This document is available to the public from the National Technical Information Service, Springfield, VA 22161

U.S. Department

of Transportation

National Highway

Traffic Safety

Administration

DOT HS 809 646 September 2003

Technical Report

Safety Belt Use in 2003

Published By:

National Center for Statistics and Analysis

Advanced Research and Analysis
i

Technical Report Documentation Page

1. Report No.

DOT HS 809 646

2. Government Accession No. 3. Recipient's Catalog No.

5. Report Date

September 2003

4. Title and Subtitle

Safety Belt Use in 2003

6. Performing Organization Code

NPO-121

7. Author(s)

Glassbrenner, Donna

8. Performing Organization Report No.

9. Performing Organization Name and Address 10. Work Unit No. (TRAIS)

Mathematical Analysis Division, National Center for Statistics and Analysis

National Highway Traffic Safety Administration

U.S. Department of Transportation

NPO-121, 400 Seventh Street, S.W.

Washington, D.C. 20590

11. Contract or Grant No.

13. Type of Report and Period Covered

NHTSA Technical Report

12. Sponsoring Agency Name and Address

Mathematical Analysis Division, National Center for Statistics and Analysis

National Highway Traffic Safety Administration

U.S. Department of Transportation

NPO-121, 400 Seventh Street, S.W.

Washington, D.C. 20590

14. Sponsoring Agency Code

15. Supplementary Notes

Abstract

Safety belt use reached 79% in 2003, a 4 percentage point improvement over the 75% rate seen last year. Approximately 17% 

of belt nonusers were converted to users, twice the rate seen in previous years. Use continues to vary in different parts of the 

country, with higher rates in states that can enforce their belt laws more stringently. These results are from the National 

Occupant Protection Use Survey (NOPUS), the only probability-based observational survey of belt use on the road nationwide. 

The survey is conducted annually by the National Center for Statistics and Analysis in the National Highway Traffic Safety 

Administration (NHTSA). This report presents the findings of the 2003 survey.

17. Key Words

safety belt, primary belt law, NOPUS, observed belt use

18. Distribution Statement

Document is available to the public through the National Technical 

Information Service, Springfield, VA 22161

http//:www.ntis.gov

19. Security Classif. (of this report)

Unclassified

20. Security Classif. (of this page)

Unclassified

21. No. of Pages

54

22. Price

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized
National Center for Statistics and Analysis 400 Seventh St., S.W., Washington, D.C. 20590

i

TABLE of CONTENTS

1. INTRODUCTION ............................................................................................................................ 1

2. THE NATIONAL USE RATE ........................................................................................................... 2

2.1 Increasing Belt Use Saves Lives........................................................................................... 2

3. SUBNATIONAL ESTIMATES........................................................................................................... 3

3.1 Use Remains Higher in States with Stronger Laws.............................................................. 3

3.2 Where Did Use Increase?...................................................................................................... 3

3.3 Where Is Use Low?............................................................................................................... 3

4. TABLES OF DETAILED ESTIMATES................................................................................................ 5

5. ON INTERPRETING THE NOPUS ESTIMATES.............................................................................. 13

5.1 Estimates Reflect Front Seat Daytime Use ......................................................................... 13

5.2 Technological Improvements.............................................................................................. 13

5.2.1 Quantifying the Effects of the Improvements................................................................. 14

5.3 Assessing Improvement: Conversion Rates........................................................................ 15

5.4 Survey Methodology........................................................................................................... 16

5.5 Definitions........................................................................................................................... 16

5.6 Assessing Change: Statistical Significance ........................................................................ 16

5.7 Computing the Margin of Error of a Use Rate ................................................................... 17

6. REFERENCES .............................................................................................................................. 18
National Center for Statistics and Analysis 400 Seventh St., S.W., Washington, D.C. 20590

ii

TABLE of FIGURES

Chart 1: Belt Use, 1994-2003.............................................................................2

Table 1: Belt Use Summary........................................................................................................ 5

Table 2: Belt Use, 2000-2002 ..................................................................................................... 6

Table 3: Sample Sizes................................................................................................................. 6

Table 4: Belt Use in States with Primary Enforcement and the District of Columbia*.............. 7

Table 5: Belt Use in States with Secondary Enforcement .......................................................... 7

Table 7: Belt Use in the Northeast, by Vehicle Type and Occupant Type ................................. 8

Table 8: Belt Use in the Midwest, by Vehicle Type and Occupant Type................................... 8

Table 9: Belt Use in the South, by Vehicle Type and Occupant Type ....................................... 9

Table 10: Belt Use in the West, by Vehicle Type and Occupant Type ........................................ 9

Table 11: Belt Use on Weekdays, by Vehicle Type and Occupant Type ................................... 10

Table 12: Belt Use on Weekends, by Vehicle Type and Occupant Type ................................... 10

Table 13: Belt Use During Rush Hour* on Weekdays, by Vehicle Type and Occupant Type .. 11

Table 14: Weekday Belt Use Outside of Rush Hour*, by Vehicle Type and Occupant Type ... 11

Table 15: Belt Use, 1994-2003 ................................................................................................... 12
National Center for Statistics and Analysis 400 Seventh St., S.W., Washington, D.C. 20590

1

1. Introduction

The National Occupant Protection Use Survey (NOPUS) is an observational survey of safety belt 

use that began in 1994 and has been used by the National Highway Traffic Safety Administration 

(NHTSA) to measure the nation’s belt use. Unlike telephone surveys that ask respondents 

whether they use belts, NOPUS observes actual use on the roads, and so provides a better 

estimate (although telephone surveys are useful for studying unobservable characteristics of use, 

such as a person’s income level). In addition, NOPUS provides a reliable estimate of use whose 

error can be measured since it collects data on a probability sample of roadways. In fact, 

NOPUS provides the only probability-based observed measure of belt use on the nation’s roads. 

