United States General Accounting Office

GAO Report to Congressional Requesters

May 1995 HIGHWAY SAFETY

Causes of Injury in

Automobile Crashes

GAO/PEMD-95-4

GAO United States

General Accounting Office

Washington, D.C. 20548

Program Evaluation and

Methodology Division

B-250039 

May 9, 1995

The Honorable Ernest F. Hollings

Ranking Minority Member

Committee on Commerce, Science,

 and Transportation

United States Senate

The Honorable Richard H. Bryan

United States Senate

We are pleased to send you this report on the causes of injury in automobile crashes in

response to your request that we expand our earlier research on automobile safety. In this

study, we reviewed the research literature and conducted analyses of traffic accident data to

examine the effects of crash characteristics, automobile size, safety belts, air bags, and

occupant age and gender on the risk of injury in automobile crashes. The report also discusses

promising areas for further reducing injury risk.

We will be sending copies of this report to the Secretary of Transportation, and we will also

make copies available to others upon request. If you have any questions or would like additional

information, please call me at (202) 512-3092. Other major contributors to this report are listed

in appendix II.

Kwai-Cheung Chan

Director for Program Evaluation

 in Physical Systems Areas
Executive Summary

Purpose In recent years, automobiles have been associated with nearly 29,000

traffic fatalities annually in the United States, including the deaths of both

automobile occupants and others involved in collisions with automobiles.

The Senate Committee on Commerce, Science, and Transportation asked

GAO to study the independent effects of important crash-related factors on

the likelihood of injury once an automobile crash has occurred. This

report addresses these questions: What are the most important predictors

of injury in a crash? How is the risk of injury in a crash affected by the

severity and type of the crash, automobile size, safety belts and air bags,

and the occupant’s age and gender? What are promising areas for reducing

further the crash injury risk of automobile occupants?

Background In Highway Safety: Have Automobile Weight Reductions Increased

Highway Fatalities? (GAO/PEMD-92-1, October 1991), GAO presented a number

of findings regarding the relationship between automobile size and safety.

GAO noted there that the safety consequences of automobile weight or of

any other automobile design factor are confounded by many other factors,

chief among them driver attributes. For example, automobiles that attract

risky drivers may have high fatality rates solely because they have

dangerous drivers, not because the cars themselves are unsafe.

Three further GAO reports examine the safety effects of automobile and

driver characteristics within the larger context of other factors that

influence traffic safety. One, Highway Safety: Factors Affecting

Involvement in Vehicle Crashes (GAO/PEMD-95-3, October 1994), examines

the influence of driver and automobile characteristics on the likelihood of

crash involvement. Another, Highway Safety: Reliability and Validity of DOT

Crash Tests (GAO/PEMD-95-5, May 1995), looks at the extent to which results

from the automobile crash test programs conducted by the National

Highway Traffic Safety Administration (NHTSA) accurately predict injury

risk in crashes.

This, the third report, focuses exclusively on the safety of automobile

occupants (in contrast to that of occupants of other passenger vehicles,

such as vans, minivans, and pick-up trucks). To study this issue, GAO

reviewed technical reports from NHTSA and other sources and consulted

auto safety experts and representatives of automobile manufacturers. GAO

also conducted its own statistical analyses of automobile crash data

obtained from NHTSA. GAO’s statistical analyses looked at the experience of

drivers of relatively new cars in three types of crashes: one-car rollover

Page 2 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Executive Summary

crashes, one-car nonrollover crashes, and collisions with cars, vans,

pick-ups, and other light trucks.

Results in Brief Not surprisingly, speed at impact and crash type are the most important

determinants of the risk of injury to drivers. Driver age and safety belt use

are also important, while automobile weight and the gender of the driver

have less influence. Injury is more likely in high-speed crashes than in

crashes with lower impact velocities, and one-car crashes, particularly

one-car rollovers, are more dangerous than two-vehicle collisions.

Compared to light cars, heavy cars both generally provide their occupants

with more crash protection and pose a greater danger to other roadway

users in multivehicle crashes. However, the protective effects of

automobile weight differ by crash type. Heavy cars offer comparatively

more protection to their occupants in one-car nonrollover and

multivehicle crashes, but once a rollover has occurred, occupants of

heavier cars are more likely to be hurt than are occupants of lighter cars.

Safety belts greatly reduce injury risk, but the effectiveness of safety belts

is not the same in all crashes; they are more effective in single-car crashes

than in multivehicle collisions. Air bags reduce injury risk in frontal

impacts, but air bags alone are less effective than safety belts alone. In

equivalent automobile crashes, women drivers and older drivers are more

likely to be injured than men and younger drivers. GAO found evidence that

safety belts are less effective overall for women drivers than for men

drivers.

Principal Findings

Crash Severity and Crash

Type Are the Most

Important Predictors of

Injury

In GAO’s statistical analysis, speed at impact was the most important

predictor of driver injury, followed by the type of crash, driver age, safety

belt use, automobile weight, and gender of the driver. The risk of driver

hospitalization or death was 25 times greater in very severe crashes (as

measured by speed at impact) than in relatively mild crashes. The risk of

driver injury was 9 times greater in dangerous types of crashes (one-car

rollovers) than in relatively benign crashes (typical two-vehicle collisions).

The risk of driver injury was 4.5 times greater for drivers age 65 and older

than for drivers 16 to 24 years of age, 3 times greater for unbelted drivers

than for drivers wearing manual lap and shoulder safety belts, 63 percent

Page 3 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Executive Summary

greater for drivers of light cars than for drivers of heavy automobiles, and

29 percent greater for women drivers than for men drivers (see chapter 4).

The Effects of Automobile

Weight Differ by Crash

Type

Considering all crash types together, GAO estimates that each 500-pound

increase in car weight reduces the risk of driver injury by 14 percent in

tow-away crashes. However, the protective effect of automobile weight

differs by the type of crash. Compared to light cars, heavier cars offer

more occupant protection in collisions with cars and light trucks, and in

one-car nonrollover crashes, but drivers of heavier cars are more likely to

be injured in one-car rollover crashes, once a rollover has occurred. One

explanation for this is that it takes more energy to roll over a heavier car

than a lighter one, meaning that rollover crashes involving heavy cars are

typically more severe than those involving light cars. GAO estimates that in

multivehicle collisions, each 500-pound increase in automobile weight

decreases a driver’s injury risk by 23 percent but increases the probability

of injury to the driver of the other car by 13 percent (see chapter 2).

The Effects of Safety Belts

and Air Bags Differ by

Crash Type

Safety belts greatly reduce the risk of driver injury in all crashes, but they

are more effective in single-car crashes than in collisions with cars and

light trucks. By comparison, air bags are effective only in frontal impacts,

not in side impacts or rollovers. In addition, air bags offer additional

protection to drivers already wearing lap and shoulder safety belts,

reducing their risk of suffering a serious injury by about 10 percent. Safety

belts alone are much more effective than air bags alone—that is, drivers

wearing safety belts in cars without air bags are much less likely to be

seriously injured than drivers not wearing belts in air bag-equipped cars

(see chapter 2).

Women and Older Drivers

Are More Likely to Be

Injured

In equivalent crashes, women drivers and older drivers are more likely to

be injured then men drivers and younger drivers. The relative risk of injury

for women drivers compared to men drivers differs by the type of crash.

More specifically, GAO estimates that women drivers have an injury risk

approximately 50 percent greater than men drivers in statistically

equivalent two-vehicle collisions but that the injury risk for women drivers

and men drivers does not differ in one-car crashes. This is particularly

important because women drivers are involved in more multivehicle

collisions than one-car crashes, while men have more one-car than

multivehicle crashes. Thus, women drivers are especially likely to be hurt

in the type of crash that they experience most often. In addition, GAO found

Page 4 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Executive Summary

evidence that heavy automobiles and safety belts offer somewhat less

protection for women drivers than for men drivers. In contrast, older

drivers are more likely to be injured in a crash than younger drivers in

almost all circumstances (see chapter 3).

Improving the Safety of

Automobile Occupants

Increasing safety belt use and effectiveness would reduce injury risk for all

automobile occupants. It is particularly important to increase safety belt

use among drivers involved in serious crashes, because they use safety

belts less than other drivers.

Women drivers and older drivers are in fewer crashes than men drivers

and younger drivers, and, because they have more multivehicle than

one-car crashes, the crashes that they are involved in are, on the average,

less severe. Nonetheless, once a crash has occurred, women and,

especially, older drivers are more likely to be injured than men and

younger drivers. For this reason, women and older drivers would benefit

substantially from improvements in automobile crashworthiness. Efforts

to improve the protection of occupants of all sizes, and to improve

protection in side-impact crashes, would be beneficial (see chapter 5).

Recommendations This report contains no recommendations.

Agency Comments In written comments on a draft of this report, the Department of

Transportation (DOT) generally agreed with GAO’s analytic methods and

findings. In addition, DOT had several comments concerning the methods

and findings of particular analyses. Those comments, and GAO’s responses

to them, are presented at the appropriate places in the report. A number of

DOT’s specific technical comments have been incorporated in the report

where appropriate.

Page 5 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Contents

Executive Summary 2

Chapter 1 

Introduction

10

Purpose 10

Background 10

Objective, Scope, and Methodology 14

Organization of the Report 16

Chapter 2 

The Effects of

Automobile Weight,

Automobile Size,

Safety Belts, and Air

Bags in Different

Types of Crashes

17

Crash Characteristics 17

Automobile Weight and Size 20

Safety Belts 28

Air Bags 31

Summary 32

Agency Comments and Our Evaluation 33

Chapter 3 

The Effects of Gender

and Age on Driver

Injury Risk

34

The Vulnerability of Women and Older Drivers 34

Possible Explanations 34

Conclusions and Implications 41

Chapter 4 

The Relative

Importance of Crash

Features, Driver

Characteristics, Safety

Belts, and Automobile

Weight

43

Chapter 5 

Future Automobile

Safety

46

NHTSA Safety Initiatives 46

Injury Reduction for Different Types of Drivers 48

Making Effective Use of Available Safety Technologies 52

Agency Comments and Our Evaluation 54

Page 6 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Contents

Appendixes Appendix I: Regression Analyses for Driver Injury 56

Appendix II: Major Contributors to This Report 70

Bibliography 71

Related GAO Products 80

Tables Table 1.1: Roadway Fatalities Involving Automobiles, 1991 11

Table 2.1: Automobile Occupant Fatalities by Rollover or

Principal Impact Point, 1991

18

Table 2.2: Driver Injury, Driver Characteristics, and Automobile

Weight, by Crash Type

19

Table 3.1: Safety Belt Use by Driver’s Injury Outcome and Gender 38

Table 3.2: Safety Belt Use by Driver’s Injury Outcome and Age 41

Table 4.1: Relative Importance of Crash-Related Factors in

Predicting Driver Hospitalization or Death

43

Table I.1: One-Car Crashes and Collisions With Other Cars or

Light Trucks: Logistic Regression Analysis Predicting Driver

Hospitalization or Death, Model With Curb Weight

59

Table I.2: One-Car Crashes and Collisions With Other Cars or

Light Trucks: Logistic Regression Analysis Predicting Driver

Hospitalization or Death, Model With Wheelbase

60

Table I.3: One-Car Rollover Crashes: Logistic Regression Analysis

Predicting Driver Hospitalization or Death, Model With Curb

Weight

62

Table I.4: One-Car Nonrollover Crashes: Logistic Regression

Analysis Predicting Driver Hospitalization or Death, Model With

Curb Weight

63

Table I.5: Collisions With Cars and Light Trucks: Logistic

Regression Analysis Predicting Driver Hospitalization or Death,

Model With Curb Weight

64

Table I.6: One-Car Rollover Crashes: Logistic Regression Analysis

Predicting Driver Hospitalization or Death, Model With

Wheelbase

66

Table I.7: One-Car Nonrollover Crashes: Logistic Regression

Analysis Predicting Driver Hospitalization or Death, Model With

Wheelbase

67

Table I.8: Collisions With Cars and Light Trucks: Logistic

Regression Analysis Predicting Driver Hospitalization or Death,

Model With Wheelbase

68

Page 7 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Contents

Figures Figure 2.1: Estimated Probability of Driver Hospitalization or

Death in One-Car Crashes and Collisions With Other Cars or

Light Trucks, by Automobile Weight and Wheelbase

23

Figure 2.2: Estimated Probability of Driver Hospitalization or

Death by Crash Type and Automobile Weight

24

Figure 2.3: Estimated Probability of Driver Hospitalization or

Death by Crash Type and Automobile Wheelbase

25

Figure 2.4: Estimated Probability of Driver Hospitalization or

Death in Collisions With Other Cars or Light Trucks by Weight of

the Other Vehicle

27

Figure 2.5: Estimated Probability of Driver Hospitalization or

Death in Collisions With Other Cars or Light Trucks by Type of

the Other Vehicle

28

Figure 2.6: Estimated Probability of Driver Hospitalization or

Death in One-Car Crashes and Collisions With Other Cars or

Light Trucks by Safety Belt Use

31

Figure 3.1: Distribution of Driver Hospitalization or Death by

Crash Type and Gender

36

Figure 3.2: Distribution of Driver Hospitalization or Death by

Crash Type and Driver Age

39

Figure 4.1: Odds of Injury Associated With Changes in

Crash-Related Factors

45

Abbreviations

AIS Abbreviated Injury Scale

DOT Department of Transportation

FARS Fatal Accident Reporting System

GAO U.S. General Accounting Office

IIHS Insurance Institute for Highway Safety

JAMA Journal of the American Medical Association

NASS National Accident Sampling System—Crashworthiness Data

System

NHTSA National Highway Traffic Safety Administration

SUDAAN Survey Data Analysis

Page 8 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Page 9 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 1 

Introduction

Purpose In recent years, automobiles have been associated with nearly 29,000

traffic fatalities annually in the United States, including the deaths of both

automobile occupants and others involved in collisions with automobiles.1

The National Highway Traffic Safety Administration (NHTSA), a unit of the

Department of Transportation (DOT), has the lead role in federal

government efforts to reduce the number of traffic crashes and to

minimize their consequences. Some types of automobiles have higher

fatality rates than others. (For example, small cars generally have higher

rates than large cars.) In addition, some categories of drivers are more

likely to be involved in serious crashes than others. (Young drivers, for

example, have higher involvement rates than other drivers.) However, as

we previously reported, one cannot conclude from differences in fatality

rates that some types of cars, or some types of drivers, are in fact more

dangerous than others, because driver and automobile characteristics are

highly related (GAO, 1991). For example, since small cars have a

disproportionate percentage of young drivers, do the high fatality rates for

those cars stem from vehicle characteristics or the recklessness with

which they are operated?

The goal of this report is to isolate the independent effects of important

crash-related factors on the likelihood of injury in a collision. The report

focuses on the most important predictors of occupant injury in a collision:

crash type and crash severity, automobile size, safety belt use, and

occupant age and gender. The report is concerned with both

crashworthiness (protecting automobile occupants) and aggressivity

(protecting other roadway users struck by automobiles). The report also

considers prospects for improving the safety of automobile occupants.

This report is one of three GAO reports examining automobile safety. One

of these, Highway Safety: Factors Affecting Involvement in Vehicle

Crashes (GAO, 1994), examines the independent effects of driver

characteristics and automobile size on crash involvement. Another,

Highway Safety: Reliability and Validity of DOT Crash Tests (GAO/PEMD-95-5),

looks at the extent to which results from the crash test programs

conducted by NHTSA accurately predict injury in actual automobile crashes.

Background Since the mid-1960’s, both the number of traffic fatalities and the fatality

rate per registered vehicle have sharply decreased in the United States.

1

We use the terms “automobile,” “auto,” and “car” interchangeably in this report. We define

automobiles as convertibles, sedans, hatchbacks, and station wagons. This definition specifically

excludes other types of passenger vehicles, such as vans, minivans, multipurpose vehicles, and pickup

trucks.

Page 10 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 1 

Introduction

The fatality rate for automobile occupants has declined by 36 percent

since 1975. The continued emphases on reducing drunk driving and

increasing safety belt use, along with the introduction of antilock brakes,

air bags, and other safety enhancing features, have increased the chances

that this favorable trend will continue. Nonetheless, in 1991 automobiles

were associated with nearly 29,000 traffic deaths in the United States.2

About 22,000 of the automobile-related fatalities were automobile

occupants (about 10,000 killed in single-car collisions and 12,000 in

multiple-vehicle collisions), about 2,500 were occupants of other types of

vehicles (for example, light trucks, vans, or motorcycles) involved in

collisions with automobiles, and approximately 4,000 were pedestrians or

cyclists hit by automobiles. (See table 1.1.)

Table 1.1: Roadway Fatalities Involving Automobiles, 1991

Number of fatalities

Crash typea

Automobile 

occupants

Occupants of 

other vehicles

Pedestrians 

and cyclists Total

Single-car rollover 4,519 0 17 4,536

Single-car nonrollover 5,495 0 3,529 9,024

Two cars 4,638 0 170 4,808

Car and motorcycle 20 717 6 743

Car and light truck 3,466 955 124 4,545

Car and heavy truck 2,277 59 37 2,373

Car and other vehicle 72 60 19 151

Three or more vehicles 1,744 686 112 2,542

Total 22,231 2,477 4,014 28,722

aThe crash type categories are mutually exclusive. We defined automobiles as Fatal Accident

Reporting System (FARS) body type codes 1-9 (including convertibles, two- and four-door

sedans, three- and five-door hatchbacks, and station wagons but not vans or minivans). Light

trucks are FARS body type codes 10-39 (including auto-based pickups, vans, minivans, and

utility vehicles). Heavy trucks are codes 40-79 and 93; motorcycles are codes 80-82, 88, and 89;

and other vehicles are codes 90-92, 97, and 99 (including all-terrain vehicles, snowmobiles, and

farm equipment).

Source: Our analysis of 1991 FARS data from National Highway Traffic Safety Administration,

Fatal Accident Reporting System 1991, DOT-HS-807-954 (Washington, D.C.: 1993).

Different models of automobiles appear to make very different

contributions to this fatality toll. For instance, the Insurance Institute for

Highway Safety (IIHS) has reported that the most “dangerous” automobile

models have occupant fatality rates more than nine times higher than the

2

In 1991, the total number of U.S. traffic fatalities was 41,462 (including deaths not related to

automobiles).

Page 11 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 1 

Introduction

“safest” models.3 Further, some of the automobile characteristics

associated with this variation in fatality rates are well known. For

instance, sports cars have higher fatality rates than station wagons, and

small cars have higher fatality rates than large cars.4

However, this does not mean that types of automobiles with high fatality

rates are necessarily more dangerous than those with low fatality rates.

