DEPARTMENT OF HEALTH AND HUMAN SERVICES 

Substance Abuse and Mental Health Services Administration 

Office of Applied Studies 

Worker Substance Use and Workplace 

Policies and Programs 

Sharon L. Larson 

Joe Eyerman 

Misty S. Foster 

Joseph C. Gfroerer 
ii 

Acknowledgments 

This report was prepared by the Division of Population Surveys, Office of Applied Studies, SAMHSA, 

and by RTI International, a trade name of Research Triangle Institute, Research Triangle Park, North 

Carolina. Work by RTI was performed under Contract No. 283-03-9028. Sharon Larson at SAMHSA was 

responsible for the content, analysis, and writing of the report. At RTI, Joe Eyerman coauthored the report 

and was the task leader for its production. Misty Foster at RTI coauthored the report and was lead 

statistician, and Mary Ellen Marsden reviewed the report. Joseph C. Gfroerer at SAMHSA coauthored 

and reviewed the report. The Division of Workplace Programs, Center for Substance Abuse Prevention, 

SAMHSA, provided suggestions on the content and reviewed the final draft of the report. Other 

contributors at RTI listed alphabetically include Walter Boyle, Andrew Clarke, Teresa Davis, David 

Heller, Erica Hirsch, and Lisa Packer. At RTI, Claudia Clark edited the report; Diane G. Eckard prepared 

the graphics; Brenda K. Porter formatted the tables; Joyce Clay-Brooks formatted and word processed the 

report; and Pamela Couch Prevatt, Teresa G. Bass, Cassandra Carter, and Shari B. Lambert prepared its 

press and Web versions. Final report production was provided by Beatrice Rouse, Coleen Sanderson, and 

Jane Feldmann at SAMHSA. 

Public Domain Notice 

All material appearing in this report is in the public domain and may be reproduced or copied without 

permission from the Substance Abuse and Mental Health Services Administration. However, this 

publication may not be reproduced or distributed for a fee without specific, written authorization of the 

Office of Communications, SAMHSA, U.S. Department of Health and Human Services. Citation of the 

source is appreciated. Suggested citation: 

Larson, S. L., Eyerman, J., Foster, M. S., & Gfroerer, J. C. (2007). Worker Substance Use 

and Workplace Policies and Programs (DHHS Publication No. SMA 07-4273, Analytic 

Series A-29). Rockville, MD: Substance Abuse and Mental Health Services 

Administration, Office of Applied Studies. 

Obtaining Additional Copies of Publication 

Copies may be obtained, free of charge, from the National Clearinghouse for Alcohol and Drug 

Information (NCADI), a service of SAMHSA. Write or call NCADI at: 

National Clearinghouse for Alcohol and Drug Information 

P.O. Box 2345 

Rockville, MD 20847-2345 

1-240-221-4017, 1-800-729-6686, TDD 1-800-487-4889 

Electronic Access to Publication 

This publication can be accessed electronically through the Internet connections listed below: 

http://www.samhsa.gov 

http://www.oas.samhsa.gov 

Originating Office 

SAMHSA, Office of Applied Studies 

1 Choke Cherry Road, Room 7-1044 

Rockville, MD 20857 

June 2007 
iii 

Table of Contents 

Chapter Page 

Highlights....................................................................................................................................... 1 

1. Introduction....................................................................................................................... 5 

1.1. Summary of NSDUH.............................................................................................. 5 

1.2. Format of Report and Explanation of Tables.......................................................... 7 

1.3. Content and Organization of This Report............................................................... 9 

2. Substance Use among Workers, by Demographic and Geographic 

Characteristics................................................................................................................. 11 

2.1. Illicit Drug Use among Full-Time Workers.......................................................... 12 

2.2. Past Month Marijuana Use among Full-Time Workers........................................ 15 

2.3. Past Month Heavy Alcohol Use among Full-Time Workers................................ 16 

2.4. Past Year Illicit Drug Dependence or Abuse among Full-Time Workers............ 17 

2.5. Past Year Alcohol Dependence or Abuse among Full-Time Workers................. 18 

2.6. Summary............................................................................................................... 19 

3. Substance Use among Workers, by Occupation, Industry, and 

Establishment Size .......................................................................................................... 21 

3.1. Standard Occupational and Industry Classifications ............................................ 22 

3.2. Illicit Drug Use among Full-Time Workers, by Occupation ................................ 22 

3.3. Heavy Alcohol Use among Full-Time Workers, by Occupation.......................... 23 

3.4. Dependence and Abuse among Full-Time Workers, by Occupation ................... 23 

3.5. Illicit Drug Use among Full-Time Workers, by Industry ..................................... 24 

3.6. Heavy Alcohol Use among Full-Time Workers, by Industry............................... 24 

3.7. Dependence and Abuse among Full-Time Workers, by Industry......................... 26 

3.8. Past Month Illicit Drug Use among Full-Time Workers, by Establishment 

Size........................................................................................................................ 26 

3.9. Past Month Marijuana Use among Full-Time Workers, by Establishment 

Size........................................................................................................................ 26 

3.10. Past Month Heavy Alcohol Use among Full-Time Workers, by 

Establishment Size................................................................................................ 26 

3.11. Past Year Illicit Drug Dependence or Abuse among Full-Time Workers, 

by Establishment Size........................................................................................... 27 

3.12. Past Year Alcohol Dependence or Abuse among Full-Time Workers, by 

Establishment Size................................................................................................ 27 

3.13. Summary............................................................................................................... 27 

4. Workplace Information Policies and Programs concerning Drug and 

Alcohol Use ...................................................................................................................... 29 

4.1. Demographic Characteristics of Workers Reporting Workplace Drug 

Policies and Programs........................................................................................... 29 

4.2. Working for Employers with Drug and Alcohol Policies and Programs, by 

Current Illicit Drug Use ........................................................................................ 34 
Table of Contents (continued) 

Chapter Page 

iv 

4.3. Working for Employers with Educational Programs, Written Policies, or 

EAPs, by Current Heavy Alcohol Use.................................................................. 37 

4.4. Working for Employers with Educational Programs, Written Policies, or 

EAPs, by Illicit Drug or Alcohol Dependence or Abuse during the Past 

Year....................................................................................................................... 39 

4.5. A Final Note about EAPs...................................................................................... 42 

4.6. Summary............................................................................................................... 43 

5. Workplace Testing.......................................................................................................... 45 

5.1. Prehire-Testing Programs among Full-Time Workers ......................................... 45 

5.2. Prehire Testing among Full-Time Workers, by Substance Use and 

Dependence and Abuse......................................................................................... 48 

5.3. Random-Testing Programs among Full-Time Workers ....................................... 53 

5.4. Random Testing among Full-Time Workers, by Substance Use and 

Dependence and Abuse......................................................................................... 55 

5.5. Summary............................................................................................................... 59 

6. Workplace Behaviors and Attitudes toward Drug Testing......................................... 61 

6.1. Workplace Behaviors among Full-Time Workers................................................ 61 

6.2. Workplace Attitudes toward Drug or Alcohol Testing among Full-Time 

Workers................................................................................................................. 63 

6.3. Multivariate Analysis of Drug Testing in Current Employment Setting and 

Willingness to Work for an Employer Who Tests for Drugs ............................... 65 

6.4. Summary............................................................................................................... 68 

Appendix 

A. Description of the Survey ..................................................................................................71 

B. Statistical Methods and Measurement ...............................................................................79 

C. Key Definitions, 2002-2004...............................................................................................91 

D. Occupational and Industry Classifications.......................................................................103 

E. Selected Data Tables........................................................................................................115 

F. References........................................................................................................................185 
v 

List of Figures 

Figure Page 

2.1 Past Month Substance Use and Past Year Substance Dependence or Abuse among 

Persons Aged 18 to 64, by Employment Status: 2002-2004 Combined........................... 11 

2.2 Percentage Distribution of Persons Aged 18 to 64, by Employment Status: 2002-

2004 Combined................................................................................................................. 12 

2.3 Past Month Substance Use and Past Year Substance Dependence or Abuse among 

Full-Time Workers, by Age Group: 2002-2004 Combined.............................................. 13 

2.4 Past Month Substance Use and Past Year Substance Dependence or Abuse among 

Full-Time Workers Aged 18 to 64, by Gender: 2002-2004 Combined............................ 13 

2.5 Past Month Substance Use among Full-Time Workers Aged 18 to 64, by Hispanic 

or Latino Origin and Race: 2002-2004 Combined ........................................................... 14 

2.6 Past Month Substance Use and Past Year Substance Dependence or Abuse among 

Full-Time Workers Aged 18 to 64, by Education: 2002-2004 Combined ....................... 14 

2.7 Past Month Substance Use and Past Year Substance Dependence or Abuse among 

Full-Time Workers Aged 18 to 64, by Family Income: 2002-2004 Combined ............... 15 

2.8 Past Year Substance Dependence or Abuse among Full-Time Workers Aged 18 to 

64, by Hispanic or Latino Origin and Race: 2002-2004 Combined ................................. 17 

3.1 Past Month Illicit Drug Use among Full-Time Workers Aged 18 to 64, by Major 

Occupational Categories: 2002-2004 Combined.............................................................. 23 

3.2 Past Month Heavy Alcohol Use among Full-Time Workers Aged 18 to 64, by 

Major Occupational Categories: 2002-2004 Combined ................................................... 24 

3.3 Past Month Illicit Drug Use among Full-Time Workers Aged 18 to 64, by 

Industry Categories: 2002-2004 Combined...................................................................... 25 

3.4 Past Month Heavy Alcohol Use among Full-Time Workers Aged 18 to 64, by 

Industry Categories: 2002-2004 Combined...................................................................... 25 

4.1 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an Employee Assistance Program concerning Drug or Alcohol Use 

among Full-Time Workers Aged 18 to 64, by Age Group: 2002-2004 Combined.......... 30 

4.2 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an Employee Assistance Program concerning Drug or Alcohol Use 

among Full-Time Workers Aged 18 to 64, by Gender: 2002-2004 Combined................ 30 
List of Figures (continued) 

Figure Page 

vi 

4.3 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an Employee Assistance Program concerning Drug or Alcohol Use 

among Full-Time Workers Aged 18 to 64, by Hispanic or Latino Origin and Race: 

2002-2004 Combined........................................................................................................ 31 

4.4 Workplace Provides Educational Information concerning Drug or Alcohol Use 

among Full-Time Workers Aged 18 to 64, by Education and Family Income: 

2002-2004 Combined........................................................................................................ 32 

4.5 Workplace Prepares a Written Policy concerning Drug or Alcohol Use among 

Full-Time Workers Aged 18 to 64, by Education and Family Income: 2002-2004 

Combined.......................................................................................................................... 33 

4.6 Workplace Maintains an Employee Assistance Program concerning Drug or 

Alcohol Use among Full-Time Workers Aged 18 to 64, by Education and Family 

Income: 2002-2004 Combined ......................................................................................... 33 

4.7 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an Employee Assistance Program concerning Drug or Alcohol Use 

among Full-Time Workers Aged 18 to 64, by Past Month Illicit Drug Use: 2002-

2004 Combined................................................................................................................. 34 

4.8 Workplace Provides Educational Information concerning Drug or Alcohol Use 

among Full-Time Workers Aged 18 to 64, by Age Group and Past Month Illicit 

Drug Use: 2002-2004 Combined...................................................................................... 35 

4.9 Workplace Prepares a Written Policy concerning Drug or Alcohol Use among 

Full-Time Workers Aged 18 to 64, by Age Group and Past Month Illicit Drug 

Use: 2002-2004 Combined ............................................................................................... 36 

4.10 Workplace Maintains an Employee Assistance Program concerning Drug or 

Alcohol Use among Full-Time Workers Aged 18 to 64, by Age Group and Past 

Month Illicit Drug Use: 2002-2004 Combined................................................................. 36 

4.11 Workplace Maintains an Employee Assistance Program concerning Drug or 

Alcohol Use among Full-Time Workers Aged 18 to 64, by Hispanic or Latino 

Origin and Race and Past Month Illicit Drug Use: 2002-2004 Combined....................... 37 

4.12 Workplace Provides Educational Information concerning Drug or Alcohol Use 

among Full-Time Workers Aged 18 to 64, by Hispanic or Latino Origin and Race 

and Past Month Heavy Alcohol Use: 2002-2004 Combined............................................ 39 
List of Figures (continued) 

Figure Page 

vii 

4.13 Workplace Prepares a Written Policy concerning Drug or Alcohol Use among 

Full-Time Workers Aged 18 to 64, by Hispanic or Latino Origin and Race and 

Past Month Heavy Alcohol Use: 2002-2004 Combined................................................... 40 

4.14 Workplace Maintains an Employee Assistance Program concerning Drug or 

Alcohol Use among Full-Time Workers Aged 18 to 64, by Hispanic or Latino 

Origin and Race and Past Month Heavy Alcohol Use: 2002-2004 Combined................. 41 

4.15 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an Employee Assistance Program concerning Drug or Alcohol Use 

among Full-Time Workers Aged 18 to 64 with Past Month Heavy Alcohol Use, 

by Education: 2002-2004 Combined ................................................................................ 42 

5.1 Workplace Drug or Alcohol Use Testing Practices among Full-Time Workers 

Aged 18 to 64: 2002-2004 Combined............................................................................... 46 

5.2 Workplace Tests Employees for Drug or Alcohol Use during Hiring Process 

among Full-Time Workers Aged 18 to 64, by Major Occupational Categories: 

2002-2004 Combined........................................................................................................ 47 

5.3 Workplace Tests during Hiring Process among Full-Time Workers Aged 18 to 64, 

by Age Group and Past Month Illicit Drug Use: 2002-2004 Combined .......................... 49 

5.4 Workplace Tests during Hiring Process among Full-Time Workers Aged 18 to 64, 

by Hispanic or Latino Origin and Race and Past Month Illicit Drug Use: 2002-

2004 Combined................................................................................................................. 49 

5.5 Workplace Tests during Hiring Process among Full-Time Workers Aged 18 to 64, 

by Gender and Past Month Illicit Drug Use: 2002-2004 Combined ................................ 50 

5.6 Workplace Tests during Hiring Process among Full-Time Workers Aged 18 to 64, 

by Education and Past Month Illicit Drug Use: 2002-2004 Combined............................ 50 

5.7 Workplace Tests during Hiring Process among Full-Time Workers Aged 18 to 64, 

by County Type and Past Month Illicit Drug Use: 2002-2004 Combined ....................... 51 

5.8 Workplace Tests during Hiring Process among Full-Time Workers Aged 18 to 64, 

by Age Group and Past Month Heavy Alcohol Use: 2002-2004 Combined.................... 51 

5.9 Workplace Tests during Hiring Process among Full-Time Workers Aged 18 to 64, 

by Establishment Size and Past Month Illicit Drug or Alcohol Use: 2002-2004 

Combined.......................................................................................................................... 52 
List of Figures (continued) 

Figure Page 

viii 

5.10 Workplace Tests Employees for Drug or Alcohol Use on a Random Basis among 

Full-Time Workers Aged 18 to 64, by Major Occupational Categories: 2002-2004 

Combined.......................................................................................................................... 54 

5.11 Workplace Tests on a Random Basis among Full-Time Workers Aged 18 to 64, 

by County Type: 2002-2004 Combined ........................................................................... 54 

5.12 Workplace Tests on a Random Basis among Full-Time Workers Aged 18 to 64, 

by Family Income and Past Month Illicit Drug Use: 2002-2004 Combined.................... 55 

5.13 Workplace Tests on a Random Basis among Full-Time Workers Aged 18 to 64, 

by Age Group and Past Month Illicit Drug Use: 2002-2004 Combined .......................... 56 

5.14 Workplace Tests on a Random Basis among Full-Time Workers Aged 18 to 64, 

by Hispanic or Latino Origin and Race and Past Month Illicit Drug Use: 2002-

2004 Combined................................................................................................................. 57 

5.15 Workplace Tests on a Random Basis among Full-Time Workers Aged 18 to 64, 

by Education and Past Month Illicit Drug Use: 2002-2004 Combined............................ 57 

5.16 Workplace Tests during Hiring Process or on a Random Basis among Full-Time 

Workers Aged 18 to 64, by Past Year Illicit Drug or Alcohol Dependence or 

Abuse: 2002-2004 Combined ........................................................................................... 58 

5.17 Workplace Tests on a Random Basis among Full-Time Workers Aged 18 to 64, 

by Establishment Size and Past Month Illicit Drug or Alcohol Use: 2002-2004 

Combined.......................................................................................................................... 59 

6.1 Workplace Behaviors among Full-Time Workers Aged 18 to 64, by Past Month 

Substance Use: 2002-2004 Combined.............................................................................. 62 

6.2 Workplace Behaviors among Full-Time Workers Aged 18 to 64, by Past Month 

Heavy Alcohol Use: 2002-2004 Combined...................................................................... 63 

6.3 Employees' Feelings toward Working for Employers Who Test during Hiring 

Process among Full-Time Workers Aged 18 to 64, by Past Month Illicit Drug 

Use: 2002-2004 Combined ............................................................................................... 64 

6.4 Employees' Feelings toward Working for Employers Who Test on a Random 

Basis among Full-Time Workers Aged 18 to 64, by Past Month Illicit Drug Use: 

2002-2004 Combined........................................................................................................ 65 

B.1 Required Effective Sample as a Function of the Proportion Estimated.............................82 
ix 

List of Tables 

Table Page 

6-A Results of Multinomial Logit Model of Willingness to Work for Employers Who 

Test for Drug or Alcohol Use during Hiring Process or on a Random Basis among 

Full-Time Workers Aged 18 to 64: 2002-2004 ................................................................ 67 

6-B Results of Logistic Models of Employers Who Test for Drug or Alcohol Use 

among Full-Time Workers Aged 18 to 64: 2002-2004 .................................................... 68 

B.1 Summary of 2004 NSDUH Suppression Rules .................................................................87 

B.2 Weighted Percentages and Sample Sizes for 2002, 2003, and 2004 NSDUHs, by 

Screening Result Code.......................................................................................................88 

B.3 Response Rates and Sample Sizes for Persons Aged 18 to 64 in the 2002, 2003 

and 2004 NSDUHs, by Demographic Characteristics.......................................................89 

2.1 Substance Use and Substance Dependence or Abuse among Persons Aged 18 to 

64, by Employment Status: Percentages, Numbers in Thousands, and Percentage 

Distributions, Annual Averages Based on 2002-2004.................................................... 117 

2.2 Illicit Drug, Marijuana, and Heavy Alcohol Use in the Past Month among FullTime Workers Aged 18 to 64, by Demographic Characteristics: Percentages and 

Numbers in Thousands, Annual Averages Based on 2002-2004 ................................... 118 

2.3 Illicit Drug, Marijuana, and Heavy Alcohol Use in the Past Month among FullTime Workers Aged 18 to 64, by Educational Attainment, Family Income, and 

Geographic Characteristics: Percentages and Numbers in Thousands, Annual 

Averages Based on 2002-2004 ....................................................................................... 119 

2.4 Substance Dependence or Abuse in the Past Year among Full-Time Workers 

Aged 18 to 64, by Demographic Characteristics: Percentages and Numbers in 

Thousands, Annual Averages Based on 2002-2004 ....................................................... 120 

2.5 Substance Dependence or Abuse in the Past Year among Full-Time Workers 

Aged 18 to 64, by Educational Attainment, Family Income, and Geographic 

Characteristics: Percentages and Numbers in Thousands, Annual Averages Based 

on 2002-2004 .................................................................................................................. 121 

3.1 Sample Sizes, Average Age, and Percentage Distribution of Males among FullTime Workers Aged 18 to 64, by Occupational Categories: Annual Averages 

Based on 2002-2004 ....................................................................................................... 122 

3.2 Sample Sizes, Average Age, and Percentage Distribution of Males among FullTime Workers Aged 18 to 64, by Industry Categories: Annual Averages Based on 

2002-2004 ....................................................................................................................... 125 
List of Tables (continued) 

Table Page 

x 

3.3 Illicit Drug, Marijuana, and Heavy Alcohol Use in the Past Month among FullTime Workers Aged 18 to 64, by Occupational Categories: Percentages and 

Numbers in Thousands, Annual Averages Based on 2002-2004 ................................... 129 

3.4 Substance Dependence or Abuse in the Past Year among Full-Time Workers 

Aged 18 to 64, by Occupational Categories: Percentages and Numbers in 

Thousands, Annual Averages Based on 2002-2004 ....................................................... 132 

3.5 Illicit Drug, Marijuana, and Heavy Alcohol Use in the Past Month among FullTime Workers Aged 18 to 64, by Industry Categories: Percentages and Numbers 

in Thousands, Annual Averages Based on 2002-2004 ................................................... 135 

3.6 Substance Dependence or Abuse in the Past Year among Full-Time Workers 

Aged 18 to 64, by Industry Categories: Percentages and Numbers in Thousands, 

Annual Averages Based on 2002-2004........................................................................... 139 

3.7 Illicit Drug, Marijuana, and Heavy Alcohol Use in the Past Month among FullTime Workers Aged 18 to 64, by Establishment Size: Percentages and Numbers 

in Thousands, Annual Averages Based on 2002-2004 ................................................... 143 

3.8 Substance Dependence and Abuse in the Past Year among Full-Time Workers 

Aged 18 to 64, by Establishment Size: Percentages and Numbers in Thousands, 

Annual Averages Based on 2002-2004........................................................................... 143 

4.1 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an EAP concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Demographic Characteristics: Percentages and Numbers in 

Thousands, Annual Averages Based on 2002-2004 ....................................................... 144 

4.2 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an EAP concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Educational Attainment, Family Income, and Geographic 

Characteristics: Percentages and Numbers in Thousands, Annual Averages Based 

on 2002-2004 .................................................................................................................. 145 

4.3 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an EAP concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Demographic Characteristics and Past Month Illicit Drug Use: 

Percentages, Annual Averages Based on 2002-2004 ..................................................... 146 
List of Tables (continued) 

Table Page 

xi 

4.4 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an EAP concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Educational Attainment, Family Income, Geographic 

Characteristics, and Past Month Illicit Drug Use: Percentages, Annual Averages 

Based on 2002-2004 ....................................................................................................... 147 

4.5 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an EAP concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Demographic Characteristics and Past Month Heavy Alcohol 

Use: Numbers in Thousands, Annual Averages Based on 2002-2004 ........................... 148 

4.6 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an EAP concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Demographic Characteristics and Past Month Heavy Alcohol 

Use: Percentages, Annual Averages Based on 2002-2004 ............................................. 149 

4.7 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an EAP concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Educational Attainment, Family Income, Geographic 

Characteristics, and Past Month Heavy Alcohol Use: Numbers in Thousands, 

Annual Averages Based on 2002-2004........................................................................... 150 

4.8 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an EAP concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Educational Attainment, Family Income, Geographic 

Characteristics, and Past Month Heavy Alcohol Use: Percentages, Annual 

Averages Based on 2002-2004 ....................................................................................... 151 

4.9 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an EAP concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Demographic Characteristics and Past Year Illicit Drug 

Dependence or Abuse: Percentages, Annual Averages Based on 2002-2004................ 152 

4.10 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an EAP concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Demographic Characteristics and Past Year Alcohol 

Dependence or Abuse: Percentages, Annual Averages Based on 2002-2004................ 153 

4.11 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an EAP concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Educational Attainment, Family Income, Geographic 

Characteristics, and Past Year Alcohol Dependence or Abuse: Percentages, 

Annual Averages Based on 2002-2004........................................................................... 154 
List of Tables (continued) 

Table Page 

xii 

5.1 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or 

on a Random Basis concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Demographic Characteristics: Percentages and Numbers in 

Thousands, Annual Averages Based on 2002-2004 ....................................................... 155 

5.2 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or 

on a Random Basis concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Educational Attainment, Family Income, and Geographic 

Characteristics: Percentages and Numbers in Thousands, Annual Averages Based 

on 2002-2004 .................................................................................................................. 156 

5.3 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or 

on a Random Basis concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Demographic Characteristics and Past Month Illicit Drug Use: 

Percentages, Annual Averages Based on 2002-2004 ..................................................... 157 

5.4 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or 

on a Random Basis concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Educational Attainment, Family Income, Geographic 

Characteristics, and Past Month Illicit Drug Use: Percentages, Annual Averages 

Based on 2002-2004 ....................................................................................................... 158 

5.5 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or 

on a Random Basis concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Demographic Characteristics and Past Month Heavy Alcohol 

Use: Numbers in Thousands, Annual Averages Based on 2002-2004 ........................... 159 

5.6 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or 

on a Random Basis concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Demographic Characteristics and Past Month Heavy Alcohol 

Use: Percentages, Annual Averages Based on 2002-2004 ............................................. 160 

5.7 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or 

on a Random Basis concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Educational Attainment, Family Income, Geographic 

Characteristics, and Past Month Heavy Alcohol Use: Percentages, Annual 

Averages Based on 2002-2004 ....................................................................................... 161 

5.8 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or 

on a Random Basis concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Demographic Characteristics and Past Month Marijuana Use: 

Numbers in Thousands, Annual Averages Based on 2002-2004 ................................... 162 
List of Tables (continued) 

Table Page 

xiii 

5.9 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or 

on a Random Basis concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Demographic Characteristics and Past Month Marijuana Use: 

Percentages, Annual Averages Based on 2002-2004 ..................................................... 163 

5.10 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or 

on a Random Basis concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Educational Attainment, Family Income, Geographic 

Characteristics, and Past Month Marijuana Use: Numbers in Thousands, Annual 

Averages Based on 2002-2004 ....................................................................................... 164 

5.11 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or 

on a Random Basis concerning Drug or Alcohol Use among Full-Time Workers 

Aged 18 to 64, by Educational Attainment, Family Income, Geographic 

Characteristics, and Past Month Marijuana Use: Percentages, Annual Averages 

Based on 2002-2004 ....................................................................................................... 165 

5.12 Type of Testing Program Reported concerning Drug or Alcohol Use among FullTime Workers Aged 18 to 64, by Establishment Size: Percentages and Numbers 

in Thousands, Annual Averages Based on 2002-2004 ................................................... 166 

6.1 Employees' Feelings toward Working for Employers Who Conduct Drug Testing 

before Hiring or Who Test Randomly concerning Drug or Alcohol Use among 

Full-Time Workers Aged 18 to 64, by Demographic Characteristics: Percentages, 

Annual Averages Based on 2002-2004........................................................................... 167 

6.2 Employees' Feelings toward Working for Employers Who Conduct Drug Testing 

before Hiring or Who Test Randomly concerning Drug or Alcohol Use among 

Full-Time Workers Aged 18 to 64, by Educational Attainment, Family Income, 

Geographic Characteristics, and Past Month Illicit Drug Use: Percentages, Annual 

Averages Based on 2002-2004 ....................................................................................... 168 

6.3 Employees' Feelings toward Working for Employers Who Conduct Drug Testing 

before Hiring concerning Drug or Alcohol Use among Full-Time Workers Aged 

18 to 64, by Demographic Characteristics and Past Month Illicit Drug Use: 

Percentages, Annual Averages Based on 2002-2004 ..................................................... 169 

6.4 Employees' Feelings toward Working for Employers Who Conduct Drug Testing 

before Hiring concerning Drug or Alcohol Use among Full-Time Workers Aged 

18 to 64, by Educational Attainment, Family Income, Geographic Characteristics, 

and Past Month Illicit Drug Use: Percentages, Annual Averages Based on 2002-

2004................................................................................................................................. 170 
List of Tables (continued) 

Table Page 

xiv 

6.5 Employees' Feelings toward Working for Employers Who Conduct Drug Testing 

Randomly concerning Drug or Alcohol Use among Full-Time Workers Aged 18 

to 64, by Demographic Characteristics and Past Month Illicit Drug Use: 

Percentages, Annual Averages Based on 2002-2004 ..................................................... 171 

6.6 Employees' Feelings toward Working for Employers Who Conduct Drug Testing 

Randomly concerning Drug or Alcohol Use among Full-Time Workers Aged 18 

to 64, by Educational Attainment, Family Income, Geographic Characteristics, 

and Past Month Illicit Drug Use: Percentages, Annual Averages Based on 2002-

2004................................................................................................................................. 172 

6.7 Employees' Feelings toward Working for Employers Who Conduct Drug Testing 

before Hiring concerning Drug or Alcohol Use among Full-Time Workers Aged 

18 to 64, by Demographic Characteristics and Past Month Heavy Alcohol Use: 

Percentages, Annual Averages Based on 2002-2004 ..................................................... 173 

6.8 Employees' Feelings toward Working for Employers Who Conduct Drug Testing 

before Hiring concerning Drug or Alcohol Use among Full-Time Workers Aged 

18 to 64, by Educational Attainment, Family Income, Geographic Characteristics, 

and Past Month Heavy Alcohol Use: Percentages, Annual Averages Based on 

2002-2004 ....................................................................................................................... 174 

6.9 Employees' Feelings toward Working for Employers Who Conduct Drug Testing 

Randomly concerning Drug or Alcohol Use among Full-Time Workers Aged 18 

to 64, by Demographic Characteristics and Past Month Heavy Alcohol Use: 

Percentages, Annual Averages Based on 2002-2004 ..................................................... 175 

6.10 Employees' Feelings toward Working for Employers Who Conduct Drug Testing 

Randomly concerning Drug or Alcohol Use among Full-Time Workers Aged 18 

to 64, by Educational Attainment, Family Income, Geographic Characteristics, 

and Past Month Heavy Alcohol Use: Percentages, Annual Averages Based on 

2002-2004 ....................................................................................................................... 176 

6.11 Employees' Feelings toward Working for Employers Who Conduct Drug Testing 

before Hiring concerning Drug or Alcohol Use among Full-Time Workers Aged 

18 to 64, by Demographic Characteristics and Past Month Marijuana Use: 

Percentages, Annual Averages Based on 2002-2004 ..................................................... 177 

6.12 Employees' Feelings toward Working for Employers Who Conduct Drug Testing 

before Hiring concerning Drug or Alcohol Use among Full-Time Workers Aged 

18 to 64, by Educational Attainment, Family Income, Geographic Characteristics, 

and Past Month Marijuana Use: Percentages, Annual Averages Based on 2002-

2004................................................................................................................................. 178 
List of Tables (continued) 

Table Page 

xv 

6.13 Employees' Feelings toward Working for Employers Who Conduct Drug Testing 

Randomly concerning Drug or Alcohol Use among Full-Time Workers Aged 18 

to 64, by Demographic Characteristics and Past Month Marijuana Use: 

Percentages, Annual Averages Based on 2002-2004 ..................................................... 179 

6.14 Employees' Feelings toward Working for Employers Who Conduct Drug Testing 

Randomly concerning Drug or Alcohol Use among Full-Time Workers Aged 18 

to 64, by Educational Attainment, Family Income, Geographic Characteristics, 

and Past Month Marijuana Use: Percentages, Annual Averages Based on 2002-

2004................................................................................................................................. 180 

6.15 Results of Multinomial Logit Model of Willingness to Work for Employers Who 

Test for Drug or Alcohol Use during Hiring Process among Full-Time Workers 

Aged 18 to 64: 2002-2004 .............................................................................................. 181 

6.16 Results of Multinomial Logit Model of Willingness to Work for Employers Who 

Test for Drug or Alcohol Use on a Random Basis among Full-Time Workers 

Aged 18 to 64: 2002-2004 .............................................................................................. 182 

6.17 Results of Logistic Models of Employers Who Test for Drug or Alcohol Use 

among Full-Time Workers Aged 18 to 64: 2002-2004 .................................................. 183 
xvi 
1 

Highlights 

This report presents findings on substance use among workers and on workplace drug 

policy and programs from the 2002, 2003, and 2004 National Surveys on Drug Use and Health 

(NSDUHs). NSDUH is an annual survey of the civilian, noninstitutionalized population of the 

United States aged 12 years or older. The survey is sponsored by the Substance Abuse and 

Mental Health Administration (SAMHSA) to provide data on substance use and related issues 

among the U.S. population. 

NSDUH collects information on employment status, type of business, specific 

occupations and industries, and information on drug-testing policies and programs from U.S. 

workers. This report analyzes the worker information in conjunction with the substance use data 

collected in the survey to investigate substance use among full-time employed U.S. workers aged 

18 to 64 during the period 2002 to 2004. 

Substance Use among Workers, by Demographic and Geographic Characteristics 

! The prevalences of substance use behaviors and substance use disorders are higher among 

unemployed persons than among full-time workers, part-time workers, and those with other 

employment status. However, because full-time workers constitute about two thirds of the 

population aged 18 to 64 (or 114.7 million persons), most substance users and most of 

those with substance use disorders are employed full time. 

! The prevalence of past month illicit drug use among full-time workers aged 18 to 64 was 

estimated to be 8.2 percent in 2002, 2003, and 2004. Nearly one out of five (19.0 percent) 

workers aged 18 to 25 used illicit drugs during the past month. This was a higher 

percentage than among the 26-to-34 (10.3 percent), 35-to-49 (7.0 percent), and 50-to-64 

(2.6 percent) age groups. 

! Males were more likely than females to report past month illicit drug use (9.7 vs. 6.2 

percent). Males accounted for about two thirds (6.4 million) of the workers who reported 

past month illicit drug use. 

! Workers with a college education had a lower prevalence of past month illicit drug use 

compared with those without a college education. The prevalence of past month use of 

illicit drugs was lower among those with higher levels of education than those with less 

education (college graduate [5.7 percent] vs. less than high school [11.2 percent]). 

! The prevalence of past month illicit drug use was lower among workers with higher family 

incomes than among workers with lower family incomes. An estimated 13.2 percent of 

workers who reported family income that was less than $20,000 had used illicit drugs 

during the past month. In contrast, 6.0 percent of workers who reported income in the 

highest category––$75,000 or more––had used illicit drugs during the past month. 
2 

! An estimated 8.8 percent, or 10.1 million, of full-time workers reported past month heavy 

alcohol use. Among younger workers (18 to 25 years old), 16.3 percent reported past 

month heavy alcohol use compared with 10.4 percent of 26- to 34-year-olds, 8.1 percent of 

35- to 49-year-olds, and 4.7 percent of 50- to 64-year-olds. 

Substance Use among Workers, by Occupation, Industry, and Establishment Size

! Of the major occupational groups, food service workers (17.4 percent) and construction 

workers (15.1 percent) exhibited a higher prevalence of past month illicit drug use than 

other occupational groups. Those working in education, training, and library occupations 

(4.1 percent), community and social services occupations (4.0 percent), and protective 

service occupations (3.4 percent) had the lowest prevalence of past month illicit drug use 

among the major occupational groups. 

! The major occupational groups with the highest prevalence of past month heavy alcohol 

use were construction and extraction occupations (17.8 percent) and installation, 

maintenance, and repair occupations (14.7 percent). Community and social services 

occupations (2.8 percent) had the lowest prevalence of past month heavy alcohol use of the 

major occupations. 

! The major industry groups with the highest prevalence of past month illicit drug use were 

accommodations and food services (16.9 percent) and construction (13.7 percent). Public 

administration (4.1 percent), educational services (4.0 percent), and utilities (3.8 percent) 

had the lowest prevalence of past month illicit drug use. 

! The industry groups with the highest prevalence of past month heavy alcohol use were 

construction (15.9 percent); arts, entertainment, and recreation (13.6 percent); and mining 

(13.3 percent) industries. However, health care and social assistance (4.3 percent) and 

educational services (4.0 percent) had the lowest prevalence of past month heavy alcohol 

use compared with the other major industries. 

! Prevalence of past month illicit drug use was lower as establishment size increased. The 

prevalence among workers in establishments with 25 to 99 employees was 8.2 percent, 

compared with 6.7 percent among workers in establishments with 100 to 499 employees 

and 5.7 percent among workers in establishments with 500 or more employees. A similar 

pattern was found for past month heavy alcohol use. 

Workplace Information Policies and Programs concerning Drug and Alcohol Use

! Among the nearly 115 million full-time workers aged 18 to 64 years in the United States, 

47.7 million (43.8 percent) reported that they had access to educational information about 

drug and alcohol use in the workplace, 87.0 million (78.7 percent) reported that they were 

aware of a written policy about drug and alcohol use in the workplace, and 60.9 million 

(58.4 percent) reported that their employer offered an employee assistance program (EAP). 
3 

! The youngest adult workers were least likely to report access to educational information 

about drug and alcohol use in the workplace. Among 18- to 25-year-old workers, 33.2 

percent reported that they had educational information available. This was significantly 

lower than among workers aged 26 to 34 years (39.6 percent), 35 to 49 years (46.3 

percent), and 50 to 64 years (48.9 percent). Young adult workers between the ages of 18 

and 25 were significantly less likely to report EAPs available in the workplace compared 

with all other age groups (39.7 vs. 56.4 to 62.6 percent). 

! Nearly 3 million (32.1 percent) full-time workers between the ages of 18 and 64 who had 

used an illicit drug in the past month reported that they worked for an employer who 

offered educational information about alcohol and drug use. An EAP was reported 

available to 3.9 million (45.4 percent) workers who were past month users of an illicit drug, 

while 6.5 million (71.0 percent) reported working for employers who had a written policy 

about drug and alcohol use. 

! Generally, past month illicit drug users were less likely to report working for employers 

who offered workplace drug or alcohol programs or policies, compared with those who did 

not use an illicit drug in the past month. An estimated 45.4 percent of past month illicit 

drug users reported that there was an EAP at their place of employment compared with 

59.6 percent of workers who had not used an illicit drug in the past month. 

Workplace Testing

! Among the Nation's full-time workers, 42.9 percent reported that tests for illicit drug or 

alcohol use occurred at their place of employment during the hiring process, or "prehire" 

testing. This equates to more than 47 million adults who worked in settings where testing 

for illicit drug or alcohol use occurred during the hiring process. 

! The youngest and oldest adult workers (18 to 25 and 50 to 64 years) were less likely to 

report working for employers with prehire drug testing than workers aged 26 to 49 years. 

An estimated 40.8 percent of 50- to 64-year-olds and 39.0 percent of 18- to 25-year-olds 

reported prehire testing, compared with 44.3 percent of workers aged 26 to 34 years and 

44.7 percent of workers aged 35 to 49 years. 

! For each age group, past month illicit drug users were less likely than nonusers to report 

working for employers who conducted prehire drug or alcohol tests (29.4 vs. 41.3 percent 

of 18- to 25-year-olds, 32.0 vs. 45.8 percent of 26- to 34-year-olds, 34.2 vs. 45.5 percent of 

35- to 49-year-olds, and 31.3 vs. 41.0 percent of 50- to 64-year-olds). 

! A total of 29.6 percent, or 32 million, of full-time workers in the United States reported 

random drug testing in their current employment setting during the study period. The 

youngest workers (18 to 25 years) were less likely than all other age groups to report 

working for an employer who conducted random drug testing (27.3 vs. 29.6 percent of 26- 

to 34-year-olds, 30.6 percent of 35- to 49-year-olds, and 29.1 percent of 50- to 64-yearolds). 
4 

! Past month illicit drug users were less likely to report working for employers who 

conducted random drug or alcohol tests than were nondrug users. For 18- to 25-year-olds, 

19.7 percent of illicit drug users reported that they worked in a random-testing environment 

compared with 29.1 percent of nonusers. The relationship was consistent for all age groups: 

20.0 versus 30.8 percent of 26- to 34-year-olds, 22.6 versus 31.2 percent of 35- to 49-yearolds, and 20.4 versus 29.3 percent of 50- to 64-year-olds. 

Workplace Behaviors and Attitudes toward Drug Testing

! Among full-time workers who reported past month illicit drug use, 12.3 percent reported 

working for three or more employers in the past year, compared with 5.1 percent of 

workers without past month drug use. They also were more likely to report missing 2 or 

more workdays in the past month due to illness or injury when compared with workers 

without past month use (16.4 vs. 11.0 percent). Finally, 16.3 percent of workers who used 

illicit drugs in the past month reported skipping 1 or more days of work in the past month 

(vs. 8.2 percent of workers who did not use an illicit drug during the past month). 

! Among full-time workers in the United States, 52.5 million (46.0 percent) workers 

indicated that they would be more likely to work for an employer who tests before hiring, 

and an additional 56.2 million (49.1 percent) workers reported that prehire testing would 

not influence their decision to work for an employer. Only 5.6 million (4.9 percent) 

workers indicated that they would be less likely to work for an employer who conducts 

prehire drug testing. 

! More than half of U.S. workers reported that it would make no difference to them if an 

employer tests employees randomly after hire for drug or alcohol use. An estimated 45.5 

million (39.8 percent) workers reported that they would be more likely to work for such an 

employer, while 10.0 million (8.7 percent) workers reported that they would be less likely 

to work for an employer who tests randomly for drug or alcohol use. An estimated 58.8 

million (51.4 percent) workers indicated that random testing would not influence their 

decision to work for an employer. 

! An estimated 29.1 percent of workers with past month illicit drug use reported that they 

would be less likely to work for employers who conduct drug testing randomly, while only 

6.9 percent of workers who did not report past month illicit drug use selected this response 

category. This relationship was consistent in the multivariate models while controlling for 

age, gender, race/ethnicity, educational attainment, family income, region, and county type 

(metropolitan statistical area). 
5 

1. Introduction 

This report presents findings on substance use among workers and workplace drug policy 

and programs from the 2002, 2003, and 2004 National Surveys on Drug Use and Health 

(NSDUHs). NSDUH is an annual survey of the civilian, noninstitutionalized population of the 

United States aged 12 years or older. It is the primary source of statistical information on the use 

of illegal drugs by the U.S. population. The purpose of this report is to describe the nature of 

illicit drug and alcohol use in the adult working population and the prevalence of workplace 

programs designed to reduce drug and alcohol use. In addition, this report provides an 

assessment of the association of these programs with the prevalence of worker substance use. 

In 1994, the Substance Abuse and Mental Health Services Administration (SAMHSA), in 

cooperation with the U.S. Department of Labor and the U.S. Small Business Administration, 

developed and implemented a module in NSDUH designed to gather specific information on 

employment status, type of business, and specific occupations and industries among persons 

aged 15 or older. In addition, this module also was designed to collect worker reports of drugtesting policies and programs. SAMHSA continues to include a workplace module in NSDUH. 

The workplace data collected in this module can be used in conjunction with drug use data 

collected in the survey to investigate drug use among U.S. workers. 

Previous NSDUH reports related to employment status and workplace drug policies have 

focused on workers aged 18 to 49 years old (Hoffmann, Brittingham, & Larison, 1996; 

Hoffmann, Larison, & Sanderson, 1997; Office of Applied Studies [OAS], 1999; Zhang, Huang, 

& Brittingham, 1999). The current report expands the age range to include full-time workers 

aged 18 to 64 years old. In 1994, 44 percent of full-time workers aged 18 to 49 in the United 

States reported a drug- and/or alcohol-testing program in their place of employment. This 

increased to 49 percent by 1997. Although there was an increase in drug testing in the workplace, 

current illicit drug use by full-time workers remained essentially unchanged, with a rate of 7.6 

percent reporting drug use in 1994 and 7.7 percent reporting use in 1997 (Zhang et al., 1999). 

The analysis presented in this report demonstrates that worker substance use is a serious 

problem, with an estimated 9.4 million full-time workers aged 18 to 64 reporting illicit drug use 

in the past month. About 43.8 percent of full-time workers reported access to educational 

information about drug and alcohol use through work, 58.4 percent reported access to an 

employee assistance program (EAP), and 78.7 percent reported access to a written workplace 

policy about drug and alcohol use. In general, past month illicit drug users were less likely to 

work for employers who provided these programs. Finally, testing programs were fairly 

prevalent, with 48.8 percent of full-time workers reporting that their employer conducted testing 

for drug use. Multivariate analysis suggests that illicit drug users are less likely to work for 

employers who have a drug-testing program. 

1.1. Summary of NSDUH 

NSDUH is the primary source of statistical information on the use of illegal drugs by the 

U.S. civilian, noninstitutionalized population aged 12 or older. Conducted by the Federal 

Government since 1971, the survey collects data by administering questionnaires to a 
6 

representative sample of the population through face-to-face interviews at their places of 

residence. The survey, which has been repeated annually since 1990, is sponsored by the 

Substance Abuse and Mental Health Services Administration (SAMHSA) of the U.S. 

Department of Health and Human Services, and is planned and managed by SAMHSA's Office 

of Applied Studies (OAS). Data collection is conducted under contract with RTI International, 

Research Triangle Park, North Carolina.1 This section briefly describes the survey methodology; 

a more complete description is provided in Appendices A and B. 

Prior to 2002, the survey was called the National Household Survey on Drug Abuse 

(NHSDA). Because of improvements to the survey in 2002, the 2002 data constitute a new 

baseline for tracking trends in substance use and other measures. For this reason, findings in this 

report are based on data only from the 2002, 2003, and 2004 NSDUHs. Estimates from these 3 

survey years should not be compared with estimates from the 2001 or earlier versions of the 

survey. A discussion of survey methodology and results from the 2002 NSDUH are presented in 

OAS (2003). A more detailed discussion of the impact of changes in NSDUH methods on the 

survey results can be found in Appendix C in the 2004 national findings report (OAS, 2005). 

NSDUH collects information from residents of households, noninstitutional group 

quarters (e.g., shelters, rooming houses, dormitories), and civilians living on military bases. The 

survey does not include homeless persons who do not use shelters, military personnel on active 

duty, and residents of institutional group quarters, such as jails and hospitals. 

Since 1999, the NSDUH interview has been carried out using computer-assisted 

interviewing (CAI). Most of the questions are administered with audio computer-assisted selfinterviewing (ACASI). ACASI is designed to provide the respondent with a highly private and 

confidential means of responding to questions to increase the level of honest reporting of illicit 

drug use and other sensitive behaviors. Less sensitive items are administered by interviewers 

using computer-assisted personal interviewing (CAPI). Overall, approximately 61 percent of the 

time that respondents spend answering questions is for items administered by ACASI. 

The 2002, 2003, and 2004 NSDUHs employed a 50-State sample design with an 

independent, multistage area probability sample for each of the 50 States and the District of 

Columbia. The eight States with the largest population (California, Florida, Illinois, Michigan, 

New York, Ohio, Pennsylvania, and Texas), which together account for 48 percent of the total 

U.S. population aged 12 or older, were designated as large sample States. For these States, the 

design provided an annual sample sufficient to support direct State estimates. For the remaining 

42 States and the District of Columbia, smaller, but adequate, samples were selected to support 

State estimates using small area estimation (SAE) techniques. The NSDUH design also 

oversampled youths and young adults, so that each State's sample was approximately equally 

distributed among three major age groups: 12 to 17 years, 18 to 25 years, and 26 years or older. 

Each year's survey was conducted from January through December of that calendar year 

(e.g., January through December 2004 for the 2004 NSDUH). Sampled dwelling units were 

screened to identify eligible residents aged 12 or older. Up to two persons per dwelling unit were 

 1

 RTI International is a trade name of Research Triangle Institute. 
7 

selected to be interviewed. In each year, respondents were given an incentive payment of $30 for 

completing the interview. 

The weighted response rate for household screening was 90.8 percent between 2002 and 

2004. The weighted response rate for interviewing among persons aged 18 to 64 was 77.9 

percent. Sample sizes for persons aged 18 to 64 were 42,215 in 2002, 42,708 in 2003, and 43,053 

in 2004, for a total of 127,976 completed interviews in this age group across the 3 years. 

A number of key measures of substance use and dependence or abuse are reported from 

the NSDUH data. A complete listing and explanation of the key definitions used in NSDUH can 

be found in Appendix C. Occupational and industry classifications are provided in Appendix D. 

NSDUH defines "full-time" as respondents who usually work 35 or more hours per week and 

who worked in the past week or had a job despite not working in the past week. Illicit drugs 

include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or 

prescription-type psychotherapeutics used nonmedically. "Heavy" alcohol use is defined as 

drinking five or more drinks on the same occasion on 5 or more days in the past 30 days. 

Analyses focus primarily on past month use, which also is referred to as "current use." NSDUH 

includes a series of questions to assess the prevalence of substance use disorders (i.e., 

dependence on or abuse of a substance) in the past year. These questions are used to classify 

persons as dependent or abusing specific substances based on criteria specified in the Diagnostic 

and Statistical Manual of Mental Disorders, 4th edition (DSM-IV; American Psychiatric 

Association [APA], 1994). The questions on dependence ask about health and emotional 

problems associated with substance use, unsuccessful attempts to cut down on use, tolerance, 

withdrawal, reducing other activities to use substances, spending a lot of time engaging in 

activities related to substance use, or using the substance in greater quantities or for a longer time 

than intended. The questions on abuse ask about problems at work, home, and school; problems 

with family or friends; physical danger; and trouble with the law due to substance use. 

Dependence is considered to be a more severe substance use problem than abuse. Although 

individuals may meet the criteria specified for both dependence and abuse, persons are classified 

with abuse of a particular substance only if they are not classified as dependent on that 

substance. Measures of dependence on or abuse of alcohol and dependence on or abuse of illicit 

drugs are used in this report. 

1.2. Format of Report and Explanation of Tables 

Tables, text, and figures present prevalence measures for the population in terms of both 

the number of persons and the percentage of the population. Estimates presented in this report 

are based on averages for the 2002, 2003, and 2004 surveys. Combining data from these 3 survey 

years increases the sample size to support estimates among more detailed demographic and 

geographic domains, including the various occupational and industry characteristics described in 

this report. 

Statistical tests have been conducted for all statements appearing in the text of the report 

that compare estimates between subgroups of the population. Unless explicitly stated that a 

difference is not statistically significant, all statements that describe differences are significant at 

the .05 level. Statistically significant differences are described using terms such as "higher" or 

"lower." Statements that use terms such as "similar," "no difference," or "same" to describe the 
8 

relationship between estimates denote that a difference is not statistically significant. In addition, 

a set of estimates for population subgroups may be presented without a statement of comparison, 

in which case a statistically significant difference between these estimates is not implied and 

testing was not conducted. 

All estimates presented in this report have met the criteria for statistical reliability (see 

Section B.2.2 of Appendix B). Estimates that do not meet these criteria are suppressed and do 

not appear in tables, figures, or text. Also, subgroups with suppressed estimates are not included 

in statistical tests of comparisons. For example, a statement that "whites had the highest 

prevalence" means that the rate among whites was higher than the rate among all racial/ethnic 

subgroups for which estimates were reliable, but not necessarily higher than the rate among a 

subgroup for which the estimate was suppressed. 

Data are presented for racial/ethnic groups, based on current standards for collecting and 

reporting race and ethnicity data (Office of Management and Budget [OMB], 1997). Because 

respondents were allowed to choose more than one racial group, a "two or more races" category 

is presented that includes persons who reported more than one category among the seven basic 

groups listed in the survey question (white, black or African American, American Indian or 

Alaska Native, Native Hawaiian, Other Pacific Islander, Asian, Other). It should be noted that, 

except for the "Hispanic or Latino" group, the racial/ethnic groups discussed in this report 

include only non-Hispanics. The category "Hispanic or Latino" includes Hispanics of any race. 

Also, more detailed categories describing specific subgroups were obtained from survey 

respondents if they reported either Asian race or Hispanic ethnicity. Data on Native Hawaiians 

and Other Pacific Islanders are combined in this report. 

Data also are presented for four U.S. geographic regions. These regions and divisions 

within these regions, defined by the U.S. Census Bureau, consist of the following groups of 

States: 

Northeast Region - New England Division: Connecticut, Maine, Massachusetts, 

New Hampshire, Rhode Island, Vermont; Middle Atlantic Division: New Jersey, 

New York, Pennsylvania. 

Midwest Region - East North Central Division: Illinois, Indiana, Michigan, Ohio, 

Wisconsin; West North Central Division: Iowa, Kansas, Minnesota, Missouri, 

Nebraska, North Dakota, South Dakota. 

South Region - South Atlantic Division: Delaware, District of Columbia, Florida, 

Georgia, Maryland, North Carolina, South Carolina, Virginia, West Virginia; East 

South Central Division: Alabama, Kentucky, Mississippi, Tennessee; West South 

Central Division: Arkansas, Louisiana, Oklahoma, Texas. 

West Region - Mountain Division: Arizona, Colorado, Idaho, Montana, Nevada, 

New Mexico, Utah, Wyoming; Pacific Division: Alaska, California, Hawaii, 

Oregon, Washington. 