NOPUS provides estimates of use at the national level and at four regional levels (the Northeast, 

Midwest, South, and West). NOPUS cannot provide state estimates, which can be found through 

surveys conducted by the states’ highway safety offices, whose results are published annually by 

NHTSA. 

The information in this report comes from NOPUS’s Moving Traffic Study, which collects a 

small amount of information on a large number of vehicles to estimate national use as accurately 

as possible. NHTSA periodically conducts an additional survey, the Controlled Intersection 

Study, which collects more information, such as estimated age and race/ethnicity and child 

restraint use, on a smaller number of vehicles to better understand where use is low and where it 

is increasing. 

This report is organized as follows. Sections 2 and 3 summarize the findings of the 2003 survey. 

Section 4 contains detailed tables of estimates. Section 5 gives the survey methodology, 

including methods newly employed in 2003, and reviews basic statistical techniques, such as 

determining statistical significance and calculating margins of error.

Several things should be kept in mind to properly interpret the estimates in this report. The 

estimates reflect use in the front outboard seating positions of passenger vehicles during daytime. 

The 2003 data collection employed new techniques that might have affected the 2003 belt use 

estimates. Several of the tables in Section 4 contain “conversion rates”. This is the percentage 

reduction in belt nonuse that occurred between 2002 and 2003. Conversion rates are used to 

assess improvement in belt use rates. The reader should consult Section 5 for more information.
National Center for Statistics and Analysis 400 Seventh St., S.W., Washington, D.C. 20590

2

Chart 1: Belt Use, 1994-2003

50%

60%

70%

80%

90%

100%

199419951996199719981999200020012002

Belt Use Upper and Lower 95% Confidence Bounds

Source: National Center for Statistics and Analysis, NHTSA, NOPUS 1994-2003

2. The National Use Rate

The 2003 survey found belt use nationwide to be 

79%. The four percentage point gain in use from 

2002 is larger than the usual two point

improvement seen. This might be viewed as

evidence of the success of the 2003 “Click It or 

Ticket” belt campaign, conducted by NHTSA and 

state highway safety offices between May 19 and 

May 26, 2003. NHTSA purchased $8 million in 

advertising on 500 TV and 350 radio spots, 

warning the public that they may be ticketed and 

fined for nonuse. Fully 12,000 law enforcement 

agencies in 43 states, the District of Columbia, 

and Puerto Rico conducted checkpoints, writing more than 600,000 tickets combined. States 

purchased $16 million in advertisements, aired on 89,000 TV and 93,000 radio spots. The 

NOPUS data were collected between June 2 and June 29, 2003, shortly after the campaign 

ended, and so may reflect a temporary bump in use due to the campaign.

However, while the 4 percentage point national gain is larger than that normally seen, the 2003 

national estimate of 79% is within the regression lines of the 95% confidence bounds of the 

previous NOPUS estimates. That is, the 2003 estimate is within statistical error of the previous 

trend, and so while the NOPUS data indicates the campaign was a success, we cannot say with 

statistical confidence that it produced larger increases in use than those seen in the past. 

In addition, half of the observation sites incorporated new data collection technologies in 2003. 

(See the section “New Technologies”.) We believe the technologies improve the accuracy of the 

NOPUS data and have a positive effect on the estimates, but we cannot quantify the effect at this 

time. That is, the while we have confidence in NOPUS’s belt use estimates in 2003, and believe 

them to be more accurate than those from previous years, the estimated changes from 2002 to 

2003 in this note might be overstated. 

2.1 Increasing Belt Use Saves Lives

Belts are approximately 50% effective for preventing fatality in crashes in which motorists 

would otherwise die, and so raising belt use saves lives. It is estimated that raising use to 79% 

from 75% prevented 1,000 deaths that would have otherwise occurred in 2003. Since belts saved 

an estimated 14,000 motorists in 2002, we would predict that belts will have prevented 15,000 

deaths by the end of 2003. (Traffic Safety Facts – Overview, 2002) In saving lives and

preventing injuries, belt use saves billions of dollars in costs to society annually, mainly through 

preventing the loss in productivity and reducing the medical costs that would otherwise occur. 

(Blincoe et al, 2000) At least 15,000 lives will be saved in each future year if belt use is 

maintained at 79% or higher. 
National Center for Statistics and Analysis 400 Seventh St., S.W., Washington, D.C. 20590

3

3. Subnational Estimates

3.1 Use Remains Higher in States with Stronger Laws

“Primary” belt enforcement laws allow officers to stop and ticket a motorist simply for not using 

their belt, whereas in a state with a “secondary” law, the motorist must exhibit another infraction, 

such as an expired license tag, to be stopped. In 2003, there were 21 primary states, 29 

secondary states, and 1 state that effectively has no belt use law. (In New Hampshire, it is legal 

for motorists over 18 to ride unbelted.) The District of Columbia and Puerto Rico have primary 

laws. 

NOPUS has consistently found higher use rates in the presence of primary laws, with collective 

statistically different rates of 83% in primary states compared to 75% in secondary ones in 2003. 

Primary states have statistically similar rates in 2002 and 2003, while the increase in secondary 

states is statistically significant. 

3.2 Where Did Use Increase?

In addition to increasing nationwide, use also rose since 2002 in the following categories with 

95% confidence:

• in the South

• in states governed by secondary belt laws

• in each type of vehicle (passenger cars; vans & sport utility vehicles; and pickup 

trucks)

• among both drivers and (right front) passengers

• during both weekdays and weekends, and 

• during both weekday rush hour and weekday non-rush hour periods.

