - - 1.000 - -

Non-Omani 0.145 0.202 0.474 1.156 0.777 1.718

Seat belt use

Yes - - - 1.000 - -

No 1.884 0.378 0.000 6.579 3.135 13.803

Licence status

Licensed 0.495 0.194 0.011 1.641 1.123 2.399

Unlicensed - - - 1.000 - -

Crash type

Vehicle collision - - - 1.000 - -

Person or animal run over 0.868 0.240 0.000 2.382 1.488 3.814

Overturned vehicle -1.358 0.269 0.000 0.257 0.152 0.436

Fixed-object collision -1.217 0.266 0.000 0.296 0.176 0.499

Motorcycle/bicycle 0.690 0.682 0.312 1.993 0.524 7.588

Reasons

Speeding - - - 1.000 - -

Inattention -0.202 0.263 0.441 0.817 0.488 1.367

Fatigue 2.366 0.735 0.001 10.652 2.524 44.955

Drink driving -1.252 0.814 0.124 0.286 0.058 1.410

Overtaking 1.019 0.300 0.001 2.771 1.538 4.992

Climatic conditions 0.722 0.614 0.240 2.058 0.618 6.855

Sudden stopping -19.370 8,962.844 0.998 0.000 0.000 0.000

Lack of safe distance -1.329 0.542 0.014 0.265 0.091 0.766

Incorrect manoeuvre -0.857 0.256 0.001 0.424 0.257 0.701

Vehicle failure 1.119 0.298 0.000 3.063 1.707 5.496

Road conditions 0.791 0.507 0.119 2.205 0.816 5.958

SE = standard error; CI = confidence interval.



Heavy Vehicle Crash Characteristics in Oman 
2009-2011

e196 | SQU Medical Journal, May 2015, Volume 15, Issue 2

regarding speeding, the analysis also could not indicate 
the relative risk of crashes for the identified factors. 
The factors analysed do, however, represent important 
areas of focus for future interventions. Importantly, 
these factors also pose a high risk for road crashes.

At a general level, heavy vehicle crashes accounted 
for 13.8% of all crashes that occurred in the three-year 
study period. This appeared to be representative of the 
12.5% of registered vehicles in Oman that are heavy 
vehicles. Given that the present data explored crashes 
serious enough to be reported by police, it is surprising 
that heavy vehicles were not over-represented. 
Specifically, the mass of a heavy vehicle should 
increase the average crash severity, leading to a higher 
level of reporting. It is also worth noting, however, 
that this comparison may not take into account heavy 
vehicles not registered in Oman that are engaged in 
cross-border transport. Furthermore, heavy vehicles 
typically conduct a greater amount of travel than 
other vehicles and the number of km travelled is often 
used to estimate levels of exposure to traffic hazards. 
Unfortunately, there is no record of km travelled in 
Oman for specific vehicle types. Thus, it is not possible 
to draw conclusions regarding the overall representative 
level of heavy vehicle involvement in crashes, nor draw 
accurate comparisons to other countries. 

Of all heavy vehicle crashes, 59.7% were the fault of 
the driver. This is reasonably low when compared with 
findings from Australia. Recent reports for the main 
insurer of heavy vehicles in Australia, the National 
Transport Insurance Company, have indicated that 
truck drivers were at fault in multivehicle crashes 
in 46.3% and 70% of cases during 2007 and 2011, 
respectively.12,13 Given that multivehicle crashes 
accounted for 24.1–24.6% of crashes, truck drivers 
therefore were at fault in 86.8–92.8% of all crashes. 
However, it should be noted that differences in 
reporting practices between countries and the 
different sources of data (insurance company versus 
police data) may partially account for this difference 
in fault rates, particularly considering multivehicle 
crashes accounted for close to half of the crashes in 
the current report. 

Just over half of the drivers involved in heavy 
vehicle crashes in Oman were under the age of 30 
years. This aligns with similar trends in road safety 
research internationally, yet contradicts a recent report 
of serious Australian heavy vehicle crashes which 
revealed a greater trend towards older drivers.13 It is, 
however, important to note that the Australian heavy 
vehicle industry is often considered an ageing industry 
which is struggling to renew its workforce and most 
companies refuse to hire drivers below 25 years of 
age due to increased insurance costs. Furthermore, 

census data from Oman has shown that a significant 
proportion of the population of Oman are young, with 
44.7% of the population under the age of 20 years.14 
The high proportion of drivers under the age of 30 years 
in the current sample suggests the need for targeted 
safety initiatives for younger heavy vehicle drivers, such 
as those included in graduated licensing systems.