Geographic comparisons also are made based on urban influence county type, which 

reflects different levels of population size, urbanization, and access to larger communities based 
9 

on county-level Urban Influence Codes (UIC) created by the Economic Research Service (ERS) 

of the U.S. Department of Agriculture. The codes group metropolitan and nonmetropolitan 

counties according to the official county-level metro status issued by the OMB in June 2003 

(OMB, 2003). Each county is either inside or outside a metropolitan statistical area (MSA), as 

defined by the OMB. The definitions of urban influence county type are different than countytype definitions used in other NSDUH reports. The definitions for this report are based on UIC, 

whereas the 2004 national findings (OAS, 2005) definitions are based on Rural-Urban 

Continuum Codes (RUCC). 

Large MSAs have a population of 1 million or more. Small MSAs have a population of 

fewer than 1 million. Nonmetropolitan areas are areas outside MSAs that have been categorized 

into four groups based on UIC. The first group consists of micropolitan statistical areas (MiSAs), 

which include a county with an urban cluster of at least 10,000 persons or more and any 

additional counties where commuting to the central county is 25 percent or higher, or where 25 

percent of the employment in an outlying county is made up of commuters from the central 

county. The remaining three groups of nonmetropolitan areas consist of noncore counties and are 

divided based on their adjacency to larger areas and whether or not they have their "own town" 

of at least 2,500 residents. The "noncore adjacent with town" group includes those areas that are 

adjacent to a large MSA, adjacent to a small MSA and have their own town, or adjacent to a 

MiSA and have their own town. Noncore areas that have no town of their own but are adjacent to 

a small MSA or MiSA compose the "noncore adjacent, no town" group. The "noncore rural, not 

adjacent" group consists of counties that are not adjacent to any MSA or MiSA and have no town 

of their own. 

1.3. Content and Organization of This Report 

Subsequent chapters contain detailed information about several issues related to worker 

substance use and workplace drug and alcohol policies and programs. Chapter 2 provides 

estimates of substance use among full-time workers in the United States by demographic and 

geographic characteristics, including age, gender, race/ethnicity, education, family income, and 

place of residence. This provides some insight about the magnitude of worker substance use 

across different settings and population subgroups. Chapter 3 examines the characteristics of 

employers by providing estimates of the prevalence of substance use behaviors and substance 

use disorders by occupation, industry, and establishment size. Chapter 4 explores worker reports 

of drug information programs and policies in their employment settings. Chapter 5 provides 

detailed estimates about the prevalence of drug testing in the workplace. Chapter 6 discusses 

workplace behaviors and attitudes toward drug testing. In addition to the selected data tables 

included in these chapters and in Appendix E of this report, supplemental tables of estimates and 

their associated standard errors are available on the Internet at 

http://www.oas.samhsa.gov/work.htm. Standard error tables are presented for the tables in 

Appendix E as well as for the supplemental Web tables. The supplemental tables of estimates, 

which are denoted by "S" after the table number, are numbered to correspond to chapters and to 

consecutively follow Appendix E tables (e.g., Table 2.6S follows Table 2.5 in Appendix E and 

contains data related to analyses presented in Chapter 2). The standard error tables, which are 

denoted by "SE" after the table number, are numbered to correspond to the tables in Appendix E 

and to the supplemental Web tables (e.g., Table 2.1SE is the standard error table for Table 2.1 in 

Appendix E). Appendix F contains the reference list for this report. 
10 
11 

2. Substance Use among Workers, by 

Demographic and Geographic 

Characteristics 

This chapter summarizes the substance use patterns of the population of full-time workers 

aged 18 to 64 in the United States between 2002 and 2004. The chapter also examines the 

differences in substance use for different demographic and geographic groups within that 

population. (See Tables 2.1 through 2.5 in Appendix E.) Demographic and geographic 

characteristics examined include age, gender, race/ethnicity, education, family income, and place 

of residence. Understanding which subpopulations in the workforce have the greatest prevalence 

of substance use behaviors and substance use disorders may allow policy makers to target 

workplace programs to specific settings and subpopulations. 

The prevalences of substance use behaviors and substance use disorders are higher 

among unemployed persons than other employment statuses (Figure 2.1). However, because fulltime workers constitute about two thirds of the population aged 18 to 64 (or 114.7 million 

persons), most substance users and most of those with substance use disorders are employed full 

time (Figure 2.2). Specifically, among those aged 18 to 64, 57.5 percent of past month illicit drug 

users, 58.0 percent of past month marijuana users, 67.3 percent of heavy alcohol users, 52.8 

percent of those with dependence on or abuse of illicit drugs, and 65.1 percent of those with 

alcohol dependence or abuse were employed full time from 2002 to 2004 (Table 2.1). 

Figure 2.1 Past Month Substance Use and Past Year Substance Dependence or Abuse 

among Persons Aged 18 to 64, by Employment Status: 2002-2004 Combined 

9.2

7.0

8.4

3.2

9.1

8.2

6.4

8.8

2.6

9.2

11.9

9.6

8.6

4.1

10.0

18.6

13.9 13.6

8.0

15.6

8.3

5.9 5.6

3.5

6.5

0

5

10

15

20

Total

Full-Time

Part-Time

Unemployed

Other

Past Month 

Illicit Drug 

Use

Past Month 

Heavy 

Alcohol Use

Past Month 

Marijuana 

Use

Past Year Illicit 

Drug Dependence 

or Abuse

Past Year 

Alcohol 

Dependence or 

Abuse

Percent

9.2

7.0

8.4

3.2

9.1

8.2

6.4

8.8

2.6

9.2

11.9

9.6

8.6

4.1

10.0

18.6

13.9 13.6

8.0

15.6

8.3

5.9 5.6

3.5

6.5

0

5

10

15

20

Total

Full-Time

Part-Time

Unemployed

Other

Past Month 

Illicit Drug 

Use

Past Month 

Heavy 

Alcohol Use

Past Month 

Marijuana 

Use

Past Year Illicit 

Drug Dependence 

or Abuse

Past Year 

Alcohol 

Dependence or 

Abuse

Percent
12 

Figure 2.2 Percentage Distribution of Persons Aged 18 to 64, by Employment Status: 

2002-2004 Combined 

2.1. Illicit Drug Use among Full-Time Workers 

! The prevalence of past month illicit drug use among adult full-time workers was 8.2 

percent (Figure 2.3 and Tables 2.2 and 2.3). 

! Nearly one out of five (19.0 percent) workers aged 18 to 25 used illicit drugs during the 

past month. This was a higher percentage than among the 26-to-34 (10.3 percent), 35-to-49 

(7.0 percent), and 50-to-64 (2.6 percent) age groups (Figure 2.3 and Table 2.2). 

! Males were more likely than females to report past month illicit drug use (9.7 vs. 6.2 

percent). Males accounted for about two thirds (6.4 million) of the workers who reported 

past month illicit drug use (Figure 2.4 and Table 2.2). 

! The prevalence of past month illicit drug use for white adults was 8.8 percent, higher than 

the prevalence for Asian (2.2 percent) or Hispanic (6.7 percent) adults, and lower than that 

reported for adults who reported two or more races (13.5 percent). The prevalence of past 

month illicit drug use by Asians was lower than that reported by all other racial/ethnic 

groups reported here (Figure 2.5 and Table 2.2). 

! Workers with a college education had a lower prevalence of current illicit drug use 

compared with those without a college education. The prevalence of past month use of 

illicit drugs was lower among those with higher levels of education than those with less 

education (college graduate [5.7 percent] vs. less than high school [11.2 percent]) (Figure 

2.6 and Table 2.3). 

Other

Full-Time Unemployed

Part-Time

64.3%

13.6%

4.2%

17.9%

Other

Full-Time Unemployed

Part-Time

64.3%

13.6%

4.2%

17.9%
13 

Figure 2.3 Past Month Substance Use and Past Year Substance Dependence or Abuse 

among Full-Time Workers, by Age Group: 2002-2004 Combined 

Figure 2.4 Past Month Substance Use and Past Year Substance Dependence or Abuse 

among Full-Time Workers Aged 18 to 64, by Gender: 2002-2004 Combined 

8.2

8.8

2.6

9.2

19.0

16.3

7.5

18.4

10.3 10.4

3.3

12.3

7.0

8.1

1.9

7.8

2.6

4.7

0.7

4.0

0

2

4

6

8

10

12

14

16

18

20

Total

18-25

26-34

35-49

50-64

Past Month Illicit 

Drug Use

Past Month Heavy 

Alcohol Use

Past Year Alcohol 

Dependence or Abuse

Past Year Illicit Drug 

Dependence or Abuse

Percent

8.2

8.8

2.6

9.2

19.0

16.3

7.5

18.4

10.3 10.4

3.3

12.3

7.0

8.1

1.9

7.8

2.6

4.7

0.7

4.0

0

2

4

6

8

10

12

14

16

18

20

Total

18-25

26-34

35-49

50-64

Past Month Illicit 

Drug Use

Past Month Heavy 

Alcohol Use

Past Year Alcohol 

Dependence or Abuse

Past Year Illicit Drug 

Dependence or Abuse

Percent

9.7

12.3

3.3

11.8

6.2

4.1

1.8

5.7

0

2

4

6

8

10

12

14

Male

Female

Past Month Illicit 

Drug Use

Past Month Heavy 

Alcohol Use

Past Year Alcohol 

Dependence or Abuse

Past Year Illicit Drug 

Dependence or Abuse

Percent

9.7

12.3

3.3

11.8

6.2

4.1

1.8

5.7

0

2

4

6

8

10

12

14

Male

Female

Past Month Illicit 

Drug Use

Past Month Heavy 

Alcohol Use

Past Year Alcohol 

Dependence or Abuse

Past Year Illicit Drug 

Dependence or Abuse

Percent
14 

Figure 2.5 Past Month Substance Use among Full-Time Workers Aged 18 to 64, by 

Hispanic or Latino Origin and Race: 2002-2004 Combined 

Figure 2.6 Past Month Substance Use and Past Year Substance Dependence or Abuse 

among Full-Time Workers Aged 18 to 64, by Education: 2002-2004 Combined 

8.8

10.1

8.0

5.4

7.3

8.7

13.0

9.4

2.2

2.9

13.5

7.5

6.7 6.9

0

2

4

6

8

10

12

14

White

Black or African American

American Indian or Alaska Native

Native Hawaiian or Other Pacific Islander

Asian

Two or More Races

Hispanic or Latino

Past Month Illicit Drug Use Past Month Heavy Alcohol Use

Percent

8.8

10.1

8.0

5.4

7.3

8.7

13.0

9.4

2.2

2.9

13.5

7.5

6.7 6.9

0

2

4

6

8

10

12

14

White

Black or African American

American Indian or Alaska Native

Native Hawaiian or Other Pacific Islander

Asian

Two or More Races

Hispanic or Latino

Past Month Illicit Drug Use Past Month Heavy Alcohol Use

Percent

11.2

10.8

5.1

11.9

9.0

10.0

2.9

9.4

8.7 8.9

2.9

9.7

5.7

6.7

1.2

7.5

0

2

4

6

8

10

12

Less Than High School

High School Graduate

Some College

College Graduate

Past Month Illicit 

Drug Use

Past Month Heavy 

Alcohol Use

Past Year Alcohol 

Dependence or Abuse

Past Year Illicit Drug 

Dependence or Abuse

Percent

11.2

10.8

5.1

11.9

9.0

10.0

2.9

9.4

8.7 8.9

2.9

9.7

5.7

6.7

1.2

7.5

0

2

4

6

8

10

12

Less Than High School

High School Graduate

Some College

College Graduate

Past Month Illicit 

Drug Use

Past Month Heavy 

Alcohol Use

Past Year Alcohol 

Dependence or Abuse

Past Year Illicit Drug 

Dependence or Abuse

Percent
15 

! The prevalence of current illicit drug use was lower among workers with higher family 

incomes than among workers with lower family incomes. An estimated 13.2 percent of 

workers who reported family income that was less than $20,000 had used illicit drugs 

during the past month. In contrast, 6.0 percent of workers who reported income in the 

highest category––$75,000 or more––had used illicit drugs during the past month (Figure 

2.7 and Table 2.3). 

! Residents of noncore counties had a lower prevalence of current illicit drug use (4.5 to 6.2 

percent) compared with residents of micropolitan statistical area (7.1 percent), small 

metropolitan statistical area (MSA; 8.8 percent), and large MSA (8.3 percent) counties 

(Table 2.3). 

Figure 2.7 Past Month Substance Use and Past Year Substance Dependence or Abuse 

among Full-Time Workers Aged 18 to 64, by Family Income: 2002-2004 

Combined 

2.2. Past Month Marijuana Use among Full-Time Workers 

! An estimated 6.4 percent, or 7.3 million, of full-time workers reported use of marijuana 

during the past month (Tables 2.2 and 2.3). 

! Adults aged 26 to 34 were only about half as likely as 18- to 25-year-olds to be past month 

marijuana users (8.0 vs. 15.9 percent). Past month use of marijuana was lower with 

increasing age (Table 2.2). 

13.2

9.8

5.6

13.3

9.1

9.7

3.0

9.8

7.5

9.1

2.0

8.7

6.0

7.3

1.7

7.6

0

2

4

6

8

10

12

14

Less Than $20,000

$20,000-49,999

$50,000-74,999

$75,000 or More

Past Month Illicit 

Drug Use

Past Month Heavy 

Alcohol Use

Past Year Alcohol 

Dependence or Abuse

Past Year Illicit Drug 

Dependence or Abuse

Percent 

13.2

9.8

5.6

13.3

9.1

9.7

3.0

9.8

7.5

9.1

2.0

8.7

6.0

7.3

1.7

7.6

0

2

4

6

8

10

12

14

Less Than $20,000

$20,000-49,999

$50,000-74,999

$75,000 or More

Past Month Illicit 

Drug Use

Past Month Heavy 

Alcohol Use

Past Year Alcohol 

Dependence or Abuse

Past Year Illicit Drug 

Dependence or Abuse

Percent 
16 

! The prevalence of past month marijuana use was higher for males than females (7.9 vs. 4.3 

percent, respectively) (Table 2.2). 

! An estimated 11.0 percent of workers reporting two or more races used marijuana during 

the past month. This was higher than among non-Hispanic white adults (6.9 percent). 

Fewer Hispanic adults (4.6 percent) reported past month marijuana use than non-Hispanic 

white adults who reported two or more races (Table 2.2). 

! Higher educational attainment and higher family income were associated with a lower 

prevalence of current marijuana use (Table 2.3). 

2.3. Past Month Heavy Alcohol Use among Full-Time Workers

! An estimated 8.8 percent, or 10.1 million, of full-time workers reported past month heavy 

alcohol use (Figure 2.3 and Tables 2.2 and 2.3). 

! Past month heavy alcohol use was related to age. Among younger workers (18 to 25 years 

old), 16.3 percent reported past month heavy alcohol use compared with 10.4 percent of 

26- to 34-year-olds, 8.1 percent of 35- to 49-year-olds, and 4.7 percent of 50- to 64-yearolds (Figure 2.3 and Table 2.2). 

! Males were three times as likely as females to be past month heavy alcohol users (12.3 vs. 

4.1 percent) (Figure 2.4 and Table 2.2). 

! An estimated 10.1 percent of white adults reported heavy alcohol use in the past month. 

This was higher than the percentage among black adults (5.4 percent), Asian adults (2.9 

percent), Hispanic adults (6.9 percent), and adults reporting two or more races (7.5 percent) 

(Figure 2.5 and Table 2.2). 

! Residents of noncore rural counties had a lower prevalence of past month heavy alcohol 

use (7.5 percent) compared with residents of micropolitan statistical area (9.2 percent), 

small MSA (9.8 percent), and large MSA (8.1 percent) counties (Table 2.3). 

! Workers with a college education had a lower prevalence of past month heavy alcohol use 

compared with those without a college education. Past month heavy alcohol use was lower 

among those with higher levels of education than those with less education (college 

graduate [6.7 percent] vs. less than high school [10.8 percent]) (Figure 2.6 and Table 2.3). 

! Workers in the Midwest had the highest prevalence of past year heavy alcohol use (10.6 vs. 

8.4 percent in the Northeast, 8.5 percent in the South, and 7.8 percent in the West) (Table 

2.3). 
17 

2.4. Past Year Illicit Drug Dependence or Abuse among Full-Time Workers 

! Approximately 3 million full-time workers (2.6 percent) aged 18 to 64 met the criteria for 

past year illicit drug dependence or abuse (Figure 2.3 and Table 2.4). 

! Approximately 7.5 percent of 18- to 25-year-old workers had past year illicit drug 

dependence or abuse. This was higher than among all other age groups studied (26- to 34-

year-olds [3.3 percent], 35- to 49-year-olds [1.9 percent], and 50- to 64-year-olds [0.7 

percent]) (Figure 2.3 and Table 2.4). 

! Males were nearly twice as likely as females to meet the criteria for past year illicit drug 

dependence or abuse (3.3 vs. 1.8 percent) (Figure 2.4 and Table 2.4). 

! Hispanics (3.2 percent) had a higher prevalence of past year illicit drug dependence or 

abuse than non-Hispanics (2.6 percent) (Figure 2.8 and Table 2.4). 

! Within non-Hispanic subgroups, Asians had the lowest prevalence of past year illicit drug 

dependence or abuse (1.1 percent). This was lower than non-Hispanic white adults (2.5 

percent), black (2.9 percent) adults, American Indian or Alaska Native (4.5 percent) adults, 

and adults reporting two or more races (4.3 percent) (Figure 2.8 and Table 2.4). 

Figure 2.8 Past Year Substance Dependence or Abuse among Full-Time Workers Aged 18 

to 64, by Hispanic or Latino Origin and Race: 2002-2004 Combined 

2.5

9.6

2.9

7.3

4.5

10.7

4.3

9.4

1.1

4.6

4.3

10.1

3.2

10.0

0

2

4

6

8

10

12 White

Black or African American

American Indian or Alaska Native

Native Hawaiian or Other Pacific Islander

Asian

Two or More Races

Hispanic or Latino

Past Year Illicit Drug Dependence or Abuse Past Year Alcohol Dependence or Abuse

Percent

2.5

9.6

2.9

7.3

4.5

10.7

4.3

9.4

1.1

4.6

4.3

10.1

3.2

10.0

0

2

4

6

8

10

12 White

Black or African American

American Indian or Alaska Native

Native Hawaiian or Other Pacific Islander

Asian

Two or More Races

Hispanic or Latino

Past Year Illicit Drug Dependence or Abuse Past Year Alcohol Dependence or Abuse

Percent
18 

! Educational attainment was linked to past year illicit drug dependence or abuse. An 

estimated 1.2 percent of college graduates met the criteria for dependence or abuse 

compared with 5.1 percent of those with less than high school education, 2.9 percent of 

high school graduates, and 2.9 percent of workers with some college (Figure 2.6 and Table 

2.5). 

! Among higher income groups ($75,000 or more and $50,000-74,999), 1.7 and 2.0 percent 

had past year illicit drug dependence or abuse, respectively. These two groups had a lower 

prevalence than among lower income groups (3.0 to 5.6 percent) (Figure 2.7 and Table 

2.5). 

2.5. Past Year Alcohol Dependence or Abuse among Full-Time Workers 

! Approximately 10.6 million full-time workers aged 18 to 64 (9.2 percent) met the criteria 

for past year alcohol dependence or abuse (Figure 2.3 and Tables 2.4 and 2.5). 

! The prevalence of past year alcohol dependence was highest among those aged 18 to 25 

(18.4 percent) compared with those aged 26 to 34 (12.3 percent), 35 to 49 (7.8 percent), 

and 50 to 64 (4.0 percent) (Figure 2.3 and Table 2.4). 

! Males were about twice as likely as females to have past year alcohol dependence or abuse 

(11.8 vs. 5.7 percent) (Figure 2.4 and Table 2.4). 

! The prevalence of past year alcohol dependence or abuse was lower among non-Hispanic 

Asian and non-Hispanic black adults than among other non-Hispanic groups (4.6 and 7.3 

percent, respectively). Hispanic and non-Hispanic adults did not differ in the prevalence of 

alcohol disorders (10.0 vs. 9.1 percent) (Figure 2.8 and Table 2.4). 

! An estimated 11.9 percent of those with less than a high school diploma reported past year 

alcohol dependence or abuse compared with 9.4 percent of high school graduates, 9.7 

percent of those with some college, and 7.5 percent of those who graduated from college 

(Figure 2.6 and Table 2.5). 

! Workers in the Midwest had the highest prevalence of past year alcohol dependence or 

abuse (10.5 vs. 8.3 percent in the Northeast, 8.5 percent in the South, and 9.9 percent in the 

West) (Table 2.5). 

! The prevalence of alcohol dependence or abuse was higher among workers with family 

incomes that were less than $20,000 (13.3 percent) compared with workers with family 

incomes that were higher than $75,000 (7.6 percent) (Figure 2.7 and Table 2.5). 
19 

2.6. Summary 

The results presented in this chapter demonstrate a consistent relationship between 

several demographic and geographic characteristics and substance use and dependence or abuse. 

Age was consistently associated with substance use behaviors and substance use disorders. 

Young adults aged 18 to 25 were more likely than other age groups to report past month illicit 

drug or heavy alcohol use or to meet the criteria for substance dependence or abuse during the 

past year. Adult males who worked full time had a higher prevalence on all substance use and 

dependence or abuse measures compared with females who worked full time. Lower educational 

attainment and lower family income also were consistently associated with a higher prevalence 

of substance use behaviors and substance use disorders. There were some race/ethnicity-related 

differences, and Asians generally had a lower prevalence of use and dependence on or abuse of 

illicit drugs and alcohol. Findings were less consistent across measures of substance use 

behaviors and substance use disorders for county type. Past month illicit drug use was highest in 

the Northeast, while past year alcohol dependence or abuse was highest in the Midwest. 
20 
21 

3. Substance Use among Workers, by 

Occupation, Industry, and Establishment 

Size 

This chapter reports the prevalence of substance use among full-time workers within 

occupations, industries, and across different sizes of workplace establishments. Prevalence is 

reported for measures of past month illicit drug use, past month heavy alcohol use, past month 

marijuana use, and past year dependence on or abuse of illicit drugs or alcohol. Major 

occupational groups are identified using the standard occupational classifications (SOCs) of the 

U.S. Department of Labor (see Appendices C and D) and selected broader and more detailed 

occupational groups. Industry groupings are identified using the North American Industry 

Classification System (NAICS) developed by the U.S. Census Bureau. Data are presented for 

NAICS sectors and selected subsectors and industry groups. The chapter also examines the 

relationship between demographic correlates of substance use within industry and occupational 

categories in order to assess if the observed rates of substance use are a function of the 

characteristics of the workers in those categories. Finally, this chapter examines the relationship 

between substance use among workers and establishment size, which ranges from small (fewer 

than 10 employees) to large (500 or more employees). 

Previous research has demonstrated that substance use and dependence or abuse may 

vary by workplace environment. In 1996, the Substance Abuse and Mental Health Services 

Administration (SAMHSA) released a report detailing the prevalence of illicit drug use among 

workers in specific occupation and industry categories (Hoffmann, Brittingham, & Larison, 

1996). Occupations involved in construction and food preparation were found to have the highest 

prevalence of illicit drug use and heavy alcohol use. Illicit drug use was lowest among public 

safety occupations, including police, teachers, child care workers, and data clerks. Heavy alcohol 

use was lowest among data clerks, personnel specialists, and secretaries. Industries associated 

with the highest prevalence of illicit drug use included eating and drinking establishments, 

certain retail sales categories, and the entertainment industry. The computer and data processing 

industry had the highest rates of heavy alcohol use. The lowest rates of illicit drug use were 

found among workers in child care, professional medical offices, and schools. 

The 1996 SAMHSA report also demonstrated that the relationship between substance 

use, age, gender, and marital status within industries and occupations was consistent with the 

pattern for all full-time workers. This suggests that substance use patterns across industries and 

occupations may partly be a function of the demographic characteristics of the workers. That is, 

demographic groups with relatively higher prevalence of substance use may be more likely to be 

employed in certain industries or occupations for reasons unrelated to substance use. For 

example, young workers tend to work in food preparation occupations because these positions 

require less experience, education, and training than other occupations. To account for these 

variations in the demographic makeup of different occupation and industry categories, it is useful 

to consider the data shown in Tables 3.1 and 3.2 in Appendix E when comparing substance use 
22 

rates across occupation and industry groups. Tables 3.1 and 3.2 show the average age and 

percentage of male workers in each group. 

Substance use, dependence, or abuse also may vary by the size of the work establishment. 

Establishment size becomes an important factor if either substance use or the prevalence of 

reduction programs is disproportionately distributed to large or small employment settings. 

Previous findings suggest that workplace drug testing is less likely to occur in small workplace 

settings (Zhang, Huang, & Brittingham, 1999; Hartwell, Steele, French, & Rodman, 1996; 

Hartwell, Steele, & Rodman, 1998). 

3.1. Standard Occupational and Industry Classifications 

The occupations are coded into groups using the 2000 Standard Occupational 

Classification (SOC) released by the U.S. Department of Labor, Bureau of Labor Statistics 

(2000), which categorizes all occupations into 21 major groups. Within these major groups are 

96 minor groups, 449 broad occupations, and 821 detailed occupations. Occupations with similar 

skills or work activities are grouped at each of the four levels of hierarchy to facilitate 

comparisons. The NAICS, which replaced the Standard Industry Classification (SIC), 

categorizes all industries into 19 major groups and is used to classify industries in this report. 

Industries are organized within the NAICS by the processes used to produce goods or services. 

This report focuses on these major groups, but a more detailed analysis of industry and 

occupational classifications can be found in Appendix D. Tables 3.1 and 3.2 show the population 

totals for industry and occupation categories. 

3.2. Illicit Drug Use among Full-Time Workers, by Occupation 

It is notable, particularly in light of demographic characteristics presented earlier in this 

report, that among the five occupations with the highest prevalence of current illicit drug use, 

three were overwhelmingly dominated by male workers. An estimated 97.4 percent of 

construction workers were male, while 96.2 percent of installation maintenance and repair and 

87.2 percent of transportation and material-moving occupations were male. Moreover, the fulltime workers in this "top five" list were among the youngest workers in the population (Table 

3.1). 

Figure 3.1 lists the 21 major occupational groups ordered highest to lowest in percentage 

of full-time workers within the occupation who reported past month use of illicit drugs. 

! Looking at the major occupational groups for 2002 through 2004, food service workers 

(17.4 percent) and construction workers (15.1 percent) exhibited a higher prevalence of 

past month illicit drug use than other occupational groups (Figure 3.1 and Table 3.3). 

! Those working in education, training, and library occupations (4.1 percent), community 

and social services occupations (4.0 percent), and protective service occupations (3.4 

percent) had the lowest prevalence of past month illicit drug use among the major 

occupational groups (Figure 3.1 and Table 3.3). 
23 

Figure 3.1 Past Month Illicit Drug Use among Full-Time Workers Aged 18 to 64, by 

Major Occupational Categories: 2002-2004 Combined 

3.3. Heavy Alcohol Use among Full-Time Workers, by Occupation 

! The major occupational groups with the highest prevalence of past month heavy alcohol 

use were construction and extraction occupations (17.8 percent) and installation, 

maintenance, and repair occupations (14.7 percent) (Figure 3.2 and Table 3.3). 

! Community and social services occupations (2.8 percent) had the lowest prevalence of past 

month heavy alcohol use of the major occupations (Figure 3.2 and Table 3.3). 

3.4. Dependence and Abuse among Full-Time Workers, by Occupation 

! The major occupational groups with the highest prevalence of illicit drug dependence or 

abuse in the past year were food preparation and serving related occupations (6.5 percent) 

and construction and extraction occupations (6.2 percent) (Table 3.4). 

! Construction and extraction occupations (16.9 percent) and food preparation and serving 

related occupations (14.7 percent) had the highest prevalence of alcohol dependence or 

abuse in the past year in the major occupational groups (Table 3.4). 

Percent Using Illicit Drugs in Past Month

Food Preparation and Serving Related

Construction and Extraction

Arts, Design, Entertainment, Sports, and Media

Sales and Related Occupations

Installation, Maintenance, and Repair

Farming, Fishing, and Forestry

Transportation and Material-Moving

Building and Grounds Cleaning and Maintenance

Personal Care and Service

Office and Administrative Support

Production Occupations

Life, Physical, and Social Science

Engineering, Architecture, and Surveyors

Mathematical and Computer Scientists

Management

Healthcare Practitioners and Technical Occupations

Financial Occupations

Legal Occupations

Education, Training, and Library

Community and Social Services

Protective Service

Major Occupational Categories 

3.4

4.0

4.1

4.8

4.9

6.1

6.1

6.9

6.9

7.0

7.4

7.5

7.7

8.2

8.4

8.7

9.5

9.6

12.4

15.1

17.4

0 5 10 15 20

Percent Using Illicit Drugs in Past Month

Food Preparation and Serving Related

Construction and Extraction

Arts, Design, Entertainment, Sports, and Media

Sales and Related Occupations

Installation, Maintenance, and Repair

Farming, Fishing, and Forestry

Transportation and Material-Moving

Building and Grounds Cleaning and Maintenance

Personal Care and Service

Office and Administrative Support

Production Occupations

Life, Physical, and Social Science

Engineering, Architecture, and Surveyors

Mathematical and Computer Scientists

Management

Healthcare Practitioners and Technical Occupations

Financial Occupations

Legal Occupations

Education, Training, and Library

Community and Social Services

Protective Service

Food Preparation and Serving Related

Construction and Extraction

Arts, Design, Entertainment, Sports, and Media

Sales and Related Occupations

Installation, Maintenance, and Repair

Farming, Fishing, and Forestry

Transportation and Material-Moving

Building and Grounds Cleaning and Maintenance

Personal Care and Service

Office and Administrative Support

Production Occupations

Life, Physical, and Social Science

Engineering, Architecture, and Surveyors

Mathematical and Computer Scientists

Management

Healthcare Practitioners and Technical Occupations

Financial Occupations

Legal Occupations

Education, Training, and Library

Community and Social Services

Protective Service

Major Occupational Categories 

3.4

4.0

4.1

4.8

4.9

6.1

6.1

6.9

6.9

7.0

7.4

7.5

7.7

8.2

8.4

8.7

9.5

9.6

12.4

15.1

17.4

0 5 10 15 20
24 

Figure 3.2 Past Month Heavy Alcohol Use among Full-Time Workers Aged 18 to 64, by 

Major Occupational Categories: 2002-2004 Combined 

3.5. Illicit Drug Use among Full-Time Workers, by Industry 

! The major industry groups with the highest prevalence of past month illicit drug use were 

accommodations and food services (16.9 percent) and construction (13.7 percent). Public 

administration (4.1 percent), educational services (4.0 percent), and utilities (3.8 percent) 

had the lowest prevalence of past month illicit drug use (Figure 3.3 and Table 3.5). 

3.6. Heavy Alcohol Use among Full-Time Workers, by Industry 

! The industry groups with the highest prevalence of past month heavy alcohol use were 

construction (15.9 percent); arts, entertainment, and recreation (13.6 percent); and mining 

(13.3 percent) industries. However, health care and social assistance (4.3 percent) and 

educational services (4.0 percent) had the lowest prevalence of past month heavy alcohol 

use compared with other major industries (Figure 3.4 and Table 3.5). 

Percent Heavy Alcohol Use in Past Month

Food Preparation and Serving Related

Construction and Extraction

Arts, Design, Entertainment, Sports, and Media

Sales and Related Occupations

Installation, Maintenance, and Repair

Farming, Fishing, and Forestry

Transportation and Material-Moving

Building and Grounds Cleaning and Maintenance

Personal Care and Service

Office and Administrative Support

Production Occupations

Life, Physical, and Social Science

Engineering, Architecture, and Surveyors

Mathematical and Computer Scientists

Management

Healthcare Practitioners and Technical Occupations

Financial Occupations

Legal Occupations

Education, Training, and Library

Community and Social Services

Protective Service

Major Occupational Categories

2.8

3.7

3.9

5.3

5.4

5.9

5.9

6.2

6.9

7.5

7.9

8.3

8.7

9.5

9.5

9.7

10.2

11.2

12.1

14.7

17.8

0 5 10 15 20

Percent Heavy Alcohol Use in Past Month

Food Preparation and Serving Related

Construction and Extraction

Arts, Design, Entertainment, Sports, and Media

Sales and Related Occupations

Installation, Maintenance, and Repair

Farming, Fishing, and Forestry

Transportation and Material-Moving

Building and Grounds Cleaning and Maintenance

Personal Care and Service

Office and Administrative Support

Production Occupations

Life, Physical, and Social Science

Engineering, Architecture, and Surveyors

Mathematical and Computer Scientists

Management

Healthcare Practitioners and Technical Occupations

Financial Occupations

Legal Occupations

Education, Training, and Library

Community and Social Services

Protective Service

Food Preparation and Serving Related

Construction and Extraction

Arts, Design, Entertainment, Sports, and Media

Sales and Related Occupations

Installation, Maintenance, and Repair

Farming, Fishing, and Forestry

Transportation and Material-Moving

Building and Grounds Cleaning and Maintenance

Personal Care and Service

Office and Administrative Support

Production Occupations

Life, Physical, and Social Science

Engineering, Architecture, and Surveyors

Mathematical and Computer Scientists

Management

Healthcare Practitioners and Technical Occupations

Financial Occupations

Legal Occupations

Education, Training, and Library

Community and Social Services

Protective Service

Major Occupational Categories

2.8

3.7

3.9

5.3

5.4

5.9

5.9

6.2

6.9

7.5

7.9

8.3

8.7

9.5

9.5

9.7

10.2

11.2

12.1

14.7

17.8

0 5 10 15 20
25 

Figure 3.3 Past Month Illicit Drug Use among Full-Time Workers Aged 18 to 64, by 

Industry Categories: 2002-2004 Combined 

 

Figure 3.4 Past Month Heavy Alcohol Use among Full-Time Workers Aged 18 to 64, by 

Industry Categories: 2002-2004 Combined 

3.8

4.0

4.1

6.1

6.2

6.2

6.5

6.8

7.3

7.5

8.0

8.5

8.8

9.4

10.9

11.3

11.6

13.7

16.9

0 5 10 15 20

Percent Using Illicit Drugs in Past Month

Accommodations and Food Services

Real Estate, Rental, and Leasing

Arts, Entertainment, and Recreation 

Retail Trade 

Construction

Management of Companies and Enterprises, Administrative, 

Support, Waste Management, and Remediation Services 

Mining

Information

Health Care and Social Assistance 

Wholesale Trade 

Manufacturing

Professional, Scientific, and Technical Services

Public Administration 

Finance and Insurance

Transportation and Warehousing 

Agriculture, Forestry, Fishing, and Hunting 

Educational Services 

Utilities 

Other Services (Except Public Administration)

Industry Categories

3.8

4.0

4.1

6.1

6.2

6.2

6.5

6.8

7.3

7.5

8.0

8.5

8.8

9.4

10.9

11.3

11.6

13.7

16.9

0 5 10 15 20

Percent Using Illicit Drugs in Past Month

Accommodations and Food Services

Real Estate, Rental, and Leasing

Arts, Entertainment, and Recreation 

Retail Trade 

Construction

Management of Companies and Enterprises, Administrative, 

Support, Waste Management, and Remediation Services 

Mining

Information

Health Care and Social Assistance 

Wholesale Trade 

Manufacturing

Professional, Scientific, and Technical Services

Public Administration 

Finance and Insurance

Transportation and Warehousing 

Agriculture, Forestry, Fishing, and Hunting 

Educational Services 

Utilities 

Other Services (Except Public Administration)

Accommodations and Food Services

Real Estate, Rental, and Leasing

Arts, Entertainment, and Recreation 

Retail Trade 

Construction

Management of Companies and Enterprises, Administrative, 

Support, Waste Management, and Remediation Services 

Mining

Information

Health Care and Social Assistance 

Wholesale Trade 

Manufacturing

Professional, Scientific, and Technical Services

Public Administration 

Finance and Insurance

Transportation and Warehousing 

Agriculture, Forestry, Fishing, and Hunting 

Educational Services 

Utilities 

Other Services (Except Public Administration)

Industry Categories

4.0

4.3

5.9

6.9

7.1

8.6

8.8

9.5

9.7

9.8

9.9

10.1

10.4

10.4

11.5

12.0

13.3

13.6

15.9

0 5 10 15 20

Percent Heavy Alcohol Use in Past Month

Accommodations and Food Services

Real Estate, Rental, and Leasing

Arts, Entertainment, and Recreation 

Retail Trade 

Construction

Management of Companies and Enterprises, Administrative, 

Support, Waste Management, and Remediation Services 

Transportation and Warehousing 

Mining

Information

Health Care and Social Assistance 

Wholesale Trade 

Manufacturing

Professional, Scientific, and Technical Services

Public Administration 

Finance and Insurance

Agriculture, Forestry, Fishing, and Hunting 

Educational Services 

Utilities 

Other Services (Except Public Administration)

Industry Categories

4.0

4.3

5.9

6.9

7.1

8.6

8.8

9.5

9.7

9.8

9.9

10.1

10.4

10.4

11.5

12.0

13.3

13.6

15.9

0 5 10 15 20

Percent Heavy Alcohol Use in Past Month

Accommodations and Food Services

Real Estate, Rental, and Leasing

Arts, Entertainment, and Recreation 

Retail Trade 

Construction

Management of Companies and Enterprises, Administrative, 

Support, Waste Management, and Remediation Services 

Transportation and Warehousing 

Mining

Information

Health Care and Social Assistance 

Wholesale Trade 

Manufacturing

Professional, Scientific, and Technical Services

Public Administration 

Finance and Insurance

Agriculture, Forestry, Fishing, and Hunting 

Educational Services 

Utilities 

Other Services (Except Public Administration)

Accommodations and Food Services

Real Estate, Rental, and Leasing

Arts, Entertainment, and Recreation 

Retail Trade 

Construction

Management of Companies and Enterprises, Administrative, 

Support, Waste Management, and Remediation Services 

Transportation and Warehousing 

Mining

Information

Health Care and Social Assistance 

Wholesale Trade 

Manufacturing

Professional, Scientific, and Technical Services

Public Administration 

Finance and Insurance

Agriculture, Forestry, Fishing, and Hunting 

Educational Services 

Utilities 

Other Services (Except Public Administration)

Industry Categories
26 

3.7. Dependence and Abuse among Full-Time Workers, by Industry 

! The major industry groups with the highest prevalence of illicit drug dependence or abuse 

in the past year were accommodations and food services (6.0 percent) and construction (5.1 

percent) (Table 3.6). 

! Construction (15.6 percent) and accommodations and food services (15.4 percent) had the 

highest prevalence of alcohol dependence or abuse in the past year in the major industry 

groups (Table 3.6). 

3.8. Past Month Illicit Drug Use among Full-Time Workers, by 

Establishment Size 

! Among the 9.4 million full-time workers who reported past month illicit drug use, 2.9 

million were employed in establishments with fewer than 10 employees. The prevalence of 

past month illicit drug use for workers in establishments with fewer than 10 employees was 

9.9 percent (Table 3.7). 

! An estimated 1.9 million workers who reported past month illicit drug use worked in 

settings with 10 to 24 employees. The past month illicit drug use prevalence among 

workers in these establishments was 9.7 percent, which was similar to the prevalence 

estimate (9.9 percent) for smaller establishments (fewer than 10 employees) (Table 3.7). 

! Prevalence of past month illicit drug use was lower as establishment size increased. The 

prevalence among workers in establishments with 25 to 99 employees was 8.2 percent, 

compared with 6.7 percent among workers in establishments with 100 to 499 employees 

and 5.7 percent among workers in establishments with 500 or more employees (Table 3.7). 

3.9. Past Month Marijuana Use among Full-Time Workers, by 

Establishment Size 

! Among full-time workers in establishments with fewer than 10 employees, 7.9 percent had 

used marijuana in the past month. Similarly, 7.8 percent of workers in slightly larger 

establishments with 10 to 24 employees and 6.4 percent of workers in establishments with 

25 to 99 employees reported past month marijuana use (Table 3.7). 

! Prevalence of past month marijuana use was lower among workers in larger establishments 

of 100 to 499 employees and 500 or more employees (4.9 and 4.1 percent, respectively) 

than among workers in smaller establishments (Table 3.7). 

3.10. Past Month Heavy Alcohol Use among Full-Time Workers, by 

Establishment Size 

! The prevalence of past month heavy alcohol use among full-time workers in the smallest 

establishments (fewer than 10 employees) was 10.1 percent. This was higher than the 

prevalence reported for similar workers in the largest establishments (6.8 percent in 

establishments with 500 or more employees) (Table 3.7). 
27 

3.11. Past Year Illicit Drug Dependence or Abuse among Full-Time Workers, 

by Establishment Size 

! An estimated 3.0 million full-time workers in the United States met the criteria for past 

year illicit drug dependence or abuse. More than half of these workers (1.6 million) were 

employed in small establishments with fewer than 25 employees (Table 3.8). 

! Among workers in small establishments with fewer than 10 employees, 3.1 percent 

reported symptoms consistent with past year illicit drug dependence or abuse. This was 

higher than the prevalence of illicit drug dependence or abuse among workers in large 

establishments with 500 or more employees (1.6 percent). There was a steady decline in 

prevalence with increases in establishment size (Table 3.8). 

3.12. Past Year Alcohol Dependence or Abuse among Full-Time Workers, by 

Establishment Size 

! Full-time workers in the largest establishments (500 or more employees) reported the 

lowest prevalence of past year alcohol dependence or abuse (7.5 vs. 9.0 to 9.9 percent in 

smaller establishments) (Table 3.8). 

3.13. Summary 

The prevalence of substance use, dependence, and abuse varied across occupations and 

industries. For example, highest rates of illicit drug use were found among food preparation, 

construction and extraction, and arts occupations and among food services, construction, and arts 

industries. These findings were likely influenced by characteristics of the workers in occupations 

and industries. Certain occupations and industries have higher percentages of males and/or 

younger workers, characteristics associated with higher rates of substance use. Indeed, the five 

occupations with the highest prevalence of illicit drug use were dominated by male workers. 

Cultural shifts that increase the rate of females working in positions previously dominated by 

males should be monitored to assess the impact of these changes on substance use prevalence 

within occupational and industrial groups. 
28 
29 

4. Workplace Information Policies and 

Programs concerning Drug and Alcohol Use 

This chapter examines the prevalence of workplace policies and programs designed to 

reduce substance use and the relationship between worker substance use and those workplace 

efforts. The three types of workplace policies and programs examined are (1) the availability of 

educational materials about the effects of substance use, (2) the use of a written policy about 

substance use, and (3) the presence of an employee assistance program (EAP). Employers may 

offer any, all, or none of these programs and policies to employees, and these programs may be 

available only to full-time employees in some workplaces. 

There is little prior evidence to suggest that these efforts alone are effective deterrents, 

unless they are combined with drug-testing programs. Some research has demonstrated that 

EAPs provide workers a venue for seeking help, but only when the employees are aware of the 

services, have a generally positive attitude toward the EAP, and believe that job security is not 

threatened as a result of seeking assistance with a substance use problem (Delaney, Grube, & 

Ames, 1998; Reynolds & Lehman, 2003). 

4.1. Demographic Characteristics of Workers Reporting Workplace Drug 

Policies and Programs 

! Among the nearly 115 million full-time workers aged 18 to 64 years old in the United 

States, 47.7 million (43.8 percent) reported that they had access to educational information 

about drug and alcohol use in the workplace, 87.0 million (78.7 percent) reported that they 

were aware of a written policy about drug and alcohol use in the workplace, and 60.9 

million (58.4 percent) reported that their employer offered an EAP (Tables 4.1 and 4.2 in 

Appendix E). 

! The youngest adult workers were least likely to report access to educational information 

about drug and alcohol use in the workplace. Among 18- to 25-year-old workers, 33.2 

percent reported that they had educational information available. This was significantly 

lower than among workers aged 26 to 34 years (39.6 percent), 35 to 49 years (46.3 

percent), and 50 to 64 years (48.9 percent) (Figure 4.1 and Table 4.1). 

! Young adult workers between the ages of 18 and 25 were significantly less likely to report 

EAPs available in the workplace compared with all other age groups (39.7 vs. 56.4 to 62.6 

percent) (Figure 4.1 and Table 4.1). 

! Females were slightly more likely to report working for an employer who provided a 

written drug and alcohol use policy in the workplace (81.8 vs. 76.4 percent) and who had 

an EAP available (61.0 vs. 56.5 percent) in comparison with males (Figure 4.2 and Table 

4.1). 
30 

Figure 4.1 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an Employee Assistance Program concerning Drug or Alcohol Use 

among Full-Time Workers Aged 18 to 64, by Age Group: 2002-2004 Combined 

Figure 4.2 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an Employee Assistance Program concerning Drug or Alcohol Use 

among Full-Time Workers Aged 18 to 64, by Gender: 2002-2004 Combined 

33.2

76.9

39.6 39.7

79.3

56.4

46.3

79.8

62.4

48.9

77.1

62.6

0

20

40

60

80

18-25

26-34

35-49

50-64

Educational Information Written Policy

Percent

Employee Assistance 

Program

33.2

76.9

39.6 39.7

79.3

56.4

46.3

79.8

62.4

48.9

77.1

62.6

0

20

40

60

80

18-25

26-34

35-49

50-64

Educational Information Written Policy

Percent

Employee Assistance 

Program

Educational Information Written Policy

44.0

76.4

56.5

43.4

81.8

61.0

0

20

40

60

80

100

Male

Female

Percent

Employee Assistance 

Program

Educational Information Written Policy

44.0

76.4

56.5

43.4

81.8

61.0

0

20

40

60

80

100

Male

Female

Percent

44.0

76.4

56.5

43.4

81.8

61.0

0

20

40

60

80

100

Male

Female

Percent

Employee Assistance 

Program
31 

! Non-Hispanic black (56.3 percent), American Indian or Alaska Native (54.1 percent), and 

Native Hawaiian or Other Pacific Islander (54.0 percent) adults were more likely to report 

that they had access to educational information in the workplace than non-Hispanic white 

(42.7 percent) and Hispanic adults (38.4 percent) (Figure 4.3 and Table 4.1). 

! Workers who were non-Hispanic Asian (41.6 percent) or who were Hispanic (38.4 percent) 

had the lowest prevalence of all racial/ethnic groups to report working for employers who 

had a written policy about drug and alcohol use (Figure 4.3 and Table 4.1). 

Figure 4.3 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an Employee Assistance Program concerning Drug or Alcohol Use 

among Full-Time Workers Aged 18 to 64, by Hispanic or Latino Origin and 

Race: 2002-2004 Combined 

! Educational attainment was consistently associated with higher access to information 

resources. Those with higher levels of education were more likely than those with a high 

school education or less to report access to drug and alcohol information (Figure 4.4). 

! The availability of an EAP also was associated with education. An estimated 32.1 percent 

of adults with less than a high school diploma reported an EAP available in the workplace, 

while 55.4 percent of high school graduates, 61.7 percent of adults with some college, and 

69.3 percent of college graduates reported access to an EAP (Table 4.2). 

60.6

65.7

62.7

57.5

62.0

40.4

78.4

86.9

84.2

77.3

80.1

73.1

42.7

56.3 54.1

41.6 42.1

38.4

54.0

0

20

40

60

80

100

Percent

Educational Information Written Policy Employee Assistance 

Program

Note: Due to low precision, estimates of workplace that provides a written policy or maintains an employee assistance program 

concerning drug or alcohol use among Native Hawaiian or Other Pacific Islander full-time workers are not shown.

White

Black or African American

American Indian or Alaska Native

Native Hawaiian or Other Pacific Islander

Asian

Two or More Races

Hispanic or Latino

60.6

65.7

62.7

57.5

62.0

40.4

78.4

86.9

84.2

77.3

80.1

73.1

42.7

56.3 54.1

41.6 42.1

38.4

54.0

0

20

40

60

80

100

Percent

Educational Information Written Policy Employee Assistance 

Program

Note: Due to low precision, estimates of workplace that provides a written policy or maintains an employee assistance program 

concerning drug or alcohol use among Native Hawaiian or Other Pacific Islander full-time workers are not shown.

White

Black or African American

American Indian or Alaska Native

Native Hawaiian or Other Pacific Islander

Asian

Two or More Races

Hispanic or Latino

White

Black or African American

American Indian or Alaska Native

Native Hawaiian or Other Pacific Islander

Asian

Two or More Races

Hispanic or Latino
32 

! For all levels of education, workers with family income less than $20,000 were less likely 

than those with higher family incomes to report availability of educational information 

about drug and alcohol use, availability of an EAP, and the presence of a written policy 

about drug and alcohol use through the employment setting (Figures 4.4 through 4.6). 

Figure 4.4 Workplace Provides Educational Information concerning Drug or Alcohol Use 

among Full-Time Workers Aged 18 to 64, by Education and Family Income: 

2002-2004 Combined 

! Workers who lived in the most rural settings (noncore adjacent, no town and noncore rural, 

not adjacent) were less likely than workers in other settings to report working for 

employers with a written policy about drug and alcohol use (Table 4.2). 

! About 47 percent of workers who resided in rural settings reported that they had an EAP at 

their place of employment (47.2 percent for noncore rural, not adjacent and 47.5 percent 

for noncore adjacent, no town), while more than 59 percent of metropolitan-residing 

workers (59.3 percent in large metropolitan statistical areas [MSAs] and 59.6 percent in 

small MSAs) reported that they had this benefit (Table 4.2). 

26.5

34.0

36.9

32.1

35.9

43.5 42.8

40.7 39.5

48.3

47.0 46.1

41.8

47.8

49.5 48.4

0

10

20

30

40

50

Less Than $20,000

$20,000-49,999

$50,000-74,999

$75,000 or More

Less Than High School High School Graduate

Percent

Some College College Graduate

26.5

34.0

36.9

32.1

35.9

43.5 42.8

40.7 39.5

48.3

47.0 46.1

41.8

47.8

49.5 48.4

0

10

20

30

40

50

Less Than $20,000

$20,000-49,999

$50,000-74,999

$75,000 or More

Less Than High School High School Graduate

Percent

Some College College Graduate
33 

Figure 4.5 Workplace Prepares a Written Policy concerning Drug or Alcohol Use among 

Full-Time Workers Aged 18 to 64, by Education and Family Income: 2002-

2004 Combined 

Figure 4.6 Workplace Maintains an Employee Assistance Program concerning Drug or 

Alcohol Use among Full-Time Workers Aged 18 to 64, by Education and 

Family Income: 2002-2004 Combined 

62.9

69.8

72.8

70.1 70.3

78.2 79.8 77.7 75.5

82.7 83.0 82.7

73.5

78.7

82.6 82.5

0

20

40

60

80

100

Less Than $20,000

$20,000-49,999

$50,000-74,999

$75,000 or More

Less Than High School High School Graduate

Percent

Some College College Graduate

62.9

69.8

72.8

70.1 70.3

78.2 79.8 77.7 75.5

82.7 83.0 82.7

73.5

78.7

82.6 82.5

0

20

40

60

80

100

Less Than $20,000

$20,000-49,999

$50,000-74,999

$75,000 or More

Less Than High School High School Graduate

Percent

Some College College Graduate

19.3

33.7

41.5

44.9

32.3

53.2

57.1

62.1

47.6

63.8

66.8

70.1

49.4

63.1

68.2

73.1

0

20

40

60

80 Less Than $20,000

$20,000-49,999

$50,000-74,999

$75,000 or More

Less Than High School High School Graduate

Percent

Some College College Graduate

19.3

33.7

41.5

44.9

32.3

53.2

57.1

62.1

47.6

63.8

66.8

70.1

49.4

63.1

68.2

73.1

0

20

40

60

80 Less Than $20,000

$20,000-49,999

$50,000-74,999

$75,000 or More

Less Than High School High School Graduate

Percent

Some College College Graduate
34 

4.2. Working for Employers with Drug and Alcohol Policies and Programs, 

by Current Illicit Drug Use 

! Nearly 3 million (32.1 percent) full-time workers between the ages of 18 and 64 who had 

used an illicit drug in the past month reported that they worked for an employer who 

offered educational information about alcohol and drug use. An EAP was reported 

available to 3.9 million (45.4 percent) workers who were past month users of an illicit drug, 

while 6.5 million (71.0 percent) reported working for employers who had a written policy 

about drug and alcohol use (Figure 4.7 and Tables 4.3 and 4.4). 