Other characteristics saw increases from the 2002 rates that were significant with lesser, but still 

fairly high, degrees of confidence. The following categories exhibited increases that are

significant with between 80% and 95% confidence:

• the Northeast (94.97% confidence)

• regions governed by primary belt laws (87% confidence), and

• the West (86% confidence).

3.3 Where Is Use Low?

Each of the following assertions is true with 95% confidence. 

• Use remains lower in secondary states than in primary ones.

• Use remains lower in pickup trucks, than in passenger cars, vans, and sport utility 

vehicles (SUVs). 

• Use is lower in the Northeast than in the South or West. 

• Use is lower in the Midwest than in the West. 
National Center for Statistics and Analysis 400 Seventh St., S.W., Washington, D.C. 20590

4

NOPUS has consistently found use to be lower in secondary states than in primary ones, and has 

consistently found pickups to have the lowest use among vehicle types. The pattern of regional 

differences seems to vary from year to year.
National Center for Statistics and Analysis 400 Seventh St., S.W., Washington, D.C. 20590

5

4. Tables of Detailed Estimates

Table 1: Belt Use Summary

2003 2002 2002-2003 Change

Characteristic

Belt Use Standard 

Error Belt Use Standard Error

Estimate

Standard 

Error

Conversion Rate

Overall 79% 1.2% 75% 1.1% 4% (S) 1.4% 17%

Primary Enforcement 83% (H) 1.6% 80% (H) 1.9% 3% 1.6% 15%

Secondary Enforcement 75% 2.1% 69% 1.2% 6% (S) 1.5% 19%

Drivers 80% (H) 1% 76% (H) 1% 4% (S) 1.3% 17%

Passengers 77% 1% 73% 1% 4% (S) 1.2% 15%

Passenger Cars 81% 1.0% 77% 1.0% 4% (S) 1.0% 17%

SUVs & Vans 83% 1.0% 78% 1.1% 5% (S) 1.3% 23%

Pickup Trucks 69% (L) 2.2% 64% (L) 1.6% 5% (S) 2.4% 14%

Northeast* 74% 1.9% 69% 1.6% 5% 2.2% 16%

Midwest* 75% 2.4% 74% 2.9% 1% 1.9% 4%

South* 80% 1.7% 76% 1.5% 4% (S) 1.9% 17%

West* 84% 3.5% 79% 2.8% 5% 3.4% 24%

Weekday 78% 1.3% 75% 1.0% 3% (S) 1.6% 12%

Rush Hour 79% 1.6% 76% 1.2% 3% (S) 1.5% 13%

Non-Rush Hour 79% 1.2% 75% 1.2% 4% (S) 1.4% 16%

Weekend 81% 1.7% 76% 1.9% 5% (S) 1.6% 21%

(S): Statistically significant change

(H), (L): Significantly high or low in category

*The following pairwise differences were significant in 2003: Northeast-South, Midwest-West, and 

Northeast-West, while Northeast-West and Northeast-South were significant in 2002

Source: National Center for Statistics and Analysis, NHTSA, NOPUS 2002-2003
National Center for Statistics and Analysis 400 Seventh St., S.W., Washington, D.C. 20590

6

Table 2: Belt Use, 2000-2002

Characteristic June 

2003

June 

2002

June 

2001

Fall 

2000

Overall 79% 75% 73% 71%

Primary Enforcement 83% 80% 78% 77%

Secondary Enforcement 75% 69% 67% 64%

Drivers 80% 76% 74% 72%

Passengers 77% 73% 72% 68%

Passenger Cars 81% 77% 76% 74%

SUVs & Vans 83% 78% 75% 74%

Pickup Trucks 69% 64% 62% 59%

Northeast 74% 69% 62% 67%

Midwest 75% 74% 72% 68%

South 80% 76% 76% 69%

West 84% 79% 77% 80%

Weekday 78% 75% 73% 71%

Rush Hour 79% 76% 75% 73%

Non-Rush Hour 79% 75% 72% 70%

Weekend 81% 76% 74% 73%

Source: National Center for Statistics and Analysis, NHTSA, 

NOPUS 2000-2003

Table 3: Sample Sizes

Numbers of 2003 2002 Change

Observation Sites 1972 1965 0%

Vehicles Observed 162,195 158,412 2%

Occupants Observed 213,668 209,037 2%

Source: National Center for Statistics and Analysis, NHTSA, NOPUS 2002-2003
National Center for Statistics and Analysis 400 Seventh St., S.W., Washington, D.C. 20590

7

Table 4: Belt Use in States with Primary Enforcement and the District of 

Columbia*

2003 2002 2002-2003 Change

Characteristic Belt 

Use

Standard 

Error

Belt 

Use

Standard 

Error

Estimate

Standard 

Error

Conversion 

Rate

Overall 83% 1.6% 80% 1.9% 3% 1.6% 15%

Drivers 83% 1.6% 81% 1.8% 2% 1.6% 11%

Passengers 81% 1.6% 77% 2.3% 4% (S) 1.6% 17%

Passenger Cars 84% 1.4% 82% 1.8% 2% 1.3% 11%

Drivers 85% 1.3% 83% 1.7% 2% 1.5% 12%

Passengers 81% 2.1% 78% 2.1% 3% 1.5% 14%

SUVs & Vans 86% 1.1% 83% 1.5% 3% (S) 1.4% 18%

Drivers 86% 1.2% 84% 1.4% 2% 1.5% 13%

Passengers 86% 1.0% 81% 1.8% 5% (S) 1.5% 26%

Pickup Trucks 73% 3.1% 70% 2.7% 3% 3.2% 10%

Drivers 74% 3.1% 71% 2.5% 3% 3.0% 10%

Passengers 73% 3.2% 67% 4.1% 6% 4.3% 18%

*D.C. also has a primary enforcement law.

