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Results from the 2010
National Survey on Drug Use and Health:
Summary of National Findings

 

 

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES
Substance Abuse and Mental Health Services Administration
Center for Behavioral Health Statistics and Quality

Acknowledgments

This report was prepared by the Center for Behavioral Health Statistics and Quality (CBHSQ), Substance Abuse and Mental Health Services Administration (SAMHSA), U.S. Department of Health and Human Services (HHS), and by RTI International (a trade name of Research Triangle Institute), Research Triangle Park, North Carolina. Work by RTI was performed under Contract No. HHSS283200800004C.

Public Domain Notice

All material appearing in this report is in the public domain and may be reproduced or copied without permission from SAMHSA. Citation of the source is appreciated. However, this publication may not be reproduced or distributed for a fee without the specific, written authorization of the Office of Communications, SAMHSA, U.S. Department of Health and Human Services.

Recommended Citation

Substance Abuse and Mental Health Services Administration, Results from the 2010 National Survey on Drug Use and Health: Summary of National Findings, NSDUH Series H-41, HHS Publication No. (SMA) 11-4658. Rockville, MD: Substance Abuse and Mental Health Services Administration, 2011.

Electronic Access and Copies of Publication

This publication may be downloaded from http://store.samhsa.gov/home. Hard copies may be obtained from SAMHSA at 1-877-SAMHSA-7 (1-877-726-4727) (English and Español).

Originating Office

Substance Abuse and Mental Health Services Administration
Center for Behavioral Health Statistics and Quality
1 Choke Cherry Road, Room 7-1044
Rockville, MD 20857

September 2011

Table of Contents

List of Figures
List of Tables

Highlights

1. Introduction
Summary of NSDUH
Limitations on Trend Measurement
Format of Report and Data Presentation
Other NSDUH Reports and Data

2. Illicit Drug Use
Age
Youths Aged 12 to 17
Young Adults Aged 18 to 25
Adults Aged 26 or Older
Gender
Pregnant Women
Race/Ethnicity
Education
College Students
Employment
Geographic Area
Criminal Justice Populations
Frequency of Use
Association with Cigarette and Alcohol Use
Driving Under the Influence of Illicit Drugs
Source of Prescription Drugs

3. Alcohol Use
3.1. Alcohol Use among Persons Aged 12 or Older
Age
Gender
Pregnant Women
Race/Ethnicity
Education
College Students
Employment
Geographic Area
Association with Illicit Drug and Tobacco Use
Driving Under the Influence of Alcohol
3.2. Underage Alcohol Use

4. Tobacco Use
Age
Gender
Pregnant Women
Race/Ethnicity
Education
College Students
Employment
Geographic Area
Association with Illicit Drug and Alcohol Use
Frequency of Cigarette Use

5. Initiation of Substance Use
Initiation of Illicit Drug Use
Comparison, by Drug
Marijuana
Cocaine
Heroin
Hallucinogens
Inhalants
Psychotherapeutics
Alcohol
Tobacco

6. Youth Prevention-Related Measures
Perceived Risk of Substance Use
Perceived Availability
Perceived Parental Disapproval of Substance Use
Attitudes toward Peer Substance Use
Fighting and Delinquent Behavior
Religious Beliefs and Participation in Activities
Exposure to Substance Use Prevention Messages and Programs
Parental Involvement

7. Substance Dependence, Abuse, and Treatment
7.1. Substance Dependence or Abuse
Age at First Use
Age
Gender
Race/Ethnicity
Education/Employment
Criminal Justice Populations
Geographic Area
7.2. Past Year Treatment for a Substance Use Problem
7.3. Need for and Receipt of Specialty Treatment
Illicit Drug or Alcohol Use Treatment and Treatment Need
Illicit Drug Use Treatment and Treatment Need
Alcohol Use Treatment and Treatment Need

8. Discussion of Trends in Substance Use among Youths and Young Adults
Youths
Young Adults
Nonmedical Use of Prescription Pain Relievers
Summary

Appendix

A. Description of the Survey
A.1 Sample Design
A.2 Data Collection Methodology
A.3 Data Processing

B. Statistical Methods and Measurement
B.1 Target Population
B.2 Sampling Error and Statistical Significance
B.3 Other Information on Data Accuracy
B.4 Measurement Issues

C. Other Sources of Data
C.1 Other National Surveys of Substance Use
C.2 Surveys of Populations Not Covered by NSDUH

D. References

E. List of Contributors

List of Figures

Figure 1.1 U.S. Census Bureau Regions

Figure 2.1 Past Month Illicit Drug Use among Persons Aged 12 or Older: 2010

Figure 2.2 Past Month Use of Selected Illicit Drugs among Persons Aged 12 or Older: 2002-2010

Figure 2.3 Past Month Nonmedical Use of Types of Psychotherapeutic Drugs among Persons Aged 12 or Older: 2002-2010

Figure 2.4 Past Month Illicit Drug Use among Persons Aged 12 or Older, by Age: 2009 and 2010

Figure 2.5 Past Month Illicit Drug Use among Persons Aged 12 or Older, by Age: 2002-2010

Figure 2.6 Past Month Use of Selected Illicit Drugs among Youths Aged 12 to 17: 2002-2010

Figure 2.7 Past Month Use of Selected Illicit Drugs among Young Adults Aged 18 to 25: 2002-2010

Figure 2.8 Past Month Illicit Drug Use among Adults Aged 50 to 59: 2002-2010

Figure 2.9 Past Month Marijuana Use among Youths Aged 12 to 17, by Gender: 2002-2010

Figure 2.10 Past Month Illicit Drug Use among Persons Aged 12 or Older, by Race/Ethnicity: 2002-2010

Figure 2.11 Past Month Illicit Drug Use among Persons Aged 18 or Older, by Employment Status: 2009 and 2010

Figure 2.12 Past Month Illicit Drug Use among Persons Aged 12 or Older, by County Type: 2010

Figure 3.1 Current, Binge, and Heavy Alcohol Use among Persons Aged 12 or Older, by Age: 2010

Figure 3.2 Current, Binge, and Heavy Alcohol Use among Persons Aged 12 or Older, by Race/Ethnicity: 2010

Figure 3.3 Binge Alcohol Use among Adults Aged 18 to 22, by College Enrollment: 2002-2010

Figure 3.4 Driving Under the Influence of Alcohol in the Past Year among Persons Aged 12 or Older: 2002-2010

Figure 3.5 Driving Under the Influence of Alcohol in the Past Year among Persons Aged 16 or Older, by Age: 2010

Figure 3.6 Current Alcohol Use among Persons Aged 12 to 20, by Age: 2002-2010

Figure 3.7 Current, Binge, and Heavy Alcohol Use among Persons Aged 12 to 20, by Gender: 2010

Figure 4.1 Past Month Tobacco Use among Persons Aged 12 or Older: 2002-2010

Figure 4.2 Past Month Tobacco Use among Youths Aged 12 to 17: 2002-2010

Figure 4.3 Past Month Cigarette Use among Persons Aged 12 or Older, by Age: 2010

Figure 4.4 Past Month Cigarette Use among Youths Aged 12 to 17, by Gender: 2002-2010

Figure 4.5 Past Month Cigarette Use among Women Aged 15 to 44, by Pregnancy Status: Combined Years 2002-2003 to 2009-2010

Figure 4.6 Past Month Smokers of One or More Packs of Cigarettes per Day among Daily Smokers, by Age Group: 2002-2010

Figure 5.1 First Specific Drug Associated with Initiation of Illicit Drug Use among Past Year Illicit Drug Initiates Aged 12 or Older: 2010

Figure 5.2 Past Year Initiates of Specific Illicit Drugs among Persons Aged 12 or Older: 2010

Figure 5.3 Mean Age at First Use for Specific Illicit Drugs among Past Year Initiates Aged 12 to 49: 2010

Figure 5.4 Past Year Marijuana Initiates among Persons Aged 12 or Older and Mean Age at First Use of Marijuana among Past Year Marijuana Initiates Aged 12 to 49: 2002-2010

Figure 5.5 Past Year Hallucinogen Initiates among Persons Aged 12 or Older: 2002-2010

Figure 5.6 Past Year Methamphetamine Initiates among Persons Aged 12 or Older and Mean Age at First Use of Methamphetamine among Past Year Methamphetamine Initiates Aged 12 to 49: 2002-2010

Figure 5.7 Past Year Cigarette Initiates among Persons Aged 12 or Older, by Age at First Use: 2002-2010

Figure 5.8 Past Year Cigarette Initiation among Youths Aged 12 to 17 Who Had Never Smoked Prior to the Past Year, by Gender: 2002-2010

Figure 6.1 Past Month Binge Drinking and Marijuana Use among Youths Aged 12 to 17, by Perceptions of Risk: 2010

Figure 6.2 Perceived Great Risk of Cigarette and Alcohol Use among Youths Aged 12 to 17: 2002-2010

Figure 6.3 Perceived Great Risk of Marijuana Use among Youths Aged 12 to 17: 2002-2010

Figure 6.4 Perceived Great Risk of Use of Selected Illicit Drugs Once or Twice a Week among Youths Aged 12 to 17: 2002-2010

Figure 6.5 Perceived Availability of Selected Illicit Drugs among Youths Aged 12 to 17: 2002-2010

Figure 6.6 Exposure to Substance Use Prevention Messages and Programs among Youths Aged 12 to 17: 2002-2010

Figure 7.1 Substance Dependence or Abuse in the Past Year among Persons Aged 12 or Older: 2002-2010

Figure 7.2 Specific Illicit Drug Dependence or Abuse in the Past Year among Persons Aged 12 or Older: 2010

Figure 7.3 Illicit Drug Dependence or Abuse in the Past Year among Persons Aged 12 or Older: 2002-2010

Figure 7.4 Alcohol Dependence or Abuse in the Past Year among Adults Aged 21 or Older, by Age at First Use of Alcohol: 2010

Figure 7.5 Alcohol and Illicit Drug Dependence or Abuse among Youths Aged 12 to 17: 2002-2010

Figure 7.6 Substance Dependence or Abuse in the Past Year, by Age and Gender: 2010

Figure 7.7 Locations Where Past Year Substance Use Treatment Was Received among Persons Aged 12 or Older: 2010

Figure 7.8 Substances for Which Most Recent Treatment Was Received in the Past Year among Persons Aged 12 or Older: 2010

Figure 7.9 Received Most Recent Treatment in the Past Year for the Use of Pain Relievers among Persons Aged 12 or Older: 2002-2010

Figure 7.10 Past Year Perceived Need for and Effort Made to Receive Specialty Treatment among Persons Aged 12 or Older Needing But Not Receiving Treatment for Illicit Drug or Alcohol Use: 2010

Figure 7.11 Reasons for Not Receiving Substance Use Treatment among Persons Aged 12 or Older Who Needed and Made an Effort to Get Treatment But Did Not Receive Treatment and Felt They Needed Treatment: 2007-2010 Combined

Figure 8.1 Past Month Alcohol Use among Youths in NSDUH and MTF: 2002-2010

Figure 8.2 Past Month Cigarette Use among Youths in NSDUH and MTF: 2002-2010

Figure 8.3 Past Month Marijuana Use among Youths in NSDUH and MTF: 2002-2010

Figure 8.4 Past Month Marijuana Use among Youths in NSDUH, MTF, and YRBS: 1971-2010

Figure 8.5 Past Year Nonmedical Pain Reliever Use among Youths and Young Adults in NSDUH and MTF: 1994-2010

Figure B.1 Required Effective Sample in the 2010 NSDUH as a Function of the Proportion Estimated

List of Tables

Table 8.1 Comparison of NSDUH and MTF Prevalence Estimates among Youths: Percentages, 2002-2010

Table 8.2 Comparison of NSDUH and MTF Prevalence Estimates among Young Adults: Percentages, 2002-2010

Table B.1 Demographic and Geographic Domains Forced to Match Their Respective U.S. Census Bureau Population Estimates through the Weight Calibration Process, 2010

Table B.2 Summary of 2010 NSDUH Suppression Rules

Table B.3 Weighted Percentages and Sample Sizes for 2009 and 2010 NSDUHs, by Final Screening Result Code

Table B.4 Weighted Percentages and Sample Sizes for 2009 and 2010 NSDUHs, by Final Interview Code

Table B.5 Response Rates and Sample Sizes for 2009 and 2010 NSDUHs, by Demographic Characteristics

Table B.6 Past Year Initiates of Marijuana and Any Illicit Drug among Persons Aged 26 or Older or Aged 26 to 49: Numbers in Thousands, 2002-2010

Table B.7 Mean Age at First Use of Marijuana and Any Illicit Drug among Past Year Initiates Aged 26 to 49, 2002-2010

Table C.1 Use of Specific Substances in Lifetime, Past Year, and Past Month among 8th, 10th, and 12th Graders in MTF and NSDUH: Percentages, 2009 and 2010

Table C.2 Lifetime and Past Month Substance Use among Students in Grades 9 to 12 in YRBS and NSDUH: Percentages, 2005, 2007, and 2009

Highlights

This report presents the first information from the 2010 National Survey on Drug Use and Health (NSDUH), an annual survey sponsored by the Substance Abuse and Mental Health Services Administration (SAMHSA). The survey is the primary source of information on the use of illicit drugs, alcohol, and tobacco in the civilian, noninstitutionalized population of the United States aged 12 years old or older. The survey interviews approximately 67,500 persons each year. Unless otherwise noted, all comparisons in this report described using terms such as "increased," "decreased," or "more than" are statistically significant at the .05 level.

Illicit Drug Use

Alcohol Use

Tobacco Use

Initiation of Substance Use (Incidence, or First-Time Use) within the Past 12 Months

Youth Prevention-Related Measures

Substance Dependence, Abuse, and Treatment

1. Introduction

This report presents a first look at results from the 2010 National Survey on Drug Use and Health (NSDUH), an annual survey of the civilian, noninstitutionalized population of the United States aged 12 years old or older. The report presents national estimates of rates of use, numbers of users, and other measures related to illicit drugs, alcohol, and tobacco products. The report focuses on trends between 2009 and 2010 and from 2002 to 2010, as well as differences across population subgroups in 2010. NSDUH estimates related to mental health, which were included in national findings reports prior to 2009, are not included in this 2010 report. A separate report focusing on 2010 mental health data, including co-occurring mental and substance use disorders, will be published later in 2011.

Summary of NSDUH

NSDUH is the primary source of statistical information on the use of illegal drugs, alcohol, and tobacco by the U.S. civilian, noninstitutionalized population aged 12 or older. Conducted by the Federal Government since 1971, the survey collects data through face-to-face interviews with a representative sample of the population at the respondent's place of residence. The survey is sponsored by the Substance Abuse and Mental Health Services Administration (SAMHSA), U.S. Department of Health and Human Services, and is planned and managed by SAMHSA's Center for Behavioral Health Statistics and Quality (CBHSQ, formerly the Office of Applied Studies, OAS). Data collection and analysis are conducted under contract with RTI International, Research Triangle Park, North Carolina.1 This section briefly describes the survey methodology; a more complete description is provided in Appendix A.

NSDUH collects information from residents of households and noninstitutional group quarters (e.g., shelters, rooming houses, dormitories) and from civilians living on military bases. The survey excludes homeless persons who do not use shelters, military personnel on active duty, and residents of institutional group quarters, such as jails and hospitals. Appendix C describes substance use surveys that cover populations outside the NSDUH target population.

From 1971 through 1998, the survey employed paper and pencil data collection. Since 1999, the NSDUH interview has been carried out using computer-assisted interviewing (CAI). Most of the questions are administered with audio computer-assisted self-interviewing (ACASI). ACASI is designed to provide the respondent with a highly private and confidential mode for responding to questions in order to increase the level of honest reporting of illicit drug use and other sensitive behaviors. Less sensitive items are administered by interviewers using computer-assisted personal interviewing (CAPI).

The 2010 NSDUH employed a State-based design with an independent, multistage area probability sample within each State and the District of Columbia. The eight States with the largest population (which together account for about half of the total U.S. population aged 12 or older) were designated as large sample States (California, Florida, Illinois, Michigan, New York, Ohio, Pennsylvania, and Texas) and had a sample size of about 3,600 each. For the remaining 42 States and the District of Columbia, the sample size was about 900 per State. The design oversampled youths and young adults; each State's sample was approximately equally distributed among three age groups: 12 to 17 years, 18 to 25 years, and 26 years or older.

Nationally, screening was completed at 147,608 addresses, and 68,487 completed interviews were obtained. The survey was conducted from January through December 2010. Weighted response rates for household screening and for interviewing were 88.8 and 74.7 percent, respectively. See Appendix B for more information on NSDUH response rates.

Limitations on Trend Measurement

Because of the shift in interviewing method in 1999, the estimates from the pre-1999 surveys are not comparable with estimates from the current CAI-based surveys. Although the design of the 2002 through 2010 NSDUHs is similar to the design of the 1999 through 2001 surveys, there are methodological differences that affect the comparability of the 2002 to 2010 estimates with estimates from prior surveys. The most important change was the incentive payment that started in 2002. Each NSDUH respondent completing the interview is given $30. Also, the name of the survey was changed in 2002, from the National Household Survey on Drug Abuse (NHSDA) to the current name. Improved data collection quality control procedures were introduced in the survey starting in 2001, and updated population data from the 2000 decennial census were incorporated into the sample weights starting with the 2002 estimates. Analyses of the effects of these factors on NSDUH estimates have shown that 2002 and later data should not be compared with 2001 and earlier data from the survey series to assess changes over time. Appendix C of the 2004 NSDUH report on national findings discusses this in more detail (see OAS, 2005).

Because of changes in the questionnaire, estimates for methamphetamine, stimulants, and psychotherapeutics in this report should not be compared with corresponding estimates presented in reports for data years prior to 2007. Estimates for 2002 to 2006 for these drug categories in this report, as well as in the 2007 and 2008 reports, incorporate statistical adjustments that enable year-to-year comparisons to be made over the period from 2002 to 2010.