This is because different types of drivers prefer particular types of

automobiles, affecting both the number of collisions involving particular

autos and, perhaps, the probability of serious injury in the event of a

collision. For example, young drivers are much more likely to be involved

in fatal accidents than others—drivers age 16 to 20 are involved in fatal

accidents at a rate three times higher than that for drivers age 45 to

54—thereby inflating the fatality rate for types of cars preferred by young

drivers. Similarly, some types of automobile occupants are more likely to

be seriously injured in a collision than others. For example, in collisions in

which at least one vehicle was towed from the accident scene, NHTSA

(1992a) recently estimated that women automobile occupants are about

36 percent more likely to be hurt than men occupants in similar collisions.

This suggests that types of cars with a disproportionate number of women

occupants may have higher fatality rates than other cars.

Injury Mechanisms As automobiles abruptly stop or change direction in a collision, occupants

continue moving in the original direction of travel. This independent

movement of an occupant within a rigid vehicle that is decelerating more

quickly than its occupant provides several opportunities for injury. First,

some occupants are injured by being ejected (either partially or totally)

from the vehicle. Ejection substantially increases the risk of serious

injury—ejected occupants are three to four times more likely to be killed

in a collision than occupants who do not leave the vehicle. Second,

occupants can collide with the interior of the vehicle or other objects

intruding into the passenger compartment. This “second collision”

(following the “first collision” of the automobile striking an object) is

understandably worse if it occurs at high speed, involves impact with a

sharp or unyielding portion of the car’s interior, or involves contact with

part of another vehicle or a roadside object that has penetrated the

passenger compartment. Finally, because different portions of an

3

For example, IIHS (1991) reported that the automobile model with the highest fatality rate in the late

1980’s was the Chevrolet Corvette Coupe, with 4.7 deaths per 10,000 registered vehicles. The Volvo 240

had the lowest fatality rate for that period at 0.5 deaths per 10,000 registered vehicles.

4

For example, according to the IIHS (1991) report of fatality rates in the late 1980’s, the fatality rate for

midsize sports cars was 2.5 times that of midsize station wagons and vans. For four-door cars, the

fatality rate for small cars was 40 percent greater than the rate for large cars.

Page 12 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 1 

Introduction

occupant’s body decelerate at different rates, internal injuries can be

caused by the “third collision” of soft tissues against hard, bony structures.

For example, in high-speed collisions, the skull decelerates more quickly

than the brain, potentially causing injury to the brain as it strikes the hard

skull.

Automobile Safety Design Automobiles, and federal automobile safety regulations, are designed to

protect their occupants from these dangers in several ways. One way is to

attempt to reduce the deceleration forces acting on occupants.

Deceleration forces can be reduced by designing the structure of a vehicle

to absorb as much energy as possible before the crash forces are

transmitted to the passenger compartment or by giving the occupant more

time to slow down, thereby reducing the maximum force level the

occupant is subjected to. The latter can be accomplished by starting the

deceleration period more quickly (for example, by designing safety belts

that begin holding back the occupant sooner) or by increasing the total

deceleration period (for example, by lengthening the front end of the

vehicle).

Another way cars may protect their occupants is by encasing them in a

protective compartment that preserves a living space and prevents the

intrusion into the passenger compartment of striking vehicles or other

objects (such as light posts or trees) that a car hits. Third, automobiles are

designed to keep their occupants both in the vehicle and away from

interior surfaces. This is most obviously accomplished through the use of

safety belts, but a number of other components are also intended to keep

the occupant in the vehicle, including door latches and windshields that

are reinforced to eliminate potential ejection routes. In addition,

automobile interiors are designed to absorb energy from the occupant and

to limit the occupant’s movement rather than serve as a rigid barrier.

Energy absorbing steering columns are one example.

There is little doubt that cars from recent model years, as a group, are

safer than automobiles from past model years and that some of this

improvement can be attributed to federal government safety regulations.

For instance, in comparing the crash test results of cars from model years

1980 and 1991, NHTSA researchers found that one set of scores measuring

injury potential had declined about 30 percent during the intervening years

(Hackney, 1991). Similarly, Evans (1991b) estimated that the total effect of

nine federal motor vehicle safety standards enacted by 1989 had been to

reduce the occupant fatality rate by about 11 percent.

Page 13 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 1 

Introduction

Objective, Scope, and

Methodology

Objective The objective of this report is to examine the independent effects of a

number of factors—crash type, crash severity, automobile weight and size,

safety belt use, and occupant age and gender—on the risk of injury in an

automobile crash. We are concerned with both crashworthiness and

aggressivity. Crashworthiness refers to the extent to which automobiles

protect their occupants in a collision, and aggressivity refers to automobile

characteristics that affect the safety of the occupants of the other vehicles

in a collision.

Scope We restricted the scope of the study in several ways in order to obtain a

clear picture of the most important phenomena. First, we looked only at

the safety of automobile occupants and the dangers automobiles pose to

occupants of other vehicles. We were not directly concerned with factors

affecting the safety of occupants of other types of passenger vehicles, such

as pickup trucks, vans, minivans, and multipurpose vehicles; we

considered these vehicles only as they affect the safety of automobile

drivers in two-vehicle collisions. In our judgment, concerns about the

safety of light trucks and other passenger vehicles differ significantly from

that of automobiles. Light trucks and other passenger vehicles are less

stable and thus roll over more frequently than automobiles, and they have

been subject to less stringent safety regulations than automobiles.

Second, our statistical analysis focused on model year 1987 and later cars,

because the safety experiences of those cars are more likely to apply to

today’s new cars than are the safety experiences of older ones. Finally, we

considered in our analysis only the injury experiences of drivers, not those

of automobile passengers or factors specifically affecting the safety of

child occupants. (Roughly half of the automobiles on the road have no

occupants other than the driver.)

Methodology To meet our objective, we reviewed technical reports from NHTSA and

other sources and consulted auto safety experts and representatives of

automobile manufacturers. We also conducted our own statistical analyses

of traffic safety databases obtained from NHTSA. Our primary data set was

compiled from the National Accident Sampling System—Crashworthiness

Page 14 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 1 

Introduction

Data System (NASS) for 1988 through 1991. NASS is a nationally

representative probability sample of all police-reported crashes involving a

passenger car, light truck, or van in which at least one vehicle was towed

from the scene. In addition, all the automobiles included in NASS were

towed from the crash site. Thus, the automobiles in NASS, as a whole, are

much more likely to have injured occupants than are cars involved in

typical crashes. Not only are police-reported crashes more severe than

those not reported to the police, but tow-away crashes on the whole are

also more severe than those not involving tow-aways. Indeed, almost all

serious occupant injuries occur in police-reported tow-away collisions.5

For our analysis, we selected a subset of cases from the NASS data for 1988

through 1991. We included all one-car collisions involving a 1987 or newer

model year automobile and all collisions between a model year 1987 or

later automobile and any other car, van, pickup truck, or other light truck.

These crash types, taken together, accounted for about 81 percent of all

automobile occupant fatalities in 1991. The remaining 19 percent occurred

in types of crashes that we did not include in our data set because of a

lack of cases, principally collisions with medium and heavy trucks (about

10 percent of the 1991 total).

In our statistical analyses, we used logistic regression to look at the

independent contributions of a variety of factors on the probability of

driver injury.6

 Driver injury was indexed with a dichotomous outcome

variable coded “1” if the driver was hospitalized or killed in the crash and

“0” otherwise. The regression analysis allowed us to isolate the effects of

one factor (for example, automobile weight) while statistically holding

constant the other factors (for example, collision severity as well as driver

age and gender). Regression analysis answers the question: If there were

no differences among these drivers except for the factor of automobile

weight, for example, how would that factor predict the probability of

driver injury? (The data sets and analyses are described in appendix I.)

5

For example, in a separate analysis not detailed here, we examined all police-reported crashes for

model year 1987 to 1989 cars in North Carolina for calendar year 1990. Injuries to automobile drivers

categorized as “serious” by North Carolina law enforcement personnel occurred about 39 times more

often in crashes in which at least one vehicle was towed away than in other crashes, and 97 percent of

all “serious” driver injuries were in tow-away crashes.

6

For the logistic regressions, we used the Survey Data Analysis (SUDAAN) statistical package.

SUDAAN takes into account the stratification and unequal selection probabilities inherent in the

sampling design of NASS. Failure to consider the sampling design in the regressions is likely to

produce artificially low standard errors, biasing the analysis in favor of finding relationships that

appear to be statistically significant but that stem, in fact, from chance. For more information about

the sampling plan for NASS, see NHTSA (1991c). For more information about SUDAAN, see Shah et al.

(1992).

Page 15 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 1 

Introduction

The studies that we reviewed from the traffic safety literature differed in

several ways that increase the difficulty of comparing their results and of

relating their conclusions to our own findings. For instance, some studies

focused on injuries to automobile drivers, as we did, while others

examined injuries to all automobile occupants, not just drivers. Similarly,

different studies looked at slightly different sets of automobile crashes—at

tow-away crashes (as we did) or at all police-reported crashes or only at

crashes in which a fatality occurred. In addition, the studies employed

different outcome measures. Our analysis concerned driver

hospitalizations or deaths, while other studies looked only at fatalities or

at injuries considered serious or worse or at injuries categorized as

moderately severe or worse, for example. While these and other

differences mean that the studies we cite rarely produced precisely

equivalent findings, in most the findings were roughly the same. In

particular, the direction of the findings was almost always the same (that

is, whether a factor increases or decreases the risk of injury), and there

was usually approximate agreement about the size of the effect (that is,

whether a factor has a large effect on injury risk or only a minor

influence).7

Our work was performed in accordance with generally accepted

government auditing standards.

Organization of the

Report

Chapter 2 looks at the effects of crash type and crash severity. It also

discusses the effects of automobile size and safety belt use in three

different configurations: one-car rollover crashes, one-car nonrollover

crashes, and collisions between cars and other light vehicles. Chapter 3

examines the influence of driver age and gender on injury probability.

Chapter 4 discusses the relative contributions of driver and automobile

factors to driver injury. Chapter 5 discusses the potential for improving

automobile safety. Appendix I describes our data set and statistical

analyses.

7

In general, because our data set included only very severe crashes, the effect sizes from our analyses

were somewhat larger than those reported from analyses using a wider range of crashes. The reason

for this is that almost all serious injuries occur in police-reported tow-away crashes, and data sets with

a wider range of crashes thus necessarily include a high proportion of cases without serious injuries.

Therefore, any statistical relationships are diluted by the presence of many cases in which there is

little chance of injury regardless of the values of the independent variables.

Page 16 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 2 

The Effects of Automobile Weight,

Automobile Size, Safety Belts, and Air Bags

in Different Types of Crashes

This chapter discusses the safety consequences of crash characteristics,

automobile weight and size, and safety belts and air bags. The chapter

begins with a discussion of crash characteristics that are related to

occupant injury, including the injury risk associated with one-car rollover

crashes, one-car nonrollover crashes, and collisions with an automobile, a

van, or a light truck. It then examines the safety consequences of

automobile weight and size as well as of safety belt use in the different

crashes. Each section summarizes relevant findings from the literature and

then presents the results of our analyses of the NASS data. The chapter ends

with a look at the effects of air bags.

Crash Characteristics

Previous Findings The great majority of traffic crashes do not involve serious injury. A large

proportion of all traffic crashes are not reported to the police (Evans,

1991b). And NHTSA has estimated that about one third of crashes reported

to the police involve personal injury (two thirds having property damage

only) and that just 6 percent involve a severe or fatal injury (NHTSA, 1991b).

Nonetheless, some crashes are much more likely to lead to serious injury

than others. First, some types of crashes are more severe than others.

Overall, single-car crashes are more likely to seriously injure occupants

than are multiple-vehicle collisions. Single-vehicle crashes account for

about 30 percent of police-reported crashes annually, yet in 1991 about

45 percent of all automobile occupant fatalities were in these collisions.

Single-car rollover crashes are particularly dangerous, accounting for only

about 2 percent of all police-reported accidents but about 20 percent of

occupant fatalities (NHTSA, 1991b). A major reason for the relative severity

of single-car crashes is that most crashes involving drunk drivers are

single-car incidents, and crashes involving drunk drivers tend to be more

severe than other collisions. For example, NHTSA reported that 53 percent

of drivers killed in single-vehicle crashes in 1991 were intoxicated,

compared with only 21 percent of the drivers killed in multiple-vehicle

collisions (NHTSA, 1993b).

Second, for nonrollover crashes, some points of impact on the automobile

are more dangerous than others. The preponderance of fatal crashes other

than rollovers involve frontal impacts, followed at a distance by left- and

right-side impacts. For example, table 2.1 indicates that 43 percent of all

Page 17 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 2 

The Effects of Automobile Weight,

Automobile Size, Safety Belts, and Air Bags

in Different Types of Crashes

automobile occupant fatalities in 1991 occurred in frontal impacts, or

more than half of all fatalities that did not occur in single-car rollovers.

Table 2.1: Automobile Occupant

Fatalities by Rollover or Principal

Impact Point, 1991

Type Fatality

Nonrollover: principal impact pointa

Front 43%

Left side 16

Right side 15

Rear 3

Other 3

Single-car rollover 20

Total 100%

aFrontal impact points are clock positions 11:00, 12:00, and 1:00; left-side impact points are clock

positions 8:00, 9:00, and 10:00; right-side, 2:00, 3:00, and 4:00; and rear, 5:00, 6:00, and 7:00.

Source: Our analysis of 1991 FARS data from National Highway Traffic Safety Administration,

Fatal Accident Reporting System 1991, DOT-HS-807-954 (Washington, D.C.: 1993).

Third, crashes at high speeds are more dangerous than others. For

example, Joksch (1993) estimated that the risk to drivers of fatal injury in

two-car collisions was about 1 percent for a 20 mph collision, 10 percent

for a 35 mph collision, and 44 percent for a collision involving a change in

velocity of 50 mph.1 NHTSA (1993e) recently reported similar findings for

restrained vehicle occupants, noting, for instance, that the probability of

fatal injury is about nine times as great in frontal collisions with a change

of velocity of 40 mph as in those with a change of 30 mph. That the

probability of death increases sharply with impact speed is one reason for

the predominance of frontal impacts in fatal crashes, since frontal impacts

are likely to involve cars that are moving forward.

The Results of Our

Analysis of Crash Data

Here we report how injury risk and driver and automobile characteristics

vary by crash type. Our data, from NASS, were for model year 1987 and later

cars in three types of police-reported tow-away crashes in 1988-91: one-car

rollovers, one-car nonrollovers, and collisions with other cars, vans, and

light trucks.

1

Change in velocity refers to the nearly instantaneous change in a vehicle’s speed in a crash. For

example, a vehicle that was abruptly stopped from a travel speed of 30 mph would have a change in

velocity of 30 mph (from 30 to 0). In contrast, a parked vehicle struck from the rear and moved sharply

forward at 10 mph would have a change in velocity of 10 mph (from 0 to 10).

Page 18 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 2 

The Effects of Automobile Weight,

Automobile Size, Safety Belts, and Air Bags

in Different Types of Crashes

The pattern of injury risk by crash type that we found in the NASS data set

reflects the pattern described in the literature. As table 2.2 indicates,

one-car crashes are more dangerous than multivehicle collisions. One-car

rollover crashes, in particular, are much more dangerous than other crash

types, with a rate of driver hospitalization or death that is double that of

one-car nonrollover crashes and four times that of collisions with cars and

light trucks.

Table 2.2: Driver Injury, Driver

Characteristics, and Automobile

Weight, by Crash Type

Crash typea

Item

One-car

rollover

One-car

nonrollover

Collision with

other cars or light

trucks

Driver characteristic

Injury

 Hospitalized or

 killed 15.7% 7.0% 4.0%

 Killed 3.0 0.7 0.2

Male 62.5 58.0 46.3

Age

 16-24 53.6 43.3 33.7

 25-44 36.1 42.1 43.3

 45-64 7.0 10.8 15.0

 65+ 3.3 3.8 8.0

Average automobile

curb weight (lbs)b 2,502 2,688 2,669

aPercentages and means weighted by the National Inflation Factor to represent population values.

The unweighted numbers of cases are 457 for one-car rollovers, 1,253 for one-car nonrollovers,

and 4,393 for collisions with other cars or light trucks. The corresponding estimated population

numbers of cases are 104,806, 422,056, and 1,510,653. (See appendix I.)

bCurb weight refers to the weight of an unoccupied automobile, including gasoline and other

fluids. In the NASS data set, curb weight is recorded only to the nearest 100 pounds. Therefore,

estimates of the average curb weight of any group of automobiles are less exact than they would

be if curb weight were recorded more precisely.

Source: NASS 1988-91 data for model year 1987 and newer automobiles.

In addition to having a higher rate of driver injury, one-car crashes are

disproportionately likely to involve men drivers and young drivers. (See

table 2.2.) We found that about 60 percent of the drivers in one-car crashes

were men, compared with approximately 46 percent in two-vehicle

collisions. In addition, while close to half of the drivers in one-car crashes

were 16 to 24 years of age, only about one third of the drivers in collisions

Page 19 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 2 

The Effects of Automobile Weight,

Automobile Size, Safety Belts, and Air Bags

in Different Types of Crashes

with other cars or light trucks were that young. These findings are

consistent with those of our companion report, Highway Safety: Factors

Affecting Involvement in Vehicle Crashes (GAO, 1994), in which we found

that driver age and gender are more strongly related to involvement in

single-vehicle crashes than they are to involvement in two-vehicle

collisions.

In addition, as table 2.2 indicates, the average curb weight of automobiles

in one-car rollover crashes was somewhat lower than that of cars involved

in other crashes. As we noted in Highway Safety: Factors Affecting

Involvement in Vehicle Crashes, involvement in rollover crashes increases

as automobile weight decreases.

Just as the literature suggests, we found that the risk of injury to drivers is

significantly affected by impact point. In particular, we found that

two-vehicle collisions involving head-on impacts between vehicles moving

in opposite directions are much more dangerous than other two-vehicle

crashes. The risk of driver injury or death is about five times as great in

head-on collisions as in other two-vehicle collisions. For crashes other

than head-on collisions, frontal impacts and left-side impacts had higher

rates of driver hospitalization or death than others.

Finally, we found that high impact speeds are, not surprisingly, more

dangerous than low impact speeds. Considering the three crash types

together, we estimated that each increase of 10 mph in the change of

velocity at impact increases the probability of driver hospitalization or

death nearly sevenfold.

Automobile Weight

and Size

Previous Findings As we have previously reported, safety experts agree that, in general,

heavier and larger cars are both more crashworthy and more aggressive

than lighter and smaller automobiles (GAO, 1991). Thus, in the event of a

collision, occupants are less likely to be hurt when they are in heavier and

larger cars and when they are struck by lighter and smaller cars.

However, there is some disagreement in the literature about which is the

more important dimension for occupant safety, weight or exterior size

Page 20 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 2 

The Effects of Automobile Weight,

Automobile Size, Safety Belts, and Air Bags

in Different Types of Crashes

(that is, overall length and width).2 Proponents of weight as the important

dimension argue that automobile mass protects occupants from injury

because it is aggressive—that is, heavier cars knock down objects and

push other vehicles back, thereby transferring momentum and energy to

the struck object, including other vehicles, that could otherwise affect

occupants of the striking vehicle (see, for example, Evans and Frick,

1992). In contrast, proponents of exterior size as the more important

dimension maintain that large vehicles protect their occupants by

absorbing crash energy without increasing the injury risk of other roadway

users (for example, see Robertson, 1991).

