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Abstract

A study was carried out in 1995-1999 to assess severity factors for truck drivers' crashes. The authors used data from the trauma registry of road crash victims of the Rhône region, France. Several descriptive characteristics of the victims (age, place of residence) and their crashes (place, time, antagonist, seatbelt wearing) were analyzed. The injuries of 300 male truck drivers were described by body region, and their severity was measured by using the injury severity score comparing these drivers with 9,488 male car drivers (age: 18-67 years). Truck drivers were more seriously injured than car drivers; the odds ratio was 1.87 (95% confidence interval: 1.33, 2.63) for having an injury severity score of 9 or more. Limb and abdominal lesions were more frequent and more serious among truck drivers. The lack of seatbelt wearing by truck drivers was one of the factors that explained the particular severity of their injuries; the odds ratio, adjusted for seatbelt wearing, for truck drivers to be seriously injured was 1.04 (95% confidence interval: 0.73, 1.47) compared with car drivers. When all of the severity factors were taken into account, the risk was even lower, but not significantly so.
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Am J Epidemiol
2003;158:753–759
American Journal of Epidemiology
Copyright © 2003 by the Johns Hopkins Bloomberg School of Public Health
All rights reserved
Vol. 158, No. 8
Printed in U.S.A.
DOI: 10.1093/aje/kwg200
Severity Factors for Truck Drivers’ Injuries
Barbara Charbotel, Jean-Louis Martin, Blandine Gadegbeku, and Mireille Chiron
From UMRETTE (Transport, Work and Environment Epidemiology Research Unit), Joint Research Unit of INRETS (French
National Institute for Transport and Safety Research) and University Claude Bernard, Lyon, France.
Received for publication July 10, 2002; accepted for publication April 11, 2003.
A study was carried out in 1995–1999 to assess severity factors for truck drivers’ crashes. The authors used
data from the trauma registry of road crash victims of the Rhône region, France. Several descriptive
characteristics of the victims (age, place of residence) and their crashes (place, time, antagonist, seatbelt
wearing) were analyzed. The injuries of 300 male truck drivers were described by body region, and their severity
was measured by using the injury severity score comparing these drivers with 9,488 male car drivers (age: 18–
67 years). Truck drivers were more seriously injured than car drivers; the odds ratio was 1.87 (95% confidence
interval: 1.33, 2.63) for having an injury severity score of 9 or more. Limb and abdominal lesions were more
frequent and more serious among truck drivers. The lack of seatbelt wearing by truck drivers was one of the
factors that explained the particular severity of their injuries; the odds ratio, adjusted for seatbelt wearing, for truck
drivers to be seriously injured was 1.04 (95% confidence interval: 0.73, 1.47) compared with car drivers. When
all of the severity factors were taken into account, the risk was even lower, but not significantly so.
accidents; injury severity score; risk factors; seat belts
Abbreviations: AIS, Abbreviated Injury Scale; ISS, injury severity score.
Road crashes during the course of work are the primary
cause of occupational fatalities in most industrialized coun-
tries. They represent 20–25 percent of fatal work accidents in
the United States (1–3) and 30 percent in Canada (4), and
they are associated with significant human and economic
costs (5). In France, nearly 40 percent of fatal work accidents
are road crashes (6, 7). Truck driving is a risky profession in
terms of work-related road crashes (2, 8), and truck drivers’
crashes are often linked to medical impairment and job loss
(9). In a previous study about work-related road crashes (10),
police data on road crash casualties were analyzed, and the
particular severity of work-related road crashes associated
with certain driver professions and also with the types of
vehicles driven were underlined. The rate of seatbelt wearing
by drivers injured in work-related crashes was analyzed: 74
percent at the wheel of a car, 61 percent at the wheel of a van,
and 9 percent at the wheel of a truck. However, the
percentage of missing values for this variable was high—14
percent, 22 percent, and 86 percent, respectively. For this
reason, it was not possible to conclude that there was an
association between crash severity and seatbelt wearing, but
the low rate of seatbelt use among truck drivers might have
explained the particular severity of their crashes.
Because of the human and economic stakes related to truck
crashes, it is important to improve knowledge of the kinds
and severity of injuries that truck drivers experience and also
to identify the severity factors for these crashes. The registry
of road crash victims in the Rhône region of France, which
contains information about crash and victim characteristics
and also includes a precise description of injuries, was
appropriate for such a study. The aim of the present study
was to understand the difference in crash severity previously
observed between truck and car drivers and to compare their
injuries and the severity factors for their crashes.