! Generally, past month illicit drug users were less likely to report working for employers 

who offered workplace drug or alcohol programs or policies, compared with those who did 

not use an illicit drug in the past month. An estimated 45.4 percent of current illicit drug 

users reported access to an EAP at their place of employment compared with 59.6 percent 

of workers who had not used an illicit drug in the past month. This finding occurred across 

demographic comparisons with few exceptions (Figure 4.7 and Tables 4.3 and 4.4). 

Figure 4.7 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an Employee Assistance Program concerning Drug or Alcohol Use 

among Full-Time Workers Aged 18 to 64, by Past Month Illicit Drug Use: 

2002-2004 Combined 

! Among 18- to 25-year-old workers, 28.2 percent of current illicit drug users reported that 

they worked for an employer who provided educational information about drug and alcohol 

use, while 34.4 percent of same-age nondrug users reported that they worked for employers 

with educational programs. This finding was similar across other age group comparisons: 

26 to 34 (31.3 vs. 40.6 percent), 35 to 49 (35.7 vs. 47.1 percent), and 50 to 64 (33.2 vs. 

49.3 percent) (Figure 4.8 and Table 4.3). 

32.1

44.8

71.0

79.4

45.4

59.6

0

20

40

60

80

Educational Information

Written Policy

Employee Assistance Program

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent

32.1

44.8

71.0

79.4

45.4

59.6

0

20

40

60

80

Educational Information

Written Policy

Employee Assistance Program

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent
35 

Figure 4.8 Workplace Provides Educational Information concerning Drug or Alcohol Use 

among Full-Time Workers Aged 18 to 64, by Age Group and Past Month Illicit 

Drug Use: 2002-2004 Combined 

! A reported written policy regarding drug and alcohol use in the employment setting was 

unrelated to current drug use among workers aged 50 to 64. An estimated 76.3 percent of 

current drug users in this age group reported that they worked for employers with a written 

policy, while 77.1 percent of workers in this cohort who had not used drugs in the past 

month reported that they were aware of a written policy at work (Figure 4.9 and Table 4.3). 

! Among all age groups, past month drug users were less likely than nondrug users to report 

access to an EAP (34.3, 44.4, 51.9, and 58.2 vs. 41.0, 57.9, 63.2, and 62.7 percent, 

respectively) (Figure 4.10). 

! Males were more likely than females to have used illicit drugs in the past month, but 

among past month drug users, females were more likely than males to report working for 

employers who offered EAPs or who had a written drug and alcohol policy (EAP: 49.4 vs. 

43.5 percent; written policy: 76.3 vs. 68.5 percent) (Table 4.3). 

! Among white adults, black adults, and adults who reported two or more races, past month 

drug users were more likely than nondrug users to report access to an EAP (47.0, 43.1, and 

31.2 vs. 61.9, 67.7, and 66.8 percent, respectively). However, reporting access to an EAP 

did not differ among Hispanic drug users and nondrug users (37.1 vs. 40.7 percent). This 

may be related to the generally low availability of EAPs as a benefit for the Hispanic 

population (Figure 4.11 and Table 4.3). 

28.2

34.4

31.3

40.6

35.7

47.1

33.2

49.3

0

10

20

30

40

50

18-25

26-34

35-49

50-64

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent

28.2

34.4

31.3

40.6

35.7

47.1

33.2

49.3

0

10

20

30

40

50

18-25

26-34

35-49

50-64

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent
36 

Figure 4.9 Workplace Prepares a Written Policy concerning Drug or Alcohol Use among 

Full-Time Workers Aged 18 to 64, by Age Group and Past Month Illicit Drug 

Use: 2002-2004 Combined 

Figure 4.10 Workplace Maintains an Employee Assistance Program concerning Drug or 

Alcohol Use among Full-Time Workers Aged 18 to 64, by Age Group and Past 

Month Illicit Drug Use: 2002-2004 Combined 

70.5

78.4

70.3

80.4

70.9

80.5

76.3 77.1

0

20

40

60

80

100

18-25

26-34

35-49

50-64

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent

70.5

78.4

70.3

80.4

70.9

80.5

76.3 77.1

0

20

40

60

80

100

18-25

26-34

35-49

50-64

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent

34.3

41.0

44.4

57.9

51.9

63.2

58.2

62.7

0

20

40

60

80

18-25

26-34

35-49

50-64

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent

34.3

41.0

44.4

57.9

51.9

63.2

58.2

62.7

0

20

40

60

80

18-25

26-34

35-49

50-64

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent
37 

Figure 4.11 Workplace Maintains an Employee Assistance Program concerning Drug or 

Alcohol Use among Full-Time Workers Aged 18 to 64, by Hispanic or Latino 

Origin and Race and Past Month Illicit Drug Use: 2002-2004 Combined 

! Among workers with less than a high school diploma, nondrug users were more likely than 

past month drug users to report that their employers provided educational information 

regarding alcohol and drug use (34.8 and 29.5 percent, respectively). The differences for 

reporting written policies (66.2 percent of past month users vs. 69.4 percent of nonusers) 

and an EAP (28.5 percent of past month users vs. 32.5 percent of nonusers) were not found 

to be significant among workers with less than a high school diploma (Table 4.4). 

! There was some regional variation among past month drug users who reported working for 

an employer with substance abuse policies and programs. Workers who resided in the 

South and who used an illicit drug in the past month were less likely to report working for 

an employer with an EAP than similar workers from other regions (39.5 vs. 48.0 to 48.5 

percent). There were no differences among the other regions (Table 4.4). 

4.3. Working for Employers with Educational Programs, Written Policies, 

or EAPs, by Current Heavy Alcohol Use 

! The relationship between current heavy alcohol use and working for an employer with drug 

and alcohol programs was generally weaker than the relationship between current illicit 

drug use and the availability of employer-sponsored programs (Tables 4.5 and 4.8). 

61.9

67.7

63.6

57.7

66.8

40.7

47.0

43.1

31.2

37.1

0

20

40

60

80

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent

Note: Due to low precision, estimates for American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, and Asian

full-time workers with past month illicit drug use are not shown. Estimates for Native Hawaiian or Other Pacific Islander full-time 

workers with no past month illicit drug use also are not shown.

White

Black or African American

American Indian or Alaska Native

Asian

Two or More Races

Hispanic or Latino

61.9

67.7

63.6

57.7

66.8

40.7

47.0

43.1

31.2

37.1

0

20

40

60

80

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent

Note: Due to low precision, estimates for American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, and Asian

full-time workers with past month illicit drug use are not shown. Estimates for Native Hawaiian or Other Pacific Islander full-time 

workers with no past month illicit drug use also are not shown.

White

Black or African American

American Indian or Alaska Native

Asian

Two or More Races

Hispanic or Latino
38 

! More than 3.6 million full-time workers in the United States who were past month heavy 

alcohol users reported that they were provided educational information about drug and 

alcohol use by their employer. An estimated 7.2 million workers who were past month 

heavy alcohol users reported that they worked for employers with written policies about 

drug and alcohol use, and 4.7 million reported that they had access to an EAP at their place 

of employment (Tables 4.5 and 4.7). 

! An estimated 71.5 percent of 18- to 25-year-old workers who were heavy alcohol users 

during the past month reported that they worked in employment settings with a written 

policy about alcohol and drug use. This was slightly less than the 77.9 percent of same-age 

workers who were not current heavy alcohol users but reported that they had a written 

policy in the workplace (Table 4.6). 

! Heavy alcohol use was not significantly associated with the reported availability of an EAP 

among 26- to 34-year-olds. However, among 18- to 25-year-olds, past month heavy alcohol 

use was associated with a lower likelihood of working in a setting that offered an EAP, 

compared with those who had no past month heavy alcohol use in the same age group (38.1 

vs. 40.1 percent). This was true in the 35-49 and 50-to-64 age categories as well (56.5 vs. 

62.9 percent and 53.4 vs. 63.1 percent, respectively) (Table 4.6). 

! Non-Hispanic white current heavy alcohol users were less likely to report working in a 

setting with an EAP available than their non-heavy alcohol user counterparts (52.4 vs. 61.5 

percent). However, among Hispanic workers, 41.4 percent of past month heavy alcohol 

users reported access to an EAP, and 40.4 percent of non-heavy alcohol users reported 

access to an EAP. Recall that Hispanic workers were generally less likely than other 

racial/ethnic groups to report access to an EAP (Figures 4.12 through 4.14 and Table 4.6). 

! Heavy alcohol use during the past month was significantly associated with the reported 

availability of an EAP among more highly educated workers. An estimated 32.9 percent of 

past month heavy alcohol users with less than a high school diploma reported that they 

worked in an environment where an EAP was available, while 61.2 percent of college 

graduates with past month heavy alcohol use reported that they had access to an EAP in 

their workplace (Figure 4.15 and Table 4.8). 

! There was a significant difference between past month heavy alcohol users and non-heavy 

alcohol users in the reported availability of a written drug policy or drug education at 

higher levels of education, but not at lower levels of education. Among college graduates, 

35.5 percent of those with past month heavy alcohol use reported drug and alcohol 

education in their workplace compared with 46.5 percent of non-heavy alcohol users. 

Similarly, 75.3 percent of past month heavy alcohol users reported that their employer had 

a written policy about drug and alcohol use, compared with 81.5 percent of non-past month 

heavy alcohol users among college graduates. Similar patterns were observed for EAPs 

(Table 4.8). 

! There were no significant differences between geographic regions or county types in the 

relationship between heavy alcohol use and the reported availability of employer-offered 

educational information about drug and alcohol use (Tables 4.7 and 4.8). 
39 

Figure 4.12 Workplace Provides Educational Information concerning Drug or Alcohol 

Use among Full-Time Workers Aged 18 to 64, by Hispanic or Latino Origin 

and Race and Past Month Heavy Alcohol Use: 2002-2004 Combined 

Note: Due to low precision, estimates for American Indian or Alaska Native and Native Hawaiian or Other 

Pacific Islander full-time workers with past month heavy alcohol use are not shown. 

4.4. Working for Employers with Educational Programs, Written Policies, 

or EAPs, by Illicit Drug or Alcohol Dependence or Abuse during the 

Past Year 

Dependence or abuse during the past year represents a more complex, chronic, and 

serious form of substance use compared with past month use alone. Dependent and abusing 

individuals may be the most likely to be affected (and subsequently helped) by drug and alcohol 

programs in their places of employment. If these programs are effective deterrents, then 

dependent or abusing individuals would be less likely to work (or continue to work) in an 

environment with strict drug policies. Previous research suggests that those with dependence on 

or abuse of illicit drugs or alcohol are more likely to miss workdays due to their substance abuse 

issues, are more likely to have work-related accidents, and are more likely to experience healthrelated consequences due to their substance problems (Normand, Lempert & O'Brien, 1994; 

Mangione et al., 1999). 

43.5

56.8 55.3

42.1

43.5

38.2

55.1

36.0

47.5

27.2

25.4

41.0

0

10

20

30

40

50

60

Past Month Heavy Alcohol Use

Percent

No Past Month Heavy Alcohol Use

White

Black or African American

American Indian or Alaska Native

Native Hawaiian or Other Pacific Islander

Asian

Two or More Races

Hispanic or Latino

43.5

56.8 55.3

42.1

43.5

38.2

55.1

36.0

47.5

27.2

25.4

41.0

0

10

20

30

40

50

60

Past Month Heavy Alcohol Use

Percent

No Past Month Heavy Alcohol Use

White

Black or African American

American Indian or Alaska Native

Native Hawaiian or Other Pacific Islander

Asian

Two or More Races

Hispanic or Latino

White

Black or African American

American Indian or Alaska Native

Native Hawaiian or Other Pacific Islander

Asian

Two or More Races

Hispanic or Latino
40 

Figure 4.13 Workplace Prepares a Written Policy concerning Drug or Alcohol Use among 

Full-Time Workers Aged 18 to 64, by Hispanic or Latino Origin and Race and 

Past Month Heavy Alcohol Use: 2002-2004 Combined 

Note: Due to low precision, estimates for American Indian or Alaska Native, Native Hawaiian or Other Pacific 

Islander, Asian, and Two or More Races full-time workers with past month heavy alcohol use are not shown. 

Estimates for Native Hawaiian or Other Pacific Islander full-time workers with no past month heavy alcohol use also 

are not shown. 

! Among those who had a past year illicit drug dependence or abuse disorder, there were few 

differences between age categories in the likelihood of having access to employersponsored programs. For example, 26.6 percent of 18- to 25-year-olds, 29.8 percent of 26- 

to 34-year-olds, and 34.3 percent of 35- to 49-year-olds with a past year disorder reported 

the availability of educational information about drug and alcohol use in their workplace. 

These percentages among age groups were not significantly different (Table 4.9). 

79.1

87.0

83.8

77.8

81.5

72.9 72.7

85.2

75.0

0

20

40

60

80

100

Past Month Heavy Alcohol Use

Percent

No Past Month Heavy Alcohol Use

White

Black or African American

American Indian or Alaska Native

Asian

Two or More Races

Hispanic or Latino

79.1

87.0

83.8

77.8

81.5

72.9 72.7

85.2

75.0

0

20

40

60

80

100

Past Month Heavy Alcohol Use

Percent

No Past Month Heavy Alcohol Use

White

Black or African American

American Indian or Alaska Native

Asian

Two or More Races

Hispanic or Latino

White

Black or African American

American Indian or Alaska Native

Asian

Two or More Races

Hispanic or Latino
41 

Figure 4.14 Workplace Maintains an Employee Assistance Program concerning Drug or 

Alcohol Use among Full-Time Workers Aged 18 to 64, by Hispanic or Latino 

Origin and Race and Past Month Heavy Alcohol Use: 2002-2004 Combined 

Note: Due to low precision, estimates for American Indian or Alaska Native, Native Hawaiian or Other Pacific 

Islander, Asian, and Two or More Races full-time workers with past month heavy alcohol use are not shown. 

Estimates for Native Hawaiian or Other Pacific Islander full-time workers with no past month heavy alcohol use 

also are not shown. 

! However, across most demographic comparisons, those who met criteria for dependence or 

abuse were less likely than those who did not meet the criteria to report working for an 

employer who had educational programs, EAPs, and written policies about drug and 

alcohol use. Among non-Hispanic white adult workers who had past year illicit drug 

dependence or abuse, 27.9 percent reported working for an employer who had educational 

information, 39.3 percent reported working for an employer who offered an EAP, and 68.4 

percent reported working for an employer with a written drug or alcohol education 

program. Among non-Hispanic white adults who did not meet criteria for past year illicit 

drug dependence, 43.1 percent reported access to educational information at their 

workplace, 61.1 percent reported that their employer had an EAP, and 78.7 percent 

reported working for an employer with a written drug and alcohol policy (Table 4.9). 

! Among those with past year illicit drug dependence or abuse, 70.6 percent reported 

working for an employer with a written policy (Table 4.9), compared with 71.0 percent of 

current users who reported working for employers with a written policy about drug and 

alcohol use (Tables 4.3 and 4.4). 

61.5

66.6

61.6

58.2

62.9

40.4

52.4 51.2

41.4

0

10

20

30

40

50

60

70

Past Month Heavy Alcohol Use

Percent

No Past Month Heavy Alcohol Use

White

Black or African American

American Indian or Alaska Native

Asian

Two or More Races

Hispanic or Latino

61.5

66.6

61.6

58.2

62.9

40.4

52.4 51.2

41.4

0

10

20

30

40

50

60

70

Past Month Heavy Alcohol Use

Percent

No Past Month Heavy Alcohol Use

White

Black or African American

American Indian or Alaska Native

Asian

Two or More Races

Hispanic or Latino

White

Black or African American

American Indian or Alaska Native

Asian

Two or More Races

Hispanic or Latino
42 

Figure 4.15 Workplace Provides Educational Information, Prepares a Written Policy, or 

Maintains an Employee Assistance Program concerning Drug or Alcohol Use 

among Full-Time Workers Aged 18 to 64 with Past Month Heavy Alcohol Use, 

by Education: 2002-2004 Combined 

! Alcohol dependence or abuse has a similar association with reported availability of 

employer-provided information and programs regarding drug and alcohol use when 

compared with illicit drug dependence or abuse. An estimated 37.2 percent of those who 

had past year alcohol dependence or abuse reported access to educational information 

about drug and alcohol use at their workplace, 51.0 percent reported access to an EAP at 

their workplace, and 74.9 percent reported that they had a written drug and alcohol use 

policy at their workplace (vs. 44.4 percent, 59.2 percent, and 79.1 percent, respectively, 

among those with no alcohol dependence or abuse during the past year) (Tables 4.10 and 

4.11). 

4.5. A Final Note about EAPs 

EAP programs are generally established to provide short-term counseling and problem 

solving and may provide a greater deterrent to illicit drug and alcohol use than educational 

information and written policies. EAPs may be considered by some employers to be too costly to 

offer, but they may serve as a first line of access to the health care system with relatively few 

barriers when appropriately implemented. There is generally no cost for the employee, 

appointments may be by phone or in person, and the EAP may serve as a referral source for 

longer term needs. However, there does appear to be unequal access to EAPs across 

demographic groups. Specifically, adult workers aged 18 to 25 were less likely than older adult 

workers to report access to an EAP. Younger workers had an increased risk for substance use 

disorders and yet were least likely to report access to an EAP. Further research will be necessary 

to assess the contribution that EAPs make to the reduction of substance use disorders, as well as 

33.1

66.9

32.9

38.7

74.1

49.4

38.9

75.8

55.1

35.5

75.3

61.2

0

20

40

60

80

Less Than High School

High School Graduate

Some College

College Graduate

Educational Information Written Policy

Percent

Employee Assistance 

Program

33.1

66.9

32.9

38.7

74.1

49.4

38.9

75.8

55.1

35.5

75.3

61.2

0

20

40

60

80

Less Than High School

High School Graduate

Some College

College Graduate

Educational Information Written Policy

Percent

Employee Assistance 

Program
43 

the development of appropriate policy and programming to develop programs targeted at specific 

demographic groups. Hispanics also were distinctive in reporting less access to EAPs. This may 

be indicative of other underlying differences among racial/ethnic groups such as educational 

attainment, occupation and industry opportunities, and age distribution. Further analysis should 

be conducted to clarify this finding and to improve access for these underserved groups. 

4.6. Summary 

Workplace drug and alcohol policies and programs serve to communicate a "no-drugsallowed" attitude that may deter current users from applying and working for employers with this 

position and also may encourage current users to leave the organization. 

Educational attainment was consistently associated with higher access to information 

resources, and those with higher levels of education were more likely than those with a high 

school education or less to report access to drug and alcohol information or an EAP. Males were 

more likely than females to report having used illicit drugs in the past month, but females were 

more likely than males to report working for employers who offered EAPs or had a written drug 

and alcohol policy. Non-Hispanic white past month heavy alcohol users were less likely to report 

working in a setting with an EAP available than their non-heavy alcohol user counterparts. 

Across most demographic comparisons, those who met criteria for dependence or abuse were 

less likely than those who did not meet the criteria to report working for an employer who had 

educational programs, EAPs, and written policies about drug and alcohol use. 

The workplace programs were all, to a greater or lesser degree, associated with a lower 

likelihood that current illicit drug users would work in settings with any of the programs. 

However, the effect of these programs on potential new hires and existing staff cannot be 

evaluated with cross-sectional data. 
44 
45 

5. Workplace Testing 

This chapter examines the relationship between worker substance use and testing 

programs while controlling for age, race/ethnicity, gender, education, income, geographic 

setting, occupational group, and establishment size. Workplace drug testing was implemented as 

an effort to deter substance abuse and its effects on productivity, health, and safety in the 

Nation's workforce. To date there is limited evidence about the effectiveness of this deterrent 

effect (Normand, Lempert, & O'Brien, 1994; Hoffmann, Larison, & Sanderson, 1997; Office of 

Applied Studies [OAS], 1999; French, Roebuck, & Alexandre, 2004). In the National Survey on 

Drug Use and Health (NSDUH), respondents were asked to indicate whether their employer ever 

tested employees for alcohol use and/or illicit drug use. Those who indicated at least one of these 

testing parameter policies then were asked to identify whether testing occurred during the hiring 

process and/or for employees on a random basis. It is important to note that NSDUH does not 

collect data related to job tenure and is not a longitudinal survey. Thus, it is not possible to draw 

conclusions about the causal direction of the relationship between testing and substance use. 

However, prehire- and random-testing programs in establishments are likely to reduce the 

prevalence of worker substance use through exclusionary screening and early termination of 

users. 

An estimated 38.7 million full-time workers reported that their employer ever conducted 

testing for alcohol use. Reported testing for alcohol use was more common among workers aged 

35 to 49 than workers aged 18 to 25, 26 to 34, and 50 to 64 (37.5 vs. 30.5, 34.2, and 35.3 percent, 

respectively), among males than females (37.7 vs. 32.1 percent), and among those living in the 

South than among those living in the Northeast, Midwest, or West (39.6 vs. 26.8, 36.7, and 34.3 

percent, respectively) (Figure 5.1 below and Tables 5.1 and 5.2 in Appendix E). 

Testing for illicit drug use was reported more often than testing for alcohol use. An 

estimated 54 million full-time workers reported that their employer ever tested for illicit drug 

use. Reported testing for illicit drug use was more common among workers aged 35 to 49 than 

workers aged 18 to 25, 26 to 34, and 50 to 64 (50.4 vs. 46.7, 49.9, and 46.0 percent, 

respectively), among males than females (51.4 vs. 45.1 percent), and among workers who were 

black than among those who were white, American Indian or Alaska Native, Native Hawaiian or 

Other Pacific Islander, or Asian, or reported two or more races (63.1 vs. 46.9, 59.9, 56.5, 44.5, 

and 49.1 percent, respectively) (Figure 5.1 and Tables 5.1 and 5.2). 

5.1. Prehire-Testing Programs among Full-Time Workers 

! Among the Nation's full-time workers, 42.9 percent reported that tests for illicit drug or 

alcohol use occurred at their place of employment during the hiring process, or "prehire" 

testing. This equates to more than 47 million adults who worked in settings where testing 

for illicit drug or alcohol use occurred during the hiring process (Figure 5.1 and Table 5.1). 
46 

Figure 5.1 Workplace Drug or Alcohol Use Testing Practices among Full-Time Workers 

Aged 18 to 64: 2002-2004 Combined 

! The youngest and oldest adult workers (18 to 25 and 50 to 64 years) were less likely to 

report working for employers with prehire drug testing than workers aged 26 to 49 years. 

An estimated 40.8 percent of 50- to 64-year-olds and 39.0 percent of 18- to 25-year-olds 

reported prehire testing, compared with 44.3 percent of workers aged 26 to 34 years and 

44.7 percent of workers aged 35 to 49 years (Table 5.1). 

! Males reported prehire testing in their place of employment more often than females (45.8 

vs. 39.1 percent) (Table 5.1). 

! The prevalence of prehire testing varied by race/ethnicity. Black (58.1 percent), Native 

Hawaiian or Other Pacific Islander (53.5 percent), and American Indian or Alaska Native 

(50.8 percent) adults reported greater rates of prehire testing than Hispanic whites (40.5 

percent), Asians (41.8 percent), or adults who reported two or more races (42.8 percent) 

(Table 5.1). 

! College graduates were least likely to report working for employers with prehire testing 

compared with all other levels of educational attainment (35.0 percent of college graduates 

vs. 42.5 percent of those with less than a high school diploma, 48.5 percent of high school 

graduates, and 45.7 percent of those with some college) (Table 5.2). 

! The lowest family income category had the lowest prevalence of prehire drug testing. An 

estimated 36.3 percent of workers with family incomes that were less than $20,000 

reported prehire testing (vs. 44.0 percent of incomes of $20,000 to $49,999, 45.9 percent of 

incomes of $50,000 to $74,999, and 41.9 percent of incomes of $75,000 or more) (Table 

5.2). 

35.4

48.8

42.9

29.6

0

10

20

30

40

50

Tests for 

Alcohol Use

Tests for Drug 

Use

Tests for Drug or 

Alcohol Use during 

Hiring Process

Percent

Tests for Drug or 

Alcohol Use on a 

Random Basis

35.4

48.8

42.9

29.6

0

10

20

30

40

50

Tests for 

Alcohol Use

Tests for Drug 

Use

Tests for Drug or 

Alcohol Use during 

Hiring Process

Percent

Tests for Drug or 

Alcohol Use on a 

Random Basis
47 

! An estimated 37.7 percent of residents of noncore rural counties and 41.7 percent of 

workers in large metropolitan statistical areas (MSAs) reported working full time at places 

of employment with prehire drug testing. These are significantly smaller proportions than 

those reported in small MSAs (45.1 percent) or micropolitan statistical areas (MiSA; 44.7 

percent) (Table 5.2). 

! Workers in protective service (76.2 percent) and transportation and material-moving (73.3 

percent) occupational categories had the highest prevalence of reported workplace testing 

for illicit drug or alcohol use during the hiring process. Workers in legal occupations (14.0) 

were the least likely category to report workplace testing for illicit drug or alcohol use 

during the hiring process (Figure 5.2). 

Figure 5.2 Workplace Tests Employees for Drug or Alcohol Use during Hiring Process 

among Full-Time Workers Aged 18 to 64, by Major Occupational Categories: 

2002-2004 Combined 

! The likelihood of working in a prehire-testing environment was steadily higher as the size 

of an establishment increased. An estimated 19.0 percent of employees who worked in an 

establishment with fewer than 10 employees reported a prehire drug-testing program. This 

is a significantly smaller proportion of workers who reported testing than was observed in 

other establishment sizes. Among employees who worked for the largest establishments of 

500 or more employees, 70.6 percent reported prehire testing (Table 5.12). 

14.0

17.3

17.9

20.7

21.8

26.3

30.2

33.6

34.7

35.6

36.5

38.3

39.1

41.4

46.6

52.5

52.7

57.4

63.1

73.3

76.2

0 10 20 30 40 50 60 70 80

Percentage Workplace Tests Employees during Hiring Process 

Major Occupational Categories 

Protective Service

Transportation and Material-Moving

Production Occupations

Installation, Maintenance, and Repair

Engineering, Architecture, and Surveyors

Healthcare Practitioners and Technical Occupations

Office and Administrative Support

Mathematical and Computer Scientists

Life, Physical, and Social Science

Management

Building and Grounds Cleaning and Maintenance

Sales and Related Occupations

Construction and Extraction

Financial Occupations 

Community and Social Services

Food Preparation and Serving Related

Farming, Fishing, and Forestry

Personal Care and Service

Education, Training, and Library

Arts, Design, Entertainment, Sports, and Media

Legal Occupations 14.0

17.3

17.9

20.7

21.8

26.3

30.2

33.6

34.7

35.6

36.5

38.3

39.1

41.4

46.6

52.5

52.7

57.4

63.1

73.3

76.2

0 10 20 30 40 50 60 70 80

Percentage Workplace Tests Employees during Hiring Process 

Major Occupational Categories 

Protective Service

Transportation and Material-Moving

Production Occupations

Installation, Maintenance, and Repair

Engineering, Architecture, and Surveyors

Healthcare Practitioners and Technical Occupations

Office and Administrative Support

Mathematical and Computer Scientists

Life, Physical, and Social Science

Management

Building and Grounds Cleaning and Maintenance

Sales and Related Occupations

Construction and Extraction

Financial Occupations 

Community and Social Services

Food Preparation and Serving Related

Farming, Fishing, and Forestry

Personal Care and Service

Education, Training, and Library

Arts, Design, Entertainment, Sports, and Media

Legal Occupations
48 

5.2. Prehire Testing among Full-Time Workers, by Substance Use and 

Dependence and Abuse 

! For age groups, current illicit drug users were less likely than nonusers to report working 

for employers who conducted prehire drug or alcohol tests (29.4 vs. 41.3 percent of 18- to 

25-year-olds, 32.0 vs. 45.8 percent of 26- to 34-year-olds, 34.2 vs. 45.5 percent of 35- to 

49-year-olds, and 31.3 vs. 41.0 percent of 50- to 64-year-olds) (Figure 5.3 and Table 5.3). 

! For each racial/ethnic category, current illicit drug users were less likely than nonusers to 

report working for employers who conducted prehire drug or alcohol tests (Figure 5.4). 

! For both males and females, current illicit drug users were less likely than nonusers to 

report working for employers who conducted prehire drug or alcohol tests (32.7 and 30.2 

vs. 47.2 and 39.7 percent, respectively) (Figure 5.5 and Table 5.3). 

! For all education categories, current illicit drug users were less likely than those who did 

not use current illicit drugs to report working for employers who conducted prehire drug or 

alcohol tests (less than high school: 31.5 vs. 43.9 percent; high school graduate: 35.8 vs. 

49.8 percent; some college: 33.7 vs. 46.8 percent; and college graduate: 23.7 vs. 35.7 

percent) (Figure 5.6 and Table 5.4). 

! For all income categories, current illicit drug users were less likely than nonusers to report 

working for employers who conducted prehire drug or alcohol tests: 26.2 versus 37.9 

percent for workers with family incomes that were less than $20,000, 33.3 versus 45.1 

percent for workers with family incomes between $20,000 and $49,999, 34.5 versus 46.9 

percent for workers with family incomes between $50,000 and 74,999, and 31.5 versus 

42.6 percent for workers with family incomes of $75,000 or more (Table 5.4). 

! For all geographic settings, current illicit drug users were less likely to report working for 

employers who conducted prehire drug or alcohol tests than those with no current illicit 

drug use: 23.8 versus 35.4 percent for workers in the Northeast, 35.9 versus 45.3 percent 

for workers in the Midwest, 35.3 versus 49.3 for workers in the South, and 30.5 versus 40.9 

percent for workers in the West (Table 5.4). 

! For all county types, current illicit drug users were less likely than those who did not use 

current illicit drugs to report working for employers who conducted prehire drug or alcohol 

tests (Figure 5.7). 

! The likelihood of working for an employer who conducted prehire drug testing was higher 

among older age groups than younger age groups who were past month heavy alcohol 

users. The pattern differed among those who were not past month heavy alcohol users. 

Among heavy alcohol users, 34.4 percent of 18- to 25-year-olds reported prehire testing in 

their employment setting, compared with 46.4 percent of 50- to 64-year-olds. Among those 

who did not report past month heavy alcohol use, the oldest and youngest full-time workers 

(18 to 25 and 50 to 64 years) were less likely to report prehire drug testing by their 

employer compared with 26- to 34-year-olds and 35- to 49-year-olds (Figure 5.8 and Table 

5.6). 
49 

Figure 5.3 Workplace Tests during Hiring Process among Full-Time Workers Aged 18 to 

64, by Age Group and Past Month Illicit Drug Use: 2002-2004 Combined 

Figure 5.4 Workplace Tests during Hiring Process among Full-Time Workers Aged 18 to 

64, by Hispanic or Latino Origin and Race and Past Month Illicit Drug Use: 

2002-2004 Combined 

29.4

41.3

32.0

45.8

34.2

45.5

31.3

41.0

0

10

20

30

40

50

18-25

26-34

35-49

50-64

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent

29.4

41.3

32.0

45.8

34.2

45.5

31.3

41.0

0

10

20

30

40

50

18-25

26-34

35-49

50-64

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent

41.5

59.5

50.0

42.0

45.7

43.0

30.1

42.9

24.0

31.6

0

10

20

30

40

50

60

70

80

Percent

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Note: Due to low precision, estimates for American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, and Asian

full-time workers with past month illicit drug use are not shown. Estimates for Native Hawaiian or Other Pacific Islander full-time 

workers with no past month illicit drug use also are not shown.

White

Black or African American

American Indian or Alaska Native

Asian

Two or More Races

Hispanic or Latino

41.5

59.5

50.0

42.0

45.7

43.0

30.1

42.9

24.0

31.6

0

10

20

30

40

50

60

70

80

Percent

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Note: Due to low precision, estimates for American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, and Asian

full-time workers with past month illicit drug use are not shown. Estimates for Native Hawaiian or Other Pacific Islander full-time 

workers with no past month illicit drug use also are not shown.

White

Black or African American

American Indian or Alaska Native

Asian

Two or More Races

Hispanic or Latino

White

Black or African American

American Indian or Alaska Native

Asian

Two or More Races

Hispanic or Latino
50 

Figure 5.5 Workplace Tests during Hiring Process among Full-Time Workers Aged 18 to 

64, by Gender and Past Month Illicit Drug Use: 2002-2004 Combined 

Figure 5.6 Workplace Tests during Hiring Process among Full-Time Workers Aged 18 to 

64, by Education and Past Month Illicit Drug Use: 2002-2004 Combined 

32.7

47.2

30.2

39.7

0

10

20

30

40

50

Male

Female

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent

32.7

47.2

30.2

39.7

0

10

20

30

40

50

Male

Female

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent

31.5

43.9

35.8

49.8

33.7

46.8

23.7

35.7

0

10

20

30

40

50

Less Than High School

High School Graduate

Some College

College Graduate

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent

31.5

43.9

35.8

49.8

33.7

46.8

23.7

35.7

0

10

20

30

40

50

Less Than High School

High School Graduate

Some College

College Graduate

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent
51 

Figure 5.7 Workplace Tests during Hiring Process among Full-Time Workers Aged 18 to 

64, by County Type and Past Month Illicit Drug Use: 2002-2004 Combined 

Note: Due to low precision, estimates for Noncore Adjacent, No Town and Noncore Rural, Not Adjacent among 

full-time workers with past month illicit drug use are not shown. 

Figure 5.8 Workplace Tests during Hiring Process among Full-Time Workers Aged 18 to 

64, by Age Group and Past Month Heavy Alcohol Use: 2002-2004 Combined 

! Among workers aged 18 to 34, past month heavy alcohol use was associated with a lower 

likelihood of working for an employer who conducted prehire drug or alcohol testing in 

comparison with their same-age peers who did not report past month heavy alcohol use 

(Figure 5.8). 

42.6

46.4 45.5

43.4

38.8

41.4

31.5 32.0

34.1 33.4

0

10

20

30

40

50

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent

Large MSA

Small MSA

MiSA

Noncore Adjacent with Town

Noncore Adjacent, No Town

Noncore Rural, Not Adjacent

42.6

46.4 45.5

43.4

38.8

41.4

31.5 32.0

34.1 33.4

0

10

20

30

40

50

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent

Large MSA

Small MSA

MiSA

Noncore Adjacent with Town

Noncore Adjacent, No Town

Noncore Rural, Not Adjacent

Large MSA

Small MSA

MiSA

Noncore Adjacent with Town

Noncore Adjacent, No Town

Noncore Rural, Not Adjacent

34.4

39.9 40.4

45.0 44.8 44.7

46.4

40.5

0

10

20

30

40

50

18-25

26-34

35-49

50-64

Past Month Heavy Alcohol Use No Past Month Heavy Alcohol Use

Percent

34.4

39.9 40.4

45.0 44.8 44.7

46.4

40.5

0

10

20

30

40

50

18-25

26-34

35-49

50-64

Past Month Heavy Alcohol Use No Past Month Heavy Alcohol Use

Percent
52 

! Females were less likely than males to report working in an employment setting that 

conducted prehire drug or alcohol testing for both heavy alcohol users and non-heavy 

alcohol users. An estimated 33.1 percent of females who reported past month heavy 

alcohol use reported working in a prehire drug and/or alcohol testing environment, 

compared with nearly half of males who did so (43.5 percent). The pattern was similar 

among males and females who did not report past month heavy alcohol use (Table 5.6). 

! There were no significant differences by race/ethnicity in the likelihood of working in a 

prehire-testing employment environment between those who reported past month heavy 

alcohol use and those who did not (Tables 5.5 and 5.6). 

! Individuals with the lowest family incomes of $20,000 or less, individuals with incomes of 

$20,000 to $49,999, and individuals with the highest family incomes of $75,000 or more 

who were current heavy alcohol users were less likely to report working in a prehire-testing 

environment than nonusers in the same income brackets (30.8 vs. 36.9 percent of lowest 

family incomes, 42.5 vs. 44.1 of incomes of $20,000 to $49,999, and 40.7 vs. 42.0 percent 

of highest family incomes) (Table 5.7). 

! For all categories of establishment size, current illicit drug users were less likely than 

nonusers to report working for employers who conducted prehire drug or alcohol tests: 15.2 

versus 19.4 percent for establishments with fewer than 10 employees, 21.2 versus 35.0 

percent for 10 to 24 employees, 34.4 versus 44.9 percent for 25 to 99 employees, 55.9 

versus 62.0 percent for 100 to 499 employees, and 61.7 versus 71.2 percent for 500 or more 

employees. However, there was no difference for current heavy alcohol users (Figure 5.9). 

Figure 5.9 Workplace Tests during Hiring Process among Full-Time Workers Aged 18 

to 64, by Establishment Size and Past Month Illicit Drug or Alcohol Use: 

2002-2004 Combined 

15.2

19.4 18.2 19.1

21.2

35.0

32.0

34.4 33.8

44.9 46.6

43.8

55.9

62.0

64.1

61.7 61.4

71.2 70.2 70.6

0

20

40

60

80

Less Than 10 Employees

10-24 Employees

25-99 Employees

100-499 Emplolyees

500 or More Employees

Past Month Heavy 

Alcohol Use

Past Month Illicit 

Drug Use

Percent

No Past Month Illicit 

Drug Use

No Past Month 

Heavy Alcohol Use

15.2

19.4 18.2 19.1

21.2

35.0

32.0

34.4 33.8

44.9 46.6

43.8

55.9

62.0

64.1

61.7 61.4

71.2 70.2 70.6

0

20

40

60

80

Less Than 10 Employees

10-24 Employees

25-99 Employees

100-499 Emplolyees

500 or More Employees

Past Month Heavy 

Alcohol Use

Past Month Illicit 

Drug Use

Percent

No Past Month Illicit 

Drug Use

No Past Month 

Heavy Alcohol Use
53 

5.3. Random-Testing Programs among Full-Time Workers 

! A total of 29.6 percent, or 32 million, of full-time workers in the United States, reported 

random drug testing in their current employment setting during the study period. The 

youngest workers (18 to 25 years) were less likely than all other age groups to report 

working for an employer who conducted random drug testing (27.3 vs. 29.6 percent of 26- 

to 34-year-olds, 30.6 percent of 35- to 49-year-olds, and 29.1 percent of 50- to 64-yearolds) (Table 5.1). 

! Nearly 21 million male workers reported that they were aware of random drug testing for 

illicit drugs or alcohol in their workplace, while 11.3 million females reported that they 

knew of random drug testing. Proportionately, more males reported random drug testing 

than females (33.0 vs. 24.9 percent) (Table 5.1). 

! There were differences in the prevalence of random drug testing reported by race/ethnicity. 

Among white adults, 28.3 percent reported random drug testing in the workplace. While 

this was comparable with the proportion of Hispanic workers reporting random testing 

(28.7 percent), it was significantly less than the proportion of black and American Indian or 

Alaska Native workers (41.9 and 48.0 percent, respectively). Only 17.4 percent of Asian 

workers reported random drug testing in their current place of employment (Table 5.1). 

! An estimated 32.9 percent of workers with less than a high school diploma reported 

random testing in their current place of employment, while 35.0 percent of high school 

graduates and 32.1 percent of those with some college reported working for employers who 

tested for illicit drugs or alcohol on a random basis. College graduates were the least likely 

to report random drug testing compared with all other levels of educational attainment 

(20.4 percent) (Table 5.2). 

! Among workers, residents of the South were most likely to report working in an 

employment setting with random testing for illicit drug or alcohol use: 36.7 percent 

compared with 20.4 percent in the Northeast, 27.9 percent in the Midwest, and 27.3 percent 

in the West (Table 5.2). 

! Workers in the transportation and material-moving (62.9 percent) and protective service 

(61.8 percent) occupational categories were the most likely to report working for 

employers who conducted random testing. Workers in legal occupations and arts, design, 

entertainment, sports, and media occupational categories were the least likely to report 

working in settings in which employees were tested for illicit drug or alcohol use on a 

random basis (Figure 5.10). 

! There were significant county type differences in the likelihood of reporting a "randomtesting" work environment. Residents of large MSAs were the least likely to report random 

testing (26.5 percent). The proportion of workers who reported random drug testing in their 

place of employment ranged from 26.5 to 37.7 percent. An estimated 36.8 percent of the 

most rural workers (noncore, nonadjacent residents) reported random drug testing in their 

work setting (Figure 5.11). 
54 

Figure 5.10 Workplace Tests Employees for Drug or Alcohol Use on a Random Basis 

among Full-Time Workers Aged 18 to 64, by Major Occupational Categories: 

2002-2004 Combined 

Figure 5.11 Workplace Tests on a Random Basis among Full-Time Workers Aged 18 to 

64, by County Type: 2002-2004 Combined 

9.9

10.4

12.1

15.6

16.8

18.7

18.8

20.0

20.6

21.8

24.0

25.2

26.7

29.5

30.9

31.9

35.1

40.9

42.0

61.8

62.9

0 10 20 30 40 50 60 70

Percentage Workplace Tests Employees on a Random Basis 

Major Occupational Categories 

Transportation and Material-Moving

Protective Service

Installation, Maintenance, and Repair

Production Occupations

Engineering, Architecture, and Surveyors

Construction and Extraction

Healthcare Practitioners and Technical Occupations

Office and Administrative Support

Building and Grounds Cleaning and Maintenance

Management

Life, Physical, and Social Science 

Sales and Related Occupations

Food Preparation and Serving Related

Farming, Fishing, and Forestry

Community and Social Services 

Financial Occupations 

Mathematical and Computer Scientists

Personal Care and Service

Education, Training, and Library

Legal Occupations

Arts, Design, Entertainment, Sports, and Media 9.9

10.4

12.1

15.6

16.8

18.7

18.8

20.0

20.6

21.8

24.0

25.2

26.7

29.5

30.9

31.9

35.1

40.9

42.0

61.8

62.9

0 10 20 30 40 50 60 70

Percentage Workplace Tests Employees on a Random Basis 

Major Occupational Categories 

Transportation and Material-Moving

Protective Service

Installation, Maintenance, and Repair

Production Occupations

Engineering, Architecture, and Surveyors

Construction and Extraction

Healthcare Practitioners and Technical Occupations

Office and Administrative Support

Building and Grounds Cleaning and Maintenance

Management

Life, Physical, and Social Science 

Sales and Related Occupations

Food Preparation and Serving Related

Farming, Fishing, and Forestry

Community and Social Services 

Financial Occupations 

Mathematical and Computer Scientists

Personal Care and Service

Education, Training, and Library

Legal Occupations

Arts, Design, Entertainment, Sports, and Media

26.5

32.3

35.1 35.2

37.7 36.8

0

10

20

30

40

Large

MSA

Noncore 

Adjacent with 

Town

Percent

Small

MSA

MiSA Noncore 

Adjacent, 

No Town

Noncore 

Rural, Not 

Adjacent

26.5

32.3

35.1 35.2

37.7 36.8

0

10

20

30

40

Large

MSA

Noncore 

Adjacent with 

Town

Percent

Small

MSA

MiSA Noncore 

Adjacent, 

No Town

Noncore 

Rural, Not 

Adjacent
55 

! Among workers, the relationship between family income and reported employment with an 

employer who tested for illicit drug or alcohol use among workers with no current illicit 

drug use on a random basis was not linear. The highest category of family income, $75,000 

or more, was associated with a lower risk of working for an employer who conducted 

random drug testing (27.5 percent), compared with family incomes of $20,000 to $49,999 

(31.9 percent) and $50,000 to $74,999 (33.2 percent). Workers with family incomes that 

were less than $20,000 were somewhat less likely to report random testing (28.3 percent) 

than higher income groups (Figure 5.12 and Table 5.4). 

! There was a steady increase in the likelihood of working in a random-testing environment 

as the size of an establishment increased. An estimated 14.5 percent of employees who 

worked in an establishment with fewer than 10 employees reported that their employer 

conducted random drug and alcohol testing. This is a significantly smaller proportion of 

workers who reported testing than was observed in other establishment sizes. Among 

employees who worked for the largest establishments of 500 or more employees, 42.6 

percent reported random drug testing (Table 5.12). 

Figure 5.12 Workplace Tests on a Random Basis among Full-Time Workers Aged 18 to 64, 

by Family Income and Past Month Illicit Drug Use: 2002-2004 Combined 

5.4. Random Testing among Full-Time Workers, by Substance Use and 

Dependence and Abuse 

! Current illicit drug users were less likely to report working for employers who conducted 

random drug or alcohol tests than were nondrug users. For 18- to 25-year-olds, 19.7 

percent of illicit drug users reported that they worked in a random-testing environment 

compared with 29.1 percent of nonusers. The relationship was consistent for all age groups: 

20.2

28.3

24.4

31.9

19.4

33.2

16.3

27.5

0

10

20

30

40 Less Than $20,000

$20,000-49,999

$50,000-74,999

$75,000 or More

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent

20.2

28.3

24.4

31.9

19.4

33.2

16.3

27.5

0

10

20

30

40 Less Than $20,000

$20,000-49,999

$50,000-74,999

$75,000 or More

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent
56 

20.0 versus 30.8 percent of 26- to 34-year-olds, 22.6 versus 31.2 percent of 35- to 49-yearolds, and 20.4 versus 29.3 percent of 50- to 64-year-olds (Figure 5.13 and Table 5.3). 

Figure 5.13 Workplace Tests on a Random Basis among Full-Time Workers Aged 18 to 

64, by Age Group and Past Month Illicit Drug Use: 2002-2004 Combined 

! Among both male and female full-time workers, past month illicit drug users were less 

likely to report working for an employer with a random drug-testing program compared 

with those who had not used illicit drugs in the past month. An estimated 18.7 percent of 

females and 21.9 percent of males with past month illicit drug use reported working in a 

random-testing employment setting, compared with 25.3 percent of females and 34.2 

percent of males who were not past month users of illicit drugs (Table 5.3). 

! Similarly, past month illicit drug use was associated with a reduced likelihood of working 

for an employer with a random-testing policy across racial/ethnic groups. An estimated 

17.8 percent of Hispanic workers and 21.2 percent of non-Hispanic workers who were past 

month illicit drug users reported working for an employer who conducted random testing, 

while 29.5 percent of Hispanic and 30.6 percent of non-Hispanic workers who did not use 

illicit drugs in the past month reported working for an employer who tested randomly. 

Black workers with past month illicit drug use were significantly more likely to report 

working in a setting with random testing than white past month illicit drug users (29.4 vs. 

20.0 percent, respectively). A similar difference existed between black and white workers 

who reported no past month illicit drug use (43.0 vs. 29.1 percent, respectively) (Figure 

5.14 and Table 5.3). 

19.7

29.1

20.0

30.8

22.6

31.2

20.4

29.3

0

5

10

15

20

25

30

35

18-25

26-34

35-49

50-64

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent

19.7

29.1

20.0

30.8

22.6

31.2

20.4

29.3

0

5

10

15

20

25

30

35

18-25

26-34

35-49

50-64

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent
57 

Figure 5.14 Workplace Tests on a Random Basis among Full-Time Workers Aged 18 to 64, 

by Hispanic or Latino Origin and Race and Past Month Illicit Drug Use: 2002-

2004 Combined 

! For all levels of education, current illicit drug users were less likely than nonusers to report 

working for employers who conducted drug or alcohol tests on a random basis: 24.0 versus 

34.0 percent for those with less than a high school diploma, 23.7 versus 36.1 percent for 

high school graduates, 20.8 versus 33.2 percent for those with some college, and 13.9 

versus 20.8 percent for college graduates (Figure 5.15 and Table 5.4). 

Figure 5.15 Workplace Tests on a Random Basis among Full-Time Workers Aged 18 to 

64, by Education and Past Month Illicit Drug Use: 2002-2004 Combined 

20.0

29.4 29.1

43.0

17.8

29.5

0

10

20

30

40

50 White

Black or African American

Hispanic or Latino

Percent

Past Month Illicit Drug Use No Past Month Illicit Drug Use

20.0

29.4 29.1

43.0

17.8

29.5

0

10

20

30

40

50 White

Black or African American

Hispanic or Latino

Percent

Past Month Illicit Drug Use No Past Month Illicit Drug Use

24.0

34.0

23.7

36.1

20.8

33.2

13.9

20.8

0

10

20

30

40

50

Less Than High School

High School Graduate

Some College

College Graduate

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent

24.0

34.0

23.7

36.1

20.8

33.2

13.9

20.8

0

10

20

30

40

50

Less Than High School

High School Graduate

Some College

College Graduate

Past Month Illicit Drug Use No Past Month Illicit Drug Use

Percent
58 

! The association between reported employment in a setting that tests for illicit drug or 

alcohol use on a random basis and past month marijuana use among full-time workers 

mirrored findings reported for past month illicit drug use. Within each demographic group, 

a smaller proportion of individuals with past month marijuana use reported working for 

employers who conducted random testing compared with workers who did not report 

current use of marijuana (Tables 5.8 through 5.11). There was no relationship between 

heavy alcohol use and the likelihood of working for a random-testing employer. 

! Findings associated with illicit drug or alcohol dependence or abuse were consistent with 

those observed for current illicit drug and heavy alcohol use. Individuals who met criteria 

for illicit drug dependence or abuse were less likely to report working for an employer with 

a random drug-testing policy compared with individuals who did not meet dependence or 

abuse criteria (Figure 5.16). 

! Alcohol disorders were associated with a lower likelihood of working in a random-testing 

environment among the youngest adult workers––those who did not complete high school 

and those who resided in large MSAs (Figure 5.16). 

Figure 5.16 Workplace Tests during Hiring Process or on a Random Basis among FullTime Workers Aged 18 to 64, by Past Year Illicit Drug or Alcohol 

Dependence or Abuse: 2002-2004 Combined 

! For all categories of establishment size, current illicit drug users were less likely than 

nonusers to report working for employers who conducted random drug or alcohol tests 

(less than 10 employees: 11.4 vs. 14.8 percent; 10 to 24 employees: 16.7 vs. 27.2 percent; 

25 to 99 employees: 24.5 vs. 33.1 percent; 100 to 499 employees: 33.7 vs. 40.7 percent; 

and 500 or more employees: 30.2 vs. 43.4 percent). However, there was no difference for 

current heavy alcohol users (Figure 5.17). 

34.6

43.2

41.4

43.1

22.6

29.8

28.1

29.8

0

10

20

30

40

50 During Hiring Process

Random Basis

Past Year Alcohol 

Dependence or Abuse

Past Year Illicit Drug 

Dependence or Abuse

Percent

No Past Year Illicit Drug 

Dependence or Abuse

No Past Year Alcohol 

Dependence or Abuse

34.6

43.2

41.4

43.1

22.6

29.8

28.1

29.8

0

10

20

30

40

50 During Hiring Process

Random Basis

Past Year Alcohol 

Dependence or Abuse

Past Year Illicit Drug 

Dependence or Abuse

Percent

No Past Year Illicit Drug 

Dependence or Abuse

No Past Year Alcohol 

Dependence or Abuse
59 

Figure 5.17 Workplace Tests on a Random Basis among Full-Time Workers Aged 18 to 

64, by Establishment Size and Past Month Illicit Drug or Alcohol Use: 2002-

2004 Combined 

5.5. Summary 

This chapter addresses the question "Are current substance users less likely to work for 

employers who conduct prehire or random drug testing?" It is important to understand that these 

data cannot inform a discussion about the cause-and-effect nature of drug testing in the 

workplace. Respondents are interviewed at one point in time and are not asked to provide 

information about testing in relation to job tenure, their own personal testing experience, or 

testing in previous employment settings. It also is possible that respondents may not be clear 

about differences in testing programs. For example, there may be some confusion about random 

testing in contrast to cause-based testing in response to a specific event or employee behavior. 

While there is strong evidence here that individuals with current or long-term illicit substance 

use problems are less likely to report working in an employment setting with either prehire or 

random drug testing, it cannot be said that drug testing caused the worker to work in one 

environment or another or that testing reduced the use patterns of an existing employee. 

The relationship of drug testing to substance use was impacted in some of these analyses 

by characteristics of the respondent or the respondent's reported employment setting. 