(S): Statistically significant change

In each year and vehicle type, driver use was statistically similar to passenger use.

Source: National Center for Statistics and Analysis, NHTSA, NOPUS 2002-2003

Table 5: Belt Use in States with Secondary Enforcement

2003 2002 2002-2003 Change

Characteristic Belt 

Use

Standard 

Error

Belt 

Use

Standard 

Error

Estimate

Standar

d Error

Conversion 

Rate

Overall 75% 2.1% 69% 1.2% 6% (S) 1.5% 19%

Drivers 76% 2.1% 69% 1.2% 7% (S) 1.6% 23%

Passengers 72% 2.0% 68% 1.5% 4% (S) 1.4% 13%

Passenger Cars 78% 1.8% 71% 1.1% 7% (S) 1.2% 24%

Drivers 79% 1.8% 72% 1.1% 7% (S) 1.2% 25%

Passengers 74% 1.9% 68% 1.8% 6% (S) 1.7% 19%

SUVs & Vans 78% 1.9% 73% 1.5% 5% (S) 2.0% 19%

Drivers 79% 2.0% 73% 1.6% 6% (S) 2.1% 22%

Passengers 77% 1.9% 74% 2.3% 3% 2.7% 12%

Pickup Trucks 63% 3.2% 53% 2.1% 10% (S) 2.8% 21%

Drivers 63% 3.4% 52% 1.9% 11% (S) 3.0% 23%

Passengers 60% 2.8% 55% 4.3% 5% 3.6% 11%

(S): Statistically significant change

In each year and vehicle type, driver use was statistically similar to passenger use.

Source: National Center for Statistics and Analysis, NHTSA, NOPUS 2002-2003
National Center for Statistics and Analysis 400 Seventh St., S.W., Washington, D.C. 20590

8

Table 7: Belt Use in the Northeast, by Vehicle Type and Occupant Type

2003 2002 2002-2003 Change

Characteristic Belt 

Use

Standard 

Error Belt Use

Standa

rd 

Error

Estimate

Standard 

Error

Conversion 

Rate

Overall 74% 1.9% 69% 1.6% 5% 2.2% 16%

Drivers 74% 1.9% 70% 1.7% 4% (S) 2.3% 13%

Passengers 71% 2.7% 67% 1.8% 4% 2.1% 12%

Passenger Cars 75% 2.0% 71% 1.7% 4% 2.3% 14%

Drivers 76% 1.9% 72% 1.7% 4% 2.5% 14%

Passengers 70% 2.8% 68% 1.8% 2% 2.2% 6%

SUVs & Vans 77% 2.4% 72% 2.1% 5% 3.0% 18%

Drivers 77% 2.0% 72% 2.3% 5% 3.1% 18%

Passengers 76% 3.7% 71% 2.4% 5% 3.4% 17%

Pickup Trucks 56% 2.8% 50% 3.1% 6% (S) 2.9% 12%

Drivers 56% 2.9% 50% 3.1% 6% (S) 12%

Passengers 58% 3.2% 51% 4.5% 7% 4.9% 14%

(S): Statistically significant change

In each year and vehicle type, driver use was statistically similar to passenger use.

Source: National Center for Statistics and Analysis, NHTSA, NOPUS 2002-2003

Table 8: Belt Use in the Midwest, by Vehicle Type and Occupant Type 

2003 2002 2002-2003 Change

Characteristic Belt 

Use

Standard 

Error Belt Use Standard Error

EstimateStandard 

Error

Conversion Rate

Overall 75% 2.4% 74% 2.9% 1% 1.9% 4%

Drivers 75% 2.4% 74% 3.0% 1% 2.1% 4%

Passengers 74% 2.5% 73% 2.9% 1% 1.9% 4%

Passenger Cars 76% 2.5% 75% 2.7% 1% 1.8% 4%

Drivers 77% 2.5% 76% 2.9% 1% 2.1% 4%

Passengers 75% 2.7% 73% 3.1% 2% 2.2% 7%

SUVs & Vans 78% 2.4% 76% 2.9% 2% 2.5% 8%

Drivers 78% 2.5% 76% 3.2% 2% 2.9% 8%

Passengers 78% 2.3% 77% 3.9% 1% 3.9% 4%

Pickup Trucks 65% 3.0% 62% 4.8% 3% 4.1% 8%

Drivers 65% 2.8% 62% 4.6% 3% 4.4% 8%

Passengers 65% 4.2% 64% 8.0% 1% 6.0% 3%

No 2002-2003 differences were statistically significant.

In each year and vehicle type, driver use was statistically similar to passenger use.

