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Accident Analysis and Prevention 34 (2002) 71–84

Risk factors for fatal road traffic accidents in Udine, Italy

Francesca Valent a, Flavio Schiava b, Cecilia Savonitto c, Tolinda Gallo d,Silvio Brusaferro a, Fabio Barbone a,e,*

a Cattedra di Igiene ed Epidemiologia, DPMSC , Uni ersity of Udine, Via Colugna 40 , 33100 Udine, Italyb Dipartimento di Preenzione, Azienda per i Serizi Sanitari N .3 ‘ Alto Friuli ’ , Piazzetta Portuzza 1, 33013 Gemona del Friuli , UD, Italy

c Dipartimento di Preenzione, Azienda per i Serizi Sanitari N .4 ‘ Medio Friuli ’ , Via Manzoni 5 , 33100 Udine, Italyd Dipartimento di Preenzione, Azienda per i Serizi Sanitari N .5 ‘ Bassa Friulana’ , Via dei Boschi 17 , 33057 Palmanoa, UD, Italy

e Department of Epidemiology and International Health, Uni ersity of Alabama at Birmingham, 220 J RPHB , 1665 Uni ersity Bouleard ,

Birmingham, AL 35294 -0022 , USA

Received 28 February 2000; received in revised form 10 September 2000; accepted 12 September 2000

Abstract

In the Province of Udine, Northeast Italy, mortality from road accidents is 37% higher than in the country as a whole. To

identify the major risk factors for fatal crashes in this area, we analyzed the Police reports of 10 320 road traffic accidents that

occurred from 1991 to 1996. Logistic regression was used to evaluate the association of characteristics of drivers and accidents

with accident severity. The risk of involvement in fatal rather than non-fatal accidents was lower among females than among

males (odds ratio (OR)=0.65; 95%confidence interval (95%CI), 0.53–0.80). Compared with subjects 30 years of age, subjects

aged 65 had a significantly increased risk of fatal injury as pedestrians (OR=10.87; 95%CI, 4.45– 26.54), car drivers

(OR=1.85; 95%CI, 1.08–3.18), moped riders (OR=3.53; 95%CI, 1.42–8.78), and bicycle riders (OR=7.72; 95%CI, 2.56– 23.29).In accidents that occurred from 1:00 to 5:00 h the risk of death was higher than from 6:00 to 11:00 h among pedestrians

(OR=8.88; 95%CI, 2.58–30.52), car drivers (OR=4.95; 95%CI, 3.09–7.95), motorcycle riders (OR=13.44; 95%CI, 2.54–71.05)

and moped riders (OR=8.76; 95%CI, 2.42–31.69). Risk of death among pedestrians, car drivers, moped, and bicycle riders was

also significantly increased on roads outside the urban center. Driver’s injury was strongly associated with lack of use of seat belts

(OR=13.27; 95%CI, 9.39– 18.74, for fatal injury; OR=2.49; 95%CI, 2.17– 2.86, for non-fatal injury). Simple interventions

focused on protecting the weakest road users and based on law enforcement, behavioral change and environmental modification

might result in reducing the significant excess of road traffic accident mortality found in the study area. © 2001 Elsevier Science

Ltd. All rights reserved.

Keywords: Injury; Road traffic accident; Mortality; Seat belts; Helmets; Elderly

www.elsevier.com/locate/aap

1. Introduction

Among the 15 European Union member countries,

Italy ranks ninth in mortality from traffic accidents

(11.7 deaths per 100 000 population in 1997) and sixth

in accident rate (330 accidents per 100 000 population

in 1997, International Road Traffic and Accident Data-

base, 1999). In the last years, as in most developed

countries, road traffic has increased (from 413 309 mil-

lion passenger-kilometers in 1980 to 746 262 in 1994)

with a consequent increase in the risk of vehicle colli-sion (Istituto Nazionale di Statistica, 1997). In 1986 a

national law was promulgated requiring motorcycle

riders of any age and moped riders aged less than 18

years to use helmets. This law has been into force until

March 2000. In 1989 another law was enacted establish-

ing mandatory seat belt use among car drivers and

front-seat passengers, with very few exceptions. En-

forcement, compliance and efficacy of these laws are

little known. In a survey conducted among moped and

motorcycle riders attending six high schools in Rome

(central Italy), only 50% of teenagers reported helmetuse sometimes or always (Centers for Disease Control,

1996). A comparison between the year before and the

* Corresponding author. Tel.: +1-205-9347163; fax: +1-205-9757058.

E -mail address: [email protected] (F. Barbone).

0001-4575/01/$ - see front matter © 2001 Elsevier Science Ltd. All rights reserved.

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F . Valent et al . / Accident Analysis and Preention 34 (2002) 71 – 84 72

year after the enactment of the seat belt law in the city

of Verona (North Italy) showed a reduction in the

number of hospital admissions following car accidents,

a decrease in mild head injuries with relative increase of

limb injuries and a slight improvement in the death/ac-

cident ratio in the post-legem period (Campello et al.,

1996). These results are dif ficult to generalize because

of substantial cultural, economic and environmentaldifferences between the northern and the southern part

of the country.

The Province of Udine, with approximately 520 000

inhabitants, is located in the North – East of Italy, near

the Slovenian and Austrian borders. In addition to cars

and motorcycles, in this area also bicycles and mopeds

are very common means of transportation, both within

and outside the towns; they are frequently used by the

elderly and by the youth (mopeds can be ridden by

anyone aged 14 years without license). An analysis

of death certificates of the residents from 1989 to 1995

estimated a standardized mortality ratio of 1.37

(95%confidence interval (95%CI), 1.28 – 1.47) for road

traf fic accidents in Udine compared with Italy as a

whole (Valent, 1998). Limitations associated with use of

residence-based death certificates include, (a) non-corre-

spondence between population-based measures of risk

and local environmental hazards when substantial

traf fic within the area is generated by tourism, com-

merce, and commuting and substantial traf fic in adja-

cent areas is generated by incoming traf fic from the

original area; (b) lack of information on non-fatal

injuries; and (c) lack of information on major riskfactors for the accident. Because of the strong excess

mortality associated with road traf fic accidents among

residents of the Province of Udine and in the absence of

other data, we conducted an analysis of all accidents

recorded by the local Police to identify the major

factors associated with road traf fic fatalities and to

suggest possible preventive measures.