Specifically, race/ethnicity appeared to influence the relationship between use status and working 

in a setting with a drug-testing program. Among current illicit drug users, non-Hispanic black 

workers were more likely to report working in a prehire- or random-testing environment when 

compared with non-Hispanic white workers. This may be an effect of other characteristics such 

as differences in occupational or educational opportunities. There also were differences among 

11.4

14.8 14.9 14.4

16.7

27.2 26.1 26.2

24.5

33.1

36.5

32.0

33.7

40.7

42.8

40.0

30.2

43.4

41.3

42.7

0

10

20

30

40

50

Less Than 10 Employees

10-24 Employees

25-99 Employees

100-499 Emplolyees

500 or More Employees

Past Month Heavy 

Alcohol Use

Past Month Illicit 

Drug Use

Percent

No Past Month Illicit 

Drug Use

No Past Month 

Heavy Alcohol Use

11.4

14.8 14.9 14.4

16.7

27.2 26.1 26.2

24.5

33.1

36.5

32.0

33.7

40.7

42.8

40.0

30.2

43.4

41.3

42.7

0

10

20

30

40

50

Less Than 10 Employees

10-24 Employees

25-99 Employees

100-499 Emplolyees

500 or More Employees

Past Month Heavy 

Alcohol Use

Past Month Illicit 

Drug Use

Percent

No Past Month Illicit 

Drug Use

No Past Month 

Heavy Alcohol Use
60 

county types. This may reflect differences in employment options in cities compared with towns 

and rural places. 

Policy makers and those who work in substance abuse programs will benefit from 

ongoing research in this area. It will be important to clarify an understanding about whether these 

programs keep substance users out of the workplace or whether these programs serve as a tool to 

route those who use illicit substances into healthier and more productive work lives. It also will 

be important to understand more clearly how demographic characteristics impact the effect of 

testing programs. As was noted in the earlier report by the Institute of Medicine (Normand, 

Lempert, & O'Brien, 1994), more could be learned by combining survey data, such as the 

NSDUH data used in this report, with drug test results collected in work settings. 
61 

6. Workplace Behaviors and Attitudes 

toward Drug Testing 

This chapter examines the work-related behaviors and attitudes toward drug testing of 

full-time workers in order to describe the potential impact of substance use on worker 

productivity and the role of drug testing in the workplace. Previous chapters in this report have 

provided estimates of the prevalence of illicit drug use, heavy alcohol use, and illicit drug and 

alcohol dependence or abuse among full-time workers aged 18 to 64 in the United States. The 

report also has detailed the proportion of workers in the United States reporting the presence of 

programs designed to identify and assist workers with substance use issues. In this final chapter, 

several related matters are presented: 

! Workplace behaviors in association with substance use 

! Attitudes held by full-time workers about their willingness to work for an employer with a 

drug-testing program 

! Multivariate analysis of employer drug-testing and the willingness of adults to work for an 

employer with a drug-testing program, by substance use, dependence, and abuse 

6.1. Workplace Behaviors among Full-Time Workers 

The National Survey on Drug Use and Health (NSDUH) does not collect direct measures 

of worker productivity or on-the-job safety. However, three work-related measures that are 

related to productivity and safety are available: 

! Worked for three or more employers in the past year 

! Missed 2 or more days in the past month due to illness or injury 

! Skipped 1 or more days of work in the past month 

All of these indicators were significantly associated with current illicit drug use, past year 

illicit drug dependence or abuse, and past year alcohol dependence or abuse. Two of the three 

indicators (working for three or more employers in the past year and skipping 1 or more days of 

work in the past month) also were positively and significantly associated with past month heavy 

alcohol use. 

! Among full-time workers who reported past month illicit drug use, 12.3 percent reported 

working for three or more employers in the past year, compared with 5.1 percent of 

workers without past month drug use (Figure 6.1). 

! Workers with past month illicit drug use were more likely to report missing 2 or more 

workdays in the past month due to illness or injury when compared with workers without 

current use (16.4 vs. 11.0 percent) (Figure 6.1). 
62 

! An estimated 16.3 percent of workers who used illicit drugs in the past month reported 

skipping 1 or more days of work in the past month (vs. 8.2 percent of workers who did not 

use an illicit drug during the past month) (Figure 6.1). 

! The pattern for past month marijuana use mirrored that found among all past month illicit 

drug users (Figure 6.1). 

Figure 6.1 Workplace Behaviors among Full-Time Workers Aged 18 to 64, by Past 

Month Substance Use: 2002-2004 Combined 

! Among workers who reported past month heavy alcohol use, 8.9 percent reported working 

for three or more employers during the past year versus 5.4 percent of those who did not 

report past month heavy alcohol use (Figure 6.2). 

! An estimated 13.6 percent of past month heavy alcohol users employed full time reported 

skipping work 1 or more days during the past month (vs. 8.4 percent of workers with no 

past month heavy alcohol use) (Figure 6.2). 

! Past month heavy alcohol use was not significantly linked to missing 2 or more days of 

work in the past month due to illness or injury (Figure 6.2). 

! The patterns of work outcomes related to dependence on or abuse of illicit drugs or alcohol 

were generally similar to those found among current users, although the magnitude of the 

relationship was greater for dependence or abuse. All three outcomes were significantly 

related to dependence or abuse. Thus, the more chronic conditions were associated with a 

greater risk for absenteeism and frequent job changes during the past year than for 

substance use per se. 

12.3

5.1

13.1

5.2

16.4

11.0

16.1

11.2

16.3

16.9

8.2 8.3

0

5

10

15

20

Worked for 3 or More Employers in the Past Year

Missed 2 or More Days of Work in the Past Month Due to Illness or Injury

Skipped 1 or More Days of Work in the Past Month

Past Month Illicit 

Drug Use

No Past Month 

Illicit Drug Use

Percent

Past Month 

Marijuana Use

No Past Month 

Marijuana Use

12.3

5.1

13.1

5.2

16.4

11.0

16.1

11.2

16.3

16.9

8.2 8.3

0

5

10

15

20

Worked for 3 or More Employers in the Past Year

Missed 2 or More Days of Work in the Past Month Due to Illness or Injury

Skipped 1 or More Days of Work in the Past Month

Past Month Illicit 

Drug Use

No Past Month 

Illicit Drug Use

Percent

Past Month 

Marijuana Use

No Past Month 

Marijuana Use
63 

Figure 6.2 Workplace Behaviors among Full-Time Workers Aged 18 to 64, by Past 

Month Heavy Alcohol Use: 2002-2004 Combined 

6.2. Workplace Attitudes toward Drug or Alcohol Testing among Full-Time 

Workers 

NSDUH respondents who were employed at the time of the interview were asked the 

following questions: 

! Would you be more or less likely to work for an employer who tests its employees for drug 

use as part of the hiring process? Would you say more likely, less likely, or it would make 

no difference to you? 

! Would you be more or less likely to work for an employer who tests its employees for drug 

or alcohol use on a random basis? Would you say more likely, less likely, or it would make 

no difference to you? 

The responses to these questions were examined for full-time workers aged 18 to 64 to determine 

if the presence of a prehire or random drug-testing program would deter users from seeking 

employment at that establishment. 

8.9

5.4

11.7 11.5

13.6

8.4

0

3

6

9

12

15

Worked for 3 or More Employers in the Past Year

Missed 2 or More Days of Work in the Past Month Due to Illness or Injury

Skipped 1 or More Days of Work in the Past Month

Past Month Heavy Alcohol Use No Past Month Heavy Alcohol Use

Percent

8.9

5.4

11.7 11.5

13.6

8.4

0

3

6

9

12

15

Worked for 3 or More Employers in the Past Year

Missed 2 or More Days of Work in the Past Month Due to Illness or Injury

Skipped 1 or More Days of Work in the Past Month

Past Month Heavy Alcohol Use No Past Month Heavy Alcohol Use

Percent
64 

! Among workers in the United States, 52.5 million (46.0 percent) indicated that they would 

be more likely to work for an employer who tests before hiring, and an additional 56.2 

million (49.1 percent) workers reported that prehire testing would not influence their 

decision to work for an employer. Only 5.6 million (4.9 percent) workers indicated that 

they would be less likely to work for an employer who conducts prehire drug testing 

(Tables 6.1 and 6.2 in Appendix E). 

! An estimated 45.5 million (39.8 percent) workers reported that they would be more likely 

to work for an employer who tests randomly for drug or alcohol use, while 10.0 million 

(8.7 percent) workers reported that they would be less likely. An estimated 58.8 million 

(51.4 percent) workers indicated that random testing would not influence their decision to 

work for an employer (Tables 6.1 and 6.2). 

! Workers reporting current illicit drug use indicated that they would be less likely to work 

for employers who conduct prehire and random testing than those workers who did not 

report current illicit drug use (Figure 6.3 and Tables 6.3 through 6.14). 

Figure 6.3 Employees' Feelings toward Working for Employers Who Test during Hiring 

Process among Full-Time Workers Aged 18 to 64, by Past Month Illicit Drug 

Use: 2002-2004 Combined 

! Workers who reported past month illicit drug use indicated that they would be less likely to 

work for employers who conduct random testing. An estimated 29.1 percent of workers 

with past month illicit drug use reported that they would be less likely to work for 

employers who conduct drug testing randomly, while only 6.9 percent of workers who did 

not report past month illicit drug use selected this response category (Figure 6.4). 

20.6

48.2

18.2

3.7

61.2

48.1

0

10

20

30

40

50

60

70

More Likely

Less Likely

Would Make No Difference

Percent

Past Month Illicit Drug Use No Past Month Illicit Drug Use

20.6

48.2

18.2

3.7

61.2

48.1

0

10

20

30

40

50

60

70

More Likely

Less Likely

Would Make No Difference

Percent

Past Month Illicit Drug Use No Past Month Illicit Drug Use
65 

! These findings also held for workers who were heavy alcohol users or who were dependent 

on or abused illicit drugs or alcohol (Table 6.9). 

Figure 6.4 Employees' Feelings toward Working for Employers Who Test on a Random 

Basis among Full-Time Workers Aged 18 to 64, by Past Month Illicit Drug 

Use: 2002-2004 Combined 

6.3. Multivariate Analysis of Drug Testing in Current Employment Setting 

and Willingness to Work for an Employer Who Tests for Drugs 

It is not possible from the analyses presented in this report to determine whether drug 

testing deters those who would be illicit drug users from using drugs. However, evidence 

presented in previous chapters confirms that those who use illicit drugs are less likely to report 

working for employers who have a drug-testing program compared with workers who do not use 

illicit drugs. In an effort to clarify some of the relationships reported in previous chapters, 

multivariate analyses were conducted. 

Multinomial logit models were used to estimate the odds that workers would report that 

they were "more likely" or "less likely" to work for an employer with a prehire or random drugtesting program compared with the reference category of "it would make no difference." In the 

multivariate models presented here, full-time workers were categorized into four recency of 

illicit drug use categories: 

! Never used an illicit drug 

! Used illicit drug in lifetime but not in the past year 

15.9

42.0

29.1

6.9

55.0 54.1

0

10

20

30

40

50

60

More Likely

Less Likely

Would Make No Difference

Percent

Past Month Illicit Drug Use No Past Month Illicit Drug Use

15.9

42.0

29.1

6.9

55.0 54.1

0

10

20

30

40

50

60

More Likely

Less Likely

Would Make No Difference

Percent

Past Month Illicit Drug Use No Past Month Illicit Drug Use
66 

! Used illicit drug in lifetime and in the past year but not in the past month 

! Used illicit drug in the past month 

Workers in the last three categories were compared with those individuals who never 

used an illicit drug. It was expected that there would be an increased probability of responding 

"less likely" and a decreased probability of responding "more likely" because drug use was more 

recent in time relative to the survey. These models were adjusted for age, gender, race/ethnicity, 

educational attainment, family income, region, and county type (metropolitan statistical area). 

All workers with information on their willingness to work for employers with testing practices 

were included in these analyses. 

In the multinomial logit analysis for prehire drug testing, there was a significantly higher 

probability of membership in the "less likely" group in comparison with the "makes no 

difference" group for all categories of drug user compared with those who had never used, and 

the odds of reporting "less likely" were higher among "more recent" than "less recent" drug 

users. Similarly, for "more recent" versus "less recent" drug users, there was a reduced 

probability of membership in the "more likely" group compared with the "would make no 

difference" group. A similar pattern was observed in models for random drug or alcohol testing 

(Tables 6-A, 6.15, and 6.16). 

The potential effect of drug testing was further evaluated using three logistic regression 

analyses. The dependent variables for the three models were (1) working for an employer with a 

drug- or alcohol-testing program, (2) working for an employer with a prehire-testing program, 

and (3) working for an employer with a random drug- or alcohol-testing program. The 

independent variables were the same as the multinomial models. The first model, presence of a 

drug- or alcohol-testing program, included all full-time workers with valid responses to the 

questions: 

! Does your workplace ever test its employees for alcohol use? 

! Does your workplace ever test its employees for drug use? 

For inclusion in the other two logistic models, individuals also must have given valid 

responses to two follow-up questions in the following order: 

! Does your workplace test its employees for drug or alcohol use as part of the hiring 

process? 

! Does your workplace test its employees for drug or alcohol use on a random basis? 
67 

Table 6-A Results of Multinomial Logit Model of Willingness to Work for Employers Who Test for Drug or 

Alcohol Use during Hiring Process or on a Random Basis among Full-Time Workers Aged 18 to 

64: 2002-2004 

Willingness to Work for Employer Who Tests for 

Drug or Alcohol Use during Hiring Process 

More Likely vs. Would Make 

No Difference 

Less Likely vs. Would Make 

No Difference 

Characteristic Odds Ratio CI (95%) Odds Ratio CI (95%) 

Illicit Drug Use1 

 No Lifetime Use -- -- -- -- 

 Lifetime Use, No Past Year Use 0.73b 0.69-0.77 1.24a 1.05-1.47 

 Past Year Use, No Past Month Use 0.45b 0.41-0.49 1.91b 1.51-2.40 

 Past Month Use 0.28b 0.26-0.31 5.18b 4.40-6.11 

Willingness to Work for Employer Who Tests for 

Drug or Alcohol Use on a Random Basis

More Likely vs. Would Make 

No Difference 

Less Likely vs. Would Make 

No Difference 

Characteristic Odds Ratio CI (95%) Odds Ratio CI (95%) 

Illicit Drug Use1 

 No Lifetime Use -- -- -- -- 

 Lifetime Use, No Past Year Use 0.71b 0.67-0.75 1.32b 1.19-1.48 

 Past Year Use, No Past Month Use 0.44b 0.40-0.49 2.30b 1.95-2.72 

 Past Month Use 0.29b 0.26-0.32 5.61b 4.96-6.34 

CI = confidence interval. 

-- Reference level. 

NOTE: In addition to recency of illicit drug use, measures of age group, gender, Hispanic origin and race, education, family 

income, geographic region, and county type were included in these models as covariates. Resulting odds ratios and 

confidence intervals for these additional controls can be found in Tables 6.15 and 6.16 in Appendix E. a Statistically significant at the 0.05 level. 

b Statistically significant at the 0.01 level. 

1

 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type 

psychotherapeutics used nonmedically. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.

In each model, there was a decreased probability of working for an employer with a 

testing program among those who had used in the past year or past month compared with those 

who had never used illicit drugs. Compared with workers with no lifetime use of illicit drugs, 

there was a decreased likelihood of working for an employer who tested for drug or alcohol use. 

There was not a significant difference between no lifetime use and lifetime but no past year use. 

Compared with workers with no lifetime use, there was a significant decrease in the probability 

of working for an employer with a prehire-testing program among past year–no past month and 

past month illicit drug users. Findings were similar for random drug testing (Tables 6-B and 

6.17). 
68 

Table 6-B Results of Logistic Models of Employers Who Test for Drug or Alcohol Use among Full-Time 

Workers Aged 18 to 64: 2002-2004 

Employer Tests for 

Drug or Alcohol Use 

Employer Tests for 

Drug or Alcohol Use 

during Hiring Process 

Employer Tests for 

Drug or Alcohol Use 

on a Random Basis 

Characteristic Odds Ratio CI (95%) Odds Ratio CI (95%) Odds Ratio CI (95%) 

Illicit Drug Use1 

 No Lifetime Use -- -- -- -- -- -- 

 Lifetime Use, No Past Year Use 1.02 0.97-1.08 0.98 0.93-1.04 1.00 0.94-1.06 

 Past Year Use, No Past Month Use 0.81b 0.74-0.89 0.77b 0.70-0.85 0.80b 0.71-0.89 

 Past Month Use 0.62b 0.57-0.68 0.55b 0.51-0.60 0.55b 0.50-0.60 

CI = confidence interval. 

-- Reference level. 

NOTE: In addition to recency of illicit drug use, measures of age group, gender, Hispanic origin and race, education, family 

income, geographic region, and county type were included in these models as covariates. Resulting odds ratios and 

confidence intervals for these additional controls can be found in Table 6.17 in Appendix E. a Statistically significant at the 0.05 level. 

b Statistically significant at the 0.01 level. 

1

 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type 

psychotherapeutics used nonmedically. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 

Generally, these models provide evidence that suggests that drug testing serves as a 

deterrent to employment in a drug-testing environment by those who are past month or past year 

illicit drug users. These findings demonstrate that fewer self-reported current and/or past year 

illicit drug users work in settings with a workplace drug-testing program. However, due to 

limitations of the data, it cannot be determined if the programs function to either: 

! deter illicit drug users from applying for work in employment settings with a testing 

program and instead choosing to work in settings with no drug-testing program, or 

! deter illicit drug users from continuing to use drugs once hired in a drug-testing 

employment setting. 

6.4. Summary 

Analysis of 2002–2004 NSDUH data provides evidence that workplace drug- and 

alcohol-testing programs are associated with a lower prevalence of current illicit drug use, heavy 

alcohol use, and dependence or abuse among workers. The evidence suggests that U.S. workers 

are generally willing to work in employment settings that have a drug-testing program in place. 

Random testing is clearly related to lower substance use than prehire-testing programs. The 

magnitude of this effect is not as large for alcohol use as it is for illicit drug use. 

Further research should be conducted to examine the mechanism for this deterrent effect. 

Additional data will need to be collected to assess whether those who use illicit drugs and engage 

in heavy alcohol use simply avoid applying for work and working in environments with a drugtesting program or whether those same workers stop use when faced with the potential for drug 

testing. This is an important question to answer when considering the overall prevalence of 

substance use in the workplace. Policy makers also should turn their attention to mechanisms for 

assessing the workforce impact of encouraging drug-testing programs in smaller establishments. 
69 

At this time, it appears that smaller employers may provide a "safe haven" for workers 

attempting to avoid drug testing. 

The evidence presented in this report confirms that current use of illicit drugs, current 

heavy alcohol use, past year dependence on or abuse of illicit drugs, and past year dependence on 

or abuse of alcohol are associated with negative work behaviors such as absenteeism and 

frequent job changes, although the magnitude of the association with alcohol is smaller than that 

found with illicit drugs. Additional data also should be collected to assess the direct effect of 

substance use on the job, particularly the risk for workplace illness and injury. 

Employers in certain industries also may be worthy of additional attention. Workers in 

food service settings and certain construction workers reported the highest prevalence of 

substance use issues. These workers also were among the least likely to report working in a 

setting with drug testing either randomly or during the prehire phase. Among food and beverage 

servers, for example, more than one in five workers reported past month use of an illicit drug. 

Further research will be required to gauge the utility of this industry- or occupation-specific 

approach. 
70 
71 

Appendix A: Description of the Survey 

A.1 Sample Design 

The sample designs for the 2002, 2003, and 2004 National Surveys on Drug Use and 

Health (NSDUHs)1 reflect a coordinated design for providing estimates for all 50 States plus the 

District of Columbia. The respondent universe is the civilian, noninstitutionalized population 

aged 12 years old or older residing within the United States and the District of Columbia. 

Persons excluded from the universe include active-duty military personnel, persons with no fixed 

household address (e.g., homeless and/or transient persons not in shelters), and residents of 

institutional group quarters, such as jails and hospitals. 

The coordinated design for 1999 through 2003 facilitated 50 percent overlap in first-stage 

units (area segments) between each 2 successive years. The 2004 NSDUH continued the 50 

percent overlap by retaining approximately half of the first-stage sampling units from the 2003 

survey. The remainder of the sample was drawn from the 1999 through 2003 reserve sample 

(i.e., area segments not used in previous years). Before selection, composite size measures2

 were 

adjusted to the 2000 census data.3 The application of a special probability sampling procedure 

initially developed by Keyfitz (1951) ensured that most of the overlap segments from 2003 were 

included in the 2004 sample. 

For the 50-State design, 8 States were designated as large sample States (California, 

Florida, Illinois, Michigan, New York, Ohio, Pennsylvania, and Texas) with samples large 

enough to support direct State estimates. In 2004, sample sizes in these States ranged from 3,575 

to 3,725. For the remaining 42 States and the District of Columbia, smaller, but adequate, 

samples were selected to support State estimates using small area estimation (SAE) techniques.4

Sample sizes in these States ranged from 828 to 934 in 2004. 

States were first stratified into a total of 900 field interviewer (FI) regions (48 regions in 

each large sample State and 12 regions in each small sample State). These regions were 

contiguous geographic areas designed to yield the same number of interviews on average. Within 

FI regions, adjacent census blocks were combined to form the first-stage sampling units, called 

area segments. A total of 96 segments per FI region were selected with probability proportional 

to population size to support the 5-year sample and any supplemental studies that the Substance 

Abuse and Mental Health Services Administration (SAMHSA) may choose to field.5

 Of these 

segments, 24 were designated for the coordinated 5-year sample, while the other 72 were 

 1

 Prior to 2002, the survey was known as the National Household Survey on Drug Abuse (NHSDA). 

2

 The composite size measure is an estimate of the population weighted by the sampling fraction in each 

age group. 3

 Composite size measures were originally formed using 1990 census data and adjusted to population 

counts from Claritas Incorporated (http://www.claritas.com). 4

 Small area estimation (SAE) is a hierarchical Bayes modeling technique used to make State-level 

estimates for approximately 20 substance-use-related measures. See the State Estimates of Substance Use from the 

2002-2003 National Surveys on Drug Use and Health (Wright & Sathe, 2004) for more details. 5

 For more details on the 5-year sample, see the sample design report in the 2003 NSDUH Methodological 

Resource Book (Bowman, Chromy, Hunter, Martin, & Odom, 2005b). 
72 

designated as "reserve" segments. It is from this reserve sample and the 2003 overlap sample that 

the 2004 NSDUH sample segments were selected. Eight sample segments per FI region were 

fielded during the 2004 survey year. 

These sampled segments were allocated equally into four separate samples, one for each 

3-month period (calendar quarter) during the year, so that the survey was essentially continuous 

in the field. In each of these area segments, a listing of all addresses was made, from which a 

sample of 169,514 addresses was selected. Of the selected addresses, 142,612 were determined 

to be eligible sample units. In these sample units (which can be either households or units within 

group quarters), sample persons were randomly selected using an automated screening procedure 

programmed in a handheld computer carried by the interviewers. The number of sample units 

completing the screening was 130,130. Youths aged 12 to 17 years and young adults aged 18 to 

25 years were oversampled at this stage. Because of the large sample size, there was no need to 

oversample racial/ethnic groups, as was done on surveys prior to 1999. A total of 81,973 persons 

were selected nationwide. Consistent with previous surveys in this series, the final respondent 

sample of 67,760 persons was representative of the U.S. general population (since 1991, the 

civilian, noninstitutionalized population) aged 12 or older. In addition, State samples were 

representative of their respective State populations. More detailed information on the disposition 

of the national screening and interview sample can be found in Appendix B. Definitions of key 

terms are provided in Appendix C. 

The survey covers residents of households (living in houses/townhouses, apartments, 

condominiums, etc.), persons in noninstitutional group quarters (e.g., shelters, rooming/boarding 

houses, college dormitories, migratory workers' camps, halfway houses), and civilians living on 

military bases. Although the survey covers these types of units (they are given a nonzero 

probability of selection), sample sizes of most specific groups are too small to provide separate 

estimates. Persons excluded from the survey include homeless people who do not use shelters, 

active military personnel, and residents of institutional group quarters, such as correctional 

facilities, nursing homes, mental institutions, and long-term hospitals. More information on the 

sample design can be found in a 2004 NSDUH report by Bowman, Chromy, Hunter, and Martin 

(2005a) on the OAS website (http://www.oas.samhsa.gov/nhsda/methods.cfm#2k4). 

An additional stage of sampling occurred within the 2004 computer-assisted interviewing 

(CAI) questionnaire. Approximately 50 percent of adult respondents aged 18 or older were 

randomly assigned to receive the full module of serious psychological distress (SPD) questions. 

The remaining adults received a reduced number of SPD questions and a new set of questions on 

depression. These complementary samples are together referred to as the SPD "split sample," the 

full SPD module is referred to as "sample A," and the reduced SPD module is referred to as 

"sample B." 

The split sample was originally set up so that 20 percent of the adult respondents received 

the full module and 80 percent received the reduced module. When a preliminary analysis 

indicated that there may be a difference between the two samples, the selection algorithm was 

modified such that 60 percent received the full module and 40 percent received the reduced 

module in Quarters 2, 3, and 4. As a result, the sample was split half and half for the year. 
73 

A.2 Data Collection Methodology 

The data collection method used in NSDUH involves in-person interviews with sample 

persons, incorporating procedures that would be likely to increase respondents' cooperation and 

willingness to report honestly about their illicit drug use behavior. Confidentiality is stressed in 

all written and oral communications with potential respondents. Respondents' names are not 

collected with the data, and CAI methods, including audio computer-assisted self-interviewing 

(ACASI), are used to provide a private and confidential setting to complete the interview. 

Introductory letters are sent to sampled addresses, followed by an interviewer visit. A 5-

minute screening procedure using a handheld computer involves listing all household members 

along with their basic demographic data. The computer uses the demographic data in a 

preprogrammed selection algorithm to select zero to two sample person(s), depending on the 

composition of the household. This selection process is designed to provide the necessary sample 

sizes for the specified population age groupings. 

Interviewers immediately attempt to conduct the NSDUH interview with each selected 

person in the household. The interviewer requests the selected respondent to identify a private 

area in the home to conduct the interview away from other household members. The interview 

averages about an hour and includes a combination of CAPI (computer-assisted personal 

interviewing) and ACASI. The interview begins in CAPI mode with the FI reading the questions 

from the computer screen and entering the respondent's replies into the computer. The interview 

then transitions to the ACASI mode for the sensitive questions. In this mode, the respondent can 

read the questions silently on the computer screen and/or listen to the questions read through 

headphones and enter his or her responses directly into the computer. At the conclusion of the 

ACASI section, the interview returns to the CAPI mode with the interviewer completing the 

questionnaire. All respondents who complete a full interview are given a $30.00 cash payment as 

a token of appreciation for their time. 

No personal identifying information is captured in the CAI record for the respondent. At 

the end of the day when an interviewer has completed one or more interviews, he or she 

transmits the data to RTI in Research Triangle Park, North Carolina, via home telephone lines. 

A.3 Data Processing 

Interviewers initiate nightly data transmissions of interview data and call records on days 

when they work. Computers at RTI direct the information to a raw data file that consists of one 

record for each completed interview. Even though editing and consistency checks are done by 

the CAI program during the interview, additional, more complex, edits and consistency checks 

are completed at RTI. Cases are retained only if respondents provided data on lifetime use of 

cigarettes and at least nine other substances. An important aspect of subsequent editing routines 

involves assignment of codes when respondents legitimately were skipped out of questions that 

definitely did not apply to them (e.g., if respondents never used a drug of interest). For key drug 

use measures, the editing procedures identify inconsistencies between related variables. 

Inconsistencies in variables pertaining to the most recent period that respondents used a drug are 

edited by assigning an "indefinite" period of use (e.g., use at some point in the lifetime, which 

could mean use in the past 30 days or past 12 months). Inconsistencies in other key drug use 
74 

variables are edited by assigning missing data codes. These inconsistencies then are resolved 

through statistical imputation procedures, as discussed below. 

A.3.1 Statistical Imputation 

For some key variables that still have missing or ambiguous values after editing, 

statistical imputation is used to replace these values with appropriate response codes. For 

example, the response is ambiguous if the editing procedures assigned a respondent's most recent 

use of a drug to "use at some point in the lifetime," with no definite period within the lifetime. In 

this case, the imputation procedures assign a definite value for when the respondent last used the 

drug (e.g., in the past 30 days, more than 30 days ago but within the past 12 months, more than 

12 months ago). Similarly, if the response is completely missing, the imputation procedures 

replace missing values with nonmissing ones. 

In most cases, missing or ambiguous values are imputed using a methodology called 

predictive mean neighborhoods (PMN), which was developed specifically for the 1999 survey 

and used in all subsequent survey years. PMN is a combination of a model-assisted imputation 

methodology and a random nearest neighbor hot-deck procedure. The hot-deck procedure is set 

up in such a way that imputed values are made consistent with preexisting nonmissing values for 

other variables. Whenever feasible, the imputation of variables using PMN is multivariate, in 

which imputation is accomplished on several response variables at once. Variables requiring 

imputation using PMN were the core demographic variables, core drug use variables (recency of 

use, frequency of use, and age at first use), income, health insurance, and noncore demographic 

variables for work status, immigrant status, and the household roster. A weighted regression 

imputation was used to impute some of the missing values in the nicotine dependence variables. 

In the modeling stage of PMN, the model chosen depends on the nature of the response 

variable Y. In the 2004 NSDUH, the models included binomial logistic regression, multinomial 

logistic regression, Poisson regression, and ordinary linear regression, where the models 

incorporated the design weights. 

In general, hot-deck imputation replaces a missing or ambiguous value taken from a 

"similar" respondent who has complete data. For random nearest neighbor hot-deck imputation, 

the missing or ambiguous value is replaced by a responding value from a donor randomly 

selected from a set of potential donors. Potential donors are those defined to be "close" to the 

unit with the missing or ambiguous value, according to a predefined function, called a distance 

metric. In the hot-deck stage of PMN, the set of candidate donors (the "neighborhood") consists 

of respondents with complete data who have a predicted mean close to that of the item 

nonrespondent. In particular, the neighborhood consists of either the set of the closest 30 

respondents or the set of respondents with a predicted mean (or means) within 5 percent of the 

predicted mean(s) of the item nonrespondent, whichever set is smaller. If no respondents are 

available who have a predicted mean (or means) within 5 percent of the item nonrespondent, the 

respondent with the predicted mean(s) closest to that of the item nonrespondent is selected as the 

donor. 

In the univariate case, the neighborhood of potential donors is determined by calculating 

the relative distance between the predicted mean for an item nonrespondent and the predicted 
75 

mean for each potential donor, then choosing those means defined by the distance metric. The 

pool of donors is further restricted to satisfy logical constraints whenever necessary (e.g., age at 

first crack use must not be younger than age at first cocaine use). 

Whenever possible, missing or ambiguous values for more than one response variable are 

considered at a time. In this (multivariate) case, the distance metric is a Mahalanobis distance 

(Manly, 1986) rather than a relative Euclidean distance. Whether the imputation is univariate or 

multivariate, only missing or ambiguous values are replaced, and donors are restricted to be 

logically consistent with the response variables that are not missing. Furthermore, donors are 

restricted to satisfy "likeness constraints" whenever possible. That is, donors are required to have 

the same values for variables highly correlated with the response. If no donors are available who 

meet these conditions, these likeness constraints can be loosened. For example, donors for the 

age at first use variable are required to be of the same age as recipients, if at all possible. Further 

details on the PMN methodology are provided in RTI International (2005) and Singh, Grau, and 

Folsom (2001, 2002). 

Although statistical imputation could not proceed separately within each State due to 

insufficient pools of donors, information about each respondent's State of residence was 

incorporated in the modeling and hot-deck steps. For most drugs, respondents were separated 

into three "State usage" categories as follows: respondents from States with high usage of a 

given drug were placed in one category, respondents from States with medium usage into 

another, and the remainder into a third category. This categorical "State rank" variable was used 

as one set of covariates in the imputation models. In addition, eligible donors for each item 

nonrespondent were restricted to be of the same State usage category (i.e., the same "State rank") 

as the nonrespondent. 

A.3.2 Development of Analysis Weights 

The general approach to developing and calibrating analysis weights involved developing 

design-based weights, dk, as the inverse of the selection probabilities of the households and 

persons. Adjustment factors, ak(λ), then were applied to the design-based weights to adjust for 

nonresponse, to poststratify to known population control totals, and to control for extreme 

weights when necessary. In view of the importance of State-level estimates with the 50-State 

design, it was necessary to control for a much larger number of known population totals. Several 

other modifications to the general weight adjustment strategy that had been used in past surveys 

also were implemented for the first time beginning with the 1999 CAI sample. 

Weight adjustments were based on a generalization of Deville and Särndal's (1992) logit 

model. This generalized exponential model (GEM) (Folsom & Singh, 2000) incorporates unitspecific bounds (Rk, uk), k0s, for the adjustment factor ak(λ) as follows: 

( )

/

/

( ) ( ) exp ( λ) λ

( ) ( ) exp ( λ)

−+ − = −+−l l

l

k k k k k k kk

k

k k k k kk

u c u c Ax

a

u c c Ax , 

where ck are prespecified centering constants, such that Rk < ck < uk and Ak = (uk - Rk) / (uk - ck)(ck - 

Rk). The variables Rk, ck, and uk are user-specified bounds, and λ is the column vector of p model 

parameters corresponding to the p covariates x. The λ-parameters are estimated by solving 
76 

∑ ( ) 0, λ− = % kkk x s xda T

where %Tx denotes control totals that could be either nonrandom, as is generally the case with 

poststratification, or random, as is generally the case for nonresponse adjustment. 

The final weights wk = dkak(λ) minimize the distance function Δ(w,d) defined as 

∑

∈ ⎭

⎬

⎫

⎩

⎨

⎧

−

− + − −

− Δ = − k s k k

k k

k k

k k

k k

k k

k

k

u c

u a

u a

c

a

a

A

d (w,d) ( )log ( )log l

l l . 

This general approach was used at several stages of the weight adjustment process, 

including (1) adjustment of household weights for nonresponse at the screener level, (2) 

poststratification of household weights to meet population controls for various demographic 

groups by State, (3) adjustment of household weights for extremes, (4) poststratification of 

selected person weights, (5) adjustment of responding person weights for nonresponse at the 

questionnaire level, (6) poststratification of responding person weights, and (7) adjustment of 

responding person weights for extremes. 

Every effort was made to include as many relevant State-specific covariates (typically 

defined by demographic domains within States) as possible in the multivariate models used to 

calibrate the weights (nonresponse adjustment and poststratification steps). Because further 

subdivision of State samples by demographic covariates often produced small cell sample sizes, 

it was not possible to retain all State-specific covariates (even after meaningful collapsing of 

covariate categories) and still estimate the necessary model parameters with reasonable 

precision. Therefore, a hierarchical structure was used in grouping States with covariates defined 

at the national level, at the census division level within the Nation, at the State group within the 

census division, and, whenever possible, at the State level. In every case, the controls for total 

population within State and the five age groups (12 to 17, 18 to 25, 26 to 34, 35 to 49, 50 or 

older) within State were maintained except that, in the last step of poststratification of person 

weights, six age groups (12 to 17, 18 to 25, 26 to 34, 35 to 49, 50 to 64, 65 or older) were used. 

Census control totals by age, race, gender, and Hispanicity were required for the civilian, 

noninstitutionalized population of each State. Beginning with the 2002 NSDUH, the Population 

Estimates Branch of the U.S. Bureau of the Census produced the necessary population estimates 

in response to a special request based on the 2000 census. 

Consistent with the surveys from 1999 onward, control of extreme weights through 

separate bounds for adjustment factors was incorporated into the GEM calibration processes for 

both nonresponse and poststratification. This is unlike the traditional method of winsorization in 

which extreme weights are truncated at prespecified levels and the trimmed portions of weights 

are distributed to the nontruncated cases. In GEM, it is possible to set bounds around the 

prespecified levels for extreme weights, and then the calibration process provides an objective 

way of deciding the extent of adjustment (or truncation) within the specified bounds. A step was 

added to poststratify the household-level weights to obtain census-consistent estimates based on 

the household rosters from all screened households; these household roster-based estimates then 

provided the control totals needed to calibrate the respondent pair weights for subsequent 

planned analyses. An additional step poststratified the selected person sample to conform to the 
77 

adjusted roster estimates. This additional step takes advantage of the inherent two-phase nature 

of the NSDUH design. The final step poststratified the respondent person sample to external 

census data (defined within the State whenever possible, as discussed above). For more detailed 

information, see the 2003 NSDUH Methodological Resource Book (RTI International, 2005). 
78 
79 

Appendix B: Statistical Methods and 

Measurement 

B.1 Target Population 

An important limitation of estimates of drug use prevalence from the National Survey on 

Drug Use and Health (NSDUH) is that they are only designed to describe the target population of 

the survey—the civilian, noninstitutionalized population aged 12 or older. Although this 

population includes almost 98 percent of the total U.S. population aged 12 or older, it excludes 

some important and unique subpopulations who may have very different drug use patterns. For 

example, the survey excludes active military personnel, who have been shown to have 

significantly lower rates of illicit drug use. Also, persons living in institutional group quarters, 

such as prisons and residential drug use treatment centers, are not included in NSDUH, yet they 

have been shown in other surveys to have higher rates of illicit drug use. Also excluded are 

homeless persons not living in a shelter on the survey date; they are another population shown to 

have higher than average rates of illicit drug use. Since this report is largely focused on the U.S 

population aged 18 to 64 who were employed full time in the past year, the exclusion of the 

aforementioned subpopulations has minimal impact. Members of these subgroups are typically 

not present in the general U.S. workforce. 

B.2 Sampling Error and Statistical Significance 

The national estimates, along with the associated variance components, were computed 

using a multiprocedure package, SUDAAN® Software for Statistical Analysis of Correlated 

Data. SUDAAN was designed for the statistical analysis of data collected using stratified, 

multistage cluster sampling designs, as well as other observational and experimental studies 

involving repeated measures or studies subject to cluster correlation effects (RTI International, 

2004). The final, nonresponse-adjusted, and poststratified analysis weights were used in 

SUDAAN to compute unbiased design-based drug use estimates. 

The sampling error (i.e., the standard error [SE]) of an estimate is the error caused by the 

selection of a sample instead of conducting a census of the population. The sampling error may 

be reduced by selecting a large sample and/or by using efficient sample design and estimation 

strategies, such as stratification, optimal allocation, and ratio estimation. 

With the use of probability sampling methods in NSDUH, it is possible to develop 

estimates of sampling error from the survey data. These estimates have been calculated in 

SUDAAN for all estimates presented in this report using a Taylor series linearization approach 

that takes into account the effects of the complex NSDUH design features. The sampling errors 

are used to identify unreliable estimates and to test for the statistical significance of differences 

between estimates. 
80 

B.2.1 Variance Estimation for Totals 

Estimates of means or proportions, pd ˆ , such as drug use prevalence estimates for a 

domain d, can be expressed as a ratio estimate 

d

d

d

N

Y

p ˆ

ˆ ˆ = , 

whereYd

ˆ is a linear statistic estimating number of substance users in the domain and Ndˆ is a linear 

statistic estimating the total number of persons in domain d (both users and nonusers). The 

SUDAAN software used to develop estimates and their SEs produces direct estimates ofYd

ˆ and 

Nd

ˆ and their SEs. The SUDAAN application also uses a Taylor series approximation method to 

estimate the SEs of the ratio estimate pd ˆ . 

When the domain size, Nd

ˆ , is free of sampling error, an appropriate estimate of the SE 

for the total number of users is 

ˆ ˆ SE ( ) SE( ) ˆ YN p ddd = . 

This approach is theoretically correct when the domain size estimates, Nd

ˆ , are among those 

forced to match their respective U.S. Bureau of the Census population projections through the 

weight calibration process (Chen et al., 2005). In these cases, Nd

ˆ is not subject to sampling error. 

For a more detailed explanation of the weight calibration process, see Section A.3.2 in Appendix 

A. 

For estimated domain totals,Yd

ˆ , where Ndˆ is not fixed (i.e., where domain size estimates 

are not forced to match the U.S. Bureau of the Census population projections), this formulation 

may still provide a good approximation if it can be assumed that the sampling variation in Nd

ˆ is 

negligible relative to the sampling variation in d pˆ . This is a reasonable assumption for most cases 

in this study. 

For a subset of the estimates produced from the 2002, 2003, and 2004 data, the above 

approach yielded an underestimate of the variance of a total because Nd

ˆ was subject to 

considerable variation. In these cases, the SEs for the total estimates calculated directly within 

SUDAAN are reported. Using the SEs from the total estimates directly from SUDAAN does not 

affect the SE estimates for the corresponding proportions presented in the same sets of tables. 

B.2.2 Suppression Criteria for Unreliable Estimates 

As has been done in past NSDUH reports, direct survey estimates produced for this study 

that are considered to be unreliable due to unacceptably large sampling errors are not shown in 

this report and are noted by asterisks (*) in the tables containing such estimates. The criteria used 
81 

for suppressing all direct survey estimates were based on the relative standard error (RSE) 

(defined as the ratio of the SE over the estimate) on nominal sample size and on effective sample 

size. 

Proportion estimates( ) pˆ within the range [0 < pˆ < 1], rates, and corresponding estimated 

number of users were suppressed if 

RSE[-ln ( )] pˆ > 0.175 when pˆ # 0.5 

or 

RSE[-ln(1 - pˆ)]> 0.175 when pˆ > 0.5. 

Using a first-order Taylor series approximation to estimate RSE[-ln ( )] pˆ and RSE[-ln(1 - 

pˆ)], the following was obtained and used for computational purposes: 

SE( ) / ˆ ˆ

ln( )ˆ

p p

− p

 > 0.175 when pˆ ≤ 0.5 

or 

SE( ) /(1 ) ˆ ˆ

ln(1 )ˆ

p p

p

−

− − > 0.175 when pˆ > 0.5. 

The separate formulas for pˆ # 0.5 and pˆ > 0.5 produce a symmetric suppression rule (i.e., 

if pˆ is suppressed, then 1 - pˆ will be as well). This ad hoc rule requires an effective sample size in 

excess of 50. When 0.05 < pˆ < 0.95, the symmetric property of the rule produces a local 

maximum effective sample size of 68 at pˆ = 0.5. Thus, estimates with these values of pˆ along 

with effective sample sizes falling below 68 are suppressed. See Figure B.1 for a graphical 

representation of the required minimum effective sample sizes as a function of the proportion 

estimated. 

A minimum nominal sample size suppression criterion (n = 100) that protects against 

unreliable estimates caused by small design effects and small nominal sample sizes was 

employed. Prevalence estimates also were suppressed if they were close to 0 or 100 percent (i.e., 

if pˆ < 0.00005 or if pˆ $ 0.99995). 

Estimates of other totals (e.g., number of initiates) along with means and rates that are not 

bounded between 0 and 1 (e.g., mean age at first use and incidence rates) were suppressed if the 

RSEs of the estimates were larger than 0.5. Additionally, estimates of the mean age at first use 

were suppressed if the sample size was smaller than 10 respondents. Also, the estimated 

incidence rate and number of initiates were suppressed if they rounded to 0. 

The suppression criteria for various NSDUH estimates are summarized in Table B.1 at 

the end of this appendix. 
82 

Figure B.1 Required Effective Sample as a Function 

of the Proportion Estimated 

B.2.3 Statistical Significance of Differences 

This section describes the methods used to compare prevalence estimates in this report. 

Customarily, the observed difference between estimates is evaluated in terms of its statistical 

significance. Statistical significance is based on the p value of the test statistic and refers to the 

probability that a difference as large as that observed would occur due to random variability in 

the estimates if there were no difference in the prevalence estimates for the population groups 

being compared. The significance of observed differences in this report is generally reported at 

the 0.05 and 0.01 levels. When comparing prevalence estimates, the null hypothesis (no 

difference between prevalence estimates) was tested against the alternative hypothesis (there is a 

difference in prevalence estimates) using the standard difference in proportions test expressed as 

1 2

1 2 12

ˆ ˆ

var( ) var( ) 2cov( , ) ˆ ˆ ˆˆ

p p Z

p p pp

− =

+ −

 , 

where p1 ˆ = first prevalence estimate, p2 ˆ = second prevalence estimate, var 1 ( ) pˆ = variance of first 

prevalence estimate, var 2 ( ) pˆ = variance of second prevalence estimate, and cov 1 2 (, ) p p ˆ ˆ =

covariance between p1 ˆ and p2 ˆ . In cases where significance tests between years were performed, 

the 2003 prevalence estimate becomes the first prevalence estimate and the 2004 estimate 

becomes the second prevalence estimate. 

Under the null hypothesis, Z is asymptotically distributed as a normal random variable. 

Therefore, calculated values of Z can be referred to the unit normal distribution to determine the 

0

20

40

60

80

100

120

140

160

180

1 8 15 22 29 36 43 50 57 64 71 78 85 92 99

Current Rule: NSDUH 2004

Proportion Estimated (P)

Required Effective Sample Size

0

20

40

60

80

100

120

140

160

180

1 8 15 22 29 36 43 50 57 64 71 78 85 92 99

Current Rule: NSDUH 2004

Proportion Estimated (P)

Required Effective Sample Size
83 

corresponding probability level (i.e., p value). Because the covariance term is not necessarily 

zero, SUDAAN was used to compute estimates of Z along with the associated p values using the 

analysis weights and accounting for the sample design as described in Appendix A. A similar 

procedure and formula for Z were used for estimated totals. 

When comparing population subgroups defined by three or more levels of a categorical 

variable, log-linear Chi-square tests of independence of the subgroups and the prevalence 

variables were conducted first to control the error level for multiple comparisons. If the Chisquare test indicated overall significant differences, the significance of each particular pairwise 

comparison of interest was tested using SUDAAN analytic procedures to properly account for 

the sample design. Using the published estimates and SEs to perform independent t tests for the 

difference of proportions usually will provide the same results as tests performed in SUDAAN. 

However, where the significance level is borderline, results may differ for two reasons: (1) the 

covariance term is included in SUDAAN tests whereas it is not included in independent t tests, 

and (2) the reduced number of significant digits shown in the published estimates may cause 

rounding errors in the independent t tests. 

B.3 Other Information on Data Accuracy 

Errors can occur from nonresponse, coding errors, computer processing errors, errors in 

the sampling frame, reporting errors, and other errors not due to sampling. These types of errors 

are reduced through data editing, statistical adjustments for nonresponse, close monitoring and 

periodic retraining of interviewers, and improvement in various quality control procedures. 

Although these types of errors often can be much larger than sampling errors, 

measurement of most of these errors is difficult. However, some indication of the effects of some 

types of these errors can be obtained through proxy measures, such as response rates and from 

other research studies. 

B.3.1 Screening and Interview Response Rate Patterns 

In 2002, 2003, and 2004, respondents received a $30 incentive in an effort to improve 

response rates over years prior to 2002. Of the 142,612 eligible households sampled for the 2004 

NSDUH, for example, 130,130 were successfully screened for a weighted screening response 

rate of 90.9 percent (Table B.2). In these screened households, a total of 53,331 persons aged 18 

to 64 were selected, and completed interviews were obtained from 43,053 of these sample 

persons, for a weighted interview response rate of 77.2 percent (Table B.3). Weighted screening 

response rates for 2002 and 2003 were 90.7 percent in each survey year (Table B.2). Weighted 

interview response rates were 78.9 percent in 2002 and 77.5 percent in 2003 (Table B.3). 

The overall weighted response rate, defined as the product of the weighted screening 

response rate and weighted interview response rate, was 70.2 percent in 2004. Nonresponse bias 

can be expressed as the product of the nonresponse rate (1-R) and the difference between the 

characteristic of interest between respondents and nonrespondents in the population (Pr - Pnr). 

Thus, assuming the quantity (Pr - Pnr) is fixed over time, the improvement in response rates in 

2002 through 2004 over prior years will result in estimates with lower nonresponse bias. 
84 

B.3.2 Inconsistent Responses and Item Nonresponse 

Among survey participants, item response rates were above 99 percent for most drug use 

items. However, inconsistent responses for some items were common. Estimates of substance 

use from NSDUH are based on responses to multiple questions by respondents, so that the 

maximum amount of information is used in determining whether a respondent is classified as a 

drug user. Inconsistencies in responses are resolved through a logical editing process that 

involves some judgment on the part of survey analysts. Additionally, missing or inconsistent 

responses are imputed using statistical methodology. Editing and imputation of missing 

responses are potential sources of error. 

In addition to reporting substance use prevalence among the full-time employed 

population as a whole, this population was further divided into subgroups based on responses to 

workplace questions presented in the noncore employment section of the NSDUH questionnaire. 

These finer categories included self-reported characteristics of their employer's substance testing 

policies and treatment programs, as well as respondent's opinions on working for employers who 

test for substance use at random and during the hiring process. Respondents were further 

classified into occupational and industry groups using the 2000 Standard Occupational 

Classification (SOC) and the North American Industry Classification System. For all these 

workplace measures, item nonresponse was present. Respondents had unknown information as a 

result of refusing to answer certain questions or being unable to answer. While standard NSDUH 

logical editing procedures were implemented, unknown responses to these noncore questions 

were not imputed. For this report, all reported estimates pertaining to a workplace-related 

characteristic are based on only those respondents who had complete data for all of the 

workplace items. That is, respondents with unknown information for a given workplace measure 

or categorization were excluded from any and all analysis regarding that workplace topic. 

B.3.3 Validity of Self-Reported Use 

Most drug use prevalence estimates, including those produced for NSDUH, are based on 

self-reports of use. Although studies have generally supported the validity of self-report data, it is 

well documented that these data often are biased (underreported or overreported) by several 

factors, including the mode of administration, the population under investigation, and the type of 

drug (Bradburn & Sudman, 1983; Hser & Anglin, 1993). Higher levels of bias also are observed 

among younger respondents and those with higher levels of drug use (Biglan, Gilpin, Rorhbach, 

& Pierce, 2004). Methodological procedures, such as biological specimens (e.g., urine, hair, 

saliva), proxy reports (e.g., family member, peer), and repeated measures (e.g., recanting), have 

been used to validate self-report data (Fendrich, Johnson, Sudman, Wislar, & Spiehler, 1999). 

However, these procedures often are impractical or too costly for community-based 

epidemiological studies (SRNT Subcommittee on Biochemical Verification, 2002). NSDUH 

utilizes widely accepted methodological practices for ensuring validity, such as encouraging 

privacy through audio computer-assisted self-interviewing (ACASI). Comparisons using these 

methods within NSDUH have been shown to reduce reporting bias (Aquilino, 1994; Turner, 

Lessler, & Gfroerer, 1992). 
85 

B.4 Measurement Issues 

A measurement issue associated with the 2004 NSDUH that may be of interest and is 

discussed in this section includes the methods for measuring substance dependence and abuse. 

B.4.1 Illicit Drug and Alcohol Dependence and Abuse 

The 2004 NSDUH CAI instrumentation included questions that were designed to 

measure dependence on and abuse of illicit drugs and alcohol. For these substances,1

 dependence 

and abuse questions were based on the criteria in the DSM-IV (APA, 1994). 

Specifically, for marijuana, hallucinogens, inhalants, and tranquilizers, a respondent was 

defined as having dependence if he or she met three or more of the following six dependence 

criteria: 

1. Spent a great deal of time over a period of a month getting, using, or getting over the 

effects of the substance. 

2. Used the substance more often than intended or was unable to keep set limits on the 

substance use. 

3. Needed to use the substance more than before to get desired effects or noticed that 

same amount of substance use had less effect than before. 

4. Inability to cut down or stop using the substance every time tried or wanted to. 

5. Continued to use the substance even though it was causing problems with emotions, 

nerves, mental health, or physical problems. 

6. The substance use reduced or eliminated involvement or participation in important 

activities. 

For alcohol, cocaine, heroin, pain relievers, sedatives, and stimulants, a respondent was 

defined as having dependence if he or she met three or more of seven dependence criteria, 

including the six standard criteria listed above plus a seventh withdrawal symptom criterion. The 

seventh withdrawal criterion is defined by a respondent reporting having experienced a certain 

number of withdrawal symptoms that vary by substance (e.g., having trouble sleeping, cramps, 

hands tremble). 

For each illicit drug and alcohol, a respondent was defined as having abused that 

substance if he or she met one or more of the following four abuse criteria and was determined 

not to be dependent on the respective substance in the past year. 

1. Serious problems at home, work, or school caused by the substance, such as 

neglecting your children, missing work or school, doing a poor job at work or school, 

or losing a job or dropping out of school. 

 

1

 Substances include alcohol, marijuana, cocaine, heroin, hallucinogens, inhalants, pain relievers, 

tranquilizers, stimulants, and sedatives. 
86 

2. Used the substance regularly and then did something that might have put you in 

physical danger. 

3. Use of the substance caused you to do things that repeatedly got you in trouble with 

the law. 

