DRUG USE

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

NATIONAL INSTITUTES OF HEALTH

RACIAL/ETHNIC

MINORITIES

REVISED

NATIONAL INSTITUTE ON DRUG ABUSE Among

mong

Drug Use Among Racial/Ethnic Minorities

U.S. Department of Health and Human Services

National Institutes of Health

National Institute on Drug Abuse

Division of Epidemiology, Services & Prevention Research

6001 Executive Blvd, Room 5164

Bethesda, MD 20892-9589

www.drugabuse.gov
ACKNOWLEDGMENTS

This publication was produced for the National Institutes of Health, National Institute on Drug Abuse (NIDA),

Division of Epidemiology, Services and Prevention Research, by faculty and staff of the Johns Hopkins

University, Bloomberg School of Public Health, Department of Mental Hygiene, under an order for services

commissioned through Management Assistance Corporation of Rockville, Maryland. Leslie Cooper, Ph.D.,

M.P.H., R.N., National Institute on Drug Abuse, provided scientific oversight, critical review, and substantive

comments for this publication.

PUBLIC DOMAIN NOTICE

All material appearing in this volume is in the public domain and may be reproduced or copied without permission from NIDA. Citation of the source is appreciated.

For questions or comments on this document, 

please send an e-mail to Dr. Leslie Cooper at: lc58q@nih.gov

National Institute on Drug Abuse

NIH Publication No. 03-3888

Printed 1995

Revised September 1998

Revised September 2003
iii

LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix

Chapter 1. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 

DEFINITION OF RACE AND ETHNICITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 

American Indians/Alaska Natives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 

Asian/Pacific Islanders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

African Americans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Hispanics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

OVERVIEW OF DRUG USE AND DRUG-RELATED PROBLEMS . . . . . . . . . . . . . . . . 12

METHODS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

DATA SOURCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Census of the United States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

National Household Survey on Drug Abuse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Partnership Attitude Tracking Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Monitoring the Future Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

National Longitudinal Survey of Youth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Dropout Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

American Indian/Alaska Native Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Youth Risk Behavior Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Drug Abuse Warning Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

AIDS Surveillance Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

Arrestee Drug Abuse Monitoring Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

ORGANIZATION OF THIS REPORT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Chapter 2. POPULATION STATISTICS FOR RACIAL/ETHNIC MINORITIES 

IN THE UNITED STATES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

POPULATION STATISTICS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

SUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Chapter 3. DRUG USE IN THE GENERAL POPULATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

PREVALENCE OF DRUG USE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36

ATTITUDES AND PERCEPTIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

SUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

CONTENTS
Contents

Chapter 4. PREVALENCE OF DRUG USE AMONG YOUTH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59

AGE AT FIRST USE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

PREVALENCE TRENDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

School-Attending Youth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

American Indian/Alaska Native Students . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66

LONGITUDINAL TRENDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

SUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69

Chapter 5. YOUTH DRUG USE AND RISK BEHAVIORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

SCHOOL DROPOUT TRENDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89

RISK BEHAVIOR TRENDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91

SUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92

Chapter 6. ADVERSE SOCIAL, BEHAVIORAL, AND HEALTH CONSEQUENCES . . . . . . . . . . 101

AIDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103

DRUG-RELATED EMERGENCY ROOM EPISODES . . . . . . . . . . . . . . . . . . . . . . . . . 104

DRUG-RELATED DEATHS AND INTENTIONAL AND 

UNINTENTIONAL INJURIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108

SUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110

Chapter 7. DRUGS AND CRIME . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129

DRUG USE AMONG BOOKED ARRESTEES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131

DRIVING UNDER THE INFLUENCE OF ALCOHOL OR ILLEGAL DRUGS . . . . . 133

SUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134

Chapter 8. SUMMARY AND FUTURE DRUG ABUSE PROGRAM AND RESEARCH NEEDS . . 139

REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145

APPENDICES

Appendix 1. NIDA POSITION STATEMENT, HEALTH DISPARITIES: DEFINITIONS . . . . . . . . . 157

Appendix 2. NIDA STRATEGIC PLAN ON REDUCING HEALTH DISPARITIES . . . . . . . . . . . . . 159

iv
v

Table 1. Estimated Percentage Distribution of U.S. Population, by Race/Ethnicity and 

Hispanic Origin: 1990–2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Table 2. Weighted Average Poverty Thresholds, by Size of Family: Selected Years . . . . . . . . . . . . . . . . . . 26

Table 3. Poverty Thresholds, by Size of Family and Number of Related Children Under 18 Years

of Age (in dollars): 2001 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

Table 4. Person and Families Living Below Poverty Level, According to Selected Characteristics, 

Race, and Hispanic Origin: 1990–2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Table 5. NHSDA Sample Sizes and U.S. Civilian Noninstitutionalized Population Totals, by Sex 

and Age Across Race/Ethnicity for Age 12 and Older: 1998 . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Table 6. Estimated Prevalence of Use of Selected Drugs Among Persons Age 12 and Older in the 

United States: 1998 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Table 7. Estimated Prevalence of Past-Month Drug Use in the United States, by Age and Sex 

(by percent): 1998 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

Table 8. Estimated Prevalence of Past-Month Drug Use in the United States, by Age, Sex, and

Race/Ethnicity (by percent): 1998 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

Table 9. Estimated Prevalence of Past-Month Drug Use Among Hispanics in the United States, 

by Age and Sex (by percent): NHSDA 1997 and 1998 Data Combined . . . . . . . . . . . . . . . . . . 52

Table 10. Estimated Percentage of Women of Childbearing Age (15–44) Using Drugs, by Age,

Race/Ethnicity, and Population Density: 1998 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

Table 11. Estimated Percentage of Live-Born Infants’ Mothers Who Reported Smoking During 

Pregnancy, by Year and Race/Ethnicity, U.S. Final Natality Statistics: 1993–1999 . . . . . . . . . . . 55

Table 12. Estimated Percentage of Respondents Who Believe That Selected Drugs Are Easy to 

Get for Themselves (Youth and Teens) and by Their Children (Parents), by Race/Ethnicity:

1997–2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

Table 13. Estimated Percentage of Respondents Who Associate Danger/Great Risk with the Use 

of Selected Drugs, by Race/Ethnicity: 1997–2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

Table 14. Estimated Percentage of Respondents Who Agree With Selected Statements About 

Specific Drugs, by Race/Ethnicity: 1997–2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

Table 15. Estimated Average Age of First Use of Cigarettes, Alcohol, and Marijuana for Youth 

Ages 12–17, by Race/Ethnicity: Selected Years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

LIST OF TABLES
List of Tables

Table 16. Estimated Prevalence of Lifetime, Annual, 30-Day, and Daily Use of Selected Drugs, by

Race/Ethnicity for Students in Grades 8, 10, and 12 (by percent): 2000 . . . . . . . . . . . . . . . . . . 72

Table 17. Trends in the Estimated Percentage of 12th-Graders Who Were Previous-Month Smokers, by

Race/Ethnicity and Gender: 1976–1999 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75

Table 18. Estimated Prevalence of Use of Selected Substances in the Past Year, Cigarette Use in the 

Past 30 Days, and Binge Drinking in the Past 2 Weeks Among 12th-Graders and 8th-Graders, 

by Sex and Race/Ethnicity (by percent): Selected Years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76

Table 19. Estimated Percentage of African-American and White 12th-Graders Who Reported Using 

or Not Using Tobacco Cigarettes and Other Substances in the Past 30 Days: 1976–1994 

Aggregate Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78

Table 20. Estimated Prevalence of Youth Age 12 and Older Having Used Alcohol, Marijuana, 

Cocaine, or Crack-Cocaine in Lifetime or Past Month, by Age, Sex, Race/Ethnicity 

(by percent): 1999 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

Table 21. Estimated Percentage of American Indian 7th–12th Graders Living on Reservations 

Who Reported Lifetime Use of Drugs: 1975–1998 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

Table 22. Estimated Lifetime Prevalence of Drug Use for American Indian and Non-Indian 8th, 

10th, and 12th-graders (by percent): 1997–1998 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

Table 23. Estimated Percentage of American Indian 4th–6th Graders Who Reported Lifetime 

Use of Drugs: Selected Years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

Table 24. Estimated Percentage of National Longitudinal Survey of Youth Cohorts Who Admitted 

Using Marijuana and Cocaine, by Race/Ethnicity and Year . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

Table 25. Rate, Number, and Distribution of Status Dropouts, by Sex, Race/Ethnicity, Age, Region, 

and Recency of Immigration: 1999 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93

Table 26. Status Dropout Rates for Persons Ages 16–24, by Family Income and 

Race/Ethnicity (by percent): 1990 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94

Table 27. Event Dropout Rates for Persons Ages 15–24 Who Dropped Out of Grades 10–12, 

by Sex and Race/Ethnicity (by percent): October 1972–October 1999 . . . . . . . . . . . . . . . . . . . 95

Table 28. Reasons for Dropping Out of School, by Sex and Race/Ethnicity (by percent): 1992 . . . . . . . . . 96

Table 29. High-School Completion Rates and Method of Completion for Persons Ages 18–24 Years, 

by Race/Ethnicity and Year (by percent): October 1995–October 1999 . . . . . . . . . . . . . . . . . . 97

Table 30. Estimated Percentage of Youth Engaging in Risk Behaviors, by Drug Users and Nonusers 

and Race/Ethnicity: 1999 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98

vi
List of Tables

Table 31. Female Adult/Adolescent AIDS Cases, by Exposure Category and Race/Ethnicity: Cumulative

Totals Through December 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

Table 32. Male Adult/Adolescent AIDS Cases, by Exposure Category and Race/Ethnicity: 

Cumulative Totals Through December 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112

Table 33. Estimated Rates of Emergency Department Drug Abuse Episodes and Mentions of 

Selected Drugs per 100,000 Population in the Coterminous United States, by Sex and 

Age: 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113

Table 34. Drug Mentioned Most Frequently by Hospital Emergency Departments, by Sex and 

Race/Ethnicity of Patients: 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114

Table 35. Estimated Number of DAWN Hospital Emergency Department Visits, by Race/Ethnicity 

and Age: 1994–2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115

Table 36. Estimated Number of DAWN Emergency Department Visits With Mention of Cocaine, 

by Race/Ethnicity and Age: 1994–2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117

Table 37. Estimated Number of DAWN Emergency Department Visits With Mention of 

Heroin/Morphine, by Race/Ethnicity and Age, 1994–2000 . . . . . . . . . . . . . . . . . . . . . . . . . . 119

Table 38. Estimated Number of DAWN Emergency Department Visits With Mention of

Methamphetamine/Speed, by Race/Ethnicity and Age, 1994–2000 . . . . . . . . . . . . . . . . . . . . 121

Table 39. Estimated Number of DAWN Emergency Department Visits With Mention of 

Marijuana/Hashish, by Race/Ethnicity and Age, 1994–2000 . . . . . . . . . . . . . . . . . . . . . . . . . 123

Table 40. Percentage of DAWN Hospital Emergency Department Drug Abuse Episodes, 

by Selected Episode Characteristics, Sex, and Race/Ethnicity: 2000 . . . . . . . . . . . . . . . . . . . . . 125

Table 41. Comparison of Race/Ethnicity Distribution for Total DAWN Hospital Emergency 

Episodes with Race/Ethnicity Distribution for Selected Drug Mentions: 2000 . . . . . . . . . . . . 125

Table 42. Drugs Mentioned Most Frequently by Medical Examiners, by Sex and Race/Ethnicity of

Decedents: 1999 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126

Table 43. Estimated Prevalence of Positive Urinalysis Tests from the Arrestee Drug Abuse 

Monitoring Program: 1987–1999 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136

Table 44. Estimated Percentage of People Having Driven a Vehicle Under the Influence of Alcohol 

or Illegal Drugs in the Past 12 Months, by Race, Sex, and Age: 1998 . . . . . . . . . . . . . . . . . . . 138

vii

ix

Figure 1. Estimated Prevalence of Illegal Drug Use for Parolees and Probationers Versus 

Other Adults: 2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Figure 2. Estimated Prevalence of Recent Illegal Drug Use by Race/Ethnicity: 1999–2000 . . . . . . . . . . 34

Figure 3. Estimated Prevalence of Recent Tobacco Cigarette Smoking, by Race/Ethnicity: 

1999–2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Figure 4. Estimated Number of New Users of Cocaine for Three Population Subgroups: 

1976–1989 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Figure 5. Trends in the Prevalence of Daily Cigarette Use Among 12th-Graders, by Race/Ethnicity 

Group: 1977–2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82

Figure 6. Trends in the Prevalence of Marijuana Use Among 12th-Graders, by Race/Ethnicity 

Group: 1977–2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83

Figure 7. Trends in the Prevalence of Inhalant Use Among 12th-Graders, by Race/Ethnicity 

Group: 1977–2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84

Figure 8. Trends in the Prevalence of Cocaine Use Among 12th-Graders, by Race/Ethnicity 

Group: 1977–2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

Figure 9. Trends in the Prevalence of LSD Use Among 12th-Graders, by Race/Ethnicity Group: 

1977–2000 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86

Figure 10. Trends in the Prevalence of Any Illicit Drug Use Among 12th-Graders, by Race/Ethnicity

Group: 1977–1999 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87

Figure 11. Status Dropout Rates for Persons Ages 16–24, by Race/Ethnicity: 

October 1972–October 1999 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99

Figure 12. Completion Rates for Persons Ages 18–24 Not Currently Enrolled in High School 

or Below, by Race/Ethnicity: October 1972–October 1999 . . . . . . . . . . . . . . . . . . . . . . . . 100

Figure 13. Manner of Drug-Related Death, by Race/Ethnicity, DAWN Medical Examiner 

Data: 1999 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127

LIST OF FIGURES

1

The purpose of this report is to provide policymakers, program leaders and staff, health administrators, scientists,

and others with information that may help them understand the nature and extent of illegal drug use, associated

behaviors, and problems that now affect our Nation’s racial/ethnic minority populations and the current nonHispanic White majority population. Its content has been culled from the best and most recent reports on 

these topics.

Data sources for this report include the U.S. Census and large- and small-scale epidemiological studies that have

been collecting and analyzing data on the incidence, prevalence, morbidity, mortality, and other adverse health

consequences of illegal drug use in the United States, with a general restriction to investigations with ample coverage of two or more racial/ethnic populations. Study sponsors comprise an array of Federal agencies, including

the U.S. Bureau of the Census (the Census Bureau); the National Institute on Drug Abuse (NIDA); the Centers

for Disease Control and Prevention (CDC) and its constituent units, such as the National Center for Health

Statistics; the Department of Education; the Department of Justice; the National Institute of Justice (NIJ); and

the Substance Abuse and Mental Health Services Administration (SAMHSA). NIDA-sponsored research programs of special prominence in this report include the Monitoring the Future (MTF) project and the Native

American youth surveys conducted by the Tri-Ethnic Center for Prevention Research in Fort Collins, Colorado.

Information on youth’s attitudes toward drugs also is included, based on surveys conducted by the Partnership

for a Drug-Free America via its Partnership Attitude Tracking Survey (PATS).

The context for this report includes major demographic changes now affecting the United States. These changes

started during the 20th century and will persist through the current century. For example, by 2030, racial/

ethnic minorities are expected to constitute one-half of the K–12 student population of the United States. In a

complementary demographic shift, the non-Hispanic White share of the total U.S. population is expected to

decline from 75 percent in the early 1990s to 60 percent in 2030, 50 percent between 2050 and 2060, and 

40 percent by 2100. By that year, non-Hispanic Whites will have become a racial/ethnic minority population of

the United States (U.S. Bureau of the Census 2000a). This demographic transformation of the U.S. population

and the composition of its minority populations warrant the attention of our policymakers and program planners,

who must help our Nation understand and cope with the changing social and demographic context of our daily

lives at home, in the workplace, and in our communities.

An historical perspective provides further context for this report. After the Second World War, medical, nonmedical, and extramedical domestic use of legitimate pharmaceutical products increased. These products, 

available over the counter or by prescription, included over-the-counter benzedrine inhalers and amphetaminecontaining diet pills, as well as over-the-counter and prescription sedative (calming) and hypnotic (sleepenhancing) medicines containing barbiturates and newer synthetic drugs. There was no assertion of a strong

association linking use of these drugs to racial/ethnic minorities. Sustained problems associated with extramedical

use of these drugs and concerns about potentially burgeoning use of heroin, marijuana, and LSD fostered a

renewal of Federal interest.

In the United States, the era of military conflict and war in Vietnam was marked by an increase in marijuana

smoking and LSD use, in addition to continued problems with psychostimulants and sedative-hypnotic 

medicines. New illegal drug use patterns surfaced in the form of recreational use of methylenedioxymethamphetamine (MDMA, “ecstasy”) and other hallucinogenic and psychostimulant drugs (e.g., mescaline and crystal

Chapter 1. INTRODUCTION
Introduction

methamphetamine) and cocaine hydrochloride powder (e.g., see National Commission on Marihuana and

Drug Abuse 1972, 1973).

During the early 1970s, the complex social context of illegal drug use was recognized in the work of a new

National Commission on Marihuana and Drug Abuse, which identified marijuana smoking and other illegal

drug use as a “signal of misunderstanding” between the generations and diverse subgroups of our Nation

(National Commission on Marihuana and Drug Abuse 1972, 1973). However, despite important scholarly 

and empirical contributions to our understanding of illegal drug use in the United States, the results of the 

commission’s work mainly were seen in isolated changes of local and State policies toward marijuana use and in

general improvements within the Federal apparatus for nationwide surveillance of illegal drug use and renovation

of Federal responsibility for support of drug-related services and scientific research on illegal drug use.

The Federal surveillance apparatus fostered by the National Commission on Marihuana and Drug Abuse proved

to be a robust contribution, in part because surveillance responsibilities soon were housed within newly established, science-oriented NIDA, before it became part of the National Institutes of Health (NIH) in 1992. One

of the benefits of this work was a much-improved base of evidence on the epidemiology of illegal drug use and

drug problems in the general population, starting with a national survey of illegal drug use completed for 

the commission in the early 1970s. After NIDA was formed in 1974, the first national survey of household 

residents evolved into a survey series that became the National Household Survey on Drug Abuse (NHSDA).

This survey now is the major instrument for epidemiological surveillance of illegal drug use in the United States

and is the responsibility of the Office of Applied Studies (OAS) within SAMHSA.

For its part, the former Bureau of Narcotics and Dangerous Drugs and current Drug Enforcement

Administration (BNDD/DEA) fostered development of the Drug Abuse Warning Network (DAWN), a form

of early sentinel surveillance to detect emerging patterns of illegal drug use that pose hazards to public health

and safety. Once developed by BNDD/DEA, DAWN surveillance responsibilities were transferred to NIDA

and then to OAS within SAMHSA. In use for about three decades, DAWN collects and reports information on

casualties secondary to illegal drug use. Sources for this information are autopsy records of medical examiners

and clinical records of hospitals with emergency rooms that have responsibility for management of drug 

overdoses and other drug-related emergency crises such as bad trips and acute infectious diseases.

Illegal drug use by high-school seniors also was recognized by the national commission as an important topic

for surveillance, due in part to a recognition that the future leadership of any country depends heavily on its

secondary school graduates. Soon after the first national survey of illegal drug use among secondary students,

the University of Michigan inaugurated the MTF series of surveys of 12th-graders in 1975. These surveys were

accompanied by a series of annual reports and monograph-length books based on a NIDA-funded repetition of

the annual surveys for over 25 years. In recent years, the MTF surveys have expanded to include samples of 

8th, 10th, and 12th grade.

After a decade of sustained surveillance via NHSDA, DAWN, and MTF, the Anti-Drug Abuse Act of 1986 and

the Anti-Drug Abuse Act of 1988 fostered a deliberate focus on the illegal drug use of racial/ethnic minority

populations and patients in drug treatment programs. Epidemiologic data about alcohol and other drug use

among youth and adult minorities have slowly been emerging, but more attention is needed to adequately

understand the nature and scope of illegal drug use and associated problems for these populations.

2
Introduction

From these surveillance systems and specialized studies, we have learned that population subgroups experiencing

high rates of illegal drug use and associated problems often are constrained by limited employment opportunities,

poverty, illiteracy or low education level, and other unhealthy environmental conditions, such as disadvantaged

neighborhoods and lack of social capital (Anthony and Helzer, in press for 2002). For some drugs (but not all),

the prevalence of illegal drug use sometimes is higher in urban areas than in suburban or rural areas. Because

minorities, particularly African Americans and Hispanics, often are concentrated in central city areas, one might

think that they are at greater risk for illegal drug use and, ultimately, more at risk for associated negative social

and health consequences. This report examines these and other preconceptions about racial/ethnic minority

populations in the United States and includes a careful selection of published evidence on the subject.

DEFINITION OF RACE AND ETHNICITY

Any serious treatment of the topic of illegal drug use and racial/ethnic minorities must address current definitions

of race and ethnicity, which are under increasing scrutiny. In addition, measurement procedures for race and

ethnicity are changing as these concepts evolve. For example, in the U.S. Census, administrative statistics, and

research projects, the head of a household or individual respondents are permitted to identify themselves in 

designations of race and ethnicity. Congruent with this approach, many scientists assert that race is a mere

“social construct” and claim that the boundaries between different races depend more on perceptions within a

social psychological context and less on fundamental biological differences. A similar claim is advanced in the

argument that genetics research has successfully delegitimized claims that races are categorically distinct human

groupings (e.g., see Begley 1995; Condit et al. 2001).

Although prominent in standard vital statistics and disease surveillance operations for almost two centuries, our

concepts of race and ethnicity represent a longstanding source of social controversy. Definitions and measurement procedures for these concepts continue to vary considerably by investigation, with no strong consensus to

support one concept or approach over another, even in programs directed toward conditions with race-lined

genetic susceptibilities such as sickle-cell disease (e.g., see Condit et al. 2001).

In the United States, administrators responsible for national-level vital statistics and disease surveillance systems

tend to steer clear of the controversies that arise in discussions of race and ethnicity. They generally have 

followed the standards outlined in Statistical Policy Directive No. 15, issued by the Office of Management 

and Budget (OMB) (U.S. Department of Commerce 1978). More recent standards have been issued,1 which

are being incorporated as revisions of the national-level vital statistics and disease surveillance systems. However,

the data available for this report largely were gathered using protocols based on the prior standards for classification of race and ethnicity.

According to the 1978 directive, the four primary racial categories are American Indian/Alaska Native,

Asian/Pacific Islander, African American or Black, and White. The directive identifies Hispanic origin as an 

ethnicity, which in this context is defined as the nationality group or country of birth of a person or a person’s

parents or ancestors before arrival in the United States. Persons of Hispanic origin may be of any race. 

3

1 “Recommendations from the Interagency Committee for the Review of the Racial and Ethnic Standards to the Office of

Management and Budget Concerning Changes to the Standards for the Classification of Federal Data on Race and Ethnicity.”

Federal Register (62 FR 36874-36946), July 9, 1997.
Introduction

The definitions for the four race categories, as specified under Directive No. 15, are as follows:

● American Indian/Alaska Native—a person having origins in any of the original peoples of North America

who maintains cultural identification through tribal affiliations or community recognition; 

● Asian/Pacific Islander—a person having origins in any of the original peoples of the Far East, Southeast

Asia, the Indian subcontinent, or the Pacific Islands;

● Black or African American—a person having origins in any of the racial groups of Africa; and

● White—a person having origins in any of the original peoples of Europe, North Africa, or the Middle East.

These race categories may be combined with an ethnicity definition that distinguishes Hispanic individuals

from those who are non-Hispanic, in accord with Directive No. 15:

● Hispanic—a person of Mexican, Puerto Rican, Cuban, Central or South American, or other Spanish 

culture or origin, regardless of race. 

Although these classification standards from 1978 have been used in many projects, they have been criticized

for their failure to reflect the growing diversity of our Nation’s population and their lack of sensitivity to distinctions within the broadly stated groups (e.g., subgroups within the Asian/Pacific Islander and American

Indian/Alaska Native groups). During the last decades of the 20th century, immigration to the United States

from Mexico, Central and South America, the Caribbean, and Asia reached historic proportions. In addition,

as a result of the increase in interracial marriages, the number of persons born of mixed race or ethnicity has

grown. Directive 15 also has been criticized as failing to be scientific. In response to these and other criticisms,

OMB initiated a new review of the classification standards for data on race and ethnicity in June 1993.

As part of the review process, OMB established the Interagency Committee for the Review of the Racial and

Ethnic Standards in March 1994 to facilitate Federal agency participation in the review process. The committee’s

30 members were employees of the agencies that represent the diverse Federal needs for data on race and 

ethnicity, including statutory requirements for such data. Two major elements of the process were (1) public

comment on present definitions and (2) research and testing to assess the possible effects of recommended

changes on the quality and usefulness of the resulting data. The goal of the committee’s work was to produce

definitions resulting in consistent, publicly accepted data on race and ethnicity to meet the needs of the Federal

Government and the public, while recognizing the diversity of the population and respecting individual dignity.

This section details the Interagency Committee’s recommendations for changes in racial and ethnic categories

for use by the U.S. Government. The Census Bureau incorporated many of these changes into the 2000 census.

According to the Interagency Committee’s recommendations, the minimum categories for data on race and 

ethnicity or Federal statistics and program administrative reporting are defined as follows:

● American Indian or Alaska Native—a person having origins in any of the original peoples of North and

South America (including Central America) who maintains cultural identification through tribal affiliations

or community recognition;

4
Introduction

● Asian or Pacific Islander—a person having origins in any of the original peoples of the Far East, Southeast

Asia, the Indian subcontinent, or the Pacific Islands. These areas include, for example, China, India, Japan,

Korea, the Philippine Islands, Hawaii, and Samoa;

● Black or African American—a person having origins in any of the Black racial groups of Africa;

● Hispanic—a person of Mexican, Puerto Rican, Cuban, Central or South American, or other Spanish 

culture or origin, regardless of race; and

● White—a person having origins in any of the original peoples of Europe, North Africa, or the Middle East.

The recommended changes for data collection also include an emphasis on data quality. The committee 

recommended that when race and ethnicity data are collected separately, ethnicity data should be collected first.

In addition, the minimum designations for ethnicity and race are as follows:

● Ethnicity 

– Hispanic origin

– Not of Hispanic origin; and

● Race 

– American Indian or Alaska Native

– Asian or Pacific Islander

– Black or African American

– White

In addition, persons are allowed but are not required to report more than one race. A minimum of one additional

racial category, designated “more than one race” has been recommended to report the aggregate number of 

multiple race responses. This classification system allows for the collection of data on special subgroups, such as

“Hispanic and one or more races” and “More than one race.”

For the full text of the committee’s analysis and recommendations, readers should refer to Appendix 2 of the

Federal Register for July 9, 1997. These recommendations, designed to provide minimum standards for Federal

data on race and ethnicity, address options for reporting by respondents, formats of questions, and several

aspects of specific categories, including possible additions, revised terminology, and changes in definition. The

Census Bureau has provided an overview of its implementation of these recommendations for the 2000 census

(U.S. Bureau of the Census 2001a).

The following population statistics and information on drug use among members of each race/ethnicity are

summarized from existing reports and provide a context for the data discussed later in this report. A summary of

Asian/Pacific Islander information is provided for completeness only; data available on drug use within this segment of the U.S. population remain very limited, although promising new investigations are being conducted

by OAS within SAMHSA and by investigators supported by NIH and CDC.

5
Introduction

Notwithstanding the importance of summarizing national statistics in terms of broadly defined racial and ethnic

subgroups, this report takes for granted that considerable heterogeneity and variation exist within the several

racial groups and ethnic categories used in reporting statistics from recent surveys. Throughout this report, we

draw the reader’s attention to the clear heterogeneity and variation within minority populations of the United

States. Statements that might be true, on average, for these aggregated populations may be wholly untrue for

individual subgroups within the aggregate. For example, we know considerably more about the illegal drug use

of American Indians than that of Alaska Natives. Broadly stated generalizations about the aggregate category 

for “American Indian/Alaska Native” populations may hold for some tribes of American Indians but not for

others, or may hold for American Indians in general but not for Alaska Natives. Distinctions of this type, and

the possibilities for variation within aggregate minority populations, are essential to remember, even as we make

use of the aggregations to understand health disparities that might exist within and across racial and ethnic 

populations of the United States.

The report also is informed by a NIDA position statement on health disparities and the relationships between

health disparities and the use of tobacco, alcohol, and illegal drugs. A copy of this statement is found in

Appendix 1.

American Indians/Alaska Natives

At the turn of the century, 220,000 American Indians/Alaska Natives lived in the United States; the 1990 and

2000 census counts indicate that this population had grown to approximately 2 million, two times the 1970

count (U.S. Bureau of the Census 1991, 2000a). This exceptional increase may be traced to improved health

care for all ages, a robust birth rate, reduced infant mortality, and possible greater willingness to report Native

American ancestry in each of the most recent decennial census enumerations.

Several social and demographic facts are pertinent. For example, in 1994, the birth rate among American

Indians/Alaska Natives was 13 percent higher than that of the country at large (U.S. Bureau of the Census

1996). The median age of the American Indian/Alaska Native population was 24.2 years in 1990, compared

with 34.4 years for U.S. Whites (Indian Health Service 1994). Sixty-two percent of American Indians now 

live away from traditional native communities or reservations, and most groups are small with not much 

land (Robbins 1994). Indian culture and physical characteristics, though believed by many to be homogeneous,

are best described as diverse. By the mid-1900s, there were more than 300 federally recognized tribes

(Hirschfelder and Montano 1993). By 1997, there were more than 550 federally recognized tribes (U.S. Bureau

of Indian Affairs 1997). 

Serious concern exists that American Indian/Alaska Native populations have not been well represented in

national statistics and surveillance activities for drug involvement (e.g., too few American Indian/Alaska Native

participants in the surveys). In addition, the statistics and surveys generally have not attended to suspected 

variation in drug involvement within and across tribal groups in this minority population. Responding to these

concerns, NIDA has sponsored research at the Tri-Ethnic Center for Prevention Research in Fort Collins,

Colorado, and other studies designed to include specific coverage of American Indian or Alaska Native minority

group members. These studies have suggested heavy use of alcohol, tobacco, and other drugs as serious public

health problems within these populations (Beauvais et al. 1989; Blum et al. 1992; Fleming et al. 1996; Indian

Health Service 1994; U.S. Department of Health and Human Services 1998; Stillner et al. 1999). Some

research indicates more excessive drinking and illegal drug use among American Indians and Alaska Natives than

6
Introduction

among most, if not all, other racial/ethnic minority groups in the United States, even when the younger median

age of the American Indian/Alaska Native population group is taken into account (U.S. Office for Substance

Abuse Prevention 1990; Bachman et al. 2001).

Excess prevalence of illegal drug use in the American Indian/Alaska Native population also is suggested in evidence

from the most recent NHSDA, from calendar year 2000. According to NHSDA 2000, an estimated 14 million

Americans age 12 and older were active and current illegal drug users (i.e., with a history of using drugs illegally

during the 1-month interval before survey assessment). Estimated as a proportion, this value for “past month”

or “current” use is slightly more than 6 percent of the total population age 12 and older. The corresponding 

survey estimate for active and current illegal drug use among American Indian/Alaska Natives is 12.6 percent

(Substance Abuse and Mental Health Services Administration 2001b). In surveys focused solely on young people,

prevalence estimates for drug involvement in the month before assessment also show that American

Indian/Alaska Native youth use marijuana, cocaine, cigarettes, and alcohol at two or more times the observed

values for Hispanic and non-Hispanic Whites and Blacks. In a recent study of young adolescents in North

Carolina, cumulative occurrence of alcohol, tobacco, marijuana, and other drug use among American Indians

exceeded the occurrence rates observed for non-Hispanic White and African-American groups (Federman et al.

1997). According to the national MTF study, by 12th grade an estimated 40 to 52 percent of American

Indian/Alaska Native students smoke tobacco. Corresponding values for African-American students range from

10 to 20 percent (Bachman et al. 2001).

The higher prevalence values observed for American Indian/Alaska Native populations have been described by

Robbins (1994) as cutting across many different subgroups of this aggregate category, affecting both sexes, 

and possibly nourishing cycles of poverty and disease. Regrettably, American Indian/Alaska Native youth have 

been observed to begin using tobacco cigarettes and alcohol at an earlier age than their White counterparts

(Young 1988) and to try marijuana at an earlier age than White youth (U.S. Office for Substance Abuse

Prevention 1990).

We already have mentioned the theme of heterogeneity or variation within aggregate racial/ethnic minority 

populations of the United States. The national statistics reported in this chapter and throughout this report are

based mainly on data for American Indians, with few Alaska Natives included in the national surveys. Although

several important recent focused studies of Alaska Native populations have been done (e.g., Stillner et al. 1999),

it is difficult to compare results from these studies with those from nationally representative sample surveys

because of differences in sampling plans, assessment methods, and other details of approach. Indeed, in reports

from recent student surveys conducted for CDC, the prevalence of drug involvement among Alaska Native 

students was not found to be appreciably different from that of other students living in Alaska (Alaska

Department of Health and Social Services 1995). For such reasons, it is not now possible to make a comprehensive comparison of illegal drug involvement and associated problems for subgroups within the American

Indian/Alaska Native population. It is important to remember that statistical summaries about this population

may be true, on average, but may not apply to specific individual tribal groups or other subgroupings within

this population. Written with the hope that readers will keep this issue firmly in mind, the remainder of this

report highlights comparisons between population-averaged values for the American Indian/Alaska Native 

population as a whole and corresponding population-averaged values for the other major population groups of

the United States.

7
Introduction

Asian/Pacific Islanders

Asian/Pacific Islanders comprise more than 60 separate racial/ethnic groups and subgroups. As was true for the

American Indian/Alaska Native population, these groups are heterogeneous and considerable variation exists

within the aggregate category described by the term “Asian/Pacific Islander” (Sue 1987). This heterogeneity

encompasses dramatic variations in drug involvement (e.g., see National Center for Health Statistics 2000; U.S.

Department of Health and Human Services 1998), not only within the continental United States, but also

across subgroups as diverse as the Chamorro people of Guam and the Commonwealth of the Northern Mariana

Islands (CNMI), native Hawaiians, the Samoans of American Samoa, and the Yapese, Chuukese, Kosraeans,

and Pohnpeians of the Federated States of Micronesia.

Several illustrations underscore the heterogeneity within the broad Asian/Pacific Islander category used in the

U.S. Census and in surveillance operations of the Federal Government. During the late 1980s and early 1990s, on

Guam and Saipan in the Mariana Island chain of western Micronesia, serious outbreaks of methamphetamine

use occurred in the form of “ice smoking,” fueled by major supply lines from the Philippines and Japan, and

coincident with early growth of Hawaii’s methamphetamine problems (Furr et al. 2000). Despite regular travel

between Hawaii, Micronesia, and Samoa, and within Micronesia, ice smoking never has posed major public

health or safety problems in the more eastern parts of Micronesia such as Pohnpei, Chuuk, and Kosrae, 

nor in American Samoa, where methamphetamine trafficking and use has been observed in no more than 

limited outbreaks. 

In addition, for decades, the chewing of betel nut for psychoactive purposes has been a common daily practice

in the CNMI, Palau, and other parts of western Micronesia. However, betel nut has become a growing public

health concern on Pohnpei and Chuuk in eastern Micronesia only within recent years and has had little salience

on the islands of American Samoa or Hawaii. Drinking of intoxicating beverages derived from Piper methysticum

(kava, sakau-en-Pohnpei) has receded from a former visible prominence in daily life for most residents of Tutuila,

the most populous island of American Samoa. Yet it still is prominent within nearby Western Samoa and to

some extent within the Manu’a island group of American Samoa and has become a public health concern on

Pohnpei (but is not common within the nearby states of Kosrae and Chuuk). Drinking of such beverages may

be increasing in the Hawaiian islands, but it is rare within the Commonwealth of the Northern Mariana Islands

and Guam (Arria and Anthony 1999).

When the statistics on different groups are aggregated into a single category, it is possible to say that during the

1990s Asian/Pacific Islanders had one of the fastest growth rates among all racial/ethnic groups identified by the

Census Bureau. In recent years, Southeast Asian refugees, Filipinos, and Koreans have been the fastest growing

Asian groups. To the extent that people of Southeast Asian, Filipino, and Korean heritage retain distinctive 

patterns of alcohol and other drug use, changes of this type will be accompanied by changes in the alcohol and

other drug use patterns of the Asian/Pacific Islander subgroup as a whole (Kim et al. 1995).

Until recently, information on drug use among Asian/Pacific Islanders generally has come to us from isolated

surveys conducted by individual researchers, although recent increases in sample size for national surveys now

provide greater coverage of drug involvement within this group. For example, based on the most recently 

published data from NHSDA 2000, it is possible to perceive important variations within the Asian/Pacific

Islander population. As stated above, slightly more than 6 percent of Americans age 12 and older are current

illegal drug users, and the corresponding value for American Indian/Alaska Natives is 12.6 percent. For

8
Introduction

Asian/Pacific Islanders, the value is 2.7 percent. Notwithstanding the overall low value for Asian/Pacific

Islanders in general, it is noteworthy that an estimated 6.9 percent of Korean Americans are current illegal drug

users, a value that is not appreciably different from the population mean or average value for all persons 

(6.3 percent). For Chinese Americans, the corresponding estimate is just 1 percent; for Asian Indian Americans,

2.1 percent; for Filipino Americans, about 3 percent; for Vietnamese Americans, 4.3 percent, and for Japanese

Americans, 5 percent (Substance Abuse and Mental Health Services Administration 2001b).

The main reason for this increased resolving power of the NHSDA findings for Asian/Pacific Islander subgroups

is a recent major increase in the survey’s sample size. For the most part, nationally representative sample surveys

with 4,000 to 5,000 respondents will have a resolving power that yields reasonably precise estimates for the most

populous Asian/Pacific Islander subgroups of the United States, such as Chinese and Vietnamese, but even

larger samples are needed to disaggregate the statistics for Korean, Japanese, and other Asian heritage subgroups

not listed specifically. In the near future, D.T. Takeuchi and colleagues will have completed a nationally representative sample survey of the larger Asian- and Hispanic-American population subgroups, which will provide

national estimates on illegal drug involvement to compare with and augment current estimates from the

NHSDA (D.T. Takeuchi, “National Latino and Asian American Study,” National Institute of Mental Health

[NIMH] grant MH62207, 2000). 

The just-described estimates from NHSDA 2000 are generally consistent with a widely held belief that illegal

drug use among Asian/Pacific Islanders occurs less frequently than for other segments of the U.S. population,

although it is noteworthy that estimates for Korean Americans and Japanese Americans are not too different

from the general population estimates. Until recently, it was thought that the underrepresentation of

Asian/Pacific Islanders among alcohol and other drug users in general population surveys might have something

to due with social stigma and a possibility that Asian/Pacific Islander American drug users are less likely to 

self-identify or pursue treatment services because such services are culturally inappropriate (Kuramoto 1994).

Indeed, when cross-national comparisons of prevalence of problem drinking and alcohol dependence have been

made, men in certain Asian countries (e.g., South Korea) have been observed to have extremely high values 

compared with men in the United States and most other countries (Anthony and Helzer 1995). Nonetheless,

especially with illegal drug use, recent epidemiological survey data indicate that prevalence of drug involvement

actually is generally lower among young Asian/Pacific Islanders than among White non-Hispanic American 

residents. This finding holds not only for NHSDA surveys but also for those of school-attending youths 

(e.g., see Bachman et al. 2001). Of course, because all results from these surveys are based on self-report data,

concerns about variation in cultural values and social stigma have not been completely ruled out. These 

variations, in part, may account for some of the observed low prevalence values for certain Asian/Pacific Islander

populations in the United States.

Within this report, it occasionally has been necessary to classify Asian/Pacific Islanders within the residual

“Other” category for individuals who do not meet the criteria for Hispanic or non-Hispanic Whites or Blacks.

This aggregate “Other” category is needed when specific estimates for Asian/Pacific Islanders are not possible

(e.g., because sample size has been too small in all but the most recent surveys of illegal drug use). For many of

the heterogeneous subgroups collected together within the “Other” category, this practice of aggregation can

change with increasing availability of larger NHSDA sample sizes, with aggregation across years of the NHSDA

surveys (e.g., see Delva et al. 1998; Obot et al. 1999; Obot and Anthony 2000), and with completion of 

studies such as the NIMH-sponsored national survey of Latinos and Asian Americans mentioned above.

9
Introduction

African Americans

As is the case with Asian and Pacific Islander populations of the United States, our national statistics tend to

convey information about African Americans in a single grouped category, despite what we know of the considerable heterogeneity within African-American communities of the United States. National statistics on illegal

drug use now generally fail to reflect this heterogeneity. It is only within smaller specialized and possibly nonrepresentative studies that we can gain a picture of variations that exist across citizens of African heritage who

have been U.S. residents for more than 200 years versus recent African-heritage immigrants from communities

as diverse as Butajira in Ethiopia, where khat use is common (Alem et al. 1999), or Sao Paulo in Brazil, where

the inhalant lanca is used by young people (Mesquita et al. 1998). There are some recent national surveys in

which the investigators have attempted to study heterogeneity in mental health and drug problems across

African-American subgroups defined in terms of Hispanic and Caribbean origins (e.g., J.S. Jackson, “National

Survey of African American Mental Health,” NIMH grant, 1999). Data from these surveys are not yet 

available for presentation in this year’s report.

Summarized in relation to an aggregate category for all members of the subgroup, non-Hispanic African

Americans comprise 12.2 percent of the total U.S. population (U.S. Bureau of the Census 2000). The nonHispanic African-American share of the total U.S. population is expected to increase to 13 percent by 2030 and

to remain stable at that level through the 21st century (U.S. Bureau of the Census 2000a).

The recent NHSDA 2000 prevalence estimates for recent illegal drug use are roughly equivalent for nonHispanic African Americans and Whites: slightly more than 6 percent of these population members qualify as

active and current illegal drug users in the month before survey assessment. By comparison, African-American

high-school seniors consistently have been found to have lower estimates than White high-school seniors for

prevalence of alcohol, tobacco, and other drug use. This finding also is true among African-American youth in

lower grades, where less dropping out has occurred.

Without contradiction of these findings, it can be said that illegal drug use and drug trafficking continue to be

major problems within African American communities of the U.S. (Johnston et al. 2001a-e; Ensminger,

Anthony and McCord 1997). Some studies have given an impression that African Americans who use alcohol

and other drugs experience higher rates of drug-related health problems than do users from other ethnic groups

(e.g., see Herd 1989). Other studies indicate that the estimated rate of transition from drug use to drug 

dependence is not generally greater for African Americans, even for those living within inner city neighborhoods

(e.g., see Anthony et al. 1994; Ensminger et al. 1997). There is some reason to believe that general impressions

about African Americans and drug problems are based on partial evidence, traced back to racial profiling and

other administrative practices that lead to overrepresentation of African Americans in criminal justice statistics

and in public drug treatment programs where admissions draw heavily on referrals from the courts (e.g., see

Blumstein and Beck 1999). Concern also has been expressed that African-American youth might be less willing

to participate in surveys and less likely to provide accurate information about their drug-using histories. 

For these reasons, it is important to note that the illegal drug-taking experiences of African Americans might be

disproportionately underrepresented in some of the data sources used in this report, including surveys such as

the MTF study. Lillie-Blanton et al. (1993) and others have expressed concern that findings from these data

sources may not accurately reflect the true nature and extent of the drug use problems in this population.

Wallace and Muroff (2002) have added important new information on the possibility of race-related conditions

10
Introduction

of risk and protection against illegal drug use, with a focus on the experience of African-American children 

and teenagers.

Hispanics

The report already has mentioned heterogeneity within the broad categories of American Indian/Alaska Natives,

Asian/Pacific Islanders, and African Americans. To be sure, the same heterogeneity characterizes the Hispanic

American segment of the U.S. population, as well as the non-Hispanic White population. For example, SokolKatz and Ulbrich (1992) observed no relationship between family structure and alcohol or drug use among 

adolescents of Cuban heritage, but found that Mexican and Puerto Rican youth had more drug involvement

when they were living in female-headed households. Freeman and colleagues (1999) recently reported differences in drug-taking patterns, AIDS knowledge, and HIV risk behaviors among recently immigrated drug users

of Cuban, Mexican, or Puerto Rican heritage. Nielsen (2000) analyzed recent NHSDA 1993 data and found

that Mexican-American men and women were somewhat more likely to have drinking problems and to drink

more heavily than their counterparts in Cuban, Puerto Rican, and Central or South American Hispanic subgroups of the population. In the most recent NHSDA 2000 estimates, Puerto Ricans were more likely to be

current illegal drug users (10.1 percent) than their counterparts in the general population age 12 years and older

(Substance Abuse and Mental Health Services Administration 2001a). Interestingly, Cuban Americans were less

likely to be illegal drug users (3.7 percent), and intermediate values were observed for Americans of Mexican

heritage (5.5 percent) and Central or South American origin (4.1 percent). Therefore, attention to diversity

within the Hispanic population is an important but often neglected feature of our national statistical summaries

on the drug experiences of racial and ethnic minority groups in the United States. It can be especially useful to

analyze the Hispanic data by country of origin, level of acculturation, and immigrant versus U.S.-born status.

However, to date, little information of this type has been reported; virtually all tables in this report present 

statistics on the aggregate Hispanic population.

As noted in the introductory paragraphs of this section, demographic projections give us special reason to pay

attention to the Hispanic segments of the U.S. population in the 21st century. Hispanics have become one 

of the fastest growing segments of the U.S. population. In 1995, Hispanics comprised 10 percent of the total

U.S. population. By 2000, that value had grown to 12 percent and it is expected to double (to 24 percent) by

2050. Population projections indicate that by 2100 Hispanics will constitute one-third of the U.S. population

(U.S. Bureau of the Census 1996, 2000a). 

It also is important to note that Hispanics comprise one of the youngest segments of the U.S. population. The

median age of Hispanics is 26.6 years, compared with 35.9 years for the U.S. population overall (U.S. Bureau

of the Census 2000b). As is true for other minority populations of the United States, this demographic fact is

important for studies of illegal drug use because the estimated risk of becoming a drug user and the estimated

risk of becoming drug dependent are at peak values between the ages of 15 and 29 (e.g., see Wagner and

Anthony 2002).

Poverty rates for Hispanics tend to be higher than rates among non-Hispanic Whites. Some 20 to 30 percent

of Hispanic families fall below the poverty level, versus under 10 percent for non-Hispanic White families

(Mayers et al. 1993; U.S. Bureau of the Census 2000c). In addition, no more than about 50 percent of 

the Hispanic population has completed 4 years or more of high school, versus more than 75 percent of 

non-Hispanics having achieved this education level. Wide socioeconomic disparities also exist among Hispanic

11
Introduction

subgroups, such as Puerto Ricans, Mexican Americans, and Cuban Americans. These disparities must be considered when interpreting data on the health status of Hispanic population members of the United States, but

they are rarely taken into account in statistical summaries.

Studies of young people indicate a tendency toward higher prevalence of several forms of drug involvement

among Hispanic adolescents than among their counterparts in the non-Hispanic African-American and White

segments of the population. Stresses associated with what often are more constrained economic conditions,

combined with lower educational attainment, a generally higher degree of drug availability, and the possible

impact of racism on self-esteem are believed to make Hispanics particularly vulnerable to alcohol and other drug

use and associated problems (Delgado 1995). Recent data on active and current illegal drug use of 12th-graders

indicate Hispanic high-school seniors have the highest prevalence estimates for use for cocaine, crack, other

cocaine, and heroin (Johnston et al. 2001a-e; Monitoring the Future 2000).

OVERVIEW OF DRUG USE AND DRUG-RELATED PROBLEMS

As indicated by the above statistics, 20th-century epidemics of drug taking in the United States have not spared

its racial/ethnic minority populations; moreover, for some subgroups evidence exists of excess risk. Concern

about illegal drug use as well as tobacco and alcohol use among members of diverse racial/ethnic groups now

accompanies a general concern about health disparities that can be readily observed within the U.S. population

(Spiegler et al. 1989; U.S. Department of Health and Human Services 1998; U.S. Department of Health and

Human Services 2000).

There can be little question that illegal drug use is linked to these observed health disparities. Alcohol, tobacco,

and illegal drug use threatens users with many negative health-related consequences—not only cancers, cardiovascular diseases and stroke, but also fatal and nonfatal overdose, hepatitis, bacterial endocarditis, HIV infection

and AIDS, and other diseases associated with high-risk behavior and sexual transmission. Drug use has been

linked to increased risk of intentional and unintentional injuries, complications in pregnancy and delivery, and

psychiatric disturbances, ranging from acute panic attacks to chronic mood disturbances. In addition, illegal

drug use is associated with negative effects on employment, school achievement, socioeconomic status, and 

family stability, if only because illegal drug use, once detected, can lead to school suspension or expulsion, 

and to arrest, conviction, and incarceration for drug-related crimes (e.g., see Blumstein and Beck 1999). It is

difficult to assess all of the complex and sometimes reciprocal linkages between illegal drug use and these 

negative health and social experiences, but there is little doubt that illegal drug use contributes to an increased

probability of arrest, conviction, and incarceration for members of racial/ethnic minority populations in the

United States and to associated health and social disparities. As such, illegal drug use is linked either directly or

indirectly to these disparities.

The linkages that connect illegal drug use with observed health and social disparities affecting racial/ethnic

minority populations of the United States generate a need for more information about the drug involvement 

of these populations and other phenomena associated with these behaviors, such as criminal offending, poor

educational achievement, and other personal and social circumstances. This report presents a selection of 

available evidence that may promote a better understanding of illegal drug use across and within racial/ethnic

minority populations of the United States. An overview of the NIDA research mission, research priorities, and

action plans for health disparities is presented in Appendices 1 and 2.

12
Introduction

METHODS

This report presents a selection of current available evidence on illegal drug use and drug-related problems

among racial/ethnic groups residing in the United States. The information was obtained from published and

unpublished data from an array of governmental and nongovernmental agencies and organizations. In each case,

the sponsoring agency or organization collected data using its own methods and procedures. Therefore, data

vary with respect to source, collection method, definitions, and reference period. Although a detailed description

and comprehensive evaluation for each data source is beyond the scope of this report, summaries of data sources

used and a general overview of their designs appear below. More complete and detailed descriptions can be

obtained from the sponsoring agencies and organizations.

Total population estimates from most of the studies contributing to this report are generally precise, with relatively

small sampling errors. Nonetheless, in some instances, estimates for specific racial/ethnic subgroups may be

based on small numbers and are relatively imprecise with associated larger sampling errors. It has not always

been possible to gauge the magnitude of these errors or their impact on the evidence presented in this report.

Where possible, the tables include footnotes that describe each sample under study and data-collection method

to help the reader evaluate the data. The reader should note that columns of numbers might not add up to their

totals because of rounding.

The data presented in the report consist primarily of prevalence proportions and corresponding summary 

statistics from national data sources. Some of the tables contain data tabulated specifically for this report, including data from NHSDA, MTF, the Youth Risk Behavior Survey (YRBS), the National Longitudinal Survey of

Youth (NLSY), the Arrestee Drug Abuse Monitoring (ADAM) program, and DAWN. Other tables present

information previously published. Standard error estimates are not presented in the tables; however, they have

been calculated for a majority of the national data sets. For those tables produced for this report, estimates with

large relative standard errors and very low precision generally have been omitted to reduce the possibility that

errors of interpretation will occur. The discussions accompanying the tables highlight only data findings and 

are not exhaustive. There is limited speculative discussion on the potential substantial and methodological 

explanations for the findings, and interpretation of programmatic or policy implications is left to the reader.

