2007 National Roadside Survey of 

Alcohol and Drug Use by Drivers

Drug Results
This publication is distributed by the U.S. Department of Transportation, National 

Highway Traffic Safety Administration, in the interest of information exchange. 

The opinions, findings and conclusions expressed in this publication are those of 

the author(s) and not necessarily those of the Department of Transportation or the 

National Highway Traffic Safety Administration. The United States Government 

assumes no liability for its content or use thereof. If trade or manufacturers’ names 

or products are mentioned, it is because they are considered essential to the object 

of the publication and should not be construed as an endorsement. The United 

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i 

Technical Report Documentation Page

1. Report No. 2. Government Accession No. 3. Recipient’s Catalog No. 

DOT HS 811 249 4. Title and Subtitle 5. Report Date 

December 2009 

6. Performing Organization Code 2007 National Roadside Survey of Alcohol and Drug Use by Drivers: 

Drug Results 

7. Author(s) 

John H. Lacey, Tara Kelley-Baker, Debra Furr-Holden, Robert B. 

Voas, Eduardo Romano, Anthony Ramirez, Katharine Brainard, 

Christine Moore, Pedro Torres, and Amy Berning 

8. Performing Organization Report No. 

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

Pacific Institute for Research and Evaluation 11. Contract or Grant No. 

11720 Beltsville Drive, Ste. 900, Calverton, MD 20705 

Phone: 301-755-2700 Fax: (301) 755-2799 DTNH22-06-C-00040 

12. Sponsoring Agency Name and Address 13. Type of Report and Period Covered 

Final Report 

14. Sponsoring Agency Code 

National Highway Traffic Safety Administration 

Office of Behavioral Safety Research 

1200 New Jersey Avenue, SE 

Washington, DC 20590

15. Supplementary Notes 

Amy Berning served as the project’s Contracting Officer’s Technical Representative. 

The National Institute on Alcohol Abuse and Alcoholism (NIAAA) provided funding and support for the assessment of 

alcohol use disorders. 

The National Institute on Drug Abuse (NIDA) provided funding for the collection of additional blood samples and the 

administration of the drug use disorders assessment. 

The National Institute of Justice (NIJ) provided support for querying participants about interaction with the criminal 

justice system.

16. Abstract 

This report presents the first national prevalence estimates for drug-involved driving derived from the recently 

completed 2007 National Roadside Survey (NRS). The NRS is a national field survey of alcohol- and drug-involved 

driving conducted primarily among nighttime weekend drivers, but also daytime Friday drivers. The survey involved 

randomly stopping drivers at 300 locations across the continental United States; sites were selected through a stratified 

random sampling procedure. This included data that we collected during a two-hour Friday daytime session at 60 

locations and during four 2-hour nighttime periods (10:00 p.m. to midnight and 1:00 a.m. to 3:00 a.m. on both Friday 

and Saturday) at 240 locations. Both self-report and biological measures were taken. Biological measures included 

breath alcohol measurements on 9,413 respondents, oral fluid from 7,719 respondents, and blood samples from 3,276 

respondents. Oral fluid and blood samples were subjected to laboratory screening and LC/MS-MS and GC/MS 

confirmation for 75 drugs and metabolites, including illegal, prescription, and over-the-counter drugs. These data were 

analyzed to develop the first national prevalence estimate of alcohol- and drug-involved driving. Two prior reports on 

the 2007 NRS described: (1) the sampling plan and data collection methodology, summarizing the response patterns to 

the various stages of the multi-part survey; and (2) the prevalence estimates for alcohol-involved driving derived from 

the study, and comparing them with the three previous National Roadside Surveys (NRS). 

17. Key Words 18. Distribution Statement 

Alcohol and driving, drugs and driving, roadside 

survey, impaired driving, drugged driving, alcoholinvolved driving, drug-involved driving 

Document is available to the public from the 

National Technical Information Service 

www.ntis.gov 

19 Security Classif. (of this report) 20. Security Classif. (of this page) 21 No. of Pages 22. Price 

Unclassified Unclassified 148 

Form DOT F 1700.7 (8/72) Reproduction of completed page authorized 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Acknowledgements 

The authors received extensive assistance from State and local officials in the conduct of this 

project. Our data collection procedures were not routine. The willingness of officials to help us 

identify cooperating local law enforcement agencies and the willingness of agencies to 

participate in the project were essential to our success. To all those who helped in conducting 

this study, the authors express their sincere gratitude. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table of Contents 

Executive Summary........................................................................................................................ 1 

Methodology............................................................................................................................... 1 

Results......................................................................................................................................... 3 

Summary..................................................................................................................................... 8 

Introduction..................................................................................................................................... 9 

Background................................................................................................................................. 9 

Prevalence of Drug-Involved Driving ...................................................................................... 10 

Impact of Drugs on Driving Skills............................................................................................ 10

Laboratory Studies................................................................................................................ 10 

Field Data.............................................................................................................................. 11 

Challenges in Measurement and Today’s Drug Testing Opportunities.................................... 13 

Project Objectives ..................................................................................................................... 14 

Methods......................................................................................................................................... 17 

Survey Sampling Procedures .................................................................................................... 17 

Preparation for the 2007 NRS Survey ...................................................................................... 20 

Driver Conversion..................................................................................................................... 23 

Selection of Drugs for Screening and Analysis ........................................................................ 24 

Oral Fluid Collection Device.................................................................................................... 27 

Blood Collection Procedures .................................................................................................... 29 

Drug Questionnaire................................................................................................................... 31 

Oral Fluid Sample Analysis Procedures ............................................................................... 32 

Gas Chromatography-Mass Spectrometry (GC/MS)............................................................ 32 

Liquid Chromatography-Tandem Mass Spectrometry (LC/MS-MS)................................... 32 

Blood Sample Analysis Procedures...................................................................................... 33 

Ethanol (Oral Fluid and Blood) ............................................................................................ 33 

Drug Classes and Categories .................................................................................................... 33 

Results........................................................................................................................................... 37 

Oral Fluid Results (Daytime and Nighttime Samples) ............................................................. 37 

Driver Drug Use Prevalence Based on Oral Fluid Results................................................... 37 

Driver Drug Use Prevalence by Drug Class Based on Oral Fluid Results ........................... 44 

Driver Drug Use Prevalence by Drug Category Based on Oral Fluid Results .................... 48 

Driver Drug Prevalence Based on Oral Fluid and BAC Results .......................................... 53 

Drugs: Oral Fluid Results and Agreement with Self-Reported Drug Use............................ 59 

Observed Safety Measures of Daytime and Nighttime Drivers (Oral Fluid) ....................... 62 

Reported Contact with the Criminal Justice System (Oral Fluid) ........................................ 66 

Reported Contact with the Health System (Oral Fluid)........................................................ 69 

Blood Results (Nighttime Samples).......................................................................................... 76 

Driver Drug Use Prevalence Based on Blood Results.......................................................... 76 

Driver Drug Use Prevalence by Drug Class Based on Blood Results.................................. 80 

Driver Drug Use Prevalence by Drug Category Based on Blood Results............................ 82 

Driver Drug Use Prevalence from Blood and BAC Results................................................. 85 

Oral Fluid and/or Blood Results (Nighttime Samples)............................................................. 89 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Driver Drug Use Prevalence Based on Oral Fluid and/or Blood Results............................. 89 

Driver Drug Use Prevalence by Drug Class Based on Oral Fluid and/or Blood Results ..... 94 

Driver Drug Use Prevalence by Drug Category Based on Oral Fluid and/or Blood Results96 

Driver Drug Use Prevalence from Oral Fluid and/or Blood and BAC Results.................... 98 

Individual Drug Prevalence Estimates from Oral Fluid, and Oral Fluid and/or Blood 

Combined................................................................................................................................ 102 

Overall Individual Drug Prevalence in Daytime and Nighttime ........................................ 103 

Individual Drug Prevalence in Nighttime Oral Fluid and/or Blood ................................... 105 

Individual Drug Prevalence Sorted by Drug Type from Oral Fluid, and Oral Fluid and/or 

Blood Combined ................................................................................................................. 107 

Discussion................................................................................................................................... 111 

Oral Fluid Analyses ............................................................................................................ 111 

Blood Analyses ................................................................................................................... 113 

Oral Fluid and/or Blood Analyses Combined..................................................................... 114 

References................................................................................................................................... 115 

Appendix A................................................................................................................................. 121

2007 National Roadside Survey Additional Tables............................................................ 123 

Tables 

Table 1. Participating Drivers (Percentages in Parentheses) .......................................................... 3 

Table 2. Drug Prevalence by Time of Day (Oral Fluid)................................................................. 3 

Table 3. Drug Categories Distribution by Time of Day (Oral Fluid) ............................................. 4 

Table 4. BAC Among Drug-Positive Drivers by Drug Category and Time of Day (Oral Fluid) .. 5 

Table 5. Drug Classes by Time of Day and Region (Oral Fluid) ................................................... 6 

Table 6. Number and Distribution of Drug Classes by Time of Day (Oral Fluid)......................... 6 

Table 7. Drug Categories Distribution (Blood) .............................................................................. 7 

Table 8. BAC Among Drug-Positive Drivers by Drug Category (Percentage by Row) (Blood)... 7 

Table 9. Comparison of Number of Nighttime Participants by Year in the National Roadside 

Surveys.................................................................................................................................. 21 

Table 10. Participating Drivers (Percentages in Parentheses) ...................................................... 22 

Table 11. Oral Fluid Analysis Results Among Converted Drivers .............................................. 23 

Table 12. Blood Analysis Results Among Converted Drivers ..................................................... 23 

Table 13. Selected Drugs and Minimum Detection Concentrations†........................................... 24 

Table 14. Extraction Efficiency of QuantisalTM Oral Fluid Collection Device over a Range of 

Drugs: Quintela..................................................................................................................... 29 

Table 15. Extraction Efficiency of QuantisalTM Oral Fluid Collection Device over a Range of 

Drugs: Moore........................................................................................................................ 29 

Table 16. Drug Questionnaire Survey .......................................................................................... 31 

Table 17. Drug Class Composition—Oral Fluid and Blood Combined ....................................... 34 

Table 18. Drug Category Composition—Oral Fluid and Blood Combined ................................. 35 

Table 19. Drug Prevalence by Time of Day (Oral Fluid)............................................................. 38 

Table 20. Drug Prevalence by Time of Day/Session (Oral Fluid)................................................ 38 

Table 21. Drug Prevalence by Time of Day and Region (Oral Fluid).......................................... 39 

Table 22. Drug Prevalence by Time of Day and Gender (Oral Fluid) ......................................... 39 

Table 23. Drug Prevalence by Time of Day and Age (Oral Fluid)............................................... 40 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 24. Drug Prevalence by Time of Day, Age, and Gender (Oral Fluid)................................ 41 

Table 25. Drug Prevalence by Race/Ethnicity (Oral Fluid).......................................................... 42 

Table 26. Drug Prevalence by Education Level (Oral Fluid) ....................................................... 42 

Table 27. Drug Prevalence by Employment Status (Oral Fluid).................................................. 43 

Table 28. Drug Prevalence by Vehicle Type (Oral Fluid)............................................................ 44 

Table 29. Number and Distribution of Drug Classes by Time of Day (Oral Fluid)..................... 44 

Table 30. Number and Distribution of Drug Classes by Time of Day (Drug Positives Only) 

(Oral Fluid) ........................................................................................................................... 45 

Table 31. Drug Classes by Time of Day and Region (Oral Fluid) ............................................... 46 

Table 32. Drug Classes Distribution by Time of Day and Gender (Oral Fluid)........................... 47 

Table 33. Drug Class Distribution by Time of Day and Age (Oral Fluid) ................................... 48 

Table 34. Drug Categories Distribution by Time of Day (Oral Fluid) ......................................... 49 

Table 35. Drug Categories Distribution by Time of Day and Region (Oral Fluid)...................... 50 

Table 36. Drug Categories Distribution by Time of Day and Gender (Oral Fluid)...................... 51 

Table 37. Drug Categories Distribution by Time of Day and Age (Oral Fluid)........................... 52 

Table 38. Drug Prevalence by Time of Day and BAC (Percentages Calculated by Row) (Oral 

Fluid)..................................................................................................................................... 54 

Table 39. Drug Prevalence by Time of Day and BAC (Percentages Calculated by Column) (Oral 

Fluid)..................................................................................................................................... 54 

Table 40. BAC Among Drug-Positive Drivers by Time of Day and Age (Oral Fluid)................ 55 

Table 41. BAC Among Drug-Positive Drivers by Number of Drug Classes and Time of Day 

(Percentages Calculated by Column) (Oral Fluid)................................................................ 55 

Table 42. BAC Among Drug-Positive Drivers by Number of Drug Classes and Time of Day 

(Percentages Calculated by Row) (Oral Fluid)..................................................................... 56 

Table 43. BAC Among Drug-Positive Drivers by Drug Category and Time of Day (Oral Fluid)

............................................................................................................................................... 56 

Table 44. BAC of Drivers by Drug Category, Age, and Time of Day (Oral Fluid)..................... 57 

Table 45. BAC of Drivers by Drug Category, Gender, and Time of Day (Oral Fluid)................ 58 

Table 46. Oral Fluid Results and Agreement with Self-Reported by Drug Type (Oral Fluid) .... 60 

Table 47. Daytime: Seat Belt Observation by Drug Prevalence (Oral Fluid) ............................. 62 

Table 48. Nighttime: Seat Belt Observation by Drug Prevalence (Oral Fluid)............................ 62 

Table 49. Daytime: Seat Belt Observation by Drug Class (Percentages Calculated by Row) (Oral 

Fluid)..................................................................................................................................... 63 

Table 50. Nighttime: Seat Belt Observation by Drug Class (Percentages Calculated by Row) 

(Oral Fluid) ........................................................................................................................... 63 

Table 51. Daytime: Seat Belt Observation by Drug Category (Percentages Calculated by Row) 

(Oral Fluid) ........................................................................................................................... 64 

Table 52. Nighttime: Belt Observation by Drug Category (Percentages Calculated by Row) (Oral 

Fluid)..................................................................................................................................... 64 

Table 53. Daytime: Helmet Use for Motorcycle Riders (Operators), by Drug Positive (Oral 

Fluid)..................................................................................................................................... 64 

Table 54. Nighttime: Helmet Use for Motorcycle Riders (Operators), by Drug Positive (Oral 

Fluid)..................................................................................................................................... 65 

Table 55. Daytime: Helmet Use for Motorcycle Riders (Operators), by Drug Class (Oral Fluid)

............................................................................................................................................... 65 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 56. Nighttime: Helmet Use for Motorcycle Riders (Operators) by Drug Class 

(Percentages Calculated by Row) (Oral Fluid)..................................................................... 65 

Table 57. Daytime: Helmet Use for Motorcycle Riders (Operators), by Drug Category (Oral 

Fluid)..................................................................................................................................... 66 

Table 58. Nighttime: Helmet Use for Motorcycle Riders (Operators), by Drug Category 

(Percentages Calculated by Row) (Oral Fluid)..................................................................... 66 

Table 59. Arrests and Drug Positives, Daytime (Oral Fluid): “During the past 12 months, were 

you arrested and booked for driving under the influence of alcohol or drugs?” .................. 66 

Table 60. Arrests and Drug Positives, Nighttime (Oral Fluid): “During the past 12 months, were 

you arrested and booked for driving under the influence of alcohol or drugs?” .................. 67 

Table 61. Arrests and Drug Class, Daytime (Oral Fluid): “During the past 12 months, were you 

arrested and booked for driving under the influence of alcohol or drugs?” ......................... 67 

Table 63. Arrests and Drug Categories, Daytime (Oral Fluid): “During the past 12 months, were 

you arrested and booked for driving under the influence of alcohol or drugs?” .................. 68 

Table 64. Arrests and Drug Categories, Nighttime (Oral Fluid): “During the past 12 months, 

were you arrested and booked for driving under the influence of alcohol or drug?” ........... 68 

Table 65. Past Treatment Program and Drug Positive, Daytime (Oral Fluid): “During the past 12 

months, did you ever stay at least overnight in an inpatient or residential drug or alcohol 

treatment program?” ............................................................................................................. 69 

Table 66. Past Treatment Program and Drug Positive, Nighttime (Oral Fluid): “During the past 

12 months, did you ever stay at least overnight in an inpatient or residential drug or alcohol 

treatment program?” ............................................................................................................. 69 

Table 67. Outpatient and Drug Positive, Daytime (Oral Fluid): “Have you ever been admitted to 

an outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?”

............................................................................................................................................... 70 

Table 68. Outpatient and Drug Positive, Nighttime (Oral Fluid): “Have you ever been admitted 

to an outpatient drug or alcohol treatment program, NOT including meetings like AA or 

NA?” ..................................................................................................................................... 70 

Table 69. AA or NA and Drug Positives, Daytime (Oral Fluid): “During the past 12 months, 

have you received treatment for your drug or alcohol use in a self-help group such as 

Alcoholics Anonymous or Narcotics Anonymous?”............................................................ 70 

Table 70. AA or NA and Drug Positives, Nighttime (Oral Fluid): “During the past 12 months, 

have you received treatment for your drug or alcohol use in a self-help group such as 

Alcoholics Anonymous of Narcotics Anonymous?”............................................................ 71 

Table 71. Inpatient and Drug Class, Daytime (Oral Fluid): “During the past 12 months, did you 

ever stay at least overnight in an impatient or residential drug or alcohol treatment program, 

for example, detox, rehab, a therapeutic community, or a hospital?” .................................. 71 

Table 72. Inpatient and Drug Class, Nighttime (Oral Fluid): “During the past 12 months, did you 

ever stay at least overnight in an impatient or residential drug or alcohol treatment program, 

for example, detox, rehab, a therapeutic community, or a hospital?” .................................. 72 

Table 73. Inpatients and Drug Category, Daytime (Oral Fluid): “During the past 12 months, were 

you arrested and booked for driving under the influence of alcohol or drugs?” .................. 72 

Table 74. Inpatients and Drug Category, Nighttime (Oral Fluid): “During the past 12 months, 

were you arrested and booked for driving under the influence of alcohol or drugs?”.......... 72 

Table 75. Outpatient and Drug Class, Daytime (Oral Fluid): “Have you ever been admitted to an 

outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?” 73 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 76. Outpatient and Drug Class, Nighttime (Oral Fluid): “Have you ever been admitted to 

an outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?”

............................................................................................................................................... 73 

Table 77. Outpatient and Categories, Daytime (Oral Fluid): “Have you ever been admitted to an 

outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?” 74 

Table 78. Outpatient and Categories, Nighttime (Oral Fluid): “Have you ever been admitted to an 

outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?” 74 

Table 79. AA, NA and Classes, Daytime (Oral Fluid): “During the past 12 months, have you 

received treatment for your drug or alcohol use in a self-help group such as AA or NA?”. 74 

Table 80. AA, NA and Classes, Nighttime (Oral Fluid): “During the past 12 months, have you 

received treatment for your drug or alcohol use in a self-help group such as AA or NA?”. 75 

Table 81. NA, AA and Drug Categories, Daytime (Oral Fluid): “During the past 12 months, have 

you received treatment for your drug or alcohol use in a self-help group such as AA or 

NA?” ..................................................................................................................................... 75 

Table 82. NA, AA and Drug Categories, Nighttime (Oral Fluid): “During the past 12 months, 

have you received treatment for your drug or alcohol use in a self-help group such as AA or 

NA?” ..................................................................................................................................... 76 

Table 83. Drug Prevalence by Time of Day (Blood).................................................................... 76 

Table 84. Drug Prevalence by Session (Blood)............................................................................ 77 

Table 85. Drug Prevalence by Region (Blood)............................................................................. 77 

Table 86. Drug Prevalence by Gender (Blood) ............................................................................ 77 

Table 87. Drug Prevalence by Age (Blood).................................................................................. 78 

Table 88. Drug Prevalence by Age and Gender (Blood).............................................................. 78 

Table 89. Drug Prevalence by Race/Ethnicity (Blood) ................................................................ 78 

Table 90. Drug Prevalence by Education Level (Blood).............................................................. 79 

Table 91. Drug Prevalence by Employment Status (Blood)......................................................... 79 

Table 92. Drug Prevalence by Vehicle Type (Blood)................................................................... 80 

Table 93. Number and Distribution of Drug Classes (Blood) ...................................................... 80 

Table 94. Drug Classes Distribution by Region (Blood).............................................................. 81 

Table 95. Drug Classes Distribution by Gender (Blood).............................................................. 81 

Table 96. Drug Classes Distribution by Age (Blood)................................................................... 82 

Table 97. Drug Categories Distribution (Blood) .......................................................................... 82 

Table 98. Drug Categories Distribution by Region (Blood)......................................................... 83 

Table 99. Drug Categories Distribution by Gender (Blood)......................................................... 84 

Table 100. Drug Categories Distribution by Age (Blood)............................................................ 85 

Table 101. Drug Prevalence by BAC (Percentages Calculated by Row) (Blood)........................ 86 

Table 102. Drug Prevalence by BAC (Percentages Calculated by Column) (Blood) .................. 86 

Table 103. BAC Among Drug-Positive Drivers by Age (Blood)................................................. 86 

Table 104. BAC Among Drug-Positive Drivers by Number of Drug Classes (Percentages 

Calculated by Column) (Blood)............................................................................................ 87 

Table 105. BAC Among Drug-Positive Drivers by Number of Drug Classes (Percentages 

Calculated by Row) (Blood) ................................................................................................. 87 

Table 106. BAC Among Drug-Positive Drivers by Drug Category (Percentage by Row) (Blood)

............................................................................................................................................... 87 

Table 107. BAC Among Drug-Positive Drivers by Drug Category (Percentage by Column) 

(Blood) .................................................................................................................................. 88 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 108. BAC of Drivers by Drug Category and Age (Blood) ................................................. 88 

Table 109. BAC of Drivers by Drug Category and Gender (Blood)............................................ 89 

Table 110. Nighttime Drug Prevalence by Time of Day (Oral Fluid and/or Blood).................... 90 

Table 111. Drug Prevalence by Session (Oral Fluid and/or Blood) ............................................. 90 

Table 112. Drug Prevalence by Region (Oral Fluid and/or Blood).............................................. 90 

Table 113. Drug Prevalence by Gender (Oral Fluid and/or Blood).............................................. 91 

Table 114. Drug Prevalence by Age (Oral Fluid and/or Blood)................................................... 91 

Table 115. Drug Prevalence by Age and Gender (Oral Fluid and/or Blood) ............................... 92 

Table 116. Drug Prevalence by Race/Ethnicity (Oral Fluid and/or Blood).................................. 92 

Table 117. Drug Prevalence by Education Level (Oral Fluid and/or Blood) ............................... 93 

Table 118. Drug Prevalence by Employment Status (Oral Fluid and/or Blood).......................... 93 

Table 119. Drug Prevalence by Vehicle Type (Oral Fluid and/or Blood).................................... 93 

Table 120. Number and Distribution of Drug Classes (Oral Fluid and/or Blood) ....................... 94 

Table 121. Number and Distribution of Drug Classes (Drug Positives Only) (Oral Fluid and/or 

Blood) ................................................................................................................................... 94 

Table 122. Drug Classes Distribution by Region (Oral Fluid and/or Blood) ............................... 95 

Table 123. Drug Classes Distribution by Gender (Oral Fluid and/or Blood)............................... 95 

Table 124. Drug Classes Distribution by Age (Oral Fluid and/or Blood).................................... 96 

Table 125. Drug Categories Distribution (Oral Fluid and/or Blood)............................................ 96 

Table 126. Drug Categories Distribution by Region (Oral Fluid and/or Blood).......................... 97 

Table 127. Drug Categories by Gender (Oral Fluid and/or Blood) .............................................. 97 

Table 128. Drug Categories Distribution by Age (Oral Fluid and/or Blood)............................... 98 

Table 129. Drug Prevalence by BAC (Percentages Calculated by Row) (Oral Fluid and/or Blood)

............................................................................................................................................... 99 

Table 130. Drug Prevalence by BAC (Percentages Calculated by Column) (Oral Fluid and/or 

Blood) ................................................................................................................................... 99 

Table 131. BAC Among Drug-Positive Drivers by Age (Oral Fluid and/or Blood).................... 99 

Table 132. BAC Among Drug-Positive Drivers by Number of Drug Classes (Percentages 

Calculated by Column) (Oral Fluid and/or Blood)............................................................. 100 

Table 133. BAC Among Drug-Positive Drivers by Number of Drug Classes (Percentages 

Calculated by Row) (Oral Fluid and/or Blood) .................................................................. 100 

Table 134. BAC Among Drug-Positive Drivers by Drug Category (Oral Fluid and/or Blood). 100 

Table 135. BAC of Drivers by Drug Category and Age (Oral Fluid and/or Blood) .................. 101 

Table 136. BAC of Drivers by Drug Category and Gender (Oral Fluid and/or Blood) ............. 102 

Table 137. Prevalence of Drugs in Daytime and Nighttime Drivers (Oral Fluid)..................... 104 

Table 138. Prevalence of Drugs in All Drug-Tested Nighttime Drivers (Oral Fluid and/or Blood)

............................................................................................................................................. 106 

Table 139. Prevalence of Drugs in Daytime and Nighttime Drivers (Oral Fluid)...................... 108 

Table 140. Prevalence of Drugs in All Drug-Tested Nighttime Drivers (Oral Fluid and/or Blood)

............................................................................................................................................. 109 

Table 141. Nighttime: Blood Results and Agreement with Self-Reported by Drug Type (Blood)

............................................................................................................................................. 123 

Table 142. Nighttime: Seat Belt Observation by Drug Prevalence (Blood)............................... 125 

Table 143. Nighttime: Seat Belt Observation by Drug Class (Percentages Calculated by Row) 

(Blood) ................................................................................................................................ 125 

Table 144. Nighttime: Seat Belt Observation by Drug Category (Blood).................................. 126 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 145. Nighttime: Helmet Use for Motorcycle Riders (Operators), by Drug Positive (Blood)

............................................................................................................................................. 126 

Table 146. Nighttime: Helmet Use for Motorcycle Riders (Operators), by Drug Class 

(Percentages Calculated by Row) (Blood).......................................................................... 126 

Table 147. Nighttime: Helmet Use for Motorcycle Riders (Operators), by Drug Category 

(Percentages Calculated by Row) (Blood).......................................................................... 126 

Table 148. Nighttime: Arrests and Drug Positives (Blood): “During the past 12 months, were you 

arrested and booked for driving under the influence of alcohol or drugs?” ....................... 127 

Table 149. Nighttime: Arrests and Drug Class (Blood): “During the past 12 months, were you 

arrested and booked for driving under the influence of alcohol or drugs?” ....................... 127 

Table 150. Nighttime: Arrests and Drug Categories (Blood): “During the past 12 months, were 

you arrested and booked for driving under the influence of alcohol or drugs?” ................ 127 

Table 151. Nighttime: Past Treatment Program and Drug Positive (Blood): “During the past 12 

months, did you ever stay at least overnight in an inpatient or residential drug or alcohol 

treatment program?” ........................................................................................................... 127 

Table 152. Nighttime: Inpatient and Drug Class (Blood): “During the past 12 months, did you 

ever stay at least overnight in an impatient or residential drug or alcohol treatment program, 

for example, detox, rehab, a therapeutic community, or a hospital?” ................................ 128 

Table 153. Nighttime: Inpatient and Drug Category (Blood): “During the past 12 months, did 

you ever stay at least overnight in an impatient or residential drug or alcohol treatment 

program, for example, detox, rehab, a therapeutic community, or a hospital?”................. 128 

Table 154. Nighttime: Outpatient and Drug Positive (Blood): “Have you ever been admitted to 

an outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?”

............................................................................................................................................. 128 

Table 155. Nighttime: Outpatient and Drug Class (Blood): “Have you ever been admitted to an 

outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?”

............................................................................................................................................. 129 

Table 156. Nighttime: Outpatient and Categories (Blood): “Have you ever been admitted to an 

outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?”

............................................................................................................................................. 129 

Table 157. Nighttime: AA or NA, and Drug Positives (Blood): “During the past 12 months, have 

you received treatment for your drug or alcohol use in a self-help group such as AA or 

NA?” ................................................................................................................................... 129 

Table 158. Nighttime: AA or NA, and Class (Blood): “During the past 12 months, have you 

received treatment for your drug or alcohol use in a self-help group such as AA or NA?”130 

Table 159. Nighttime: AA or NA, and Drug Categories (Blood): “During the past 12 months, 

have you received treatment for your drug or alcohol use in a self-help group such as AA or 

NA?” ................................................................................................................................... 130 

Figures 

Figure 1. Map of Sixty 2007 National Roadside Survey Sites ..................................................... 19

Figure 2. Collecting an Oral Fluid Sample with the QuantisalTM Oral Fluid Collection Device . 28
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Executive Summary 

This report presents the first U.S. national prevalence estimate of drug-involved driving. It is 

based on the results of analyses of oral fluid, blood, and breath specimens collected during the 

2007 National Roadside Survey of Alcohol- and Drug-Involved Driving. It is one of the three 

reports that summarize the results of a 2007 study conducted by the Pacific Institute for Research 

and Evaluation (PIRE) for the National Highway Traffic Safety Administration (NHTSA) under 

Contract DTNH22-06-C-00040, “2007 National Roadside Survey of Alcohol and Drugged 

Driving.” There are two prior reports on the 2007 National Roadside Survey (NRS): (1) “2007 

National Roadside Survey of Alcohol and Drug Use by Drivers: Methodology” (Lacey, KelleyBaker, Furr-Holden, Voas, Moore, Brainard, Tippetts, Romano, Torres, & Berning, 2009a) 

which describes the sampling plan and data collection methodology, and summarizes the 

response patterns to the various stages of the multi-part survey; and (2) “2007 National Roadside 

Survey of Alcohol and Drug Use by Drivers: Alcohol Results” (Lacey, Kelley-Baker, FurrHolden, Voas, Romano, Tippetts, Ramirez, Brainard, & Berning, 2009b) which presents the 

prevalence estimates for alcohol-involved driving derived from the study, and compares those 

estimates with data from the three previous National Roadside Surveys. 

Methodology 

Three prior national roadside surveys of drivers to estimate prevalence of drinking and driving 

and determine changes over time have been conducted in the United States. These surveys, 

which included a brief interview and a breath sample to determine blood alcohol concentration 

(BAC), were conducted on a stratified random sample of weekend nighttime drivers in the 48 

contiguous States. The first National Roadside Survey (NRS), sponsored by NHTSA, was 

conducted in 1973 (Wolfe, 1974). The second NRS was sponsored by the Insurance Institute for 

Highway Safety (IIHS) and conducted in 1986 (Lund & Wolfe, 1991), and the third, jointly 

funded by IIHS and NHTSA, was conducted in 1996 (Voas, Wells, Lestina, Williams, & Greene, 

1998). NHTSA sponsored the 2007 NRS described in this report, with additional funding from 

the National Institute on Alcohol Abuse and Alcoholism (NIAAA), the National Institute on 

Drug Abuse (NIDA), and the National Institute of Justice (NIJ). Like its predecessors, the 2007 

NRS covered the 48 contiguous States. 

As in previous NRS studies, the 2007 NRS data were collected during the following periods on 

both Friday and Saturday nights: 10:00 p.m. to midnight and 1:00 a.m. to 3:00 a.m.1

 In addition, 

the 2007 survey also included a Friday daytime data collection period either from 9:30 a.m. to 

11:30 a.m. or from 1:30 p.m. to 3:30 p.m. The prior three surveys did not include commercial 

vehicles and motorcycles in the sample; this survey, however, included motorcycles. In addition 

to a daytime survey and the inclusion of motorcycles, the 2007 NRS included other features that 

the prior surveys did not: (1) more data collectors per survey site to achieve a larger sample size; 

(2) the collection of biological samples (oral fluid and blood) to determine the presence of drugs 

other than alcohol in the driving population; (3) a questionnaire to allow an estimation of alcohol 

use disorders (AUDs) among drinking drivers; (4) a questionnaire to study drivers’ patterns of 

 

1

 In this report, a “Friday night” or a “Saturday night” includes the early hours of the following day. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

2 

drug consumption; (5) questions about interaction with the criminal justice system and the 

treatment system; and (6) collection of information on passengers. 

In all four NRS studies, police officers directed vehicles to a safe location, where an interviewer 

approached the driver and requested participation in a survey followed by a breath test. Random 

selection of drivers was insured by selecting the next vehicle when an interviewer became 

available. Any driver suspected of impairment was subjected to a safety protocol designed to 

dissuade his/her continued driving on that trip. See the Methodology Report for details (Lacey et 

al., 2009a). 

As noted above, the original 1973 survey used a four-stage sampling plan, and the 1986 NRS 

attempted to replicate the 1973 locations. In the 1996 and 2007 surveys, the first stage was taken 

from the NHTSA’s National Automotive Sampling System/Crashworthiness Data System 

(NASS/CDS, 1995). The second stage involved the selection of police jurisdictions within the 

NASS/CDS primary sampling units. The third stage of the sampling design involved the 

selection of survey sites within police jurisdictions, and the fourth stage consisted of selecting 

drivers at random from the traffic flow at these sites. Details regarding the sampling plan can be 

found in the Methodology Report (Lacey et al., 2009a). 

New to the 2007 survey was the collection of additional types of biological samples (oral fluid 

and blood) to determine the presence of drugs other than alcohol in the driving population. Oral 

fluid and blood samples were analyzed in a laboratory using enzyme-linked immunosorbent 

assay (ELISA) screening, followed by a confirmatory analysis by Liquid ChromatographyTandem Mass Spectrometry (LC/MS-MS) or Gas Chromatography/Mass Spectrometry 

(GC/MS). This 2007 NRS is more extensive than any previous NRS study and provides a much 

broader perspective on alcohol and drug use in the driving population than previously available. 

These data are essential to developing more precise estimates of the presence of alcohol and 

other drugs in drivers, and in measuring the prevalence of alcohol- and drug-involved driving. 

This report summarizes the drug-involved driving prevalence estimates obtained through 

analyses of oral fluid and blood specimen results, and combined with alcohol using breath 

alcohol measurements. It should be emphasized that prevalence estimates do not necessarily 

imply “impairment,” but rather, in this case, the presence of drugs and alcohol in the driver 

population. For many drug types, drug presence can be detected long after any impairment that 

might affect driving has passed.2

 Other studies are required to assess whether that presence 

implies an increased risk of crash involvement. In this study, we developed driver-prevalence 

estimates for illegal, prescription, and over-the-counter drugs which were determined by a panel 

of experts to possibly cause impairment. It should be noted that prescription and over-the-counter 

drugs can be used according to medical advice or extra-medicinally. Again, the prevalence 

estimates indicate the presence of the drugs in drivers but do not necessarily indicate that the 

drivers were impaired. 

 

2

 For example, traces of marijuana can be detected in blood samples several weeks after chronic users stop 

ingestion. Also, whereas the impairment effects for various concentration levels of alcohol is well understood, little 

evidence is available to link concentrations of other drug types to driver performance. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

3 

As discussed earlier, we gathered data from drivers on U.S. roadways during Friday daytime 

hours, and Friday nights and Saturday nights. As indicated in Table 1, we obtained oral fluid 

samples from drivers in each of those data collection periods (1,850 during daytime and 5,869 

during nighttime). We also collected blood samples during the nighttime data collection periods 

(3,276).