In most cases, this debate is of little practical significance now, since

weight and exterior size are very highly correlated—that is, heavy cars are

almost invariably also long and wide—but it has important implications

for the design of future automobiles. If exterior size is the more important

dimension, using lighter weight materials could make future automobiles

lighter without decreasing exterior size, thus increasing fuel efficiency

without exacting a safety cost. Conversely, using lighter weight materials

would involve a safety cost if weight is the more important dimension.

In addition, estimates of the amount of additional protection offered by a

given increase in automobile weight vary considerably. For example,

consider the effects of a 500-pound increase in the weight of one

automobile in a collision with another, assuming no change in the weight

of the latter. Klein, Hertz, and Borener (1991) used data from two states to

generate two different estimates of the decreased risk of serious driver

injury from that automobile weight increase—13 percent and 20 percent.

Other estimates are higher. For example, Evans (1982) concluded that this

increase in automobile weight would reduce a driver’s risk of fatal injury

by about 29 percent.

Further, the protective effect of automobile size appears to differ by crash

type. First, it is likely that this effect is somewhat less pronounced in

one-car nonrollover crashes than in multivehicle collisions (Evans, 1991b).

For example, in the 1991 paper by Klein and colleagues, NHTSA researchers

estimated that a 500-pound increase in automobile weight reduces the risk

of driver fatality by not quite 5 percent in one-car nonrollover crashes,

somewhat less than the estimates of 13 percent and 20 percent for two-car

collisions.

2

Exterior size is measured by wheelbase—that is, the distance between the front and rear axles.

Page 21 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 2 

The Effects of Automobile Weight,

Automobile Size, Safety Belts, and Air Bags

in Different Types of Crashes

Second, although it is well documented that small cars are much more

likely to be involved in one-car rollover crashes than are large cars (see,

for example, GAO, 1994), the literature is less clear about the safety

consequences of automobile size once a rollover has occurred. On the one

hand, in examining the effects of reduced automobile weight and size on

safety in rollover crashes, some researchers have focused on the increased

number of rollover crashes among light and small cars (Evans, 1991b;

Kahane, 1990; NHTSA, 1991a). The implication of these studies is that

automobile weight and size do not affect crashworthiness in rollovers;

otherwise, these researchers would have included weight and size as

factors in their calculations. On the other hand, some direct studies of

crashworthiness in rollovers have found that drivers of larger cars are

more likely to be injured than drivers of smaller cars in rollovers (see, for

example, Partyka and Boehly, 1989). One explanation for this finding is

that it takes more energy to roll over a heavy automobile than a light one,

meaning that the typical rollover crash involving heavy autos is more

severe (that is, occurs at a higher speed) than the typical rollover involving

light cars (see, for example, Terhune, 1991).

The Results of Our

Analysis of Crash Data

The Effects of Automobile

Weight and Size Vary by Crash

Type

After combining all the crashes in our database (one-car rollovers, one-car

nonrollovers, and collisions with cars and light trucks), we found that the

risk of injury to drivers was significantly reduced as car weight and

wheelbase increased in our sample. (See figure 2.1.) We estimated that the

risk of driver hospitalization or death decreases about 14 percent for every

additional 500 pounds of automobile weight and about 13 percent for each

additional 5 inches of wheelbase. (See tables I.1 and I.2.)

Page 22 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 2 

The Effects of Automobile Weight,

Automobile Size, Safety Belts, and Air Bags

in Different Types of Crashes

Figure 2.1: Estimated Probability of

Driver Hospitalization or Death in

One-Car Crashes and Collisions With

Other Cars or Light Trucks, by

Automobile Weight and Wheelbasea

0.04


0.03


0.02


0.01

Estimated probability of driver hospitalization or death

Curb weight (pounds)/wheelbase (inches)

Curb weight


Wheelbase

2,000/93


2,200/95.5


2,400/98


2,600/100.5

2,800/103


3,000/105.5


3,200/108


3,400/110.5

3,600/113


aEstimated probability of driver injury in an average crash for a typical driver: a 30-year-old man

wearing manual lap and shoulder safety belts. Injury probability changes by 0.97 for each

additional 100 pounds of automobile weight and by 0.973 for each additional inch of wheelbase.

Source: Our analysis of NASS 1988-91 data for model year 1987 and newer automobiles.

Further, considering all crash types taken together, we could not

statistically differentiate the injury reduction effects of curb weight and

wheelbase. That is, the benefits of increasing weight and wheelbase were

roughly equivalent in reducing injuries, and we were unable to establish

that one had a stronger influence than the other. The nearly equivalent

slopes of the lines for weight and wheelbase in figure 2.1 demonstrate this.

The endpoints of the lines in figure 2.1 represent approximately the 5th

and 95th percentiles of automobile weight and wheelbase in this data set.

Thus, 2,000-pound cars are among the lightest and 3,600-pound cars are

among the heaviest in this database of cars involved in serious crashes;

similarly, cars with a wheelbase of 93 inches are among the shortest, 113

Page 23 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 2 

The Effects of Automobile Weight,

Automobile Size, Safety Belts, and Air Bags

in Different Types of Crashes

inches among the longest.3 Figure 2.1 shows that, for all three crash types

taken together, whether measured by weight or wheelbase, drivers in the

heaviest and largest cars had a risk of hospitalization or death about

40 percent less than the drivers of the lightest and smallest cars.

However, these overall effects mask the fact that automobile weight and

wheelbase have very different safety consequences in different types of

crashes. Figure 2.2 shows the estimated effects of curb weight separately

for the three crash types (see also tables I.3-I.5); figure 2.3, the estimated

effects of wheelbase (see also tables I.6-I.8).

Figure 2.2: Estimated Probability of

Driver Hospitalization or Death by

Crash Type and Automobile Weighta

0.12


0.10


0.08


0.06


0.04


0.02


 0

Estimated probability of driver hospitalization or death

Curb weight (pounds)

One-car rollovers


One-car nonrollovers


Collisions with other cars or light trucks

2,000

2,200

2,400


2,600

2,800

3,000

3,200

3,400

3,600

aEstimated probability of driver injury in an average crash for a typical driver: a 30-year-old man

wearing manual lap and shoulder safety belts. Injury probability changes by 1.097 for each

additional 100 pounds of automobile weight in one-car rollover crashes, by 0.968 in one-car

nonrollover crashes, and by 0.948 in collisions with other cars or light trucks.

Source: Our analysis of NASS 1988-91 data for model year 1987 and newer automobiles.

3

The heaviest cars in the data set weighed more than 4,400 pounds, the lightest less than 1,600 pounds.

The longest cars had wheelbases of more than 120 inches, the shortest less than 84 inches.

Page 24 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 2 

The Effects of Automobile Weight,

Automobile Size, Safety Belts, and Air Bags

in Different Types of Crashes

Figure 2.3: Estimated Probability of

Driver Hospitalization or Death by

Crash Type and Automobile

Wheelbasea

0.12


0.10


0.08


0.06


0.04


0.02


 0

Estimated probability of driver hospitalization or death

Wheelbase (inches)

One-car rollovers


One-car nonrollovers


Collisions with other cars or light trucks

93

95.5

98

100.5

103

105.5

108

110.5

113

aEstimated probability of driver injury in an average crash for a typical driver: a 30-year-old man

wearing manual lap and shoulder safety belts. Injury probability changes by 1.020 for each

additional wheelbase inch in one-car rollover crashes, by 0.980 in one-car nonrollover crashes,

and by 0.958 in collisions with other cars or light trucks.

Source: Our analysis of NASS 1988-91 data for model year 1987 and newer automobiles.

Most importantly, although increasing weight and wheelbase reduces the

risk of driver injury in one-car nonrollover crashes and in collisions with

other cars or light trucks, drivers in heavier cars were much more likely to

be hospitalized or killed in one-car rollover crashes than were drivers of

lighter automobiles. For one-car rollover crashes, we estimated that each

500 pounds of additional automobile weight increases the risk of driver

hospitalization or death by about 59 percent. This effect is solely a

function of automobile weight, not of wheelbase; we found that the

relationship between wheelbase and driver injury was not statistically

significant in one-car rollovers. This finding agrees with the report of

Partyka and Boehly (1989) that drivers of heavier and larger cars are more

Page 25 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 2 

The Effects of Automobile Weight,

Automobile Size, Safety Belts, and Air Bags

in Different Types of Crashes

likely to be injured in rollovers than drivers of lighter and smaller cars.

This finding is also consistent with the explanation that it takes more

energy to roll over a heavy automobile than a light one, meaning that

rollover crashes involving heavy autos occur at higher speeds than

rollovers involving light cars. However, it is important to keep in mind that

the rate of involvement in one-car rollover crashes is much greater for

light cars than for heavy ones, so this finding does not necessarily mean

that, considering both involvement and crashworthiness, drivers of heavy

cars are more likely to suffer injuries in one-car rollovers.

Figures 2.2 and 2.3 also show that we found a tendency for the risk of

driver hospitalization or death to decrease with increasing car weight and

size in one-car nonrollover crashes, but neither curb weight nor wheelbase

was a statistically significant predictor of driver injury in those crashes. In

contrast, we found that in collisions with other cars and light trucks, both

automobile weight and wheelbase were statistically significant predictors

of driver injury. In those crashes, we estimate that each additional 500

pounds of automobile weight decreased the risk of driver hospitalization

or death by about 23 percent and each 5 inches of additional wheelbase

lowered the risk of driver injury approximately 19 percent. These findings

reflect the pattern, described in the literature, that the protective effects of

automobile weight and wheelbase are somewhat greater in multivehicle

collisions than in single-car nonrollover crashes.

Characteristics of the Other

Vehicle Affect Injury Risk

In two-vehicle collisions, the injury risk of an automobile occupant is

affected not only by the characteristics of his or her own automobile but

also by the characteristics of the other vehicle. We looked at the effects of

the weight and vehicle type of the other vehicle on the probability of injury

for the first driver: both factors affect the aggressivity of the other vehicle.

First, not surprisingly, heavier vehicles pose more of a risk than lighter

vehicles. (See figure 2.4.) In our analysis, each increase of 500 pounds in

the weight of the other vehicle increased the probability of hospitalization

or death by about 13 percent, holding other factors constant. (See table

I.5.) It is important to note that the magnitude of this aggressive effect of

vehicle weight is less than that of the protective effect of weight described

earlier. (We estimated that each additional 500 pounds of automobile

weight reduces the probability of injury by about 23 percent.) After

statistically controlling for the influence of other factors, we found that

this ratio of the protective effect to the aggressive effect of automobile

weight of 1.77 to 1 is roughly consistent with the findings of other

researchers. For example, Klein, Hertz, and Borener (1991), analyzing data

Page 26 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 2 

The Effects of Automobile Weight,

Automobile Size, Safety Belts, and Air Bags

in Different Types of Crashes

from two different states, generated two estimates of the size of this ratio

in two-car collisions: 1.54 to 1 and 1.30 to 1.

Figure 2.4: Estimated Probability of

Driver Hospitalization or Death in

Collisions With Other Cars or Light

Trucks by Weight of the Other Vehiclea

0.04


0.03


0.02


0.01


 0

Estimated probability of driver hospitalization or death

Other vehicle curb weight (pounds)

2,000

2,300

2,600

2,900

3,200

3,500

3,800

4,100

4,400

aEstimated probability of driver injury in an average crash for a typical driver: a 30-year-old man

wearing manual lap and shoulder safety belts. Injury probability changes by 1.025 for each

additional 100 pounds in the weight of the other vehicle.

Source: Our analysis of NASS 1988-91 data for model year 1987 and newer automobiles.

Second, figure 2.5 shows that driver injury risk is strongly influenced by

the body type of the other vehicle. We found that while pickup trucks do

not pose more danger than automobiles, vans and other light trucks are

more aggressive than automobiles. Indeed, statistically controlling for the

weight of the driver’s car and of the other vehicle, we estimate that the

risk of hospitalization or death for the driver is more than twice as great in

collisions with vans and light trucks than with other cars or light vehicles.

(See also table I.5.) This finding reflects two characteristics of vans and

light trucks. One is that because vans and light trucks can carry heavy

cargo loads, these vehicles may be, in reality, heavier than the curb weight

measurements available to us indicate. The second characteristic is that

Page 27 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 2 

The Effects of Automobile Weight,

Automobile Size, Safety Belts, and Air Bags

in Different Types of Crashes

the structure and design of vans and other light trucks make those vehicles

especially dangerous for automobile occupants in two-vehicle collisions

(National Research Council, 1992; Terhune and Ranney, 1984).

Figure 2.5: Estimated Probability of

Driver Hospitalization or Death in

Collisions With Other Cars or Light

Trucks by Type of the Other Vehiclea

Estimated probability of driver hospitalization or death

0

0.01

0.02

0.03

0.04

0.05

Car Pickup

truck

Van Other

light

truck

Other vehicle body type

aEstimated probability of driver injury in an average crash for a typical driver: a 30-year-old man

wearing manual lap and shoulder safety belts.

Source: Our analysis of NASS 1988-91 data for model year 1987 and newer automobiles.

Safety Belts

Previous Findings Safety belts greatly reduce the risk of injury and death in roadway crashes.

In a recent review of studies of safety belt effectiveness, we concluded

that most studies show that belted vehicle occupants have a risk of serious

injury or death that is approximately 50 to 75 percent less than that of

unrestrained occupants (GAO, 1992). Other researchers have found safety

belts to have slightly smaller effects. For example, NHTSA (1993d)

estimated that when manual lap and shoulder safety belts are used in

Page 28 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 2 

The Effects of Automobile Weight,

Automobile Size, Safety Belts, and Air Bags

in Different Types of Crashes

serious crashes, they reduce fatality risk by 45 percent. Similarly, Evans

(1986) estimated that three-point lap and shoulder safety belts reduce a

driver’s risk of fatality by about 43 percent, with about half of that benefit

the result of eliminating or attenuating impacts with the interior of the

vehicle and about half the result of preventing occupant ejection.

There are three other important points about safety belt effectiveness.

First, the effectiveness of safety belts varies by crash type. Belts are most

effective in rollover crashes because they largely prevent occupant

ejection (Evans, 1990; Partyka, 1988). They are also more effective in

one-car crashes than in multivehicle collisions. For example, Evans and

Frick (1986) estimated that safety belts reduce the risk of driver fatality in

one-car crashes by 62 percent but by only 30 percent in two-car crashes.

Second, belt effectiveness also varies by point of impact. Belts are most

effective in frontal impacts and least effective in left-side impacts (Evans,

1990). Since one-car crashes are more likely to involve frontal impacts

than are two-car collisions, this offers one possible explanation for the

greater efficacy of safety belts in one-car crashes.

Third, it is likely that manual lap and shoulder belts are somewhat more

effective than other safety belt configurations. For example, Evans (1991a)

estimated that lap and shoulder belts reduce fatality risk in serious

collisions by about 41 percent, compared with estimated risk reductions of

18 percent for lap belts only and 29 percent for shoulder belts only. Evans

speculated that these two components have somewhat different functions,

with lap belts primarily preventing ejection and shoulder belts mitigating

contact with the interior of the vehicle. Comparing manual lap and

shoulder belts to automatic belts, NHTSA (1993d) estimated that automatic

safety belts, when used in serious crashes, reduce the risk of fatality by

42.5 percent, compared with an estimated fatality reduction of 45 percent

for manual lap and shoulder belts.

The Results of Our

Analysis of Crash Data

Considering all three crash types together, NASS researchers categorized

73 percent of the drivers in the NASS data set as using a safety belt at the

time of collision, with those involved in one-car rollovers slightly less

likely to be belted than others. This figure is higher than might be

expected from the results of other estimates of safety belt use among the

general driving population, particularly given that drivers involved in

crashes are less likely to wear safety belts than others and that all the

drivers included in our analysis had been involved in a crash. In one point

of comparison, NHTSA estimated a 51-percent safety belt usage rate for all

Page 29 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 2 

The Effects of Automobile Weight,

Automobile Size, Safety Belts, and Air Bags

in Different Types of Crashes

passenger cars in 1991 (NHTSA, 1992a). Further, it is well established that

unbelted drivers are more reckless than belted drivers (Evans and

Wasielewski, 1983; Evans, 1987; Preusser, Williams, and Lund, 1991;

Stewart, 1993). As a result, unbelted drivers have much higher crash

involvement rates than belted drivers: NHTSA (1992a) estimated that

unbelted drivers have an involvement rate in potentially fatal crashes that

is more than double that of belted drivers.4

We cannot determine with certainty if, or to what degree, the safety belt

use figures reported in NASS are incorrect, nor can we determine with

certainty the extent to which any potential bias in those figures affected

our analyses. For that reason, our results should be interpreted with

caution. Nonetheless, because the results of our analyses concerning the

relative effectiveness of different safety belt configurations in different

types of crashes are consistent with the findings from the traffic safety

literature, we believe that any potential bias has not seriously affected our

findings.

For each of the three categories of crashes, we examined the performance

of three safety belt configurations: (1) manual lap and shoulder belts,

(2) automatic and manual belts combined (most commonly automatic

shoulder belts and manual lap belts), and (3) automatic belts without

manual components. Other safety belt configurations, including manual

lap belts alone, had too few cases in the data set for us to estimate their

effectiveness.

Statistically controlling for crash severity, driver characteristics, and other

background factors, we found that, compared with unbelted drivers,

drivers using any of the three safety belt configurations had greatly

reduced risks of injury. We also found that, looking at the three types of

crashes together, manual lap and shoulder belts were somewhat more

effective in preventing driver injury than the other configurations. (See

figure 2.6.) Compared with unbelted drivers, the estimated risk of

hospitalization or death was reduced about 70 percent for those using

manual lap and shoulder belts, about 63 percent for those using automatic

and manual belts combined, and about 54 percent for those using

automatic belts without manual components. (See also table I.1.)

4

More specifically, NHTSA (1992a, pp. 20-21) estimated that an automobile fleet composed entirely of

cars equipped with manual safety belts would have had a 48-percent belt usage rate in 1991 (with

52 percent of drivers unbelted) and that the manual belt use rate in “potentially fatal” crashes would

have been 29.5 percent (with 70.5 percent of drivers unbelted). Therefore, by these estimates, the odds

of drivers not using a belt in the general population would be 1.08 (52/48), the odds of drivers not using

a belt in the crash-involved population would be 2.39 (70.5/29.5), and the relative risk of involvement in

serious crashes of unbelted drivers would be 2.21 (2.39/1.08).