DATA SOURCES

Brief descriptions of each data source used in this report are provided below. For more detailed information on

the data sources, readers may contact the sponsoring organizations. A general comment that applies to virtually

all of these data sources involves the experience of Americans who represent linguistic minorities and whose 

preferred language is not English. In some instances, the administrators of these data sources have devised both

English and Spanish versions of their data-collection procedures and assessment instruments, but for the most

part these procedures are conducted in English. Some observers have noted that the validity of these data may

be questionable when the survey respondent or other data source speaks English not at all or only as a second,

infrequently used language.

Census of the United States

The U.S. Census Bureau has conducted censuses of the population in the United States every 10 years since

1790, with assessment of mental health and alcoholism issues starting during the interval from 1830 to 1880

13
Introduction

(Anthony and Van Etten 1998). In both the 1990 and 2000 census, data were collected on sex, race, age, and

marital status from 100 percent of the enumerated population of the country. More detailed information on

topics such as income, education, housing, occupation, and industry were collected from a representative 

sample of the total population. For example, in 1990, across most of the country, one out of six households

received a more detailed census form. In places estimated to have a population of under 2,500 residents, 

50 percent of households received the more detailed questionnaire.

For more information on the 1990 and 2000 censuses, see U.S. Bureau of the Census, 1990 Census of the

Population, General Population Characteristics, Series 1990, CP-1, and the corresponding reports on the 2000

census, or write U.S. Bureau of the Census, Population Division, Washington, DC 20233.

National Household Survey on Drug Abuse

NHSDA collects data on the use of tobacco cigarettes, smokeless tobacco, and alcoholic beverages, as well as on

marijuana, heroin, and other illegal drug use, based on survey responses from a representative sample of U.S.

residents age 12 and older, with exclusion of certain nonhousehold segments of the population (e.g., homeless

individuals). NHSDA began in 1971 under the auspices of the National Commission on Marijuana and Drug

Abuse. NIDA sponsored the survey from 1974 to September 1992. Since October 1992, the survey has been

sponsored by SAMHSA and is the responsibility of OAS, which is within SAMHSA.

Since 1991, NHSDA has covered the U.S. civilian noninstitutionalized population age 12 and older. This

includes civilians living on military bases and persons living in noninstitutionalized group quarters, such as 

college dormitories, rooming houses, and shelters. Hawaii and Alaska were included for the first time in 1991.

In 1994 and in several subsequent years, the survey methodology was changed and refined in a manner that

may have induced changes in the time series of evidence, with an intention of improving the quality of the 

evidence. With respect to some of the changes, it has been possible to construct the survey with both the old

and the new methods and generate two sets of estimates for comparison. For this reason, there sometimes are

two sets of estimates based on the 1994 data. The first set, called the 1994-A estimates, was based on the same

questionnaire and editing method as had been used in 1993. The second set, called the 1994-B estimates, was

based on a new questionnaire and editing methods. For the most part, the OAS staff has been attentive to these

changes and refinements and developed adjustment procedures to compensate for artifactual variation associated

with change in methods. A description of the adjustment method associated with the 1994 methodological

refinements can be found in NHSDA Advance Report Number 18, Appendix A, available from SAMHSA

(Substance Abuse and Mental Health Administration 1996).

In general, NHSDA over the years has employed a multistage probability sample design, with participation of

90 to 95 percent of households designated for that stage of sampling, and with participation of 70 to 80 percent

of respondents designated for sampling within households. Over the past 15 years, the NHSDA sample size has

grown from under 10,000 respondents per year before 1990 to more than 70,000 respondents per year since

2000. For example, almost 170,000 household addresses were screened in 2002 for eligibility and then sampled;

the reported response rate for screened households is 92.8 percent. A total of 71,764 designated respondents

were sampled and were interviewed within screened households, yielding a 73.9-percent individual level

response rate.

14
Introduction

For many years, young people (e.g., ages 12–17 years), African Americans, and Hispanics have been oversampled

to improve the precision of NHSDA estimates for these population subgroups. In recent years, the sampling

plan was redesigned to yield survey-based estimates for a selection of States and the District of Columbia, with

synthetic estimates for other states. Features of oversampling, multistage sampling, clustering within sampled

segments, multiple respondents within households, and survey nonresponse are taken into account via appropriate

estimation procedures for proportions, means, and their variances.

For most of its history, NHSDA has relied on a self-report answer sheet methodology to elicit information from

individual respondents. In brief, according to the standard NHSDA protocol, an interviewer on the survey field

staff followed standardized procedures to sample and recruit each designated respondent in accord with directions

approved by an Institutional Review Board for protection of human subjects. The interviewer then secured a

private location within or close by the household and completed the interview either as a face-to-face interview

or as a questionnaire assessment. In many instances, the face-to-face interview involved the interviewers reading

the standardized interview questions and the respondent marking the answers on an individualized precoded

answer sheet before filing the completed answer sheet in a sealed envelope. This procedure provided an additional level of protection because the interviewer read the questions but did not know the respondent’s answers.

In other instances, a questionnaire approach was used, with the interviewer not even reading the questions and

having no “interviewing” role per se; the respondent read the questions privately and then marked the answer

sheet and sealed the sheet in the envelope. Sometimes, due to illiteracy or vision problems, the interviewer 

conducted the interview in a standard face-to-face manner, not only reading the questions aloud and listening

for an answer, but also marking the answer on behalf of the respondent. 

Methodological experiments in the mid-1990s suggested that increased completeness and accuracy of reporting

might be gained by changing the method to that of an audio computer-assisted personal interview (ACASI).

Starting in 1999, virtually all NHSDA interviews have been completed with the ACASI method, by which the

field staff member first samples, recruits, and secures informed consent from each designated respondent.

Thereafter, the task has been to set up the laptop computer for a private ACASI assessment session, during

which the interviewer is nearby but unable to hear or see the question-answer sequence of the ACASI interview.

Of course, the respondent still has options and may request the traditional face-to-face interview (e.g., when

there are vision problems or computer illiteracy). Nevertheless, in most instances, the interviewer’s role during

the interview assessment has been suppressed and the respondent interacts solely with the computer during the

assessment interval. 

For more information on NHSDA, see any of their recent reports, which include abbreviated descriptions of

the methods, or refer to the more detailed appendix materials and methodological reports. Many of these 

materials are available on the SAMHSA Web site at www.samhsa.gov/oas. Alternately, readers may request 

hardcopy reports by writing to the Office of Applied Studies, Substance Abuse and Mental Health Services

Administration, Room 16-105, 5600 Fishers Lane, Rockville, MD 20857.

Partnership Attitude Tracking Survey

PATS originally was designed to measure the extent to which the Partnership for a Drug-Free America’s media

campaign might be successful in changing attitudes toward illegal drug use. Its current purpose is to monitor,

on an ongoing basis, the behavior and attitudes of young people and adults toward drugs. PATS is one of the

Nation’s largest surveys on attitudes toward illegal drugs and the only national level research tool for measuring

15
Introduction

the attitudes of students in grades 4–6. In the 1996 PATS studies, 12,292 interviews were conducted. Since

then, each year the PATS sample has included 2,000 to 3,000 children in grades 4–6; 6,000 to 8,000 teenagers

in grades 7–12; and 700 to 900 adults. 

PATS consists of a series of studies conducted from 1988 to the present. In the earliest installments, interview

methods were used to secure information from respondents sampled from schools or homes. In more recent

years, all of the assessments have been via self-administered anonymous questionnaires, completed with due

attention to confidentiality requirements.

When PATS samples students in schools, it does so in three parts: a national sample of approximately 100

schools, a supplemental sample of about 25 schools in heavily African-American areas, and a supplemental sample of about 25 schools in heavily Hispanic areas. The PATS in-home surveys of adults focus on a randomly

selected parent living within a sampled household, with a child or children under age 19.

For more information on PATS and its methods, visit its Web site at www.drugfreeamerica.org, email to 

webmail@drugfree.org, or write to Partnership for a Drug Free America, Suite 1601, 405 Lexington Avenue,

New York, NY 10174.

Monitoring the Future Study

This large-scale epidemiological survey of illegal student drug use was initiated in 1975 and has been conducted

annually through a NIDA grant awarded to the University of Michigan’s Institute for Social Research. The MTF

survey is based on a nationally representative probability sample of public- and private-school students in the

contiguous United States. The survey originally included only high-school seniors, but 8th- and 10th-grade

samples were added in the 1990–1991 school year to survey students who might drop out before graduating.

The measures and procedures employed have been standardized and applied consistently to the data collection

since 1975. The survey design also includes a longitudinal study of a subsample of each graduating class. This

element of the research design allows monitoring of the maturational factors associated with drug abuse. The

followup data for high-school graduates is divided into two groups: those who went to college and those who

did not go to college after graduating from high school. The adult portion of the annual report provides many

tables that allow comparisons to be made between these two groups.

This survey is ongoing. The latest data available when this report was prepared are from the 1999–2000 school

year surveys. Each year, for the national survey of 8th-graders, 150 to 160 schools are sampled, and 17,000 to

19,000 students are surveyed. For the 10th-graders, 120 to 160 high schools are sampled, and approximately

13,000 to 16,000 students are surveyed. For the 12th-graders, 130 to 140 schools are sampled and 12,000 to

15,000 students are surveyed. The data in routine MTF reports are not available on a State or sub-State level,

and the confidentiality of individual schools and students is protected. A report on the data is released 6 to 8

months after the end of a school year and initially is disseminated by NIDA press release, with subsequent

release in annual report format. The annual report includes long-term trend data. In general, MTF data on 

the 8th-, 10th-, and 12th-graders are published in one volume with an overview report and a comprehensive

main report; data on the young adults and college students are published in a second volume. Methodological

reports and book-length monographs augment the annual statistical report from the NIDA-supported MTF

research group.

16
Introduction

For more information on the MTF study, see National Survey Results on Drug Use from the Monitoring the Future

Study, 1975–2001, as well as annual reports, press releases, and occasional books, which can be located via 

www.monitoringthefuture.org or by writing to NIDA, Division of Epidemiology, Services and Prevention

Research, 6001 Executive Boulevard, Suite 525, MSC 9589, Bethesda, MD 20892.

National Longitudinal Survey of Youth

NLSY is an ongoing longitudinal study sponsored by the Bureau of Labor Statistics. Annual interviews have

been conducted with a national sample of approximately 12,000 men and women who were 14–21 years of age

in January 1979. Yearly interviews have been conducted with more than 90 percent of the original respondents

since 1979. The 1988, 1992, 1994, and 1998 surveys include information about drug use obtained in the 1984

interview along with complete pregnancy records for women, including information about prenatal care, 

alcohol and tobacco use during pregnancy, and the length and weight of each child at birth. An additional 5,500

children of the female participants have been evaluated for cognitive, socioemotional, and physiologic aspects

of their development. NIDA and the Bureau of Labor Statistics developed an interagency agreement to add sets

of questions about illegal drug use for the 1988, 1992, 1994, and 1998 rounds of NLSY. These questions assess

characteristics such as the recency and frequency of marijuana and cocaine use. Also included are questions

about the use of marijuana and cocaine during pregnancy for those who gave birth since 1987.

For more information on NLSY, visit www.bls.gov/nls or write to the Center for Human Resource Research,

Ohio State University, 921 Chatham Lane, Suite 200, Columbus, OH 43221. 

Dropout Statistics

The Department of Education’s National Center for Education Statistics (NCES) collects and reports annually

on statistics and other data related to education in the United States and other countries, including school

dropout rates. In most years, NCES dropout data have included event rates and status rates. The event rate

measures the proportion of students who drop out of school in a single year without completing high school.

The status rate measures the proportion of the population that has not completed high school and is not

enrolled at one point in time regardless of when they dropped out.

For more information on dropout statistics, see Dropout Rates in the United States 1995, National Center for

Educational Statistics 97-473, visit www.necs.ed.gov, or write to the National Center for Educational Statistics,

U.S. Department of Education, Office of Educational Research and Improvement, 555 New Jersey Avenue,

NW, Washington, DC 20208.

American Indian/Alaska Native Statistics

There is no single comprehensive Federal effort to collect data on drug use within the American Indian/Alaska

Native populations of the United States. Consequently, data on American Indian/Alaska Native populations

were obtained for this report from publications by Beauvais and colleagues (1985a-b, 1989; see also Beauvais

2001) and from recent data issued by the MTF study and NHSDA. Beauvais’ research team has collected data

on drug use rates among American Indian youth since 1975. In addition to monitoring levels of use, they have

conducted studies examining the etiology of drug and alcohol use in this population (e.g., see Beauvais et al.

1989). The data for this project are gathered through anonymous self-report surveys administered in school

classes. The survey includes questions about lifetime history of using 11 drugs. Currently active use, depth of

17
Introduction

involvement, and patterns of use are assessed for the more frequently used drugs. Other topic areas involve 

correlates of drug use, including variables such as demographics, attitudes toward drugs, peer and family 

influence, general deviance, cultural identification, school adjustment, personal adjustment, and attitudes

toward the future. 

Due to the difficulty involved in obtaining permission to conduct the survey on individual reservations,

researchers are not able to guarantee that the sample is nationally representative of the total American

Indian/Alaska Native population. To compensate for this problem, 2 years of data often are combined to 

borrow information across the survey years and to increase the representativeness and precision of the sample.

The project team is confident that this procedure of borrowing information across survey years promotes 

consistency of the drug use rates across tribes and over time.

For more information on Native American data, visit www.colostate.edu/depts/TEC or write to the Tri-Ethnic

Center for Prevention Research, C-78 Clark Building, Psychology Department, Colorado State University, Fort

Collins, CO 80523.

Youth Risk Behavior Survey

YRBS is a component of the Youth Risk Behavior Surveillance System (YRBSS), maintained by CDC. YRBSS

comprises three complementary components: (1) national school-based surveys, (2) State and local school-based

surveys, and (3) a national household-based survey. Each of these components has provided useful information

about various subpopulations of adolescents in the United States.

The school-based survey first was conducted in 1990, and the household-based survey was initiated in 1992.

The school-based survey is conducted biennially in odd-numbered years among national probability samples of

students in grades 9–12 from public and private schools. Schools with a large proportion of Black and Hispanic

students are oversampled to provide stable estimates for these subgroups. For this report, the most recently 

available data are from the 1999 YRBS.

For more information on YRBSS, write to Centers for Disease Control and Prevention, 4770 Buford Highway,

NE, Atlanta, GA, or visit www.cdc.gov/nccdphp/dash/yrbs and the CDC Web site.

Drug Abuse Warning Network

Starting with a pilot study and then expanding to more participating sites, DAWN was originated as a surveillance system by DEA, which operated the network from 1973 through 1979. Thereafter, NIDA assumed

responsibility for DAWN operations from 1980 through 1991. Since 1992, SAMHSA has operated DAWN,

which now functions as a surveillance system for drug-related events in hospital emergency room (ER) and 

medical examiner facilities. DAWN collects information on the occurrence of drug-related casualties that have

resulted in a medical crisis or death. Since its inception, DAWN’s major objectives have included monitoring

illegal drug use patterns and trends (especially newly emerging patterns), identifying specific drugs associated

with adverse drug-related events, and assessing drug-related consequences and other health hazards of 

illegal drug use.

18
Introduction

Hospital ERs eligible for DAWN participation are in non-Federal, short-stay general hospitals and must be open

24 hours a day. Since 1988, the DAWN ER data have been collected from a representative sample of these 

hospitals, including 21 oversampled metropolitan area hospitals. Data from this sample are used to generate

national estimates of the total number of ER drug use episodes and drug mentions in all such hospitals.

Within each participating facility, a designated DAWN reporter is responsible for identifying drug abuse

episodes by reviewing official records, transcribing, and submitting data on each case. Data collected by DAWN

include the drug(s) involved in the ER episode; sex, age, and race/ethnicity of patients; reasons for the ER visit;

single or multiple drug use; and the route of administration.

For more information on DAWN, see Drug Abuse Warning Network Annual Medical Examiner Data: 1999

or write to the Office of Applied Studies, Substance Abuse and Mental Health Services Administration, 

Room 16C-06, 5600 Fishers Lane, Rockville, MD 20857. Information is also available at

www.samhsa.gov/oas/dawn.htm.

AIDS Surveillance Data

CDC maintains AIDS surveillance data by using information collected by health departments in each state, 

territory, and the District of Columbia. Although surveillance activities range from passive to active, most areas

employ multifaceted active surveillance programs, which include the following four major reporting sources 

of AIDS information: (1) hospitals and hospital-based physicians, (2) physicians in nonhospital practice, 

(3) public and private clinics, (4) and medical record systems (e.g., death certificates, tumor registries, hospital

discharge abstracts, and communicable disease reports). Using a standard confidential case report form, the

health departments collect information without personal identifiers; this information then is coded and 

computerized either at CDC or at health departments, which transmit the information electronically to CDC.

AIDS surveillance data are used to detect epidemiologic trends to identify unusual cases requiring followup and

for quarterly publication in CDC’s HIV/AIDS Surveillance Report. Studies to determine the completeness of

reporting of AIDS cases that meet the national surveillance definition suggest reporting at greater than or equal

to 90 percent. The number of deaths among AIDS cases reported to CDC’s AIDS Surveillance System differs

from the number of HIV infection deaths based on the National Vital Statistics System. The major reasons for

these differences are (1) not all persons diagnosed with AIDS are reported to the AIDS Surveillance System, 

(2) not all deaths of persons with AIDS are due to AIDS, and (3) not all deaths due to HIV infection are

reported as such on the death certificate.

For more information on AIDS surveillance, write to CDC National AIDS Clearinghouse, P.O. Box 6003,

Rockville, MD 20849-6003 or to Chief, Surveillance Branch, Division of HIV/AIDS, National Center for HIV,

AIDS, STD, and TB, Centers for Disease Control and Prevention, Atlanta, GA 30333. Information is also

available at www.cdc.gov/hiv/dhap.htm.

Arrestee Drug Abuse Monitoring Program

As a refinement of a surveillance system formerly known as the Drug Use Forecasting program, ADAM measures

recent drug use among booked arrestees at multiple sites in major metropolitan areas across the United States.

Originally, there were 20 to 25 ADAM sites within the United States; today, 35 cities are represented in the

19
Introduction

ADAM domestic surveillance network and there are participating international sites as well. Pending availability

of funds through NIJ, plans are in place to expand ADAM to more than 70 sites.

ADAM’s primary purpose has been to monitor illegal drug use among booked arrestees in major U.S. cities. It

provides information about the effectiveness of local drug policies and practices and offers a solid basis for

resource allocation decisions. By collecting urine samples and interviewing arrestees on a quarterly basis, ADAM

has become a consistent tool for tracking drug use trends among this difficult-to-study population of users.

Arrestee participation is voluntary and anonymous. The ADAM sampling strategy is site specific, and participants are not necessarily statistically representative of all arrestees. All female arrestees are eligible to be included

in the ADAM sample. However, the large numbers of male arrestees require that a selection be made. Males

arrested for vagrancy, loitering, and traffic violations may be excluded and generally have been. Other arrestees

are chosen by type of charge using the following priority: (1) nondrug felony charges, (2) nondrug misdemeanor

charges, (3) drug felony charges, and (4) warrants for any charge. To prevent oversampling arrestees with a high

propensity for drug use, only 20 percent of males arrested and charged with drug offenses are interviewed. In

consequence, it is likely that ADAM data underestimate the proportion of arrestees who have used drugs less

recently, because urinalysis reveals the presence of most drugs only within 48 to 72 hours of their use.

On average, 80 to 90 percent of designated arrestees have agreed to participate in the ADAM assessments, with

80 percent providing a urine sample. The total sample of booked arrestees in the ADAM program from 1987

through 1999 included 337,450 adults, of which 247,655 were males and 89,795 were females. In some sites,

there is a supplementary ADAM program for juvenile arrestees.

The ADAM sample should not be regarded as a random sample of booked arrestees; it was determined early in

the ADAM program’s development that selecting random samples would not be feasible in the environment in

which the program would have to operate. In most sites, 225 males are now interviewed each quarter. For female

arrestees, the goal is to interview at least 100.

For more information on the ADAM program, write to the U.S. Department of Justice, National Institute of

Justice, 633 Indiana Avenue, N.W., Washington, DC 20531. Information also is available at www.adam-nij.net.

ORGANIZATION OF THIS REPORT

The remaining chapters of this report present detailed data on drug use among U.S. racial/ethnic groups, based

on the above data sources and ancillary studies. Chapter 2 presents basic population statistics from the Census

Bureau and projections for racial/ethnic minorities in the United States. This information is useful for determining the relative size of the major racial/ethnic populations within the United States and for comparing

demographic factors such as family income.

Chapter 3 provides an overview of drug use patterns for the total U.S. population and for the four racial population groups and two ethnic categories defined in the first sections of this chapter. Data for Chapter 3 were

obtained from NHSDA, which has become the most comprehensive source of population-level illegal drug use

prevalence data available in the United States. Chapter 3 also includes estimates for (1) prevalence proportions

based on recently active illegal drug use in the United States (i.e., illegal drug use in the month before the 

survey assessment) and (2) the cumulative occurrence of illegal drug use. Estimates of cumulative occurrence are

20
Introduction

derived by estimating the cumulative number of illegal drug users who report either a recent or a past history

of illegal drug use, where cumulative number is the total number of individuals whose lifetime history includes

at least one occasion of illegal drug use.

One useful way to think about cumulative occurrence of illegal drug use starts by conceptualizing the prevalence

proportion for recently active or current illegal drug use (i.e., use in the month before the survey assessment).

This prevalence proportion often is called “1-month prevalence” or “past-month prevalence” of illegal drug use

because it is an index of the fraction of the population who have used illegal drugs at least one time in the month

before assessment. We then can extend the time frame to encompass the year before the survey assessment,

deriving a “1-year prevalence” or “past-year prevalence” of illegal drug use. Notice that these time intervals are

fixed at 1 month and 1 year. For “1-month prevalence” the interval stretches back 1 month before the date of

assessment. For “1-year prevalence” the interval stretches back to 1 year before the date of assessment.

Extending this concept, we can think about a time interval that stretches back to the birth of the respondent,

but here we no longer have a fixed span of time (i.e., 1 month, or 1 year). Instead, we have the number of 

years that have spanned the gap from an individual’s birth to the time of assessment. This is the nature of the

“cumulative occurrence” estimate. It covers the time span from the individual’s birth to the date of the survey

assessment. Individuals who report having used drugs illegally are counted in the numerator of a ratio for the

cumulative occurrence of illegal drug use; all individuals are counted in the denominator of the ratio. Because

the span for assessment covers the complete interval from birth to the time of assessment, the “cumulative 

occurrence” estimate sometimes is called the “lifetime prevalence” estimate.

One of the complications of all of these estimates is that they do not reflect the experience of illegal drug users

who have died as a result of their illegal drug use, in association with their illegal drug use, or unconnected to

their illegal drug use. All of these estimates from cross-sectional survey data are based on individuals who have

survived to the date of assessment. These estimates must be interpreted with this limitation in mind, no matter

how they are constructed and what they are called.

In some instances, corresponding estimates are presented for tobacco and alcoholic beverages for comparative

purposes. When appropriate, estimates are presented for a prevalence proportion that is based on the number

of individuals who have engaged in illegal drug use during the year before assessment (sometimes called 

“past-year prevalence”). Proportions of this type may be interpreted as a fraction (or percentage) of the total

study population under study, or as a fraction (or percentage) of a specific population subgroup of interest 

(e.g., African Americans age 12 and older). Throughout this report, the concept of illegal drug use encompasses

the use of Schedule I drugs such as marijuana and heroin, regarded by the Federal Government as having no

acceptable medical use in the United States, plus Schedule II drugs such as cocaine, regarded as having acceptable medical uses but with essentially similar levels of risk to public health or safety, as well as other controlled

drugs such as barbiturates and the amphetamines. The latter have been thought to pose somewhat lower levels

of risk to public health or safety as compared to heroin or cocaine. 

Illegal drug use also encompasses extramedical use of prescribed drugs, such as methylphenidate (Ritalin®),

when consumed for recreational purposes or for nonmedical or extramedical reasons that go beyond the boundaries of medically prescribed use (e.g., for suicide attempts), as well as the use of inhalant drugs such as glue or

ether when the intent is to get high or for other related extramedical purposes. Anthony and colleagues (1994) 

provide a detailed description of the concept of “extramedical drug use” as a complement to the concept of 

21
Introduction

“illegal drug use,” with attention to the recreational use of inhalants and other chemicals that do not necessarily

represent illegal uses of the chemicals but that may pose risks for public health and safety. The notion of

“extramedical” drug use is needed because sometimes a patient has taken a medicine that a doctor has prescribed

and become dependent by taking more than the doctor had intended (e.g., to secure effective pain relief).

Strictly speaking, this patient behavior fails to qualify as “nonmedical drug use” because the patient is administering the drug for reasons that the doctor intended. However, it is “extramedical” use in the sense that the

patient has exceeded the prescribed dosage regimen in an misguided attempt to secure effective pain relief when

the prescribed dosage level is not working as it should (Anthony et al. 1994). The term “nonmedical” might

imply that this patient sought an effect such as “getting high,” which would be beyond the boundaries of the

prescribed indication, whereas the term “extramedical” simply implies that the patient might be administering

the medicine to secure a medically legitimate result or indication (i.e., effective pain relief), even if the patient

ends up taking more than the doctor prescribed to achieve this result. That is, the notion of “nonmedical drug

use” groups patients who are seeking the pain relief intended by a doctor with those who use the prescribed

medicines to get high. The notion of “extramedical use” provides an additional element of elaboration and

encompasses the patient who might be taking more than was prescribed—not to get high, but to achieve the

physician’s desired result of effective pain relief.

Chapter 4 of this report examines illegal drug use, attitudes about drugs, and drug-related behaviors among

minority youth; it also includes data on the overall prevalence of drug use among youth. These data originate

from several sources including the Census Bureau, MTF study, NLSY, NHSDA, and PATS.

Chapter 5 presents data on risk behaviors such as dropping out of school, driving under the influence of alcohol

or drugs, and engaging in high-risk sexual behaviors. Data sources for this chapter were the Department of

Education, NHSDA, and YRBS.

Chapter 6 examines the adverse health consequences of drug use. Data sources for this chapter were DAWN

and CDC’s AIDS Surveillance System. This chapter presents prevalence estimates on drug-related medical

emergencies, drug-related deaths, and information on the medical consequences of drug use.

Chapter 7 addresses drug use and crime. Data on the drug use history of booked arrestees and the percent of

arrestees who committed their offense under the influence of drugs are presented in this chapter. Data were

obtained from the ADAM program.

Chapter 8 summarizes this report and presents future programmatic and research needs pertinent to illegal drug

use and associated problems. A discussion of limitations to the understanding of illegal drug use of minority

populations is offered, along with a summary of issues that merit consideration when conducting research and

interpreting results on illegal and extramedical drug use of racial/ethnic minority populations.

22
23

This chapter presents census data on the general population residing in the United States and projections for

the population growth rate of racial/ethnic minorities. Also presented in this chapter are data on the percentage

of the population living below the poverty threshold. The distribution of racial/ethnic groups in the United

States is changing. As noted in Chapter 1, rigorously derived population projections show that major demographic changes will continue through the 21st century (U.S. Bureau of the Census 2000a). The non-Hispanic

White share of the population is projected to decline steadily, as Asian/Pacific Islander and Hispanic populations

increase in number and proportional representation; the non-Hispanic African-American share will remain 

relatively stable over this period. Coincident with general growth in the size of the U.S. population, it is estimated

that the African-American population will roughly double—from about 30 million in 2000 to 60 to 70 million

in 2080. By comparison, the Hispanic population will more than triple—growing from about 30 million in

2000 to almost 100 million in 2050; the Asian/Pacific Islander population will also more than triple—increasing

from about 10 to 11 million in 2000 to more than 30 million in 2050 (U.S. Bureau of the Census 2000a).

Racial and ethnic minority groups in the United States do not share identical circumstances of daily life and 

residential location. Residential location is of special importance in studies of the nature and extent of illegal

drug use because sometimes considerable urban-rural differences exist in the distribution and dynamics of drug

involvement within the United States, as well as variations in drugs of choice (e.g., see James et al 2002;

Johnston et al. 1993). Some drugs, such as sustained-release oxycodone (OxyContin®) have become major

problems in rural areas, whereas most metropolitan areas have been less affected by this drug (National Institute

on Drug Abuse 2001a). In addition, within U.S. cities, there sometimes are extreme versions of social and 

cultural conditions and processes conducive to drug trafficking, availability of drugs, and drug taking, such as

limited opportunities for lucrative employment in otherwise impoverished neighborhoods (e.g., see Levitt and

Venkatesh 2000), neighborhood disadvantage, disorganization, and constraints on collective efficacy and social

capital (Newcomb 1995; Sampson et al. 1997).

Of course, drug distribution and drug use have not been limited to urban areas; rural areas have been affected

as well. For example, prevalence of tobacco smoking is greatest in rural America (Substance Abuse and Mental

Health Services Administration 1999b, 2000c-d, 2001b). Marijuana cultivation became commonplace in rural

America, starting before 1950 with legal wartime cultivation of hemp for rope. Marijuana’s position as an illegal

rural cash crop increased in the last quarter of the 20th century, and it now is grown and distributed widely in

rural areas throughout most of the continental United States and Hawaii (Joy et al. 1999). In theory, cocaine

also can be grown in some of the more mountainous parts of the United States. However, climate, altitude, and

other circumstances have constrained domestic cultivation of cocaine (Montagne 1991). Hence, cocaine supply,

distribution, and use have become more prominent among the social problems facing urban rather than rural

residents of the United States.

Census Bureau data indicate that minorities were overrepresented in central cities and metropolitan areas. For

example, about one-half of the U.S. population lives in large standard metropolitan statistical areas with a 

population of 1 million people or more. Non-Hispanic Whites now account for about 70 percent of the total

U.S. population (71.4 percent), but only one-fifth (21.7 percent) of Whites live in central cities. In contrast,

African Americans account for about 12 percent of the total U.S. population, more than one-half (55 percent)

of whom live in central cities (McKinnon and Humes 2000).

Chapter 2. POPULATION STATISTICS FOR RACIAL/ETHNIC

MINORITIES IN THE UNITED STATES
Population Statistics for Racial/Ethnic Minorities in The United States

POPULATION STATISTICS

Based on estimates from the Census Bureau (1990), Table 1 presents percentage distributions for the resident

population of the United States by race/ethnicity for 1990 and projections for selected years from 2000 to 2100.

These data indicate that the Asian/Pacific Islander segment of the U.S. population will experience the greatest

proportional change between 2000 and 2100, followed by persons of Hispanic origin. If these projections hold,

non-Hispanic Whites will no longer be a majority population within the United States sometime between 2050

and 2060.

Table 2 displays 1993, 1995, 1997, 1999, and 2000 weighted average poverty thresholds estimated from the

1980 and 1990 censuses, by size of family unit. Families or individuals with incomes below their appropriate

thresholds are classified as below the poverty level. These thresholds are updated annually to reflect changes in

the Consumer Price Index for all suburban consumers. The table shows that in 2000, the average poverty

threshold for a family of four was $17,601, an increase of about 19 percent from 1993 (U.S. Bureau of the

Census 2001b, 2000c).

Table 3 presents the 2000 income thresholds below which people are classified as living in poverty, by family

size and number of related children under age 18. In 2000, the poverty threshold for a single person under age

65 was $8,958 per year, and the poverty threshold for a family of four with two children under age 18 was

$17,463 per year.

Table 4 presents the percentage and number of people in the United States living below poverty level by

racial/ethnic group, as shown in Census Bureau data from 1990 through 2000. The proportion of individuals

classified below the poverty level decreased over this period, from 13.5 percent in 1990 to 11.3 percent in 2000,

reflecting a period of economic expansion that ended in 2000–2001. A comparison of poverty level by race/

ethnicity indicates that less than 25 percent of African Americans were living in poverty in 2000, compared with

relatively stable values of 30 percent to 33 percent between 1973 and 1993. The proportion of Hispanic people

living in poverty was relatively stable between 1980 and 1998, with values between 25 percent and 31 percent,

but declined to 21.2 percent in 2000. Whites have the lowest proportion of people living in poverty. This 

proportion increased from 8.4 percent in 1973 to 12.2 percent in 1993, but declined to 9.4 percent by 2000

(U.S. Bureau of the Census 2000c).

Table 4 also presents the proportions of female-headed families with children under age 18 who are living in

poverty. In 2000, just under one-half of African-American and Hispanic households with children under age

18 and no husband present lived below the poverty level (the figure for both groups is 41.1 percent).

Furthermore, African-American and Hispanic children under age 18 were two to three times more likely than

White children to live below the poverty level in 2000 (30.7 percent and 27.3 percent, respectively, compared

with 12.4 percent for Whites).

24
Population Statistics for Racial/Ethnic Minorities in The United States

SUMMARY

Census Bureau data draw attention to important demographic, social, and economic features of our Nation’s

population. Racial/ethnic minorities tend to be overrepresented within the central cities of the United States,

where certain drugs (such as cocaine) pose more challenges for public health and safety. Demographic projections indicate that the distribution of racial/ethnic minorities in the U.S. population is changing significantly.

Recent and projected growth of the Asian/Pacific Islander and the non-Hispanic White segments of the U.S.

population deserve special note.

On average, racial/ethnic minorities tend to be at greater economic disadvantage than are non-Hispanic Whites.

About 10 percent of Whites were living in poverty in 2000, whereas the corresponding value is about 25 percent for both non-Hispanic African-American and Hispanic people. In addition, almost one-half of nonHispanic African-American and Hispanic households with children under age 18 and no husband present lived

below the poverty level; non-Hispanic African-American and Hispanic children under age 18 were some two to

three times more likely than non-Hispanic White children to live below the poverty level.

25
Population Statistics for Racial/Ethnic Minorities in The United States

26

Table 1. Estimated Percentage Distribution of U.S. Population, 

by Race/Ethnicity and Hispanic Origin: 1990–2100a

Non-Hispanic

Year Total Population African- Asian American/ American 

(thousands) American Pacific Islander Indianb White Hispanic

1990 249,402 11.8 2.8 0.7 75.6 9.0

2000 275,306 12.2 3.9 0.7 71.4 11.8

2005 287,715 12.3 4.3 0.8 69.3 13.3

2010 299,861 12.5 4.8 0.8 67.3 14.6

2015 312,268 12.7 5.3 0.8 65.5 15.8

2020 324,926 12.8 5.7 0.8 63.8 17.0

2030 351,070 13.0 6.7 0.8 60.1 19.4

2040 377,349 13.1 7.8 0.8 56.3 21.9

2050 403,686 13.2 8.9 0.8 52.8 24.3

2060 432,010 13.3 9.8 0.8 49.6 26.6

2070 463,639 13.2 10.6 0.8 46.8 28.6

2080 497,829 13.1 11.3 0.8 44.4 30.4

2090 533,605 13.1 12.0 0.8 42.2 32.0

2100 570,954 13.0 12.6 0.7 40.3 33.3

a

All population figures for 2000 and after are based on the 1990 census.

b

Includes Eskimos and Aleuts.

SOURCE: Population Projections Program, Population Division, U.S. Bureau of the Census, 2002a.

Table 2. Weighted Average Poverty Thresholds, by Size of Family: Selected Years

Weighted Average Poverty Thresholds (in dollars)

Family Size 1993 1995 1997 1999 2000

One person 7,363 7,763 8,178 8,500 8,787

Under 65 years 7,518 7,710 8,350 8,667 8,958

65 years and over 6,930 7,108 7,698 7,991 8,259

Two persons 9,414 9,661 10,468 10,869 11,234

Householder under 65 years 9,728 9,976 10,806 11,214 11,591

Householder 65 years and over 8,740 8,976 9,709 10,080 10,414

Three persons 11,522 11,821 12,803 13,290 13,737

Four persons 14,763 15,141 16,404 17,028 17,601

Five persons 17,449 17,900 19,387 20,115 20,804

Six persons 19,718 20,235 21,880 22,719 23,491

Seven persons 22,383 22,923 24,825 25,815 26,783

Eight persons 24,836 25,427 27,713 28,788 29,941

Nine persons or more 29,529 30,300 32,705 34,075 35,574

SOURCE: U.S. Bureau of the Census, 2001b, 2002c.
Population Statistics for Racial/Ethnic Minorities in The United States

27

Table 3. Poverty Thresholds, by Size of Family and Number of Related Children 

Under 18 Years of Age (in dollars): 2000

Related Children Under 18 Years

Weighted 

Average Eight

Poverty or 

Size of Family Thresholds None One Two Three Four Five Six Seven More

One person (unrelatedindividual)Under 65 years 8,958 8,95865 years and over 8,259 8,259Two personsHouseholder under 65 years 11,531 11,531 11,869Householder 65 years and over 10,414 10,409 11,824Three persons 13,737 13,470 13,861 13,874Four persons 17,601 17,761 18,052 17,463 17,524Five persons 20,804 21,419 21,731 21,065 20,550 20,236Six persons 23,491 24,636 24,734 24,224 23,736 23,009 22,579Seven persons 26,783 28,347 28,524 27,914 27,489 26,696 25,772 24,758Eight persons 29,941 31,704 31,984 31,408 30,904 30,188 29,279 28,334 28,093Nine persons or more 35,574 38,138 38,322 37,813 37,385 36,682 35,716 34,841 34,625 33,291

SOURCE: U.S. Bureau of the Census, 2001d.
Population Statistics for Racial/Ethnic Minorities in The United States

28

Table 4. Person and Families Living Below Poverty Level, According to Selected

Characteristics, Race, and Hispanic Origin: 1990–2000

NOTES: The Black and White race groups include persons of both Hispanic and non-Hispanic origin. Conversely, persons of Hispanic 

origin may be of any race.

SOURCE: U.S. Bureau of the Census, 2000c.

Selected Characteristics 

and Race/Ethnicity 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

Percent Below Poverty

All races 13.5 14.2 14.5 15.1 14.5 13.8 13.7 13.3 12.7 11.8 11.3

White 10.7 11.3 11.6 12.2 11.7 11.2 11.2 11.0 10.5 9.8 9.4

Black 31.9 32.7 33.3 33.1 30.6 29.3 28.4 26.5 26.1 23.6 22.1

Hispanic 28.1 28.7 29.3 30.6 30.7 30.3 29.4 27.1 25.6 22.8 21.2

Related children under 18 years of age in families

All races 19.9 21.1 21.1 22.0 21.2 20.2 19.8 19.2 18.3 16.3 15.7

White 15.1 16.1 16.0 17.0 16.3 15.5 15.5 15.4 14.4 12.9 12.4

Black 44.2 45.6 46.3 45.9 43.3 41.5 39.5 36.8 36.4 32.7 30.7

Hispanic 37.7 39.8 38.8 39.9 41.1 39.3 39.9 36.4 33.6 29.9 27.3

Families with female householder, no husband present, and children under 18 years of age

All races 44.5 47.1 45.7 46.1 44.0 41.5 41.9 41.0 38.7 35.7 32.5

White 37.9 39.6 39.1 39.6 38.3 35.6 36.9 37.6 33.8 30.1 27.5

Black 56.1 60.5 57.2 57.7 53.9 53.2 51.0 46.9 47.5 46.1 41.1

Hispanic 58.2 60.1 57.4 60.5 59.2 59.3 59.7 54.2 52.2 46.6 41.4

Number Below Poverty (in thousands)

All races 33,585 35,708 36,880 39,265 38,059 36,425 36,529 35,574 34,476 32,258 31,139

White 22,326 23,747 24,523 26,226 25,379 24,423 24,650 24,396 23,454 21,922 21,291

Black 9,837 10,242 10,613 10,877 10,196 9,872 9,694 9,116 9,091 8,360 7,901

Hispanic 6,006 6,339 6,655 8,126 8,416 8,574 8,697 8,308 8,070 7,439 7,155

Related children under 18 years of age in families

All races 12,715 13,658 13,876 14,961 14,610 13,999 13,764 13,422 12,845 11,510 11,086

White 7,696 8,316 8,333 9,123 8,826 8,474 8,488 8,441 7,935 7,123 6.873

Black 4,412 4,637 4,850 5,030 4,787 4,644 4,411 4,116 4,073 3,644 3,454

Hispanic 2,750 2,977 2,946 3,666 3,966 3,938 4,090 3,865 3,670 3,382 3,173

Families with female householder, no husband present, and children under 18 years of age

All races 3,426 3,767 3,761 4,034 3,816 3,634 3,755 3,614 3,456 3,116 2,767

White 1,814 1,969 1,980 2,123 2,064 1,980 2,032 2,069 1,926 1,656 1,475

Black 1,513 1,676 1,659 1,780 1,591 1,533 1,593 1,436 1,397 1,333 1,164

Hispanic 536 584 543 706 700 735 760 701 707 630 541
29

This chapter provides an overview of drug use patterns for the U.S. population. The overview mainly draws on

data from the Substance Abuse and Mental Health Administration’s (SAMHSA) National Household Survey

on Drug Abuse (NHSDA), which has become the premier source of epidemiological evidence on recent drug

use in the United States. Each year, using methods that help promote accuracy of reporting and confidentiality

of the results, NHSDA staff draws large population samples and solicits participation of respondents sampled

for the survey from among all civilian noninstitutionalized residents age 12 and older. These designated respondents, selected to yield a national representative sample, are asked to answer standardized questions about their

use of alcohol, tobacco, and other drugs. The chapter also presents data on attitudes and perceptions toward

drug use as surveyed by the Partnership for a Drug-Free America’s Partnership Attitude Tracking Survey (PATS),

as well as vital statistics abstracted from birth certificates in selected states. 

For the most part, survey-based estimates presented in this chapter are for “prevalence” proportions that describe

the nature and extent of illegal drug, alcohol, and tobacco use in the United States. One set of estimates is used

to describe the cumulative occurrence or “lifetime prevalence” of illegal drug use in the population. These estimates

answer the question, “Within the current population or population group being surveyed, what proportion has

either a past history of illegal drug use or recently active illegal drug use?” 

In contrast, estimates for “1-month prevalence” pertain to the most recent 1-month interval up to and including

the date of survey assessment of each individual survey participant. The estimates for “1-month prevalence”

answer questions of the following form: “Within the current population or population group being surveyed,

what proportion has a recent history of illegal drug use?” and “What proportion of the survey population is a

‘current’ illegal drug user?” Estimates for “1-year prevalence” shift the focus of this question to the 1-year interval

up to and including the date of survey assessment.

In this report’s estimates, the use of glue, gases, and inhalant drugs to get high generally has been combined with

extramedical or illegal use of internationally and federally controlled drugs. Foremost among the internationally

and federally controlled drugs are marijuana and hashish, heroin, LSD, and certain other hallucinogenic drugs,

all of which have been assigned to high-level Schedule I controls designated for drugs that have no federally 

recognized safe use in the practice of medicine; their only legal use is in research approved by national 

governmental authorities.

Other schedules of the international and Federal regulations encompass a broad array of prescription and overthe-counter (nonprescription) medicines with clearly legitimate medical uses. This group includes cocaine and

other anesthetics; morphine, codeine, oxycodone, and other pain-relieving and cough-suppressing medicines;

barbiturates and other sleep-promoting or calmative preparations; tranquilizers and other anxiety-relieving 

medicines or muscle relaxants; and methylphenidate and other psychostimulant medicines used to treat attention deficit disorder with hyperactivity and narcolepsy, or administered as diet aids. Any use of marijuana, LSD,

or heroin qualifies as illegal under U.S. law, but cocaine, tranquilizers, sleeping pills, pain relievers, and many

psychostimulants have legal medicinal uses.

In most epidemiological studies, the use of these internationally and federally regulated medicines is considered

illegal or extramedical when the user intends to get high or to commit suicide, when the motive for intoxication

Chapter 3. DRUG USE IN THE GENERAL POPULATION
Drug Use in the General Population

leads to taking more than the doctor prescribed, and when the medicine is used for intoxicating or withdrawalrelieving effects that are beyond the boundaries of the medical prescription. These forms of extramedical drug

use, beyond the boundaries of the medical prescription, generally are grouped with nonresearch use of Schedule

I drugs in a category called “illegal drug use” even if the drug user ordinarily would not be prosecuted (e.g., in

an incident of unsuccessful suicide attempt by overdose). 

Epidemiological information is crucial to our understanding of the nature and scope of alcohol, tobacco, and

illegal drug use. Information on illegal drug use generally is derived from population surveys because the use of

alcohol, tobacco, and other drugs cannot be probed deeply in the traditional sources of epidemiological data on

morbidity and mortality, such as hospital or clinic records, death certificates, and national registries. A large

majority of illegal drug users seek care from primary care health providers in any given year. Nonetheless, health

professionals largely do not talk with the patient about illegal drug use, with such use remaining undetected or

unmentioned and thus never becoming part of official medical records available for epidemiological scrutiny

(e.g., see Anthony and Helzer 1991, 1995; Anthony 2000).

Necessarily, reliance on survey-based estimates provokes legitimate concern about the sources of error in the 

survey data, just as epidemiologists tend to be concerned about sources of error in medical records and vital 

statistics. One source of error can be understood in relation to the difficulty of surveying potentially important

population subgroups, such as homeless individuals and incarcerated prisoners. Numerically, these subgroups

represent small fractions of the total U.S. population. However, research on these subgroups tends to disclose

large values for cumulative occurrence and prevalence of alcohol and tobacco use, as well as illegal drug taking

(e.g., see Anthony and Helzer 1991).

One way to constrain this source of error is to respecify the population of interest. For example, the NHSDA

population generally is described as a national survey of the U.S. “civilian, non-institutionalized population age

12 and older,” which excludes subgroups like incarcerated prisoners. This distinction between the total U.S.

population and the specified NHSDA population is important to recall in interpreting NHSDA statistics.

Figure 1 from the NHSDA 2000 provides evidence that this distinction may be important.

Although the NHSDA population has been defined to exclude incarcerated prisoners and other institutionalized

citizens, the adult survey respondents include recently released prisoners who are parolees or on probation or

supervised release at the time of assessment. As shown in Figure 1, recently incarcerated individuals now on

supervised release, parole, or probation are more likely to be recent illegal drug users (Substance Abuse and

Mental Health Administration 2001b). Once the analysis takes into account male-female and age differences

between these recently incarcerated individuals and the rest of the corresponding civilian noninstitutionalized

population, the recent prisoners are two to three times more likely to have been recent illegal or extramedical

drug users (i.e., use in the month prior to survey).

Epidemiological surveillance operations based on sample surveys face another potential source of error, which

is displayed in confidence intervals that can be constructed for each survey estimate. These confidence intervals

serve to index the precision of each estimate; when properly calculated, the intervals provide general boundary

conditions for each prevalence estimate from the surveys. Any single prevalence number from a survey sample

is not quite accurate, if only because of random fluctuations when a sample of several thousand individuals is

used to represent characteristics of millions of individuals in the total population. However, we can have more

certainty about the accuracy of the confidence intervals, in that each interval encompasses a range of estimates.

30
Drug Use in the General Population

In general, all else being equal and up to a point, the width of the confidence interval becomes smaller with

increases in effective sample size, and the interval allows us to make a roughly accurate assessment of the magnitude of alcohol, tobacco, and illegal drug use in the population being surveyed at the same time, even when

we cannot be entirely confident about the accuracy of the reported prevalence number. To illustrate, in the

NHSDA 1999 report, we learn that an estimated 10.2 percent of those ages 20–25 in the U.S. civilian noninstitutionalized population never have tried alcohol, tobacco cigarettes, or marijuana (i.e., about 90 percent had

used one or more of these drugs). The value of 10.2 percent is the best NHSDA estimate, and it demonstrates

that use of these drugs is prevalent among young adults in our Nation. However, we can be almost totally confident that 10.2 percent is not exactly correct. The true value might be 10.21 percent or 10.19 percent or even

9 percent or 11 percent, because even a sample of hundreds of thousands would be too small to yield absolute

certainty about a population of millions. The reported NHSDA 95-percent confidence interval for this estimate

of 10.2 percent runs from a lower bound of 9.5 percent to an upper bound of 10.9 percent, which provides a

boundary of rough accuracy and precision. It is appropriate to summarize the survey result by saying that about

9 to 11 percent of young adults in the survey population have never used any of these three drugs. It would be

inappropriate to claim that exactly 10.2 percent of young adult Americans have never used any of these three

drugs.

For any given subgroup of the population, the width of the confidence interval will tend to increase as effective

sample size decreases, up to a point. For example, the just-described national estimate of 10.2 percent (95-percent

31

Figure 1. Estimated Prevalence of Illegal Drug Use for Parolees and 

Probationers Versus Other Adults: 2000

25

20

15

10

5

0

Percent Using in Past Month

On Parole/

Supervised

Release

Not on Parole/

Supervised

Release

On

Probation

Not on

Probation

SOURCE: National Household Survey on Drug Abuse, Substance Abuse and Mental Health Services Administrations, Office of Applied 

Studies, 2001b.
Drug Use in the General Population

confidence interval = 9.5–10.9 percent) can be compared to State-level estimates, for which the sample size is

smaller. To illustrate, the NHSDA 1999 estimate for the State of Kansas, 10.8 percent, is no more than slightly

larger than the same year’s national estimate of 10.2 percent. Nonetheless, the national estimate draws strength

from almost 67,000 NHSDA survey participants, whereas the Kansas estimate is based on statistical projections

from a sample of fewer than 2,000 Kansans and has been strengthened via an estimation procedure that borrows

information from participants residing in other States. Whereas the Kansas estimate is almost the same value as

the U.S. estimate (10.8 percent versus 10.2 percent), the smaller number of Kansas respondents yields a 95-percent

confidence interval that is quite wide: 7.4–15.4 percent (Substance Abuse and Mental Health Administration

2001b). Hence, the numerical difference between the national estimate of 10.2 percent and the Kansas estimate

of 10.8 percent cannot be taken seriously, even though the Kansas estimate is numerically larger.

Epidemiologically and statistically speaking within the limits of these observed data, the national estimate and

the Kansas estimate are indistinguishable.

In contrast, the corresponding NHSDA estimate for individuals ages 20–25 residing in the State of Utah is 

34.9 percent, with a 95-percent confidence interval from 29.6 percent to 40.7 percent. That is, an estimated 

29 to 41 percent of young adult Utahns have never tried alcohol, tobacco, or marijuana. There is a large separation

between the 95-percent confidence interval derived for these Utahns versus corresponding intervals for young

adults in Kansas and the entire Nation. On this basis, we can have some confidence when we say that the cumulative occurrence of drug experience for young adult Utahns in the civilian noninstitutionalized population is

substantially lower than cumulative occurrence of drug experience among young adult Kansans or among young

adults in corresponding civilian noninstitutionalized populations elsewhere in the United States.

As it happens, when survey-based confidence intervals for epidemiological survey estimates are taken into

account and used as a gauge of the population prevalence of illegal drug use in the United States, the width of

the confidence intervals generally is so large that the intervals tend to accommodate the survey undercoverage

of homeless individuals or incarcerated prisoners. That is, when all drug-using homeless individuals and prisoners

are added to the total population prevalence estimates, the resulting sum generally falls within confidence intervals

derived for the civilian noninstitutionalized population. This conclusion can be derived via mathematics and

simulation studies, but in addition, Anthony and Helzer (1991) have provided an empirical demonstration,

drawing on data from epidemiological surveys in which both noninstitutionalized and institutionalized U.S.

populations were assessed using the same methods and by the same survey research teams. Prevalence estimates

based on civilian noninstitutionalized populations did not change appreciably when they were “corrected” to

include prevalence data from institutionalized persons.