Table 1. Participating Drivers (Percentages in Parentheses) 

 2007 

 Daytime Nighttime Total 

Signaled to enter site 3,516 9,553 13,069 

Did not enter site 933 1,016 1,949 

Entered site 2,583 8,537 11,120 

Eligible 2,525 8,384 10,909 

Entered site and interviewed 2,174 (86.1%) † 6,920 (82.5%) † 9,094 (83.4%) †

Valid breath sample 2,254 (89.3%) † 7,159 (85.4%) † 9,413 (86.3%) †

Oral Fluid sample 1,850(73.3%) † 5,869 (70.0%) † 7,719 (70.7%) †

Blood sample NA 3,276 (39.1%) † NA 

AUD &/or Drug Questionnaire 1,889 (75.2%) † 5,983 (71.4%) † 7,882 (72.2%) †

NA (not applicable): Blood samples were not collected during daytime sessions. 

In this table, percentages are unweighted. 

† Percent of eligible 

Results 

In this study, analyses of the oral fluid and blood samples were conducted to identify the 

presence of some 75 drugs and metabolites, including illegal, prescription, and over-the-counter 

drugs. 

Comparison of overall drug prevalence by time of day (Table 2) indicates that 11 percent of 

drivers in the daytime sample were drug-positive. This level was significantly lower than the 

14.4 percent of nighttime drives who tested positive for drugs (p < .01).3 

Table 2. Drug Prevalence by Time of Day (Oral Fluid) 

Time of Day 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Daytime 1,850 11.0% 

Nighttime 5,869 14.4% 

To make the presentation of results most useful, we identified three broad categories of drugs: 

illegal, prescription, and over-the-counter. Because few over-the-counter drugs were found, the 

prescription and over-the-counter drugs were combined for many analyses and labeled 

 

3

 p < .01 indicates that under the null hypothesis, the probability of encountering this difference by chance is less 

than 1 percent; p < .05 indicates that the probability of encountering this difference by chance is less than 5 percent. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

4 

“Medications.” Additionally, some respondents tested positive for more than one category of 

drug. Thus, tables presenting drug categories present four mutually exclusive categories: Illegal; 

Medications; Illegal and Medications; and Negative. So as not to double count individual 

positive results, an individual’s result appears in only one of these categories. However, for 

example in Table 3, to determine the proportion of daytime drivers who tested positive for illegal 

drugs, one could sum the daytime values for the “Illegal” category (5.8%) and for the ” Illegal & 

Medications” category (0.5%) to arrive at a prevalence estimate of 6.3% of daytime drivers who 

were positive for at least one illegal drug. Detailed summaries of prevalence estimates for 

individual drugs appear in Tables 137-140 later in the report. As indicated in Table 3, 

comparison of drug categories by time of day revealed that, based on oral fluid analyses, almost 

6 percent of daytime drivers tested positive for drugs in the “Illegal” category (primarily 

marijuana and cocaine), as opposed to over 10 percent of nighttime drivers. There was a 

statistically significant difference between daytime and nighttime drivers (p < .01). 

Table 3. Drug Categories Distribution by Time of Day (Oral Fluid) 

Time of Day Drug Category 

N 

(Unweighted) 

% 

(Weighted) 

Illegal 125 5.8% 

Medications 107 4.8% 

Illegal & Medications 14 0.5% 

Negative 1,604 89.0% 

 

Daytime

Overall Daytime 1,850 100.0% 

Illegal 575 10.5% 

Medications 201 3.0% 

Illegal & Medications 60 0.9% 

Negative 5,033 85.6% 

 

Nighttime

Overall Nighttime 5,869 100.0% 

“Medications” includes prescription and over-the-counter drugs. 

Positive results in the “Medications” category, though not statistically significant, were found to 

be slightly higher among the daytime drivers (almost 5%) than nighttime drivers (3%). 

Additionally, some drivers tested positive for both “Illegal drugs and Medications” (0.5% of 

daytime drivers and 0.9% of nighttime drivers). This indicates that drugs were not detected in 

89.0 percent of daytime drivers and 85.6 percent of nighttime drivers. 

When oral fluid drug category findings were combined with BAC results we found that, in both 

the daytime and nighttime samples, the drug-positive drivers who were also alcohol-positive 

were more likely to be positive for “Illegal” drugs than “Medications” (Table 4). This was 

particularly true in the nighttime sample, in which 17.3 percent of drivers in the illegal category 

had BACs between zero and .08 grams per deciliter (g/dL) (compared to 6.3% in the 

“Medications” category) and 5.7 percent had BACs greater than .08 (compared to 1.2% in the 

“Medications” category) (p < .01). In the daytime sample, however, the differences were 

statistically non-significant (p value = .05). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

5 

Table 4. BAC Among Drug-Positive Drivers by Drug Category and Time of Day (Oral Fluid) 

 BAC (g/dL) 

Time of 

Day Drug Category 

N 

(Unweighted) Zero 

Between 

Zero and .08 .08+ 

 Illegal 125 97.1% 2.3% 0.6% 

Daytime Medications 107 99.6% 0.4% 0.0% 

 Illegal & Medications 14 98.3% 1.7% 0.0% 

 Negative 1,604 99.2% 0.6% 0.2% 

 Illegal 575 77.0% 17.3% 5.7% 

Nighttime Medications 199 92.5% 6.3% 1.2% 

 Illegal & Medications 60 81.4% 17.7% 0.9% 

 Negative 5,033 90.2% 8.1% 1.7% 

“Medications” includes prescription and over-the-counter drugs. 

In this table, percentages are weighted. 

In addition to the three drug categories, we also examined drug class (Table 5). The drug classes 

were antidepressants, marijuana, narcotic-analgesics, sedatives, stimulants, and other, plus a 

“more than one drug” class. To avoid double counting individual positive results, the classes 

were mutually exclusive. Thus, for example, since marijuana is both a class by itself and could 

appear in the “More than 1 class” cell as well (as could other classes of drugs) from this table 

one cannot arrive at an overall prevalence estimate for marijuana alone. However, detailed 

summaries of prevalence estimates for individual drugs appear in Tables 137-140 later in the 

report. In comparing prevalence of drug classes by time and region,4 we found that marijuana 

was generally the most common drug class across all the regions both in daytime (3.9%) and 

nighttime (6.1%) samples. Among the nighttime sample, drivers in the Midwest and Northeast 

regions were more likely to test positive for marijuana than daytime drivers (p < .05). In the 

South and West regions, however, there was little difference between daytime and nighttime 

drivers with respect to marijuana. For stimulants, a higher percentage of nighttime drivers in all 

regions tested positive than did daytime drivers. However, the difference was statistically 

significant only in the Midwest (p < .01) and West (p < .05). 

When one examines the “All” column of Table 5, one finds that, overall, sedatives were found in 

1.6 percent of daytime drivers and in 0.6 percent of nighttime drivers. Stimulants were found in 

1.6 percent of daytime drivers and in 3.2 percent of nighttime drivers. 

 

4

 Regions are defined by the NASS/GES system according to U.S. Census Regions (Midwest includes the West 

North Central and East North Central States, Northeast includes New England and Middle Atlantic States, South 

includes the West South Central, East South Central, and South Atlantic States, and West includes West and 

Mountain States. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

6 

Table 5. Drug Classes by Time of Day and Region (Oral Fluid) 

Time of 

Day Drug Class 

Midwest 

% 

Northeast 

% 

South 

% 

West 

% 

All 

% 

 N=546 N=379 N=472 N=453 N=1,850 

Antidepressants 0.4% 0.6% 0.5% 0.5% 0.5% 

Marijuana 3.4% 3.0% 5.5% 4.0% 3.9% 

Narcotic-Analgesics 2.7% 2.1% 1.3% 0.6% 1.6% 

Sedatives 1.9% 2.6% 2.1% 0.7% 1.6% 

Stimulants 0.8% 1.7% 2.2% 2.0% 1.6% 

Other 0.0% 1.3% 0.0% 0.0% 0.2% 

More than 1 Class 2.2% 1.0% 1.4% 1.2% 1.5% 

Overall Drug Positive Daytime 11.5% 12.5% 13.1% 8.9% 11.0% 

Daytime

Negative 88.5% 87.5% 86.9% 91.1% 89.0% 

 N=1,694 N=1,111 N=1,559 N=1,505 N=5,869 

Antidepressants 0.5% 0.2% 0.0% 0.1% 0.2% 

Marijuana 7.7% 7.6% 6.3% 4.1% 6.1% 

Narcotic-Analgesics 1.0% 2.8% 1.2% 1.8% 1.6% 

Sedatives 1.1% 0.2% 0.7% 0.4% 0.6% 

Stimulants 3.0% 2.3% 2.7% 4.0% 3.2% 

Other 0.2% 0.0% 0.1% 0.5% 0.3% 

More than 1 Class 1.6% 4.1% 2.9% 2.0% 2.3% 

Overall Drug Positive Nighttime 15.0% 17.3% 14.0% 12.9% 14.4% 

Nighttime

Negative 85.0% 82.7% 86.0% 87.1% 85.6% 

In this table, percentages are weighted. 

 “More than 1 Class” – Drivers testing positive for more than one drug class are counted only in this category.

Further, as indicated in Table 6, comparison of number of drug classes by time of day indicated 

that nighttime drivers (2.3%) were significantly more likely to test positive for more than one 

drug class than daytime drivers (1.5%) (p < .01). 

Table 6. Number and Distribution of Drug Classes by Time of Day (Oral Fluid) 

Time of Day 

Number of 

Drug Classes 

N 

 (Unweighted) 

% 

(Weighted) 

1 206 9.5% 

2+ 40 1.5% 

Negative 1,604 89.0% Daytime 

Overall Daytime 1,850 100.0% 

1 680 12.1% 

2+ 156 2.3% 

Negative 5,033 85.6% Nighttime 

Overall Nighttime 5,869 100.0% 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

7 

As mentioned earlier, 3,276 blood samples were obtained from nighttime drivers. As expected, 

the results of the blood analyses were quite close to those obtained by the nighttime driver oral 

fluid analyses. For example (Table 7), among nighttime drivers, 9.1 percent tested positive for 

“Illegal” drugs, 4 percent for “Medications,” and 0.7 percent for the combination of both “Illegal 

and Medications.” 

Table 7. Drug Categories Distribution (Blood) 

Drug Category 

N 

(Unweighted) 

% 

(Weighted) 

Illegal 267 9.1% 

Medications 169 4.0% 

Illegal & Medications 30 0.7% 

Negative 2,810 86.2% 

Overall 3,276 100.0% 

“Medications” includes prescription and over-the-counter drugs. 

Additionally, as indicated in Table 8, 28.3 percent of nighttime drivers testing positive for 

“Illegal” drugs in blood also tested positive for alcohol, as did 6.4 percent of drivers who tested 

positive for “Medications” and 23.2 percent of those testing positive for both “Illegal drugs and 

Medications.” 

Table 8. BAC Among Drug-Positive Drivers by Drug Category (Percentage by Row) (Blood) 

 BAC (g/dL) 

Drug Category 

N 

(Unweighted) Zero 

Between 

Zero and .08 .08+ 

Illegal 267 71.7% 20.4% 7.9% 

Medications 169 93.6% 4.9% 1.5% 

Illegal & Medications 30 76.8% 23.2% 0.0% 

 “Medications” includes prescription and over-the-counter drugs. 

In this table, percentages are weighted. 

As indicated in Table 6, some individuals tested positive for more than one drug. Thus, we also 

present the drug analysis results by individual drug where drug is the unit of analysis (Tables 

137-140). Those results indicate that the most prevalent drug, other than alcohol, was marijuana. 

The overall marijuana prevalence rate in oral fluid was 4.5 percent daytime and 7.7 percent 

nighttime. 

When we examined the analysis results of the combination of oral fluid and/or blood in the 

nighttime driver population, we found that the marijuana prevalence rate was 8.7 percent. The 

next most frequently encountered individual drug was cocaine, with a daytime oral fluid 

prevalence rate of 1.5 percent, and a nighttime rate of 3.9 percent. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

8 

Summary 

Overall, analyses of the oral fluid samples obtained indicated a drug use prevalence rate of 11 

percent for daytime drivers and 14.4 percent for nighttime drivers. This difference between day 

and night is statistically significant (p < .01). Among nighttime drivers providing blood samples, 

13.8 percent overall tested positive for at least one of the drugs in our panel. This includes all 

drugs for which we tested, whether illegal, prescription, or over-the-counter. Additionally, of the 

9.8 percent of drivers testing positive for “Illegal” drugs in blood, 28 percent, also tested positive 

for alcohol as did 6.4 percent who tested positive for “Medications” and 23.2 percent for those 

testing for both “Illegal drugs and Medications.” The most frequently encountered individual 

drug, other than alcohol, was marijuana. 

Again, it is important to emphasize that the results presented in this report are estimates of the 

prevalence of drug use among drivers. Further research is needed to determine the effect of drug 

prevalence on crash risk. This report provides detailed displays of the data discussed above. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

9 

Introduction 

This report presents prevalence estimates for drug-involved driving obtained from the 2007 

National Roadside Survey of alcohol- and drug-involved driving. Though national roadside 

surveys of alcohol-involved driving have been conducted on a decennial basis since the mid1970s, this is the first U.S. national roadside survey where biological measures of drugs other 

than alcohol were obtained. 

Background 

Forty years ago, when the Department of Transportation (DOT) was established, it was well 

understood that alcohol was an important factor in traffic crashes. In 1968, a new agency that 

was to become the National Highway Traffic Safety Administration (NHTSA) delivered its 

Report to the Congress on Alcohol and Highway Safety, pointing to the need for improved data 

on drinking and driving (USDOT, 1968). This need led to the establishment of incentives for 

States to conduct blood alcohol concentration (BAC) tests on all fatally injured drivers and 

pedestrians, and eventually to the establishment of the Fatality Analysis Reporting System5

(FARS) in 1975. Initially, this data file was limited by the low level of testing for alcohol by the 

States, but since 1982, through the use of an imputation system and increased testing by states, it 

has provided a reliable means of assessing the Nation’s progress in reducing crashes in which 

drivers have been drinking. It is important to note, however, that FARS provides very limited 

information related to drugs. While States routinely test drivers involved in fatal vehicle crashes 

for alcohol, only a few also routinely test for other drugs. According to the Centers for Disease 

Control and Prevention, less than half of the fatalities in the 2005 FARS had drug test results 

available (CDC, 2006). In our review of the FARS data, we identified a lack of information 

related to drug use. 

In addition to FARS, the national roadside survey (NRS) series estimates the prevalence of 

drinking and driving on weekends in the 48 contiguous States and assesses changes in prevalence 

over time. The first NRS was conducted in 1973 (Wolfe, 1974), the second in 1986 (Lund & 

Wolfe, 1991), and the third in 1996 (Voas, Wells, Lestina, Williams, & Greene, 1998). Each of 

these surveys included a brief verbal survey and a breath sample to determine BAC. Together, 

the first three national surveys and FARS (1995) document reductions in the number of drinking 

drivers on U.S. roadways and alcohol-related fatalities over three decades. The fourth NRS, 

conducted in 2007, followed the general methodology of the three prior surveys in obtaining 

BACs to enable comparison with the earlier surveys, but also incorporated several new features. 

These included questionnaires on drug and alcohol use disorders, and biological sampling of oral 

fluid and blood to determine the extent of the presence of drugs other than alcohol (i.e., illegal, 

prescription, and over-the-counter) among drivers. 

In 2005, NHTSA conducted a pilot study as a precursor to this full decennial 2007 NRS (Lacey 

et al., 2007). The primary objective of the pilot study was to determine whether it was feasible to 

collect data for drugs other than alcohol through oral fluid and blood samples. The pilot study 

consisted of six rounds of nighttime data collection, with over 800 drivers participating in the 

survey. Approximately 78 percent of the drivers participating in the survey agreed to provide an 

 

5

 FARS was originally called the Fatal Accident Reporting System. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

10 

oral fluid sample, and almost 50 percent of the drivers participating in the survey provided blood 

samples. The pilot study showed that it was clearly feasible to conduct a survey that included 

drugs other than alcohol. Such data are essential to developing more precise estimates of the 

presence of alcohol and other drugs in drivers and for estimating the prevalence of alcohol- and 

drug-involved driving. 

Prevalence of Drug-Involved Driving 

In their review of the research literature, Kelly, Darke, and Ross (2004) cite the 2001 National 

Household Survey to report that 4 percent of U.S. residents reported driving while under the 

influence of drugs in the preceding 12 months. These data, based on self-report, did not 

distinguish between legal and illegal drugs. Using data collected in Tennessee in December 

1986, Lund, Preusser, Blomberg and Williams (1988) studied a sample of truck drivers to report 

prevalence of marijuana (15%); cocaine (2%); prescription stimulants (5%); and nonprescription 

stimulants (12%) among the drivers. According to a literature review by Jones, Shinar, and 

Walsh (2003), the Lund et al. study (1988) was at that time the only U.S. study that had 

performed chemical tests of drivers stopped at a roadside location. 

With respect to prescription drugs, Jones et al. (2003) reported that benzodiazepines 

(tranquilizers) were found in four percent of non-crash-involved drivers. De Gier (2006) 

reviewed the literature and reported that benzodiazepines were more commonly found in middleaged to older drivers, “presumably due to the high rates of benzodiazepine prescriptions among 

these age groups.” Neutel (1998) estimated a lower crash risk for older persons (OR = 2.8) after 

benzodiazepine use than younger persons (OR = 3.2). 

Impact of Drugs on Driving Skills 

Laboratory Studies 

A number of laboratory studies have been conducted on the impact of both legal and illegal 

drugs on driving-related skills. Still, results from these experimental studies are not 

straightforward and are sometimes contradictory. One confounding factor is that different drugs 

have different effects on driving-related skills, with the thresholds at which those different 

effects occur varying as a function of the measure used (Shinar, 2006). Additionally, Shinar 

found that because of the large individual variation in human response to drug consumption, 

attempts to define a “norm” for the behavioral response to drugs is difficult. 

Some studies have found that drugs that stimulate the central nervous system, (e.g., 

amphetamines, cocaine, caffeine) sometimes may improve laboratory driving performance 

(Ward, Kelly, Foltin, & Fischman, 1997; Burns, 1993; Higgins et al., 1990; Hurst, 1976). 

However, in the Jones et al. (2003) literature review, it is reported that amphetamines are not 

usually associated with easily observable behavioral impairments. 

There is considerable evidence from laboratory studies that cannabis (marijuana) impairs 

reaction time, attention, tracking, hand-eye coordination, and concentration, although not all of 

these impairments were equally detected by all studies (Couper & Logan, 2004a; Heishman, 

Stitzer, & Yingling, 1989; Gieringer, 1988; Moskowitz, 1985). In reviewing the literature on 

marijuana, Smiley (1998) concluded that marijuana impairs performance in divided attention 

tasks (i.e., a poorer performance on subsidiary tasks). Jones et al. (2003) adds that Smiley’s 

finding is relevant to the multitasking essence of driving, in particular by making marijuana-
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

11 

impaired drivers perhaps less able to handle unexpected events. Interestingly, there is also 

evidence showing that, unlike alcohol, marijuana enhances rather than mitigates the individual’s 

perception of impairment (Lamers & Ramaekers, 1999; Robbe & O'Hanlon, 1993; Perez-Reyes, 

Hicks, Bumberry, Jeffcoat, & Cook, 1988). Robbe and O'Hanlon (1993) reported that in 

laboratory conditions, drivers under the influence of marijuana were aware of their impairment, 

which led them to decrease speed, avoid passing other vehicles, and reduce other risk-taking 

behaviors. Such was not the case with alcohol; for the authors reported that alcohol-impaired 

drivers were generally not aware of impairment, and therefore did not adjust their driving 

accordingly. 

There is laboratory evidence that benzodiazepines impair some driving skills (Drummer, 2002). 

However, there are some contradictory results. Mathijssen et al. (2002) reported on a casecontrol study conducted in the Netherlands that found there is an increased risk for 

benzodiazepine and alcohol use together, but no increased risk for benzodiazepine use alone. 

Additionally, there is evidence that the impairing effects of benzodiazepine might be 

circumscribed to the first days of benzodiazepine use, before tolerance develops (Lucki, Rickels, 

& Geller, 1985) leading some to conclude that the extent to which benzodiazepines increase 

crash risk has to be balanced against the health benefits for those taking these drugs for 

medicinal purposes (Beirness, Simpson, & Williams, 2006). 

Laboratory reports are not necessarily the best indicators of the impact of drugs on driving skills. 

As Beirness et al. (2006, pages 16-17) stated: “an impairment or skill enhancement identified in 

a laboratory test may not show up on the road because the drugs may lead to other changes in 

driver behavior. Additionally, laboratory tests can address the effects of drugs only on skills, not 

judgment, and the latter may be as important when it comes to driving. Thus even if drugs are 

found to affect driving skills in laboratory tests, actual crash risk may or may not be affected.” 

Field Data 

Data from drivers apprehended for impaired driving have been used to estimate the prevalence of 

drug use. Jones et al. (2003) reviewed the literature on drug involvement among arrested drivers 

and reported a variety of drug prevalence levels based on the location and the population under 

study. White et al. (1981) reported the following prevalence of drugs among drivers arrested for 

impaired driving in California in the 1970s with BACs lower than .10 g/dL: sedative/hypnotic 

(30 to 47%); phencyclidine or PCP (79%); and morphine (62%). In contrast, Polkis, Maginn, and 

Barr (1987) reported the following prevalence rates among drivers arrested in St. Louis, 

Missouri, in the 1980s: phencyclidine or PCP (47%); marijuana (47%); benzodiazepines (22%); 

barbiturates (15%); opiates (11%); and cocaine (9%). Walsh et al. (2000) reported that marijuana 

and cocaine were the primary drugs detected (19% and 16%, respectively) among arrested 

drivers in Tampa, Florida, with narcotics and amphetamines found in less than 1 percent of the 

drivers. Thus, as studies of drug-use patterns in the United States have shown, the types of 

substances consumed vary across locations and time, making it difficult to characterize the drug 

involvement of drivers. 

As part of the Drug Evaluation and Classification (DEC) Program, trained drug recognition 

experts are used to determine drug usage by looking for relevant signs and symptoms. Preusser, 

Ulmer, and Preusser (1992) evaluated DEC programs in Arizona, California, Colorado, New 

York, and Texas from 1986 to 1991 reported that about 1 to 3 percent of the drivers arrested for 

driving while intoxicated (DWI) were classified as drug-impaired by Drug Recognition Experts 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

12 

trained in the DEC Program. The most prevalent substances found were marijuana (42%), 

stimulants (36%), depressants (16%), narcotic analgesics (13%), and PCP (5%). As Jones et al. 

(2003) pointed out, these estimates apply only to the restricted group of driving-under-theinfluence-of-drugs (DUID) suspects that were evaluated by officers who participated in the DEC 

program, rather than to all drivers arrested for DWI or all drivers on the road. 

Other studies have been conducted using crash data to estimate the prevalence of drugs among 

injured drivers and their role in crashes. Terhune et al. (1992) used a responsibility-analysis 

approach6

 in studying fatally injured drivers and reported no increase in crash risk due to 

marijuana or cocaine use alone, although multiple drug use could be associated with increased 

responsibility. They also reported that “drivers with alcohol in their systems had the highest 

crash responsibility rates” and “an alcohol-drug combined impairment effect was suggested by 

the responsibility analysis” (pg. ix). Leveille et al. (1994) used a small matched-case control 

study design to study crash risk among drivers aged 65 or older in Seattle, Washington. The 

authors did not find an association between crash risk and benzodiazepine or sedating 

antihistamines among this group, although they acknowledged that the sample size (234 drivers) 

might have been too small for significance. Ray, Fought, and Decker (1992) also studied crash 

risk for drivers aged 65 years or older using data from the Tennessee Medicaid program. With 

this larger sample (16,262 drivers), they found an association between presence of 

benzodiazepines or tricyclic antidepressants and crash risk. However, they did not find a 

correlation for people taking oral opioid analgesics. Other studies of drug over-involvement in 

crashes report contradictory results (e.g., Hemmelgarn, Suissa, Huang, Boivin, & Pinard, 1997). 

These results should be considered cautiously due to data limitations such as small sample size. 

In summary, Jones et al. (2003, pp. 85-86) stated: “The role of drugs as a causal factor in traffic 

crashes involving drug-positive drivers is still not understood. Drug risk factors are still not 

known with acceptable precision, with some evidence suggesting little or no increase in crash 

risk at drug levels being detected by current chemical test procedures. Further, current research 

does not enable one to predict whether a driver testing positive for a drug, even at some 

measured level of concentration, was actually impaired by that drug at the time of crash. This is 

in sharp contrast to alcohol where BAC measurements can provide a good estimate of 

impairment.”

Jones et al. (2003, p. 86) also stated: “Another complicating factor is the role of drugs taken in 

combination with alcohol. For many drugs, a drug in combination with alcohol accounts for a 

significant percentage of the occurrences of that drug in crash victims. Waller et al. (1995) 

found that roughly one-half of the occurrences of drivers positive for marijuana, cocaine, and / 

or opiates had elevated BACs, and that the crashes of drivers testing positive for drugs alone 

were very similar to the crashes of drivers testing negative for both alcohol and drugs. This adds 

further doubts about the role of drugs in the impairment of crash-involved drivers, and suggests 

that it may be much smaller than had been suspected.” 

 

6

 Responsibility-analysis was used to suggest which drugs contributed to the occurrence of the crashes. This method 

involves examining crash reports which have no indication of driver drug use, and rating each driver’s crash 

responsibility. If proportionately more drug-present drivers are judged responsible than are those free of drugs, this 

is considered evidence of drug impairment effects. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

13 

Challenges in Measurement and Today’s Drug Testing 

Opportunities 

According to the review of the drug impaired literature conducted by Jones et al. (2003), blood is 

usually the “gold standard” for linking drug concentration to behavioral impairment. However, 

the collection of other types of biological fluids (e.g., sweat, oral fluid, urine) is less invasive and 

easier to collect in both field studies and law enforcement operations, and thus, oral fluid has 

emerged as a valid alternative to blood collection for field use. Oral fluids normally contain the 

parent drug substance rather than drug metabolites that are present in urine. Additionally, Jones 

et al. (2003) concluded that collection of oral fluid is generally considered less invasive than 

either blood or urine, and “could be an excellent matrix to tie recent drug use with behavioral 

impairment.” 

In some applications, oral fluid samples are collected and then subjected to a screening analysis 

in the field or at the police station to develop a basis for more definitive collection of and 

laboratory analysis of urine or blood. In the application used for this study, the oral fluid sample 

was collected and then sent to a laboratory for a more refined enzyme-linked immunosorbent 

assay (ELISA) screening followed by a confirmatory analysis by Liquid ChromatographyTandem Mass Spectrometry (LC/MS-MS) or Gas Chromatography/Mass Spectrometry 

(GC/MS). 

In a recent study conducted by Cone et al. (2002), oral fluid testing of 77,218 subjects in private 

industry showed a 5 percent positive rate for any of the five Substance Abuse and Mental Health 

Services Administration drug categories (marijuana, cocaine, opiates, phencyclidine, and 

amphetamines). The pattern and frequency of drug positives was remarkably similar to urine 

drug prevalence rates in the general workplace from other surveys (Cone et al., 2002). Further, in 

a study of 180 drivers given blood, urine, and oral fluid tests which were analyzed using 

quantitative Gas Chromatography/Mass Spectrometry (GC/MS), the positive predictive value of 

oral fluids was 98 percent for amphetamines, 92 percent for cocaine, and 90 percent for 

cannabinoids (Samyn et al., 2002). 

However, in an analysis of blood, urine, saliva, and sweat from 198 injured drivers admitted to a 

hospital, saliva detected only 14 positives for cannabinoids, while 22 positives were detected in 

the urine (Klintz et al. 2000). According to the study authors, the amount of matrix (body fluid) 

collected in saliva appears to be smaller when compared to urine, and the levels of drugs are 

typically higher in urine than in saliva. In a study of saliva and sweat, Samyn and van Haeren 

(2000) concluded that saliva should be considered a useful analytical matrix for the detection of 

recent drug use when analyzed using GC/MS. This finding indicates oral fluid testing would be 

desirable in the roadside testing of drivers. 

Yacoubian et al. (2001) tested 114 adult arrestees using saliva and urine and concluded that 

saliva testing may have certain advantages over urine testing for drugs, including (1) ease of 

sample collection, (2) subject preference for giving saliva over urine, (3) less vulnerability of 

adulteration in saliva, (4) little concern for subjects producing an adequate sample with saliva, 

and (5) saliva storage is easier than urine. The authors found a sensitivity of 100 percent and a 

specificity7

 of 99 percent for cocaine in saliva and a sensitivity of 88 percent and specificity of 

 

7 Sensitivity: Sensitivity is the ability of a test to measure what it purports to measure or in this case the ability of 

the oral fluid tests to correctly identify active drug users. It is operationalized as a proportion represented by the true 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

14 

100 percent for heroin. However, saliva results only had a sensitivity of five percent for 

marijuana, likely reflecting only detection of very recent smoking, as marijuana does not migrate 

from the blood supply to the oral fluid. Thus, some positives may indicate residual marijuana 

remaining in the mouth after ingestion. This may well be a positive factor for this study in that, 

when marijuana is detected in saliva, it is more likely to be in its active phase in the body rather 

than simply evidence the marijuana has been consumed during a “look-back” period that could 

be as long as two weeks, and may no longer have a potential impairing effect. 

Hold et al. (1999) conducted a review of the literature concerning using oral fluid for drug 

testing; the review included 135 references and provided guidelines for techniques for collecting 

and measuring drugs in saliva. In an earlier review of drug use evidence found in oral fluid, 

Schramm et al. (1992) concluded that initial studies with cocaine and phencyclidine or PCP 

suggested a correlation between oral fluid and blood concentration, but that tetrahydrocannabinol 

(THC) does not appear to be transferred from blood to saliva. Recent marijuana smoking, 

however, can be detected in saliva from the buccal cavity.8

With regard to oral fluid and BAC, Bates et al. (1993) found a high correlation between saliva 

strips and breath tester results for alcohol (r = .89-.90). Blood sample analyses, however, still 

remain the “gold standard” measurement of drugs in the human body because evidence 

supporting accuracy is best established for that approach. 

Project Objectives 

New to the 2007 National Roadside Survey was the collection of biological samples that could 

be used to determine the extent of the presence of drugs other than alcohol in the nighttime 

driving population. These additional data are essential to estimating the national progress in 

reducing the prevalence of alcohol- and drug-involved driving. 

The objective of this report is to present the first U.S. national prevalence estimates of druginvolved driving. The first report stemming from this study described the methods used in the 

sampling, data collection, and biological specimen analysis portions of the 2007 NRS (Lacey et 

al, 2009a). The second report describes the study’s analytic approach and summarizes the 

alcohol data; we place the set of descriptive estimates of alcohol use within the context of 

societal trends by comparing these measures with similar ones from the prior surveys over the 

 positives (i.e., those who are drug positive and actually test positive) divided by all persons who are drug positive 

(i.e., those who are positive and test positive [i.e., true positives] plus those who are positive and test negative [false 

negatives]). The formula for sensitivity is Sn = TP / (TP + FN) where TP and FN are the number of true positive and 

false negative results, respectively. Sensitivity can also be thought of as 1 minus the false negative rate. Notice that 

the denominator for sensitivity is the number of drug positive persons. 

 Specificity: Specificity is the ability of a test to correctly identify non-cases of disease or in this case the ability of 

the oral fluid tests to correctly identify non-drug users. It is operationalized as a proportion represented by the true 

negatives (i.e., those who are drug negative and test negative) divided by all persons who are drug negative (i.e., 

those who are negative and test negative [true negatives] plus those who are negative, but falsely test positive [false 

positives]). The formula for specificity is Sp = TN / (TN + FP) where TN and FP are the number of true negative 

and false positive results, respectively. Specificity can be thought of as 1 minus the false-positive rate. Notice that 

the denominator for specificity is the number of nondrug users. 

8

 The buccal cavity includes that part of the mouth bounded anteriorly and laterally by the lips and the cheeks, 

posteriorly and medially by the teeth and/or gums, and above and below by the reflections of the mucosa from the 

lips and cheeks to the gums.
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

15 

last four decades. These trend analyses enable detection of changes in our population's rates and 

degree of alcohol-involved driving over time (Lacey et al, 2009b). The current report provides 

insight into the use of drugs other than alcohol (illegal, prescription, and over the counter) in the 

driving population and will provide a baseline for future studies to assess trends and changes. 

The report will first present a summary of the methods and procedures used in survey sampling 

and biological sampling. This is followed by a description of the drugs selected for analysis, and 

then, a description of the actual drug-collection instruments and how they were administered. 

The results of our analyses are divided into three sections. The first presents the analyses of the 

oral fluid results, with BAC measurement obtained through breath tests. These data include both 

daytime and nighttime drivers. The second section will report the results of the blood analysis, 

again with the BAC measurements from breath tests. In both of these sections, we also contrast 

the results obtained from the biological specimens with drivers’ self-report drug use. 

Additionally, we present drug prevalence estimates for nighttime weekend drivers based on the 

combination of results of analyses of both oral fluid and blood combined. Finally, we discuss the 

implications of these analyses in terms of estimating the prevalence of drug use among Friday 

daytime drivers and weekend nighttime drivers. Additional tables with further blood results are 

included in Appendix A. These analyses include results of self-reported drug use by drug type, 

safety observation measures (seatbelt, helmet use, etc.), as well as the results on items relating to 

interaction with the criminal justice and treatment systems. The presence of drugs in these 

drivers does not necessarily imply that they are impaired and at greater risk of crash 

involvement. Indication of impairment and increased risk will be addressed in an upcoming 

study of the potential contribution of drugs to crash risk. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

16 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

17 

Methods 

This section of the report briefly summarizes the methodology used in conducting the 2007 NRS, 

with special emphasis on sampling procedures. A separate Methodology Report (Lacey et al., 

2009a) provides detailed descriptions of the multiple components of the data collection process. 

Survey Sampling Procedures 

This section presents an abridged description of the sampling approach we followed in 

conducting the 2007 NRS. Because it is infeasible to conduct surveys on all the roads in the 

United States, we constructed a sampling system for the 2007 NRS that represented the whole 

Nation but required interviewing only a practical portion of the almost 203 million drivers on 

U.S. roads (FHWA, 2006). As in the three prior surveys, the area covered in this study was 

limited to the 48 contiguous States. 

For practicality, we limited locations to roadways where surveys could be performed safely and 

with sufficient traffic to recruit the number of participants required for valid estimates of the 

national prevalence of drinking and drug involved-drivers, as did prior NRS studies. 

The past three national surveys provided information on private four-wheel vehicle operators at 

representative, then randomly selected, locations during weekend, nighttime periods when 

drinking and driving is most prevalent. The 2007 NRS covered the same time periods and added 

two Friday daytime periods. As in the three earlier surveys, the 2007 NRS excluded commercial 

vehicles but, unlike previous practice, included motorcycles. 

The 2007 NRS followed the practice of the 1973, 1986, and 1996 national surveys by using a 

multistage sampling system that represented the drivers at risk for crash involvement in the 48 

contiguous States. In this process, the initial sample structure was taken from NHTSA’s National 

Automotive Sampling System/General Estimates System (NASS/GES) (NHTSA, 1995), which 

was constructed to provide a basis for making nationally representative estimates of highway 

crashes. The four steps included: 

1. Selecting the primary sampling units (PSUs), which are cities, large counties, or groups 

of counties from within four regions of the United States and three levels of population 

density. 