MATERIALS AND METHODS
Data used
A trauma registry of road crash victims in the Rhône
region (population, 1.6 million inhabitants; main city, Lyon)
has been operational since January 1995 (11). Any injury
victim of a road crash that happened within the Rhône region
Correspondence to Dr. Barbara Charbotel, UMRETTE, Université Claude Bernard Lyon I, Domaine Universitaire Rockefeller, 8 avenue
Rockefeller, 69373 Lyon CEDEX 08, France (e-mail: barbara.charbotel@rockefeller.univ-lyon1.fr).
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Am J Epidemiol
2003;158:753–759
is eligible for inclusion. No matter what type of vehicle is
involved, every road accident is reported, including those on
roads closed to public traffic. Victims are defined as all
persons presenting with at least one injury of a severity level
of 1 or more according to the 1990 revision of the Abbrevi-
ated Injury Scale (AIS) defined by the Association for the
Advancement of Automotive Medicine (12). Data collection
is based on the participation of various medical centers
involved in the health care of crash victims. The network
also encompasses centers that are outside but close to the
Rhône region and may, nevertheless, receive eligible
victims. Overall, about 100 medical services are involved
from private, civil, and military centers dealing with crashes:
fire and emergency services, emergency on-site medical
care, and emergency and follow-up services (intensive care,
surgery, and rehabilitation units). To avoid losing “dead at
the scene” cases, mortuaries and forensic institutes are also
in the network.
Inclusion in the registry is automatic; however, coopera-
tion from victims and their families is directly requested by
means of posters put up in the treatment centers. They are
invited to familiarize themselves with the contents of the
poster, which asks them to let the medical staff know the
place, date, time, and circumstances of their accident and
reminds them of their right to refuse to be included in the
registry. However, nobody has been known to refuse. To
ensure maximum exhaustiveness and quality of the data, the
data collection sheet is as simple as possible. The informa-
tion collected consists of the characteristics of the victim
(name, gender, date of birth), the characteristics of the crash
(place, date, time, type of collision, road user category), the
medical assessment, and the injured person’s subsequent
progress.
After the data are cross-checked from one source to
another, they are coded by a physician in accordance with
the 1990 revision of the AIS. All crash data and medical data
are computerized for statistical analysis, and all precautions
are taken to preserve victim anonymity and confidentiality.
Study design
Data collected in the Rhône registry for crashes occurring
from 1995 to 1999 were analyzed with the aim of under-
standing the difference previously observed between the
severity of truck drivers’ injuries and those of car drivers. In
this article, “truck crashes” are those in which a driver of a
truck weighing 3.5 tons or more is injured; “car crashes”
refer to those in which a car driver is injured.
Truck crashes and car crashes were described in terms of
the following:
1. The drivers’ characteristics (age, place of residence).
2. Their crash characteristics (place, time, antagonist, seat-
belt wearing). An “antagonist” is the third party involved in
the harmful event. It can be another vehicle with which the
driver had the collision, or it can be a fixed object. There also
might have been no antagonist, which means that no colli-
sion occurred (e.g., overturned vehicle).
3. Victims’ injuries, described by body region, and their
severity measured by using the injury severity score (ISS):
the total of the squares of the highest AIS scores for the three
body regions injured most severely (12).
Chi-square tests (or Fisher’s exact tests when expected
frequencies were below 5) were performed to compare truck
and car crashes. Only significant differences over a threshold
of 5 percent were indicated.
Classic severity factors such as victims’ and crash charac-
teristics (age, time and place of the crash, antagonist, seatbelt
wearing) were assessed for truck and car drivers. A multi-
variate analysis using logistic regression was then conducted
to point out the predominance of the severity factors identi-
fied. For this analysis, quantitative variables were trans-
formed into dummy variables. In this paper, results are
shown as odds ratios comparing drivers with an ISS score of
9 or more (case group) with drivers who had an ISS score of
less than 9 (control group).
RESULTS
Of the 52,315 road crash victims included in the Rhône
registry from 1995 to 1999 who sustained at least one AIS
injury (or who died, and no lesion description was included),
368 (0.7 percent) were injured in a truck. Of these 368
victims, 310 (84 percent) were at the wheel of the truck (47
were passengers, and the position in the vehicle was
unknown for 11 persons). Of the truck drivers, 300 were
males aged 18–67 years. Because of the low number of
female truck drivers, the following analysis compared male
truck drivers’ characteristics with those of the 9,488 male car
drivers aged 18–67 years.