Page 30 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 2 

The Effects of Automobile Weight,

Automobile Size, Safety Belts, and Air Bags

in Different Types of Crashes

Figure 2.6: Estimated Probability of

Driver Hospitalization or Death in

One-Car Crashes and Collisions With

Other Cars or Light Trucks by Safety

Belt Usea

Estimated probability of driver hospitalization or death

0

0.02

0.04

0.06

0.08

0.10

0.12

No belts used

Manual lap and

shoulder belts

Automatic and manual belts

Automatic belts only

aEstimated probability of driver injury in an average crash for a 30-year-old man.

Source: Our analysis of NASS 1988-91 data for model year 1987 and newer automobiles.

We also found small variations in safety belt performance among the

different types of crashes. Safety belts were somewhat less effective in

collisions with other cars or light trucks than they were in single-car

crashes. For example, in our analysis, manual lap and shoulder belts

reduced the risk of driver hospitalization or death by 83 percent in one-car

rollover crashes and by 80 percent in one-car nonrollover crashes but by

only 64 percent in collisions with other cars or light trucks. (See tables

I.3-I.5.)

Air Bags Evaluations of the effectiveness of air bags are hampered by the relatively

small number of cars now equipped with them (although all passenger

cars, vans, and light trucks will be required to have both driver- and

passenger-side air bags by the 1998 model year). There were too few

Page 31 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 2 

The Effects of Automobile Weight,

Automobile Size, Safety Belts, and Air Bags

in Different Types of Crashes

automobiles with air bags in the NASS data set for us to conduct our own

analysis of air bag effectiveness. Nonetheless, some of the characteristics

of air bag performance have already been established. First, air bags are

effective only in frontal impacts; they do not protect drivers in side

impacts or other nonfrontal collisions (see, for example, Zador and

Ciccone, 1993). While frontal impacts account for by far the greatest

proportion of automobile occupant fatalities, more than half of occupant

fatalities do not involve frontal impacts. (See table 2.1.)

Second, air bags offer additional protection to drivers already wearing

safety belts. Researchers have found that belted drivers with air bags are

about 10 percent less likely to be fatally injured than are belted drivers

without air bags (Evans, 1991b; Zador and Ciccone, 1993). For example,

NHTSA (1993d) estimated that lap and shoulder safety belts alone reduce

automobile driver fatality risk by about 45 percent. In that paper, NHTSA

also estimated that drivers with lap and shoulder belts and air bags are

about 50 percent less likely to be killed than unbelted drivers, for a safety

increment of close to 10 percent (50/45 = 1.11, or about 10 percent).

Finally, safety belts alone are much more effective than air bags alone.

Estimates of the effectiveness of air bags for drivers who do not wear

safety belts indicate that those drivers are approximately 20 to 30 percent

less likely to be killed in a collision than are unbelted drivers without air

bags (NHTSA, 1993d; Zador and Ciccone, 1993). In contrast, as noted

previously, drivers wearing lap and shoulder safety belts are, by the most

conservative estimate, 41 percent less likely to be killed than unbelted

drivers.5

Summary One-car crashes have higher injury rates than multivehicle collisions, and

one-car rollover crashes are more dangerous than one-car nonrollover

crashes. Further, automobile drivers are especially likely to suffer serious

injury in crashes involving a frontal impact, and the probability of injury is

greater at higher impact speeds.

5

A potential concern about air bags that has not yet been thoroughly examined is that driver ejection

rates may be somewhat higher in cars with air bags. NHTSA (1992a, pp. 50-51) reported that, in fatal

accidents, drivers in vehicles with air bags are significantly more likely to be ejected from the vehicles

than are drivers in cars with only manual safety belts. NHTSA appropriately noted that this result in a

database containing only fatal accidents is suspect, since drivers “saved” by air bags are not included

in the database unless another person in the crash was killed. However, the fact that a statistically

significant relationship between air bags and ejection was found in a data set with a relatively small

number of cases suggests that this may be a strong effect. At the least, this question deserves further

investigation.

Page 32 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 2 

The Effects of Automobile Weight,

Automobile Size, Safety Belts, and Air Bags

in Different Types of Crashes

The protective effects of automobile weight and wheelbase differ by crash

type. In one-car rollover crashes, drivers of heavier cars are more likely to

be hospitalized or killed than drivers of lighter cars. Automobile

wheelbase is not statistically related to injury risk in rollovers. In contrast,

increasing both weight and wheelbase reduces the risk of driver injury in

one-car nonrollover crashes and in collisions with other cars or light

trucks, with a larger safety benefit in multivehicle collisions than in

one-car nonrollover crashes.

Safety belts substantially reduce the risk of driver injury. Manual lap and

shoulder belts are somewhat more effective than other belt configurations,

and safety belts are more beneficial in one-car crashes than in multivehicle

collisions. The traffic safety literature indicates that air bags offer a

modest degree of additional protection to belted occupants and that safety

belts without air bags are much more effective than air bags without safety

belts.

Agency Comments

and Our Evaluation

DOT had one general comment concerning the topics presented in this

chapter: it maintained that the subset of the NASS data we used in the

report is inappropriate for studying the effect of car size on safety and,

more particularly, that the sample size is inadequate for assessing the

consequences of changing the weight of both vehicles in a two-vehicle

collision. We disagree. As the findings presented in this chapter

demonstrate, the NASS data set we constructed clearly was adequate for

uncovering a number of statistically significant relationships (the analyses

are described in appendix I). In addition, our findings are similar to NHTSA’s

findings from statistical analyses of state accident databases (particularly

concerning the effects of the weights of both vehicles in two-car collisions;

see Klein, Hertz, and Borener, 1991) and to NHTSA’s findings from statistical

analyses of a slightly different NASS database (see table I.1 and NHTSA,

1992a, p. 72).

Page 33 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 3 

The Effects of Gender and Age on Driver

Injury Risk

The Vulnerability of

Women and Older

Drivers

Previous Findings Safety researchers have consistently found that women automobile

occupants have a greater risk of injury in a collision than men and that the

risk of injury increases with occupant age. For example, NHTSA (1992a)

found that women vehicle occupants involved in tow-away crashes are

36 percent more likely than men to suffer an injury categorized as

moderately severe or worse. NHTSA also found that the risk of moderate

injury increases about 2 percent for each year of age, meaning that,

compared with 20-year-olds, 30-year-olds have a 21-percent greater risk of

injury and 60-year-olds are more than twice as likely to be injured.

Similarly, Evans (1988b) reported that 30-year-old women have a fatality

risk in traffic crashes about 31-percent higher than 30-year-old men and

that the risk of fatality increases about 2 percent for each year of age.

The Results of Our

Analysis of Crash Data

Our analysis of the NASS data set of police-reported tow-away crashes

produced similar findings. For statistically equivalent crashes, we found

that women drivers are about 29 percent more likely to be hospitalized or

killed than men drivers. We also found that drivers 65 and older are about

4.5 times more likely to be seriously hurt than drivers 16 to 24 years old in

equivalent crashes. (See table I.1.)

Possible Explanations

Previous Findings One explanation for the greater vulnerability of women drivers and older

drivers emphasizes their inherent physical frailty. This view postulates that

the same degree of physical trauma is more likely to produce injury in

women than in men and in older automobile occupants than in younger

ones, because women and older people are physically less resilient than

men and younger people. Indeed, there is some support for the view that

women are physically more vulnerable than men (Evans, 1988b), and that

older people are more fragile than younger ones is well documented (for

example, Mackay, 1988; Pike, 1989). The implication of this view is that the

greater vulnerability of women and older persons is not amenable to

Page 34 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 3 

The Effects of Gender and Age on Driver

Injury Risk

correction through automobile design changes, because weaker

individuals will be hurt more often than stronger ones no matter what.

Other possible explanations have not been carefully developed in the

literature, but they tend to involve speculation that some characteristic of

the vulnerable group interacts with automobile design to cause a safety

problem. For example, because women are shorter than men, on the

average, they may sit closer to the steering wheel, causing them to hit the

steering column more quickly in a crash. Similarly, the interaction of lower

height and safety belts designed for average-sized drivers may oblige

women, for reasons of comfort, to wear safety belts incorrectly more than

men do, thereby increasing the injury risk of ostensibly belted women

drivers relative to that of belted men drivers (see, for example, National

Transportation Safety Board, 1988).

The Results of Our

Analysis of Crash Data

Here, we discuss whether the factors we examined in chapter 2

differentially affect the probability of injury of women and men and of

older and younger drivers. If the “inherent frailty” view is correct, women

should be injured more than men, and older drivers more than younger

drivers, regardless of crash type, automobile weight, or safety belt use. If

any of these factors affect the relationship between gender or age and

injury risk, the credibility of this view would be called into question, as

this would mean that something other than frailty also makes an important

difference. It would also indicate that the safety of women and older

drivers could be at least somewhat improved by automobile design

changes.

Factors Affecting Women

Drivers

Crash Type. The pattern of injury by crash type varies for women drivers

and men drivers. Multivehicle collisions are a greater source of injury for

women than they are for men. Figure 3.1 shows our finding that 67 percent

of the women drivers hospitalized or killed were injured in collisions with

cars and light trucks, with only one third injured in one-car crashes

(11 percent in rollovers, 22 percent in nonrollovers). In contrast, only

45 percent of the men drivers hospitalized or killed were injured in

collisions with cars and light trucks; most of the men drivers were hurt in

one-car crashes (20 percent of the total in rollovers, 35 percent in

nonrollovers).

Page 35 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 3 

The Effects of Gender and Age on Driver

Injury Risk

Figure 3.1: Distribution of Driver

Hospitalization or Death by Crash Type

and Gendera

Percent of drivers hospitalized or killed

0

10

20

30

40

50

60

70

80

Men Women

All one-car crashes

Collisions with other cars or light trucks

aDriver injuries are weighted by the National Inflation Factor to produce population estimates.

Columns sum to 100 percent separately for men and women.

Source: Our analysis of NASS 1988-91 data for model year 1987 and newer automobiles.

One reason for these differences in the pattern of injury is that men and

women drivers tend to be involved in different types of crashes, as

described in chapter 2. Men drivers are involved in one-car crashes more

often than women drivers.1

 In our analysis, 69 percent of the crash

involvements of men drivers were in collisions with cars and light trucks,

with about 31 percent in one-car crashes. In contrast, about 79 percent of

the crash involvements of women drivers were in collisions with cars and

light trucks, with only about 21 percent in one-car crashes.

However, another reason is that women drivers are much more likely than

men drivers to be hospitalized or killed in collisions with cars and light

trucks. That is, women drivers are especially likely to be hurt in the type of

1

See also Highway Safety: Factors Affecting Involvement in Vehicle Crashes (GAO, 1994). There, we

found that men drivers are more frequently involved in single-vehicle crashes than women drivers but

that men and women drivers do not differ in their involvement in two-vehicle collisions.

Page 36 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 3 

The Effects of Gender and Age on Driver

Injury Risk

crash that they are also particularly likely to experience.2 In statistically

equivalent crashes, women drivers are 52 percent more likely than men

drivers to be hospitalized or killed in collisions with other cars or light

trucks, but injury risks for women drivers are roughly the same as those

for men drivers in one-car crashes—4 percent higher in one-car rollovers

and 6 percent lower in other one-car crashes.3

 (See tables I.3-1.5.)

Automobile Weight. In our data set, women drove lighter and smaller cars

than men. The automobiles women drove had an average curb weight of

2,615 pounds and a mean wheelbase of 100.7 inches; for men drivers, the

figures were 2,715 pounds and 101.5 inches.

We also found that the protective effect of increasing automobile weight

was less evident for women drivers than for men drivers. Since increasing

weight generally offers protection in a crash, the average automobile

weight for drivers who were hospitalized or killed should be lower than

the average weight for those who were not injured. This was true for men

but not for women. The average curb weight of the cars driven by men

who were hospitalized or killed was 2,626 pounds, compared with a

greater average curb weight of 2,719 pounds for men who were not

injured. In contrast, the average automobile curb weight for women

drivers who were hospitalized or killed was 2,611 pounds, compared with

an equivalent average curb weight of 2,615 pounds for women drivers who

were not injured.4

Safety Belts. Each of the safety belt configurations that we examined

(manual lap and shoulder belts, automatic and manual belts, and

automatic belts only) significantly reduced the injury risk of both men and

2

As noted at the begining of the chapter, combining the three types of crashes, our overall estimate is

that women drivers are about 29 percent more likely to be hospitalized or killed in a collision than men

drivers.

3

These estimates were derived from logistic regression analyses that compared the injury experiences

of women and men drivers in crashes that were statistically equivalent on a number of important

dimensions, including crash severity, impact point, safety belt use, driver age, and automobile weight.

This means that any differences that may exist between men and women drivers on these dimensions

cannot account for the finding that women drivers are more likely than men drivers to be injured in

collisions with cars and light trucks. Thus, whether or not women and men drivers differ on these

dimensions, women drivers’ increased injury risk in these crashes is not the result of, for example,

women being involved in more severe crashes or of women more often driving smaller cars, among

other possible explanations.

4

Using the SUDAAN statistical software, we also conducted logistic regression analyses separately for

men and women drivers. For men drivers, the coefficient for automobile curb weight (–0.043) has a

p-value of less than 0.01; that coefficient translates to an odds ratio of 0.958. For women drivers, the

coefficient for automobile curb weight (–0.012) was not statistically significant and translates to an

odds ratio of 0.988.

Page 37 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 3 

The Effects of Gender and Age on Driver

Injury Risk

women drivers.5 However, we also uncovered evidence that, in this data

set, safety belts were somewhat less effective for women drivers than for

men drivers.

Table 3.1 compares men and women automobile drivers hospitalized as

the result of a crash by safety belt use. For all three types of crashes, the

table separates the percentage of drivers who were hospitalized or killed

from those not hospitalized as well as separating men and women in each

group. Safety belt use did not differ by gender for drivers who were not

hospitalized: about three quarters of both the men and women drivers in

that group were belted. If safety belts offered equivalent protection to men

and women drivers, the belt use percentages among hospitalized or killed

drivers should reflect the same pattern—in this case, rough equivalence

for men and women. However, the table shows that among drivers who

were hospitalized or killed, women were more likely to have been wearing

safety belts than men. In particular, injured women drivers were about

50 percent more likely to have been wearing manual lap and shoulder belts

than were injured men (36 percent to 24 percent).6

Table 3.1: Safety Belt Use by Driver’s

Injury Outcome and Gendera

Hospitalized or killed Not hospitalized

Injury outcome

Safety belt configuration Men Women Men Women

Total belted 44% 55% 74% 75%

Manual lap and shoulder

belts 24 36 48 52

Automatic and manual

belts 6 9 12 12

Automatic belts 14 10 15 11

Total unbelted 56% 45% 26% 25%

Total 100% 100% 100% 100%

aThe percentages are weighted by the National Inflation Factor to represent population values.

Source: Our analysis of NASS 1988-91 data for model year 1987 and newer automobiles.

5

As we discussed in chapter 2, the percentage of drivers coded as using safety belts in the NASS data

set is higher than expected. While we do not believe that any potential bias in the data set has seriously

affected our findings, these results should be interpreted with caution.

6

Using the SUDAAN statistical software, we conducted logistic regression analyses to discriminate

between men and women drivers. We did separate analyses for drivers who were hospitalized or killed

and for those who were not injured, and we used our standard set of crash-related independent

variables. For injured drivers, the only statistically significant safety belt factor was the variable for

manual lap and shoulder belts. For drivers who were not injured, none of the safety belt variables was

statistically significant.

Page 38 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 3 

The Effects of Gender and Age on Driver

Injury Risk

Factors Affecting Older

Drivers

Crash Type. The patterns of injury by crash type are very different for

drivers 65 and older and for younger drivers.7

 Figure 3.2 shows that, in our

analysis, nearly four fifths of the drivers 65 or older who were hospitalized

or killed were injured in collisions with cars or light trucks, while only

about one fifth were injured in one-car crashes (and almost none were

hurt in one-car rollovers—just 3 percent). Conversely, just over half of the

drivers 16 to 64 who were hospitalized or killed were injured in collisions

with cars or light trucks, while about 29 percent were hurt in one-car

nonrollovers and 17 percent were in one-car rollovers.

Figure 3.2: Distribution of Driver

Hospitalization or Death by Crash Type

and Driver Agea

Percent of drivers hospitalized or killed

0

10

20

30

40

50

60

70

80

90

Drivers 16 to 64 Drivers 65 and

older

All one-car crashes

Collisions with other cars or light trucks

aDriver injuries are weighted by the National Inflation Factor to produce population estimates.

Columns sum to 100 percent separately for each age category.

Source: Our analysis of NASS 1988-91 data for model year 1987 and newer automobiles.

7

We chose to compare drivers 65 and older with younger drivers in order to present the results of our

analysis in a straightforward manner. However, any division of age categories is arbitrary. Driver age

has many possible values and the relationship between driver age and injury risk is roughly

linear—that is, for a given level of trauma, injury risk increases with each additional year of age.

Page 39 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 3 

The Effects of Gender and Age on Driver

Injury Risk

The primary reason for this difference between the age categories is that

drivers in the two groups are involved in different types of crashes. Drivers

younger than 65 are involved in collisions with cars and light trucks less

often, and in one-car crashes more often, than are drivers 65 and older.8

 In

our analysis, 73 percent of the crash involvements of drivers 16 to 64 were

in collisions with cars and light trucks, about 22 percent in one-car

nonrollover crashes, and about 5 percent in one-car rollover crashes. In

contrast, about 86 percent of the crash involvements of drivers 65 and

older were collisions with cars and light trucks, with only about 11 percent

one-car nonrollover crashes and just 3 percent one-car rollovers.

Older drivers are much more likely to be hurt in crashes than younger

drivers in almost all circumstances. For one-car nonrollover crashes, we

found that, in statistically equivalent crashes, drivers 65 and older were

hospitalized or killed about 6.6 times more often than the youngest drivers,

those 16 to 24. Similarly, for collisions with cars and light trucks, drivers

65 and older had a probability of injury more than four times as great as

drivers 16 to 24.

Automobile Weight. Drivers 65 and older operated heavier and larger cars

than younger drivers. The automobiles of drivers 65 and older had an

average curb weight of 2,874 pounds and a mean wheelbase of 104.9

inches. The automobiles of drivers 16 to 64 had an average curb weight of

2,649 pounds and a mean wheelbase of 100.8 inches.

We also found that the protective effect of increasing automobile weight

was only slightly less strong for drivers 65 and older than for younger

drivers. Thus, the average curb weight of the cars driven by those 16 to 64

who were hospitalized or killed was 2,590 pounds, compared with a larger

average curb weight of 2,652 pounds for those who were not hospitalized.

The average automobile curb weight for drivers 65 and older who were

hospitalized or killed was 2,836 pounds, compared with an average curb

weight of 2,878 pounds for drivers who were not hospitalized.

Safety Belts. Although the safety belt use figures in the NASS data set may

be inflated, as we discussed earlier, we found that safety belts reduced the

risk of injury for drivers in both age categories. We also found that the

effectiveness of safety belts was roughly equivalent for drivers 16 to 64 and

for drivers 65 and older in this data set. For example, table 3.2 shows the

8

See Highway Safety: Factors Affecting Involvement in Vehicle Crashes (GAO, 1994). There, we

reported that younger drivers are particularly likely to be involved in one-car crashes but not

multivehicle collisions; conversely, older drivers are less likely than others to be involved in one-car

crashes but more likely to experience multivehicle collisions.