A topic for future research includes reassessment of this situation for racial and ethnic minority populations 

in the United States. Based on the analyses reported by Anthony and Helzer (1991), it is possible to be fairly

confident that 95-percent confidence intervals based on surveys of civilian noninstitutionalized U.S. residents

do not understate the prevalence of illegal drug use in the United States. Estimates corrected for exclusion of

the homeless and institutionalized U.S. populations fall within the bounds of these confidence intervals.

However, minority population subgroups, especially young African-American males, are overrepresented among

incarcerated prisoners (e.g., see Blumstein and Beck 1999). Hence, it is possible that survey-derived 95-percent

confidence intervals for minority subgroups are differentially influenced by exclusion of the homeless and 

prisoners. This open question for future research deserves careful attention, given the well-known racial/ethnic

imbalances of the U.S. incarcerated population relative to the civilian noninstitutionalized population.

32
Drug Use in the General Population

Even if the NHSDA population could be redefined to include institutionalized and homeless persons, there

would be good reason to regard the survey estimates as understatements about the nature and scope of illegal

drug use in the United States, due to the various sources of survey error described above and elsewhere 

(e.g., Substance Abuse and Mental Health Administration 2001a), the fact that sampled respondents can

decline to participate in accord with principles for protection of human subjects, and to reliance on self-report

methods. A similar situation has been found in surveys of alcohol use, which tend to understate the actual 

volume of alcoholic beverages consumed, as independently assessed via sales tax receipts. These sources of error

also make it difficult to compare the nature and scope of alcohol, tobacco, and illegal drug use across racial and

ethnic minority subgroups because it is not possible to be sure that population coverage and accuracy of 

self-report are equally distributed across these subgroups. Nevertheless, as described in this chapter, many of the

survey-based statistics on nature and scope of alcohol, tobacco, and illegal drug use are illuminating. The 

statistics often challenge popular beliefs about these topics, and they help identify gaps in our epidemiological

evidence that merit attention in future research.

One set of popular beliefs already has been discussed in Chapter 1 and in prior editions of this report. For example, despite considerable heterogeneity and subgroup variation within the main racial/ethnic categories used in

official U.S. statistics, a popular belief persists that African Americans and Hispanic Americans are substantially

more likely to be involved in illegal drug use than are non-Hispanic Whites, and that Asian Americans are less

likely to be illegal drug users. Recently produced epidemiological estimates from NHSDA 1999–2000 survey

findings tend to challenge at least some of these beliefs.

For example, based on the NHSDA 1999–2000 data, an estimated 6.4 percent of non-Hispanic Whites have

recently engaged in illegal drug use; corresponding estimates for non-Hispanic African Americans and Hispanic

Americans are virtually indistinguishable from these values, once precision of the estimates has been taken into

account (e.g., via 95-percent confidence intervals). The only Hispanic Americans showing numerically greater

1-month prevalence of illegal drug use are those of Puerto Rican heritage (10.1 percent). Otherwise, observed

1-month prevalence values for Hispanic-American subgroups are no different or tend to be smaller than the 

corresponding values for non-Hispanic Whites and Black (Figure 2).

Another important observation from Figure 2 is the excess 1-month prevalence estimate, close to 12 percent,

observed for American Indian/Alaska Native members of the population, as compared with other subgroups.

Whether this excess frequency of recent illegal drug use is due to a greater accuracy of reporting by American

Indian/Alaska Native survey respondents is an open question. Further, even if there is comparable accuracy of

reporting, we will need more definitive evidence from future replications of the national survey. However, the

observed excess might be identifying a difference of public health importance with respect to orientation of 

public health intervention programs for American Indians and Alaska Natives in the United States—a topic we

will return to later in this report.

Figure 2 also demonstrates noteworthy variation within the Asian subgroups of the U.S. population under survey

in NHSDA, with data on Pacific Islanders missing because there were too few Pacific Islander respondents for

precise estimation. In NHSDA 2000, the estimated prevalence proportion for Native Hawaiian and other

Pacific Islander group is 6.2 percent, close to the value for non-Hispanic Whites, whereas the estimate for the

Asian subgroup within the Asian/Pacific Islander population is 2.7 percent. Hence, in general, Asian Americans

appear to be less likely to report recent illegal drug use than other U.S. population groups. However, this 

generalization does not hold true for Korean Americans, for whom the 1-month prevalence estimate from 

33
Drug Use in the General Population

combined 1999–2000 data (6.9 percent) is not appreciably different from the values observed for non-Hispanic

Whites and Blacks (e.g., see Figure 1 and Substance Abuse and Mental Health Administration 2001a).

A remarkably similar profile of subgroup variation can be seen in Figure 3, which presents the most recent

NHSDA 1999–2000 prevalence estimates for tobacco cigarette smoking. Here, with respect to recent tobacco

smoking, we again see an excess prevalence for the American Indian/Alaska Native subgroup (about 40 percent),

whereas the estimates for non-Hispanic Whites and Blacks in the same age range are 25.9 percent and 23.3 percent, respectively. The estimate for Korean-American youth ages 12–20 is 27 percent, the largest value observed

among Asian-American subgroups. Grouping all Asian subgroups, the corresponding estimate is 16.5 percent

(Substance Abuse and Mental Health Administration 2001a).

Notwithstanding the observed variation within and across these relatively refined subcategories within the official

broad categories, the remainder of this chapter generally presents epidemiological statistics for the broad three,

four, or five categories used in past official U.S. statistics on racial and ethnic issues (e.g., White, Black, Other).

However, while reviewing the estimates for these broad categories, readers should recall that Figures 2 and 

3 challenge popular preconceptions and beliefs about the nature and scope of illegal drug use among racial/

ethnic minorities in this country and throw new light on subgroup variation within these broad categories.

What is true for Hispanic Americans in general may not hold for subgroups within the Hispanic-American 

34

Figure 2. Estimated Prevalence of Recent Illegal Drug Use by Race/Ethnicity: 1999–2000

0 2 4 6 8 10 12

Percent Using in Past Month

White

Black

American Indian/Alaska Native

Hispanic Subgroups

Mexican

Puerto Rican

Central/South American

Cuban

Asian Subgroups

Chinese

Filipino

Japanese

Asian Indian

Korean

Vietnamese

SOURCE: National Household Survey on Drug Abuse, Substance Abuse and Mental Health Services Administrations, Office of Applied 

Studies, 2001b.
Drug Use in the General Population

population (e.g., those of Puerto Rican or of Cuban heritage), just as what is true for Asian/Pacific Islanders in

general may not hold for Korean Americans, Chinese Americans, or the separate summary categories that 

distinguish Asian Americans from Americans of Pacific Island heritage.

We also note that the NHSDA reports provide no confidence intervals for these estimates across racial/ethnic

subgroups. One of the first items on an agenda for future inquiry will be to clarify whether the subgroup 

variations, depicted in these figures and elsewhere in this report, are large enough for us to be confident that

illegal drug use is more prevalent in one subgroup versus another. Based on these recent NHSDA data, we can

be fairly confident that non-Hispanic Whites, Blacks, Pacific Islanders, and Korean Americans have roughly

equivalent prevalence of recently active illegal and extramedical drug use. However, the other numerical estimates

suggest considerable heterogeneity across and within racial/ethnic minority subgroups, with a dramatic excess

among American Indians/Alaska Natives. Once confidence intervals are available, it will be possible to make

more definitive claims about the observed numerical variation from group to group.

In addition to presenting data by race and ethnicity, this chapter presents data by age and sex. These data provide

a framework for comparing drug use across and within race, ethnicity, age, and sex groups. Although race/

ethnicity is the focus of this report, it is important to note both age and sex differences occur irrespective of race

or ethnicity. For illegal drug use, the peak periods for risk of starting drug use are during adolescence and young

35

Figure 3. Estimated Prevalence of Recent Tobacco Cigarette Smoking, 

by Race/Ethnicity: 1999–2000

0 10 20

Percent Using in Past Month

30 40

White

Black

American Indian/Alaska Native

Hispanic Subgroups

Mexican

Puerto Rican

Central/South American

Cuban

Asian Subgroups

Chinese

Filipino

Japanese

Asian Indian

Korean

Vietnamese

SOURCE: National Household Survey on Drug Abuse, Substance Abuse and Mental Health Services Administrations, Office of Applied 

Studies, 2001b.
Drug Use in the General Population

adulthood. Consequently, young people often are targeted in prevention programming because they are an 

especially high-risk group for initiation of illegal drug use, alcohol use, and smoking tobacco. In addition, malefemale differences in risk and prevalence of drug use also have been found in many surveys. In general, boys

have tended to initiate drug use earlier than girls and to use slightly greater quantities. For many drugs (but not

all), this pattern of male-female differences in drug use is maintained throughout much of adulthood.

PREVALENCE OF DRUG USE

Most of the subsequent statistics in this chapter are based on data from NHSDA 1998, the most recent survey

for which public use datasets are available for analysis. In 1998, the NHSDA sample included almost 12,000

non-Hispanic Whites, nearly 6,000 non-Hispanic Blacks, almost 7,000 Hispanic Americans, and slightly 

more than 1,100 participants in the other main racial/ethnic minority groups. Table 5 presents these values 

and corresponding population size estimates based on the U.S. Census, which show that NHSDA includes an

“oversampling” of racial/ethnic minority groups to ensure a sufficient number of minorities for precise estimation.

The tabled values also indicate NHSDA oversampling of young people, which ensures a sufficient number of

adolescents for precise estimation. As noted above, it is widely believed that NHSDA estimates of the prevalence

of illegal drug use are conservative in that some high-risk subgroups are not included in the NHSDA sample

(e.g., prison inmates and the homeless). Because drug use is a sensitive illegal activity and social tolerance for

drug use varies considerably over time, it also might be expected that some respondents deny illegal drug use

even when they have been users. Overexaggeration also is a potential source of error in reporting, although such

errors have been observed mainly in drug surveys of young adolescents (e.g., see Harrison and Hughes 1997;

Anthony et al. 2000).

The issue of accuracy in self-reports takes on special importance in research on ethnicity. The concept of ethnicity

encompasses socially shared and learned modes of interpersonal interaction and styles of communication, which

appear in various forms. Without clarification of these potential sources of error in self-report survey data, it is

difficult to be confident about the meaning of observed ethnic variation in prevalence estimates for illegal drug

use (e.g., larger estimates for American Indians/Alaska Natives and smaller estimates for African Americans). 

At the same or similar levels of drug involvement, we might find that members of historically 

disadvantaged minority groups are more or less likely to acknowledge that they have engaged in illegal drug 

use (Harrison and Hughes 1997).

NHSDA estimates for lifetime and past-month prevalence of drug use among members of the general population

age 12 and older are presented in Table 6. In 1998, for example, an estimated 78 million people age 12 and

older had engaged in illegal drug use at some point in their lifetimes. For the recent interval of 1 month up to

and including the day of survey assessment, an estimated 13.6 million had been recently active illegal drug users

(Table 6). Corresponding estimates from NHSDA 2000 are 86 to 87 million with a history of illegal drug use

and 14 million with recently active illegal drug use (Substance Abuse and Mental Health Administration

2001b).

For many years, marijuana has been prominent among illegally used drugs. Marijuana has been called a “gateway”

drug because its use often precedes other illegal drug use (e.g., cocaine and heroin), perhaps not because 

marijuana kindles biological cravings for other drugs but more because marijuana use is part of a more general

social fabric (e.g., see Kandel et al. 1987; Joy et al. 1999). In some investigations, long-term marijuana use has

been linked to serious health problems, such as emphysema (e.g., Joy et al. 1999).

36
Drug Use in the General Population

As depicted in Table 6, in 1998, an estimated 72 million Americans had tried marijuana at least one time, and

an estimated 11 million were recently active marijuana users. (Here and elsewhere in this report, “recently

active” use means use occurring in the month just before the assessment.) Among all Americans age 12 and

older, the corresponding “cumulative occurrence” or lifetime prevalence of marijuana use was 33 percent in

1998 and the corresponding 1-month prevalence estimate was 5 percent (Table 6). That is, one-third already

had become marijuana users; one in 20 had started to use marijuana at some point in time and had engaged in

marijuana use during the month just before assessment. Corresponding estimates from NHSDA 2000 are not

appreciably different: an estimated 76 million, or just over 34 percent with a history of marijuana use and an

estimated 10 million, or about 5 percent with recently active marijuana use (Substance Abuse and Mental

Health Administration, 2001b).

Table 6 also presents prevalence estimates for illegal use of cocaine, which includes cocaine hydrochloride powder

and crack-cocaine. Cocaine is of special health importance because within the first 1 to 2 years of use, an estimated

5 to 6 percent of cocaine users develop the clinical syndrome of cocaine dependence (Wagner and Anthony

2001). An estimated one in six cocaine users had developed cocaine dependence within 10 to 20 years of initial

cocaine use (Anthony et al. 1994; Wagner and Anthony 2002).

Among drugs used illegally and surveyed in NHSDA, cocaine is second in prevalence only to marijuana. Based

on the NHSDA 1998 data presented in Table 6, an estimated 23 million Americans age 12 and older had tried

cocaine at least once (10.6 percent), and an estimated 4.4 million had tried smoking crack-cocaine at least one

time (2.0 percent). Re-estimated via NHSDA 2000, these values are 24.9 million for all forms of cocaine use,

or an estimated 11.2 percent of the survey population, and 5.3 million for crack-cocaine use specifically, or 

2.4 percent (Substance Abuse and Mental Health Administration, 2001b). 

During 1998, an estimated 1.75 million (0.8 percent) people age 12 and older had used cocaine recently and an

estimated 400,000 to 500,000 (0.3 percent) had used crack-cocaine recently (Table 6). Corresponding estimates

based on NHSDA 2000 are 1.2 million (0.5 percent) for cocaine generally and 265,000 (0.1 percent) for crackcocaine (Substance Abuse and Mental Health Administration 2001b).

In recent years, use of LSD and other hallucinogenic drugs has become almost as common as cocaine use in the

United States. For example, in 1998 an estimated 22 million Americans had tried LSD or other hallucinogenic

drugs at least one time (9.9 percent), as compared to the 23 million who had used cocaine (10.6 percent) 

(Table 6). For recently active use as estimated from the 1998 survey, an estimated 1.5 million recently have 

used hallucinogenic drugs (0.7 percent), compared with 1.75 million, or 0.8 percent, with recent cocaine use

(Table 6). Based on NHSDA 2000, an estimated 26 million (11.7 percent) had used hallucinogens at least one

time, as compared to the 24.9 million (11.2 percent) who had used cocaine at least one time. However, regarding

recently active drug use estimated in the most recent NHSDA statistics from 2000, almost 1 million individuals

used hallucinogens in the month up to and including the date of the interview assessment (0.4 percent); comparable hallucinogen values from 1998 were 1.5 million, or 0.7 percent (Table 6 and Substance Abuse and

Mental Health Administration 2001b).

Controlled drugs available by prescription or over the counter also may be used for illegal or extramedical 

reasons. For example, based on NHSDA 1998, an estimated 11 to 12 million Americans (5.3 percent) had tried

analgesic (pain-relieving) drugs at least one time to get high or for other extramedical reasons; an estimated 

1.7 million (0.8 percent) had engaged in recently active extramedical use of these analgesic medicines (Table 6).

37
38

Drug Use in the General Population

Corresponding NHSDA 2000 values are 19.2 million (8.6 percent) for lifetime history of use and 2.8 million

(1.2 percent) for recently active use in the month before survey assessment (Substance Abuse and Mental Health

Administration, 2001b).

The use of pain-relieving pharmaceuticals for nonmedical reasons recently has become a more prominent 

issue in American society, due to concern about diversion and illegal use of sustained-release oxycodone

(OxyContin®), especially in rural America but also in several cities, including Boston (e.g., see National Institute

on Drug Abuse 2001). Based on the most recently published NHSDA survey reports, there has been a recent

increase in extramedical use of OxyContin®, from an estimated 220,000 extramedical users in 1999 to almost

400,000 users in 2000 (Substance Abuse and Mental Health Administration 2001b). We do not yet know

whether this oxycodone phenomenon will become more dominant in the national level statistics or will be 

constrained to more local and isolated outbreaks. This is a topic deserving future epidemiological inquiry.

Psychostimulants, a drug group that includes prescription medicines like methylphenidate (Ritalin), as well as

illegally produced methamphetamine (e.g., “ice”), also are prominent among drugs used illegally or extramedically.

In 1998, an estimated 9.6 million (4.7 percent) had used these psychostimulants illegally or extramedically

(Table 6). The corresponding estimates from NHSDA 2000 are 14.7 million, or 6.6 percent (Substance Abuse

and Mental Health Administration 2001b). For recently active use, in 1998 an estimated 633,000 (0.3 percent)

engaged in illegal or extramedical use of psychostimulant drugs in the month before survey assessment, compared

with an estimated 790,000 (0.4 percent) in 2000 (Table 6; Substance Abuse and Mental Health Administration

2001b).

Tranquilizing or antianxiety medicines also are prominent among prescription medicines used illegally or

extramedically. In 1998, an estimated 600,00 to 700,000 individuals (0.3 percent of the survey population) had

engaged in recently active illegal or extramedical use of these tranquilizing medicines (Table 6). By comparison,

the estimates from NHSDA 2000 are 1 million recently active users in the month before survey assessment, or

0.4 percent of the survey population (Substance Abuse and Mental Health Administration 2001b).

Sleeping preparations and other sedative medicines were somewhat less likely to be represented among recently

active illegal and extramedical drug users. In 1998, roughly 200,000 individuals (about 0.1 percent of the survey

population) used sedatives illegally or extramedically. Based on NHSDA 2000, the corresponding estimates are

180,000, still about 0.1 percent of the survey population (Substance Abuse and Mental Health Administration

2001b).

Alcohol is by far the most frequently used drug in the United States. In addition to its purchase and consumption

being legal for those age 21 and older, alcoholic beverages are readily available and socially acceptable in most

parts of the United States. These beverages generally are relatively inexpensive, as compared with the unit dose

prices for many other intoxicating drugs. Data from NHSDA 1998 indicate that slightly more than 80 percent

of the population age 12 and older have tried alcohol at least one time, and just over one-half of the survey population (51.7 percent) consumed alcohol in the month before the survey (Table 6). Corresponding values from

NHSDA 2000 are 81 percent and 47 percent (Substance Abuse and Mental Health Administration 2001b).

Although smoking tobacco is not illegal, this drug is of concern because of its well-established reinforcing functions and negative effects on health. For example, an estimated one in three tobacco smokers has developed a

clinical syndrome of tobacco dependence (Anthony et al. 1994). In addition, tobacco smoking is implicated in

progression toward later illegal drug use (Kandel and Davies 1991).
Drug Use in the General Population

According to estimates from NHSDA 1998, slightly more than 150 million Americans in the survey population

(69 to 70 percent) had tried tobacco cigarettes at least one time, and more than 60 million (27 to 28 percent)

were recently active tobacco smokers in the month before the survey (Table 6). Estimates from the NHSDA

2000 indicate no marked change in these estimates, with 148,000 individuals having a history of tobacco 

smoking and an estimated 56,000 considered recently active smokers (Substance Abuse and Mental Health

Administration 2001b).

Estimated male-female differences and age-specific prevalence of past-month alcohol, tobacco, and illegal drug

are depicted in Table 7. In general, the largest prevalence estimates for recently active use are observed for young

adults ages 18–25 and for males. For all drug groups depicted in Table 7, the illegal drug use prevalence 

estimates for individuals age 35 and older are lower than values observed for younger age groups, due in part to

a combination of effects associated with birth cohorts, secular periods, and aging. The variation by age is somewhat less pronounced for alcohol and tobacco, although the lower values observed for adolescents ages 12–17

signify opportunities for preventive interventions during the childhood and early adolescent years.

Generally observed male-female differences in the Table 7 estimates are least pronounced for tobacco cigarettes.

In 1998, an estimated 29 to 30 percent of men in the survey population were recently active tobacco cigarette

smokers. The corresponding estimate for women is 25.7 percent (Table 7). This male-female difference

remained relatively stable at about 4 to 5 percentage points during the last years of the 20th century. Based on

NHSDA 2000, an estimated 27 percent of males age 12 and older in the survey population had smoked tobacco

cigarettes in the month before survey assessment, compared with an estimated 23 percent of females in the 

survey population (Substance Abuse and Mental Health Administration 2001b).

Table 8 expands the epidemiological description to encompass features of race and ethnicity, based on new

analyses of public use datasets distributed after completion of the NHSDA 1998 data gathering and completed

specifically for this report. Public use datasets from NHSDA 1999 and 2000 have not yet been released, so it has

not been possible for this report to include estimates based on these more recent data. Nonetheless, the general

epidemiological patterns depicted in evidence from these analyses are not expected to change dramatically from

year to year, with some important exceptions. One important exception involves dynamic epidemiological

changes in the incidence of drug use, as observed in the late 1980s with cocaine. Whereas lifetime prevalence

of cocaine use remained relatively stable or declined somewhat during the 1980s when national-level statistics

were examined, data on the number of new initiates show dramatic changes across different raceethnicity groups. For example, as depicted in Figure 4, data reveal that for non-Hispanic Whites, the number

of new initiates reached a peak in the late 1970s and early 1980s, while the number of new Black and Hispanic

initiates remained at lower levels. It was not until several years after peak incidence among Whites that the 

incidence curves for Blacks and Hispanics showed their peaks (Figure 4). Hence, the national epidemic of

cocaine use in the United States really can be subdivided into more than one epidemic, with an earlier epidemic

and earlier peak for non-Hispanic Whites and a later epidemic and later peak for Blacks and Hispanics (Gfroerer

and Brodsky 1992; figure adapted from Gfroerer and Brodsky 1992).

Notwithstanding the dynamic epidemiological conditions that were evolving during the 1980s and early 1990s,

it generally is true that patterns of race- and ethnicity-related alcohol, tobacco, and illegal drug use tend not to

change over short spans of time. Until new analyses of the 1999 and 2000 NHSDA data have been completed,

the NHSDA 1998 estimates provide the best available epidemiological descriptions for racial/ethnic minority

population groups in America. As depicted in Table 8, and based on summaries across the broad five racial/

39
Drug Use in the General Population

ethnic categories (rather than looking for subgroup variation within these categories), the estimates show that

Asian/Pacific Islanders tend to have the lowest prevalence of past-month drug use. For example, as seen in the

last column of Table 8, the prevalence estimate for recently active illegal drug use is 2.8 percent for Asian/Pacific

Islanders, versus estimates that range from 6.1 percent to 9.3 percent for the other subgroups listed in the table.

Similar contrasts of varying magnitude can be seen for recently active use of marijuana, cocaine, and alcoholic

beverages, heavy use of alcoholic beverages, and tobacco cigarette smoking (Table 8, last column). Numerical

estimates for the American Indian/Alaska Native subgroup tend to display the largest values in the last column

of Table 8, except for recently active drinking of alcoholic beverages. However, without confidence intervals and

statistical adjustment for differences in the age distributions of these subgroups, it is difficult to assess whether

American Indians and Alaska Natives have higher prevalence than the other subgroups.

In addition, as discussed by Lillie-Blanton et al. (1993), the observed variation in drug experience across racialethnic subgroups may be a function of socially shared neighborhood characteristics that are extrinsic with

respect to race and ethnicity. That is, in analyses that did not take neighborhood into account, Lillie-Blanton

and colleagues found that Blacks were more likely than Whites to have become crack-cocaine users. However,

comparing Blacks and Whites living in the same neighborhood areas (i.e., with neighborhood-matching), there

were no such Black-White differences in occurrence of crack-cocaine use. Flewelling and colleagues (1992)

40

Figure 4. Estimated Number of New Users of Cocaine for Three 

Population Subgroups: 1976–1989

NOTE: This figure has been prepared for this report, based on results from retrospective age of onset analyses of NHSDA data (Gfroerer 

and Brodsky 1992). The number of White, non-Hispanic new initiates is shown on the y-axis to the left. The numbers of Black 

non-Hispanic initiates and Hispanic initiates are shown on the right y-axis.

1600

1200

800

400

0

400

300

200

100

0

1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989

Year

Number of New Users (in thousands)

●

■ ■

■

■

■

■

■

■ ■

■

■

■ ■

■

▲

▲

▲

▲ ▲

▲ ▲ ▲ ▲

▲ ▲

▲

▲

▲

●

●

●

● ● ●

●

●

●

● ●

● ●

●

▲

■

White Non-Hispanic

Black, Non-Hispanic

Hispanic
Drug Use in the General Population

reported similar conclusions based on analyses with statistical adjustments for characteristics of census tracts as

measured in the U.S. Census (Lillie-Blanton et al. 1993). Interpretation of racial/ethnic variations, as depicted

in Table 8, remains uncertain until statistical precision of the estimates has been taken into account; misinterpretation of the evidence is possible without comparison to estimates that control for features of social context

and socioeconomic circumstances.

The data in Table 8 also are generally consistent with the patterns of age-specific variation seen in Table 7. For

example, estimates for past-month illegal drug use show the largest values for individuals ages 18–25. This

observed excess prevalence among this age group is due in part to peak periods of risk of initiating illegal drug

use during the middle and later years of adolescence and in part to the epidemiological fact that many adolescent drug users sustain their illegal drug use into young adulthood, sometimes in association with development

of drug dependence syndromes (e.g., see Wagner and Anthony 2002; Substance Abuse and Mental Health

Administration 2001a). The lower values observed after age 34 are due in part to the lower risk of initiating 

illegal drug use in these years, as well as the lower risk of becoming drug dependent after young adulthood 

(e.g., see Eaton et al. 1989; Warner et al. 1995; Wagner and Anthony 2002).

Comparison of male-female differences shown in the next-to-last columns of Table 8 shows a general male excess

in prevalence of recently active illegal drug use, alcohol use, heavy alcohol use (defined as “5 or more drinks on

the same occasion on at least 5 or more days in the month prior to assessment”), and tobacco cigarette smoking,

across all racial/ethnic groups under study. For example, looking across the five racial/ethnic groups, for marijuana

and cocaine use, men are some one-and-a-half to three times more likely than women to be recently active 

marijuana users and to be recently active cocaine users. One exception is seen among American Indians/Alaska

Natives, where the ratio of prevalence estimates is more than tenfold (Table 8).

To some extent, this pattern of male excess prevalence for illegal drug use may be traced back to males being

more likely to have opportunities to try marijuana, cocaine, and other controlled drugs. To date, the epidemiological evidence from the United States indicates that males are more likely than females to have opportunities

to initiate illegal drug use, but females are generally just as likely as males to initiate illegal drug use once the

opportunity is presented (Van Etten and Anthony 2001). In addition, with the most controlled drugs, women

are just as likely to become drug dependent once they initiate extramedical drug use. There may be a female

excess in risk of developing dependence on prescription medicines, once extramedical use of these medicines has

started, but these medicines are not included in the list of drugs in Table 8 (e.g., see Anthony et al. 1994).

A general age-related decline can be observed in comparing Table 8 estimates for individuals ages 26–34 with

those for adults age 35 and older. Noteworthy exceptions are apparent for several drugs and groups, where there

may be no age-related difference at all. One exception involves prevalence of recently active cocaine use among

American Indian/Alaska Natives, for whom the estimate is 0.3 percent for individuals ages 25–34 and 1.5 percent

for adults age 35 and older. Another exception involving the American Indian/Alaska Native population group

involves heavy alcohol use, with a prevalence of 16 percent for individuals ages 26–34 and 14.3 percent for older

adults. These exceptions are noteworthy because in general the above-mentioned effects of aging, birth cohort

differences, and secular periods tend to contribute to lower prevalence estimates among older adults. In

American Indian/Alaska Native populations, these general effects may be cancelled to some extent by excess

mortality risk for middle-aged members of this racial/ethnic minority group and (more speculatively) by excess

risk of alcohol or other drug dependence.

41
Drug Use in the General Population

The exceptions observed for tobacco cigarette smoking in Table 8 also are noteworthy. Among Black Americans

and Hispanic Americans, no age-related decline in prevalence of recently active tobacco cigarette smoking is 

evident in comparing individuals ages 26–34 with older adults age 35 and older. If the age-related declines

observed for non-Hispanic Whites are attributed to effective public health interventions, it is possible that the

impact of these interventions has not been so prominent among these racial/ethnic minority groups.

Across all age groups, American Indian/Alaska Natives exhibit the highest prevalence estimates for past-month

use of marijuana. This observation requires replication as well as error checking and evaluation in relation to

confidence intervals. Once the NHSDA 1998 data are subdivided by recently active (past month) drug use, age,

and race/ethnicity, the numbers of American Indian/Alaska Native recently active drug users in each age group

become quite small and the corresponding estimates become quite imprecise.

The apparent excess prevalence of recently active cocaine use among African Americans ages 26–34 has been

observed since the early 1990s. The lower prevalence of cocaine use among the youngest African Americans 

also has been noted. These are epidemiological patterns that merit attention in planning for public health 

intervention. Nonetheless, as noted already within this chapter, with neighborhood matching or statistical

adjustment for neighborhood characteristics, the excess occurrence of cocaine use among African Americans 

is much attenuated. An excess, if any, might be traced back to greater street-level cocaine availability and 

relatively uncontrolled drug dealing in still-segregated neighborhoods with a high density of African Americans

(e.g., see Lillie-Blanton et al. 1991; Ensminger et al. 1997).

Table 9 presents a detailed look at recently active (past month) use of alcohol, tobacco, and other drugs within

the U.S. Hispanic population, with subgroupings for six Hispanic subgroups. There is some value in presentation

of prevalence estimates for these Hispanic subgroups, but caution must be voiced. Compared with prior annual

NHSDA surveys, the NHSDA 1998 dataset was unusual in the number of Hispanic respondents (n=6,795).

Nonetheless, once six subgroups are created and additional subdivisions into four age groups are made, the

number of illegal drug users within each subgroup is limited, as is the total size of each subgroup. In consequence,

the confidence intervals for most of the age-specific estimates in Table 9 are wide, and the observed variation may

well be an artifact. Nevertheless, several general conclusions are warranted. For example, as depicted in the last

column of Table 9, for recently active illegal drug use, considerable subgroup variation in prevalence exists across

the various Hispanic heritage groups. For example, the lowest prevalence estimates are observed for U.S. Hispanic

residents of South American and Cuban heritage: 2.1 percent and 3.4 percent, respectively. These lower values

are observed not only for all members of these subgroups (last column) but also for males and females (next-tolast columns). The largest estimates are obtained for the “Other” group of Hispanic residents and for those of

Puerto Rican heritage: 8.2 percent and 6.9 percent, respectively (shown in the last and next-to-last columns 

of Table 9). The excess prevalence of illegal drug use among South Americans is especially interesting because

this group’s value cannot be explained by their marijuana and cocaine use. Adding the marijuana and cocaine

prevalence values for the “Other” group yields a sum of just 5.1 percent, not large enough to account for the

8.2 percent estimate for “any illegal drug use,” even if none of the marijuana users consumed cocaine and none

of the cocaine users consumed marijuana—an unlikely circumstance. Hence, some other form of illegal drug

use must be contributing to the observed general excess prevalence in relation to illegal drug use—perhaps

inhalant drugs as described by Mesquita and colleagues (1997) or extramedical use of prescription medicines as

described by Nappy and Carlini (1993) and others.

42
Drug Use in the General Population

Hispanic residents of Puerto Rican heritage also have relatively higher prevalence estimates for marijuana,

cocaine, and tobacco cigarette smoking. This excess prevalence among Puerto Ricans is observed for marijuana

and tobacco smoking for both males and females, but the observed excess prevalence of recently active cocaine

use is seen for males of Puerto Rican heritage but not females. This epidemiological pattern merits greater 

attention in future research. As depicted in Figure 2, the apparent excess prevalence of illegal drug use among

U.S. Hispanic residents of Puerto Rican heritage has been replicated independently in the data from NHSDA

1999–2000, and also was seen in data from NHSDA 1996. Associated implications for planning of public

health interventions will become more clear once there are more probing analyses of these initial epidemiological

observations, with attention to social context, geographic locations, and other circumstances, conditions, and

processes associated with illegal drug use in this population subgroup.

Based on data in Table 9 from NHSDA 1998, persons of South and Central American heritage had the highest

prevalence values for recently active consumption of alcohol (46 percent and 47.2 percent, respectively), but it

was U.S. Hispanic residents of Mexican heritage who had the highest prevalence of recently active heavy alcohol

use (7.4 percent). The South and Central American values for heavy alcohol consumption were intermediate in

level (4.1 percent), and Cuban-Americans had the lowest prevalence of heavy alcohol consumption (1.7 percent).

The data on male-female differences among Hispanic subgroups show a pattern that is generally consistent with

sex-specific estimates for other racial/ethnic minority groups (Table 9). That is, in general, Hispanic females

have a lower prevalence of recently active drug use for all drug categories compared with males. In many contrasts, Hispanic males are two to three times more likely to be recently active drug users. Women of CubanAmerican heritage have the lowest prevalence estimates observed for marijuana, cocaine, and heavy alcohol use. 

As noted in the initial description of Table 9, imprecision in these epidemiological estimates prompts some 

hesitation in the interpretation of the observed variation across age groups within the Hispanic subgroups.

Nevertheless, it is noteworthy that the general pattern of age-specific variation described in relation to the 

Table 8 estimates also is apparent for many of the Hispanic subgroups depicted in Table 9. One interesting 

age-specific relationship is seen in relation to recently active heavy alcohol consumption. There is relatively

invariant prevalence of recently active heavy alcohol use across the three adult age groups of Mexican Americans,

with values of 9.2 percent for individuals ages 18–25, 8.6 percent for those ages 26–34, and 7.5 percent for

adults age 35 and older. There is a sharp decline from the value observed for individuals ages 18–25 of Puerto

Rican heritage, compared with values observed for older adults (11.9 percent to 5.4 percent to 6.1 percent) in

this subgroup. With other subgroups for which there is an adequate number of participants, the age-specific

estimates show age-related declines among non-Hispanic Whites and most of the other groups represented in

Table 8.

In many public health reports, women ages 15–44 are considered to be of childbearing age. Table 10 presents

NHSDA 1998 estimates for the prevalence of drug use among women ages 15–44 by age, race/ethnicity, and

metropolitan/nonmetropolitan location. Estimates for lifetime history of illegal drug use indicate that use is

highest among White women (51.2 percent), followed by African-American women (36.0 percent), Hispanic

women (26.2 percent), and women of other race/ethnicity groups (20.2 percent). Recently active illegal drug

use showed a somewhat different pattern across these groups, with a slightly higher prevalence of past-month

illegal drug use for both non-Hispanic White and African-American women (7.6 percent and 8.1 percent,

respectively), compared with Hispanic women and women in the “Other” group (6.1 percent and 3.0 percent,

respectively). In general, prevalence estimates for illegal drug use and for recently active use of marijuana and

43
Drug Use in the General Population

cocaine were highest among women ages 15–24. There were several exceptions, and a noteworthy pattern of

age-specific estimates was observed for recently active cocaine use among African-American women. Among

that group, an estimated 0.4 percent of women ages 15–24 were recently active cocaine users, compared with

2.2 percent and 2.1 percent for individuals ages 25–29 and 30–44, respectively. The lower prevalence value for

the youngest women is not seen in the age-specific estimates for non-Hispanic White women or for Hispanic

women. Within these two groups, the youngest women are the most likely to be recently active cocaine users.

Observed variations across metropolitan and nonmetropolitan areas also are noteworthy in several instances. For

example, among non-Hispanic White women and African-American women, there is a general tendency toward

higher prevalence of illegal drug use in metropolitan areas than in nonmetropolitan areas. This pattern is not

seen for women of Hispanic heritage nor for women in the “Other” racial/ethnicity group (Table 10).

From vital statistics data abstracted from birth certificates in selected States, it is possible to add a different perspective on the drug use of women in the childbearing years. These statistics disclose trends in the prevalence of

tobacco smoking during pregnancy among mothers of live-born infants. From 1993 through 1999, there were

modest declines in these estimates (Table 11), which represent a continuation of declines observed between

1989 through 1993 (National Institute on Drug Abuse 1998). For example, evaluating the estimates for all

mothers of live-born infants (last row of Table 11), the proportion that smoked during pregnancy in 1993 was

almost 16 percent. By comparison, the value observed in 1999 was 12 to 13 percent.

Supplementing the NHSDA statistics, these epidemiological data add more information about heterogeneity

within the broad racial/ethnicity subgroups generally displayed in official statistics. To illustrate, in these data,

the observed prevalence of smoking during pregnancy is substantially greater for Hawaiian and part-Hawaiian

women than for the other Asian and Pacific Islander groups represented in the table. Whether this impression

is a result of a sampling artifact or other errors remains an open question for future research. It is possible that

this type of subgroup variation might be due to methodological difficulties in vital statistics, such as incomplete

coverage of Hawaiian versus other Asian live-borns in the birth certificate database. It certainly is true that 

completeness and accuracy of information on birth certificates can vary from place to place and time to time.

For example, it may be possible that birth certificate processes and recording of tobacco smoking status of the

mothers is more complete in public health districts serving Hawaiian mothers and live-born infants than in

other areas of the country.

ATTITUDES AND PERCEPTIONS

In accord with sociological concepts elaborated by George Herbert Mead, several social psychological theories

of drug-taking link an individual’s attitudes about drug use and perceptions of the harmfulness of drug use to

the individual’s risk of becoming and remaining a drug user. Recent economic theories also incorporate links

between subjective assessments of the utility of drug-taking behavior, both short- and long-term, and the probability of choosing to initiate or sustain drug use. According to most of these theories, when people anticipate

or perceive there are risks of harm attached to drug-using behaviors, they are less likely to engage in those

behaviors.

Ecological analyses of national-level statistics yield evidence consistent with these theories. For example, time

trends in perceived harmfulness of drug use are linked with time trends in prevalence of drug use, even when

perceived availability of drugs remains constant or is held constant statistically.

44
Drug Use in the General Population

These theories and data have prompted speculation about the possibility of preventing or reducing youth’s drug

use by manipulating attitudes or perceptions about the harmfulness of drug use, either through family process,

peer communication, drug education programs, or mass media and other social marketing campaigns. Of

course, it is possible that alternative processes are at work in generating the observed data. For example, mass

media campaigns and drug prevention efforts often are redoubled during periods of increasing prevalence of

drug use, but concurrent with these periods are processes of personal exposure to the casualties of drug use. To

the extent that a youth has an older brother, other relative, or friend who becomes a casualty of drug use, the

harmfulness of drug use may acquire an immediacy that has substantial impact on the likelihood of future drug

use. Of course, as prevalence of drug use begins to mount, these personal experiences with the harm and casualties

associated with drug use also increase, all else held constant. Consequently, perceptions of harmfulness of 

drug use may be more influenced by increasing prevalence of drug use and personal observation of drug-related

casualties and less influenced by concurrent mass media or drug prevention campaigns. 

Theories about the links between perceived harmfulness and prevalence of illegal drug use remain incomplete

to the extent that they fail to account for these reciprocities between prevalence of drug use at the population

level and perceptions about harmfulness of drug use at the individual level. Nevertheless, theoretical concerns

aside, there is good reason to speculate about whether drug prevention campaigns might be aided by a better

understanding of the interrelationships between a person’s attitudes and perceptions about drug use and the person’s individual-level probability of becoming a drug user. For this reason, several studies have been measuring

attitudes and perceptions about drug use in an effort to track and improve understanding of their relationships

with drug-taking behavior.

PATS is an ongoing national study that seeks information about the attitudes of students and parents, as well

as estimates of drug-related behavior in these populations. For example, in 2000, more than 7,000 students in

the middle- and high-school grades (7–12) answered questions administered as part of the PATS classroom 

surveys. Parents generally are interviewed at home. In some years, the PATS survey has extended to children in

primary school (grades 4–6), but this was not the case in 2000, the 13th wave of this research project since its

initiation in 1986.

Table 12 presents estimates from PATS, as reported from 1997 through 2000. For example, in the first row of

Table 12, it is possible to see a downward trend in the proportion of youth (grades 4–6) who report that marijuana is easy to get, with general parallel trends for Whites (columns 1–4), Blacks (columns 5–8), and Hispanics

(columns 9–12). The trends for teens and for parents are not as regular. For example, among White parents

asked whether marijuana was very easy for their children to get, the estimate for 1997 was 27 percent, and in

2000 it was 25 percent—not a large enough difference to be remarkable. Similarly among Black parents, the

corresponding values were 33 percent and 31 percent, with values of 36 percent and 42 percent in 1998 and

1999, respectively. It might be said that White teens perceived reduced availability of marijuana between 1997

(60 percent) and 2000 (54 percent), but the corresponding trends for Black and Hispanic teens were relatively

more stable.

The patterns for cocaine and crack are of note and show possible variation across the racial/ethnic subgroups.

For example, in 1997, an estimated 14 percent of White youth in grades 4–6 reported that cocaine and crackcocaine were easy to get, and 17 percent of White parents reported congruent impressions about cocaine/crack

availability to their children. By 1999, the estimate based on the youth’s reports was only 7 to 8 percent (close

to a value of 6 percent observed in 1993), and in 2000, the estimate based on parents’ reports was 9 percent.

45
Drug Use in the General Population

Downward shifts of somewhat smaller magnitude can be seen in the estimates for Black youth and parents, but

there are no similar shifts in the Hispanic segment of the PATS sample. Whether these estimates on perceived

availability of marijuana and cocaine actually reflect prevailing availability in the communities surveyed remains

an open research question, but the apparent numerical difference across these several racial/ethnic groups is

provocative and warrants more detailed scrutiny (e.g., confidence interval estimation and investigation of other

circumstances, conditions, and processes). When seen in the context of differences between reports of Black

youths and their parents, the apparent general congruence between reports of Hispanic youth and their parents

also merits investigation. Many Black parents sampled have a sense that cocaine and crack are very easy for their

children to get, but less than half as many children see it that way. The same patterns of child-parent incongruence and congruence are seen in the estimates for marijuana availability (Table 12).

Perception of risk is quantified in PATS by the estimated proportion of grade-school children and teens who

associate great risk or danger with the use of various drugs, and by the corresponding proportion for parents

who are asked to describe their child’s perceptions about the dangers of drug use. The PATS assessments asked

grade-school children to report their perceptions of the risks and dangers of cocaine and crack use separately,

while teens and parents were asked to report about cocaine and crack as a single entity. As depicted in Table 13,

from 1997 to 1999, there was general stability in the proportion of youths in grades 4–6 and teens in grades

7–12 who reported that marijuana use is dangerous. For example, in the first row of Table 13, fluctuation occurs

around a value of about 80 percent for White children, 75 percent for Black children, and 75 to 77 percent for

Hispanic children. Without confidence intervals, it is difficult to judge whether the observed variation in these

statistics is meaningful. The general stability in the parents’ reports of their child’s perceptions about the danger

of marijuana use also is noteworthy, with somewhat larger values in 1997 for White and Black parents, but with

no clear pattern among Hispanic parents.

It also is noteworthy that the children do not assign greater danger and risk values to use of cocaine and crack

or heroin than use of marijuana. These perceptions of danger and risk do not reflect what is known about the

relative likelihood of becoming dependent on cocaine or heroin versus marijuana or the relative likelihood of

drug-related death in association with these three drugs (e.g., see Anthony et al. 1994; Wagner and Anthony

2002; Chapter 6, this report). The children’s relatively lower danger and risk evaluations of inhalant drugs also

deserve more detailed investigations, given the public health importance of inhalant drug use in childhood and

adolescence (e.g., see Neumark et al. 1998). These lower evaluations of danger associated with inhalant use also

were seen in the PATS data from 1993 through 1996 (National Institute on Drug Abuse 1998).

Table 14 reports the PATS estimates for the proportion of youth and teens that report being afraid of taking

drugs. In general, youth in grades 4–6 are more likely to report being afraid than are teens in grades 7–12. This

is true for all three of the reported racial/ethnic groups. The estimates across the years reported in Table 14 

(i.e., from 1997 to 2000) are generally stable, with no marked upward or downward change from year to year.

The belief that “smoking marijuana is okay sometimes” has been generally stable across these years. One exception can be seen in the last columns of Table 14, where it appears that Hispanic youths became less likely to

report agreement with this statement 1997 to 1999. However, no similar difference across these years was seen

for Hispanic teens or for the parents. White and Black parents were slightly more likely than their teens and

younger children to agree with the statement that it is okay to smoke marijuana sometimes. This discrepancy

between parents and children was not seen for the Hispanic group, except in 1997, when the younger children

showed the relatively high and perhaps anomalous agreement value of 29 percent.

46
Drug Use in the General Population

Fluctuation has occurred in the observed numerical proportions, but in general between 1997 and 2000, there are

relatively stable estimates for the statement “If parents use marijuana, their children are likely to use marijuana.”

For example, among White parents, an estimated 75 percent agreed somewhat or strongly with this statement in

1997 and the corresponding value for 2000 was 72 percent. It is noteworthy that Black parents are substantially

less likely to agree with this statement than are White and Hispanic parents (Table 14).

Table 14 also shows general stability in respondents’ agreement with the statement “It’s really hard to give my

child reasons not to use marijuana.” Across the years, between 14 and 20 percent of White parents endorsed

this statement, compared with about 18 to 25 percent of Black parents. However, there were marked fluctuations

for the Hispanic parents, with a value of 36 percent observed in 1999 and a value of 13 percent observed in

2000. Information about confidence intervals and possible differences in sampling plans or methods for

Hispanic parents across these years will be required before a difference of this magnitude can be interpreted.

PATS respondents also are asked if they want to hang around people who use drugs; responses are presented in

Table 14. Generally, there is stability in the reports of youth and teens on this aspect of interpersonal relations

and values toward drugs. What is more striking is the difference in values for the younger students in grades 4–6

versus those of the older students in grades 7–12. Whites, Blacks, and Hispanics in older grades have greater

acceptance of social relationships with drug-using people.

Data on youth’s and teens’ attitudes toward selling drugs to make money also are presented in Table 14. These

estimates for younger and older students complement the just-reported values on social relationships with 

drug-using people. In contrast to youth in grades 4–6, a much greater percentage of teens feel it is okay to sell

drugs to make money. This finding is consistent across racial/ethnic groupings for the 2 years (1997 and 1998)

in which this comparison can be made.

Comparing the percentage of children and teens in different racial/ethnic groups who feel it is okay to sell drugs

indicates that White students are less favorably disposed to drug dealing than are Black and Hispanic students.

For example, in 2000, an estimated 17 percent of White teens reported strongly or somewhat agreeing with the

statement that it is okay to sell drugs to make money. In that same year, an estimated 27 percent of Black teens

and an estimated 24 percent of Hispanic teens expressed these values.

SUMMARY

Data from NHSDA have started to shed new light on variations within the four or five main racial/ethnic

groupings that typically have been used in summaries of epidemiological evidence about illegal drug use, alcohol,

and tobacco smoking. Several patterns are beginning to emerge, including challenges to preconceptions and

beliefs about greater occurrence and prevalence of illegal drug use among Blacks and Hispanics than among

non-Hispanic White members of the U.S. civilian noninstitutionalized population. Several observations are

noteworthy and merit sustained inquiry, including the prominence of Puerto Ricans among Hispanic illegal

drug users; the pattern of age-specific prevalence estimates for recently active cocaine use among African

Americans, including women of child-bearing age; and the apparent excess prevalence of illegal drug use among

American Indian/Alaska Native groups. In many respects, these data raise more questions than they answer.

PATS data were examined to ascertain information on attitudes of youth, teens, and parents about drug use.

Youth, teens, and parents were asked about the perceived ease of obtaining several illicit drugs; statements

47
Drug Use in the General Population

reflecting attitudes toward drug use, drug users, and drug dealers; and assessments of the relative danger or risk

associated with different drugs. In general, patterns of general stability characterize these statistics; nevertheless,

noteworthy variations are evident between children, teens, and their parents, sometimes reflecting discrepancies

that merit more study because they might provide new information for use in planning drug prevention programs.

In addition, interesting differences define attitudes of primary school and older students toward social relationships with drug users and acceptability of drug dealing to make money. The general observation that Black and

Hispanic teens are more likely than White teens to accept drug dealing as a means of earning money is striking.

Whether this attitude of acceptance is an artifact of sampling or other methodological features of the PATS

approach must be investigated in more detail before this intriguing observation can be translated into public

health action. If confirmed, the observation should provoke planning and implementation of new intervention

programs directed toward shaping the orientation of social networks to address personal involvement in drug

supply and distribution.

Finally, the age-related variation in perceptions about the harmfulness of marijuana, cocaine, heroin, and

inhalants is striking. To some extent, younger students misperceive the relative danger and risk associated with

use of marijuana versus cocaine, heroin, and inhalant drugs, if danger and risk are evaluated based on evidence

about adverse health consequences. However, if danger and risk refer to the likelihood of apprehension by 

the criminal justice agencies and the adverse consequences of conviction and incarceration, it is possible that

younger children’s appraisals have some factual basis.

48
Drug Use in the General Population

49

Table 5. NHSDA Sample Sizes and U. S. Civilian Noninstitutionalized Population Totals, 

by Sex and Age Across Race/Ethnicity for Age 12 and Older: 1998

White, Non-Hispanic Black, Non-Hispanic Hispanic Other

Population Population Population Population

Sex and Age Sample Estimate Sample Estimate Sample Estimate Sample Estimate

(in thousands) (in thousands) (in thousands) (in thousands)

Sex

Male 5,303 78,312 2,339 11,139 3,043 11,325 576 4,421Female 6,406 83,680 3,476 13,636 3,752 11,017 605 4,914

Age

12–17 years 3,091 15,209 1,374 3,243 1,869 3,108 444 1,18018–25 years 2,926 18,753 1,798 3,927 2,187 3,910 407 1,37626–34 years 1,890 23,786 1,053 4,360 1,432 4,672 162 1,78435+ years 3,802 104,243 1,590 13,245 1,307 10,652 168 4,995

Total 11,709 161,991 5,815 24,775 6,795 22,342 1,181 9,336

SOURCE: National Household Survey on Drug Abuse, Substance Abuse and Mental Health Services Administration, Office of Applied Studies, 1998 public use dataset, 2000a.
Drug Use in the General Population

50

Table 6. Estimated Prevalence of Use of Selected Drugs Among Persons 

Age 12 and Older in the United States: 1998

Ever Used Used in Past Month

Population Population

Drug Percent Estimate Percent Estimate 

(in thousands) (in thousands)

Any illegal drug use 35.8 78,123 6.2 13,615

Marijuana 33.0 72,070 5.0 11,016

Hallucinogens 9.9 21,607 0.7 1,514

Inhalants 5.8 12,589 0.3 713

Cocaine 10.6 23,089 0.8 1,750

Crack 2.0 4,476 0.2 437

Heroin 1.1 2,371 0.1 130

Nonmedical use of 

Stimulants 4.4 9,614 0.3 633

Sedatives 2.1 4,640 0.1 210

Tranquilizers 3.5 7,726 0.3 655

Analgesics 5.3 11,595 0.8 1,709

Alcohol 81.3 177,512 51.7 112,850

Cigarettes 69.7 152,313 27.7 60,406

SOURCE: National Household Survey on Drug Abuse, Substance Abuse and Mental Health Services Administration, Office of Applied

Studies, 1998 public use dataset, 2000a.