2. Materials and methods

In Italy, the Istituto Nazionale di Statistica (ISTAT)

collects data on all traf fic accidents occurred on roads

open to public traf fic, in which at least one person was

killed or injured and in which at least one moving

vehicle was involved. The Police of ficers (Traf fic Police-

men, Carabineers or Municipal Policemen) who arrive

at the site of the accident are responsible for filling the

appropriate of ficial, structured form (Rapporto Statis-

tico di Incidente Stradale or ISTAT/CTT/INC) and for

sending it to ISTAT. Information on ISTAT/CTT/INC

includes time and place of the accident, characteristics

of the vehicles involved, sex and age of drivers, injuredpassengers and pedestrians. The ISTAT definition of

‘trucks’ includes vehicles used for carrying objects only,

trailer trucks with tow, articulated vehicles, semitrailers,

vehicles equipped with special instruments, non-farm

tractors and vehicles used for towing only. On the

contrary, vans and pickups are considered as cars.

Information is collected about seat belt and helmet use

at the time of accident but neither on airbags nor on

use of child restraint systems. Complete information is

obtained for up to three drivers. If more than threevehicles are involved in the same accident, the exceed-

ing drivers can only contribute to the total number of

injured persons, with no distinction from other vehicle

occupants. However, from 1991 to 1996 only 1% of all

accidents involved more than three vehicles (0.7% in-

volved four vehicles, 0.2% involved five vehicles and

0.1% involved more than five). Consequences of acci-

dents are defined as non-fatal injury (regardless of its

severity) or fatal injury (if death occurs within 7 days

from the date of the accident).

Using ISTAT/CTT/INC as data source, we analyzed

information on all accidents occurred in the Province of

Udine from 1991 to 1996. These dates were selected

because since 1991 the definition of a road accident

excludes events only causing damage to property and

1996 is the most recent year for which complete data

were available. In 6 years, 10 320 accidents were

recorded involving 18 227 drivers; 14 525 people were

non-fatally injured and 658 were killed. A validation

conducted in 1993 by the Statistical Service of the city

of Brescia (North Italy) showed that in 1991 and 1992

ISTAT received data from the Police on approximately

80% of the injuries caused by road traf fic accidentsattended by local health personnel and funeral homes.

Accidents appeared not to be severe at first sight and

accidents involving a single vehicle were those more

likely to be missed by the Police (Istituto Nazionale di

Statistica, 1997).

Since the goal of our analysis was to identify factors

influencing crash severity, we chose to use the driver

rather than any subject involved in the accident as the

unit of analysis. In fact, for drivers, but not for passen-

gers, information is collected regardless of whether they

are injured or not. In addition, information on passen-

ger’s use of the seat belt is collected only for car and

truck occupants of the front seat. Finally, the driver

and, generally, not the passenger may hold some re-

sponsibility of the accident and should be the main

target of prevention. We also conducted separate analy-

ses on pedestrians. We chose to evaluate the association

of seat belts and helmets regardless of whether their use

was mandatory, because we were interested in their

overall ef ficacy. Although alcohol and drug consump-

tion are important risk factors for mortality from traf fic

accidents, we did not include them in the model be-

cause, according to ISTAT/CTT/INC, during the studyperiod only 1.5% of all drivers were found to be driving

under the influence of alcohol (DUI) and less than 0.1%

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under the influence of drugs. According to a survey

that we conducted in this area in 1998, values ob-

tained from the Police grossly underestimate the cur-

rent prevalence of DUI in our region. Even among

drivers who were killed, the Police reported very low

prevalence of DUI (2% of fatally injured drivers). No

blood alcohol concentration (BAC) levels were avail-

able since such an exam was not performed by foren-sic pathologists on the accident victims.

2 .1. Statistical analysis

For all drivers combined, we estimated the likeli-

hood of being involved in a fatal versus non-fatal acci-

dent. For car and truck drivers, we estimated both the

likelihood of being personally killed versus not injured

and the likelihood of being personally non-fatally in-

jured versus not injured. For accidents involving riders

of motorcycles, mopeds and bicycles, or pedestrians,

we compared fatal versus non-fatal injuries, because it

is unlikely that these subjects escape injury in an acci-

dent involving at least one injured person.

The odds ratio (OR) was used to estimate the likeli-

hood of the more severe outcome as compared with

the lesser one, under the condition that an accident

involving at least one injury had occurred. Therefore,

the ORs we present are estimates of the relative risk of

people dying or being injured given that they have

been involved in an accident. We conducted unad-

justed and adjusted analyses using unconditional logis-

tic regression (Hosmer and Lemeshow, 1989).However, only adjusted analyses are presented. The

goal of adjusted analyses was to allow for the effect of

potential confounders so that the effect of a given

exposure was not distorted. Since in our study each

variable held some interest both as an exposure and as

a confounder of other exposures, adjustment was sim-

ply obtained including several exposure terms in a

single multivariate model. Multivariate logistic models

included terms for sex and age of involved persons,

seat belt or helmet use, vehicle type (and, for cars,

engine size), road type, accident type, time of day,

weekday and month. We could not include weight of

vehicle in our analyses, since the Police reported this

information for less than 1% of vehicles. Two-tailed

95%CI were also computed. The models were tested

against the global null hypothesis using the log likeli-

hood ratio test. Their goodness of fit was tested using

the Hosmer and Lemeshow (1989) test.

3. Results

3 .1. All dri ers combined

Table 1 describes accident fatality according to

characteristics of the driver, the accident, the vehicle,

the road and the time of occurrence. Women were less

frequently involved in fatal accidents than men. When

adjustment for other factors was allowed, the OR in-

creased with age. There was a strong direct association

with certain types of vehicles (i.e. motorcycle, bicycle

and truck rather than car), with type of road (i.e.

municipal roads within the urban center were thesafest; the OR increased for other urban roads and

was even higher for accidents outside the urban cen-

ter), and with type of accident (i.e. the most fatal

involved pedestrians). The accident was more likely to

be fatal from 18:00 h to midnight and most of all in

the early morning hours. Fatality was approximately

20% lower for accidents which occurred in the sum-

mer.