Format of Report and Data Presentation

This report has separate chapters that discuss findings on the use of illicit drugs; use of alcohol; use of tobacco products; initiation of substance use; prevention-related issues; and substance dependence, abuse, and treatment. A final chapter summarizes the results and discusses key findings in relation to other research and survey results. The data and findings described in this report are based on a comprehensive set of tables, referred to as "detailed tables," that include population estimates (e.g., numbers of drug users), rates (e.g., percentages of the population using drugs), and standard errors of estimates. These tables are available separately on the CBHSQ Web site (http://www.samhsa.gov/data/). In addition, the tables are accompanied by a glossary that covers key definitions used in this report and in the detailed tables. Appendices in this report describe the survey (Appendix A), technical details on the statistical methods and measurement (Appendix B), and other sources of related data (Appendix C). A list of references cited in the report (Appendix D) and contributors to this report (Appendix E) also are provided.

Text, figures, and detailed tables present prevalence measures for the population in terms of both the number of persons and the percentage of the population. Substance use tables show prevalence estimates by lifetime (i.e., ever used), past year, and past month use. Analyses focus primarily on past month use, which also is referred to as "current use." Where applicable, footnotes are included in tables and figures to indicate whether the 2010 estimates are significantly different from 2009 or earlier estimates. In addition, some estimates are presented based on data combined from two or more survey years to increase precision of the estimates; those estimates are annual averages based on multiple years of data.

Statistical tests have been conducted for all statements appearing in the text of the report that compare estimates between years or subgroups of the population. Unless explicitly stated that a difference is not statistically significant, all statements that describe differences are significant at the .05 level. Statistically significant differences are described using terms such as "higher," "lower," "increased," and "decreased." Statements that use terms such as "similar," "no difference," "same," or "remained steady" to describe the relationship between estimates denote that a difference is not statistically significant. When a set of estimates for survey years or population subgroups is presented without a statement of comparison, statistically significant differences among these estimates are not implied and testing may not have been conducted.

All estimates presented in the report have met the criteria for statistical reliability (see Section B.2.2 in Appendix B). Estimates that do not meet these criteria do not appear in tables, figures, or text. Suppressed estimates are not included in statistical tests of comparisons. For example, a statement that "whites had the highest prevalence" means that the rate among whites was higher than the rate among all nonsuppressed racial/ethnic subgroups, but not necessarily higher than the rate among a subgroup for which the estimate was suppressed.

Data are presented for racial/ethnic groups based on guidelines for collecting and reporting race and ethnicity data (Office of Management and Budget [OMB], 1997). Because respondents could choose more than one racial group, a "two or more races" category is included for persons who reported more than one category (i.e., white, black or African American, American Indian or Alaska Native, Native Hawaiian, Other Pacific Islander, Asian, Other). Respondents choosing both Native Hawaiian and Other Pacific Islander but no other categories are classified as being in the "Native Hawaiian or Other Pacific Islander" category instead of the "two or more race" category. Except for the "Hispanic or Latino" group, the racial/ethnic groups include only non-Hispanics. The category "Hispanic or Latino" includes Hispanics of any race.

Data in this report also are presented for four U.S. geographic regions as defined by the U.S. Census Bureau (Figure 1.1). Other geographic comparisons also are made based on county type, a variable that reflects different levels of urbanicity and metropolitan area inclusion of counties. This county classification was originally developed and subsequently updated by the U.S. Department of Agriculture (Butler & Beale, 1994). Each county is either inside or outside a metropolitan statistical area (MSA), based on metropolitan area definitions issued by the OMB in June 2003 (OMB, 2003). Large metropolitan areas have a population of 1 million or more. Small metropolitan areas have a population of fewer than 1 million. Nonmetropolitan areas are outside of MSAs. Counties in nonmetropolitan areas are further classified based on the number of people in the county who live in an urbanized area, as defined by the Census Bureau at the subcounty level. "Urbanized" counties have a population of 20,000 or more in urbanized areas, "less urbanized" counties have at least 2,500 but fewer than 20,000 population in urbanized areas, and "completely rural" counties have populations of fewer than 2,500 in urbanized areas.

Figure 1.1 U.S. Census Bureau Regions

Figure 1.1     D

Other NSDUH Reports and Data

Other reports focusing on specific topics of interest will be produced using the 2010 NSDUH data and made available on SAMHSA's Web site. In particular, data on mental health will be discussed in a separate report to be released later this year: Results from the 2010 National Survey on Drug Use and Health: Mental Health Findings. A report on State-level estimates for substance use and mental health for 2009-2010 is scheduled to be released in the spring of 2012. A report on substate estimates using data from 2008-2010 is scheduled for publication in the summer of 2012.

The detailed tables, other descriptive reports and in-depth analytic reports focusing on specific issues or populations, and methodological information on NSDUH, including the questionnaire, are all available at http://www.samhsa.gov/data/. In addition, CBHSQ makes public use data files available through the Substance Abuse and Mental Health Data Archive at http://www.datafiles.samhsa.gov. Currently, files are available from the 1979 to 2009 surveys. The 2010 NSDUH public use file will be available by the end of 2011.

2. Illicit Drug Use

The National Survey on Drug Use and Health (NSDUH) obtains information on nine categories of illicit drug use: use of marijuana, cocaine, heroin, hallucinogens, and inhalants, as well as the nonmedical use of prescription-type pain relievers, tranquilizers, stimulants, and sedatives. In these categories, hashish is included with marijuana, and crack is considered a form of cocaine. Several drugs are grouped under the hallucinogens category, including LSD, PCP, peyote, mescaline, psilocybin mushrooms, and "Ecstasy" (MDMA). Inhalants include a variety of substances, such as nitrous oxide, amyl nitrite, cleaning fluids, gasoline, spray paint, other aerosol sprays, and glue. Respondents are asked to report use of inhalants to get high but not to report times when they accidentally inhaled a substance.

The four categories of prescription-type drugs (pain relievers, tranquilizers, stimulants, and sedatives) cover numerous medications that currently are or have been available by prescription. They also include drugs within these groupings that originally were prescription medications but currently may be manufactured and distributed illegally, such as methamphetamine, which is included under stimulants. Respondents are asked to report only "nonmedical" use of these drugs, defined as use without a prescription of the individual's own or simply for the experience or feeling the drugs caused. Use of over-the-counter drugs and legitimate use of prescription drugs are not included. NSDUH reports combine the four prescription-type drug groups into a category referred to as "psychotherapeutics."

Estimates of "illicit drug use" reported from NSDUH reflect the use of any of the nine drug categories listed above. Use of alcohol and tobacco products, while illegal for youths, is not included in these estimates, but is discussed in Chapters 3 and 4.

Figure 2.1 Past Month Illicit Drug Use among Persons Aged 12 or Older: 2010

Figure 2.1     D

1 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used nonmedically.

Figure 2.2 Past Month Use of Selected Illicit Drugs among Persons Aged 12 or Older: 2002-2010

Figure 2.2     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Figure 2.3 Past Month Nonmedical Use of Types of Psychotherapeutic Drugs among Persons Aged 12 or Older: 2002-2010

Figure 2.3     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Age

Figure 2.4 Past Month Illicit Drug Use among Persons Aged 12 or Older, by Age: 2009 and 2010

Figure 2.4     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Figure 2.5 Past Month Illicit Drug Use among Persons Aged 12 or Older, by Age: 2002-2010

Figure 2.5     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Youths Aged 12 to 17

Figure 2.6 Past Month Use of Selected Illicit Drugs among Youths Aged 12 to 17: 2002-2010

Figure 2.6     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Young Adults Aged 18 to 25

Figure 2.7 Past Month Use of Selected Illicit Drugs among Young Adults Aged 18 to 25: 2002-2010

Figure 2.7     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Adults Aged 26 or Older

Figure 2.8 Past Month Illicit Drug Use among Adults Aged 50 to 59: 2002-2010

Figure 2.8     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Gender

Figure 2.9 Past Month Marijuana Use among Youths Aged 12 to 17, by Gender: 2002-2010

Figure 2.9     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Pregnant Women

Race/Ethnicity

Figure 2.10 Past Month Illicit Drug Use among Persons Aged 12 or Older, by Race/Ethnicity: 2002-2010

Figure 2.10     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level. 
Note: Sample sizes for American Indians or Alaska Natives and for persons of two or more races were too small for reliable trend presentation for these groups. Due to low precision, estimates for Native Hawaiians or Other Pacific Islanders are not shown.

Education

College Students

Employment

Figure 2.11 Past Month Illicit Drug Use among Persons Aged 18 or Older, by Employment Status: 2009 and 2010

Figure 2.11     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.
1 The Other Employment category includes retired persons, disabled persons, homemakers, students, or other persons not in the labor force.

Geographic Area

Figure 2.12 Past Month Illicit Drug Use among Persons Aged 12 or Older, by County Type: 2010

Figure 2.12     D

Criminal Justice Populations

Frequency of Use

Association with Cigarette and Alcohol Use

Driving Under the Influence of Illicit Drugs

Source of Prescription Drugs

3. Alcohol Use

The National Survey on Drug Use and Health (NSDUH) includes questions about the recency and frequency of consumption of alcoholic beverages, such as beer, wine, whiskey, brandy, and mixed drinks. An extensive list of examples of the kinds of beverages covered is given to respondents prior to the question administration. A "drink" is defined as a can or bottle of beer, a glass of wine or a wine cooler, a shot of liquor, or a mixed drink with liquor in it. Times when the respondent only had a sip or two from a drink are not considered to be consumption. For this report, estimates for the prevalence of alcohol use are reported primarily at three levels defined for both males and females and for all ages as follows:

These levels are not mutually exclusive categories of use; heavy use is included in estimates of binge and current use, and binge use is included in estimates of current use.

This chapter is divided into two main sections. Section 3.1 describes trends and patterns of alcohol use among the population aged 12 or older. Section 3.2 is concerned particularly with the use of alcohol by persons aged 12 to 20. These persons are under the legal drinking age in all 50 States and the District of Columbia.

3.1. Alcohol Use among Persons Aged 12 or Older

Age

Figure 3.1 Current, Binge, and Heavy Alcohol Use among Persons Aged 12 or Older, by Age: 2010

Figure 3.1     D

Gender

Pregnant Women

Race/Ethnicity

Figure 3.2 Current, Binge, and Heavy Alcohol Use among Persons Aged 12 or Older, by Race/Ethnicity: 2010

Figure 3.2     D

Note: Due to low precision, estimates for Native Hawaiians or Other Pacific Islanders are not shown.

Education

College Students

Figure 3.3 Binge Alcohol Use among Adults Aged 18 to 22, by College Enrollment: 2002-2010

Figure 3.3     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Employment

Geographic Area

Association with Illicit Drug and Tobacco Use

Driving Under the Influence of Alcohol

Figure 3.4 Driving Under the Influence of Alcohol in the Past Year among Persons Aged 12 or Older: 2002-2010

Figure 3.4     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Figure 3.5 Driving Under the Influence of Alcohol in the Past Year among Persons Aged 16 or Older, by Age: 2010

Figure 3.5     D

3.2. Underage Alcohol Use

Figure 3.6 Current Alcohol Use among Persons Aged 12 to 20, by Age: 2002-2010

Figure 3.6     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Figure 3.7 Current, Binge, and Heavy Alcohol Use among Persons Aged 12 to 20, by Gender: 2010

Figure 3.7     D

4. Tobacco Use

The National Survey on Drug Use and Health (NSDUH) includes a series of questions about the use of tobacco products, including cigarettes, chewing tobacco, snuff, cigars, and pipe tobacco. Cigarette use is defined as smoking "part or all of a cigarette." For analytic purposes, data for chewing tobacco and snuff are combined as "smokeless tobacco."

Figure 4.1 Past Month Tobacco Use among Persons Aged 12 or Older: 2002-2010

Figure 4.1     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Age

Figure 4.2 Past Month Tobacco Use among Youths Aged 12 to 17: 2002-2010

Figure 4.2     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Figure 4.3 Past Month Cigarette Use among Persons Aged 12 or Older, by Age: 2010

Figure 4.3     D

Gender

Figure 4.4 Past Month Cigarette Use among Youths Aged 12 to 17, by Gender: 2002-2010

Figure 4.4     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Pregnant Women

Figure 4.5 Past Month Cigarette Use among Women Aged 15 to 44, by Pregnancy Status: Combined Years 2002-2003 to 2009-2010

Figure 4.5     D

+ Difference between this estimate and the 2009-2010 estimate is statistically significant at the .05 level.

Race/Ethnicity

Education

College Students

Employment

Geographic Area

Association with Illicit Drug and Alcohol Use

Frequency of Cigarette Use

Figure 4.6 Past Month Smokers of One or More Packs of Cigarettes per Day among Daily Smokers, by Age Group: 2002-2010

Figure 4.6     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

5. Initiation of Substance Use

Information on substance use initiation, also known as incidence or first-time use, is important for policymakers and researchers. Measures of initiation are often leading indicators of emerging patterns of substance use. They provide valuable information that can be used to assess the effectiveness of current prevention programs and to focus prevention efforts.

With its large sample size and oversampling of youths aged 12 to 17 and young adults aged 18 to 25, the National Survey on Drug Use and Health (NSDUH) provides a variety of estimates related to initiation of substance use (illicit drugs, cigarettes, and alcohol) based on reported age and on year and month at first use. This chapter presents estimates of initiation occurring in the 12 months prior to the interview date. Individuals who initiated use within the past 12 months are referred to as recent or past year initiates. One caveat of this approach is that because the survey interviews persons aged 12 or older and asks about the past 12 months, the initiation estimates will represent some, but not all, of the initiation at age 11 and no initiation occurring at age 10 or younger. This underestimation problem primarily affects estimates of initiation for cigarettes, alcohol, and inhalants because they tend to be initiated at a younger age than other substances. See Section B.4.1 in Appendix B for further discussion of the methods and bias in initiation estimates.

This chapter includes estimates of the number and rate of past year initiation of illicit drug, cigarette, and alcohol use among the total population aged 12 or older and by age and gender categories from the 2002 to 2010 NSDUHs. Also included are initiation estimates that pertain to persons at risk for initiation. At risk for initiation is defined as persons who never used the substance in their lifetime along with persons who used the substance for the first time in the 12 months prior to the interview. In other words, persons at risk are those who had never used as of 12 months prior to the interview date. Some analyses are based on the ages at the time of interview, and others focus on the age at the time of first substance use. Readers need to be aware of these alternative estimation approaches when interpreting NSDUH incidence estimates and pay close attention to the approach used in each situation. Titles and notes on figures and associated detailed tables document which method applies.

For trend measurement, initiation estimates for each year (2002 to 2010) are produced independently based on the data from the survey conducted that year. It should be mentioned that trend estimates of incidence based on long recall periods have not been considered because of concerns about their validity (Gfroerer, Hughes, Chromy, Heller, & Packer, 2004).

Regarding the age at first use estimates, means, as measures of central tendency, are heavily influenced by the presence of extreme values in the data. Thus, for the purposes of this report and unless specified otherwise, the mean age at initiation pertains to persons aged 12 to 49. This constraint was implemented so that the mean age estimates reported would not be influenced by those few respondents who were past year initiates at age 50 or older. However, initiates aged 26 to 49 can have a smaller, but substantial effect on the stability of mean age estimates of persons aged 12 to 49, so caution is needed in describing these trends. Section B.4.1 in Appendix B discusses this issue in more detail. Note that this constraint only affects estimates of mean age at initiation; other estimates in this chapter, including the number and prevalence of past year initiates, are among all persons aged 12 or older.

Another important consideration in examining incidence estimates across different drug categories is that substance users typically initiate use of different substances at different times in their lives. Thus, the estimates for past year initiation of each specific illicit drug cannot be added to obtain the total number of overall illicit drug initiates because some of the initiates previously had used other drugs. The first illicit drug initiation estimate only includes the past year initiation of use of a specific drug that was not preceded by use of other drugs. For example, a respondent who reported initiating marijuana use in the past 12 months is counted as a marijuana initiate. The same respondent also can be counted as an illicit drug initiate with marijuana as the first drug only if his or her marijuana use initiation was not preceded by use of any other drug (cocaine, heroin, hallucinogens, inhalants, pain relievers, tranquilizers, stimulants, or sedatives).

Initiation of Illicit Drug Use

Figure 5.1 First Specific Drug Associated with Initiation of Illicit Drug Use among Past Year Illicit Drug Initiates Aged 12 or Older: 2010

Figure 5.1     D

Note: The percentages do not add to 100 percent due to rounding or because a small number of respondents initiated multiple drugs on the same day. The first specific drug refers to the one that was used on the occasion of first-time use of any illicit drug.

Comparison, by Drug

Figure 5.2 Past Year Initiates of Specific Illicit Drugs among Persons Aged 12 or Older: 2010

Figure 5.2     D

Note: The specific drug refers to the one that was used for the first time, regardless of whether it was the first drug used or not.

Figure 5.3 Mean Age at First Use for Specific Illicit Drugs among Past Year Initiates Aged 12 to 49: 2010

Figure 5.3     D

Marijuana

Figure 5.4 Past Year Marijuana Initiates among Persons Aged 12 or Older and Mean Age at First Use of Marijuana among Past Year Marijuana Initiates Aged 12 to 49: 2002-2010

Figure 5.4     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level. 1 Mean-age-at-first-use estimates are for recent initiates aged 12 to 49.

Cocaine

Heroin

Hallucinogens

Figure 5.5 Past Year Hallucinogen Initiates among Persons Aged 12 or Older: 2002-2010

Figure 5.5     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Inhalants

Psychotherapeutics

Figure 5.6 Past Year Methamphetamine Initiates among Persons Aged 12 or Older and Mean Age at First Use of Methamphetamine among Past Year Methamphetamine Initiates Aged 12 to 49: 2002-2010

Figure 5.6     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.
1 Mean-age-at-first-use estimates are for recent initiates aged 12 to 49.