Table 7. Estimated Prevalence of Past-Month Drug Use in the United States, 

by Age and Sex (by percent): 1998

Age Group Sex

All Ages,

Drug 12–17 18–25 26–34 35+ Male Female Both Sexes

Any illegal drug 9.9 16.1 7.0 3.3 8.1 4.5 6.2

Marijuana 8.3 13.8 5.5 2.5 6.7 3.5 5.0

Cocaine 0.8 2.0 1.2 0.5 1.1 0.5 0.8

Alcohol 19.1 60.0 60.9 53.1 58.7 45.1 51.7

Heavy alcohol 2.9 13.4 6.9 4.2 9.3 2.3 5.7

Cigarettes 18.2 41.6 32.5 25.1 29.7 25.7 27.7

NOTE: Heavy alcohol use has been defined as “5 or more drinks on the same occasion on at least 5 or more days in the month prior to 

assessment,” in accord with the National Household Survey on Drug Abuse specifications on pp. 99 and 102 of source materials.

SOURCE: National Household Survey on Drug Abuse, Substance Abuse and Mental Health Services Administration, Office of Applied 

Studies, 1998 public use dataset, 2000a.
Drug Use in the General Population

51

Table 8. Estimated Prevalence of Past-Month Drug Use in the United States, 

by Age, Sex, and Race/Ethnicity (by percent): 1998

Age Group Sex

All Ages,

Drug 12–17 18–25 26–34 35+ Male Female Both Sexes

Any illicit drug

White, non-Hispanic 10.3 17.6 7.1 3.2 7.7 4.5 6.1

Black, non-Hispanic 9.9 17.1 9.4 4.8 12.0 5.2 8.2

American Indian/Alaska Native 16.3 24.9 15.5 6.0 16.6 5.4 9.3

Asian/Pacific Islander 5.2 7.3 2.8 0.7 3.7 1.8 2.8

Hispanic 9.9 11.1 5.4 3.5 7.7 4.5 6.1

Marijuana

White, non-Hispanic 8.7 14.9 5.7 2.5 6.5 3.6 5.0

Black, non-Hispanic 8.3 15.2 7.4 3.3 9.9 3.8 6.6

American Indian/Alaska Native 10.3 23.3 12.9 5.4 13.5 5.0 8.0

Asian/Pacific Islander 3.7 7.3 2.8 0.7 3.3 1.8 2.6

Hispanic 7.6 9.0 3.2 2.4 5.7 3.2 4.5

Cocaine

White, non-Hispanic 0.9 2.2 1.0 0.3 0.9 0.5 0.7

Black, non-Hispanic * 0.6 2.7 1.3 1.7 0.9 1.3

American Indian/Alaska Native 2.0 2.3 0.3 1.5 3.7 0.2 1.4

Asian/Pacific Islander * 0.3 * * 0.1 0.0 0.0

Hispanic 1.4 2.7 1.1 0.9 1.8 0.8 1.3

Alcohol

White, non-Hispanic 20.9 65.0 65.2 56.2 61.2 49.7 55.3

Black, non-Hispanic 13.1 50.3 54.8 38.3 49.0 32.3 39.8

American Indian/Alaska Native 32.1 67.4 50.7 40.9 69.1 29.2 43.3

Asian/Pacific Islander 10.5 44.0 37.5 36.7 39.9 29.2 34.5

Hispanic 18.9 50.8 53.1 47.7 56.8 33.6 45.4

Heavy alcohol**

White, non-Hispanic 3.4 16.7 7.1 4.2 9.3 2.5 6.0

Black, non-Hispanic 0.7 6.3 7.8 4.6 8.3 1.8 4.9

American Indian/Alaska Native 5.2 12.3 16.0 14.3 31.9 3.7 13.7

Asian/Pacific Islander 1.7 4.2 4.8 2.1 5.8 0.1 2.9

Hispanic 2.4 10.5 7.7 5.8 10.3 2.0 6.5

Tobacco cigarettes

White, non-Hispanic 20.5 46.9 34.1 24.1 28.9 26.9 27.9

Black, non-Hispanic 13.7 30.7 31.5 32.2 33.8 25.9 29.4

American Indian/Alaska Native 24.7 54.5 46.1 26.8 35.2 29.0 31.2

Asian/Pacific Islander 8.7 27.1 30.7 21.6 30.1 15.1 22.5

Hispanic 15.1 31.5 25.4 27.0 31.4 20.0 25.8

*Low precision, no estimate reported.

**Heavy alcohol use has been defined as “5 or more drinks on the same occasion on at least 5 or more days in the month prior to

assessment,” in accord with the National Household Survey on Drug Abuse specifications on pp. 99 and 102 of source materials.

SOURCE: National Household Survey on Drug Abuse, Substance Abuse and Mental Health Services Administration, Office of Applied

Studies, 1998 public use dataset, 2000a.
Drug Use in the General Population

52

Table 9. Estimated Prevalence of Past-Month Drug Use Among Hispanics in the United

States, by Age and Sex (by percent): NHSDA 1997 and 1998 Data Combined

Age Group Sex

All

Drug 12–17 18–25 26–34 35+ Male Female Persons

Any illegal drug

Hispanic 10.2 10.8 4.6 3.6 7.4 4.5 6.0

Puerto Rican 11.5 15.7 7.9 2.2 8.7 5.1 6.9

Mexican 9.9 10.4 4.2 4.1 7.5 4.8 6.2

Cuban 9.9 12.1 3.3 1.0 4.7 2.2 3.4

Central American 10.1 9.6 4.6 3.0 6.8 3.5 5.3

South American 16.5 1.8 * * 2.3 2.0 2.1

Other 8.1 10.7 7.7 7.8 11.9 5.7 8.2

Marijuana

Hispanic 8.0 8.4 2.8 2.3 5.4 3.1 4.3

Puerto Rican 10.7 14.6 4.6 1.4 6.8 4.4 5.6

Mexican 7.6 8.2 2.9 2.8 5.5 3.6 4.5

Cuban 6.5 7.9 2.9 0.3 3.5 0.9 2.1

Central American 8.0 5.0 1.5 2.3 5.2 1.0 3.2

South American 16.5 1.3 * * 2.1 2.0 2.1

Other 1.8 7.4 4.3 2.5 5.7 1.8 3.4

Cocaine

Hispanic 1.2 2.1 1.0 0.7 1.6 0.5 1.0

Puerto Rican 0.6 2.4 0.9 1.0 1.6 0.8 1.2

Mexican 1.2 2.2 1.0 0.7 1.8 0.4 1.1

Cuban 0.9 4.6 * * 1.0 0.1 0.5

Central American 1.0 0.9 0.7 0.6 0.9 0.5 0.7

South American 4.7 0.6 * * 0.2 1.2 0.6

Other 1.0 1.2 3.4 1.5 2.0 1.6 1.7

Alcohol

Hispanic 18.9 49.7 52.4 45.3 55.2 32.2 43.9

Puerto Rican 20.1 54.1 54.9 46.6 51.7 39.4 45.4

Mexican 18.7 47.7 52.6 44.8 56.1 29.6 43.2

Cuban 23.3 47.9 58.2 39.0 49.2 35.1 41.7

Central American 17.3 53.2 45.8 53.7 57.5 35.6 47.2

South American 23.9 66.5 62.0 38.6 56.4 32.8 46.0

Other 13.5 52.1 54.2 40.3 51.4 34.7 41.5

Heavy alcohol

Hispanic 3.1 9.5 7.0 5.7 10.4 2.1 6.3

Puerto Rican 2.4 11.9 5.4 6.1 8.6 4.3 6.4

Mexican 3.2 9.2 8.6 7.5 12.4 2.2 7.4

Cuban 2.8 4.6 4.5 0.3 3.0 0.6 1.7

Central American 2.5 10.7 4.4 2.1 6.6 1.2 4.1

South American 11.4 17.2 0.6 * 6.2 1.5 4.1

Other 0.9 3.3 * 4.5 7.9 0.1 3.2

(continued on next page)
Drug Use in the General Population

53

*Low precision, no estimate reported.

**Heavy alcohol use has been defined as “5 or more drinks on the same occasion on at least 5 or more days in the month prior to

assessment,” in accord with National Household Survey on Drug Abuse specifications on pp. 99 and 102 of source materials.

SOURCE: National Household Survey on Drug Abuse, Substance Abuse and Mental Health Services Administration, Office of

Applied Studies, 1997–1998 public use datasets, 1999a and 2000a.

Table 9 (continued). Estimated Prevalence of Past-Month Drug Use Among Hispanics in

the United States, by Age and Sex (by percent): NHSDA 1997 and 1998 Data Combined

Age Group Sex

All

Drug 12–17 18–25 26–34 35+ Male Female Persons

Tobacco cigarettes

Hispanic 15.5 31.2 27.0 27.9 31.9 21.1 26.6

Puerto Rican 18.4 35.9 32.1 35.6 33.4 31.7 32.5

Mexican 15.2 29.7 27.4 29.2 32.5 20.8 26.9

Cuban 12.6 28.1 24.1 20.4 26.7 16.1 21.1

Central American 14.5 37.5 21.7 20.4 28.3 16.3 22.6

South American 26.6 36.4 40.9 27.5 40.2 20.3 31.5

Other 10.9 24.0 21.5 22.4 30.4 15.0 21.3

Table 10. Estimated Percentage of Women of Childbearing Age (15–44) Using Drugs, 

by Age, Race/Ethnicity, and Population Density: 1998

Any Illicit Drug Marijuana Cocaine Cigarettes

Age Race/ Population

Ethnicity Density Lifetime Past Year Past Month Lifetime Past Year Past Month Lifetime Past Year Past Month Lifetime Past Year Past Month

All All Total U.S. 44.6 13.3 7.3 42.4 10.9 5.8 13.3 2.2 0.9 66.9 34.6 30.9

ages Groups Nonmetro 37.9 10.5 5.1 35.5 8.6 3.9 8.8 1.9 0.6 68.6 39.8 36.8

Metro 46.1 14.0 7.8 44.0 11.4 6.3 14.3 2.2 1.0 66.5 33.4 29.6

White, NH Total U.S. 51.2 14.2 7.6 49.3 11.7 6.2 15.8 2.4 0.9 73.8 37.8 33.7

Nonmetro 40.4 10.0 4.1 38.3 8.2 3.0 9.3 1.9 0.5 71.2 40.9 38.0

Metro 54.2 15.4 8.6 52.4 12.7 7.1 17.6 2.5 1.0 74.6 36.9 32.5

Black, NH Total U.S. 36.0 14.0 8.1 32.6 11.4 6.0 7.5 2.2 1.5 56.7 31.6 29.5

Nonmetro 25.4 9.9 6.6 21.3 7.0 4.5 4.0 1.6 1.0 58.3 33.7 31.3

Metro 37.9 14.7 8.4 34.7 12.2 6.3 8.1 2.4 1.7 56.4 31.2 29.2

Hispanic Total U.S. 26.2 10.4 6.1 22.8 8.0 4.5 8.3 1.6 0.9 49.7 25.2 21.3

Nonmetro 28.0 14.1 10.5 24.2 12.9 9.7 7.7 2.4 1.6 56.1 37.0 33.3

Metro 26.0 10.0 5.6 22.6 7.4 3.9 8.4 1.5 0.8 49.0 23.9 19.9

Others Total U.S. 20.2 6.4 3.0 19.7 5.2 2.9 6.2 0.2 0.1 38.5 21.2 19.9

Nonmetro 36.1 20.6 16.6 35.0 19.4 15.5 17.7 0.9 0.5 59.1 37.2 31.7

Metro 18.7 5.0 1.8 18.2 3.9 1.7 5.2 0.1 0.1 36.5 19.7 18.8

15–24 All Total U.S. 37.8 23.2 13.0 35.2 21.2 11.4 7.0 3.7 1.5 59.4 40.3 33.8

Groups Nonmetro 30.7 17.0 9.0 28.7 14.9 7.3 5.0 2.7 1.4 64.3 45.5 39.6

Metro 40.0 24.9 14.1 37.0 23.0 12.6 7.6 4.0 1.6 58.0 38.8 32.2

White, NH Total U.S. 42.5 26.3 14.4 40.5 24.3 12.9 8.6 4.6 1.8 67.2 47.6 40.2

Nonmetro 32.8 17.3 8.5 31.0 15.3 7.0 5.4 2.6 1.1 68.6 50.0 43.8

Metro 46.0 29.4 16.4 43.9 27.4 15.0 9.7 5.3 2.0 66.8 46.8 39.0

(continued on next page)
Drug Use in the General Population

54

Table 10 (continued). Estimated Percentage of Women of Childbearing Age (15–44)

Using Drugs, by Age, Race/Ethnicity, and Population Density: 1998

Any Illicit Drug Marijuana Cocaine Cigarettes

Age Race/ Population

Ethnicity Density Lifetime Past Year Past Month Lifetime Past Year Past Month Lifetime Past Year Past Month Lifetime Past Year Past Month

15–24 Black, NH Total U.S. 30.2 19.4 11.9 26.2 17.6 10.1 1.0 0.5 0.4 42.3 24.7 21.1

Nonmetro 20.4 14.9 11.6 16.4 11.5 7.6 1.3 1.3 1.3 49.6 24.3 20.9

Metro 31.9 20.1 12.0 27.9 18.6 10.6 0.9 0.4 0.2 41.1 24.8 21.2

Hispanic Total U.S. 30.3 17.7 10.3 26.0 15.0 8.0 7.9 3.7 2.1 47.2 27.5 21.5

Nonmetro 28.1 21.8 13.9 24.6 19.6 12.5 7.7 5.8 4.3 47.6 31.9 27.0

Metro 30.5 17.2 9.9 26.2 14.4 7.4 7.9 3.4 1.8 47.1 26.9 20.8

Others Total U.S. 15.4 7.6 4.6 14.2 7.2 4.3 1.2 0.6 0.3 36.8 22.1 18.4

Nonmetro 17.8 5.7 3.0 17.3 4.9 2.0 1.7 1.4 0.6 39.9 30.0 20.5

Metro 15.0 8.0 4.9 13.6 7.7 4.7 1.1 0.5 0.3 36.2 20.5 18.0

25–29 All groups Total U.S. 42.3 9.1 3.6 40.2 7.1 2.9 9.5 1.3 0.5 63.9 34.9 31.1

Nonmetro 34.0 3.5 1.8 31.8 3.1 1.5 7.9 0.3 * 61.7 30.6 29.4

Metro 44.1 10.3 4.0 42.1 7.9 3.2 9.9 1.5 0.6 64.4 35.8 31.5

White, NH Total U.S. 50.3 8.8 2.9 48.3 7.0 2.6 10.5 1.0 0.1 72.8 40.8 36.5

Nonmetro 37.1 2.2 0.7 34.8 2.0 0.7 8.2 0.2 * 65.3 31.1 30.6

Metro 54.0 10.7 3.6 52.2 8.4 3.1 11.1 1.3 0.1 74.9 43.5 38.2

Black, NH Total U.S. 38.6 14.4 7.7 35.5 10.8 5.7 7.0 3.2 2.2 57.8 27.0 24.4

Nonmetro 20.1 6.2 5.7 19.1 5.2 4.7 0.5 * * 56.6 41.0 33.9

Metro 41.1 15.5 7.9 37.7 11.6 5.8 7.9 3.7 2.5 58.0 25.2 23.1

Hispanic Total U.S. 21.3 7.0 3.5 19.1 4.6 1.9 8.6 1.1 0.4 43.7 21.8 18.0

Nonmetro 8.1 4.0 2.8 6.1 1.9 0.7 5.8 1.9 * 29.7 9.6 8.3

Metro 22.6 7.3 3.6 20.5 4.9 2.1 8.9 1.1 0.5 45.1 23.0 19.0

Others Total U.S. 14.4 4.6 1.9 14.0 4.3 1.8 7.9 0.1 0.1 30.4 21.2 20.9

Nonmetro 61.2 35.2 20.8 59.7 33.8 19.3 33.6 0.7 0.7 61.5 39.4 39.4

Metro 10.4 2.0 0.3 10.2 1.8 0.3 5.7 * * 27.8 19.7 19.4

30–44 All groups Total U.S. 49.2 8.9 5.1 47.2 6.2 3.5 18.0 1.5 0.8 72.0 31.3 29.2

Nonmetro 44.2 8.0 3.3 41.5 5.9 2.2 11.8 1.8 0.3 73.6 38.6 37.1

Metro 50.2 9.1 5.5 48.4 6.2 3.7 19.3 1.4 0.9 71.6 29.8 27.5

White, NH Total U.S. 56.0 9.2 5.4 54.2 6.4 3.6 20.9 1.5 0.7 77.5 31.9 29.5

Nonmetro 46.7 7.3 2.1 44.4 5.1 0.9 12.3 1.9 0.2 74.8 37.6 36.2

Metro 58.2 9.7 6.2 56.6 6.7 4.3 23.0 1.4 0.8 78.2 30.4 27.9

Black, NH Total U.S. 39.1 10.0 5.5 36.2 7.3 3.2 12.3 3.1 2.1 66.4 38.1 37.3

Nonmetro 29.8 7.8 3.8 24.9 4.7 2.6 6.5 2.1 1.1 63.9 37.5 36.8

Metro 41.0 10.4 5.9 38.5 7.8 3.4 13.5 3.3 2.3 66.9 38.3 37.4

Hispanic Total U.S. 25.2 6.5 4.1 21.9 4.3 3.1 8.5 0.3 0.3 53.9 25.0 22.4

Nonmetro 35.1 11.7 10.8 30.5 11.7 10.8 8.4 * * 72.4 50.9 47.4

Metro 24.1 6.0 3.4 20.9 3.4 2.2 8.5 0.4 0.3 51.8 22.1 19.6

Others Total U.S. 25.1 6.3 2.6 25.0 4.4 2.5 8.7 * * 42.4 20.7 20.5

Nonmetro 57.7 41.7 41.3 55.4 40.1 40.1 40.1 * * 96.1 50.3 49.7

Metro 23.5 4.5 0.6 23.5 2.7 0.6 7.1 * * 39.8 19.2 19.1

*Low precision, no estimate reported.

NH: Non-Hispanic.

SOURCE: National Household Survey on Drug Abuse, Substance Abuse and Mental Health Services Administration, Office of Applied

Studies, 1998 public use dataset, 2000a.
Drug Use in the General Population

55

Race/Ethnicity 1993 1994 1995 1996 1997 1998 1999

Race of mother*

African-American

American Indian/Alaska Native

Asian/Pacific Islander

Chinese

Filipino

Hawaiian and part-Hawaiian

Japanese

Other Asian/Pacific Islander

White

Hispanic origin of mother

Hispanic origin

Cuban

Central and South American

Mexican American

Other and unknown Hispanic

Puerto Rican

African American, non-Hispanic

White, non-Hispanic

Total

Table 11. Estimated Percentage of Live-Born Infants’ Mothers Who Reported Smoking

During Pregnancy, by Year and Race/Ethnicity, U.S. Final Natality Statistics: 1993–1999

12.7

21.6

4.3

1.1

4.3

17.2

6.7

3.2

16.8

5.0

5.0

2.3

3.7

9.3

11.2

12.7

18.6

15.8

11.4

21.0

3.6

0.9

3.7

16.0

5.4

2.9

15.6

4.6

4.8

1.8

3.4

8.1

10.9

11.5

17.7

14.6

10.6

20.9

3.4

0.8

3.4

15.9

5.2

2.9

15.0

4.3

4.1

1.8

3.1

8.2

10.4

10.6

17.1

13.9

10.2

21.3

3.3

0.7

3.5

15.3

4.8

2.7

14.7

4.3

4.7

1.8

3.1

9.1

11.0

10.3

16.9

13.6

9.7

20.8

3.2

1.0

3.4

15.8

4.7

2.5

14.3

4.1

4.2

1.8

2.9

8.5

11.0

9.8

16.5

13.2

9.5

20.2

3.1

0.8

3.3

16.8

4.8

2.4

14.0

4.0

3.7

1.5

2.8

8.0

10.7

9.6

16.2

12.9

9.3

20.2

2.9

0.5

3.3

14.7

4.5

2.3

13.6

3.7

3.3

1.4

2.6

7.7

10.5

9.4

15.9

12.6

*Includes data for 46 States and the District of Columbia in 1993–1999. Excludes data for California, Indiana, New York (but includes 

New York City), and South Dakota, which did not report tobacco use on the birth certificate.

SOURCES: National Center for Health Statistics, 2000; Ventura et al., 1998–2001.
Drug Use in the General Population

56

Table 12. Estimated Percentage of Respondents Who Believe That Selected Drugs 

Are Easy to Get for Themselves (Youth and Teens) and by Their Children (Parents), 

by Race/Ethnicity: 1997–2000

Drug and White Black Hispanic

Respondent 1997 1998 1999 2000 1997 1998 1999 2000 1997 1998 1999 2000

Marijuana

Youtha 19 13 9 N/A 16 10 13 N/A 21 15 18 N/A

Teensb 60 57 54 54 59 59 57 55 60 56 56 56

Parentsb 27 22 34 25 33 36 42 31 22 34 21 20

Cocaine

Youtha 14 7 7 N/A 10 7 8 N/A 14 9 14 N/A

Crack

Youthb 14 9 8 N/A 10 9 8 N/A 13 12 15 N/A

Cocaine/Crack

Parentsb 17 7 16 9 26 26 28 20 14 25 14 13

a

Easy

b

Very easy

N/A: Not available. As of 2000, youth target is no longer surveyed.

SOURCE: Partnership Attitude Tracking Study, Partnership for a Drug-Free America, 2001.

Drug and White Black Hispanic

Respondent 1997 1998 1999 2000 1997 1998 1999 2000 1997 1998 1999 2000

Marijuana

Youth 80 76 84 N/A 76 76 74 N/A 75 82 73 N/A

Teens 60 61 60 62 58 60 59 59 56 58 56 55

Parents 72 63 63 61 75 64 66 60 71 82 70 67

Cocaine

Youth 82 80 83 N/A 80 79 78 N/A 77 82 73 N/A

Crack

Youth 76 72 79 N/A 80 78 74 N/A 66 75 69 N/A

Cocaine/Crack

Teens 88 87 85 86 74 79 75 77 78 77 79 77

Parents 95 89 92 91 90 86 82 89 88 95 84 79

Inhalants

Youth 61 58 55 N/A 55 54 50 N/A 55 50 51 N/A

Heroin

Youth 58 59 58 N/A 54 51 45 N/A 54 53 46 N/A

Table 13. Estimated Percentage of Respondents Who Associate Danger/Great Risk 

With the Use of Selected Drugs, by Race/Ethnicity: 1997–2000

N/A: Not available. As of 2000, youth target is no longer surveyed.

SOURCE: Partnership Attitude Tracking Study, Partnership for a Drug-Free America, 2001.
Drug Use in the General Population

57

Table 14. Estimated Percentage of Respondents Who Agree With Selected Statements

About Specific Drugs, by Race/Ethnicity: 1997–2000

a

Agree a lot.

b

Agree strongly.

c

Agree a lot/agree a little.

d

Agree strongly/agree somewhat.

N/A: Not available. As of 2000, youth target is no longer surveyed.

SOURCE: Partnership Attitude Tracking Study, Partnership for a Drug-Free America, 2001.

White Black Hispanic

Respondent 1997 1998 1999 2000 1997 1998 1999 2000 1997 1998 1999 2000

Taking drugs scares respondent.

Youtha 68 70 81 N/A 73 73 75 N/A 59 70 75 N/A

Teensb 31 29 33 34 44 40 42 38 33 31 28 27

Smoking marijuana is okay sometimes.

Youthc 13 12 11 N/A 21 13 20 N/A 29 16 19 N/A

Teensd 19 15 14 15 17 17 13 14 18 16 13 17

Parentsd 24 27 24 35 20 24 19 20 17 16 16 14

If parents use marijuana, their children are likely to use marijuana.

Parentsd 75 70 72 72 56 61 67 55 71 74 79 70

It’s really hard to give my child reasons not to use marijuana.

Parentsd 20 14 15 17 18 21 25 19 28 22 36 13

Don’t want to hang around people who use drugs.

Youtha 72 75 84 N/A 70 72 78 N/A 66 70 75 N/A

Teensb 33 28 34 33 44 28 42 41 30 26 30 28

It’s okay to sell drugs to make money.

Youthc 6 5 N/A N/A 10 9 N/A N/A 14 9 N/A N/A

Teensd 21 19 17 17 31 31 26 27 27 25 24 24

59

This chapter presents data on drug use among minority youth, including age at first use; prevalence of lifetime,

past-month, and past-year use; and longitudinal trends in prevalence of drug use. It also includes a special section

on drug use among American Indian youth. As described in Chapter 3, the lifetime prevalence estimates convey

“cumulative occurrence” of drug taking within the survey population, answering such questions as, “What 

proportion of the population has become an illegal drug user?” In comparison, the past-month estimates answer

questions such as, “What proportion has been a recently active illegal drug user?”, with recently active use

defined in terms of the 1-month interval up to and including the day of the assessment.

The most extensive surveys of drug use among U.S. adolescents have been completed as part of the National

Household Survey on Drug Abuse (NHSDA), described in Chapters 1 and 3, and as part of the Monitoring

the Future (MTF) study sponsored by the National Institute on Drug Abuse (NIDA), already described in

Chapter 1. These surveys provide some of the best data available for prevalence estimates of drug use among

young people in this country. Each surveillance tool has its own strengths and limitations. For example, in theory,

the NHSDA sample encompasses truants and dropouts, who are included within the population definition but

may be missing from the sampling frame. By comparison, dropouts are not included in the population definition

for the MTF study, which samples schools, classrooms within schools, and students within classrooms. Truants

are included within the population definition for the MTF study, but they may not be present on the day or

days of classroom assessment via self-report standardized questionnaire. Also contained in this chapter are data

from the Youth Risk Behavior Survey (YRBS), the National Longitudinal Survey of Youth (NLSY), and surveys

of American Indian/Alaska Native students and dropouts, which have been conducted by the Colorado State

University Tri-Ethnic Center for Prevention Research. Each of these studies has the strengths and limitations

noted with the NHSDA and the MTF investigations.

Recent estimates for the age-specific incidence of various drugs help shed new light on recent trends in drug

taking among youth in the United States. For example, based on a retrospective method for modeling past and

recent risk of starting to use marijuana, the NHSDA research team has estimated that the risk of starting to

smoke marijuana increased sharply during the 1960s. For youth ages 12–17 in 1965, the estimated risk of

becoming a new marijuana smoker in that year was just under 1 percent. By 1969–1970, the risk for this age

group had increased to about 3.3 to 4.9 percent per year. Thereafter, there were sustained increases in the risk

of starting to smoke marijuana from 1970 onward, with peak values of about 8 percent per year during the last

few years of the 1970s. Subsequently, the rate dropped to 4.3 to 4.5 percent per year for youth ages 12–17 in

the early 1990s—a reduced level not seen since the late 1960s. During the 1990s, these risk estimates again

increased, with the risk among this group about 8.8 percent in 1996. The 1996 risk estimate is larger than any

other value estimated in the series, and it was followed by risk estimates of 8.5 to 8.7 percent per year in 1997

and 1998 (Substance Abuse and Mental Health Administration 2001a).

Although these estimates are subject to the limitations of the NHSDA data and the retrospective method for

risk estimation, these are the best available epidemiological estimates for risk of becoming a marijuana smoker

in the United States. In addition, recent MTF estimates for the cumulative occurrence (lifetime prevalence) of

cocaine use among 8th-, 10th-, and 12th-graders also show increases between 1995 and 1998 (Johnston et al.

2001). The observation that youth ages 12–17 now may be experiencing record high levels of risk for becoming

marijuana smokers deserves our attention. It is possible that the retrospective method overstates the risk in the

most recent years of any given series. Nevertheless, even if the estimate is off by 10 percent or even 25 percent,

Chapter 4. PREVALENCE OF DRUG USE AMONG YOUTH
Prevalence of Drug Use Among Youth

substantial risk exists for becoming a marijuana smoker during adolescence, with levels of risk corresponding to

values estimated for the United States during the military conflict and war in Vietnam.

The same analytical procedures have been applied to the NHSDA data on cocaine, with similar provocative

results. For example, for youth ages 12–17 alive in the mid-1970s who participated in subsequent NHSDA

assessments, the risk of becoming a new user of cocaine is estimated to have been about 5 to 6 new users 

per 1,000 youths per year (Substance Abuse and Mental Health Administration 2001a). Peak levels of risk for

becoming a cocaine user during these adolescent years were observed between 1977 and 1989, with estimated

values between 7 and 11 new cocaine users per 1,000 youths per year, followed by a trough year of 4 to 5 new

users per 1,000 youths in 1991. During the 1990s, the estimated risk values have been increasing and now are

above 10 per 1,000 youths per year (i.e., 1 percent per year). For example, the risk estimate for 1997 is 13 new

cocaine users per 1,000 youths ages 12–17, and the risk of becoming a new cocaine user in 1998 is estimated as

14 per 1,000 per year (i.e., 1.4 percent per year). This apparent return to levels of risk last seen during the 

epidemic of the 1980s poses a challenge for new epidemiological investigation. If the estimation procedure is

valid, it is conveying information that signals a need for renewed public health action oriented toward cocaine.

Marijuana and cocaine are not the only two drugs showing recent increases in risk of initiation. For example,

in 1998, the estimated number of new users of hallucinogens among youth ages 12–17 is just over 650,000,

corresponding with an estimated risk of 2 to 3 percent per year. This estimate is four to five times greater than

the corresponding risk estimate for the “flower power” years of the late 1960s, and the risk level has doubled

since the late 1980s. Risk estimates for becoming a new illegal user of stimulant drugs in adolescence now are

at about one-half the level of risk of becoming a new user of hallucinogens (Substance Abuse and Mental Health

Administration 2001a).

These risk estimates convey values that were developed for the entire U.S. population and may not hold for all

subgroups within the population. For example, Gfroerer and Brodsky (1992) used NHSDA data and a similar

analysis methodology to estimate the risk of becoming a new cocaine user between 1976 and 1989, producing

separate estimates for non-Hispanic Whites, non-Hispanic Blacks, and Hispanics in the United States, already

presented in Figure 4 in Chapter 3. As depicted in that figure, Gfroerer and Brodsky (1992) observed that, for

Whites, the number of new initiates reached a peak in the early 1980s, while the number of new Black and

Hispanic initiates did not peak until later in the 1980s. Hence, the national epidemic of cocaine use in the

United States really may be subdivided into different experiences, with an earlier epidemic trend and peak for

White Americans and a later peak for Blacks and Hispanic Americans.

Because initiation of illegal drug use, alcohol, and tobacco smoking tends to occur during adolescence, NHSDA

and the MTF study assume crucial importance as we seek to monitor and understand the drug experience of

the U.S. population (Kandel and Logan 1984; Wagner and Anthony 2002; Substance Abuse and Mental Health

Administration 2001a). From a social and public health perspective, it also is important to monitor the trends

and patterns of drug use among youth because of links with other problem behaviors, including deviant and

delinquent activities (e.g., vandalism and starting fights), maladaptation within the family and in school, truancy,

and school dropout. For many youth, drug use becomes part of a more general clustering or syndrome of 

maladaptive behavior that involves conduct problems, failure at school, precocious sexual activity, unsafe sex and

other unhealthy behaviors, and affiliation with other deviant and other drug-using peers (e.g., see Jessor 1998) 

60
Prevalence of Drug Use Among Youth

AGE AT FIRST USE

A great many drug users begin using drugs before age 14 and almost all illegal drug use starts before age 35.

NHSDA estimates for the average (mean) age at first use of tobacco cigarettes, alcohol, marijuana, and cocaine

for adolescents ages 12–17 during selected years between 1991 and 1998 are presented in Table 15. Trends in

the average age of first use were similar across all racial/ethnic groups examined. Although the estimates fluctuate,

year-to-year variation in age at first use for these drugs has been relatively modest.

Comparison of age of first use by type of drug indicates average age at initiation for tobacco cigarettes rose 

modestly from 1991 to 1998 for all race/ethnicity groups shown in the table. For example, among White youth,

the mean age for starting to smoke tobacco cigarettes was estimated as 11.4 years old in 1991 and as 12.3 in

1998. Corresponding values for Black youth are 11.3 and 12.8; for Hispanic youth, the estimates are 12.0 and

12.7 (Table 15).

The mean age at first use of alcohol and the mean age for first use of marijuana showed relative stability and no

more than modest increases over this period for all race/ethnicity groups under study (Table 15). To some

extent, this stability is a function of studying a broad age range (ages 12–17) over short intervals (e.g., 1 to 2

year intervals). The populations of youth under study overlap considerably. For example, a 12-year-old in 1992

becomes a 13-year-old in 1993 and remains eligible for inclusion in the population as a 17-year-old in 1997.

This degree of continuity in the birth cohorts represented in each year of the survey tends to yield a relatively

stable estimate for the mean age of initiation of drug use, even when individual respondents are excluded from

participation in successive years of the survey.

The mean age of cocaine use has been relatively stable during the 1990s. However, coupled with the abovementioned increased risk of starting to use cocaine during the late 1990s, the slight decline in mean age of first

cocaine use for 1997 and 1998 may represent more than a random fluctuation around a grand mean. If the risk

estimates are correct for youth ages 12–17, there may be an actual trend toward declining mean age of first

cocaine use. This recent trend of declining mean age of first cocaine use has been described for the total

NHSDA survey population in its most recent series of reports (e.g., see Substance Abuse and Mental Health

Administration 2001a). 

The observed mean age of 13 years for Black adolescents in 1998 represents a sharp drop and may be a signal

of a changing dynamic of cocaine use in this population, when considered against a backdrop of relatively stable

estimates between values of age 14.0 in 1991 and age 14.3 in 1997. New values from more recent NHSDA data

will be needed to evaluate this possible trend, but public use datasets for NHSDA 1999 and 2000 are not

expected to be available until late 2002 or 2003.

PREVALENCE TRENDS

This section presents prevalence trends for estimated cumulative and recent occurrence of illegal drug use, alcohol

use, and tobacco cigarette smoking among minority youth. Data are for secondary school students, American

Indian/Alaska Native youth, and youth ages 12–21.

School-Attending Youth

The MTF Study, funded by NIDA, is a nationally representative cross-sectional sample survey of schoolattending youth in the United States, administered to 8th-, 10th-, and 12th-graders, with longitudinal followup

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Prevalence of Drug Use Among Youth

of subsamples as these students progress into the college years and young adulthood. One of the major purposes

of the survey is to develop an accurate picture of drug use and related attitudes and behaviors among youth

(Johnston and O’Malley 1997; Johnston et al. 2001). Data presented in this report are from the MTF crosssectional surveys only.

Examination of racial/ethnic variations in MTF estimates for 2000, presented on the first page of Table 16, tend

to indicate that Hispanic 8th-graders are more likely to have started using marijuana, inhalants, LSD, other 

hallucinogens, and cocaine than are 8th-grade non-Hispanic Whites or Blacks (Table 16, first page). Among

12th-graders, Hispanic students are more likely to have started to use marijuana and cocaine, but the excess

cumulative occurrence of use is not observed for inhalants, LSD, or other hallucinogens. As depicted in the last

row of page one of Table 16, there is a slight tendency for Hispanic students to be more likely to be daily 

marijuana users, but the numerical excess is seen only for 8th-graders and 12th-graders, and these estimates may

be too imprecise for definitive interpretation.

Consistent with findings from NHSDA, as reported in Chapter 3, the MTF estimates for Black students show

generally lower values for all drugs except marijuana. For example, Black students are less likely to have become

cocaine users (“lifetime prevalence”), to have used in the year leading up to and including the date of the 

survey (“annual prevalence”), and to have used in the month leading up to and including the date of the survey

(“30-day prevalence”). By comparison, Black and White students have roughly comparable estimates for prevalence of marijuana use, whether the focus is on the lifetime experience (23.8 percent versus 19 percent among

8th-graders), the past year (16.1 percent versus 14.9 percent among 8th-graders), the past month (9.3 percent

versus 8.4 percent among 8th-graders), or daily use (1.0 percent versus 1.2 percent among 8th-graders), as

depicted in the first column of Table 16. Where differences emerge between the racial/ethnic groups for 

marijuana, the largest values tend to be observed for Hispanic students and the smallest for Black students.

With inhalant drug use, White and Hispanic students tend to have generally comparable prevalence estimates;

Black students have comparatively lower prevalence estimates. For example, among 8th-graders, an estimated

19.9 percent of Whites, 23.1 percent of Hispanics, and only 10.5 percent of Black students have tried inhalant

drugs. The same general pattern is seen for inhalant drug use among the 10th- and 12th-graders (Table 16, 

first page, columns 4–6). A similar pattern is seen for LSD and other hallucinogenic drugs, with Whites 

and Hispanics having larger and more similar values, and with Black students tending to have lower values

(Table 16, first page, columns 7–12).

Scanning across the lifetime or cumulative occurrence estimates for the different grade levels for each drug, there

is a tendency for the estimates to increase across grades 8 to 10 to 12. To some extent, the same is true for the

estimates of recently active drug use (i.e., use in the month prior to survey). An important exception is the

inhalant drug use group, which remains relatively stable from grade to grade, perhaps because inhalant drug use

in 8th grade is associated with dropping out of school or more frequent truancy by 12th grade. That is, students

who start to use inhalant drugs in high school may be especially more likely to drop out or to be truant than

other students in Grades 10 and 12; this association would contribute to a relative stability in the grade-specific

estimates for inhalant drug use.

Table 16 (second page) reports MTF estimates on crack-cocaine, cocaine other than crack, heroin, other opioid

drugs (e.g., morphine, codeine), and stimulant drugs. Here again, evidence exists of greater prevalence among

Hispanic and White youth for use of crack-cocaine and other heroin, and to some extent for heroin and other

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Prevalence of Drug Use Among Youth

opioids, and stimulants; Black students have lower values at virtually every grade level. By grade 12, stimulants

become more prevalent among White than Hispanic students. Of note, an estimated 18.2 percent of White

12th-graders have tried stimulants at least once; the corresponding estimates for Blacks and Hispanics in 12th

grade are 4.9 percent and 15.1 percent, respectively.

Table 16 (third page) conveys the same general pattern. However, for barbiturate drugs (sleep preparations and

calmatives) and for tranquilizers, White 12th-graders tend to have larger prevalence estimates than Hispanic

youth, and Black seniors have the lowest prevalence values of the three groups. Prevalence estimates for Whites

and Hispanics are more similar for alcohol, for having been drunk, and for drinking five or more drinks on an

occasion (sometimes called “binge drinking”). For example, an estimated two-thirds of White and Hispanic 

seniors have been drunk at least once in their lifetimes. By comparison, the corresponding value for Black 

seniors is 40.9 percent. One hypothesis about this finding is that Black students who get heavily involved with

alcohol or other drugs are more likely than White and Hispanic students to drop out of school or become 

truant. However, the lower prevalence values also are seen for 8th-graders when truancy and dropout have

started to occur, but are less prominent as a cause of school absence on the day of a school survey. Until there

is evidence that drug-associated truancy and dropout problems exert a differentially greater influence on Black

8th-graders than on other 8th-graders, the observed lower prevalence of drug use among Black students merits

careful evaluation. Protective or resiliency conditions and processes among Black adolescents can be identified,

and it may be able to harness the evidence in prevention and intervention programs tailored specifically to this

important minority population, especially if the programs also can retain Black students through graduation

(Crum and Anthony 2000).

Data on daily tobacco cigarette use indicate that among 12th-graders, an estimated 25.7 percent of Whites

smoke daily, compared with 15.7 percent of Hispanic seniors and 8.0 percent of Black seniors (Table 16, fourth

page). The origins of the greater prevalence of daily smoking among White and Hispanic seniors may be seen

in the cumulative occurrence or lifetime prevalence estimates in the first row and first column of Table 16

(fourth page). For example, between 8th and 12th grade, a stronger association between race/ethnicity and risk

of starting to smoke tobacco emerges, with greater increases as we look from grade to grade for Whites and

Hispanics—among seniors, two-thirds of these students have started to smoke. In contrast, the risk of starting

to smoke apparently remains at lower levels for Black students, with occurrence of tobacco smoking remaining

below 50 percent even in 12th grade.

Smokeless tobacco use is most prevalent among White students, with Hispanics in an intermediate position.

Again, Black students are least likely to use this drug. An estimated 4.3 percent of White students have become

daily smokeless tobacco users by 12th grade. Corresponding estimates for Hispanic and Black seniors are below

1 percent.

By comparison, the pattern for steroid use follows that seen for other drugs, with both Whites and Hispanics

sharing higher prevalence values (e.g., lifetime prevalence of 2.8 percent to 3.4 percent among 12th graders).

Blacks are substantially less likely to have started to use steroids (1.3 percent by 12th grade).

Long span trend estimates for occurrence of drug use among high-school seniors are shown in Figures 5–9,

with distinctions between non-Hispanic Whites and Blacks, Hispanics, and a “Total” category. These long span

trend estimates are not available for 8th- and 10th-graders because MTF surveys of those grades did not start

until 1991.

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Prevalence of Drug Use Among Youth

The long span trend data help sustain some of the general impressions gained from the numerical estimates 

presented in Table 16. For example, the generally lower prevalence values for Black seniors were present in the

earliest MTF surveys during the 1970s and have been sustained to the present. Indeed, for trends in prevalence

of daily tobacco cigarette smoking, the separation between Whites and Blacks has increased. In the late 1970s,

Hispanic seniors were less likely to have become and remained daily tobacco smokers, but in the early 1980s,

the curve crossed when daily smoking became more common among Hispanics than Whites (Figure 5). 

To some extent, these long span trend data on daily tobacco smoking are congruent with recent reports from

the Surgeon General’s office, which have noted that cigarette smoking prevalence increased in the 1990s among

African American and Hispanic youth after some years of substantial decline (U.S. Department of Health and

Human Services 1998). This increase, the report states, “is particularly striking among African American youth,

who had the greatest decline of the four groups during the 1970s and 1980s” (p. 6). The prevalence of cigarette

smoking among African American adolescents in the 1980s and 1990s has been lower than the prevalence

among any other racial/ethnic group (see Table 17). Also of note in the MTF data is that American

Indian/Alaska Native 12th-graders had the highest prevalence of tobacco cigarette smoking between 1976 and

1994, whereas Asian Americans/Pacific Islanders had the second lowest prevalence rates (Table 17). Data from

the Youth Risk Behavior Surveillance System (YRBSS) of the Centers for Disease Control and Prevention

(CDC) show similar patterns for the long decline of prevalence of cigarette smoking with recent increases

among African Americans compared with other racial/ethnic groups; similar patterns are evident with the other

minority groups mentioned above (data not shown in a table). 

Figure 6 shows generally parallel trends for Whites, Hispanics, and Blacks. However, for many years between

the late 1970s and the late 1980s, White seniors were more likely than Hispanic seniors to have become and

remained marijuana users. This situation changed in the early 1990s, with generally comparable prevalence

estimates for Whites and Hispanics during the last decade of the 20th century. By 1999, the marijuana prevalence estimates for Hispanics had become numerically larger than the estimates for non-Hispanic Whites, but

the observed estimates actually are not appreciably different from one another.

Figure 7 offers an interesting epidemiological puzzle. First, the observed low prevalence values for inhalant drug

use among Black seniors deserves scrutiny until we understand why inhalant drug use has not taken hold in this

segment of the U.S. population. Second, Hispanic seniors started with inhalant prevalence estimates lower than

those of non-Hispanic Whites in the late 1970s; however, during the intervening years, they lost and regained,

then again lost and regained the advantage associated with lower inhalant prevalence values. The size of the

observed differences between Whites and Hispanics generally is too great to explain as a manifestation of imprecision in the estimates. Some other explanation is needed.

To some extent, the trend data on prevalence of recently active cocaine use reflect the epidemiological experience

described above, with earlier peaks in the cocaine epidemic affecting non-Hispanic Whites and later peaks for

non-Hispanic Blacks and Hispanics. In the most recent years of the MTF data series, there are signs of increasing

prevalence of cocaine use among the two minority group populations of seniors, but these signs are not present

for non-Hispanic White seniors (Figure 8). These estimates do not contradict the NHSDA risk estimates for

cocaine in recent years. Whereas the NHSDA research team has completed analyses to focus attention on a 

possibly increasing risk of starting to use cocaine in recent years, the MTF estimates shown in Figure 8 are for

occurrence of recently active cocaine use (i.e., not for risk of becoming a cocaine user, but for probability of

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Prevalence of Drug Use Among Youth

using cocaine in the recent past). This distinction between risk of becoming a drug user and probability of being

a drug user is a crucial distinction in drug dependence epidemiology (e.g., see Anthony and Helzer 1995).

Figure 9 depicts the estimated probability of being an LSD user and shows a now-familiar pattern of relatively

low prevalence estimates for non-Hispanic Black seniors. There were unstable fluctuations in the prevalence estimates for Hispanic seniors in the late 1970s and early 1980s. Since then, non-Hispanic White seniors have been

more likely to use LSD than their Hispanic counterparts. However, evidence exists of increasing comparability

of the prevalence estimates for non-Hispanic White seniors and Hispanic seniors during the last years of the

20th century.

Figure 10 summarizes the prevalence of any illegal drug use among high-school seniors from 1977 through

2000, with estimates showing that the probability of being an illegal drug user is least likely for Black seniors.

Hispanic seniors, for a time, were less likely than non-Hispanic White seniors to be illegal drug users, but this

difference between non-Hispanic Whites and Hispanics disappeared in the early 1990s, for reasons that remain

unknown and understudied.

Data on trends in drug use for 8th- and 12th-graders are presented in Table 18, with separate estimates for boys

and girls and for racial/ethnic minority status. The prevalence of tobacco cigarette smoking among 12th-graders

fluctuated throughout the 1980–2000 survey period for females, increased since the early 1990s for males and

for Whites, and first declined and then increased for Blacks. Among 8th-graders, there is some evidence of a

possibly promising decline (or random fluctuation) in the final years of the 20th century.

Values for prevalence of marijuana use presented in Table 18 show the previously mentioned increases during

1990s. Fluctuations observed between 1998 and 2000 are so small as to be uninterpretable. It is of interest that,

among 8th-graders, both males and females and Whites and Blacks have prevalence estimates of about 14 to 

17 percent in 2000, versus corresponding values of roughly 14 to 20 percent in 1996. By comparison, among

12th-graders in 2000, the estimates are almost double these values and fall in a range of 30 to 40 percent.

Though subject to attrition (e.g., due to dropping out of school), the 8th-graders of 1996 became the 

12th-graders of 2000, and in the process the prevalence of marijuana use more than doubled for each group

except females. The estimate for female 8th-graders in 1996 was 16.9 percent and among female seniors in 

2000 had risen to 33.4 percent (Table 18).

Estimates for prevalence of being a student cocaine user shown in Table 18 do not reflect the previously mentioned apparent recent increases in risk of becoming a cocaine user among noninstitutionalized U.S. residents

ages 12–17. The observed variation in the MTF cocaine prevalence estimates over the past several years is rather

small, relative to fluctuations over the prior span of more than a decade. Whereas the senior class of 2000 had

marijuana prevalence values double between 1996 (when they were 8th-graders) and the time of the MTF 

survey in their senior year, the magnitude of cocaine use was somewhat smaller and substantially less than a 

doubling for Blacks in the graduating class of 2000. This process may reflect greater attrition of cocaine-using

Blacks during high school, but we have no definitive evidence on this research issue.

Some promising trend data on prevalence of inhalant drug use may be seen in Table 18 (second page). From

1996 to 2000, inhalant prevalence estimates generally declined for males and females and for Whites. The

inhalant prevalence estimates for Blacks are quite low, which makes detection of declining trends quite difficult.

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Prevalence of Drug Use Among Youth

Table 18 reveals no recent striking increases nor decreases in prevalence of alcohol use. The pattern for so-called

“binge drinking” (five or more drinks on a single occasion) also is quite stable in recent years.

MTF data have also been analyzed to explore possible interactions between tobacco smoking among African

American and White youth and use of alcohol and other drugs. Table 19 shows that between 1976 and 1994,

the percentage of African-American 12th-graders who did not use tobacco cigarettes or illegal drugs in the previous month was higher than for White 12th-graders and increased more rapidly in every category of drug use.

Trends in the use of tobacco cigarettes, alcohol, and other substances among 12th-graders indicate that among

smokers and nonsmokers, African Americans were generally less likely than Whites to use drugs other than

tobacco cigarettes. Furthermore, concurrent use of tobacco cigarettes and other illegal drugs was lower and

showed greater declines for African-American 12th-graders than for White 12th-graders between 1976 and 1994.

CDC’s ongoing YRBSS, mentioned earlier in this chapter, monitors health risk behaviors among youth and

young adults, including their use of alcohol, tobacco, and other drugs. YRBSS includes a national school-based

survey conducted by CDC, in addition to surveys conducted by individual State and local education agencies.

Estimates from the 1999 YRBSS are presented in Table 20, with values for individual drugs and separate estimates

for boys and girls, race/ethnicity groups, and age groups. With use of alcoholic beverages and several other

drugs, the pattern from the YRBSS prevalence data resembles the pattern from the MTF data, with Whites and

Hispanics most often having the higher prevalence estimates and Blacks having lower prevalence values. For

example, among male students 18 and older, the estimated cumulative occurrence of alcohol use in their lifetime is close to 90 percent for Whites and Hispanics and close to 70 percent for Blacks. A similar pattern also

is seen for cocaine among male and female older students. Here also, we see that prevalence of cocaine use is

lower for Black students than for Whites and Hispanics, both males and females, at each of the three age levels.

The pattern is somewhat different for marijuana, with roughly equivalent estimates for Whites and Blacks

among the older students, but with a male-female difference in prevalence of use (Table 20). For example, the

prevalence estimates for cumulative occurrence of marijuana use are 65 to 66 percent for White males and Black

males, but are 51 to 52 percent for White and Black females. The corresponding estimate for Hispanic males is

about 60 percent (lower than the values for the other males) and for Hispanic females it is 53 percent (roughly

comparable to the values for the other females).

Male-female differences are present for virtually all of the drugs considered in Table 20, except in the estimates

for recently active alcohol use and for recently active cocaine use among the oldest students. For recently active

alcohol use among these students, there is a modest male-female difference for Whites, essentially no difference

for Blacks, and a male excess for Hispanics. For recently active cocaine use, there is a modest male-female 

difference for Whites, a possible female excess for Blacks, and a male excess for Hispanics. As discussed above

in relation to the MTF studies, it is possible that cocaine use is more prominent as a determinant of dropping

out of high school for Blacks than for other racial/ethnic groups. Cocaine use also may be more prominent as

a determinant of school dropout for Black male students than for female Black students. 

American Indian/Alaska Native Students

Since 1975, the Colorado State University Tri-Ethnic Center for Prevention Research, with support from NIDA

grant awards has conducted an ongoing survey of American Indian/Alaska Native students in grades 7–12

enrolled in Indian reservation schools. Results from the 1975 through 1997–1998 school year surveys are 

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Prevalence of Drug Use Among Youth

provided in Tables 21–23. In addition, estimates from more recently conducted surveys and a substudy of

American Indian/Alaska Native school dropouts have been incorporated into these tables.