4. Had problems with family or friends that were probably caused by using the 

substance and continued to use the substance even though you thought the substance 

use caused these problems. 

Criteria used to determine whether a respondent was asked the dependence and abuse 

questions included responses from core substance use and frequency of substance use questions, 

as well as noncore substance use questions. Unknown responses in the core substance use and 

frequency of substance use questions were imputed. However, the imputation process did not 

take into account reported data in the noncore (i.e., substance dependence and abuse) CAI 

modules. Responses to the dependence and abuse questions that were inconsistent with the 

imputed substance use or frequency of substance use could have existed. Because different 

criteria and different combinations of criteria were used as skip logic for each substance, 

different types of inconsistencies may have occurred for certain substances between responses to 

the dependence and abuse questions and the imputed substance use and frequency of substance 

use as described below. 

For alcohol and marijuana, respondents were asked the dependence and abuse questions 

if they reported substance use in the past year but did not report their frequency of substance use 

in the past year. Therefore, inconsistencies could have occurred where the imputed frequency of 

use response indicated less frequent use than required for respondents to be asked the 

dependence and abuse questions originally. 

For cocaine, heroin, and stimulants, respondents were asked the dependence and abuse 

questions if they reported past year use in a core drug module or past year use in the noncore 

special drugs module. Thus, inconsistencies could have occurred when the response to a core 

substance use question indicated no use in the past year, but responses to dependence and abuse 

questions indicated substance dependence or abuse for the respective substance. 

A respondent might have provided ambiguous information about past year use of any 

individual substance, in which case these respondents were not asked the dependence and abuse 

questions for that substance. Subsequently, these respondents could have been imputed to be past 

year users of the respective substance. In this situation, the dependence and abuse data were 

unknown; thus, these respondents were classified as not dependent on or abusing the respective 

substance. However, the respondent was never actually asked the dependence and abuse 

questions. 
87 

Table B.1 Summary of 2004 NSDUH Suppression Rules 

Estimate Suppress if: 

Prevalence rate, pˆ , 

with nominal sample 

size, n, and design 

effect, deff

(1) The estimated prevalence rate, pˆ , is < 0.00005 or $ 0.99995, or 

(2) > 0.175 -ln( ˆ)

SE( ˆ) / ˆ

p

p p when pˆ ≤ 0.5 , or 

 > 0.175 -ln(1 - ˆ)

SE( ˆ) / (1 - ˆ)

p

p p when 0.5 pˆ > , or 

(3) Effective n < 68 , where deff

n Effective or n =

(4) n <100 . 

Note: The rounding portion of this suppression rule for prevalence rates will produce 

some estimates that round at one decimal place to 0.0 or 100.0 percent but are 

not suppressed from the tables. 

Estimated number 

(numerator of pˆ ) 

The estimated prevalence rate, pˆ , is suppressed. 

Note: In some instances when pˆ is not suppressed, the estimated number may appear 

as a 0 in the tables. This means that the estimate is greater than 0 but less than 

500 (estimated numbers are shown in thousands). 

Mean age at first use, 

x , with nominal 

sample size, n

(1) RSE(x) > 0.5 , or 

(2) 10 n < . 

Incidence rate, rˆ (1) The incidence rate,rˆ, rounds to < 0.1 per 1,000 person-years of exposure, or 

(2) 0.5 RSE(rˆ) > . 

Number of initiates, t

ˆ (1) The number of initiates, t,ˆ rounds to < 1,000 initiates, or 

(2) RSE(t

ˆ) > 0.5 . 

SE = standard error; RSE = relative standard error; deff = design effect. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2004. 
88 

Table B.2 Weighted Percentages and Sample Sizes for 2002, 2003, and 2004 NSDUHs, by 

Screening Result Code 

Sample Size Weighted Percentage 

2002 2003 2004 2002 2003 2004 

Total Sample 178,013 170,762 169,514 100.00 100.00 100.00 

Ineligible cases 27,851 27,277 26,902 15.27 15.84 15.76 

Eligible cases 150,162 143,485 142,612 84.73 84.16 84.24 

Ineligibles 27,851 27,277 26,902 15.27 15.84 15.76 

Vacant 14,417 14,588 15,204 51.55 52.56 56.24 

Not a primary residence 4,580 4,377 4,122 17.36 17.07 15.54 

Not a dwelling unit 2,403 2,349 2,062 8.16 8.08 7.51 

All military personnel 289 356 282 1.08 1.39 1.07 

Other, ineligible 6,162 5,607 5,232 21.86 20.90 19.65 

Eligible Cases 150,162 143,485 142,612 84.73 84.16 84.24 

Screening complete 136,349 130,605 130,130 90.72 90.72 90.92 

No one selected 80,557 74,310 73,732 53.14 51.04 50.86 

One selected 30,738 30,702 30,499 20.58 21.46 21.53 

Two selected 25,054 25,593 25,899 17.00 18.22 18.53 

Screening not complete 13,813 12,880 12,482 9.28 9.28 9.08 

No one home 3,031 2,446 2,207 2.02 1.68 1.55 

Respondent unavailable 411 280 259 0.26 0.18 0.18 

Physically or mentally 

incompetent 307 290 265 0.20 0.18 0.17 

Language barrier—

Hispanic 66 42 51 0.05 0.03 0.04 

Language barrier—Other 461 450 391 0.35 0.39 0.32 

Refusal 8,556 8,414 8,588 5.86 5.98 6.10 

Other, access denied 471 923 660 0.30 0.81 0.67 

Other, eligible 12 12 10 0.01 0.01 0.01 

Resident < 1/2 of quarter 0 0 0 0.00 0.00 0.00 

Segment not accessible 0 0 0 0.00 0.00 0.00 

Screener not returned 15 16 15 0.01 0.01 0.01 

Fraudulent case 479 6 14 0.21 0.00 0.02 

Electronic screening 

problem 4 1 22 0.00 0.00 0.02 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
89 

Table B.3 Response Rates and Sample Sizes for Persons Aged 18 to 64 in the 2002, 2003, 

and 2004 NSDUHs, by Demographic Characteristics 

Selected Persons Completed Interviews Weighted Response Rate

2002 2003 2004 2002 2003 2004 2002 2003 2004 

Total 51,129 52,726 53,331 42,215 42,708 43,053 78.85% 77.53% 77.23% 

Age in Years 

18-25 27,216 27,259 27,408 23,271 22,941 23,075 85.16% 83.47% 83.87% 

26-34 7,672 8,060 8,052 6,191 6,371 6,366 79.41% 78.69% 78.61% 

35-49 12,076 12,604 12,907 9,616 9,829 9,927 78.95% 77.20% 75.96% 

50-64 4,165 4,803 4,964 3,137 3,567 3,685 73.89% 73.12% 73.61% 

Gender 

Male 24,676 25,432 25,838 19,721 19,943 20,279 76.17% 74.98% 74.83% 

Female 26,453 27,294 27,493 22,494 22,765 22,774 81.47% 79.97% 79.53% 

Race/Ethnicity 

Hispanic 6,582 7,061 7,273 5,345 5,687 5,869 79.62% 79.07% 78.25% 

White 35,387 36,437 36,364 29,189 29,515 29,209 78.85% 77.59% 77.13% 

Black 5,702 5,769 5,888 4,884 4,824 5,010 82.60% 79.71% 82.68% 

All other races 3,458 3,459 3,806 2,797 2,682 2,965 70.46% 69.36% 66.73% 

Region 

Northeast 10,521 10,837 10,884 8,544 8,625 8,626 76.44% 76.06% 75.47% 

Midwest 14,283 14,666 14,794 11,861 12,028 11,899 80.39% 78.47% 77.73% 

South 15,514 15,857 16,133 12,927 12,915 13,246 80.25% 78.48% 79.06% 

West 10,811 11,366 11,520 8,883 9,140 9,282 77.13% 76.31% 75.30% 

County Type 

Large metro 20,637 23,866 24,382 16,637 18,804 19,188 77.06% 75.42% 75.74% 

Small metro 18,145 18,083 18,017 15,141 15,018 14,819 79.90% 80.16% 78.48% 

Nonmetro 12,347 10,777 10,932 10,437 8,886 9,046 81.92% 79.96% 80.07% 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003 and 2004. 
90 
91 

Appendix C: Key Definitions, 2002-2004 

This appendix provides definitions for many of the measures and terms used in this report 

on the National Survey on Drug Use and Health (NSDUH). Where relevant, cross-references 

also are provided. For some key terms, specific question wording, including "feeder questions" 

that precede the question(s), is provided for clarity. 

Abuse A respondent was defined with abuse of a substance if he or she 

met one or more of the four criteria for abuse included in the 

Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) 

(American Psychiatric Association [APA], 1994) and did not meet 

the definition for dependence for that substance. Additional criteria 

for alcohol and marijuana abuse are that if respondents reported a 

specific number of days that they used these drugs in the past 12 

months, they must have used these drugs on 6 or more days in that 

period. These questions have been included in the survey since 

2000. 

SEE: "Prevalence." 

Age Age of the respondent was defined as "age at time of interview." 

The interview program calculated the respondent's age from the 

date of birth and interview date. The interview program prompts 

the interviewer to confirm the respondent's age after it has been 

calculated. 

Alcohol Use Measures of use of alcohol in the respondent's lifetime, the past 

year, and the past month were developed from responses to the 

question about recency of use: "How long has it been since you 

last drank an alcoholic beverage?" 

Feeder question: "The next questions are about alcoholic 

beverages, such as, beer, wine, brandy, and mixed drinks. Listed 

on the next screen are examples of the types of beverages we are 

interested in. Please review this list carefully before you answer 

these questions. These questions are about drinks of alcoholic 

beverages. Throughout these questions, by a 'drink,' we mean a can 

or bottle of beer, a glass of wine or a wine cooler, a shot of liquor, 

or a mixed drink with liquor in it. We are not asking about times 

when you only had a sip or two from a drink. Have you ever, even 

once, had a drink of an alcoholic beverage? Please do not include 

times when you only had a sip or two from a drink." 
92 

SEE: "Binge Use of Alcohol," "Current Use," "Heavy Use of 

Alcohol," "Lifetime Use," "Past Month Use," "Past Year 

Use," "Prevalence," and "Recency of Use." 

American Indian or 

Alaska Native American Indian or Alaska Native only, not of Hispanic, Latino, or 

Spanish origin (including North American, Central American, or 

South American Indian); does not include respondents reporting 

two or more races. (Respondents reporting that they were 

American Indians or Alaska Natives and of Hispanic, Latino, or 

Spanish origin were classified as Hispanic.) 

SEE: "Hispanic" and "Race/Ethnicity." 

Asian Asian only, not of Hispanic, Latino, or Spanish origin; does not 

include respondents reporting two or more races. (Respondents 

reporting that they were Asian and of Hispanic, Latino, or Spanish 

origin were classified as Hispanic.) Specific Asian groups that 

were asked about were Asian Indian, Chinese, Filipino, Japanese, 

Korean, Vietnamese, and "Other Asian." 

SEE: "Hispanic" and "Race/Ethnicity." 

Black Black/African American only, not of Hispanic, Latino, or Spanish 

origin; does not include respondents reporting two or more races. 

(Respondents reporting that they were black or African American 

and of Hispanic, Latino, or Spanish origin were classified as 

Hispanic.) 

SEE: "Hispanic" and "Race/Ethnicity." 

College Enrollment 

Status Respondents aged 18 to 22 were classified as full-time 

undergraduate students or as some other status (including part-time 

students, students in other grades, or nonstudents). Respondents 

were classified as full-time students if they reported that they were 

attending (or will be attending) their first through fourth year of 

college or university and that they were (or will be) a full-time 

student. Respondents whose current enrollment status was 

unknown were excluded from the analysis. 

County Type Geographic comparisons also are made based on urban influence 

county type, which reflects different levels of population size, 

urbanization, and access to larger communities based on countylevel Urban Influence Codes (UIC) created by the Economic 

Research Service (ERS) of the U.S. Department of Agriculture 
93 

(USDA). The codes group metropolitan and nonmetropolitan 

counties according to the official county-level metro status issued 

by the Office of Management and Budget (OMB) in June 2003 

(OMB, 2003). Each county is either inside or outside a 

metropolitan statistical area (MSA), as defined by the OMB. The 

definitions of urban influence county type are different than 

county-type definitions used in other NSDUH reports. The 

definitions for this report are based on UIC, whereas the 2004 

national findings (OAS, 2005) definitions are based on RuralUrban Continuum Codes (RUCC). 

 Large MSAs have a population of 1 million or more. Small MSAs 

have a population of fewer than 1 million. Nonmetropolitan areas 

are areas outside MSAs that have been categorized into four 

groups based on UIC. The first group consists of micropolitan 

statistical areas (MiSAs), which include a county with an urban 

cluster of at least 10,000 persons or more and any additional 

counties where commuting to the central county is 25 percent or 

higher, or where 25 percent of the employment in an outlying 

county is made up of commuters from the central county. The 

remaining three groups of nonmetropolitan areas consist of 

noncore counties and are divided based on their adjacency to larger 

areas and whether or not they have their "own town" of at least 

2,500 residents. The "noncore adjacent with town" group includes 

those areas that are adjacent to a large MSA, adjacent to a small 

MSA and have their own town, or adjacent to a MiSA and have 

their own town. Noncore areas that have no town of their own but 

are adjacent to a small MSA or MiSA compose the "noncore 

adjacent, no town" group. The "noncore rural, not adjacent" group 

consists of counties that are not adjacent to any MSA or MiSA and 

have no town of their own. 

Current Use Any reported use of a specific drug in the past 30 days. 

SEE: "Lifetime Use," "Past Month Use," "Past Year Use," 

"Prevalence," and "Recency of Use." 

Dependence A respondent was defined with dependence on illicit drugs or 

alcohol if he or she met three out of seven dependence criteria (for 

substances that included questions to measure a withdrawal 

criterion) or three out of six criteria (for substances that did not 

include withdrawal questions) for that substance, based on criteria 

included in the Diagnostic and Statistical Manual of Mental 

Disorders (DSM-IV) (APA, 1994). Additional criteria for alcohol 

and marijuana dependence since 2000 are that if respondents 

reported a specific number of days that they used these drugs in the 

past 12 months, they must have used these drugs on 6 or more days 
94 

in that period. This definition did not apply to Nicotine (Cigarette) 

Dependence. 

SEE: "Prevalence." 

Education This is the measure of educational attainment among respondents 

who are aged 18 or older. It is based on respondents' reports of 

their highest grade or year of school that they completed. Response 

alternatives were presented in terms of single years of education, 

ranging from 0 if respondents never attended school to 17 if 

respondents completed 5 or more years at the college or university 

level. Respondents were classified into four categories based on 

their answers: less than high school, high school graduate, some 

college, and college graduate. Persons who completed 

postgraduate work were classified as college graduates. 

Employment Respondents were asked to report whether they worked in the 

week prior to the interview, and if not, whether they had a job 

despite not working in the past week. Respondents who worked in 

the past week or who reported having a job despite not working 

were asked whether they usually work 35 or more hours per week. 

Respondents who did not work in the past week but had a job were 

asked to look at a card that described why they did not work in the 

past week despite having a job. Respondents who did not have a 

job in the past week were asked to look at a different card that 

described why they did not have a job in the past week. 

Full-time "Full-time" in the tables includes respondents who 

usually work 35 or more hours per week and who 

worked in the past week or had a job despite not 

working in the past week. 

Part-time "Part-time" in the tables includes respondents who 

usually work fewer than 35 hours per week and who 

worked in the past week or had a job despite not 

working in the past week. 

Unemployed "Unemployed" in the tables refers to respondents 

who did not have a job, were on layoff, and were 

looking for work. For consistency with the Current 

Population Survey definition of unemployment, 

respondents who reported that they did not have a 

job but were looking for work needed to report 

making specific efforts to find work in the past 30 

days. 
95 

Other "Other" includes all other responses, including 

being a student, someone who is keeping house or 

caring for children full time, retired, disabled, or 

other miscellaneous work statuses. Respondents 

who reported that they did not have a job, were on 

layoff, and were not looking for work were 

classified as not being in the labor force. Similarly, 

respondents who reported not having a job and 

looking for work also were classified as not being in 

the labor force if they did not report making specific 

efforts to find work in the past 30 days. 

Establishment Size Data are presented for the number of persons who work for an 

employer and include less than 10 employees, 10 to 24 employees, 

25 to 99 employees, 100 to 499 employees, and 500 or more 

employees. 

Ethnicity SEE: "Race/Ethnicity." 

Ever Use SEE: "Lifetime Use." 

Family Income Family income was ascertained by asking respondents: "Of these 

income groups, which category best represents (your/SAMPLE 

MEMBER's) total combined family income during [the previous 

calendar year]? (Income data are important in analyzing the health 

information we collect. For example, the information helps us to 

learn whether persons in one income group use certain types of 

medical care services or have conditions more or less often than 

those in another group.)" 

NOTE: For respondents who were unable to respond to the 

insurance or income questions, proxy responses were 

accepted from a household member identified as being 

better able to give the correct information about insurance 

and income. 

Geographic Division Data are presented for nine geographic divisions within the four 

geographic regions. Within the Northeast Region are the New 

England Division (Connecticut, Maine, Massachusetts, New 

Hampshire, Rhode Island, Vermont) and the Middle Atlantic 

Division (New Jersey, New York, Pennsylvania). Within the 

Midwest Region are the East North Central Division (Illinois, 

Indiana, Michigan, Ohio, Wisconsin) and the West North Central 

Division (Iowa, Kansas, Minnesota, Missouri, Nebraska, North 

Dakota, South Dakota). Within the South Region are the South 

Atlantic Division (Delaware, District of Columbia, Florida, 
96 

Georgia, Maryland, North Carolina, South Carolina, Virginia, 

West Virginia), the East South Central Division (Alabama, 

Kentucky, Mississippi, Tennessee), and the West South Central 

Division (Arkansas, Louisiana, Oklahoma, Texas). Within the 

West Region are the Mountain Division (Arizona, Colorado, Idaho, 

Montana, Nevada, New Mexico, Utah, Wyoming) and the Pacific 

Division (Alaska, California, Hawaii, Oregon, Washington). 

 SEE: "Region." 

Heavy Use of Alcohol Heavy use of alcohol was defined as drinking five or more drinks 

on the same occasion (i.e., at the same time or within a couple of 

hours of each other) on 5 or more days in the past 30 days. Heavy 

alcohol users also were defined as binge users of alcohol. 

 Feeder question: "How long has it been since you last drank an 

alcoholic beverage?" 

SEE: "Alcohol Use" and "Binge Use of Alcohol." 

Hispanic Hispanic was defined as anyone of Hispanic, Latino, or Spanish 

origin. Respondents were classified as Hispanic in the 

race/ethnicity measure regardless of race. 

SEE: "American Indian or Alaska Native," "Asian," "Black," 

"Race/Ethnicity," "Two or More Races," and "White." 

Illicit Drugs Illicit drugs include marijuana or hashish, cocaine (including 

crack), inhalants, hallucinogens (including phencyclidine [PCP], 

lysergic acid diethylamide [LSD], and Ecstasy [MDMA]), heroin, 

or prescription-type psychotherapeutics used nonmedically, which 

include stimulants, sedatives, tranquilizers, and pain relievers. 

Illicit drug use refers to use of any of these drugs. 

SEE: "Current Use," "Lifetime Use," "Past Month Use," "Past 

Year Use," "Prevalence," "Psychotherapeutic Drugs," and 

"Recency of Use." 

Income SEE: "Family Income." 

Industry Data are provided for the business or industry in which a person 

currently works. The North American Industry Classification 

System (NAICS) is used to classify industries in the report. The 

NAICS replaced the Standard Industry Classification (SIC) and 

categorizes all industries into 19 major groups. Industries are 

organized within the NAICS by the processes used to produce 
97 

goods or services. This report focuses on these major groups, but a 

more detailed analysis of industry classifications can be found in 

Appendix D. 

Large MSA SEE: "County Type." 

Lifetime Use Lifetime use indicates use of a specific drug at least once in the 

respondent's lifetime. This measure includes respondents who also 

reported last using the drug in the past 30 days or past 12 months. 

SEE: "Current Use," "Past Month Use," "Past Year Use," 

"Prevalence," and "Recency of Use." 

Low Precision Prevalence estimates based on only a few respondents or with 

relatively large standard errors were not shown in the tables, but 

have been replaced with an asterisk (*) and noted as "low 

precision." These estimates have been omitted because one cannot 

place a high degree of confidence in their accuracy. See Table B.1 

in Appendix B for a complete list of the rules used to determine 

low precision. 

Marijuana Use Measures of use of marijuana in the respondent's lifetime, the past 

year, and the past month were developed from responses to the 

question about recency of use: "How long has it been since you 

last used marijuana or hashish?" Responses to questions about use 

of cigars with marijuana in them (blunts) were not included in 

these measures. 

Feeder question: "The next questions are about marijuana and 

hashish. Marijuana is also called pot or grass. Marijuana is usually 

smoked—either in cigarettes called joints, or in a pipe. It is 

sometimes cooked in food. Hashish is a form of marijuana that is 

also called hash. It is usually smoked in a pipe. Another form of 

hashish is hash oil. Have you ever, even once, used marijuana or 

hash?" 

SEE: "Current Use," "Lifetime Use," "Past Month Use," "Past 

Year Use," "Prevalence," and "Recency of Use." 

Midwest Region The States included are those in the East North Central Division—

Illinois, Indiana, Michigan, Ohio and Wisconsin—and the West 

North Central Division—Iowa, Kansas, Minnesota, Missouri, 

Nebraska, North Dakota, and South Dakota. 

 SEE: "Geographic Division" and "Region." 
98 

MiSA SEE: "County Type." 

Native Hawaiian or 

Other Pacific Islander Native Hawaiian or Other Pacific Islander, not of Hispanic, Latino, 

or Spanish origin; does not include respondents reporting two or 

more races. (Respondents reporting that they were Native 

Hawaiian or Other Pacific Islander and of Hispanic, Latino, or 

Spanish origin were classified as Hispanic.) 

SEE: "Hispanic" and "Race/Ethnicity." 

Nonmetro SEE: "County Type." 

Northeast Region The States included are those in the New England Division—

Connecticut, Maine, Massachusetts, New Hampshire, Rhode 

Island, and Vermont—and the Middle Atlantic Division—New 

Jersey, New York, and Pennsylvania. 

SEE: "Geographic Division" and "Region." 

Occupation Data are provided for the kind of work or occupation in which a 

person currently works. The occupations are coded into groups 

using the 2000 Standard Occupational Classification (SOC) 

released by the U.S. Department of Labor, Bureau of Labor 

Statistics, which categorizes all occupations into 21 major groups. 

Within these major groups are 96 minor groups, 449 broad 

occupations, and 821 detailed occupations. Occupations with 

similar skills or work activities are grouped at each of the four 

levels of hierarchy to facilitate comparisons. This report focuses on 

these major groups, but a more detailed analysis of occupational 

classifications can be found in the Appendix D. 

Past Month Use This measure indicates use of a specific drug in the 30 days prior 

to the interview. Respondents who indicated past month use of a 

specific drug also were classified as lifetime and past year users. 

SEE: "Current Use," "Lifetime Use," "Past Year Use," 

"Prevalence," and "Recency of Use." 

Past Year Use This measure indicates use of a specific drug in the 12 months 

prior to the interview. This definition includes those respondents 

who last used the drug in the 30 days prior to the interview. 

Respondents who indicated past year use of a specific drug also 

were classified as lifetime users. 
99 

SEE: "Current Use," "Lifetime Use," "Past Month Use," 

"Prevalence," and "Recency of Use." 

Percentages In this report, all of the 2004 tables contain percentages based on 

weighted data. 

SEE: "Rounding." 

Prevalence General term used to describe the estimates for lifetime, past year, 

and past month substance use, dependence or abuse, or other 

behaviors of interest within a given period (e.g., the past 12 

months). The latter include delinquent behavior, driving under the 

influence of alcohol or drugs, perceived help from treatment for 

mental health problems, perceived need for alcohol or illicit drug 

use treatment, serious psychological distress, treatment for mental 

health problems, treatment for a substance use problem, and unmet 

need for treatment for mental health problems. 

SEE: "Abuse," "Current Use," "Dependence," and "Recency of 

Use." 

Race/Ethnicity Race/ethnicity is used to refer to the respondent's self-classification 

as to racial and ethnic origin and identification. For Hispanic 

origin, respondents were asked, "Are you of Hispanic, Latino, or 

Spanish origin or descent?" For race, respondents were asked, 

"Which of these groups best describes you?" Response alternatives 

were (1) white, (2) black/African American, (3) American Indian 

or Alaska Native, (4) Native Hawaiian, (5) Other Pacific Islander, 

(6) Asian, and (7) Other. Categories for race/ethnicity included 

Hispanic; non-Hispanic groups where respondents indicated only 

one race (white, black, American Indian or Alaska Native, Native 

Hawaiian or Other Pacific Islander, Asian); and non-Hispanic 

groups where respondents reported two or more races. These 

categories are based on classifications developed by the U.S. 

Bureau of the Census. 

SEE: "American Indian or Alaska Native," "Asian," "Black," 

"Hispanic," "Native Hawaiian or Other Pacific Islander," 

"Two or More Races," and "White." 

Recency of Use The recency question for each drug was the source for the lifetime, 

past year, and past month prevalence estimates. 

The question was essentially the same for all classes of drugs. The 

question was: "How long has it been since you last used [drug 

name]?" For the four classes of psychotherapeutics, the phrase 
100 

"that was not prescribed for you or only for the experience or 

feeling it caused" was added after the name of the drug. 

For tobacco products (cigarettes, snuff, chewing tobacco, or 

cigars), the response alternatives were (1) within the past 30 days; 

(2) more than 30 days ago but within the past 12 months; (3) more 

than 12 months ago but within the past 3 years; and (4) more than 

3 years ago. For the remaining drugs, the response alternatives 

were (1) within the past 30 days; (2) more than 30 days ago but 

within the past 12 months; and (3) more than 12 months ago. 

SEE: "Current Use," "Lifetime Use," "Past Month Use," "Past 

Year Use," and "Prevalence." 

Region There were four regions to consider: Northeast, Midwest, South, 

and West. These regions are based on classifications developed by 

the U.S. Bureau of the Census. 

SEE: "Geographic Division," "Midwest Region," "Northeast 

Region," "South Region," and "West Region." 

Rounding The decision rules for the rounding of percentages were as follows. 

If the second number to the right of the decimal point was greater 

than or equal to 5, the first number to the right of the decimal point 

was rounded up to the next higher number. If the second number to 

the right of the decimal point was less than 5, the first number to 

the right of the decimal point remained the same. Thus, a 

prevalence estimate of 16.55 percent would be rounded to 16.6 

percent, while an estimate of 16.44 percent would be rounded to 

16.4 percent. Although the percentages in the 2004 tables generally 

total 100 percent, the use of rounding sometimes produces a total 

of slightly less than or more than 100 percent. 

SEE: "Percentages." 

Significance In tables in which trends are shown, the levels of significance for 

the changes between the two most recent survey years are noted as 

follows: 0.05 and 0.01. A significance level of 0.05 is used in 

comparing two estimates in the text for demographic subgroups of 

the most recent survey sample. 

Small MSA SEE: "County Type." 

South Region The States included are those in the South Atlantic Division— 

Delaware, District of Columbia, Florida, Georgia, Maryland, North 

Carolina, South Carolina, Virginia, and West Virginia; the East 
101 

South Central Division—Alabama, Kentucky, Mississippi, and 

Tennessee; and the West South Central Division—Arkansas, 

Louisiana, Oklahoma, and Texas. 

SEE: "Geographic Division" and "Region." 

Two or More Races Respondents were asked to report which racial group describes 

them. Response alternatives were (1) white, (2) black/African 

American, (3) American Indian or Alaska Native, (4) Native 

Hawaiian, (5) Other Pacific Islander, (6) Asian, and (7) Other. 

Respondents were allowed to choose more than one of these 

groups. Persons who chose both the "Native Hawaiian" and "Other 

Pacific Islander" categories (and no additional categories) were 

classified in a single category: Native Hawaiian or Other Pacific 

Islander. Otherwise, persons reporting two or more of the above 

groups and that they were not of Hispanic, Latino, or Spanish 

origin were included in a "Two or More Races" category. This 

category does not include respondents who reported more than one 

Asian subgroup but who reported "Asian" as their only race. 

Respondents reporting two or more races and reporting that they 

were of Hispanic, Latino, or Spanish origin were classified as 

Hispanic. 

SEE: "Hispanic" and "Race/Ethnicity." 

West Region The States included are those in the Mountain Division—Arizona, 

Colorado, Idaho, Montana, Nevada, New Mexico, Utah, and 

Wyoming; and the Pacific Division—Alaska, California, Hawaii, 

Oregon, and Washington. 

SEE: "Geographic Division" and "Region." 

White White, not of Hispanic, Spanish, or Latino origin; does not include 

respondents reporting two or more races. (Respondents reporting 

that they were white and of Hispanic, Latino, or Spanish origin 

were classified as Hispanic.) 

SEE: "Hispanic" and "Race/Ethnicity." 

Workplace Testing Respondents were asked if they would be more likely or less likely 

to want to work for an employer who tests for drug or alcohol use 

before hiring or on a random basis. 
102 
103 

Appendix D: Occupational and Industry 

Classifications 
104 
105 

D.1 Occupational Classification System 

2000 

Census 

code Occupation category 

 

Executive, Administrative, and Managerial 

 Occupations 

0010 Chief Executives 

0020 General and Operations Managers 

0030 Legislators 

0040 Advertising and Promotions Managers 

0050 Marketing and Sales Managers 

0060 Public Relations Managers 

0100 Administrative Services Managers 

0110 Computer and Information Systems Managers 

0120 Financial Managers 

0130 Human Resources Managers 

0140 Industrial Production Managers 

0150 Purchasing Managers 

0160 Transportation, Storage, and Distribution 

 Managers 

0200 Farm, Ranch, and Other Agricultural Managers 

0210 Farmers and Ranchers 

0220 Construction Managers 

0230 Education Administrators 

0300 Engineering Managers 

0310 Food Service Managers 

0320 Funeral Directors 

0330 Gaming Managers 

0340 Lodging Managers 

0350 Medical and Health Services Managers 

0360 Natural Sciences Managers 

0400 Postmasters and Mail Superintendents 

0410 Property, Real Estate, and Community Association 

 Managers 

0420 Social and Community Service Managers 

0430 Managers, All Other 

Management Related Occupations 

0500 Agents and Business Managers of Artists, 

 Performers, and Athletes 

0510 Purchasing Agents and Buyers, Farm Products 

0520 Wholesale and Retail Buyers, Except Farm 

 Products 

0530 Purchasing Agents, Except Wholesale, Retail, and 

 Farm Products 

0540 Claims Adjusters, Appraisers, Examiners, and 

 Investigators 

0560 Compliance Officers, Except Agriculture, 

Construction, Health And Safety, And 

Transportation 

0600 Cost Estimators 

0620 Human Resources, Training, and Labor Relations 

 Specialists 

0700 Logisticians 

0710 Management Analysts 

0720 Meeting and Convention Planners 

0730 Other Business Operations Specialists 

Financial Related Occupations 

0800 Accountants and Auditors 

0810 Appraisers and Assessors of Real Estate 

0820 Budget Analysts 

0830 Credit Analysts 

0840 Financial Analysts 

0850 Personal Financial Advisors 

2000 

Census 

code Occupation category 

Financial Related Occupations-Con 

0860 Insurance Underwriters 

0900 Financial Examiners 

0910 Loan Counselors and Officers 

0930 Tax Examiners, Collectors, and Revenue Agents 

0940 Tax Preparers 

0950 Financial Specialists, All Other 

Mathematical and Computer Scientists 

1000 Computer Scientists and Systems Analysts 

1010 Computer Programmers 

1020 Computer Software Engineers 

1040 Computer Support Specialists 

1060 Database Administrators 

1100 Network and Computer Systems Administrators 

1110 Network Systems and Data Communications 

 Analysts 

1200 Actuaries 

1210 Mathematicians 

1220 Operations Research Analysts 

1230 Statisticians 

1240 Miscellaneous Mathematical Occupations 

Engineers, Architects, and Surveyors 

1300 Architects, Except Naval 

1310 Surveyors, Cartographers, and Photogrammetrists 

1320 Aerospace Engineers 

1330 Agricultural Engineers 

1340 Biomedical Engineers 

1350 Chemical Engineers 

1360 Civil Engineers 

1400 Computer Hardware Engineers 

1410 Electrical and Electronics Engineers 

1420 Environmental Engineers 

1430 Industrial Engineers, Including Health and Safety 

1440 Marine Engineers and Naval Architects 

1450 Materials Engineers 

1460 Mechanical Engineers

 Engineers, Including Mining Safety Engineers 

1510 Nuclear Engineers 

1520 Petroleum Engineers 

1530 Engineers, All Other 

Engineering and Related Technicians 

1540 Drafters 

1550 Engineering Technicians, Except Drafters 

1560 Surveying and Mapping Technicians 

Physical Scientists 

1600 Agricultural and Food Scientists 

1610 Biological Scientists 

1640 Conservation Scientists and Foresters 

1650 Medical Scientists 

1700 Astronomers and Physicists 

1710 Atmospheric and Space Scientists 

1720 Chemists and Materials Scientists 

1740 Environmental Scientists and Geoscientists 

1760 Physical Scientists, All Other 
106 

2000 

Census 

code Occupation category 

Social Scientists and Related Workers 

1800 Economists 

1810 Market and Survey Researchers 

1820 Psychologists 

1830 Sociologists 

1840 Urban and Regional Planners 

1860 Miscellaneous Social Scientists and Related 

 Workers 

Life, Physical, and Social Science Technicians 

1900 Agricultural and Food Science Technicians 

1910 Biological Technicians 

1920 Chemical Technicians 

1930 Geological and Petroleum Technicians 

1940 Nuclear Technicians 

1960 Other Life, Physical, and Social Science 

 Technicians 

Counselors, Social, and Religious Workers 

2000 Counselors 

2010 Social Workers 

2020 Miscellaneous Community and Social Service 

 Specialists 

2040 Clergy 

2050 Directors, Religious Activities and Education 

2060 Religious Workers, All Other 

Lawyers, Judges, and Legal Support Workers 

2100 Lawyers 

2110 Judges, Magistrates, and Other Judicial Workers 

2140 Paralegals and Legal Assistants 

2150 Miscellaneous Legal Support Workers 

Teachers 

2200 Postsecondary Teachers 

2300 Preschool and Kindergarten Teachers 

2310 Elementary and Middle School Teachers 

2320 Secondary School Teachers 

2330 Special Education Teachers 

2340 Other Teachers and Instructors 

Education, Training and Library Workers 

2400 Archivists, Curators, and Museum Technicians 

2430 Librarians 

2440 Library Technicians 

2540 Teacher Assistants 

2550 Other Education, Training, and Library Workers 

Entertainers and Performers, Sports and Related 

 Workers 

2600 Artists and Related Workers 

2630 Designers 

2700 Actors 

2710 Producers and Directors 

2720 Athletes, Coaches, Umpires, and Related Workers 

2740 Dancers and Choreographers 

2750 Musicians, Singers, and Related Workers 

2760 Entertainers and Performers, Sports and Related 

Workers, All Other 

2000 

Census 

code Occupation category 

Media and Communication Workers 

2800 Announcers 

2810 News Analysts, Reporters and Correspondents 

2820 Public Relations Specialists 

2830 Editors 

2840 Technical Writers 

2850 Writers and Authors 

2860 Miscellaneous Media and Communication 

 Workers 

2900 Broadcast and Sound Engineering Technicians 

 and Radio Operators 

2910 Photographers 

2920 Television, Video, and Motion Picture Camera 

 Operators and Editors 

2960 Media and Communication Equipment Workers, 

 All Other 

Health Diagnosing and Treating Practitioners 

3000 Chiropractors 

3010 Dentists 

3030 Dietitians and Nutritionists 

3040 Optometrists 

3050 Pharmacists 

3060 Physicians and Surgeons 

Health Diagnosing and Treating Practitioners 

3110 Physician Assistants 

3120 Podiatrists 

3130 Registered Nurses 

3140 Audiologists 

3150 Occupational Therapists 

3160 Physical Therapists 

3200 Radiation Therapists 

3210 Recreational Therapists 

3220 Respiratory Therapists 

3230 Speech-Language Pathologists 

3240 Therapists, All Other 

3250 Veterinarians 

3260 Health Diagnosing and Treating Practitioners, All 

 Other 

Health Care Technical and Support Occupations 

3300 Clinical Laboratory Technologists and Technicians 

3310 Dental Hygienists 

3320 Diagnostic Related Technologists and Technicians 

3400 Emergency Medical Technicians and Paramedics 

3410 Health Diagnosing and Treating Practitioner 

 Support Technicians 

3500 Licensed Practical and Licensed Vocational 

 Nurses 

3510 Medical Records and Health Information 

 Technicians 

3520 Opticians, Dispensing 

3530 Miscellaneous Health Technologists and 

 Technicians 

3540 Other Healthcare Practitioners and Technical 

 Occupations 
107 

2000 

Census 

code Occupation category 

 Health Care Technical and Support Occupations- 

 con 

3600 Nursing, Psychiatric, and Home Health Aides 

3610 Occupational Therapist Assistants and Aides 

3620 Physical Therapist Assistants and Aides 

3630 Massage Therapists 

3640 Dental Assistants 

3650 Medical Assistants and Other Healthcare Support 

 Occupations 

Protective Service Occupations 

3700 First-Line Supervisors/Managers of Correctional 

 Officers 

3710 First-Line Supervisors/Managers of Police and 

 Detectives 

3720 First-Line Supervisors/Managers of Fire Fighting 

 and Prevention Workers 

3730 Supervisors, Protective Service Workers, All Other 

3740 Fire Fighters 

3750 Fire Inspectors 

3800 Bailiffs, Correctional Officers, and Jailers 

3820 Detectives and Criminal Investigators 

3830 Fish and Game Wardens 

3840 Parking Enforcement Workers 

3850 Police and Sheriff's Patrol Officers 

3860 Transit and Railroad Police 

3900 Animal Control Workers 

3910 Private Detectives and Investigators 

3950 Lifeguards and Other Protective Service Workers 

 Food Preparation and Serving Related 

 Occupations 

4000 Chefs and Head Cooks 

4010 First-Line Supervisors/Managers of Food 

4020 Cooks 

4030 Food Preparation Workers 

4040 Bartenders 

4120 Food Servers, Nonrestaurant 

4130 Dining Room and Cafeteria Attendants and 

 Bartender Helpers 

4140 Dishwashers 

4150 Hosts and Hostesses, Restaurant, Lounge, and 

 Coffee Shop 

4160 Food Preparation and Serving Related Workers, 

 All Other 

Cleaning and Building Service Occupations 

4200 First-Line Supervisors/Managers of Housekeeping 

 and Janitorial Workers 

4210 First-Line Supervisors/Managers of Landscaping, 

 Lawn Service, and Groundskeeping Workers 

4220 Janitors and Building Cleaners 

4230 Maids and Housekeeping Cleaners 

4240 Pest Control Workers 

4250 Grounds Maintenance Workers 

Entertainment Attendants and Related Workers 

4300 First-Line Supervisors/Managers of Gaming 

 Workers 

4320 First-Line Supervisors/Managers of Personal 

 Service Workers 

2000 

Census 

code Occupation category 

 Entertainment Attendants and Related Workers- 

 con 

4340 Animal Trainers 

4350 Nonfarm Animal Caretakers 

4400 Gaming Services Workers 

4410 Motion Picture Projectionists 

4420 Ushers, Lobby Attendants, and Ticket Takers 

4430 Miscellaneous Entertainment Attendants and 

 Related Workers 

Funeral Related Occupations 

4460 Funeral Service Workers 

Personal Care and Service Workers 

4500 Barbers 

4510 Hairdressers, Hairstylists, and Cosmetologists 

4520 Miscellaneous Personal Appearance Workers 

4530 Baggage Porters, Bellhops, and Concierges 

4540 Tour and Travel Guides 

4550 Transportation Attendants 

4600 Child Care Workers 

4610 Personal and Home Care Aides 

4620 Recreation and Fitness Workers 

4640 Residential Advisors 

4650 Personal Care and Service Workers, All Other 

Sales and Related Workers 

4700 First-Line Supervisors/Managers of Retail Sales 

 Workers 

4710 First-Line Supervisors/Managers of Non-Retail 

 Sales Workers 

4720 Cashiers 

4740 Counter and Rental Clerks 

4750 Parts Salespersons 

4760 Retail Salespersons 

4800 Advertising Sales Agents 

4810 Insurance Sales Agents 

4820 Securities, Commodities, and Financial Services 

 Sales Agents 

4830 Travel Agents 

4840 Sales Representatives, Services, All Other 

4850 Sales Representatives, Wholesale and 

 Manufacturing 

4900 Models, Demonstrators, and Product Promoters 

4920 Real Estate Brokers and Sales Agents 

4930 Sales Engineers 

4940 Telemarketers 

4950 Door-To-Door Sales Workers, News and Street 

 Vendors, and Related Workers 

4960 Sales and Related Workers, All Other 

Office and Administrative Support Workers 

5000 First-Line Supervisors/Managers of Office and 

 Administrative Support Workers 

5010 Switchboard Operators, Including Answering 

 Service 

5020 Telephone Operators 

5030 Communications Equipment Operators, All Other 
108 

2000 

Census 

code Occupation category 

Office and Administrative Support Workers-con 

5100 Bill and Account Collectors 

5110 Billing and Posting Clerks and Machine Operators 

5120 Bookkeeping, Accounting, and Auditing Clerks 

5130 Gaming Cage Workers 

5140 Payroll and Timekeeping Clerks 

Office and Administrative Support Workers 

5150 Procurement Clerks 

5160 Tellers 

5200 Brokerage Clerks 

5210 Correspondence Clerks 

5220 Court, Municipal, and License Clerks 

5230 Credit Authorizers, Checkers, and Clerks 

5240 Customer Service Representatives 

5250 Eligibility Interviewers, Government Programs 

5260 File Clerks 

5300 Hotel, Motel, and Resort Desk Clerks 

5310 Interviewers, Except Eligibility and Loan 

5320 Library Assistants, Clerical 

5330 Loan Interviewers and Clerks 

5340 New Accounts Clerks 

5350 Order Clerks 

5360 Human Resources Assistants, Except Payroll and 

 Timekeeping 

5400 Receptionists and Information Clerks 

5410 Reservation and Transportation Ticket Agents and 

 Travel Clerks 

5420 Information and Record Clerks, All Other 

5500 Cargo and Freight Agents 

5510 Couriers and Messengers 

5520 Dispatchers 

5530 Meter Readers, Utilities 

5540 Postal Service Clerks 

5550 Postal Service Mail Carriers 

5560 Postal Service Mail Sorters, Processors, and 

 Processing Machine Operators 

5600 Production, Planning, and Expediting Clerks 

5610 Shipping, Receiving, and Traffic Clerks 

5620 Stock Clerks and Order Fillers 

5630 Weighers, Measurers, Checkers, and Samplers, 

 Recordkeeping 

5700 Secretaries and Administrative Assistants 

5800 Computer Operators 

5810 Data Entry Keyers 

5820 Word Processors and Typists 

5830 Desktop Publishers 

5840 Insurance Claims and Policy Processing Clerks 

5850 Mail Clerks and Mail Machine Operators, Except 

 Postal Service 

5860 Office Clerks, General 

5900 Office Machine Operators, Except Computer 

5910 Proofreaders and Copy Markers 

5920 Statistical Assistants 

5930 Office and Administrative Support Workers, All 

 Other 

Farming, Fishing, and Forestry Occupations 

6000 First-Line Supervisors/Managers/Contractors of 

 Farming, Fishing, and Forestry Workers 

6010 Agricultural Inspector 

2000 

Census 

code Occupation category 

Farming, Fishing, and Forestry Occupations-con 

6020 Animal Breeders 

6040 Graders and Sorters, Agricultural Products 

6050 Other Agricultural Workers 

6100 Fishers and Related Fishing Workers 

6110 Hunters and Trappers 

6120 Forest and Conservation Workers 

6130 Logging Workers 

 Construction Trades and Extraction Workers 

6200 First-Line Supervisors/Managers of Construction 

 Trades and Extraction Workers 

6210 Boilermakers 

6220 Brickmasons, Blockmasons, and Stonemasons 

6230 Carpenters 

6240 Carpet, Floor, and Tile Installers and Finishers 

6250 Cement Masons, Concrete Finishers, and 

 Terrazzo Workers 

6260 Construction Laborers 

6300 Paving, Surfacing, and Tamping Equipment 

 Operators 

6310 Pile-Driver Operators 

6320 Operating Engineers and Other Construction 

 Equipment Operators 

6330 Drywall Installers, Ceiling Tile Installers, and 

 Tapers 

6350 Electricians 

6360 Glaziers 

6400 Insulation Workers 

6420 Painters, Construction and Maintenance 

6430 Paperhangers 

6440 Pipelayers, Plumbers, Pipefitters, and Steamfitters 

6460 Plasterers and Stucco Masons 

6500 Reinforcing Iron and Rebar Workers 

6510 Roofers 

6520 Sheet Metal Workers 

6530 Structural Iron and Steel Workers 

6600 Helpers, Construction Trades 

6660 Construction and Building Inspectors 

6700 Elevator Installers and Repairers 

6710 Fence Erectors 

6720 Hazardous Materials Removal Workers 

6730 Highway Maintenance Workers 

6740 Rail-Track Laying and Maintenance Equipment 

 Operators 

6750 Septic Tank Servicers and Sewer Pipe Cleaners 

6760 Miscellaneous Construction and Related Workers 

6800 Derrick, Rotary Drill, and Service Unit Operators, 

 Oil, Gas, and Mining 

6820 Earth Drillers, Except Oil and Gas 

6830 Explosives Workers, Ordnance Handling Experts, 

 and Blasters 

6840 Mining Machine Operators 

6910 Roof Bolters, Mining 

6920 Roustabouts, Oil and Gas 

6930 Helpers--Extraction Workers 

6940 Other Extraction Workers 

Installation, Maintenance, and Repairs Workers 

7000 First-Line Supervisors/Managers of Mechanics, 

 Installers, and Repairers 
109 

2000 

Census 

code Occupation category 

Installation, Maintenance, and Repairs Workers- 

 con 

7010 Computer, Automated Teller, and Office Machine 

 Repairers 

7020 Radio and Telecommunications Equipment 

 Installers and Repairers 

7030 Avionics Technicians 

7040 Electric Motor, Power Tool, and Related Repairers 

7050 Electrical and Electronics Installers and Repairers, 

 Transportation Equipment 

7100 Electrical and Electronics Repairers, Industrial and 

 Utility 

7110 Electronic Equipment Installers and Repairers, 

 Motor Vehicles 

7120 Electronic Home Entertainment Equipment 

 Installers and Repairers 

7130 Security and Fire Alarm Systems Installers 

7140 Aircraft Mechanics and Service Technicians 

7150 Automotive Body and Related Repairers 

7160 Automotive Glass Installers and Repairers 

7200 Automotive Service Technicians and Mechanics 

7210 Bus and Truck Mechanics and Diesel Engine 

 Specialists 

7220 Heavy Vehicle and Mobile Equipment Service 

 Technicians and Mechanics 

7240 Small Engine Mechanics 

7260 Miscellaneous Vehicle and Mobile Equipment 

 Mechanics, Installers, and Repairers 

7300 Control and Valve Installers and Repairers 

7310 Heating, Air Conditioning, and Refrigeration 

 Mechanics and Installers 

7320 Home Appliance Repairers 

7330 Industrial and Refractory Machinery Mechanics 

7340 Maintenance and Repair Workers, General 

7350 Maintenance Workers, Machinery 

7360 Millwrights 

7410 Electrical Power-Line Installers and Repairers 

7420 Telecommunications Line Installers and Repairers 

7430 Precision Instrument and Equipment Repairers 

7510 Coin, Vending, and Amusement Machine 

 Servicers and Repairers 

7520 Commercial Divers 

7540 Locksmiths and Safe Repairers 

7550 Manufactured Building and Mobile Home Installers 

7560 Riggers 

7600 Signal and Track Switch Repairers 

7610 Helpers--Installation, Maintenance, and Repair 

 Workers 

7620 Other Installation, Maintenance, and Repair 

 Workers 

Production and Operating Workers 

7700 First-Line Supervisors/Managers of Production 

 and Operating Workers 

7710 Aircraft Structure, Surfaces, Rigging, and Systems 

 Assemblers 

7720 Electrical, Electronics, and Electromechanical 

 Assemblers 

7730 Engine and Other Machine Assemblers 

7740 Structural Metal Fabricators and Fitters 

7750 Miscellaneous Assemblers and Fabricators 

 

2000 

Census 

code Occupation category 

Food Preparation Occupations 

7800 Bakers 

7810 Butchers and Other Meat, Poultry, and Fish 

 Processing Workers 

7830 Food and Tobacco Roasting, Baking, and Drying 

 Machine Operators and Tenders 

7840 Food Batchmakers 

7850 Food Cooking Machine Operators and Tenders 

Setters, Operators, and Tenders 

7900 Computer Control Programmers and Operators 

7920 Extruding and Drawing Machine Setters, 

 Operators, and Tenders, Metal and Plastic 

7930 Forging Machine Setters, Operators, and Tenders, 

 Metal and Plastic 

7940 Rolling Machine Setters, Operators, and Tenders, 

 Metal and Plastic 

7950 Cutting, Punching, and Press Machine Setters, 

 Operators, and Tenders, Metal and Plastic 

7960 Drilling and Boring Machine Tool Setters, 

 Operators, and Tenders, Metal and Plastic 

8000 Grinding, Lapping, Polishing, and Buffing Machine 

 Tool Setters, Operators, and Tenders, Metal and 

 Plastic 

8010 Lathe and Turning Machine Tool Setters, 

 Operators, and Tenders, Metal and Plastic 

8020 Milling and Planing Machine Setters, Operators, 

 and Tenders, Metal and Plastic 

8030 Machinists 

8040 Metal Furnace and Kiln Operators and Tenders 

8060 Model Makers and Patternmakers, Metal and 

 Plastic 

8100 Molders and Molding Machine Setters, Operators, 

 and Tenders, Metal and Plastic 

8120 Multiple Machine Tool Setters, Operators, and 

 Tenders, Metal and Plastic 

8130 Tool and Die Makers 

8140 Welding, Soldering, and Brazing Workers 

8150 Heat Treating Equipment Setters, Operators, and 

 Tenders, Metal and Plastic 

8160 Lay-Out Workers, Metal and Plastic 

8200 Plating and Coating Machine Setters, Operators, 

 and Tenders, Metal and Plastic 

8210 Tool Grinders, Filers, and Sharpeners 

8220 Metalworkers and Plastic Workers, All Other 

8230 Bookbinders and Bindery Workers 

8240 Job Printers 

8250 Prepress Technicians and Workers 

8260 Printing Machine Operators 

8300 Laundry and Dry-Cleaning Workers 

8310 Pressers, Textile, Garment, and Related Materials 

8320 Sewing Machine Operators 

8330 Shoe and Leather Workers and Repairers 

8340 Shoe Machine Operators and Tenders 

8350 Tailors, Dressmakers, and Sewers 

8360 Textile Bleaching and Dyeing Machine Operators 

 and Tenders 

8400 Textile Cutting Machine Setters, Operators, and 

 Tenders 

8410 Textile Knitting and Weaving Machine Setters, 

 Operators, and Tenders 
110 

2000 

Census 

code Occupation category 

Setters, Operators, and Tenders-con 

8420 Textile Winding, Twisting, and Drawing Out 

 Machine Setters, Operators, and Tenders 

8430 Extruding and Forming Machine Setters, 

 Operators, and Tenders, Synthetic and Glass 

 Fibers 

8440 Fabric and Apparel Patternmakers 

8450 Upholsterers 

8460 Textile, Apparel, and Furnishings Workers, All 

 Other 

8500 Cabinetmakers and Bench Carpenters 

8510 Furniture Finishers 

8520 Model Makers and Patternmakers, Wood 

8530 Sawing Machine Setters, Operators, and Tenders, 

 Wood 

8540 Woodworking Machine Setters, Operators, and 

 Tenders, Except Sawing 

8550 Woodworkers, All Other 

8600 Power Plant Operators, Distributors, and 

 Dispatchers 

8610 Stationary Engineers and Boiler Operators 

8620 Water and Liquid Waste Treatment Plant and 

 System Operators 

8630 Miscellaneous Plant and System Operators 

8640 Chemical Processing Machine Setters, Operators, 

 and Tenders 

8650 Crushing, Grinding, Polishing, Mixing, and 

 Blending Workers 

8710 Cutting Workers 

8720 Extruding, Forming, Pressing, and Compacting 

 Machine Setters, Operators, and Tenders 

8730 Furnace, Kiln, Oven, Drier, and Kettle Operators 

 and Tenders 

8740 Inspectors, Testers, Sorters, Samplers, and 

 Weighers 

8750 Jewelers and Precious Stone and Metal Workers 

8760 Medical, Dental, and Ophthalmic Laboratory 

 Technicians 

8800 Packaging and Filling Machine Operators and 

 Tenders 

8810 Painting Workers 

8830 Photographic Process Workers and Processing 

 Machine Operators 

8840 Semiconductor Processors 

8850 Cementing and Gluing Machine Operators and 

 Tenders 

8860 Cleaning, Washing, and Metal Pickling Equipment 

 Operators and Tenders 

8900 Cooling and Freezing Equipment Operators and 

 Tenders 

8910 Etchers and Engravers 

8920 Molders, Shapers, and Casters, Except Metal and 

 Plastic 

8930 Paper Goods Machine Setters, Operators, and 

 Tenders 

8940 Tire Builders 

8950 Helpers--Production Workers 

8960 Production Workers, All Other 

2000 

Census 

code Occupation category 

Transportation and Material Moving Workers 

9000 Supervisors, Transportation and Material Moving 

 Workers 

9030 Aircraft Pilots and Flight Engineers 

9040 Air Traffic Controllers and Airfield Operations 

 Specialists 

9110 Ambulance Drivers and Attendants, Except 

 Emergency Medical Technicians 

9120 Bus Drivers 

9130 Driver/Sales Workers and Truck Drivers 

9140 Taxi Drivers and Chauffeurs 

9150 Motor Vehicle Operators, All Other 

9200 Locomotive Engineers and Operators 

9230 Railroad Brake, Signal, and Switch Operators 

9240 Railroad Conductors and Yardmasters 

9260 Subway, Streetcar, and Other Rail Transportation 

 Workers 

9300 Sailors and Marine Oilers 

9310 Ship and Boat Captains and Operators 

9330 Ship Engineers 

9340 Bridge and Lock Tenders 

9350 Parking Lot Attendants 

9360 Service Station Attendants 

9410 Transportation Inspectors 

9420 Other Transportation Workers 

9500 Conveyor Operators and Tenders 

9510 Crane and Tower Operators 

9520 Dredge, Excavating, and Loading Machine 

 Operators 

9560 Hoist and Winch Operators 

9600 Industrial Truck and Tractor Operators 

9610 Cleaners of Vehicles and Equipment 

9620 Laborers and Freight, Stock, and Material Movers, 

 Hand 

9630 Machine Feeders and Offbearers 

9640 Packers and Packagers, Hand 

9650 Pumping Station Operators 

9720 Refuse and Recyclable Material Collectors 

9730 Shuttle Car Operators 

9740 Tank Car, Truck, and Ship Loaders 

9750 Material Moving Workers, All Other 

 

 ARMED FORCES (FOR CPS) 

*9840 Armed Forces 

CPS Special Codes 

*9970 Problem Referral 

*9990 Not Reported (Includes Refused, Classified, Blank 

 and all other noncodable 

 

 MILITARY SPECIFIC OCCUPATIONS (FOR 

 ACS) 

9800 Military officer special and tactical operations l

 leaders/managers 

9810 First-line enlisted military supervisors/managers 

9820 Military enlisted tactical operations and 

 air/weapons specialists and crew members 

9830 Military, rank not specified 

* Code changed from 2000
111 

D.2 Industrial Classification System 

2000 

Census 

code Industry category 

 AGRICULTURE, FORESTRY, FISHING AND 

 HUNTING 

0170 AGR-Crop production 

0180 AGR-Animal production 

0190 AGR-Forestry except Logging 

0270 AGR-Logging 

0280 AGR-Fishing, hunting, and trapping 

0290 AGR-Support activities for agriculture and forestry 

 MINING 

0370 EXT-Oil and gas extraction 

0380 EXT-Coal mining 

0390 EXT-Metal ore mining 

0470 EXT-Nonmetallic mineral mining and quarrying 

0480 EXT-Not specified type of mining 

0490 EXT-Support activities for mining Utilities 

0570 UTL-Electric power generation, transmission and 

 distribution 

0580 UTL-Natural gas distribution 

0590 UTL-Electric and gas, and other combinations 

0670 UTL-Water, steam, air conditioning, and irrigation 

 systems 

0680 UTL-Sewage treatment facilities 

0690 UTL-Not specified utilities 

 CONSTRUCTION 

0770 ** CON-Construction 

(Includes the cleaning of buildings and dwellings is 

incidental during construction and immediately after 

construction) 

 MANUFACTURING 

 Nondurable Goods 

 Food Manufacturing 

1070 MFG-Animal food, grain and oilseed milling 

1080 MFG-Sugar and confectionery products 

1090 MFG-Fruit and vegetable preserving and specialty 

 foods 

1170 MFG-Dairy products 

1180 MFG-Animal slaughtering and processing 

1190 MFG-Retail bakeries 

1270 MFG-Bakeries, except retail 3118 exc. 

1280 MFG-Seafood and other miscellaneous foods, 

 n.e.c. 