Alcohol

Tobacco

Figure 5.7 Past Year Cigarette Initiates among Persons Aged 12 or Older, by Age at First Use: 2002-2010

Figure 5.7     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Figure 5.8 Past Year Cigarette Initiation among Youths Aged 12 to 17 Who Had Never Smoked Prior to the Past Year, by Gender: 2002-2010

Figure 5.8     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

6. Youth Prevention-Related Measures

Research has shown that substance use by adolescents can be prevented through interventions involving risk and protective factors associated with the onset or escalation of use (Catalano, Hawkins, Berglund, Pollard, & Arthur, 2002). Risk and protective factors include variables that operate at different stages of development and reflect different domains of influence, including the individual, family, peer, school, community, and societal levels (Hawkins, Catalano, & Miller, 1992; Robertson, David, & Rao, 2003). Interventions to prevent substance use generally are designed to ameliorate the influence of risk factors and enhance the effectiveness of protective factors.

The National Survey on Drug Use and Health (NSDUH) includes questions for youths aged 12 to 17 to measure the risk and protective factors that may affect the likelihood that they will engage in substance use. This chapter presents findings on youth prevention-related measures, comparing the findings from 2002 to 2010. Included are measures of perceived risk from substance use (cigarettes, alcohol, and illicit drugs), perceived availability of substances, being approached by someone selling drugs, perceived parental disapproval of youth substance use, feelings about peer substance use, involvement in fighting and delinquent behavior, participation in religious and other activities, exposure to substance use prevention messages and programs, and parental involvement. Also presented are findings on the associations between selected measures of risk and protective factors and substance use from NSDUH, although the cross-sectional nature of these data preclude making any causal connections between these risk and protective factors and substance use.

Perceived Risk of Substance Use

One factor that can influence whether youths will use tobacco, alcohol, or illicit drugs is the extent to which they believe these substances might cause them harm. NSDUH respondents were asked how much they thought people risk harming themselves physically and in other ways when they use various substances in certain amounts or frequencies. Response choices for these items were "great risk," "moderate risk," "slight risk," or "no risk."

Figure 6.1 Past Month Binge Drinking and Marijuana Use among Youths Aged 12 to 17, by Perceptions of Risk: 2010

Figure 6.1     D

Figure 6.2 Perceived Great Risk of Cigarette and Alcohol Use among Youths Aged 12 to 17: 2002-2010

Figure 6.2     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Figure 6.3 Perceived Great Risk of Marijuana Use among Youths Aged 12 to 17: 2002-2010

Figure 6.3     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Figure 6.4 Perceived Great Risk of Use of Selected Illicit Drugs Once or Twice a Week among Youths Aged 12 to 17: 2002-2010

Figure 6.4     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Perceived Availability

Figure 6.5 Perceived Availability of Selected Illicit Drugs among Youths Aged 12 to 17: 2002-2010

Figure 6.5     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Perceived Parental Disapproval of Substance Use

Attitudes toward Peer Substance Use

Fighting and Delinquent Behavior

Religious Beliefs and Participation in Activities

Exposure to Substance Use Prevention Messages and Programs

Figure 6.6 Exposure to Substance Use Prevention Messages and Programs among Youths Aged 12 to 17: 2002-2010

Figure 6.6     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.
1 Estimates are from youths aged 12 to 17 who were enrolled in school in the past year.

Parental Involvement

7. Substance Dependence, Abuse, and Treatment

The National Survey on Drug Use and Health (NSDUH) includes a series of questions to assess the prevalence of substance use disorders (substance dependence or abuse) in the past 12 months. Substances include alcohol and illicit drugs, such as marijuana, cocaine, heroin, hallucinogens, inhalants, and the nonmedical use of prescription-type psychotherapeutic drugs. These questions are used to classify persons as dependent on or abusing specific substances based on criteria specified in the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) (American Psychiatric Association [APA], 1994).

The questions related to dependence ask about health and emotional problems associated with substance use, unsuccessful attempts to cut down on use, tolerance, withdrawal, reducing other activities to use substances, spending a lot of time engaging in activities related to substance use, or using the substance in greater quantities or for a longer time than intended. The questions on abuse ask about problems at work, home, and school; problems with family or friends; physical danger; and trouble with the law due to substance use. Dependence is considered to be a more severe substance use problem than abuse because it involves the psychological and physiological effects of tolerance and withdrawal. Although individuals may meet the criteria specified here for both dependence and abuse, persons meeting the criteria for both are classified as having dependence, but not abuse. Persons defined with abuse in this report do not meet the criteria for dependence.

This chapter provides estimates of the prevalence and patterns of substance use disorders occurring in the past year from the 2010 NSDUH and compares these estimates against the results from the 2002 through 2009 surveys. It also provides estimates of the prevalence and patterns of the receipt of treatment in the past year for problems related to substance use. This chapter concludes with a discussion of the need for and the receipt of treatment at specialty facilities for problems associated with substance use.

7.1. Substance Dependence or Abuse

Figure 7.1 Substance Dependence or Abuse in the Past Year among Persons Aged 12 or Older: 2002-2010

Figure 7.1     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Figure 7.2 Specific Illicit Drug Dependence or Abuse in the Past Year among Persons Aged 12 or Older: 2010

Figure 7.2     D

Figure 7.3 Illicit Drug Dependence or Abuse in the Past Year among Persons Aged 12 or Older: 2002-2010

Figure 7.3     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Age at First Use

Figure 7.4 Alcohol Dependence or Abuse in the Past Year among Adults Aged 21 or Older, by Age at First Use of Alcohol: 2010

Figure 7.4     D

Age

Figure 7.5 Alcohol and Illicit Drug Dependence or Abuse among Youths Aged 12 to 17: 2002-2010

Figure 7.5     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Gender

Figure 7.6 Substance Dependence or Abuse in the Past Year, by Age and Gender: 2010

Figure 7.6     D

Race/Ethnicity

Education/Employment

Criminal Justice Populations

Geographic Area

7.2. Past Year Treatment for a Substance Use Problem

Estimates described in this section refer to treatment received for illicit drug or alcohol use, or for medical problems associated with the use of illicit drugs or alcohol. This includes treatment received in the past year at any location, such as a hospital (inpatient), rehabilitation facility (outpatient or inpatient), mental health center, emergency room, private doctor's office, prison or jail, or a self-help group, such as Alcoholics Anonymous or Narcotics Anonymous. Persons could report receiving treatment at more than one location. Note that the definition of treatment in this section is different from the definition of specialty treatment described in Section 7.3. Specialty treatment only includes treatment at a hospital (inpatient), a rehabilitation facility (inpatient or outpatient), or a mental health center.

Individuals who reported receiving substance use treatment but were missing information on whether the treatment was specifically for alcohol use or illicit drug use were not counted in estimates of either illicit drug use treatment or alcohol use treatment; however, they were counted in estimates for "drug or alcohol use" treatment.

Figure 7.7 Locations Where Past Year Substance Use Treatment Was Received among Persons Aged 12 or Older: 2010

Figure 7.7     D

Figure 7.8 Substances for Which Most Recent Treatment Was Received in the Past Year among Persons Aged 12 or Older: 2010

Figure 7.8     D

Figure 7.9 Received Most Recent Treatment in the Past Year for the Use of Pain Relievers among Persons Aged 12 or Older: 2002-2010

Figure 7.9     D

+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

7.3. Need for and Receipt of Specialty Treatment

This section discusses the need for and receipt of treatment for a substance use problem at a "specialty" treatment facility. Specialty treatment is defined as treatment received at any of the following types of facilities: hospitals (inpatient only), drug or alcohol rehabilitation facilities (inpatient or outpatient), or mental health centers. It does not include treatment at an emergency room, private doctor's office, self-help group, prison or jail, or hospital as an outpatient. An individual is defined as needing treatment for an alcohol or drug use problem if he or she met the DSM-IV (APA, 1994) diagnostic criteria for alcohol or illicit drug dependence or abuse in the past 12 months or if he or she received specialty treatment for alcohol use or illicit drug use in the past 12 months.

In this section, an individual needing treatment for an illicit drug use problem is defined as receiving treatment for his or her drug use problem only if he or she reported receiving specialty treatment for drug use in the past year. Thus, an individual who needed treatment for illicit drug use but only received specialty treatment for alcohol use in the past year or who received treatment for illicit drug use only at a facility not classified as a specialty facility was not counted as receiving treatment for drug use. Similarly, an individual who needed treatment for an alcohol use problem was only counted as receiving alcohol use treatment if the treatment was received for alcohol use at a specialty treatment facility. Individuals who reported receiving specialty substance use treatment but were missing information on whether the treatment was specifically for alcohol use or drug use were not counted in estimates of specialty drug use treatment or in estimates of specialty alcohol use treatment; however, they were counted in estimates for "drug or alcohol use" treatment.

In addition to questions about symptoms of substance use problems that are used to classify respondents' need for treatment based on DSM-IV criteria, NSDUH includes questions asking respondents about their perceived need for treatment (i.e., whether they felt they needed treatment or counseling for illicit drug use or alcohol use). In this report, estimates for perceived need for treatment are only discussed for persons who were classified as needing treatment (based on DSM-IV criteria) but did not receive treatment at a specialty facility. Similarly, estimates for whether a person made an effort to get treatment are only discussed for persons who felt the need for treatment.

Illicit Drug or Alcohol Use Treatment and Treatment Need

Figure 7.10 Past Year Perceived Need for and Effort Made to Receive Specialty Treatment among Persons Aged 12 or Older Needing But Not Receiving Treatment for Illicit Drug or Alcohol Use: 2010

Figure 7.10     D

Figure 7.11 Reasons for Not Receiving Substance Use Treatment among Persons Aged 12 or Older Who Needed and Made an Effort to Get Treatment But Did Not Receive Treatment and Felt They Needed Treatment: 2007-2010 Combined

Figure 7.11     D

[NOTE: Estimates corrected in this figure, April 2012]

Illicit Drug Use Treatment and Treatment Need

Alcohol Use Treatment and Treatment Need

8. Discussion of Trends in Substance Use among Youths and Young Adults

This report presents findings from the 2010 National Survey on Drug Use and Health (NSDUH). Conducted since 1971 and previously named the National Household Survey on Drug Abuse (NHSDA), the survey underwent several methodological improvements in 2002 that have affected prevalence estimates. As a result, the 2002 through 2010 estimates are not comparable with estimates from 2001 and earlier surveys. Therefore, the primary focus of this report is on comparisons of measures of substance use across subgroups of the U.S. population in 2010, changes between 2009 and 2010, and changes between 2002 and 2010. This chapter provides an additional discussion of the findings concerning a topic of great interest—trends in substance use among youths and young adults.

An important step in the analysis and interpretation of NSDUH or any other survey data is to compare the results with those from other data sources. This can be difficult sometimes because the other surveys typically have different purposes, definitions, and designs. Research has established that surveys of substance use and other sensitive topics often produce inconsistent results because of different methods used. Thus, it is important to understand that conflicting results often reflect differing methodologies, not incorrect results. Despite this limitation, comparisons can be very useful. Consistency across surveys can confirm or support conclusions about trends and patterns of use, and inconsistent results can point to areas for further study. Further discussion of this issue is included in Appendix C, along with descriptions of methods and results from other sources of substance use data.

Unfortunately, few additional data sources are available at this time to compare with NSDUH results. One established source is Monitoring the Future (MTF), a study sponsored by the National Institute on Drug Abuse (NIDA). MTF surveys students in the 8th, 10th, and 12th grades in classrooms during the spring of each year, and it also collects data by mail from a subsample of adults who had participated earlier in the study as 12th graders (Johnston, O'Malley, Bachman, & Schulenberg, 2011a, 2011b). Historically, NSDUH rates of substance use among youths have been lower than those of MTF, and occasionally the two surveys have shown different trends over a short time period. Nevertheless, the two sources have shown very similar long-term trends in prevalence. NSDUH and MTF rates of substance use generally have been similar among young adults, and the two sources also have shown similar trends.

A comparison of NSDUH and MTF estimates for 2002 to 2010 is shown in Tables 8.1 and 8.2 at the end of this chapter for several substances that are defined similarly in the two surveys. For comparison purposes, MTF data on 8th and 10th graders are combined to give an age range close to 12 to 17 years, the standard youth age group for NSDUH. Appendix C provides comparisons according to MTF definitions (8th, 10th, and 12th grades). MTF follow-up data on persons aged 19 to 24 provide the closest match on age to estimates for NSDUH young adults aged 18 to 25. The NSDUH results are remarkably consistent with MTF trends for both youths and young adults, as discussed in the following paragraphs.

Youths

Both surveys showed decreases between 2002 and 2010 in the percentages of youths who used cocaine, alcohol, and cigarettes in the past month (Table 8.1). The data on trends in alcohol use showed remarkably similar patterns in the two surveys, with a significant decline between 2007 and 2008, no change between 2008 and 2009, and a significant decline between 2009 and 2010 (Figure 8.1). However, the results for cigarette use differed. NSDUH showed a continuing decline in youth cigarette use between 2008 and 2010, while MTF estimates did not change significantly over this period (Figure 8.2). NSDUH and MTF data showed consistent trends for past month use of marijuana (Figure 8.3) and Ecstasy, with decreases in use from 2002 to the middle of the decade, then increasing use from 2007 or 2008 to 2010. Both surveys indicated little change in past month use of LSD or inhalants.

Figure 8.1 Past Month Alcohol Use among Youths in NSDUH and MTF: 2002-2010

Figure 8.1     D

MTF = Monitoring the Future; NSDUH = National Survey on Drug Use and Health.
+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Figure 8.2 Past Month Cigarette Use among Youths in NSDUH and MTF: 2002-2010

Figure 8.2     D

MTF = Monitoring the Future; NSDUH = National Survey on Drug Use and Health.
+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

Figure 8.3 Past Month Marijuana Use among Youths in NSDUH and MTF: 2002-2010

Figure 8.3     D

MTF = Monitoring the Future; NSDUH = National Survey on Drug Use and Health.
+ Difference between this estimate and the 2010 estimate is statistically significant at the .05 level.

NSDUH and MTF data on perceived risk of harm provide an important context for these trends. The extent to which youths believe that substances might cause them harm is an important factor influencing whether or not they will use these substances. Declining levels of perceived risk among youths historically have been associated with subsequent increases in rates of use, and this association continues to be evident in the most recent data. Among youths aged 12 to 17, the percentage reporting in NSDUH that they thought there was a great risk of harm in smoking marijuana once or twice a week was 54.7 percent in 2007, 53.1 percent in 2008, 49.3 percent in 2009, and 47.5 percent in 2010. MTF data for combined 8th and 10th graders showed a similar decline in perceived harmfulness of regular marijuana use over this time period. NSDUH does not obtain data on perceived harm for Ecstasy use, but MTF data showed significant declines among youths who perceived risk in using Ecstasy. For example, the percentage of 8th and 10th graders reporting great risk in occasionally using Ecstasy declined from 69.9 percent in 2004 to 52.1 percent in 2010.

Another source of data on trends in the use of drugs among youths is the Youth Risk Behavior Survey (YRBS), sponsored by the Centers for Disease Control and Prevention (CDC). YRBS surveys students in the 9th through 12th grades in classrooms every other year during the spring (Eaton et al., 2010). The most recent survey was completed in 2009. Generally, the YRBS showed higher prevalence rates but similar long-term trends when compared with NSDUH and MTF. However, comparisons between the YRBS and NSDUH or MTF were less straightforward because of the different periodicity (i.e., biennially instead of annually) and ages covered, the limited number of drug use questions, and smaller sample size in the YRBS. For the substances for which information on current use was collected in the YRBS, including alcohol, cigarettes, marijuana, and cocaine, the YRBS trend results between 2001 and 2009 were consistent with NSDUH and MTF (see http://www.cdc.gov/HealthyYouth/yrbs/; Grunbaum et al., 2002). YRBS data for the combined grades 9 through 12 showed significant decreases in past month alcohol use (47.1 percent in 2001 and 41.8 percent in 2009) and cigarette use (28.5 percent in 2001 and 19.5 percent in 2009). YRBS showed a decline in past month marijuana use between 2001 (23.9 percent) and 2007 (19.7 percent), but the rate was 20.8 percent in 2009. This increase was consistent with the recent NSDUH and MTF increases since 2007, but the MTF and YRBS increases were not statistically significant.

Although changes in NSDUH survey methodology preclude direct comparisons of recent estimates with estimates from before 2002, it is important to put the recent trends in context by reviewing longer term trends in use. NSDUH data (prior to the design changes in 1999 and 2002) on youths aged 12 to 17 and MTF data on high school seniors showed substantial increases in youth illicit drug use during the 1970s, reaching a peak in the late 1970s. Both surveys then showed significant declines throughout the 1980s until about 1992, when rates reached a low point. These trends were driven by the trend in marijuana use. With the start of annual data collection in NSDUH in 1991, along with the biennial YRBS and the annual 8th and 10th grade samples in MTF, trends among youths are well documented since the low point that occurred in the early 1990s. Although they employ different survey designs and cover different age groups, the three surveys are consistent in showing increasing rates of marijuana use during the early to mid-1990s, reaching a peak in the late 1990s (but lower than in the late 1970s). This peak in the late 1990s was followed by declines in use after the turn of the 21st century and an increase in the most recent years (Figure 8.4).

Figure 8.4 Past Month Marijuana Use among Youths in NSDUH, MTF, and YRBS: 1971-2010

Figure 8.4     D

MTF = Monitoring the Future; NSDUH = National Survey on Drug Use and Health; YRBS = Youth Risk Behavior Survey. 
Note: NSDUH data for youths aged 12 to 17 are not presented for 1999 to 2001 because of design changes in the survey. These design changes preclude direct comparisons of estimates from 2002 to 2010 with estimates prior to 1999.