Although prevalence estimates for drug use have tended to be larger for American Indian/Alaska Native youth

on reservations than for non-Indian youth, the general trends in both groups have been parallel over the last 

several decades. A pattern of large increases in the late 1970s, a leveling off in the 1980s, and modest declines

in the 1990s has emerged for both American Indian and non-Indian youth. However, among non-Indian 

adolescents, there has been a general trend of increasing drug use, especially marijuana use, since 1992 (National

Institute on Drug Abuse 1998). During the mid-1990s, it appeared that American Indian/Alaska Native youth

on reservations might be spared this general trend, but more recent data suggest otherwise.

For example, as shown in Table 21, there has been a declining trend in the proportion of reservation American

Indian/Alaska Native youth who have started drinking alcohol (Table 21, row 1). However, the value of 

69-percent prevalence for marijuana use, observed during the 1996–1998 surveys, suggests a possible increasing

trend seen in marijuana use, in tandem with the previously mentioned increasing trend in general population

statistics.

Cumulative occurrence for many drugs in this survey showed peak values in 1980–1981 with subsequent

declines through the mid-1990s. An exception to this pattern was for use of psychedelics, which showed

increases from the early 1980s to the early 1990s and has remained relatively high, with prevalence estimates in

a range from 19 to 22 percent since 1991–1992.

As with other school-based surveys, drug use information from this survey of American Indians/Alaska Natives

is affected by school dropouts, and it is acknowledged that dropouts as a group may have more social and adaptational problems, including problems associated with drug use. Estimates for reservation-dwelling American

Indians/Alaska Natives suggest especially large school dropout rates. Although these dropout estimates are sparse

and highly variable, Beauvais et al. (1995) developed a method to correct the drug use prevalence estimates by

taking into account a 50-percent school dropout rate. The estimates in the last column of Table 21 include an

attempted correction for the drug use of school dropouts. To strengthen these estimates, Tri-Ethnic Center

investigators, including Beauvais, surveyed a sample of American Indian high-school dropouts. Their drug 

use experiences were assessed, and the results of this assessment have been weighted into a correction for the

prevalence estimates from the 1992–1994 surveys. As seen in comparing the last column of Table 21 with the

third-to-last column, the net effect of this correction for school dropouts is generally an increase in the estimated

prevalence values.

Table 22 compares estimates from the survey of reservation-schooled American Indian/Alaska Native students

with corresponding estimates from the MTF surveys for 1997–1998. Alcohol and marijuana show a somewhat

similar pattern across the grades under study. In 8th and 10th grade, the American Indian/Alaska Native youth

have larger prevalence estimates for drinking alcoholic beverages and alcohol intoxication than the non-Indian

youth surveyed in the MTF study, but in 12th grade the estimates for American Indian/Alaska Native and 

non-Indian seniors are roughly comparable. For virtually all of the other drugs considered, cumulative occurrence

(“lifetime prevalence”) was greater for American Indian/Alaska Native youth than for their non-Indian student

counterparts in the MTF survey. For example, an estimated two-thirds of the American Indian/Alaska Native

youths had started to smoke marijuana when they were surveyed in 8th grade; the values for 10th-graders and

12th-graders are 82 percent and 74 percent, respectively. The corresponding marijuana estimates for non-Indian

students are 23 percent, 42 percent, and 50 percent.

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Prevalence of Drug Use Among Youth

The comparison for inhalant drugs may challenge a preconception about glue or gasoline sniffing on the reservations. For example, among 8th-graders, non-Indian students are more likely than Indian students to have

started using inhalant drugs (21 percent versus 14 percent), and the same is the case for 10th-graders. It is only

in 12th grade that the American Indian/Alaska Native students are more likely that the non-Indian students to

have started using inhalant drugs (16 percent for Indian youth, 10 percent for non-Indian youth).

The cocaine experience of the American Indian/Alaska Native students also may challenge preconceptions. In

1997–1998, an estimated 20 percent of the reservation-dwelling students had tried cocaine, whereas only 9 percent

of the non-Indian seniors had done so. Similar differences are present in the estimates for cocaine use among

8th- and 10th-graders.

Striking differences also appear for both tobacco cigarettes and smokeless tobacco. In 8th grade, an estimated 

79 percent of American Indian/Alaska Native youth had started to smoke tobacco, compared with 47 percent of

non-Indian students. In 12th grade, an estimated 75 percent of the American Indian/Alaska Native seniors had

started to smoke tobacco, compared with 65 percent of non-Indian seniors. The pattern for smokeless tobacco

is comparable, with about 45 percent of the American Indian/Alaska Native 8th-graders having started to use

smokeless tobacco. By comparison, estimated cumulative occurrence for non-Indian students is only 17 percent.

Table 23 presents time trends in estimated cumulative occurrence of drug use among American Indian/Alaska

Native 4th- and 6th-graders. In 1980–1981, an estimated one-third of these students had tried alcohol. A sharp

decline occurred between 1981 and 1987, with no more than modest declines to 17 percent through 1994,

when the last survey of these grades was completed. The epidemiological pattern for marijuana is somewhat 

different, with sustained declines from 23 percent in 1980–1981 to 7 percent in 1992–1994. By comparison,

there has been little change in the estimates for use of inhalant drugs or tobacco cigarettes among students in

grades 4–6.

LONGITUDINAL TRENDS

Table 24 presents estimates on drug use for a cohort of young adults participating in NLSY (Bureau of Labor

Statistics 1996). To control for potential attrition effects, only those respondents remaining in the 1994 sample

were used for the analysis of all 4 years. Additionally, calculation of estimates for cumulative occurrence of 

drug use during the lifetime of these youths was achieved by summing the drug use reported for each of the 

survey years.

The table shows the estimated proportion of NLSY participants who had started to use marijuana in their lifetimes, as well as prevalence estimates for more recent intervals, for non-Hispanic Whites, non-Hispanic Blacks,

and “Other” race/ethnicity groups. Between 1984 and 1994, the study population generally exhibited declines

in estimated 1-year prevalence of marijuana use (i.e., use in the year up to and including the date of assessment).

Between 1992 and 1994, some evidence emerges of increasing prevalence of marijuana use among nonHispanic African Americans. Prevalence of recently active marijuana use (use in the month before assessment)

tended to decline over the interval.

By studying the successive reports of individuals in the longitudinal sample, it was possible to ascertain that most

of the participants in the sample had started to use marijuana before or during 1984. For example, an estimated

66.5 percent of non-Hispanic White members of the study population had started marijuana use by the time

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Prevalence of Drug Use Among Youth

of the assessment in 1984. Reassessed in 1994, an estimated 77.9 percent had started marijuana use. Roughly

14 percent of the marijuana users identified in 1994 had started since 1984, and the remainder had started in

1984 or before.

Table 24 also presents corresponding estimates for cocaine use. The estimated proportion using cocaine showed

declines for non-Hispanic Whites for the 1984–1992 period but a modest increase from 1992 to 1994. Among

African-American youth, there were increases in prevalence of cocaine use to 1988, a modest decline in 1992,

and a modest increase in 1994. Estimated cumulative occurrence of cocaine use doubled between 1984 and

1994 for non-Hispanic Whites and “Other” groups and tripled for non-Hispanic Blacks.

SUMMARY

Estimates from NHSDA help clarify that the risks of starting illegal drug use, alcohol use, and tobacco cigarette

smoking are concentrated during the adolescent and young adult years. NHSDA estimates provide new information about the risks of starting to use each drug of interest during adolescence. The most recent evidence

indicates recent increases in risk of starting to use these drugs, with risk estimates as large or larger than have

ever been experienced since the 1960s—possibly with larger values than ever before in U.S. history.

The risk of starting illegal drug use and the probability of being an illegal drug user have not been constant over

the time spans examined in this chapter. The ebb and flow of the estimates reminds us that drug-taking behavior

represents a dynamic phenomenon. We appear to be entering a period of increased risk for youthful drug 

taking, with increasing numbers of new initiates for several different drugs during the last years of the 

20th century. One of the emerging trends involves initiation of LSD and other hallucinogen use (e.g., ecstasy).

If confirmed, these findings have important implications as plans are laid for prevention and intervention activities. In addition to validating the NHSDA risk estimation methodology, it will be important to study these

recent risk estimates for racial and ethnic minority groups. This chapter’s NHSDA estimates for becoming a

new illegal drug user are for the total population of civilian noninstitutionalized adolescents ages 12–17 in the

United States and are dominated by the experiences of non-Hispanic White adolescents. If we generalize from

epidemiological patterns for incidence of cocaine use between 1975 and 1990, as depicted in Figure 4, the

observed recent increases in risk of starting illegal drug use during adolescence may now be limited to nonHispanic White adolescents. If there is to be a new increase in risk of illegal drug use for the adolescent

racial/ethnic minority population groups in the United States, there may be a lag of several years before that

increase can be perceived in the national-level NHSDA statistics.

MTF estimates clarify changing epidemiological patterns in the prevalence of drug use among students, with

estimates for Hispanics substantially increasing and decreasing since the late 1970s, relative to estimates for nonHispanic Whites. Nonetheless, the most recent estimates indicate that non-Hispanic Whites and Hispanics

often have larger prevalence estimates, with non-Hispanic Blacks having lower prevalence estimates for many

illegally used drugs, alcohol, and tobacco.

Comparisons of drug use data for 8th-graders versus recent high-school seniors indicate dramatic increases 

during the school years, even when some drug users drop out of school and are surveyed in 12th grade. By 8th

grade, many students already have started to use alcohol, tobacco, and other illegal drugs, and between 8th and

12th grade, the prevalence of use often doubles or almost doubles. These increases are seen for each of the

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Prevalence of Drug Use Among Youth

racial/ethnic groups under study, despite almost certain associations between use of these drugs, truancy and

other forms of school absenteeism, and dropping out of school.

Epidemiological studies of American Indian/Alaska Native youths in reservation schools have been completed

in parallel with the MTF studies for the entire Nation. These American Indian/Alaska Native surveys highlight

two epidemiological features. First, this racial/ethnic group may be at especially increased risk of drug involvement, and there is special concern that early drug use may be associated with dropping out of school. Second,

trends in drug use among American Indian/Alaska Native students tend to be responsive to the broader influences

on trends in drug use for the rest of adolescent society in the United States. The trends for this minority group

may lag somewhat behind the more general trends. Nonetheless, the general impression is one of parallel or

slightly lagged trends, and for many drugs, an excess prevalence of use among the American Indians/Alaska

Natives who attend schools on reservations. When the American Indian/Alaska Native estimates are analyzed

with a method to correct for school dropout, the prevalence estimates become larger after the correction.

During the first half of the 21st century, changing demographic, social, economic, and family circumstances are

likely to have profound influences on the epidemiological patterns of drug experiences of young people in the

United States. The social and family circumstances of African-American youth changed markedly during the

last half of the 20th century, young African Americans disproportionately exhibit sustained troubling patterns

of arrest for drug-related crimes, conviction, and incarceration. Over the next several decades, social and family

circumstances for young Hispanics will change dramatically, while Hispanic Americans become increasingly

numerous and prominent within our Nation’s minority populations. If recent trends continue, contrasts

between the “haves” and the “have nots” will be more prominent and will affect all population groups, including

these racial/ethnic minority groups. If we are to understand the drug experiences of young people, and the links

between illegal drug use and health disparities affecting racial/ethnic minorities, it will be important to improve

our epidemiological surveillance operations for the methodological and measurement issues mentioned in this

chapter and in Chapter 3. It also will be important to sustain and strengthen research projects with specific, 

targeted research aims intended to probe these linkages in more detail than can be achieved via analyses of 

epidemiology’s surveillance data.

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Prevalence of Drug Use Among Youth

71

Table 15. Estimated Average Age of First Use of Cigarettes, Alcohol, and Marijuana for

Youth Ages 12–17, by Race/Ethnicity: Selected Years

Drug and Race/Ethnicity of Student 1991 1993 1995 1996 1997 1998

Cigarettes

White, non-Hispanic 11.4 11.8 12.2 12.3 12.3 12.3

Black, non-Hispanic 11.3 11.8 12.7 12.6 12.8 12.8

Hispanic 12.0 12.0 12.8 12.8 12.7 12.7

Alcohol

White, non-Hispanic 12.6 12.9 12.8 13.1 13.1 13.1

Black, non-Hispanic 12.9 13.2 13.1 13.2 13.0 13.1

Hispanic 12.8 13.0 13.1 13.3 13.0 13.2

Marijuana

White, non-Hispanic 14.4 13.9 13.8 14.0 13.8 13.8

Black, non-Hispanic 13.7 14.0 14.1 14.0 13.8 13.8

Hispanic 13.1 13.7 13.9 13.6 13.5 13.5

Cocaine

White, non-Hispanic 14.3 14.6 14.6 14.7 14.8 14.7

Black, non-Hispanic 14.0 14.5 * 14.3 14.3 13.0

Hispanic 14.4 14.3 14.3 14.9 14.8 14.3

*Low precision, no estimate reported.

SOURCE: National Household Survey on Drug Abuse, Substance Abuse and Mental Health Service Administration, Office of Applied

Studies, selected years.
Prevalence of Drug Use Among Youth

72

Table 16. Estimated Prevalence of Lifetime, Annual, 30-Day, and Daily Use of Selected Drugs, 

by Race/Ethnicity for Students in Grades 8, 10, and 12 (by percent): 2000*

(continued on next page)

Estimated Marijuana Inhalants Hallucinogens LSD Cocaine Crack-cocainePrevalence 8th 10th 12th 8th 10th 12th 8th 10th 12th 8th 10th 12th 8th 10th 12th 8th 10th 12thLifetimeWhite, non-Hispanic 19.0 40.1 49.4 19.9 18.5 16.7 4.9 10.5 14.9 4.2 9.1 13.2 4.2 7.4 9.9 2.8 3.7 4.4Black, non-Hispanic 23.8 39.5 45.7 10.5 6.6 4.6 1.3 1.4 2.1 0.9 1.2 1.7 1.4 1.2 1.9 0.9 0.9 0.8Hispanic 27.1 46.0 55.0 23.1 17.6 15.4 6.8 8.6 15.3 5.8 7.6 13.1 8.9 12.4 13.3 5.6 6.8 6.3AnnualWhite, non-Hispanic 14.9 32.6 38.2 10.9 8.4 6.4 3.1 7.6 9.9 2.6 6.5 8.3 2.5 4.7 6.2 1.7 2.2 2.5Black, non-Hispanic 16.1 27.6 30.0 4.3 2.0 1.9 0.7 1.0 1.6 0.5 0.9 1.3 0.8 0.6 1.0 0.4 0.5 0.5Hispanic 20.1 34.8 40.5 12.2 6.3 6.3 4.0 5.2 9.6 3.5 4.6 7.6 4.7 8.0 7.6 2.9 4.0 3.430-dayWhite, non-Hispanic 8.4 20.2 22.7 5.2 2.9 2.1 1.2 2.9 3.2 1.0 2.2 2.3 1.1 1.8 2.5 0.8 0.8 1.0Black, non-Hispanic 9.3 15.8 19.0 2.3 1.1 1.3 0.5 0.5 0.9 0.3 0.5 0.8 0.4 0.3 0.8 0.2 0.3 0.4Hispanic 12.7 20.5 24.6 5.6 2.3 3.1 2.0 2.0 3.8 1.7 1.6 2.4 2.7 3.0 3.6 1.5 1.4 2.1DailyWhite, non-Hispanic 1.2 4.0 6.0 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/ABlack, non-Hispanic 1.0 3.2 4.6 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/AHispanic 1.9 3.2 6.9 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A
Prevalence of Drug Use Among Youth

73

Table 16 (continued). Estimated Prevalence of Lifetime, Annual, 30-Day, and Daily Use of Selected Drugs, 

by Race/Ethnicity for Students in Grades 8, 10, and 12 (by percent): 2000* 

Estimated Other Cocaine Heroin Other Opiates Stimulants Barbiturates TranquilizersPrevalence 8th 10th 12th 8th 10th 12th 8th 10th 12th 8th 10th 12th 8th 10th 12th 8th 10th 12thLifetimeWhite, non-Hispanic 3.3 6.5 9.0 1.9 2.4 2.4 N/A N/A 12.4 11.8 18.2 18.2 N/A N/A 10.3 4.7 9.2 10.6Black, non-Hispanic 1.0 1.0 1.9 0.8 0.7 0.5 N/A N/A 2.8 4.4 5.1 4.9 N/A N/A 2.4 1.5 1.9 1.5Hispanic 7.4 11.1 11.0 3.4 2.3 3.1 N/A N/A 8.1 11.4 13.4 15.1 N/A N/A 8.1 6.8 6.5 8.5AnnualWhite, non-Hispanic 1.9 4.1 5.7 1.2 1.5 1.3 N/A N/A 8.3 8 12.7 11.9 N/A N/A 6.9 3 6.4 6.9Black, non-Hispanic 0.6 0.5 1.0 0.5 0.5 0.5 N/A N/A 1.7 2.4 2.5 2.6 N/A N/A 1.3 0.5 1.1 0.7Hispanic 3.9 7.1 6.6 2.0 1.4 2.0 N/A N/A 4.6 6.8 9.1 9.2 N/A N/A 5.1 3.5 4.0 4.330-dayWhite, non-Hispanic 0.8 1.5 2.3 0.5 0.6 0.6 N/A N/A 3.3 4 6.1 5.3 N/A N/A 3.2 1.4 2.7 3Black, non-Hispanic 0.3 0.3 0.7 0.4 0.2 0.5 N/A N/A 0.7 1.3 1.4 1.2 N/A N/A 0.8 0.3 0.5 0.4Hispanic 2.3 2.7 2.9 0.8 0.6 1.2 N/A N/A 1.7 3.1 4.2 4.5 N/A N/A 2.2 1.7 1.8 2.1DailyWhite, non-Hispanic N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/ABlack, non-Hispanic N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/AHispanic N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A

(continued on next page)
Prevalence of Drug Use Among Youth

74

*To derive percentages for each racial subgroup, data for the specified year and the previous year have been combined to increase sample sizes and thus provide more stable estimates.N/A: Not available.SOURCE: Monitoring the Future Study, University of Michigan, 2000; Johnson et al., 2001d.

Table 16 (continued). Estimated Prevalence of Lifetime, Annual, 30-Day, and Daily Use of Selected Drugs, 

by Race/Ethnicity for Students in Grades 8, 10, and 12 (by percent): 2000* 

Estimated Alcohol Been Drunk 5+ Drinks Cigarettes Smokeless Tobacco Steroids

Prevalence 8th 10th 12th 8th 10th 12th 8th 10th 12th 8th 10th 12th 8th 10th 12th 8th 10th 12th

LifetimeWhite, non-Hispanic 52.1 72.8 82.0 26.3 53.3 66.5 N/A N/A N/A 42.6 58.4 67.2 16.2 23.0 29.7 3.1 3.1 2.8Black, non-Hispanic 47.7 61.2 70.3 18.0 29.9 40.9 N/A N/A N/A 39.8 45.4 45.5 8.0 7.8 5.2 1.7 2.3 1.3Hispanic 57.7 74.1 84.3 27.7 48.1 67.3 N/A N/A N/A 45.7 57.6 66.1 9.9 13.4 11.5 3.0 3.1 3.4AnnualWhite, non-Hispanic 45.1 67.7 76.7 20.4 46.2 58.1 N/A N/A N/A N/A N/A N/A N/A N/A N/A 1.9 2.1 1.8Black, non-Hispanic 33.0 49.0 58.8 10.6 19.6 27.2 N/A N/A N/A N/A N/A N/A N/A N/A N/A 0.7 1.2 1.0Hispanic 48.5 65.9 76.0 19.3 37.7 53.1 N/A N/A N/A N/A N/A N/A N/A N/A N/A 1.8 1.8 2.430-dayWhite, non-Hispanic 24.7 43.9 55.1 10 26.7 37 N/A N/A N/A 17.7 28.2 37.9 5.2 7.5 10.5 0.8 0.9 0.8Black, non-Hispanic 16 24.7 30 4.7 8.6 14.9 N/A N/A N/A 9.6 11.1 14.3 2.7 2.0 1.5 0.4 0.7 0.4Hispanic 26.7 40.5 51.2 8.5 18.0 29.8 N/A N/A N/A 16.6 19.6 27.7 3.7 4.5 3.8 0.9 1.0 1.5DailyWhite, non-Hispanic 0.8 1.8 3.3 N/A N/A N/A 14.9 28.1 34.6 9.0 17.7 25.7 0.8 1.7 4.3 N/A N/A N/ABlack, non-Hispanic 0.5 1.1 1.4 N/A N/A N/A 10.0 12.9 11.5 3.2 5.2 8.0 0.4 0.2 0.1 N/A N/A N/AHispanic 1.1 2.0 5.0 N/A N/A N/A 19.1 28.3 31.0 7.1 8.8 15.7 0.6 0.7 0.9 N/A N/A N/A
Prevalence of Drug Use Among Youth

75

Table 17. Trends in the Estimated Percentage of 12th-Graders Who Were 

Previous-Month Smokers, by Race/Ethnicity and Gender: 1976–1999

12th-Grade Smokers 1976–79 1980–84 1985–89 1990–94 1995–99

Males

African-American 33.1 19.4 15.6 11.6 19.3

American Indian/Alaska Native 50.3 39.5 36.8 41.1 42.3

Asian/Pacific Islander 20.7 21.5 16.8 20.6 25.5

Hispanic 30.3 23.8 23.3 28.5 28.8

White 35.0 27.5 29.8 33.4 39.7

Females

African-American 33.6 22.8 13.3 8.6 10.8

American Indian/Alaska Native 55.3 50.0 43.6 39.4 51.7

Asian/Pacific Islander 24.4 16.0 14.3 13.8 17.5

Hispanic 31.4 25.1 20.6 19.2 24.4

White 39.1 34.2 34.0 33.1 39.5

SOURCE: Bachman et al., 2001; Institute for Social Research, University of Michigan, unpublished data.
Prevalence of Drug Use Among Youth

76

Table 18. Estimated Prevalence of Use of Selected Substances in the Past Year,

Cigarette Use in the Past 30 Days, and Binge Drinking in the Past 2 Weeks Among 

12th-Graders and 8th-Graders, by Sex and Race/Ethnicity (by percent): Selected Years

(continued on next page)

Use by Drug Type 1980 1985 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

Cigarettes

All 12th-graders 30.5 30.1 29.4 28.3 27.8 29.9 31.2 33.5 34.0 36.5 35.1 34.6 31.4

Male 26.8 28.2 29.1 29.0 29.2 30.7 32.9 34.5 34.9 37.3 36.3 35.4 32.8

Female 33.4 31.4 29.2 27.5 26.1 28.7 29.2 32.0 32.4 35.2 33.3 33.5 29.7

White 33.0 31.3 32.3 32.2 31.8 33.2 35.2 36.6 38.1 40.7 41.7 40.1 37.9

Black 26.8 18.1 12.2 10.6 8.7 9.5 10.9 12.9 14.2 14.3 14.9 14.9 14.3

All 8th-graders N/A N/A N/A 14.3 15.5 16.7 18.6 19.1 21.0 19.4 19.1 17.5 14.6

Male N/A N/A N/A 15.5 14.9 17.2 19.3 18.8 20.6 19.1 18.0 16.7 14.3

Female N/A N/A N/A 13.1 15.9 16.3 17.9 19.0 21.1 19.5 19.8 17.7 14.7

White N/A N/A N/A N/A 16.2 17.8 18.9 20.7 22.7 22.8 21.5 20.1 17.7

Black N/A N/A N/A N/A 5.3 6.6 8.7 8.9 9.6 10.9 10.6 10.7 9.6

Marijuana

All 12th-graders 48.8 40.6 27.0 23.9 21.9 26.0 30.7 34.7 35.8 38.5 37.5 37.8 36.5

Male 53.4 43.1 29.4 27.2 24.4 29.0 35.1 38.1 39.4 40.9 41.7 41.4 39.2

Female 44.1 37.8 24.2 20.1 18.9 22.4 26.4 30.6 31.6 35.5 33.0 34.1 33.4

White 51.2 41.6 31.6 28.2 24.9 25.9 30.2 34.2 36.4 38.7 39.9 39.1 38.2

Black 37.9 33.4 13.7 11.4 11.5 14.2 20.7 26.8 30.2 30.4 30.0 30.4 30.0

All 8th-graders N/A N/A N/A 6.2 7.2 9.2 13.0 15.8 18.3 17.7 16.9 16.5 15.6

Male N/A N/A N/A 7.3 7.4 10.5 15.1 17.7 19.6 19.2 18.0 18.1 16.7

Female N/A N/A N/A 5.1 6.9 8.0 10.9 13.7 16.9 16.1 15.3 14.9 14.3

White N/A N/A N/A N/A 6.4 7.8 10.0 13.5 16.7 17.8 16.7 15.4 14.9

Black N/A N/A N/A N/A 4.1 5.7 8.9 11.9 14.0 15.3 16.0 16.3 16.1

Cocaine

All 12th-graders 12.3 13.1 5.3 3.5 3.1 3.3 3.6 4.0 4.9 5.5 5.7 6.2 5.0

Male 14.8 14.8 6.6 4.1 3.7 4.0 4.5 4.8 6.0 6.6 6.8 7.3 5.8

Female 9.8 11.2 3.8 2.6 2.4 2.3 2.8 3.1 3.5 4.2 4.5 5.0 3.9

White 12.8 13.0 6.3 4.6 3.3 3.1 3.5 4.0 4.5 5.5 6.3 6.7 6.2

Black 5.2 5.3 1.7 1.5 1.2 0.8 0.9 1.0 0.8 0.9 0.9 0.9 1.0

All 8th-graders N/A N/A N/A 1.1 1.5 1.7 2.1 2.6 3.0 2.8 3.1 2.7 2.6

Male N/A N/A N/A 1.4 1.5 1.9 2.1 2.5 2.7 3.1 2.9 2.8 2.6

Female N/A N/A N/A 0.9 1.5 1.5 2.1 2.6 3.1 2.5 3.1 2.7 2.6

White N/A N/A N/A N/A 1.2 1.3 1.6 2.3 2.8 3.0 2.8 2.6 2.5

Black N/A N/A N/A N/A 0.7 0.7 0.7 0.6 0.6 0.5 0.7 0.8 0.8
Prevalence of Drug Use Among Youth

77

Table 18 (continued). Estimated Prevalence of Use of Selected Substances in the Past

Year, Cigarette Use in the Past 30 Days, and Binge Drinking in the Past 2 Weeks Among

12th-Graders and 8th-Graders, by Sex and Race/Ethnicity (by percent): Selected Years

*To derive percentages for each racial subgroup, data for the specified year and the previous year have been combined to increase sample

sizes and thus provide more stable estimates.

N/A: Not available.

SOURCE: Monitoring the Future Study, University of Michigan; Johnston et al., 2001d.

Use by Drug Type 1980 1985 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

Inhalants

All 12th-graders 4.6 5.7 6.9 6.6 6.2 7.0 7.7 8.0 7.6 6.7 6.2 5.6 5.9

Male 5.9 6.9 8.8 8.2 8.0 9.2 9.6 9.9 9.1 8.3 7.5 6.5 6.8

Female 3.5 4.5 4.9 5.0 4.5 4.8 6.0 6.2 6.1 5.2 5.1 4.9 5.1

White 5.3 5.9 7.2 7.6 7.2 7.6 8.6 9.1 9.0 8.6 7.9 7.0 6.4

Black 2.2 2.0 2.1 2.7 2.5 2.2 2.4 2.6 2.2 1.9 1.7 1.4 1.9

All 8th-graders N/A N/A N/A 9.0 9.5 11.0 11.7 12.8 12.2 11.8 11.1 10.3 9.4

Male N/A N/A N/A 9.0 9.2 10.4 11.2 11.5 10.3 10.5 10.6 9.5 8.9

Female N/A N/A N/A 9.0 9.8 11.9 12.2 14.0 14.1 12.9 11.6 11.1 9.9

White N/A N/A N/A N/A 10.1 11.3 12.4 13.8 14.6 14.1 13.3 12.1 10.9

Black N/A N/A N/A N/A 4.4 4.6 5.3 5.0 4.2 3.8 4.2 4.2 4.3

Alcohol

All 12th-graders 72.0 65.9 57.1 54.0 51.3 48.6 50.1 51.3 50.8 52.7 52.0 51.0 50.0

Male 77.4 69.8 61.3 58.4 55.8 54.2 55.5 55.7 54.8 56.2 57.3 55.3 54.0

Female 66.8 62.1 52.3 49.0 46.8 43.4 45.2 47.0 46.9 48.9 46.9 46.8 46.1

White 75.4 71.2 63.8 60.0 56.8 55.6 54.0 54.5 54.8 56.4 57.7 56.3 55.1

Black 47.6 42.8 35.8 33.7 31.7 32.4 33.8 35.2 36.5 34.3 33.3 32.2 30.0

All 8th-graders N/A N/A N/A 25.1 26.1 24.3 25.5 24.6 26.2 24.5 23.0 24.0 22.4

Male N/A N/A N/A 26.3 26.3 25.3 26.5 25.0 26.6 25.2 24.0 24.8 22.5

Female N/A N/A N/A 23.8 25.9 23.7 24.7 24.0 25.8 23.9 21.9 23.3 22.0

White N/A N/A N/A N/A 26.6 27.1 25.3 25.4 26.6 26.7 24.8 24.7 24.7

Black N/A N/A N/A N/A 18.6 19.7 19.4 18.7 18.1 17.9 16.1 16.1 16.0

Binge drinking

All 12th graders 41.2 36.7 32.2 29.8 27.9 27.5 28.2 29.8 30.2 31.3 31.5 30.8 30.0

Male 52.1 45.3 39.1 37.8 35.6 34.6 37.0 36.9 37.0 37.9 39.2 38.1 36.7

Female 30.5 28.2 24.4 21.2 20.3 20.7 20.2 23.0 23.5 24.4 24.0 23.6 23.5

White 44.3 41.5 36.6 34.6 32.1 31.3 31.5 32.3 33.4 35.1 36.4 35.7 34.6

Black 17.7 15.7 14.4 11.7 11.3 12.6 14.4 14.9 15.3 13.4 12.3 12.3 11.5

All 8th-graders N/A N/A N/A 12.9 13.4 13.5 14.5 14.5 15.6 14.5 13.7 15.2 14.1

Male N/A N/A N/A 14.3 13.9 14.8 16.0 15.1 16.5 15.3 14.4 16.4 14.4

Female N/A N/A N/A 11.4 12.8 12.3 13.0 13.9 14.5 13.5 12.7 13.9 13.6

White N/A N/A N/A N/A 12.7 12.6 12.9 13.9 15.1 15.1 14.1 14.3 14.9

Black N/A N/A N/A N/A 9.6 10.7 11.8 10.8 10.4 9.8 9.0 9.9 10.0
Prevalence of Drug Use Among Youth

78

Table 19. Estimated Percentage of African-American and White 12th-Graders 

Who Reported Using or Not Using Tobacco Cigarettes and Other Substances in the 

Past 30 Daysa: 1976–1994 Aggregate Data

a

Refers to use of these substances in the last 30 days.

b

Entries are percentage of the entire African-American 12th-grade population.

c

Entries are percentage of the entire White 12th-grade population.

d

Any illicit drug use includes any use of marijuana, hallucinogens, cocaine, or heroine or any use of other opiates, stimulants, barbiturates,

methaqualone, or tranquilizers not under physician’s orders. Methaqualone is excluded from the definition of illicit drugs for 1990–94 survey data.

SOURCE: Monitoring the Future Study, University of Michigan, public use data tapes, 1976–1994; Johnston et al., 2001d.

Cigarette Use Among African Americans b

Use of 1976–79 1980–84 1985–89 1990–94

Substance Yes No Yes No Yes No Yes No

Alcohol

Yes 22.7 25.6 15.2 31.2 11.0 29.5 7.2 26.2

No 9.7 41.7 5.3 48.4 3.1 56.4 2.6 64.1

Marijuana

Yes 17.2 11.9 11.2 14.2 6.4 7.8 3.1 5.8

No 15.0 55.9 9.3 65.3 7.6 78.2 6.6 84.5

Cocaine

Yes 1.4 0.6 1.4 1.3 1.0 1.0 0.3 0.2

No 31.7 66.3 19.7 77.6 13.3 84.8 9.6 89.8

Any illicit drug usec

Yes 17.6 12.9 11.4 15.2 6.6 9.3 3.3 6.8

No 14.0 55.5 8.8 64.6 7.0 77.1 6.2 83.7

Cigarette Use Among Whitesc

Use of 1976–79 1980–84 1985–89 1990–94

Substance Yes No Yes No Yes No Yes No

Alcohol

Yes 33.7 40.5 28.2 46.0 28.6 40.9 27.5 29.7

No 3.3 22.4 2.7 23.1 3.6 26.8 5.7 37.1

Marijuana

Yes 22.4 13.7 16.9 12.8 14.4 8.1 11.8 4.4

No 14.3 49.6 13.8 56.5 17.5 60.0 21.3 62.5

Cocaine

Yes 2.6 1.1 3.5 2.0 3.4 1.1 1.2 0.2

No 34.3 62.0 27.3 67.2 28.5 66.6 31.9 66.7

Any illicit drug used

Yes 23.3 14.8 18.9 15.5 16.1 10.0 13.3 5.9

No 13.3 48.6 11.7 53.9 15.7 58.3 19.6 61.2
Prevalence of Drug Use Among Youth

79

Table 20. Estimated Prevalence of Youth Age 12 and Older Having Used Alcohol,

Marijuana, Cocaine, or Crack-Cocaine in Lifetime or Past Month, 

by Age, Sex, Race/Ethnicity (by percent): 1999

Use by Drug and Race/Ethnicity Male Female

12–15 16–17 18+ 12–15 16–17 18+

Use in Lifetime

Alcohol

White 77.7 81.6 90.7 77.2 83.8 89.2

Black 66.4 80.1 71.3 70.8 78.4 79.6

Hispanic 70.2 89.5 86.9 80.8 88.1 82.5

Marijuana

White 40.4 49.9 66.0 27.3 50.0 51.8

Black 39.9 63.7 65.1 30.7 49.0 51.2

Hispanic 41.1 65.3 59.6 36.9 51.4 53.1

Cocaine or crack-cocaine

White 6.4 12.6 15.5 4.6 10.8 11.8

Black 2.7 3.1 2.0 0.8 2.2 1.3

Hispanic 14.8 21.0 17.7 11.3 13.9 8.3

Use in Past Month

Alcohol

White 45.7 57.4 65.7 42.2 51.9 61.5

Black 22.7 49.5 49.5 35.0 42.2 50.3

Hispanic 43.6 61.8 70.0 45.7 51.6 50.0

Marijuana

White 24.2 31.4 35.1 19.1 24.9 24.7

Black 19.1 36.5 46.7 14.3 24.6 31.5

Hispanic 28.9 39.8 32.4 22.4 21.0 23.2

Cocaine or crack-cocaine

White 3.6 6.8 4.1 1.7 3.4 3.5

Black 0.8 1.3 0.8 0.5 1.6 1.3

Hispanic 7.0 9.0 7.0 6.9 4.9 3.5

SOURCE: Youth Risk Behavior Surveillance System, Centers for Disease Control and Prevention, 1999.
Prevalence of Drug Use Among Youth

80

1977–78 1980–81 1982–83 1984–85 1986–87 1988–89 1990–91 1992–93 1996–97 1992–94

Drug/Activity 1975 1978–79 1981–82 1983–84 1985–86 1987–88 1989–90 1991–92 1993–94 1997–98 Corrected

Alcohol 76 79 85 81 79 81 75 75 68 68 71Get drunk N/A N/A N/A N/A 46 49 55 62 51 52 55Marijuana 41 53 74 70 57 61 55 56 50 69 54Inhalants 16 26 30 31 21 24 24 25 21 15 25Cocaine 6 7 11 6 7 8 9 12 9 13 12Stimulants* 10 15 24 22 21 25 17 18 13 18 17Legal stimulants N/A N/A N/A N/A 14 15 13 15 14 18 12Sedatives* 6 10 9 7 10 11 7 6 4 5 5Heroin 3 4 5 2 5 5 4 3 3 4 4Psychedelics 7 9 9 6 9 10 13 22 19 21 21Tranquilizers* N/A 9 6 3 7 7 3 2 2 2 3PCP N/A N/A N/A N/A 10 10 7 3 3 5 6Cigarettes N/A N/A N/A N/A 79 78 71 74 71 76 73Smokeless tobacco N/A N/A N/A N/A N/A 58 56 52 45 39 43Sample size 1,235 3,105 2,159 1,411 1,510 2,683 5,300 1,710 2,096 1,848 2,096

*Only illicit or nonprescribed use is included.N/A: Not applicable.SOURCE: Tri-Ethnic Center for Prevention Research, Colorado State University, 2001, unpublished data.

Table 21. Estimated Percentage of American Indian 7th–12th Graders Living on Reservations 

Who Reported Lifetime Use of Drugs: 1975–1998
Prevalence of Drug Use Among Youth

81

Table 23. Estimated Percentage of American Indian 4th–6th Graders 

Who Reported Lifetime Use of Drugs: Selected Years

Drug 1980–81 1987–88 1989–90 1990–91 1992–94

Alcohol 33 22 21 18 17

Marijuana 23 16 10 8 7

Inhalants 14 14 15 12 10

Cigarettes 34 33 32 30 31

SOURCE: Tri-Ethnic Center for Prevention Research, Colorado State University, 1995, unpublished data.

Table 24. Estimated Percentage of National Longitudinal Survey of Youth Cohorts Who

Admitted Using Marijuana and Cocaine, by Race/Ethnicity and Year 

Drug by 1984 1988 1992 1994

Race/Ethnicity Lifetime Past Year Past Month Past Year Past Month Past Year Past Month Lifetime Past Year Past Month

Marijuana

White, non-Hispanic 66.5 33.8 19.5 23.3 12.7 14.1 8.3 77.9 12.8 5.4

Black, non-Hispanic 57.7 31.5 21.0 20.4 11.4 10.5 4.9 75.0 11.5 4.4

Other 53.8 29.5 17.5 16.0 9.0 11.2 6.9 68.9 9.5 4.7

Cocaine

White, non-Hispanic 19.5 12.1 4.8 10.8 3.2 3.8 1.2 39.9 6.3 2.1

Black, non-Hispanic 10.2 6.8 2.8 8.2 3.5 4.8 1.9 32.7 7.4 3.1

Other 17.4 10.6 4.7 9.4 3.3 4.4 1.7 36.5 7.4 2.2

SOURCE: National Longitudinal Survey of Youth, Bureau of Labor Statistics, 1996.

Table 22. Estimated Lifetime Prevalence of Drug Use for American Indian and 

Non-Indian 8th-, 10th-, and 12th-Graders (by percent): 1997–1998

8th-Graders 10th-Graders 12th-Graders

Drug Indian Non-Indian Indian Non-Indian Indian Non-Indian

Alcohol 65 54 84 72 83 82

Alcohol intoxication 46 25 71 49 68 64

Marijuana 67 23 82 42 74 50

Inhalants 14 21 22 18 10 16

Cocaine 8 4 19 7 20 9

Stimulants 15 12 26 17 20 17

Sedatives 3 N/A 5 N/A 2 8

Heroin 4 2 4 2 5 2

Psychedelics 19 5 26 11 27 15

Tranquilizers 1 5 4 7 21 9

PCP 4 N/A 4 N/A 6 4

Cigarettes 79 47 87 60 75 65

Smokeless tobacco 45 17 41 26 41 25

Sample size 431 18,700 244 15,400 196 15,800

N/A: Not available.

SOURCES: Tri-Ethnic Center for Prevention Research, Colorado State University; Monitoring the Future Study, University of Michigan;

Johnston et al., 2001d-e.
Prevalence of Drug Use Among Youth

82

Figure 5. Trends in Prevalence of Daily Cigarette Use Among 12th-Graders, 

by Race/Ethnicity: 1977–2000

SOURCE: Monitoring the Future Study, University of Michigan, 2000; Johnston et al., 2001d.

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Prevalence of Drug Use Among Youth

83

Figure 6. Trends in Prevalence of Marijuana Use Among 12th-Graders, 

by Race/Ethnicity: 1977–2000

SOURCE: Monitoring the Future Study, University of Michigan, 2000; Johnston et al., 2001d.

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Prevalence of Drug Use Among Youth

84

Figure 7. Trends in Prevalence of Inhalant Use Among 12th-Graders, 

by Race/Ethnicity: 1977–2000

SOURCE: Monitoring the Future Study, University of Michigan, 2000; Johnston et al., 2001d.

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Prevalence of Drug Use Among Youth

85

Figure 8. Trends in Prevalence of Cocaine Use Among 12th-Graders, 

by Race/Ethnicity: 1977–2000

SOURCE: Monitoring the Future Study, University of Michigan, 2000; Johnston et al., 2001d.

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Prevalence of Drug Use Among Youth

86

Figure 9. Trends in Prevalence of LSD Use Among 12th-Graders, 

by Race/Ethnicity: 1977–2000

SOURCE: Monitoring the Future Study, University of Michigan, 2000; Johnston et al., 2001d.

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Prevalence of Drug Use Among Youth

87

Figure 10. Trends in Prevalence of Any Illicit Drug Use Among 12th-Graders, 

by Race/Ethnicity: 1977–1999

NOTES: Use of “any illicit drug” includes any use of marijuana, LSD, other hallucinogens, crack, other cocaine, or heroin, or any use of 

other narcotics, amphetamines, barbiturates, methaqualone (excluded since 1990), or tranquilizers, not under a doctor's order.

Beginning in 1982, the MTF survey question about amphetamine use was revised to reduce inappropriate reporting of 

nonprescription amphetamine use. The prevalence estimates dropped slightly as a result of this methodological change.

SOURCE: Monitoring the Future Study, University of Michigan, 1999; Johnston et al., 2001d.

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89

This chapter provides data from the U.S. Department of Education on school dropout trends and data from

the Youth Risk Behavior Survey (YRBS) on risk behaviors such as fighting, carrying a weapon, and engaging in

sexual activity. The use of alcohol and other drugs by youth is associated with many social and health problems.

The leading causes of death among adolescents are accidents, homicides, and suicides, all of which are linked to

use of alcohol and other drugs. Alcohol use is mentioned as a factor in approximately one-half of homicides,

suicides, and deaths from motor vehicle crashes, (Kolbe et al. 1993; National Institute on Alcoholism and

Alcohol Abuse 2000). Alcohol and other drug use are associated with increased risk of dropping out of school,

contracting sexually transmitted diseases, and getting into trouble with law enforcement officials.

In many studies, risk-taking and deviant behaviors cluster more than is expected by random co-occurrence of

these behaviors (Kokatailo 1995; Jessor 1998). In some studies, the temporal ordering of these behaviors is clear.

For example, failing to complete high school is associated with increased later risk of becoming alcohol dependent,

even when drinking starts after age 18 (Crum et al. 1992); dropping out of school may precede many life 

problems, including unemployment, poverty, poor health, and greater complications arising from alcohol or

other drug abuse (Jillson-Boostrom 1993).

These interrelationships between alcohol, other drug use, delinquency, and risk-taking behaviors have been

observed in many cross-sectional and longitudinal studies. Even so, no study has produced definitive evidence

on the causal origins of this observed covariation of risk behaviors. What seems most likely is that in some

instances one risk behavior is a direct consequence of another risk behavior—the link between alcohol intoxication and unprotected or otherwise unsafe sex comes to mind as an example. In other instances, two risk

behaviors may be a manifestation of some underlying shared vulnerability, as exemplified by youth living and

growing up in socially disadvantaged neighborhoods with negligent parents who fail to provide adequate supervision and monitoring in the primary school years and beyond. In still other instances, the risk behaviors may

combine artifactually—a prominent concern when questionnaires on multiple risk behaviors fail to take into

account the shared methods covariation, whereby similar questions can induce response tendencies that yield

substantive covariation even when there is no substantive covariation (Ryan and Irwin 1992; Anthony et al.

2000).

SCHOOL DROPOUT TRENDS

Because of this Nation’s history of compulsory education for children, individuals who drop out of school have

long been a concern and an area of interest for researchers. In the last decades of the 20th century, the dropout

issue became particularly important because of increasing awareness of the exceptionally high dropout rates

among inner city and Hispanic youth (Dryfoos 1990; U.S. Department of Education 2000). This issue is of

particular interest to drug use researchers because the relationship between dropping out of school and using

drugs has been well documented (National Institute on Drug Abuse, 1993; Substance Abuse and Mental Health

Administration 2001b).

In the study of dropout rates, it can be useful to compare and contrast different indicators, each with its own

strengths and weaknesses. Three prominent dropout indicators are (1) the event dropout rate, (2) the status

dropout rate, and (3) the cohort dropout rate. The event dropout rate measures the number of students dropping

out of school during any given year as a function of time and the total number of enrolled students. This rate

Chapter 5. YOUTH DRUG USE AND RISK BEHAVIORS
Youth Drug Use and Risk Behaviors

calculates only the number of students leaving a given school district and may not take into account students

who enroll in other school districts or students who leave school, return, and leave again. The status dropout

rate attempts to evaluate through surveys the proportion of individuals in a given age group who have completed school or are enrolled in school at one time. Because of its increased sensitivity to the cumulative annual

event rate, the status dropout rate always appears higher than the event rate. The cohort dropout rate is obtained

by following a single group of students across time and evaluating their school completion rates (Chavez 1993).

Status dropout rates for youth from various races/ethnicities and selected demographic characteristics are presented

in Table 25. Based on 1999 data, this indicator suggests that Hispanic youth are substantially more likely 

to have dropped out of school than youth in other groups such as non-Hispanic Whites (7.3 percent), nonHispanic Blacks (12.6 percent), and Asian/Pacific Islanders (4.3 percent, the lowest dropout rate) (Table 25, 

column 1).

Far in excess of their 14.8-percent representation in the general population of young people (Table 25, column

5), Hispanic youth account for almost 40 percent of all dropouts. By comparison, non-Hispanic Whites and

Asian/Pacific Islanders are underrepresented among dropouts (Table 25, column 4).

The interpretation of these statistics is complicated by imbalances in recency of immigration, regional distribution

of various racial/ethnic groups, and the distribution of material wealth and social capital, which also are related

to success in schooling. Regarding recency of immigration, both first- and second-generation Hispanic youth

have status dropout rates that are not as extreme as the mean value for Hispanic youths in general, as shown in

the lower rows of column 1 of Table 25. Among Hispanic youth born outside of the United States, for example,

the risk of having dropped out of school is 44.2 percent. Comparison values for first- and second-generation

Hispanic youth are 16.1 percent and 16.0 percent, respectively. Nonetheless, in comparing recent immigrants

and first- and second-generation youth, Hispanic youth are more likely to have dropped out (See Table 25, 

column 1).

Table 25 also shows considerable regional variation in status dropout rates. Youth are most likely to have

dropped out of school in the West and South. By comparison, youth in the Northeast and Midwest are about

66 percent as likely to have dropped out.

Based on data from 1996, Table 26 clarifies that socioeconomic status also can be an important determinant of

success in school (Table 26, column 1) and is associated not only with recent immigration status, but also with

race and ethnicity (e.g., Diez-Roux 2001). Nonetheless, when examined within socioeconomic levels, Hispanic

youth remain more likely to have dropped out of school than non-Hispanic Black and White youth. Even

within the lowest income level, Hispanic youth are more likely to have dropped out (42.4 percent) than are 

non-Hispanic Whites (13.9 percent) and non-Hispanic Blacks (21.9 percent).

Table 27 presents trend data on the event dropout rates for youth in grades 10–12 from October 1972 through

October 1999 by sex and race/ethnicity. These values reflect the percentages of students who had not graduated

from high school, among those who had been enrolled at the beginning of a new school year. As with the data

on status dropout rates, Hispanic youth consistently show the highest dropout rates among the three subgroups,

followed next by African-American youth. Year-to-year variation indicates that event dropout rates fluctuated

somewhat from 1972 to the mid-1990s for Hispanic youth, with values of 7.8 percent to 9.5 percent between

1996 and 1999. Declines also are seen for non-Hispanic Whites and Blacks, but the most recent data indicate

90
Youth Drug Use and Risk Behaviors

persisting imbalances: 4.0 percent for non-Hispanic Whites, 6.5 percent for non-Hispanic Blacks, and 7.8 percent

for Hispanic students (Table 27, last row).

Students drop out of school for a variety of reasons, as illustrated in Table 28, based on self-report survey data

from the National Center for Education Statistics. Based on students’ answers to the survey questions, a large

percentage of all students who dropped out of school said they did not like school and were failing their classes

(42.9 and 38.7 percent, respectively). More African-American students reported being suspended or expelled

from school (24.4 percent) than did Whites (15.4 percent) and Hispanics (10.1 percent). African-American and

Hispanic students were more likely than White students to cite not feeling safe at school as an explanation for

dropping out (8.5 and 8.3 percent for African-American and Hispanic students, respectively, versus 4.8 percent

for White students). White students were more likely than African-American and Hispanic students to report

a drug or alcohol problem as their reason for dropping out (5.9 percent for Whites, compared with 2.1 and 

1.8 percent for African Americans and Hispanics, respectively). A large percentage of female dropouts reported

pregnancy as the reason (26.8 percent). The distribution of pregnancy by race/ethnicity indicated that African

Americans (34.5 percent) and Hispanics (30.6 percent) said they dropped out more frequently due to pregnancy

than did White students (25.6 percent).

Table 29 shows high-school completion rates and method completion by race/ethnicity for the 1995–1999

period. These data indicate that throughout this period, about 85 to 86 percent of youth ages 18–24 years 

completed high school, and 74 to 78 percent received their high-school diploma (Table 29, rows 1 and 2). The

number of youth reporting receiving some alternative to the diploma (e.g., GED certificate) has increased

slightly. In the most recent years (e.g., 1999), non-Hispanic Whites were most likely to have graduated from

high school and to have received a diploma, followed by non-Hispanic Blacks. Hispanics were least likely to

graduate, to receive the high-school diploma, and to receive an alternative such as the GED certificate.

Trend data on completion rates and status dropout by race/ethnicity for 1972 through 1999 are plotted in

Figures 11 and 12. The trends in status dropout and completion rates by race/ethnicity showed minor fluctuations

during this span of over two decades. Of greatest note is the persistent difference in the levels of status dropout

rates for Whites, African Americans, and Hispanics. In addition, the gap between the rates for African

Americans and Whites was closing for the first decade, but has not changed much since the mid-1980s.

RISK BEHAVIOR TRENDS

The use of alcohol and other drugs by youth can threaten their physical and mental health and can alter social

development. The YRBSS data describe student drug use and patterns of other behaviors that may place them

at greater risk of motor vehicle crash injury, other unintentional injury, homicide, suicide, heart disease, and

cancer (Kann et al. 1993). Transmission of HIV and other sexually transmitted diseases also can occur indirectly

as a consequence of alcohol and other drug use, which can impair judgment and reduce inhibitions about 

engaging in sexual intercourse (Blanken 1993).

Comparison of YRBSS data for students who have used marijuana, cocaine, or crack-cocaine and youth who

have never used these drugs shows a consistent pattern of association with other risky behaviors. As illustrated

in Table 30, YRBSS data from 1999 indicate that youth who reported a past or recently active history of smoking

marijuana are generally more likely to have reported engaging in other recent risk-related behaviors, such as

fighting, carrying a weapon, and not wearing a seat belt. This general pattern holds for White, Black, and

91
Youth Drug Use and Risk Behaviors

Hispanic youth. For example, among White students reporting a history of marijuana use, about 43 to 44 percent

reported recent fighting, 21 to 22 percent carried a weapon, and 23 percent reported rarely wearing a seat belt.