3 .2 . Car dri ers

Table 2 displays the relative fatality of accidents

involving car drivers. Of the 13 844 car drivers, 73.6%

were using seat belts at the time of the accident, 8.7%

were not using them and we lack information on use

for the remaining 17.6%. No relevant differences in

seat belt use were seen with regard to sex and age

category (data not shown). The utilization percentage

was lower on provincial and state roads within the

urban center (69.1 and 67.1%, respectively) and on

municipal roads outside the urban center (64.9%),while it was higher on highways (81.5%). Overall,

when death was considered as the outcome, the OR

for non-users of seat belts was 13.27 (95%CI, 9.39 –

18.74). For non-fatal injury, the OR for non-users was

2.49 (95%CI, 2.17 – 2.86). Women had significantly

higher odds of non-fatal injury and lower odds of

fatal injury than men. Older age was strongly associ-

ated with a higher risk of death, whereas drivers aged

30 had the highest risk of non-fatal injury. There

was a strong association both of death and of non-fa-

tal injury with road type, municipal urban roads

having the lowest odds. When non-fatal injury was

the outcome of interest, municipal urban roads had

half the risk of all other roads. When death is

considered, the association with driving on roads

outside the urban center was much stronger (OR=

5.52 (95%CI, 2.39 – 12.77) for municipal non-

urban roads; OR=13.83 (95%CI, 8.43 – 22.70) for

highways). There was a significantly increased OR

both of death and of non-fatal injury after 18:00 h. In

particular, from 1:00 to 5:00 h the OR of injury and

death were approximately two and five, respectively.

Car accidents were more likely to be injurious andfatal during the fall and winter as compared with the

summer months.

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3 .3 . Truck dri ers

Among the 1193 truck drivers involved in accidents,

injury (n=305) and death (n=12) were more likely to

occur when they were driving on roads outside the

urban center and on Sunday and holidays (Table 3).

Table 1

OR and 95%CI of involvement in fatal rather than non-fatal road accidents among vehicle drivers in the Province of Udine, Italy, 1991 – 1996

Drivers involved in road accidentsIndependent variable Adjusted modela

Total Fatal Fatal (%) OR (95% CI)

4.990318 227Total

Sex of dri er

789 5.6 1.00Maleb 14 154

Female 4028 113 2.8 0.65 (0.53 – 0.80)

1 2.2Unknown 45

Age of dri er

318 4.8 1.0030 yearsb 6678

468 4.9 1.1330 – 64 years (0.97 – 1.32)9467

(1.06 – 1.79)1.385.465 years 851565

32Unknown 6.2517

Vehicle type

1.004.562513 845Carb

121 5.7 1.66Motorcycle (including moped) (1.35 – 2.05)2105

Truck 1001193 8.4 1.79 (1.42 – 2.27)

42 5.2Bicycle 2.16813 (1.54 – 3.04)

Other vehicle 1.335.515271 (0.76 – 2.32)

Road type

Within the urban center

8298Municipal roadb 186 2.2 1.00

55 6.0915Provincial road (2.13 – 4.00)2.92

87 4.71838 2.30State road (1.76 – 2.99)

Outside the urban center

Municipal road 36482 7.5 3.64 (2.49 – 5.31)Provincial road 1311697 7.7 3.92 (3.08 – 4.99)

285 (3.54 – 5.28)4.338.1State road 3530

111 8.01386 3.81Highway (2.93 – 4.97)

12 14.8Unknown 81

Accident type

567 4.0 1.00Moving vehicles crashb 14 257

Pedestrian knocking down (3.77 – 6.52)4.9611.373648

86 6.61299 1.48Collision with a stationary object (1.16 – 1.89)

177Other type 8.72023 1.61 (1.33 – 1.95)

Time of day

3.8 1.001646 – 11b 4328

251 3.9 1.0212 – 17 (0.83 – 1.25)6497

336 5.9 1.5818 – 24 (1.30 – 1.92)5644(1.54 – 2.58)2.008.61 – 5 1301514

Unknown 244 22 9.0

Day of week

1.004.757012 196Working Monday – Fridayb

166 5.2 1.01Saturday (0.84 – 1.22)3171

Sunday and holidays 1672860 5.8 1.03 (0.85 – 1.24)

Month

4.62465302July – Septemberb 1.00

248 5.1October – December 1.204850 (0.99 – 1.44)

1.175.11793490January – March (0.96 – 1.43)

230 5.0 1.124585 (0.93 – 1.35)April – June

a Adjusted for all the variables which are shown in the table. −2LogLikelihood=6624.869; 2(28)=562.553; P=0.0001. Hosmer – Lemeshowstatistic=14.86 with 8 DF; P=0.0620.

b Referent category.

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Table 2

OR and 95%CI of injury rather than no consequence and of death rather than no consequence among car drivers in the Province of Udine, Italy,

1991 – 1996

Independent variable Number of drivers Injury vs. no Death vs. no

consequenceconsequence

Dead Non-fatally injuredTotal Unhurt Adjusted modela Adjusted modelb

N % N N % N % OR (95%CI) OR (95%CI)

252 1.8 6529 47.2 7063 51.0Total 13 844

Seat belt use

110 1.1 4570 44.8 5512 54.1 1.00 1.00Yesc 10 192

85 7.0 764 63.2 3591208 29.7No 2.49 (2.17 – 2.86) 13.27 (9.39 – 18.74)

2444Unknown 57 2.3 1195 48.9 1192 48.8

Sex

219 2.1 4665 44.5Malec 559210 476 53.4 1.00 1.00

33 1.0 1864 55.3 1471 43.7Female 1.613368 (1.48 – 1.76) 0.77 (0.51 – 1.16)

Age

86 1.7 2576 51.2 2372 47.1 1.00 1.0030 yearsc 5034

139 1.8 3383 44.9 40047526 53.230 – 64 years 0.86 (0.80 – 0.93) 1.24 (0.91 – 1.69)97565 years 21 2.1 459 47.1 495 50.8 1.01 (0.87 – 1.16) 1.85 (1.08 – 3.18)