Victims and crash characteristics
Age of the victims.
Most of the truck drivers were in the
age group 25–44 years (table 1). Car drivers differed greatly
in their age distribution, 30 percent of the total being aged
18–24 years. The mean age was 36.6 (standard deviation,
10.7) years for truck drivers and 33.3 (standard deviation,
12.3) years for car drivers.
Place of residence.
Of the 300 males injured at the wheel
of a truck, 57 percent lived in the Rhône region, 19 percent
in an adjacent region, 19 percent in another area of France,
and 5 percent in a foreign country. In contrast, 87 percent of
car drivers lived in the Rhône region, and less than 1 percent
of them came from a foreign country.
Crash characteristics.
The time of the crash was
unknown for only 18 percent of all crashes. When the infor-
mation was available, 87 percent of truck crashes occurred
between 4 a.m. and 6 p.m. versus 70 percent of car crashes.
Car crashes were more uniformly distributed during the
whole day, whereas truck crashes were distributed with
peaks between 8 a.m. and 9 a.m., between 10 a.m. and 11
a.m. (9 percent and 10 percent, respectively), and between 3
p.m. and 4 p.m. (8 percent). No more than 9 percent of truck
crashes occurred between 9 p.m. and 4 a.m. compared with
19 percent of car crashes.
Truck crashes were more frequent during the first 5 days
of the week, uniformly distributed among the different days.
Only 7 percent occurred on Saturdays and 3 percent on
Sundays. On the contrary, car crashes occurred more often
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during weekends. Indeed, 47 percent of them occurred
between Friday and Sunday. Crash incidences vary greatly
depending on the time of year; 60 percent of the truck
crashes occurred between July and December, and a peak
occurred during July that accounted for 13 percent of the
total versus, for car crashes, 52 percent in July and 8 percent
in December.
Truck crashes took place more frequently on highways
(expressways included) than car crashes did: 37 percent and
15 percent, respectively. Eighteen percent of truck crashes
and 14 percent of car crashes occurred on main or secondary
roads, and, respectively, 25 percent and 51 percent took
place on streets.
Truck and car crashes differed greatly when we compared
their antagonist. In 39 percent of the instances, the truck
crash occurred with no antagonist compared with 14 percent
for car crashes. The antagonist was also more often a heavy
vehicle in truck crashes than in car crashes, 19 percent
compared with 6 percent, and less often a car, 28 percent
compared with 66 percent.
A seatbelt was worn by only 14 percent of truck drivers
compared with 72 percent of car drivers. Moreover, 51
percent of truck drivers did not wear one compared with 15
percent of car drivers. For the other cases, the information on
seatbelt wearing was unknown.
General severity and types of injuries
All in all, truck drivers were more seriously injured than
car drivers. Indeed, 13.3 percent of them had an ISS score of
9 or more compared with 7.6 percent of car drivers (odds
ratio = 1.87, 95 percent confidence interval: 1.33, 2.63). The
same was true for their mortality rate: 3.3 percent for truck
drivers and 1.5 percent for car drivers. For truck drivers, the
most frequent injuries involved the limbs (table 2), followed
by the cranium and brain and then the thorax.
Limb lesions were more frequent and more severe in truck
drivers than in car drivers. Compared with 5.6 percent of car
drivers, 9.3 percent of truck drivers had one or more lesion
with an AIS score of 2 or more for lower limbs. Upper limb
injuries were more frequent in truck drivers; however, the
difference observed in their severity was not significant.
Abdominal lesions were more frequent and more severe in
truck drivers, 2.7 percent versus 1.2 percent for car drivers,
with an AIS score of 2 or more. No significant difference
was observed for thoracic injuries between the two groups of
drivers. Neck and spine injuries were less frequent in truck
drivers.
Severity factors
Univariate analysis.
No matter what type of vehicle was
driven, a car or a truck, a positive link was found between
drivers’ ages divided into three age classes (18–34, 35–54,
and 55–67 years) and injury severity (table 1).
No difference was observed in the severity of truck
drivers’ injuries when the place of the crash was considered.
Whatever the road category—motorway, road, or urban
area—the rate of seriously injured drivers was the same (14–
15 percent). On the contrary, for car crashes, a growing
TABLE 1. Ages of truck drivers and car drivers injured in a crash, trauma
registry of road crash victims in the Rhône region of France, 1995–1999
* ISS, injury severity score.