Young Adults

Data on young adults also showed similar trends in NSDUH and MTF, although not as consistent as for the youth data (Table 8.2). Potential reasons for differences from the data for youths are the relatively smaller MTF sample size for young adults and possible bias in the MTF sample due to noncoverage of school dropouts and a low overall response rate; the response rate is affected by nonresponse by schools, by students in the 12th grade survey, and by students in the follow-up mail survey.

Both surveys showed an increase in past month marijuana use among young adults from 2008 to 2010, although the change in MTF was not significant. Both surveys showed declines in cigarette use, but no significant change between 2002 and 2010 in the rate of current alcohol use among young adults. Both surveys showed declines in past year and past month cocaine use from 2003 to 2010. Both surveys showed a significant increase in past month Ecstasy use between 2007 and 2010.

Nonmedical Use of Prescription Pain Relievers

As noted in Chapter 2 of this report, nonmedical use of prescription drugs among youths and young adults in 2010 was the second most prevalent illicit drug use category, with marijuana being first. NSDUH data showed a decline in past month nonmedical prescription drug use among youths between 2002 (4.0 percent) and 2008 (2.9 percent), with no significant change between 2008 and 2010 (3.0 percent). Among young adults aged 18 to 25, past month prevalence of nonmedical prescription drug use was 5.9 percent in 2010, similar to the rates in other years since 2002, which varied between 5.5 percent in 2002 and 6.5 percent in 2006. The most prevalent category of misused prescription drugs is pain relievers. Nonmedical pain reliever use in the past month among youths declined from 3.2 percent in 2002 to 2.5 percent in 2010, while the rate among young adults was similar in 2002 (4.1 percent) and 2010 (4.5 percent).

NSDUH and MTF use different definitions and questioning strategies to track misuse of prescription drugs. For example, NSDUH defines misuse as use of prescription drugs that were not prescribed for the respondent or use of these drugs only for the experience or feeling they caused; MTF defines misuse as use not under a doctor's orders. MTF also does not estimate overall prescription drug misuse. However, MTF asks questions about "narcotics other than heroin," a category similar in coverage to the pain relievers category in NSDUH. These data are reported for 12th graders and for young adults. In addition, as is the case with NSDUH trends, methodological changes in MTF have sometimes resulted in discontinuities. For the data on use of narcotics other than heroin, there was a questionnaire change in the 2002 MTF that resulted in increased reporting of opiates, such that estimates prior to 2002 are not strictly comparable with estimates for 2002 and beyond.

Figure 8.5 shows NSDUH data for past year misuse of pain relievers from 1994 and to 1998 and 2002 to 2010 for youths and young adults (comparable estimates for prior years are not available). MTF data for 12th graders also are shown for past year misuse of narcotics other than heroin since 1994. From 1994 to 2001, the MTF rate of nonmedical use of narcotics other than heroin nearly doubled among high school seniors. NSDUH estimates for youths and young adults were more stable from 1994 to 1998.

Figure 8.5 Past Year Nonmedical Pain Reliever Use among Youths and Young Adults in NSDUH and MTF: 1994-2010

Figure 8.5     D

MTF = Monitoring the Future; NSDUH = National Survey on Drug Use and Health. 
Note: NSDUH data are not presented for 1999 to 2001 because of design changes in the survey. These design changes preclude direct comparisons of estimates from 2002 to 2010 with estimates prior to 1999. 
Note: Data for MTF are for "narcotics other than heroin." MTF estimates from 1994 to 2001 are not comparable with MTF estimates for 2002 and later due to questionnaire changes.

Both surveys showed relatively little change in the prevalence of past year misuse of pain relievers/narcotics other than heroin from 2002 to 2010 among these population groups, although some significant differences were observed in NSDUH. The prevalence in MTF among 12th graders ranged from 8.7 to 9.5 percent over this period, with a rate of 8.7 percent in 2010. Among youths in NSDUH, the prevalence ranged from 6.2 to 7.7 percent over this time period, with the rate in 2010 (6.2 percent) lower than rates in 2002, 2003, 2004, and 2006. Among young adults in NSDUH, the prevalence ranged from 11.1 to 12.4 percent over this time period, with the rate in 2010 (11.1 percent) lower than the rates in 2003 to 2009. MTF estimates for young adults aged 19 to 24 years ranged from 8.5 to 9.9 percent during this period, with no statistically significant changes (Table 8.2).

Although these data do not indicate an overall increase in nonmedical pain reliever use from 2002 to 2010, other trends indicate a growing problem. According to NSDUH, initiation rates for nonmedical pain reliever use continue to be second only to marijuana rates, with 2 million or more new nonmedical pain reliever users each year since 2002, including over 500,000 who initiate use without ever having used another illicit drug. The sustained numbers of new and continuing users have contributed to substantial increases in indicators of problems associated with use, especially among adults. The rate of pain reliever dependence for persons aged 12 or older increased from 2002 to 2010 (from 0.4 to 0.6 percent of the population), and the number of persons with dependence increased from 936,000 to 1.4 million. Most of these pain reliever-dependent persons were aged 26 or older (56.6 percent), but about one third (463,000) were aged 18 to 25. The number of people receiving specialty treatment in the past year in 2010 (2.6 million) was similar to the number in 2002 (2.3 million). However, the number of persons receiving specialty substance use treatment within the past year for misuse of pain relievers more than doubled during this period, from 199,000 to 406,000. In 2010, 65.7 percent were aged 26 or older, and 25.9 percent were aged 18 to 25. Other data sources confirm these trends, with admissions to publicly funded substance abuse treatment programs for a primary non-heroin opiate problem increasing from 45,816 in 2002 to 138,639 in 2009; in 2009, 72 percent of such admissions were aged 25 or older, and 27 percent were aged 18 to 24 (Center for Behavioral Health Statistics and Quality [CBHSQ], 2011b). The number of emergency department visits involving nonmedical use of narcotic pain relievers increased from 145,000 in 2004 to 306,000 in 2008 (CBHSQ, 2011a).

Summary

Despite the methodological differences between MTF and NSDUH, the two surveys generally showed similar trends for most substances among youths, including the increase in marijuana use from 2008 to 2010 and the decrease in alcohol use from 2002 to 2010. NSDUH showed a 10 percent increase in the past month rate of marijuana use from 2008 to 2010, while MTF showed a 27 percent increase. The prevalence of past month alcohol use declined by 23 percent from 2002 to 2010 in NSDUH and by 22 percent in MTF. For youth cigarette use, the two surveys showed similar declines in current use from 2002 to 2008, but trends differed in the following years. For 2008 to 2010, NSDUH indicated a continuing decline from 9.1 to 8.3 percent, but MTF data suggested a stall or reversal of the downward trend, with rates of 9.6 percent in 2008 and 10.4 percent in 2010 (not a statistically significant difference). This discrepancy in the recent trend in youth cigarette use requires further study to determine whether methodological differences in the surveys could affect the comparison. NSDUH and MTF data for young adults both indicated continuing declines in cigarette use from 2002 to 2010, including declines between 2008 and 2010.

Multiple datasets confirm the trends associated with the misuse of prescription pain relievers among youths and young adults. Although there was no evidence of overall increases from 2002 to 2010, nonmedical use of pain relievers continued to be prevalent among youths and young adults. Substantial increases in consequences associated with pain reliever misuse were observed, especially among adults.

Table 8.1 Comparison of NSDUH and MTF Prevalence Estimates among Youths: Percentages, 2002-2010
Substance/
Time Period
NSDUH
(2002)
NSDUH
(2003)
NSDUH
(2004)
NSDUH
(2005)
NSDUH
(2006)
NSDUH
(2007)
NSDUH
(2008)
NSDUH
(2009)
NSDUH
(2010)
MTF
(2002)
MTF
(2003)
MTF
(2004)
MTF
(2005)
MTF
(2006)
MTF
(2007)
MTF
(2008)
MTF
(2009)
MTF
(2010)
MTF = Monitoring the Future; NSDUH = National Survey on Drug Use and Health.
-- Not available.
NOTE: NSDUH data are for youths aged 12 to 17, and MTF data are simple averages of estimates for 8th and 10th graders. MTF data for 8th and 10th graders are reported in Johnston, O'Malley, Bachman, and Schulenberg (2011a). MTF design effects used for variance estimation are reported in Johnston, O'Malley, Bachman, and Schulenberg (2010).
a Difference between this estimate and 2010 estimate is statistically significant at the .05 level.
Sources: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2002-2010. National Institute on Drug Abuse, Monitoring the Future Study, University of Michigan, 2002-2010.
Marijuana                                    
Lifetime 20.6a 19.6a 19.0a 17.4 17.3 16.2 16.5 17.0 17.0 29.0a 27.0 25.7 25.3 23.8 22.6a 22.3a 24.0 25.4
Past Year 15.8a 15.0a 14.5 13.3 13.2 12.5a 13.0a 13.6 14.0 22.5a 20.5 19.7 19.4 18.5a 17.5a 17.4a 19.3a 20.6
Past Month 8.2a 7.9 7.6 6.8 6.7a 6.7a 6.7a 7.3 7.4 13.1 12.3 11.2a 10.9a 10.4a 10.0a 9.8a 11.2a 12.4
Cocaine                                    
Lifetime 2.7a 2.6a 2.4a 2.3a 2.2a 2.1a 1.9a 1.6 1.5 4.9a 4.4a 4.4a 4.5a 4.1a 4.2a 3.8 3.6 3.2
Past Year 2.1a 1.8a 1.6a 1.7a 1.6a 1.5a 1.2 1.0 1.0 3.2a 2.8a 2.9a 2.9a 2.6a 2.7a 2.4 2.2 1.9
Past Month 0.6a 0.6a 0.5a 0.6a 0.4a 0.4a 0.4a 0.3 0.2 1.4a 1.1a 1.3a 1.3a 1.3a 1.1a 1.0 0.9 0.8
Ecstasy                                    
Lifetime 3.3a 2.4 2.1a 1.6a 1.9a 1.8a 2.1a 2.3 2.5 5.5 4.3 3.6a 3.4a 3.5a 3.8a 3.4a 3.9a 4.9
Past Year 2.2 1.3a 1.2a 1.0a 1.2a 1.3a 1.4a 1.7 1.9 3.9 2.6a 2.1a 2.2a 2.1a 2.5a 2.3a 2.5a 3.6
Past Month 0.5 0.4 0.3a 0.3a 0.3a 0.3a 0.4 0.5 0.5 1.6 0.9a 0.8a 0.8a 1.0a 0.9a 1.0a 1.0a 1.5
LSD                                    
Lifetime 2.7a 1.6a 1.2a 1.1 0.9 0.8 1.1 1.0 0.9 3.8a 2.8 2.3 2.2 2.2 2.3 2.3 2.4 2.4
Past Year 1.3a 0.6 0.6 0.6 0.4 0.5 0.7 0.6 0.6 2.1a 1.5 1.4 1.4 1.3 1.5 1.6 1.5 1.6
Past Month 0.2 0.2 0.2 0.1 0.1 0.1 0.2 0.1 0.2 0.7 0.6 0.6 0.6 0.6 0.6 0.6 0.5 0.7
Inhalants                                    
Lifetime 10.5a 10.7a 11.0a 10.5a 10.1a 9.6a 9.3a 9.2a 8.2 14.4 14.3 14.9a 15.1a 14.7a 14.6a 14.3 13.6 13.3
Past Year 4.4a 4.5a 4.6a 4.5a 4.4a 3.9 3.9 3.9 3.6 6.8 7.1 7.8a 7.8a 7.8a 7.5 7.4 7.1 6.9
Past Month 1.2 1.3 1.2 1.2 1.3 1.2 1.1 1.0 1.1 3.1 3.2 3.5a 3.2 3.2 3.2 3.1 3.0 2.8
Alcohol                                    
Lifetime 43.4a 42.9a 42.0a 40.6a 40.4a 39.4a 38.3a 38.1a 35.2 57.0a 55.8a 54.1a 52.1a 51.0a 50.3a 48.6 47.9 47.0
Past Year 34.6a 34.3a 33.9a 33.3a 32.9a 31.8a 30.8a 30.3a 28.5 49.4a 48.3a 47.5a 45.3a 44.7a 44.1a 42.3 41.6 40.7
Past Month 17.6a 17.7a 17.6a 16.5a 16.6a 15.9a 14.6a 14.7a 13.6 27.5a 27.6a 26.9a 25.2a 25.5a 24.7a 22.4 22.7a 21.4
Cigarettes                                    
Lifetime 33.3a 31.0a 29.2a 26.7a 25.8a 23.7a 22.9a 22.2a 20.3 39.4a 35.7a 34.3a 32.4a 30.4a 28.4a 26.1 26.4 26.5
Past Year 20.3a 19.0a 18.4a 17.3a 17.0a 15.7a 15.0 15.0 14.1 -- -- -- -- -- -- -- -- --
Past Month 13.0a 12.2a 11.9a 10.8a 10.4a 9.8a 9.1a 8.9 8.3 14.2a 13.5a 12.6a 12.1a 11.6a 10.6 9.6 9.8 10.4

Table 8.2 Comparison of NSDUH and MTF Prevalence Estimates among Young Adults: Percentages, 2002-2010
Substance/
Time Period
NSDUH
(2002)
NSDUH
(2003)
NSDUH
(2004)
NSDUH
(2005)
NSDUH
(2006)
NSDUH
(2007)
NSDUH
(2008)
NSDUH
(2009)
NSDUH
(2010)
MTF
(2002)
MTF
(2003)
MTF
(2004)
MTF
(2005)
MTF
(2006)
MTF
(2007)
MTF
(2008)
MTF
(2009)
MTF
(2010)
MTF = Monitoring the Future; NSDUH = National Survey on Drug Use and Health.
-- Not available.
NOTE: NSDUH data are for persons aged 18 to 25. MTF data were calculated for persons aged 19 to 24 using simple averages of modal age groups 19-20, 21-22, and 23-24 (source data at http://www.monitoringthefuture.org/pubs.html). For the 19 to 24 age group in the MTF data, significance tests were performed assuming independent samples between years an odd number of years apart because two distinct cohorts a year apart were monitored longitudinally at 2-year intervals. Although appropriate for comparisons of 2003, 2005, 2007, and 2009 estimates with 2010 estimates, this assumption results in conservative tests for comparisons of 2002, 2004, 2006, and 2008 data with 2010 estimates because it does not take into account covariances that are associated with repeated observations from the longitudinal samples. Estimates of covariances were not available.
a Difference between this estimate and 2010 estimate is statistically significant at the .05 level.
1 MTF data are for "narcotics other than heroin." In 2002, MTF question text was changed in half of the sample by updating the example list of narcotics other than heroin. To be consistent with MTF data for 2003 and later years, MTF data for 2002 past year use of narcotics other than heroin are based on the half sample that received the new question text.
Sources: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2002-2010. National Institute on Drug Abuse, Monitoring the Future Study, University of Michigan, 2002-2010.
Marijuana                                    
Lifetime 53.8a 53.9a 52.8a 52.4 52.4 50.8 50.4 52.2 51.1 56.1a 56.4a 55.6 54.4 53.8 53.9 53.0 53.8 53.2
Past Year 29.8 28.5a 27.8a 28.0a 28.0a 27.5a 27.6a 30.6 29.8 34.2a 33.0 31.6 31.4 30.9 31.0 30.9 32.1 31.7
Past Month 17.3a 17.0a 16.1a 16.6a 16.3a 16.4a 16.5a 18.1 18.5 19.8a 19.9a 18.2 17.0 17.0 17.5 17.3 18.5 17.8
Cocaine                                    
Lifetime 15.4a 15.0a 15.2a 15.1a 15.7a 15.0a 14.4a 14.8a 13.3 12.9a 14.5a 14.3a 12.6a 13.6a 12.4 12.2 12.2 11.0
Past Year 6.7a 6.6a 6.6a 6.9a 6.9a 6.4a 5.5a 5.3a 4.6 6.5a 7.3a 7.8a 6.9a 7.0a 6.3a 6.0a 5.7 4.7
Past Month 2.0a 2.2a 2.1a 2.6a 2.2a 1.7 1.5 1.4 1.5 2.5a 2.6a 2.4a 2.1a 2.4a 1.9 1.9 1.8 1.4
Ecstasy                                    
Lifetime 15.1a 14.8a 13.8a 13.7a 13.4a 12.8 12.1 12.4 12.4 16.0a 16.6a 14.9a 12.4 11.5 9.5 10.1 9.4 10.3
Past Year 5.8a 3.7a 3.1a 3.1a 3.8a 3.5a 3.9 4.3 4.4 8.0a 5.3 3.3a 3.4 3.6 2.8a 3.8 3.6 4.7
Past Month 1.1 0.7a 0.7a 0.8a 1.0 0.7a 0.9 1.1 1.2 1.6 1.0 0.8 0.6 0.9 0.3a 0.9 0.7 1.2
LSD                                    
Lifetime 15.9a 14.0a 12.1a 10.5a 8.9a 7.3a 6.5 6.8 6.4 13.9a 13.8a 10.4a 7.9a 6.7 5.9 5.6 5.3 5.7
Past Year 1.8 1.1a 1.0a 1.0a 1.2a 1.1a 1.5 1.5 1.6 2.4 1.5 1.2a 1.1a 1.5 1.4 1.9 2.1 1.9
Past Month 0.1a 0.2 0.3 0.2 0.2a 0.2 0.3 0.3 0.3 0.4 0.2a 0.2a 0.2a 0.3 0.3 0.5 0.3 0.5
Inhalants                                    
Lifetime 15.7a 14.9a 14.0a 13.3a 12.5a 11.3a 10.4 10.7a 9.9 11.7a 11.4a 10.6a 9.3a 9.7a 7.5 8.4 7.7 6.9
Past Year 2.2a 2.1a 2.1a 2.1a 1.8 1.6 1.6 1.9 1.7 2.2 1.5 2.3 1.6 1.8 1.1 1.7 1.2 1.7
Past Month 0.5 0.4 0.4 0.5 0.4 0.4 0.3 0.4 0.4 0.8a 0.3 0.4 0.3 0.4 0.3 0.6 0.2 0.3
Alcohol                                    
Lifetime 86.7a 87.1a 86.2 85.7 86.5 85.2 85.6 85.8 85.7 88.4a 87.6a 87.2a 87.1a 87.0a 86.0 86.4 85.7 84.8
Past Year 77.9 78.1 78.0 77.9 78.8 77.9 78.0 78.8 78.7 83.9a 82.3 83.1a 82.8a 83.2a 82.8a 82.5a 82.0 80.5
Past Month 60.5 61.4 60.5 60.9 61.9 61.2 61.2 61.8 61.5 67.7 66.3 67.3 66.8 67.0 67.4 67.4 68.1 65.8
Cigarettes                                    
Lifetime 71.2a 70.2a 68.7a 67.3a 66.6a 64.7a 64.2a 63.7a 62.1 -- -- -- -- -- -- -- -- --
Past Year 49.0a 47.6a 47.5a 47.2a 47.0a 45.1a 45.0a 45.2a 43.1 41.8a 40.8a 41.4a 40.2a 37.1a 36.2a 35.4a 35.0 33.0
Past Month 40.8a 40.2a 39.5a 39.0a 38.4a 36.2a 35.7a 35.8a 34.2 31.4a 29.5a 30.2a 28.7a 26.7a 25.7a 24.3a 23.5 21.8
Pain Relievers1                                    
Lifetime 22.1b 23.7 24.3 25.5b 25.5b 24.8 24.4 24.3 23.8 -- 17.3 17.7 16.9 17.9 17.8 17.8 17.2 16.6
Past Year 11.4 12.0a 11.9a 12.4b 12.4b 12.1b 12.0a 11.9a 11.1 8.5 9.7 9.7 9.2 9.9 9.0 9.2 8.5 9.1
Past Month 4.1 4.7 4.7 4.7 4.9 4.6 4.6 4.8 4.5 -- 3.4 3.4 3.7 3.6 3.5 3.7 3.2 3.4