6 1.9 111 35.9 192 62.1309Unknown

Engine size (cm3 )

66 1.4 2433 52.9 20961200 45.64595 1.00 1.00

97 2.0 2232 46.0 25274856 52.01200 – 1799 0.78 (0.71 – 0.85) 0.95 (0.67 – 1.35)

28431800 61 2.1 1110 39.0 1672 58.8 0.59 (0.53 – 0.65) 0.79 (0.53 – 1.18)

28Unknown 1.81550 754 48.6 768 49.5

Road type


32 0.5 2314Municipal roadc 38.85965 3619 60.7 1.00 1.00

12Provincial road 1.7692 360 52.0 320 46.2 1.81 (1.54 – 2.13) 3.95 (1.97 – 7.91)

17 1.2 685 48.2 720 50.6 1.551422 (1.37 – 1.75)State road 2.73 (1.49 – 5.01)


8 2.2 213 58.8 141 38.9 2.27 (1.81 – 2.84) 5.52 (2.39 – 12.77)Municipal road 362

40 3.0 798 59.4 5061344 37.6Provincial road 2.52 (2.22 – 2.86) 7.24 (4.40 – 11.92)

2876State road 90 3.1 1553 54.0 1233 42.9 2.12 (1.93 – 2.33) 8.62 (5.63 – 13.20)

48 4.3 579 51.5 497Highway 44.21124 2.43 (2.11 – 2.79) 13.83 (8.43 – 22.70)

5 8.5 27 45.8 27 45.859Unknown

Time of day

41 1.3 1412 44.8 1699 53.9 1.00 1.006 – 11c 3152

62 1.3 2126 44.3 26144802 54.412 – 17 1.00 (0.91 – 1.10) 1.09 (0.72 – 1.66)

439718 – 24 88 2.0 2089 47.5 2220 50.5 1.17 (1.06 – 1.29) 1.75 (1.17 – 2.62)

57 4.4 807 61.7 444 33.91 – 5 2.331308 (2.01 – 2.69) 4.95 (3.09 – 7.95)

4 2.2 95 51.3 86 46.5185Unknown

Day of week Working Monday 8903 156 1.7 4199 47.2 4548 51.1 1.00 1.00

– Fridayc

Saturday 2583 55 2.1 1195 46.3 1333 51.6 0.90 (0.82 – 0.99) 0.87 (0.62 – 1.23)

41 1.7 1135 48.1 1182 50.1 0.882358 (0.80 – 0.97)Sunday and holidays 0.60 (0.40 – 0.88)

Month

74 1.9July – Septemberc 16543856 42.9 2128 55.2 1.00 1.00

73 1.9 1897 49.8 18423812 48.3October – December 1.41 (1.28 – 1.55) 1.40 (0.98 – 2.02)

2761January – March 46 1.7 1399 50.7 1316 47.7 1.47 (1.32 – 1.63) 1.34 (0.89 – 2.01)

3415April – June 59 1.7 1579 46.2 1777 52.0 1.18 (1.07 – 1.31) 1.13 (0.78 – 1.65)

a Adjusted for all the variables which are shown in the table. −2LogLikelihood=17674.172; 2(25)=1147.356; P=0.0001. Hosmer – Lemeshow

statistic=7.73 with 8 DF; P=0.4605.b Adjusted for all the variables which are shown in the table. −2LogLikelihood=1707.739; 2(25)=485.078; P=0.0001. Hosmer – Lemeshow

statistic=7.30 with 8 DF; P=0.5045.c Referent category.

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Table 3

OR and 95% CI of injury rather than no consequence and of death rather than no consequence among truck drivers in the Province of Udine,

Italy, 1991 – 1996

Injury vs. no consequenceIndependent Death vs. no consequenceNumber of drivers

variable

Non-fatallyTotal Dead Unhurt Adjusted modela Adjusted modelb

injured

% N %N N % OR (95%CI) OR (95%CI)N

121193 1.0 305 25.6 876 73.4Total

Seat belt use

1.1 77 29.1 185Yesc 69.8265 1.00 1.003

0.8 114 29.2 273 70.0No 0.92390 (0.93 – 1.33) 0.66 (0.12 – 3.60)3

1.1 114 21.2 418 77.76Unknown 538

Sex

1.0 288 24.8 861 74.2Malec 1.001161 1.0012

0 17 53.1 15 46.9 3.78 (1.79 – 8.02)0 – 32Female

Age

334 5 1.5 103 30.8 226 67.7 1.0030 yearsc

806 7 0.9 186 23.1 613 76.0 0.67 (0.50 – 0.91) 0.46 (0.13 – 1.58)30 – 64 years

0 9 42.9 12 57.10 2.0265 years (0.77 – 5.30) – 21

0Unknown 732 21.9 25 78.10

Road type


0.6 49 14.1Municipal roadc 296347 85.3 1.00 1.002

2.1 8 16.7 39Provincial road 81.248 1.33 (0.57 – 3.08) 5.05 (0.42 – 61.03)1

1.5 25 18.2 110 80.3 1.53 (0.89 – 2.63)2 2.77State road (0.37 – 20.65)137


030 0 13 43.3 17 56.7 5.48 (2.45 – 12.28) – Municipal road

2.8 35 32.4 70 64.83 3.13Provincial road (1.85 – 5.30) 8.77 (1.26 – 61.04)108

2301 0.7 92 30.6 207 68.8 2.95 (1.97 – 4.41) 1.63 (0.22 – 12.25)State road

Highway 0.9217 83 38.2 132 60.8 3.78 (2.44 – 5.86) 1.97 (0.24 – 16.40)20 0 0 5 100.00Unknown 5