Source: National Center for Statistics and Analysis, NHTSA, NOPUS 2002-2003
National Center for Statistics and Analysis 400 Seventh St., S.W., Washington, D.C. 20590

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Table 9: Belt Use in the South, by Vehicle Type and Occupant Type 

2003 2002 2002-2003 Change

Characteristic

Belt Use

Standa

rd 

Error

Belt Use

Standa

rd 

Error

Estimate

Standard 

Error

Conversion 

Rate

Overall 80% 1.7% 76% 1.5% 4% (S) 1.9% 17%

Drivers 81% 1.7% 77% 1.3% 4% (S) 1.9% 17%

Passengers 78% 1.6% 73% 2.5% 5% (S) 2.5% 19%

Passenger Cars 84% 1.3% 78% 1.4% 6% (S) 1.5% 27%

Drivers 85% (H) 1.3% 79% (H) 1.3% 6% (S) 1.4% 29%

Passengers 80% 1.4% 74% 2.2% 6% (S) 2.4% 23%

SUVs & Vans 85% 1.2% 80% 1.7% 5% (S) 2.0% 25%

Drivers 85% 1.2% 81% 1.6% 4% (S) 2.1% 21%

Passengers 83% 1.4% 79% 2.2% 4% 2.5% 19%

Pickup Trucks 68% 3.2% 63% 2.7% 5% 3.1% 14%

Drivers 68% 3.3% 64% 2.4% 4% 3.2% 11%

Passengers 65% 3.4% 59% 4.8% 6% 4.2% 15%

(S): Statistically significant change

(H): Statistically significant driver-passenger difference in use 

Source: National Center for Statistics and Analysis, NHTSA, NOPUS 2002-2003

Table 10: Belt Use in the West, by Vehicle Type and Occupant Type 

2003 2002 2002-2003 Change

Characteristic Belt 

Use

Standard 

Error

Belt 

Use

Standard 

Error

EstimateStandard 

Error

Conversion Rate

Overall 84% 3.5% 79% 2.8% 5% 3.4% 24%

Drivers 85% 3.6% 80% 2.8% 5% 3.8% 25%

Passengers 80% 3.0% 76% 3.1% 4% 2.3% 17%

Passenger Cars 86% 3.4% 81% 2.9% 5% 2.9% 26%

Drivers 88% 3.0% 83% 2.8% 5% 3.2% 29%

Passengers 81% 4.4% 77% 3.2% 4% 2.8% 17%

SUVs & Vans 87% 2.7% 82% 2.3% 5% 3.4% 28%

Drivers 88% 3.2% 82% 2.6% 6% 4.3% 33%

Passengers 85% 1.6% 81% 2.1% 4% (S) 2.0% 21%

Pickup Trucks 76% 4.3% 68% 3.0% 8% 5.0% 25%

Drivers 77% 4.6% 69% 2.8% 8% 5.4% 26%

Passengers 73% 4.3% 68% 4.7% 5% 6.0% 16%

(S): Statistically significant change

In each year and vehicle type, driver use was statistically similar to passenger use.

Source: National Center for Statistics and Analysis, NHTSA, NOPUS 2002-2003
National Center for Statistics and Analysis 400 Seventh St., S.W., Washington, D.C. 20590

10

Table 11: Belt Use on Weekdays, by Vehicle Type and Occupant Type

2003 2002 2002-2003 Change

Characteristic

Belt Use Standard 

Error Belt Use Standard Error

Estimate

Standard 

Error

Conversion Rate

Overall 78% 1.3% 75% 1.0% 3% (S) 1.6% 12%

Drivers 79% 1.4% 76% (H) 1.0% 3% (S) 1.6% 13%

Passengers 76% 1.3% 72% 1.3% 4% (S) 1.7% 14%

Passenger Cars 81% 1.1% 77% 1.0% 4% (S) 1.4% 17%

Drivers 82% (H) 1.1% 78% (H) 1.0% 4% (S) 1.4% 18%

Passengers 77% 1.2% 73% 1.4% 4% (S) 1.6% 15%

SUVs & Vans 82% 1.1% 78% 1.2% 4% (S) 1.7% 18%

Drivers 82% 1.1% 78% 1.4% 4% (S) 1.9% 18%

Passengers 80% 1.1% 77% 1.6% 3% 1.8% 13%

Pickup Trucks 68% 2.7% 63% 1.4% 5% 2.9% 14%

Drivers 69% 2.7% 64% 1.4% 5% 3.0% 14%

Passengers 65% 3.1% 60% 2.6% 5% 4.0% 13%

(S): Statistically significant change

(H): Statistically significant driver-passenger difference in use

Source: National Center for Statistics and Analysis, NHTSA, NOPUS 2002-2003

Table 12: Belt Use on Weekends, by Vehicle Type and Occupant Type

2003 2002 2002-2003 Change

Characteristic

Belt Use Standar

d Error Belt Use Standard Error

EstimateStandard 

Error

Conversion Rate

Overall 81% 1.7% 76% 1.9% 5% (S) 1.6% 21%

Drivers 81% 1.6% 77% 1.8% 4% (S) 1.7% 17%

Passengers 79% 2.0% 75% 2.0% 4% (S) 1.5% 16%

Passenger Cars 82% 1.6% 78% 1.8% 4% (S) 1.5% 18%

Drivers 84% 1.4% 79% 1.8% 5% (S) 1.5% 24%

Passengers 78% 2.5% 76% 2.0% 2% 2.0% 8%

SUVs & Vans 84% 1.5% 79% 2.0% 5% (S) 2.0% 24%

Drivers 84% 1.6% 80% 1.9% 4% (S) 2.2% 20%

Passengers 84% 1.6% 79% 2.3% 5% (S) 2.3% 24%

Pickup Trucks 72% 2.2% 66% 3.1% 6% (S) 2.6% 18%

Drivers 71% 2.4% 65% 2.9% 6% (S) 3.0% 17%

Passengers 73% 2.8% 67% 4.1% 6% (S) 2.8% 18%

(S): Statistically significant change

In each year and vehicle type, driver use was statistically similar to passenger use.