2. Randomly selecting 30 specific square-mile-grid areas within each PSU, and randomly 

numbering them to form an order of priority from among the total of all the square mile 

sectors comprising the PSU area. Then we attempted to recruit the cooperation of local 

law enforcement agencies that had jurisdiction over the selected grids. One law 

enforcement agency often would cover several of the selected square mile areas. 

3. Identifying appropriate survey sites within the square-mile-grid areas. Appropriate sites 

had a safe area large enough to accommodate the survey operation and had sufficient 

traffic flow to generate an adequate number of subjects. In some cases, more than one 

such location was available within a square mile grid. In this case, the survey manager 

exercised her/his judgment to select the optimal location for safe data collection. This 

resulted in selection of five data collection or survey sites within each PSU. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

18 

4. Selecting at random drivers to be interviewed from the traffic passing by the survey site. 

The total number of eligible vehicles was counted to determine the proportion of the 

traffic passing by each survey site that was sampled. 

These sampling procedures were followed to ensure that the probability of selecting a PSU, a 

survey location within the PSU, and a driver at a survey location was known at each of the 

sample design stages. Knowing these probabilities permitted the computation of the probability 

that a given driver would be interviewed in the survey. This was done by multiplying the 

sampling probabilities at each of the four steps to obtain the final overall probability of being 

sampled. The weight given to each case in the final totals (sampling weight) was computed as 

the inverse of the sampling probability. This statistical procedure accounts for differences among 

PSUs in the size of the driver population. In other words, although we sampled approximately 

the same number of drivers at each PSU, the actual number of individuals driving at each 

sampling site was not uniform. To make the sample of drivers at each site representative of the 

actual number of drivers, we applied the above-described weights. As a result, drivers 

interviewed at sites with a relatively heavy traffic flow (i.e., a relatively large pool of actual 

drivers) carry a larger weight than drivers sampled from sites with less traffic loads. This ensured 

that the basic requirement of sampling theory—that every driver has an equal chance of being 

interviewed—was met by adjusting for the biases inherent in the selection of locations within the 

sampling frame. 

The major barrier to carrying out this staged sampling system was obtaining law enforcement 

support for the survey. In some localities, city attorneys or law enforcement leadership with 

concerns such as potential liability and scare resources declined to participate. In these cases, 

substitution PSUs were obtained. Although this process was time-consuming, similar difficulties 

had also been experienced in all three previous NRS studies. Replacement PSUs were chosen 

from within the same GES geographic region9

 and the same GES PSU type (city, large suburban 

area, all others) as the unavailable PSU. For more information on PSU replacement, see Lacey et 

al. (2009a). The 60 PSUs used in the 2007 NRS are shown in Figure 1. 

 

9

 GES defines four geographic strata. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

19 

Figure 1. Map of Sixty 2007 National Roadside Survey Sites 

As mentioned, the roadside survey procedures used in the 2007 NRS followed, as closely as 

possible, those used in the previous three surveys (see Lacey et al., 2009a; Lestina et al., 1999). 

However, the 2007 NRS departed from the earlier surveys in several important ways. The earlier 

surveys included only a brief questionnaire and a breath test that generally required less than 5 

minutes of a participant’s time. The 2007 NRS included a more extensive set of questions (base 

survey, a drug questionnaire, questions about interaction with the criminal justice and treatment 

systems, an alcohol-use disorder and a drug-use disorder survey). The 2007 survey protocol also 

attempted to collect two biological samples (oral fluid and blood) from participants, as well as a 

breath test. Data collection for the earlier surveys was conducted by three teams of three 

interviewers; the 2007 NRS consisted of 6 teams of 10 to 12 members. The earlier surveys were 

conducted at 24 PSUs, whereas the 2007 survey was conducted at 60 PSUs. This increase in the 

number of PSUs allowed us to maximize the use of all possible PSUs defined by the NASS/GES 

and increase the representativeness of the sample. The earlier surveys had four 2-hour data 

collection periods on weekend nights; the 2007 survey added a 2-hour data collection period 

during the daytime on Fridays, for a total of five 2-hour survey periods during the weekend. 

Finally, the number of participants in the 2007 survey was about three times as many as in the 

1973 study. 

PIRE employed and trained six specialized teams of interviewers from both the east and west 

coasts of the United States. All staff was trained during the summer of 2007. Surveys began the 

weekend of July 20 and 21, 2007, and concluded 20 weeks later on December 1, 2007. As in the 

three previous NRS studies, nighttime surveys were conducted between 10 p.m. and midnight, 

and between 1 a.m. and 3 a.m. on both Friday and Saturday. For the 2007 survey, a 2-hour 

Friday daytime data collection period was added, either between 9:30 a.m. and 11:30 a.m. or 

between 1:30 p.m. and 3:30 p.m. The daytime data collection period was randomly selected for 

each PSU. The daytime periods were added to determine the extent of alcohol- and drug-
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

20 

involved driving during the day and whether the number of drivers using drugs and the types of 

drugs used differed between day and night. Each component used in the roadside survey is 

thoroughly described in the Methodology Report (Lacey et al., 2009a). 

Preparation for the 2007 NRS Survey 

The size and complexity of the 2007 NRS required extensive preparation that NHTSA began 

years before the actual survey was initiated, including a pilot test of survey procedures (Lacey, 

Kelley-Baker, Furr-Holden, Voas, Brainard, & Moore, 2007). The preparation activities—

selection and testing of equipment for collecting biological samples; recording and organizing 

the self-report and observational data at the roadside; recruiting and training of survey staff; 

pretesting of survey procedures; developing procedures for protection of survey respondents and 

the public—are fully described in the Methodology Report (Lacey et al., 2009a). Only a brief 

overview of this work is described here. 

Survey equipment: Interviewers recorded the responses to the traditional NRS interview on a 

handheld, portable digital assistant (PDA). Through a special program developed for the 2007 

NRS, the PDA provided a means of prompting the interviewer through each step of the data 

collection process. 

As part of the program, to protect survey participants and the public, it was important to know 

the extent of the drivers’ drinking. To this end, a passive alcohol sensor (PAS), attached to the 

PDA with VelcroTM, was used to collect mixed expired air from approximately 6 inches in front 

of the driver’s face (we used the PAS Vr.TM manufactured by PAS International, Inc. of 

Fredericksburg, Virginia). This small handheld unit was used because it was less obvious and 

intimidating than the larger flashlight-based passive sensors. We researched three available styles 

of PAS models: (1) the handheld unit that was used in the pilot study; (2) the flashlight PAS; and 

(3) a clipboard device with an alcohol sensor built into one corner. We tested the devices for 

accuracy, ease of use, and reliability and found that the PAS Vr.TM was best suited to the needs 

of this study. The PAS unit can detect alcohol in emitted breath around the face (Kiger, Lestina, 

& Lund, 1993). The PAS was held within 6 inches of the participant’s face, and when the subject 

spoke, the interviewer activated the small electrical pump, which pulled in the exhaled breath 

from the participant and produced an estimate of the participant’s breath alcohol level. 

Data collection: To compare results from the 2007 survey to prior surveys, a strong effort was 

made to follow the same data collection protocol employed in the three prior NRS studies, 

despite the addition of a large number of questions and new biological specimen collections 

following the traditional questionnaire and breath test. As described in the Methodology Report 

(Lacey et al., 2009a), we placed the traditional NRS interview and breath-test collection before 

the new NRS questions and the specimen collections. We believed that by structuring data 

collection in this way, the additions to the basic survey would not affect our ability to compare 

the responses to the basic survey with responses from the three earlier surveys. Nevertheless, the 

2007 NRS experienced a somewhat larger refusal rate than the 1996 NRS (see Table 9). 

To determine whether the 2007 survey procedure accounted for producing the lower response 

rate, we conducted a replica of the 1996 NRS procedure in one of our 2007 sites (Knox County, 

Tennessee). The simpler protocol followed that used in the 1996 and earlier surveys, collecting 

the traditional interview and a breath sample only. About 16 percent of all drivers signaled to 

stop by the officer during this “replica survey” failed to stop and/or enter the site. This is similar 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

21 

to the 15 percent that failed to stop (when the police signaled) in the 2007 NRS study. Among 

those who entered the research bay and were eligible for the survey, the proportion of refusals in 

the replica survey was similar to the full 2007 NRS (16.3% and 17.5%, respectively). Thus, it 

appears that the lower response rate in the 2007 NRS reflects a change in the driving public’s 

willingness to be interviewed, rather than an effect of the more elaborate survey procedures 

implemented in 2007. 

Table 9. Comparison of Number of Nighttime Participants by Year in the 

National Roadside Surveys 

 1973 1986 1996 2007 

Signaled to enter site Not reported 3,260 6,480 9,553

Did not enter site Not reported 217 182 1,016 

Entered site 3,698 3,043 6,298 8,537 

Eligible for survey Not reported Not reported Not reported 8,384†

Entered site and interviewed 3,353 (90.7%) 2,971 (97.6%) 6,045 (96.0%) 6,920 (82.5%)††

Valid breath sample††† 3,192 (86.3%) 2,850 (93.7%) 6,028 (95.7%) 7,159 (85.4%)††

† Commercial vehicles not eligible. 

†† Because previous surveys did not inform about the eligibility of the drivers, percentages for the years 1973, 1986, 

and 1996 are based on drivers who stopped and entered the site. Percentages for 2007 are based on drivers who not 

only were stopped and entered site, but also were eligible for the survey (i.e., noncommercial drivers, drivers aged 16 

and older, and not constrained by language barriers). Percentages are based on nighttime drivers. 

††† Some drivers provided breath samples but declined to be interviewed. 

In this table, percentages are unweighted. 

The basic procedure in the 2007 NRS, as well as in the prior three surveys, was for the law 

enforcement officer working with the survey team to direct the potential respondent into the 

survey site without speaking to the driver. Once in the site, the driver was directed into a 

research bay and was approached by an interviewer and recruited to participate in the interview. 

Prospective participants were informed that they had done nothing wrong and that the interview 

concerned traffic safety and was anonymous. A PAS reading was also taken at this point. If the 

individual agreed to participate, the interviewer asked the 22 questions on the traditional NRS 

protocol and requested a breath sample. Only after the completion of the standard NRS 

procedure did the additional data collection for the 2007 NRS begin. A detailed description of 

the survey procedures is provided in the Methodology Report (Lacey et al., 2009a). 

As indicated in Table 10, which presents response patterns for both the daytime and nighttime 

data collection periods, over 13,000 vehicles were selected to participate in the 2007 NRS; of 

these, 10,909 entered the data collection site and the drivers were determined to be eligible for 

survey participation (for example, commercial vehicles such as pizza delivery vehicles, drivers 

under the age of 16, and drivers who could not communicate with us either in English or Spanish 

were not eligible to participate). Eighty-three percent of eligible drivers participated in the 

survey, and because some of those that refused the survey did agree to provide a breath sample, 

BACs from the PBTs were available on 86 percent of the eligible drivers. Among eligible 

drivers, 71 percent provided an oral fluid sample, 72 percent completed a drug questionnaire 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

22 

and/or the AUD questionnaire, and 39 percent of eligible nighttime drivers provided a blood 

sample.10 

Table 10. Participating Drivers (Percentages in Parentheses) 

 2007 

 Daytime Nighttime Total 

Signaled to enter site 3,516 9,553 13,069 

Did not enter site 933 1,016 1,949 

Entered site 2,583 8,537 11,120 

Eligible 2,525 8,384 10,909 

Entered site and interviewed 2,174 (86.1%)

† 6,920 (82.5%)† 9,094 (83.4%)†

Valid breath sample 2,254 (89.3%)

† 7,159 (85.4%)† 9,413 (86.3%)†

Oral Fluid sample 1,850(73.3%)

† 5,869 (70.0%)† 7,719 (70.7%)†

Blood sample NA 3,276 (39.1%)

† NA 

AUD &/or Drug Questionnaire 1,889 (75.2%)

† 5,983 (71.4%)† 7,882 (72.2%)†

NA (not applicable): Blood samples were not collected during daytime sessions. 

In this table, percentages are unweighted. 

† Percent of eligible. 

To prevent impaired drivers from continuing to drive, a special “Impaired Driver Protocol” was 

developed to ensure the safety of both the drivers and the public. Impairment was determined by 

the interviewer’s observation of the driver’s behavior and by the use of a PAS. If there was any 

sign of possible impairment, the interviewer signaled the survey manager who administered a 

breath test with a preliminary breath test (PBT) device that displayed the actual BAC. If the 

driver’s BAC was .05 g/dL (grams per deciliter) or higher, the survey manager provided the 

participant with several options for getting home without driving.11 This system has been 

successful in preventing identified impaired drivers from returning to the road where they could 

be a danger to themselves or others. A full description of the Impaired Driver Protocol is 

provided in Appendix E of the Methodology Report (Lacey et al., 2009a). 

A significant concern for all four NRS studies was that high BAC drivers might be less likely to 

agree to participate, resulting in an underestimate of the number of risky drinking drivers on the 

road. Data from the 1996 NRS and from relative risk studies, such as that of Blomberg, Peck, 

Moskowitz, Burns, and Fiorentino (2001, p. 117), have suggested that drivers who refuse the 

breath test are likely to have higher BACs than those who agree to participate. This was 

corrected somewhat in the 1996 and 2007 NRS studies by using the PAS data collected as part of 

the consent process. During the data collection process, a PAS was used when the driver was 

first approached to participate in the survey. The PAS provides a nine-unit estimate of what a 

true BAC measure collected by the PBT device would be. We correlated the PAS and other 

measures (specifically, gender and time of night) to impute the BACs of drivers who entered the 

site but refused to provide a breath sample. Thus, the actual BACs collected in both the 1996 and 

the 2007 NRS studies were corrected for nonparticipating drivers. 

 

10 Typically, only drivers who had completed the oral fluid step provided a blood sample. 

11 Our threshold of .05 g/dL was more conservative than the legal per se limit of .08 g/dL. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

23 

Driver Conversion 

As presented in the Methodology Report (Lacey et al., 2009a), there were 444 attempts to 

convert drivers who had initially declined to participate in our study (i.e., to change their minds 

and provide us with at least a breath sample). This was done to develop an understanding of 

whether drivers who refused to participate were more or less likely to be alcohol or drug positive 

than those who initially agreed to participate. Drivers who refused were offered a $100 incentive 

as an inducement to convert. Of the 444 total attempts, 50 percent were successfully converted 

(i.e., provided a breath sample). Among those converted drivers, 156 (70%) also provided an oral 

fluid sample and 49 drivers (22%) also provided a blood sample. 

Tables 11 and 12 show the outcome of the Oral Fluid and Blood analyses (respectively) 

performed on the converted drivers. Among converted drivers who provided an oral fluid 

sample, the distribution of drivers who were drug positive appears to be somewhat higher than 

that of the total sample of daytime and nighttime participants, where 11.0 percent of the general 

daytime samples were positive (as compared to 16.2% of converted drivers) and 14.4 percent of 

the general nighttime samples were positive (compared to the 17.0% of converted drivers). These 

differences, however, were not statistically significant. 

Table 11. Oral Fluid Analysis Results Among Converted Drivers 

Daytime Nighttime 

Presence of Drugs 

in Oral Fluid

N 

(Unweighted)

% 

(Weighted)

N 

(Unweighted) 

% 

(Weighted)

Negative 27 83.8% 107 83.1% 

Positive 6 16.2% 16 17.0% 

All 33 100% 123 100% 

Among drivers who were converted and provided a blood sample, 12.7 percent were drug 

positive. This distribution is very similar to that of the total nighttime participants who provided 

blood, where 13.8 percent were drug positive (blood was not collected in the daytime sample). 

Given the low sample size, statistical tests were not performed.

Table 12. Blood Analysis Results Among Converted Drivers 

Nighttime 

Presence of 

Drugs in Blood

N 

(Unweighted)

% 

(Weighted)

Negative 43 87.3% 

Positive 6 12.7% 

All 49 100% 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

24 

Selection of Drugs for Screening and Analysis 

PIRE and NHTSA jointly developed an initial list of drugs to be detected based on the literature 

(e.g., Jones, Shinar, & Walsh, 2003; Couper & Logan, 2004) and experience with drug-involved 

driving research. The drugs were selected because of a combination of their potential impaireddriving effects, their likelihood of appearing in drivers, and in the case of oral fluid, the 

availability of scientific techniques to analyze oral fluid to detect and quantify the drug. NHTSA 

then provided this list to experts in the field of epidemiology of drug use, driving, and toxicology 

both in the United States and abroad. The experts responded to the list with additions and 

deletions. 

The list of selected drugs is shown in Table 13. The first five categories of drugs listed constitute 

the National Institute on Drug Abuse (NIDA)-5, which are prevalent drugs of abuse and of 

universal interest in the study of drug involvement. The NIDA-5 are routine components of a 

drug-screening panel. The other drugs on the list (with the exception of barbiturates) appear in 

the NHTSA publication titled “Drugs and Human Performance Fact Sheets” (Couper & Logan, 

2004) and are of interest because the expert panel for that effort believed those drugs presented 

potential traffic safety risks. The drugs we tested for represented illegal, prescription, and overthe-counter drugs that (1) have the potential to impair driving performance and (2) could 

reasonably be expected to appear in the driver population. 

Table 13. Selected Drugs and Minimum Detection Concentrations†

Drug Class 

Minimum Concentration 

Oral Fluid (ng/mL) 

Minimum Concentration 

Blood (ng/mL) Self-report Item 

 Screen Confirm Screen Confirm 

Cocaine 

(Cocaine, 

benzoylecgonine) 

20 8 25 10 Cocaine (e.g., crack 

or coke) 

Opiates 

(6-AM, codeine, 

morphine, 

hydrocodone, 

hydromorphone) 

40 10 25 10 

Heroin 

Morphine or Codeine 

(e.g., Tylenol®

 with 

codeine) 

Amphetamine/ 

Methamphetamine 

(MDMA, MDA, MDEA, 

Ephedrine, 

Psuedoephedrine) 

50 

50 

50 20 

20 10 

Amphetamine or 

Methamphetamine 

(e.g., speed, crank, 

crystal meth) 

Ecstasy 

Cannabinoids 

(THC, THCCOO[THCA]) 

4 2 10 1 Marijuana (e.g., pot, 

hash, weed) 

Phencyclidine 10 10 10 10 PCP (e.g., angeldust) 

Benzodiazepines 

(oxazepam, 

nordiazepam, 

bromazepam, 

flurazepam, 

10 5 20 10 

Benzodiazepines 

(e.g., Valium®

 or 

tranquilizers) 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

25 

Drug Class 

Minimum Concentration 

Oral Fluid (ng/mL) 

Minimum Concentration 

Blood (ng/mL) Self-report Item 

 Screen Confirm Screen Confirm 

flunitrazepam, 

lorazepam, 

chlordiazepoxide, 

temazepam, diazepam, 

clonazepam, 

alprazolam, triazolam, 

midazolam, 

nitrazepam) 

 Barbiturates 

(Phenobarbital, 

pentobarb, 

secobarbital, butalbital) 

50 50 500 500 Barbiturates (e.g., 

phenobarbital) 

Methadone 50 25 50 10 Methadone 

Ethyl alcohol .02% .02% .02% .02% Alcohol 

Oxycodone (Percocet®) 25 10 25 10 

Propoxyphene 

(Darvon®

) 10 10 10 10 

Tramadol (Ultram®) 50 25 50 10 

Carisoprodol (Soma®) 100 50 500 500 

Meperidine (Demerol®) 

Prescription pain 

killers (e.g., 

Percocet®, 

OxyContin®

, 

oxycodone, Demerol®

, 

Darvon®

) 

Sertraline (Zoloft®) 50 25 50 10 

Fluoxetine (Prozac®) 50 25 50 10 

Tricyclic 

Antidepressants 

(amitryptiline, 

nortriptyline) 

25 25 25 10 

Antidepressants (e.g., 

Prozac®

, Zoloft®) 

Zolpidem (Ambien®) 10 10 10 10 Ambien®

 or other 

sleep aids 

Methylphenidate 

(Ritalin®

) 10 10 10 10 ADHD medications (e.g., Ritalin®) 

Dextromethorphan 50 20 50 20 

Cough medicines 

(e.g., Robitussin®, 

Vicks 44®

, etc.) 

Ketamine 10 10 10 10 Ketamine/Special K 

†Screening utilizes ELISA micro-plate and confirmation utilizes GC/MS or LC/MS/MS technology. 

We screened using ELISA micro-plate technology. Confirmation was performed using GC/MS 

or LC/MS/MS technology. Our toxicological laboratory, Immunalysis Corporation, provided all 

necessary confirmations. 

Cocaine, which can be used as a local anesthetic, is often abused because of its stimulating 

effects on the central nervous system (CNS). At low doses, cocaine might actually have 

performance enhancing effects; however, little is known about its effects on human performance 

at higher levels and in conjunction with alcohol. It is clearly a drug of abuse in the United States 

and worthy of study in drivers. 

Opiates are narcotic analgesics used both medicinally and as drugs of abuse. After an initial rush, 

opiates act as CNS depressants and certainly could have performance-decreasing effects. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

26 

Amphetamines are CNS stimulants and are used both medicinally and as drugs of abuse. 

Amphetamines are generally taken recreationally and to enhance performance (e.g., truck drivers 

staying awake). Ecstasy falls within this category, and as a methylated amphetamine derivative it 

also has hallucinogenic properties. Amphetamines have been associated with crash occurrence 

and could logically be associated with driving impairment both in the stimulation and withdrawal 

stages; in the latter case especially as the drug interacts with fatigue. The analytical methodology 

is described in an article by Moore, Coulter, and Crompton (2007). 

Cannabinoids have a variety of effects on humans and can be associated with stimulant, sedative, 

and hallucinogenic effects. Both the experimental and epidemiologic evidence on cannabinoids’ 

effects on driving are mixed. When marijuana is found in drivers, however, it is often in 

conjunction with alcohol, where an impairing effect is more likely. The most prevalent drug 

detected in the pilot study was marijuana (Lacey et al., 2007). There appeared to be a strong 

positive correlation between the oral fluid and blood tests, and the only discrepancies found in 

the pilot study (negative oral fluid and a positive blood) were from 10 cases in which the inactive 

metabolites were detected in blood but not the active tetrahydrocannabinol (THC). A positive 

metabolite result (THCA) with a negative parent compound (THC) is consistent with less recent 

use (e.g., in the days before sample was taken). A positive oral fluid for the parent compound is 

likely to be associated with very recent THC use, the timeframe consistent with potential 

impairing effects. Thus, such oral fluid results can be very informative. The laboratory 

procedures for testing the oral fluid results have been previously published in several articles 

(Moore et al., 2006; Moore, Rana, & Coulter, 2007c; Coulter, Miller, Crompton, & Moore, 

2008). 

Phencyclidine (PCP) is related to veterinary tranquilizers such as ketamine, that impair motor 

ability, but it also has hallucinogenic effects and is used as a recreational drug. PCP has serious 

performance diminishing effects and has been found in impaired-driving cases. Its determination 

in oral fluid has recently been published in Coulter, Crompton, and Moore (2008). 

Benzodiazepines include many widely prescribed drugs (e.g., Valium®, Xanax®) to reduce 

anxiety. These drugs act as CNS depressants, show cross-tolerance to ethanol, and are potentially 

associated with driver impairment. Different types of benzodiazepines have very short to very 

long half-lives. For example, the desired/therapeutic effect of lorazepam (Ativan®) is sedation, 

which would obviously have a detrimental effect on driving a motor vehicle. The most common 

benzodiazepine is diazepam (Valium®) and/or its metabolites: nordiazepam, oxazepam, and 

temazepam. The confirmation procedure for the 2007 study included LC/MS/MS confirmation 

using the method described in Moore, Coulter, Crompton, and Zumwalt (2007). 

Barbiturates are still widely prescribed CNS depressants and in some cases as anti-epileptic 

medications. Because of their depressive effects, barbiturates are associated with delayed 

reaction times and possibly loss of concentration; both effects likely to affect driving 

performance. 

Methadone, a narcotic analgesic, is used both medicinally for opiate detoxification and 

maintenance, and for pain relief. It has also been used as a drug of abuse. It may have differential 

performance effects in naïve or recreational users versus tolerant therapeutic users, and certainly 

deserves study. 

Painkillers are a class of drugs that may lead to driving impairment. Commonly used painkillers 

include oxycodone (an opioid). Oxycodone has similar effects to morphine and heroin. If used in 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

27 

combination with other depressants of the CNS, such as alcohol or benzodiazepines, it can cause 

severe impairment or lead to death. Tramadol, an opiate analgesic, has similar effects to 

oxycodone. Propoxyphene and meperidine, also atypical opiates, are included in the panel. The 

methods used for their analysis are described (Rana et al., 2006; Moore, Rana et al., 2007b). 

Other painkillers such as carisoprodol, a CNS depressant, and muscle relaxant (Soma® also 

called Miltown®), are used as prescription drugs but can lead to abuse. Even at therapeutic 

concentrations, carisoprodol and its metabolite meprobamate may cause driving impairment as 

the desired effect is sedation. 

Antidepressants are most commonly in the form of selective serotonin uptake inhibitors (SSRIs), 

such as fluoxetine (Prozac®) and sertraline (Zoloft®). They can cause impairment, especially in 

circumstances where extremely high blood concentrations are measured or if they are taken 

outside of medical need or therapeutic treatment. There is also an additional risk of impairment 

associated with combined use with alcohol. 

Sleep aids such as Ambien® cause drowsiness and may cause dizziness. If consumed with 

alcohol, there is an increased likelihood of these symptoms. Sleep aids alone or in combination 

with alcohol could have a detrimental effect on driving ability. 

Other stimulants, such as methylphenidate (sold as Ritalin®), are amphetamine-like prescription 

drugs commonly used to treat Attention Deficit Hyperactivity Disorder (ADHD) in children and 

adults. They are CNS stimulants. Some people abuse these drugs by crushing the tablets and 

snorting them. The effect of this other stimulant abuse is similar to that of cocaine or 

amphetamine. 

Dextromethorphan, a synthetic analog of codeine, is an antitussive widely used in cough 

medicines (e.g., Robitussin®, Sucrets®, Vicks Formula 44®). When consumed in high doses in 

recreational use, it is a CNS depressant and may have driving impairment effects at those levels. 

The analytical method has recently been published in Rodrigues et al. (2008). 

Ketamine (Special K) is used medicinally as a veterinary tranquilizer, but it is also abused as a 

recreational drug for its psychedelic effects. Ketamine use by humans would likely be associated 

with decrements in skills related to driving. 

Oral Fluid Collection Device 

Following the NRS interview and collection of the breath test, the interviewer requested an oral 

fluid sample and offered a $10 incentive for providing one. We used the QuantisalTM 

(manufactured by Immunalysis Corporation) oral fluid collection device (see Appendix F of the 

Methodology Report [Lacey et al., 2009a]). The subject placed this device under his/her tongue 

and its pad changed color (blue) when 1 mL of oral fluid (the necessary sample volume) was 

collected. The collection device was then placed into a tube containing 3 mL of a stabilizing 

buffer solution, and capped for storage and transport to the laboratory. The steps are illustrated in 

Figure 2. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

28 

Figure 2. Collecting an Oral Fluid Sample with the QuantisalTM Oral Fluid Collection Device 

distributed by Immunalysis, Inc., Pomona, CA. 

http://www.immunalysis.com/quantisal_procedure.htm 

The oral fluid samples were labeled with pre-printed Chain-of-Custody (CoC) labels to be linked 

with the subject and additional data collected. This allowed the specimen to be tracked 

throughout the project. The CoC labels contained a unique identifier that corresponded to that 

sample. This number was also entered into the PDA. CoC numbers were preprinted by the 

laboratory and were used to maintain a documented link between each sample collected and the 

respondent who provided it. A different CoC number was assigned to the oral fluid and blood 

sample for an individual subject and the laboratory was blinded to any link between them. This 

assured the oral fluid and blood analyses and results were independent of one another. 

The collection of oral fluid, while less invasive than the collection of blood or urine, has some 

associated difficulties (O'Neal, Crouch, Rollins, & Fatah, 2000). Various researchers have noted 

that the method of collection and the medium itself (oral fluid) significantly affect drug 

concentration in the specimen and, consequently, whether some drugs can be detected at all. 

However, while some collection devices give no indication of the amount of oral fluid actually 

collected (rendering a quantitative result meaningless), the QuantisalTM oral fluid collection 

device collects 1 mL (+10%) of clear oral fluid from the donor. Researchers have studied the 

device to assess the efficiency of drug release from the collection pad (Quintela, Crouch, & 

Andrenyak, 2006; Moore et al., 2006; Moore, Rana, & Coulter, 2007b) and have found a high 

rate of extraction efficiency. Tables 14 and 15 summarize the effectiveness of the QuantisalTM 

oral fluid collection device across a range of drugs by two different research groups. Findings 

above 100 percent are due to slight variations in the amount of the substances actually added to 

the scientific control samples (scientific error). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

29 

Table 14. Extraction Efficiency of QuantisalTM Oral Fluid Collection Device 

over a Range of Drugs: Quintela 

Drug Target Value (ng/mL) Mean Recovery from the Pad (%) 

Amphetamine 50 94.3%

Methamphetamine 50 103.8%

Cocaine 20 91.2%

Benzoylecgonine 20 86.9%

Codeine 40 95.6%

Morphine 40 92.6%

6-acetylmorphine 4 92.2%

THC 4 91.4%

Methadone 50 99.7%

Oxazepam 20 101.3%

Source: Quintela et al., 2006.

Table 15. Extraction Efficiency of QuantisalTM Oral Fluid Collection Device 

over a Range of Drugs: Moore

Drug Target Value (ng/mL) Mean Recovery from the Pad (%) 

Meperidine 25 86.7%

Tramadol 25 87.7%

Oxycodone 20 96.6%

Source: Moore, Rana, & Coulter, 2007a; Moore et al., 2006: THC recovery from the pad > 80%. 

For a more thorough discussion of the Quantisal device, see the pilot study report (Lacey et al., 

2007). 

Blood Collection Procedures 

After completion of the oral fluid sample and the drug questionnaire, the interviewer requested 

that the subject provide a blood sample in exchange for an additional $50 incentive. The 

incentives were given as money orders so subjects could not spend the money immediately, 

especially on items such as alcohol and other drugs. 

Licensed phlebotomists conducted the blood draws. The phlebotomist set up the blood draw 

station in the rear seat of a rental van. The subject sat in the back seat of the van and the 

phlebotomist stood just outside the van or sat in the adjoining seat. 

During blood draws, one gray-top tube (10 mL) of the subject’s blood was drawn. There are 

several types of tubes available for the collection of blood specimens, with different color tops. 

The choice of tube is dependent upon the type of test to be performed on the blood. The Federal 

Aviation Administration (FAA) recommends the gray-topped tube for drug and alcohol testing of 

blood specimens. The gray-top tube contains two preservatives: potassium oxalate and sodium 

fluoride. The oxalate is an anti-coagulant, and the sodium fluoride is an anti-bacterial stabilizer. 

These preservatives reduce the need for refrigeration but do not affect the ability to detect and 

quantify drugs. Both additives are inorganic; therefore, they oxidize very slowly and are 

extremely stable. The preservative helps inhibit the degradation of cocaine in storage to its 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

30 

metabolite, benzoylecgonine (Toennes & Kauert, 2001). The presence of sodium fluoride, with 

or without refrigeration, and potassium oxalate, effectively inhibits cocaine degradation, with 86 

to 91 percent of the drug present after 48 hours. In contrast, substantial degradation of cocaine 

occurs in the samples stored without sodium fluoride (Brogan et al., 1992). The presence of the 

parent drug is particularly useful in the determination of recent use since more cocaine per se 

(prior to its transformation to benzoylecgonine) indicates more recent drug use. Additionally, 

gray-top tubes are helpful in conducting ethanol analysis because the sodium fluoride is an 

effective antibacterial agent that helps inhibit endogenous alcohol production. 

For this study, glass tubing was used, as opposed to plastic, to better maintain reliable drug 

results. For example, in a study by Christophersen (1986) on the stability of THC in whole blood 

during storage, THC concentration in blood stored in glass vials for four weeks at -20 C 

remained unchanged; however, blood stored in plastic vials lost 60 to 100 percent of its THC 

content during storage. Thus, glass vials are recommended for collection of blood samples where 

marijuana content is suspected. In this study, approximately 10 percent of the blood samples 

were analyzed immediately upon receipt by the laboratory. However, the remaining samples 

were stored at 4 degrees Centigrade until additional funding was obtained for their analyses, 

approximately one year later. As a check, on 13 samples, which had been analyzed initially and 

were found to be positive for THC and/or its metabolites, reanalysis for THC and its metabolites 

one year later revealed that, though values obtained were generally lower than in the initial 

analyses, each specimen tested positive for THC and/or a metabolite at the retest. Additionally, 

six samples which initially had been found to be positive for cocaine and/or its metabolites were 

reanalyzed and though parent drug values had eroded, metabolite values had increased and all 

were still positive for cocaine at retest. For eight opiate samples and six amphetamine samples, 

the results at retest remained positive after one year. 

The blood sample tubes were labeled with pre-printed Chain-of-Custody (CoC) labels that linked 

the blood sample to the oral fluid sample to the subject, so the specimen could be tracked 

throughout the project. The CoC labels contained a unique identifier that corresponded to that 

sample, thus there was no identifying information traceable to the subject. This number was also 

entered into the PDA. CoC numbers were preprinted by the laboratory and were used to maintain 

a documented link between each sample collected and the respondent who provided it. As noted 

above, a different CoC number was assigned to the oral fluid and blood sample for an individual 

subject and the laboratory was blinded to any link between them. 

In the few cases where phlebotomists were not able to draw a full tube for a subject because 

some individuals had small and/or difficult-to-locate veins, the laboratory was able to conduct an 

initial screening test; however, it was not able to conduct a confirmatory analysis by GC/MS due 

to the insufficient volume. 

At the conclusion of the blood draw procedure, the subject received the $50 incentive and sat for 

a moment in the blood draw station. The subject was offered a piece of candy before being 

directed safely out of the survey site and back onto the roadway. 

Once collected, blood samples were stored either in refrigerators or in coolers with blue ice 

packs if no refrigeration was available. The samples were subsequently shipped to the laboratory 

with blue ice as an additional precaution. 

Spanish-speaking participants were escorted to the phlebotomist by the Spanish-speaking 

interviewer, and a Spanish consent form was given to the participant. The interviewer read the 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

31 

consent form to them and stayed with the participant to answer any questions and provide 

translation between the phlebotomist and participant. 

Drug Questionnaire 

While they provided an oral fluid sample, drivers were asked to complete a drug questionnaire. 

The 27-item questionnaire (Table 16) included a list of drugs including tobacco, cough medicine, 

other illegal, prescription, and over-the-counter drugs. For items 1-23, subjects indicated when 

they last used a particular medication/drug, by responding “Tonight,” “Past 2 days,” “Past 

month,” Past year,” “Over a year ago,” or “Never.” 