Age (years)
ISS* < 9 ISS 9 (or dead) Total
No. % No. % No. %
18–24
Truck drivers 36 92 3 8 39 13
Car drivers 2,606 93 210 7 2,816 30
25–34
Truck drivers 95 91 9 9 104 35
Car drivers 2,908 94 202 6 3,110 33
35–44
Truck drivers 71 85 13 15 84 28
Car drivers 1,505 92 132 8 1,637 17
45–54
Truck drivers 45 82 10 18 55 18
Car drivers 1,065 91 109 9 1,174 12
55–67
Truck drivers 13 72 5 28 18 6
Car drivers 682 91 69 9 751 8
Tot a l
Truck drivers 260 87 40 13 300 100
Car drivers 8,766 92 722 8 9,488 100
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severity was observed among urban areas, motorways,
and main roads: 5 percent, 10 percent, and 17 percent,
respectively.
Seatbelt use is a protective factor. None of the 41 belted
truck drivers was seriously injured, whereas 14 percent of
the nonbelted drivers were. When this information was
unknown, 18 percent had an ISS score higher than 9. For car
drivers’ crashes, the figures were 5 percent, 14 percent, and
15 percent, respectively. The most critically injured seat-
belted truck driver had an ISS score of 6.
When the antagonist of the truck was a car, 8 percent of
truck drivers were seriously injured compared with 10
percent when there was no antagonist, 14 percent when the
other vehicle was a heavy vehicle, 32 percent when the
antagonist was a fixed object, and 29 percent when the
antagonist was unknown. When the antagonist of the car was
another car, 6 percent of car drivers were seriously injured
compared with 8 percent when there was no antagonist, 16
percent when the other vehicle was a heavy vehicle, 17
percent when the antagonist was a fixed object, and 11
percent when the antagonist was unknown.
All of the crashes were more serious between 12 a.m. and
6 a.m. (24 percent of serious crashes compared with 14
percent during the rest of the day for truck drivers; 14
percent and 8 percent, respectively, for car drivers).
However, the difference was significant for car drivers’ but
not for truck drivers’ crashes, probably because of the low
frequencies of crashes during these hours.
Multivariate analysis.
When the type of vehicle and seat-
belt wearing were included in the model, the odds ratio for
truck drivers, compared with car drivers, being seriously
injured was 1.04 (95 percent confidence interval: 0.73, 1.47).
TABLE 2. Abbreviated Injury Scale severity score* for 300 truck drivers and 9,476 car drivers,† trauma registry of
road crash victims in the Rhône region of France, 1995–1999
* Highest score for each body region.
† Information on body lesions was unknown for 12 car drivers.
‡ NS, not significant.
§ Specific Abbreviated Injury Scale term that includes several regions, especially the skin.
Body region
Severity score (%) Total
p
value
123456 No.%
Cranium and brain
Truck drivers 19.3 6.3 1.3 0.7 0.3 1.0 87 29.0 NS‡
Car drivers 14.7 8.4 1.0 0.7 0.3 0.3 2,410 25.4
Face
Truck drivers 17.3 1.0 0.3 56 18.7 NS
Car drivers 18.7 1.7 0.1 0.1 1,945 20.5
Neck
Truck drivers 7.7 0.3 24 8.0 <0.01
Car drivers 14.5 0.1 <0.1 1,379 14.5
Thorax
Truck drivers 16.3 1.7 2.0 1.0 0.7 0.3 66 22.0 NS
Car drivers 17.1 2.5 1.1 0.7 0.3 0.4 2,079 21.9
Abdomen
Truck drivers 9.7 1.0 0.7 1.0 37 12.3 <0.01
Car drivers 4.8 0.5 0.3 0.2 0.1 <0.1 563 5.9
Spine
Truck drivers 16.0 3.0 1.3 61 20.3 <0.01
Car drivers 26.5 2.2 0.2 <0.1 0.1 <0.1 2,747 29.0
Upper limbs
Truck drivers 26.3 7.0 1.3 104 34.7 <0.01
Car drivers 18.8 5.3 1.0 2,374 25.0
Lower limbs
Truck drivers 28.3 4.7 4.7 113 37.7 <0.01
Car drivers 16.6 3.6 1.9 0.1 <0.1 2,102 22.2
External region§
Truck drivers 8.3 25 8.3 <0.01
Car drivers 2.4 <0.1 0.1 238 2.5
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Interestingly, when all of the different severity factors iden-
tified were taken into account (age, antagonist, time and
place of the crash, and seatbelt wearing), the difference
observed between the two vehicle types was even lower but
not significant. Indeed, the odds ratio for truck drivers
compared with car drivers was 0.74 (95 percent confidence
interval: 0.51, 1.07) (table 3). In this last model, the interac-
tions between vehicle type and the other variables were
tested and were found not to be significant.