Page 40 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 3 

The Effects of Gender and Age on Driver

Injury Risk

percentage of belted drivers separately for those hospitalized or killed and

for those not hospitalized, as well as separating these categories by age.

The table shows that drivers 65 and older used safety belts more often

than drivers 16 to 64 and that this pattern holds both among those who

were hospitalized or killed and among those who were not hospitalized.

Thus, while older drivers use safety belts more frequently, this difference

from younger drivers is found across the board, rather than only among

the hospitalized and killed, as it was for the comparison between women

drivers and men drivers.

Table 3.2: Safety Belt Use by Driver’s

Injury Outcome and Agea

Hospitalized or killed Not hospitalized

Injury outcome

Safety belt configuration Age 16-64

Age 65 and

older Age 16-64

Age 65 and

older

Total belted 48% 66% 74% 82%

Manual lap and shoulder

belts 29 39 49 55

Automatic and manual

belts 8 8 12 8

Automatic belts 11 19 13 19

Total unbelted 52% 34% 26% 18%

Total 100% 100% 100% 100%

aThe percentages are weighted by the National Inflation Factor to represent population values.

Source: Our analysis of NASS 1988-91 data for model year 1987 and newer automobiles.

Conclusions and

Implications

Taken as a whole, the evidence indicates that the “inherent frailty”

hypothesis does not accurately describe the injury experience of women

drivers in automobile crashes but is consistent with that of older drivers.

This is because the relative injury risk of women drivers compared with

men drivers differs as a function of crash type, automobile size, and safety

belt use, while the relative injury risk of drivers 65 and older compared

with younger drivers is largely unaffected by those three factors. Women

drivers are more likely than men drivers to be hospitalized or killed in

collisions with cars and light trucks but not in one-car crashes, and women

drivers may be protected less well by heavier cars and by safety belts than

are men drivers. In contrast, drivers 65 and older have a greater risk of

hospitalization or death than younger drivers in one-car as well as

multivehicle crashes, and they are afforded roughly the same degree of

Page 41 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 3 

The Effects of Gender and Age on Driver

Injury Risk

protection as drivers 16 to 64 by greater automobile weight and safety belt

use.

The NASS data set did not allow us to pursue more specific explanations for

differences stemming from gender and age. For example, men and women

differ in many ways—on the average, women are shorter than men, weigh

less than men, and have bones that are less strong than men’s, among

other potentially relevant differences. It is difficult to identify the key

difference that accounts for women’s greater injury risk. Our findings

about the applicability of the inherent frailty hypothesis suggest that the

concerns of women drivers are more likely to be ameliorated by

automobile design changes than are those of older drivers. This means not

that it is impossible to reduce the injury risk of drivers 65 and older but

only that it may be difficult to close the gap between older and younger

drivers. The implications of our findings for future automobile safety are

discussed in chapter 5.

Three other points are worthy of mention. First, it is not surprising that the

injury risk in one-car rollover crashes is similar both for women and men

drivers and for drivers older and younger than 65. One-car rollover crashes

are very severe events, meaning that differences between individual

drivers are likely to be overwhelmed by the magnitude of the crash.

Further, few of the drivers in one-car rollover crashes were either women

or 65 or older.

Second, while our finding that safety belts may not protect women drivers

as well as men drivers is far from definitive, other researchers examining

data from other sources have also reported that the benefits of safety belts

are not as great for women as they are for men. (See, for example, Hill,

Mackay, and Morris, 1994; Mercier et al., 1993.)

Third, the types of crashes experienced by drivers 65 and older reduce the

protective influence of automobile weight for them. Not only are older

drivers much more likely to have multivehicle than one-car crashes; also,

those multivehicle collisions occur disproportionately in intersections and,

therefore, disproportionately involve side impacts. (See Viano et al., 1990.)

Automobile weight offers less protection in side-impact collisions than in

frontal impacts.

Page 42 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 4 

The Relative Importance of Crash Features,

Driver Characteristics, Safety Belts, and

Automobile Weight

As we demonstrated in chapters 2 and 3, crash severity, crash type,

automobile weight and wheelbase, safety belt use, and driver age and

gender, taken separately, each significantly influences the probability of

driver hospitalization or death. For this chapter, we also assessed the

relative importance of these factors simultaneously to see which ones are

the most important predictors of injury in a crash and which ones have

relatively little influence.

We found that crash severity is the most important predictor of driver

hospitalization or death, followed by crash type, safety belt use, driver age

and gender, and automobile weight. Crash severity refers to the speed of

impact, while crash type refers to the number of vehicles in a crash,

whether the car rolled over, and its points of impact. If information about

only one of these several factors were available for predicting whether the

driver would be seriously injured, having access to crash severity

information would lead to the greatest number of accurate predictions. If

crash severity information could not be obtained, information about the

crash type would give the best chance of accurately predicting whether or

not the driver would be injured. And so on down the list of factors.

Table 4.1 documents this finding. It shows a statistical measure of the

“explanatory power” of each factor. The table shows that the largest value

for this measure is for crash severity, followed by crash type, and then the

other factors in the order previously noted. The “explanatory power” of

automobile weight is substantially less than that of all the other factors.

Table 4.1: Relative Importance of

Crash-Related Factors in Predicting

Driver Hospitalization or Deatha Factor

Change in log

likelihood

Degrees of

freedom Probability

Crash severity 110.70 3 0.01

Crash type 71.75 5 0.01

Safety belts 38.88 3 0.01

Driver age and gender 26.04 4 0.01

Automobile weight 2.36 1 0.03

aLarger change in log likelihood values indicates the more important explanatory factors. The

probability column shows that all these factors are statistically significant. The change in log

likelihood values was computed first by estimating the logistic regression equation without the

variables representing each factor and then comparing the minus log likelihood values of those

equations with the minus log likelihood from the full model. The minus log likelihood for the full

equation is 1,020.13 (see table I.1). For crash severity, two variables measure change in velocity

at impact and one measures the speed limit of the roadway section where the crash occurred.

For crash type, five categorical variables represent a one- or two-vehicle crash, a vehicle rollover,

a head-on crash, and front or left-side impact points. Three categorical variables measure driver

age, and one indicates gender. Automobile weight is a continuous variable.

Source: GAO analysis of NASS 1988-91 data for model year 1987 and newer automobiles.

Page 43 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 4 

The Relative Importance of Crash Features,

Driver Characteristics, Safety Belts, and

Automobile Weight

Another way to illustrate the great importance of the crash severity and

crash type factors is presented in figure 4.1. Each column in the figure

shows the estimated increment in risk of injury associated with a change

in the associated crash-related factor, combining the three types of

crashes in our analysis. Thus, the “crash severity” bar in the figure shows

that crashes involving a change in velocity of 23 mph have an estimated

risk of driver injury 25 times as great as crashes with a change in velocity

of only 6 mph.1

 The bar for crash type shows our estimate that drivers

involved in one-car rollover crashes are about nine times more likely to be

hurt than drivers involved in collisions with cars and light trucks that are

not head-on crashes.

Similarly, figure 4.1 shows that drivers 65 and older are about 4.5 times

more likely to be hospitalized or killed than drivers 16 to 24 and that

unbelted drivers have an injury risk more than three times as great as

drivers wearing manual lap and shoulder safety belts. Drivers of

2,000-pound automobiles have an estimated injury risk in a crash that is

about 1.63 times (or 63 percent greater than) that of drivers of 3,600-pound

cars.2

 Finally, the estimated injury risk for women drivers is about 1.29

times (or 29 percent greater than) that of men drivers.

1

We used change in velocity values of 23 and 6 mph in this example because those values are near the

endpoints of the change in velocity distribution. Twenty-three mph is the 95th percentile of the change

in velocity distribution, while 6 mph is the 5th percentile.

2

Two thousand pounds represents the 5th percentile of the distribution of automobile weights in this

data set; 3,600 pounds is the 95th percentile.

It is important to note that this finding about the injury risks to individual drivers of automobiles of

different weights does not mean that the overall “downsizing” of automobiles over the past 20 years

has led to more total highway fatalities (see GAO, 1991).

Page 44 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 4 

The Relative Importance of Crash Features,

Driver Characteristics, Safety Belts, and

Automobile Weight

Figure 4.1: Odds of Injury Associated

With Changes in Crash-Related

Factorsa

Magnitude of injury risk increase

0

5

10

15

20

25

Crash severity

Crash type

Driver’s age

Safety belt use

Automobile weight

Driver’s gender

aEstimates include all one-car crashes and collisions with cars and light trucks. Endpoints for

each factor:

Crash severity: 23 mph change in velocity versus baseline 6 mph change in velocity.

Crash type: drivers in one-car rollovers versus baseline drivers in collisions with cars and light

trucks that are not head-on.

Driver’s age: drivers 65+ versus baseline drivers 16-24.

Safety belt use: unbelted drivers versus baseline drivers wearing manual lap and shoulder safety

belts.

Automobile weight: drivers of 2,000-lb cars versus baseline drivers of 3,600-lb cars.

Driver’s gender: women versus baseline men.

Source: Our analysis of NASS 1988-91 data for model year 1987 and newer automobiles.

Page 45 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 5 

Future Automobile Safety

Here we discuss the implications of our findings for future automobile

safety. The first section below reviews the safety initiatives from NHTSA

that have the greatest importance for automobile crashworthiness. The

next section discusses ways to reduce the injury risk for particular

categories of automobile drivers. The last section discusses the most

effective uses of available safety technologies.

It is important to keep two points in mind when considering alternative

approaches to automobile crashworthiness. First, crashworthy

automobiles must offer as much protection as possible for a broad matrix

of crash types, crash speeds, and occupant characteristics that pose very

different occupant protection problems. For example, we found that

one-car crashes, particularly rollovers, are much more dangerous than

collisions with cars and light trucks. We also found that men drivers and

young drivers are disproportionately involved in one-car crashes, while

women drivers and older drivers are more likely to be involved in

collisions with cars and light trucks. Protecting young men in severe

one-car crashes is very different from protecting women and older drivers

in multivehicle collisions. Second, individual safety features often affect

only one portion of the matrix of crash types and occupant characteristics.

For example, air bags clearly help protect occupants in frontal collisions,

but they do not contribute to occupant safety in side-impact collisions or

rollover crashes.

NHTSA Safety

Initiatives

Recent Regulations

Frontal Impacts Starting with the 1990 model year, all automobiles sold in the United

States have had to demonstrate driver and right-front-seat passenger

safety with passive restraints in a full-frontal crash at 30 mph into a rigid

barrier.1

 “Passive restraint” means without the use of any safety device

requiring actions by the driver or passenger, such as manual safety belts.2

In model year 1987, the first year of the phase-in period for this regulation,

all the automobiles NHTSA tested met this requirement with automatic

1

See Highway Safety: Reliability and Validity of DOT Crash Tests (GAO/PEMD-95-5).

2

Under this regulation, automobiles can be equipped with manual safety belts, but the safety standards

of the compliance test must be met without benefit of the protection afforded by the manual belts.

Page 46 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 5 

Future Automobile Safety

safety belts. By 1993, almost all the tested cars fulfilled the passive

restraint requirement with air bags rather than automatic belts alone,

although many of the cars with air bags also had automatic safety belts.

NHTSA has announced major changes in this regulation.3 All cars

manufactured in September 1997 or later will be required to have both air

bags and manual lap and shoulder safety belts for both drivers and

right-front-seat passengers. Very importantly, the revised regulation

prohibits automatic safety belts—not just for use in the compliance tests

but as safety equipment. All cars will have to be equipped with manual

safety belts.

Side Impacts Beginning with the 1994 model year, NHTSA began phasing in a requirement

for automobile occupant protection in side impacts. By model year 1997,

all automobiles will have to meet safety standards in crash tests simulating

the impact of a 3,000-pound vehicle hitting the target car in a side-impact

collision at 33.5 mph. Unlike the frontal impact crash tests, active restraint

systems, such as manual safety belts, must be used in these tests.

Other Activities NHTSA is also undertaking a variety of efforts to deal with particular

mechanisms of occupant injury rather than points of contact on the

automobile. For example, to reduce head injuries, NHTSA is developing a

regulation that would require energy-absorbing padding in the areas of

automobile interiors that occupants’ heads frequently strike in side-impact

collisions. Also, NHTSA is studying ways to further reduce injuries in

rollover crashes, primarily by reducing the risk of ejection, by improving

door latches and increasing the strength of automobile windows other

than windshields, as well as by considering tougher roof crush standards.

Other NHTSA activities are concerned with particular types of automobile

occupants, especially children and elderly persons. It is important to note

that NHTSA is seeking ways to improve protection for elderly drivers,

although a major focus of NHTSA’s work involves programs to improve their

driving skills or otherwise reduce their likelihood of crash involvement.

(See Transportation Research Board, 1992, and NHTSA, 1993a; see also

NHTSA 1992b for its activities priority plan through 1994.)

3

Federal Register, September 2, 1993 (49 C.F.R. 571-585).

Page 47 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 5 

Future Automobile Safety

Injury Reduction for

Different Types of

Drivers

Automobile manufacturers understand that different segments of the

consumer market for automobiles prefer different types of cars. For

example, young men are likely to prefer sports cars over station wagons,

and older drivers disproportionately prefer large cars over smaller ones. In

other words, in the marketplace for automobiles, one size does not fit all.

Similarly, one size does not fit all when it comes to automobile safety: the

crashworthiness problems of different types of drivers, and of drivers

involved in different types of crashes, require a variety of different

solutions. Here, we look at the differential safety concerns of segments of

the safety “marketplace” that are defined by safety belt use and driver age

and gender.

Unbelted and Belted

Drivers

Drivers involved in traffic crashes, on the whole, operate their vehicles in

a riskier manner than drivers who are not involved in crashes. For

example, the rate of safety belt use for drivers involved in crashes is less

than the use rate for the general driving population. Estimates of the

degree to which drivers who do not wear safety belts are overinvolved in

roadway crashes vary considerably. For example, NHTSA (1992a) estimated

that unbelted drivers experience potentially fatal crashes 2.2 times more

than belted drivers, while Hunter et al. (1993) found that unbelted drivers

had a crash involvement rate 35 percent higher than belt users.

Unbelted and belted drivers have very different injury experiences in a

crash. Unbelted drivers are more likely to suffer severe injuries, and their

injuries are more likely to result from contact with the steering wheel or

windshield (Danner, Langieder, and Hummel, 1987; Lestina et al., 1991).

These differences are explained by the mechanisms of safety belt

effectiveness. Safety belts tie the occupant to the car, helping the occupant

decelerate over a relatively long period. In addition, by restricting

movement, safety belts reduce the chances of the wearer’s striking the

interior of the vehicle and help make his or her course of motion within

the car more predictable. In contrast, unbelted occupants keep moving

within the automobile in the moments after collision, the direction of their

movement within the vehicle is relatively unpredictable, and it is likely

either that their rapid motion will be abruptly stopped by contact with a

rigid surface within the vehicle or that they will be ejected from it.

Therefore, optimally safe vehicle interiors are conceptually dissimilar for

belted and unbelted occupants (Mackay, 1993). For belted occupants, the

more interior space the better, as increasing the space reduces the odds of

contact with interior surfaces. Conversely, for unbelted occupants, the

Page 48 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 5 

Future Automobile Safety

goal is to restrict movement and provide a soft place to land, so heavily

padded interiors that minimize interior space are preferred.

How can crash protection be improved for unbelted and belted drivers?

For unbelted drivers, the obvious answer is to put them in safety belts. In

practical terms, the best way to do this is to increase the number of

automobiles with automatic safety belts. As NHTSA (1992a) and Williams et

al. (1992) have reported, automobiles equipped with automatic safety belts

have much higher belt usage rates than those with manual belts. While

experimental vehicles have been designed with substantial protection for

unbelted occupants, we do not believe that any combination of interior

padding, air bags, and other passive restraint systems will be able to rival

the effectiveness of safety belts in production automobiles for the

foreseeable future. One reason for this is that, as noted above, designing

an optimally safe car for unrestrained drivers may require abandoning

safety belts as the centerpiece of occupant protection strategies. And

safety belts are extraordinarily effective; alone, they are much more

effective at reducing serious injuries than are air bags alone.

For belted drivers, the prospects for dramatic improvements in crash

protection are less obvious. On the one hand, promising efforts are under

way to reduce much of the residual risk of injury confronting belted

drivers. These include improvements in safety belt technology, the greater

availability of air bags, and NHTSA’s efforts to improve occupant protection

in side impacts. On the other hand, the great success of recent occupant

protection efforts means that further crashworthiness improvements are

harder to achieve, primarily because the dwindling proportion of crashes

that still cause serious injury and death to belted occupants are

exceptionally severe events. For example, Mackay et al. (1992), reviewing

a sample of crashes involving the death of restrained front-seat occupants

in Britain, found that the deaths occurred in extremely severe crashes.

Fifty percent of the deaths in frontal crashes were in collisions with large

trucks, and 86 percent involved passenger compartments crushed so

severely as to eliminate the space occupied by the fatally injured person

before the crash. Similarly, Green et al. (1994) reported that most of the

fatalities of restrained occupants that they examined involved severe

intrusion into the passenger compartment and multiple injuries so severe

that 90 percent of the victims died within an hour of the crash.

Driver Age and Gender The “market segments” for automobile safety defined by driver age and

gender require very different strategies for reducing fatalities. For men

Page 49 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 5 

Future Automobile Safety

drivers and younger drivers, the problem is crash involvement, not

crashworthiness. As we demonstrated in chapter 2, compared to women

and older drivers, not only are men drivers and younger drivers involved in

more automobile crashes but also the crashes they are particularly likely

to be involved in have comparatively severe consequences—that is,

single-car crashes have much higher driver injury rates than multivehicle

crashes. However, as we saw in chapter 3, men drivers and younger

drivers are significantly less likely to be hurt in a crash than women and

older drivers. That is, men and younger drivers benefit from a degree of

occupant protection that is not available to women and older drivers (we

will discuss some of the reasons later). In summary, the surest way to

improve the safety of men drivers and younger drivers is to attempt to

reduce their crash involvement rates, particularly their rates of

involvement in single-car crashes.

The situation is exactly the reverse for women and older drivers. The

problem for them is crashworthiness, not crash involvement. Compared to

men and younger drivers, women and older drivers are involved in fewer

automobile crashes, and the crashes they are involved in are, on the

average, less severe, since they are less likely to be involved in single-car

crashes than in multivehicle collisions. However, once a crash has

occurred, women and, especially, older drivers are more likely to be

hospitalized or killed.