Appendix A: Description of the Survey

A.1 Sample Design

The sample design for the 2010 National Survey on Drug Use and Health (NSDUH)2 is an extension of a coordinated 5-year design providing estimates for all 50 States plus the District of Columbia initially for the years 2005 through 2009, then continuing through 2011. The respondent universe is the civilian, noninstitutionalized population aged 12 years old or older residing within the United States. The survey covers residents of households (persons living in houses/townhouses, apartments, condominiums; civilians living in housing on military bases, etc.) and persons in noninstitutional group quarters (e.g., shelters, rooming/boarding houses, college dormitories, migratory workers' camps, halfway houses). Excluded from the survey are persons with no fixed household address (e.g., homeless and/or transient persons not in shelters), active-duty military personnel, and residents of institutional group quarters, such as correctional facilities, nursing homes, mental institutions, and long-term hospitals.

The coordinated design for 2005 through 2009 facilitated a 50 percent overlap in second-stage units (area segments) within each successive 2-year period from 2005 through 2009. The 2010 NSDUH continued the 50 percent overlap by retaining half of the second-stage units from the 2009 survey. The remainder of the sample was drawn from the 2005 through 2009 reserve sample. This reserve sample consisted of area segments not used in previous years but reserved for any supplemental samples or field tests that may be implemented. Because the coordinated design enables estimates to be developed by State in all 50 States plus the District of Columbia, States may be viewed as the first level of stratification and as a reporting variable.

For the 50-State design, 8 States were designated as large sample States (California, Florida, Illinois, Michigan, New York, Ohio, Pennsylvania, and Texas) with target sample sizes of 3,600. In 2010, sample sizes in these States ranged from 3,590 to 3,731. For the remaining 42 States and the District of Columbia, the target sample size was 900. Sample sizes in these States ranged from 868 to 974 in 2010. This approach ensures there is sufficient sample in every State to support State estimation by either direct methods or small area estimation (SAE)3 while at the same time maintaining efficiency for national estimates.

States were first stratified into a total of 900 State sampling regions (SSRs) (48 regions in each large sample State and 12 regions in each small sample State). These regions were contiguous geographic areas designed to yield approximately the same number of interviews.4 Unlike the 1999 through 2001 NHSDAs and the 2002 through 2004 NSDUHs in which the first-stage sampling units were clusters of census blocks called area segments, the first stage of selection for the 2005 through 2011 NSDUHs was census tracts.5 This stage was included to contain sample segments within a single census tract to the extent possible.6

Within each SSR, 48 census tracts were selected with probability proportional to population size. Within sampled census tracts, adjacent census blocks were combined to form the second-stage sampling units or area segments. One area segment was selected within each sampled census tract with probability proportional to population size. Although only 24 segments were needed to support the coordinated 5-year sample, an additional 24 segments were selected to support any supplemental studies that the Substance Abuse and Mental Health Services Administration (SAMHSA) may choose to field. These 24 segments constitute the reserve sample and were available for use in 2010. Eight sample segments per SSR were fielded during the 2010 survey year. Four of these segments were retained from the 2009 survey, and four were selected from the reserve sample. An additional four reserve segments per SSR will be selected for use in the 2011 survey.

These sampled segments were allocated equally into four separate samples, one for each 3-month period (calendar quarter) during the year. That is, a sample of addresses was selected from two segments in each calendar quarter so that the survey was relatively continuous in the field. In each of the area segments, a listing of all addresses was made from which a national sample of 201,865 addresses was selected. Of the selected addresses, 166,435 were determined to be eligible sample units. In these sample units (which can be either households or units within group quarters), sample persons were randomly selected using an automated screening procedure programmed in a handheld computer carried by the interviewers. The number of sample units completing the screening was 147,608. Youths aged 12 to 17 years and young adults aged 18 to 25 years were oversampled at this stage, with 12 to 17 year olds sampled at an actual rate of 86.6 percent and 18 to 25 year olds at a rate of 71.3 percent on average, when they were present in the sampled households or group quarters. Similarly, persons in age groups 26 or older were sampled at rates of 31.4 percent or less, with persons in the eldest age group (50 years or older) sampled at a rate of 7.9 percent on average. The overall population sampling rates were 0.09 percent for 12 to 17 year olds, 0.07 percent for 18 to 25 year olds, 0.02 percent for 26 to 34 year olds, 0.02 percent for 35 to 49 year olds, and 0.01 percent for those 50 or older. Nationwide, 85,668 persons were selected. Consistent with previous surveys in this series, the final respondent sample of 68,487 persons was representative of the U.S. general population (since 1991, the civilian, noninstitutionalized population) aged 12 or older. In addition, State samples were representative of their respective State populations. More detailed information on the disposition of the national screening and interview sample can be found in Appendix B.

More information on the sample design can be found in the 2010 NSDUH sample design report by Morton, Martin, Chromy, Hirsch, and Ridenhour (2011).

A.2 Data Collection Methodology

The data collection method used in NSDUH involves in-person interviews with sample persons, incorporating procedures that would be likely to increase respondents' cooperation and willingness to report honestly about their illicit drug use behavior. Confidentiality is stressed in all written and oral communications with potential respondents. Respondents' names are not collected with the data, and computer-assisted interviewing (CAI) methods are used to provide a private and confidential setting to complete the interview.

Introductory letters are sent to sampled addresses, followed by an interviewer visit. When contacting a dwelling unit (DU), the field interviewer (FI) asks to speak with an adult resident (aged 18 or older) of the household who can serve as the screening respondent. Using a handheld computer, the FI completes a 5-minute procedure with the screening respondent that involves listing all household members along with their basic demographic data. The computer uses the demographic data in a preprogrammed selection algorithm to select zero to two sample persons, depending on the composition of the household. This selection process is designed to provide the necessary sample sizes for the specified population age groupings. In areas where a third or more of the households contain Spanish-speaking residents, the initial introductory letters written in English are mailed with a Spanish version on the back. All interviewers carry copies of this letter in Spanish. If the interviewer is not certified bilingual, he or she will use preprinted Spanish cards to attempt to find someone in the household who speaks English and who can serve as the screening respondent or who can translate for the screening respondent. If no one is available, the interviewer will schedule a time when a Spanish-speaking interviewer can come to the address. In households where a language other than Spanish is encountered, another language card is used to attempt to find someone who speaks English to complete the screening.

The NSDUH interview is available in English and Spanish, and both versions have the same content. If the sample person prefers to complete the interview in Spanish, a certified bilingual interviewer is sent to the address to conduct the interview. Because the interview is not translated into any other language, if a sample person does not speak English or Spanish, the interview is not conducted.

Interviewers attempt to conduct the NSDUH interview immediately with each sample person in the household. The interviewer requests the selected respondent to identify a private area in the home to conduct the interview away from other household members. The interview averages about an hour and includes a combination of CAPI (computer-assisted personal interviewing, in which the interviewer reads the questions) and ACASI (audio computer-assisted self-interviewing).

The NSDUH interview consists of core and noncore (i.e., supplemental) sections. A core set of questions critical for basic trend measurement of prevalence estimates remains in the survey every year and comprises the first part of the interview. Noncore questions, or modules, that can be revised, dropped, or added from year to year make up the remainder of the interview. The core consists of initial demographic items (which are interviewer-administered) and self-administered questions pertaining to the use of tobacco, alcohol, marijuana, cocaine, crack cocaine, heroin, hallucinogens, inhalants, pain relievers, tranquilizers, stimulants, and sedatives. Topics in the remaining noncore self-administered sections include (but are not limited to) injection drug use, perceived risks of substance use, substance dependence or abuse, arrests, treatment for substance use problems, pregnancy and health care issues, and mental health issues. Noncore demographic questions (which are interviewer-administered and follow the ACASI questions) address such topics as immigration, current school enrollment, employment and workplace issues, health insurance coverage, and income. It should be noted that some of the noncore portions of the interview have remained in the survey, relatively unchanged, from year to year (e.g., current health insurance coverage, employment).

Thus, the interview begins in CAPI mode with the FI reading the questions from the computer screen and entering the respondent's replies into the computer. The interview then transitions to the ACASI mode for the sensitive questions. In this mode, the respondent can read the questions silently on the computer screen and/or listen to the questions read through headphones and enter his or her responses directly into the computer. At the conclusion of the ACASI section, the interview returns to the CAPI mode with the FI completing the questionnaire. Each respondent who completes a full interview is given a $30 cash payment as a token of appreciation for his or her time.

No personal identifying information is captured in the CAI record for the respondent. FIs transmit the completed interview data to RTI in Research Triangle Park, North Carolina, via home telephone analog lines.

After the data are transmitted to RTI, cases are selected for verification. The verification process involves contacting respondents to verify the quality of an FI's work based on information that respondents provide at the end of screening (if no one is selected for an interview at the DU or the entire DU is ineligible for the study) or at the end of the interview. For screening, the adult DU member who served as the screening respondent provides his or her first name and telephone number to the FI, who enters the information into a handheld computer and transmits the data to RTI. For completed interviews, respondents write their home telephone number and mailing address on a quality control form and seal the form in a preaddressed envelope that FIs mail back to RTI. All contact information is kept completely separate from the answers provided during the screening or interview.

Samples of respondents who completed screenings or interviews are randomly selected for verification. These cases are called by telephone interviewers who ask scripted questions designed to determine the accuracy and quality of the data collected. Any cases discovered to have a problem or discrepancy are flagged and routed to a small specialized team of telephone interviewers who recontact respondents for further investigation of the issue(s). Depending on the amount of an FI's work that cannot be verified through telephone verification, including bad telephone numbers (e.g., incorrect number, disconnected, not in service), a field verification may be conducted. Field verifications involve another FI returning to the sampled DU to verify the accuracy and quality of the data in person. If the verification procedures identify situations in which an FI has falsified data, the FI is terminated. All cases completed that quarter by the FI who falsified data are reworked by the FI conducting the field verification.

A.3 Data Processing

Computers at RTI direct the information to a raw data file (i.e., in which no logical editing of the data had been done) that consists of one record for each completed interview. Cases are retained only if respondents provided data on lifetime use of cigarettes and at least nine other substances in the core section of the questionnaire. Written responses to questions (e.g., names of other drugs that were used) are assigned numeric codes as part of the data processing procedures. Even though editing and consistency checks are done by the CAI program during the interview, additional, more complex edits and consistency checks are completed at RTI. Additionally, statistical imputation is used to replace missing or ambiguous values after editing for some key variables. Analysis weights are created so that estimates will be representative of the target population. Details of the editing, imputation, and weighting procedures for 2010 will appear in the 2010 NSDUH Methodological Resource Book, which is in process. Until that volume becomes available, refer to the 2009 NSDUH Methodological Resource Book (RTI International, 2011).

A.3.1 Data Coding and Logical Editing

With the exception of industry and occupation data, coding of written answers that respondents or interviewers typed was performed at RTI for the 2010 NSDUH. These written answers include mentions of drugs that respondents had used or other responses that did not fit a previous response option (subsequently referred to as "OTHER, Specify" data). Coding of the "OTHER, Specify" variables was accomplished through computer-assisted survey procedures and the use of a secure Web site that allowed for coding and review of the data. The computer-assisted procedures entailed a database check for a given "OTHER, Specify" variable that contained typed entries and the associated numeric codes. If an exact match was found between the typed response and an entry in the system, the computer-assisted procedures assigned the appropriate numeric code. Typed responses that did not match an existing entry were coded through the Web-based coding system. Data on the industries in which respondents worked and respondents' occupations were assigned numeric industry and occupation codes by staff at the U.S. Census Bureau.

As noted above, the CAI program included checks that alerted respondents or interviewers when an entered answer was inconsistent with a previous answer in a given module. In this way, the inconsistency could be resolved while the interview was in progress. However, not every inconsistency was resolved during the interview, and the CAI program did not include checks for every possible inconsistency that might have occurred in the data.

Therefore, the first step in processing the raw NSDUH data was logical editing of the data. Logical editing involved using data from within a respondent's record to (a) reduce the amount of item nonresponse (i.e., missing data) in interview records, including identification of items that were legitimately skipped; (b) make related data elements consistent with each other; and (c) identify ambiguities or inconsistencies to be resolved through statistical imputation procedures (see Section A.3.2).

For example, if respondents reported that they never used a given drug, the CAI logic skipped them out of all remaining questions about use of that drug. In the editing procedures, the skipped variables were assigned codes to indicate that the respondents were lifetime nonusers. Similarly, respondents were instructed in the prescription psychotherapeutics modules (i.e., pain relievers, tranquilizers, stimulants, and sedatives) not to report the use of over-the-counter (OTC) drugs. Therefore, if a respondent's only report of lifetime use of a particular type of "prescription" psychotherapeutic drug was for an OTC drug, the respondent was logically inferred never to have been a nonmedical user of the prescription drugs in that psychotherapeutic category.

In addition, respondents could report that they were lifetime users of a drug but not provide specific information on when they last used it. In this situation, a temporary "indefinite" value for the most recent period of use was assigned to the edited recency-of-use variable (e.g., Used at some point in the lifetime LOGICALLY ASSIGNED), and a final, specific value was statistically imputed. The editing procedures for key drug use variables also involved identifying inconsistencies between related variables so that these inconsistencies could be resolved through statistical imputation. For example, if a respondent reported last using a drug more than 12 months ago and also reported first using it at his or her current age, both of those responses could not be true. In this example, the inconsistent period of most recent use was replaced with an "indefinite" value, and the inconsistent age at first use was replaced with a missing data code. These indefinite or missing values were subsequently imputed through statistical procedures to yield consistent data for the related measures, as discussed in the next section.

A.3.2 Statistical Imputation

For some key variables that still had missing or ambiguous values after editing, statistical imputation was used to replace these values with appropriate response codes. For example, a response is ambiguous if the editing procedures assigned a respondent's most recent use of a drug to "use at some point in the lifetime," with no definite period within the lifetime. In this case, the imputation procedure assigns a value for when the respondent last used the drug (e.g., in the past 30 days, more than 30 days ago but within the past 12 months, more than 12 months ago). Similarly, if a response is completely missing, the imputation procedures replace missing values with nonmissing ones.

For most variables, missing or ambiguous values are imputed in NSDUH using a methodology called predictive mean neighborhoods (PMN), which was developed specifically for the 1999 survey and used in all subsequent survey years. The PMN method offers a rigorous and flexible method that was implemented to improve the quality of estimates and allow more variables to be imputed. Some additional key reasons for implementing this method include the following: (1) the ability to use covariates to determine donors is greater than that offered in the hot-deck imputation procedure, (2) the relative importance of covariates can be determined by standard modeling techniques, (3) the correlations across response variables can be accounted for by making the imputation multivariate, and (4) sampling weights can be easily incorporated in the models. The PMN method has some similarity with the predictive mean matching method of Rubin (1986) except that, for the donor records, Rubin used the observed variable value (not the predictive mean) to compute the distance function. Also, the well-known method of nearest neighbor imputation is similar to PMN, except that the distance function is in terms of the original predictor variables and often requires somewhat arbitrary scaling of discrete variables. PMN is a combination of a model-assisted imputation methodology and a random nearest neighbor hot-deck procedure. The hot-deck procedure within the PMN method ensures that missing values are imputed to be consistent with nonmissing values for other variables. Whenever feasible, the imputation of variables using PMN is multivariate, in which imputation is accomplished on several response variables at once. Variables requiring imputation using PMN are the core demographic variables, core drug use variables (recency of use, frequency of use, and age at first use), income, health insurance, and noncore demographic variables for work status, immigrant status, and the household roster.

In the modeling stage of PMN, the model chosen depends on the nature of the response variable Y. In the 2010 NSDUH, the models included binomial logistic regression, multinomial logistic regression, Poisson regression, and ordinary linear regression, where the models incorporated the sampling design weights.