The high number of expatriate heavy vehicle 
drivers is not surprising given that 29.4% of Oman’s 
population in 2010 were expatriate.15 Heavy vehicle 
drivers in Oman also may be transporting goods 
to or from the UAE, KSA or Yemen, which conduct 
trade with Oman. Anecdotally, it is also commonly 
suggested that the majority of heavy vehicle drivers are 
expatriate. While it is difficult to tell how representative 
the proportion of Omanis and expatriates is in the 
current sample, it does highlight the need for a safety 
initiative that would account for cultural differences. 
In the context of traffic safety, the influence of culture 
has recently gained increased attention, even forming 
the topic of a recent special edition of a traffic-related 
journal.16 When such a high proportion of truck 
drivers are from other nations, it would be an error 
to assume that standardised approaches known to 
be effective for one culture would necessarily have a 
sufficient impact on the industry as a whole. Thus, it is 
important for future research to examine the influence 
of culture on safety in the heavy vehicle industry of 
Oman and identify safety initiatives which either 
operate effectively across cultural barriers or provide 
education targeted to specific subcultural groups in 
the industry. 

With regards to the types of crashes, 52.4% did not 
involve any other vehicle, which is substantially higher 
than reports on serious major highway crashes in the 
USA, where approximately 34% of accidents involve 
just a single vehicle.17 However, this finding is higher 
than serious crash insurance statistics from Australia, 
where approximately 75% involved a single vehicle.12,13 
It is important, however, to recognise that the current 
statistics do not include non-fault crashes due to the 
data collection focus of the ROP. If it is assumed that the 
remainder of crashes in which the heavy vehicle driver 
was not at fault all involved another vehicle, single 
vehicle crashes would represent 31.6% of crashes, which 
would be comparable to rates in the USA. 

Similar to other reports published in the literature, 
the majority of heavy crashes in the current study were 
caused by common driver behaviours such as speeding, 
incorrect manoeuvres and inattention.18–21 Worth 
noting, however, is the fact that fatigue was a factor in 
very few of the serious heavy vehicle crashes in the 
dataset (n = 9). This is quite different to statistics from 
Australia where fatigue accounted for 11.9% of serious 



Islam Al-Bulushi, Jason Edwards, Jeremy Davey, Kerry Armstrong, Hamed Al-Reesi and Khalid Al-Shamsi

Special Contribution | e197

crashes; however, similar statistics from the USA with 
fatigue accounting for approximately 0.7% of serious 
crashes.13,17 It should be recognised that Oman is 
a geographically smaller nation than Australia and 
the USA, and that therefore there may be less long-
distance driving resulting in reduced likelihood of 
road fatigue. However, there may be alternative 
explanations for this finding. Research has shown 
fatigue to be a major contributor to heavy vehicle 
crashes, while driving long hours has been associated 
with falling asleep at the wheel and increased injury 
severity in the case of a crash.8,17,22–25 However, fatigue 
is commonly under-represented in crash statistics.26,27 
Whenever a driver is fatally injured, it is impossible 
to enquire directly regarding fatigue; thus, it can be 
difficult to determine fatigue as the crash cause within 
police investigations. In the literature, a number of 
factors have been used to determine the involvement 
of fatigue in crashes, including single-vehicle crashes 
during high risk fatigue times (e.g. 12:00–6:00 am and 
2:00–4:00 pm), head-on collisions while overtaking, 
the absence of evidence of evasive actions and the 
location of the crash being clearly visible for several 
seconds prior to the crash.6,28 The ROP do not have 
a formal inspection process by which fatigue is 
determined. In Oman, a crash is classified as being 
caused by fatigue according to the findings and view 
of the ROP investigator or by a direct confession from 
the driver. Additionally, the crash database does not 
indicate all factors contributing to crashes, but only the 
single predominant cause. Thus, fatigue-related crashes 
could be primarily identified as being caused by incorrect 
manoeuvres or other behaviours. By introducing a 
more thorough approach to determining fatigue as well 
as enabling the use of multiple causal factors, it may be 
possible to increase the accuracy of investigation reports 
and gain better insight into the impact of fatigue on the 
drivers of heavy vehicles in Oman. 