Table 16. Drug Questionnaire Survey 

Item # Drugs 

1 Tobacco (e.g., cigarettes, cigars) 

2 Cough medicines (e.g., Robitussin, Vicks 44, etc.) 

3 Other over-the-counter medicines 

4 Prescription Pain Killers (e.g., Percocet, OxyContin, Oxycodone, Demerol, Darvon) 

5 Ambien or other sleep aids 

6 ADHD medications (e.g., Ritalin, Aderall, Concerta) 

7 Muscle relaxants (e.g., Soma, Miltown) 

8 Prescription dietary supplements (e.g., Phentermine) 

9 Antidepressants (e.g., Prozac, Zoloft) 

10 Marijuana (e.g., pot, hash, weed) 

11 Cocaine (e.g., crack or coke) 

12 Heroin 

13 Methadone 

14 LSD (acid) 

15 Morphine or Codeine (e.g., Tylenol with Codeine) 

16 Ecstasy (e.g., “E”, Extc, MDMA, “X”) 

17 Amphetamine or Methamphetamine ( e.g., speed, crank, crystal meth) 

18 GHB 

19 PCP (e.g., Angeldust) 

20 Rohypnol (Ruffies) 

21 Ketamine (Special K) 

22 Benzodiazepines (e.g., Valium or tranquilizers) 

23 Barbiturates (e.g., Phenobarbital) 

24 Do you believe any of the medications/drugs you have taken (or are taking) could affect your 

driving? 

25 Have you taken any medications or drugs in the past YEAR that you think may have affected your 

driving? 

26 Have you taken any medications or drugs TODAY that you think may affect your driving? 

27 Have you ever NOT driven because you were on a medication/drug? 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

32 

Biological Sample Analysis Procedures 

The following sections briefly describe the analytic techniques used in the analyses of oral fluid 

and blood samples to determine the presence of the drugs of interest in this study. 

Oral Fluid Sample Analysis Procedures 

Each weekend, the tubes from each data-collection period were packaged together and sent 

overnight to a laboratory for analysis. Upon receipt of the specimens in the testing facility, 

screening analysis was carried out using enzyme-linked immunosorbent assays (ELISA) at the 

cut-off concentrations described in Table 13. Screen positive specimens were then reanalyzed, 

using a separate sample of the fluid, using gas chromatography-mass spectrometry (GC/MS) or 

liquid chromatography with tandem mass spectral detection (LC/MS/MS) according to standard 

operating procedures. All methods were fully validated according to good laboratory practices, 

and all standard operating procedures are on file at Immunalysis Corporation. 

Gas Chromatography-Mass Spectrometry (GC/MS) 

Instrumentation: 

Agilent 6890 gas chromatography - 5973 or 5975 mass selective detector (GC/MSD); 

electron impact (EI) mode. 

Extraction: 

Oral fluid (1 mL) of diluted specimen (1:3 buffer) was extracted using mixed mode 

solid phase methods with drug specific column phases. 

Derivatization: 

Drug specific derivatives used for maximum detectability and stability. 

Drugs included in the confirmation profile are shown in Table 13. 

Liquid Chromatography-Tandem Mass Spectrometry (LC/MS-MS) 

Instrumentation: 

Agilent LC/MS-MS System: 1200 Series LC pump 6410 Triple Quadropole. 

Zorbax Eclipse XDB C18 (4.6 x 50mm x 1.8 μm) column. 

Extraction: 

Blood (1 mL); protein precipitate with cold acetonitrile; mixed mode solid phase 

extraction using drug specific column phases. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

33 

Blood Sample Analysis Procedures 

Upon receipt of the specimens by the testing facility, screening analysis for 10 percent of the 

sample was carried out using enzyme-linked immunosorbent assays (ELISA) at the cut-off 

concentrations described in Table 13. The remaining 90 percent of the sample was stored at 4° 

centigrade until funding was provided for their analysis. Again, specific drugs tested are shown 

in Table 13. Screen positive specimens were confirmed using either gas chromatography with 

mass spectral detection (GC/MS) or liquid chromatography with tandem mass spectral detection 

(LC/MS/MS). All methods were fully validated according to good laboratory practices. See 

above for instrumentation. 

Ethanol (Oral Fluid and Blood) 

Screen positive alcohol specimens were sent for confirmation to BioTox Laboratories or 

Immunalysis Corporation. 

Instrumentation:

Perkin-Elmer: Model F-45 Gas Chromatograph. 

Flame ionization detector (FID). 

0.2 percent Carbowax 1500 Graphpac-GC, 80/100 column (6 ft. x 1/8 in. ID). 

Extraction: 

Whole blood or 1:3 buffered oral fluid (0.1 mL), add 1 mL double deionized water 

containing 0.1 percent propanol. 

Analyzed using headspace GC/FID. 

Drug Classes and Categories 

Due to the large number of drugs tested, results were consolidated into drug classes and 

categories. Drug classes are defined according to potential drug effects and include stimulants, 

sedatives, marijuana, antidepressants, narcotic analgesics, and other. Drugs were separately 

categorized as illegal, prescription, and over-the-counter.12 13 Though some drugs could logically 

fall into more than one category, we made the categories mutually exclusive and assigned each 

drug to only one category. This approach facilitates clear presentation of results. 

Tables 17 and 18 present drug classes and categories. In the tables, the shaded entries indicate 

drugs that were identified only through blood analyses. The non-shaded entries are drugs that 

were identified through both oral fluid and blood analyses. 

 

12 Drugs may be classified in different ways depending on the use of the classification system. For example, in 

NHTSA’s drug evaluation and classification (DEC) program the categories CNS Depressants, CNS Stimulants, 

Hallucinogens, Dissociative Anesthetic (PCP), Narcotic Analgesics, Inhalants, and Cannabis are used. 13 Due to relative small sample sizes and for analytical purposes, the over-the-counter and prescription categories 

were further collapsed into a single category (“Medications”) 
2007 National Roadside Survey of Alcohol and Drug Use 

Table 17. Drug Class Composition—Oral Fluid and Blood Combined 

Stimulants Sedatives Marijuana Antidepressants Narcotic Analgesics 

Amphetamines Barbiturates Cannabinoids SSRIs* Methadone Amphetamine Butalbital THC Fluoxetine Methadone 

MDA Phenobarbital 11-OH-THC Desmethylsertraline EDDP 

MDEA Pentobarbital THC-COOH Sertraline 

MDMA Secobarbital Norfluoxetine Opiates 

Methamphetamine 6-AM (Heroin) 

Phentermine Benzodiazepines Tricyclics 6-AC (Heroin impurity) 

Pseudoephedrine Alprazolam Amitriptyline Codeine 

Phenylpropanolamine Alpha-hydroxyalprazolam Nortriptyline Morphine 

Chlordiazepoxide Doxepin Hydrocodone 

Cocaine Diazepam Desmethyldoxepin Hydromorphone 

Cocaine Lorazepam Imipramine Oxycodone 

Benzoylecgonine Oxazepam Desipramine Oxymorphone Cocaethylene Temazepam Trimipramine 

 Norcocaine Triazolam Clomipramine Atypical Opioids

Alpha-hydroxytriazolam Amoxapine Tramadol 

ADHD Medications Clonazepam Protriptyline Meperidine Methylphenidate Flunitrazepam Maprotiline Normeperidine 

7-aminoflunitrazepam Propoxyphene Bromazepam Sleep Aids Norpropoxyphene Nitrazepam Zolpidem Estazolam Midazolam Flurazepam Nordiazepam CarisoprodolCarisoprodol Meprobamate 

Note: Shaded entries indicate drugs identified through blood analyses only. Non-shaded entries are drugs identified through both blood * Selective Serotonin Uptake Inhibitors (SSRIs). 
2007 National Roadside Survey of Alcohol and Drug Use 

Table 18. Drug Category Composition—Oral Fluid and Blood Combined

Illegal Prescription Prescription (cont.) Prescription (cont.) 

Cocaine Benzodiazepines Tricyclics, Antidepressants Methadone CouCocaine Alprazolam Amitriptyline Methadone DexBenzoylecgonine Alpha-hydroxyalprazolam Nortriptyline EDDP Cocaethylene Nordiazepam Doxepin Col

Norcocaine Chlordiazepoxide Desmethyldoxepin Opiates Pse

 Diazepam Imipramine Codeine 

Cannabinoids Lorazepam Desipramine Morphine 

THC Oxazepam Trimipramine Hydrocodone 

11-OH-THC Temazepam Clomipramine Hydromorphone THC-COOH Triazolam Amoxapine Oxycodone 

Alpha-hydroxytriazolam Protriptyline Oxymorphone 

Street Drugs Flurazepam Maprotiline Ketamine Flunitrazepam Atypical Opioids

Norketamine 7-aminoflunitrazepam Stimulants Tramadol 

PCP Nitrazepam Methylphenidate Meperidine  Midazolam Phentermine Normeperidine 

Street Amphetamines Bromazepam Propoxyphene 

Amphetamine Clonazepam Barbiturates Norpropoxyphene 

MDA Estazolam Butalbital 

MDMA Phenobarbital Sleep Aids

MDEA SSRIs* Pentobarbital Zolpidem 

Methamphetamine Fluoxetine Secobarbital 

Phenylpropanolamine Desmethylsertraline Carisoprodol

 Sertraline Carisoprodol Opiates Norfluoxetine Meprobamate 

6-AM (Heroin) 

6-AC (Heroin impurity) 

Note: Shaded entries indicate drugs identified through blood analyses only. Non-shaded entries are drugs identified through both blood * Selective Serotonin Uptake Inhibitors (SSRIs).
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

36 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

37 

Results 

Since two different biological matrices (oral fluid and blood) were gathered to be analyzed for 

the presence of drugs, we present prevalence estimates in three different ways in this report. 

 1) We present both daytime and nighttime drug prevalence estimates based on the 

analyses of the oral fluid samples alone, and then in combination with alcohol using breath 

alcohol test results. Tables reporting self-report drug use, observed safety measures, and reports 

with contact with the criminal justice system and the health care system follow these results. 

 2) We next present nighttime drug prevalence estimates based on analyses of blood,14

and then in combination with alcohol using breath alcohol test results. 

 3) The third section presents nighttime prevalence results based on the combination of 

the results of the oral fluid / blood analyses, and subsequently in combination with alcohol using 

breath alcohol test results. We conclude this section by presenting prevalence estimates for 

specific drugs from oral fluid and/or blood combined. In each of the sections, the results are 

presented first in terms of drivers who were positive for any drug, then by class, followed by 

category as described in Tables 17 and 18. 

Throughout this report, we do not combine results for daytime and nighttime survey respondents, 

but display the two groups separately because the sampling frame is different for the two groups. 

The daytime drivers were sampled during a single Friday two-hour period in each PSU, while the 

nighttime drivers were sampled during four two-hour periods (two on Friday night and two on 

Saturday night in each PSU). Thus, combining the daytime and nighttime samples would not 

result in a meaningful representation of driver drug use overall. 

Each of the various sampling stages (or frames) required a separate calculation of probability, 

which then became a component of the final probability computation, reflecting all levels or 

frames. The total weighted number of the sample was identical to the total number of eligible 

drivers entering the survey bays, including refusers, but was adjusted to reflect the estimated 

distribution of those drivers in the 48 contiguous States. Error terms for the analyses were 

computed by STATA (Stat Corp., 2006) to account for the differential weights, and the amount 

of variance attributable to the various sampling frames. Further information on the weighting of 

the data can be found in the Methodology Report (Lacey et al., 2009a). 

Oral Fluid Results (Daytime and Nighttime Samples) 

Driver Drug Use Prevalence Based on Oral Fluid Results 

This section of the report presents the overall results of oral fluid analyses for all of the drugs 

indicated in the introductory section. Drivers who tested positive for one or more of the drugs we 

tested in oral fluid are categorized as drug-positive. It should be emphasized that this set of tables 

aggregates over-the-counter, prescription, and illegal drugs and metabolites of drugs in each 

category, indicating only that those who tested positive have recently consumed at least one of 

the tested drugs and not that they were necessarily impaired by the substance. 

 

14 Daytime data collection did not include requests for blood samples. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

38 

Unless explicitly indicated, sample size (N) refers to the actual, unweighted number of 

respondents. Percentages are weighted. Sample size may vary between tables because of missing 

values. 

Comparison of drug prevalence by time of day (Table 19) indicates that 11 percent of drivers in 

the daytime sample were drug-positive. This level was significantly lower than the 14.4 percent 

of nighttime drivers who tested positive for drugs (p < .01). 

Table 19. Drug Prevalence by Time of Day (Oral Fluid) 

Time of Day 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Daytime 1,850 11.0%

Nighttime 5,869 14.4%

Further, when we examined drug prevalence by time of day/session (Table 20), we found that 

late night (Sessions 3 and 5) drivers were significantly more likely to be drug-positive (17.2% 

and 17.4% respectively) than Friday daytime (Session 1) drivers (11%) or Friday and Saturday 

early evening (Sessions 2 and 4) drivers (12.9% and 13.6% respectively) (p < .01). 

Table 20. Drug Prevalence by Time of Day/Session (Oral Fluid) 

Session 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

1: Friday, 9:30 a.m. – 11:30 a.m. or 

 1:30 p.m. – 3:30 p.m. 1,850 11.0%

2: Friday, 10:00 p.m. – Midnight 1,610 12.9%

3: Friday, 1:00 a.m. – 3:00 a.m. 1,299 17.2%

4: Saturday, 10:00 p.m. – Midnight 1,684 13.6%

5: Saturday, 1:00 a.m. – 3:00 a.m. 1,276 17.4%

Comparison of drug prevalence by time and region (Table 21) revealed that the Northeast region 

had the greatest percentage of drug-positive findings in the nighttime driving sample, at 17.3 

percent (p < .05). The Northeast region also had the second highest percentage in the daytime 

driving sample at 12.5 percent (although there were no statistical differences by region during 

the daytime). In spite of the Northeast regions’ relatively high prevalence of drug-positives, no 

clear pattern by region emerged. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

39 

Table 21. Drug Prevalence by Time of Day and Region15 (Oral Fluid) 

Time of Day Region 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Midwest 546 11.5%

Northeast 379 12.5%

South 472 13.1%

West 453 8.9%

Daytime 

Overall Daytime 1,850 11.0%

Midwest 1,694 15.0%

Northeast 1,111 17.3%

South 1,559 14.0%

West 1,505 12.9%

Nighttime 

Overall Nighttime 5,869 14.4%

Although the daytime driving sample showed no statistically significant difference in drug 

prevalence between males and females (Table 22), in the nighttime driving sample, male drivers 

were significantly more likely to be drug-positive (16.5%) than female drivers (11.3%) (p < .01). 

Table 22. Drug Prevalence by Time of Day and Gender (Oral Fluid) 

Time of Day Gender 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Males 1,032 11.0%

Daytime Females 811 11.3%

Overall Daytime 1,843 11.0%

Males 3,605 16.5%

Nighttime Females 2,250 11.3%

Overall Nighttime 5,855 14.4%

Comparison of drug prevalence by time of day and age (Table 23) showed that, within the 

daytime driving sample, drivers aged 45-64 showed the highest percentage of drug positives, and 

drivers aged 16-20 and aged 65+ were significantly less likely to be positive than other ages of 

drivers (p < .05). In the nighttime driving sample, drivers aged 45-64 and 65+ were significantly 

less likely to be drug positive (p < .01). Drivers aged 16-20, 21-34 years, and 35-44 years all had 

results similar to each other. Age was self-reported by respondent. Note that in Table 23 as well 

as upcoming tables, the age ranges are not of equal intervals but were developed to roughly 

 

15 Regions are defined by the NASS/GES system according to U.S. Census Regions (Midwest includes the West 

North Central and East North Central States, Northeast includes New England and Middle Atlantic States, South 

includes the West South Central, East South Central, and South Atlantic States, and West includes West and 

Mountain States. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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categorize underage drivers (16-20), young drivers (21-34), followed by middle age and late 

middle age (35-44 and 45-64), and finally by senior drivers (65+ years). 

Table 23. Drug Prevalence by Time of Day and Age (Oral Fluid) 

Time of Day Age 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

16-20 99 6.2%

21-34 436 11.2%

35-44 374 11.6%

45-64 668 13.3%

65+ 245 6.4%

Daytime 

Overall Daytime 1,822 11.1%

16-20 961 16.1%

21-34 2,437 17.1%

35-44 1,042 15.2%

45-64 1,216 9.5%

65+ 148 2.0%

Nighttime 

Overall Nighttime 5,804 14.6%

Gender comparisons within age groups (Table 24) revealed that, within the daytime sample, drug 

prevalence among female daytime drivers aged 45-64 (16.8%) was significantly higher than 

male drivers of the same age group (9.7%) (p < .05). The same was true of the nighttime sample, 

with drug prevalence among female drivers aged 45-64 (13.1%) being significantly higher than 

male drivers of the same age group (7.2%) (p < .01). 

Within the daytime sample, drug prevalence among male drivers aged 21-34 years was 

statistically higher than among female drivers of the same age group (13.9% vs. 7.5%) (p < .05). 

Additionally, in the nighttime sample, drug prevalence among male drivers in age categories 

16-20 years, 21-34 years, and 35-44 years was significantly higher than the same-aged female 

counterparts (p < .01). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 24. Drug Prevalence by Time of Day, Age, and Gender (Oral Fluid)

Time of Day Gender Age 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

16-20 59 4.5%

21-34 243 13.9%

35-44 192 13.7%

45-64 362 9.7%

65+ 161 7.1%

Males 

Overall Males – Daytime 1,017 11.0%

16-20 39 10.3%

21-34 192 7.5%

35-44 181 10.1%

45-64 304 16.8%

65+ 84 4.8%

Daytime 

Females 

Overall Females – Daytime 800 11.4%

16-20 598 20.7%

21-34 1,492 20.2%

35-44 630 18.2%

45-64 734 7.2%

65+ 101 1.9%

Males 

Overall Males – Nighttime 3,555 16.7%

16-20 362 9.5%

21-34 940 11.9%

35-44 409 10.9%

45-64 480 13.1%

65+ 47 2.3%

Nighttime 

Females 

Overall Females – Daytime 2,238 11.3%

Comparisons by self-reported race and ethnicity (Table 25) showed that, in both the daytime and 

nighttime samples, drivers who identified themselves as Asian were significantly less likely to be 

drug-positive (4.1% and 1.8% respectively) than drivers who identified themselves as African 

American, Hispanic, White, or Other (p < .05 at daytime, p < .01 at nighttime). Although 

statistically non-significant, African American drivers were found to have the highest percentage 

of drug-positive results in both daytime (14.4%) and nighttime (20.5%) samples, followed by 

Other (12.8% daytime and 16.2% nighttime), and White (11.6% daytime and 15% nighttime). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 25. Drug Prevalence by Race/Ethnicity (Oral Fluid) 

Time of Day Race/Ethnicity 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

African American 267 14.4%

Asian 46 4.1%

Hispanic 253 8.9%

White 1,192 11.6%

Other 59 12.8%

Daytime 

Overall Daytime 1,817 11.2%

African American 973 20.5%

Asian 191 1.8%

Hispanic 1,006 11.8%

White 3,355 15.0%

Other 272 16.2%

Nighttime 

Overall Nighttime 5,797 14.6%

Race/Ethnic groups other than “Hispanic” are always “non-Hispanic.” 

Comparisons of drug prevalence by education level (Table 26) revealed that prevalence of drug 

use increased from the daytime sample to the nighttime sample across all education levels except 

“some college.” Daytime drivers who identified themselves as college graduates or having some 

graduate experience were statistically less likely to be drug-positive than those with less 

education (p < .01). This remained the case within the nighttime sample, but only for drivers who 

identified themselves as college graduates (p < .01). 

Table 26. Drug Prevalence by Education Level (Oral Fluid) 

Time of Day Education Level 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Not a High School Graduate 162 15.4%

High School Graduate 476 15.0%

Some College 593 13.9%

College Graduate 419 5.5%

Some Graduate Work 173 4.1%

Daytime 

Overall Daytime 1,823 11.1%

Not a High School Graduate 573 18.4%

High School Graduate 1,470 22.4%

Some College 2,218 11.6%

College Graduate 1,156 9.5%

Some Graduate Work 387 15.7%

 Nighttime 

Overall Nighttime 5,804 14.6%

Comparing drug prevalence by employment status (Table 27) showed that, in the daytime 

sample, drug prevalence among unemployed drivers and drivers on disability was significantly 

higher than that of employed drivers or homemakers, students and those who reported they were 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

43 

retired (p < .01). In the nighttime sample, drug prevalence among drivers on disability was again 

significantly higher than employed drivers (p < .01), while no statistical difference in drug 

prevalence was found in the nighttime sample between unemployed and employed drivers. 

Within the nighttime sample, employed drivers had significantly higher drug prevalence than 

“homemaker” and “retired” drivers (p < .01). 

Table 27. Drug Prevalence by Employment Status (Oral Fluid) 

Time of Day Gender 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Employed/Self Employed 1,240 10.4%

Homemaker 90 4.2%

Student 73 7.2%

Unemployed 78 21.3%

Retired 286 13.9%

On Disability 45 38.7%

Other 11 30.7%

Daytime 

Overall Daytime 1,823 11.1%

Employed/Self Employed 4,618 15.0%

Homemaker 104 5.9%

Student 585 13.2%

Unemployed 204 16.8%

Retired 205 7.4%

On Disability 67 41.2%

Other 22 4.3%

 Nighttime 

Overall Nighttime 5,805 14.6%

Drug prevalence rates among drivers of various vehicle types (passenger vehicle, pickup, sports 

utility vehicles (SUV), van/minivan, and motorcycles) (Table 28) were not statistically different 

in the daytime sample. Note, however, that motorcyclists had the greatest percentage of drugpositive results in both the daytime and nighttime samples, although this difference was found to 

be statistically significant only in the nighttime sample (p < .01). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

44 

Table 28. Drug Prevalence by Vehicle Type (Oral Fluid) 

Time of 

Day Vehicle Type 

N 

(Unweighted)

% Drug 

Positive 

(Weighted) 

Passenger Vehicle 952 12.1%

Pickup 285 6.6%

SUV 394 9.7%

Van & Minivan 177 12.6%

Motorcycle 30 24.8%

Daytime 

Overall Daytime 1,838 11.0%

Passenger Vehicle 3,623 15.1%

Pickup 695 14.4%

SUV 1055 12.1%

Van & Minivan 381 13.0%

Motorcycle 73 32.4%

Nighttime 

Overall Nighttime 5,827 14.5%

Driver Drug Use Prevalence by Drug Class Based on Oral Fluid Results 

In this section of the report, we display driver drug use prevalence by class of drug. The classes 

of drugs for which we tested were: antidepressants, marijuana, narcotic-analgesics, sedatives, 

stimulants, and other (see Table 17). Because some drivers tested positive for drugs in more than 

one class, an additional, mutually exclusive category “More than 1 Class” appears in the drug 

class tables. This was done to avoid double counting individual positive results. Thus, for 

example, since marijuana is both a class by itself and could appear in the “More than 1 class” 

cell as well (as could other classes of drugs) from these tables one cannot arrive at an overall 

prevalence estimate for marijuana alone. Detailed summaries of prevalence estimates for 

individual drugs appear in Tables 137-140 later in the report. 

Drug Class 

Comparison of drug classes by time of day (Table 29) indicated that, when examining all drivers, 

nighttime drivers were significantly more likely to test positive for more than one drug class 

(2.3%) than daytime drivers (1.5%) (p < .01). 

Table 29. Number and Distribution of Drug Classes by Time of Day (Oral Fluid) 

Time of Day 

Number of 

Drug Classes 

N 

 (Unweighted) 

% 

(Weighted) 

1 206 9.5%

2+ 40 1.5%

Negative 1,604 89.0% Daytime 

Overall Daytime 1,850 100.0%

1 680 12.1%

2+ 156 2.3%

Negative 5,033 85.6% Nighttime 

Overall Nighttime 5,869 100.0%
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

45 

However, when examining only drug-positive drivers (Table 30), there were no significant 

differences between daytime and nighttime drivers in the percentage of single-drug users 

(86.2% vs. 83.7%) or multi-drug users (13.8% vs. 16.3%). 

Table 30. Number and Distribution of Drug Classes by Time of Day 

(Drug Positives Only) (Oral Fluid) 

Time of Day 

Number of 

Drug Classes 

N 

(Unweighted) 

% 

(Weighted) 

1 206 86.2% 

Daytime 2+ 40 13.8% 

Overall Daytime 246 100.0% 

1 680 83.7% 

Nighttime 2+ 156 16.3% 

Overall Nighttime 836 100.0% 

In comparing prevalence of drug classes by time and region (Table 31), it was found that 

marijuana was generally the most common drug class across all the regions both in daytime 

(3.9%) and nighttime (6.1%) samples. Nighttime drivers in the Midwest and Northeast regions 

were more likely to test positive for marijuana than daytime drivers (p < .05). However, 

marijuana results in the South and West regions did not differ between daytime and nighttime 

drivers. For stimulants, a higher percentage of nighttime drivers in all regions tested positive 

than did daytime drivers. However, the difference was statistically significant only in the 

Midwest (p < .01) and West (p < .05). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 31. Drug Classes by Time of Day and Region (Oral Fluid) 

Time of 

Day Drug Class 

Midwest 

% 

Northeast 

% 

South 

% 

West 

% 

All 

% 

 N=546 N=379 N=472 N=453 N=1,850 

Antidepressants 0.4% 0.6% 0.5% 0.5% 0.5% 

Marijuana 3.4% 3.0% 5.5% 4.0% 3.9% 

Narcotic-Analgesics 2.7% 2.1% 1.3% 0.6% 1.6% 

Sedatives 1.9% 2.6% 2.1% 0.7% 1.6% 

Stimulants 0.8% 1.7% 2.2% 2.0% 1.6% 

Other 0.0% 1.3% 0.0% 0.0% 0.2% 

More than 1 Class 2.2% 1.0% 1.4% 1.2% 1.5% 

Overall Drug Positive Daytime 11.5% 12.5% 13.1% 8.9% 11.0% 

Daytime

Negative 88.5% 87.5% 86.9% 91.1% 89.0% 

 N=1,694 N=1,111 N=1,559 N=1,505 N=5,869 

Antidepressants 0.5% 0.2% 0.0% 0.1% 0.2% 

Marijuana 7.7% 7.6% 6.3% 4.1% 6.1% 

Narcotic-Analgesics 1.0% 2.8% 1.2% 1.8% 1.6% 

Sedatives 1.1% 0.2% 0.7% 0.4% 0.6% 

Stimulants 3.0% 2.3% 2.7% 4.0% 3.2% 

Other 0.2% 0.0% 0.1% 0.5% 0.3% 

More than 1 Class 1.6% 4.1% 2.9% 2.0% 2.3% 

Overall Drug Positive Nighttime 15.0% 17.3% 14.0% 12.9% 14.4% 

Nighttime

Negative 85.0% 82.7% 86.0% 87.1% 85.6% 

 “More than 1 Class” – Drivers testing positive for more than one drug are only counted in this category. 

In this table, percentages are weighted. 

Comparison of drug class by time and gender (Table 32) showed that males were significantly 

more likely to test positive for marijuana than females in samples of both daytime (5.9% males 

vs.1.7% females) and nighttime (7.4% males vs. 4.1% females) drivers (p < .01). In the daytime 

sample, females were more likely to test positive for narcotic-analgesics and sedatives than were 

males (p < .01); however, a statistical difference of this kind was not detected in the nighttime 

sample. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 32. Drug Classes Distribution by Time of Day and Gender (Oral Fluid) 

Time of 

Day Drug Class 

Males 

% 

Females 

% 

Total 

% 

N=1,032 N=811 N=1,843 

Antidepressants 0.1% 0.9% 0.5% 

Marijuana 5.9% 1.7% 4.0% 

Narcotic-Analgesics 1.0% 2.5% 1.7% 

Sedatives 1.2% 2.2% 1.6% 

Stimulants 1.8% 1.4% 1.6% 

Other 0.0% 0.5% 0.2% 

More than 1 Class 1.0% 2.1% 1.5% 

Overall Drug Positive Daytime 11.0% 11.3% 11.1% 

Daytime

Negative 89.0% 88.7% 88.9% 

 N=3,605 N=2,250 N=5,855 

Antidepressants 0.3% 0.1% 0.2% 

Marijuana 7.4% 4.1% 6.1% 

Narcotic-Analgesics 1.8% 1.3% 1.6% 

Sedatives 0.4% 1.0% 0.6% 

Stimulants 3.3% 3.1% 3.2% 

Other 0.3% 0.3% 0.3% 

More than 1 Class 3.0% 1.4% 2.4% 

Overall Drug Positive Nighttime 16.5% 11.3% 14.5% 

Nighttime

Negative 83.5% 88.7% 85.5% 

“More than 1 Class” – Drivers testing positive for more than one drug are only counted in this 

category. 

In this table, percentages are weighted. 

When we examined drug classes by time of day and age (Table 33), we found that daytime 

drivers aged 21-34 were more likely to use marijuana (7.4%) than daytime drivers in other age 

groups (p < .01). However, drivers aged 16-20 years had the highest marijuana use (9.8%) in the 

nighttime sample, followed by the 21-34 year age group (8.5%) both of which were statistically 

higher than the other age groups (p < .01). The prevalence of narcotic-analgesics was highest 

among daytime drivers aged 44-64 (2.9%) (p < .01); however, in the nighttime sample, the 35-44 

age group recorded the highest prevalence of narcotic-analgesics (4.2%) (p < .01). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 33. Drug Class Distribution by Time of Day and Age (Oral Fluid) 

Time of 

Day Drug Class 

16-20 

% 

21-34 

% 

35-44 

% 

45-64 

% 

65+ 

% 

Total 

% 

 N=99 N=436 N=374 N=668 N=245 N=1,822

Antidepressants 0.9% 0.2% 0.3% 0.8% 0.3% 0.5% 

Marijuana 4.4% 7.4% 4.8% 1.7% 0.7% 4.0% 

Narcotic-Analgesics 0.0% 0.7% 1.9% 2.9% 0.8% 1.7% 

Sedatives 0.7% 0.2% 1.4% 2.3% 4.0% 1.6% 

Stimulants 0.3% 2.2% 1.2% 2.2% 0.1% 1.6% 

Other 0.0% 0.0% 0.0% 0.7% 0.0% 0.2% 

More than 1 Class 0.0% 0.6% 2.1% 2.6% 0.3% 1.5% 

Overall Drug Positive 

Daytime 6.2% 11.2% 11.6% 13.3% 6.4% 11.1% 

Daytime

Negative 93.8% 88.8% 88.4% 86.7% 93.6% 88.9% 

 N=961 N=2,437 N=1,042 N=1,216 N=148 N=5,804

Antidepressants 0.3% 0.1% 0.4% 0.1% 0.3% 0.2% 

Marijuana 9.8% 8.5% 4.1% 1.1% 0.0% 6.2% 

Narcotic-Analgesics 1.1% 0.8% 4.2% 1.4% 0.4% 1.6% 

Sedatives 0.0% 0.6% 1.2% 0.7% 1.3% 0.7% 

Stimulants 2.0% 3.6% 2.8% 4.5% 0.0% 3.3% 

Other 0.2% 0.5% 0.2% 0.1% 0.0% 0.3% 

More than 1 Class 2.7% 2.9% 2.2% 1.5% 0.0% 2.4% 

Overall Drug Positive 

Nighttime 16.1% 17.1% 15.2% 9.5% 2.0% 14.6% 

Nighttime

Negative 83.9% 82.9% 84.8% 90.5% 98.0% 85.4% 

 “More than 1 Class” – Drivers testing positive for more than one drug are only counted in this category. 

In this table, percentages are weighted. 

Driver Drug Use Prevalence by Drug Category Based on 

Oral Fluid Results 

In this section of the report, we display drug use prevalence results from oral fluid tests by drug 

category. The three drug categories were: illegal, prescription, and over-the-counter. Because 

there were very few positive results for over-the-counter drugs, the prescription and over-thecounter categories are combined in these tables into a single category (“Medications”). 

Additionally, some respondents tested positive for more than one category of drug. Thus, tables 

presenting drug categories present four mutually exclusive categories: Illegal; Medications; 

Illegal and Medications; and Negative. So as not to double count individual positive results, an 

individual’s result appears in only one of these categories. However, for example in Table 34, to 

determine the proportion of daytime drivers who tested positive for illegal drugs, one could sum 

the daytime values for the “Illegal” category (5.8%) and for the ” Illegal & Medications” 

category (0.5%) to arrive at a prevalence estimate of 6.3% of daytime drivers who were positive 

for at least one illegal drug. Detailed summaries of prevalence estimates for individual drugs 

appear in Tables 137-140 later in the report. 

 As previously noted, drugs may be classified in different ways depending on the use of the 

classification system. For example, in NHTSA’s drug evaluation and classification (DEC) 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

49 

program, the categories CNS Depressants, CNS Stimulants, Hallucinogens, Dissociative 

Anesthetic (PCP), Narcotic Analgesics, Inhalants, and Cannabis are used. 

Comparison of drug categories by time of day (Table 34) reveal that almost 6 percent of daytime 

drivers tested positive for drugs in the “Illegal” category as opposed to over 10 percent of 

nighttime drivers. This was a statistically significant difference between the two groups (p < .01). 

Positive results in the “Medications” category, although not statistically significant, were found 

to be slightly higher among the daytime drivers (almost 5%) than nighttime drivers (3%). 

Table 34. Drug Categories Distribution by Time of Day (Oral Fluid) 

Time of Day Drug Category 

N 

(Unweighted) 

% 

(Weighted) 

Illegal 125 5.8% 

Medications 107 4.8% 

Illegal & Medications 14 0.5% 

Negative 1,604 89.0% 

 

Daytime

Overall Daytime 1,850 100.0% 

Illegal 575 10.5% 

Medications 201 3.0% 

Illegal & Medications 60 0.9% 

Negative 5,033 85.6% 

 

Nighttime

Overall Nighttime 5,869 100.0% 

“Medications” includes prescription and over-the-counter drugs. 

Comparison of drug categories by time of day and region (Table 35) showed that, of daytime 

drivers, the South region had the highest percentage of positive results for “Illegal” followed by 

the West region, however these differences were not statistically significant. In the nighttime 

sample, the Midwest region had the highest percentage of “Illegal” drug prevalence, although 

this difference was not statistically significant. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 35. Drug Categories Distribution by Time of Day and Region (Oral Fluid) 

Time Region Drug Category 

N 

(Unweighted) 

% 

(Weighted) 

Illegal 38 4.2% 

Medications 47 6.7% 

Illegal & Medications 5 0.5% 

Negative 456 88.5% 

 

Midwest 

Overall 546 100.0% 

Illegal 20 4.9% 

Medications 20 7.5% 

Illegal & Medications 2 0.1% 

Negative 337 87.5% 

 

Northeast 

Overall 379 100.0% 

Illegal 35 8.2% 

Medications 22 4.6% 

Illegal & Medications 5 0.3% 

Negative 410 86.9% 

South 

Overall 472 100.0% 

Illegal 32 6.3% 

Medications 18 2.0% 

Illegal & Medications 2 0.7% 

Negative 401 91.1% 

Daytime 

West 

Overall 453 100.0% 

Illegal 185 11.5% 

Medications 68 3.0% 

Illegal & Medications 14 0.4% 

Negative 1,427 85.0% 

Midwest 

Overall 1,694 100.0% 

Illegal 112 10.8% 

Medications 32 4.2% 

Illegal & Medications 14 2.3% 

Negative 953 82.7% 

Northeast 

Overall 1,111 100.0% 

Illegal 131 10.2% 

Medications 59 2.5% 

Illegal & Medications 22 1.3% 

Negative 1,347 86.0% 

South 

Overall 1,559 100.0% 

Illegal 147 9.8% 

Medications 42 2.6% 

Illegal & Medications 10 0.5% 

Negative 1,306 87.1% 

Nighttime 

West 

Overall 1,505 100.0% 

“Medications” includes prescription and over-the-counter drugs. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

51 

When examining prevalence by drug category and gender (Table 36), we found that, in the 

daytime sample, male drivers were more likely to test positive for “Illegal” drugs (8.2%) than 

female drivers (3.0%) (p < .01). Conversely, daytime female drivers were more likely to show 

positive results for “Medications” (7.6%) than daytime male drivers (2.5%) (p < .01). In the 

nighttime sample, 12.5 percent of male drivers tested positive for “Illegal” drugs, as opposed to 

7.5 percent of female drivers (p < .01). The difference in percentage of positive results for 

“Medications” between male and female drivers was not as striking in the nighttime sample as in 

the daytime sample and was not statistically significant. 