Time of day

391 6 1.5 94 24.0 291 74.4 1.00 1.006 – 11c

0.6 118 23.9 372 75.53 0.92493 (0.66 – 1.28) 0.31 (0.07 – 1.36)12 – 17

0.5 57 26.4 158 73.118 – 24 1.05216 (0.70 – 1.58) 0.22 (0.02 – 2.03)1

2.6 30 38.5 46 59.02 1.361 – 5 (0.77 – 2.38) 1.23 (0.19 – 8.02)78

0 6 40.0 9 50.0Unknown 15 0

Day of week

8 0.8 255 24.8Working Monday 7671030 74.5 1.00 1.00

– Fridayc

1.9 30 28.3 74 69.8Saturday 1.07106 (0.67 – 1.72) 2.38 (0.45 – 12.53)2

2 3.5 20 35.1 35 61.4 1.7957 (0.97 – 3.32)Sunday and 5.72 (0.99 – 33.09)

holidays

Month

0.9 77 24.4 236 74.7 1.00July – Septemberc 1.00316 3

2 0.6 83 26.2 232 73.2317 1.05October (0.72 – 1.54) 0.57 (0.09 – 3.59)

– December

January – March 4 1.6 58 22.6 195 75.9 1.00 (0.66 – 1.51) 1.34 (0.27 – 6.57)257

303 3 1.0 87 28.7 213 70.3 1.24 (0.85 – 1.82) 1.10 (0.20 – 5.92)April – June


statistic=6.42 with 8 DF; P=0.6002.b Adjusted for all the variables which are shown in the table. −2LogLikelihood=108.732; 2(22)=18.403; P=0.6819. Hosmer – Lemeshow

statistic=5.00 with 8 DF; P=0.7572.c Referent category.

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Table 4

OR and 95%CI of death rather than non-fatal injury among motorcycle riders in the Province of Udine, Italy, 1991 – 1996

Independent variable Number of drivers Death vs. non-fatal injury

Adjusted modelaUnhurtNon-fatally injuredDeadTotal

% N % ORN (95%CI)N % N

86.7 7.254Total 745 45 6.0 646

Helmet use

37606 39Yesb 6.1 6.4 1.0087.5530

2.9 1.73 (0.45 – 6.70)No 34 3 8.8 30 88.2 1

81.9 14 13.3Unknown 105 5 4.8 86

Sex

1.007.55486.4623Maleb 721 44 6.1

0095.8234.21 0.6324Female (0.07 – 5.23)

Age

87.6 30 6.6 1.0030 yearsb 452 26 5.7 396

(0.93 – 3.92)1.917.81985.230 – 64 years 2087.017244

100.0 0 0 – 65 years 16 0 0 16

78.8 5 15.1Unknown 33 2 6.1 26

Road type


87.5 9.7 1.0038344Municipal roadb 393 11 2.8

5 11.4 37 84.1 2 4.5 3.21Provincial road (1.00 – 10.36)44

91.2 2 2.9 1.53State road 68 4 (0.45 – 5.19)5.9 62


3.585.911411.82Municipal road 17 (0.62 – 20.64)82.3

85.95512.58 164Provincial road 1.6 3.51 (1.26 – 9.75)

6 4.8 2.30State road 125 10 8.0 109 87.2 (0.91 – 5.80)

(0.32 – 8.97)1.6913.8479.3Highway 236.9229

40.0 0 0Unknown 5 3 60.0 2

Time of day89.1 14 9.5 1.006 – 11b 147 2 1.4 131

7.189.4 182283.5912 – 17 (0.59 – 13.58)2.83255

84.82348.022 20276 6.6718 – 24 (1.49 – 29.95)7.2

79.2 2 3.8 13.44 (2.54 – 71.05)1 – 5 53 9 17.0 42

78.6 0 0Unknown 14 3 21.4 11

Day of week

6.1263795.423428Working Monday – Fridayb 1.0088.5

1186.69137 86.1Saturday 10 7.3 0.95 (0.40 – 2.27)

18 10.0 1.20Sunday and holidays 180 13 7.2 149 (0.55 – 2.61)82.8

Month

2088.52775.116313July – Septemberb 1.006.4

86.7 5 4.8 2.58October – December 105 9 8.6 (1.01 – 6.61)91

7 9.3 0.37January – March 75 1 1.3 67 (0.05 – 2.99)89.383.7 22 8.7 2.04 (0.95 – 4.36)April – June 252 19 7.5 211


statistic=12.43 with 8 DF; P=0.1329.b Referent category.

3 .4 . Motorcycle riders

Female motorcycle drivers and motorcyclists aged

65 were 3 and 2%, respectively (Tables 2 and 4).Among all riders, 81.3% were wearing helmets at the

moment of the accident; only 4.6% were not wearing

them and information on helmet use was missing for

14.1% of all motorcyclists. The OR for not wearing a

helmet was 1.73 (95%CI, 0.45 – 6.70). Fatal accidents

occurred relatively more frequently on provincial roads,both within and outside the urban center. Other risk

factors for fatal accidents among motorcyclists were

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evening (OR=6.67; 95%CI, 1.49 – 29.95) and early

morning hours (OR=13.44; 95%CI, 2.54 – 71.05) and

season (fall and spring).

3 .5 . Moped riders

Fifty moped riders died during the study period and

1253 were injured (Table 5). Only 15.6% of all moped

riders were using helmets when the accident occurred

while 42.9% were not and information on helmet use

was lacking for 41.5% of all riders. Wearing helmets at

the moment of the accident was almost exclusively

restricted to subjects under 30 years of age (30.7 vs.