In general, hot-deck imputation replaces an item nonresponse (missing or ambiguous value) with a recorded response that is donated from a "similar" respondent who has nonmissing data. For random nearest neighbor hot-deck imputation, the missing or ambiguous value is replaced by a responding value from a donor randomly selected from a set of potential donors. Potential donors are those defined to be "close" to the unit with the missing or ambiguous value according to a predefined function called a distance metric. In the hot-deck procedure of PMN, the set of candidate donors (the "neighborhood") consists of respondents with complete data who have a predicted mean close to that of the item nonrespondent. The predicted means are computed both for respondents with and without missing data, which differs from Rubin's method where predicted means are not computed for the donor respondent (Rubin, 1986). In particular, the neighborhood consists of either the set of the closest 30 respondents or the set of respondents with a predicted mean (or means) within 5 percent of the predicted mean(s) of the item nonrespondent, whichever set is smaller. If no respondents are available who have a predicted mean (or means) within 5 percent of the item nonrespondent, the respondent with the predicted mean(s) closest to that of the item nonrespondent is selected as the donor.

In the univariate case (where only one variable is imputed using PMN), the neighborhood of potential donors is determined by calculating the relative distance between the predicted mean for an item nonrespondent and the predicted mean for each potential donor, then choosing those means defined by the distance metric. The pool of donors is restricted further to satisfy logical constraints whenever necessary (e.g., age at first crack use must not be less than age at first cocaine use).

Whenever possible, missing or ambiguous values for more than one response variable are considered together. In this (multivariate) case, the distance metric is a Mahalanobis distance, which takes into account the correlation between variables (Manly, 1986), rather than a Euclidean distance. The Euclidean distance is the square root of the sum of squared differences between each element of the predictive mean vector for the respondent and the predictive mean vector for the nonrespondent. The Mahalanobis distance standardizes the Euclidean distance by the variance-covariance matrix, which is appropriate for random variables that are correlated or have heterogeneous variances. Whether the imputation is univariate or multivariate, only missing or ambiguous values are replaced, and donors are restricted to be logically consistent with the response variables that are not missing. Furthermore, donors are restricted to satisfy "likeness constraints" whenever possible. That is, donors are required to have the same values for variables highly correlated with the response. For example, donors for the age at first use variable are required to be of the same age as recipients, if at all possible. If no donors are available who meet these conditions, these likeness constraints can be loosened. Further details on the PMN methodology are provided by Singh, Grau, and Folsom (2002).

Although statistical imputation could not proceed separately within each State due to insufficient pools of donors, information about each respondent's State of residence was incorporated in the modeling and hot-deck steps. For most drugs, respondents were separated into three "State usage" categories as follows: respondents from States with high usage of a given drug were placed in one category, respondents from States with medium usage into another, and the remainder into a third category. This categorical "State rank" variable was used as one set of covariates in the imputation models. In addition, eligible donors for each item nonrespondent were restricted to be of the same State usage category (i.e., the same "State rank") as the nonrespondent.

In the 2010 NSDUH, the majority of variables that underwent statistical imputation required less than 5 percent of their records to be logically assigned or statistically imputed. Variables for measures that are highly sensitive or that may not be known to younger respondents (e.g., family income) often have higher rates of item nonresponse. In addition, certain variables that are subject to a greater number of skip patterns and consistency checks (e.g., frequency of use in the past 12 months and past 30 days) often require greater amounts of imputation.

A.3.3 Development of Analysis Weights

The general approach to developing and calibrating analysis weights involved developing design-based weights as the product of the inverse of the selection probabilities at each selection stage. Similar to the 2008 and 2009 NSDUHs, the 2010 NSDUH used a four-stage sample selection scheme in which an extra selection stage of census tracts was added before the selection of a segment. Thus, the design-based weights, d sub k, for the 2010 NSDUH incorporated an extra layer of sampling selection to reflect the sample design change. Adjustment factors, a sub k as a function of lambda, then were applied to the design-based weights to adjust for nonresponse, to poststratify to known population control totals, and to control for extreme weights when necessary. In view of the importance of State-level estimates with the 50-State design, it was necessary to control for a much larger number of known population totals. Several other modifications to the general weight adjustment strategy that had been used in past surveys also were implemented for the first time beginning with the 1999 CAI sample.

Weight adjustments were based on a generalization of Deville and Särndal's (1992) logit model. This generalized exponential model (GEM) (Folsom & Singh, 2000) incorporates unit-specific bounds where the lower and upper bounds are l sub k and u sub k, respectively, and k is an element of s for the adjustment factor a sub k as a function of lambda as follows:

Equation A.1     D

where c sub k are prespecified centering constants, such that c sub k is bounded below by l sub k and bounded above by u sub k and Capital A sub k is defined as the ratio of two quantities. The quantity in the numerator is calculated as the difference between u sub k and l sub k. The quantity in the denominator is calculated as the product of the difference between u sub k and c sub k and the difference between c sub k and l sub k.. The variables l sub k, c sub k, and u sub k are user-specified bounds, and lambda is the column vector of p model parameters corresponding to the p covariates x. The lambda-parameters are estimated by solving

Equation A.2     D

where capital T tilde sub x denotes control totals that could be either nonrandom, as is generally the case with poststratification, or random, as is generally the case for nonresponse adjustment.

The final weights The w sub k equals the product of d sub k and a sub k as a function of lambda. minimize the distance function delta of the parameters w and d defined as

Equation A.3     D

This general approach was used at several stages of the weight adjustment process, including (1) adjustment of household weights for nonresponse at the screener level, (2) poststratification of household weights to meet population controls for various household-level demographics by State, (3) adjustment of household weights for extremes, (4) poststratification of selected person weights, (5) adjustment of responding person weights for nonresponse at the questionnaire level, (6) poststratification of responding person weights, and (7) adjustment of responding person weights for extremes.

Every effort was made to include as many relevant State-specific covariates (typically defined by demographic domains within States) as possible in the multivariate models used to calibrate the weights (nonresponse adjustment and poststratification steps). Because further subdivision of State samples by demographic covariates often produced small cell sample sizes, it was not possible to retain all State-specific covariates (even after meaningful collapsing of covariate categories) and still estimate the necessary model parameters with reasonable precision. Therefore, a hierarchical structure was used in grouping States with covariates defined at the national level, at the census division level within the Nation, at the State group within the census division, and, whenever possible, at the State level. In every case, the controls for the total population within a State and the five age groups (12 to 17, 18 to 25, 26 to 34, 35 to 49, 50 or older) within a State were maintained except that, in the last step of poststratification of person weights, six age groups (12 to 17, 18 to 25, 26 to 34, 35 to 49, 50 to 64, 65 or older) were used. Census control totals by age, race, gender, and Hispanic origin were required for the civilian, noninstitutionalized population of each State. Beginning with the 2002 NSDUH, the Population Estimates Branch of the U.S. Census Bureau has produced the necessary population estimates for the same year as each NSDUH survey in response to a special request.

Consistent with the surveys from 1999 onward, control of extreme weights through separate bounds for adjustment factors was incorporated into the GEM calibration processes for both nonresponse and poststratification. This is unlike the traditional method of winsorization in which extreme weights are truncated at prespecified levels and the trimmed portions of weights are distributed to the nontruncated cases. In GEM, it is possible to set bounds around the prespecified levels for extreme weights, then the calibration process provides an objective way of deciding the extent of adjustment (or truncation) within the specified bounds. A step was added to poststratify the household-level weights to obtain census-consistent estimates based on the household rosters from all screened households; these household roster-based estimates then provided the control totals needed to calibrate the respondent pair weights for subsequent planned analyses. An additional step poststratified the selected person sample to conform to the adjusted roster estimates. This additional step takes advantage of the inherent two-phase nature of the NSDUH design. The final step poststratified the respondent person sample to external census data (defined within the State whenever possible, as discussed above).

For certain populations of interest, 2 years of NSDUH data were combined to obtain annual averages. The person-level weights for estimates based on the annual averages were obtained by dividing the analysis weights for the 2 specific years by a factor of 2.

Appendix B: Statistical Methods and Measurement

B.1 Target Population

The estimates of drug use prevalence from the National Survey on Drug Use and Health (NSDUH) are designed to describe the target population of the survey—the civilian, noninstitutionalized population aged 12 or older living in the United States. This population includes almost 98 percent of the total U.S. population aged 12 or older. However, it excludes some small subpopulations that may have very different drug use patterns. For example, the survey excludes active military personnel, who have been shown to have significantly lower rates of illicit drug use. The survey also excludes two groups that have been shown to have higher rates of illicit drug use: persons living in institutional group quarters, such as prisons and residential drug use treatment centers, and homeless persons not living in a shelter. Readers are reminded to consider the exclusion of these subpopulations when interpreting results. Appendix C describes other surveys that provide data for some of these populations.

B.2 Sampling Error and Statistical Significance

This report includes national estimates that were drawn from a set of tables referred to as "detailed tables."7 The national estimates, along with the associated standard errors (SEs, which are the square roots of the variances), were computed for all detailed tables using a multiprocedure package, SUDAAN® Software for Statistical Analysis of Correlated Data. This software accounts for the complex survey design of NSDUH in estimating the SEs (RTI International, 2008). The final, nonresponse-adjusted, and poststratified analysis weights were used in SUDAAN to compute unbiased design-based drug use estimates.

The sampling error (i.e., the SE) of an estimate is the error caused by the selection of a sample instead of conducting a census of the population. The sampling error may be reduced by selecting a large sample and/or by using efficient sample design and estimation strategies, such as stratification, optimal allocation, and ratio estimation. The use of probability sampling methods in NSDUH allows estimation of sampling error from the survey data. SEs have been calculated using SUDAAN for all estimates presented in this report using a Taylor series linearization approach that takes into account the effects of NSDUH's complex design features. The SEs are used to identify unreliable estimates and to test for the statistical significance of differences between estimates.

B.2.1 Variance Estimation for Totals

The variances and SEs of estimates of means and proportions can be calculated appropriately in SUDAAN using a Taylor series linearization approach. Estimates of means or proportions, p hat sub d, such as drug use prevalence estimates for a domain d, can be expressed as a ratio estimate:

Equation B.1,     D

where capital Y hat sub d is a linear statistic estimating the number of substance users in the domain d and capital N hat sub d is a linear statistic estimating the total number of persons in domain d (both users and nonusers). The SUDAAN software package is used to calculate direct estimates of capital Y hat sub d and capital N hat sub d (and, therefore, p hat sub d ) and also can be used to estimate their respective SEs. A Taylor series approximation method implemented in SUDAAN provides the estimate for the SE of p hat sub d .

When the domain size, capital N hat sub d , is free of sampling error, an appropriate estimate of the SE for the total number of substance users is

Equation B.2.     D

This approach is theoretically correct when the domain size estimates, capital N hat sub d , are among those forced to match their respective U.S. Census Bureau population estimates through the weight calibration process. In these cases, capital N hat sub d is not subject to a sampling error induced by the NSDUH design. Section A.3.3 in Appendix A contains further information about the weight calibration process. In addition, more detailed information about the weighting procedures for 2010 will appear in the 2010 NSDUH Methodological Resource Book, which is in process. Until that volume becomes available, refer to the 2009 NSDUH Methodological Resource Book (RTI International, 2011).

For estimated domain totals, capital Y hat sub d , where capital N hat sub d is not fixed (i.e., where domain size estimates are not forced to match the U.S. Census Bureau population estimates), this formulation still may provide a good approximation if it can be assumed that the sampling variation in capital N hat sub d is negligible relative to the sampling variation in p hat sub d . This is a reasonable assumption for many cases in this study.

For various subsets of estimates, the above approach yielded an underestimate of the variance of a total because capital N hat sub d was subject to considerable variation. Because of this underestimation, alternatives for estimating SEs of totals were implemented. Since the 2005 NSDUH report, a "mixed" method approach has been implemented for all detailed tables to improve the accuracy of SEs and to better reflect the effects of poststratification on the variance of total estimates. This approach assigns the method of SE calculation to domains (subgroups for which the estimates were calculated) within tables so that all estimates among a select set of domains with fixed capital N hat sub d were calculated using the formula above, and all other estimates were calculated directly in SUDAAN, regardless of other estimates within the same table. The set of domains considered controlled (i.e., those with a fixed capital N hat sub d ) was restricted to main effects and two-way interactions in order to maintain continuity between years. Domains consisting of three-way interactions may be controlled in a single year but not necessarily in preceding or subsequent years. The use of such SEs did not affect the SE estimates for the corresponding proportions presented in the same sets of tables because all SEs for means and proportions are calculated directly in SUDAAN. As a result of the use of this mixed-method approach, the SEs for the total estimates within many detailed tables were calculated differently from those in NSDUH reports prior to the 2005 report.

Table B.1 at the end of this appendix contains a list of domains with a fixed capital N hat sub d . This table includes both the main effects and two-way interactions and may be used to identify the method of SE calculation employed for estimates of totals. For example, Table 1.23 in the 2010 detailed tables8 presents estimates of illicit drug use among persons aged 18 or older within the domains of gender, Hispanic origin and race, education, and current employment. Estimates among the total population (age main effect), males and females (age by gender interaction), and Hispanics and non-Hispanics (age by Hispanic origin interaction) were treated as controlled in this table, and the formula above was used to calculate the SEs. The SEs for all other estimates, including white and black or African American (age by Hispanic origin by race interaction) were calculated directly from SUDAAN. Estimates presented in this report for racial groups are for non-Hispanics. For instance, the domain for whites is actually non-Hispanic whites and is therefore a two-way interaction.

B.2.2 Suppression Criteria for Unreliable Estimates

As has been done in past NSDUH reports, direct survey estimates produced for this study that are considered to be unreliable are not shown in this report and are noted by asterisks (*) in figures containing such estimates. The criteria used for suppressing all direct survey estimates were based on the prevalence (for proportion estimates), relative standard error (RSE) (defined as the ratio of the SE over the estimate), nominal (actual) sample size, and effective sample size for each estimate. These suppression criteria for various NSDUH estimates are summarized in Table B.2 at the end of this appendix.

Proportion estimates (p hat), or rates, within the range [zero less than p hat less than 1], and the corresponding estimated number of users were suppressed if

Equation B.3     D

or

Equation B.4     D

Using a first-order Taylor series approximation to estimate the relative standard error of the negative of the natural logarithm of p hat and the relative standard error of the negative of the natural logarithm of the difference 1 minus p hat the following equation was derived and used for computational purposes when developing a suppression rule dependent on effective sample size:

Equation B.5     D

or

Equation B.6.     D

The separate formulas for p hat less than or equal to .5 and p hat greater than .5 produce a symmetric suppression rule; that is, if p hat is suppressed, l − 1 minus p hat will be suppressed as well (see Figure B.1 following Table B.2). When p hat greater than .05 and less than .95 the symmetric properties of the rule produce a local minimum of 50 at p hat = .2 and at p hat = .8. Using the minimum for the suppression rule would mean that estimates of p hat between .05 and .95 would be suppressed if their corresponding effective sample sizes were less than 50. Within this same interval, a local maximum of 68 is found at p hat = .5. To simplify requirements and maintain a conservative suppression rule, estimates of p hat between .05 and .95 were suppressed if they had an effective sample size below 68.

In addition, a minimum nominal sample size suppression criterion (n = 100) that protects against unreliable estimates caused by small design effects and small nominal sample sizes was employed; Table B.2 shows a formula for calculating design effects. Prevalence estimates also were suppressed if they were close to 0 or 100 percent (i.e., if p hat < .00005 or if p hat ≥ .99995).

Estimates of totals were suppressed if the corresponding prevalence rates were suppressed. Estimates of means that are not bounded between 0 and 1 (e.g., mean age at first use) were suppressed if the RSEs of the estimates were larger than .5 or if the sample size was smaller than 10 respondents.

B.2.3 Statistical Significance of Differences

This section describes the methods used to compare prevalence estimates in this report. Customarily, the observed difference between estimates is evaluated in terms of its statistical significance. Statistical significance is based on the p value of the test statistic and refers to the probability that a difference as large as that observed would occur because of random variability in the estimates if there were no difference in the prevalence estimates for the population groups being compared. The significance of observed differences in this report is reported at the .05 level. When comparing prevalence estimates, the null hypothesis (no difference between prevalence estimates) was tested against the alternative hypothesis (there is a difference in prevalence estimates) using the standard difference in proportions test expressed as

Equation B.7,     D

where p hat sub 1 = first prevalence estimate, p hat sub 2 = second prevalence estimate, var(variance of p hat sub 1) = variance of first prevalence estimate, var(variance of p hat sub 2) = variance of second prevalence estimate, and the covariance of p hat sub 1 comma p hat sub 2 = covariance between p hat sub 1 and p hat sub 2. In cases where significance tests between years were performed, the prevalence estimate from the earlier year (e.g., 2002, 2003, 2004, 2005, 2006, 2007, 2008, or 2009) becomes the first estimate, and the prevalence estimate from the later year (e.g., 2003, 2004, 2005, 2006, 2007, 2008, 2009, or 2010) becomes the second estimate.

Under the null hypothesis, Z is asymptotically distributed as a normal random variable. Therefore, calculated values of Z can be referred to the unit normal distribution to determine the corresponding probability level (i.e., p value). Because the covariance term between the two estimates is not necessarily zero, SUDAAN was used to compute estimates of Z along with the associated p values using the analysis weights and accounting for the sample design as described in Appendix A. A similar procedure and formula for Z were used for estimated totals. Whenever it was necessary to calculate the SE outside of SUDAAN (i.e., when domains were forced by the weighting process to match their respective U.S. Census Bureau population estimates), the corresponding test statistics also were computed outside of SUDAAN.

When comparing population subgroups across three or more levels of a categorical variable, log-linear chi-square tests of independence of the subgroups and the prevalence variables were conducted using SUDAAN in order to first control the error level for multiple comparisons. If Shah's Wald F test (transformed from the standard Wald chi-square) indicated overall significant differences, the significance of each particular pairwise comparison of interest was tested using SUDAAN analytic procedures to properly account for the sample design (RTI International, 2008). Using the published estimates and SEs to perform independent t tests for the difference of proportions usually will provide the same results as tests performed in SUDAAN. However, where the significance level is borderline, results may differ for two reasons: (1) the covariance term is included in SUDAAN tests, whereas it is not included in independent t tests; and (2) the reduced number of significant digits shown in the published estimates may cause rounding errors in the independent t tests.