Table 36. Drug Categories Distribution by Time of Day and Gender (Oral Fluid) 

Time of Day Gender Drug Category 

N 

(Unweighted) 

% 

(Weighted) 

Illegal 87 8.2% 

Medications 35 2.5% 

Illegal & Medications 9 0.3% 

Negative 901 89.0% 

 

Male

Overall 1,032 100.0% 

Illegal 38 3.0% 

Medications 72 7.6% 

Illegal & Medications 5 0.6% 

Negative 696 88.7% 

Daytime 

 

Female

Overall 811 100.0% 

Illegal 410 12.5% 

Medications 106 2.8% 

Illegal & Medications 41 1.1% 

Negative 3,048 83.5% 

 

Male

Overall 3,605 100.0% 

Illegal 164 7.5% 

Medications 95 3.3% 

Illegal & Medications 19 0.5% 

Negative 1,972 88.7% 

Nighttime 

 

Female

Overall 2,250 100.0% 

“Medications” includes prescription and over-the-counter drugs. 

In this table, percentages are weighted. 

In comparing drug categories by time of day and age (Table 37), it was clear that, within the 

daytime sample, “Illegal” drug use was highest for drivers aged 21-34 (9.9%) followed by 

drivers aged 35-44 (6.5%). The prevalence of “Illegal” drugs for these age groups differed 

significantly from that in the remaining age groups (p < .01). In the nighttime sample, drivers in 

the 21-34 year age group still maintained the highest percentage (14.2%) of positive results for 

“Illegal” drugs; however, that group was followed by the youngest age group (16-20 years) for 

“Illegal” drugs (13.1%) (p < .01). The use of “Medications” was highest among the 45-64 year 

age group (8.8%) in the daytime sample (non-significant), and in the 35-44 year old age group 

the nighttime sample (6.9%) (p < .01). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

52 

Table 37. Drug Categories Distribution by Time of Day and Age (Oral Fluid) 

Time of Day Age Drug Category 

N 

 (Unweighted) 

% 

(Weighted) 

Illegal 9 4.6% 

Medications 2 1.6% 

Illegal & Medications 0 0.0% 

Negative 88 93.8% 

16-20 

Overall 99 100.0% 

Illegal 54 9.9% 

Medications 14 1.2% 

Illegal & Medications 4 0.1% 

Negative 364 88.8% 

21-34 

Overall 436 100.0% 

Illegal 25 6.5% 

Medications 23 4.2% 

Illegal & Medications 3 1.0% 

Negative 323 88.4% 

35-44 

Overall 374 100.0% 

Illegal 32 3.9% 

Medications 51 8.8% 

Illegal & Medications 7 0.6% 

Negative 578 86.7% 

45-64 

Overall 668 100.0% 

Illegal 3 0.8% 

Medications 17 5.6% 

Illegal & Medications 0 0.0% 

Negative 225 93.6% 

Daytime 

65+ 

Overall 245 100.0% 

Illegal 120 13.1% 

Medications 11 1.6% 

Illegal & Medications 12 1.4% 

Negative 818 83.9% 

16-20 

Overall 961 100.0% 

Illegal 308 14.2% 

Medications 55 1.9% 

Illegal & Medications 28 1.0% 

Negative 2,045 82.9% 

 

21-34 

Overall 2,436 100.0% 

Illegal 82 7.6% 

Medications 57 6.9% 

Illegal & Medications 11 0.7% 

Nighttime 

35-44 

Negative 892 84.8% 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

53 

Time of Day Age Drug Category 

N 

 (Unweighted) 

% 

(Weighted) 

Overall 1,042 100.0% 

Illegal 64 5.7% 

Medications 67 3.0% 

Illegal & Medications 9 0.7% 

Negative 1,075 90.5% 

45-64 

Overall 1,215 100.0% 

Illegal 0 0.0% 

Medications 9 2.0% 

Illegal & Medications 0 0.0% 

Negative 139 98.0% 

65+ 

Overall 148 100.0% 

“Medications” includes prescription and over-the-counter drugs. 

In this table, percentages are weighted. 

Driver Drug Prevalence Based on Oral Fluid and BAC Results 

The following section presents the results of the oral fluid drug analyses combined with the 

blood alcohol concentration (BAC) results obtained from breath tests.16 Categories for BAC by 

grams per deciliter (g/dL) are indicated as “zero” (BAC less than .005 g/dL), “between zero and 

.08” (greater than .005 up to .08 g/dL), and “.08+” (BAC greater than .08 g/dL). Note that the 

daytime sample consisted of very few drug positive drivers with alcohol positive results, which 

limited the statistical testing that could be done. 

In comparing the number of drug-positive drivers by time of day and BAC level (Tables 38 and 

39), a statistically significant association was found between drug-positive and alcohol-positive 

drivers within the nighttime driving sample. In other words, the percentage of nighttime drivers 

with BAC g/dL .08+ was significantly higher among drug-positive drivers than among drugnegative drivers (p < .01). 

The same association was observed with the “between zero and .08” category among drugpositive nighttime drivers (p < .01) relative to drug-negative drivers. However, for daytime 

drivers, no statistical association was found, largely because of the small number of alcoholpositive drivers in the daytime sample. 

Note that, because of the small number of alcohol-positive drivers in the daytime sample (n = 

23), comparisons involving drug-positive drivers for this group of drivers were not attempted in 

the remaining portion of this report. 

 

16 More complete information on the alcohol results (not including drug results) is available in Lacey et al. (2009b). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

54 

Table 38. Drug Prevalence by Time of Day and BAC (Percentages Calculated by Row) (Oral Fluid) 

 BAC (g/dL) 

Time of 

Day 

Drug 

Result 

N 

(Unweighted) Zero 

Between 

Zero and .08 .08+ 

 Positive 246 98.2% 1.4% 0.3% 

Daytime Negative 1,599 99.2% 0.6% 0.2% 

 Overall Daytime 1,845 99.1% 0.7% 0.2% 

Positive 836 80.5% 15.0% 4.5% 

Negative 5,031 90.2% 8.1% 1.7% 

 

Nighttime 

 Overall Nighttime 5,867 88.8% 9.1% 2.1% 

In this table, percentages are weighted. 

Table 39. Drug Prevalence by Time of Day and BAC (Percentages Calculated by Column) 

(Oral Fluid) 

 BAC (g/dL)

Time of 

Day Drug 

 Result Zero 

Between 

Zero and .08 .08+ All 

 N=1,822 N=18 N=5 N=1,845 

Daytime Positive 10.9% 22.2% 17.1% 11.0% 

 Negative 89.1% 77.8% 82.9% 89.0% 

 N=5,207 N=530 N=130 N=5,867 

Nighttime Positive 13.1% 23.9% 30.6% 14.4% 

 Negative 86.9% 76.1% 69.4% 85.6% 

In this table, “Ns” are unweighted and percentages are weighted.

Table 40 shows that, within the daytime sample, drug-positive drivers in the age groups 16-20 

and 21-34 had the greatest percentage of alcohol-positive results; however, it should be noted 

that the sample size for the youngest group was only 11. Among nighttime drug-positive 

participants, drivers aged 21-34 had the greatest percentage of alcohol positives (in both the 

categories BAC between zero and .08, and BAC .08+) (p < .01). As noted earlier, the number of 

years within age categories is not equivalent. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

55 

Table 40. BAC Among Drug-Positive Drivers by Time of Day and Age (Oral Fluid) 

 BAC (g/dL) 

Time of 

Day Age 

N 

(Unweighted) Zero 

Between 

Zero and .08 .08+ 

16-20 11 89.7% 0.0% 10.3% 

21-34 72 95.5% 4.5% 0.0% 

35-44 51 99.2% 0.8% 0.0% 

45-64 90 99.8% 0.2% 0.0% 

65+ 20 100.0% 0.0% 0.0% 

Daytime 

Overall Positive Daytime 244 98.2% 1.4% 0.3% 

16-20 143 86.8% 10.0% 3.2% 

21-34 392 75.0% 19.7% 5.3% 

35-44 150 87.8% 8.5% 3.7% 

45-64 141 81.0% 14.3% 4.7% 

65+ 9 83.6% 16.4% 0.0% 

Nighttime 

Overall Positive Nighttime 835 80.4% 15.0% 4.5% 

In this table, percentages are weighted.

Among both daytime and nighttime drivers, there were fewer alcohol-positive drivers among 

drug-positive drivers with 2+ classes of drugs than among those with one class of drug (Tables 

41 and 42); however, due to the small sample size, there was no statistical difference.

Table 41. BAC Among Drug-Positive Drivers by Number of Drug Classes and Time of Day 

(Percentages Calculated by Column) (Oral Fluid) 

 BAC (g/dL) 

Time of Day 

Number of Drug 

Classes 

N 

(Unweighted) Zero 

Between 

Zero and .08 .08+ 

1 206 86.0% 95.1% 100.0% 

Daytime 2+ 40 14.0% 4.9% 0.0% 

Overall Daytime 246 100.0% 100.0% 100.0% 

1 680 83.4% 81.6% 96.3% 

Nighttime 2+ 156 16.6% 18.4% 3.7% 

Overall Nighttime 836 100.0% 100.0% 100.0% 

In this table, percentages are weighted.
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

56 

Table 42. BAC Among Drug-Positive Drivers by Number of Drug Classes and Time of Day 

(Percentages Calculated by Row) (Oral Fluid) 

 BAC (g/dL) 

Time of Day 

Number of Drug 

Classes 

N 

(Unweighted) Zero 

Between 

Zero and .08 .08+ 

1 206 98.0% 1.6% 0.4% 

Daytime 2+ 40 99.5% 0.5% 0.0% 

Overall Daytime 246 98.2% 1.4% 0.3% 

1 680 80.1% 14.7% 5.2% 

Nighttime 2+ 156 82.0% 17.0% 1.0% 

Overall Nighttime 836 80.5% 15.0% 4.5% 

In this table, percentages are weighted.

When oral fluid drug category findings were combined with BAC results we found that, in both 

the daytime and nighttime samples, the drug-positive drivers who were also alcohol-positive 

were more likely to be positive for “Illegal” drugs than “Medications” (Table 43). This was 

particularly true in the nighttime sample, in which 17.3 percent had BACs between zero and .08 

(compared to 6.3% in the “Medications” category) and 5.7 percent had BACs greater than .08 

(compared to 1.2% in the “Medications” category) (p < .01). In the daytime sample, however, the 

differences were statistically non-significant (p value = .05). 

Table 43. BAC Among Drug-Positive Drivers by Drug Category and Time of Day (Oral Fluid) 

 BAC (g/dL) 

Time of 

Day Drug Category 

N 

(Unweighted) Zero 

Between 

Zero and .08 .08+ 

 Illegal 125 97.1% 2.3% 0.6% 

Daytime Medications 107 99.6% 0.4% 0.0% 

 Illegal & Medications 14 98.3% 1.7% 0.0% 

 Negative 1,604 99.2% 0.6% 0.2% 

 Illegal 575 77.0% 17.3% 5.7% 

Nighttime Medications 199 92.5% 6.3% 1.2% 

 Illegal & Medications 60 81.4% 17.7% 0.9% 

 Negative 5,033 90.2% 8.1% 1.7% 

“Medications” includes prescription and over-the-counter drugs. 

In this table, percentages are weighted. 

Table 44 presents the findings by drug category, age, and time of day. Due to the number of 

groupings (and thus, relatively small sample sizes in included cells), caution should be exercised 

in the interpretation of the findings, especially among the daytime driving sample. Overall, 

among the nighttime driving sample, the high alcohol-positive drivers (i.e., drivers registering 

greater than .08 BAC g/dL) tested positive for drugs in the “Illegal” category more frequently 

than “Medications” across all age groups except 65+ (an age group producing a very small 

sample size for drug positives). Further, the same pattern emerged among drivers with BACs 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

57 

between zero and .08 across all age groups, except for the age category 45-64, where a high 

proportion of drivers tested positive for both “Illegal and Medications.”

Table 44. BAC of Drivers by Drug Category, Age, and Time of Day (Oral Fluid) 

 BAC (g/dL) 

Time of 

Day Age Drug Category 

N 

(Unweighted) Zero 

Between 

Zero and .08 .08+ 

Illegal 9 86.1% 0.0% 13.9% 

Medications 2 100.0% 0.0% 0.0% 

Illegal & Medications 0 NA NA NA 

Negative 88 99.3% 0.7% 0.0% 

16-20 

Overall 99 98.7% 0.7% 0.6% 

Illegal 54 95.7% 4.3% 0.0% 

Medications 14 93.2% 6.8% 0.0% 

Illegal & Medications 4 100.0% 0.0% 0.0% 

Negative 364 99.4% 0.5% 0.1% 

21-34 

Overall 436 99.0% 1.0% 0.1% 

Illegal 25 98.6% 1.4% 0.0% 

Medications 23 100.0% 0.0% 0.0% 

Illegal & Medications 3 100.0% 0.0% 0.0% 

Negative 323 99.1% 0.7% 0.2% 

35-44

Overall 374 99.1% 0.7% 0.1% 

Illegal 32 100.0% 0.0% 0.0% 

Medications 51 100.0% 0.0% 0.0% 

Illegal & Medications 7 95.8% 4.2% 0.0% 

Negative 578 98.7% 0.9% 0.4% 

45-64 

Overall 668 98.9% 0.8% 0.3% 

Illegal 3 100.0% 0.0% 0.0% 

Medications 17 100.0% 0.0% 0.0% 

Illegal & Medications 0 NA NA NA 

Negative 225 99.8% 0.1% 0.1% 

Daytime 

 

65+ 

Overall 245 99.8% 0.1% 0.1% 

Illegal 120 83.9% 12.1% 4.0% 

Medications 11 100.0% 0.0% 0.0% 

Illegal & Medications 12 99.0% 1.0% 0.0% 

Negative 818 94.4% 5.1% 0.5% 

 

16-20 

Overall 961 93.1% 5.9% 1.0% 

Illegal 308 73.6% 20.4% 6.1% 

Medications 55 80.9% 17.0% 2.1% 

Illegal & Medications 28 84.6% 15.4% 0.0% 

Negative 2,045 87.8% 9.8% 2.4% 

21-34 

Overall 2,436 85.6% 11.5% 2.9% 

Illegal 82 77.7% 15.9% 6.4% 

Medications 57 98.5% 0.4% 1.1% 

Illegal & Medications 11 92.7% 7.3% 0.0% 

Negative 892 91.9% 6.7% 1.4% 

Nighttime 

35-44

Overall 1,042 91.3% 7.0% 1.7% 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

58 

 BAC (g/dL) 

Time of 

Day Age Drug Category 

N 

(Unweighted) Zero 

Between 

Zero and .08 .08+ 

Illegal 64 80.8% 12.6% 6.6% 

Medications 67 92.2% 7.0% 0.8% 

Illegal & Medications 9 33.3% 60.9% 5.8% 

Negative 1,075 90.1% 8.7% 1.3% 

45-64 

Overall 1,215 89.2% 9.2% 1.6% 

Illegal 0 NA NA NA 

Medications 9 83.6% 16.4% 0.0% 

Illegal & Medications 0 NA NA NA 

Negative 139 88.7% 6.6% 4.7% 

65+ 

Overall 148 88.6% 6.8% 4.6% 

“Medications” includes prescription and over-the-counter drugs. 

In this table, percentages are weighted. 

When examining drug category by gender and time of day (Table 45), male drivers who tested 

positive for “Illegal” drugs in both the daytime and nighttime samples also had greater 

percentages of alcohol-positive results than their female counterparts. However, the small sample 

size precluded valid statistical testing on the daytime sample. Within the nighttime sample, 

differences were statistically significant (p < .01). 

Table 45. BAC of Drivers by Drug Category, Gender, and Time of Day (Oral Fluid) 

BAC (g/dL) 

Time of 

Day Gender Drug Category 

N 

(Unweighted) Zero 

Between 

Zero and .08 .08+ 

Illegal 87 96.7% 2.5% 0.8% 

Medications 35 98.5% 1.5% 0.0% 

Illegal & Medications 9 95.6% 4.4% 0.0% 

Negative 901 99.1% 0.8% 0.1% 

Males 

Overall 1,032 98.9% 0.9% 0.2% 

Illegal 38 98.4% 1.6% 0.0% 

Medications 72 100.0% 0.0% 0.0% 

Illegal & Medications 5 100.0% 0.0% 0.0% 

Negative 696 99.3% 0.5% 0.3% 

Daytime 

 

Females

Overall 811 99.3% 0.5% 0.2% 

Illegal 410 74.3% 18.0% 7.6% 

Medications 106 96.0% 3.1% 1.0% 

Illegal & Medications 41 76.6% 22.3% 1.1% 

Negative 3,048 90.0% 7.9% 2.1% 

 

Males

Overall 3,605 88.1% 9.2% 2.7% 

Illegal 164 84.2% 15.2% 0.6% 

Medications 95 87.5% 11.0% 1.5% 

Illegal & Medications 19 99.0% 1.0% 0.0% 

Negative 1,972 90.4% 8.3% 1.2% 

Nighttime 

 

Females

Overall 2,250 89.9% 8.9% 1.2% 

“Medications” includes prescription and over-the-counter drugs. 

In this table, percentages are weighted. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

59 

Drugs: Oral Fluid Results and Agreement with Self-Reported Drug Use 

Table 46 compares the results of the oral fluid analyses with responses to the self-reported drug 

use questionnaire. This questionnaire was administered to all drivers who provided an oral fluid 

sample, and was completed while the oral fluid device was collecting the saliva. 

The cross tabulation results of self-reported drug use (in the past 24 hours, past 2 days, past 

month, past year, over a year, and never) and oral fluid analysis results (by drug category) 

revealed interesting findings. Note that this table only reports on drivers who were drug-positive. 

Agreement between reported past 24-hour use and drug-positive analysis results for the 

nighttime driving sample was greatest (highest percentage) among antidepressants, cough 

suppressants, and pain killers. 

The lowest correspondence (lowest percentages) was found for amphetamines and barbiturates. 

Interestingly, approximately one-quarter of marijuana-positive nighttime drivers admitted to 

marijuana use in the previous 24 hours; this increased to over one-third when combined within 

the past two days. A smaller proportion (7.5% and 5.8% respectively) admitted to recent use of 

cocaine. 

 Among nighttime drivers who tested positive for antidepressants, the majority (66.4%) indicated 

they in fact used the substance in the past 24 hours. Thus, in this example, agreement between 

self-reports and oral fluid analysis results are fairly high. However, when we examine 

amphetamines (typically viewed as a recreational or illegal drug), agreement between self-report 

and a positive test analysis is low. Here, about 72 percent of nighttime positive drivers indicated 

they “never” had used the substance yet the drug analysis revealed a positive result. In some 

instances this may be related to a reluctance to disclose; however, in other instances a driver may 

not have been aware that the substance they were taking contained the drug being reported (for 

example, some drivers may not be aware that some diet pills contain amphetamines). Similar 

results were obtained for nighttime drivers providing blood samples. A table reflecting those 

results appears in Appendix A. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

60 

Table 46. Oral Fluid Results and Agreement with Self-Reported by Drug Type (Oral Fluid) 

Oral Fluid: Positive for that Drug 

Daytime Nighttime 

Drug Category 

Self-Reported 

Drug Use 

N 

(Unwtd) 

% 

(Weighted) 

N 

(Unwtd) 

% 

(Weighted) 

Past 24 Hours 13 85.7% 18 66.4% 

Past 2 Days 0 0.0% 0 0.0% 

Past Month 0 0.0% 2 9.6% 

Past Year 1 4.7% 0 0.0% 

Over a Year 0 0.0% 1 21.2% 

Never 4 9.6% 4 2.8% 

Antidepressants 

Overall 18 100.0% 25 100.0% 

Past 24 Hours 0 0.0% 1 2.0% 

Past 2 Days 0 0.0% 0 0.0% 

Past Month 0 0.0% 4 8.6% 

Past Year 0 0.0% 3 8.9% 

Over a Year 1 3.2% 10 8.8% 

Never 13 96.8% 51 71.8% 

Amphetamines 

Overall 14 100.0% 69 100.0% 

Past 24 Hours 1 1.4% 2 3.1% 

Past 2 Days 0 0.0% 0 0.0% 

Past Month 1 0.8% 0 0.0% 

Past Year 0 0.0% 0 0.0% 

Over a Year 0 0.0% 0 0.0% 

Never 4 97.8% 8 96.9% 

Barbiturates 

Overall 6 100.0% 10 100.0% 

Past 24 Hours 11 15.8% 14 24.4% 

Past 2 Days 0 0.0% 4 3.4% 

Past Month 0 0.0% 2 2.6% 

Past Year 0 0.0% 0 0.0% 

Over a Year 3 3.8% 5 2.2% 

Never 20 80.4% 37 67.4% 

Benzodiazepines 

Overall 34 100.0% 62 100.0% 

Past 24 Hours 1 0.4% 10 7.5% 

Past 2 Days 2 2.2% 7 5.8% 

Past Month 1 0.6% 10 4.8% 

Past Year 0 0.0% 17 6.8% 

Over a Year 3 18.6% 29 17.0% 

Never 30 78.2% 146 57.9% 

Cocaine 

Overall 37 100.0% 219 100.0% 

Past 24 Hours 2 94.5% 6 39.3% 

Past 2 Days 0 0.0% 2 19.8% 

Past Month 0 0.0% 3 12.9% 

Past Year 0 0.0% 1 2.3% 

 Cough 

Suppressants 

Over a Year 0 0.0% 1 3.7% 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

61 

Oral Fluid: Positive for that Drug 

Daytime Nighttime 

Drug Category 

Self-Reported 

Drug Use 

N 

(Unwtd) 

% 

(Weighted) 

N 

(Unwtd) 

% 

(Weighted) 

Never 1 5.5% 2 22.0% 

Overall 3 100.0% 15 100.0% 

Past 24 hrs 0 NA 0 0.0% 

Past 2 days 0 NA 0 0.0% 

Past Month 0 NA 0 0.0% 

Past Year 0 NA 0 0.0% 

Over a Year 0 NA 0 0.0% 

Never 0 NA 1 100.0% 

Ketamine 

Overall 0 NA 1 100.0% 

Past 24 hrs 21 21.7% 91 25.7% 

Past 2 days 10 14.9% 37 10.5% 

Past Month 15 15.2% 55 11.4% 

Past Year 6 4.6% 44 7.4% 

Over a Year 19 16.7% 65 13.1% 

Never 28 26.7% 134 32.1% 

Marijuana 

Overall 99 100.0% 426 100.0% 

Past 24 hrs 1 96.6% 6 29.8% 

Past 2 days 0 0.0% 0 0.0% 

Past Month 1 2.9% 0 0.0% 

Past Year 0 0.0% 0 0.0% 

Over a Year 0 0.0% 0 0.0% 

Never 1 0.4% 4 70.2% 

Methadone 

Overall 3 100.0% 10 100.0% 

Past 24 hrs 4 13.0% 11 11.1% 

Past 2 days 2 3.7% 7 4.5% 

Past Month 6 18.7% 8 18.7% 

Past Year 4 1.9% 13 2.4% 

Over a Year 2 11.6% 17 15.7% 

Never 13 51.1% 51 47.6% 

Opiates 

Overall 31 100.0% 107 100.0% 

Past 24 hrs 13 27.5% 24 59.9% 

Past 2 days 5 12.9% 11 12.9% 

Past Month 6 13.1% 8 4.6% 

Past Year 4 6.5% 7 2.9% 

Over a Year 2 30.9% 7 13.8% 

Never 4 9.2% 9 5.8% 

Pain Killers 

Overall 34 100.0% 66 100.0% 

Past 24 hrs 1 100.0% 0 0.0% 

Past 2 days 0 0.0% 0 0.0% 

Past Month 0 0.0% 1 22.9% 

Past Year 0 0.0% 0 0.0% 

Over a Year 0 0.0% 0 0.0% 

Never 0 0.0% 1 77.1% 

PCP 

Overall 1 100.0% 2 100.0% 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

62 

Observed Safety Measures of Daytime and Nighttime Drivers (Oral 

Fluid) 

In the 2007 NRS, interviewers observed and recorded seat belt use of drivers and helmet use of 

motorcycle riders. Additionally, participating drivers were asked if they were acting as 

designated drivers (“Tonight/Today, are you, or have you been a designated driver?”). The 

results of analyses of these variables by alcohol level are discussed in some detail in a previous 

report summarizing the alcohol results (Lacey et al., 2009b). One issue that arose in that analysis 

was that many respondents appeared to not understand the ‘designated driver’ question. Thus, in 

this report we are not reporting on the designated driver results. Additionally, since the nighttime 

results are quite similar, whether summarized by oral fluid results or blood results, we are 

presenting these tables on observed seat belt and helmet use only in the oral fluid results section 

of the body of the report. The nighttime blood results are presented in Appendix A. 

Information on seat belt and helmet use is presented by overall prevalence (daytime and 

nighttime), drug class (daytime and nighttime), and drug category (daytime and nighttime) in 

Tables 47-52, respectively. 

In Table 47, there was no statistically significant association between overall daytime drug 

prevalence among drivers and seat belt use in the daytime sample. 

Table 47. Daytime: Seat Belt Observation 

by Drug Prevalence (Oral Fluid) 

 

 N 

(Unweighted)

% Drug 

Negative 

(Weighted)

% Drug 

Positive 

(Weighted) 

Driver Seat Belt Observation 

Yes 1,750 89.0% 11.0% 

No 92 86.2% 13.8% 

When examining nighttime drug use as measured in oral fluid by observed seat belt use (Table 

48), drug prevalence among nighttime drivers was significantly higher among those who did not 

wear a seat belt than among those who did (p < .01). 

Table 48. Nighttime: Seat Belt Observation by Drug Prevalence (Oral Fluid)

 

 N 

(Unweighted)

% Drug 

Negative 

(Weighted)

% Drug 

Positive 

(Weighted) 

Driver Seat Belt Observation 

Yes 5,654 85.9% 14.1% 

No 192 75.4% 24.6% 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

63 

Table 49 shows the daytime distribution of drug classes in oral fluid by observed seat belt use. 

Most of the observed differences in this distribution were not statistically significant. The 

exception was marijuana, which was significantly more prevalent among daytime drivers who 

did not wear a seat belt than among drivers who did (p < .01). 

Table 49. Daytime: Seat Belt Observation by Drug Class 

(Percentages Calculated by Row) (Oral Fluid) N (Unweighted) % Antidepressants (Weighted) % Marijuana (Weighted) % Narcotic-Analgesic (Weighted) % Sedatives (Weighted) % Stimulants (Weighted) 

% Other (Weighted) % >1 Drug Class (Weighted) % Negative (Weighted) 

Driver Seat Belt Observation

Yes 1,750 0.5% 3.7% 1.7% 1.7% 1.7% 0.2% 1.5% 89.0% 

No 92 0.8% 9.8% 1.3% 0.4% 0.0% 0.0% 1.5% 86.2% 

Table 50 shows the nighttime distribution of drug classes by seat belt use. Stimulants were 

significantly more prevalent among those drivers who did not wear a safety belt than those who 

did (p < .01). 

Table 50. Nighttime: Seat Belt Observation by Drug Class 

(Percentages Calculated by Row) (Oral Fluid) 

 

N (Unweighted) % Antidepressants (Weighted) % Marijuana (Weighted) % Narcotic-Analgesic (Weighted) % Sedatives (Weighted) % Stimulants (Weighted) % Other (Weighted) % >1 Drug Class  (Weighted) % Negative (Weighted) 

Driver Seat Belt Observation

Yes 5,654 0.1% 6.1% 1.6% 0.7% 3.1% 0.3% 2.2% 85.9%

No 192 2.3% 6.3% 2.1% 0.0% 7.9% 0.6% 5.3% 75.4%
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

64 

Table 51 shows the daytime distribution of drug categories by seat belt use. Differences in 

daytime oral fluid drug category results involving seat belt use by the driver were not statistically 

significant. 

Table 51. Daytime: Seat Belt Observation by Drug Category (Percentages Calculated by Row) 

(Oral Fluid)

 N 

(Unwtd) 

% 

Illegal 

(Weighted)

% 

Medications

(Weighted) 

% Illegal & 

Medications 

(Weighted) 

% 

Negative 

(Weighted)

Driver Seat Belt Observation 

Yes 1,750 5.6% 5.0% 0.4% 89.0%

No 92 10.3% 2.7% 0.7% 86.2%

Table 52 shows the nighttime distribution of drug categories by seat belt use. The prevalence of 

illegal (“Illegal” and “Illegal and Medication” combined) drugs was higher among those who did 

not use a seat belt (p < .01).

Table 52. Nighttime: Belt Observation by Drug Category (Percentages Calculated by Row) (Oral 

Fluid) 

 N 

(Unwtd) 

% 

Illegal 

(Weighted)

% 

Medications

(Weighted) 

% Illegal & 

Medications 

(Weighted) 

% Negative 

(Weighted) 

Driver Seat Belt Observation 

Yes 5,353 10.2% 3.0% 0.9% 85.9%

No 192 18.1% 5.0% 1.5% 75.4%

The number of motorcyclists sampled in the daytime was very small, thus limiting our ability to 

perform meaningful statistical comparisons. However, we display daytime and nighttime helmet 

use (for the operator) by overall drug use prevalence, class and category in Tables 53-58. Note 

there were an extremely low number of motorcycle riders with passengers. Thus, these are 

excluded from our tables and our analyses. 

Table 53. Daytime: Helmet Use for Motorcycle Riders (Operators), by Drug Positive (Oral Fluid) 

 

N 

(Unweighted)

% Drug Positive 

(Weighted) 

Motorcycle Riders (Operators) 30 24.8% 

Helmet 23 23.8% 

No Helmet Use 6 29.9% 

Unknown 1 0.0% 

Small sample size precluded meaningful statistical comparisons. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

65 

Table 54 shows a statistically significant difference in nighttime drug prevalence as measured in 

oral fluid among riders with and without helmets. Drug prevalence was higher for riders who 

were not using helmets (p < .01). 

Table 54. Nighttime: Helmet Use for Motorcycle Riders (Operators), by Drug Positive (Oral Fluid) 

 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Motorcycle Riders (Operators) 73 32.4% 

Helmet 57 14.7% 

No Helmet Use 14 65.3% 

Unknown 2 0.0% 

Examining daytime and nighttime motorcycle riders by drug class as measured in oral fluid, 

some classes had no positives, perhaps due to the small sample size (Tables 55 and 56), thus 

rendering statistical tests inappropriate. 

Table 55. Daytime: Helmet Use for Motorcycle Riders (Operators), by Drug Class (Oral Fluid)

 

N (Unweighted) % Antidepressants (Weighted) % Marijuana (Weighted) % Narcotic-Analgesic (Weighted) % Sedatives (Weighted) % Stimulants (Weighted) % Other (Weighted) % >1 Drug Class  (Weighted) % Negative (Weighted) 

Motorcycle Riders (Operators) 30 0.0% 13.2% 0.0% 1.3% 2.8% 0.0% 7.6% 75.2% 

Helmet 23 0.0% 16.9% 0.0% 1.7% 3.6% 0.0% 1.7% 76.2% 

No Helmet Use 6 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 29.9% 70.1% 

Unknown 1 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 

Small sample size precluded meaningful statistical comparisons. 

Table 56. Nighttime: Helmet Use for Motorcycle Riders (Operators) by Drug Class 

(Percentages Calculated by Row) (Oral Fluid) 

 

N (Unweighted) % Antidepressants (Weighted) % Marijuana (Weighted) % Narcotic-Analgesic (Weighted) % Sedatives (Weighted) % Stimulants (Weighted) % Other (Weighted) % >1 Drug Class  (Weighted) % Negative (Weighted) 

Motorcycle Riders (Operators) 73 6.3% 4.5% 0.0% 0.0% 8.3% 0.5% 12.8% 67.6% 

Helmet 57 1.0% 2.9% 0.0% 0.0% 1.3% 0.7% 8.7% 85.3% 

No Helmet Use 14 16.1% 7.5% 0.0% 0.0% 21.2% 0.0% 20.5% 34.7% 

Unknown 2 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100.0% 

Small sample size precluded meaningful statistical comparisons. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

66 

The small sample size encountered when examining daytime motorcycle riders by drug category 

as measured in oral fluid (Table 57) rendered statistical tests inappropriate. 

Table 57. Daytime: Helmet Use for Motorcycle Riders (Operators), by Drug Category (Oral Fluid)

 

 N 

(Unwtd)

% 

Illegal 

(Weighted) 

% 

Medications

(Weighted) 

% Illegal & 

Medications 

(Weighted) 

% 

Negative 

(Weighted) 

Motorcycle Riders (Operators) 30 15.9% 1.3% 7.6% 75.2% 

Helmet 23 20.4% 1.7% 1.7% 76.2% 

No Helmet Use 6 0.0% 0.0% 29.9% 70.1% 

Unknown 1 0.0% 0.0% 0.0% 100.0% 

Small sample size precluded meaningful statistical comparisons. 

Table 58 shows that, overall, drug prevalence was higher for riders who were not using a helmet 

(p < .01). However, no statistically significant difference was observed between riders who 

consumed “Illegal” and “Illegal and Medications,” and those who consumed “Medications” 

alone. 

Table 58. Nighttime: Helmet Use for Motorcycle Riders (Operators), by Drug Category 

(Percentages Calculated by Row) (Oral Fluid) 

 

 N 

(Unwtd) 

% 

Illegal 

(Weighted) 

% 

Medications 

(Weighted) 

% Illegal & 

Medications 

(Weighted) 

% 

Negative 

(Weighted) 

Motorcycle Riders (Operators) 73 20.0% 6.8% 5.6% 67.6% 

Helmet 57 4.2% 1.8% 8.7% 85.3% 

No Helmet Use 14 49.2% 16.1% 0.0% 34.7% 

Unknown 2 0.0% 0.0% 0.0% 0.0% 

Reported Contact with the Criminal Justice System (Oral Fluid) 

Of the 1,790 daytime NRS participants who provided an oral fluid sample and responded to the 

question, “During the past 12 months, were you arrested and booked for driving under the 

influence of alcohol or drugs?” about 3 percent indicated “Yes” (n = 47 unweighted). Of these, 

almost 29 percent were drug positive (Table 59). The difference between daytime drivers who 

indicated “Yes” to this question and were drug positive is statistically different from those who 

indicated “No” (p < .01). 

Table 59. Arrests and Drug Positives, Daytime (Oral Fluid): “During the past 12 months, were you 

arrested and booked for driving under the influence of alcohol or drugs?” 

 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Yes 47 28.9% 

No 1,743 10.8% 

Total 1,790 11.3% 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

67 

Among the nighttime NRS participants who provided an oral fluid sample and responded to the 

question, “During the past 12 months, were you arrested and booked for driving under the 

influence of alcohol or drugs?” (Table 60) approximately 4 percent indicated “Yes” (n = 234 

unweighted). Of these, 29 percent were drug positive compared to the 14 percent who were drug 

positive and indicated “No” (p < .01). 