Among White students with no reported history of marijuana use, the corresponding estimates are 23 to 

24 percent for fighting, 11 to 12 percent for carrying weapons, and 9 to 10 percent for rarely wearing seat belts

(Table 30, rows 1 and 5). The estimates are somewhat higher for youth who had been recently active users of 

marijuana, and intermediate for youth with past but no recently active marijuana use (Table 30, rows 9 and 13).

A similar pattern of associations between marijuana use and other risky behaviors holds for Black and Hispanic

students who participated in YRBSS (Table 30).

Similar patterns of association can be seen in the prevalence of risk-related behaviors for students who reported

past, recently active (past-month), and no use of crack-cocaine (Table 31). For example, among White youth

reporting recently active crack or other cocaine use, an estimated 20 to 21 percent reported having multiple sex

partners in the 3 months before assessment (Table 30, second page, row 9), as compared with 7 to 8 percent of

White students with recently active marijuana use (Table 30, first page), and 1 to 2 percent of White youth who

never had used crack or other cocaine (Table 30, second page, row 5). Corresponding values for Black youth are

50 to 51 percent, 28 to 29 percent and 14 to 15 percent, showing a similar pattern of association. The same

type of pattern of associations holds for Hispanic students who reported cocaine-crack use (17 percent), recently

active marijuana use (10 to 11 percent), and never having used crack or other cocaine (3 to 4 percent).

This pattern of association extends to use of condoms during most recent sexual encounters. For example, as

shown in Table 31, among White students who reported having used crack or other cocaine, an estimated 41

to 42 percent said they had used no condom in the most recent sexual encounter. Corresponding values for

Black and Hispanic cocaine-using students are 57 to 58 percent and 44 to 45 percent (Table 30, second page).

At the other extreme, students with no history of trying crack or other cocaine were more likely to have used

condoms; the prevalence of failing to use a condom was 24 to 25 percent for Whites, 51 percent for Blacks, and

28 to 29 percent for Hispanics (Table 30, second page). 

SUMMARY

In this chapter, the statistics help clarify the social disadvantage experienced by African-American and especially

Hispanic youth in the United States, as seen in dropout rates and failure to receive diplomas or GED certificates.

The statistics also clarify patterns of association linking lifetime and recently active use of illegal drugs like 

marijuana and cocaine to risk-related behaviors such as not wearing seat belts, having multiple sex partners, and

not using condoms

YRBSS data provide clear evidence of the patterns of association between risk-related behaviors, but fail to take

into account a possibility of a shared methods covariation that induces the patterns of association. Namely, 

students willing to report on their illegal drug use may also be more willing to report on their engagement in

other risky behaviors. As such, these statistics create new research questions that will need to be addressed if we

are to translate these initial observations into effective public health intervention strategies. This new research

on methodological and substantive sources of variation in the observed rates of risk-related behaviors represents

an important element of future research on health disparities affecting our Nation’s racial and ethnic minorities.

92
Youth Drug Use and Risk Behaviors

93

Table 25. Rate, Number, and Distribution of Status Dropouts, by Sex, Race/Ethnicity, 

Age, Region, and Recency of Immigration: 1999

Status Number of All

Characteristics Dropout Rate Status Dropouts Population Dropouts Population

(percent) (thousands) (thousands) (percent) (percent)

Total* 11.2 3,829 34,173 100.0 100.0

Sex

Male 11.9 2,032 17,106 53.1 50.1

Female 10.5 1,797 17,066 46.9 49.9

Race/Ethnicity

White, non-Hispanic 7.3 1,636 22,408 42.7 65.6

Black, non-Hispanic 12.6 621 4,94 16.2 14.5

Hispanic 28.6 1,445 5,060 37.7 14.8

Asian/Pacific Islander 4.3 65 1,515 1.7 4.4

Age

16 3.5 139 3,995 3.6 11.7

17 6.7 278 4,137 7.3 12.1

18 12.6 489 3,870 12.8 11.3

19 13.6 559 4,121 14.6 12.1

20–24 13.1 2,366 18,050 61.8 52.8

Recency of Immigration

Born Outside the 

50 States and the 

District of Columbia

Hispanic 44.2 994 2,250 26.0 6.6

Non-Hispanic 7.0 133 1,909 3.5 5.6

First generation

Hispanic 16.1 240 1,494 6.3 4.4

Non-Hispanic 5.0 94 1,893 2.5 5.5

Second generation or more

Hispanic 16.0 211 1,316 5.5 3.9

Non-Hispanic 8.5 2,156 25,130 56.3 74.1

Region

Northeast 8.7 531 6,133 13.9 17.9

Midwest 8.3 676 8,177 17.7 23.8

South 12.7 1,516 11,902 39.6 34.8

West 13.8 1,106 8,021 28.9 23.5

*Due to relatively small sample sizes, American Indians/Alaska Natives are included in the total but are not shown separately.

SOURCE: U. S. Department of Education, National Center for Education Statistics, Dropout Rates in the United States: 1999 (based on the 

Current Population Survey), 2000.
Youth Drug Use and Risk Behaviors

94

Table 26. Status Dropout Rates for Persons Ages 16–24, 

by Family Income and Race/Ethnicity (by percent): 1990

Race/Ethnicitya

Family Income Total White, Non-Hispanic Black, Non-Hispanic Hispanic 

Total 11.1 7.3 13.0 29.4

Family incomeb

Low-income level 22.1 13.9 21.9 42.4

Middle-income level 10.8 8.3 9.0 24.9

High-income level 2.6 2.0 2.5 11.0

a

Non-Hispanics who are neither Black nor White are not shown separately but are included in the total.

b

Family income in current residence. Low income is defined as the bottom 20 percent of all family incomes for 1994; middle income is

between 20 and 80 percent of all family incomes; and high incomes is the top 20 percent of all family incomes.

SOURCE: U.S. Bureau of the Census, Current Population Survey, October 1994, unpublished data.
Youth Drug Use and Risk Behaviors

95

Table 27. Event Dropout Ratesa for Persons Ages 15–24 Who Dropped Out of 

Grades 10–12, by Sex and Race/Ethnicity (by percent): October 1972–October 1999

Sex Race/Ethnicity b

White Black

Year Total Male Female Non-Hispanic Non-Hispanic Hispanic

1972 6.1 5.9 6.3 5.3 9.5 11.2

1973 6.3 6.8 5.7 5.5 9.9 10.0

1974 6.7 7.4 6.0 5.8 11.6 9.9

1975 5.8 5.4 6.1 5.0 8.7 10.9

1976 5.9 6.6 5.2 5.6 7.4 7.3

1977 6.5 6.9 6.1 6.1 8.6 7.8

1978 6.7 7.5 5.9 5.8 0.2 12.3

1979 6.7 6.8 6.7 6.0 9.9 9.8

1980 6.1 6.7 5.5 5.2 8.2 11.7

1981 5.9 6.0 5.8 4.8 9.7 10.7

1982 5.5 5.8 5.1 4.7 7.8 9.2

1983 5.2 5.8 4.7 4.4 7.0 10.1

1984 5.1 5.4 4.8 4.4 5.7 11.1

1985 5.2 5.4 5.0 4.3 7.8 9.8

1986 4.7 4.7 4.7 3.7 5.4 11.9

1987 4.1 4.3 3.8 3.5 6.4 5.4

1988 4.8 5.1 4.4 4.2 5.9 10.4

1989 4.5 4.5 4.5 3.5 7.8 7.8

1990 4.0 4.0 3.9 3.3 5.0 7.9

1991 4.1 3.8 4.2 3.2 6.0 7.3

1992 4.4 3.9 4.9 3.7 5.0 8.2

1993 4.5 4.6 4.3 3.9 5.8 6.7

1994 5.3 5.2 5.4 4.2 6.6 10.0

1995 5.7 6.2 5.3 4.5 6.4 12.4

1996 5.0 5.0 5.1 4.1 6.7 9.0

1997 4.6 5.0 4.1 3.6 5.0 9.5

1998 4.8 4.6 4.9 3.9 5.2 9.4

1999 5.0 4.6 5.4 4.0 6.5 7.8

a

The event dropout rate is the percentage of those in grades 10–12, ages 15–24 who were enrolled in the previous October but were not

enrolled and had not graduated the following October.

b

Due to relatively small sample sizes, American Indians/Alaska Natives and Asian/Pacific Islanders are included in the total but are not

shown separately.

SOURCE: U. S. Department of Education, National Center for Education Statistics, Dropout Rates in the United States: 1999 (based on the 

Current Population Survey), 2000.
Youth Drug Use and Risk Behaviors

96

Table 28. Reasons for Dropping Out of School, by Sex and Race/Ethnicity 

(by percent): 1992

Sex Race/Ethnicity

Black, White,

Reason for Dropping Out Total Male Female Hispanic Non-Hispanic Non-Hispanic

School-related

Did not like school 42.9 43.6 42.2 48.0 28.8 45.5

Could not get along with teachers 22.8 24.6 21.1 24.6 27.8 21.5

Could not get along with students 14.5 17.7 11.6 15.6 18.4 13.6

Did not feel safe at school 6.0 7.0 5.1 8.3 8.5 4.8

Felt did not belong 24.2 25.8 22.7 16.0 25.9 26.6

Could not keep up with schoolwork 31.3 32.7 29.9 35.0 25.6 30.3

Was failing school 38.7 43.4 34.5 40.6 39.6 36.6

Changed school and did not like new school 10.6 10.5 10.7 12.3 9.1 10.2

Was suspended/expelled from school 10.5 21.6 10.0 10.1 24.4 15.4

Job-related

Could not work and go to school at same time 22.8 26.9 19.1 20.4 15.4 24.6

Found a job 28.5 35.9 21.8 34.1 19.1 27.5

Family-related:

Had to support family 11.2 10.4 11.9 15.8 11.8 9.9

Wanted to have family 7.5 6.4 8.4 9.1 4.6 8.2

Was pregnant 26.8 N/A 26.8 30.6 34.5 25.6

Became parent 14.7 7.7 21.0 13.4 2.0 15.1

Got married 12.1 3.7 19.7 13.4 2.0 15.1

Had to care for family member 11.9 9.5 14.0 8.5 14.7 10.7

Other

Wanted to travel 8.1 8.2 8.0 6.6 7.3 7.1

Friends dropped out 8.0 8.5 7.5 7.6 6.7 8.6

Had a drug and/or alcohol problem 4.4 6.1 2.8 1.8 2.1 5.9

N/A: Not applicable.

SOURCE: National Educational Longitudinal Study of 1988 Second Followup Survey, National Center for Education Statistics, 1992, 

unpublished data.
Youth Drug Use and Risk Behaviors

97

Table 29. High-School Completion Rates and Method of Completion for Persons Ages

18–24 Years, by Race/Ethnicity and Year (by percent): October 1995–October 1999

Race/Ethnicity and Completion Rate 1995 1996 1997 1998 1999

Total

Completed 85.3 86.2 85.9 84.8 85.9

Diploma 77.9 76.4 76.7 74.7 76.8

Alternative* 7.4 7.4 9.1 10.1 9.2

White, non-Hispanic

Completed 90.7 91.5 90.5 90.2 91.2

Diploma 82.9 81.0 81.1 80.2 82.0

Alternative 6.9 10.5 9.4 10.0 9.2

Black, non-Hispanic

Completed 84.5 83.0 82.0 81.4 83.5

Diploma 75.9 73.0 72.2 71.7 72.9

Alternative 8.5 10.0 9.7 9.6 10.7

Hispanic

Completed 62.8 61.9 66.7 62.8 63.4

Diploma 54.2 55.2 59.1 52.1 54.9

Alternative 8.6 6.7 7.7 10.7 8.5

*Completed high school by means of an equivalent test, such as a General Educational Development (GED) exam.

NOTE: Because of rounding, details may not add to totals.

SOURCE: U. S. Bureau of the Census, Current Population Survey, October 1999; U.S. Department of Education, 2000.
Youth Drug Use and Risk Behaviors

98

Table 30. Estimated Percentage of Youth Engaging in Risk Behaviors, 

by Drug Users and Nonusers and Race/Ethnicity: 1999

a

Had sex with four or more partners during 3 months preceding the survey.

b

Included Hispanic or Latino and Multiple-Hispanic.

c

Included American Indian/Alaska Native, Asian, Native Hawaiian/Other Pacific Islanders, and Multiple non-Hispanic.

SOURCE: Youth Risk Behavior Surveillance System, Centers for Disease Control and Prevention, 1999.

Carried a Rarely Multiple Ridden in Used Drugs or Used No

Fight in Weapon in Wears Sex Partners Car While Alcohol Before Condom During

Drug, Type of Use, Last Last a Seat During Last Driver Was Last Sexual Last Sexual

and Race/Ethnicity 12 Months 30 Days Belt 3 Months a Drinking Encounter Encounter

Marijuana

Lifetime use

White 43.6 21.8 23.0 5.7 48.4 22.6 37.2

Black 50.0 26.7 26.6 23.8 43.9 21.8 63.9

Hispanic b 54.7 29.9 17.8 8.4 53.7 21.2 43.0

Other c 52.3 27.9 21.7 6.4 45.7 20.8 37.1

No lifetime use

White 23.7 11.9 9.1 0.6 18.8 2.4 15.6

Black 33.3 8.0 18.6 7.6 24.7 1.1 39.1

Hispanic 24.3 6.8 10.5 1.5 24.6 0.7 18.0

Other 23.9 13.1 7.3 1.1 12.8 1.8 15.2

Used last 30 days

White 48.5 24.8 27.1 7.7 60.2 30.0 39.0

Black 57.3 40.5 34.1 28.7 52.9 33.8 66.0

Hispanic 64.8 37.9 22.5 10.6 65.1 30.5 51.9

Other 64.2 41.2 23.9 9.7 54.2 27.2 40.9

No use last 30 days

White 27.5 13.4 11.4 1.2 22.3 5.0 21.0

Black 35.5 8.7 18.3 10.8 27.8 3.0 45.6

Hispanic 29.8 10.8 11.0 2.6 29.1 3.4 22.4

Other 27.8 12.7 10.6 1.5 19.1 5.0 20.2

Cocaine or crack

Lifetime use

White 53.9 34.6 31.6 12.8 62.4 43.8 41.3

Black 77.4 63.2 48.2 45.0 69.0 43.2 57.2

Hispanic b 71.3 43.5 25.9 17.0 67.6 32.3 44.1

Other c 59.1 51.6 29.3 18.9 47.1 40.8 47.5

No lifetime use

White 30.8 14.4 13.8 1.9 29.2 8.3 24.2

Black 40.3 16.3 21.8 14.9 33.6 10.7 51.0

Hispanic 34.4 14.4 12.5 3.1 34.5 7.3 28.5

Other 34.9 16.1 12.4 1.8 26.5 7.4 23.3

Used last 30 days

White 59.9 47.2 40.8 20.5 72.9 49.5 38.4

Black 80.3 74.6 41.3 50.3 63.3 58.4 31.9

Hispanic 82.1 54.6 37.8 23.7 77.3 44.3 44.8

Other 77.0 69.2 42.1 28.4 67.9 52.1 31.4

No use last 30 days

White 31.9 15.1 14.5 2.3 30.7 10.3 25.4

Black 40.7 16.6 22.2 15.1 34.1 10.9 51.3

Hispanic 37.1 16.3 12.9 3.9 36.8 8.8 29.8

Other 35.4 17.3 12.9 2.5 26.8 9.0 25.5
Youth Drug Use and Risk Behaviors

99

Figure 11. Status Dropout Rates for Persons Ages 16–24, by Race/Ethnicity: 

October 1972–October 1999

SOURCE: U. S. Bureau of the Census, Current Population Survey, October 1972–1999.

●

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White

Black

Hispanic

Total

1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998

Year

40

35

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20

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10

5

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Percent

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Youth Drug Use and Risk Behaviors

100

Figure 12. Completion Rates for Persons Ages 18–24 Not Currently Enrolled in High

School or Below, by Race/Ethnicity: October 1972–October 1999

SOURCE: U. S. Bureau of the Census, Current Population Survey, October 1972–1999.

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Black

Hispanic

Total

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Year

100

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101

This chapter presents data from three data sources: (1) the registry of cases of AIDS maintained by the Centers

for Disease Control and Prevention (CDC), (2) the panel of emergency rooms (ER) that provide information

about drug-related casualties as part of the national Drug Abuse Warning Network (DAWN), and (3) the panel

of medical examiner (ME) offices that report drug-related deaths to DAWN. These three data sources offer 

epidemiological observations on an important subset of the Nation’s total experience with drug-related morbidity

and mortality. These are important sources of data on health disparities that affect racial and ethnic minority

groups within the United States. As described in the Strategic Plan on Reducing Health Disparities (National

Institute on Drug Abuse 2001b; included as Appendix 2 in this report), a portion of these health disparities can

be traced directly or indirectly to illegal drug-using behaviors. Accordingly, the NIDA definition for health 

disparities research is as follows: “Basic, clinical, and behavioral research that addresses the magnitude and/or

impact of drug use within racial/ethnic minority populations, where the goal of the study is to determine 

differential use and/or effects of drugs on the racial/ethnic minority groups included in the study. Health 

disparities research addresses issues related to epidemiology, prevention, services, and treatment outcomes within

and across racial and ethnic populations” (NIDA 2001b).

There now is a broad profile of adverse social, behavioral, and health consequences attributed to illegal drug-using

behaviors, in part due to a well-recognized association between illegal drug use, smoking of tobacco cigarettes

and cigars, and heavy drinking of alcoholic beverages (e.g., see U.S. Department of Health and Human Services

1998; Furr et al. 2000; Substance Abuse and Mental Health Administration 2001a-b). Within the domain of

brain diseases and mental health, the spectrum of adverse health consequences extends from relatively time-limited and circumscribed acute panic attacks and transient delusion-like experiences to more severe and chronic 

syndromes associated with lesions to aminergic pathways in brain (Tien and Anthony 1990; Anthony and

Petronis 1991; Johannessen and Markey 1984; McCann et al. 2000). In the domain of more general medical

conditions, there is an equally broad range from acute palpitations and stroke to lung cancer and chronic conditions such as hepatitis and liver cirrhosis, as well as infections and infectious diseases—hepatitis, HIV, and

AIDS, to mention just a few (e.g., see Petronis and Anthony 1989; Vlahov et al. 1990; Ford et al. 2000). 

At one end of the life span, the spectrum of drug-associated adverse health effects begins with fetal distress, low

birthweight, deficits in fetal growth, and other complications of pregnancy (e.g., see Bandstra et al. 2001). In the

adolescent and young adult years, self-inflicted injuries and homicides become more prominent in this spectrum

(e.g., see Petronis et al. 1990; Tardiff et al. 1997). Excess deaths also are associated with illegal drug use and drug

dependence, even in middle age and late life (e.g., see Neumark et al. 2000; Rosenberg and Anthony 2001). In

addition, illegal drug use has a prominent rank order among causes of the global burden of disease and disability

(Murray and Lopez 1996). Globally, some population projections indicate an increase in this rank ordering over

the next several decades, coupled with an increasing number of adolescents and young adults in many parts of

the world (Anthony and Helzer 1995).

For most of the 20th century, claims of association between illegal drug use and many of these negative consequences were based primarily on case studies and anecdotes. During the past 25 years, clinical and epidemiological

research supported by NIDA and other agencies often has substantiated these claims (e.g., see National Institute

on Drug Abuse 1998), although it sometimes has challenged firmly held beliefs about drug-related harm 

(e.g., see Frank et al. 2001).

Chapter 6. ADVERSE SOCIAL, BEHAVIORAL, AND

HEALTH CONSEQUENCES
Adverse Social, Behavioral, and Health Consequences

Socioeconomic imbalances across race/ethnicity groups of the U.S. population represent a plausible source of

variation when comparisons are made for differences across historically disadvantaged minority group members.

To some extent, health disparities faced by racial/ethnic minority groups in the United States might be traced

back to illegal drug-using behaviors. These health disparities are not necessarily due to excess in illegal drug use in

these groups, but they may be associated with illegal drug use and associated conditions, such as delays in medical

recognition or inefficiencies in the care and management of the conditions once the conditions are detected.

Some of the observed health disparities also may be associated with a disproportionate representation of minority

group members among street-level lieutenants for drug trafficking, which may have substantial income-related

benefits as well as injury-related costs and risks (e.g., see MacCoun and Reuter 1992).

Disproportionate or not, the involvement of African-American young people in drug trafficking within dynamically changing drug markets must be considered as a plausible partial explanation for an otherwise unexpected

excess in homicide death rates that affect this minority subgroup. For example, among White males ages 15–24,

the national death statistics in 1997–1999 indicated 10 to 13 homicides per 100,000 persons; the corresponding

values for African-American males in the same age group are 85 to 113 homicides per 100,000 persons.

Moreover, origins of the seven- to eightfold excess observed for males ages 15–24 in this particular contrast can

be seen in a three- to fivefold excess when this comparison is made for males ages 1–14, and an approximate

fivefold excess among males ages 25–44 (National Center for Health Statistics 2000; also see Chapter 7).

The observed African-American excess in homicide rates is not restricted to males. Compared with White female

homicide rates of 2.8 to 3.2 homicides per 100,000 persons in the 15–44 age group during 1997–1999, the 

corresponding values for African-American females in this same age group range from 11.5 to 14.5 homicides

per 100,000 persons. An excess also can be seen for younger females ages 1–14: recent values of about 1 homicide

per 100,000 persons are seen for White girls in this age group, versus recent values of 3.0 to 3.4 homicides per

100,000 persons for African-American girls of the same age (National Center for Health Statistics 2000).

Notwithstanding the importance of drug trafficking and homicides among African Americans, other drugrelated sources of mortality also emerge when examining comparative mortality statistics. For example, the U.S.

Department of Health and Human Services Task Force on African American and Minority Health found that

among African Americans, mortality rates for chronic disease and cirrhosis have been nearly twice as high 

as the rates among Whites; in the 1980s, cocaine-related deaths tripled among African Americans but only 

doubled among Whites. This excess in cocaine-related deaths may reflect inaccuracy in estimates of the prevalence of cocaine use, which in general show roughly comparable values for African Americans versus Whites, or

may reflect excess risk of cocaine-related harm once cocaine use begins—a topic of continuing inquiry

(Flewelling et al. 1992). 

Analyses of variation in mortality also highlight excess mortality rates for some of the drug-related causes 

of death among certain subgroups of the American Indian/Alaska Native populations in the United States. 

For example, between 1997 and 1999, the suicide mortality rates experienced by American Indian/Alaska

Native males ages 15–24 ranged from 36 to 42 suicides per 100,000 persons. Corresponding values for 

White males in this age group are just 23 to 26 suicides per 100,000 persons (National Center for Health

Statistics 2000). No excess of similar magnitude is seen for American Indian/Alaska Native females in 

this age group. One is left to speculate whether the observed excess in male suicide is attributable to heavy 

drinking, illegal drug use, or other life circumstances or processes that have a different effect on young male

American Indians/Alaska Natives.

102
Adverse Social, Behavioral, and Health Consequences

Noteworthy in comparing age-adjusted death rates for Whites versus Asian/Pacific Islander and Hispanic citizens

in recent years is that Whites generally have higher rates across the categories of causes of death. One exception

is homicide death rates, for which the Whites and Asian/Pacific Islanders have values that are not appreciably

different (3.8 per 100,000 persons versus 3.2 per 100,000 persons, respectively, in 1999). This exception is noteworthy because Whites experienced excess mortality rates in virtually all other categories of causes of death

(National Center for Health Statistics 2001).

AIDS

AIDS surveillance data are gathered by CDC, which uses information collected by health departments in each

State, U.S. territory, and the District of Columbia. Between 1987 and 1995, the age-adjusted death rate for

AIDS and HIV disease more than doubled, from 5.6 to 16.3 deaths per 100,000 population. AIDS and HIV

disease remain high among leading causes of death for persons ages 25–44. However, since 1995, there generally

have been declines in mortality due to AIDS and HIV-related disease (16.3 deaths per 100,000 persons in 1995

to a projected 5.4 deaths per 100,000 persons for 1999).

Through December 2000, State and local health departments reported between 750,000 and 800,000 adolescent

and adult AIDS cases to CDC. Table 31 presents information reported through December 2000 for 130,104

female adolescent/adult AIDS cases, and Table 32 presents information about 635,451 male AIDS cases.

Among the over 130,000 female cases, just over 70,000 were Black, non-Hispanic, and roughly 25,000 were

Hispanic. Among the more than 635,000 male cases, just over 210,000 were non-Hispanic Blacks and 114,000

were Hispanics. As gauged against the relative sizes of these groups in the U.S. population, these numbers show

disproportionate overrepresentation of these racial/ethnic minorities among AIDS cases.

As shown in the cumulative total panel of Table 31, about two of five female AIDS cases have been traced to

injecting drug use (41 percent). This value is roughly comparable across all of the racial/ethnic minority groups

depicted in Table 31; Asian/Pacific Islanders are a noteworthy exception (16 percent). Heterosexual contact also

is a prevalent exposure category, representing 40 percent of female AIDS cases overall. As shown in the cumulative total panel of Table 32, injecting drug use generally is less prominent as an exposure category for male AIDS

cases (22 percent), where men having sex with men accounts for almost three of five cases overall (56 percent).

Noteworthy racial/ethnic variation appears in the prevalence of these exposure categories. For example, among

men with AIDS, only 9 percent of White non-Hispanic cases are traced to injecting drug use and 74 percent

are traced to men having sex with men. The corresponding values are 34 percent versus 37 percent for nonHispanic Black men with AIDS, 35 percent versus 42 percent for Hispanic men with AIDS, 5 percent versus

72 percent for Asian/Pacific Islander men with AIDS, and 16 percent versus 57 percent for American

Indian/Alaska Native men with AIDS (Table 32). Summing across the two tables, about one-quarter or roughly

193,000 of the 766,000 adolescent/adult AIDS cases reported through December 2000 might be traced to

injecting drug use.

The estimated number of AIDS deaths in 1999 was 8 percent smaller than the value observed in 1998. The

number of AIDS deaths declined most among American Indians/Alaska Natives (16 percent), followed next by

non-Hispanic Whites (15 percent), Asian/Pacific Islanders (11 percent), and Hispanics (7 percent). NonHispanic African Americans showed the smallest decline in death rate due to AIDS (3 percent) across that same

time span (Centers for Disease Control and Prevention 2001).

103
Adverse Social, Behavioral, and Health Consequences

DRUG-RELATED EMERGENCY ROOM EPISODES

Year-to-year variation in drug-related hospital ER statistics serves as one important manifestation of underlying

health risks associated with illegal drug use. Data on the occurrence rates for drug overdoses and other ER 

casualties associated with illegal drug use are important to the Nation’s surveillance and monitoring of its drug

problems. However, year-to-year variation of these ER statistics can be determined by factors other than variations

in the underlying risk of becoming a drug user or of developing drug problems. Over time, this variation also

depends on complex conditions and processes, including diverse life circumstances and dynamic social conditions,

and the relative street-level availability of toxic drugs and the introduction of new products, such as OxyContin®

(sustained-release oxycodone). 

The example of heroin overdose serves a useful illustrative purpose. On one hand, a city with a shortfall in funds

for emergency medical services may show an increase in heroin overdose deaths, even when no change has

occurred in the underlying dynamics of the heroin-using population of the city. On the other hand, active 

programs to distribute Narcan® (naloxone) or to use other harm-reduction methods may reduce or increase the

number of heroin overdose cases seen in the city’s ERs, depending on whether the victim survives to be taken

to the ER or dies and is taken directly to the morgue. Over time, and from place to place, variation in the number

of drug overdose cases also has depended on administrative counting procedures. For example, in many places,

a heroin overdose case has been counted as an ER admission even when the victim is dead on arrival (DOA)

and cannot be resuscitated by ER staff. In other jurisdictions, this type of DOA heroin overdose victim is

recorded as an ER admission only if the resuscitation efforts are successful; in all other cases, the “admission” is

to the hospital morgue.

As such, the range of sources of variation in number of DAWN episodes by time and place is crucial. This range

encompasses not only changes in prevalence of illegal drug use, but also changes in dosages used, potency, 

frequency of use, routes of administration, aging of drug users and other vulnerability characteristics of existing

users, and the combined use of two or more drugs (e.g., with alcoholic beverages). As noted above, there are

“threshold” factors, associated with decisions about whether to bring a DOA victim to the ER for resuscitation

attempts and whether the DOA victim will be recorded in the ER statistics before transfer to the morgue. There

also are “nosocomial” factors, relating to the quality of care provided in the ER, and other conditions and

processes under the control of ER personnel, supervisors, and hospital administrators. Research on these threshold and nosocomial factors has been prominent in the epidemiology generally and in psychiatric epidemiology

specifically, but has not been prominent in discussions of statistics from DAWN surveillance activities or

research on drug overdoses generally.

DAWN, now operated by the Substance Abuse and Mental Health Services Administration (SAMHSA) Office

of Applied Studies, originated as a pilot project of the Bureau of Narcotics and Dangerous Drugs and the Drug

Enforcement Administration in the early 1970s. NIDA assumed responsibility for DAWN during the mid1970s and transferred this responsibility to SAMHSA more than 10 years ago. Over the years, DAWN’s profile

as an instrument of drug surveillance has changed considerably. Currently, DAWN may be described as a largescale, ongoing surveillance system that monitors potential adverse consequences of illegal drug use and other

drug-related emergencies, as abstracted from records of participating hospital ERs and selected ME offices

throughout the country. For the first decade or more of DAWN’s existence, the sample of ER and ME offices

represented a nonsystematic sampling of these facilities; there also was participation by other facilities, such as

youth emergency crisis services and telephone hotlines for callers with concerns about illegal drug use and 

104
Adverse Social, Behavioral, and Health Consequences

drug-related problems. Thereafter, the network was constrained to include only ER and ME facilities, and a

more systematic effort was made to derive a nationally representative sample suitable for projections to the 

entire Nation.

A DAWN report is supposed to be generated at the participating facility each time a patient or deceased individual is found to have a drug-related problem or to have died a drug-related death. By design, a DAWN episode

report is submitted for each incident of this type. Data for each episode report, abstracted from medical records,

generally include demographic information about the patient (alive or deceased), circumstances about the

episode that prompted emergency care or an ME’s attention, and information about the drug and judgments

about the circumstances of drug use (e.g., whether the drug had been taken as an effort to commit suicide).

DAWN counts events rather than individuals. Individual drug users may contribute multiple ER episodes and

generate multiple drug mentions in any given year. Of course, an ME mention is an “absorbing” event—once

an individual drug user has appeared in the ME statistics, there is no subsequent reappearance in either ER or

ME statistics.

Interpretation of DAWN statistics requires attention to DAWN administrative decisions about drugs used in

combination. These administrative decisions can be appreciated best by considering specific cases. Consider a

hypothetical overdose victim brought to the ER with signs and symptoms of acute cocaine toxicity. Combining

information obtained through interviews with the victim and his friends with results from drug-screening tests,

the ER staff may be able to confirm that the victim had smoked a small amount of marijuana in a pipe early in

the evening and then had injected cocaine just before losing consciousness. This single ER episode will generate

a DAWN overdose report that mentions both cocaine and marijuana. If the victim had consumed a single can

of beer, this episode also would generate an “alcohol-in-combination” mention on top of the marijuana and

cocaine mentions just described. That is, a DAWN drug mention does not require causal attribution or any 

sorting of drugs into refined categories of “proximal cause,” “precipitating cause,” “non-causal concomitant,” or

other groups that might indicate which drug or drugs actually prompted the ER visit. However, alcohol-related

episodes are reported to DAWN only when alcohol is used in combination with another drug. For example, a

car crash victim who drank a six-pack of beer and then crashed his car will not appear in the DAWN statistics

if alcohol is the only drug involved. A different car crash victim who drank a six-pack of beer and is discovered

to have taken one puff on a marijuana cigarette will appear in the DAWN statistics, even if the car crash is

judged by the police or ER staff to be due to the alcohol intoxication. Hence, a DAWN “mention” or “drugrelated episode” does not imply causal attribution. It simply means that recent use of the drug was identified

either through interviews with the victim or acquaintances or through toxicological screening or formal drug

testing. This difference between a “DAWN drug-related ER mention” and a “drug-caused ER event” is crucial

in the interpretation of DAWN statistics. The relative frequency of individual drugs within the DAWN statistics

depends heavily on the prevalence of use of each drug in the population and is not necessarily a reflection of the

causal importance of each drug. Frequently used drugs appear often in DAWN statistics, even if they have not

caused an overdose and even if they have a noncausal peripheral involvement in the drug-related ER episode

(e.g., see Anthony and Trinkoff 1986).

Subject to these issues of interpretation, DAWN projections for the coterminous United States in 2000 indicate

almost 250 drug-related ER episodes per 100,000 residents age 6 and older (243.4 cases per 100,000 residents,

as shown in the first row of Table 33). Sorted into categories by whether cocaine, marijuana, and either heroin 

or morphine were mentioned in the DAWN ER report, data reveal 70.7 cocaine-related ER mentions per

105
Adverse Social, Behavioral, and Health Consequences

100,000 residents, almost 40 heroin/morphine-related ER mentions per 100,000 residents, and almost 

40 marijuana-related ER mentions per 100,000 residents. (As described in the prior paragraph, the terms 

“marijuana-related” or “cocaine-related” do not mean that the marijuana use or the cocaine use caused the ER

casualty, but that these drugs were mentioned as concomitant circumstances in relation to the ER visit.)

There is slight male excess in the projected occurrence of the ER episodes. Males accounted for almost 260 ER

episodes per 100,000 persons, compared with about 220 ER episodes per 100,000 females (Table 33, first column).

Substantial age-related variation emerges in the occurrence rates for ER episodes, with very low rates for children

ages 6–11, and the highest rates observed for young adults ages 18–25 (Table 33, first column). Studied drugby-drug, somewhat different age-related patterns emerge. For example, the highest rates of cocaine-related and

heroin-related mentions are observed for males ages 26–34 years of age, with females of this age having somewhat lower rates. Peak values for marijuana mentions are observed for individuals ages 18–25 (Table 33).

The youngest and oldest age categories merit special mention. Changes in demographic structure and drug

experience within the United States soon will necessitate respecification of these age categories. There no longer

is homogeneity of drug experience within the 6–11 age group, nor among adults age 35 and older. For example,

illegal drug-using behavior in the preadolescent years of childhood formerly was an extremely rare occurrence;

it now is more prevalent in the later primary school grades (e.g., see Johnson et al. 2001). Moreover, in comparing individuals ages 26–34 with adults age 35 and older, there is an apparent sharp drop in the occurrence

of ER episodes, perhaps leading the reader to believe that those ages 30–34 are at substantially higher risk of

being an ER casualty than individuals ages 35–39. However, the apparent drop in occurrence rates in the older

age group mainly is a consequence of grouping people ages 35–39 with the increasing numbers of U.S. residents

who are age 50 and older and for whom illegal drug use rates are quite low. The single “average” summary 

statistics for children under age 12 and for adults age 35 and older no longer serve well in this context, given

what we now know about age-specific prevalence of illegal drug use and the “aging” of the U.S. population. This

attention to more refined age categories will become a topic of greater importance in comparisons across

racial/ethnic minority groups because the demographic structure and age composition of these subgroups 

differ substantially.

Interesting male-female differences and racial/ethnic variations appear in the relative frequency of different

drugs mentioned in the DAWN statistics. In general, because alcohol use is a relatively frequent behavior 

for many Americans and often is concomitant with other drug use in the United States, the most frequently

mentioned drug in the DAWN statistics is “alcohol-in-combination” with other drugs. Alcohol-in-combination

appears in almost two in five of the DAWN ER episodes involving male patients (39 percent, as shown in 

Table 34) and in just over one-fourth of DAWN ER episodes involving female patients (28.7 percent, also in

Table 34). However, this ranking of alcohol-in-combination is not the case for DAWN ER episodes involving

non-Hispanic Black patients and Hispanic patients, for whom cocaine is the most frequently mentioned drug

(Table 34). Furthermore, heroin/morphine is the third-ranked drug group in the statistics for non-Hispanic

Blacks and Hispanic patients. Heroin/morphine also is prominent for all male patients, but not for all female

patients, among whom marijuana/hashish is in the third rank (Table 34).

Table 35 presents trends in the estimated numbers of drug-related ER episodes by race/ethnicity and age from

1994 to 2000. The total number of drug-related episodes was highest in 2000, increasing from almost 900,000

episodes in 1994 to almost 1.1 million episodes in 2000.

106
Adverse Social, Behavioral, and Health Consequences

By stratifying episodes in relation to race/ethnicity, it is possible to see that the percentage increase in total 

number of drug-related episodes from 1999 to 2000 was 12 to 13 percent for Whites, more than 20 percent 

for Hispanics, and almost negligible for Blacks (Table 35). Between 1999 and 2000, all age groups shown in

Table 35 exhibit increases in drug-related ER episodes, except for Blacks and the “Other” category, which most

likely is a result of a change in administrative coding practices.

In 1994, the total number of cocaine mentions in ER visits was 143,000 (Table 36). Cocaine mentions

decreased to 135,700 in 1995, but they have increased to nearly 175,000 mentions in 2000. In the ER cocaine

statistics for all race/ethnicity groups combined, there has been a demographic shift since 1998, when there were

more ER cocaine mentions for individuals ages 6–34 than for adults age 35 and older. Thereafter, the greater

number of ER cocaine mentions involved older adults, mainly as a consequence of greater occurrence of

cocaine-related ER visits (Table 36). African Americans are disproportionately represented among the ER victims

in these cocaine mentions for every age group except youth ages 12–17. During 2000, non-Hispanic Whites

and Blacks in the 26–34 age group had roughly equivalent numbers of ER victims in the cocaine mention 

category (about 19,000 to 20,000 victims), compared with 7,500 for Hispanics and smaller numbers for other

race-ethnicity groups. After yearly increases between 1994 through 1998 in the total number of Black

Americans mentioned in the DAWN cocaine statistics, there were declines in subsequent years. In contrast,

there were continuing increases for Whites and Hispanics. Among Americans age 35 and older, virtually all raceethnicity groups represented in the table showed increased numbers for 2000 versus 1999, consistent with the

previously described aging of the population in general and of active cocaine users within the U.S. population.

As with cocaine mentions, total mentions for heroin/morphine also increased, from 63,158 mentions in 1994

(Substance Abuse Mental Health Services Administration, 1999a) to 94,804 mentions in 2000 (see Table 37).

There were recent increases in the late 1990s for virtually all racial/ethnic groups represented in the table.

Scanning across age groups in 2000 (Table 37), the largest number of heroin/morphine ER mentions was

observed for adults age 35 and older (over 51,000 mentions). Reflecting the increased survivorship of the U.S.

population, and the aging of heroin/morphine users within this population, a substantial number of ER mentions

for the heroin/morphine drug group now involve older adults in virtually all racial/ethnicity groups within 

the population. 

Table 38 shows DAWN ER statistics for the methamphetamine/speed drug group, which increased during the

1980s and were at plateau levels during most of the 1990s, with large increases observed between 1993 and

1994. Total methamphetamine/speed mentions increased to 17,557 mentions in 1994 and then ranged between

10,000 and 18,000 mentions from 1994 to 2000.

Among racial/ethnic groups, a large increase between 1994 and 2000 occurred among Hispanics (201 percent),

but there were no appreciable increases during the last decades of the 20th century except for American

Indians/Alaska Natives and the “Other” subgroup (Table 38). Whereas the absolute number of methamphetamine/

speed cases recently has been increasing among Hispanics ages 12–17, this increase generally has paralleled

increases in the size of this Hispanic subgroup. Whether there also are increases in the risk of becoming a

methamphetamine/speed user or developing associated problems is unknown. 

DAWN ER mentions for marijuana/hashish (Table 39) have been increasing since 1994, and this trend sustains

increases observed since the late 1980s (National Institute on Drug Abuse 1998). For example, scanning all

groups combined, there were slightly over 40,000 mentions of marijuana/hashish in 1994. By 2000, the 

107
Adverse Social, Behavioral, and Health Consequences

number of the DAWN ER mentions had increased steadily to almost 100,000, more than doubling. This 

dramatic increase between 1994 and 2000 can be seen for each racial/ethnic subgroup represented in Table 39,

except for Black Americans. Among Blacks, there were steady increases in the number of DAWN ER mentions

for marijuana/hashish, from almost 15,000 in 1994 to more than 26,000 in 2000, but the number did not 

double over that period. 

Table 40 provides information about drugs used in combination, as well as patient dispositions, based on

DAWN statistics for 2000, the most recent year for which total statistics are available. Detection of multiple

drugs was modestly more likely for men represented in DAWN statistics than for women, but no appreciable

variation emerged across racial/ethnic groups represented in the table. Episodes were most likely to be associated

with an admission for White females (almost 60 percent) and were least likely to be associated with an 

admission for Hispanic males (about 40 percent). Other subgroups were intermediate, with females generally

somewhat more likely to be admitted than males in each of the three racial/ethnic groups represented in the

table. The sources of the observed variation remain open questions and may be due to differential prominence

of suicide and suicide-related behavior when women are seen in DAWN facilities for drug-related episodes;

or the sources of this variation might be traced back to race-related differentials in hospitalization coverage or 

third-party payment for health care.

Apportioned into four groups, the U.S. population age 12 and older is roughly 70 to 75 percent White, about

10 to 12 percent Black, approximately 10 percent Hispanic, and about 4 percent for other racial/ethnic subgroups, as depicted in Chapter 1 of this report. According to Table 41, the distribution of racial/ethnic groups

in DAWN ER mentions for 2000 does not follow this pattern. In that year, about 57 to 58 percent of the

DAWN ER mentions involved White patients, just over 21 percent involved Black patients, and nearly 11 percent

involved Hispanic patients. The reasons for overrepresentation of Blacks in these statistics is unknown and do

not seem to involve greater prevalence of illegal drug use among Blacks in the United States (see Chapter 3).

Table 41 also compares the racial/ethnic distributions, drug group by drug group, with some interesting 

patterns. For example, the racial/ethnic distribution of LSD is of note. Here, we see White patients represented

among LSD casualties roughly in proportion to their population representation, whereas Blacks appear to be

underrepresented among these victims (72.6 percent versus 6.3 percent). At the other extreme, Whites are

underrepresented among victims of DAWN cocaine-related and marijuana-related casualties, whereas Blacks are

overrepresented (roughly 34 percent versus 43 percent for cocaine, and 51 percent versus 27 percent for marijuana).

With mentions for amphetamines and for methamphetamine/speed, Hispanics are overrepresented (15 to 

16 percent) whereas Blacks are underrepresented (under 6 percent). These patterns merit more detailed scrutiny

in advanced epidemiological analyses that take into account local area variations in drug-taking behaviors, as

well as life circumstances, conditions, and process of the type mentioned early in this chapter.

DRUG-RELATED DEATHS AND INTENTIONAL 

AND UNINTENTIONAL INJURIES

ME data presented in DAWN reports are collected from a nonrandom sample and should not be evaluated 

as if they were statistically representative of the Nation or of the respective metropolitan areas. As has been 

discussed in relation to nonfatal DAWN ER mentions and episodes, DAWN defines a drug-related death as 

any death in which drug use is a contributory factor but not necessarily the sole cause; alcohol-in-combination

108
Adverse Social, Behavioral, and Health Consequences

is mentioned only when alcohol is mentioned concomitantly with some other controlled substance or related

drug of abuse. In consequence, causation of death by the drug is not implied. Some MEs may include cases

based on circumstantial evidence; others may report drug-related deaths confirmed only through toxicological

analyses. These circumstances necessitate caution before definitive interpretation of the DAWN data on 

drug-related deaths.

The heroin/morphine drug group, cocaine, and alcohol-in-combination rank at the top of the drugs mentioned

in connection with DAWN statistics for drug-related deaths (Table 42). For example, among male decedents,

heroin/morphine was mentioned in association with about 45 percent of deaths judged to be drug-related; the

corresponding value for female decedents was just over 33 percent. Cocaine was mentioned in association with

almost 45 percent of drug-related deaths for males and nearly 31 percent for female decedents. Alcohol-incombination was implicated in slightly over 37 percent of reports on male decedents, versus nearly 24 percent

for female decedents (Table 42).

The prominence of acetaminophen among drug mentions associated with female decedents represents an 

epidemiological puzzle, partly because it is a widely available and oft-used over-the-counter pharmaceutical

product. Acetaminophen may appear on this list of the top-10 ranked drugs or drug groups in the DAWN ME

statistics simply because acetaminophen is a commonly used drug in the United States—used often not only 

by drug-dependent females who die from drug-related causes, but also used frequently by females who do 

not die from drug-related causes and who do not engage in illegal drug use (e.g., see Anthony and Trinkoff

1986). Acetaminophen can be used in drug overdose attempts. Or, its presence in connection with a drugrelated death might be implicated via toxicological analysis or other forensic investigation (e.g., psychological

autopsy or post-mortem interview), even when the acetaminophen played no contributing causal role in the

occurrence of death.

The prominence of marijuana/hashish among the top-10 ranked drugs also may be explained in this fashion. It

certainly is possible for marijuana and hashish to be implicated in drug-related deaths (e.g., driving while intoxicated). However, the potential for a “fatal drug overdose” is substantially more likely for heroin, morphine, and

cocaine than for marijuana and hashish. It is possible that the appearance of marijuana/hashish in Table 42 can

be traced back to the general prevalence of marijuana/hashish use in U.S. populations, with no implication that

this drug has caused the death observed in the DAWN statistics.

For racial/ethnic variations in relation to the DAWN ME mentions, the prominence of cocaine is noteworthy

in relation to Black and Hispanic decedents. Whereas cocaine is ranked third and is mentioned in connection

with 32 percent of White decedents, it is first-ranked and mentioned in connection with almost two-thirds 

of Black decedents and second-ranked and mentioned in connection with more than 45 percent of Hispanic

decedents. It is possible that the toxicity of cocaine accounts for this prominence, but we cannot rule out 

the possibility that MEs are more likely to test for cocaine metabolites when the decedent is a minority; we 

also cannot rule out the “prevalence” circumstances described above. That is, in some populations, recently

active cocaine use is more common among African Americans and Hispanic Americans. To the extent that

DAWN ME statistics draw more heavily on these populations, the overrepresentation of cocaine mentions in

DAWN ME statistics may correspond with this greater prevalence of recently active cocaine use within these

minority populations.

109
Adverse Social, Behavioral, and Health Consequences

The prominence of lidocaine and quinine detected among Black decedents may reflect greater occurrence of

narcotics overdose in this subgroup of the population (Table 42). Alternately, this prominence may simply be

an artifact of administrative procedures in ME offices, such as greater surveillance for lidocaine and quinine

among young adult Black decedents dying from other causes.

Figure 13 is based on DAWN ME statistics for 2000 and examines the manner of drug-related deaths by

race/ethnicity. Arranged in sequence, the columns within each racial/ethnicity subgroup pertain to so-called

“accidental” deaths, suicides, and deaths due to unknown or other causes. This arrangement yields an ogive (or

“backwards J”) pattern for all three racial/ethnic subgroups represented in the figure, with the accidental deaths

being most common, the suicide deaths being least common, and the other/unknown deaths being intermediate

in frequency. Among DAWN ME statistics, Hispanics are overrepresented among accidental deaths, and Whites

are overrepresented among suicide deaths. There is a disproportionate representation of Blacks among deaths

assigned to the “other/unknown” category, which may be a manifestation of race-related administrative practices

within ME offices.

SUMMARY

Data from CDC on HIV/AIDS cases indicate disproportionate representation of African Americans and

Hispanics among AIDS cases. Most striking is the finding that although African Americans and Hispanics 

collectively comprise about no more than 25 percent of the U.S. population, they now account for more than

50 percent of the reported AIDS cases.

Many men and women in the United States with HIV/AIDS have contracted the disease through injecting drug

use or via homosexual or heterosexual contact with injecting drug users. Through December 2000, among 

adolescent and adult women with AIDS, it was possible to trace the HIV infection back to injecting drug use

for 40 to 45 percent of the estimated 130,000 AIDS cases—about two in five cases. Women of Asian/Pacific

Islander heritage were an exception, with only 16 percent traced back to injecting drug use. The corresponding

value for the estimated 635,000 male AIDS cases is 22 percent—about one in five.

DAWN ER and ME statistics prompt new research questions about the overrepresentation of racial/ethnic

minority groups in certain categories. For example, with cocaine-related ER and ME mentions, we now cannot

say whether the apparent overrepresentation of Blacks is due to an excess risk of drug-related morbidity. It might

be due to other conditions or processes such as an excess in frequency or form of recently active illegal drug use

or to associated life circumstances. Social conditions and processes are likely to be important, including access

and availability to primary care services, nature of health benefits available to drug users, or a variety of other

factors. We cannot rule out the possibility that patients of African heritage are more likely to be asked about

their use of cocaine or are more likely to be tested for cocaine through toxicological methods.

At present, drug surveillance statistics such as these can help us raise questions about health disparities affecting

racial and ethnic minority groups. Nevertheless, by themselves, these surveillance statistics are unsatisfactory. In

general, they open new research questions, but they do not settle the questions with definitive or compelling

evidence. The CDC Web site (www.cdc.gov) provides useful surveillance data on this topic and related topics.

110
Adverse Social, Behavioral, and Health Consequences

111

Table 31. Female Adult/Adolescent AIDS Cases, by Exposure Category and 

Race/Ethnicity: Cumulative Totals Through December 2000

*Includes 179 women whose race/ethnicity is unknown.SOURCE: Center for Disease Control and Prevention, HIV/AIDS Surveillance Report (Volume 12, Number 2), 2001.