Source: National Center for Statistics and Analysis, NHTSA, NOPUS 2002-2003
National Center for Statistics and Analysis 400 Seventh St., S.W., Washington, D.C. 20590

11

Table 13: Belt Use During Rush Hour* on Weekdays, by Vehicle Type and 

Occupant Type

2003 2002 2002-2003 Change

Characteristic

Belt Use Standard 

Error Belt Use Standard Error

EstimateStandard 

Error

Conversion Rate

Overall 79% 1.6% 76% 1.2% 3% (S) 1.5% 13%

Drivers 80% 1.6% 76% 1.2% 4% (S) 1.6% 17%

Passengers 76% 1.6% 73% 1.5% 3% 1.6% 11%

Passenger Cars 81% 1.4% 78% 1.2% 3% (S) 1.4% 14%

Drivers 82% (H) 1.4% 78% 1.1% 4% (S) 1.4% 18%

Passengers 77% 1.7% 75% 1.8% 2% 1.8% 8%

SUVs & Vans 82% 1.3% 78% 1.4% 4% (S) 1.7% 18%

Drivers 82% 1.4% 78% 1.7% 4% 2.2% 18%

Passengers 79% 1.3% 77% 2.5% 2% 2.5% 9%

Pickup Trucks 68% 2.6% 64% 2.1% 4% 2.4% 11%

Drivers 69% 2.8% 65% 2.0% 4% 2.3% 11%

Passengers 65% 2.6% 61% 4.2% 4% 4.1% 10%

*Rush hour is defined to comprise 8-9:30 AM and 3:30-6 PM.

(S): Statistically significant change

(H): Statistically significant driver-passenger difference in use

Source: National Center for Statistics and Analysis, NHTSA, NOPUS 2002-2003

Table 14: Weekday Belt Use Outside of Rush Hour*, by Vehicle Type 

and Occupant Type 

2003 2002 2002-2003 Change

Characteristic Belt Use Standard 

Error Belt Use Standard Error

EstimateStandard 

Error

Conversion Rate

Overall 79% 1.2% 75% 1.2% 4% (S) 1.4% 16%

Drivers 80% 1.2% 76% 1.1% 4% (S) 1.6% 17%

Passengers 77% 1.1% 73% 1.5% 4% (S) 1.4% 15%

Passenger Cars 81% 1.0% 77% 1.2% 4% (S) 1.3% 17%

Drivers 82% (H) 1.0% 78% 1.2% 4% (S) 1.4% 18%

Passengers 77% 1.2% 73% 1.4% 4% (S) 1.3% 15%

SUVs & Vans 83% 1.1% 79% 1.2% 4% (S) 1.6% 19%

Drivers 83% 1.1% 79% 1.2% 4% (S) 1.7% 19%

Passengers 82% 1.1% 78% 1.4% 4% (S) 1.8% 18%

Pickup Trucks 69% 2.4% 63% 1.8% 6% (S) 2.9% 16%

Drivers 70% 2.3% 64% 1.7% 6% (S) 3.1% 17%

Passengers 68% 2.8% 63% 2.9% 5% 3.6% 14%

*The weekday period outside of rush hour is defined to be 9:30 AM - 3:30 PM.

(S): Statistically significant change

(H): Statistically significant driver-passenger difference in use

Source: National Center for Statistics and Analysis, NHTSA, NOPUS 2002-2003
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Table 15: Belt Use, 1994-2003

Date Use Change, in 

Percentage Points

Conversion 

Rate

Fall 1994 58%

Fall 1996 61% 3 7%

May 1998 62% 1 3%

June 1998 65% 3 8%

Fall 1998 69% 4 11%

Dec 1998 70% 1 3%

Dec 1999 67% -3 -10%

June 2000 71% 4 12%

Fall 2000 71% 0 0%

June 2001 73% 2 7%

June 2002 75% 2 8%

June 2003 79% 4 17%

Source: National Center for Statistics and Analysis, NHTSA, NOPUS 2002-

2003
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5. On Interpreting the NOPUS Estimates

5.1 Estimates Reflect Front Seat Daytime Use

NOPUS provides a snapshot of actual belt use on the roads. Since its data are obtained through 

direct observation of traffic, certain restrictions are necessary. The survey observes shoulder belt 

use of the driver and any passenger in the right front seat in passenger vehicles in motion having 

no commercial or government markings between the hours of 8 AM and 6 PM. That is, NOPUS 

estimates basically reflect use among front seat occupants in the daytime. It is difficult to 

observe belt use at night or in the rear seat from the roadside or from inside a moving vehicle. 

Since NOPUS provides a snapshot of use on the roads, the correct interpretation of the national 

rate is that at the average daylight moment in 2002, 79% of the front seat outboard occupants on 

the road were belted. From this, one can infer that motorists (in the front seat in daylight) were 

belted for 79% of their travel time in 2002. Although NOPUS estimates are frequently

interpreted as the percentage of the population who buckle up with some degree of regularity, 

this is not strictly correct. 

5.2 Technological Improvements

The survey is in the process of phasing in two technological improvements to the data collection 

process. 

1. We are phasing in the use of Personal Data Assistants (PDAs) to replace clicker 

counters and paper forms. 

2. We are phasing in the collection of interstate data from vehicles traveling the

interstate, replacing the proxy observation of vehicles from exit ramps. 

The PDAs are equipped with Global Positioning Systems (GPS) and have been programmed in a 

way that allows observers to record data with their thumbs without looking away from the road. 

The second improvement only applies to limited access highways, which comprise interstates, 

US, state, and county highways that have no traffic signals and allow entry and exit only through 

access ramps. For simplicity, we will call such roadways “interstates”. 

Using the new technologies improves the quality of the data. Using PDAs eliminates all errors 

that arise from entering data from paper forms into a database. Data collectors simply download 

their data over a phone line to a central computer. In addition, PDAs prevent or reduce the 

occurrence of certain types of errors. Using the GPS technology, the PDAs alert data collectors 

if they are not at the scheduled observation site or are not collecting data at the scheduled time. 