Additionally, since the nighttime results are quite similar, whether summarized by oral fluid 

results or blood results, we are presenting these tables on contact with the criminal justice system 

based on nighttime blood results in Appendix A. 

Table 60. Arrests and Drug Positives, Nighttime (Oral Fluid): “During the past 12 months, were you 

arrested and booked for driving under the influence of alcohol or drugs?” 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Yes 234 29.1% 

No 5,458 14.0% 

Total 5,692 14.5% 

Of the daytime drivers who were drug positive and responded to the question, “During the past 

12 months, were you arrested and booked for driving under the influence of alcohol or drugs?” 

(Table 61) the majority tested positive for marijuana (20.7%).

Table 61. Arrests and Drug Class, Daytime (Oral Fluid): “During the past 12 months, were you 

arrested and booked for driving under the influence of alcohol or drugs?” 

 

N (Unweighted) % Antidepressants (Weighted) % Marijuana (Weighted) % Narcotic-Analgesic (Weighted) % Sedatives (Weighted) % Stimulants (Weighted) % Other (Weighted) % >1 Drug Class  (Weighted) % Negative (Weighted) 

Yes 47 0.0% 20.7% 2.0% 2.6% 2.4% 0.0% 1.1% 71.1%

No 1,743 1.6% 3.6% 1.7% 1.6% 1.6% 0.2% 1.6% 89.2%

Total 1,790 1.6% 4.0% 1.7% 1.6% 1.6% 0.2% 1.6% 88.7%

Similar to results in the daytime sample, the nighttime drivers who were drug positive and 

responded to the question, “During the past 12 months, were you arrested and booked for driving 

under the influence of alcohol or drugs?” (Table 62) the majority tested positive for marijuana 

(11.8%). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

68 

Table 62. Arrests and Drug Class, Nighttime (Oral Fluid): “During the past 12 months, were you 

arrested and booked for driving under the influence of alcohol or drugs?” N (Unweighted) % Antidepressants (Weighted) % Marijuana (Weighted) % Narcotic-Analgesic (Weighted) % Sedatives (Weighted) % Stimulants (Weighted) % Other (Weighted) % >1 Drug Class (Weighted) % Negative 

(Weighted) 

Yes 234 0.0% 11.8% 0.2% 0.2% 10.8% 0.0% 6.0% 70.9%

No 5,458 0.2% 5.8% 1.7% 0.7% 3.0% 0.3% 2.3% 86.0%

Total 5,692 0.2% 6.0% 1.7% 0.7% 3.3% 0.3% 2.4% 85.5%

When examining the data by drug category, among daytime participants who responded to the 

question, “During the past 12 months, were you arrested and booked for driving under the 

influence of alcohol or drugs?” (Table 63) more participants tested positive for “Illegal” drugs 

than any other drug category (23.3%). 

Table 63. Arrests and Drug Categories, Daytime (Oral Fluid): “During the past 12 months, were 

you arrested and booked for driving under the influence of alcohol or drugs?” 

 

 N 

(Unwtd) 

% 

Illegal 

(Weighted) 

% 

Medications 

(Weighted) 

% Illegal & 

Medications 

(Weighted) 

% 

Negative 

(Weighted) 

Yes 47 23.3% 5.3% 0.2% 71.1% 

No 1,743 5.4% 4.9% 0.5% 89.2% 

Total 1,790 5.9% 4.9% 0.5% 88.7% 

Among nighttime participants who responded to the question, “During the past 12 months, were 

you arrested and booked for driving under the influence of alcohol or drugs?” (Table 64) more 

tested positive for “Illegal” drugs than any other drug category (26%). Although this was slightly 

higher than the daytime population, the difference was not statistically different. 

Table 64. Arrests and Drug Categories, Nighttime (Oral Fluid): “During the past 12 months, were 

you arrested and booked for driving under the influence of alcohol or drug?” 

 

 N 

(Unwtd) 

% 

Illegal 

(Weighted) 

% 

Medications 

(Weighted) 

% Illegal & 

Medications 

(Weighted) 

% 

Negative 

(Weighted) 

Yes 234 26.0% 1.3% 1.7% 70.9% 

No 5,458 9.9% 3.1% 0.9% 86.0% 

Total 5,692 10.5% 3.1% 0.9% 85.5% 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

69 

Reported Contact with the Health System (Oral Fluid) 

As indicated in previous reports on the 2007 NRS, questions relating to the criminal sanctions for 

drinking and drug use while driving were added to the survey items, as well as questions related 

to treatment for drug and alcohol use. These questions were added to the survey to investigate 

potential intervention opportunities. 

As shown in Table 65, less than 1 percent of daytime drivers responded “Yes” to the question, 

“During the past 12 months, did you ever stay at least overnight in an inpatient or residential 

drug or alcohol treatment program?” Of these, almost 45 percent were drug positive. 

Table 65. Past Treatment Program and Drug Positive, Daytime (Oral Fluid): “During the past 12 

months, did you ever stay at least overnight in an inpatient or residential drug or alcohol 

treatment program?” 

 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Yes 7 44.7% 

No 1,738 11.2% 

Total 1,745 11.2% 

Among nighttime drivers, less than 1 percent responded “Yes” to the question, “During the past 

12 months, did you ever stay at least overnight in an inpatient or residential drug or alcohol 

treatment program?” (Table 66) Of these, 37 percent were drug positive. 

The response patterns to these questions by nighttime drivers providing blood samples are quite 

similar to those reported here for nighttime oral fluid, and are presented separately in Appendix 

A. 

Table 66. Past Treatment Program and Drug Positive, Nighttime (Oral Fluid): “During the past 12 

months, did you ever stay at least overnight in an inpatient or residential drug or alcohol 

treatment program?” 

 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Yes 51 37.0% 

No 5,449 14.5% 

Total 5,500 14.6% 

(p < .01) 

Of daytime drivers who responded to the question, “Have you ever been admitted to an 

outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?”17

approximately 2.5 percent responded “Yes” (Table 67). Of these, 38.4 percent were drug 

positive. 

 

17 AA is Alcoholics Anonymous and NA is Narcotics Anonymous. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

70 

Table 67. Outpatient and Drug Positive, Daytime (Oral Fluid): “Have you ever been admitted to an 

outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?” 

 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Yes 44 38.4% 

No 1,754 10.7% 

Total 1,798 11.2% 

(p < .01) 

Of nighttime drivers who responded to the question, “Have you ever been admitted to an 

outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?” 

approximately 2.8 percent responded “Yes” (Table 68). Of these, 36 percent were drug positive. 

Table 68. Outpatient and Drug Positive, Nighttime (Oral Fluid): “Have you ever been admitted to an 

outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?” 

 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Yes 159 36.1% 

No 5,541 14.1% 

Total 5,700 14.5% 

(p < .01) 

Of daytime drivers who responded to the question, “During the past 12 months, have you 

received treatment for your drug or alcohol use in a self-help group such as Alcoholics 

Anonymous or Narcotics Anonymous?” approximately 1 percent responded “Yes” (Table 69). 

Of these, 43 percent were drug positive. Of the nighttime drivers who were asked the same 

question, approximately 2 percent responded “Yes” (Table 70), and approximately 18 percent of 

those were drug positive. 

Table 69. AA or NA and Drug Positives, Daytime (Oral Fluid): “During the past 12 months, have 

you received treatment for your drug or alcohol use in a self-help group such as Alcoholics 

Anonymous or Narcotics Anonymous?” 

 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Yes 17 43.1% 

No 1,778 10.9% 

Total 1,795 11.2% 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

71 

Table 70. AA or NA and Drug Positives, Nighttime (Oral Fluid): “During the past 12 months, have 

you received treatment for your drug or alcohol use in a self-help group such as Alcoholics 

Anonymous of Narcotics Anonymous?” 

 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Yes 107 18.3% 

No 5,587 14.5% 

Total 5,694 14.6% 

Of daytime drivers who responded to the question, “During the past 12 months, did you ever stay 

at least overnight in an impatient or residential drug or alcohol treatment program, for example, 

detox, rehab, a therapeutic community, or a hospital?” less than .5 percent responded “Yes” 

(Table 71). Of these, approximately 20 percent tested positive for marijuana and nearly 25 

percent tested positive for more than one drug. 

Table 71. Inpatient and Drug Class, Daytime (Oral Fluid): “During the past 12 months, did you ever 

stay at least overnight in an impatient or residential drug or alcohol treatment program, for 

example, detox, rehab, a therapeutic community, or a hospital?” N (Unweighted) % Antidepressants (Weighted) % Marijuana (Weighted) % Narcotic-Analgesic (Weighted) % Sedatives (Weighted) % Stimulants (Weighted) % Other (Weighted) % >1 Drug Class (Weighted) 

% Negative (Weighted) 

Yes 7 0.0% 20.3% 0.0% 0.0% 0.0% 0.0%24.5% 55.3%

No 1,738 0.5% 3.9% 1.7% 1.7% 1.6% 0.2% 1.6% 88.8%

Total 1,745 0.5% 3.9% 1.7% 1.7% 1.6% 0.2% 1.6% 88.8%

Of the nighttime drivers who were asked the same question, approximately 1 percent responded 

“Yes” (Table 72). Of those, approximately 14 percent tested positive for marijuana, and 

approximately 12 percent tested positive for more than one drug. Although a higher percentage 

responded “Yes” to the marijuana item during the day than at night, this difference was not 

statistically significant. 

 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

72 

Table 72. Inpatient and Drug Class, Nighttime (Oral Fluid): “During the past 12 months, did you 

ever stay at least overnight in an impatient or residential drug or alcohol treatment program, for 

example, detox, rehab, a therapeutic community, or a hospital?” N (Unweighted) % Antidepressants (Weighted) % Marijuana (Weighted) % Narcotic-Analgesic (Weighted) % Sedatives (Weighted) % Stimulants (Weighted) % Other (Weighted) % >1 Drug Class (Weighted) 

% Negative (Weighted) 

Yes 51 0.0% 14.4% 0.3% 1.4% 9.4% 0.0%11.5% 63.0%

No 5,449 0.2% 6.1% 1.6% 0.7% 3.2% 0.3% 2.4% 85.5%

Total 5,500 0.2% 6.1% 1.6% 0.7% 3.2% 0.3% 2.4% 85.4%

Of daytime drivers who responded to the question, “During the past 12 months, were you 

arrested and booked for driving under the influence of alcohol or drugs?” less than .5 percent 

responded “Yes” (Table 73). 

Table 73. Inpatients and Drug Category, Daytime (Oral Fluid): “During the past 12 months, were 

you arrested and booked for driving under the influence of alcohol or drugs?” 

 

 N 

(Unwtd) 

% 

Illegal 

(Weighted) 

% 

Medications 

(Weighted) 

% Illegal & 

Medications 

(Weighted) 

% 

Negative 

(Weighted) 

Yes 7 44.7% 0.0% 0.0% 55.3% 

No 1,738 5.7% 5.0% 0.5% 88.8% 

Total 1,745 5.8% 5.0% 0.5% 88.8% 

Of these, nearly 45 percent tested positive for “Illegal” drugs. Of the nighttime drivers who were 

asked the same question, approximately 1 percent responded “Yes” (Table 74), and 

approximately 23 percent of those tested positive for “Illegal” drugs. The difference in “Illegal” 

drug use from daytime to nighttime was not significant. 

Table 74. Inpatients and Drug Category, Nighttime (Oral Fluid): “During the past 12 months, were 

you arrested and booked for driving under the influence of alcohol or drugs?” 

 

 N 

(Unwtd) 

% 

Illegal 

(Weighted) 

% 

Medications 

(Weighted) 

% Illegal & 

Medications 

(Weighted) 

% 

Negative 

(Weighted) 

Yes 51 23.4% 2.3% 11.3% 63.0% 

No 5,449 10.6% 3.0% 0.9% 85.5% 

Total 5,500 10.6% 3.0% 1.0% 85.4% 

Of daytime drivers who responded to the question, “Have you ever been admitted to an 

outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?” 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

73 

approximately 2.5 percent responded “Yes” (Table 75). Of these, the most prevalent drug was 

marijuana (15.4%). Additionally, nearly 15 percent tested positive for narcotic-analgesics. 

Table 75. Outpatient and Drug Class, Daytime (Oral Fluid): “Have you ever been admitted to an 

outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?” N (Unweighted) % Antidepressants (Weighted) % Marijuana (Weighted) % Narcotic-Analgesic (Weighted) % Sedatives (Weighted) % Stimulants (Weighted) % Other (Weighted) % >1 Drug Class (Weighted) % Negative (Weighted) 

Yes 44 3.4% 15.4% 14.7% 0.0% 3.7% 0.0% 1.1% 61.6%

No 1,754 0.4% 3.8% 1.4% 1.7% 1.6% 0.2% 1.6% 89.3%

Total 1,798 0.4% 4.0% 1.7% 1.6% 1.6% 0.2% 1.6% 88.8%

Of the nighttime drivers who were asked the same question, nearly 3 percent responded “Yes” 

(Table 76), and nearly 14 percent tested positive for stimulants, which was more than any other 

drug category. Approximately 10 percent of those tested positive for marijuana, which was more 

than the daytime percentage; however, this difference was not statistically significant. 

Table 76. Outpatient and Drug Class, Nighttime (Oral Fluid): “Have you ever been admitted to an 

outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?” N (Unweighted) % Antidepressants (Weighted) % Marijuana (Weighted) % Narcotic-Analgesic (Weighted) % Sedatives (Weighted) % Stimulants (Weighted) % Other (Weighted) % >1 Drug Class (Weighted) % Negative (Weighted) 

Yes 159 1.6% 10.1% 6.5% 1.7% 13.8% 0.0% 2.3% 63.9%

No 5,541 0.2% 6.0% 1.6% 0.6% 3.0% 0.3% 2.4% 85.9%

Total 5,700 0.2% 6.0% 1.7% 0.7% 3.2% 0.3% 2.4% 85.5%

Of daytime drivers who responded to the question, “Have you ever been admitted to an 

outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?” 

approximately 2.5 percent responded “Yes” (Table 77). Of these, approximately 38 percent were 

drug positive, with nearly 20 percent testing positive for “Illegal” drugs. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

74 

Table 77. Outpatient and Categories, Daytime (Oral Fluid): “Have you ever been admitted to an 

outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?” 

 

 N 

(Unwtd) 

% 

Illegal 

(Weighted) 

% 

Medications 

(Weighted) 

% Illegal & 

Medications 

(Weighted) 

% 

Negative 

(Weighted) 

Yes 44 19.9% 18.1% 0.4% 61.6% 

No 1,754 5.6% 4.6% 0.5% 89.3% 

Total 1,798 5.9% 4.9% 0.5% 88.8% 

Of the nighttime drivers who were asked the same question, nearly 3 percent responded “Yes” 

(Table 78), and approximately 36 percent of those were drug positive, with nearly 25 percent 

testing positive for “Illegal” drugs. Although that percentage was higher for nighttime drivers 

than for daytime drivers, there was no statistical difference in the number of people testing 

positive for “Illegal” drugs between daytime and nighttime. 

Table 78. Outpatient and Categories, Nighttime (Oral Fluid): “Have you ever been admitted to an 

outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?” 

 

 N 

(Unwtd) 

% 

Illegal 

(Weighted) 

% 

Medications 

(Weighted) 

% Illegal & 

Medications 

(Weighted) 

% 

Negative 

(Weighted) 

Yes 159 24.9% 10.0% 1.2% 63.9% 

No 5,541 10.3% 2.9% 0.9% 85.9% 

Total 5,700 10.5% 3.1% 0.9% 85.5% 

Of daytime drivers who responded to the question, “During the past 12 months, have you 

received treatment for your drug or alcohol use in a self-help group such as AA or NA?” 

approximately 1 percent responded “Yes” (Table 79). Of these, the most prevalent drug class 

was narcotic-analgesic (23.3%). 

Table 79. AA, NA and Classes, Daytime (Oral Fluid): “During the past 12 months, have you 

received treatment for your drug or alcohol use in a self-help group such as AA or NA?” N (Unweighted) % Antidepressants (Weighted) % Marijuana (Weighted) % Narcotic-Analgesic (Weighted) % Sedatives (Weighted) % Stimulants (Weighted) % Other (Weighted) % >1 Drug Class (Weighted) % Negative (Weighted) 

Yes 17 2.1% 17.7% 23.3% 0.0% 0.0% 0.0% 0.0% 56.9%

No 1,778 0.4% 3.9% 1.5% 1.7% 1.6% 0.2% 1.6% 89.1%

Total 1,795 0.4% 4.0% 1.7% 1.6% 1.6% 0.2% 1.6% 88.8%
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

75 

Of the nighttime drivers who were asked the same question, nearly 2 percent responded “Yes” 

(Table 80), and nearly 10 percent tested positive for stimulants, which was more than any other 

drug category. Approximately 5 percent of those tested positive for marijuana, which was less 

than the daytime percentage of 18 percent; however, this difference was not statistically 

significant. 

Table 80. AA, NA and Classes, Nighttime (Oral Fluid): “During the past 12 months, have you 

received treatment for your drug or alcohol use in a self-help group such as AA or NA?” 

Of daytime drivers who responded to the question, “During the past 12 months, have you 

received treatment for your drug or alcohol use in a self-help group such as AA or NA?” 

approximately 1 percent responded “Yes” (Table 81). Of these, slightly more than 25 percent 

tested positive for “Medications,” and nearly 18 percent tested positive for “Illegal” drugs. 

Table 81. NA, AA and Drug Categories, Daytime (Oral Fluid): “During the past 12 months, have you 

received treatment for your drug or alcohol use in a self-help group such as AA or NA?” 

 

 N 

(Unwtd) 

% 

Illegal 

(Weighted) 

% 

Medications 

(Weighted) 

% Illegal & 

Medications 

(Weighted) 

% 

Negative 

(Weighted) 

Yes 17 17.7% 25.4% 0.0% 56.9% 

No 1,778 5.8% 4.7% 0.5% 89.1% 

Total 1,795 5.9% 4.9% 0.5% 88.8% 

Of the nighttime drivers who were asked the same question, nearly 2 percent responded “Yes” 

(Table 82), and nearly 15 percent tested positive for “Illegal” drugs. Although a greater 

percentage tested positive for “Illegal” drugs during the day than at night, this difference was not 

statistically significant. N (Unweighted) 

% Antidepressants (Weighted) % Marijuana (Weighted) % Narcotic-Analgesic (Weighted) % Sedatives (Weighted) % Stimulants (Weighted) % Other (Weighted) % >1 Drug Class  (Weighted) % Negative (Weighted) 

Yes 107 0.4% 5.3% 0.4% 0.5% 9.5% 0.0% 2.2% 81.7%

No 5,587 0.2% 6.1% 1.7% 0.7% 3.1% 0.3% 2.4% 85.5%

Total 5,694 0.2% 6.1% 1.7% 0.7% 3.2% 0.3% 2.4% 85.4%
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

76 

Table 82. NA, AA and Drug Categories, Nighttime (Oral Fluid): “During the past 12 months, have 

you received treatment for your drug or alcohol use in a self-help group such as AA or NA?” 

 

 N 

(Unwtd) 

% 

Illegal 

(Weighted) 

% 

Medications 

(Weighted) 

% Illegal & 

Medications 

(Weighted) 

% 

Negative 

(Weighted) 

Yes 107 14.9% 3.0% 0.4% 81.7% 

No 5,587 10.5% 3.1% 0.9% 85.5% 

Total 5,694 10.6% 3.1% 0.9% 85.4% 

Blood Results (Nighttime Samples) 

Driver Drug Use Prevalence Based on Blood Results 

This section of the report presents the overall results of blood analyses for all of the drugs 

indicated in the introductory section of this report. Blood samples were collected in addition to 

oral fluid samples because, typically, blood analyses are considered the “gold standard ”and is 

the more established technique for gathering information on drugs and their metabolites, as oral 

fluid analyses are a more recently developed technique. As expected, the results between the 

oral fluid and blood results are very similar. These blood results are presented to provide more 

complete results from our data analyses for those who are interested in seeing the results from 

both approaches. 

If a driver tested positive for one or more of the drugs for which we tested in blood, s/he was 

categorized as drug positive. Note that blood samples were only collected in the nighttime, and 

that more drivers provided oral fluid samples than blood samples. 

 

About 14 percent of the 3,276 nighttime drivers who provided blood samples were drug-positive 

(Table 83). 

Table 83. Drug Prevalence by Time of Day (Blood) 

Time of Day 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Daytime NA NA 

Nighttime 3,276 13.8% 

NA = “Not Applicable” 

Comparison of drug prevalence by session (Table 84) revealed that late-night (Sessions 3 and 5) 

drivers were significantly more likely to be drug-positive (17.9% and 16.8% respectively), as 

opposed to the earlier nighttime (Sessions 2 and 4) drivers (13.6% and 11.1% respectively) 

(p < .01). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 84. Drug Prevalence by Session (Blood) 

Session 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

2: Friday, 10:00 p.m. – Midnight 857 13.6% 

3: Friday, 1:00 a.m. – 3:00 a.m. 743 17.9% 

4: Saturday, 10:00 p.m. – Midnight 986 11.1% 

5: Saturday, 1:00 a.m. – 3:00 a.m. 690 16.8% 

Although the Northeast region had the greatest percentage of drug-positive findings in the 

nighttime driving sample (Table 85), such differences were not statistically significant. Thus, no 

clear pattern of drug prevalence by region emerged from the blood sample results. 

Table 85. Drug Prevalence by Region (Blood) 

Region 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Midwest 971 14.0% 

Northeast 584 14.5% 

South 862 13.4% 

West 859 13.5% 

Overall 3,276 13.8% 

Comparison of blood samples by gender (Table 86) revealed that male drivers were more likely 

to be drug-positive (14.5%) than female drivers (13.0%); however, such differences were not 

statistically significant. 

Table 86. Drug Prevalence by Gender (Blood) 

Gender 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Males 1,992 14.5% 

Females 1,278 13.0% 

Overall 3,270 13.9% 

When examining drug prevalence by age, the prevalence of drug-positives was higher among 

young drivers (Table 87). Drivers aged 16-20 years showed a significantly higher prevalence 

than drivers aged 21-34 years and drivers aged 35-44 years (p < .01). Drivers aged 35-44, 45-64, 

and 65+ were significantly less likely to be drug positive than drivers in the combined age range 

of 16 to 34 years old (p < .01). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 87. Drug Prevalence by Age (Blood) 

Age 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

16-20 459 20.5% 

21-34 1,372 15.2% 

35-44 625 10.7% 

45-64 697 11.2% 

65+ 91 6.0% 

Overall 3,244 14.0% 

Comparisons between gender within age group (Table 88) showed that drug prevalence among 

male drivers ages 16-20 was significantly higher than female drivers ages 16-20 (p < .01). 

Further, drug prevalence among male drivers aged 21-34 was also significantly higher than the 

same-aged female counterparts (p < .05).Among drivers aged 45-64, however, drug prevalence 

was higher in females than in males (p < .01).

Table 88. Drug Prevalence by Age and Gender (Blood) 

Gender Age 

N 

(Unweighted)

% Drug Positive 

(Weighted) 

16-20 301 22.8% 

21-34 825 16.9% 

35-44 368 11.2% 

45-64 413 8.3% 

65+ 61 6.0% 

Males 

Overall Males 1,968 14.6% 

16-20 158 16.5% 

21-34 547 12.2% 

35-44 254 10.5% 

45-64 283 16.7% 

65+ 30 5.8% 

Females 

Overall Females 1,272 13.0% 

Comparing drug prevalence between race/ethnicity (Table 89), Asian drivers were significantly 

less likely to be drug positive (1.3%) than drivers who identified themselves as African 

American, Hispanic, White, or Other (p < .01). 

Table 89. Drug Prevalence by Race/Ethnicity (Blood) 

Race/Ethnicity 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

African American 569 16.8% 

Asian 87 1.3% 

Hispanic 585 10.0% 

White 1,836 15.5% 

Other 165 19.7% 

Overall 3,242 14.0% 

Race/Ethnic groups other than “Hispanic” are always “non-Hispanic.” 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Looking at drug prevalence by education level (Table 90), drivers who identified themselves as 

college graduates or having some college experience were significantly less likely to be drugpositive (p < .01) than drivers with other educational attainment. 

Table 90. Drug Prevalence by Education Level (Blood) 

Education Level 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Not a High School Graduate 289 20.3% 

High School Graduate 831 16.5% 

Some College 1,318 12.5% 

College Graduate 594 10.8% 

Some Graduate Work 212 13.5% 

Overall Nighttime 3,245 14.0% 

When examining drug prevalence by employment status (Table 91), drivers on disability showed 

drug prevalence that was significantly higher than employed drivers, as well as homemakers, 

students, unemployed drivers, and drivers who reported that they were retired (p < .01). No 

statistical difference in drug prevalence was found between employed and unemployed drivers 

(p value = .06). “Retired” drivers had significantly lower drug prevalence than employed drivers 

(p < .05). 

Table 91. Drug Prevalence by Employment Status (Blood) 

Gender 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Employed/Self Employed 2,592 13.6% 

Homemaker 67 12.0% 

Student 274 15.3% 

Unemployed 121 20.4% 

Retired 124 6.0% 

On Disability 47 41.4% 

Other 20 15.6% 

Overall 3,245 14.0% 
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Comparisons across vehicle type (Table 92) showed drug prevalence rates among drivers of 

passenger vehicles, SUV, and van/minivans were not statistically different (p value = .12). Note, 

however, that motorcyclists had the greatest percentage of drug-positive results (p < .05), while 

pickup drivers had the smallest prevalence (p < .05). 

Table 92. Drug Prevalence by Vehicle Type (Blood) 

Vehicle Type 

N 

(Unweighted)

% Drug Positive 

(Weighted) 

Passenger Vehicle 1,971 14.6% 

Pickup 401 9.3% 

SUV 586 11.6% 

Van & Minivan 250 16.2% 

Motorcycle 48 24.0% 

Overall 3,256 13.9% 

Driver Drug Use Prevalence by Drug Class Based on Blood Results 

In this section of the report, we display driver drug use prevalence by class of drug, based on 

blood results. The classes of drugs tested for were antidepressants, marijuana, narcoticanalgesics, sedatives, stimulants, and other (see Tables 94-96). 

Drug Class 

Two percent of the blood-sampled drivers tested positive for more than one drug class (Table 

93). 

Table 93. Number and Distribution of Drug Classes (Blood) 

Number of 

Drug Classes 

N 

 (Unweighted) 

% 

(Weighted) 

1 398 11.8% 

2+ 68 2.0% 

Negative 2,810 86.2% 

Overall 3,276 100.0% 
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In comparing prevalence of drug classes by region (Table 94), marijuana was the most common 

drug class across all of the regions (6.7%). However, drivers in the West region were less likely 

to test positive for marijuana than in the other regions (p < .05). 

Table 94. Drug Classes Distribution by Region (Blood) 

Drug Class 

Midwest 

% 

Northeast 

% 

South 

% 

West 

% 

All 

% 

N=971 N=584 N=862 N=859 N=3,276 

Antidepressants 0.7% 0.4% 1.3% 1.5% 1.1% 

Marijuana 7.9% 9.5% 6.0% 4.7% 6.7% 

Narcotic-Analgesics 1.1% 0.4% 1.4% 0.8% 0.9% 

Sedatives 0.9% 0.4% 1.6% 1.4% 1.1% 

Stimulants 2.1% 1.0% 1.5% 2.2% 1.9% 

Other 0.0% 0.0% 0.2% 0.5% 0.2% 

More than 1 Class 1.3% 2.9% 1.3% 2.4% 2.0% 

Overall Drug Positive 14.0% 14.5% 13.4% 13.5% 13.8% 

Negative 86.0% 85.5% 86.6% 86.5% 86.2% 

 “More than 1 Class” – Drivers testing positive for more than one drug are only counted in this category. 

In this table, percentages are weighted. 

Comparison of drug class by gender (Table 95) revealed that male drivers were significantly 

more likely to test positive for marijuana than female drivers (7.4% males vs. 5.6% females) 

(p < .05). 

Table 95. Drug Classes Distribution by Gender (Blood) 

Drug Class 

Males 

% 

Females 

% 

Total 

% 

N=1,992 N=1,278 N=3,270 

Antidepressants 1.0% 1.2% 1.1% 

Marijuana 7.4% 5.6% 6.7% 

Narcotic-Analgesics 0.8% 1.0% 0.9% 

Sedatives 0.7% 1.8% 1.1% 

Stimulants 1.8% 2.0% 1.9% 

Other 0.4% 0.0% 0.2% 

More than 1 Class 2.4% 1.4% 2.0% 

Overall Drug Positive 14.5% 13.0% 13.9% 

Negative 85.5% 87.0% 86.1% 

In this table, percentages are weighted. 

“More than 1 Class” – Drivers testing positive for more than one drug are only counted in this 

category.
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Comparison of drug class by age (Table 96) showed that drivers 34 or younger were more likely 

to test positive for marijuana than drives in other age groups (p < .01). Among drivers aged 16-

34, drivers aged 16-20 years had the highest marijuana positives (15.2%). The prevalence of 

narcotic-analgesics was higher among the 16-20 and 35-44 year age group (1.3% and 1.7%) than 

among any other age group (p < .01). 

Table 96. Drug Classes Distribution by Age (Blood) 

Drug Class 

16-20 

% 

21-34 

% 

35-44 

% 

45-64 

% 

65+ 

% 

Total 

% 

 N=459 N=1,372 N=625 N=697 N=91 N=3,244

Antidepressants 0.3% 0.6% 0.9% 2.8% 1.0% 1.1% 

Marijuana 15.2% 8.8% 3.1% 1.0% 0.0% 6.8% 

Narcotic-Analgesics 1.3% 0.7% 1.7% 0.4% 0.0% 0.9% 

Sedatives 0.0% 0.8% 1.0% 2.1% 4.8% 1.1% 

Stimulants 0.7% 1.8% 2.0% 2.7% 0.0% 1.8% 

Other 0.2% 0.4% 0.2% 0.0% 0.0% 0.2% 

More than 1 Class 2.7% 1.9% 1.8% 2.3% 0.1% 2.0% 

Overall Drug Positive 20.5% 15.2% 10.7% 11.2% 6.0% 14.0% 

Negative 79.5% 84.8% 89.3% 88.8% 94.0% 86.0% 

“More than 1 Class” – Drivers testing positive for more than one drug are only counted in this category. 

In this table, percentages are weighted.

Driver Drug Use Prevalence by Drug Category Based on Blood Results 

In this section of the report, we display drug use prevalence results from blood tests by drug 

category. 

About 9 percent of the nighttime drivers providing blood tested positive for drugs in the “Illegal” 

category (Table 97). Four percent were positive for “Medications,” and 0.7 percent were positive 

for both “Illegal and Medications.” 

Table 97. Drug Categories Distribution (Blood) 

Drug Category 

N 

(Unweighted) 

% 

(Weighted) 

Illegal 267 9.1% 

Medications 169 4.0% 

Illegal & Medications 30 0.7% 

Negative 2,810 86.2% 

Overall 3,276 100.0% 

“Medications” includes prescription and over-the-counter drugs. 
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The percentage of “Illegal” drug prevalence was slightly higher (p < .05) in the Midwest and 

Northeast than in the remaining regions (Table 98). 

Table 98. Drug Categories Distribution by Region (Blood) 

Region Drug Category 

N 

(Unweighted) 

% 

(Weighted) 

Illegal 81 10.2% 

Medications 52 3.2% 

Illegal & Medications 8 0.6% 

Negative 830 86.0% 

Midwest 

Overall 971 100.0% 

Illegal 57 11.0% 

Medications 26 2.7% 

Illegal & Medications 4 0.8% 

Negative 497 85.5% 

Northeast 

Overall 584 100.0% 

Illegal 56 7.6% 

Medications 51 4.9% 

Illegal & Medications 12 0.9% 

Negative 743 86.6% 

South 

Overall 862 100.0% 

Illegal 73 8.2% 

Medications 40 4.9% 

Illegal & Medications 6 0.5% 

Negative 740 86.5% 

West 

Overall 859 100.0% 

“Medications” includes prescription and over-the-counter drugs. 

When examining prevalence by drug category and gender (Table 99), we found that over 10 

percent of male drivers had positive results for “Illegal” drugs, as did about 7 percent of female 

drivers (p < .01). The difference in percentage of positive results for “Medications” between 

male and female drivers was not statistically significant. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 99. Drug Categories Distribution by Gender (Blood) 

Gender Drug Category 

N 

(Unweighted) 

% 

(Weighted) 

Illegal 191 10.4% 

Medications 75 3.3% 

Illegal & Medications 19 0.8% 

Negative 1,707 85.5% 

 

Male

Overall 1,992 100.0% 

Illegal 76 7.2% 

Medications 94 5.4% 

Illegal & Medications 11 0.4% 

Negative 1,097 87.0% 

 

Female

Overall 1,278 100.0% 

“Medications” includes prescription and over-the-counter drugs. 

Examining drug use by age (Table 100), “Illegal” drug use was highest for drivers in the 

youngest age group (16-20 years) (p < .01), followed by drivers aged 21-34. “Illegal” drug use 

among drivers 35 and older was significantly lower than among drivers younger than age 35 

(p < .01). “Medication” usage followed the opposite trend, with prevalence increasing with age. 

Prevalence of “Medication” was significantly higher for drivers aged 35 and older than for 

drivers younger than age 35 (p < .01). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 100. Drug Categories Distribution by Age (Blood) 

Age Drug Category 

N 

(Unweighted) 

% 

 (Weighted) 

Illegal 56 17.7% 

Medications 8 1.9% 

Illegal & Medications 4 0.9% 

Negative 391 79.5% 

16-20 

Overall 459 100.0% 

Illegal 141 11.7% 

Medications 48 2.7% 

Illegal & Medications 13 0.7% 

Negative 1,170 84.8% 

 

21-34 

Overall 1,372 100.0% 

Illegal 43 5.3% 

Medications 43 5.0% 

Illegal & Medications 7 0.4% 

Negative 532 89.3% 

35-44 

Overall 625 100.0% 

Illegal 26 3.1% 

Medications 61 7.3% 

Illegal & Medications 6 0.8% 

Negative 604 88.8% 

45-64 

Overall 697 100.0% 

Illegal 0 0.0% 

Medications 9 6.0% 

Illegal & Medications 0 0.0% 

Negative 82 94.0% 

65+ 

Overall 91 100.0% 

“Medications” includes prescription and over-the-counter drugs. 

Driver Drug Use Prevalence from Blood and BAC Results 

The following section presents the results of the blood drug analyses combined with the BAC 

results from breath tests. 

The numbers of drug-positive drivers by BAC level are shown in Tables 101 and 102. Table 101 

shows BAC level with respect to the total number of drivers in each drug result category 

(positives, negatives, and overall). Table 102 shows drug prevalence with respect to the total 

number of drivers in each of the three BAC categories. A statistically significant association was 

found between drug-positive and alcohol-positive drivers. The percentage of drivers with BAC 

g/dL .08+ was significantly higher among drug-positive drivers than among drug-negative 

drivers (p < .01). The percentage of drivers with a BAC between zero and .08 was also 

significantly higher for drug-positive drivers (p < .01). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 101. Drug Prevalence by BAC (Percentages Calculated by Row) (Blood) 

 BAC (g/dL) 

Drug 

Result 

N 

(Unweighted) Zero 

Between 

Zero and .08 .08+ 

Positive 466 78.3% 16.0% 5.7% 

Negative 2,810 93.7% 5.2% 1.1% 

Overall 3,276 91.6% 6.7% 1.7% 

In this table, percentages are weighted.