3.0% among subjects 30 – 64 and 1.3% among elderly

riders, data not shown). The adjusted OR for not

wearing a helmet was 1.02 (95%CI, 0.36 – 2.89). When

Table 5

OR and 95%CI of death rather than non-fatal injury among moped riders in the Province of Udine, Italy, 1991 – 1996

Death vs. non-fatal injuryNumber of driversIndependent variable

Non-fatally injured Unhurt Adjusted modelaTotal Dead

N % N % OR (95%CI)N % N

50 4.21360 57Total 92.112533.7

Helmet use

190 89.6 16 7.5 1.00212Yesb 6 2.8583 25 4.3 544No 93.3 (0.36 – 2.89)1.022.414

91.919565Unknown 4.8275193.4

Sex

46 4.3 1.00Maleb 1074 46 4.3 982 91.4

286 94.8 11 3.8 0.44 (0.15 – 1.29)4 1.4Female 271

Age

1.005.25192.3 291330 yearsb 561 92.5

3.4 1.44 (0.63 – 3.29)17505 1730 – 64 years 93.34713.4

5 2.1 3.5365 years (1.42 – 8.78)233 15 6.4 213 91.4

Unknown 661 9.85 8.2 50 82.0

Road type

Within the urban center42 4.7Municipal roadb 1.00893 19 2.1 832 93.2

78 3 3.8Provincial road (0.58 – 7.49)71 2.095.1491.0

98.2114 (0.04 – 2.68)State road 0.340.911120.91


1 2.0Municipal road 4.2150 (1.28 – 13.91)4 8.0 45 90.0

13 12.9 85 84.2 3 3.0 6.35Provincial road 101 (2.88 – 13.98)

5.0 3.85 (1.65 – 8.96)68.3 104120 10 86.7State road

0 0 – Highway 1 0 0 1 100.0

100.03 0 00 0 3Unknown

Time of day

1.002.9994.56 – 11b 2922.68309

22 4.2 0.94 (0.38 – 2.32)12 – 17 526 15 2.8 489 93.0

461 21 4.618 – 24 (0.79 – 4.64)417 1.915.02390.56 (2.42 – 31.69)491 – 5 8.766.134012.2 81.6

0 0Unknown 15 0 0 15 100.0

Day of week

42 4.1Working Monday – Fridayb 1.001018 36 3.5 940 92.3

(0.34 – 1.92)189 8 4.2 173 91.5 8 4.2 0.81Saturday

4.6 0.56 (0.20 – 1.51)Sunday and holidays 76153 3.9 140 91.5

Month

25 5.4 1.00July – Septemberb 459 11 2.4 423 92.2

319 93.3 11 3.2 1.57 (0.65 – 3.80)12October – December 3.5342

8 3.6January – March 3.49223 (1.51 – 8.08)17 7.6 198 88.8

April – June 93.13133.010 (0.56 – 3.49)1.403.9336 13



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Table 6

OR and 95%CI of death rather than non-fatal injury among cyclists in the Province of Udine, Italy, 1991 – 1996

Independent variable Death vs. non-fatal injuryNumber of cyclists

Dead Non-fatally injuredTotal Unhurt Adjusted modela

N %N N % N % OR (95%CI)

Total 41813 5.0 733 90.2 39 4.8

Sex

29 5.8 437Maleb 87.4500 34 6.8 1.00

12 3.8 296 94.6Female 5313 1.6 0.86 (0.40 – 1.82)

Age

5 1.9 23430 yearsb 89.3262 23 8.8 1.00

30 – 64 years 252 13 5.2 231 91.7 8 3.2 3.28 (1.08 – 9.99)

23 8.2 253 90.7279 365 years 1.1 7.72 (2.56 – 23.29)

0 0 15 75.0 5 25.0Unknown 20

Road type


16 2.7Municipal roadb 545586 93.0 25 4.3 1.00

3 9.1 29Provincial road 87.933 1 3.0 3.19 (0.80 – 12.70)5 7.8 55 85.9 4 6.264 2.86State road (0.92 – 8.91)


2 11.1 16Municipal road 88.918 0 0 4.93 (0.94 – 25.85)

6 10.9 43 78.255 6Provincial road 10.9 4.85 (1.68 – 14.02)

9 16.7 43 79.6State road 254 3.7 10.23 (3.85 – 27.19)

0 0 0 00 0Highway 0 –

3Unknown 0 0 2 66.7 1 33.3

Time of day

9 3.6 233 92.1253 116 – 11b 4.3 1.00

32112 – 17 10 3.1 291 90.6 20 6.2 1.00 (0.38 – 2.66)

21518 – 24 20 9.3 187 87.0 8 3.7 5.02 (2.00 – 12.61)

1 8.3 11 91.712 01 – 5 0 3.22 (0.28 – 36.69)

1 8.3 11 91.7 0 0Unknown 12

Day of week

32 5.2 553Working Monday – Fridayb 89.8616 31 5.0 1.00

7Saturday 6.7105 94 89.5 4 3.8 0.79 (0.31 – 2.03)

2 2.2 86 93.5 4 4.392 0.22Sunday and holidays (0.04 – 1.09)

Month

11 3.9 256July – Septemberb 91.8279 12 4.3 1.00

10 4.9 184 91.1202 8October – December 4.0 1.38 (0.52 – 3.64)

6 5.5 98 89.9 5 4.6 1.27January – March (0.41 – 3.95)109

14 6.3 195 87.4223 14April – June 6.3 1.72 (0.71 – 4.15)


statistic=11.91 with 8 DF; P=0.1554.b Referent category.

we repeated the analysis stratifying by age, road type

and type of accident, we found that any excess was

restricted to riders under 18 years of age (OR=4.11

(95%CI, 0.89 – 18.98)), to municipal roads (OR=3.13

(95%CI, 0.39 – 24.95) and falls from mopeds, mopeds

crashing into stationary objects, leaving the road or

knocking down pedestrians (OR= infinity (95%CI,

0.31 – )). Women represent 21% of moped riders and

among them the odds of death were lower than amongmen. There is evidence of an increase in odds ratios as

age increased, on roads outside the urban center, by

night (OR=8.76 from 1:00 to 5:00 h; 95%CI, 2.42 –

31.69) and in winter (OR=3.49; 1.51 – 8.08).

3 .6 . Cyclists

Forty-one cyclists died in the 6-year period and 733

got injured on the road (Table 6). Age was strongly

associated with death (OR=3.28 (95%CI, 1.08 – 9.99)

among middle-aged cyclists and OR=7.72 (95%CI,2.56 – 23.29) among the elderly). Fatality was signifi-

cantly increased among cyclists who were involved in

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accidents on non-municipal urban roads; the highest

OR refers to non-urban state roads (OR=10.23;

95%CI, 3.85 – 27.19) and at night.