In our judgment, improving the crash protection offered by automobiles to

women and older drivers so that it approaches the level enjoyed by men

and younger drivers offers the greatest chance for reducing roadway

injuries for them.4

 In the absence of compelling evidence for the inherent

physical frailty of women compared to men, we are optimistic that

crashworthiness for women can be substantially improved. In contrast, the

evidence we have reviewed indicates that older drivers are, in fact, more

fragile than young drivers. Nonetheless, we believe that older drivers can

be afforded better protection by automobiles than they now receive (see

subsequent discussion and Mackay, 1988). It is important that occupant

protection for women drivers and older drivers be improved without

4

This does not mean that efforts to reduce the crash involvement rates of women drivers and older

drivers should not continue, but it does mean that the predominant focus should be on improving

crashworthiness. This is particularly true for women drivers; notwithstanding recent calls to focus

crash prevention programs on women drivers (for example, Centers for Disease Control, 1992), men

drivers have much higher crash involvement rates than women drivers (GAO, 1994). In recent years,

men drivers have been involved in more than three times as many fatal crashes as women drivers. For

older drivers, efforts to understand, measure, and control the deterioration of physical and cognitive

abilities that can impair driving skills are obviously important, but the crash involvement risk of older

drivers is already reduced because they drive so many fewer miles than younger drivers (Evans, 1988a;

“As Nation Grows Older,” 1992; NHTSA, 1993a).

Page 50 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 5 

Future Automobile Safety

compromising the crash protection of men drivers and younger drivers;

design changes that merely shift injury risk from one group of drivers to

another will not improve traffic safety in the aggregate.

One possible reason for the relatively high degree of crash protection

enjoyed by men drivers and younger drivers is that efforts at improving

automobile crashworthiness have concentrated on the crash types and

occupant characteristics most often experienced by them. Current safety

regulations and automobile safety designs emphasize protection in

high-speed frontal collisions, and men drivers and younger drivers are

more likely to be in single-car crashes, which disproportionately involve

frontal impacts. The automobile crash tests NHTSA currently requires for all

cars include full-frontal crashes into a rigid barrier at 30 mph (although the

introduction of a requirement for side-impact tests is under way). Air bags

reduce the risk of injury in frontal impacts only, not in side impacts.

Similarly, safety belts are more effective in frontal than in side impacts

(for example, Evans, 1990), and because of this, safety belts have a

somewhat greater benefit in single-car crashes than in collisions with cars

and light trucks.

A second possible reason for the crashworthiness deficit of women drivers

compared with men drivers is that current NHTSA regulations require the

use of only one size of crash test dummy—a dummy representing the 50th

percentile of the male population, or 5 feet 9 inches tall, weighing 165

pounds. Maximizing the safety of persons with these characteristics may,

in a relative sense, compromise the safety of others.

Another possible explanation for the greater injury risk for women drivers

is that, on the average, women are shorter and lighter than men.

Automobiles designed to accommodate taller and heavier men drivers may

not accommodate women as well. For example, the Insurance Institute for

Highway Safety (1993) recommends that drivers sit back as far as possible

from the steering wheel and dashboard in order to minimize the risk of

hitting those structures in a crash. Shorter drivers obviously cannot sit as

far back as taller drivers if they hope to reach the accelerator and brake

pedals, and this may expose them to more risk.

Page 51 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 5 

Future Automobile Safety

Making Effective Use

of Available Safety

Technologies

Enhanced Safety Belts All safety belts are not equally effective. In particular, many cars on the

market today have safety belts with automatic pretensioners or web

locking devices that substantially improve their effectiveness (IIHS, 1993).

Pretensioners work by reducing the amount of slack in the belts or by

tightening them in a crash a fraction of a second sooner. They cause the

belted occupant to begin decelerating sooner in a crash, thereby

increasing the total deceleration period. In addition, they increase the

chances that the occupant’s forward motion will be stopped before he or

she contacts the interior of the automobile.

To give an idea of the magnitude of the safety increment available from

belts with these features, Viano (1988) compared the performance of

several restraint mechanisms in frontal crash tests. Depending on the

outcome measure used, lap and shoulder belts with pretensioners had

injury scores about 15 to 40 percent below those of lap and shoulder belts

without pretensioners.

NHTSA’s Implementation

of the Requirement for Air

Bags

NHTSA has recently announced regulations that would implement the

requirement in the Intermodal Surface Transportation Efficiency Act of

1991 that all passenger cars and light trucks be equipped with air bags and

lap and shoulder safety belts. Beginning with all cars manufactured in

September 1997, both drivers and right-front-seat passengers will have

both air bags and manual lap and shoulder safety belts; automatic safety

belts are prohibited.

We are concerned that NHTSA’s implementation of the requirement for air

bags may not achieve the greatest degree of improvement in the aggregate

safety of the population of automobile occupants. Automobile occupants

who travel in cars with air bags and who wear manual lap and shoulder

safety belts will be well protected. However, because safety belts alone

offer much more protection than air bags alone, occupants of air

bag-equipped cars who do not wear lap and shoulder safety belts will be

less well protected than if they were traveling in cars with automatic

safety belts. This is important because cars with automatic safety belts

have higher safety belt usage rates than cars with manual belts, and

Page 52 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 5 

Future Automobile Safety

individuals involved in serious automobile crashes have lower safety belt

use rates than others. If many automobile occupants in serious crashes do

not wear manual safety belts, the aggregate safety of automobile

occupants under NHTSA’s proposal would be less than if, in addition to air

bags, automatic safety belts were encouraged or required.

To examine this question, we compared the average amount of occupant

protection available to all automobile occupants under three different

safety-belt-use scenarios based on a recent NHTSA report (NHTSA, 1992a). In

that report, NHTSA noted that cars equipped with manual lap and shoulder

belts had a belt usage rate of 56 percent in 1991, while cars equipped with

automatic safety belts had usage rates ranging from 64 to 97 percent,

depending on the type of automatic belt.5

 If all cars had air bags and

manual lap and shoulder belts and a belt usage rate of 56 percent, we

estimate that fatality risk would fall 37.2 percent for the average

automobile occupant compared with unprotected occupants.6

 If all cars

had air bags and automatic safety belts and a belt usage rate of 64 percent,

we estimate that the average automobile occupant would have a

37.7-percent reduction in fatality risk.7

 If all cars had air bags and

automatic safety belts and a belt usage rate of 97 percent, we estimate that

the total fatality risk reduction would be 46 percent.8

Thus, from the standpoint of maximizing the aggregate safety of all

automobile occupants, the best proposal may be one that requires both air

5

For the following calculations, we used figures reported by NHTSA. We assumed that unbelted drivers

are 2.2 times more likely than belted drivers to be involved in serious crashes (NHTSA, 1992a, p. 21),

that manual lap and shoulder belts reduce the risk of fatality by 45 percent (1993d, p. II-13), that

automatic safety belts reduce fatality risk by 42.5 percent (1993d, p. II-13), that air bags alone reduce

fatality risk by 30 percent, and that air bags with manual lap and shoulder belts reduce the risk of

fatality by 50 percent (1993d, p. II-13). Assuming that air bags improve the lot of belted occupants by

about 11 percent (as NHTSA estimates for manual lap and shoulder belts), we estimated for this

analysis that air bags with automatic safety belts reduce fatality risk by 47 percent (42.5 x 1.11 = 47).

6

If 56 percent of all drivers wore manual lap and shoulder safety belts, then about 37 percent of drivers

in crashes would be belted. Those drivers would have a fatality risk reduction of 50 percent, while the

remaining 63 percent of crash-involved drivers—that is, those not wearing safety belts—would have a

fatality risk reduction of 30 percent, for an overall fatality risk reduction of 37.2 percent.

7

If 64 percent of all drivers wore automatic lap and shoulder safety belts, then about 45 percent of

drivers in crashes would be belted. Those drivers would have a fatality risk reduction of 47 percent,

while the remaining 55 percent of crash-involved drivers—that is, those not wearing safety

belts—would have a fatality risk reduction of 30 percent, for an overall fatality risk reduction of

37.7 percent.

8

If 97 percent of all drivers wore automatic lap and shoulder safety belts, then about 94 percent of

drivers in crashes would be belted. Those drivers would have a fatality risk reduction of 47 percent,

while the remaining 6 percent of crash-involved drivers—that is, those not wearing safety

belts—would have a fatality risk reduction of 30 percent, for an overall fatality risk reduction of

46.1 percent.

Page 53 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 5 

Future Automobile Safety

bags and automatic lap and shoulder safety belts. The magnitude of the

fatality risk reduction arising from that configuration compared to NHTSA’s

regulation requiring manual lap and shoulder safety belts depends on the

difference between the usage rates of automatic and manual safety belts

for automobile occupants involved in serious crashes. As our estimates

show, if that difference is small, the automatic safety belt alternative offers

only a very slight aggregate safety improvement. Conversely, if the usage

rate difference is high, placing air bags and automatic lap and shoulder

safety belts in all cars would substantially improve the safety of

automobile occupants in the aggregate.

Agency Comments

and Our Evaluation

DOT had two comments regarding the implications of our finding that,

holding constant crash characteristics and automobile weight, women are

more likely than men to suffer serious injury in a crash. The first is that

NHTSA plans to conduct crash tests with test dummies of different sizes

rather than only the standard dummy that represents a 50th percentile

man driver. The second is that NHTSA has recently made final a rule

requiring improvements in the adjustability of safety belts that may

increase the percentage of vehicle occupants using belts correctly. We

applaud both these developments. Nonetheless, in our opinion, there is no

definitive evidence that either size differences or patterns of safety belt

use fully account for the differences in injury rates between men and

women.

DOT also had two comments on our discussion of NHTSA’s implementation

of the requirement for air bags. First, it contended that the usage figures

for automatic safety belts that we used in our example are unrealistically

high. More specifically, DOT stated that the usage rates for complete

automatic belt systems are much less than the 97-percent scenario we

described, since some drivers use only one component but not the other

(for example, using the shoulder belt but not the lap belt) and other

drivers disconnect the automatic belt system entirely. Second, DOT

disagreed with our conclusion that manual and automatic safety belts

provide “a roughly equivalent degree of protection.”

For the first point, we understand that it is extremely difficult to

accurately measure safety belt use, especially the use of particular safety

belt components (see chapter 2). However, NHTSA (1992a) has concluded

that automatic safety belts are used more often than manual belts, and our

97-percent usage rate scenario was based on a NHTSA report, not on our

own analysis. Further, our findings would not differ even if automatic

Page 54 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Chapter 5 

Future Automobile Safety

safety belts had usage rates much less than 97 percent; thus, we found that

the scenario with a 64-percent usage rate for automatic belts (NHTSA’s

lowest estimate) still provided slightly more total protection than the other

scenario we considered, manual belts with a 56-percent usage rate. For the

second point, our conclusion that manual and automatic safety belts

provide approximately equivalent protection is based on NHTSA’s work, not

on our own analyses of automobile crash data. For example, NHTSA (1993d,

p.II-13) estimated that, when used in a crash, manual lap and shoulder

safety belts reduce fatality risk by 45 percent and automatic three-point

belts reduce fatality risk by 42.5 percent. Similarly, NHTSA earlier reported

that it was unable to find any statistically significant differences between

several different configurations of manual and automatic safety belts

(NHTSA, 1992a, p.66).

Most importantly, neither of DOT’s comments about our discussion of

NHTSA’s implementation of the requirement for air bags addressed our main

point—that drivers involved in serious crashes use safety belts much less

than the general driving population. Our discussion is aimed at improving

crash protection for drivers who have the greatest risk of involvement in

serious crashes. A comprehensive evaluation of the best ways to increase

safety belt use for those drivers is beyond the scope of this report.

However, as our analysis demonstrates, NHTSA’s decision to prohibit

automatic safety belts may not achieve the best result from that

perspective. At a minimum, NHTSA needs to continue to emphasize in its

public education efforts the importance of wearing safety belts even in

cars equipped with air bags.

Page 55 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Appendix I 

Regression Analyses for Driver Injury

The Data Set We compiled the data set for our analyses from the National Accident

Sampling System—Crashworthiness Data System (NASS) for 1988 through

1991. NASS is a nationally representative probability sample of all

police-reported crashes involving a passenger car, light truck, or van in

which at least one vehicle was towed from the scene. For more

information about NASS, including the sampling frame, sampling plan, and

variable definitions, see NHTSA (1991c, 1991d).

For our data set, we selected the subset of cases from NASS that included

all one-car crashes involving 1987 or later model year automobiles and all

collisions between a model year 1987 or later automobile and any other

car, van, pickup truck, or light truck. We discarded automobiles that had

no valid curb weight information or no identifiable driver or a driver

younger than 16 years of age. The final data set included 6,103 cases of

eligible automobiles and their drivers: 457 in one-car rollover crashes,

1,253 in one-car nonrollover crashes, and 4,393 in collisions with other

cars or light trucks.

The Outcome Variable The outcome variable in our analyses was a dichotomous variable for

driver injury coded “1” if the driver was hospitalized or killed in the crash

and coded “0” otherwise. We chose this outcome measure because it is

easy to understand and unambiguous. This variable was created from the

“treatment” variable in the NASS file. In NASS, occupants were coded as

hospitalized if they were admitted to a hospital for an overnight stay and

coded as killed if they died within 30 days of the crash from injuries

sustained in the crash.

To relate this measure of driver hospitalization or death to other measures

of injury severity, our measure overlaps with injuries categorized as

moderate to serious by the Abbreviated Injury Scale (AIS). (See Evans,

1991b.) Thus, we classified 19 percent of the drivers in this data set as

hospitalized or killed. Had we used the AIS scheme, 24 percent of all

drivers would have been classified as suffering a moderate or more severe

injury (AIS 2-6) and 10 percent as suffering a serious or more severe injury

(AIS 3-6).1

 For the drivers we coded as hospitalized or killed, 18 percent

were killed, 33 percent had an injury listed as serious or critical on AIS (AIS

3-6), 33 percent had a moderate injury on AIS (AIS 2), and 16 percent had

minor or no injuries according to the AIS scale.

1

All the percentages in this paragraph are unweighted.

Page 56 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Appendix I 

Regression Analyses for Driver Injury

The Predictor Variables For independent variables in the regressions, we used a number of factors

measuring crash type, crash severity, automobile characteristics, driver

safety belt use, and driver age and gender. All the independent variables

are listed below. As the following regression tables show, not all these

variables were used in all the regression analyses. The estimated

population values for the variables are listed in the tables.

Crash Type • One-car crash was coded “1” if only one car was involved in the crash and

coded “0” if the crash was a two-vehicle collision.

• Rollover was coded “1” if the automobile rolled over (either as the primary

crash event or as a secondary event) and coded “0” otherwise.

• Head-on collision was coded “1” if the crash was a two-vehicle collision

between vehicles moving in opposite directions and coded “0” otherwise.

• Front area damage to the car was coded “1” if the crash was not head-on

yet the car sustained frontal damage and coded “0” otherwise.

• Left side damage to the car was coded “1” if the crash was not head-on and

the car sustained left-side damage and coded “0” otherwise.

Crash Severity • Speed limit 40 mph or greater was coded “1” if the speed limit at the

roadway location of the crash was 40 mph or greater and coded “0”

otherwise.

• Has change in velocity value was coded “1” if the automobile had a valid

change in velocity value in NASS and coded “0” otherwise. (Many

automobiles had missing values for change in velocity in NASS; in

particular, all the cars in one-car rollover crashes had missing values.)

• Change in velocity was measured in miles per hour. (Change in velocity

refers to the nearly instantaneous change in a vehicle’s speed that occurs

in a crash. For example, a vehicle that was abruptly stopped from a travel

speed of 30 mph would have a change in velocity of 30 mph.) Automobiles

coded “0” on the “has change in velocity value” variable were assigned the

mean value of the change in velocity scores for each analysis.

Automobile Characteristics • Model year was indexed by three categorical variables for model years

1987, 1988, and 1989. Cars from those model years were coded “1” for the

appropriate year and “0” for the other years. Automobiles from the 1990

model year and later were coded “0” for all three variables.

• Curb weight was measured in 100-pound increments in NASS. Curb weight

refers to the weight of the unoccupied automobile, including gasoline and

other fluids.

• Wheelbase was measured in inches. (Wheelbase is a measure of

automobile length that is one indication of the exterior size of a vehicle.

Wheelbase refers to the distance between the front and rear axles.) Many

Page 57 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Appendix I 

Regression Analyses for Driver Injury

of the cars in the data set had missing wheelbase values in NASS. We were

able to assign valid values to most of them by matching the missing cases

to cars that had valid wheelbase values, based on model year, make,

model, and body type. Nonetheless, slightly fewer cars had valid

wheelbase values than had valid curb weight values in our final data set.

Driver Safety Belt Use • Manual lap and shoulder belt use was coded “1” if the driver was noted by

NASS researchers as wearing manual lap and shoulder safety belts (a

“3-point belt”) at the time of crash and coded “0” otherwise.

• Automatic belt use was coded “1” if the driver was noted by NASS

researchers as wearing an automatic safety belt (a 3-point belt, a lap belt

only, or a shoulder belt only) at the time of the crash and coded “0”

otherwise.

• Both manual and automatic belt use was coded “1” if the driver was noted

by NASS researchers as wearing both an automatic shoulder belt and a

manual lap belt at the time of the crash and coded “0” otherwise.

Driver Age and Gender • Driver age was indexed with four categorical variables representing ages

16 to 24 years, 25 to 44, 45 to 64, and 65 and older. Drivers were coded “1”

for the appropriate age category and “0” for the other categories.

• Driver gender was coded “1” for men and “0” for women.

Results of the

Regression Analyses

Tables I.1 through I.8 present the results of our regression analyses. The

eight tables show the analyses for four sets of crashes (all crashes

included in the data set, one-car rollover crashes, one-car nonrollover

crashes, and collisions with cars and light trucks), using two measures of

automobile size (curb weight and wheelbase).