Table 102. Drug Prevalence by BAC (Percentages Calculated by Column) (Blood) 

 BAC (g/dL) 

Drug 

Result Zero 

Between 

Zero and .08 .08+ All 

 N=2,984 N=241 N=51 N=3,276 

Positive 11.8% 33.2% 45.3% 13.8% 

Negative 88.2% 66.8% 54.7% 86.2% 

In this table, percentages are weighted.

Examining BAC among drug-positive drivers by age (Table 103), a large percentage of alcoholpositives were found in drug-positive drivers aged 16-20 and 21-34 (p < .01). Drivers aged 65 

and older had the largest percentage of drivers at intermediate BAC (i.e., between zero and .08); 

however, the sample size of this category was quite small. 

Table 103. BAC Among Drug-Positive Drivers by Age (Blood) 

 BAC (g/dL) 

Age 

N 

(Unweighted) Zero 

Between Zero 

and .08 .08+ 

16-20 68 73.7% 21.2% 5.1% 

21-34 202 73.3% 18.7% 8.0% 

35-44 93 84.7% 9.4% 5.9% 

45-64 93 95.5% 4.5% 0.0% 

65+ 9 59.9% 40.1% 0.0% 

Overall Positive 465 78.6% 15.8% 5.7% 

In this table, percentages are weighted.

There were fewer alcohol-positive drivers among drug-positive drivers with 2+ classes of drugs 

than those with one class (Tables 104 and 105); however, due to the small sample size, this 

difference was statistically non-significant. 
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Table 104. BAC Among Drug-Positive Drivers by Number of Drug Classes 

(Percentages Calculated by Column) (Blood) 

 BAC (g/dL) 

No. of Drug 

Classes Zero 

Between 

Zero and .08 .08+ 

N=386 N=62 N=18 

1 84.0% 88.1% 99.5% 

2+ 16.0% 11.9% 0.5% 

Overall 100.0% 100.0% 100.0% 

In this table, percentages are weighted.

Table 105. BAC Among Drug-Positive Drivers by Number of Drug Classes 

(Percentages Calculated by Row) (Blood) 

 BAC (g/dL) 

Number of 

Drug Classes 

N 

(Unweighted) Zero 

Between 

Zero and .08 .08+ 

1 398 76.9% 16.5% 6.6% 

2+ 68 86.7% 13.1% 0.2% 

Overall 466 78.3% 16.0% 5.7% 

In this table, percentages are weighted.

The majority of drug-positive drivers who were also alcohol-positive tested positive more often 

were positive for “Illegal” drugs (Tables 106 and 107). More than 90 percent of those drivers 

having a BAC between zero and .08 tested positive for “Illegal” drugs (either alone or in 

conjunction with “Medications”). This percentage was significantly higher than the 

approximately 65 percent of non-drinking (BAC = zero) drug-positive drivers who also had an 

“Illegal” drug in their system (alone or combined with “Medications”) (p < .01). 

Table 106. BAC Among Drug-Positive Drivers by Drug Category (Percentage by Row) (Blood) 

 BAC (g/dL) 

Drug Category 

N 

(Unweighted) Zero 

Between 

Zero and .08 .08+ 

Illegal 267 71.7% 20.4% 7.9% 

Medications 169 93.6% 4.9% 1.5% 

Illegal & Medications 30 76.8% 23.2% 0.0% 

 “Medications” includes prescription and over-the-counter drugs. 

In this table, percentages are weighted. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 107. BAC Among Drug-Positive Drivers by Drug Category (Percentage by Column) (Blood) 

 BAC (g/dL) 

Drug Category Zero 

Between Zero 

and .08 .08+ 

 N=386 N=62 N=18 

Illegal 60.5% 84.2% 92.5% 

Medications 34.9% 9.0% 7.5% 

Illegal & Medications 4.6% 6.8% 0.0% 

“Medications” includes prescription and over-the-counter drugs. 

In this table, percentages are weighted. 

High alcohol-positive drivers (i.e., drivers with a .08 BAC g/dL or greater) who tested positive 

for “Illegal” drugs were more likely to be age 44 or younger (p < .01). The sample size was very 

small for drivers aged 45 or older, in particular those aged 65 or older. (Note that, due to the 

number of groupings in Table 108 and the small sample sizes, caution should be exercised in 

interpretation of these findings.)

Table 108. BAC of Drivers by Drug Category and Age (Blood) 

 BAC (g/dL) 

Age Drug Category 

N 

(Unweighted) Zero 

Between 

Zero and .08 .08+ 

Illegal 56 69.8% 24.3% 5.9%

Medications 8 100.0% 0.0% 0.0%

Illegal & Medications 4 95.6% 4.4% 0.0%

Negative 391 97.8% 1.9% 0.3%

 

16-20 

Overall 459 92.9% 5.9% 1.3%

Illegal 141 69.3% 20.9% 9.7%

Medications 48 96.3% 1.0% 2.7%

Illegal & Medications 13 49.0% 51.0% 0.0%

Negative 1,170 91.7% 7.0% 1.3%

21-34 

Overall 1,372 88.9% 8.7% 2.3%

Illegal 43 78.1% 12.6% 9.3%

Medications 43 90.6% 6.6% 2.8%

Illegal & Medications 7 100.0% 0.0% 0.0%

Negative 532 95.6% 3.4% 1.0%

35-44

Overall 625 94.4% 4.1% 1.5%

Illegal 26 91.8% 8.2% 0.0%

Medications 61 96.6% 3.4% 0.0%

Illegal & Medications 6 100.0% 0.0% 0.0%

Negative 604 92.5% 6.0% 1.5%

45-64 

Overall 697 92.8% 5.8% 1.3%

Illegal 0 NA NA NA

Medications 9 59.9% 40.1% 0.0%

Illegal & Medications 0 NA NA NA

Negative 82 95.3% 4.7% 0.0%

65+ 

Overall 91 93.2% 6.8% 0.0%

“Medications” includes prescription and over-the-counter drugs. 

NA = “Not Applicable.” 

 In this table, percentages are weighted. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Male drivers who tested positive for “Illegal” drugs (Table 109) had statistically greater 

percentages of alcohol-positive results than their female counterparts (p < .05).

Table 109. BAC of Drivers by Drug Category and Gender (Blood) 

 BAC (g/dL) 

Gender Drug Category 

N 

(Unweighted) Zero 

Between Zero 

and .08 .08+ 

Illegal 191 72.1% 17.4% 10.6% 

Medications 75 90.5% 8.4% 1.1% 

Illegal & Medications 19 70.8% 29.2% 0.0% 

Negative 1,707 92.9% 5.8% 1.3% 

Males 

Overall 1,992 90.5% 7.3% 2.2% 

Illegal 76 70.7% 27.8% 1.5% 

Medications 94 96.8% 1.4% 1.8% 

Illegal & Medications 11 96.1% 3.9% 0.0% 

Negative 1,097 95.0% 4.2% 0.8% 

Females 

Overall 1,278 93.3% 5.7% 0.9% 

“Medications” includes prescription and over-the-counter drugs. 

In this table, percentages are weighted. 

Oral Fluid and/or Blood Results (Nighttime Samples) 

Driver Drug Use Prevalence Based on Oral Fluid and/or Blood Results 

This section of the report presents the joint results of oral fluid and blood analyses for all of the 

drugs indicated in the introductory section (see Tables 17 and 18) for nighttime drivers. As noted 

earlier, blood was only obtained from nighttime drivers. The tables in this section are based on 

the 5,910 nighttime drivers from whom an oral fluid and/or a blood sample was obtained and 

analyzed. If a driver tested positive for one or more of the drugs in either the oral fluid and/or in 

the blood analyses, he/she was categorized as drug-positive. Thus, this section provides the most 

comprehensive nighttime drug prevalence estimates available using the biological specimens 

obtained in this study. Again, these are overall drug prevalence estimates, including illegal, 

prescription, and over-the-counter drugs or their metabolites and do not necessarily imply 

impairment. Within individual tables, overall counts may not total 5,910 because of missing 

values on some variables. 

When we examine the test results from nighttime drivers providing oral fluid and/or blood, 16.3 

percent of drivers were drug-positive, as indicated in Table 110. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 110. Nighttime Drug Prevalence by Time of Day (Oral Fluid and/or Blood) 

Time of Day 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Daytime NA NA 

Nighttime 5,910 16.3% 

When we examined drug prevalence by time of day (Table 111), we found that late-night 

(Sessions 3 and 5) drivers were significantly more likely to be drug positive (19.1% and 18.3% 

respectively) than Friday and Saturday earlier in the night (Sessions 2 and 4) drivers (15.4% and 

15.2% respectively) (p < .01). 

Table 111. Drug Prevalence by Session (Oral Fluid and/or Blood) 

Session 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

2: Friday, 10:00 p.m. – Midnight 1,618 15.4% 

3: Friday, 1:00 a.m. – 3:00 a.m. 1,313 19.1% 

4: Saturday, 10:00 p.m. – Midnight 1,695 15.2% 

5: Saturday, 1:00 a.m. – 3:00 a.m. 1,284 18.3% 

Overall 5,910 16.3% 

Comparison of drug prevalence by region (Table 112) showed that the Northeast region had the 

greatest percentage of drug-positive findings, at 18.3 percent. However, this difference was not 

statistically significant. Thus, no clear pattern by region emerged.

Table 112. Drug Prevalence by Region (Oral Fluid and/or Blood) 

Region 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Midwest 1,708 16.9% 

Northeast 1,119 18.3% 

South 1,566 16.3% 

West 1,517 15.0% 

Overall 5,910 16.3% 

Examining drug prevalence by gender (Table 113) revealed that male drivers were significantly 

more likely to be drug-positive than female drivers (18.0% male vs. 13.8% female) (p < .01). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

91 

Table 113. Drug Prevalence by Gender (Oral Fluid and/or Blood) 

Gender 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Males 3,634 18.0% 

Females 2,262 13.8% 

Overall 5,896 16.4% 

Comparison of drug prevalence by age (Table 114) indicated that drivers aged 16-44 showed 

statistically similar drug prevalence (i.e., no statistical difference among these age groups). 

Conversely, drivers aged 45-64 and 65+ were significantly less likely to be drug-positive than 

drivers aged 16-44 (p < .01).

Table 114. Drug Prevalence by Age (Oral Fluid and/or Blood) 

Age 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

16-20 974 18.8% 

21-34 2,451 18.2% 

35-44 1,046 17.0% 

45-64 1,225 12.1% 

65+ 148 4.0% 

Overall Nighttime 5,844 16.5% 

When examining drug prevalence by age and gender (Table 115), we found that drug prevalence 

among male drivers in the age categories 16-20 and 21-34 years was significantly higher than 

their same-aged female counterparts (p < .01). Drug prevalence among male drivers in the age 

category 35-44 years was also significantly higher than their same-aged female counterparts 

(p < .05). However, drug prevalence among female drivers aged 45-64 (15.4%) was significantly 

higher than male drivers of the same age group (10.0%) (p < .01). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 115. Drug Prevalence by Age and Gender (Oral Fluid and/or Blood) 

Gender Age 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

16-20 605 22.1% 

21-34 1502 21.1% 

35-44 634 19.4% 

45-64 741 10.0% 

65+ 101 4.0% 

Males 

Overall Males 3583 18.2% 

16-20 368 14.0% 

21-34 944 13.5% 

35-44 409 13.7% 

45-64 482 15.4% 

65+ 47 4.2% 

Females 

Overall Females 2250 13.8% 

Table 116 shows drug prevalence by race/ethnicity. Drivers who identified themselves as Asian 

were significantly less likely to be drug positive (1.9%) than drivers who identified themselves 

as African American, Hispanic, White, or Other (p < .01). African American drivers were found 

to have the highest percentage of drug-positive results (22.4%), which was a significantly higher 

rate than that of their Hispanic or White counterparts (p < .01). 

Table 116. Drug Prevalence by Race/Ethnicity (Oral Fluid and/or Blood) 

Race/Ethnicity 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

African American 980 22.4% 

Asian 191 1.9% 

Hispanic 1015 13.3% 

White 3,378 17.2% 

Other 273 18.1% 

Overall 5,837 16.5% 

Race/Ethnic groups other than “Hispanic” are always “non-Hispanic.” 

As shown in Table 117, drivers who identified themselves as having at least some college 

experience were statistically less likely to be drug-positive than those reporting being a high 

school graduate or less education (p < .01). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 117. Drug Prevalence by Education Level (Oral Fluid and/or Blood) 

Education Level 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Not a High School Graduate 579 20.3% 

High School Graduate 1482 24.0% 

Some College 2,234 14.0% 

College Graduate 1159 10.9% 

Some Graduate Work 389 16.9% 

Overall 5,843 16.5% 

Comparison of drug prevalence by employment status (Table 118) indicated that drivers on 

disability showed a drug prevalence that was significantly higher than that of employed drivers 

(p < .01). The prevalence of drug positives among employed drivers did not differ significantly 

from that of unemployed drivers. Retired drivers had significantly lower drug prevalence than 

employed drivers (p < .01). 

Table 118. Drug Prevalence by Employment Status (Oral Fluid and/or Blood) 

Employment Status 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Employed/Self Employed 4,646 16.7% 

Homemaker 104 8.5% 

Student 593 15.9% 

Unemployed 206 18.2% 

Retired 206 8.3% 

On Disability 67 44.7% 

Other 23 15.0% 

Overall 5,845 16.5% 

Table 119 shows drug prevalence by vehicle type. Drug prevalence rates among drivers of 

various vehicle types (passenger vehicle, pickup, SUV, and van/minivans) were statistically 

different from motorcyclists, who had the greatest percentage of drug-positive results (p <.01). 

Table 119. Drug Prevalence by Vehicle Type (Oral Fluid and/or Blood) 

Vehicle Type 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Passenger Vehicle 3,650 16.5% 

Pickup 703 15.9% 

SUV 1058 15.2% 

Van & Minivan 381 17.4% 

Motorcycle 75 31.9% 

Overall 5,867 16.4% 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Driver Drug Use Prevalence by Drug Class Based on Oral Fluid and/or 

Blood Results 

In this section of the report, we display driver drug use prevalence by class of drug. The classes 

of drugs tested for were antidepressants, marijuana, narcotic-analgesics, sedatives, stimulants, 

and other (see Tables 17-18). 

Drug Class 

As indicated in Table 120, 13.5 percent of the drivers tested positive for one drug class and 2.8 

percent tested positive for more than one drug class. 

Table 120. Number and Distribution of Drug Classes (Oral Fluid and/or Blood) 

Number of 

Drug Classes 

N 

 (Unweighted) 

% 

(Weighted) 

1 792 13.5% 

2+ 184 2.8% 

Negative 4,934 83.7% 

Overall 5,910 100.0% 

Further, drivers testing positive for only one drug class constituted about 83 percent of drugpositive drivers (Table 121). 

Table 121. Number and Distribution of Drug Classes (Drug Positives Only) (Oral Fluid and/or 

Blood) 

Number of 

Drug Classes 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

1 792 82.8% 

2+ 184 17.2% 

Overall 976 100.0% 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 122 presents distribution of drug classes by region. Generally, marijuana was the most 

common drug class across all the regions (6.8%), followed by stimulants (3.2%). Drivers in the 

West were less likely to test positive for marijuana than drivers from the other regions (p < .01). 

Table 122. Drug Classes Distribution by Region (Oral Fluid and/or Blood) 

Drug Class 

Midwest 

% 

Northeast 

% 

South 

% 

West 

% 

All 

% 

 N=1,708 N=1,119 N=1566 N=1,517 N=5,910 

Antidepressants 0.7% 0.4% 0.7% 0.7% 0.7% 

Marijuana 8.8% 7.8% 7.2% 4.7% 6.8% 

Narcotic-Analgesics 1.0% 2.9% 1.6% 1.6% 1.6% 

Sedatives 1.2% 0.3% 0.8% 0.8% 0.8% 

Stimulants 3.1% 1.8% 2.6% 4.2% 3.2% 

Other 0.2% 0.0% 0.1% 0.5% 0.3% 

More than 1 Class 1.8% 5.1% 3.2% 2.5% 2.8% 

Overall Drug Positive 16.9% 18.3% 16.3% 15.0% 16.3% 

Negative 83.1% 81.7% 83.7% 85.0% 83.7% 

“More than 1 Class” – Drivers testing positive for more than one drug are only counted in this category. 

In this table, percentages are weighted. 

As is shown in Table 123, males were significantly more likely to be positive for marijuana than 

females (8.0% males vs. 5.0% females) (p < .01). 

Table 123. Drug Classes Distribution by Gender (Oral Fluid and/or Blood) 

Drug Class 

Males 

% 

Females 

% 

Total 

% 

N=3,634 N=2,262 N=5,896 

Antidepressants 0.7% 0.7% 0.7% 

Marijuana 8.0% 5.0% 6.9% 

Narcotic-Analgesics 1.7% 1.5% 1.6% 

Sedatives 0.6% 1.2% 0.8% 

Stimulants 3.1% 3.5% 3.3% 

Other 0.3% 0.3% 0.3% 

More than 1 Class 3.5% 1.7% 2.8% 

Overall Drug Positive 18.0% 13.8% 16.4% 

Negative 82.0% 86.2% 83.6% 

“More than 1 Class” – Drivers testing positive for more than one drug are only 

counted in this category. 

In this table, percentages are weighted. 

When we examined drug class prevalence by age (Table 124), we found that drivers aged 16-20 

were more likely to use marijuana (12.0%) than drivers in the 21-34 age group (p < .05) and any 

other age group (p < .01). The age group with the second highest prevalence of marijuana was 

21-34; the prevalence in this age group (9.2%) was also significantly higher than in older age 

groups (p < .01). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 124. Drug Classes Distribution by Age (Oral Fluid and/or Blood) 

Drug Class 

16-20 

% 

21-34 

% 

35-44 

% 

45-64 

% 

65+ 

% 

Total 

% 

 N=974 N=2,451 N=1,046 N=1,225 N=148 N=5,844 

Antidepressants 0.4% 0.3% 0.9% 1.5% 0.6% 0.7% 

Marijuana 12.0% 9.2% 4.6% 1.1% 0.0% 6.9% 

Narcotic-Analgesics 1.2% 0.8% 4.3% 1.4% 0.4% 1.6% 

Sedatives 0.0% 0.6% 1.5% 1.2% 3.0% 0.9% 

Stimulants 2.2% 3.3% 3.1% 4.7% 0.0% 3.3% 

Other 0.2% 0.5% 0.2% 0.1% 0.0% 0.3% 

More than 1 Class 2.7% 3.6% 2.3% 2.2% 0.1% 2.8% 

Overall Drug Positive 18.8% 18.2% 17.0% 12.1% 4.0% 16.5% 

Negative 81.2% 81.8% 83.0% 87.9% 96.0% 83.5% 

“More than 1 Class” – Drivers testing positive for more than one drug are only counted in this 

category. 

In this table, percentages are weighted. 

Driver Drug Use Prevalence by Drug Category Based on Oral Fluid 

and/or Blood Results 

In this section of the report, we display drug use prevalence results from the combined results of 

oral fluid and blood tests by drug category as described in Table 18. 

Table 125 shows that 11.3 percent of drivers tested positive for “Illegal” drugs, and an additional 

1.1 percent tested positive for “Illegal” drugs in conjunction with “Medications”. Thus, a total of 

12.4 percent tested positive for “Illegal” drugs, of which 1.1 percent also tested positive for a 

“Medication”. 

Table 125. Drug Categories Distribution (Oral Fluid and/or Blood) 

Drug Category 

N 

(Unweighted) 

% 

(Weighted) 

Illegal 621 11.3% 

Medications 277 3.9% 

Illegal & Medications 78 1.1% 

Negative 4,934 83.7% 

Overall 5,910 100.0% 

“Medications” includes prescription and over-the-counter drugs. 

Table 126 displays the drug category results by region. No statistically significant differences 

were found in the prevalence of “Illegal” drugs across regions. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 126. Drug Categories Distribution by Region (Oral Fluid and/or Blood) 

Region Drug Category 

N 

(Unweighted) 

% 

(Weighted) 

Illegal 197 12.7% 

Medications 97 3.5% 

Illegal & Medications 19 0.6% 

Negative 1,395 83.1% 

Midwest 

Overall 1,708 100.0% 

Illegal 121 11.3% 

Medications 43 4.6% 

Illegal & Medications 17 2.4% 

Negative 938 81.7% 

Northeast 

Overall 1,119 100.0% 

Illegal 145 10.9% 

Medications 79 3.8% 

Illegal & Medications 28 1.6% 

Negative 1314 83.7% 

South 

Overall 1,566 100.0% 

Illegal 158 11.3% 

Medications 58 3.9% 

Illegal & Medications 14 1.1% 

Negative 1287 83.7% 

West 

Overall 1,517 100.0% 

“Medications” includes prescription and over-the-counter drugs. 

When examining prevalence by drug category and gender (Table 127), we found that male 

drivers were more likely to be positive for “Illegal” drugs (combining the categories for “Illegal” 

and “Illegal and Medications”) than female drivers (14.4% male vs. 8.5 % female) (p < .01). 

Table 127. Drug Categories by Gender (Oral Fluid and/or Blood) 

Gender Drug Category 

N 

(Unweighted) 

% 

(Weighted) 

Illegal 444 13.1% 

Medications 136 3.5% 

Illegal & Medications 53 1.3% 

Negative 3,001 82.0% 

 

Male

Overall 3,634 100.0% 

Illegal 176 8.0% 

Medications 141 6.6% 

Illegal & Medications 25 0.5% 

Negative 1,920 84.9% 

 

Female

Overall 2,262 100.0% 

“Medications” includes prescription and over-the-counter drugs. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Comparison of drug categories by age (Table 128) revealed that drivers aged 16-20 and 21-34 

had the highest percentage of drug-positive results for “Illegal” (“Illegal” plus “Illegal and 

Medications”) drugs (p < .01). 

Table 128. Drug Categories Distribution by Age (Oral Fluid and/or Blood) 

Age Drug Category 

N 

 (Unweighted) 

% 

(Weighted) 

Illegal 131 15.5% 

Medications 15 1.9% 

Illegal & Medications 14 1.4% 

Negative 814 81.2% 

16-20 

Overall 974 100.0% 

Illegal 329 14.8% 

Medications 70 2.2% 

Illegal & Medications 37 1.2% 

Negative 2,015 81.8% 

 

21-34 

Overall 2,451 100.0% 

Illegal 91 8.2% 

Medications 78 8.1% 

Illegal & Medications 15 0.8% 

Negative 862 83.0% 

35-44 

Overall 1,046 100.0% 

Illegal 68 5.7% 

Medications 101 5.4% 

Illegal & Medications 12 1.0% 

Negative 1,044 87.9% 

45-64 

Overall 1,225 100.0% 

Illegal 0 0.0% 

Medications 13 4.0% 

Illegal & Medications 0 0.0% 

Negative 135 96.0% 

65+ 

Overall 148 100.0% 

“Medications” includes prescription and over-the-counter drugs. 

Driver Drug Use Prevalence from Oral Fluid and/or Blood 

and BAC Results 

The following section presents the results of the oral fluid and blood analyses combined with the 

blood alcohol concentration (BAC) results obtained through breath tests. 

Tables 129 and 130 show the number of drug-positive drivers by BAC level. As seen in Table 

129, drug-positive drivers (4.1%) were significantly more likely to have a BAC of .08 or higher 

than were drug negative drivers (1.7%) (p < .01). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 129. Drug Prevalence by BAC (Percentages Calculated by Row) (Oral Fluid and/or Blood) 

 BAC (g/dL) 

Drug 

Result 

N 

(Unweighted) Zero 

Between 

Zero and .08 .08+ 

Positive 976 79.5% 16.4% 4.1% 

Negative 4,932 90.6% 7.7% 1.7% 

Overall 5,908 88.8% 9.1% 2.1% 

In this table, percentages are weighted. 

Table 130 provides another way of looking at this issue and indicates that among drivers with a 

BAC g/dL .08+, almost a third (31.8%) were also positive for drugs. The difference in drug 

prevalence between BAC categories for drug positive drivers, however, was not statistically 

significant. 

Table 130. Drug Prevalence by BAC (Percentages Calculated by Column) (Oral Fluid and/or Blood) 

 BAC (g/dL) 

Drug 

Result Zero 

Between Zero 

and .08 .08+ All 

N=5,241 N=536 N=131 N=5,908 

Positive 14.6% 29.3% 31.8% 16.3% 

Negative 85.4% 70.7% 68.2% 83.7% 

In this table, percentages are weighted.

Table 131 shows that, among participants who were drug positive, drivers younger than 35 were 

the most likely to be alcohol-positive. The prevalence of drivers with a BAC greater than zero 

among drivers less than 35-years-old was significantly higher than among older driver groups 

(p < .01). Though a high proportion of drug-positive drivers 65+ were also alcohol positive, that 

pattern is not statistically significant compared to the other age groups due to the small sample 

size.

Table 131. BAC Among Drug-Positive Drivers by Age (Oral Fluid and/or Blood) 

BAC (g/dL) 

Age 

N 

(Unweighted) 

Zero Between Zero 

and .08 

.08+ 

16-20 160 79.9% 17.4% 2.8% 

21-34 436 75.0% 20.0% 5.0% 

35-44 184 87.6% 8.7% 3.79% 

45-64 181 84.2% 12.2% 3.6% 

65+ 13 58.7% 41.3% 0.0% 

Overall Positive 974 79.6% 16.3% 4.1% 

In this table, percentages are weighted.
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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As shown in Table 132, the majority of alcohol-positive drivers among drug-positive drivers 

were positive for only one class of drug. 

Table 132. BAC Among Drug-Positive Drivers by Number of Drug Classes 

(Percentages Calculated by Column) (Oral Fluid and/or Blood) 

 BAC (g/dL) 

Number of Drug 

Classes Zero 

Between 

Zero and .08 .08+ 

 N=468 N=71 N=20 

1 81.9% 83.7% 96.1% 

2+ 18.1% 16.3% 3.9% 

Overall 100.0% 100.0% 100.0% 

In this table, percentages are weighted. 

In Table 133, those drivers with 2+ classes of drugs were significantly less likely to be positive 

for alcohol than those drug-positive for one class (p < .05). 

Table 133. BAC Among Drug-Positive Drivers by Number of Drug Classes 

(Percentages Calculated by Row) (Oral Fluid and/or Blood) 

 BAC (g/dL) 

Number of Drug 

Classes 

N 

(Unweighted) Zero 

Between 

Zero and .08 .08+ 

1 792 78.6% 16.6% 4.8% 

2+ 184 83.6% 15.5% 0.9% 

Overall 976 79.5% 16.4% 4.1% 

In this table, percentages are weighted.

As indicated in Table 134, drug-positive drivers who were also alcohol-positive were more likely 

to be positive for “Illegal” drugs than for “Medications” (p < .01).

Table 134. BAC Among Drug-Positive Drivers by Drug Category (Oral Fluid and/or Blood) 

 BAC (g/dL) 

Drug Category 

N 

(Unweighted) Zero 

Between 

Zero and .08 .08+ 

Illegal 621 75.21% 19.35% 5.44% 

Medications 277 91.40% 7.31% 1.29% 

Illegal & Medications 78 81.10% 18.16% 0.75% 

Negative 4,932 88.79% 9.09% 2.12% 

 “Medications” includes prescription and over-the-counter drugs. 

In this table, percentages are weighted. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 135 presents the BACs of drivers by drug category and age. Drivers with BAC a of .08 or 

higher who tested positive for drugs, were more likely to test positive for “Illegal” drugs than 

those in the “Medications” category across all age groups. However, this difference was not 

statistically significant.

Table 135. BAC of Drivers by Drug Category and Age (Oral Fluid and/or Blood) 

 BAC (g/dL) 

Age Drug Category 

N 

(Unweighted) Zero 

Between Zero 

and .08 .08+ 

Illegal 131 75.9% 20.8% 3.3% 

Medications 15 100.0% 0.0% 0.0% 

Illegal & Medications 14 97.5% 2.5% 0.0% 

Negative 814 96.1% 3.4% 0.5% 

 

16-20 

Overall 974 93.0% 6.0% 1.0% 

Illegal 329 73.1% 20.9% 6.0% 

Medications 70 83.7% 14.6% 1.7% 

Illegal & Medications 37 81.2% 18.8% 0.0% 

Negative 2,014 88.0% 9.6% 2.4% 

21-34 

Overall 2,450 85.6% 11.5% 2.9% 

Illegal 91 79.4% 14.7% 5.9% 

Medications 78 95.3% 2.7% 2.0% 

Illegal & Medications 15 93.2% 6.8% 0.0% 

Negative 862 92.1% 6.6% 1.3% 

35-44

Overall 1,046 91.3% 7.0% 1.7% 

Illegal 68 80.8% 12.6% 6.6% 

Medications 101 93.4% 6.1% 0.4% 

Illegal & Medications 12 53.6% 42.4% 4.0% 

Negative 1,044 89.9% 8.8% 1.3% 

45-64 

Overall 1,225 89.2% 9.2% 1.6% 

Illegal 0 NA NA NA 

Medications 13 58.7% 41.3% 0.0% 

Illegal & Medications 0 NA NA NA 

Negative 135 89.9% 5.3% 4.8% 

65+ 

Overall 148 88.6% 6.8% 4.6% 

In this table, percentages are weighted.

When examining BAC by drug category by gender (Table 136), male drivers that tested positive 

for “Illegal” drugs were more likely to have a BAC at or above .08 g/dL than their female 

counterparts (p < .01). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 136. BAC of Drivers by Drug Category and Gender (Oral Fluid and/or Blood) 

 BAC (g/dL) 

Gender Drug Category 

N 

(Unweighted) Zero 

Between Zero 

and .08 .08+ 

Illegal 444 74.9% 17.9% 7.2% 

Medications 136 92.8% 6.4% 0.8% 

Illegal & Medications 53 76.0% 23.1% 1.0% 

Negative 3,001 90.2% 7.8% 2.1% 

Males

Overall 3,634 88.1% 9.2% 2.7% 

Illegal 176 76.1% 23.1% 0.9% 

Medications 141 89.6% 8.4% 2.0% 

Illegal & Medications 25 97.9% 2.1% 0.0% 

Negative 1,919 91.2% 7.6% 1.2% 

Females

Overall 2,261 89.9% 8.9% 1.2% 

In this table, percentages are weighted.

Individual Drug Prevalence Estimates from Oral Fluid, and 

Oral Fluid and/or Blood Combined 

In this section of the report we present prevalence estimates for individual drugs, illegal, 

prescription, and over-the-counter drugs, obtained from the analyses of oral fluid and blood 

specimens. In Tables 137 and 139 there are three main columns. The first column lists the 

individual drugs for which we tested and at least one driver tested positive in oral fluid. The 

second main column presents the oral fluid results (unweighted N and weighted percentage) of 

samples obtained from daytime drivers on a drug-by-drug basis. The third column presents 

results of oral fluid analyses from nighttime drivers in a similar manner. Similarly, tables 138 

and 140 present the combined analyses of oral fluid and/or blood samples provided by nighttime 

drivers. Note in these tables there were 5,910 nighttime drivers who provided either oral fluid, 

blood, or both oral fluid and blood for analysis. If a driver tested positive for a specific drug or a 

metabolite of that drug in either oral fluid, or blood, or in both substances, that driver was 

counted as positive for that drug once. Thus, these tables provide us with a robust estimate of 

nighttime drug prevalence available from the biological samples we collected because it takes 

advantage of the larger sample size of nighttime drivers providing oral fluid samples (5,869), 

augmented with information obtained from analyses of blood samples obtained from 3,276 

nighttime drivers. Most drivers who provided blood also provided oral fluid, so including the 

blood results only increased the sample size by 41 drivers, to 5,910. However, since in some 

cases specific drugs were found in oral fluid and not blood, and conversely in blood but not oral 

fluid, this dataset provides us with the most comprehensive estimates of individual drug 

prevalence. 

The Ns in the tables represent the actual unweighted number of positive tests for the listed drug 

or a metabolite of that drug. The percentages are the weighted prevalence estimates for each 

drug. Since individual drug use was the unit of analysis and some drivers were positive for more 

than one drug, the sum of the individual drug prevalence estimates exceeds the overall 

prevalence estimates appearing elsewhere in this report. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

103 

Of particular interest may be the prevalence estimates for relatively frequently encountered drugs 

such as marijuana. Marijuana (and its metabolites) appears as a separate drug class in the 

typology presented in Table 17 and used in the subsequent tabulations of results by drug class. 

However, a number of drivers tested positive for more than one drug class (sometimes including 

marijuana) and were classified as such in the tabulations. Thus, drivers who were positive for 

marijuana were split between the mutually exclusive classifications of “marijuana” and “more 

than one drug class” in those tables. Here, in these tables we present the prevalence estimates for 

a drug, such as marijuana, independent of whether other drugs were found in an individual 

driver. Thus, a driver, for example, who tested positive for marijuana and cocaine would appear 

twice in the tables in this section of the report. Finally, as indicated earlier in the report, in many 

instances we tested both for the parent drug and its metabolites. In cases where we found both 

the parent drug and its metabolite (for example, THC and 11-OH-THC), we only counted that as 

one drug positive for the parent drug. In the case in which a parent drug was identified alone, 

which could also be a metabolite of another drug, we only counted the observation as the parent 

drug itself, and not again as the drug for which it could be a metabolite. 

Thus, the values in the tables in this section of the report represent estimates of individual drug 

prevalence based on the analytic techniques available. 

Overall Individual Drug Prevalence in Daytime and Nighttime 

Review of Tables 137 and 138 reveals that the two highest prevalence drugs found in the 2007 

NRS were in the “Illegal” drug category. 

The most frequently encountered single drug in oral fluid in both daytime and nighttime was 

THC (marijuana). Marijuana was detected in oral fluid in 4.46 percent of daytime drivers and 

7.66 percent of nighttime drivers (Table 137). The results from nighttime drivers who provided 

oral fluid and/or blood indicated that 8.65 percent of drivers were positive for marijuana or its 

metabolites (Table 138). 

The second most frequently encountered drug was cocaine, with either cocaine or a metabolite 

detected in oral fluid in 1.46 percent of daytime drivers and 3.90 percent of nighttime drivers. 

The corresponding nighttime figure for oral fluid and/or blood nighttime was 3.92 percent. 

During the daytime, the next most frequently encountered drug was alprazolam at 1.12 percent. 

Alprazolam (a benzodiazepine) exhibited a nighttime prevalence rate in oral fluid of 0.61 

percent. 

Among opioids, oxycodone exhibited a daytime prevalence rate of 0.37 percent and hydrocodone 

0.31 percent. Among the nighttime oral fluid samples, oxycodone had a prevalence rate of 0.80 

percent. Another opioid, hydrocodone, had a 0.22 percent daytime and 0.61 percent nighttime 

oral fluid prevalence rate. The atypical opioid propoxyphene was detected in 0.93 percent of 

daytime oral fluid samples and 0.46% of nighttime oral fluid samples. 