In the event an observer collects data for more or less than the assigned 30 minutes, the 

collection time recorded by his/her PDA is used to make the proper adjustment to the estimation 

process. 

PDAs also reduce errors arising from certain distractions. The machines give verbal

confirmation of the data entered, so observers are not distracted from wondering if they recorded 

the correct data (e.g. clicked the correct clicker). If the observer has entered incorrect

information, s/he can press an “Oops” button that flags the information as erroneous. The PDAs 
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are also programmed to record information that could not feasibly be added to clicker data 

collection, such as when an observer cannot discern the presence of a passenger or whether a belt 

is in use. It can be difficult to see a (right front) passenger in a vehicle with tinted windows, in 

inclement weather, or when the passenger is a child. It can be difficult to ascertain belt use in 

inclement weather, when the vehicle has tinted windows, when the shoulder belt is attached to 

the seat instead of to the vehicle’s frame (as it is in convertibles), or when the motorist’s shirt is 

similar in color to the belt.

We believe that PDAs also make data collection more efficient. Only one data collector is 

needed to collect data with PDAs, while two are needed with clickers. It is not feasible for a 

single observer to record all data items, including vehicle type, seating position, and whether or 

not an occupant is belted, with clickers in any reasonably efficient manner. This can be done 

with PDAs since observers can record information quickly with their thumbs. At the time of this 

report’s publication, we had not yet analyzed the relative efficiency of PDAs. Analyzing the 

observations per person hour billed is complicated because one should control for differences in 

the amount of travel that teams incurred to reach their observation sites. 

Collecting interstate data from the interstate is an improvement in data quality over proxy

collection from exit ramps. Observing from exit ramps, one encounters more travelers on short 

trips than one would from observing on the interstate. Consequently the exit ramp methodology 

observes a different population of travelers, who might have a different belt use rate. The Motor 

Vehicle Occupant Safety Survey consistently finds that part time users use belts less frequently 

on short trips. (Block, 2000) Consequently we would expect that observing use on the interstate 

from moving vehicles would produce higher and more accurate use estimates.

5.2.1 Quantifying the Effects of the Improvements

We do not have sufficient data to quantify the effects of using PDAs and collecting interstate 

data from moving vehicles at this time. We believe that each new method yields higher and 

more accurate use estimates than the data collection method it replaces. That is, we believe that 

previous NOPUS estimates understated use and the 2002-2003 change estimate overstates the 

change, but we cannot currently quantify the amounts of understatement and overstatement. We 

hope to be able to quantify the effects in 2004, and may revise previous NOPUS estimates at that 

time. 

We would expect each of the two new collection methods to raise use estimates. As noted 

previously, we would expect use at any given time to be higher on an interstate than on its exit 

ramps, since the ramps contain a disproportionately large number of travelers on short trips. We 

would expect PDAs to increase use estimates, since we have found that observers collecting data 

with clickers tend to record unknowns, such as unknown belt use or inability to discern the 

presence of a passenger, as unbelted occupants. The clickers are simply marked as “Yes” and 

“No” for brevity, and particularly when collecting observations rapidly in heavy traffic, it might 

be natural to misinterpret the “No” clicker sometimes as “No passenger”. Observers were told to 

use their best judgment to discern use, but generally to only click “Yes” (i.e. belted) if they can 

see a shoulder belt in front of the motorist’s chest. Consequently it might be natural to 

disproportionately record nonuse when use is difficult to discern. We are examining the extent 

to which unknown values were recorded in the PDAs data to get a handle on how difficult it is to 

discern various characteristics and the extent to which unknowns might have contributed to 
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clicker-based estimates. We note that while we expect the new methods to raise use estimates, 

we also expect them to produce more accurate ones. 

A test comparing the moving vehicle method with PDAs to the exit ramp method without PDAs 

at 12 interstate sites in 2001 found that the former produced statistically higher estimates, as we 

would expect. The test estimated positive changes both overall and in 7 of 9 categories, formed 

from 3 characterizations of the site as urban/rural/suburban and 3 vehicle types. The Wilcoxon 

signed rank test concluded from these 9 differences, with 95% confidence, that the new method 

has a positive effect. However, standard errors were generally large (6-23 percentage points), 

and the overall difference of 4 percentage points was not statistically different from 0 with 95%

confidence, and so the effect of the new method could not be quantified. 

However, the implementation of these methods in the 2002 NOPUS indicated the opposite 

effect. The moving vehicle method with PDAs was instituted at roughly 13% of the interstate 

sites in 2002, while the remaining interstate sites used the traditional clickers and paper forms. 

The collective use estimate from the sites that used the new method was 5 percentage points 

lower than that from the old method sites, but again this difference was not statistically different 

from 0. A breakdown into 18 categories (from 3 vehicle types, 2 occupant types, and 3 times of 

day and week) found the new method estimates higher in only 2 of the 18 categories. However, 

it is possible that the sites that used the new method had lower belt use than those using the old 

method. 

Implementation at the interstate sites in the 2003 survey found the two collection methods to be 

statistically similar. Use was 0.9 percentage points higher at the sites that used the new method, 

which was not statistically different from 0.

As for using PDAs rather than clickers and paper forms on surface streets, we did not conduct a 

test comparing the two methods on the same collection of surface streets. The implementation of 

these methods on the surface streets in the 2003 survey found that the collective use estimate on 

the surface streets that used PDAs was 5 percentage points higher than the estimate from the 

clicker sites, and this difference was statistically significant. However this again could be due to 

an actual difference in belt use at the two sets of sites. Consequently we cannot conclude from 

this data that PDAs have an effect on surface streets, much less quantify any effect that might 

exist. We would expect that PDAs raise use estimates by a small amount.