As part of a comparative analysis discussed in Chapter 8, prevalence estimates from the Monitoring the Future (MTF) study, sponsored by the National Institute on Drug Abuse (NIDA), were presented for recency measures of selected substances (see Tables 8.1 and 8.2). The analyses focused on prevalence estimates for 8th and 10th graders and prevalence estimates for young adults aged 19 to 24 for 2002 through 2010. Estimates for the 8th and 10th grade students were calculated using MTF data as the simple average of the 8th and 10th grade estimates. Estimates for young adults aged 19 to 24 were calculated using MTF data as the simple average of three modal age groups: 19 and 20 years, 21 and 22 years, and 23 and 24 years. Published results were not available from NIDA for significant differences in prevalence estimates between years for these subgroups, so testing was performed using information that was available.

For the 8th and 10th grade average estimates, tests of differences were performed between 2010 and the 8 prior years. Estimates for persons in grade 8 and grade 10 were considered independent, simplifying the calculation of variances for the combined grades. Across years, the estimates for 2010 involved samples independent of those in 2002, 2003, 2004, 2005, 2006, 2007, and 2008. For 2009 and 2010, however, the sample of schools overlapped 50 percent, creating a covariance in the estimates. Design effects published in Johnston et al. (2010) for adjacent and nonadjacent year testing were used.

For the 19- to 24-year-old age group, tests of differences were done assuming independent samples between years an odd number of years apart because two distinct cohorts a year apart were monitored longitudinally at 2-year intervals. This is appropriate for comparisons of 2003, 2005, 2007, and 2009 with 2010. However, this assumption results in conservative tests for comparisons of 2002, 2004, 2006, and 2008 data with 2010 data because testing did not take into account covariances associated with repeated observations from the longitudinal samples. Estimates of covariances were not available.

As an example, the difference between the 2009 and 2010 averages of prevalence estimates for persons in grades 8 and 10 can be expressed as

Equation B.8,     D

where The p bar sub 1 equals one half the quantity of p hat sub one one plus p hat sub one two. ; p hat sub one one and p hat sub one two are the prevalence estimates for the 8th and 10th grades, respectively, for 2009; and p bar sub 2 is defined similarly for 2010. The variance of a prevalence estimate p hat can be written as

Equation B.9,     D

where n is the sample size and D is the appropriate design effect obtained from the sampling design. In the MTF study, design effects were available for comparisons between adjacent-year (i.e., 2009 vs. 2010) estimates and nonadjacent-year (i.e., 2002 vs. 2010, 2003 vs. 2010, 2004 vs. 2010, 2005 vs. 2010, 2006 vs. 2010, 2007 vs. 2010, and 2008 vs. 2010) estimates; therefore, the variance of the difference between 2 years of estimates for a particular grade can be expressed as

Equation B.10,     D

where i = 1 indexes the 8th grade, i = 2 indexes the 10th grade, capital D sub i is the design effect appropriate for comparisons between estimates of the 2 years (with separate design effect parameters for adjacent and nonadjacent years), and the n sub j i are the sample sizes corresponding to the indexed year and grade prevalence estimates, i comma j equals 1 comma 2. Because the 8th and 10th grade samples were drawn independently, the variance of the difference between the 8th and 10th grade averages can be expressed as

Equation B.11.     D

The test statistic can therefore be written as

Equation B.12,     D

where Z is asymptotically distributed as a standard normal random variable.

B.3 Other Information on Data Accuracy

The accuracy of survey estimates can be affected by nonresponse, coding errors, computer processing errors, errors in the sampling frame, reporting errors, and other errors not due to sampling. These types of "nonsampling errors" and their impact are reduced through data editing, statistical adjustments for nonresponse, close monitoring and periodic retraining of interviewers, and improvement in quality control procedures.

Although these types of errors often can be much larger than sampling errors, measurement of most of these errors is difficult. However, some indication of the effects of some types of these errors can be obtained through proxy measures, such as response rates, and from other research studies.

B.3.1 Screening and Interview Response Rate Patterns

In 2010, respondents continued to receive a $30 incentive in an effort to maximize response rates. The weighted screening response rate (SRR) is defined as the weighted number of successfully screened households9 divided by the weighted number of eligible households (as defined in Table B.3), or

Equation B.13,     D

where w sub h h is the inverse of the unconditional probability of selection for the household and excludes all adjustments for nonresponse and poststratification defined in Section A.3.3 of Appendix A. Of the 166,435 eligible households sampled for the 2010 NSDUH, 147,608 were screened successfully, for a weighted screening response rate of 88.8 percent (Table B.3). At the person level, the weighted interview response rate (IRR) is defined as the weighted number of respondents divided by the weighted number of selected persons (see Table B.4), or

Equation B.14,     D

where w sub i is the inverse of the probability of selection for the person and includes household-level nonresponse and poststratification adjustments (adjustments 1, 2, and 3 in Section A.3.3 of Appendix A). To be considered a completed interview, a respondent must provide enough data to pass the usable case rule.10 In the 147,608 screened households, a total of 85,668 sample persons were selected, and completed interviews were obtained from 68,487 of these sample persons, for a weighted IRR of 74.7 percent (Table B.4). A total of 12,216 (18.1 percent) sample persons were classified as refusals or parental refusals, 2,801 (3.3 percent) were not available or never at home, and 2,164 (3.9 percent) did not participate for various other reasons, such as physical or mental incompetence or language barrier (see Table B.4, which also shows the distribution of the selected sample by interview code and age group). Among demographic subgroups, the weighted IRR was higher among 12 to 17 year olds (84.8 percent), females (76.0 percent), blacks (80.3 percent), persons in the South (76.2 percent), and residents of nonmetropolitan areas (76.7 percent) than among other related groups (Table B.5).

The overall weighted response rate, defined as the product of the weighted screening response rate and weighted interview response rate or

Equation B.15,     D

was 66.3 percent in 2010. Nonresponse bias can be expressed as the product of the nonresponse rate (1 minus capital R) and the difference between the characteristic of interest between respondents and nonrespondents in the population ( capital P sub r minus capital P sub n r). By maximizing NSDUH response rates, it is hoped that the bias due to the difference between the estimates from respondents and nonrespondents is minimized. Drug use surveys are particularly vulnerable to nonresponse because of the difficult nature of accessing heavy drug users. However, in a study that matched 1990 census data to 1990 NHSDA nonrespondents,11 it was found that populations with low response rates did not always have high drug use rates. For example, although some populations were found to have low response rates and high drug use rates (e.g., residents of large metropolitan areas and males), other populations had low response rates and low drug use rates (e.g., older adults and high-income populations). Therefore, many of the potential sources of bias tend to cancel each other in estimates of overall prevalence (Gfroerer, Lessler, & Parsley, 1997a).

B.3.2 Inconsistent Responses and Item Nonresponse

Among survey participants, item response rates were generally very high for most drug use items. However, respondents could give inconclusive or inconsistent information about whether they ever used a given drug (i.e., "yes" or "no") and, if they had used a drug, when they last used it; the latter information is needed to identify those lifetime users of a drug who used it in the past year or past month. In addition, respondents could give inconsistent responses to items such as when they first used a drug compared with their most recent use of a drug. These missing or inconsistent responses first are resolved where possible through a logical editing process. Additionally, missing or inconsistent responses are imputed using statistical methodology. These imputation procedures in NSDUH are based on responses to multiple questions, so that the maximum amount of information is used in determining whether a respondent is classified as a user or nonuser, and if the respondent is classified as a user, whether the respondent is classified as having used in the past year or the past month. For example, ambiguous data on the most recent use of cocaine are statistically imputed based on a respondent's data for use (or most recent use) of tobacco products, alcohol, inhalants, marijuana, hallucinogens, and nonmedical use of prescription psychotherapeutic drugs. Nevertheless, editing and imputation of missing responses are potential sources of measurement error. For more information on editing and statistical imputation, see Sections A.3.1 and A.3.2 of Appendix A. Details of the editing and imputation procedures for 2010 also will appear in the 2010 NSDUH Methodological Resource Book, which is in process. Until that volume becomes available, refer to the 2009 NSDUH Methodological Resource Book (RTI International, 2011).

B.3.3 Data Reliability

A reliability study was conducted as part of the 2006 NSDUH to assess the reliability of responses to the NSDUH questionnaire. An interview/reinterview method was employed in which 3,136 individuals were interviewed on two occasions during 2006 generally 5 to 15 days apart; the initial interviews in the reliability study were a subset of the main study interviews. The reliability of the responses was assessed by comparing the responses of the first interview with the responses from the reinterview. Responses from the first interview and reinterview that were analyzed for response consistency were raw data that had been only minimally edited for ease of analysis and had not been imputed (see Sections A.3.1 and A.3.2 in this report).

This section summarizes the results for the reliability of selected variables related to substance use and demographic characteristics. Reliability is expressed by estimates of Cohen's kappa (κ) (Cohen, 1960), which can be interpreted according to benchmarks proposed by Landis and Koch (1977, p. 165): (a) poor agreement for kappas less than 0.00, (b) slight agreement for kappas of 0.00 to 0.20, (c) fair agreement for kappas of 0.21 to 0.40, (d) moderate agreement for kappas of 0.41 to 0.60, (e) substantial agreement for kappas of 0.61 to 0.80, and (f) almost perfect agreement for kappas of 0.81 to 1.00.

The kappa values for the lifetime and past year substance use variables (marijuana use, alcohol use, and cigarette use) all showed almost perfect response consistency, ranging from 0.82 for past year marijuana use to 0.93 for lifetime marijuana use and past year cigarette use. The value obtained for the substance dependence or abuse measure in the past year showed substantial agreement (0.67), while the substance abuse treatment variable showed almost perfect consistency in both the lifetime (0.89) and past year (0.87). The variables for age at first use of marijuana and perceived great risk of smoking marijuana once a month showed substantial agreement (0.74 and 0.68, respectively). The demographic variables showed almost perfect agreement, ranging from 0.95 for current enrollment in school to 1.00 for gender. For further information on the reliability of a wide range of measures contained in NSDUH, see the complete methodology report (Chromy et al., 2010).

B.3.4 Validity of Self-Reported Substance Use

Most substance use prevalence estimates, including those produced for NSDUH, are based on self-reports of use. Although studies generally have supported the validity of self-report data, it is well documented that these data may be biased (underreported or overreported). The bias varies by several factors, including the mode of administration, the setting, the population under investigation, and the type of drug (Aquilino, 1994; Brener et al., 2006; Harrison & Hughes, 1997; Tourangeau & Smith, 1996; Turner, Lessler, & Gfroerer, 1992). NSDUH utilizes widely accepted methodological practices for increasing the accuracy of self-reports, such as encouraging privacy through audio computer-assisted self-interviewing (ACASI) and providing assurances that individual responses will remain confidential. Comparisons using these methods within NSDUH have shown that they reduce reporting bias (Gfroerer, Eyerman, & Chromy, 2002). Various procedures have been used to validate self-report data, such as biological specimens (e.g., urine, hair, saliva), proxy reports (e.g., family member, peer), and repeated measures (e.g., recanting) (Fendrich, Johnson, Sudman, Wislar, & Spiehler, 1999). However, these procedures often are impractical or too costly for general population epidemiological studies (SRNT Subcommittee on Biochemical Verification, 2002).

A study cosponsored by the Substance Abuse and Mental Health Services Administration (SAMHSA) and the National Institute on Drug Abuse (NIDA) examined the validity of NSDUH self-report data on drug use among persons aged 12 to 25. The study found that it is possible to collect urine and hair specimens with a relatively high response rate in a general population survey, and that most youths and young adults reported their recent drug use accurately in self-reports (Harrison, Martin, Enev, & Harrington, 2007). However, there were some reporting differences in either direction, with some respondents not reporting use but testing positive, and some reporting use but testing negative. Technical and statistical problems related to the hair tests precluded presenting comparisons of self-reports and hair test results, while small sample sizes for self-reports and positive urine test results for opiates and stimulants precluded drawing conclusions about the validity of self-reports of these drugs. Further, inexactness in the window of detection for drugs in biological specimens and biological factors affecting the window of detection could account for some inconsistency between self-reports and urine test results.

B.4 Measurement Issues

B.4.1 Incidence

In epidemiological studies, incidence is defined as the number of new cases of a disease occurring within a specific period of time. Similarly, in substance use studies, incidence refers to the first use of a particular substance.

In the 2004 NSDUH national findings report (Office of Applied Studies [OAS], 2005), a new measure related to incidence was introduced and since then has become the primary focus of Chapter 5 in this national findings report series. The incidence measure is termed "past year initiation" and refers to respondents whose date of first use of a substance was within the 12 months prior to their interview date. This measure is determined by self-reported past year use, age at first use, year and month of recent new use, and the interview date.

Since 1999, the survey questionnaire has allowed for collection of year and month of first use for recent initiates (i.e., persons who used a particular substance for the first time in a given survey year). Month, day, and year of birth also are obtained directly or are imputed for item nonrespondents as part of the data postprocessing. Additionally, the computer-assisted interviewing (CAI) instrument records and provides the date of the interview. By imputing a day of first use within the year and month of first use, a specific date of first use, t sub f u comma d comma i, can be used for estimation purposes.

Past year initiation among persons using a substance in the past year can be viewed as an indicator variable defined as follows:

Equation B.16,     D

where day of interview for person i, month of interview for person i, and year of interview for person i, denote the day, month, and year of the interview, respectively, and t sub f u comma d comma i denotes the date of first use.

The calculation of this estimate does not take into account whether a respondent initiated substance use while a resident of the United States. This method of calculation has little effect on past year estimates and allows for direct comparability with other standard measures of substance use because the populations of interest for the measures will be the same (i.e., both measures examine all possible respondents and are not restricted to those initiating substance use only in the United States).

One important note for incidence estimates is the relationship between main categories and subcategories of substances (e.g., illicit drugs would be a main category, and inhalants and marijuana would be subcategories in relation to illicit drugs). For most measures of substance use, any member of a subcategory is by necessity a member of the main category (e.g., if a respondent is a past month user of a particular drug, then he or she is also a past month user of illicit drugs in general). However, this is not the case with regard to incidence statistics. Because an individual can only be an initiate of a particular substance category (main or sub) a single time, a respondent with lifetime use of multiple substances may not, by necessity, be included as a past year initiate of a main category, even if he or she were a past year initiate for a particular subcategory because his or her first initiation of other substances within the main category could have occurred earlier.

Caution also is recommended for interpreting data on the estimated numbers of past year initiates aged 26 or older because of the small numbers of respondents in this age group who report initiation of use and because of variability in the trend data. Specifically, the number of past year initiates of marijuana aged 12 or older remained unchanged between 2009 and 2010 (approximately 2.4 million in both years). However, the estimated number of past year initiates of marijuana among persons aged 26 or older in 2010 (247,000) was nearly 5 times the estimated number in 2009 (49,000) (Table B.6). In contrast, the number of past year initiates in this age group in 2008 (159,000) was not significantly different from that in 2010.

The number of past year initiates of marijuana aged 26 or older also has shown considerable variability from 2002 to 2010. Although the estimated number of past year initiates of marijuana in this age group appeared to peak at 252,000 persons in 2005, this estimate is significantly different only from the estimate in 2009. The estimate in 2009 also is significantly different from the estimates in 2004 to 2008. In most years, past year initiates of marijuana aged 26 or older primarily were aged 26 to 49. The number of past year initiates of marijuana aged 26 to 49 also increased from 2009 (49,000) to 2010 (210,000).

Unlike past year initiation of marijuana, the number of past year initiates aged 26 or older for any illicit drug was stable from 2009 (430,000) to 2010 (458,000). As for marijuana, however, the number of past year initiates of any illicit drug aged 26 to 49 increased from 2009 (201,000) to 2010 (366,000).

Small numbers of respondents aged 26 or older reported past year initiation of marijuana in 2009 and 2010 (15 and 30, respectively). The increase in the estimated number of past year initiates in this age group from 2009 to 2010 occurred because of an increase in the average analysis weights for past year initiates aged 26 or older, from 3,275 in 2009 to about 8,230 in 2010. Given that the estimated numbers of past year initiates of marijuana aged 26 or older were not significantly different between 2010 and all years from 2004 to 2008, the change from 2009 to 2010 may be an anomaly.

In addition to estimates of the number of persons initiating use of a substance in the past year, estimates of the mean age of past year first-time users of these substances are computed. Unless specified otherwise, estimates of the mean age at initiation in the past 12 months have been restricted to persons aged 12 to 49 so that the mean age estimates reported are not influenced by those few respondents who were past year initiates at age 50 or older. As a measure of central tendency, means are influenced heavily by the presence of extreme values in the data, and this constraint should increase the utility of these results to health researchers and analysts by providing a better picture of the substance use initiation behaviors among the civilian, noninstitutionalized population in the United States. This constraint was applied only to estimates of mean age at first use and does not affect estimates of incidence.

As noted in Chapter 5, the mean age at first use of marijuana in 2010 (18.4 years) among past year initiates aged 12 to 49 was higher than the average in 2009 (17.0 years) and in 2002 to 2005 (ranging from 16.8 to 17.4 years) (Figure 5.4). The mean age at first use of marijuana also decreased significantly from 2008 (17.8 years) to 2009. Similarly, the mean age at first use of any illicit drug among past year initiates aged 12 to 49 did not change significantly between consecutive years from 2004 to 2008 (ranging from 18.0 to 19.0 years). However, the mean decreased from 18.8 years in 2008 to 17.6 years in 2009, then increased to 19.1 years in 2010.