White, Black, Asian/Pacific American Indian/ Cumulative 

Exposure Category Non-Hispanic Non-Hispanic Hispanic Islander Alaska Native Total*

Number Percent Number Percent Number Percent Number Percent Number Percent Number Percent

Injecting drug use 11,714 42 30,745 41 10,171 40 110 16 190 45 52,991 41Hemophilia/coagulation disorder 105 0 112 0 55 0 6 1 3 1 283 0Heterosexual contact 11,280 40 28,608 38 12,085 47 346 49 157 37 52,520 40Receipt of blood transfusion, 1,828 6 1,307 2 554 2 100 14 14 3 3,806 3

blood component, or tissue

Risk not reported or identified 3,226 11 14,225 19 2,778 11 145 21 62 15 20,504 16Total 28,151 100 74,997 100 25,643 100 707 100 426 100 130,104 100
Adverse Social, Behavioral, and Health Consequences

112

Table 32. Male Adult/Adolescent AIDS Cases, by Exposure Category and 

Race/Ethnicity: Cumulative Totals Through December 2000

White, Black, Asian/Pacific American Indian/ Cumulative 

Exposure Category Non-Hispanic Non-Hispanic Hispanic Islander Alaska Native Total*

Number Percent Number Percent Number Percent Number Percent Number Percent Number Percent

Men who have sex with men 223,470 74 78,651 37 48,287 42 3,562 72 1,067 57 355,409 56Injecting drug use 28,050 9 71,747 34 40,025 35 258 5 296 16 140,536 22Men who have sex with men 24,958 8 15,848 7 7,673 7 184 4 308 16 48,989 8

and inject drug

Hemophilia/coagulation disorder 3,793 1 571 0 437 0 70 1 30 2 4,907 1Heterosexual contact 5,586 2 16,993 8 6,598 6 198 4 54 3 29,460 5Receipt of blood transfusion, 3,173 1 1,077 1 592 1 112 2 9 0 4,971 1

blood component, or tissue

Risk not reported or identified 12,428 4 27,407 13 10,407 9 586 12 115 6 51,179 8Total 301,458 100 212,294 100 114,019 100 4,970 100 1,879 100 635,451 100

*Includes 831 men whose race/ethnicity is unknown.SOURCE: Center for Disease Control and Prevention, HIV/AIDS Surveillance Report (Volume 12, Number 2), 2001.
Adverse Social, Behavioral, and Health Consequences

113

Table 33. Estimated Rates of Emergency Department Drug Abuse Episodes and 

Mentions of Selected Drugs per 100,000 Population in the Coterminous United States,

by Sex and Age: 2000

Total Cocaine Heroin/Morphine Marijuana/Hashish Total

Sex and Age Episodes Mentions Mentions Mentions Populationa

Total

b (6 years & up) 243.4 70.7 39.3 39.0 247,279,858

6–11 years 4.3 0.0 0.0 * 24,062,996

12–17 years 271.6 18.8 4.6 67.1 23,362,981

18–25 years 426.0 88.9 63.5 105.0 28,977,842

26–34 years 410.7 154.6 73.2 66.2 32,997,576

35 years & up 201.1 67.7 38.7 20.5 137,878,463

Male (6 years & up) 258.9 94.8 53.5 51.5 119,580,672

6–11 years 4.4 * 0.0 0.3 12,314,419

12–17 years 185.3 16.7 4.4 76.1 11,956,318

18–25 years 454.9 118.5 78.8 47.7 14,245,527

26–34 years 442.1 193.9 91.2 86.1 16,147,206

35 years & up 231.5 97.1 57.5 26.9 64,917,202

Female (6 years & up) 220.8 46.4 24.5 26.1 127,699,187

6–11 years 4.1 0.1 0.0 * 11,748,577

12–17 years 350.1 20.9 4.2 55.9 11,406,663

18–25 years 381.4 58.2 44.5 59.8 14,732,315

26–34 years 367.7 112.9 52.5 45.3 16,850,371

35 years & up 168.8 40.1 21.1 14.3 72,961,261

a

Average 2000 civilian noninstitutional population estimated by the Substance Abuse and Mental Health Services Administration based on a

procedure using three Census Bureau data files.

b

Total includes patients whose gender was unknown or not reported.

*Low precision, no estimate reported.

SOURCE: Office of Applied Studies, Substance Abuse and Mental Health Services Administration, Drug Abuse Warning Network, 2001a.
Adverse Social, Behavioral, and Health Consequences

114

Table 34. Drug Mentioned Most Frequently by Hospital Emergency Departments, 

by Sex and Race/Ethnicity of Patients: 2000

Percentage of Percentage of

Rank Drug Name Total Episodes Rank Drug Name Total Episodes

Male Patients Female Patients

1 Alcohol-in-Combination 39.0 1 Alcohol-in-Combination 28.7

2 Cocaine 36.6 2 Cocaine 21.0

3 Heroin/Morphine 20.7 3 Marijuana/Hashish 11.8

4 Marijuana/Hashish 19.9 4 Heroin/Morphine 11.1

5 Unspec. Benzodiazepine 4.2 5 Acetaminophen 8.3

6 Acetaminophen 3.1 6 Unspec. Benzodiazepine 5.3

7 Amphetamine* 2.9 7 Alprazolam 5.1

8 Methamphetamine/Speed 2.7 8 Ibuprofen 4.7

9 Hydrocodone 2.5 9 Aspirin 4.1

10 Alprazolam 2.4 10 Clonazepam 4.1

White Patients Black patients

1 Alcohol-in-Combination 32.7 1 Cocaine 56.7

2 Cocaine 17.9 2 Alcohol-in-Combination 40.2

3 Marijuana/Hashish 14.6 3 Heroin/Morphine 23.3

4 Heroin/Morphine 12.1 4 Marijuana/Hashish 19.8

5 Acetaminophen 6.4 5 Acetaminophen 2.6

6 Unspec. Benzodiazepine 5.7 6 Unspec. Benzodiazepine 2.3

7 Alprazolam 5.4 7 Ibuprofen 1.9

8 Hydrocodone 4.5 8 PCP/PCP Combinations 1.7

9 Clonazepam 4.4 9 Aspirin 1.0

10 Ibuprofen 3.2 10 Hydrocodone 1.0

Hispanic Patients

1 Cocaine 34.8 6 Unspec. Benzodiazepine 4.6

2 Alcohol-in-Combination 32.4 7 Amphetamine* 3.7

3 Heroin/Morphine 22.0 8 Methamphetamine/Speed 3.2

4 Marijuana/Hashish 17.2 9 Ibuprofen 3.0

5 Acetaminophen 6.4 10 Aspirin 2.5

*Does not include methamphetamine or other unspecified amphetamine.

NOTES: These estimates are based on a representative sample of non-Federal hospitals with 24-hour emergency departments in the 

coterminous United States.

Percentages are based on weighted emergency room episode estimates of 309,619 for male patients; 281,994 for female patients;

334,985 white patients; 133,776 black patients; and 68,282 Hispanic patients.

SOURCE: Office of Applied Studies, Substance Abuse and Mental Health Services Administration, Drug Abuse Warning Network, 2001a.
Adverse Social, Behavioral, and Health Consequences

115

Table 35. Estimated Number of DAWN Hospital Emergency Department Visits, 

by Race/Ethnicity and Age: 1994–2000

Race/Ethnicity

and Age 1994 1995 1996 1997 1998 1999 2000

Total 899,601 900,287 906,367 942,382 981,764 1,014,243 1,099,306

6–34 554,587 532,307 524,444 538,831 535,728 530,376 577,750

12–17 93,039 92,847 96,544 98,442 95,193 82,976 102,874

18–25 191,104 178,480 170,983 185,402 184,230 198,285 221,228

26–34 269,252 259,152 255,373 252,629 255,226 247,566 252,389

35+ 340,555 365,720 380,313 400,671 443,449 482,463 519,890

Unknown 4,458 2,261 1,609 2,879 2,587 1,404 1,666

White 499,194 503,778 496,036 524,359 555,379 589,670 632,313

6–34 310,786 300,488 293,298 309,107 313,082 318,011 342,196

12–17 62,292 62,374 65,770 68,424 65,526 55,116 67,789

18–25 108,303 101,319 96,364 106,847 112,381 124,954 136,423

26–34 139,432 135,590 130,183 132,701 134,353 136,981 137,292

35+ 187,143 201,983 202,407 214,004 240,792 270,895 289,347

Unknown 1,265 1,307 332 1,248 1,505 765 770

Black 240,582 240,266 233,643 236,437 238,955 234,742 235,083

6–34 139,445 132,698 117,298 116,157 108,120 101,488 97,012

2–17 11,936 12,015 8,909 8,629 6,462 7,322 7,991

18–25 43,635 40,070 31,101 33,449 29,526 30,890 30,755

26–34 83,733 80,337 77,009 73,676 72,034 62,948 57,921

35+ 100,691 107,272 115,510 119,613 130,501 132,985 137,728

Unknown 445 296 836 667 334 268 343

Hispanic 80,359 74,942 93,221 91,315 98,715 97,518 120,126

6–34 53,679 48,866 63,448 60,812 63,317 60,453 75,046

12–17 9,990 8,546 13,371 12,107 13,805 11,454 14,997

18–25 19,823 18,917 23,768 25,342 24,127 23,456 30,565

26–34 23,778 21,271 26,210 23,125 25,336 25,498 29,388

35+ 26,576 26,005 29,693 30,418 35,228 36,927 44,851

Unknown 104 71 80 85 170 138 229

(continued on next page)
Adverse Social, Behavioral, and Health Consequences

116

Table 35 (continued). Estimated Number of DAWN Hospital Emergency Department

Visits, by Race/Ethnicity and Age: 1994–2000

*Low precision, no estimate reported.

SOURCE: Office of Applied Studies, Substance Abuse and Mental Health Services Administration, Drug Abuse Warning Network, 2001a.

Race/Ethnicity

and Age 1994 1995 1996 1997 1998 1999 2000

American Indian/

Alaska Natives 2,427 1,619 3,047 1,685 1,669 1,280 1,980

6–34 1,438 756 2,276 935 1,397 810 910

12–17 217 102 690 146 208 110 58

18–25 577 189 832 362 313 268 419

26–34 643 466 750 423 875 433 434

35+ 989 861 771 750 272 469 1,063

Unknown * 2 * 1 * * 8

Asian/Pacific 

Islanders 5,774 5,637 5,527 5,823 4,922 5,391 6,227

6–34 4,131 4,208 4,097 4,503 3,258 3,714 4,345

12–17 658 1,026 787 847 697 934 670

18–25 1,873 2,042 2,038 2,079 1,377 1,287 2,209

26–34 1,449 1,130 1,269 1,573 1,184 1,492 1,463

35+ 1,633 1,425 1,416 1,320 1,656 1,675 1,875

Unknown 9 5 14 * 7 2 7

Unknown 69,682 72,344 72,491 80,429 79,331 83,054 103,496

6–34 44,048 43,968 42,488 45,949 44,553 44,371 58,197

12–17 7,759 8,664 6,878 7,898 8,286 7,850 11,352

18–25 16,475 15,226 16,061 16,692 15,576 16,552 20,843

26–34 19,765 19,873 19,370 20,784 20,582 19,814 25,878

35+ 23,012 27,801 29,655 33,605 34,213 38,453 44,990

Unknown 2,622 575 348 875 565 230 310

Other 1,583 1,701 2,402 2,334 2,793 2,588 81

6–34 1,059 1,323 1,540 1,370 2,002 1,529 45

12–17 186 121 139 391 209 191 17

18–25 419 717 819 632 929 877 15

26–34 454 484 582 347 863 400 13

35+ 511 372 862 960 786 1,058 36

Unknown 12 5 * 4 6 1 * 
Adverse Social, Behavioral, and Health Consequences

117

Table 36. Estimated Number of DAWN Emergency Department Visits 

With Mention of Cocaine, by Race/Ethnicity and Age: 1994–2000

Race/Ethnicity

and Age 1994 1995 1996 1997 1998 1999 2000

Total 143,336 135,712 152,420 161,082 172,011 168,752 174,882

6–34 88,194 78,042 83,383 86,003 87,877 82,621 81,162

12–17 2,064 2,044 2,581 3,630 4,308 3,214 4,394

18–25 25,430 21,110 22,060 25,218 24,507 25,264 25,753

26–34 60,686 54,881 58,729 57,143 59,008 54,058 51,007

35+ 54,463 57,341 68,717 74,600 83,730 85,869 93,357

Unknown 680 328 319 480 403 261 362

White 40,813 39,950 44,715 50,867 52,954 56,724 59,820

6–34 28,038 26,278 27,715 31,016 31,121 33,045 32,795

12–17 771 990 1,158 1,925 2,380 1,465 2,114

18–25 9,309 8,544 8,413 10,490 10,477 11,930 11,655

26–34 17,959 16,744 18,145 18,598 18,212 19,607 19,025

35+ 12,732 13,636 16,960 19,756 21,738 23,637 26,856

Unknown 43 36 41 96 95 42 169

Black 77,106 73,414 77,984 82,260 84,556 78,017 75,889

6–34 43,756 38,298 37,097 37,996 35,767 30,144 26,027

12–17 378 456 433 489 315 489 407

18–25 10,625 8,090 6,778 8,203 6,425 6,099 5,865

26–34 32,751 29,745 29,880 29,300 29,023 23,515 19,752

35+ 33,178 35,017 40,699 43,980 48,660 47,782 49,729

Unknown 173 99 189 285 129 91 134

Hispanic 13,355 11,495 17,737 16,760 21,209 20,456 23,728

6–34 9,097 7,343 12,231 11,130 13,737 12,964 15,114

12–17 667 318 680 1,076 1,354 1,049 1,514

18–25 3,134 2,820 5,038 4,762 5,390 5,220 6,063

26–34 5,290 4,205 6,508 5,290 6,994 6,695 7,534

35+ 4,238 4,135 5,481 5,609 7,394 7,418 8,594

Unknown 19 17 26 21 78 74 20

(continued on next page)
Adverse Social, Behavioral, and Health Consequences

118

Table 36 (continued). Estimated Number of DAWN Emergency Department Visits 

With Mention of Cocaine, by Race/Ethnicity and Age: 1994–2000

Race/Ethnicity

and Age 1994 1995 1996 1997 1998 1999 2000

American Indian/

Alaska Natives 273 139 159 93 103 72 140

6–34 60 73 104 59 52 44 67

12–17 7 3 2 6 1 3 3

18–25 14 28 16 21 16 14 23

26–34 38 41 86 32 35 26 41

35+ 213 66 55 34 51 28 69

Unknown * * * * * * 3

Asian/Pacific 

Island 483 296 339 494 476 503 699

6–34 385 189 226 309 374 327 466

12–17 16 10 9 1 4 3 12

18–25 88 73 79 98 125 62 127

26–34 281 106 138 210 245 262 327

35+ 98 106 111 186 102 175 228

Unknown * 1 1 * * * 5

Unknown 11,163 10,311 11,183 10,371 12,472 12,846 14,594

6–34 6,780 5,796 5,821 5,345 6,666 6,027 6,686

12–17 219 264 299 131 249 204 342

18–25 2,234 1,524 1,645 1,564 2,037 1,914 2,016

26–34 4,321 4,009 3,872 3,648 4,380 3,909 4,326

35+ 3,942 4,341 5,299 4,948 5,705 6,764 7,878

Unknown 441 173 63 77 101 55 30

Other 143 107 303 237 241 134 12

6–34 77 66 189 150 161 70 7

12–17 5 3 * 3 4 1 2

18–25 26 31 91 81 37 24 4

26–34 47 31 99 66 120 44 1

35+ 62 40 114 86 79 65 4

Unknown 4 1 * 1 * * * 

*Low precision, no estimate reported.

SOURCE: Office of Applied Studies, Substance Abuse and Mental Health Services Administration, Drug Abuse Warning Network, 2001a.
Adverse Social, Behavioral, and Health Consequences

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Table 37. Estimated Number of DAWN Emergency Department Visits 

With Mention of Heroin/Morphine, by Race/Ethnicity and Age, 1994–2000

Race/Ethnicity

and Age 1994 1995 1996 1997 1998 1999 2000

Total 63,159 69,557 72,981 70,712 75,689 82,193 94,805

6–34 30,115 31,318 31,544 31,357 33,224 35,730 42,859

12–17 365 396 492 1,365 896 675 1,052

18–25 8,336 8,376 9,166 9,703 11,251 14,901 18,065

26–34 21,413 22,544 21,886 20,289 21,075 20,153 23,742

35+ 32,887 38,145 41,328 39,259 42,351 46,356 51,698

Unknown 157 93 108 96 113 106 247

White 22,516 26,113 24,696 25,895 28,041 31,827 38,426

6–34 12,216 13,249 12,729 14,018 15,089 17,441 22,235

12–17 250 225 247 1,090 489 398 701

18–25 3,570 3,680 4,532 5,062 6,705 9,461 11,606

26–34 8,395 9,344 7,950 7,865 7,895 7,582 9,929

35+ 10,285 12,849 11,947 11,859 12,919 14,355 16,075

Unknown 15 14 21 19 33 31 115

Black 25,996 27,047 28,295 26,490 27,616 28,646 30,934

6–34 10,566 10,733 9,941 9,393 9,070 9,343 8,986

12–17 29 97 41 46 42 148 50

18–25 2,989 2,904 1,969 2,172 1,696 1,901 1,716

26–34 7,547 7,730 7,932 7,176 7,330 7,293 7,219

35+ 15,381 16,274 18,295 17,053 18,503 19,266 21,913

Unknown 49 40 59 44 42 38 36

Hispanic 9,423 9,814 11,739 9,145 11,448 11,779 14,944

6–34 5,012 4,518 5,036 4,023 4,957 4,726 7,251

12–17 43 35 49 120 168 87 106

18–25 1,146 1,040 1,486 1,211 1,514 1,834 3,200

26–34 3,823 3,443 3,501 2,691 3,274 2,806 3,946

35+ 4,404 5,287 6,693 5,120 6,481 7,046 7,672

Unknown 6 8 9 2 11 7 20

(continued on next page)
Adverse Social, Behavioral, and Health Consequences

120

Table 37 (continued). Estimated Number of DAWN Emergency Department Visits 

With Mention of Heroin/Morphine, by Race/Ethnicity and Age, 1994–2000

Race/Ethnicity

and Age 1994 1995 1996 1997 1998 1999 2000

American Indian/

Alaska Natives 83 87 78 128 58 40 76

6–34 35 32 30 22 22 16 36

12–17 * * 1 * * 1 1

18–25 9 12 15 4 6 10 12

26–34 25 20 15 18 16 5 23

35+ 48 55 47 106 36 23 39

Unknown * * * * * * 1

Asian/Pacific 

Island 127 223 178 248 358 175 290

6–34 66 94 99 104 220 106 202

12–17 1 2 8 9 * 1 60

18–25 20 34 34 47 110 61 86

26–34 44 58 57 47 111 43 56

35+ 61 129 78 144 137 69 88

Unknown * * * * * * *

Unknown 4,938 6,217 7,781 8,522 7,946 9,501 10,125

6–34 2,183 2,670 3,687 3,732 3,764 4,059 4,147

12–17 41 36 146 97 197 40 134

18–25 589 699 1,120 1,183 1,199 1,616 1,444

26–34 1,553 1,935 2,420 2,452 2,368 2,403 2,569

35+ 2,669 3,517 4,075 4,759 4,158 5,412 5,903

Unknown 86 30 20 31 24 30 75

Other 76 56 214 284 222 225 10

6–34 37 22 22 65 102 40 1

12–17 * * * 3 * * * 

18–25 12 7 10 22 21 17 * 

26–34 26 16 12 40 81 22 1

35+ 38 33 192 219 117 185 9

Unknown * * * * 2 * *

*Low precision, no estimate reported.

SOURCE: Office of Applied Studies, Substance Abuse and Mental Health Services Administration, Drug Abuse Warning Network, 2001a.
Adverse Social, Behavioral, and Health Consequences

121

Table 38. Estimated Number of DAWN Emergency Department Visits With Mention of

Methamphetamine/Speed, by Race/Ethnicity and Age, 1994–2000

Race/Ethnicity

and Age 1994 1995 1996 1997 1998 1999 2000

Total 17,537 15,934 11,002 17,155 11,485 10,448 13,506

6–34 13,199 11,706 7,828 12,451 8,250 7,121 9,044

12–17 1,960 1,438 1,028 1,810 1,081 808 1,120

18–25 5,432 4,787 3,728 4,718 3,482 3,289 3,711

26–34 5,804 5,481 3,004 5,924 3,686 2,988 4,211

35+ 4,327 4,221 3,165 4,696 3,230 3,316 4,456

Unknown 11 7 9 7 6 10 4

White 12,223 10,259 6,779 11,802 8,449 7,180 8,600

6–34 9,294 7,383 4,907 8,199 6,051 4,865 5,548

12–17 1,609 758 752 1,371 974 529 754

18–25 3,730 2,858 2,407 2,655 2,558 2,202 2,333

26–34 3,952 3,767 1,679 4,172 2,520 2,134 2,462

35+ 2,924 2,871 1,870 3,596 2,398 2,308 3,050

Unknown 6 4 2 7 * 6 2

Black 983 927 800 866 490 637 837

6–34 444 675 339 555 266 327 606

12–17 15 17 15 7 8 14 8

18–25 80 176 90 218 71 110 201

26–34 350 483 235 330 187 166 397

35+ 539 251 461 311 223 309 229

Unknown * 1 * * 1 1 3

Hispanic 2,607 2,865 1,674 2,553 1,479 1,489 2,177

6–34 2,122 2,230 1,382 2,245 1,161 1,117 1,731

12–17 279 428 203 287 58 175 237

18–25 1,018 1,156 670 1,237 565 578 688

26–34 825 646 509 721 537 364 804

35+ 483 635 292 309 318 370 446

Unknown 2 * * * * 1 *

(continued on next page)
Adverse Social, Behavioral, and Health Consequences

122

Table 38 (continued). Estimated Number of DAWN Emergency Department Visits 

With Mention of Methamphetamine/Speed, by Race/Ethnicity and Age, 1994–2000

Race/Ethnicity

and Age 1994 1995 1996 1997 1998 1999 2000

American Indian/

Alaska Natives 22 157 86 14 9 9 136

6–34 21 23 9 14 3 6 5

12–17 2 2 1 1 * 1 * 

18–25 10 15 4 8 * 4 3

26–34 863531 1

35+ 1 133 77 * 7 3 131

Unknown ****** *

Asian/Pacific 

Island 79 243 68 105 65 104 183

6–34 65 222 59 86 49 86 155

12–17 16 116 6 10 9 3 41

18–25 32 84 29 36 23 67 77

26–34 17 22 24 40 17 16 38

35+ 14 21 9 19 16 18 27

Unknown ***** *

Unknown 1,612 1,473 1,428 1,680 985 982 1,573

6–34 1,248 1,164 1,042 1,223 716 711 1,000

12–17 37 117 49 67 32 85 81

18–25 560 489 520 503 264 320 409

26–34 651 557 472 653 420 306 509

35+ 360 308 379 457 265 270 573

Unknown 4 1 7 * 5 1 * 

Other 11 10 167 135 8 47 * 

6–34 5 9 90 130 4 9 * 

12–17 2 * 2 67 * * * 

18–25 1 9 7 61 2 8 * 

26–34 1 * 82 2 3 1 * 

35+ 6 1 76 4 4 38 * 

Unknown ****** *

*Low precision, no estimate reported.

SOURCE: Office of Applied Studies, Substance Abuse and Mental Health Services Administration, Drug Abuse Warning Network, 2001a.
Adverse Social, Behavioral, and Health Consequences

123

Table 39. Estimated Number of DAWN Emergency Department Visits With Mention of

Marijuana/Hashish, by Race/Ethnicity and Age, 1994–2000

Race/Ethnicity

and Age 1994 1995 1996 1997 1998 1999 2000

Total 40,035 45,259 53,770 64,721 76,841 87,067 96,426

6–34 31,681 35,269 41,308 47,485 55,815 61,605 68,047

12–17 6,513 7,972 9,980 11,057 13,137 12,730 15,678

18–25 13,671 14,798 15,722 19,385 22,895 27,266 30,413

26–34 11,489 12,473 15,433 16,912 19,760 21,410 21,841

35+ 8,308 9,877 12,387 17,039 20,789 25,387 28,271

Unknown 46 113 75 196 237 75 108

White 18,810 20,883 24,503 31,892 38,432 45,395 49,015

6–34 15,330 16,863 19,582 24,141 29,656 33,665 34,604

12–17 3,955 4,579 5,537 6,988 8,400 7,505 8,909

18–25 6,421 7,211 7,398 9,276 11,588 14,840 15,441

26–34 4,953 5,061 6,496 7,874 9,658 11,156 10,174

35+ 3,465 3,944 4,906 7,669 8,709 11,707 14,374

Unknown 15 76 16 82 67 23 36

Black 14,896 16,895 18,936 21,056 24,430 25,607 26,446

6–34 11,113 12,297 13,068 14,296 15,396 15,889 16,903

12–17 1,148 1,753 1,962 1,536 1,553 1,749 2,167

18–25 4,913 4,780 4,899 5,986 6,444 7,239 7,895

26–34 5,045 5,752 6,196 6,763 7,391 6,875 6,817

35+ 3,770 4,575 5,837 6,668 9,005 9,697 9,508

Unknown 13 22 32 92 29 21 35

Hispanic 3,100 3,743 6,301 6,735 7,666 9,064 11,739

6–34 2,607 3,046 5,439 5,252 6,063 6,886 9,544

12–17 850 701 1,551 1,722 2,020 2,135 2,801

18–25 1,051 1,540 1,981 2,260 2,525 3,038 4,193

26–34 706 804 1,899 1,155 1,514 1,709 2,539

35+ 491 691 855 1,470 1,548 2,169 2,177

Unknown 3 7 7 13 55 9 17

(continued on next page)
Adverse Social, Behavioral, and Health Consequences

124

Table 39 (continued). Estimated Number of DAWN Emergency Department Visits 

With Mention of Marijuana/Hashish, by Race/Ethnicity and Age, 1994–2000

Race/Ethnicity

and Age 1994 1995 1996 1997 1998 1999 2000

American Indian/

Alaska Natives 55 136 63 58 112 66 123

6–34 42 57 36 47 95 52 37

12–17 9 13 8 16 54 13 15

18–25 9 26 16 10 21 21 8

26–34 24 18 11 21 20 18 13

35+ 13 77 27 11 17 13 86

Unknown * 1 * * * * * 

Asian/Pacific 

Island 206 196 267 297 280 461 468

6–34 190 177 234 277 171 421 391

12–17 27 53 59 50 37 125 79

18–25 140 79 139 163 82 154 235

26–34 23 45 36 62 51 142 78

35+ 16 19 28 20 109 40 76

Unknown * * 4 * * * 1

Unknown 2,924 3,337 3,647 4,514 5,817 6,285 8,624

6–34 2,371 2,773 2,910 3,323 4,352 4,559 6,558

12–17 512 859 858 720 1,061 1,189 1,703

18–25 1,121 1,137 1,265 1,591 2,196 1,880 2,636

26–34 736 775 787 1,013 1,093 1,489 2,218

35+ 542 558 720 1,182 1,378 1,704 2,049

Unknown 11 6 17 9 86 22 18

Other 44 69 53 169 104 189 11

6–34 29 57 38 149 81 132 10

12–17 12 14 6 24 11 15 4

18–25 16 25 23 100 38 94 4

26–34 1 18 9 25 33 22 2

35+ 11 13 15 19 23 57 1

Unknown 4 * * * * * * 

*Low precision, no estimate reported.

SOURCE: Office of Applied Studies, Substance Abuse and Mental Health Services Administration, Drug Abuse Warning Network, 2001a.
Adverse Social, Behavioral, and Health Consequences

125

Table 40. Percentage of DAWN Hospital Emergency Department Drug Abuse Episodes, 

by Selected Episode Characteristics, Sex, and Race/Ethnicity: 2000

Males Females

Episode Characteristics1 White Black Hispanic White Black Hispanic

Drug concomitance

Single-drug episodes 40.1 40.3 42.9 45.0 46.4 48.3

Multi-drug episodes 59.9 59.7 57.1 55.0 53.6 51.7

Patient disposition

Treated and released 44.9 54.1 55.9 37.6 52.0 48.3

Admitted to hospital 50.9 42.9 39.8 59.5 45.0 49.2

Other 4.2 3.0 4.3 2.9 3.0 2.5

SOURCE: Office of Applied Studies, Substance Abuse and Mental Health Services Administration, Drug Abuse Warning Network, 2001a.

Table 41. Comparison of Race/Ethnicity Distribution for Total DAWN Hospital

Emergency Episodes With Race/Ethnicity Distribution for Selected Drug Mentions: 2000

Race/Ethnicity

Selected Drug Mention White Black Hispanic

Percentage of Total DAWN ER episodes 57.5 21.4 10.9

Percentage of ER drug mention

Heroin/morphine 40.5 32.6 15.8

Methadone 67.9 10.4 8.6

LSD 72.6 6.3 9.7

PCP/PCP combinations 42.1 35.1 12.5

Cocaine 34.2 43.4 13.6

Marijuana/hashish 50.8 27.4 12.2

Amphetamine 63.9 5.6 15.4

Methamphetamine/speed 63.7 6.2 16.1

SOURCE: Office of Applied Studies, Substance Abuse and Mental Health Services Administration, Drug Abuse Warning Network, 2001a.
Adverse Social, Behavioral, and Health Consequences

126

a

Excludes data on homicides, deaths in which AIDS was reported, and deaths in which "drug unknown" was the only substance mentioned. b

Includes opiates not specified as to type.

c

Does not include methamphetamine or other unspecified amphetamines.

NOTES: Percentages are based on raw medical examiner drug abuse cases counts of 8,516 male decedents and 3,083 female decedents.

Percentages are based on total raw medical examiner drug abuse case counts of 7,042 white decedents, 3,023 black decedents, 

and 1,286 Hispanic decedents.

SOURCE: Substance Abuse and Mental Health Service Administration, Drug Abuse Warning Network, 1999 Annual Report.

Table 42. Drugs Mentioned Most Frequently by Medical Examiners, 

by Sex and Race/Ethnicity of Decedents: 1999

Percentage of Percentage of

Rank Drug Name Total Episodesa Rank Drug Name Total Episodesa

Male Patients Female Patients

1 Heroin/Morphine b 45.3 1 Cocaine 33.3

2 Cocaine 44.8 2 Heroin/Morphine b 30.6

3 Alcohol-in-Combination 37.2 3 Alcohol-in-Combination 23.6

4 Codeine 12.4 4 Codeine 10.7

5 Diazepam 6.7 5 Diphenhydramine 8.6

6 Marijuana/Hashish 6.5 6 Diazepam 7.6

7 Methamphetamine/Speed 6.3 7 Amitriptyline 7.3

8 Methadone 5.1 8 d-Propoxyphene 6.8

9 Diphenhydramine 4.4 9 Methadone 6.7

10 Amphetaminec 4.1 10 Acetaminophen 6.5

White Patients Black patients

1 Heroin/Morphine b 41.4 1 Cocaine 64.1

2 Alcohol-in-Combination 33.0 2 Heroin/Morphine b 39.5

3 Cocaine 32.1 3 Alcohol-in-Combination 31.2

4 Codeine 12.4 4 Codeine 11.4

5 Diazepam 9.3 5 Marijuana/Hashish 4.7

6 Methamphetamine/Speed 7.9 6 Diphenhydramine 4.6

7 Marijuana/Hashish 6.6 7 Lidocaine 4.5

8 Methadone 6.4 8 Quinine 4.1

9 Diphenhydramine 6.3 9 Methadone 3.9

10 d-Propoxyphene 5.6 10 Diazepam 2.9

Hispanic Patients

1 Heroin/Morphine b 46.7 6 Methadone 4.9

2 Cocaine 45.2 7 Lidocaine 4.7

3 Alcohol-in-Combination 42.9 8 Marijuana/Hashish 4.0

4 Codeine 11.8 9 Diazepam 3.6

5 Methamphetamine/Speed 5.4 10 Amphetaminec 3.3
Adverse Social, Behavioral, and Health Consequences

127

Figure 13. Manner of Drug-Related Death, by Race/Ethnicity, 

DAWN Medical Examiner Data: 1999

SOURCE: Drug Abuse Warning Network, Substance Abuse and Mental Health Services Administration, 1999 (July 2000 update).

100

90

80

70

60

50

40

30

20

10

0

Percent

59

6.1

34.9

68.3

11.4

20.4

50.9

21

28.1

Black Hispanic White

Race/Ethnicity

Accidental

Suicide

Other/Unknown

129

Drug-related crime is considered one of the major problems facing the United States today. This problem

encompasses concern about public safety and crime-related injuries suffered by our citizens, as well as the high

cost of law enforcement to control drug-related crime (Miller 1992, Harrison and Backenheimer 1998). Much

has been learned from recent efforts to evaluate different approaches to reduce drug-related crime. Nonetheless,

as reported recently by a committee of the National Research Council, much remains to be learned before we

can be certain about the policy instruments chosen to control drug-related crime (Manski et al. 2001).

A casual visit to local drug courts provides convincing evidence that drug use is linked to criminal offending

such as theft and assault. Perpetrators testify that the use of methamphetamine, cocaine, heroin, and alcohol is

at the root of their crimes and caused them to violate the law. Victims often explain that they were intoxicated

and made vulnerable to attack by virtue of their own drug use. However, this abundance of testimonial evidence

must be counterbalanced by an appreciation that many of the perpetrators were prone to criminal offending

and might have committed the crime even if drugs never had been used. Many perpetrators have a history 

of aggressive misbehavior, social maladaptation, and delinquency that stretches back well before their drug use

ever started.

Several lines of research are shedding new light on the link between drugs and crime. Goldstein and Brownstein

proposed and refined a tripartite descriptive framework that has inspired one of these lines of research within

criminology (Goldstein 1985; Brownstein and Goldstein 1990). Although their conceptualization drew primarily

from experience during the late 1970s and early 1980s cocaine epidemic, the tripartite framework also has been

applied to other drugs. In brief, they sorted drug-related crimes into offenses that may be understood as a consequence of acute drug intoxication per se, those of a more economic-compulsive nature arising from longer

term neuroadaptation that follows repeated drug use, and those that are more systemic and interlinked with

social context and individual propensities that promote criminal activity, even when the perpetrators are not

drug users (e.g., with respect to high-level drug trafficking). Crimes of the first “pharmacological” type include

assaults that might be precipitated by paranoia or delusions caused by the use of phencyclidine (PCP), sustained

methamphetamine use (e.g., “ice smoking”), or cocaine self-administration. Examples of crimes of the second

“economic-compulsive” type include shoplifting, theft, and robbery with a goal of securing enough money to

buy enough heroin to stave off withdrawal symptoms. Crimes of the “systemic” type include intergang violence

such as drive-by shootings intended to intimidate or kill street-level drug dealers who have crossed boundaries

of local market control. This type of crime also includes the criminal activity of drug users who would have been

committing crimes even if they never had used drugs (e.g., due to predisposing liabilities and susceptibilities 

of complex origin—history of child abuse, incomplete socialization, difficult temperament, and antisocial 

personality disorder).

Evidence from highly controlled laboratory studies and epidemiological field research has clarified the importance

of acute pharmacological effects with respect to aggression. Nonetheless, it is important to note that drug 

self-administration does not always produce aggression or aggressive behavior. The link between drug use and

aggression, if any, is heavily dependent on factors such as the specific drug being studied, the setting and 

conditions of drug use, and other explanatory conditions and processes.

Chapter 7. DRUGS AND CRIME
Drugs and Crime

In many respects, the evidence to date is most compelling with alcoholic beverages; it is less compelling 

with drugs like marijuana, LSD, and ecstasy (methylenedioxymethamphetamine). With cocaine and other 

psychostimulant drugs, there is mixed evidence: Under some circumstances and with some species of laboratory

animals, there appears to be a release of aggression or aggressive behavior after drug exposure, but not under all

circumstances and not with all species. The category of pharmacologically induced crimes encompasses the role

of intoxication as a predisposing vulnerability for victims of crime (e.g., see Coker et al. 2000).

Evidence from ethnographic, criminal justice, clinical, and social survey research has clarified the importance of

the economic-compulsive type of drug crimes described by Goldstein and Brownstein. In this respect, finegrained investigations of day-to-day behavior of street-level drug users have been important and have disclosed

cycles of drug-taking behavior followed by drug withdrawal states and drug-seeking behavior, followed by more

drug use (e.g., Grapendaal 1992; Nurco et al. 1991; Nurco 1998; Lipton et al. 1998; Britton 1998; Conroy

1999). As observed, this cycle sometimes includes gainful employment to secure income for drug purchases and

sometimes involves shoplifting, petty theft, robbery and assault, procurement, or prostitution. 

Observational studies of the criminal behavior of drug users before, during, and after treatment and incarceration

also have helped illuminate possible links between drug withdrawal symptoms and criminal activity. At least

during the initial periods of treatment and unless there is relapse to drug use, there are reductions in criminal

offending. There is some evidence that individuals using drugs several times a day are more likely to be involved

in criminal activity than are those who are less regular in their drug use. In one study, heavily dependent drug

users were found to commit four to six times more crime during periods of heavy drug use than during periods

when they were relatively drug free. These links between drug use and crime seem to have been exacerbated 

during the late 20th-century epidemic of crack-cocaine smoking. Whereas most of the evidence on these 

relationships has been derived from nonexperimental observational studies, a few randomized clinical trials have

tended to confirm these findings from observational research, with reductions in criminal activity being

observed even within the more highly standardized and controlled confines of experimental research, especially

when social and psychological services have been provided in addition to pharmacological treatments (Hunt et

al. 1984; Nurco et al. 1989; Brecht et al. 1990-91; Miller 1992; Bureau of Justice Statistics 1996; Bell et al 1997;

Lipton et al. 1998; Nurco 1998; Wexler et al. 1998; McClellan et al. 1998; MacDonald et al. 1999; Harwood

et al. 2001).

There is a small but growing base of evidence on the more systemic form of drug-related crime. Recent studies

on the neighborhood and gang contexts of drug use and drug trafficking are informative, and some studies 

provide suggestions for community action to reduce drug and crime problems (e.g., Fagan and Chin 1990;

Hillenbrand and Davis 1993; Waldorf 1993; Clapp 1995; Popkin et al. 1995; Surratt 1995; Curtis 1998;

Fleisher 1998; Van Nostrand and Tewksbury 1999; Barton 1999). Several pioneering investigators have probed

the generally neglected world of high-level drug traffickers (Natarajan and Belanger 1998).

During the late 20th century, it became virtually impossible to study interrelationships between drugs and crime

in the United States without paying attention to the life circumstances of U.S. citizens who are members of

racial/ethnic minority groups. The recent surge in arrests, convictions, and incarcerations across the United

States has been fueled mainly by increases in drug-related law enforcement, prosecution, and judicial activity.

For example, Federal prison drug-related sentences increased by 290 percent between 1980 and 1995; more

than one-half of all Federal offenders sentenced to prison in 1996 were convicted of drug offences (Bureau of

130
Drugs and Crime

Justice Statistics 1996). In general, members of racial/ethnic minorities are more likely to be arrested, more likely

to be convicted once arrested, and more likely to be incarcerated once convicted; the disproportionate representation of minority group members is especially true for drug-related offenses of virtually all types (e.g., Blumstein

and Beck 1999; A. Blumstein, personal communication). Processes of selection that yield disproportionate 

representation of minority group members, including police practices such as racial profiling, must be taken into

account when examining and drawing interpretations from administrative and social statistics on drugs and

drug-related crimes (e.g., see Bush-Baskette 1998; Leiber and Stairs 1994; Kalunta-Crumpton 1999).

The manifestations of links between drugs and crime also appear in medical statistics from hospital emergency

rooms (ERs) and medical examiners. For example, in a 1991 review of hospital ER records for individuals

treated for violence-related injuries, about 14 percent of the records indicated the victim or someone else

involved in the incident had been drinking alcohol or using drugs (Bureau of Justice Statistics 1996).

Research on causes of homicide in three metropolitan areas indicates that about 25 percent to 50 percent of all

homicides are drug related (Bureau of Justice Statistics 1996). Homicide in general and drug-related homicides

disproportionately affect African Americans. For example, the National Center for Health Statistics has reported

a range of age-adjusted homicide death rates that indicates 20 to 30 homicide deaths per 100,000 non-Hispanic

Blacks for each year between 1995 and 1999 (National Center for Health Statistics 2000). During that same

period, the corresponding values were much lower for American Indian/Alaska Natives (9–11 homicide deaths

per 100,000), Hispanics (8 to 13 homicide deaths per 100,000), non-Hispanic Whites (3–5 homicide deaths

per 100,000), and Asian/Pacific Islanders (3 to 5 homicide deaths per 100,000).

The other administrative statistics on drugs and crime reported in this chapter come from two sources: the

Arrestee Drug Abuse Monitoring (ADAM) Program of the National Institute of Justice (NIJ) and Bureau of

Justice Assistance (BJA), which represents a refinement and more rigorous form of the former NIJ/BJA Drug

Use Forecasting (DUF) system, and the National Household Survey on Drug Abuse (NHSDA). Co-funded by

NIJ and BJA, the ADAM Program measures recently active drug use among booked arrestees at multiple

selected sites in major metropolitan areas across the United States. The primary purpose of ADAM is to monitor

illegal drug use among booked arrestees in major U.S. cities. It provides information about the effectiveness of

local drug policies and practices and provides a solid basis for resource allocation decisions. By collecting urine

samples and periodically interviewing arrestees, ADAM has become a consistent tool for tracking drug use

trends among this difficult-to-study population of users. In reports on these statistics, ADAM administrators

urge cautious interpretation because ADAM sites do not constitute a nationally representative sample and

because of other methodological reasons. Nonetheless, the ADAM statistics now provide our most complete

view of drug experiences among booked arrestees in the United States. Methodological limitations of the

NHSDA data (e.g., reliance on self-report) have been described in Chapter 1 of this report and elsewhere 

(e.g., see Anthony et al. 2000; Manski et al. 2001).

DRUG USE AMONG BOOKED ARRESTEES

The following information is from a standardized data set and reports based upon all DUF and ADAM urinalysis

tests from 1987 to 1999 (see Table 43). The data show interesting trends in marijuana use across races and

through time, as indicated by tests to screen for recently active marijuana use (i.e., use within the 2 to 4 weeks

before testing). 

131
Drugs and Crime

In the table’s first column, rows 1–13 show time trends for Whites. This range of values is relatively stable, with

positive marijuana test values between 23 and 40 percent. The lowest values (25 percent and 23 percent) occurred

in 1990 and 1991. By 1998–1999, the percentage was 36 percent, almost as large as the largest values in the

series, 39 to 40 percent, which were observed in 1987 and 1988. Similar trends and values were observed for

Blacks and Hispanics, also with relatively low values in 1990–1991, and with values of 33 to 42 percent

observed in 1998–1999.

Due to sample size limitations, DUF and ADAM provide much less information about American Indian/Alaska

Native and Asian/Pacific Islander groups; the precision of these estimates is constrained, as is their capacity for

national projections. Nonetheless, the observed values for the final years of the 20th century indicate values for

American Indian/Alaska Native arrestees that are not too distant from values observed for the above-listed

groups; that is, the recent drug-taking experience of American Indian/Alaska Native arrestees seems not to differ

substantially from the recent drug-taking experience of nonminority arrestees. Values for Asian/Pacific Islanders

are generally lower than values observed for the other groups (Table 43). Whether this difference is an artifact

of sampling or methodology is unknown. There is a firmly established site-to-site variation in the prevalence of

positive marijuana urinalysis test results and in the trends over time (Golub and Johnson 2001), and there is no

ADAM site in Hawaii, where marijuana experience may be substantially different from what is observed on the

U.S. mainland (National Institute on Drug Abuse 2001a). Whether the observed trends are artifacts of changes

in the DUF/ADAM methodologies is an item on the agenda for future research; some investigators believe that

the methodologies of recent years are stable enough to warrant discussion of an emerging marijuana use epidemic

among arrestees in many (but not all) of the areas with ADAM coverage (Golub and Johnson 2001).

The DUF/ADAM values for cocaine urinalysis results reflect the experience of booked arrestees not only for

cocaine hydrochloride powder (whether insufflated, injected, or taken by mouth), but also for other forms of

cocaine, such as crack, freebase, and coca paste; this bioassay cannot discriminate one route of administration

or dosage form from another. It also is noteworthy that the sensitivity of the test for cocaine metabolites in urine

is high for the first 24 hours after cocaine use, but then declines. Whereas the urinalysis test for marijuana might

detect marijuana used up to 1 month or so before arrest, the corresponding urine test for cocaine will have a

detection window of less than 1 week, and often has sensitivity for no more than 1 to 3 days, depending on

individual circumstances and conditions of use, metabolism, biotransformation, and excretion.

With respect to cocaine of all forms, the African-American arrestees were more likely to test positive in every

year under study, with higher values in the first DUF years (e.g., 56 to 63 percent) and with tangibly lower values

in the most recent years (e.g., 41 to 45 percent). In these recent years, corresponding values for Whites and

Hispanics have been somewhat lower (25 to 26 percent and 31 to 32 percent, respectively), but the lowest values

have been observed for Asian/Pacific Islander and American Indian/Alaska Native arrestees (18 to 19 percent

and 12 to 15 percent, respectively). Whether these differences reflect true between-group variations in the prevalence of actual cocaine use in the U.S. population is unknown. For example, the White-Black difference is not

observed in self-report data on cocaine use from the NHSDA and the Monitoring the Future (MTF) surveys,

and the magnitude of the observed differences might well be due to race-biased selection processes that lead an

individual to be identified, apprehended, booked, and sent to an arrest facility with ADAM coverage. That is,

cocaine-using African Americans may be more likely to be apprehended and booked for arrest than are cocaineusing individuals of other racial/ethnic subgroups (e.g., see pertinent discussion by Manski et al. 2001).

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Drugs and Crime

The third column of values in Table 43 shows DUF/ADAM evidence on the arrestees’ experience with heroin,

methadone, morphine, oxycodone, codeine, and other opiate or opioid drugs, whether administered for legitimate

medical reasons (e.g., methadone maintenance, pain relief, and cough suppression) or for extramedical reasons

(e.g., to get high). Note that in recent years White, Black, and Hispanic arrestees all are equally likely 

to test positive for the opiate/opioid drugs. Values for the other two racial/ethnic minority groups are 

somewhat smaller.

NIJ began testing arrestees for methamphetamine use in 1991. The two racial/ethnic arrestee groups with the

highest values are Whites and Asian/Pacific Islanders. By comparison, African-American arrestees are extremely

unlikely to test positive for methamphetamines (e.g., 0.8 percent in 1999); Hispanics are intermediate (6 percent).

DRIVING UNDER THE INFLUENCE OF ALCOHOL OR ILLEGAL DRUGS

NIDA has made a concerted effort to support research projects on links between drug use, delinquency, and

crime, including highly controlled experimental research in laboratory settings, clinical studies, epidemiological

studies, ethnographies, and anthropological investigations. In the 1970s, NIDA initiated a line of NHSDA

research on drugs and criminal activities, which has been sustained and elaborated by the Substance Abuse and

Mental Health Services Administration.

In recent years, NHSDA assessments have included questions on various illegal activities. One question asked

of respondents is whether, during the 12 months before being interviewed they had driven any kind of vehicle

while they were under the influence (DUI) of alcohol or illegal drugs. Table 44 presents data on driving under

the influence by age, sex, and two broad race/ethnicity groups (White/Black), based on estimates from NHSDA

1998. Within the noninstitutionalized population surveyed for NHSDA (age 12 and older), an estimated 10.3

percent reported DUI behavior, but this estimate is heavily influenced by a large number of youth ages 12–15

who do not drive. A more informative value is presented for people ages 18–25, among whom about one-fifth

reported DUI episodes (21.7 percent), with males ages 18–25 almost twice as likely to be DUI drivers than

females in the same age group. Estimates for adults age 26–34 and for those age 35 and older are somewhat

lower than the observed values for those ages 18–25, but the male-female differences are maintained even in the

older age groups.

DUI driving is substantially more likely among Whites, both male and female, than among African Americans.

For example, about one in three White males ages 18–25 were DUI drivers (31.1 percent); the corresponding

value is 13.3 percent for African-American males ages 18–25. Whereas the occurrence of DUI driving generally

shows a marked decline across the three older age groups depicted in Table 44, this is not the case for AfricanAmerican males and females younger than age 35. Among African Americans ages 18–25 and 25–34, the 

estimated prevalence values for DUI driving are 9.3 percent and 8.9 percent, respectively (Table 44).

Males are more likely to drive under the influence of alcohol or illegal drugs across all age and racial groupings,

with the exception of the 12–17 age group. In this youngest age group, adolescent girls are just as likely as 

adolescent boys to have been DUI drivers. Given the level of precision of these DUI estimates, the male-female

differences for youth ages 12–17 are so small as to be negligible.

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Drugs and Crime

SUMMARY

Links between drugs, delinquency, and crime continue to inspire investigators from a broad range of disciplines—

from the bench and laboratory sciences such as pharmacology to the clinical and field research sciences such as

epidemiology, criminology, and ethnography (e.g., see Anthony and Forman 2002). Studies on these links have

special policy implications and warrant continuing public scrutiny (e.g., see Manski et al. 2001).

Criminal justice and medical statistics are sufficient to draw our attention to disparities in how drugs and crimes

affect U.S. racial/ethnic minority groups. African Americans, especially, exhibit excess rates of arrest, conviction,

and incarceration for drug-related crimes and of homicide in general and drug-related homicide in particular.

These observed excess rates of criminal justice incidents and medical casualties are not consistent with other 

evidence on the drug experiences of African Americans in the United States (e.g., from NHSDA and MTF). As

such, this is a topic that deserves special focus in research on the social and health disparities affecting our

African-American citizens.

Subject to the methodological constraints already discussed, data from the DUF/ADAM Program are used to

examine the drug experiences of booked arrestees in selected sites across the United States. In recent years, the

percentage of White arrestees testing positive for marijuana (34 to 36 percent) has been approaching the 

percentage of African-American arrestees testing positive (39 to 42 percent), and the percentage of AfricanAmerican arrestees testing positive for opiate/opioid drugs (6 to 8 percent) has been approaching the percentage

of White arrestees testing positive for these drugs (9 percent). Corresponding values for other racial/ethnic

minority groups are generally not too distant from the values observed for Whites; or are lower (e.g. for the

Asian/Pacific Islander arrestees.)

Data for cocaine and for methamphetamine present the most noteworthy variation across booked arrestee 

subgroups. African-American arrestees are most likely to test positive for cocaine after booking, whereas they 

are extremely unlikely to test positive for methamphetamine. In recent years, Asian/Pacific Islander arrestees are

observed to have the lowest test-positive values for cocaine, among all subgroups studied, but 11–14 percent 

are testing positive for methamphetamine, which is close to the observed value for Whites (13–15 percent). The

ADAM data on methamphetamine experiences of Asian/Pacific Islander Americans is convergent with other

data sources, especially where these other data sources represent the experience of Hawaiians and other Pacific

Islanders specifically (e.g., see Furr et al. 2000; Substance Abuse Mental Health Services Administration 1997,

1998, 1999b, 2000a, 2000b, 2001a).

Data from NHSDA illuminate the experience of Americans driving under the influence of alcohol or illegal

drugs. Overall, in 1998, nearly twice as many Whites had driven under the influence as had African Americans.

This disparity is even more pronounced among White youth, who are two to three times more likely to have

driven under the influence during that 12-month interval. A general male excess in the occurrence of DUI 

driving appears for both White and African-American subgroups of the population, but it is not present for 

adolescents (ages 12–17). This is a pattern of DUI findings that merits future research, especially if the absence

of a male-female difference among adolescents is a signal of a future increasing trend for DUI driving in birth

cohorts born within the past two decades.

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Drugs and Crime

The DUF/ADAM data provide a reminder of the heterogeneity within the broad “minority” category that often

is used to designate members of African-American, Hispanic, Asian/Pacific Islander, and American

Indian/Alaska Native groups. Without attention to this heterogeneity, we would not be able to discover the 

disparate experience of African-American arrestees with cocaine, nor the excess burden of Asian/Pacific Islanders

with methamphetamine.

This chapter does not speak to the heterogeneity within the major racial/ethnic minority categories, due to 

sample size constraints. In future revisions of this report, it should be possible to take advantage of the continued

growth in ADAM and NHSDA samples to shed new light on variations within minority groups, such as we

have illustrated in Chapter 3. In addition, new data from the Centers from Disease Control and Prevention, the

National Longitudinal Study of Youth, and other sources can be tapped to provide a more complete picture of

the relationships between drugs and crime, within and between the important racial/ethnic minority groups of

the U.S. population.