An important category of crash causes, is the 
influence of external factors, including those related 
to the vehicle, road and climate. As previously stated, 
this analysis reviewed at-fault serious crashes. The fact 
that 8.8% of heavy vehicle driver at-fault crashes were 
attributed to factors not directly under the driver’s 
control again brings into question the classification 
of crash causes on ROP reports. In such cases, it 
is anticipated that some driver behaviours were 
unsuitable for the conditions at the time of the crash 
and this further highlights the need for changes to the 
ROP crash investigation processes.

fa c t o r s a s s o c i at e d w i t h fata l 
c r a s h e s

With regards specifically to fatal crashes, it is important 

to note the differences between statistical significance 
and real-world applicability. Factors which were found 
to be associated with the likelihood of a fatality did 
not always represent those which account for the 
greatest number of fatalities. In both the univariate 
and multivariate analyses, drivers aged 41–50 years 
were at higher risk of fatalities. The fact that this 
statistic remained significant in the multivariate model 
suggests that other factors do not account for this 
variance. While it could be argued that older drivers 
are more susceptible to a greater severity of injuries 
in crashes, drivers over the age of 50 years were not 
at a higher risk. The sample size of these older drivers 
may have been insufficient to reveal trends; however, 
there is a need for further research to examine the 
risks associated with drivers over the age of 41 years. 
Nonetheless, drivers aged 21–30 years (35.8%) and 
31–40 years (29.4%) showed a higher proportion of 
crashes in comparison to drivers aged 41–50 years 
(20.9%). Thus, while older drivers may need specific 
attention in order to address the reasons for their 
increased likelihood of fatal crashes, younger drivers 
represent the highest proportion of drivers in Oman 
and should be targeted to reduce the total number 
of fatalities. 

Nationality was significant in the univariate 
analysis, with expatriates at a higher risk of fatalities 
due to the over-representation of Omanis in non-fatal 
crashes. However, this significance did not hold in the 
multivariate analysis. This suggests that the difference 
in fatality rates may be accounted for by other 
predictors, such as the cause of crashes. Additionally, 
it should be noted that the overall differences in 
the proportions of fatal and non-fatal crashes may 
highlight differences in the reporting of crashes. 
Given that expatriate drivers may be on visas which 
could be lost if they are found to have broken any laws, 
less severe crashes may therefore not be reported. 
Furthermore, differing employment conditions have 
been shown, internationally, to have an impact on 
heavy vehicle safety. For example, subcontractors, 
owner-operators and informal employees have higher 
rates of crash involvement and associated injuries.29–31 
Regardless of the reasons for these differences, the loss 
of significance when accounting for other variables 
suggests differences of behaviour or other crash factors 
which should be explored to better understand how 
nationality and/or culture influences heavy vehicle 
crashes.

In both the univariate and multivariate analyses, 
the lack of seatbelt use increased the likelihood of 
fatalities. Given the nature of seatbelts, the difference 
in the likelihood of fatalities may directly relate to the 
potential loss of life for truck drivers; however, further 



Heavy Vehicle Crash Characteristics in Oman 
2009-2011

e198 | SQU Medical Journal, May 2015, Volume 15, Issue 2

research is needed to confirm whether this is the case or 
whether individuals who do not wear seatbelts are also 
more likely to engage in other high-risk behaviours. 
It should be noted that the frequency of seatbelt use 
in the reported dataset was very high. In the current 
dataset, almost all of drivers were reported to be 
wearing a seatbelt at the time of the crash. Although 
seatbelt use is mandatory for truck drivers in both 
Australia and Oman, one study found that seatbelt use 
was very low among Australian heavy vehicle drivers, 
with many seeing seatbelt use as unrelated to safety.32 
Given the reliance on police investigation data in the 
current dataset, it is thought that seatbelt use can only 
be confidently ascertained from crashes in which the 
truck driver died in other crashes there may be a high 
level of over-reported seatbelt use by drivers who do 
not want to admit to breaking the law in front of a 
police officer. An investigation into the prevalence of 
seatbelt use in the heavy vehicle industry of Oman is 
needed to better understand usage rates and associated 
behaviours. Furthermore, to see the direct benefits of 
seatbelt use, a more detailed analysis of crashes in which 
the heavy vehicle driver was injured or killed is required.

Licence status was found to be associated 
significantly with the severity of the crashes in both 
the univariate and multivariate analyses. Interestingly, 
drivers holding valid heavy vehicle licences contri-
buted more to the occurrence of fatal crashes 
compared to those not licensed to drive heavy vehicle. 
Research on driving in the general population has 
shown that unlicensed drivers are over-represented 
in serious crashes and are more likely to engage in 
higher-risk behaviours.33 It is unclear why unlicensed 
drivers would not be more frequently involved in fatal 
crashes given their representation in the total sample. 
It is important to recognise that, in this analysis, the 
classification of “unlicensed” included drivers with the 
wrong class of licence as well as those with no licence. It 
is important to note, however, that there is no current 
licence demerit point system in Oman, meaning that 
unlicensed drivers in the current sample represent 
those who have never received the appropriate type 
of licence for heavy vehicle driving. The finding that 
holding a licence increases the likelihood of a fatality 
could be explained predominantly by the much higher 
prevalence of unlicensed drivers in non-fatal crashes, 
perhaps indicating a higher proportion of minor 
error-related crashes from lack of driving skills and 
experience. Nonetheless, it is clear that the proportion 
of drivers without a licence in the current sample 
demonstrates a need to increase appropriate licensing 
in Oman. Moreover, the unexpected trend of crash 
severity related to licence status may highlight a need 
to improve the current licensing standards.