3 .7 . Pedestrians

Table 7 shows the distribution of events and OR

regarding pedestrians. Males have significantly higherodds of fatal injuries than women. Among the elderly

there was a 10-fold increased fatality as compared with

subjects 30 years of age. Non-urban roads, time

(between 18:00 and 5:00 h) and season (winter) were

also associated with fatality among pedestrians.

4. Discussion

4 .1. Car seat belts

Many studies have reported the effectiveness of car

seat belts in preventing injury or death from traf fic

accidents (Newman, 1986; Latimer and Lave, 1987;

Table 7

OR and 95%CI of death rather than non-fatal injury among pedestrians in the Province of Udine, Italy, 1991 – 1996

Number of pedestrians Death vs. non-fatal injuryIndependent variable

Total Dead Non-fatally injured Adjusted modela

N N % N % OR (95%CI)

89.463910.676715Total

Sex

376 53Maleb 14.1 323 85.9 1.00

339 0.4893.2 (0.27 – 0.85)316Female 6.823

Age

7215 1.0030 yearsb 96.72083.3

20 7.9 232 92.1 2.2030 – 64 years (0.86 – 5.59)252

220 43 19.565 years 177 (4.45 – 26.54)10.8780.4

21.4 22 78.628Unknown 6

Road type

Within the urban center37 92.7509 1.00Municipal roadb 4727.3

4 13.8 25 86.2Provincial road 2.4329 (0.71 – 8.25)

9State road 12.373 64 87.7 1.66 (0.71 – 3.88)


Municipal road 8 3 37.5 5 62.5 7.97 (1.44 – 44.02)

(1.38 – 13.62)4.3470.014Provincial road 30.0620

17 27.9State road 4461 72.1 5.55 (2.66 – 11.57)

12 100.0 – Highway 12 0 0

03 100.0Unknown 30

Time of day

13 7.1 170 92.9 1.006 – 11b 183

19 8.5 205 91.5 1.5412 – 17 (0.68 – 3.46)224

35 12.9 236 87.1 2.1418 – 24 (0.99 – 4.60)271(2.58 – 30.52)8.8875.8251 – 5 24.2833

1 25.0Unknown 34 75.0

Day of week

1.0089.947010.153523Working Monday – Fridayb

8.39108 99Saturday 0.6291.7 (0.27 – 1.40)

14Sunday and holidays 16.784 70 83.3 1.17 (0.55 – 2.52)

Month

July – Septemberb 170 8.2 156 91.8 1.0014

1.53223October – December 27 12.1 196 87.9 (0.70 – 3.36)

15.9 132 84.125 2.64157 (1.19 – 5.87)January – March

10 6.1 155 93.9 1.00April – June (0.39 – 2.59)165



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Cooper and Salzberg, 1993; Evans, 1996; Petridou et

al., 1998). Our results support these findings, providing

evidence that restriction prevents both fatal and non-fa-

tal injuries, although risk reduction is larger in associa-

tion with fatalities.

A number of methodological issues deserve a com-

ment. Evans (1996) reported clear evidence that, when

severity of the crash was measured by the amount of vehicle deformation, unbelted drivers were involved in

more severe crashes because travelling at higher speed

and because of other risky habits. This observation

suggests that the association between lack of use of seat

belts and injury severity might be confounded by other

risk taking behaviors. For this reason, we adjusted our

OR for variables related to characteristics of the driver,

the road, and the time of the accident. The association

did not disappear. Nevertheless, since we lack informa-

tion on amount of vehicle deformation (a proxy of

change in speed of the car as a consequence of crash-

ing), we cannot exclude residual confounding or effect

modification by risk taking behaviors other than lack of

seat belt use.

More than 70% of all car drivers were using seat belts

according to the Police inspection of the accident scene,

and little more than 10% were certainly not. A differen-

tial misclassification of seat belt use could have been

possible if some uninjured or not seriously injured

drivers were erroneously classified as restrained. If this

were true, the real protective effect provided by safety

belts would be lower, but this seems to be unlikely for

two reasons. First, according to a survey we conductedin this area in 1998, 63% of people having a car driving

license were regular seat belt users, 26% were occasional

users and 11% were non-users. These values include

subjects both when driving and when sitting as car

passengers, and may be somehow different from per-

centages among drivers only. In spite of that, they

strengthen our confidence in the reliability of the Police

classification, although this value is much higher than

from other national (Campello et al., 1996) and interna-

tional (Centers for Disease Control, 1993, 1995; Petri-

dou et al., 1998) estimates. Second, the Police did not

record the information on restraint for a relevant frac-

tion of drivers (more than 20%), indicating that they

did not report seat belt use unless they were absolutely

sure. We also repeated the analyses considering all

drivers with unknown safety belt use as restrained and

as unrestrained, in the first case the results did not

change, in the second we obtained slightly lower ORs,

but still showing a clear protective effect both for injury

and for death. The ORs for the ‘seat belt use unknown’

category were 1.30 (95%CI, 1.18 – 1.43) for non-fatal

injuries and 2.79 (95%CI, 1.98 – 3.94) when death was

considered.We did not take into account accidents only causing

damage to property, and this probably led to an under-

estimation of the real seat belt protective effect because

it is likely that many drivers involved in accidents had

escaped injury just because they were restrained. Be-

cause the Police classified subjects as dead if death hadoccurred within 7 days from the date of the accident,

fatalities were certainly more than ISTAT reported. It

has been estimated that about 92% of deaths occur

within 7 days and about 97% within 30 days (IstitutoNazionale di Statistica, 1997). In addition, in Italy

deaths occurring from the second to the seventh day are

also underestimated because it is dif ficult for the Policeto follow an injured subject through his hospital move-

ments after 24 h (Istituto Nazionale di Statistica, 1997).

However, this underreporting may affect both re-

strained and unrestrained drivers; therefore, it should

not have affected our findings.The study had several other limitations. First, we did

not perform separate analyses for each accident type,

therefore, it is possible that the real seat belt protection

is lower for certain mechanisms and higher for others,such as frontal crashes, as shown by Newman (1986).