1290 MFG-Not specified food industries 

Beverage and Tobacco Products 

 Manufacturing 

1370 MFG-Beverage 

1390 MFG-Tobacco 

2000 

Census 

code Industry category 

 MANUFACTURING Nondurable Goods-Con

 Textile Mills and Textile Product Mills 

1470 MFG-Fiber, yarn, and thread mills 

1480 MFG-Fabric mills, except knitting 

1490 MFG-Textile and fabric finishing and coating mills 

1570 MFG-Carpets and rugs 

1590 MFG-Textile product mills except carpets and rugs 

 Apparel Manufacturing 

1670 MFG-Knitting mills 

1680 MFG-Cut and sew apparel 

1690 MFG-Apparel accessories and other apparel 

 Leather and Allied Product Manufacturing 

1770 MFG-Footwear 

1790 MFG-Leather tanning and products, except 

 footwear 

 Paper Manufacturing 

1870 MFG-Pulp, paper, and paperboard mills 

1880 MFG-Paperboard containers and boxes 

1890 MFG-Miscellaneous paper and pulp products 

 Printing and Related Support Activities 

1990 MFG-Printing and related support activities 

Petroleum and Coal Products Manufacturing 

2070 MFG-Petroleum refining 

2090 MFG-Miscellaneous petroleum and coal products 

 Chemical Manufacturing 

2170 MFG-Resin, synthetic rubber and fibers, and 

 filaments 

2180 MFG-Agricultural chemicals 

2190 MFG-Pharmaceuticals and medicines 

2270 MFG-Paint, coating, and adhesives 

2280 MFG-Soap, cleaning compound, and cosmetics 

2290 MFG-Industrial and miscellaneous chemicals 

 Plastics and Rubber Product Manufacturing 

2370 MFG-Plastics products 

2380 MFG-Tires 

2390 MFG-Rubber products, except tires 

 Durable Goods 

Nonmetallic Mineral Product Manufacturing 

2470 MFG-Pottery, ceramics, and related products 

2480 MFG-Structural clay products 

2490 MFG-Glass and glass products 

2570 MFG-Cement, concrete, lime, and gypsum 

 products 

2590 MFG-Miscellaneous nonmetallic mineral products 

 Metal Industries 

2670 MFG-Iron and steel mills and steel products 

2680 MFG-Aluminum production and processing 

2690 MFG-Nonferrous metal, except aluminum, 

 production and processing 

2770 MFG-Foundries 

2780 MFG-Metal forgings and stampings 
112 

2000 

Census 

code Industry category 

 MANUFACTURING Durable Goods-Con 

Metal Industries-Con 

2790 MFG-Cutlery and hand tools 

2870 MFG-Structural metals, and tank and shipping 

 containers 

2880 MFG-Machine shops; turned products; screws, 

 nuts and bolts 

2890 MFG-Coating, engraving, heat treating and allied 

 activities 

2970 MFG-Ordnance 

2980 MFG-Miscellaneous fabricated metal products 

2990 MFG-Not specified metal industries 

 Machinery Manufacturing 

3070 MFG-Agricultural implements 33311 

3080 MFG-Construction mining and oil field machinery 

3090 MFG-Commercial and service industry machinery 

3170 MFG-Metalworking machinery 

3180 MFG-Engines, turbines, and power transmission 

 equipment 

3190 MFG-Machinery, n.e.c. 

3290 MFG-Not specified machinery 

 Computer and Electronic Product Manufacturing 

3360 MFG-Computer and peripheral equipment 

3370 MFG-Communications, audio, and video 

 equipment 

3380 MFG-Navigational, measuring, electomedical, and 

 control instruments 

3390 MFG-Electronic components and products, n.e.c. 

 Electrical Equipment, Appliances, and Component 

 Manufacturing 

3470 MFG-Household appliances 

3490 MFG-Electrical machinery, equipment, and 

 supplies, n.e.c. 

 Transportation Equipment Manufacturing 

3570 MFG-Motor vehicles and motor vehicle equipment 

3580 MFG-Aircraft and parts 

3590 MFG-Aerospace products and parts 

3670 MFG-Railroad rolling stock 

3680 MFG-Ship and boat building 

3690 MFG-Other transportation equipment 

 Wood Products, including Furniture, 

 Manufacturing 

3770 MFG-Sawmills and wood preservation 

3780 MFG-Veneer, plywood, and engineered wood 

 products 

3790 MFG-Prefabricated wood buildings and mobile 

 homes 

3870 MFG-Miscellaneous wood products 

3890 MFG-Furniture and Fixtures 

 Miscellaneous Manufacturing 

3960 MFG-Medical equipment and supplies 

3970 MFG-Toys, amusement, and sporting goods 

3980 MFG-Miscellaneous manufacturing, n.e.c. 

3990 MFG-Not specified industries 

2000 

Census 

code Industry category 

 WHOLESALE TRADE 

 Durable Goods, Wholesalers 

4070 ** WHL-Motor vehicles, parts and supplies 

4080 ** WHL-Furniture and home furnishing 

4090 ** WHL-Lumber and other construction materials 

4170 ** WHL-Professional and commercial equipment 

 and supplies 

4180 ** WHL-Metals and minerals, except petroleum 

4190 ** WHL-Electrical goods 

4260 ** WHL-Hardware, plumbing and heating 

 equipment, and supplies 

4270 ** WHL-Machinery, equipment , and supplies 

4280 ** WHL-Recyclable material 

4290 ** WHL-Miscellaneous durable goods 

 Nondurable Goods, Wholesalers 

4370 ** WHL-Paper and paper products 

4380 ** WHL-Drugs, sundries, and chemical and allied 

 products 

4390 ** WHL-Apparel, fabrics, and notions 

4470 ** WHL-Groceries and related products 

4480 ** WHL-Farm product raw materials 

4490 ** WHL-Petroleum and petroleum products 

4560 ** WHL-Alcoholic beverages 

4570 ** WHL-Farm supplies 

4580 ** WHL-Miscellaneous nondurable goods 

*4585 *** WHL-Wholesale electronic markets, agents, 

 and brokers (New Industry)* 

4590 WHL-Not specified trade 

 RETAIL TRADE 

4670 RET-Automobile dealers 

4680 RET-Other motor vehicle dealers 

4690 RET-Auto parts, accessories, and tire stores 

4770 RET-Furniture and home furnishings stores 

4780 RET-Household appliance stores 

4790 RET-Radio, TV, and computer stores 

4870 RET-Building material and supplies dealers 

4880 RET-Hardware stores 

4890 RET-Lawn and garden equipment and supplies 

 stores 

4970 RET-Grocery stores 

4980 RET-Specialty food stores 

4990 RET-Beer, wine, and liquor stores 

5070 RET-Pharmacies and drug stores 

5080 RET-Health and personal care, except drug, 

 stores 

5090 RET-Gasoline stations 

5170 RET-Clothing and accessories, except shoe, 

 stores 

5180 RET-Shoe stores 

5190 RET-Jewelry, luggage, and leather goods stores 

5270 RET-Sporting goods, camera, and hobby and toy 

 stores 

5280 RET-Sewing, needlework and piece goods stores 

5290 RET-Music stores 

5370 RET-Book stores and news dealers 

5380 **RET-Department stores and Discount stores 

5390 RET-Miscellaneous general merchandise stores 

5470 RET-Retail florists 

5480 RET-Office supplies and stationary stores 

5490 RET-Used merchandise stores 
113 

2000 

Census 

code Industry category 

 RETAIL TRADE-Con 

5570 RET-Gift, novelty, and souvenir shops 

5580 RET-Miscellaneous stores 

5590 *** RET-Electronic shopping (New Industry) 

*5591 *** RET-Electronic auctions (New Industry) 

*5592 ** RET-Mail order houses 

5670 RET-Vending machine operators 

5680 RET-Fuel dealers 

5690 RET-Other direct selling establishments 

5790 RET-Not specified trade 

 TRANSPORTATION AND WAREHOUSING 

6070 TRN-Air transportation 

6080 TRN-Rail transportation 

6090 TRN-Water transportation 

6170 TRN-Truck transportation 

6180 TRN-Bus service and urban transit 

6190 TRN-Taxi and limousine service 

6270 TRN-Pipeline transportation 

6280 TRN-Scenic and sightseeing transportation 

6290 TRN-Services incidental to transportation 

6370 TRN-Postal Service 

6380 TRN-Couriers and messengers 

6390 TRN-Warehousing and storage 

 INFORMATION AND COMMUNICATIONS 

 Publishing Industries 

6470 INF-Newspaper publishers 

6480 INF-Publishing, except newspapers and software 

6490 INF-Software publishing 

6570 INF-Motion pictures and video industries 

6590 INF-Sound recording industries 

 Broadcasting and Telecommunications 

6670 INF-Radio and television broadcasting and cable 

*6675 ***INF-Internet publishing and broadcasting 

 (New Industry) 

6680 INF-Wired telecommunications carriers 

6690 INF-Other telecommunication services 

*6692 ***INF-Internet service providers (New Industry) 

*6695 **INF-Data processing, hosting, and related 

 services 

 Information Services and Data Processing Services 

6770 INF-Libraries and archives 

6780 INF-Other information services 

 FINANCE, INSURANCE, REAL ESTATE, AND 

 RENTAL AND LEASING 

 Finance and Insurance 

6870 FIN-Banking and related activities 

6880 FIN-Savings institutions, including credit unions 

6890 FIN-Non-depository credit and related activities 

6970 FIN-Securities, commodities, funds, trusts, and 

 other financial investments 

6990 FIN-Insurance carriers and related activities 

2000 

Census 

code Industry category 

 FINANCE, INSURANCE, REAL ESTATE, AND 

 RENTAL AND LEASING-Con 

 Real Estate and Rental and Leasing 

7070 FIN-Real estate 

7080 FIN-Automotive equipment rental and leasing 

7170 FIN-Video tape and disk rental 

7180 FIN-Other consumer goods rental 

7190 FIN-Commercial, industrial, and other intangible 

 assets rental and leasing 

PROFESSIONAL, SCIENTIFIC, MANAGEMENT, 

 ADMINISTRATIVE, AND WASTE 

 MANAGEMENT SERVICES 

 Professional, Scientific, and Technical Services 

7270 PRF-Legal services 

7280 PRF-Accounting, tax preparation, bookkeeping 

 and payroll services 

7290 PRF-Architectural, engineering, and related 

 services 

7370 PRF-Specialized design services 

7380 PRF-Computer systems design and related 

 services 

7390 PRF-Management, scientific and technical 

 consulting services 

7460 PRF-Scientific research and development services 

7470 PRF-Advertising and related services 

7480 PRF-Veterinary services 

7490 PRF-Other professional, scientific and technical 

 services 

 Management, Administrative and Support, and 

 Waste Management Services 

7570 PRF-Management of companies and enterprises 

7580 PRF-Employment services 

7590 PRF-Business support services 

7670 PRF-Travel arrangements and reservation 

 services 

7680 PRF-Investigation and security services 

7690 **PRF-Services to buildings and dwellings (except 

 cleaning during construction and immediately after 

 construction 

7770 PRF-Landscaping services 

7780 PRF-Other administrative, and other support 

 services 

7790 PRF-Waste management and remediation 

 services 

 EDUCATIONAL, HEALTH AND SOCIAL 

 SERVICES

 Educational Services 

7860 EDU-Elementary and secondary schools 

7870 EDU-Colleges, including junior colleges, and 

 universities 

7880 EDU-Business, technical, and trade schools and 

 training 

7890 EDU-Other schools, instruction and educational 

 services 
114 

2000 

Census 

code Industry category 

 EDUCATIONAL, HEALTH AND SOCIAL 

 SERVICES-Con 

 Health Care 

7970 MED-Offices of physicians 

7980 MED-Offices of dentists 

7990 MED-Office of chiropractors 

8070 MED-Offices of optometrists 

8080 MED-Offices of other health practitioners 

8090 MED-Outpatient care centers 

8170 MED-Home health care services 

8180 MED-Other health care services 

8190 MED-Hospitals 

8270 MED-Nursing care facilities 

8290 MED-Residential care facilities, without nursing 

 Social Assistance 

8370 SCA-Individual and family services 

8380 SCA-Community food and housing, and 

 emergency services 

8390 SCA-Vocational rehabilitation services 

8470 SCA-Child day care services 

 ARTS, ENTERTAINMENT, RECREATION, 

 ACCOMMODATIONS, AND FOOD SERVICES 

 Arts, Entertainment, and Recreation 

8560 ENT-Independent artists, performing arts, 

 spectator sports and related industries 

8570 ENT-Museums, art galleries, historical sites, and 

 similar institutions 

8580 ENT-Bowling centers 

8590 ENT-Other amusement, gambling, and recreation 

 industries 

 Accommodations and Food Services 

8660 ENT-Traveler accommodation 

8670 ENT-Recreational vehicle parks and camps, and 

 rooming and boarding houses 

8680 ENT-Restaurants and other food services 

8690 ENT-Drinking places, alcohol beverages 

 OTHER SERVICES (EXCEPT PUBLIC 

 ADMINISTRATION) 

 Repair and Maintenance 

8770 SRV-Automotive repair and maintenance 

8780 SRV-Car washes 

8790 SRV-Electronic and precision equipment repair 

 and maintenance 

8870 SRV-Commercial and industrial machinery and 

 equipment repair and maintenance 

8880 SRV-Personal and household goods repair and 

 maintenance 

8890 SRV-Footwear and leather goods repair 

 Personal and Laundry Services 

8970 SRV-Barber shops 

8980 SRV-Beauty salons 

8990 SRV-Nail salons and other personal care services 

9070 SRV-Dry cleaning and laundry services 

9080 SRV-Funeral homes, cemeteries and crematories 

9090 SRV-Other personal services 

 

2000 

Census 

code Industry category 

 Religious, Grantmaking, Civic, Business, and 

 Similar Organizations 

9160 SRV-Religious organizations 

9170 SRV-Civic, social, advocacy organizations and 

 grantmaking and giving service 

9180 SRV-Labor unions 

9190 SRV-Business, professional, political and similar 

 organizations 

 Private Households 

9290 SRV-Private households 

PUBLIC ADMINISTRATION 

9370 ADM-Executive offices and legislative bodies 

9380 ADM-Public finance activities 

9390 ADM-Other general government and support 

9470 ADM-Justice, public order, and safety activities 

9480 ADM-Administration of human resource programs 

9490 ADM-Administration of environmental quality and 

 housing programs 

9570 ADM-Administration of economic programs and 

 space research 

9590 ADM-National security and international affairs 

* ARMED FORCES (FOR CPS ONLY) 

9890 Armed Forces 

 CPS Special Codes 

9970 Problem Referral 

9990 Uncodable (Includes Refused or reported 

 Classified) 

 Active Duty Military (for Census and ACS) 

9670 U. S. Army 

9680 U. S. Air Force 

9690 U. S. Navy 

9770 U. S. Marines 

9780 U. S. Coast Guard 

9790 U. S. Armed Forces, Branch Not Specified 

9870 Military Reserves or National Guard 

 * Code changed from 2000 

 ** Name changed from 2000 and Industry content 

changed 

*** New industry 
115 

Appendix E: Selected Data Tables 
116 
117

 70322 

Table 2.1 Substance Use and Substance Dependence or Abuse among Persons Aged 18 to 64, by Employment Status: Percenta

Thousands, and Percentage Distributions, Annual Averages Based on 2002-2004 

Employment Status 

Past Month 

Illicit Drug Use1 

Past Month 

Marijuana Use 

Past Month Heavy 

Alcohol Use2

Past Year Illicit Drug 

Dependence or Abuse3 

Percentage Total 9.2 7.0 8.4 3.2  Full-Time 8.2 6.4 8.8 2.6  Part-Time 11.9 9.6 8.6 4.1  Unemployed 18.6 13.9 13.6 8.0  Other4 8.3 5.9 5.6 3.5 Number (in Thousands) Total 16,363 12,569 15,017 5,737  Full-Time 9,413 7,293 10,113 3,030  Part-Time 2,903 2,339 2,094 989  Unemployed 1,405 1,050 1,028 608  Other4 2,642 1,888 1,783 1,110 Percentage Distribution Total 100.0 100.0 100.0 100.0  Full-Time 57.5 58.0 67.3 52.8  Part-Time 17.7 18.6 13.9 17.2  Unemployed 8.6 8.4 6.8 10.6  Other4 16.1 15.0 11.9 19.4 

*Low precision; no estimate reported. 1 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used non2 Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) 

the past 30 days. 

3 Dependence or abuse is based on the definition found in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). 4 Retired persons, disabled persons, homemakers, students, or other persons not in the labor force are included in the Other Employment category. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
118

70320 Table 2.2 Illicit Drug, Marijuana, and Heavy Alcohol Use in the Past Month among Full-Time Workers Aged 18 to 64, by Dem

Percentages and Numbers in Thousands, Annual Averages Based on 2002-2004 

Past Month Illicit Drug Use1 Past Month Marijuana Use Past Mo

Demographic Characteristic Percentage 

Number 

(in Thousands) Percentage 

Number 

(in Thousands) Percent

Total 8.2 9,413 6.4 7,293 8.8 Age 18-25 19.0 2,798 15.9 2,343 16.3  26-34 10.3 2,573 8.0 1,982 10.4  35-49 7.0 3,309 5.2 2,444 8.1 

50-64 2.6 733 1.9 525 4.7 

Gender Male 9.7 6,384 7.9 5,167 12.3  Female 6.2 3,029 4.3 2,126 4.1 Hispanic Origin and Race Not Hispanic or Latino 8.4 8,389 6.6 6,597 9.1  White 8.8 6,989 6.9 5,510 10.1  Black or African American 8.0 1,060 6.4 847 5.4  American Indian or Alaska  Native 7.3 44 4.7 28 8.7  Native Hawaiian or Other  Pacific Islander 13.0 47 9.1 33 9.4  Asian 2.2 106 1.3 64 2.9  Two or More Races 13.5 143 11.0 116 7.5  Hispanic or Latino 6.7 1,024 4.6 696 6.9 

*Low precision; no estimate reported. 1 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used non2 Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) 

past 30 days. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
119

70320 Table 2.3 Illicit Drug, Marijuana, and Heavy Alcohol Use in the Past Month among Full-Time Workers Aged 18 to 64, by Edu

Family Income, and Geographic Characteristics: Percentages and Numbers in Thousands, Annual Averages Based o

Past Month Illicit Drug Use1 Past Month Marijuana Use Past Mo

Educational Attainment, Family Income, and Geographic Characteristic Percentage 

Number 

(in Thousands) Percentage 

Number 

(in Thousands) Percent

Total 8.2 9,413 6.4 7,293 8.8 Education Less Than High School 11.2 1,605 8.6 1,227 10.8  High School Graduate 9.0 3,193 7.0 2,479 10.0  Some College 8.7 2,604 6.9 2,068 8.9  College Graduate 5.7 2,011 4.3 1,519 6.7 Family Income  Less Than $20,000 13.2 1,570 10.0 1,191 9.8  $20,000-49,999 9.1 3,815 7.3 3,032 9.7  $50,000-74,999 7.5 1,853 5.7 1,419 9.1  $75,000 or More 6.0 2,175 4.6 1,652 7.3 Geographic Region Northeast 8.9 1,947 7.4 1,608 8.4  Midwest 8.0 2,085 6.2 1,613 10.6  South 7.6 3,143 5.6 2,318 8.5 

West 8.8 2,239 6.9 1,754 7.8 

County Type3 Large MSA 8.3 5,323 6.5 4,149 8.1  Small MSA 8.8 2,908 6.9 2,262 9.8  MiSA 7.1 757 5.4 581 9.2  Noncore Adjacent with Town 6.2 311 4.6 228 10.4  Noncore Adjacent, No Town 4.5 47 3.1 32 9.1  Noncore Rural, Not Adjacent 5.7 67 3.5 40 7.5 

*Low precision; no estimate reported. 1 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used non2 Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) 

past 30 days. 

3 Definitions for county type are based on 2003 Urban Influence Codes (UICs), which are provided as a service by the United States Department of Ag

estimates are not comparable with estimates by county type published in other NSDUH reports. MSA refers to metropolitan statistical area and MiSA statistical area. Noncore is defined as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
120

70320 Table 2.4 Substance Dependence or Abuse in the Past Year among Full-Time Workers Aged 18 to 64, by Demographic Charac

Numbers in Thousands, Annual Averages Based on 2002-2004 

Past Year Illicit Drug Dependence or Abuse Past Year Alcohol Dep

Demographic Characteristic Percentage 

Number 

(in Thousands) Percentage 

Total 2.6 3,030 9.2 Age 18-25 7.5 1,109 18.4  26-34 3.3 831 12.3  35-49 1.9 887 7.8 

50-64 0.7 203 4.0 

Gender Male 3.3 2,152 11.8  Female 1.8 878 5.7 Hispanic Origin and Race Not Hispanic or Latino 2.6 2,546 9.1  White 2.5 2,020 9.6  Black or African American 2.9 382 7.3  American Indian or Alaska  Native 4.5 27 10.7  Native Hawaiian or Other  Pacific Islander 4.3 16 9.4  Asian 1.1 56 4.6  Two or More Races 4.3 46 10.1  Hispanic or Latino 3.2 484 10.0 

*Low precision; no estimate reported. NOTE: Dependence or abuse is based on the definition found in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-I

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
121

70320 Table 2.5 Substance Dependence or Abuse in the Past Year among Full-Time Workers Aged 18 to 64, by Educational Attainm

Geographic Characteristics: Percentages and Numbers in Thousands, Annual Averages Based on 2002-2004 

Educational Attainment, Family Past Year Illicit Drug Dependence or Abuse Past Year Alcohol DepIncome, and Geographic Characteristic Percentage 

Number 

(in Thousands) Percentage 

Total 2.6 3,030 9.2 Education Less Than High School 5.1 725 11.9  High School Graduate 2.9 1,018 9.4  Some College 2.9 863 9.7  College Graduate 1.2 425 7.5 Family Income  Less Than $20,000 5.6 661 13.3  $20,000-49,999 3.0 1,255 9.8  $50,000-74,999 2.0 500 8.7  $75,000 or More 1.7 613 7.6 Geographic Region Northeast 2.6 570 8.3  Midwest 2.4 614 10.5  South 2.7 1,104 8.5 

West 2.9 742 9.9 

County Type1 Large MSA 2.7 1,725 9.3  Small MSA 2.7 902 9.5  MiSA 2.7 283 8.2  Noncore Adjacent with Town 1.7 87 9.2  Noncore Adjacent, No Town 1.1 11 8.0  Noncore Rural, Not Adjacent 1.9 22 7.9 

*Low precision; no estimate reported. NOTE: Dependence or abuse is based on the definition found in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-I1 Definitions for county type are based on 2003 Urban Influence Codes (UICs), which are provided as a service by the United States Department of Ag

estimates are not comparable with estimates by county type published in other NSDUH reports. MSA refers to metropolitan statistical area and MiSA statistical area. Noncore is defined as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
122

61115 Table 3.1 Sample Sizes, Average Age, and Percentage Distribution of Males among Full-Time Workers Aged 18 to 64, by Occu

Annual Averages Based on 2002-2004 

Occupational Category Sample Size 

Population 

(in Thousands) Average Age 

Total1 73,325 114,675 40.1 Management Occupations 7,097 14,272 42.7  Chief Executives 333 962 46.6  Advertising, Marketing, Promotions, Public Relations,  and Sales Managers 408 798 40.3 Financial Occupations 1,482 2,734 41.3 Mathematical and Computer Scientists 1,685 3,216 39.0 Engineering, Architecture, and Surveyors 1,452 2,883 41.7  Drafters and Engineering Technicians 355 597 39.6 Life, Physical, and Social Science Occupations 792 1,370 40.5  Physical Scientists 360 690 40.4  Social Scientists and Related Workers 190 327 41.5 Community and Social Services Occupations 1,180 2,010 42.7 Legal Occupations 719 1,401 42.3  Lawyers 327 758 42.7 Education, Training, and Library Occupations 3,679 6,241 42.5  Elementary and Middle School Teachers 1,359 2,456 42.3  Secondary School Teachers 587 1,010 42.3  Special Education Teachers 201 347 43.2  Other Teachers and Instructors 1,024 1,590 41.6 Arts, Design, Entertainment, Sports, and Media Occupations 1,298 2,155 38.9 

See notes at end of table. 
123

61115 Table 3.1 Sample Sizes, Average Age, and Percentage Distribution of Males among Full-Time Workers Aged 18 to 64, by Occu

Annual Averages Based on 2002-2004 (continued) 

Occupational Category Sample Size 

Population 

 (in Thousands) Average Age 

Healthcare Practitioners and Technical Occupations 4,823 7,605 40.8  Health Diagnosing and Treatment Practitioners 1,782 3,609 42.8  Registered Nurses 1,000 2,057 43.8  Health Care Technical and Support Occupations 3,041 3,995 39.0  Nursing, Psychiatric, and Home Health Aides 1,238 1,564 39.8 Protective Service Occupations 1,532 2,605 40.1  Protective Service Managers and Supervisors, 

Firefighter and Prevention Workers, Law 

 Enforcement Workers 943 1,747 40.0 

 Other Protective Service Workers 589 858 40.4 Food Preparation and Serving Related Occupations 4,779 4,660 33.9  Food Preparation Supervisors and Managers 599 595 34.2  Cooks 1,540 1,745 36.1  Food Preparation Workers 513 570 34.5  Food and Beverage Serving and Other Food  Preparation Serving Related Occupations 2,127 1,751 31.5 Building and Grounds Cleaning and Maintenance Occupations 2,269 3,439 40.4 Personal Care and Service Occupations 1,845 2,357 38.3  Personal Appearance Workers 457 622 37.7  Child Care Workers 784 922 37.7  Personal and Homecare Aides 270 446 41.5 Sales and Related Occupations 8,102 11,581 39.1  Retail Sales 1,621 1,956 37.4  Sales Representatives, Services 259 473 38.9  Sales Representatives, Wholesale and Manufacturing 708 1,393 40.5 

See notes at end of table. 
124

61115 Table 3.1 Sample Sizes, Average Age, and Percentage Distribution of Males among Full-Time Workers Aged 18 to 64, by Occu

Annual Averages Based on 2002-2004 (continued) 

Occupational Category Sample Size 

Population 

 (in Thousands) Average Age 

Office and Administrative Support Occupations 10,504 15,587 40.0 Farming, Fishing, and Forestry Occupations 746 1,022 40.3 Construction and Extraction Occupations 5,881 8,234 37.5  Carpenters 1,387 1,892 37.3  Carpet, Floor, Tile Installers, and Finishers 197 241 33.4  Construction Laborer 805 927 33.1  Construction Equipment Operator 261 409 42.5  Electricians 516 815 38.9  Roofers 218 217 33.0  Other Construction Related Workers 1,682 2,377 37.6  Extraction Workers 115 117 36.2 Installation, Maintenance, and Repair Occupations 3,001 4,931 39.6 Production Occupations 5,502 8,930 40.0 Transportation and Material-Moving Occupations 4,469 6,752 39.6  Motor Vehicle Operators 119 236 42.9  Bus Drivers 162 405 44.6  Truck Drivers, Heavy and Tractor-Trailer 1,945 3,379 40.2  Material-Moving Workers 1,782 2,010 36.2 

*Low precision; no estimate reported. 1 Estimates in the Total row include respondents with unknown or other occupational information. Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
125

60425 Table 3.2 Sample Sizes, Average Age, and Percentage Distribution of Males among Full-Time Workers Aged 18 to 64, by Indu

Averages Based on 2002-2004 

Industry Category Sample Size 

Population 

(in Thousands) Average Age 

Total1 73,325 114,675 40.1 Agriculture, Forestry, Fishing, and Hunting 1,258 1,740 41.4  Crop Production 486 721 40.7  Animal Production 491 643 42.4 Mining 377 516 43.7 Utilities 535 1,077 43.6 Construction 7,231 10,671 38.3 Manufacturing 9,369 16,946 40.8  Food Manufacturing 940 1,443 39.3  Textile Mills and Textile Product Mills 194 385 39.4  Apparel Manufacturing 192 378 38.8  Wood Product Manufacturing 797 1,205 39.2  Paper Manufacturing 281 552 41.0  Printing and Related Support Activities 458 798 39.9  Chemical Manufacturing 677 1,329 40.7  Plastics and Rubber Products Manufacturing 437 762 39.9  Nonmetallic Mineral Product Manufacturing 278 494 40.7  Metal Industries Manufacturing 992 1,696 40.6  Machinery Manufacturing 710 1,324 42.6  Computer and Electronic Product Manufacturing 799 1,653 39.9  Electrical Equipment, Appliance, and Component  Manufacturing 295 521 41.6  Transportation Equipment Manufacturing 1,439 2,725 42.7  Miscellaneous Manufacturing 651 1,238 40.3 Wholesale Trade 2,399 3,928 39.3  Merchant Wholesalers, Durable Goods 1,134 1,964 39.8  Merchant Wholesalers, Nondurable Goods 1,265 1,964 38.9 

See notes at end of table. 
126

60425 Table 3.2 Sample Sizes, Average Age, and Percentage Distribution of Males among Full-Time Workers Aged 18 to 64, by Indu

Averages Based on 2002-2004 (continued) 

Industry Category Sample Size 

Population 

(in Thousands) Average Age 

Retail Trade 8,532 10,831 37.7  Motor Vehicle and Parts Dealers 975 1,325 38.4  Furniture and Home Furnishings Stores 412 559 38.6  Electronics and Appliance Stores 523 722 37.2  Building Material and Garden Equipment and Supplies  Dealers 710 972 38.9  Food and Beverage Stores (including Beer, Wine, and  Liquor Stores) 1,544 2,008 37.7  Health and Personal Care Stores 571 721 37.2  Gasoline Stations 442 433 35.2  Clothing and Clothing Accessories Stores 865 930 35.0  Sporting Goods, Hobby, Book, and Music Stores 453 522 36.9  General Merchandise Stores 187 242 38.0  Department Stores 762 771 35.4  Miscellaneous Store Retailers 544 853 41.7 

Non-Store Retailers 544 774 38.9 

Transportation and Warehousing 2,628 5,094 42.3  Air Transportation 241 441 41.7  Rail Transportation 127 249 43.5  Truck Transportation 802 1,522 41.4  Transit and Ground Passenger Transportation 266 634 43.6  Support Activities for Transportation 384 656 41.0  Postal Service 325 783 46.7  Warehousing and Storage 143 254 40.3 Information 1,721 2,821 39.2  Publishing Industries (except Internet) 525 826 38.0  Broadcasting (except Internet) and  Telecommunications 978 1,642 39.4  Internet Publishing and Broadcasting, Internet Service  Providers, Web Search Portals, and Data Processing  Services 195 323 41.6 

See notes at end of table. 
127

60425 Table 3.2 Sample Sizes, Average Age, and Percentage Distribution of Males among Full-Time Workers Aged 18 to 64, by Indu

Averages Based on 2002-2004 (continued) 

Industry Category Sample Size 

Population 

(in Thousands) Average Age 

Finance and Insurance 3,678 5,795 39.9  Securities, Commodity Contracts, Funds, Trusts, and  Other Financial Investments and Related Activities 560 1,116 39.7  Insurance Carriers and Related Activities 1,232 2,097 41.6  Banking, Savings Institutions (including Credit  Unions), and Related Activities 1,252 1,702 39.1 Real Estate and Rental and Leasing 1,057 1,992 42.3  Real Estate 803 1,691 43.3  Rental and Leasing Services (including Leasers of Non- Financial Intangible Assets) 254 301 36.7 Professional, Scientific, and Technical Services 4,115 7,508 40.2 Management of Companies and Enterprises, Administrative, Support, Waste Management, and Remediation Services 2,948 4,133 37.9  Investigation and Security Services 407 573 39.0  Janitorial Services 573 912 39.4  Landscaping Services 712 937 36.1  Waste Management and Remediation Services 214 376 39.8 Educational Services 4,709 8,929 43.6  Elementary and Secondary Schools 3,676 7,036 43.7  Colleges 811 1,523 43.6 Health Care and Social Assistance 8,467 13,326 41.0  Home Health Care Services 322 598 43.5  Hospitals 1,941 3,272 41.3  Nursing and Residential Care Facilities 1,267 1,707 40.0  Social Assistance 1,741 2,224 39.3  Individual and Family Services 561 887 42.2  Child Day Care Services 1,069 1,212 37.4 

See notes at end of table. 
128

60425 Table 3.2 Sample Sizes, Average Age, and Percentage Distribution of Males among Full-Time Workers Aged 18 to 64, by Indu

Averages Based on 2002-2004 (continued) 

Industry Category Sample Size 

Population 

(in Thousands) Average Age 

Arts, Entertainment, and Recreation 1,253 1,607 37.9  Performing Arts, Spectator, and Related Industries 325 533 38.7  Amusement, Gambling, and Recreation Industries 779 840 37.0 Accommodations and Food Services 5,887 5,771 34.1  Traveler Accommodation 659 814 39.2  Food Services and Drinking Places 5,174 4,916 33.2 Other Services (except Public Administration) 3,504 5,236 39.5  Repair and Maintenance 1,672 2,428 38.3  Automotive Repair and Maintenance 1,126 1,585 37.1  Commercial and Industrial Machinery and  Equipment 208 356 40.3  Personal and Laundry Services 960 1,392 38.7  Personal Care Services 565 779 37.9  Religious, Grantmaking, Civic, Professional, and  Similar Organizations 537 944 43.3  Religious Organizations 274 553 44.7  Civic and Social Organizations 204 289 40.0 Public Administration 3,443 6,373 42.9  Executive, Legislative, and Other General Government  Support 934 1,705 44.1  Justice, Public Order, and Safety Activities 1,351 2,545 41.2 

*Low precision; no estimate reported. 1 Estimates in the Total row include respondents with unknown or other industry information. Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
129

61115 Table 3.3 Illicit Drug, Marijuana, and Heavy Alcohol Use in the Past Month among Full-Time Workers Aged 18 to 64, by Occu

Percentages and Numbers in Thousands, Annual Averages Based on 2002-2004 

Past Month Illicit Drug Use Past Month Marijuana Use 

Occupational Category Percentage 

Number 

(in Thousands) Percentage 

Number 

(in Thousands) Per

Total1 8.2 9,413 6.4 7,293 Management Occupations 6.1 876 4.5 641  Chief Executives 3.6 35 3.1 30  Advertising, Marketing, Promotions, Public Relations,  and Sales Managers 6.2 50 3.5 28 Financial Occupations 4.9 133 3.3 91 Mathematical and Computer Scientists 6.9 222 5.5 178 Engineering, Architecture, and Surveyors 6.9 199 6.0 172  Drafters and Engineering Technicians 12.7 76 10.2 61 Life, Physical, and Social Science Occupations 7.0 95 5.0 68  Physical Scientists 7.2 50 4.6 32  Social Scientists and Related Workers 7.4 24 6.7 22 Community and Social Services Occupations 4.0 80 2.4 49 Legal Occupations 4.8 68 3.9 55  Lawyers 4.3 33 3.0 23 Education, Training, and Library Occupations 4.1 254 3.2 198  Elementary and Middle School Teachers 3.1 76 2.3 57  Secondary School Teachers 4.4 44 3.3 33  Special Education Teachers 5.3 19 2.9 10  Other Teachers and Instructors 5.1 82 4.4 70 Arts, Design, Entertainment, Sports, and Media Occupations 12.4 267 10.1 218 

See notes at end of table. 
130

61115 Table 3.3 Illicit Drug, Marijuana, and Heavy Alcohol Use in the Past Month among Full-Time Workers Aged 18 to 64, by Occu

Percentages and Numbers in Thousands, Annual Averages Based on 2002-2004 (continued) 

Past Month Illicit Drug Use Past Month Marijuana Use 

Occupational Category Percentage 

Number 

(in Thousands) Percentage 

Number 

(in Thousands) Per

Healthcare Practitioners and Technical Occupations 6.1 463 3.9 293  Health Diagnosing and Treatment Practitioners 4.4 159 2.6 95  Registered Nurses 4.6 95 3.3 68  Health Care Technical and Support Occupations 7.6 303 4.9 198  Nursing, Psychiatric, and Home Health Aides 7.5 117 5.7 89 Protective Service Occupations 3.4 89 2.4 63  Protective Service Managers and Supervisors, 

Firefighter and Prevention Workers, Law 

 Enforcement Workers 1.5 25 1.1 19 

 Other Protective Service Workers 7.4 63 5.2 44 Food Preparation and Serving Related Occupations 17.4 809 14.2 661  Food Preparation Supervisors and Managers 12.6 75 10.1 60  Cooks 16.8 294 14.2 248  Food Preparation Workers 9.2 53 7.4 42  Food and Beverage Serving and Other Food  Preparation Serving Related Occupations 22.2 388 17.7 310 Building and Grounds Cleaning and Maintenance Occupations 8.2 284 6.6 225 Personal Care and Service Occupations 7.7 181 5.7 135  Personal Appearance Workers 8.2 51 7.0 44  Child Care Workers 6.9 64 4.6 43  Personal and Homecare Aides 6.6 30 5.2 23 Sales and Related Occupations 9.6 1,114 7.4 857  Retail Sales 11.7 229 9.1 179  Sales Representatives, Services 9.8 46 7.3 34  Sales Representatives, Wholesale and Manufacturing 9.8 137 7.0 98 

See notes at end of table. 
131

61115 Table 3.3 Illicit Drug, Marijuana, and Heavy Alcohol Use in the Past Month among Full-Time Workers Aged 18 to 64, by Occu

Percentages and Numbers in Thousands, Annual Averages Based on 2002-2004 (continued) 

Past Month Illicit Drug Use Past Month Marijuana Use 

Occupational Category Percentage 

Number 

(in Thousands) Percentage 

Number 

(in Thousands) Per

Office and Administrative Support Occupations 7.5 1,172 5.7 892 Farming, Fishing, and Forestry Occupations 8.7 89 3.3 34 Construction and Extraction Occupations 15.1 1,247 12.9 1,063  Carpenters 20.0 378 16.5 312  Carpet, Floor, Tile Installers, and Finishers 18.7 45 17.4 42  Construction Laborer 14.8 137 11.6 107  Construction Equipment Operator 8.6 35 6.1 25  Electricians 13.0 106 12.7 104  Roofers 16.9 37 14.1 31  Other Construction Related Workers 15.1 359 13.0 310  Extraction Workers 9.9 12 5.9 7 Installation, Maintenance, and Repair Occupations 9.5 468 8.1 401 Production Occupations 7.4 663 5.7 510 Transportation and Material-Moving Occupations 8.4 569 6.3 427  Motor Vehicle Operators 7.2 17 5.4 13  Bus Drivers 1.5 6 * *  Truck Drivers, Heavy and Tractor-Trailer 7.4 249 5.2 176  Material-Moving Workers 12.7 255 10.1 204 

*Low precision; no estimate reported. NOTE: Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics uNOTE: Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each 

days in the past 30 days. 

1 Estimates in the Total row include respondents with unknown or other occupational information. Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
132

70320 Table 3.4 Substance Dependence or Abuse in the Past Year among Full-Time Workers Aged 18 to 64, by Occupational Catego

Numbers in Thousands, Annual Averages Based on 2002-2004 

Past Year Illicit Drug Dependence or Abuse Past Year Alcoho

Occupational Category Percentage 

Number 

(in Thousands) Percentage 

Total1 2.6 3,030 9.2 Management Occupations 1.7 236 8.7  Chief Executives * * 7.9  Advertising, Marketing, Promotions, Public Relations,  and Sales Managers 1.5 12 8.1 Financial Occupations 1.6 43 6.9 Mathematical and Computer Scientists 1.3 40 7.2 Engineering, Architecture, and Surveyors 1.6 47 9.2  Drafters and Engineering Technicians 5.4 32 11.7 Life, Physical, and Social Science Occupations 1.2 16 8.1  Physical Scientists 0.9 6 6.6  Social Scientists and Related Workers 1.9 6 11.7 Community and Social Services Occupations 1.4 29 6.9 Legal Occupations 0.3 4 8.1  Lawyers 0.0 0 9.7 Education, Training, and Library Occupations 0.9 55 4.8  Elementary and Middle School Teachers 0.4 10 4.6  Secondary School Teachers 1.1 11 7.8  Special Education Teachers 1.9 7 3.1  Other Teachers and Instructors 0.9 14 3.6 Arts, Design, Entertainment, Sports, and Media Occupations 3.2 69 8.2 

See notes at end of table. 
133

70320 Table 3.4 Substance Dependence or Abuse in the Past Year among Full-Time Workers Aged 18 to 64, by Occupational Catego

Numbers in Thousands, Annual Averages Based on 2002-2004 (continued) 

Past Year Illicit Drug Dependence or Abuse Past Year Alcoho

Occupational Category Percentage 

Number 

(in Thousands) Percentage 

Healthcare Practitioners and Technical Occupations 1.4 103 5.4  Health Diagnosing and Treatment Practitioners 0.8 29 4.6  Registered Nurses 0.8 17 4.0  Health Care Technical and Support Occupations 1.9 74 6.0  Nursing, Psychiatric, and Home Health Aides 2.0 31 5.5 Protective Service Occupations 1.0 25 7.3  Protective Service Managers and Supervisors, 

Firefighter and Prevention Workers, Law 

 Enforcement Workers 0.2 4 7.3 

 Other Protective Service Workers 2.5 21 7.3 Food Preparation and Serving Related Occupations 6.5 303 14.7  Food Preparation Supervisors and Managers 5.0 30 9.4  Cooks 5.5 96 12.0  Food Preparation Workers 3.7 21 13.4  Food and Beverage Serving and Other Food  Preparation Serving Related Occupations 8.9 156 19.6 Building and Grounds Cleaning and Maintenance Occupations 3.4 118 10.0 Personal Care and Service Occupations 2.7 63 6.6  Personal Appearance Workers 1.8 11 8.5  Child Care Workers 1.8 16 4.2  Personal and Homecare Aides * * 7.3 Sales and Related Occupations 3.1 355 10.3  Retail Sales 3.6 70 12.2  Sales Representatives, Services 2.3 11 20.7  Sales Representatives, Wholesale and Manufacturing 3.4 47 12.4 

See notes at end of table. 
134

70320 Table 3.4 Substance Dependence or Abuse in the Past Year among Full-Time Workers Aged 18 to 64, by Occupational Catego

Numbers in Thousands, Annual Averages Based on 2002-2004 (continued) 

Past Year Illicit Drug Dependence or Abuse Past Year Alcoho

Occupational Category Percentage 

Number 

(in Thousands) Percentage 

Office and Administrative Support Occupations 2.5 385 7.6 Farming, Fishing, and Forestry Occupations 2.8 28 8.9 Construction and Extraction Occupations 6.2 514 16.9  Carpenters 7.4 139 16.6  Carpet, Floor, Tile Installers, and Finishers 7.0 17 16.8  Construction Laborer 9.8 91 21.7  Construction Equipment Operator 2.4 10 10.6  Electricians 4.1 33 14.8  Roofers 8.0 17 21.1  Other Construction Related Workers 6.0 143 18.0  Extraction Workers * * 10.9 Installation, Maintenance, and Repair Occupations 2.1 105 9.9 Production Occupations 2.9 256 9.5 Transportation and Material-Moving Occupations 3.1 207 11.1  Motor Vehicle Operators 3.2 8 *  Bus Drivers * * 3.1  Truck Drivers, Heavy and Tractor-Trailer 2.6 88 11.6  Material-Moving Workers 4.8 96 12.8 

*Low precision; no estimate reported. NOTE: Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics uNOTE: Dependence or abuse is based on the definition found in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-I1 Estimates in the Total row include respondents with unknown or other occupational information. Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
135

70320 Table 3.5 Illicit Drug, Marijuana, and Heavy Alcohol Use in the Past Month among Full-Time Workers Aged 18 to 64, by Indu

Percentages and Numbers in Thousands, Annual Averages Based on 2002-2004 

Past Month Illicit Drug Use Past Month Marijuana Use 

Industry Category Percentage 

Number 

(in Thousands) Percentage 

Number 

(in Thousands) Pe

Total1 8.2 9,413 6.4 7,293 Agriculture, Forestry, Fishing, and Hunting 6.2 108 2.3 40  Crop Production 5.7 41 1.7 12  Animal Production 3.1 20 1.1 7 Mining 7.3 38 2.5 13 Utilities 3.8 41 3.3 36 Construction 13.7 1,465 11.7 1,251 Manufacturing 6.5 1,109 5.1 857  Food Manufacturing 6.5 93 5.3 76  Textile Mills and Textile Product Mills 5.3 20 3.9 15  Apparel Manufacturing 7.2 27 3.6 14  Wood Product Manufacturing 8.1 98 6.3 76  Paper Manufacturing 6.0 33 4.8 26  Printing and Related Support Activities 9.2 74 7.7 62  Chemical Manufacturing 5.6 74 4.4 58  Plastics and Rubber Products Manufacturing 6.3 48 4.4 34  Nonmetallic Mineral Product Manufacturing 6.2 31 5.1 25  Metal Industries Manufacturing 10.8 182 8.3 140  Machinery Manufacturing 6.1 80 4.4 59  Computer and Electronic Product Manufacturing 4.2 69 3.7 61  Electrical Equipment, Appliance, and Component  Manufacturing 5.7 30 5.2 27  Transportation Equipment Manufacturing 5.4 147 3.9 105  Miscellaneous Manufacturing 6.6 82 4.8 59 Wholesale Trade 8.5 335 6.5 255  Merchant Wholesalers, Durable Goods 9.2 181 7.3 144  Merchant Wholesalers, Nondurable Goods 7.8 154 5.7 111 

See notes at end of table. 
136

70320 Table 3.5 Illicit Drug, Marijuana, and Heavy Alcohol Use in the Past Month among Full-Time Workers Aged 18 to 64, by Indu

Percentages and Numbers in Thousands, Annual Averages Based on 2002-2004 (continued) 

Past Month Illicit Drug Use Past Month Marijuana Use 

Industry Category Percentage 

Number 

(in Thousands) Percentage 

Number 

(in Thousands) Per

Retail Trade 9.4 1,015 7.3 786  Motor Vehicle and Parts Dealers 11.1 147 8.5 113  Furniture and Home Furnishings Stores 10.2 57 7.8 44  Electronics and Appliance Stores 9.8 70 8.8 64  Building Material and Garden Equipment and Supplies  Dealers 9.0 88 6.8 66  Food and Beverage Stores (including Beer, Wine, and  Liquor Stores) 7.8 158 6.0 120  Health and Personal Care Stores 8.8 64 5.8 42  Gasoline Stations 11.0 48 7.9 34  Clothing and Clothing Accessories Stores 10.2 95 7.9 73  Sporting Goods, Hobby, Book, and Music Stores 11.5 60 8.8 46  General Merchandise Stores 15.4 37 9.3 23  Department Stores 4.9 38 3.9 30  Miscellaneous Store Retailers 8.6 73 7.4 63  Non-Store Retailers 10.5 81 8.8 68 Transportation and Warehousing 6.2 318 4.5 230  Air Transportation 3.4 15 1.9 8  Rail Transportation 3.3 8 2.1 5  Truck Transportation 6.4 98 5.2 79  Transit and Ground Passenger Transportation 4.3 27 2.2 14  Support Activities for Transportation 7.6 50 5.5 36  Postal Service 6.1 48 3.6 29  Warehousing and Storage 3.1 8 2.8 7 Information 11.3 318 9.2 260  Publishing Industries (except Internet) 12.2 100 10.9 90  Broadcasting (except Internet) and  Telecommunications 11.9 196 9.4 155  Internet Publishing and Broadcasting, Internet Service  Providers, Web Search Portals, and Data Processing  Services 5.8 19 4.7 15 

See notes at end of table. 
137

70320 Table 3.5 Illicit Drug, Marijuana, and Heavy Alcohol Use in the Past Month among Full-Time Workers Aged 18 to 64, by Indu

Percentages and Numbers in Thousands, Annual Averages Based on 2002-2004 (continued) 

Past Month Illicit Drug Use Past Month Marijuana Use 

Industry Category Percentage 

Number 

(in Thousands) Percentage 

Number 

(in Thousands) Pe

Finance and Insurance 6.8 392 4.9 286  Securities, Commodity Contracts, Funds, Trusts, and  Other Financial Investments and Related Activities 6.7 75 5.2 58  Insurance Carriers and Related Activities 5.8 123 3.7 77  Banking, Savings Institutions (including Credit  Unions), and Related Activities 5.8 99 4.6 79 Real Estate and Rental and Leasing 7.5 150 5.6 111  Real Estate 7.3 124 5.7 96  Rental and Leasing Services (including Leasers of Non- Financial Intangible Assets) 8.6 26 5.2 16 Professional, Scientific, and Technical Services 8.0 598 6.2 469 Management of Companies and Enterprises, Administrative, Support, Waste Management, and Remediation Services 10.9 452 8.7 360  Investigation and Security Services 5.3 30 4.5 26  Janitorial Services 9.1 83 6.7 61  Landscaping Services 14.4 135 12.9 121  Waste Management and Remediation Services 12.2 46 8.8 33 Educational Services 4.0 353 2.9 263  Elementary and Secondary Schools 3.6 255 2.7 187  Colleges 5.2 80 4.1 63 Health Care and Social Assistance 6.1 808 4.0 532  Home Health Care Services 6.3 37 4.0 24  Hospitals 5.1 166 3.7 123  Nursing and Residential Care Facilities 7.4 126 4.8 82  Social Assistance 7.6 170 5.1 113  Individual and Family Services 8.1 72 5.4 47  Child Day Care Services 7.2 87 4.8 58 

See notes at end of table. 
138

70320 Table 3.5 Illicit Drug, Marijuana, and Heavy Alcohol Use in the Past Month among Full-Time Workers Aged 18 to 64, by Indu

Percentages and Numbers in Thousands, Annual Averages Based on 2002-2004 (continued) 

Past Month Illicit Drug Use Past Month Marijuana Use 

Industry Category Percentage 

Number 

(in Thousands) Percentage 

Number 

(in Thousands) Per

Arts, Entertainment, and Recreation 11.6 187 9.5 153  Performing Arts, Spectator, and Related Industries 15.5 83 13.2 71  Amusement, Gambling, and Recreation Industries 10.4 87 8.4 70 Accommodations and Food Services 16.9 975 13.9 804  Traveler Accommodation 7.8 64 6.6 54  Food Services and Drinking Places 18.4 902 15.1 743 Other Services (except Public Administration) 8.8 459 7.3 381  Repair and Maintenance 11.6 281 9.7 235  Automotive Repair and Maintenance 12.5 198 10.8 172  Commercial and Industrial Machinery and  Equipment 10.7 38 7.0 25  Personal and Laundry Services 9.5 133 8.1 113  Personal Care Services 9.2 71 8.1 63  Religious, Grantmaking, Civic, Professional, and  Similar Organizations 2.3 22 2.0 18  Religious Organizations 0.5 3 0.3 1  Civic and Social Organizations 5.6 16 4.9 14 Public Administration 4.1 261 2.8 182  Executive, Legislative, and Other General Government  Support 6.3 108 4.5 78  Justice, Public Order, and Safety Activities 2.0 51 1.3 33 

*Low precision; no estimate reported. NOTE: Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics uNOTE: Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each 

days in the past 30 days. 