DISCUSSION
The qualities of the Rhône registry have been demon-
strated in previous analyses; indeed, this registry is almost
exhaustive (11, 13, 14). Information on the crash is provided
by the patients or their families. However, it would not be
possible to complete the medical information by using the
police data corresponding to the crash because police data on
road crash casualties are less exhaustive than the Rhône
registry data. Actually, a study comparing the Rhône registry
data with the police data on road crash casualties for the year
1996 showed important selection bias in the police data as a
result of underreporting (14). In that year, the police data
reported 4,572 victims and the registry 10,202. Following
the police data and registry linkage process, 2,994 victims
were determined to be common to both databases. From
these numbers, evaluation of the completeness of the data
sources could be attempted by means of the capture-
recapture method, but a number of requirements for this
method cannot be achieved, especially the independence.
Given that data are collected not only in all hospitals but also
by all of the health care organization chain, we are quite
confident that we collected data on all road fatalities and
severely injured people. In other words, people missing from
the registry and recorded by the police are mainly those
whom the police consider slightly injured, which can mean
that these people either are under the severity threshold of
AIS 1 required to be included in the registry or have been
taken care of by their general practitioner (or other health
care people). A specific study concerning this item is
currently in progress and has not yet been published. This
severity criterion is, at any rate, the only bias we identified to
explain the fact that these persons were recorded by the
police and not by the registry. On the contrary, three biases
were identified to explain why they were recorded by the
registry and not by the police: underestimation is signifi-
cantly dependent on injury severity and on the type of road
user (maximum for pedal cyclists), and it is higher when
there is no third party. Overrepresentation of severely
injured persons described in other trauma registries, focused
mainly on inpatients, is not a bias observed in the Rhône
registry, which also includes outpatients (15).
Information on seatbelt wearing is usually difficult to
collect. For example, in the police data on road crash casual-
ties, the information is often missing, making any analysis of
the link between crash severity and seatbelt wearing more
difficult (10). In the present study, this information was
known for 65 percent of the truck drivers and 87 percent of
the car drivers, enabling us to perform a multivariate anal-
ysis. The difference observed in missing information
between truck and car drivers may be explained by the lack
of seatbelt equipment in many trucks.
In the analysis, missing data on seatbelt wearing were
given the value “unknown” so we could assess the severity
of this category of crashes and compare it with the others. In
fact, the risk of serious injury was very similar for this
unknown group and the group of unbelted drivers. This study
based on an exhaustive census of victims of road crash inju-
ries permitted us to assess the effect of seatbelt wearing on
injury severity, but, because no uninjured drivers were
included, it was impossible to assess the effect on preventing
injuries. The aim of the study was to understand the differ-
ence previously observed between the severity of truck
drivers’ injuries and those of car drivers, that is, to find
factors to explain the greater severity of truck drivers’ inju-
ries (when they are injured). For this reason, we did not study
safety factors such as drivers’ medical condition, driver
fatigue, or other items known to be risk factors for being
involved in a crash. To be included in the registry, the main
TABLE 3. Injury severity* associated with truck drivers’ and
car drivers’ crashes determined by logistic regression analysis,
trauma registry of road crash victims in the Rhône region of
France, 1995–1999
* Injury severity score of 9.
† The third party involved in the harmful event.
‡ Truck weighing 3.5 tons, bus, tractor.
Odds
ratio
95% confidence
interval
Age (years)
55– 67 1.71 1.30, 2.25
35–54 1.46 1.23, 1.73
18–34 1
Seatbelt use
No 2.81 2.31, 3.41
Unknown 3.18 2.62, 3.86
Ye s 1
Antagonist†
Fixed obstacle 3.03 2.47, 3.74
Heavy vehicle‡ 3.04 2.35, 3.94
Other/unknown 1.75 1.21, 2.51
No antagonist 1.16 0.93, 1.46
Light vehicle 1
Road category
Highway 1.70 1.38, 2.59
Road 3.51 2.91, 4.22
Urban area
Time of crash
12 a.m.–5:59 a.m. 1.83 1.49, 2.25
6 a.m.–11:59 p.m. 1
Driver vehicle
Tr u ck 0.74 0.51, 1.07
Light vehicle 1
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criterion is to have been injured (AIS score of 1 or more),
and the type of user is not considered. Thus, the probability
of being included is not linked with the type of vehicle
driven, ruling out this type of selection bias. However,
because no uninjured drivers are in the registry, we could not
assess the ability of the truck to protect the driver. The same
is true for car drivers, for whom type and weight of the
vehicle can also influence injury severity, including the
absence of any injuries.