Crash type was also significantly predictive of 
the likelihood of fatalities. It is to be expected that 
when a heavy vehicle crash is classified as involving 
an animal or person being run over, those involving 
humans would have a much higher fatality rate. 
Unfortunately, it was not possible to distinguish in 
the database which crashes involved an animal and 
which involved a human being run over; thus, gaining 
a further understanding of the exact likelihood of 
these types of crashes influencing fatality rates was not 
possible. For example, it may be the case that 100% of 
crashes which involved a human being run over were 
fatal. Single-vehicle crashes (overturned and fixed 
vehicles-object collisions) were less likely to result in 
a fatality. Given the mass of heavy vehicles, and the 
relative protection given to truck drivers inside the 
vehicle, it is not surprising that crashes involving 
other vehicles would result in a higher risk of fatalities 
than single-vehicle crashes. Nonetheless, it should be 
noted that recent reports from Australia have shown 
that fatalities resulting from multivehicle crashes 
are typically the fault of the other vehicle’s driver.13 
When a single-vehicle crash occurs, it is more likely 
to lead to a truck driver’s death. Thus, it is an unusual 
finding that, within at-fault heavy vehicle crashes in 
Oman, single-vehicle crashes were at lower risk of 
resulting in fatalities. Without further examination to 
separate truck driver fatalities from other road user 
fatalities, and to better understand factors related to 
the non-fault vehicles, it is difficult to understand the 
implication of this finding.

The final category of factors which contributed 
to the likelihood of fatalities was the reason for a 
crash. While there were only three crash reasons 
that were significant in the univariate analysis, the 
use of speeding as a reference category revealed five 
significant predictors within this category. Specifically, 
crashes caused by fatigue, overtaking and vehicle 
defects were all more likely to result in fatalities 
than crashes predominantly attributed to speeding. 
While the issues associated with detecting fatigue in 
crashes were discussed above, it is worth noting that 
despite the significant finding in the current analysis, 
the very small number of fatigue-related crashes, 
most likely due to under-reporting, prevents any 
meaningful interpretation of the associated likelihood 
of fatalities. Overtaking may be viewed internationally 
as an unusual predictor of crashes; however, it should 
be noted that, within Oman, heavy vehicles are not 
permitted to overtake. For this reason, there may 
be other dangerous behaviours that occur while 
overtaking, as drivers may be in a rush to complete 
the manoeuvre. Further investigation is required to 
understand the association between overtaking and 



Islam Al-Bulushi, Jason Edwards, Jeremy Davey, Kerry Armstrong, Hamed Al-Reesi and Khalid Al-Shamsi

Special Contribution | e199

fatalities in heavy vehicle crashes. 
Vehicle defects have been commonly associated 

with the likelihood of crashes; however, tyre defects 
have specifically been associated with increased 
crash severity.17 While it is not possible to determine 
what type of vehicle defects were associated with 
crash severity in the current dataset, anecdotally, 
a high number of trucks have bald tyres in Oman. 
Additionally, the fines that exist for bald tyres in 
Oman are insufficient when compared to the cost of 
replacing tyres. In fact, when considering only the 
financial implications, it is cheaper to receive a high 
number of fines than to replace a single tyre. While 
further research is needed to explain the variation in 
fatalities associated with vehicle defects, tyre defects 
may play a significant role in these crashes.