1 Estimates in the Total row include respondents with unknown or other industry information. Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
139

70320 Table 3.6 Substance Dependence or Abuse in the Past Year among Full-Time Workers Aged 18 to 64, by Industry Categories: 

in Thousands, Annual Averages Based on 2002-2004 

Past Year Illicit Drug Dependence or Abuse Past Year Alcoho

Industry Category Percentage 

Number 

(in Thousands) Percentage 

Total1 2.6 3,030 9.2 Agriculture, Forestry, Fishing, and Hunting 2.3 39 8.8  Crop Production 2.7 20 8.3  Animal Production 1.3 8 7.2 Mining 3.3 17 8.6 Utilities 1.9 21 9.4 Construction 5.1 548 15.6 Manufacturing 2.4 411 9.5  Food Manufacturing 3.8 54 10.1  Textile Mills and Textile Product Mills * * 11.0  Apparel Manufacturing * * 7.2  Wood Product Manufacturing 3.3 40 12.2  Paper Manufacturing 2.4 13 8.4  Printing and Related Support Activities 2.1 17 9.8  Chemical Manufacturing 2.4 32 7.4  Plastics and Rubber Products Manufacturing 2.4 18 9.9  Nonmetallic Mineral Product Manufacturing 1.8 9 12.3  Metal Industries Manufacturing 4.5 77 11.7  Machinery Manufacturing 1.7 23 7.8  Computer and Electronic Product Manufacturing 1.5 25 7.7  Electrical Equipment, Appliance, and Component  Manufacturing 1.0 5 8.2  Transportation Equipment Manufacturing 1.9 52 9.5  Miscellaneous Manufacturing 1.7 21 9.0 Wholesale Trade 2.8 109 12.0  Merchant Wholesalers, Durable Goods 2.6 51 13.2  Merchant Wholesalers, Nondurable Goods 2.9 58 10.8 

See notes at end of table. 
140

70320 Table 3.6 Substance Dependence or Abuse in the Past Year among Full-Time Workers Aged 18 to 64, by Industry Categories: 

in Thousands, Annual Averages Based on 2002-2004 (continued) 

Past Year Illicit Drug Dependence or Abuse Past Year Alcoho

Industry Category Percentage 

Number 

(in Thousands) Percentage 

Retail Trade 3.1 341 9.1  Motor Vehicle and Parts Dealers 2.7 36 9.9  Furniture and Home Furnishings Stores 1.9 11 8.4  Electronics and Appliance Stores 3.9 28 12.0  Building Material and Garden Equipment and Supplies  Dealers 2.7 26 10.0  Food and Beverage Stores (including Beer, Wine, and  Liquor Stores) 3.1 62 9.7  Health and Personal Care Stores 3.8 28 9.6  Gasoline Stations 5.4 23 11.1  Clothing and Clothing Accessories Stores 4.7 43 9.0  Sporting Goods, Hobby, Book, and Music Stores 2.7 14 6.5  General Merchandise Stores * * 7.5  Department Stores 2.5 20 8.5  Miscellaneous Store Retailers 2.1 18 4.9 

Non-Store Retailers 3.5 27 9.4 

Transportation and Warehousing 2.2 111 8.1  Air Transportation 0.6 2 7.9  Rail Transportation * * 8.9  Truck Transportation 2.7 40 8.7  Transit and Ground Passenger Transportation 1.8 11 4.6  Support Activities for Transportation 2.2 14 8.8  Postal Service 0.8 6 7.5  Warehousing and Storage * * 4.5 Information 2.2 61 8.9  Publishing Industries (except Internet) 3.4 28 7.2  Broadcasting (except Internet) and  Telecommunications 1.7 28 9.5  Internet Publishing and Broadcasting, Internet Service  Providers, Web Search Portals, and Data Processing  Services 1.7 5 8.3 

See notes at end of table. 
141

70320 Table 3.6 Substance Dependence or Abuse in the Past Year among Full-Time Workers Aged 18 to 64, by Industry Categories: 

in Thousands, Annual Averages Based on 2002-2004 (continued) 

Past Year Illicit Drug Dependence or Abuse Past Year Alcoho

Industry Category Percentage 

Number 

(in Thousands) Percentage 

Finance and Insurance 1.9 112 8.4  Securities, Commodity Contracts, Funds, Trusts and  Other Financial Investments and Related Activities 1.9 22 10.2  Insurance Carriers and Related Activities 1.5 31 8.3  Banking, Savings Institutions (including Credit  Unions) and Related Activities 1.5 25 6.1 Real Estate and Rental and Leasing 2.3 45 8.2  Real Estate 2.1 35 8.3  Rental and Leasing Services (including Leasers of Non- Financial Intangible Assets) 3.5 11 7.2 Professional, Scientific, and Technical Services 1.9 142 8.5 Management of Companies and Enterprises, Administrative, Support, Waste Management, and Remediation Services 4.3 176 12.4  Investigation and Security Services 2.9 16 8.7  Janitorial Services 4.9 45 9.3  Landscaping Services 6.0 57 19.3  Waste Management and Remediation Services 1.9 7 * Educational Services 0.7 64 4.7  Elementary and Secondary Schools 0.8 56 4.6  Colleges 0.3 5 4.0 Health Care and Social Assistance 1.7 226 5.6  Home Health Care Services * * 5.1  Hospitals 0.9 31 5.5  Nursing and Residential Care Facilities 2.2 38 6.9  Social Assistance 1.8 41 5.0  Individual and Family Services 2.2 20 6.2  Child Day Care Services 1.6 20 3.6 

See notes at end of table. 
142

70320 Table 3.6 Substance Dependence or Abuse in the Past Year among Full-Time Workers Aged 18 to 64, by Industry Categories: 

in Thousands, Annual Averages Based on 2002-2004 (continued) 

Past Year Illicit Drug Dependence or Abuse Past Year Alcoho

Industry Category Percentage 

Number 

(in Thousands) Percentage 

Arts, Entertainment, and Recreation 4.0 65 11.1  Performing Arts, Spectator, and Related Industries 6.2 33 12.9  Amusement, Gambling, and Recreation Industries 3.1 26 10.7 Accommodations and Food Services 6.0 349 15.4  Traveler Accommodation 2.7 22 10.8  Food Services and Drinking Places 6.6 323 16.3 Other Services (except Public Administration) 2.3 122 8.3  Repair and Maintenance 3.2 78 11.1  Automotive Repair and Maintenance 3.5 55 11.4  Commercial and Industrial Machinery and  Equipment 2.1 7 9.7  Personal and Laundry Services 2.8 39 8.4  Personal Care Services 2.7 21 9.0  Religious, Grantmaking, Civic, Professional, and  Similar Organizations 0.3 3 3.3  Religious Organizations 0.3 2 1.8  Civic and Social Organizations 0.3 1 2.4 Public Administration 0.9 56 6.1  Executive, Legislative, and Other General Government  Support 1.3 23 6.6  Justice, Public Order, and Safety Activities 0.4 11 7.1 

*Low precision; no estimate reported. NOTE: Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics uNOTE: Dependence or abuse is based on the definition found in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-I1 Estimates in the Total row include respondents with unknown or other industry information. Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
143

50909 Table 3.7 Illicit Drug, Marijuana, and Heavy Alcohol Use in the Past Month among Full-Time Workers Aged 18 to 64, by Esta

Percentages and Numbers in Thousands, Annual Averages Based on 2002-2004 

Past Month Illicit Drug Use1 Past Month Marijuana Use Past Mont

Establishment Size Percentage 

Number 

(in Thousands) Percentage 

Number 

(in Thousands) Percentage 

Total3 8.2 9,413 6.4 7,293 8.8 Less Than 10 Employees 9.9 2,874 7.9 2,286 10.1 10-24 Employees 9.7 1,891 7.8 1,513 9.2 25-99 Employees 8.2 2,165 6.4 1,690 8.5 100-499 Employees 6.7 1,531 4.9 1,114 8.6 500 or More Employees 5.7 928 4.1 674 6.8 

*Low precision; no estimate reported. 1 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used non2 Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) 

past 30 days. 3 Estimates in the Total row include respondents with unknown establishment size information. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.50909 Table 3.8 Substance Dependence and Abuse in the Past Year among Full-Time Workers Aged 18 to 64, by Establishment Size: 

in Thousands, Annual Averages Based on 2002-2004 

Past Year Illicit Drug Dependence or Abuse Past Year Alcohol Depend

Establishment Size Percentage 

Number 

(in Thousands) Percentage 

Total1 2.6 3,030 9.2 Less Than 10 Employees 3.1 891 9.8 10-24 Employees 3.5 676 9.9 25-99 Employees 2.4 624 9.4 100-499 Employees 2.5 577 9.0 500 or More Employees 1.6 256 7.5 

*Low precision; no estimate reported. NOTE: Dependence or abuse is based on the definition found in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-I1 Estimates in the Total row include respondents with unknown establishment size information. Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
144

70320 

Table 4.1 Workplace Provides Educational Information, Prepares a Written Policy, or Maintains an EAP concerning Drug or 

Time Workers Aged 18 to 64, by Demographic Characteristics: Percentages and Numbers in Thousands, Annual Av

Educational Information about 

Drug or Alcohol Use 

Written Policy about 

Drug or Alcohol Use 

Demographic Characteristic Percentage 

Number 

(in Thousands) Percentage 

Number 

(in Thousands) Percent

Total 43.8 47,701 78.7 87,010 58.4 Age 18-25 33.2 4,685 76.9 10,856 39.7  26-34 39.6 9,411 79.3 18,993 56.4  35-49 46.3 20,827 79.8 36,552 62.4 

50-64 48.9 12,778 77.1 20,609 62.6 

Gender Male 44.0 27,630 76.4 48,806 56.5  Female 43.4 20,071 81.8 38,204 61.0 Hispanic Origin and Race Not Hispanic or Latino 44.6 42,099 79.5 76,200 61.2  White 42.7 32,219 78.4 59,920 60.6  Black or African American 56.3 7,106 86.9 11,210 65.7  American Indian or Alaska  Native 54.1 313 84.2 494 62.7  Native Hawaiian or Other  Pacific Islander 54.0 176 * * *  Asian 41.6 1,862 77.3 3,476 57.5  Two or More Races 42.1 423 80.1 823 62.0  Hispanic or Latino 38.4 5,601 73.1 10,810 40.4 

EAP = Employee Assistance Program. *Low precision; no estimate reported. Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
145

70320 Table 4.2 Workplace Provides Educational Information, Prepares a Written Policy, or Maintains an EAP concerning Drug or 

Time Workers Aged 18 to 64, by Educational Attainment, Family Income, and Geographic Characteristics: PercentaThousands, Annual Averages Based on 2002-2004 

Educational Information about 

Drug or Alcohol Use 

Written Policy about 

Educational Attainment, Family Drug or Alcohol Use Income, and Geographic Characteristic Percentage 

Number 

(in Thousands) Percentage 

Number 

(in Thousands) Percent

Total 43.8 47,701 78.7 87,010 58.4 Education Less Than High School 34.2 4,670 69.0 9,564 32.1  High School Graduate 44.3 14,868 78.4 26,952 55.4  Some College 45.4 12,957 80.9 23,506 61.7  College Graduate 45.8 15,205 81.1 26,989 69.3 Family Income  Less Than $20,000 31.9 3,652 68.2 7,876 31.4  $20,000-49,999 41.5 16,419 77.1 31,106 52.1  $50,000-74,999 46.6 11,004 82.3 19,681 65.4  $75,000 or More 48.4 16,625 81.5 28,348 69.2 Geographic Region Northeast 41.2 8,487 75.4 15,587 58.9  Midwest 43.6 10,723 80.4 20,161 62.0  South 45.8 18,119 79.9 32,238 56.3 

West 42.8 10,372 77.7 19,024 57.7 

County Type1 Large MSA 42.0 25,431 78.1 47,795 59.3  Small MSA 45.9 14,456 80.8 25,857 59.6  MiSA 45.5 4,609 78.5 8,132 56.1  Noncore Adjacent with Town 47.5 2,254 75.1 3,665 49.3  Noncore Adjacent, No Town 49.2 487 77.1 784 47.5  Noncore Rural, Not Adjacent 41.2 464 69.6 777 47.2 

EAP = Employee Assistance Program. *Low precision; no estimate reported. 1 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United States Department of Ag

estimates are not comparable with estimates by county type published in other NSDUH reports. MSA refers to metropolitan statistical area and MiSA statistical area. Noncore is defined as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
146

70320 Table 4.3 Workplace Provides Educational Information, Prepares a Written Policy, or Maintains an EAP concerning Drug or 

Time Workers Aged 18 to 64, by Demographic Characteristics and Past Month Illicit Drug Use: Percentages, Annua

2004 

Educational Information about 

Drug or Alcohol Use 

Written Policy about 

Drug or Alcohol Use 

Demographic Characteristic 

Past Month 

Illicit Drug Use1 

No Past Month 

Illicit Drug Use1

Past Month 

Illicit Drug Use1 

No Past Month 

Illicit Drug Use1 

Past Mo

Illicit Dru

Total 32.1 44.8 71.0 79.4 45.4 Age 18-25 28.2 34.4 70.5 78.4 34.3  26-34 31.3 40.6 70.3 80.4 44.4  35-49 35.7 47.1 70.9 80.5 51.9 

50-64 33.2 49.3 76.3 77.1 58.2 

Gender Male 31.7 45.3 68.5 77.3 43.5  Female 32.8 44.2 76.3 82.2 49.4 Hispanic Origin and Race Not Hispanic or Latino 32.0 45.8 71.2 80.3 46.4  White 30.6 43.9 69.9 79.2 47.0  Black or African American 40.6 57.6 77.9 87.7 43.1  American Indian or Alaska  Native * 54.2 * 84.1 *  Native Hawaiian or Other  Pacific Islander * 54.5 * * *  Asian * 41.9 * 77.3 *  Two or More Races 27.2 44.5 69.7 81.7 31.2  Hispanic or Latino 32.7 38.9 69.9 73.3 37.1 

EAP = Employee Assistance Program. *Low precision; no estimate reported. 1 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used non

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
147

70320 Table 4.4 Workplace Provides Educational Information, Prepares a Written Policy, or Maintains an EAP concerning Drug or 

Time Workers Aged 18 to 64, by Educational Attainment, Family Income, Geographic Characteristics, and Past MoPercentages, Annual Averages Based on 2002-2004 

Educational Information about 

Drug or Alcohol Use 

Written Policy about 

Educational Attainment, Family Drug or Alcohol Use Income, and Geographic Characteristic 

Past Month 

Illicit Drug Use1 

No Past Month 

Illicit Drug Use1

Past Month 

Illicit Drug Use1 

No Past Month 

Illicit Drug Use1 

Past Mo

Illicit Dru

Total 32.1 44.8 71.0 79.4 45.4 Education Less Than High School 29.5 34.8 66.2 69.4 28.5  High School Graduate 32.6 45.4 71.2 79.1 43.8  Some College 34.2 46.5 73.3 81.6 48.2  College Graduate 30.7 46.7 71.7 81.7 57.5 Family Income  Less Than $20,000 27.9 32.5 63.1 68.9 25.9  $20,000-49,999 32.3 42.4 71.9 77.7 44.3  $50,000-74,999 30.4 47.9 74.8 82.9 51.8  $75,000 or More 36.2 49.2 72.2 82.1 55.3 Geographic Region Northeast 29.3 42.3 68.2 76.1 48.0  Midwest 31.4 44.7 73.6 81.0 48.4  South 33.4 46.9 71.3 80.6 39.5 

West 33.2 43.7 70.7 78.3 48.5 

County Type2 Large MSA 31.0 43.0 70.7 78.7 47.9  Small MSA 34.8 47.0 72.6 81.6 43.7  MiSA 30.6 46.6 69.5 79.2 39.5  Noncore Adjacent with Town 30.7 48.7 64.3 75.8 34.2  Noncore Adjacent, No Town * 50.5 * 77.8 *  Noncore Rural, Not Adjacent * 41.8 * 69.2 * 

EAP = Employee Assistance Program. *Low precision; no estimate reported. 1 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used non2 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United States Department of Ag

estimates are not comparable with estimates by county type published in other NSDUH reports. MSA refers to metropolitan statistical area and MiSA statistical area. Noncore is defined as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
148

70320 Table 4.5 Workplace Provides Educational Information, Prepares a Written Policy, or Maintains an EAP concerning Drug or 

Time Workers Aged 18 to 64, by Demographic Characteristics and Past Month Heavy Alcohol Use: Numbers in Tho

Based on 2002-2004 

Educational Information about 

Drug or Alcohol Use 

Written Policy about 

Drug or Alcohol Use 

Demographic Characteristic 

Past Month Heavy 

Alcohol Use1 

No Past Month 

Heavy Alcohol 

Use1

Past Month Heavy 

Alcohol Use1 

No Past Month 

Heavy Alcohol 

Use1 

Past Month 

Alcohol 

Total 3,611 44,089 7,240 79,770 4,692 Age 18-25 703 3,981 1,650 9,206 792  26-34 906 8,505 1,851 17,142 1,238  35-49 1,569 19,259 2,811 33,741 2,003 

50-64 433 12,344 929 19,680 659 

Gender Male 2,954 24,676 5,771 43,035 3,736  Female 658 19,413 1,469 36,735 956 Hispanic Origin and Race Not Hispanic or Latino 3,194 38,905 6,475 69,724 4,299  White 2,770 29,449 5,676 54,244 3,828  Black or African American 330 6,775 596 10,614 338  American Indian or Alaska  Native * 292 * 448 *  Native Hawaiian or Other  Pacific Islander * 161 * * *  Asian 37 1,825 * 3,401 *  Two or More Races 20 403 * 773 *  Hispanic or Latino 417 5,184 765 10,045 393 

EAP = Employee Assistance Program. *Low precision; no estimate reported. 1 Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) 

past 30 days. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
149

70320 Table 4.6 Workplace Provides Educational Information, Prepares a Written Policy, or Maintains an EAP concerning Drug or 

Time Workers Aged 18 to 64, by Demographic Characteristics and Past Month Heavy Alcohol Use: Percentages, An2002-2004 

Educational Information about 

Drug or Alcohol Use 

Written Policy about 

Drug or Alcohol Use 

Demographic Characteristic 

Past Month Heavy 

Alcohol Use1 

No Past Month 

Heavy Alcohol 

Use1

Past Month Heavy 

Alcohol Use1 

No Past Month 

Heavy Alcohol 

Use1 

Past Month 

Alcohol 

Total 37.2 44.4 73.7 79.2 51.1 Age 18-25 30.3 33.8 71.5 77.9 38.1  26-34 36.0 40.1 74.1 79.9 53.4  35-49 43.1 46.6 75.0 80.3 56.5 

50-64 35.0 49.5 73.4 77.3 53.4 

Gender Male 37.8 44.9 73.1 76.9 50.5  Female 34.6 43.8 76.5 82.0 53.7 Hispanic Origin and Race Not Hispanic or Latino 36.7 45.4 73.6 80.2 52.2  White 36.0 43.5 72.7 79.1 52.4  Black or African American 47.5 56.8 85.2 87.0 51.2  American Indian or Alaska  Native * 55.3 * 83.8 *  Native Hawaiian or Other  Pacific Islander * 55.1 * * *  Asian 27.2 42.1 * 77.8 *  Two or More Races 25.4 43.5 * 81.5 *  Hispanic or Latino 41.0 38.2 75.0 72.9 41.4 

EAP = Employee Assistance Program. *Low precision; no estimate reported. 1 Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) 

past 30 days. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
150

70320 Table 4.7 Workplace Provides Educational Information, Prepares a Written Policy, or Maintains an EAP concerning Drug or 

Time Workers Aged 18 to 64, by Educational Attainment, Family Income, Geographic Characteristics, and Past MoNumbers in Thousands, Annual Averages Based on 2002-2004 

Educational Information about 

Drug or Alcohol Use 

Written Policy about 

Drug or Alcohol Use 

Educational Attainment, Family Income, and Geographic Characteristic 

Past Month Heavy 

Alcohol Use1 

No Past Month 

Heavy Alcohol 

Use1 Past Month Heavy Alcohol Use1 

No Past Month 

Heavy Alcohol 

Use1 Past Month 

Alcohol 

Total 3,611 44,089 7,240 79,770 4,692 Education Less Than High School 495 4,175 998 8,566 460  High School Graduate 1,318 13,550 2,568 24,384 1,589  Some College 994 11,963 1,994 21,512 1,353  College Graduate 804 14,401 1,681 25,308 1,291 Family Income  Less Than $20,000 327 3,325 716 7,160 299  $20,000-49,999 1,399 15,020 2,870 28,235 1,710  $50,000-74,999 912 10,092 1,733 17,948 1,222  $75,000 or More 973 15,652 1,921 26,427 1,461 Geographic Region Northeast 599 7,888 1,219 14,367 883  Midwest 988 9,735 1,986 18,175 1,340  South 1,283 16,835 2,550 29,688 1,468 

West 741 9,631 1,485 17,540 1,001 

County Type2 Large MSA 1,766 23,665 3,740 44,055 2,560  Small MSA 1,234 13,222 2,362 23,495 1,447  MiSA 358 4,251 696 7,436 412  Noncore Adjacent with Town 194 2,060 325 3,340 208  Noncore Adjacent, No Town * 459 * 720 *  Noncore Rural, Not Adjacent * 433 * 724 * 

EAP = Employee Assistance Program. *Low precision; no estimate reported. 1 Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) 

past 30 days. 

2 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United States Department of Ag

estimates are not comparable with estimates by county type published in other NSDUH reports. MSA refers to metropolitan statistical area and MiSA statistical area. Noncore is defined as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
151

70320 Table 4.8 Workplace Provides Educational Information, Prepares a Written Policy, or Maintains an EAP concerning Drug or 

Time Workers Aged 18 to 64, by Educational Attainment, Family Income, Geographic Characteristics, and Past MonPercentages, Annual Averages Based on 2002-2004 

Educational Information about 

Drug or Alcohol Use 

Written Policy about 

Drug or Alcohol Use 

Educational Attainment, Family Income, and Geographic Characteristic 

Past Month Heavy 

Alcohol Use1 

No Past Month 

Heavy Alcohol 

Use1

Past Month Heavy 

Alcohol Use1 

No Past Month 

Heavy Alcohol 

Use1 

Past Month 

Alcohol 

Total 37.2 44.4 73.7 79.2 51.1 Education Less Than High School 33.1 34.4 66.9 69.3 32.9  High School Graduate 38.7 44.9 74.1 78.8 49.4  Some College 38.9 46.0 75.8 81.4 55.1  College Graduate 35.5 46.5 75.3 81.5 61.2 Family Income  Less Than $20,000 28.8 32.2 64.1 68.6 29.2  $20,000-49,999 36.1 42.1 72.8 77.6 47.1  $50,000-74,999 42.2 47.1 78.5 82.7 58.7  $75,000 or More 38.2 49.2 75.2 82.0 59.9 Geographic Region Northeast 34.1 41.8 69.7 76.0 53.6  Midwest 37.2 44.3 74.3 81.1 54.4  South 37.6 46.6 73.9 80.5 45.0 

West 39.3 43.1 76.4 77.8 55.5 

County Type2 Large MSA 35.4 42.6 73.9 78.5 53.8  Small MSA 39.8 46.6 75.9 81.3 49.7  MiSA 38.1 46.2 72.2 79.2 46.6  Noncore Adjacent with Town 38.5 48.6 63.6 76.5 45.3  Noncore Adjacent, No Town * 51.0 * 77.9 *  Noncore Rural, Not Adjacent * 41.6 * 69.9 * 

EAP = Employee Assistance Program. *Low precision; no estimate reported. 1 Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) 

past 30 days. 

2 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United States Department of Ag

estimates are not comparable with estimates by county type published in other NSDUH reports. MSA refers to metropolitan statistical area and MiSA statistical area. Noncore is defined as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
152

70320 Table 4.9 Workplace Provides Educational Information, Prepares a Written Policy, or Maintains an EAP concerning Drug or 

Time Workers Aged 18 to 64, by Demographic Characteristics and Past Year Illicit Drug Dependence or Abuse: Per

Based on 2002-2004 

Educational Information about 

Drug or Alcohol Use 

Written Policy about 

Drug or Alcohol Use 

Demographic Characteristic 

Past Year Illicit 

Drug Dependence 

or Abuse

No Past Year 

Illicit Drug 

Dependence or 

Abuse 

Past Year Illicit 

Drug Dependence 

or Abuse

No Past Year 

Illicit Drug 

Dependence or 

Abuse 

Past Year 

Drug Depe

or Ab

Total 29.5 44.2 70.6 78.9 38.4 Age 18-25 26.6 33.8 69.3 77.5 30.9  26-34 29.8 40.0 70.9 79.6 37.5  35-49 34.3 46.5 73.9 80.0 45.4 

50-64 * 49.0 * 77.2 * 

Gender Male 30.2 44.5 69.2 76.7 37.3  Female 27.8 43.7 74.1 81.9 40.8 Hispanic Origin and Race Not Hispanic or Latino 28.9 45.0 69.8 79.8 39.9  White 27.9 43.1 68.4 78.7 39.3  Black or African American 34.5 56.9 76.6 87.2 40.5  American Indian or Alaska  Native * 55.0 * 85.6 *  Native Hawaiian or Other  Pacific Islander * 53.9 * * *  Asian * 41.9 * 77.5 *  Two or More Races * 42.8 * 80.0 *  Hispanic or Latino 32.6 38.6 74.9 73.0 30.0 

EAP = Employee Assistance Program. *Low precision; no estimate reported. NOTE: Dependence or abuse is based on the definition found in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-I

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
153

70320 Table 4.10 Workplace Provides Educational Information, Prepares a Written Policy, or Maintains an EAP concerning Drug or 

Time Workers Aged 18 to 64, by Demographic Characteristics and Past Year Alcohol Dependence or Abuse: Percen

Based on 2002-2004 

Educational Information about 

Drug or Alcohol Use 

Written Policy about 

Drug or Alcohol Use 

Demographic Characteristic 

Past Year Alcohol 

Dependence or 

Abuse

No Past Year 

Alcohol 

Dependence or 

Abuse 

Past Year Alcohol 

Dependence or 

Abuse

No Past Year 

Alcohol 

Dependence or 

Abuse 

Past Year 

Depende

Abu

Total 37.2 44.4 74.9 79.1 51.0 Age 18-25 29.2 34.1 73.4 77.7 36.7  26-34 34.1 40.4 73.4 80.2 49.8  35-49 43.1 46.6 77.0 80.1 58.6 

50-64 45.8 49.0 75.8 77.1 61.8 

Gender Male 38.0 44.8 73.1 76.9 49.5  Female 35.0 44.0 80.3 81.9 55.5 Hispanic Origin and Race Not Hispanic or Latino 38.1 45.2 76.0 79.9 54.1  White 36.3 43.4 74.8 78.8 54.7  Black or African American 51.6 56.6 84.8 87.1 51.5  American Indian or Alaska  Native * 54.9 * 83.8 *  Native Hawaiian or Other  Pacific Islander * * * * *  Asian * 42.0 * 77.5 *  Two or More Races * 42.7 * 80.3 *  Hispanic or Latino 32.1 39.2 68.5 73.6 32.9 

EAP = Employee Assistance Program. *Low precision; no estimate reported. NOTE: Dependence or abuse is based on the definition found in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-I

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
154

70320 Table 4.11 Workplace Provides Educational Information, Prepares a Written Policy, or Maintains an EAP concerning Drug o

Time Workers Aged 18 to 64, by Educational Attainment, Family Income, Geographic Characteristics, and Past Ye

Abuse: Percentages, Annual Averages Based on 2002-2004 

Educational Information about 

Drug or Alcohol Use 

Written Policy about 

Drug or Alcohol Use 

Educational Attainment, Family Income, and Geographic Characteristic 

Past Year Alcohol 

Dependence or 

Abuse

No Past Year 

Alcohol 

Dependence or 

Abuse 

Past Year Alcohol 

Dependence or 

Abuse

No Past Year 

Alcohol 

Dependence or 

Abuse 

Past Year A

Dependen

Abus

Total 37.2 44.4 74.9 79.1 51.0 Education Less Than High School 29.0 34.9 66.6 69.4 28.1  High School Graduate 41.0 44.6 76.4 78.6 48.6  Some College 38.6 46.1 76.3 81.4 55.3  College Graduate 36.3 46.6 77.0 81.4 64.4 Family Income  Less Than $20,000 28.8 32.4 64.4 68.7 28.7  $20,000-49,999 34.9 42.2 74.3 77.4 47.1  $50,000-74,999 41.8 47.1 81.2 82.4 59.9  $75,000 or More 42.0 48.9 77.0 81.9 62.3 Geographic Region Northeast 33.1 41.9 70.9 75.8 52.6  Midwest 39.5 44.1 76.8 80.8 56.0  South 37.1 46.7 74.9 80.4 46.7 

West 37.8 43.3 75.8 77.9 50.7 

County Type1 Large MSA 35.8 42.6 74.4 78.5 52.1  Small MSA 39.0 46.7 77.1 81.2 50.8  MiSA 38.1 46.1 75.6 78.8 50.4  Noncore Adjacent with Town 39.0 48.4 66.8 76.0 42.4  Noncore Adjacent, No Town * 49.9 * 77.8 *  Noncore Rural, Not Adjacent * 41.2 77.2 69.0 * 

EAP = Employee Assistance Program. *Low precision; no estimate reported. NOTE: Dependence or abuse is based on the definition found in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-I1 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United States Department of Ag

estimates are not comparable with estimates by county type published in other NSDUH reports. MSA refers to metropolitan statistical area and MiSA statistical area. Noncore is defined as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
155

50930 Table 5.1 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or on a Random Basis concerning Drug 

Full-Time Workers Aged 18 to 64, by Demographic Characteristics: Percentages and Numbers in Thousands, Annua

2004 

Tests for Alcohol Use Tests for Drug Use 

Tests for Drug or Alcohol 

Use during Hiring Process 

T

Demographic Characteristic Percentage 

Number 

(in 

Thousands) Percentage 

Number 

(in 

Thousands) Percentage 

Number 

(in 

Thousands) P

Total 35.4 38,743 48.8 54,019 42.9 47,050 Age 18-25 30.5 4,306 46.7 6,654 39.0 5,534  26-34 34.2 8,175 49.9 12,058 44.3 10,631  35-49 37.5 16,934 50.4 23,025 44.7 20,220 

50-64 35.3 9,328 46.0 12,282 40.8 10,666 

Gender Male 37.7 23,969 51.4 32,953 45.8 29,034  Female 32.1 14,775 45.1 21,065 39.1 18,016 Hispanic Origin and Race Not Hispanic or Latino 35.1 33,235 49.1 47,130 43.1 40,828  White 33.3 25,181 46.9 35,975 40.5 30,691  Black or African American 46.7 5,914 63.1 8,058 58.1 7,340  American Indian or Alaska  Native 48.1 277 59.9 342 50.8 289  Native Hawaiian or Other  Pacific Islander * * 56.5 203 53.5 191  Asian 30.3 1,368 44.5 2,048 41.8 1,881  Two or More Races 34.4 347 49.1 504 42.8 436  Hispanic or Latino 37.4 5,508 46.5 6,888 42.3 6,222 

*Low precision; no estimate reported. Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
156

50930 Table 5.2 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or on a Random Basis concerning Drug 

Full-Time Workers Aged 18 to 64, by Educational Attainment, Family Income, and Geographic Characteristics: PerThousands, Annual Averages Based on 2002-2004 

Tests for Alcohol Use Tests for Drug Use 

Tests for Drug or Alcohol 

Use during Hiring Process 

T

Educational Attainment, Family Income, and Geographic Characteristic Percentage 

Number 

(in 

Thousands) Percentage 

Number 

(in 

Thousands) Percentage 

Number 

(in 

Thousands) P

Total 35.4 38,743 48.8 54,019 42.9 47,050 Education Less Than High School 38.6 5,351 48.1 6,698 42.5 5,890  High School Graduate 40.6 13,773 54.6 18,786 48.5 16,528  Some College 37.9 10,866 51.7 15,068 45.7 13,142  College Graduate 26.5 8,753 40.4 13,467 35.0 11,490 Family Income  Less Than $20,000 30.9 3,521 42.2 4,846 36.3 4,143  $20,000-49,999 36.7 14,690 49.8 20,137 44.0 17,643  $50,000-74,999 38.7 9,178 52.3 12,563 45.9 10,858  $75,000 or More 33.0 11,354 47.3 16,472 41.9 14,407 Geographic Region Northeast 26.8 5,557 38.7 8,058 34.4 7,073  Midwest 36.7 9,080 50.6 12,675 44.5 10,986  South 39.6 15,771 54.7 22,079 48.2 19,304 

West 34.3 8,335 45.6 11,207 39.9 9,688 

County Type1 Large MSA 33.3 20,244 46.6 28,628 41.7 25,307  Small MSA 37.4 11,813 51.7 16,506 45.1 14,253  MiSA 38.7 3,949 51.9 5,379 44.7 4,571  Noncore Adjacent with Town 39.9 1,940 50.3 2,462 42.7 2,074  Noncore Adjacent, No Town 36.3 365 48.2 494 41.4 420  Noncore Rural, Not Adjacent 38.6 433 48.3 549 37.7 425 

*Low precision; no estimate reported. 1 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United States Department of Ag

estimates are not comparable with estimates by county type published in other NSDUH reports. MSA refers to metropolitan statistical area and MiSA statistical area. Noncore is defined as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
157

70320 Table 5.3 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or on a Random Basis concerning Drug 

Full-Time Workers Aged 18 to 64, by Demographic Characteristics and Past Month Illicit Drug Use: Percentages, A2002-2004 

Tests for Alcohol Use Tests for Drug Use 

Tests for Drug or Alcohol 

Use during Hiring Process 

Demographic Characteristic 

Past Month 

Illicit Drug 

Use1 

No Past 

Month 

Illicit Drug 

Use1 

Past Month 

Illicit Drug 

Use1 

No Past 

Month 

Illicit Drug 

Use1 

Past Month 

Illicit Drug 

Use1 

No Past 

Month 

Illicit Drug 

Use1 

Total 25.3 36.3 39.5 49.6 31.9 44.0 Age 18-25 21.0 32.8 37.6 48.8 29.4 41.3  26-34 23.5 35.5 38.3 51.3 32.0 45.8  35-49 29.5 38.1 42.4 51.0 34.2 45.5 

50-64 29.6 35.5 38.1 46.2 31.3 41.0 

Gender Male 26.1 39.0 40.0 52.7 32.7 47.2  Female 23.7 32.6 38.5 45.5 30.2 39.7 Hispanic Origin and Race Not Hispanic or Latino 25.4 36.0 39.9 50.0 31.9 44.1  White 24.0 34.2 38.3 47.8 30.1 41.5  Black or African American 32.5 48.0 48.9 64.3 42.9 59.5  American Indian or Alaska  Native * 48.3 * 59.6 * 50.0  Native Hawaiian or Other  Pacific Islander * * * * * *  Asian * 30.4 * 44.7 * 42.0  Two or More Races * 35.1 40.1 50.5 24.0 45.7  Hispanic or Latino 25.1 38.3 36.7 47.2 31.6 43.0 

*Low precision; no estimate reported. 1 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used non

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
158

70320 Table 5.4 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or on a Random Basis concerning Drug 

Full-Time Workers Aged 18 to 64, by Educational Attainment, Family Income, Geographic Characteristics, and PasPercentages, Annual Averages Based on 2002-2004 

Tests for Alcohol Use Tests for Drug Use 

Tests for Drug or Alcohol 

Use during Hiring Process 

T

Educational Attainment, Family Income, and Geographic Characteristic 

Past Month 

Illicit Drug 

Use1 

No Past 

Month 

Illicit Drug 

Use1 

Past Month 

Illicit Drug 

Use1 

No Past 

Month 

Illicit Drug 

Use1 

Past Month 

Illicit Drug 

Use1 

No Past 

Month 

Illicit Drug 

Use1 

P

I

Total 25.3 36.3 39.5 49.6 31.9 44.0 Education Less Than High School 27.8 40.0 39.6 49.2 31.5 43.9  High School Graduate 29.8 41.7 45.5 55.5 35.8 49.8  Some College 25.5 39.1 40.0 52.9 33.7 46.8  College Graduate 16.0 27.1 29.1 41.1 23.7 35.7 Family Income  Less Than $20,000 20.8 32.5 34.8 43.3 26.2 37.9  $20,000-49,999 26.4 37.8 41.0 50.7 33.3 45.1  $50,000-74,999 29.7 39.4 44.1 53.0 34.5 46.9  $75,000 or More 23.1 33.6 36.4 48.0 31.5 42.6 Geographic Region Northeast 17.7 27.8 28.2 39.8 23.8 35.4  Midwest 26.3 37.7 42.6 51.3 35.9 45.3  South 29.9 40.4 45.1 55.5 35.3 49.3 

West 24.6 35.3 38.4 46.3 30.5 40.9 

County Type2 Large MSA 24.3 34.1 38.1 47.4 31.5 42.6  Small MSA 26.2 38.6 41.3 52.7 32.0 46.4  MiSA 27.0 39.6 42.6 52.6 34.1 45.5  Noncore Adjacent with Town 29.9 40.6 39.7 51.0 33.4 43.4  Noncore Adjacent, No Town * 36.1 * 48.5 * 41.4  Noncore Rural, Not Adjacent * 39.6 * 49.3 * 38.8 

*Low precision; no estimate reported. 1 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used non2 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United States Department of Ag

estimates are not comparable with estimates by county type published in other NSDUH reports. MSA refers to metropolitan statistical area and MiSA statistical area. Noncore is defined as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
159

70320 Table 5.5 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or on a Random Basis concerning Drug 

Time Workers Aged 18 to 64, by Demographic Characteristics and Past Month Heavy Alcohol Use: Numbers in ThoBased on 2002-2004 

Tests for Alcohol Use Tests for Drug Use 

Tests for Drug or Alcohol 

Use during Hiring Process 

Demographic Characteristic 

Past Month 

Heavy 

Alcohol Use1 

No Past 

Month Heavy 

Alcohol Use1 

Past Month 

Heavy 

Alcohol Use1 

No Past 

Month Heavy 

Alcohol Use1 

Past Month 

Heavy 

Alcohol Use1 

No Past 

Month Heavy 

Alcohol Use1 

Total 3,313 35,431 4,892 49,127 4,071 42,980 Age 18-25 559 3,748 989 5,664 802 4,732  26-34 818 7,357 1,253 10,804 1,025 9,605  35-49 1,428 15,506 1,964 21,061 1,664 18,556 

50-64 508 8,820 685 11,597 580 10,086 

Gender Male 2,825 21,143 4,115 28,839 3,436 25,599  Female 487 14,287 777 20,288 635 17,381 Hispanic Origin and Race Not Hispanic or Latino 2,958 30,277 4,376 42,755 3,642 37,186  White 2,546 22,634 3,778 32,198 3,102 27,588  Black or African American 321 5,593 455 7,603 415 6,924  American Indian or Alaska  Native * 250 * 304 * 256  Native Hawaiian or Other  Pacific Islander * * * * * *  Asian * 1,343 * 1,996 * 1,832  Two or More Races * 321 * 467 * 406  Hispanic or Latino 355 5,154 516 6,372 428 5,794 

*Low precision; no estimate reported. 1 Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) 

past 30 days. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
160

70320 Table 5.6 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or on a Random Basis concerning Drug 

Time Workers Aged 18 to 64, by Demographic Characteristics and Past Month Heavy Alcohol Use: Percentages, An2002-2004 

Tests for Alcohol Use Tests for Drug Use 

Tests for Drug or Alcohol 

Use during Hiring Process 

Demographic Characteristic 

Past Month 

Heavy 

Alcohol Use1 

No Past 

Month Heavy 

Alcohol Use1 

Past Month 

Heavy 

Alcohol Use1 

No Past 

Month Heavy 

Alcohol Use1 

Past Month 

Heavy 

Alcohol Use1 

No Past 

Month Heavy 

Alcohol Use1 

Total 33.6 35.5 49.5 48.7 41.5 43.1 Age 18-25 24.0 31.8 42.4 47.5 34.4 39.9  26-34 32.2 34.5 49.2 50.0 40.4 44.8  35-49 38.7 37.4 52.8 50.2 45.0 44.7 

50-64 39.6 35.1 53.5 45.7 46.4 40.5 

Gender Male 35.7 38.0 51.8 51.4 43.5 46.1  Female 25.3 32.4 40.3 45.3 33.1 39.3 Hispanic Origin and Race Not Hispanic or Latino 33.5 35.2 49.3 49.1 41.4 43.2  White 32.4 33.4 48.0 46.8 39.8 40.6  Black or African American 45.7 46.8 64.4 63.0 58.8 58.1  American Indian or Alaska  Native * 47.6 * 58.4 * 49.4  Native Hawaiian or Other  Pacific Islander * * * * * *  Asian * 30.7 * 44.8 * 42.0  Two or More Races * 34.4 * 49.0 * 43.0  Hispanic or Latino 35.1 37.5 51.6 46.1 42.4 42.2 

*Low precision; no estimate reported. 1 Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) 

past 30 days. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
161

70320 Table 5.7 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or on a Random Basis concerning Drug 

Full-Time Workers Aged 18 to 64, by Educational Attainment, Family Income, Geographic Characteristics, and Pas

Use: Percentages, Annual Averages Based on 2002-2004 

Tests for Alcohol Use Tests for Drug Use 

Tests for Drug or Alcohol 

Use during Hiring Process 

T

Educational Attainment, Family Income, and Geographic Characteristic 

Past Month 

Heavy 

Alcohol Use1 

No Past 

Month Heavy 

Alcohol Use1 

Past Month 

Heavy 

Alcohol Use1 

No Past 

Month Heavy 

Alcohol Use1 

Past Month 

Heavy 

Alcohol Use1 

No Past 

Month Heavy 

Alcohol Use1 

P

A

Total 33.6 35.5 49.5 48.7 41.5 43.1 Education Less Than High School 37.3 38.8 49.9 47.9 39.1 42.9  High School Graduate 36.9 41.0 53.6 54.7 45.3 48.8  Some College 34.4 38.2 51.0 51.8 44.3 45.8  College Graduate 25.4 26.6 41.2 40.3 33.9 35.1 Family Income  Less Than $20,000 26.0 31.4 38.5 42.6 30.8 36.9  $20,000-49,999 34.4 37.0 50.7 49.7 42.5 44.1  $50,000-74,999 39.3 38.6 56.5 51.9 46.1 45.9  $75,000 or More 30.9 33.1 46.5 47.3 40.7 42.0 Geographic Region Northeast 24.3 27.1 37.6 38.8 32.8 34.5  Midwest 35.7 36.9 50.7 50.5 43.9 44.6  South 36.4 39.9 53.6 54.8 44.5 48.5 

West 34.4 34.3 51.6 45.1 40.7 39.9 

County Type2 Large MSA 30.2 33.6 46.9 46.6 39.9 41.8  Small MSA 35.8 37.6 52.2 51.6 42.9 45.4  MiSA 41.0 38.4 53.9 51.7 44.1 44.7  Noncore Adjacent with Town 38.6 40.0 51.0 50.2 44.1 42.6  Noncore Adjacent, No Town * 36.2 * 48.6 * 42.1  Noncore Rural, Not Adjacent * 38.5 * 48.0 * 37.3 

*Low precision; no estimate reported. 1 Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) 

past 30 days. 