Because of the large proportion of workers who were truck
drivers, most of the truck drivers included in this study were
aged 25–44 years, and car drivers were younger (mean ages,
36.6 and 33.3 years, respectively). For the same reason, truck
crashes took place during working hours and were propor-
tionally less frequent than car crashes at night.
Truck crashes and car crashes differed greatly when their
antagonists were compared. Truck crashes more often were
associated with no antagonist or occurred with another heavy
vehicle. Few studies have been published on truck drivers’
injuries. A comparison can be made with a study by Bylund
et al. (9) in Sweden of workers with a medical impairment
injured in a road crash during work time. Nearly a third of
those traveling in heavy trucks were injured in a collision
with another heavy vehicle. Single crashes accounted for
more than one quarter of all injuries.
In the present study, limb injuries were more frequent in
injured truck drivers than in car drivers. Indeed, 34.6 percent
of truck drivers had upper limb injuries, and 37.7 percent had
lower limb injuries. On the contrary, injuries involving the
neck, face, and external region (specific AIS term that
includes several regions, especially the skin) were less
frequent in drivers of heavy vehicles than in car drivers. In
the Bylund et al. study (9), similar results were observed: 23
percent of the single lesions were lower limb injuries in
drivers of heavy vehicles versus 14 percent in car drivers.
For upper limb injuries, the figures were 20 percent and 10
percent, respectively.
In our study, injuries were more severe for victims injured
while driving a truck. In the Bylund et al. study (9), the
proportion of persons who sustained moderate or severe
injuries (M(maximal)AIS 2) was also lower for those
driving cars compared with heavy vehicles—40 percent and
63 percent, respectively. The authors pointed out a low
frequency of seatbelt use among truck drivers and also
among other occupational drivers, all exempt from the seat-
belt law. Eighty percent of the car drivers wore their seat-
belts compared with very few of the truck drivers. For
Bylund et al., the low rate of seatbelt use could explain the
great severity of injury in truck crashes. A truck’s cabin
design places drivers near the front, which could also
contribute to the particular severity of truck drivers’ injuries,
especially if they do not wear a seatbelt. In fact, we identified
the highest severity of truck crashes when drivers did not
wear their seatbelts. The most severely injured belted truck
driver had an ISS score of 6; none of the drivers who were
belted died. Many studies have focused on the effectiveness
of seatbelts regarding severe injuries or death from traffic
crashes (16–18). However, few of them distinguished the
rate of seatbelt wearing among truck drivers. Evans (17)
reported recruitment biases in the analysis of crash severity;
unbelted drivers may be involved in more severe crashes
because of other risky habits such as speeding. This finding
suggests that the association between lack of seatbelt use and
injury severity might be confounded by drivers’ behaviors.
The behavioral factor also could have influenced the present
study results. Even if we took into account several factors
that influenced injury severity, such as driver age and type of
collision, risky behavior by unbelted truck drivers was not
distinguished in this analysis.
The impact that large trucks have on crash severity has
been shown in the crash analysis literature (19), but the
authors did not focus on the specific severity of truck
drivers’ injuries. When the results concerning the severity of
injuries were analyzed, the Rhône registry showed the
particular severity of truck drivers’ crashes. However, our
study demonstrated that the main part of the difference
regarding the severity of the injuries of car and truck drivers
can be explained by seatbelt wearing. Furthermore, when we
adjusted on age, antagonist, time and place of the crash, and
seatbelt use, the odds ratio of truck versus car drivers for
severe injury patterns was less than one, but not significantly
so. This finding could mean that a belted truck driver could
be less vulnerable than a belted car driver given the same
crash conditions.