The daytime prevalence rate of methamphetamine was 0.32 percent and amphetamine was 0.23 

percent. Among nighttime drivers providing oral fluid samples, methamphetamine had a 

prevalence rate of 0.80 percent. Amphetamine had a prevalence rate of 0.36 percent. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

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Table 137. Prevalence of Drugs in Daytime and Nighttime Drivers (Oral Fluid) 

Oral Fluid 

Daytime Nighttime 

Drug 

N 

(Unweighted)

% 

(Weighted)

N 

(Unweighted) 

% 

(Weighted)

Alprazolam 18 1.12% 36 0.61%

Amitriptyline 6 0.27% 7 0.03%

Amphetamine 9 0.56% 41 0.86%

Butalbital 5 0.26% 8 0.17%

Carisoprodol 2 0.05% 6 0.05%

Chlordiazepoxide 14 1.03% 18 0.21%

Clonazepam 2 0.03% 7 0.12%

Cocaine 38 1.46% 222 3.90%

Codeine 4 0.13% 8 0.46%

Dextromethorphan 3 0.23% 16 0.22%

Diazepam 13 0.93% 21 0.23%

Fluoxetine 11 0.34% 14 0.23%

Heroin 2 0.09% 10 0.22%

Hydrocodone 17 0.31% 58 0.61%

Hydromorphone 2 0.09% 0 0.00%

Ketamine 0 0.00% 1 0.08%

Lorazepam 0 0.00% 1 0.01%

MDMA 2 0.06% 8 0.09%

Meperidine 1 0.01% 2 0.00%

Meprobamate 0 0.00% 3 0.03%

Methadone 3 0.21% 11 0.18%

Methamphetamine 9 0.56% 53 1.16%

Methylphenidate 0 0.00% 3 0.01%

Morphine 2 0.09% 10 0.22%

Oxycodone 14 0.37% 43 0.80%

PCP 1 0.04% 3 0.13%

Phenobarbital 1 0.00% 1 0.00%

Phentermine 5 0.15% 11 0.11%

Propoxyphene 22 0.93% 34 0.46%

Sertraline 2 0.44% 4 0.13%

Temazepam 3 0.18% 3 0.03%

THC (Marijuana) 103 4.46% 438 7.66%

Tramadol 12 0.19% 34 0.46%

Zolpidem 2 0.12% 1 0.01%

 

All Tested Drivers † 1,850 11.0% 5,869 14.4%

† Number and percentages for "All tested drivers" indicate number of drivers providing samples and the 

percentage of those drivers who tested positive for at least one drug. 

In this table, percentages are weighted. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

105 

Individual Drug Prevalence in Nighttime Oral Fluid and/or Blood 

Results for drivers who provided oral fluid and/or blood yielded an overall drug positive 

prevalence estimate of 16.3 percent (Table 138). Again, marijuana (8.65%) and cocaine (3.92%) 

were the most frequently encountered drugs. The next most frequently encountered drug was 

methamphetamine (0.84%). Amphetamine was present in 0.45 percent of this nighttime driver 

population. The opioids oxycodone (0.82%) and hydrocodone (0.68%) and the benzodiazepine 

alprazolam (0.64%) were the next most frequently encountered drugs in this nighttime driver 

population. The atypical opioid propoxyphene was present in 0.52% of these nighttime drivers. 

Note, however, as indicated in the introduction of this section, the unit of analysis in these tables 

is individual drug use. Some drivers were positive for more than one drug, thus the sum of the 

individual drug prevalence estimates exceed the overall prevalence estimates noted earlier in this 

report. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

106 

Table 138. Prevalence of Drugs in All Drug-Tested Nighttime Drivers (Oral Fluid and/or Blood) 

Drug 

N 

(Unweighted)

% 

(Weighted)

Alprazolam 40 0.64% 

Amitriptyline 14 0.07% 

Amphetamine 49 0.98% 

Butalbital 9 0.17% 

Carisoprodol 6 0.05% 

Chlordiazepoxide 40 0.52% 

Clonazepam 10 0.14% 

Cocaine 225 3.92% 

Codeine 8 0.46% 

Dextromethorphan 16 0.22% 

Diazepam 45 0.55% 

Fluoxetine 25 0.37% 

Heroin 15 0.26% 

Hydrocodone 63 0.68% 

Hydromorphone 0 0.00% 

Imipramine 1 0.00% 

Ketamine 1 0.08% 

Lorazepam 2 0.03% 

MDMA 8 0.09% 

Meperidine 2 0.00% 

Meprobamate 5 0.05% 

Methadone 14 0.19% 

Methamphetamine- 62 1.29% 

Methylphenidate 3 0.01% 

Morphine 15 0.26% 

Oxycodone 47 0.82% 

PCP 3 0.13% 

Phenobarbital 2 0.01% 

Phentermine 21 0.26% 

Propoxyphene 36 0.54% 

Sertraline 36 0.50% 

Temazepam 6 0.05% 

THC (Marijuana) 499 8.65% 

Tramadol 35 0.46% 

Zolpidem 4 0.03% 

 

All Tested Drivers † 5,910 16.3% 

† Number and percentages for "All tested drivers" indicate number of drivers providing 

samples and percentage of those drivers who tested positive. 

In this table, percentages are weighted. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

107 

Individual Drug Prevalence Sorted by Drug Type from Oral Fluid, and 

Oral Fluid and/or Blood Combined 

In Tables 139 and 140 we present prevalence estimates by drug within drug type for both 

daytime and nighttime drivers based on oral fluid analyses (Table 139) and for nighttime drivers 

based on the results of analyses of oral fluid and/or blood (Table 140). These tables contain the 

same information provided in Tables 137 and 138 except that the drugs are sorted by drug type. 

(Drug types are the subgrouping of similar drugs noted by class and category in Tables 17 and 

18.) 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

108 

Table 139. Prevalence of Drugs in Daytime and Nighttime Drivers (Oral Fluid) 

 Oral Fluid 

 Daytime Nighttime 

N % N % 

Drug (Unweighted) (Weighted) (Unweighted) (Weighted) 

THC (Marijuana) 103 4.46% 438 7.66% 

Cocaine 38 1.46% 222 3.90% 

Opioids 

 Codeine 4 0.13% 8 0.44% 

 Heroin 2 0.09% 10 0.22% 

 Hydrocodone 17 0.31% 58 0.61% 

 Hydromorphone 2 0.09% 0 0.00% 

 Meperidine 1 0.01% 2 0.00% 

 Methadone 3 0.21% 11 0.18% 

 Morphine 2 0.09% 10 0.22% 

 Oxycodone 14 0.37% 43 0.80% 

 Propoxyphene 22 0.93% 34 0.46% 

 Tramadol 12 0.19% 34 0.46% 

Amphetamines/Stimulants 

 MDMA 2 0.06% 8 0.09% 

 Amphetamine 9 0.56% 41 0.86% 

 Methamphetamine 9 0.56% 53 1.16% 

 Methylphenidate 0 0.00% 3 0.01% 

 Phentermine 5 0.15% 11 0.11% 

Street Drugs 

 Ketamine 0 0.00% 1 0.08% 

 PCP 1 0.04% 3 0.13% 

Benzodiazepines 

 Alprazolam 18 1.12% 36 0.61% 

 Chlordiazepoxide 14 1.03% 18 0.21% 

 Clonazepam 2 0.03% 7 0.12% 

 Diazepam 13 0.93% 21 0.23% 

 Lorazepam 0 0.00% 1 0.01% 

 Temazepam 3 0.18% 3 0.03% 

Antidepressants 

 Amitriptyline 6 0.27% 7 0.03% 

 Fluoxetine 11 0.34% 14 0.23% 

 Imipramine 

 Sertraline 2 0.44% 4 0.13% 

Barbiturates 

 Butalbital 5 0.26% 8 0.17% 

 Phenobarbital 1 0.00% 1 0.00% 

Pain Drugs 

 Carisoprodol 2 0.05% 6 0.05% 

 Meprobamate 0 0.00% 3 0.03% 

Sleep Aids 

 Zolpidem 2 0.12% 1 0.01% 

Cough Suppressants 

 Dextromethorphan 3 0.23% 16 0.22% 

All Tested Drivers† 1,850 11.0% 5,869 14.4% 

† Number and percentages for "All tested drivers" indicate number of drivers providing samples and percentage of those 

drivers who tested positive. In this table, percentages are weighted. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

109 

Table 140. Prevalence of Drugs in All Drug-Tested Nighttime Drivers (Oral Fluid and/or Blood) 

Drug 

N 

(Unweighted)

% 

(Weighted) 

THC (Marijuana) 499 8.65% 

Cocaine 225 3.92% 

Opioids 

 Codeine 8 0.46% 

 Heroin 15 0.26% 

 Hydrocodone 63 0.68% 

 Hydromorphone 0 0.00% 

 Meperidine 2 0.00% 

 Methadone 14 0.19% 

 Morphine 15 0.26% 

 Oxycodone 47 0.82% 

 Propoxyphene 36 0.54% 

 Tramadol 35 0.46% 

Amphetamines/Stimulants 

 MDMA 8 0.09% 

 Amphetamine 49 0.98% 

 Methamphetamine 62 1.29% 

 Methylphenidate 3 0.01% 

 Phentermine 21 0.26% 

Street Drugs 

 Ketamine 1 0.08% 

 PCP 3 0.13% 

Benzodiazepines 

 Alprazolam 40 0.64% 

 Chlordiazepoxide 40 0.52% 

 Clonazepam 10 0.14% 

 Diazepam 45 0.55% 

 Lorazepam 2 0.03% 

 Temazepam 6 0.05% 

Antidepressants 

 Amitriptyline 14 0.07% 

 Fluoxetine 25 0.37% 

 Imipramine 1 0.00% 

 Sertraline 36 0.50% 

Pain drugs 

 Carisoprodol 6 0.05% 

 Meprobamate 5 0.05% 

Barbiturates 

 Butalbital 9 0.17% 

 Phenobarbital 2 0.01% 

 Total 11 0.18% 

Sleep Aids 

 Zolpidem 4 0.03% 

Cough Suppressants 

 Dextromethorphan 16 0.22% 

All Tested Drivers† 5,910 16.3% 

† Number and percentages for "All tested drivers" indicate number of drivers 

providing samples and percentage of those drivers who tested positive. 

In this table, percentages are weighted. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

110 

Drugs that were infrequently encountered in the study population included the sedative pain 

drugs carisoprodol and meprobamate; the sleep aid zolpidem; and the street drugs ketamine and 

PCP. Barbiturates and cough suppressants were also infrequent in the studied driver population. 

Examination of the results of the daytime and the nighttime oral fluid analyses, and the 

combination of oral fluid and/ or blood analyses (when either one or both types of samples were 

provided) indicates that similar relative patterns of prevalence estimates are realized in the 

daytime and nighttime. Marijuana is the most frequently encountered drug whether compared 

with other drugs individually or with drug types. Cocaine is the next most frequently 

encountered drug or drug type in the nighttime sample, but during the daytime, benzodiazepines 

and opioids exhibited higher prevalence rates as classes than cocaine. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

111 

Discussion 

This report summarizes the results of the first U.S. National Roadside Survey to estimate druginvolved driving prevalence based on biological measures. It should be emphasized that this is a 

prevalence study, and not a study that addresses the risk that may be presented by drug use 

among drivers. For many drug types, drug presence can be detected long after any impairment 

that might affect driving has passed. However, it is important to our understanding of drugs and 

driving to know the extent of the use of certain drugs in the driving population. That was the 

intent of this study. 

As indicated earlier in the report, we gathered data from drivers on U.S. roadways during Friday 

daytime hours, as well as during Friday nights and Saturday nights. We obtained oral fluid 

samples (1,850 during daytime and 5,869 during nighttime) from drivers in each of those data 

collection periods, and collected blood samples (3,276), as well, during the nighttime data 

collection periods (Table 10). 

In this study, analyses of the oral fluid and blood samples were conducted to identify the 

presence of some 75 drugs and metabolites (Tables 17 and 18). To make the presentation of 

results most useful, we identified six classes of these drugs, including antidepressants, marijuana, 

narcotic-analgesics, sedatives, stimulants, and other, plus a “more than one drug” class. We also 

identified three broader categories: illegal, prescription, and over-the-counter. Because few overthe-counter drugs were found, the prescription and over-the-counter drugs were combined for 

many analyses and labeled “Medications.” 

Oral Fluid Analyses 

Analyses of the oral fluid samples obtained from daytime drivers indicated an overall drug use 

prevalence of 11 percent, and for nighttime drivers, 14.4 percent (Table 19). This includes 

illegal, prescription, and over-the-counter drugs combined. This overall difference between day 

and night is statistically significant (p < .01). 

In examining the prevalence of drugs by class (Table 31), marijuana was identified in 3.9 percent 

of daytime drivers and 6.1 percent of nighttime drivers. Sedatives were found in 1.6 percent of 

daytime drivers and in 0.6 percent of nighttime drivers. Conversely, stimulants were found in 1.6 

percent of daytime drivers but in 3.2 percent of nighttime drivers. 

Comparison of drug classes by time of day indicated that nighttime drivers were significantly 

more likely to test positive for more than one drug class than daytime drivers (2.3% nighttime vs. 

1.5% daytime) (p < .01). Comparison of drug categories by time of day (Table 34) revealed that 

almost 6 percent of daytime drivers tested positive for drugs in the “Illegal” category (primarily 

marijuana and cocaine) as did over 10 percent of nighttime drivers (there was a statistically 

significant difference between the two groups [p < .01]). Positive results in the “Medications” 

category (prescription and over-the-counter drugs combined) were found to be slightly higher 

among the daytime drivers (almost 5%) than nighttime drivers (3%), although this difference was 

not statistically significant. 

When examining drug prevalence by time of day and gender (Table 22), the daytime driving 

sample showed no statistically significant difference in drug prevalence between males and 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

112 

females; however, in the nighttime driving sample, male drivers were significantly more likely to 

be drug-positive than female drivers (16.5% males vs. 11.3% females) (p < .01). 

Further, comparison of drug class by time and gender (Table 32) showed that males were 

significantly more likely to test positive for marijuana than females in both daytime (5.9% males 

vs. 1.7% females) and nighttime samples (7.4% males vs. 4.1% females) (p < .01). 

When examining prevalence by drug category by time of day and gender (Table 36), we found 

that, in the daytime sample, male drivers were more likely to test positive for “Illegal” drugs 

(8.2%) than female drivers (3.0%) (p < .01). Conversely, daytime female drivers were more 

likely to show positive results for “Medications” (7.6%) than daytime male drivers (2.5%) (p < 

.01). This pattern was similar in the nighttime sample, with 12.5 percent of male drivers testing 

positive for “Illegal” drugs, as opposed to 7.5 percent of female drivers (p < .01). The difference 

in percentage of positive results for “Medications” between male (2.8%) and female (3.3%) 

drivers was not as striking in the nighttime sample as in the daytime sample. 

Comparison of overall drug prevalence by time of day and age18 (Table 23) revealed that, within 

the daytime driving sample, drivers aged 45-64 showed the highest percentage of drug positives, 

and drivers aged 16-20 and aged 65+ were significantly less likely to be positive than other ages 

of drivers (p < .05). In the nighttime driving sample, drivers aged 45-64 and 65+ were 

significantly less likely to be drug positive (p < .01), while drivers aged 16-20 showed no 

difference in drug prevalence from drivers aged 21-34 years and drivers aged 35-44 years. 

When we examined drug classes by time of day and age (Table 33), we found that daytime 

drivers aged 21-34 were more likely to use marijuana (7.4%) than daytime drivers in other age 

groups (p < .01). However, drivers aged 16-20 years had the highest marijuana use (9.8%) in the 

nighttime sample, followed by the 21-34 year age group (8.5%) (p < .01). The prevalence of 

narcotic-analgesics among daytime drivers was highest among drivers aged 45-64 (2.9%) 

(p < .01); however, in the nighttime sample, this changed to the age 35-44 group (4.2%) (p < 

.01). 

In comparing drug categories by time of day and age (Table 37), it was clear that, within the 

daytime sample, “Illegal” drug use was highest for drivers aged 21-34 (9.9%) followed by 

drivers aged 35-44 (6.5%). The prevalence of “Illegal” drugs for these age groups differed 

significantly from that in the remaining age groups (p < .01). In the nighttime sample, drivers in 

the 21-34 year age group still maintained the highest percentage of positive results for “Illegal” 

drugs (14.2%); however, that group was then followed by the youngest age group (16-20 years) 

for “Illegal” drugs (13.1%) (p < .01). “Medications” usage was highest among the 45-64 year age 

group (8.8%) in the daytime sample (non-significant), and in the 35-44 year old age group in the 

nighttime sample (6.9%) (p < .01). 

In comparing the number of drug-positive drivers by time of day and BAC level (Tables 38 and 

39), a statistically significant association was found between drug-positive and alcohol-positive 

drivers within the nighttime driving sample. In other words, the percentage of nighttime drivers 

with a BAC g/dL of .08+ was significantly higher among drug-positive drivers than among drugnegative drivers (p < .01). However, for daytime drivers, no such statistical association was 

found, largely because of the small number of alcohol-positive drivers in the daytime sample. 

 

18 Age ranges between groups are not equivalent. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

113 

In both the daytime and nighttime samples, the majority of drug-positive drivers who were 

alcohol-positive were in the “Illegal” drug category (Table 43). This was particularly true in the 

nighttime sample, in which 17.3 percent in the “Illegal” drug category had BACs between zero 

and .08 (compared to 6.3% in the “Medications” category) and 5.7 percent had BACs greater 

than .08 (compared to 1.2% in the “Medications” category [p < .01]). In the daytime sample, 

however, the differences were statistically non-significant. 

Blood Analyses 

About 14 percent of the 3,276 blood samples obtained from nighttime drivers were drug-positive 

(Table 83). Two percent of the blood-sampled drivers tested positive for more than one drug 

class (Table 93 and about 9 percent of driver tested positive for drugs in the “Illegal” category 

(Table 97). 

Review of blood sample findings by gender (Table 86) revealed that male drivers were more 

likely to be drug-positive than female drivers (14.5% males vs. 13.0% females). However, such 

differences were not statistically significant. Comparison of drug class by gender (Table 95) 

revealed that male drivers were significantly more likely to test positive for marijuana than 

female drivers (7.4% males vs. 5.6% females) (p < .05). When examining prevalence by drug 

category and gender (Table 99), we found that over 10 percent of male drivers had positive 

results for “”Illegal” drugs, as did about 7 percent of female drivers (p < .01). The difference in 

percentage of positive results for “Medications” between male and female drivers was not 

statistically significant. 

When examining drug prevalence by age (Table 87), the prevalence of drug-positives was higher 

among young drivers. Drivers aged 16-20 years showed a significantly higher prevalence than 

drivers aged 21-34 years and drivers aged 35-44 years (p < .01). Drivers aged 45-64 and 65+ 

were significantly less likely to be drug positive than drivers ages 16 to 34 years old (p < .01). 

Comparison of drug class by age (Table 96) showed that drivers younger than 35-years-old were 

more likely to test positive for marijuana than drivers in other age groups (p < .01). Among 

drivers aged 16-34, drivers aged 16-20 years had the highest marijuana use (15.2%). The 

prevalence of narcotic-analgesics was higher among the 16-20 and 35-44 year age groups (1.3% 

and 1.7% respectively) than any other age group (p < .01). 

“Illegal” drug use was highest for drivers in the youngest age group (16-20 years), followed by 

drivers aged 21-34 years old (p < .01). “Illegal” drug use among drivers older than 35-years-old 

was significantly lower than among drivers under the age of 35 (p < .01). “Medication” usage 

followed the opposite trend, with prevalence increasing with age. Prevalence of “Medication” 

was higher for drivers aged 35 and older than for drivers younger than age 35 (p < .01) (Table 

100). 

A statistically significant association was found between drug-positive and alcohol-positive 

drivers (Tables 101 and 102). The percentages of drivers with a BAC g/dL between zero and .08 

and with a BAC g/dL .08+ were significantly higher among drug-positive drivers than among 

drug-negative drivers (p < .01). 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

114 

Oral Fluid and/or Blood Analyses Combined 

Similar patterns of results were obtained when we examined the drug prevalence for the 5,910 

nighttime drivers who provided oral fluid and/or blood samples. If a driver tested positive for one 

or more of the drugs in either the oral fluid and/or in the blood analyses, he/she was categorized 

as drug-positive (Table 110). This yielded an overall drug positive rate of 16.3 percent. 

When we examined individual drugs and their metabolites (Tables 137 and 138), we found that 

the most frequently encountered drug was marijuana, whether it was measured in oral fluid in the 

daytime (4.5%), oral fluid at nighttime (7.7%), or the combination of oral fluid and/or blood at 

nighttime (8.7%). The next most frequently encountered individual drug (again by all measures) 

was cocaine, which was present in 1.5 percent of daytime oral fluid samples, 3.9 percent of 

nighttime oral fluid samples, and 3.9 percent of nighttime combined oral fluid and/or blood 

analyses. 

During the daytime, the next most frequently encountered drug was alprazolam at 1.12 percent. 

Among nighttime drivers providing oral fluid samples, the most frequently encountered drugs, 

after marijuana and cocaine, were methamphetamine and oxycodone, each with a prevalence rate 

of 0.80percent. The data collected during the 2007 National Roadside Survey provides new 

insight into the extent and patterns of drug use, and the combination of drug and alcohol use, 

among our Nation’s drivers. As noted earlier, the data collected can not determine whether the 

drug-use patterns we observed affected driver performance, For example, although all the drugs 

examined in this study can potentially impair driving skills, some of the drug-positive drivers 

could drive better with the therapeutic effects of medicinal drugs they are taking. What this study 

has provided is a careful estimate of the extent of alcohol-involved and drug-involved driving in 

the contiguous 48 States. 

The next step in this process is to conduct a study that attempts to quantify the risk that druginvolved driving may pose for crash involvement. One way to establish that is to conduct a case 

control study where data including objective measures of drug use are gathered from crashinvolved drivers and non-crash-involved drivers matched to the time, location, and direction of 

travel of the crash-involved drivers. Those two sets of data can then be compared to estimate the 

risk posed by various drugs. 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results

115 

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..........

Appendix A 

2007 National Roadside 

Survey: Additional Tables 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results 

122 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results 

123 

Appendix A 

2007 National Roadside Survey 

Additional Tables 

Table 141. Nighttime: Blood Results and Agreement with Self-Reported by Drug Type (Blood) 

Blood 

Positive for this Drug 

Drug Category 

Self-Reported 

Drug Use 

N 

(Unweighted)

% 

(Weighted) 

Past 24 Hours 41 81.4% 

Past 2 Days 1 0.8% 

Past Month 1 0.2% 

Past Year 0 0.0% 

Over a Year 1 2.4% 

Never 13 15.2% 

Antidepressants 

Overall 57 100.0% 

Past 24 Hours 1 3.1% 

Past 2 Days 0 0.0% 

Past Month 3 12.9% 

Past Year 1 12.5% 

Over a Year 8 10.9% 

Never 38 60.5% 

Amphetamines 

Overall 51 100.0% 

Past 24 Hours 2 1.3% 

Past 2 Days 0 0.0% 

Past Month 0 0.0% 

Past Year 0 0.0% 

Over a Year 0 0.0% 

Never 6 98.7% 

Barbiturates 

Overall 8 100.0% 

Past 24 Hours 11 21.5% 

Past 2 Days 4 3.8% 

Past Month 4 8.0% 

Past Year 3 2.0% 

Over a Year 5 2.1% 

Never 36 62.6% 

Benzodiazepines 

Overall 63 100.0% 

Past 24 Hours 4 2.9% 

Past 2 Days 2 10.8% 

Past Month 5 17.0% 

Past Year 1 1.0% 

Cocaine 

Over a Year 6 10.6% 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results 

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Blood 

Positive for this Drug 

Drug Category 

Self-Reported 

Drug Use 

N 

(Unweighted)

% 

(Weighted) 

Never 23 57.7% 

Overall 41 100.0% 

Past 24 Hours 2 15.7% 

Past 2 Days 1 22.2% 

Past Month 1 60.6% 

Past Year 0 0.0% 

Over a Year 0 0.0% 

Never 1 1.4% 

 Cough 

Suppressants 

Overall 5 100.0% 

Past 24 hrs 0 0.0% 

Past 2 days 0 0.0% 

Past Month 0 0.0% 

Past Year 0 0.0% 

Over a Year 0 0.0% 

Never 1 100.0% 

Ketamine 

Overall 1 100.0% 

Past 24 hrs 59 37.1% 

Past 2 days 18 5.4% 

Past Month 38 16.2% 

Past Year 22 6.8% 

Over a Year 27 9.3% 

Never 63 25.2% 

Marijuana 

Overall 227 100.0% 

Past 24 hrs 6 98.0% 

Past 2 days 0 0.0% 

Past Month 0 0.0% 

Past Year 0 0.0% 

Over a Year 0 0.0% 

Never 1 2.0% 

Methadone 

Overall 7 100.0% 

Past 24 hrs 7 22.7% 

Past 2 days 6 13.1% 

Past Month 3 24.0% 

Past Year 8 3.7% 

Over a Year 8 16.3% 

Never 17 20.4% 

Opiates 

Overall 49 100.0% 

Past 24 hrs 13 73.0% 

Past 2 days 3 1.4% 

Past Month 5 23.0% 

Past Year 1 1.3% 

Over a Year 2 0.7% 

Never 2 0.6% 

Pain Killers 

Overall 26 100.0% 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results 

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Blood 

Positive for this Drug 

Drug Category 

Self-Reported 

Drug Use 

N 

(Unweighted)

% 

(Weighted) 

Past 24 hrs 0 NA 

Past 2 days 0 NA 

Past Month 0 NA 

Past Year 0 NA 

Over a Year 0 NA 

Never 0 NA 

PCP 

Overall 0 NA 

Table 142. Nighttime: Seat Belt Observation by Drug Prevalence (Blood) 

 

 N 

(Unweighted) 

% Drug 

Negative 

(Weighted) 

% Drug 

Positive 

(Weighted 

Driver Seat Belt Observation

Yes 3,159 86.5% 13.5% 

No 106 75.8% 24.2% 

Table 143. Nighttime: Seat Belt Observation by Drug Class (Percentages Calculated by Row) 

(Blood) 

 

N (Unweighted) % Antidepressants (Weighted) % Marijuana (Weighted) % NarcoticAnalgesic (Weighted) % Sedatives (Weighted) % Stimulants (Weighted) % Other (Weighted) % >1 Drug Class  (Weighted) % Negative (Weighted) 

Driver Seat Belt Observation 

Yes 3,156 1.1% 6.5% 0.8% 1.2% 1.8% 0.3% 1.9% 86.5%

No 106 0.2% 13.9% 3.1% 0.0% 4.4% 0.0% 2.5% 75.8%
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results 

126 

Table 144. Nighttime: Seat Belt Observation by Drug Category (Blood) 

 

 N 

(Unwtd) 

% 

Illegal 

(Weighted)

% 

Medications

(Weighted) 

% Illegal & 

Medications 

(Weighted) 

% 

Negative 

(Weighted)

Driver Seat Belt Observation 

Yes 3,156 8.81% 4.00% 0.66% 86.53%

No 106 20.25% 3.39% 0.55% 75.81%

Table 145. Nighttime: Helmet Use for Motorcycle Riders (Operators), by Drug Positive (Blood) 

 

N 

(Unweighted)

% Drug Positive 

(Weighted) 

Motorcycle Riders (Operators) 48 24.00% 

Helmet 37 15.90% 

No Helmet Use 9 44.05% 

Unknown 2 0.00% 

Table 146. Nighttime: Helmet Use for Motorcycle Riders (Operators), by Drug Class 

(Percentages Calculated by Row) (Blood) 

 

N (Unweighted) % Antidepressants (Weighted) % Marijuana (Weighted) % Narcotic-Analgesic (Weighted) % Sedatives (Weighted) % Stimulants (Weighted) % Other (Weighted) % >1 Drug Class  (Weighted) % Negative (Weighted) 

Motorcycle Riders (Operators) 48 0.85% 4.73% 0.00% 7.13% 10.70% 0.58% 0.00% 76.00%

Helmet 37 1.24% 1.92% 0.00% 10.34% 1.56% 0.84% 0.00% 84.10%

No Helmet Use 9 0.00% 11.52% 0.00% 0.00% 32.53% 0.00% 0.00% 55.95%

Unknown 2 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 100.00%

Table 147. Nighttime: Helmet Use for Motorcycle Riders (Operators), by Drug Category 

(Percentages Calculated by Row) (Blood) 

 

 N 

(Unwtd) 

% 

Illegal 

(Weighted) 

% 

Medications

(Weighted) 

% Illegal & 

Medications 

(Weighted) 

% 

Negative 

(Weighted)

Motorcycle Riders (Operators) 48 15.43% 8.57% 0.00% 76.00% 

Helmet 37 3.48% 12.42% 0.00% 84.10% 

No Helmet Use 9 44.05% 0.00% 0.00% 55.95% 

Unknown 2 0.00% 0.00% 0.00% 100.00% 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results 

127 

Table 148. Nighttime: Arrests and Drug Positives (Blood): “During the past 12 months, were you 

arrested and booked for driving under the influence of alcohol or drugs?” 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Yes 122 31.7% 

No 3,080 13.2% 

Total 3,202 13.9% 

(p < .01) 

Table 149. Nighttime: Arrests and Drug Class (Blood): “During the past 12 months, were you 

arrested and booked for driving under the influence of alcohol or drugs?” 

 

N (Unweighted) % Antidepressants (Weighted) % Marijuana (Weighted) % Narcotic-Analgesic (Weighted) % Sedatives (Weighted) % Stimulants (Weighted) % Other (Weighted) % >1 Drug Class  (Weighted) % Negative (Weighted) 

Yes 122 1.6% 10.9% 0.4% 0.2% 10.4% 0.0% 8.2% 68.3% 

No 3,080 1.1% 6.5% 0.9% 1.1% 1.6% 0.3% 1.8% 86.8% 

Total 3,202 1.1% 6.7% 0.9% 1.0% 1.9% 0.3% 2.0% 86.1% 

Table 150. Nighttime: Arrests and Drug Categories (Blood): “During the past 12 months, were you 

arrested and booked for driving under the influence of alcohol or drugs?” 

 

 N 

(Unwtd) 

% 

Illegal 

(Weighted) 

% 

Medications 

(Weighted) 

% Illegal & 

Medications 

(Weighted) 

% 

Negative 

(Weighted) 

Yes 122 22.3% 3.6% 5.8% 68.3% 

No 3,080 8.7% 4.1% 0.4% 86.8% 

Total 3,202 9.2% 4.1% 0.6% 86.1% 

Table 151. Nighttime: Past Treatment Program and Drug Positive (Blood): “During the past 12 

months, did you ever stay at least overnight in an inpatient or residential drug or alcohol 

treatment program?” 

 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Yes 31 22.0% 

No 3,065 13.7% 

Total 3,096 13.8% 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results 

128 

Table 152. Nighttime: Inpatient and Drug Class (Blood): “During the past 12 months, did you ever 

stay at least overnight in an impatient or residential drug or alcohol treatment program, for 

example, detox, rehab, a therapeutic community, or a hospital?” 

 

N (Unweighted) % Antidepressants (Weighted) % Marijuana (Weighted) % Narcotic-Analgesic (Weighted) % Sedatives (Weighted) % Stimulants (Weighted) % Other (Weighted) % >1 Drug Class  (Weighted) % Negative (Weighted) 

Yes 31 0.0% 2.2% 1.5% 0.9% 2.4% 0.0% 15.0% 78.0% 

No 3,065 1.1% 6.8% 0.9% 1.1% 1.7% 0.3% 1.8% 86.3% 

Total 3,096 1.1% 6.8% 0.9% 1.1% 1.7% 0.3% 1.9% 86.2% 

Table 153. Nighttime: Inpatient and Drug Category (Blood): “During the past 12 months, did you 

ever stay at least overnight in an impatient or residential drug or alcohol treatment program, for 

example, detox, rehab, a therapeutic community, or a hospital?” 

 

 N 

(Unwtd) 

% 

Illegal 

(Weighted) 

% 

Medications 

(Weighted) 

% Illegal & 

Medications 

(Weighted) 

% 

Negative 

(Weighted) 

Yes 31 4.6% 2.5% 15.0% 78.0% 

No 3,065 9.3% 3.9% 0.4% 86.3% 

Total 3,096 9.3% 3.9% 0.6% 86.2% 

Table 154. Nighttime: Outpatient and Drug Positive (Blood): “Have you ever been admitted to an 

outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?” 

 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Yes 109 22.3% 

No 3,089 13.5% 

Total 3,198 13.7% 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results 

129 

Table 155. Nighttime: Outpatient and Drug Class (Blood): “Have you ever been admitted to an 

outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?” 

 

N (Unweighted) % Antidepressants (Weighted) % Marijuana (Weighted) % Narcotic-Analgesic (Weighted) % Sedatives (Weighted) % Stimulants (Weighted) % Other (Weighted) % >1 Drug Class  (Weighted) % Negative (Weighted) 

Yes 109 2.1% 8.9% 0.6% 0.3% 9.3% 0.0% 1.1% 77.7% 

No 3,089 1.1% 6.6% 0.9% 1.1% 1.5% 0.3% 2.0% 86.5% 

Total 3,198 1.1% 6.7% 0.9% 1.0% 1.7% 0.3% 2.0% 86.3% 

Table 156. Nighttime: Outpatient and Categories (Blood): “Have you ever been admitted to an 

outpatient drug or alcohol treatment program, NOT including meetings like AA or NA?” 

 

 N 

(Unwtd) 

% 

Illegal 

(Weighted) 

% 

Medications 

(Weighted) 

% Illegal & 

Medications 

(Weighted) 

% 

Negative 

(Weighted) 

Yes 109 18.5% 3.0% 0.8% 77.7% 

No 3,089 8.9% 4.0% 0.6% 86.5% 

Total 3,198 9.1% 4.0% 0.6% 86.3% 

Table 157. Nighttime: AA or NA, and Drug Positives (Blood): “During the past 12 months, have you 

received treatment for your drug or alcohol use in a self-help group such as AA or NA?” 

 

N 

(Unweighted) 

% Drug Positive 

(Weighted) 

Yes 74 26.2% 

No 3,120 13.4% 

Total 3,194 13.8% 

(p < .01) 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results 

130 

Table 158. Nighttime: AA or NA, and Class (Blood): “During the past 12 months, have you received 

treatment for your drug or alcohol use in a self-help group such as AA or NA?” 

 

N (Unweighted) % Antidepressants (Weighted) % Marijuana (Weighted) % Narcotic-Analgesic (Weighted) % Sedatives (Weighted) % Stimulants (Weighted) % Other (Weighted) % >1 Drug Class  (Weighted) % Negative (Weighted) 

Yes 74 0.0% 17.1% 1.1% 0.3% 5.3% 0.0% 2.3% 73.8% 

No 3,120 1.1% 6.4% 0.9% 1.1% 1.6% 0.3% 2.0% 86.6% 

Total 3,194 

1. 

1% 6.7% 0.9% 1.0% 1.7% 0.3% 2.0% 86.2% 

Table 159. Nighttime: AA or NA, and Drug Categories (Blood): “During the past 12 months, have 

you received treatment for your drug or alcohol use in a self-help group such as AA or NA?” 

 

 N 

(Unwtd) 

% 

Illegal 

(Weighted) 

% 

Medications 

(Weighted) 

% Illegal & 

Medications 

(Weighted) 

% 

Negative 

(Weighted) 

Yes 74 22.5% 3.3% 0.4% 73.8% 

No 3,120 8.8% 4.0% 0.6% 86.6% 

Total 3,194 9.2% 4.0% 0.6% 86.2% 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results 

131 
2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results 

132 

DOT HS 811 249

December 2009