Page 58 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Appendix I 

Regression Analyses for Driver Injury

Table I.1: One-Car Crashes and Collisions With Other Cars or Light Trucks: Logistic Regression Analysis Predicting Driver

Hospitalization or Death, Model With Curb Weight

Variable Coefficienta

Odds

ratiob

ChisquarecProbability

leveld

Population

meane

Automobile model year (versus 1990 and newer)

1987 0.188 1.207 0.75 0.39 0.31

1988 –0.024 0.976 0.01 0.91 0.29

1989 0.205 1.227 0.71 0.40 0.21

Speed limit 40+ mph 0.459 1.582 9.76 0.01 0.50

One-car crash (versus two-vehicle crash) 0.915 2.497 38.37 0.01 0.26

Rollover 1.291 3.637 36.35 0.01 0.06

Head-on collision 1.159 3.188 24.65 0.01 0.03

Area of damage to the car (if not head-on collision)

Front 0.521 1.684 8.45 0.01 0.60

Left side 0.690 1.994 17.38 0.01 0.21

Safety belt use (versus unbelted)

Manual lap and shoulder belts –1.216 0.297 51.77 0.01 0.49

Automatic belts –0.769 0.464 17.14 0.01 0.13

Both manual and automatic belts –1.002 0.367 20.48 0.01 0.11

Male driver –0.251 0.778 4.18 0.04 0.50

Driver age in years (versus 16-24)

25-44 0.542 1.720 9.19 0.01 0.43

45-64 0.940 2.559 33.72 0.01 0.14

65+ 1.509 4.521 54.35 0.01 0.07

Collision severity: change in velocity

Has change in velocity value 0.833 2.300 35.01 0.01 0.35

Change in velocity (mph) 0.191 1.211 116.89 0.01 14.55

Automobile weight (100s of pounds) –0.030 0.970 6.98 0.01 26.64

Constant –6.447

(Table notes on next page)

Page 59 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Appendix I 

Regression Analyses for Driver Injury

aCoefficients are from logistic regression analyses conducted with the SUDAAN software

package. The outcome variable is dichotomous—that is, “1” indicates that the driver was

hospitalized or killed, “0” that the driver was neither hospitalized nor killed.

bThe odds ratio is the exponentiated coefficient (ecoefficient). The odds ratio indicates the change in

the odds of injury that occur with a change of one unit in the variable. For example, increasing

automobile weight by 100 pounds decreases the odds of hospitalization or death by a factor of

0.970, or 3 percent. The odds ratio for categorical variables indicates the change from the left-out

group. For example, the injury odds for men drivers are 0.778 that of women drivers, the left-out

group.

cThe chi-square values test the statistical significance of the coefficients. The values are

calculated from the Satterthwaite approximation to the chi-square distribution. This procedure

reduces the chances of a Type I error. (See J. N. K. Rao and D. R. Thomas, “Chi-Squared Tests

for Contingency Tables,” in C. J. Skinner, D. Holt, and T. M. F. Smith (eds.), Analysis of Complex

Surveys (New York: John Wiley and Sons, 1989).)

dProbability levels are from the Satterthwaite adjusted chi-square tests. Probability level refers to

the chances that the coefficient equals zero in the population. By convention, coefficients with a

probability level less than or equal to 5 percent (0.05) are regarded as statistically significant. In

this table, 0.01 indicates a probability less than or equal to 0.01.

eThe population means are the variable values in this sample weighted by the National Inflation

Factor to approximate population values.

Table I.2: One-Car Crashes and Collisions With Other Cars or Light Trucks: Logistic Regression Analysis Predicting Driver

Hospitalization or Death, Model With Wheelbase

Variable Coefficienta

Odds

ratiob

ChisquarecProbability

leveld

Population

meane

Automobile model year (versus 1990 and newer)

1987 0.210 1.233 0.90 0.34 0.31

1988 –0.029 0.971 0.02 0.89 0.29

1989 0.254 1.289 1.03 0.31 0.21

Speed limit 40+ mph 0.456 1.577 10.05 0.01 0.50

One-car crash (versus two-vehicle crash) 0.873 2.395 34.11 0.01 0.26

Rollover 1.306 3.693 33.75 0.01 0.06

Head-on collision 1.102 3.010 22.12 0.01 0.03

Area of damage to the car (if not head-on collision)

Front 0.542 1.719 8.72 0.01 0.60

Left side 0.675 1.964 16.04 0.01 0.21

Safety belt use (versus unbelted)

Manual lap and shoulder belts –1.240 0.289 53.03 0.01 0.49

Automatic belts –0.763 0.466 16.77 0.01 0.13

Both manual and automatic belts –1.048 0.351 22.28 0.01 0.11

Male driver –0.262 0.769 4.54 0.03 0.50

Driver age in years (versus 16-24)

25-44 0.565 1.760 9.65 0.01 0.43

(continued)

Page 60 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Appendix I 

Regression Analyses for Driver Injury

Variable Coefficienta

Odds

ratiob

ChisquarecProbability

leveld

Population

meane

45-64 0.966 2.627 34.93 0.01 0.14

65+ 1.609 4.997 51.73 0.01 0.07

Collision severity: change in velocity

Has change in velocity value 0.817 2.264 31.53 0.01 0.35

Change in velocity (mph) 0.192 1.212 115.64 0.01 14.55

Automobile wheelbase (inches) –0.028 0.973 9.24 0.01 101.07

Constant –4.456

aCoefficients are from logistic regression analyses conducted with the SUDAAN software

package. The outcome variable is dichotomous—that is, “1” indicates that the driver was

hospitalized or killed, “0” that the driver was neither hospitalized nor killed.

bThe odds ratio is the exponentiated coefficient (ecoefficient). The odds ratio indicates the change in

the odds of injury that occur with a change of one unit in the variable. For example, increasing

automobile wheelbase by 1 inch decreases the odds of hospitalization or death by a factor of

0.973, not quite 3 percent. The odds ratio for categorical variables indicates the change from the

left-out group. For example, the injury odds for men drivers are 0.769 that of women drivers, the

left-out group.

cThe chi-square values test the statistical significance of the coefficients. The values are

calculated from the Satterthwaite approximation to the chi-square distribution. This procedure

reduces the chances of a Type I error. (See J. N. K. Rao and D. R. Thomas, “Chi-Squared Tests

for Cotingency Tables,” in C. J. Skinner, D. Holt, and T. M. F. Smith (eds.) Analysis of Complex

Surveys (New York: John Wiley and Sons, 1989).)

dProbability levels are from the Satterthwaite adjusted chi-square tests. Probability level refers to

the chances that the coefficient equals zero in the population. By convention, coefficients with a

probability level less than or equal to 5 percent (0.05) are regarded as statistically significant. In

this table, 0.01 indicates a probability less than or equal to 0.01.

eThe population means are the variable values in this sample weighted by the National Inflation

Factor to approximate population values.

Page 61 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Appendix I 

Regression Analyses for Driver Injury

Table I.3: One-Car Rollover Crashes: Logistic Regression Analysis Predicting Driver Hospitalization or Death, Model With

Curb Weight

Variable Coefficienta

Odds

ratiob

ChisquarecProbability

leveld

Population

meane

Automobile model year (versus 1990 and newer)

1987 0.468 1.596 0.78 0.38 0.31

1988 –0.124 0.883 0.03 0.86 0.35

1989 0.458 1.581 0.55 0.46 0.18

Speed limit 40+ mph 1.111 3.038 8.50 0.01 0.75

Area of damage to the car

Front 1.202 3.326 18.17 0.01 0.32

Left side 0.108 1.114 0.05 0.82 0.16

Safety belt use (versus unbelted)

Manual lap and shoulder belts –1.775 0.169 18.89 0.01 0.44

Automatic belts –0.684 0.505 2.05 0.15 0.14

Both manual and automatic belts –0.806 0.447 1.91 0.17 0.10

Male driver –0.040 0.961 0.01 0.93 0.63

Driver age in years (versus 65+)

16-24 0.114 1.121 0.02 0.89 0.54

25-44 0.350 1.419 0.17 0.68 0.36

45-64 0.920 2.508 1.15 0.29 0.07

Automobile weight (100s of pounds) 0.092 1.097 4.44 0.04 25.02

Constant –5.110

aCoefficients are from logistic regression analyses conducted with the SUDAAN software

package. The outcome variable is dichotomous—that is, “1” indicates that the driver was

hospitalized or killed, “0” that the driver was neither hospitalized nor killed.

bThe odds ratio is the exponentiated coefficient (ecoefficient). The odds ratio indicates the change in

the odds of injury that occur with a change of one unit in the variable. For example, increasing

automobile weight by 100 pounds increases the odds of hospitalization or death by a factor of

1.097, not quite 10 percent. The odds ratio for categorical variables indicates the change from the

left-out group. For example, the injury odds for men drivers are 0.961 that of women drivers, the

left-out group.

cThe chi-square values test the statistical significance of the coefficients. The values are

calculated from the Satterthwaite approximation to the chi-square distribution. This procedure

reduces the chances of a Type I error. (See J. N. K. Rao and D. R. Thomas, “Chi-Squared Tests

for Contingency Tables,” in C. J. Skinner, D. Holt, and T. M. F. Smith (eds.), Analysis of Complex

Surveys (New York: John Wiley and Sons, 1989).)

dProbability levels are from the Satterthwaite adjusted chi-square tests. Probability level refers to

the chances that the coefficient equals zero in the population. By convention, coefficients with a

probability level less than or equal to 5 percent (0.05) are regarded as statistically significant. In

this table, 0.01 indicates a probability less than or equal to 0.01.

eThe population means are the variable values in this sample weighted by the National Inflation

Factor to approximate population values.

Page 62 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Appendix I 

Regression Analyses for Driver Injury

Table I.4: One-Car Nonrollover Crashes: Logistic Regression Analysis Predicting Driver Hospitalization or Death, Model

With Curb Weight

Variable Coefficienta

Odds

ratiob

ChisquarecProbability

leveld

Population

meane

Automobile model year (versus 1990 and newer)

1987 –0.220 0.803 0.34 0.56 0.32

1988 –0.366 0.694 0.57 0.45 0.31

1989 0.050 1.051 0.01 0.90 0.21

Speed limit 40+ mph –0.006 0.994 0.00 0.98 0.59

Area of damage to the car

Front 0.502 1.652 1.83 0.18 0.67

Left side 0.346 1.414 1.17 0.28 0.15

Safety belt use (versus unbelted)

Manual lap and shoulder belts –1.624 0.197 35.85 0.01 0.48

Automatic belts –0.816 0.442 3.35 0.07 0.12

Both manual and automatic belts –1.027 0.358 4.94 0.03 0.12

Male driver 0.059 1.060 0.04 0.85 0.58

Driver age in years (versus 16-24)

25-44 0.777 2.174 7.56 0.01 0.42

45-64 0.609 1.839 3.03 0.08 0.11

65+ 1.889 6.611 11.19 0.01 0.04

Automobile weight (100s of pounds) –0.032 0.968 2.00 0.16 26.88

Collision severity: change in velocity

Has change in velocity value 0.927 2.527 7.79 0.01 0.18

Change in velocity (mph) 0.200 1.221 23.24 0.01 13.98

Constant –5.604

(Table notes on next page)

Page 63 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Appendix I 

Regression Analyses for Driver Injury

aCoefficients are from logistic regression analyses conducted with the SUDAAN software

package. The outcome variable is dichotomous—that is, “1” indicates that the driver was

hospitalized or killed, “0” that the driver was neither hospitalized nor killed.

bThe odds ratio is the exponentiated coefficient (ecoefficient). The odds ratio indicates the change in

the odds of injury that occur with a change of one unit in the variable. For example, increasing

automobile weight by 100 pounds decreases the odds of hospitalization or death by a factor of

0.968, about 3 percent. The odds ratio for categorical variables indicates the change from the

left-out group. For example, the injury odds for men drivers are 1.060 that of women drivers, the

left-out group.

cThe chi-square values test the statistical significance of the coefficients. The values are

calculated from the Satterthwaite approximation to the chi-square distribution. This procedure

reduces the chances of a Type I error. (See J. N. K. Rao and D. R. Thomas, “Chi-Squared Tests

for Contingency Tables,” in C. J. Skinner, D. Holt, and T. M. F. Smith (eds), Analysis of Complex

Surveys (New York: John Wiley and Sons, 1989).)

dProbability levels are from the Satterthwaite adjusted chi-square tests. Probability level refers to

the chances that the coefficient equals zero in the population. By convention, coefficients with a

probability level less than or equal to 5 percent (0.05) are regarded as statistically significant. In

this table, 0.01 indicates a probability less than or equal to 0.01.

eThe population means are the variable values in this sample weighted by the National Inflation

Factor to approximate population values.

Table I.5: Collisions With Cars and Light Trucks: Logistic Regression Analysis Predicting Driver Hospitalization or Death,

Model With Curb Weight

Variable Coefficienta

Odds

ratiob

ChisquarecProbability

leveld

Population

meane

Automobile model year (versus 1990 and newer)

1987 0.263 1.301 0.83 0.36 0.31

1988 0.021 1.021 0.01 0.93 0.28

1989 0.191 1.211 0.38 0.54 0.21

Speed limit 40+ mph 0.667 1.948 14.74 0.01 0.46

Head-on collision 1.642 5.166 22.30 0.01 0.05

Area of damage to the car (if not head-on collision)

Front 0.273 1.314 1.27 0.26 0.55

Left side 0.874 2.396 9.90 0.01 0.23

Safety belt use (versus unbelted)

Manual lap and shoulder belts –1.029 0.357 23.48 0.01 0.49

Automatic belts –0.654 0.520 8.24 0.01 0.13

Both manual and automatic belts –0.989 0.372 10.27 0.01 0.11

Male driver –0.419 0.658 6.07 0.01 0.46

Driver age in years (versus 16-24)

25-44 0.365 1.441 2.31 0.13 0.43

45-64 0.920 2.509 23.02 0.01 0.15

65+ 1.420 4.139 38.59 0.01 0.08

(continued)

Page 64 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Appendix I 

Regression Analyses for Driver Injury

Variable Coefficienta

Odds

ratiob

ChisquarecProbability

leveld

Population

meane

Collision severity: change in velocity

Has change in velocity value 0.969 2.635 35.60 0.01 0.41

Change in velocity (mph) 0.195 1.215 95.11 0.01 13.94

Automobile weight (100s of pounds) –0.054 0.948 12.85 0.01 26.69

Weight of other vehicle (100s of pounds) 0.025 1.025 3.47 0.06 30.60

Body type of other vehicle (versus automobiles)

Pickup truck 0.166 1.181 0.62 0.43 0.13

Van 0.803 2.231 3.54 0.06 0.05

Other light vehicle 1.000 2.720 6.82 0.01 0.04

Constant –6.784

aCoefficients are from logistic regression analyses conducted with the SUDAAN software

package. The outcome variable is dichotomous—that is, “1” indicates that the driver was

hospitalized or killed, “0” that the driver was neither hospitalized nor killed.

bThe odds ratio is the exponentiated coefficient (ecoefficient). The odds ratio indicates the change in

the odds of injury that occur with a change of one unit in the variable. For example, increasing

automobile weight by 100 pounds decreases the odds of hospitalization or death by a factor of

0.948, about 5 percent. The odds ratio for categorical variables indicates the change from the

left-out group. For example, the injury odds for men drivers are 0.658 that of women drivers, the

left-out group.

cThe chi-square values test the statistical significance of the coefficients. The values are

calculated from the Satterthwaite approximation to the chi-square distribution. This procedure

reduces the chances of a Type I error. (See J. N. K. Rao and D. R. Thomas, “Chi-Squared Tests

for Contingency Tables,” in C. J. Skinner, D. Holt, and T. M. F. Smith (eds.), Analysis of Complex

Surveys (New York: John Wiley and Sons, 1989).)

dProbability levels are from the Satterthwaite adjusted chi-square tests. Probability level refers to

the chances that the coefficient equals zero in the population. By convention, coefficients with a

probability level less than or equal to 5 percent (0.05) are regarded as statistically significant. In

this table, 0.01 indicates a probability less than or equal to 0.01.

eThe population means are the variable values in this sample weighted by the National Inflation

Factor to approximate population values.

Page 65 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Appendix I 

Regression Analyses for Driver Injury

Table I.6: One-Car Rollover Crashes: Logistic Regression Analysis Predicting Driver Hospitalization or Death, Model With

Wheelbase

Variable Coefficienta

Odds

ratiob

ChisquarecProbability

leveld

Population

meane

Automobile model year (versus 1990 and newer)

1987 0.365 1.440 0.52 0.47 0.31

1988 –0.182 0.833 0.07 0.79 0.35

1989 0.386 1.471 0.39 0.53 0.18

Speed limit 40+ mph 1.155 3.173 10.12 0.01 0.75

Area of damage to the car

Front 1.247 3.480 17.72 0.01 0.32

Left side 0.142 1.152 0.09 0.76 0.16

Safety belt use (versus unbelted)

Manual lap and shoulder belts –1.795 0.166 15.93 0.01 0.44

Automatic belts –0.683 0.505 2.11 0.15 0.14

Both manual and automatic belts –0.915 0.400 2.91 0.09 0.10

Male driver –0.017 0.983 0.00 0.97 0.63

Driver age in years (versus 65+)

16-24 –0.315 0.730 0.14 0.70 0.54

25-44 0.071 1.073 0.01 0.93 0.36

45-64 0.707 2.027 0.74 0.39 0.07

Automobile wheelbase (inches) 0.020 1.020 0.34 0.56 98.83

Constant –4.398

aCoefficients are from logistic regression analyses conducted with the SUDAAN software

package. The outcome variable is dichotomous—that is, “1” indicates that the driver was

hospitalized or killed, “0” that the driver was neither hospitalized nor killed.

bThe odds ratio is the exponentiated coefficient (ecoefficient). The odds ratio indicates the change in

the odds of injury that occur with a change of one unit in the variable. For example, increasing

automobile wheelbase by 1 inch increases the odds of hospitalization or death by a factor of

1.020, or 2 percent. The odds ratio for categorical variables indicates the change from the left-out

group. For example, the injury odds for men drivers are 0.983 that of women drivers, the left-out

group.

cThe chi-square values test the statistical significance of the coefficients. The values are

calculated from the Satterthwaite approximation to the chi-square distribution. This procedure

reduces the chances of a Type I error. (See J. N. K. Rao and D. R. Thomas, “Chi-Squared Tests

for Contingency Tables,” in C. J. Skinner, D. Holt, and T. M. F. Smith (eds.), Analysis of Complex

Surveys (New York: John Wiley and Sons, 1989).)

dProbability levels are from the Satterthwaite adjusted chi-square tests. Probability level refers to

the chances that the coefficient equals zero in the population. By convention, coefficients with a

probability level less than or equal to 5 percent (0.05) are regarded as statistically significant. In

this table, 0.01 indicates a probability less than or equal to 0.01.

eThe population means are the variable values in this sample weighted by the National Inflation

Factor to approximate population values.