The low rate of seatbelt use could be a factor in explaining
the difference in the injuries suffered by truck drivers
compared with car drivers resulting in a higher rate of limb
and abdominal injuries. For a long time, French legislation
has imposed seatbelt wearing for drivers of vehicles
weighing up to 3.5 tons. Until now, drivers of trucks
weighing more than 3.5 tons were allowed to drive without
wearing a seatbelt. In May 2003, French legislation changed;
these drivers will now have to wear a seatbelt. However,
because seatbelt equipment was not obligatory for new
heavy trucks and buses until 1997, when a European law
required seatbelt equipment for heavy vehicles (all new ones
were required to be equipped beginning in 2002), old vehi-
cles still have no seatbelts.
Conclusion
Trucks have been identified as being dangerous for other
road users (19, 20); moreover, professional driving is also a
high-risk occupation. This study confirmed the particular
severity of truck drivers’ road injuries and identified specific
severity factors: driver age, type of antagonist, and lack of
wearing seatbelts. These severity factors enabled us to
explain the greater severity of truck drivers’ injuries
compared with those of car drivers. Safety devices have been
recommended for a long time (21) but are still misused, and
more could be done to improve truck drivers’ safety.
ACKNOWLEDGMENTS
The authors thank all of the staff of the ARVAC (Associa-
tion du Registre des Victimes d’Accidents de la Circulation)
and its president, Professor V. Banssillon; Dr. B. Laumon, in
charge of scientific aspects of the registry; and all those who
by guest on May 30, 2013http://aje.oxfordjournals.org/Downloaded from
Severity Factors for Truck Drivers’ Injuries 759
Am J Epidemiol
2003;158:753–759
participated in collecting registry data: T. Ait Idir, T. Ait Si
Selmi, M. Andrillat, F. Artru, Y. Asencio, I. Assossou, G.
Bagou, C. Balogh, G. Banssillon, N. Barnier, X. Barth, J. F.
Bec, J. Bejui, J. C. Bel, E. Bérard, J. Bérard, J. C. Bernard, J.
C. Bertrand, L. Besson, B. Biot, C. Bœuf, D. Boisson, M.
Bonjean, C. Bouchedor, P. Bouletreau, V. Boyer, Y. Breda,
P. Bret, R. Brilland, S. Bussery, A. Cannamela, B. Careg-
nato, M. Carre, Y. Catala, P. Y. Chagnon, C. Chantran, P.
Chardon, P. Charnay, P. Chatelain, H. Chavanne, G. Chazot,
N. Chevreton, E. Chevrillon, S. Chevrillon, P. Chotel, P.
Cochard, C. Combe, B. Contamin, E. Coppard, Z. Crettenet,
B. Dal Gobbo, M. P. De Angelis, L. Decourt, A. Delfosse, J.
Demazière, R. Deruty, G. Desjardins, A. Emonet, J. Escar-
ment, M. Eyssette, L. Fallavier, D. Felten, P. Feuglet, N.
Fifis, G. Fisher, L. P. Fischer, B. Floccard, D. Floret, G.
Fournier, J. F. Fredenucci, M. Freidel, L. Galin, P. Gaillard,
M. Gallon, N. Garnier, A. Garzanti, P. Gaussorgues, V.
Gautheron, M. Genevrier, F. Gibaud, Y. Gillet, A. Goubsky,
M. Granger, P. Grattard, P. Y. Gueniaud, C. Guenot, M.
Guignand, M. Haddak, D. Hamel, C, Jacquemard. T. Joffre,
R. Kohler, C. Lagier, B. Lapierre, M. C. Laplace, R. Laurent,
M. Lebel, G. Leblay, R. Lille, R. Lucas, D. Malicier, B.
Mangola, Y. N. Marduel, F. Marty, C. Messikh, F. Meyer, S.
Meyrand, E. Morel-Chevillet, E. Mioulet, C. Mollet, J.
Monnet, S. Moreno, A. Ndiaye, J. P. Neidhart, E. Ngandu, S.
Ny, T. Ould, D. Paris, B. Patay, P. Pauget, D. Peillon, D.
Perrin-Blondeau, P. Petit, J. L. Piton, M. Plantier, C.
Pramayon, B. Quelard, F. Rigal, D. Robert, J. P. Romanet, F.
Rongieras, C. Roset, A. Rousson, P. Roussouli, H. Roux, C.
Ruhl, J. Salamand, P. Sametzky, N. Scappaticci, M.
Schneider, C. Simonet, R. Soldner, J. Stagnara, D. Stamm,
B. Suc, F. Tasseau, L. Tell, S. Tilhet-Coartet, M. Trifot, A.
Vancuyck, I. Vergnes, M. P. Verney, E. J. Voiglio, G.