2 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United States Department of Ag

estimates are not comparable with estimates by county type published in other NSDUH reports. MSA refers to metropolitan statistical area and MiSA statistical area. Noncore is defined as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
162

70320 Table 5.8 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or on a Random Basis concerning Drug 

Time Workers Aged 18 to 64, by Demographic Characteristics and Past Month Marijuana Use: Numbers in Thousanon 2002-2004 

Tests for Alcohol Use Tests for Drug Use 

Tests for Drug or Alcohol 

Use during Hiring Process 

Demographic Characteristic 

Past Month 

Marijuana 

Use

No Past 

Month 

Marijuana 

Use

Past Month 

Marijuana 

Use

No Past 

Month 

Marijuana 

Use

Past Month 

Marijuana 

Use

No Past 

Month 

Marijuana 

Use

Total 1,580 37,163 2,667 51,351 2,066 44,985 Age 18-25 445 3,862 827 5,827 625 4,910  26-34 398 7,777 702 11,356 560 10,070  35-49 610 16,324 962 22,063 742 19,478 

50-64 127 9,201 * 12,106 139 10,526 

Gender Male 1,164 22,805 1,917 31,036 1,501 27,533  Female 416 14,358 751 20,315 565 17,452 Hispanic Origin and Race Not Hispanic or Latino 1,455 31,780 2,452 44,678 1,890 38,938  White 1,145 24,036 1,960 34,015 1,476 29,215  Black or African American 249 5,665 394 7,664 338 7,002  American Indian or Alaska  Native * 269 * 328 * 277  Native Hawaiian or Other  Pacific Islander * * * 184 * *  Asian * 1,356 * 2,026 * 1,862  Two or More Races * 316 * 461 27 410  Hispanic or Latino 125 5,383 215 6,674 175 6,047 

*Low precision; no estimate reported. Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
163

70320 Table 5.9 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or on a Random Basis concerning Drug 

Time Workers Aged 18 to 64, by Demographic Characteristics and Past Month Marijuana Use: Percentages, Annual 

2004 

Tests for Alcohol Use Tests for Drug Use 

Tests for Drug or Alcohol 

Use during Hiring Process 

Demographic Characteristic 

Past Month 

Marijuana 

Use

No Past 

Month 

Marijuana 

Use

Past Month 

Marijuana 

Use

No Past 

Month 

Marijuana 

Use

Past Month 

Marijuana 

Use

No Past 

Month 

Marijuana 

Use

Total 22.2 36.3 37.3 49.5 29.0 43.9 Age 18-25 19.6 32.6 36.2 48.7 27.4 41.2  26-34 20.4 35.4 35.8 51.2 28.6 45.7  35-49 25.7 38.2 40.2 50.9 31.1 45.5 

50-64 25.0 35.5 * 46.3 27.5 41.0 

Gender Male 23.1 39.0 37.8 52.6 29.7 47.2  Female 20.2 32.6 36.0 45.5 27.2 39.6 Hispanic Origin and Race Not Hispanic or Latino 22.7 36.0 37.9 49.9 29.3 44.1  White 21.3 34.2 36.2 47.7 27.4 41.5  Black or African American 30.5 47.9 48.0 64.1 41.3 59.3  American Indian or Alaska  Native * 49.0 * 60.3 * 51.0  Native Hawaiian or Other  Pacific Islander * * * 56.4 * *  Asian * 30.5 * 44.7 * 42.0  Two or More Races * 35.2 * 50.3 23.8 45.1  Hispanic or Latino 18.4 38.3 31.2 47.2 25.5 43.1 

*Low precision; no estimate reported. Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
164

70320 Table 5.10 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or on a Random Basis concerning Dru

Full-Time Workers Aged 18 to 64, by Educational Attainment, Family Income, Geographic Characteristics, and PaNumbers in Thousands, Annual Averages Based on 2002-2004 

Tests for Alcohol Use Tests for Drug Use 

Tests for Drug or Alcohol 

Use during Hiring Process 

T

Educational Attainment, Family Income, and Geographic Characteristic 

Past Month 

Marijuana 

Use

No Past 

Month 

Marijuana 

Use

Past Month 

Marijuana 

Use

No Past 

Month 

Marijuana 

Use

Past Month 

Marijuana 

Use

No Past 

Month 

Marijuana 

Use

P

M

Total 1,580 37,163 2,667 51,351 2,066 44,985 Education Less Than High School 299 5,052 455 6,242 349 5,541  High School Graduate 638 13,134 1,063 17,723 792 15,737  Some College 448 10,418 758 14,310 621 12,521  College Graduate 195 8,558 391 13,076 303 11,187 Family Income  Less Than $20,000 208 3,313 383 4,463 276 3,867  $20,000-49,999 685 14,005 1,143 18,994 900 16,743  $50,000-74,999 370 8,808 588 11,975 427 10,430  $75,000 or More 317 11,038 553 15,919 463 13,944 Geographic Region Northeast 250 5,307 441 7,617 368 6,705  Midwest 372 8,707 642 12,032 516 10,470  South 588 15,183 965 21,114 713 18,591 

West 369 7,966 619 10,588 469 9,218 

County Type1 Large MSA 836 19,408 1,459 27,169 1,152 24,154  Small MSA 518 11,295 877 15,630 657 13,596  MiSA 146 3,802 230 5,149 173 4,397  Noncore Adjacent with Town 66 1,874 84 2,378 69 2,005  Noncore Adjacent, No Town * 358 * 486 * 413  Noncore Rural, Not Adjacent * 426 * 538 * 418 

*Low precision; no estimate reported. 1 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United States Department of Ag

estimates are not comparable with estimates by county type published in other NSDUH reports. MSA refers to metropolitan statistical area and MiSA statistical area. Noncore is defined as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
165

70320 Table 5.11 Workplace Tests Employees for Alcohol or Drug Use, during Hiring Process or on a Random Basis concerning Dru

Full-Time Workers Aged 18 to 64, by Educational Attainment, Family Income, Geographic Characteristics, and PaPercentages, Annual Averages Based on 2002-2004 

Tests for Alcohol Use Tests for Drug Use 

Tests for Drug or Alcohol 

Use during Hiring Process 

T

Educational Attainment, Family Income, and Geographic Characteristic 

Past Month 

Marijuana 

Use

No Past 

Month 

Marijuana 

Use

Past Month 

Marijuana 

Use

No Past 

Month 

Marijuana 

Use

Past Month 

Marijuana 

Use

No Past 

Month 

Marijuana 

Use

P

M

Total 22.2 36.3 37.3 49.5 29.0 43.9 Education Less Than High School 25.0 39.9 37.8 49.1 29.2 43.8  High School Graduate 26.5 41.7 43.6 55.5 32.6 49.7  Some College 22.2 39.0 37.4 52.8 30.7 46.8  College Graduate 13.2 27.1 26.4 41.0 20.5 35.7 Family Income  Less Than $20,000 18.0 32.4 32.9 43.3 23.7 37.7  $20,000-49,999 23.2 37.8 38.3 50.7 30.4 45.1  $50,000-74,999 26.9 39.4 42.3 52.9 30.8 46.9  $75,000 or More 19.7 33.6 34.2 47.9 28.7 42.5 Geographic Region Northeast 16.0 27.7 28.0 39.6 23.4 35.3  Midwest 24.0 37.6 40.7 51.2 33.0 45.3  South 25.8 40.4 42.1 55.4 31.2 49.2 

West 21.7 35.3 36.2 46.3 27.4 40.9 

County Type1 Large MSA 20.7 34.2 35.9 47.4 28.4 42.6  Small MSA 23.5 38.5 39.5 52.6 29.8 46.3  MiSA 25.8 39.4 40.1 52.6 30.5 45.5  Noncore Adjacent with Town 29.8 40.4 37.8 50.9 31.0 43.3  Noncore Adjacent, No Town * 36.8 * 49.0 * 42.1  Noncore Rural, Not Adjacent * 39.4 * 49.1 * 38.4 

*Low precision; no estimate reported. 1 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United States Department of Ag

estimates are not comparable with estimates by county type published in other NSDUH reports. MSA refers to metropolitan statistical area and MiSA statistical area. Noncore is defined as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
166

51117 Table 5.12 Type of Testing Program Reported concerning Drug or Alcohol Use among Full-Time Workers Aged 18 to 64, by E

Percentages and Numbers in Thousands, Annual Averages Based on 2002-2004 

Tests for Drug or Alcohol Use during Hiring Process Tests for Drug or Alcohol U

Establishment Size Percentage 

Number 

(in Thousands) Percentage 

Total1 42.9 47,050 29.6 Less Than 10 Employees 19.0 5,383 14.5 10-24 Employees 33.7 6,313 26.2 25-99 Employees 44.1 11,118 32.4 100-499 Employees 61.6 13,279 40.2 500 or More Employees 70.6 10,832 42.6 

*Low precision; no estimate reported. NOTE: Respondents with unknown workplace testing information were excluded. 1 Estimates include respondents with unknown establishment size information. Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
167

50930 Table 6.1 Employees' Feelings toward Working for Employers Who Conduct Drug Testing before Hiring or Who Test Random

Alcohol Use among Full-Time Workers Aged 18 to 64, by Demographic Characteristics: Percentages, Annual Averag

Employer Tests before Hiring Employer Tests 

Demographic Characteristic More Likely Less Likely 

Would Make 

No Difference More Likely Less Lik

Total 46.0 4.9 49.1 39.8 8.7 Age 18-25 36.7 5.6 57.8 31.4 10.0  26-34 43.1 4.8 52.1 36.6 9.1  35-49 47.1 5.1 47.8 40.9 9.1 

50-64 51.6 4.2 44.2 45.5 7.1 

Gender Male 47.4 5.6 47.1 41.1 9.8  Female 44.1 4.0 51.9 38.2 7.3 Hispanic Origin and Race Not Hispanic or Latino 44.8 5.1 50.0 38.3 9.3  White 43.4 5.5 51.1 36.8 9.7  Black or African American 51.4 2.7 45.9 45.7 6.5  American Indian or Alaska  Native 51.8 4.0 44.2 47.2 7.0  Native Hawaiian or Other  Pacific Islander 54.0 * 33.5 50.6 11.1  Asian 49.2 5.3 45.4 40.8 10.1  Two or More Races 43.6 6.0 50.4 37.4 10.6  Hispanic or Latino 53.3 3.5 43.2 50.1 5.1 

*Low precision; no estimate reported. Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
168

60515 Table 6.2 Employees' Feelings toward Working for Employers Who Conduct Drug Testing before Hiring or Who Test Random

Alcohol Use among Full-Time Workers Aged 18 to 64, by Educational Attainment, Family Income, Geographic Char

Month Illicit Drug Use: Percentages, Annual Averages Based on 2002-2004 

Educational Attainment, Family Employer Tests before Hiring Employer Tests Income, and Geographic Characteristic More Likely Less Likely 

Would Make 

No Difference More Likely Less Lik

Total 46.0 4.9 49.1 39.8 8.7 Education Less Than High School 51.3 4.3 44.3 48.7 6.1  High School Graduate 50.0 3.7 46.3 44.7 6.0  Some College 48.0 4.0 48.0 40.7 8.3  College Graduate 37.9 7.1 55.0 30.6 12.9 Family Income  Less Than $20,000 46.2 5.4 48.4 42.6 8.2  $20,000-49,999 46.7 4.6 48.7 41.6 7.7  $50,000-74,999 47.4 4.3 48.3 40.6 8.1  $75,000 or More 44.1 5.4 50.5 36.4 10.5 Geographic Region Northeast 35.6 6.2 58.2 30.4 10.6  Midwest 46.1 4.4 49.6 38.3 8.5  South 51.1 3.4 45.5 45.8 6.1 

Midwest 46.3 6.8 46.9 39.8 11.7 

County Type1 Large MSA 43.2 5.6 51.2 36.8 10.5  Small MSA 48.5 4.4 47.1 42.0 7.6  MiSA 50.3 3.2 46.5 45.2 5.0  Noncore Adjacent with Town 52.0 3.2 44.8 48.8 4.2  Noncore Adjacent, No Town 52.4 3.1 44.5 46.9 3.7  Noncore Rural, Not Adjacent 54.3 3.6 42.1 49.3 4.6 

*Low precision; no estimate reported. 1 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United States Department of Ag

estimates are not comparable with estimates by county type published in other NSDUH reports. MSA refers to metropolitan statistical area and MiSA statistical area. Noncore is defined as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
169

50930 Table 6.3 Employees' Feelings toward Working for Employers Who Conduct Drug Testing before Hiring concerning Drug or A

Time Workers Aged 18 to 64, by Demographic Characteristics and Past Month Illicit Drug Use: Percentages, Annua2004 

Employer Tests before Hiring 

More Likely Less Likely Would 

Demographic Characteristic 

Past Month 

Illicit Drug Use1 

No Past Month 

Illicit Drug Use1 

Past Month 

Illicit Drug Use1 

No Past Month 

Illicit Drug Use1 

Past Mo

Illicit Drug 

Total 20.6 48.2 18.2 3.7 61.2 Age 18-25 17.7 41.1 16.9 2.9 65.4  26-34 19.9 45.7 17.5 3.4 62.6  35-49 23.1 48.9 19.2 4.1 57.7 

50-64 23.2 52.3 21.2 3.7 55.6 

Gender Male 20.6 50.2 19.8 4.0 59.7  Female 20.7 45.6 14.9 3.3 64.4 Hispanic Origin and Race Not Hispanic or Latino 19.3 47.2 19.0 3.8 61.7  White 17.0 46.0 20.5 4.0 62.5  Black or African American 31.5 53.1 9.4 2.1 59.0  American Indian or Alaska  Native * 53.6 * 3.5 *  Native Hawaiian or Other  Pacific Islander * * * * *  Asian * 49.7 * 5.1 *  Two or More Races 24.3 46.6 22.0 3.6 53.7  Hispanic or Latino 31.2 54.9 11.8 2.9 57.0 

*Low precision; no estimate reported. 1 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used non

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
170

60515 Table 6.4 Employees' Feelings toward Working for Employers Who Conduct Drug Testing before Hiring concerning Drug or A

Time Workers Aged 18 to 64, by Educational Attainment, Family Income, Geographic Characteristics, and Past Mon

Percentages, Annual Averages Based on 2002-2004 

Employer Tests before Hiring 

Educational Attainment, Family More Likely Less Likely Would Income, and Geographic Characteristic 

Past Month 

Illicit Drug Use1 

No Past Month 

Illicit Drug Use1 

Past Month 

Illicit Drug Use1 

No Past Month 

Illicit Drug Use1 

Past Mo

Illicit Drug 

Total 20.6 48.2 18.2 3.7 61.2 Education Less Than High School 25.5 54.6 14.0 3.1 60.5  High School Graduate 23.2 52.7 17.1 2.4 59.8  Some College 21.2 50.6 15.0 3.0 63.8  College Graduate 11.9 39.5 27.5 5.8 60.6 Family Income  Less Than $20,000 24.2 49.5 20.3 3.2 55.5  $20,000-49,999 21.7 49.2 18.0 3.2 60.3  $50,000-74,999 19.2 49.7 16.4 3.4 64.4  $75,000 or More 17.4 45.8 18.6 4.6 64.0 Geographic Region Northeast 13.8 37.8 21.0 4.7 65.3  Midwest 22.3 48.1 16.6 3.3 61.1  South 24.4 53.3 14.1 2.5 61.5 

West 19.8 48.9 23.0 5.2 57.2 

County Type2 Large MSA 19.7 45.4 18.7 4.4 61.6  Small MSA 21.4 51.1 17.9 3.1 60.6  MiSA 22.5 52.4 16.9 2.1 60.6  Noncore Adjacent with Town 20.8 54.0 15.7 2.4 63.5  Noncore Adjacent, No Town * 53.3 * 2.3 *  Noncore Rural, Not Adjacent * 56.1 * 2.7 * 

*Low precision; no estimate reported. 1 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used non2 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United States Department of Ag

estimates are not comparable with estimates by county type published in other NSDUH reports. MSA refers to metropolitan statistical area and MiSA statistical area. Noncore is defined as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
171

50930 Table 6.5 Employees' Feelings toward Working for Employers Who Conduct Drug Testing Randomly concerning Drug or Alc

Workers Aged 18 to 64, by Demographic Characteristics and Past Month Illicit Drug Use: Percentages, Annual Aver

Employer Tests Randomly 

More Likely Less Likely Would 

Demographic Characteristic 

Past Month 

Illicit Drug Use1 

No Past Month 

Illicit Drug Use1 

Past Month 

Illicit Drug Use1 

No Past Month 

Illicit Drug Use1 

Past Mo

Illicit Drug 

Total 15.9 42.0 29.1 6.9 55.0 Age 18-25 13.4 35.6 27.6 5.9 59.0  26-34 14.8 39.1 30.8 6.6 54.4  35-49 17.6 42.6 28.6 7.6 53.8 

50-64 21.6 46.2 30.5 6.4 47.8 

Gender Male 15.8 43.8 31.0 7.5 53.2  Female 16.0 39.7 25.0 6.1 58.9 Hispanic Origin and Race Not Hispanic or Latino 14.6 40.5 30.3 7.4 55.0  White 13.3 39.0 31.5 7.6 55.3  Black or African American 21.5 47.8 24.5 4.9 54.0  American Indian or Alaska  Native * 48.4 * 6.2 *  Native Hawaiian or Other  Pacific Islander * * * 7.8 *  Asian * 41.1 * 9.9 *  Two or More Races 14.2 41.0 32.7 7.2 53.1  Hispanic or Latino 26.5 51.8 18.6 4.1 54.9 

*Low precision; no estimate reported. 1 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used non

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
172

60515 Table 6.6 Employees' Feelings toward Working for Employers Who Conduct Drug Testing Randomly concerning Drug or Alc

Workers Aged 18 to 64, by Educational Attainment, Family Income, Geographic Characteristics, and Past Month Ill

Annual Averages Based on 2002-2004 

Employer Tests Randomly 

Educational Attainment, Family More Likely Less Likely Would Income, and Geographic Characteristic 

Past Month 

Illicit Drug Use1 

No Past Month 

Illicit Drug Use1 

Past Month 

Illicit Drug Use1 

No Past Month 

Illicit Drug Use1 

Past Mo

Illicit Drug 

Total 15.9 42.0 29.1 6.9 55.0 Education Less Than High School 20.3 52.4 24.7 3.8 55.0  High School Graduate 18.5 47.3 24.8 4.1 56.7  Some College 15.2 43.2 28.7 6.4 56.2  College Graduate 9.3 31.9 39.8 11.3 50.9 Family Income  Less Than $20,000 19.1 46.1 29.9 4.9 51.0  $20,000-49,999 17.7 44.0 28.1 5.7 54.2  $50,000-74,999 13.7 42.8 29.3 6.4 57.0  $75,000 or More 12.4 37.9 29.9 9.2 57.7 Geographic Region Northeast 11.2 32.3 30.8 8.6 58.0  Midwest 15.4 40.3 29.5 6.7 55.1  South 19.4 48.0 23.6 4.6 57.0 

West 15.6 42.2 34.8 9.5 49.6 

County Type2 Large MSA 15.0 38.8 31.7 8.5 53.3  Small MSA 16.8 44.4 27.2 5.7 55.9  MiSA 18.8 47.2 21.6 3.8 59.6  Noncore Adjacent with Town 16.2 51.0 21.7 3.0 62.2  Noncore Adjacent, No Town * 48.6 * 3.0 *  Noncore Rural, Not Adjacent * 51.0 * 3.4 * 

*Low precision; no estimate reported. 1 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used non2 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United States Department of Ag

estimates are not comparable with estimates by county type published in other NSDUH reports. MSA refers to metropolitan statistical area and MiSA statistical area. Noncore is defined as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
173

70320 Table 6.7 Employees' Feelings toward Working for Employers Who Conduct Drug Testing before Hiring concerning Drug or A

Time Workers Aged 18 to 64, by Demographic Characteristics and Past Month Heavy Alcohol Use: Percentages, An2002-2004 

Employer Tests before Hiring 

More Likely Less Likely Would 

Demographic Characteristic 

Past Month 

Heavy Alcohol 

Use1 

No Past Month 

Heavy Alcohol 

Use1 

Past Month 

Heavy Alcohol 

Use1 

No Past Month 

Heavy Alcohol 

Use1 

Past Mo

Heavy Alc

Use1 

Total 33.7 47.1 8.2 4.6 58.0 Age 18-25 23.6 39.2 10.2 4.7 66.2  26-34 31.9 44.4 7.5 4.5 60.7  35-49 38.3 47.9 7.6 4.9 54.0 

50-64 42.7 52.0 7.9 4.0 49.4 

Gender Male 35.6 49.0 8.7 5.1 55.8  Female 26.4 44.9 6.5 3.9 67.1 Hispanic Origin and Race Not Hispanic or Latino 32.1 46.1 8.4 4.8 59.4  White 30.9 44.8 8.9 5.1 60.2  Black or African American 43.7 51.8 4.2 2.6 52.1  American Indian or Alaska  Native * 52.7 * 4.1 *  Native Hawaiian or Other  Pacific Islander * * * * *  Asian * 49.6 * 5.4 *  Two or More Races * 44.0 * 5.4 *  Hispanic or Latino 47.7 53.7 6.6 3.3 45.8 

*Low precision; no estimate reported. 1 Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) 

past 30 days. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
174

70320 Table 6.8 Employees' Feelings toward Working for Employers Who Conduct Drug Testing before Hiring concerning Drug or 

Time Workers Aged 18 to 64, by Educational Attainment, Family Income, Geographic Characteristics, and Past MoPercentages, Annual Averages Based on 2002-2004 

Employer Tests before Hiring 

More Likely Less Likely Would 

Educational Attainment, Family Income, and Geographic Characteristic 

Past Month 

Heavy Alcohol 

Use1 

No Past Month 

Heavy Alcohol 

Use1 

Past Month 

Heavy Alcohol 

Use1 

No Past Month 

Heavy Alcohol 

Use1 

Past Mo

Heavy Alc

Use1 

Total 33.7 47.1 8.2 4.6 58.0 Education Less Than High School 38.9 52.8 8.3 3.8 52.8  High School Graduate 36.9 51.5 7.9 3.2 55.2  Some College 34.8 49.3 7.6 3.7 57.6  College Graduate 24.5 38.9 9.5 6.9 66.1 Family Income  Less Than $20,000 28.6 48.1 12.0 4.7 59.3  $20,000-49,999 33.5 48.1 8.5 4.2 58.0  $50,000-74,999 35.8 48.5 7.4 4.0 56.8  $75,000 or More 34.6 44.8 6.9 5.3 58.4 Geographic Region Northeast 25.2 36.6 10.8 5.8 64.0  Midwest 34.3 47.5 6.8 4.1 58.8  South 39.4 52.2 5.5 3.2 55.1 

West 30.9 47.6 12.7 6.3 56.4 

County Type2 Large MSA 31.7 44.2 9.4 5.3 58.9  Small MSA 35.7 49.9 7.1 4.1 57.2  MiSA 34.0 51.9 7.6 2.8 58.5  Noncore Adjacent with Town 39.0 53.5 5.7 2.9 55.3  Noncore Adjacent, No Town * 54.7 8.2 2.6 *  Noncore Rural, Not Adjacent * 54.5 * 3.4 * 

*Low precision; no estimate reported. 1 Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) 

past 30 days. 2 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United States Department of Ag

estimates are not comparable with estimates by county type published in other NSDUH reports. MSA refers to metropolitan statistical area and MiSA statistical area. Noncore is defined as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
175

70320 Table 6.9 Employees' Feelings toward Working for Employers Who Conduct Drug Testing Randomly concerning Drug or Alc

Workers Aged 18 to 64, by Demographic Characteristics and Past Month Heavy Alcohol Use: Percentages, Annual A

2004 

Employer Tests Randomly 

More Likely Less Likely Would 

Demographic Characteristic 

Past Month 

Heavy Alcohol 

Use1 

No Past Month 

Heavy Alcohol 

Use1 

Past Month 

Heavy Alcohol 

Use1 

No Past Month 

Heavy Alcohol 

Use1 

Past Mo

Heavy Alc

Use1 

Total 28.0 41.0 15.0 8.1 57.0 Age 18-25 19.3 33.7 18.1 8.4 62.5  26-34 26.7 37.7 15.4 8.4 57.9  35-49 30.9 41.7 14.0 8.7 55.1 

50-64 37.6 45.9 11.7 6.8 50.7 

Gender Male 29.9 42.6 15.3 9.0 54.7  Female 20.0 39.0 13.8 7.0 66.2 Hispanic Origin and Race Not Hispanic or Latino 26.1 39.5 15.7 8.7 58.2  White 24.9 38.1 16.1 9.0 59.0  Black or African American 37.5 46.2 12.2 6.1 50.3  American Indian or Alaska  Native * 47.6 * 6.9 *  Native Hawaiian or Other  Pacific Islander * * * 10.0 *  Asian * 41.0 7.4 10.1 *  Two or More Races * 38.5 17.0 10.1 *  Hispanic or Latino 43.9 50.5 9.3 4.8 46.8 

*Low precision; no estimate reported. 1 Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) 

past 30 days. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
176

70320 Table 6.10 Employees' Feelings toward Working for Employers Who Conduct Drug Testing Randomly concerning Drug or Al

Time Workers Aged 18 to 64, by Educational Attainment, Family Income, Geographic Characteristics, and Past MoPercentages, Annual Averages Based on 2002-2004 

Employer Tests Randomly 

More Likely Less Likely Would 

Educational Attainment, Family Income, and Geographic Characteristic 

Past Month 

Heavy Alcohol 

Use1 

No Past Month 

Heavy Alcohol 

Use1 

Past Month 

Heavy Alcohol 

Use1 

No Past Month 

Heavy Alcohol 

Use1 

Past Mo

Heavy Alc

Use1 

Total 28.0 41.0 15.0 8.1 57.0 Education Less Than High School 34.8 50.4 12.0 5.4 53.2  High School Graduate 31.5 46.2 12.4 5.3 56.1  Some College 28.0 42.0 16.1 7.6 55.9  College Graduate 18.2 31.4 19.7 12.4 62.1 Family Income  Less Than $20,000 25.7 44.4 18.8 7.1 55.5  $20,000-49,999 27.9 43.0 13.8 7.1 58.3  $50,000-74,999 31.4 41.6 14.4 7.5 54.2  $75,000 or More 26.1 37.2 15.8 10.1 58.1 Geographic Region Northeast 21.1 31.2 17.7 9.9 61.1  Midwest 25.7 39.7 14.1 7.9 60.2  South 34.5 46.9 11.7 5.5 53.8 

West 25.7 41.0 19.8 11.0 54.5 

County Type2 Large MSA 25.5 37.8 18.4 9.8 56.1  Small MSA 30.6 43.2 12.2 7.1 57.1  MiSA 27.9 46.9 11.2 4.4 60.9  Noncore Adjacent with Town 35.4 50.3 8.7 3.7 55.9  Noncore Adjacent, No Town * 49.3 6.4 3.4 *  Noncore Rural, Not Adjacent * 50.0 * 4.2 * 

*Low precision; no estimate reported. 1 Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) 

past 30 days. 2 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United States Department of Ag

estimates are not comparable with estimates by county type published in other NSDUH reports. MSA refers to metropolitan statistical area and MiSA statistical area. Noncore is defined as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
177

70320 Table 6.11 Employees' Feelings toward Working for Employers Who Conduct Drug Testing before Hiring concerning Drug or 

Time Workers Aged 18 to 64, by Demographic Characteristics and Past Month Marijuana Use: Percentages, Annua

2002-2004 

Employer Tests before Hiring 

More Likely Less Likely Would 

Demographic Characteristic 

Past Month 

Marijuana Use

No Past Month 

Marijuana Use

Past Month 

Marijuana Use

No Past Month 

Marijuana Use

Past Mo

Marijuan

Total 15.5 48.0 21.2 3.8 63.3 Age 18-25 14.7 40.8 19.0 3.0 66.3  26-34 14.2 45.6 20.8 3.4 65.0  35-49 17.4 48.7 22.8 4.2 59.8 

50-64 15.6 52.3 24.7 3.8 59.8 

Gender Male 16.1 50.0 22.3 4.1 61.6  Female 14.1 45.5 18.4 3.3 67.5 Hispanic Origin and Race Not Hispanic or Latino 15.0 47.0 21.9 3.9 63.1  White 12.8 45.7 23.5 4.1 63.6  Black or African American 27.7 53.0 11.1 2.1 61.2  American Indian or Alaska  Native * 53.7 * 3.5 *  Native Hawaiian or Other  Pacific Islander * * * * *  Asian * 49.7 * 5.2 *  Two or More Races 23.0 46.1 26.1 3.6 50.9  Hispanic or Latino 20.4 54.9 14.8 3.0 64.9 

*Low precision; no estimate reported. Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
178

70320 Table 6.12 Employees' Feelings toward Working for Employers Who Conduct Drug Testing before Hiring concerning Drug or 

Time Workers Aged 18 to 64, by Educational Attainment, Family Income, Geographic Characteristics, and Past Mo

Percentages, Annual Averages Based on 2002-2004 

Employer Tests before Hiring 

Educational Attainment, Family More Likely Less Likely Would Income, and Geographic Characteristic 

Past Month 

Marijuana Use

No Past Month 

Marijuana Use

Past Month 

Marijuana Use

No Past Month 

Marijuana Use

Past Mo

Marijuan

Total 15.5 48.0 21.2 3.8 63.3 Education Less Than High School 20.3 54.3 16.8 3.2 62.9  High School Graduate 18.2 52.5 19.9 2.5 61.9  Some College 16.2 50.4 17.9 3.0 65.9  College Graduate 6.4 39.3 31.2 6.0 62.3 Family Income  Less Than $20,000 19.7 49.1 24.2 3.4 56.1  $20,000-49,999 16.2 49.1 20.9 3.3 62.8  $50,000-74,999 14.1 49.4 18.8 3.5 67.1  $75,000 or More 12.5 45.6 21.5 4.7 66.0 Geographic Region Northeast 12.0 37.5 22.8 4.9 65.2  Midwest 17.0 48.0 20.2 3.3 62.8  South 18.3 53.1 16.7 2.6 65.0 

West 13.7 48.8 26.6 5.3 59.8 

County Type1 Large MSA 14.9 45.2 21.3 4.5 63.8  Small MSA 15.9 50.9 21.3 3.2 62.9  MiSA 17.3 52.2 21.1 2.2 61.5  Noncore Adjacent with Town 18.1 53.6 16.7 2.6 65.3  Noncore Adjacent, No Town * 53.7 * 2.3 *  Noncore Rural, Not Adjacent * 55.6 * 2.9 * 

*Low precision; no estimate reported. 1 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United States Department of Ag

estimates are not comparable with estimates by county type published in other NSDUH reports. MSA refers to metropolitan statistical area and MiSA statistical area. Noncore is defined as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
179

70320 

Table 6.13 Employees' Feelings toward Working for Employers Who Conduct Drug Testing Randomly concerning Drug or Al

Time Workers Aged 18 to 64, by Demographic Characteristics and Past Month Marijuana Use: Percentages, Annua

2002-2004 

Employer Tests Randomly 

More Likely Less Likely Would 

Demographic Characteristic 

Past Month 

Marijuana Use

No Past Month 

Marijuana Use

Past Month 

Marijuana Use

No Past Month 

Marijuana Use

Past Mo

Marijuan

Total 11.4 41.8 33.5 7.1 55.1 Age 18-25 10.5 35.3 30.9 6.1 58.6  26-34 9.9 38.9 35.5 6.9 54.6  35-49 12.6 42.4 33.9 7.8 53.5 

50-64 * 46.1 35.8 6.5 48.9 

Gender Male 11.9 43.5 34.6 7.7 53.5  Female 10.1 39.5 30.9 6.2 59.0 Hispanic Origin and Race Not Hispanic or Latino 10.9 40.2 34.6 7.5 54.6  White 9.8 38.8 35.8 7.8 54.5  Black or African American 17.3 47.7 27.4 5.0 55.3  American Indian or Alaska  Native * 48.5 * 6.1 *  Native Hawaiian or Other  Pacific Islander * 55.1 * 7.7 *  Asian * 41.2 * 9.9 *  Two or More Races * 40.1 34.5 7.7 50.1  Hispanic or Latino 16.3 51.7 23.4 4.2 60.3 

*Low precision; no estimate reported. Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
180

70320 Table 6.14 Employees' Feelings toward Working for Employers Who Conduct Drug Testing Randomly concerning Drug or Al

Time Workers Aged 18 to 64, by Educational Attainment, Family Income, Geographic Characteristics, and Past MoPercentages, Annual Averages Based on 2002-2004 

Employer Tests Randomly 

Educational Attainment, Family More Likely Less Likely Would Income, and Geographic Characteristic 

Past Month 

Marijuana Use

No Past Month 

Marijuana Use

Past Month 

Marijuana Use

No Past Month 

Marijuana Use

Past Mo

Marijuan

Total 11.4 41.8 33.5 7.1 55.1 Education Less Than High School 14.5 52.0 29.4 3.9 56.1  High School Graduate 14.3 47.0 29.1 4.3 56.6  Some College 11.2 42.9 32.1 6.6 56.7  College Graduate 4.5 31.7 45.9 11.4 49.7 Family Income  Less Than $20,000 14.7 45.7 34.6 5.3 50.7  $20,000-49,999 12.6 43.9 32.6 5.8 54.8  $50,000-74,999 9.1 42.6 33.8 6.6 57.1  $75,000 or More 8.9 37.7 34.1 9.4 57.1 Geographic Region Northeast 9.0 32.1 34.0 8.7 57.0  Midwest 11.9 40.0 34.3 6.8 53.8  South 14.1 47.7 27.5 4.8 58.4 

West 9.6 42.1 40.1 9.6 50.2 

County Type1 Large MSA 10.8 38.6 36.3 8.7 52.9  Small MSA 11.8 44.2 31.4 5.9 56.8  MiSA 13.3 47.0 26.3 3.8 60.4  Noncore Adjacent with Town 12.9 50.5 22.8 3.3 64.2  Noncore Adjacent, No Town * 48.1 * 2.9 *  Noncore Rural, Not Adjacent * 50.4 * 3.8 * 

*Low precision; no estimate reported. 1 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United States Department of Ag

estimates are not comparable with estimates by county type published in other NSDUH reports. MSA refers to metropolitan statistical area and MiSA statistical area. Noncore is defined as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
181 

70320 

Table 6.15 Results of Multinomial Logit Model of Willingness to Work for Employers Who Test for Drug or 

Alcohol Use during Hiring Process among Full-Time Workers Aged 18 to 64: 2002-2004 

Willingness to Work for Employer Who Tests for 

Drug or Alcohol Use during Hiring Process 

More Likely vs. Would Make 

No Difference 

Less Likely vs. Would Make 

No Difference 

Characteristic Odds Ratio CI (95%) Odds Ratio CI (95%) 

Intercept 0.49b 0.45-0.54 0.08b 0.06-0.10 

Illicit Drug Use1 

 No Lifetime Use -- -- -- -- 

 Lifetime Use, No Past Year Use 0.73b 0.69-0.77 1.24a 1.05-1.47 

 Past Year Use, No Past Month Use 0.45b 0.41-0.49 1.91b 1.51-2.40 

 Past Month Use 0.28b 0.26-0.31 5.18b 4.40-6.11 

Age Group 

 18-25 -- -- -- -- 

 26-34 1.29b 1.21-1.37 1.10 0.97-1.25 

 35-49 1.53b 1.46-1.62 1.46b 1.31-1.64 

 50-64 1.69b 1.57-1.83 1.52b 1.27-1.81 

Gender 

 Male 1.26b 1.20-1.32 1.38b 1.23-1.54 

 Female -- -- -- -- 

Hispanic Origin and Race 

 Not Hispanic or Latino 

 White -- -- -- -- 

 Black or African American 1.30b 1.19-1.41 0.61b 0.49-0.76 

 American Indian or Alaska Native 1.21 0.85-1.71 0.88 0.43-1.81 

 Native Hawaiian or Other 

 Pacific Islander 1.94b 1.25-3.00 2.86a 1.04-7.92 

 Asian 1.39b 1.19-1.63 1.10 0.80-1.52 

 Two or More Races 1.06 0.84-1.33 1.01 0.69-1.47 

 Hispanic or Latino 1.35b 1.23-1.49 0.76b 0.63-0.93 

Education 

 Less Than High School 1.70b 1.55-1.86 0.65b 0.54-0.77 

 High School Graduate 1.68b 1.57-1.80 0.57b 0.49-0.66 

 Some College 1.58b 1.47-1.70 0.60b 0.50-0.70 

 College Graduate -- -- -- -- 

Family Income 

 Less Than $20,000 0.89a 0.81-0.98 1.41b 1.17-1.70 

 $20,000-49,999 0.90b 0.84-0.97 1.16 1.00-1.34 

 $50,000-74,999 1.00 0.93-1.08 0.98 0.85-1.14 

 $75,000 or More -- -- -- -- 

Geographic Region 

 Northeast 0.63b 0.58-0.68 0.76b 0.64-0.90 

 Midwest 0.96 0.89-1.03 0.66b 0.55-0.79 

 South 1.10a 1.02-1.19 0.57b 0.48-0.68 

 West -- -- -- -- 

County Type2 

 Large MSA -- -- -- -- 

 Small MSA 1.23b 1.15-1.30 0.86a 0.76-0.98 

 MiSA 1.23b 1.14-1.34 0.68b 0.54-0.85 

 Noncore Adjacent with Town 1.21b 1.08-1.37 0.79 0.56-1.12 

 Noncore Adjacent, No Town 1.24 0.90-1.70 0.82 0.50-1.37 

 Noncore Rural, Not Adjacent 1.35b 1.10-1.67 0.85 0.54-1.34 

CI = confidence interval. 

-- Reference level. 

a Statistically significant at the 0.05 level. 

b Statistically significant at the 0.01 level. 

1

 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type 

psychotherapeutics used nonmedically. 

2

 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United 

States Department of Agriculture (USDA). These estimates are not comparable with estimates by county type published in other 

NSDUH reports. MSA refers to metropolitan statistical area and MiSA refers to micropolitan statistical area. Noncore is defined

as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
182 

60608 

Table 6.16 Results of Multinomial Logit Model of Willingness to Work for Employers Who Test for Drug or 

Alcohol Use on a Random Basis among Full-Time Workers Aged 18 to 64: 2002-2004 

Willingness to Work for Employer Who Tests for 

Drug or Alcohol Use on a Random Basis 

More Likely vs. Would Make 

No Difference 

Less Likely vs. Would Make 

No Difference 

Characteristic Odds Ratio CI (95%) Odds Ratio CI (95%) 

Intercept 0.36b 0.32-0.41 0.17b 0.14-0.20 

Illicit Drug Use1 

 No Lifetime Use -- -- -- -- 

 Lifetime Use, No Past Year Use 0.71b 0.67-0.75 1.32b 1.19-1.48 

 Past Year Use, No Past Month Use 0.44b 0.40-0.49 2.30b 1.95-2.72 

 Past Month Use 0.29b 0.26-0.32 5.61b 4.96-6.34 

Age Group 

 18-25 -- -- -- -- 

 26-34 1.27b 1.20-1.36 1.08 0.97-1.19 

 35-49 1.59b 1.50-1.67 1.29b 1.18-1.42 

 50-64 1.76b 1.63-1.90 1.21a 1.05-1.40 

Gender 

 Male 1.26b 1.20-1.32 1.37b 1.25-1.49 

 Female -- -- -- -- 

Hispanic Origin and Race 

 Not Hispanic or Latino 

 White -- -- -- -- 

 Black or African American 1.34b 1.22-1.46 0.85a 0.72-0.99 

 American Indian or Alaska Native 1.28 0.89-1.86 0.97 0.56-1.66 

 Native Hawaiian or Other 

 Pacific Islander 1.96b 1.21-3.20 1.22 0.68-2.20 

 Asian 1.35b 1.11-1.64 1.08 0.83-1.40 

 Two or More Races 1.07 0.86-1.34 1.04 0.73-1.50 

 Hispanic or Latino 1.47b 1.33-1.62 0.65b 0.54-0.77 

Education 

 Less Than High School 1.89b 1.72-2.09 0.54b 0.46-0.63 

 High School Graduate 1.74b 1.62-1.87 0.50b 0.45-0.56 

 Some College 1.57b 1.46-1.69 0.67b 0.59-0.75 

 College Graduate -- -- -- -- 

Family Income 

 Less Than $20,000 0.97 0.87-1.07 1.15 0.98-1.36 

 $20,000-49,999 0.95 0.89-1.03 1.02 0.90-1.16 

 $50,000-74,999 1.02 0.95-1.10 0.95 0.85-1.06 

 $75,000 or More -- -- -- -- 

Geographic Region 

 Northeast 0.65b 0.60-0.71 0.74b 0.64-0.84 

 Midwest 0.90a 0.83-0.98 0.72b 0.63-0.82 

 South 1.13b 1.04-1.23 0.57b 0.50-0.66 

 West -- -- -- -- 

County Type2 

 Large MSA -- -- -- -- 

 Small MSA 1.21b 1.13-1.29 0.77b 0.70-0.85 

 MiSA 1.27b 1.17-1.39 0.56b 0.48-0.66 

 Noncore Adjacent with Town 1.34b 1.19-1.51 0.55b 0.41-0.74 

 Noncore Adjacent, No Town 1.22 0.84-1.77 0.49b 0.30-0.80 

 Noncore Rural, Not Adjacent 1.38b 1.11-1.71 0.55b 0.36-0.85 

CI = confidence interval. 

-- Reference level. 

a Statistically significant at the 0.05 level. 

b Statistically significant at the 0.01 level. 

1

 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type 

psychotherapeutics used nonmedically. 

2

 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United 

States Department of Agriculture (USDA). These estimates are not comparable with estimates by county type published in other 

NSDUH reports. MSA refers to metropolitan statistical area and MiSA refers to micropolitan statistical area. Noncore is defined

as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004.
183 

60608 

Table 6.17 Results of Logistic Models of Employers Who Test for Drug or Alcohol Use among Full-Time 

Workers Aged 18 to 64: 2002-2004 

Employer Tests for 

Drug or Alcohol Use 

Employer Tests for 

Drug or Alcohol Use 

during Hiring Process 

Employer Tests for 

Drug or Alcohol Use 

on a Random Basis 

Characteristic Odds Ratio CI (95%) Odds Ratio CI (95%) Odds Ratio CI (95%)

Intercept 0.51b 0.46-0.57 0.36b 0.32-0.40 0.16b 0.14-0.18 

Illicit Drug Use1 

 No Lifetime Use -- -- -- -- -- -- 

 Lifetime Use, No Past Year Use 1.02 0.97-1.08 0.98 0.93-1.04 1.00 0.94-1.06 

 Past Year Use, No Past Month Use 0.81b 0.74-0.89 0.77b 0.70-0.85 0.80b 0.71-0.89 

 Past Month Use 0.62b 0.57-0.68 0.55b 0.51-0.60 0.55b 0.50-0.60 

Age Group 

 18-25 -- -- -- -- -- -- 

 26-34 1.12b 1.05-1.19 1.21b 1.15-1.29 1.14b 1.07-1.22 

 35-49 1.08b 1.03-1.15 1.19b 1.13-1.25 1.15b 1.09-1.22 

 50-64 0.90a 0.84-0.98 0.99 0.91-1.08 1.05 0.96-1.15 

Gender 

 Male 1.35b 1.28-1.42 1.39b 1.32-1.46 1.58b 1.49-1.67 

 Female -- -- -- -- -- -- 

Hispanic Origin and Race 

 Not Hispanic or Latino 

 White -- -- -- -- -- -- 

 Black or African American 2.00b 1.85-2.17 2.08b 1.92-2.24 1.82b 1.68-1.98 

 American Indian or Alaska Native 1.65b 1.18-2.32 1.58b 1.14-2.17 2.08b 1.48-2.94 

 Native Hawaiian or Other 

 Pacific Islander 1.65a 1.05-2.58 1.96b 1.24-3.09 1.51 0.93-2.44 

 Asian 1.16 0.96-1.39 1.27a 1.05-1.53 0.70b 0.57-0.86 

 Two or More Races 1.14 0.92-1.41 1.15 0.92-1.44 1.15 0.92-1.43 

 Hispanic or Latino 1.00 0.92-1.09 1.08 0.99-1.18 0.95 0.87-1.04 

Education 

 Less Than High School 1.56b 1.43-1.71 1.56b 1.42-1.70 1.97b 1.77-2.18 

 High School Graduate 1.86b 1.74-1.98 1.88b 1.75-2.01 2.07b 1.92-2.23 

 Some College 1.63b 1.52-1.74 1.63b 1.53-1.75 1.84b 1.71-1.98 

 College Graduate -- -- -- -- -- -- 

Family Income 

 Less Than $20,000 0.58b 0.53-0.63 0.57b 0.52-0.63 0.69b 0.61-0.76 

 $20,000-49,999 0.85b 0.79-0.91 0.84b 0.78-0.90 0.90b 0.83-0.97 

 $50,000-74,999 1.04 0.97-1.12 1.00 0.93-1.08 1.06 0.97-1.16 

 $75,000 or More -- -- -- -- -- -- 

Geographic Region 

 Northeast 0.72b 0.65-0.80 0.77b 0.69-0.85 0.66b 0.59-0.74 

 Midwest 1.15b 1.05-1.25 1.18b 1.08-1.29 0.92 0.84-1.01 

 South 1.31b 1.20-1.43 1.31b 1.20-1.42 1.36b 1.25-1.48 

 West -- -- -- -- -- -- 

County Type2 

 Large MSA -- -- -- -- -- -- 

 Small MSA 1.19b 1.12-1.27 1.14b 1.07-1.22 1.26b 1.18-1.34 

 MiSA 1.16b 1.07-1.26 1.09a 1.01-1.18 1.38b 1.27-1.50 

 Noncore Adjacent with Town 1.03 0.92-1.14 0.94 0.84-1.04 1.26b 1.12-1.43 

 Noncore Adjacent, No Town 0.95 0.71-1.26 0.91 0.64-1.29 1.44a 1.08-1.92 

 Noncore Rural, Not Adjacent 0.94 0.76-1.16 0.77a 0.60-0.98 1.37a 1.07-1.74 

CI = confidence interval. 

-- Reference level. 

a Statistically significant at the 0.05 level. 

b Statistically significant at the 0.01 level. 

1

 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type 

psychotherapeutics used nonmedically. 

2

 Definitions for county type are based on 2003 Urban Influence Codes (UIC), which are provided as a service by the United 

States Department of Agriculture (USDA). These estimates are not comparable with estimates by county type published in other 

NSDUH reports. MSA refers to metropolitan statistical area and MiSA refers to micropolitan statistical area. Noncore is defined

as a nonmetro area that does not contain an urban cluster of 10,000 or more residents. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, and 2004. 
184 
185 

Appendix F: References 

American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders 

(DSM-IV) (4th ed.). Washington, DC: American Psychiatric Association. 

Aquilino, W. S. (1994). Interview mode effects in surveys of drug and alcohol use: A field 

experiment. Public Opinion Quarterly, 58, 210-240. 

Biglan, M., Gilpin, E. A., Rohrbach, L. A., & Pierce, J. P. (2004). Is there a simple correction 

factor for comparing adolescent tobacco-use estimates from school- and home-based 

surveys? Nicotine & Tobacco Research, 6, 427-437. 

Bowman, K. R., Chromy, J. R., Hunter, S. R., & Martin, P. C. (2005a, February). 2004 National 

Survey on Drug Use and Health: Sample design report. In 2004 National Survey on Drug 

Use and Health: Methodological resource book (Section 2, prepared for the Substance 

Abuse and Mental Health Services Administration, Office of Applied Studies, under 

Contract No. 283-03-9028, Deliverable No. 8, RTI/8726). Research Triangle Park, NC: 

RTI International. [To be available as a PDF at 

http://www.oas.samhsa.gov/nhsda/methods.cfm#2k4] 

Bowman, K. R., Chromy, J. R., Hunter, S. R., Martin, P. C., & Odom, D. M. (2005b, January). 

2003 National Survey on Drug Use and Health: Sample design report. In 2003 National 

Survey on Drug Use and Health: Methodological resource book (Section 2, prepared for 

the Substance Abuse and Mental Health Services Administration, Office of Applied 

Studies, under Contract No. 283-98-9008, Deliverable No. 10, RTI/7190.530.400). 

Research Triangle Park, NC: RTI International. [Available as a PDF at 

http://www.oas.samhsa.gov/nhsda/methods.cfm#2k3] 

Bradburn, N. M., & Sudman, S. (1983). Improving interview method and questionnaire design. 

Washington, DC: Jossey-Bass. 

Chen, P., Dai, L., Gordek, H., Shi, W., Singh, A., & Westlake, M. (2005, January). Person-level 

sampling weight calibration for the 2003 NSDUH. In 2003 National Survey on Drug Use 

and Health: Methodological resource book (Section 3, prepared for the Substance Abuse 

and Mental Health Services Administration, Office of Applied Studies, under Contract 

No. 283-98-9008, Deliverable No. 28, RTI/07190.574.100). Research Triangle Park, NC: 

RTI International. [Available as a PDF at 

http://www.oas.samhsa.gov/nhsda/methods.cfm#2k3] 

Delaney, W., Grube, J. W., & Ames, G. M. (1998). Predicting likelihood of seeking help through 

the employee assistance program among salaried and union hourly employees. Addiction, 

93(3), 399-410. 

Deville, J. C., & Särndal, C. E. (1992). Calibration estimating in survey sampling. Journal of the 

American Statistical Association, 87, 376-382. 
186 

Fendrich, M., Johnson, T. P., Sudman, S., Wislar, J. S., & Spiehler, V. (1999). Validity of drug 

use reporting in a high-risk community sample: A comparison of cocaine and heroin 

survey reports with hair tests. American Journal of Epidemiology, 149, 955-962. 

Folsom, R. E., & Singh, A. C. (2000). The generalized exponential model for sampling weight 

calibration for extreme values, nonresponse, and poststratification. In Proceedings of the 

2000 Joint Statistical Meetings, American Statistical Association, Survey Research 

Methods Section, Indianapolis, IN (pp. 598-603). Alexandria, VA: American Statistical 

Association. [Available as a PDF at http://www.amstat.org/sections/SRMS/proceedings/] 

French, M. T., Roebuck, M. C., & Kebreau Alexandre, P. (2004). To test or not to test: Do 

workplace drug testing programs discourage employee drug use? Social Science 

Research, 33(1), 45-63. 

Hartwell, T. D., Steele, P. D., French, M. T., & Rodman, N. F. (1996). Prevalence of drug testing 

in the workplace. Monthly Labor Review, 119(11), 35-42. 

Hartwell, T. D., Steele, P. D., & Rodman, N. F. (1998). Workplace alcohol-testing programs: 

Prevalence and trends. Monthly Labor Review, 121(6), 27-34. 

Hoffmann, J. P., Brittingham, A., & Larison, C. (1996, May). Drug use among U.S. workers: 

Prevalence and trends by occupation and industry categories (Report No. DHHS 

Publication No. SMA 96-3089). Rockville, MD: Substance Abuse and Mental Health 

Services Administration. [Available at http://www.oas.samhsa.gov/work1996/toc.htm

and as a WordPerfect 6.1 file from http://www.oas.samhsa.gov/analytic.htm] 

Hoffmann, J. P., Larison, C., & Sanderson, A. (1997). An analysis of worker drug use and 

workplace policies and programs (Report No. DHHS Publication No. SMA 97-3142, 

Analytic Series A-2). Rockville, MD: Office of Applied Studies. [Available at 

http://www.oas.samhsa.gov/analytic.htm] 

Hser, Y., & Anglin, M. D. (Eds.). (1993). Prevalence estimation techniques for drug-using 

populations [Special issue]. Journal of Drug Issues, 23(2), 163-360. 

Keyfitz, N. (1951). Sampling with probabilities proportional to size: Adjustment for changes in 

the probabilities. Journal of the American Statistical Association, 46, 105-109. 

Mangione, T. W., Howland, J., Amick, B., Cote, J., Lee, M., Bell, N., & Levine, S. (1999). 

Employee drinking practices and work performance. Journal of Studies on Alcohol, 

60(2), 261-270. 

Manly, B. F. J. (1986). Multivariate statistical methods: A primer. London, England: Chapman 

and Hall. 

Normand, J., Lempert, R. O., & O'Brien, C. P. (1994). Under the influence? Drugs and the 

American work force. Washington, DC: National Academy Press. 
187 

Office of Applied Studies. (1999). Substance use and mental health characteristics by 

employment status (DHHS Publication No. SMA 99-3311, Analytic Series A-10). 

Rockville, MD: Substance Abuse and Mental Health Services Administration. [Prepared 

by T. N. Townsend, J. D. Lane, C. S. Dewa, A. M. Brittingham, & M. Pergamit; 

available as a PDF at http://www.oas.samhsa.gov/analytic.htm] 

Office of Applied Studies. (2003). Results from the 2002 National Survey on Drug Use and 

Health: National findings (DHHS Publication No. SMA 03-3836, NSDUH Series H-22). 

Rockville, MD: Substance Abuse and Mental Health Services Administration. [Available 

at http://www.oas.samhsa.gov/p0000016.htm#Standard] 

Office of Applied Studies, Substance Abuse and Mental Health Services Administration. (2005, 

September). Results from the 2004 National Survey on Drug Use and Health: National 

findings. (Report No. DHHS Publication No. SMA 05-4062, NSDUH Series H-28). 

Rockville, MD: Substance Abuse and Mental Health Services Administration, Office of 

Applied Studies. [Available at http://www.oas.samhsa.gov/p0000016.htm#2k4] 

Office of Management and Budget. (1997). Revisions to the standards for the classification of 

federal data on race and ethnicity. Federal Register, 62(210), 58781-58790. [Available at 

http://www.whitehouse.gov/omb/fedreg/1997standards.html] 

Office of Management and Budget. (2003, June 6). OMB Bulletin No. 03-04: Revised 

definitions of metropolitan statistical areas, new definitions of micropolitan statistical 

areas and combined statistical areas, and guidance on uses of the statistical definitions of 

these areas [Web Page]. URL http://www.whitehouse.gov/omb/bulletins/b03-04.html

[July 18, 2006; August 17, 2005; July 22, 2004; June 7, 2004; September 29, 2003; July 

30, 2003] 

Reynolds, G. S., & Lehman, W. E. (2003). Levels of substance use and willingness to use the 

Employee Assistance Program. Journal of Behavioral Health Services & Research, 

30(2), 238-248. 

RTI International. (2004). SUDAAN® language manual, Release 9.0. Research Triangle Park, 

NC: Author. 

RTI International. (2005). 2003 National Survey on Drug Use and Health: Methodological 

resource book (RTI 7190, prepared for the Substance Abuse and Mental Health Services 

Administration, Office of Applied Studies, under Contract No. 283-98-9008, Deliverable 

No. 28). Research Triangle Park, NC: Author. [Available as a PDF at 

http://www.oas.samhsa.gov/nhsda/methods.cfm#2k3] 

Singh, A., Grau, E., & Folsom, R., Jr. (2001). Predictive mean neighborhood imputation with 

application to the person-pair data of the National Household Survey on Drug Abuse. In 

Proceedings of the 2001 Joint Statistical Meetings, American Statistical Association, 

Survey Research Methods Section, Atlanta, GA [CD-ROM]. Alexandria, VA: American 

Statistical Association. [Available as a PDF at 

http://www.amstat.org/sections/SRMS/proceedings/] 
188 

Singh, A., Grau, E., & Folsom, R., Jr. (2002). Predictive mean neighborhood imputation for 

NHSDA substance use data. In J. Gfroerer, J. Eyerman, & J. Chromy (Eds.), Redesigning 

an ongoing national household survey: Methodological issues (DHHS Publication No. 

SMA 03-3768, pp. 111-133). Rockville, MD: Substance Abuse and Mental Health 

Services Administration, Office of Applied Studies. [Available as a PDF at 

http://www.oas.samhsa.gov/nhsda/methods.cfm#Reports] 

SRNT Subcommittee on Biochemical Verification. (2002). Biochemical verification of tobacco 

use and cessation. Nicotine &Tobacco Research, 4, 149-159. 

Turner, C. F., Lessler, J. T., & Gfroerer, J. C. (Eds.). (1992). Survey measurement of drug use: 

Methodological studies (DHHS Publication No. ADM 92-1929). Rockville, MD: 

National Institute on Drug Abuse. 

U.S. Department of Labor, Bureau of Labor Statistics. (2000). Standard Occupational 

Classification (SOC) User Guide. Retrieved December 21, 2006, from 

http://www.bls.gov/soc/socguide.htm

Wright, D., & Sathe, N. (2004). State estimates of substance use from the 2002-2003 National 

Surveys on Drug Use and Health (DHHS Publication No. SMA 05-3989, NSDUH Series 

H-26). Rockville, MD: Substance Abuse and Mental Health Services Administration, 

Office of Applied Studies. [Available at http://www.oas.samhsa.gov/states.htm and 

http://www.oas.samhsa.gov/states.htm#Prevalence] 

Zhang, Z., Huang, L. X., & Brittingham, A. M. (1999). Worker drug use and workplace policies 

and programs: Results from the 1994 and 1997 National Household Survey on Drug 

Abuse. (Report No. DHHS Publication No. SMA 99-3352, Analytic Series A-11). 

Rockville, MD: Substance Abuse and Mental Health Services Administration, Office of 

Applied Studies. [Available at http://www.oas.samhsa.gov/analytic.htm]