The final two crash causes that were significantly 
less likely to produce fatalities than speeding were 
failure to keep a safe distance behind the preceding 
vehicle and incorrect manoeuvres. Failing to keep a 
safe distance typically results in rear-end crashes which 
could be expected to produce lower fatality rates. 
Unfortunately, an incorrect manoeuvre is a somewhat 
vague category that is not easily interpretable.

f u t u r e d i r e c t i o n s
During the analysis of the findings, a number of 
key directions for future research emerged. Due to 
the nature of the data analysed and their inherent 
limitations, this analysis primarily highlighted specific 
areas requiring research in the Omani context. There 
is a need for an estimation of km travelled per vehicle 
in order to understand the relative risk presented by 
heavy vehicles. In the current data, heavy vehicles 
appeared representative of their registration numbers, 
which may actually indicate that these drivers are 
under-represented in the statistics, given that trucks 
usually travel further and more often than other 
vehicles. There is also a need for research to examine 
why drivers aged 41–50 years were at a higher risk 
of fatalities; to understand the impact of cultural 
differences between expatriate and Omani drivers so as 
to enable targeted initiatives; to differentiate between 
fatality risks for truck drivers and members of the 
general public in heavy vehicle crashes, and to better 
understand the role of overtaking in heavy vehicle 
crashes in Oman. Due to the high representation of 
younger drivers in the current dataset, it is clear that 
specific initiatives should be aimed at these drivers, 
perhaps by implementing a graduated driver licensing 
system, as well as investigating potential issues with 
the current licensing system of heavy vehicle drivers 
in Oman. 

Finally, there is a need for a more thorough crash 
investigation process. The current investigation 
process may be sufficient for identifying culpability and 
resolving legal issues related to crashes, but the data 
do not seem sufficient for understanding road safety in 
Oman. Without more comprehensive data, it is difficult 
to determine the relative contributions of different 
factors and to determine paths forward for future 
initiatives. The main issues in the current investigation 
process and dataset include unclear methods to 
determine the impact of fatigue; a lack of information 
about the involved vehicles and drivers who were not 
deemed culpable; a lack of data regarding multiple 
crash causes and behaviour; unclear information 
about vehicle defects and incorrect manoeuvres, and 
the combination of crashes involving a pedestrian 
or animals being run over into a single category. If 
police data are to provide sufficient information about 
crashes to help direct future government and policing 
efforts, there is a need to address each of these issues 
and conduct an evaluation of the current investigation 
process to identify weaknesses.

Despite limitations in the data, a broad range of 
factors were found to be significantly related to fatal 
crashes, including factors associated with people, 
society and culture, behaviour, vehicles, roads 
and government policies and practices, including 
licensing. This highlights the need for a broad 
approach to address the issue of heavy vehicle safety 
in Oman. As can be seen by these data, road safety is 
a complex topic, requiring strategies which target the 
many groups that share responsibility for improving 
outcomes. This lends itself to a ‘safe system’ approach, 
in which all aspects of the road network are addressed 
and all associated parties are involved to produce 
a safer road network for all users. This approach is 
used in other countries, including Australia, to great 
effect.34 Additionally, it is important to recognise that, 
unlike private road users, heavy vehicle drivers are 
performing a transportation service and typically do 
so under the employment of an organisation. There is a 
need for all parties associated with the transportation 
of goods and customers via roads to play a role in 
ensuring everyone’s safety. Some countries, such as 
Australia, have implemented laws which require that 
all parties who have a role in heavy vehicle transport 
be accountable for safety. Within Oman, the inclusion 
of heavy vehicles as workplaces under health and 
safety legislation could increase employer involvement 
in ensuring safety. Furthermore, the introduction of 
supply chain laws which hold both customers and 
organisations accountable should further ensure that 
safety is sufficiently prioritise within the industry.



Heavy Vehicle Crash Characteristics in Oman 
2009-2011

e200 | SQU Medical Journal, May 2015, Volume 15, Issue 2

Conclusion

Increased development within Oman has also 
increased the need for heavy vehicles, thereby 
increasing the risk of traffic accidents involving these 
vehicles. Data analysis of police records revealed that 
there were 3,114 crashes in Oman involving heavy 
vehicles (between January 2009 and December 2011). 
While the majority of these crashes were attributed to 
driver behaviours, a small proportion were attributed 
to factors relating to the vehicle, road and climate. 
Fatalities were more likely for drivers aged 41–50 
years, those not wearing seatbelts and those who 
had the correct licence. When compared to the most 
common crash cause (speeding), fatigue, overtaking 
and vehicle defect-related crashes were more likely to 
result in a fatality. This analysis highlighted the need 
for further research on crash investigation processes 
as well as an improvements to the current licensing 
system in Oman and methods to incorporate age- 
and culture-targeted road safety initiatives for heavy 
vehicle operators.

a c k n o w l e d g e m e n t s

The research team wishes to acknowledge the support 
of the ROP in providing and sharing the data required 
for the analysis and interpretation of the results. 
The research team also acknowledges the assistance 
of The Research Council-Oman in supporting 
communication with several governmental agencies 
and private organisations to enable this work. This 
report reflects research findings only and not the 
legislation or policy positions of the ROP or any other 
governmental associated bodies.

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