Vourey, and L. Willemen.
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... They also indicated that crash duration follows a log-normal distribution, and overturns have the longest durations. In 2003, Charbotel et al. (2003) analyzed five years of trauma registry data to investigate contributing factors affecting truck drivers' crashes compared to car drivers' crashes by developing Chi-square tests. They showed that truck-related crashes are more severe, with an odds ratio of 1.87. ...
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... They also indicated that crash duration follows a log-normal distribution, and overturns have the longest durations. In 2003, Charbotel et al. (2003) analyzed five years of trauma registry data to investigate contributing factors affecting truck drivers' crashes compared to car drivers' crashes by developing Chi-square tests. They showed that truck-related crashes are more severe, with an odds ratio of 1.87. ...
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Medically impairing occupational injuries sustained in traffic in Sweden were analysed. More than half of the cases with a permanent medical impairment were caused by minor injuries. Soft tissue injuries to the neck (whiplash injuries) made up nearly half of all permanently impairing injuries, and half of these were caused by rear-end collisions. As a final result, just over one third (37%) of the total group had a permanent decreased work capacity, or needed to change jobs because of residual problems from their injuries. Professional drivers had the highest injury incidence per employed and they accounted for 28% of the total number of permanent impairment cases, and for 43% of the fatalities. Professional drivers also had a higher percentage of serious injuries and severe permanent impairments than other occupational groups. This might be associated with the low use of safety belts (16%) compared to other occupational groups, where usage was 4–5 times higher. This occupational injury problem ought to be handled in the same way as other occupational safety problems, i.e. protective equipment in a vehicle should be used and the use of safe vehicles should be encouraged.
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"On the job" motor vehicle deaths number more than 4,000 annually in the U.S. and comprise nearly one-third of all work-related deaths. Yet the Department of Labor has set no standards relating to on-the-road safety of the millions of workers whose jobs entail large amounts of driving, and Department of Transportation standards affecting occupational safety cover only drivers in interstate commerce. Drivers of some commercial vehicles, such as heavy trucks, are at special risk of injury because trucks have usually been exempted for many years from federal motor vehicle safety standards--such as standards for brakes and seatbelts--designed to prevent crashes or protect occupants in crashes. Observations based on a series of 150 fatal crashes involving tractor trailers illustrate the need for better protection of this large population of high-risk workers. Clarification of responsibility within the various federal agencies and application of available knowledge and technology are essential.
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Surveillance of injury at work is beset with problems of method and definition. As a result, national agencies have widely varying estimates of the number of fatal work injuries in the United States. One plausible method for identifying fatal work injuries is to use the Place of Injury variable, which is entered on all US death certificates but is not encoded by the National Center for Health Statistics. To use this method, one would assume that work injuries largely occur at "typical work sites," ie, places coded as industrial, farm, and mine and quarry. Data to test this method were derived from the National Traumatic Occupational Fatality data base maintained by the National Institute for Occupational Safety and Health. Analysis of this data base showed that work-related fatal injuries mostly occur in places where many non-work-related injuries also occur. Only about one third of fatal work injuries took place at locations coded as industrial, farm, and mine and quarry. As a method for identifying fatal work injuries, the Place of Injury variable appears to have little value.
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The purpose of the study was to estimate the death rates from occupational injuries in the province of Quebec for the period 1981 through 1988. Worker's compensation files were used to ascertain numbers of deaths, which were used as the numerators in figuring the rates (it was estimated that these files reported 83% of the true number of deaths among men). Annual average estimates of the labor force were used as denominators. From 1981 through 1988, compensation was awarded for 1227 fatal work injuries. Among men (96% of the victims), rates declined from 1981 to 1988 (from 12.7 to 8.1 per 100,000); women's rates were stable (< or = 1.0 per 100,000). Compared with men, women had excess mortality from violent acts. Motor vehicle crashes accounted for 36% of all fatal injuries in 1984 and 1985 and declined thereafter. Fatal injury rates in forestry and mining rose to a 1987 maximum of 67.6 per 100,000. The construction sector had the largest number of deaths, despite a decline in rates from 1981 to 1988 (from 27.8 to 15.9 per 100,000). Except for construction and agriculture, reported fatal occupational injury rates in Quebec were similar to those in the United States. Motor vehicle crashes, falls, violent acts, and farming-related injuries were the most frequent causes of death.
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