Page 66 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Appendix I 

Regression Analyses for Driver Injury

Table I.7: One-Car Nonrollover Crashes: Logistic Regression Analysis Predicting Driver Hospitalization or Death, Model

With Wheelbase

Variable Coefficienta

Odds

ratiob

ChisquarecProbability

leveld

Population

meane

Automobile model year (versus 1990 and newer)

1987 –0.147 0.863 0.15 0.70 0.32

1988 –0.298 0.743 0.39 0.53 0.31

1989 0.162 1.176 0.13 0.71 0.21

Speed limit 40+ mph –0.020 0.980 0.00 0.95 0.59

Area of damage to the car

Front 0.574 1.775 2.54 0.11 0.67

Left side 0.322 1.380 1.00 0.32 0.15

Safety belt use (versus unbelted)

Manual lap and shoulder belts –1.640 0.194 38.01 0.01 0.48

Automatic belts –0.798 0.450 3.30 0.07 0.12

Both manual and automatic belts –1.058 0.347 5.56 0.02 0.12

Male driver 0.025 1.025 0.01 0.93 0.58

Driver age in years (versus 16-24)

25-44 0.830 2.293 9.19 0.01 0.42

45-64 0.661 1.938 3.78 0.05 0.11

65+ 1.977 7.220 12.27 0.01 0.04

Automobile wheelbase (inches) –0.020 0.980 1.38 0.24 100.53

Collision severity: change in velocity

Has change in velocity value 0.907 2.475 7.31 0.01 0.18

Change in velocity (mph) 0.200 1.221 23.70 0.01 13.98

Constant –4.588

(Table notes on next page)

Page 67 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Appendix I 

Regression Analyses for Driver Injury

aCoefficients are from logistic regression analyses conducted with the SUDAAN software

package. The outcome variable is dichotomous—that is, “1” indicates that the driver was

hospitalized or killed, “0” that the driver was neither hospitalized nor killed.

bThe odds ratio is the exponentiated coefficient (ecoefficient). The odds ratio indicates the change in

the odds of injury that occur with a change of one unit in the variable. For example, increasing

automobile wheelbase by 1 inch decreases the odds of hospitalization or death by a factor of

0.980, or 2 percent. The odds ratio for categorical variables indicates the change from the left-out

group. For example, the injury odds for men drivers are 1.025 that of women drivers, the left-out

group.

cThe chi-square values test the statistical significance of the coefficients. The values are

calculated from the Satterthwaite approximation to the chi-square distribution. This procedure

reduces the chances of a Type I error. (See J. N. K. Rao and D. R. Thomas, “Chi-Squared Tests

for Contingency Tables,” in C. J. Skinner, D. Holt, and T. M. F. Smith (eds.), Analysis of Complex

Surveys (New York: John Wiley and Sons, 1989).)

dProbability levels are from the Satterthwaite adjusted chi-square tests. Probability level refers to

the chances that the coefficient equals zero in the population. By convention, coefficients with a

probability level less than or equal to 5 percent (0.05) are regarded as statistically significant. In

this table, 0.01 indicates a probability less than or equal to 0.01.

eThe population means are the variable values in this sample weighted by the National Inflation

Factor to approximate population values.

Table I.8: Collisions With Cars and Light Trucks: Logistic Regression Analysis Predicting Driver Hospitalization or Death,

Model With Wheelbase

Variable Coefficienta

Odds

ratiob

ChisquarecProbability

leveld

Population

meane

Automobile model year (versus 1990 and newer)

1987 0.284 1.329 1.01 0.31 0.31

1988 0.001 1.000 0.00 1.00 0.28

1989 0.242 1.273 0.59 0.44 0.21

Speed limit 40+ mph 0.653 1.921 13.97 0.01 0.46

Head-on collision 1.589 4.900 21.13 0.01 0.05

Area of damage to the car (if not head-on collision)

Front 0.286 1.331 1.39 0.24 0.55

Left side 0.848 2.335 9.42 0.01 0.23

Safety belt use (versus unbelted)

Manual lap and shoulder belts –1.056 0.348 23.44 0.01 0.49

Automatic belts –0.631 0.532 7.39 0.01 0.13

Both manual and automatic belts –1.043 0.353 11.01 0.01 0.11

Male driver –0.445 0.641 6.77 0.01 0.46

Driver age in years (versus 16 to 24)

25-44 0.375 1.455 2.45 0.12 0.43

45-64 0.902 2.464 20.98 0.01 0.15

65+ 1.499 4.476 37.71 0.01 0.08

(continued)

Page 68 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Appendix I 

Regression Analyses for Driver Injury

Variable Coefficienta

Odds

ratiob

ChisquarecProbability

leveld

Population

meane

Collision severity: change in velocity

Has change in velocity value 0.965 2.624 34.19 0.01 0.41

Change in velocity (mph) 0.196 1.217 93.85 0.01 13.94

Automobile wheelbase (inches) –0.043 0.958 9.56 0.01 101.37

Weight of other vehicle (100s of pounds) 0.026 1.026 3.58 0.06 30.60

Body type of other vehicle (versus automobiles)

Pickup truck 0.185 1.203 0.75 0.39 0.13

Van 0.845 2.327 4.05 0.04 0.05

Other light vehicle 0.957 2.603 6.16 0.01 0.04

Constant –3.899

aCoefficients are from logistic regression analyses conducted with the SUDAAN software

package. The outcome variable is dichotomous—that is, “1” indicates that the driver was

hospitalized or killed, “0” that the driver was neither hospitalized nor killed.

bThe odds ratio is the exponentiated coefficient (ecoefficient). The odds ratio indicates the change in

the odds of injury that occur with a change of one unit in the variable. For example, increasing

automobile wheelbase by 1 inch decreases the odds of hospitalization or death by a factor of

0.958, just over 4 percent. The odds ratio for categorical variables indicates the change from the

left-out group. For example, the injury odds for men drivers are 0.641 that of women drivers, the

left-out group.

cThe chi-square values test the statistical significance of the coefficients. The values are

calculated from the Satterthwaite approximation to the chi-square distribution. This procedure

reduces the chances of a Type I error. (See J. N. K. Rao and D. R. Thomas, “Chi-Squared Test for

Contingency Tables,” in C. J. Skinner, D. Holt, and T. M. F. Smith (eds.), Analysis of Complex

Surveys (New York: John Wiley and Sons, 1989).)

dProbability levels are from the Satterthwaite adjusted chi-square tests. Probability level refers to

the chances that the coefficient equals zero in the population. By convention, coefficients with a

probability level less than or equal to 5 percent (0.05) are regarded as statistically significant. In

this table, 0.01 indicates a probability less than or equal to 0.01.

eThe population means are the variable values in this sample weighted by the National Inflation

Factor to approximate population values.

Page 69 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Appendix II 

Major Contributors to This Report

Program Evaluation

and Methodology

Division

Robert E. White, Assistant Director

Martin T. Gahart, Project Manager

Dale W. Harrison, Project Adviser

Beverly A. Ross, Project Adviser

Penny Pickett, Communications Analyst

Page 70 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Bibliography

“As Nation Grows Older, Traffic Safety Officials Confront Questions of

Who Should Drive.” Journal of the American Medical Association, 268:3

(1992), 307-8.

Centers for Disease Control. “Trends in Alcohol-Related Traffic Fatalities,

by Sex—United States.” Journal of the American Medical Association,

268:3 (1992), 313-14.

Danner, M., K. Langieder, and Thomas Hummel. “Experience from the

Analysis of Accidents with a High Belt Usage Rate and Aspects of

Continued Increase in Passenger Safety.” Presented at the Eleventh

International Technical Conference on Experimental Safety Vehicles,

Washington, D.C., 1987.

Evans, Leonard. Car Mass and Likelihood of Occupant Fatality. Technical

paper 820807. Warrendale, Pa.: Society of Automotive Engineers, 1982.

Evans, Leonard. “The Effectiveness of Safety Belts in Preventing

Fatalities.” Accident Analysis and Prevention, 18:3 (1986), 229-41.

Evans, Leonard. “Belted and Unbelted Driver Accident Involvement Rates

Compared.” Journal of Safety Research, 18:2 (1987), 57-64.

Evans, Leonard. “Older Driver Involvement in Fatal and Severe Traffic

Crashes.” Journal of Gerontology: Social Sciences, 43:6 (1988a), 5186-93.

Evans, Leonard. “Risk of Fatality from Physical Trauma versus Sex and

Age.” The Journal of Trauma, 28:3 (1988b), 368-78.

Evans, Leonard. “Restraint Effectiveness, Occupant Ejection From Cars,

and Fatality Reductions.” Accident Analysis and Prevention, 22:2 (1990),

167-75.

Evans, Leonard. “Motorized Two-Point Safety Belt Effectiveness in

Preventing Fatalities.” Accident Analysis and Prevention, 23:2/3 (1991a),

165-74.

Evans, Leonard. Traffic Safety and the Driver. New York: Van Nostrand

Reinhold, 1991b.

Evans, Leonard, and Michael C. Frick. “Safety Belt Effectiveness in

Preventing Driver Fatalities Versus a Number of Vehicular, Accident,

Page 71 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Bibliography

Roadway, and Environmental Factors.” Journal of Safety Research, 17:4

(1986), 143-54.

Evans, Leonard, and Michael C. Frick. “Car Size or Car Mass: Which Has

Greater Influence on Fatality Risk?” American Journal of Public Health,

82:8 (1992), 1105-12.

Evans, Leonard, and Paul Wasielewski. “Risky Driving Related to Driver

and Vehicle Characteristics.” Accident Analysis and Prevention, 15:2

(1983), 121-36.

Green, R.N., et al. “Fatal Injuries to Restrained Passenger Car Occupants in

Canada: Crash Modes and Kinematics of Injury.” Accident Analysis and

Prevention, 26:2 (1994), 207-14.

Hackney, James R. “The Effects of FMVSS No. 208 and NCAP on Safety as

Determined from Crash Test Results.” Presented at the Thirteenth

International Technical Conference on Experimental Safety Vehicles,

Paris, France, 1991.

Hill, J.R., G.M. Mackay, and A.P. Morris. “Chest and Abdominal Injuries

Caused by Seat Belt Loading.” Accident Analysis and Prevention, 26:1

(1994), 11-26.

Hunter, William W., et al. “Observed and Self-Reported Seat Belt Wearing

as Related to Prior Traffic Accidents and Convictions.” Accident Analysis

and Prevention, 25:5 (1993), 545-54.

Insurance Institute for Highway Safety. “Death Rates Vary Among Cars by

More than 800 Percent.” Status Report, 26:4 (1991), 1-5.

Insurance Institute for Highway Safety, Shopping for a Safer Car: 1994

Models. Arlington, Va.: 1993.

Joksch, Hans C. “Velocity Change and Fatality Risk in a Crash—A Rule of

Thumb.” Accident Analysis and Prevention, 25:1 (1993), 103-4.

Kahane, Charles J. Effect of Car Size on the Frequency and Severity of

Rollover Crashes. Washington, D.C.: National Highway Traffic Safety

Administration, 1990.

Page 72 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Bibliography

Klein, T.M., E. Hertz, and S. Borener. A Collection of Recent Analyses of

Vehicle Weight and Safety, DOT-HS-807-677. Washington, D.C.: National

Highway Traffic Safety Administration, 1991.

Lestina, Diane C., et al. “Motor Vehicle Crash Injury Patterns and the

Virginia Seat Belt Law.” Journal of the American Medical Association,

265:11 (1991), 1409-13.

Mackay, G.M., et al. “Restrained Front Seat Car Occupant Fatalities—The

Nature and Circumstances of Their Injuries.” Accident Analysis and

Prevention, 24:3 (1992), 307-15.

Mackay, Murray. “Crash Protection for Older Persons.” In Transportation

Research Board. Transportation in an Aging Society, special report 218.

Washington, D.C.: Transportation Research Board, 1988.

Mackay, Murray. “Occupant Protection and Vehicle Design.” Presented at

The Biomechanics of Impact and Motor Vehicle Crash Performance: A

Global Concern, conference sponsored by the Association for the

Advancement of Automotive Medicine and the International Research

Council on the Biomechanics of Impact, Atlanta, May 1993.

Mercier, Cletus R., et al. “Age as a Predictor of Injury Severity in

Broad-Side and Angle Vehicular Collisions.” Presented at the annual

meeting of the American Statistical Association, New Orleans, 1993.

National Highway Traffic Safety Administration. Effect of Car Size on

Fatality and Injury Risk. Washington, D.C.: 1991a.

National Highway Traffic Safety Administration. General Estimates System

1990, DOT-HS-807-781. Washington, D.C.: 1991b.

National Highway Traffic Safety Administration. National Accident

Sampling System—Crashworthiness Data System: Analytical User’s

Manual, 1991 File. Washington, D.C.: 1991c.

National Highway Traffic Safety Administration. National Accident

Sampling System—1991 Crashworthiness Data System: Data Collection,

Coding, and Editing Manual. Washington, D.C.: 1991d.

Page 73 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Bibliography

National Highway Traffic Safety Administration. Evaluation of the

Effectiveness of Occupant Protection, Federal Motor Vehicle Safety

Standard 208: Interim Report, DOT-HS-807-843. Washington, D.C.: 1992a.

National Highway Traffic Safety Administration. Moving America Safely:

Priority Plan, NHTSA’s Activities Through 1994. Washington, D.C.: 1992b.

National Highway Traffic Safety Administration. Addressing the Safety

Issues Related to Younger and Older Drivers, DOT-HS-807-957. Washington,

D.C.: 1993a.

National Highway Traffic Safety Administration. 1991 Alcohol Fatal Crash

Facts. Washington, D.C.: 1993b.

National Highway Traffic Safety Administration. Fatal Accident Reporting

System 1991, DOT-HS-807-954. Washington, D.C.: 1993c.

National Higway Traffic Safety Administration. Final Regulatory

Evaluation, FMVSS No. 208, Mandatory Air Bag Installation, Docket

74-14-N82-002. Washington, D.C.: 1993d.

National Highway Traffic Safety Administration. New Car Assessment

Program: Response to the NCAP FY 1992 Congressional Requirements.

Washington, D.C.: 1993e.

National Research Council. Automobile Fuel Economy: How Far Should

We Go? Washington, D.C.: National Academy Press, 1992.

National Transportation Safety Board. Safety Study—Performance of

Lap/Shoulder Belts in 167 Motor Vehicle Crashes, NTSB/SS-88/02.

Washington, D.C.: 1988.

Partyka, Susan C. Papers on Adult Seat Belts—Effectiveness and Use,

DOT-HS-807-285. Washington, D.C.: National Highway Traffic Safety

Administration, 1988.

Partyka, Susan C., and William A. Boehly. “Passenger Car Weight and

Injury Severity in Single Vehicle Nonrollover Crashes.” Presented at the

Twelfth International Technical Conference on Experimental Safety

Vehicles, Goteborg, Sweden, 1989.

Page 74 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Bibliography

Pike, J.A. “The Quantitative Effect of Age on Injury Outcome.” Presented

at the Twelfth International Technical Conference on Experimental Safety

Vehicles, Goteborg, Sweden, 1989.

Preusser, David F., Allan F. Williams, and Adrian K. Lund. “Characteristics

of Belted and Unbelted Drivers.” Accident Analysis and Prevention, 23:6

(1991), 475-82.

Robertson, Leon S. “How to Save Fuel and Reduce Injuries in

Automobiles.” The Journal of Trauma, 31:1 (1991), 107-9.

Shah, Babubhai V., et al. SUDAAN User’s Manual, Release 6.0. Research

Triangle Park, N.C.: Research Triangle Institute, 1992.

Stewart, J. Richard. “Seat Belt Use and Accident Involvement: A

Comparison of Driving Behavior Before and After a Seat Belt Law.”

Accident Analysis and Prevention, 25:6 (1993), 757-63.

Terhune, Kenneth W. The Contribution of Rollover to Single-Vehicle Crash

Injuries, Calspan report 7881-1. Buffalo: Arvin/Calspan Transportation

Sciences Center, 1991.

Terhune, Kenneth W., and Thomas A. Ranney. “Components of Vehicle

Aggressiveness.” Presented at the Twenty-Eighth Annual Meeting of the

American Association for Automotive Medicine, Denver, 1984.

Transportation Research Board. Research and Development Needs for

Maintaining the Safety and Mobility of Older Drivers, circular 398.

Washington, D.C.: 1992.

U.S. General Accounting Office. Highway Safety: Have Automobile Weight

Reductions Increased Highway Fatalities? GAO/PEMD-92-1. Washington, D.C.:

October 1991.

U.S. General Accounting Office. Highway Safety: Safety Belt Use Laws

Save Lives and Reduce Costs to Society, GAO/RCED-92-106. Washington, D.C.:

May 1992.

U.S. General Accounting Office. Highway Safety: Factors Affecting

Involvement in Vehicle Crashes, GAO/PEMD-95-3. Washington, D.C.:

October 1994.

Page 75 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Bibliography

Viano, David C. “Limits and Challenges of Crash Protection.” Accident

Analysis and Prevention, 20:6 (1988), 421-29.

Viano, David C., et al. “Involvement of Older Drivers in Multivehicle

Side-Impact Crashes.” Accident Analysis and Prevention, 22:2 (1990),

177-88.

Williams, Allan F., et al. “Use of Seatbelts in Cars with Automatic Belts.”

Public Health Reports, 107:2 (1992), 182-88.

Zador, Paul L., and Michael A. Ciccone. “Automobile Driver Fatalities in

Frontal Impacts: Air Bags Compared with Manual Belts.” American

Journal of Public Health, 83:5 (1993), 661-66.

Page 76 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Bibliography

Page 77 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Bibliography

Page 78 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Bibliography

Page 79 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Related GAO Products

Highway Safety: Reliability and Validity of DOT Crash Tests (GAO/PEMD-95-5,

May 1995).

Highway Safety: Factors Affecting Involvement in Vehicle Crashes

(GAO/PEMD-95-3, Oct. 1994).

Highway Safety: Safety Belt Use Laws Save Lives and Reduce Costs to

Society (GAO/RCED-92-106, May 1992).

Highway Safety: Have Automobile Weight Reductions Increased Highway

Fatalities? (GAO/PEMD-92-1, Oct. 1991).

Highway Safety: Motorcycle Helmet Laws Save Lives and Reduce Costs to

Society (GAO/RCED-91-179, July 1991).

Highway Safety: Fatalities in Light Trucks and Vans (GAO/PEMD-91-8,

Nov. 1990).

Highway Safety: Trends in Highway Fatalities 1975-87 (GAO/PEMD-90-10,

Mar. 1990).

Motor Vehicle Safety: Passive Restraints Needed to Make Light Trucks

Safer (GAO/RCED-90-56, Nov. 1989).

Drinking-Age Laws: An Evaluation Synthesis of Their Impact on Highway

Safety (GAO/PEMD-87-10, Feb. 1987).

(973380) Page 80 GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes
Ordering Information

The first copy of each GAO report and testimony is free.

Additional copies are $2 each. Orders should be sent to the

following address, accompanied by a check or money order

made out to the Superintendent of Documents, when

necessary. Orders for 100 or more copies to be mailed to a

single address are discounted 25 percent.

Orders by mail:

U.S. General Accounting Office

P.O. Box 6015

Gaithersburg, MD 20884-6015

or visit:

Room 1100

700 4th St. NW (corner of 4th and G Sts. NW)

U.S. General Accounting Office

Washington, DC

Orders may also be placed by calling (202) 512-6000 

or by using fax number (301) 258-4066, or TDD (301) 413-0006.

Each day, GAO issues a list of newly available reports and

testimony. To receive facsimile copies of the daily list or any

list from the past 30 days, please call (301) 258-4097 using a

touchtone phone. A recorded menu will provide information on

how to obtain these lists.

PRINTED ON RECYCLED PAPER
United States

General Accounting Office

Washington, D.C. 20548-0001

Official Business

Penalty for Private Use $300

Address Correction Requested

Bulk Mail

Postage & Fees Paid

GAO

Permit No. G100
GAO/PEMD-95-4 Highway Safety: Causes of Injury in Automobile Crashes