Second, we only estimated the protection for restrained

drivers, therefore, generalization of our results to car

passengers deserves caution. Third, we did not know if

cars were equipped with airbags, but as they work

better if used together with correctly fastened safety

belts, higher ORs among non-users of seat belts may

reflect poorer airbag performances as well. Finally, weconsidered non-fatally injured subjects as a homoge-

neous category because ISTAT/CTT/INC does not dis-

tinguish between light and severe traumas or among

anatomic sites of injury. Different risk values would

have probably been obtained if we had considered them

as separate outcomes.

4 .2 . Helmets

In contrast with others (Sarkar et al., 1995; Rowland

et al., 1996; Petridou et al., 1998), our study found only

a weak, imprecise association between wearing helmets

and fatality among motorcycle riders, and no effect

with regard to moped riders. Several factors, depending

on the nature of the available data, could have pre-vented us from obtaining clear evidence of helmet

protective effect, (a) chance; (b) our study did not

include just those riders who sustained head or neck

injuries, which are the only ones that could be pre-

vented by helmets; (c) different helmet types could be

worn by moped operators, providing various degrees of

protection; (d) we considered as non-fatally injured

riders who died more than 7 days after the accident.

This outcome misclassification could have been differ-ential if non-helmeted riders had sustained more head

injuries leading them to coma and to delayed death

than helmeted subjects had — in this case, helmetef ficacy would have been underestimated; (e) helmetsmay not actually reduce the risk of death.

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The analysis stratified by age suggested a protective

effect of helmet at least among moped riders 18

years of age. The difference in protective ef ficacy be-

tween the youngest riders and the others could be

accounted for by various factors, (a) they could have

been involved in accident of different severity because

of a different riding pattern; (b) helmets could have

caused impairment of seeing and hearing among oldermoped operators increasing rather than reducing the

risk of death; (c) helmets could have damaged older

riders directly, although there are studies contrasting

with this possibility (Wagle et al., 1993); (d) the ex-

tremely low number of events among older helmet users

made the estimates very imprecise; (e) chance alone,

since the analyses are based on small numbers. Helmets

seem to be more effective when riding on municipal

than on provincial and state roads. Since road type may

be considered a good proxy for vehicle speed, accidents

on municipal streets involve on average slower vehicles

and accidents are generally less severe; in such a situa-

tion helmets appear to be the most useful. This is in

accordance with Sarkar et al. (1995) who found that

helmets did not offer much protection in crashes that

led to very severe body damage.

4 .3 . Sex

Women were involved in less serious accidents than

men. In addition, female drivers were less likely to die

in a car accident than male drivers. This is consistent

with findings by Li et al. (1998). However, non-fatalinjuries as opposed to no consequence occurred more

often among women than men. A similar tendency was

also emphasized by Massie et al. (1995). A concurrent

higher risk of accident with lower risk of being involved

in fatal accidents and of being personally killed could

be explained by behavioral differences between sexes,

women being possibly more inattentive or less experi-

enced or skilled than men, but perhaps less risk-taker

(lower speeds, less driving by night, less DUI). In fact,

although we did not have information on vehicle speed,

our data showed that in this area nighttime driving and

DUI are habits almost completely limited to men.

Risky driving habits and lack of vehicle-handling skills

were also pointed out by Laapotti and Keskinen (1998)

as different causes of fatal loss-of-control accidents

between male and female drivers.

4 .4 . Age

The elderly are the weakest road users. In fact, they

have the highest risk of death after an accident both

when driving vehicles, as shown also by Massie et al.

(1995), and when walking, probably because of comor-bility, which reduces the possibility of recovery from

traumas. Mopeds and, most of all, bicycles are the most

dangerous means of transportation for them, not only a

much higher proportion of old subjects was involved in

accidents while riding two-wheeled vehicles than while

driving cars, but, after an accident had occurred, the

risk of death in those cases was much higher than

among subjects 65. A very high proportion of elderly

pedestrians was also involved in accidents and these

subjects seem to be at extremely high risk of beingfatally injured.

4 .5 . Trucks

Our study showed that Sundays and holidays are

particularly dangerous for truck drivers. This finding

supports the law forbidding most types of trucks to

move during these days.

4 .6 . Season

In our area, car drivers and motorcycle riders should

be particularly careful during the fall, because the risk

of death from road accidents is higher than in the rest

of the year. A previous study (Valent, 1998) also

demonstrated a high number of deaths from traf fic

accidents in the 3 months October – December among

the inhabitants of the province of Udine. This mortality

excess might be accounted for by a number of charac-

teristics typical of this area, (a) in October daylight

duration becomes shorter and sunset coincides with

heavy traf fic; moreover, in November there is the

switch from daylight saving time to solar standard timeand, therefore, at rush hour people must drive in the

dark without having got used to that; (b) the province

of Udine is a rather foggy area and in fall this phe-

nomenon becomes considerable; (c) fall is the most

rainy season; (d) in the province of Udine there are

many small mountain villages and the first snowfalls

and frosts often occur in November or in December; (e)

leaves fall from the trees and make the ground slippery;

(f) the consumption of alcohol, that is a well-known

risk factor for severe motor vehicle crashes (Decker et

al., 1988; Baker et al., 1992), may be particularly high

during the fall. Despite the fact that we lack informa-

tion on alcohol consumption by season, in our wine

producing area the new wine starts to be sold and

drunk after September’s grape harvest. Moreover, alco-

hol intake may be increased by the cold because of its

warming effect on drinkers.

4 .7 . Two-wheeled ehicles

Some factors may explain the high fatality among

moped riders from January to March, (a) these months

are darker and mopeds could be seen by car driverswith more dif ficulty, especially if they have weak or no

light; (b) riding a moped on iced surface is particularly

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Petridou, E., Skalkidou, A., Ioannou, N., Trichopoulos, D., 1998.

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Alexander, B., Felix, D., Bergman, A.B., 1994. The Seattle chil-

dren’s bicycle helmet campaign: changes in helmet use and head

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Rowland, J., Rivara, F., Salzberg, P., Soderberg, R., Maier, R.,

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and hospitalization costs from crashes in Washington State. Jour-

nal of Public Health 86, 41 – 45.

Sacks, J.J., Holmgreen, P., Smith, S.M., Sosin, D.M., 1991. Bicycle-

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