In 2004, we hope to use both methods at the same large sample of interstates and surface streets 

to quantify the effects. 

5.3 Assessing Improvement: Conversion Rates

Improvement in belt use is frequently measured by the percentage point increase in the use rate. 

However increasing belt use one percentage point from a 90% use rate is more difficult than it is 

from 50%. Doing so from 90% requires changing the behavior of a larger fraction of nonusers. 

(In addition when use is at 90%, many of those who do not buckle up are hard-core nonusers, 

and not likely to be swayed by media or enforcement campaigns.) A more rational measure of 

improvement is the reduction in nonuse, which we call the conversion rate. For instance nonuse 

was reduced from 25% in 2002 to 21% in 2003, yielding a conversion rate of (25-21)/25, or 

16%. Using unrounded rates produces the 17% conversion rate that appears in Table 1. 
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Although it is not strictly correct, we often think of the conversion rate as the percentage of 

nonusers that were converted to users in the given time period. This would be a correct 

interpretation if NOPUS measured the percentage of the population that used belts (with some 

degree of regularity). E.g. if 79% of the population used safety belts more than half of the time, 

and 75% had previously done so, then 16% of those who used belts less frequently were 

converted to using belts at least half the time. However NOPUS measures a snapshot of belt use 

on the road, and so our interpretation is an oversimplification used only to help comprehend the 

concept.

5.4 Survey Methodology

NOPUS collects data at a random nationally representative sample of 2,000 sites during

randomly assigned 30-minute observation periods. Data collectors observe the shoulder belt use 

of drivers and right front seat passengers in passenger vehicles in motion having with no 

commericial or government markings from the roadside or from a moving vehicle during

daylight hours. A belt is considered in use if the observer can see the belt drawn across the 

chest, whether or not it is under the arm. When they cannot discern use observers collecting data 

with PDAs record the belt use as unknown, while those using clickers use their best judgment to 

decide whether the motorist appears belted or not. Children in child safety seats and booster 

seats with the shoulder belt in use are counted as belted. Relatively few children are observed 

since most children are in the unobserved back seat. The classification of vehicles into passenger 

cars, vans & sport utility vehicles (SUVs), and pickup trucks is made by the observers using their 

best judgment. Observers collect data between 8 AM and 6 PM, on all days of the week. Data 

for the 2003 NOPUS were observed between June 2 and June 29, 2003. Data are weighted in a 

way that incorporates the NOPUS sample design. See (Glassbrenner, 2002) for more

information on the sample design, estimation, and data collection. 

5.5 Definitions

NOPUS categorizes the states and the District of Columbia into the following four regions: 

Northeast: ME, VT, NH, MA, RI, CT, NY, PA, NJ 

Midwest: MI, OH, IN, IL, WI, MN, IA, MO, KS, NE, SD, ND 

South: WV, MD, DE, VA, KY, TN, NC, SC, GA, FL, AL, MS, AR, LA, OK, 

TX, DC

West: AK, WA, OR, CA, NV, ID, UT, AZ, NM, CO, WY, MT, HI

Weekday data is broken down into rush hour, defined to comprise the periods 8:00 – 9:30 AM and 

3:30 – 6:00 PM, with non-rush hour reflecting the period 9:30 AM to 3:30 PM (on weekdays). 

5.6 Assessing Change: Statistical Significance

NOPUS observes a sample of motorists, and so may not yield the actual use rates. The amount 

of variation that would occur in the use rates of all possible samples (selected using the same 

design as NOPUS) is measured by the standard error. For instance the standard error on the 

nationwide increase of 4 percentage points in use is 1.4 percentage points. If the change in an 

estimate is larger than twice its standard error, we are 95% confident that the change we saw in 
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our sample reflects an actual change in use. The nationwide increase from 75% to 79% use fits 

this description, and so we are 95% confident that belt use actually rose in the past year. (In fact, 

a more complicated calculation yields 99.7% confidence in the increase.)

5.7 Computing the Margin of Error of a Use Rate

Similarly, we can be 95% confident that an actual use rate is within twice the standard error of 

that seen in the sample. For instance, the national rate of 79% seen in our sample has a standard 

error of 1.2 percentage points, and so we are 95% confident that belt use in the U.S. was between 

77% and 81% in 2003. 
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6. References

Blincoe, L., Seay, A., Zaloshnja, E., Miller, T., Romano, E., Luchter, S., Spicer, R., The 

Economic Impact of Motor Vehicle Crashes, 2000, NHTSA Technical Report, DOT HS 809 446, 

May 2002

Block, A., 2000 Motor Vehicle Occupant Safety Survey, Volume 2: Seat Belt Report, NHTSA 

Technical Report, DOT HS 809 389, November 2001

Glassbrenner, D., Improving the Calculations of the Lives Saved and Savable by Safety Belts and 

Air Bags, NHTSA Technical Report, to appear in September 2003

Glassbrenner, D., Safety Belt and Helmet Use in 2002 – Overall Results, NHTSA Technical 

Report, DOT HS 809 500, August 2002

Mix, W., Shapiro, G., Huey, R., Giangrande, M., Utter, D., Glassbrenner, D., The Use of 

Technology in Observational Surveys, to be presented at the Transportation Research Board 

Annual Meeting, January 2004

Traffic Safety Facts 2002 - Overview, NHTSA Fact Sheet, DOT HS 809 612, undated

Tyson, R., U.S. Transportation Secretary Mineta Launches Massive Law Enforcement 

Mobilization for Traffic Safety, NHTSA Press Release, NHTSA 19-03, May 2003
DOT HS 809 646

September 2003