135
Drugs and Crime

136

Table 43. Estimated Prevalence of Positive Urinalysis Tests from the 

Arrestee Drug Abuse Monitoring Program: 1987–1999

Race/Ethnicity and Year Marijuana Cocaine Opiates Methamphetamine*

White

1987 39 26 13 N/A

1988 40 31 13 N/A

1989 30 32 11 N/A

1990 25 26 10 N/A

1991 23 29 9 7

1992 27 32 9 7

1993 29 31 10 14

1994 27 30 9 17

1995 28 29 10 14

1996 35 28 9 10

1997 34 26 9 13

1998 36 25 9 14

1999 36 26 9 15

Black

1987 36 56 10 N/A

1988 35 63 10 N/A

1989 21 61 8 N/A

1990 16 53 8 N/A

1991 15 56 6 0.3

1992 22 55 6 0.3

1993 26 54 7 0.6

1994 28 53 7 0.8

1995 30 50 7 0.8

1996 40 43 6 0.3

1997 39 41 6 0.7

1998 40 42 7 0.7

1999 42 45 8 0.8

(continued on next page)
Drugs and Crime

137

Race/Ethnicity and Year Marijuana Cocaine Opiates Methamphetamine*

Hispanic

1987 34 43 22 N/A

1988 34 51 21 N/A

1989 25 43 18 N/A

1990 21 36 15 N/A

1991 20 38 13 2

1992 23 39 12 3

1993 25 37 13 5

1994 25 36 12 6

1995 25 33 11 7

1996 34 29 9 5

1997 33 26 8 8

1998 34 32 8 5

1999 33 31 9 6

American Indian/

Alaska Native

1995 37 19 7 4

1996 29 23 9 6

1997 36 14 5 6

1998 37 19 5 4

1999 34 18 4 3

Asian/Pacific

Islander

1995 9 20 5 7

1996 14 11 2 9

1997 17 9 3 14

1998 17 12 2 13

1999 22 15 1 11

Table 43 (continued). Estimated Prevalence of Positive Urinalysis Tests from the 

Arrestee Drug Abuse Monitoring Program: 1987–1999

*The denominator of prevalence includes all the arrestees.

N/A: Not applicable.

SOURCE: National Institute of Justice, Arrestee Drug Abuse Monitoring Program, 2001a-c.
Drugs and Crime

138

Table 44. Estimated Percentage of People Having Driven a Vehicle Under the Influence

of Alcohol or Illegal Drugs in the Past 12 Months, by Race, Sex, and Age: 1998

Age Group

Race and Sex 12 and Older 12–17 18–25 26–34 35+

All races

Both sexes 10.3 3.5 21.71 4.3 8.0

Male 14.6 3.7 27.9 19.4 12.3

Female 6.3 3.2 15.4 9.4 4.3

White

Both sexes 11.2 3.9 24.6 15.7 8.7

Male 15.7 4.1 31.1 20.8 13.1

Female 7.0 3.7 17.7 10.5 4.8

Black

Both sexes 5.4 1.7 9.3 8.9 3.9

Male 8.3 1.8 13.3 14.1 6.4

Female 3.0 1.6 5.5 4.6 2.1

SOURCE: National Household Survey on Drug Abuse, Substance Abuse and Mental Health Services Administration. Office of Applied 

Studies, 2000a.
139

This report examines issues linked to health disparities now experienced by members of racial and ethnic 

minority groups within the United States, with specific attention to the drugs of primary focus in the mission

statement of the National Institute on Drug Abuse (NIDA). Available information indicates that use of these

drugs may be harming the health and social well-being of these population groups disproportionately, based 

on their reported use of these drugs. Adverse consequences suffered by some of our racial/ethnic minority 

populations include excess risks of arrest, conviction, and incarceration for drug-related crimes, against a 

background of statistics that suggest no excess involvement in illegal drug use. These adverse consequences

extend to overrepresentation in statistics of drug-related morbidity and mortality, disruption of educational

achievement (e.g., greater failure to earn the regular high-school diploma), and social disadvantage.

The report draws attention to some of the open research questions that must be pursued as elements in a future

agenda of research on drug use and health disparities. For example, it has been suggested, without strong 

evidence, that African Americans may be at greater risk than Whites to fatal and nonfatal health consequences

of drug taking due to a greater preference for injecting drug use, more frequent choice of drugs such as crackcocaine, or to differences in access to health care opportunities. At present, there is no good evidence to settle

these questions. For example, we can state that African Americans are overrepresented among decedents found

to have used cocaine, but we do not know whether this overrepresentation is artifactual and due to a greater

likelihood of testing for cocaine when the decedent is African in heritage. Furthermore, we can note that White

women seen in hospital emergency rooms for drug-related reasons are more likely to be admitted to the hospital

than all other subgroups examined, but we do not know whether this difference is attributable to better hospitalization coverage by third-party payers—or whether it is explained by other reasons.

Currently available epidemiological data on drug use of racial/ethnic minorities disclose several important signs

of differences in reported use. Among youth, Asian and Pacific Islanders often have been found to be less likely

to report illegal drug use than other groups. This difference is pronounced for alcohol, possibly due to racial/

ethnic variations in genetic susceptibility to toxic ethanol responses (e.g., the flushing syndrome) and does not

appear to be present for methamphetamine, at least among Pacific Islanders. It also is of interest that AfricanAmerican youth consistently report less involvement in drug use than do White youth, whereas Hispanic youth

often have been found to have greater prevalence of drug use than African-American youth and only slightly

less use than White youth. Patterns of illegal drug use among American Indian/Alaska Native youth have 

generally been neglected and merit greater scrutiny, both on and off reservations, with close attention to possible

methodological explanations for observed excess drug involvement of this minority subgroup. 

The just-described variation may have causal importance and may reflect true differences in the drug involvement

of minority and nonminority populations in the United States. If so, this variation has important implications

for public health interventions, with targeting to the individual needs of specific minority populations. On the

other hand, it is possible that the observed variation is no more than methodological artifact, due to the incomplete resolving power of our available evidence on drug involvement across and within these populations. If 

the variation can be traced back to methodological artifacts, then there are different implications for public

health action.

Chapter 8. SUMMARY AND FUTURE DRUG ABUSE 

PROGRAM NEEDS AND RESEARCH NEEDS
Summary and Future Drug Abuse Program Needs and Research Needs

This report presents interesting findings for patterns of association linking illegal drug use to other risk-related

behaviors among racial/ethnic groups. Data from the Youth Risk Behavior Survey indicate risky sexual practices

were reported in connection with reports on illegal drug use. For example, youths who reported cocaine use

were more likely to report multiple sex partners and failure to use condoms; this pattern was observed for each

of the racial/ethnic minority groups under study, including White students. Data on AIDS cases, minority and

nonminority alike, indicate that HIV infection often can be traced back to injecting drug use of the victim or

to heterosexual or homosexual activities with an injecting drug user. Each of these findings may have useful

implications for conceptualizing prevention, referral, and treatment programs that can effectively address drug

use among racial/ethnic groups, even if the findings do not inform delivery of services directly.

The issues represented by AIDS, infectious diseases, drug use, and race/ethnicity are particularly important. The

preponderance of African Americans and Hispanics among injecting drug users with AIDS is at least in part due

to a failure of prevention programs at the local, State, and national levels, perhaps connected with insufficient

funding for targeted prevention programs oriented toward the needs of minority populations. Other life 

circumstances, conditions, and processes merit attention, such as differences in drug use practices and general

health status of minority groups, but at the end of the day, the observed excess in AIDS-related morbidity and

mortality is a failure of our past and current public health and prevention programs.

Higher HIV seroprevalence and other infectious disease rates among African Americans and Hispanics support

an argument for improving our current profile of interventions intended to reduce these infections and their

consequences. More research is needed to identify the best intervention choices from among those presently

available and to design new choices that represent real improvements over existing programs and techniques,

with selections most appropriate to the minority group of interest. To be sure, the burdens of HIV and AIDSrelated diseases, disabilities, and family suffering will continue to mount over the coming decades as we deal

with the failure of our prevention and intervention programs to date.

Of course, there are limitations to our understanding of health disparities connected with alcohol and other

drug use of American minority populations, just as there are limitations to our understanding of that for White

and non-Hispanic Americans. Changing social and demographic characteristics of illegal drug users merit close

scrutiny in future research, as more illegal drug users move into middle age and beyond. It is possible that there

are developmental and social status delays in so-called “maturing out” of illegal drug use. Some of these delays

may occur more frequently in association with minority group membership and they require greater attention

among developmental scientists. At the same time, legitimate concern exists about the inadequacy of our 

current epidemiological statistics on these topics, giving good reason to improve our data. For example, known

distortions will occur when there is a reliance on drug arrest and treatment data, due to race-related differentials

in arrest rates and facility admission rates. To the extent that the U.S. Census and our social surveys fail to 

enumerate young minority group members, there are additional methodological sources of bias in our 

epidemiological estimates on the illegal drug-taking behavior of these subgroups, even if self-reports and other

measurements had 100-percent validity.

An improved conceptual framework and better theoretical models for conditions and processes affecting risk

and protection against illegal drug use also are needed. The most recent empirical research by Wallace and

Muroff (2002) suggests that associations that link illegal drug use to suspected risk and protective factors are not

necessarily the same for African-American children and teenagers as for nonminority youth.

140
Summary and Future Drug Abuse Program Needs and Research Needs

Research on drug use among racial/ethnic minorities has not advanced to a stage that allows policymakers and

program managers to make the intervention choices required to reduce drug-related health and social problems.

To some degree, this inadequacy of past and current research may be understood as a consequence of the 

illegality and sensitivity of the behaviors and problems under study. It is not altogether clear that definitive 

evidence is possible when potential participants can decline to participate and often choose not to provide 

information that is essential for valid measurement of behavior or diagnosis of health-related and social disturbances. Nonetheless, improvements can be made and must be made if there are to be effective reductions in

drug-related health disparities.

To date, we have an accumulation of data that might help a clinician choose between alternative interventions

for drug-dependent individuals within different race-ethnic groups within the U.S. population. However, 

definitive evidence is lacking for these issues, such as knowing the extent to which special alternatives are essential

to achieve mutually valued results with members of these groups when they are in target populations for 

prevention, early intervention, treatment, or long-term rehabilitation. Consensus exists that program efficacy

and effectiveness might be increased with greater attention and sensitivity to race, culture, and ethnicity.

Ignorance of or inattention to these issues may result in evidence that is misleading or wrong. At least as a working hypothesis, investigators must entertain the possibility that racial, ethnic, and cultural conditions and

processes will influence virtually every arena of the NIDA research mission, ranging from the initial stages of

drug involvement to serious drug dependence and fatal complications of drug use.

It is important to note that some progress has been made in research. For example, an increasing number of

studies of illegal drug use among minorities have been completed over the past two decades. These studies have

comprised general population studies and special investigations of presumed high-risk groups, such as school

dropouts, runaways, or arrestees. Even so, for reasons discussed in this report, the current estimates of illegal

drug use in minority populations may misrepresent the extent of the problem, and the magnitude of the 

misrepresentation is unknown or understudied. Available data suggest that research can both effectively assess

and meet the needs of racial and ethnic minority groups and strengthen school-based drug prevention and 

intervention programs and those in the community at large. However, research on selection processes is needed

in these contexts, including studies of (1) processes that influence who remains in school and can be influenced

through school-based programs, (2) processes that help protect or increase the resilience of minority and 

nonminority students even when they drop out of school, and (3) the role that educational systems might play

with public health systems to reduce, delay, or eliminate illegal drug use in the population at large.

Race and ethnicity are difficult concepts and much controversy remains about how best to sort individual 

members of a population into racial/ethnic minority groups. Current definitions of race/ethnicity tend to 

oversimplify a complex set of personal, social, and biological attributes or tend to neglect social context 

(e.g., marginality). Increasing immigration creates a dynamically changing set of circumstances. In consequence

of immigration and different rates of acculturation or assimilation, tremendous diversity is found among 

individuals of the same racial or ethnic group.

Although considerable interest exists in having data on race and ethnicity, the breakdowns are often restricted

to “White” “Black” and “Other.” As introduced in Chapter 1 of this report, when information is collected on

minority groups, the information rarely takes into account the heterogeneity of the population. We have data,

for example, on drug abuse among American Indians in general, but there are more than 200 American Indian

tribes for which we have almost no specific data. In addition, although some national-level data on drug use by

141
Summary and Future Drug Abuse Program Needs and Research Needs

race and ethnicity are stratified by age and male-female differences, rarely are factors such as education or

income status entered into the analysis. Data on Hispanic and Asian/Pacific Islander subgroups, illustrated in

this report, indicate there are important distinctions in reported drug use within these populations. More

research is needed to create a stronger base of evidence on these differences.

Limitations of the available data have been described throughout this report. To some extent, these limitations

can be addressed as national statistics and surveillance systems implement the most recent recommendations

and standards for classification of racial and ethnic groups. Nonetheless, challenges with reliability and validity

of evidence will remain, even when improved classifications are in place. For example, concern continues about

underenumeration of young minority group members in survey research and the possibility of underreporting

of illegal drug involvement due to English language difficulties. These limitations merit attention in methodologically oriented research designed to yield lasting improvements in our national statistics and surveillance

efforts, as well as more refined research in other domains of inquiry supported by NIDA and other Federal 

agencies.

Some additional improvements may result if there are deliberate efforts to:

■ Include more minority researchers in leadership roles within the scientific community;

■ Increase collaboration with people of color when plans are being laid for each new research agenda, with

identification of funding priorities that are culturally appropriate and sensitive;

■ Encourage meaningful analyses of existing databases on various stages of drug involvement across a range

of racial/ethnic minority groups; 

■ Identify conceptually motivated constructs and theories in new research on health disparities as they 

are manifest across the various stages of drug involvement and in response to prevention and treatment

interventions; and

■ Develop and implement new lines of research on race- and ethnicity-related discrimination, quality of 

life, self-sufficiency, and other factors important to an understanding of the processes through which health

disparities emerge.

In closing, NIDA is reconceptualizing its mission in addressing health disparities affecting racial and ethnic

minority groups in the U.S. population, with an appreciation that the definition of “minority” will change 

during the 21st century. This reconceptualization process cuts across all NIDA divisions and branches, including

basic laboratory science research in neuroscience and pharmacology, but may be most visible in epidemiological

and clinical studies of racial, ethnic, and cultural factors associated with the causes and consequences of illegal

drug use for all racial/ethnic groups. These studies include case-control as well as longitudinal studies and experiments that attend to the various characteristics of the populations under study. More research is needed to

examine the natural history and clinical course of drug problems as experienced by the array of racial and ethnic

populations of the country and the differential influences on and consequences of illegal drug use over time.

These studies will help target the factors most important in the initiation and continuation of drug use among

racial/ethnic populations and identify the culturally relevant factors associated with drug use. Further examination

of cultural factors also may help shed light on the protective mechanisms among subpopulations, resiliency

processes that help sustain susceptible populations, and contextual influences on risks associated with drug use.

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Summary and Future Drug Abuse Program Needs and Research Needs

To the extent that NIDA-supported investigators are successful in this research arena, our Nation’s policymakers

and program managers will be better able to respond to observed health disparities and to reduce these disparities

through health-promoting intervention choices.

143

NIDA asks readers of this report to make suggestions that can be

used to improve future revisions of the report. These comments

and suggestions may be sent to Dr. Leslie Cooper at:

lc58q@nih.gov

Thank you!

145

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155

157

Health disparities research within the context of programs conducted or supported by the National Institute on

Drug Abuse (NIDA) refers to studies involving human subjects that focus on one or more minority population

groups (e.g., African Americans, Asian/Pacific Islanders, Hispanics, and Native Americans). Racial/ethnic

minority populations are adversely affected by the stigma of drug abuse and its effects leading to misperceptions

about drug abuse and addiction in minority communities and the way in which prevention and treatment are

delivered to them. The common perception is that minority groups, particularly Blacks and Hispanics, use drugs

more than Whites—even though epidemiologic data show little difference in overall use by race/ethnicity. In fact,

in some instances minority groups are less likely to use licit or illicit drugs. 

While the prevalence of drug abuse is similar for minorities and Whites ages 12–17 with the progression of drug

use into early adulthood, the adverse consequences tend to be greater for minorities than for Whites. This is 

evident in arrest, sentencing, and incarceration rates; school dropout rates, and the rates of drug-related hospital

emergency room visits. Because of the extreme differences in the consequences of drug use for racial/ethnic

minorities, there is an urgent need to better understand factors such as socioeconomic status, discrimination,

culture, neighborhood/environmental conditions, access to health care, and employment status, which place

minorities at risk for drug use and its adverse consequences. Disparities are readily apparent in the reported rates

of HIV/AIDS infection, violence and victimization, incarceration, school dropout, and morbidity in ethnic

minority communities. Science-based information is needed to inform prevention, treatment, and health services

targeted at minorities and to reverse the effects of the stigma attached to drug addiction.

Health disparities and minority-related research have been defined as follows:

■ Health Disparities Research—Basic, clinical, and behavioral research that addresses the magnitude and

impact of drug use within racial/ethnic minority populations, where the goal of the study is to determine

the differential use and/or effects of drugs on the racial/ethnic minority groups included in the study.

Health disparities research addresses issues related to epidemiology, prevention, services, and treatment 

outcomes within and across racial and ethnic populations. 

■ Minority-Related Research—Research that includes racial/ethnic minorities as participants but where the

goals, aims, and hypotheses of the study do not specifically address drug use and/or its effects as they

are experienced by racial/ethnic minority populations. 

■ Coding—For coding purposes, 100 percent of the funded amount for projects that meet the definition for

health disparities research should be included in NIDA’s Health Disparities Research budget reporting.

Appendix 1. NIDA POSITION STATEMENT 

HEALTH DISPARITIES: DEFINITIONS

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Mission and Introduction

The mission of the National Institute on Drug Abuse (NIDA) is to lead the Nation in bringing the power of

science to bear on drug abuse and addiction by (1) providing strategic support and conduct of research across

a broad range of disciplines and (2) ensuring the rapid and effective dissemination and use of the results of that

research to significantly improve drug abuse and addiction prevention, treatment, and policy.

Unlike other diseases, drug addiction poses many peculiar challenges to health researchers, providers, and public

health officials in the search for effective prevention and treatment strategies and policies. These challenges

emanate primarily from the fact that drug abuse and addiction are usually the result of illegal activity and drug

abusers are often viewed as morally corrupt or weak-willed individuals who engage in not only voluntary selfand socially destructive behavior but also criminal activity. In short, despite the fact that we know unequivocally

that addiction is a disease like any other medical disease, it remains a stigmatized disease. And this stigma spills

over to all aspects of drug abuse research, prevention, and treatment (e.g., obtaining measures of use, addressing

safety and legal concerns, and providing early intervention are compromised by efforts to hide the disease and

denial of dependency). 

Racial/ethnic minority populations are perhaps most adversely affected by this stigma and its effects, leading to

misperceptions about drug abuse and addiction in minority communities and the way in which prevention and

treatment is delivered to them. For example, the common perception is that minority groups, particularly Blacks

and Hispanics, use drugs more than Whites even though epidemiologic data show little difference in overall use

by race/ethnicity. In fact, in some instances minority groups are less likely to use licit or illicit drugs. There are,

however, great differences in the consequences of drug use for racial/ethnic minorities, creating a great need to

better understand the unique prevention, treatment, and health services needs of these communities.

NIDA has made a concerted effort, particularly over the last 6 years, to better understand and address the drug

abuse and addiction research needs of racial/ethnic populations, focusing on research areas where there are 

significant gaps in knowledge and/or clear disparities in prevention and treatment. In 1993, NIDA established

a Special Populations Office, which has two overall goals: (1) to encourage increased research on drug abuse in

minority populations in NIDA divisions and (2) to encourage and enable increased minority participation in

drug abuse research. Moreover, NIDA formed an institute-wide work group, the Consortium on Minority

Concerns, which meets monthly to address research and research development issues of concern to minority

populations. Each program division and office is represented on the Consortium. 

Several institute-wide initiatives and policies were implemented, which has led to progress in research that

addresses health disparities and the underrepresentation of minority scholars in drug abuse research. Some of

these initiatives include:

■ Historically Black Colleges and Universities (HBCU) Initiative. This was designed to encourage HBCUs 

to become involved in drug abuse research and to assist them in developing the capacity to conduct drug

abuse research. Some selected outcomes of this initiative include increased support of HBCUs through the

NIH competitive process (which has led to research on underresearched areas such as developing prevention

Appendix 2. NIDA STRATEGIC PLAN 

ON REDUCING HEALTH DISPARITIES
NIDA Strategic Plan on Reducing Health Disparities

programs for rural African-American youth, understanding risk for drug abuse in African-American youth

at developmental transition points), establishment of a center on drug abuse research at Howard University

(which has since received a substance abuse grant from the Robert Wood Johnson Foundation), support of

an established research scientist cooperative agreement program at four HBCUs in collaboration with the

Office of Research on Minority Health (ORMH) (North Carolina Central has recruited a distinguished

NIDA scientist with three independent awards—this has already led to collaborations for student and 

faculty research and training opportunities with Wake Forest University and the University of North

Carolina, and increased activity on the campuses around substance abuse awareness and prevention. 

■ Enhancement of the Underrepresented Minority Supplement Program. NIDA instituted a new policy 

for the funding and receipt and review of minority supplement applications. In the last 5 years, NIDA 

has more than doubled its support of Minority Supplements in amount of funds allocated yearly to the 

program and nearly doubled the number of new awards made (from FY 1994 to FY 1999). NIDA also

established a policy to include Asians and Pacific Islanders in behavioral and clinical work because they are

underrepresented in these areas of drug abuse research. Former recipients are applying for and receiving 

independent research awards, and often these recipients focus on disparities research issues and/or intend 

to mentor other underrepresented students and scholars. 

■ Summer Research with NIDA. To address concerns about the insufficient pipeline of minority researchers,

NIDA established a summer program to place minority high-school and undergraduate students with

extramural scientists. Response has been very positive from students and investigators. This summer marks

the fourth year of the program. Initially started with ORMH funds, NIDA completely supports the program

now. Thirty-nine students were placed in 1999, some of them returning to the same investigators. 

■ Minority Recruitment and Training Program. This is an intramural summer research program for students

and faculty. It accepts minority high-school, college, graduate and medical students, and faculty members.

About 25 students are placed each summer. One of NIDA’s HBCU principal investigators is a former 

participant in this program. A successful minority student development program at Temple University

requested that some of their students be placed with NIDA’s intramural program based on the reputation

of this program and its director. 

■ Minority Work Groups. Work groups comprised of experts in substance abuse and addiction or health

concerns of minority populations have been created. These Work Groups advise the NIDA Director on

research and research development needs of the particular minority communities that will lead to effective

prevention and treatment approaches for each group. Work groups exist for African-American, Hispanic,

and Asian/Pacific Islander communities. A Native American work group meeting will be held in May

2000. Some outcomes of the work of these groups include new principle investigators, identification of

candidates for the supplement program, new opportunities for NIDA to interact with professional and

community groups, new ideas for research, new study section members, and increased mentoring and 

collaboration among group members.

■ Development of public announcements (PAs) and requests for applications (RFAs). NIDA released a new

program announcement, Minority Institution’s Drug Abuse Research Program, to support minority institutions wishing to develop their capacity to conduct drug abuse research. Two new programs were funded

under this PA last year. One will focus on Hispanic issues in drug abuse prevention. Another, in Puerto

Rico, was recently approved for funding and it will focus on Hispanic populations. An RFA, the HBCU

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Cooperative Agreement, was released in collaboration with ORMH. Four projects were funded under this

RFA: One will focus on prevention interventions with urban African-American youth and one will focus

on prevention issues and perinatal care in minority populations. All include research training opportunities

for minority faculty and students.

■ Research Development Technical Assistance Workshops. NIDA offers technical assistance to minority 

and women scholars in developing research studies on drug abuse and addiction. Participants are provided

information on conceptual and methodological concerns in drug abuse and addiction research in addition

to information on the NIH grants application and review processes. Many of the participants in this 

program have become NIDA/NIH grantees, NIH peer reviewers, and grantees of other agencies and 

foundations.

As a result of these activities and individual division activities, NIDA has experienced approximately a 97-percent

growth in minority researchers since FY 1993. With this growth in minority researchers (although all are not

involved in minority-focused research) and an intense focus on drug use and addiction in minority communities,

we have observed an increase in applications and awards that focus on drug abuse disparities and needs in

minority communities.

This proposed strategic plan reflects NIDA’s insights and knowledge gained from our efforts to address health

disparities among racial/ethnic groups over the last few years. In addition, the plan incorporates the recommendations made by the expert work groups described above and an extensive review of NIDA’s research 

programs and activities conducted by staff. 

Over the next 5 years, NIDA will strive to (1) improve our understanding of the incidence and causes of drug

abuse and addiction in all racial/ethnic groups recognizing the diversity by gender, socioeconomic status, and

other factors within racial/ethnic populations, (2) strengthen and expand the community and research infrastructure for conducting research within racial/ethnic populations, (3) improve prevention and treatment for

racial/ethnic groups at highest risk for addiction and medical consequences of drug use and addiction, and 

(4) widely disseminate information on drug use and the disease of addiction in racial/ethnic communities 

identifying best approaches to prevention and treatment.

Area of Focus #1: Epidemiology of Drug Abuse, Health Consequences and Infectious Diseases

among Minority Populations

Introduction/Background. Having a good knowledge base on the incidence and patterns of drug use, abuse,

and addiction is critical to assessing the need for and shaping the content of prevention and treatment programs.

Current surveys such as the NIDA-supported Monitoring the Future study (a national survey of 8th-, 10th-,

and 12th-graders) and the Substance Abuse and Mental Health Services Administration (SAMHSA)-supported

National Household Survey on Drug Abuse (NHSDA—a national survey of persons 12 and older residing in

households) provide important information on drug use patterns and trends. However, they are limited in the

extent to which they reveal indepth information about racial/ethnic groups. For example, neither survey has

adequate representation of Native Americans, Alaska Natives, Asians, or Pacific Islanders. Although this 

may change beginning with the increased sample size in the 1999 NHSDA survey, there is still concern about

obtaining adequate adolescent samples for these subgroups. African Americans and Hispanics are included, but

their numbers are not sufficient to form reliable subgroups to investigate within group profiles (e.g., develop

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separate profiles for Mexicans and Puerto Ricans). Moreover, there are selection biases that disproportionately

affect minorities that may suppress their numbers in these general surveys. For example, Hispanics have a higher

school dropout rate than other groups and therefore may be more likely to be excluded from the school surveys

and may be difficult to reach in household surveys. Since dropout rates correlate with higher risk for deviant

behavior, we may be missing information on a group with a high risk for drug abuse and addiction. 

More work is needed to better understand the causes of drug use in minority communities. Promising studies

are underway on risk and protective factors especially on the role of culture, religiosity, ethnic identity, family,

peer, and environmental/community level factors in drug initiation. For example, minority youth tend to initiate

drug use later than White youth. Yet, when African Americans start using, they seem to progress to addiction

faster. Among Hispanic youth, drug use seems to increase with increased acculturation to U.S. norms and with

years and generations in the United States. We know little about predictors of use in Pacific Islander and Asian

subpopulations. 

Better measures and designs are needed to appropriately assess drug abuse and addiction and related behaviors

in racial/ethnic populations. 

Minority populations are disproportionately affected by HIV/AIDS and other infectious diseases that are a 

consequence of using drugs and engaging in other risky behaviors. African Americans and Hispanics, especially

women, comprised 54.7 percent of the AIDS cases reported to the Centers for Disease Control and Prevention

(CDC) in 1998. This percentage is far greater than their representation in the general population. Other studies

indicate a plethora of ways in which minorities may be adversely affected by drug abuse-related diseases:

■ Women, particularly African-American women, are at higher, unique risk for HIV/AIDS;

■ Injection drug users are at increased risk for mycobacterium tuberculosis infection (TB) and Hepatitis B

and C infection (HBV and HCV, respectively);

■ A possible association exists between vascular injury of the neonatal central nervous system and the level of 

prenatal cocaine exposure; and 

■ Hispanic homeless are more likely to share needles. 

We know relatively little about the varying patterns of initiation of drug use and addiction among women of

diverse racial and ethnic groups.

NIDA has continuously attempted to respond to the need to understand the patterns and causes of drug abuse

in all populations through several activities, such as releasing PAs and RFAs and convening conferences 

and meetings. For example, in 1998 NIDA reissued its "Epidemiologic Research on Drug Abuse” PA, which

encourages numerous epidemiologic strategies, including monitoring of trends over time of drugs of use/abuse,

identification and measurement of health problems associated with drug abuse, and international epidemiology

of drug abuse. Applications submitted in response to this PA are expected to guide the development of interventions; define subpopulations; identify groups at risk for various health conditions, such as HIV, TB, hepatitis,

poor pregnancy outcomes, ADHD, mental disorder, and other conditions (predisposing and consequential to

drug use/abuse); inform and influence local state and Federal health agencies; and provide guidance for public

policy. Investigators have been strongly encouraged to conduct analyses by race/ethnicity.

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NIDA Strategic Plan on Reducing Health Disparities

NIDA staff has been working actively at numerous meetings to increase the number of grant applications in

such areas as HIV in the African-American population, health care/primary care access and utilization among

minority drug abusers with HIV infections, and epidemiology of HIV in the Caribbean.

Goal 1: Improve the knowledge base on the patterns and origins of drug abuse and addiction in 

all racial/ethnic populations including producing estimates of racial disparities on the incidence and

prevalence of drug use and addiction within those populations, examining both risk and protective factors.

Action Plan 

■ Expand research to

● Assess, within and across racial/ethnic groups, the magnitude, incidence, and prevalence of drug abuse,

analyzing by gender;

● Identify and assess both individual and community/environmental vulnerability, risk, and protective 

factors for drug use and abuse and related consequences in various racial/ethnic populations, analyzing 

by gender;

● Develop better sampling methods for hard-to-reach minority populations and more effective ways to

reduce survey nonresponse and increase the validity of self-reported drug use and associated behaviors;

and

● Support the secondary analysis of data obtained under NIH-supported research pertinent to 

understanding the epidemiology and etiology of drug abuse in racial/ethnic populations, including 

analyses by gender. 

Goal 2: Identify and examine issues of health disparities in drug abuse and associated infectious diseases,

particularly HIV/AIDS within racial/ethnic populations, including analyses by gender. 

Action Plan 

■ Expand research to

● Increase scientific knowledge about the medical and health consequences of HIV infections in 

women and men of racial/ethnic minority groups, including assessing the magnitude, incidence, and

prevalence of HIV/AIDS and other sexually transmitted diseases, HBV, HCV, TB, and their impact on

racial/minority populations; identifying the associated risk and protective factors for HIV/AIDS and

other sexually transmitted diseases, HBV, HCV, TB, mental disorders and socioeconomic status among

racial/minority populations; and identifying subgroups within racial/minority groups at greatest risk

(e.g., homeless, homosexuals, and prison inmates). Develop and implement appropriate intervention

strategies for reducing risk factors among women and men in these groups;

● Increase access to, utilization of, and adherence to antiviral therapies by HIV-infected ethnic minority

male and female drug users through identifying new, simplified, and innovative strategies/approaches

and mechanisms to complement and improve traditional approaches for individuals in this population;

and

● Increase scientific knowledge on how gender and other factors such as community, culture, education,

and socioeconomic status affect HIV transmission within racial/ethnic populations. 

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NIDA Strategic Plan on Reducing Health Disparities

Goal 3: Identify both the short- and long-term effects of drug use, abuse, addiction, and violence and

their interrelationships on the overall health (including physical, mental, and emotional health) of men,

women, and children in racial/ethnic populations.

Action Plan 

■ Expand research to

● Identify and assess issues of comorbidity across the age span for all racial/ethnic groups and the 

relationship between drug abuse, comorbid conditions, and health disparities within and across those

groups and by gender within these groups;

● Investigate health and developmental disparities across racial/ethnic groups for children and adolescents

who have experienced prenatal drug exposure and/or early use of illicit drugs by gender within these

groups;

● Identify and review the state of knowledge and availability of data on the coexistence of substance abuse

and mental/emotional disorders and the presence of health disparities across and within racial/ethnic

groups, including analyses by gender;

● Identify the impact of the drug-using environment on racial/ethnic women and men living under those

conditions. Assess proposed strategies for interventions to reduce drug abuse in these groups;

● Evaluate the role of stress (e.g., cultural adaptation) in initiating and escalating drug use/abuse and its

impact on various male and female racial/ethnic populations. Sensitivity and responsiveness of the needs

of the target audience must be considered in all instrument development, administration, analysis, and

evaluation of the data; and

● Explore the contextual relationships between drug use, violence, employability, school performance, 

family structure, and economic well-being of the community. Sponsor a series of workshops and 

meetings with grantees and others to explore the current state of the knowledge.

Area of Focus #2: Prevention of Drug Abuse and Addiction

Introduction/Background. NIDA has made great strides in the last few years in its prevention research 

program. The Institute has supported two long-term minority prevention research centers that focus on African

Americans, Hispanics, and Native Americans, as well as several other research projects that include ethnic

minorities. Results from these and other research studies suggest that racial/ethnic populations may have special

prevention needs and that prevention strategies may have to be specific to their culture and circumstances to be

successful. For example, research indicates that including culturally specific components in “generic” prevention

programs enhances effectiveness with African Americans. 

Epidemiologic data show that race/ethnic groups differ in patterns of drug use, preferences, and accessibility 

and risks requiring prevention programs that attend to these needs. For example, Hispanic youth are more likely

to be school dropouts, making school-based prevention programs unlikely to reach Hispanic youth at greatest

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risk. African Americans have late (or delayed) onset of drug use, suggesting that they may be more in need of

prevention programs after high school, in their late adolescent/early adult years. Native Americans on 

reservations need prevention programs at an early age and such programs must be acceptable to tribal councils.

Second-generation immigrants may be at higher risk for drug use than first-generation immigrants. Moreover,

the heterogeneity or diversity within racial/ethnic groups must be acknowledged in prevention efforts (e.g., gender,

socioeconomic status, education, cultural styles, rural-urban differences, and the specific risk factors for these

subgroups need to be better understood to inform prevention efforts). 

More prevention programs are needed to reach minority populations in high-risk settings and neglected, hardto-reach areas or communities. This includes, for example, persons in correctional facilities (more likely to be

African Americans and Hispanics), persons in rural areas, migrant workers/seasonal farm workers (often

Hispanic and Haitian), children in drug-abusing families, and minority women addicts (who are at great risk

for infectious diseases). More research is needed on prevention efforts with Asian/ Pacific Islanders and Native

Americans/Alaska Natives and their subgroups.

Goal 1: Support prevention research targeting racial/ethnic minorities to (1) understand the drug abuse and

HIV/AIDS prevention needs of minority populations across the life span, with specific attention to very early

and late onset initiation of use and diversity in vulnerability to use across the life cycle (e.g., immigrant groups

adapting to new environment, transition points, and stress); (2) understand how to develop culturally appropriate prevention interventions and how to adapt “generic” prevention models for specific minority populations;

(3) examine the effectiveness of mass media prevention/education messages that target specific minority populations; (4) develop more prevention interventions that reach minority populations in contexts such as the family,

church/faith community, and other community programs to ensure that prevention expertise becomes a 

permanent part of the community; (5) address the complexities and requirements of developing effective 

prevention programs for diverse groups within multiethnic, multicultural settings (e.g., schools with multiethnic

student bodies and persons with multiple ethnic identification or affiliations); and (6) identify how cultural

norms affect gender differences in drug use and risk factors.

Action Plan

■ Develop research opportunities in the above areas.

Goal 2: Ensure that racial/ethnic minority populations are fully incorporated into the planning and

implementation of NIDA’s Next Generation of Prevention Research Initiative, designed to gain a better

understanding of the factors that account for prevention program effectiveness.

Action Plan

■ NIDA staff will review plans for the next generation studies to make certain that concerns of racial/ethnic

minorities are adequately addressed.

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Goal 3: Develop effective, culturally specific drug abuse prevention strategies for minority populations

who are at increased risk for drug abuse, such as individuals in detention or correctional facilities, the homeless,

and persons who have been abused or neglected, and those groups who are underserved, such as those living on

Indian reservations or in rural areas, migrants or seasonal farmworkers, and youth in the early stages of cultural

adaptation and acculturation.

Action Plan 

■ Expand research opportunities in this area.

Area of Focus #3: Addressing Disparities in Treatment and Health Services Research

Introduction/Background. NIDA currently supports several activities that focus on racial/ethnic groups and 

cultural factors in treatment for addiction. For example, the Behavioral Therapy Development Program 

supports several studies that are evaluating family-based treatment approaches for drug-using minority youth

(based on research findings suggesting that family variables are more influential in substance use in certain

minority youth). Some of these studies suggest that treatment engagement procedures may be different for

Mexican-American and Cuban youth. Analyses will be conducted to ascertain whether outcome differences are

due to cultural factors associated with Mexican-American and Cuban families or other factors. A study was

recently funded that is evaluating the efficacy of adding a culturally relevant, community-based community

reinforcement enhancement to an existing residential treatment program for homeless, crack-using, AfricanAmerican women with children. This study is using the Black church as a vehicle for implementing the intervention. To advance the current knowledge base about potential ethnic differences in nicotine dependence,

NIDA is supporting a study that will design and test the efficacy of smoking cessation programs in treating

Chinese-American smokers. 

NIDA’s newly established National Drug Abuse Treatment Clinical Trials Network (CTN) will provide yet

another vehicle for NIDA to ensure that minority populations are included in both NIDA’s treatment research

protocols and in conducting treatment research. The CTN will provide a much-needed national research and

dissemination infrastructure to more rapidly and systematically bring new science-based addiction treatments

into real-life treatment settings. 

Considering the severe consequences of drug abuse and addiction on racial/ethnic populations, NIDA realizes

that minority populations need to be more fully included in treatment research and clinical trials. Moreover,

more attention needs to be directed at examining medical, social, and cultural factors that may influence adherence to treatment and treatment outcomes. For example, some minority populations are included in NIDAsupported clinical trials of pharmacotherapies and behavioral therapies; however, data are not completely

analyzed by race/ethnicity to better understand behavior in treatment or outcomes of treatment. In some clinical

research studies, there have been difficulties in enrolling and retaining adequate numbers of minorities in order

to conduct meaningful data analyses. Other research indicates that race/ethnicity may be important in physiological responsiveness to drugs. For example, pharmacokinetic studies indicate that there are differences in some

ethnic populations in their ability to metabolize different drugs. 

Racial/ethnic minorities may experience more difficulties in obtaining the most appropriate health care services.

Research suggests that they may be more vulnerable to gaps and lack of coordination in systems of care and that

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they may encounter bias in treatment assignments. The need for services appears to differ by race/ethnicity 

(e.g., one study suggests that Latinos may require more intensive services). 

Goal 1: Increase the number of treatment research studies that focus on racial/ethnic differences and

improve dissemination of the study results.

Action Plan

■ Ensure that all racial/ethnic minority populations are fully included in NIDA’s newly established National

Drug Abuse Treatment CTN as clients, advisors, and research staff. Ensure that a sufficiently large sample

is recruited in each study to allow for analyses by specific racial/ethnic groups;

■ Develop a strategy to obtain more input from minority populations for the NIDA research agenda;

■ Encourage research to develop and test behavioral treatments that are culturally and gender sensitive and

relevant for racial/ethnic minorities; encourage studies of behavioral treatments, alone and in combination

with pharmacological treatments, for racial and ethnic minority drug abusers, including adolescents,

women, and those involved with the criminal justice system;

■ Develop systems to encourage NIDA grantees to include sufficient numbers of minority populations, 

analyze the data that are collected on racial/ethnic minorities, and publish the results;

■ Encourage research to develop validated, reliable clinical screening and assessment instruments in languages

other than English for use in clinical research with non-English speaking subjects;

■ Expand NIDA’s intramural clinical research to address treatment issues by race/ethnicity, and further

develop the program focusing on smoking cessation techniques with minority youth; and 

■ Sponsor a series of workshops and meetings with grantees and the minority advisory groups to explore the

current state of knowledge, identify gaps in the research, and make recommendations for future research.

The professional organizations representing different minority populations should also participate in this

process.

Goal 2: Determine the factors that contribute to differences, if any, experienced by racial/ethnic minority

populations in access to services and outcomes of treatment in managed care and other service systems.

In addition, assess the impact of welfare reform on substance abuse services provided to ethnic minorities,

especially minority women.

Action Plan

■ Expand the treatment and prevention services research portfolio to better understand the organization,

management, financing, and delivery of services and to enhance the integration of treatment and prevention

strategies and programs into existing community level service delivery systems; and

■ Sponsor workshops and meetings with grantees and the minority advisory groups to explore the current

state of knowledge, identify gaps in the research, and make recommendations for future research. The 

professional organizations representing different minority populations should also participate in this

process.

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Area of Focus #4: Addressing Racial/Ethnic Disparities in Basic and Clinical Neurosciences

Introduction/Background. Research is needed to better understand racial/ethnic differences in genetic 

vulnerability and/or resilience to drug abuse and addiction; neurotoxicity; and neurobiological and behavioral

processes underlying tolerance, dependence, and relapse. Pharmacokinetic studies have revealed distinct 

differences in some ethnic populations in the ability to metabolize different drugs, indicating a clear biological

basis in response to drugs. Studies focusing on the interaction between racial/ethnic differences and the effects

of drugs on underlying neural and behavioral processes will provide the basis for more targeted treatment and

prevention approaches in different populations.

Goal 1: Increase the number of neuroscience, clinical neuroscience, and basic behavioral science studies

that focus on racial/ethnic differences.

Action Plan

■ Provide support to key investigators to over sample underrepresented groups in their studies.

■ Require NIDA program staff to emphasize the importance of inclusion of minority subjects to all principal

investigators conducting human subject research and to work closely with those who are deficient in their

minority recruitment;

■ Provide avenues for publication of basic research findings comparing subgroups, including NIDA sponsored

publications such as NIDA monographs;

■ Provide information on strategies for recruiting underrepresented groups into basic human subject based

research; and

■ Expand research that directly targets minorities in the basic and clinical neurosciences and behavioral 

sciences, with the intent of addressing minority health disparities.

Area of Focus #5: Infrastructure Development and Enhancement

Introduction/Background. NIDA recognizes that conducting scientifically valid health disparities research

requires a research infrastructure that includes well-informed and trained scientists, knowledgeable and cooperative communities (e.g., community-based organizations, professional associations, faith communities, and

tribal councils), and academic institutions with competency and interest in health disparities research. NIDA

has made concerted efforts to build this critical infrastructure for health disparities research. We have worked to

increase the number of underrepresented scholars involved in drug abuse research and to increase our support

of useful and appropriate research on drug abuse in minority communities. Several initiatives, programs, and

activities have been implemented to eliminate this underrepresentation; examples include establishing expert

work groups on racial/ethnic populations, strengthening the Minority Supplement Program, developing an

HBCU Initiative, providing technical assistance in grants development, and developing program announcements and RFAs to build the minority research infrastructure. NIDA plans to build on these already successful

programs and expand them to increase training and career development opportunities for underrepresented

minorities. In addition, NIDA plans to increase the numbers of researchers and research studies that focus on

abuse and addiction in minority communities and to, in general, stimulate interest and enhance competency in

conducting research for eliminating disparities experienced by racial/ethnic populations related to drug abuse

and addiction.

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NIDA Strategic Plan on Reducing Health Disparities

Goal 1: Ensure proper resource requirements through training/career development.

Action Plan

Student Development and Support. NIDA will continue to support its current activities to increase the 

number of underrepresented students entering drug abuse research careers. This includes the Minority

Recruitment and Training program sponsored by the intramural program, the extramural Summer Research

with NIDA program for minority high-school and undergraduate students, and the Minority Supplement 

program. In addition:

■ NIDA will encourage applications for short-term training grants (T35) from drug abuse and addiction

programs particularly those involved in the National Drug Abuse CTN to offer summer research training

experiences for promising undergraduate and graduate minority students.

Faculty and Investigator Development. NIDA will continue to support its current activities to increase the

number of faculty and scholars conducting drug abuse and addiction research. This includes the Minority

Supplement Program, the Research Development Technical Assistance program, and the online research grants

development program. In addition, NIDA will:

■ Develop a Visiting Scholar Program to recruit and train African-American, Hispanic, and other minority

drug abuse researchers, with a special outreach to scholars from minority programs and institutions such 

as HBCUs, HSIs, and tribal colleges to spend time in selected research programs learning state-of-the-art

methodology. The small grant mechanism (R03) could be used to support a period of training in laboratories

using state-of-the-art technologies to examine a variety of aspects of drug abuse and addiction;

■ Develop a Career Development Award (K01) for minority faculty interested in all areas of drug abuse and

addiction research. This program would be aimed at faculty seeking a period of protected time to devote to

developing drug abuse research projects at their institutions. Special efforts will be undertaken to increase

the number of minority researchers in prevention and clinical research;

■ Establish a Minority Clinical Research Scholars Program in the NIDA Intramural Research Program;

■ Develop a plan with the Center for Substance Abuse Treatment to bring more minority scientists into drug

abuse and addiction clinical research. Explore the possibility of supporting minority supplement grants on

Center for Substance Abuse Treatment research and evaluation projects; and

■ Establish a Minority Clinical Research Scholars Fellowship as part of NIDA’s CTN program.

Academic Institution Development. NIDA will continue its efforts to increase the capacity of academic institutions, especially minority colleges and universities, to conduct drug abuse research. This includes the Minority

Institutions Drug Abuse Research Program and the HBCU Initiative. In addition, NIDA will:

■ Develop partnerships between institutions with well-established drug abuse research programs and minority

institutions that are interested in developing capacity in this area. Collaborate with ORMH on plans to

establish partnerships between drug abuse research centers and minority institutions;

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NIDA Strategic Plan on Reducing Health Disparities

■ Establish a NIDA Minority Access to Drug Abuse Research Careers Program through the National

Research Services Act (NRSA) to encourage and engage promising minority undergraduate scientists in

drug abuse and addiction research; and 

■ Support or examine the possibility of establishing Training Centers (T32s) in the basic neurosciences and

behavioral sciences, and clinical neurosciences at HBCUs and other minority education-oriented colleges

and universities. Encourage the participation of minority students at already existing centers.

Professional and Community Development. NIDA will continue its efforts to involve the broader community in addressing health disparities in racial/ethnic communities caused by drug abuse and addiction. This

includes the various expert work groups on African-American, Hispanic, Asian-American and Pacific Islander,

and Native American and Alaska Native communities. In addition, NIDA will:

■ Encourage clinical minority professional organizations to create and administer clinical minority research

development programs through the K–12 mechanism. This can be modeled after the successful American

Psychiatric Association and American Academy of Child and Adolescent Psychiatry programs to recruit 

and train minority clinicians interested in drug abuse and addiction research;

■ Host writing workshops to facilitate publications in peer-reviewed journals by minority scholars;

■ Develop opportunities (e.g., forums at professional meetings) to discuss drug abuse research needs, plans,

and opportunities with key stakeholder groups to include practitioners and consumers; and

■ Support workshops or programs to train investigators on conducting responsible drug abuse research 

in racial/ethnic minority communities. Consider creating guidelines for ensuring that such research is

appropriate and sensitive.

Area of Focus #6: Public Information/Outreach/Education and Dissemination

Introduction/Background. There are special challenges and problems in creating culturally appropriate 

information for special populations. To meet these challenges, NIDA has organized and convened ethnic 

advisory panels for Latinos, Asian/Pacific Islanders, and African Americans to improve our outreach to these 

various ethnic and minority groups. Acting on the advice of these experts, NIDA has:

■ Developed Spanish translations of two popular marijuana pamphlets, Marijuana: Facts for Teens and

Marijuana: Facts Parents Should Know;

■ Created a radio public service announcement (PSA) campaign on marijuana abuse for African-American

males ages 13–25;

■ Produced over 30 fact sheets about drug abuse and addiction in Spanish as part of our fax-back system,

“INFOFAX”;

■ Marketed the “INFOFAX” series, as well as the NIDA Web site via a Spanish art card distributed to 

appropriate outlets nationally;

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■ Given financial and editorial support to Pro Salud, a national publication marketed to Hispanic 

communities; and

■ Developed Spanish translations of the drug abuse Problem-Oriented Screening and Assessment Instrument

for adolescents.

In addition to these efforts NIDA routinely distributes all of its press releases to media outlets designed to reach

special populations.

Goal 1: Educate racial/ethnic minority populations about drug abuse and addiction prevention and

treatment. Also, identify and improve mechanisms for dissemination of research findings within and

across minority groups. NIDA is focusing on four key cultural minorities at present: Asians/Pacific Islanders,

Hispanics, Native Americans, and African Americans. Based on discussions with members of our cultural

minority advisory panels, we have also identified some subpopulations with special needs (e.g., Vietnamese,

Cambodian, Filipino, and other Pacific Islanders). 

Action Plan

■ Develop a series of radio PSAs and educational videos targeting Hispanic women. Hispanic women have 

a strong influence in health and lifestyle decisions within the Hispanic community. In addition to PSAs, a

Hispanic family-targeted brochure and video highlighting specific drugs of abuse known to be a problem

in various Hispanic communities (as well as among mainstream youth) will be provided as collateral 

materials. A comprehensive marketing plan to get the PSAs aired and the brochure distributed includes

forming partnerships with appropriate Hispanic organizations and persons of influence (such as journalists

and entertainers etc.). NIDA will work closely with the NIH Hispanic Initiative Coordinator during the

preparation of all related materials;

■ Create a year 2001 calendar for Native Americans that will be used to provide information about drug

abuse. It will be marketed broadly in the Fall 2000 via appropriate organizations, the media, and other 

venues (e.g., Native American-owned businesses and Indian Health Service clinics);

■ Create television drug abuse PSAs and videos in Spanish, which will be distributed to appropriate Hispanic

outlets. The PSAs and videos will follow the theme of NIDA’s national campaign, “Addiction is a Brain

Disease,” in an effort to educate the Hispanic community about the disease of addiction;

■ Translate and adapt other popular NIDA publications into Spanish, including Principles of Drug Addiction

Treatment. When completed, these materials will be packaged as a comprehensive set and broadly distributed

to Hispanic-oriented schools, health organizations, and community groups. Provide 

targeted training to Hispanic substance abuse treatment providers on effective treatment methods; and

■ Enhance NIDA collaboration with minority professional organizations through forums such as the NIDA

Constituent Conference and NIDA Town Meetings.

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Goal 2: Put research into practice in minority communities by providing science-based prevention and

treatment information to service providers serving these populations.

Action Plan

■ Translate Preventing Drug Use Among Children and Adolescents: A Research-Based Guide and Principles of

Drug Addiction Treatment: A Research-Based Guide into Spanish and distribute them to caregivers and 

service providers who work with Hispanic populations;

■ Distribute the “NIDA Toolkit” to service providers working in minority communities. The toolkit is a

national NIDA initiative to get the latest treatment information, including a set of NIDA treatment 

manuals, to service providers across the Nation;

■ Develop an outreach program to community leaders of specific special populations groups that will enable

them to help families understand drug abuse problems within their communities and give those families

the culturally appropriate tools for prevention and treatment;

■ Translate the NIDA treatment manuals into Spanish and distribute them to treatment providers who work

with minority populations; and

■ Develop a research-based prevention guide for persons working with racial/ethnic minority groups.

Goal 3. Educate the research and practice community about the state-of-the-art in drug abuse and 

addiction research with racial/ethnic minority populations.

Action Plan

■ Sponsor a national conference on drug abuse and addiction research and racial/ethnic communities;

■ Develop a guide and Web site that offers information on research with racial/ethnic populations.

Information such as current research, research findings, and valid measures would be available;

■ Provide guidelines and training on how to conduct research with racial/ethnic groups, including information

on cultural styles and ethical issues; and

■ Identify and improve mechanisms for dissemination of research findings within and across minority

groups.

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NIH Publication No. 03-3888

Printed 1995 • Revised September 1998 • Revised September 2003