To understand the change from 2009 to 2010 in the mean age at first use of any illicit drug among past year initiates aged 12 to 49, data for the number of past year initiates were examined for all of the drugs that comprise the category of any illicit drug use. The only illicit drug category where the number of past year initiates increased significantly from 2009 to 2010 was for marijuana among persons aged 26 to 49. Among past year initiates of marijuana aged 26 to 49, the mean age at first use in 2010 was 36.3 years, which was higher than the averages in 2002 to 2006 (ranging from 29.1 to 31.2 years) (Table B.7). Although the mean age at first use in 2009 (32.1 years) appeared to be lower than the mean of 36.3 years in 2010, these two averages were not significantly different.

Nevertheless, increases in the numbers of past year initiates of marijuana and any illicit drug aged 26 to 49 between 2009 and 2010 affected the 2010 mean age at first use of marijuana and any illicit drug for the 26 to 49 and 12 to 49 age groups. Among past year initiates of any illicit drug aged 26 to 49, the mean age at first use in 2010 (37.2 years) was higher than the average in 2009 (31.7 years). However, the mean age at first use in 2010 was not significantly different from the mean ages between 2005 to 2008 (ranging from 32.9 to 35.1 years). Thus, similar to estimates for the numbers of past year initiates aged 26 to 49, the mean ages at first use in 2009 among past year initiates aged 26 to 49 for marijuana and any illicit drug may be anomalous.

Because NSDUH is a survey of persons aged 12 years old or older at the time of the interview, younger individuals in the sample dwelling units are not eligible for selection into the NSDUH sample. Some of these younger persons may have initiated substance use during the past year. As a result, past year initiate estimates suffer from undercoverage if a reader assumes that these estimates reflect all initial users instead of only for those above the age of 11. For earlier years, data can be obtained retrospectively based on the age at and date of first use. As an example, persons who were 12 years old on the date of their interview in the 2010 survey may report having initiated use of cigarettes between 1 and 2 years ago; these persons would have been past year initiates reported in the 2009 survey had persons who were 11 years old on the date of the 2009 interview been allowed to participate in the survey. Similarly, estimates of past year use by younger persons (age 10 or younger) can be derived from the current survey, but they apply to initiation in prior years and not the survey year.

To get an impression of the potential undercoverage in the current year, reports of substance use initiation reported by persons aged 12 or older were estimated for the years in which these persons would have been 1 to 11 years younger. These estimates do not necessarily reflect behavior by persons 1 to 11 years younger in the current survey. Instead, the data for the 11 year olds reflect initiation in the year prior to the current survey; the data for the 10 year olds reflect behavior between the 12th and 23rd months prior to this year's survey, and so on. A very rough way to adjust for the difference in the years that the estimate pertains to without considering changes in the population is to apply an adjustment factor to each age-based estimate of past year initiates. This adjustment factor can be based on a ratio of lifetime users aged 12 to 17 in the current survey year to the same estimate for the prior applicable survey year. To illustrate the calculation, consider past year use of alcohol. In the 2010 survey, 77,477 persons 12 years old were estimated to have initiated use of alcohol between 1 and 2 years earlier. These persons would have been past year initiates in the 2009 survey conducted on the same dates had the 2009 survey covered younger persons. The estimated number of lifetime users currently aged 12 to 17 was 8,573,937 for 2010 and 9,382,813 for 2009, indicating fewer overall initiates of alcohol use among persons aged 17 or younger in 2010. Thus, an adjusted estimate of initiation of alcohol use by persons who were 11 years old in 2010 is given by

Equation B.17.     D

This yielded an adjusted estimate of 70,798 persons 11 years old on a 2010 survey date and initiating use of alcohol in the past year:

Equation B.18.     D

A similar procedure was used to adjust the estimated number of past year initiates among persons who would have been 10 years old on the date of the interview in 2008 and for younger persons in earlier years. The overall adjusted estimate for past year initiates of alcohol use by persons 11 years of age or younger on the date of the interview was 167,528, or about 3.6 percent of the estimate based on past year initiation by persons 12 or older only (167,528 ÷ 4,673,215 = 0.0358).

Based on similar analyses, the estimated undercoverage of past year initiates was 4.1 percent for cigarettes, 0.7 percent for marijuana, and 19.4 percent for inhalants. These 2010 results are comparable with undercoverage estimates presented in prior reports using data from the 2005 through 2009 surveys.

The undercoverage of past year initiates aged 11 or younger also affects the mean age at first use estimate. An adjusted estimate of the mean age at first use was calculated using a weighted estimate of the mean age at first use based on the current survey and the numbers of persons aged 11 or younger in the past year obtained in the aforementioned analysis for estimating undercoverage of past year initiates. Analysis results showed that the mean age at first use was changed from 17.2 to 16.9 for alcohol, from 17.3 to 16.9 for cigarettes, from 18.4 to 18.3 for marijuana, and from 16.3 to 15.0 for inhalants. The decreases reported above are comparable with results generated in prior survey years.

B.4.2 Illicit Drug and Alcohol Dependence and Abuse

The 2010 NSDUH CAI instrumentation included questions that were designed to measure alcohol and illicit drug dependence and abuse. For these substances,12 dependence and abuse questions were based on the criteria in the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) (American Psychiatric Association [APA], 1994). Specifically, for marijuana, hallucinogens, inhalants, and tranquilizers, a respondent was defined as having dependence if he or she met three or more of the following six dependence criteria:

  1. Spent a great deal of time over a period of a month getting, using, or getting over the effects of the substance.
  2. Used the substance more often than intended or was unable to keep set limits on the substance use.
  3. Needed to use the substance more than before to get desired effects or noticed that the same amount of substance use had less effect than before.
  4. Inability to cut down or stop using the substance every time tried or wanted to.
  5. Continued to use the substance even though it was causing problems with emotions, nerves, mental health, or physical problems.
  6. The substance use reduced or eliminated involvement or participation in important activities.

For alcohol, cocaine, heroin, pain relievers, sedatives, and stimulants, a seventh withdrawal criterion was added. A respondent was defined as having dependence if he or she met three or more of seven dependence criteria. The seventh withdrawal criterion is defined by a respondent reporting having experienced a certain number of withdrawal symptoms that vary by substance (e.g., having trouble sleeping, cramps, hands tremble).

For each illicit drug and alcohol, a respondent was defined as having abused that substance if he or she met one or more of the following four abuse criteria and was determined not to be dependent on the respective substance in the past year:

  1. Serious problems at home, work, or school caused by the substance, such as neglecting your children, missing work or school, doing a poor job at work or school, or losing a job or dropping out of school.
  2. Used the substance regularly and then did something that might have put you in physical danger.
  3. Use of the substance caused you to do things that repeatedly got you in trouble with the law.
  4. Had problems with family or friends that were probably caused by using the substance and continued to use the substance even though you thought the substance use caused these problems.

Criteria used to determine whether a respondent was asked the dependence and abuse questions during the interview included responses from the core substance use questions and the frequency of substance use questions, as well as the noncore substance use questions. Missing or incomplete responses in the core substance use and frequency of substance use questions were imputed. However, the imputation process did not take into account reported data in the noncore (i.e., substance dependence and abuse) CAI modules. Very infrequently, this may result in responses to the dependence and abuse questions that were inconsistent with the imputed substance use or frequency of substance use.

For alcohol and marijuana, respondents were asked the dependence and abuse questions if they reported substance use on more than 5 days in the past year, or if they reported any substance use in the past year but did not report their frequency of past year use. Therefore, inconsistencies could have occurred where the imputed frequency of use response indicated less frequent use than required for respondents to be asked the dependence and abuse questions originally. For alcohol, for example, the final number of respondents who were past year alcohol users in 2010 was 41,597. Of these, 78 respondents (0.2 percent) were asked the alcohol dependence and abuse questions, but their final imputed frequency of use indicated that they used alcohol on 5 or fewer days in the past year.

For cocaine, heroin, and stimulants, respondents were asked the dependence and abuse questions if they reported past year use in a core drug module or past year use in the noncore special drugs module. Thus, the CAI logic allowed some respondents to be asked the dependence and abuse questions for these drugs even if they did not report past year use in the corresponding core module. For cocaine, for example, 1,535 respondents in 2010 were asked the questions about cocaine dependence and abuse because they reported past year use of cocaine or crack in the core section of the interview. Fewer than 10 additional respondents were asked these questions because they reported past year use of cocaine with a needle in the special drugs module despite not having previously reported past year use of cocaine or crack.

In 2005, two new questions were added to the noncore special drugs module about past year methamphetamine use: "Have you ever, even once, used methamphetamine?" and "Have you ever, even once, used a needle to inject methamphetamine?" In 2006, an additional follow-up question was added to the noncore special drugs module confirming prior responses about methamphetamine use: "Earlier, the computer recorded that you have never used methamphetamine. Which answer is correct?" The responses to these new questions were used in the skip logic for the stimulant dependence and abuse questions. Based on the decisions made during the methamphetamine analysis,13 respondents who indicated past year methamphetamine use solely from these new special drug use questions (i.e., did not indicate methamphetamine use from the core drug module or other questions in the special drugs module) were categorized as NOT having past year stimulant dependence or abuse regardless of how they answered the dependence and abuse questions. Furthermore, if these same respondents were categorized as not having past year dependence or abuse of any other substance (e.g., pain relievers, tranquilizers, or sedatives for the psychotherapeutic drug grouping), then they were categorized as NOT having past year dependence or abuse of psychotherapeutics, illicit drugs, illicit drugs or alcohol, and illicit drugs and alcohol.

In 2008, questionnaire logic for determining hallucinogen, stimulant, and sedative dependence or abuse was modified. The revised skip logic used information collected in the noncore special drugs module in addition to that collected in questions from the core drug modules. Respondents were asked about hallucinogen dependence and abuse if they additionally reported in the special drugs module using Ketamine, DMT, AMT, Foxy, or Salvia divinorum; stimulant dependence and abuse if they reported additionally using Adderall®; and sedative dependence and abuse if they reported additionally using Ambien®. Complying with the previous decision to exclude respondents whose methamphetamine use was based solely on responses in a noncore module from being classified as having stimulant dependence or abuse, respondents who indicated past year hallucinogen, stimulant, or sedative use based solely on these special drug questions were categorized as NOT having past year dependence or abuse of the relevant substance regardless of how they answered the dependence and abuse questions.

Respondents might have provided ambiguous information about past year use of any individual substance, in which case these respondents were not asked the dependence and abuse questions for that substance. Subsequently, these respondents could have been imputed to be past year users of the respective substance. In this situation, the dependence and abuse data were unknown; thus, these respondents were classified as not having dependence or abuse of the respective substance. However, such a respondent never actually was asked the dependence and abuse questions.

Table B.1 Demographic and Geographic Domains Forced to Match Their Respective U.S. Census Bureau Population Estimates through the Weight Calibration Process, 2010
Main Effects Two-Way Interactions
1 Combinations of the age groups (including but not limited to 12 or older, 18 or older, 26 or older, 35 or older, and 50 or older) also were forced to match their respective U.S. Census Bureau population estimates through the weight calibration process.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2010.
Age Group  
12-17  
18-25  
26-34  
35-49  
50-64  
65 or Older  
All Combinations of Groups Listed Above1  
  Age Group × Gender
Gender (e.g., Males Aged 12 to 17)
Male  
Female  
  Age Group × Hispanic Origin
Hispanic Origin (e.g., Hispanics or Latinos Aged 18 to 25)
Hispanic or Latino  
Not Hispanic or Latino  
  Age Group × Race
Race (e.g., Whites Aged 26 or Older)
White  
Black or African American  
  Age Group × Geographic Region
Geographic Region (e.g., Persons Aged 12 to 25 in the Northeast)
Northeast  
Midwest  
South Age Group × Geographic Division
West (e.g., Persons Aged 65 or Older in New England)
   
Geographic Division  
New England Gender × Hispanic Origin
Middle Atlantic (e.g., Not Hispanic or Latino Males)
East North Central  
West North Central  
South Atlantic Hispanic Origin × Race
East South Central (e.g., Not Hispanic or Latino Whites)
West South Central  
Mountain  
Pacific  

Table B.2 Summary of 2010 NSDUH Suppression Rules
Estimate Suppress if:
deff = design effect; RSE = relative standard error; SE = standard error.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2010.
Prevalence Rate, p hat, with Nominal
Sample Size, n, and Design Effect,
deff

Design effect is equal to the quantity of n times the standard error of p hat squared divided by the quantity of p hat times 1 minus p hat.
(1) The estimated prevalence rate, p hat, is < .00005 or ≥ .99995, or

(2) The ratio of two quantities is greater than .175. The numerator of the ratio is the standard error of p hat divided by p hat. The denominator is the negative of the natural logarithm of p hat. > .175 when p hat is less than or equal to .5, or

     The ratio of two quantities is greater than .175. The numerator of the ratio is the standard error of p hat divided by 1 minus p hat. The denominator is the negative of the natural logarithm of the quantity 1 minus p hat. > .175 when p hat greater than .5, or

(3) Effective n is less than 68., where Effective n = Effective n is the ratio of n over the design effect, which is equal to the quantity of p hat times 1 minus p hat divided by the quantity of the standard error of p hat squared., or

(4) The n is less than 100..

Note: The rounding portion of this suppression rule for prevalence rates will produce some estimates that round at one decimal place to 0.0 or 100.0 percent but are not suppressed from the tables.
Estimated Number
(Numerator of p hat)
The estimated prevalence rate, p hat, is suppressed.
Note: In some instances when p hat is not suppressed, the estimated number may appear as a 0 in the tables. This means that the estimate is greater than 0 but less than 500 (estimated numbers are shown in thousands).
Mean Age at First Use, x bar, with
Nominal Sample Size, n
(1) The relative standard error of x bar is greater than .5., or

(2) The n is less than 10..

Figure B.1 Required Effective Sample in the 2010 NSDUH as a Function of the Proportion Estimated

Figure B.1     D

Table B.3 Weighted Percentages and Sample Sizes for 2009 and 2010 NSDUHs, by Final Screening Result Code
Final Screening Result Code Sample Size
2009
Sample Size
2010
Weighted
Percentage
2009
Weighted
Percentage
2010
1 Examples of "Other, Ineligible" cases are those in which all residents lived in the dwelling unit for less than half of the calendar quarter and dwelling units that were listed in error.
2 "Other, Access Denied" includes all dwelling units to which the field interviewer was denied access, including locked or guarded buildings, gated communities, and other controlled access situations.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2009 and 2010.
TOTAL SAMPLE 195,132 201,865 100.00 100.00
Ineligible Cases 33,811 35,430 17.27 17.24
Eligible Cases 161,321 166,435 82.73 82.76
INELIGIBLES 33,811 35,430 17.27 17.24
10 - Vacant 18,933 19,833 55.68 55.29
13 - Not a Primary Residence 7,279 8,348 22.15 24.41
18 - Not a Dwelling Unit 2,547 2,430 7.35 6.12
22 - All Military Personnel 347 323 1.09 0.88
Other, Ineligible1 4,705 4,496 13.74 13.29
ELIGIBLE CASES 161,321 166,435 82.73 82.76
Screening Complete 143,565 147,608 88.77 88.76
30 - No One Selected 84,727 88,284 51.78 52.63
31 - One Selected 31,874 32,449 19.79 19.56
32 - Two Selected 26,964 26,875 17.20 16.57
Screening Not Complete 17,756 18,827 11.23 11.24
11 - No One Home 2,951 3,115 1.76 1.79
12 - Respondent Unavailable 451 482 0.27 0.28
14 - Physically or Mentally Incompetent 419 423 0.28 0.25
15 - Language Barrier - Hispanic 107 65 0.06 0.04
16 - Language Barrier - Other 579 505 0.41 0.33
17 - Refusal 11,910 13,045 7.60 7.83
21 - Other, Access Denied2 1,269 1,070 0.79 0.64
24 - Other, Eligible 15 16 0.01 0.01
27 - Segment Not Accessible 0 0 0.00 0.00
33 - Screener Not Returned 23 79 0.01 0.04
39 - Fraudulent Case 27 25 0.03 0.02
44 - Electronic Screening Problem 5 2 0.00 0.00

Table B.4 Weighted Percentages and Sample Sizes for 2009 and 2010 NSDUHs, by Final Interview Code
Final Interview Code 12+
Sample
Size
2009
12+
Sample
Size
2010
12+
Weighted
Percentage
2009
12+
Weighted
Percentage
2010
12-17
Sample
Size
2009
12-17
Sample
Size
2010
12-17
Weighted
Percentage
2009
12-17
Weighted
Percentage
2010
18+
Sample
Size
2009
18+
Sample
Size
2010
18+
Weighted
Percentage
2009
18+
Weighted
Percentage
2010
1 "Other" includes eligible person moved, data not received from field, too dangerous to interview, access to building denied, computer problem, and interviewed wrong household member.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2009 and 2010.
TOTAL 85,429 85,668 100.00 100.00 26,377 26,157 100.00 100.00 59,052 59,511 100.00 100.00
70 - Interview Complete 68,700 68,487 75.68 74.66 22,644 22,246 85.73 84.79 46,056 46,241 74.59 73.57
71 - No One at Dwelling Unit 1,252 1,170 1.56 1.39 202 202 0.71 0.65 1,050 968 1.65 1.46
72 - Respondent Unavailable 1,772 1,631 1.96 1.94 324 313 1.07 1.21 1,448 1,318 2.05 2.02
73 - Break-Off 21 21 0.03 0.03 4 4 0.02 0.01 17 17 0.03 0.04
74 - Physically/Mentally Incompetent 847 881 1.83 1.80 208 212 0.78 0.95 639 669 1.94 1.90
75 - Language Barrier - Hispanic 155 128 0.23 0.20 7 7 0.03 0.03 148 121 0.25 0.22
76 - Language Barrier - Other 430 413 1.08 1.15 29 20 0.11 0.11 401 393 1.18 1.26
77 - Refusal 9,498 9,929 16.15 17.20 756 756 2.92 2.87 8,742 9,173 17.60 18.74
78 - Parental Refusal 2,087 2,287 0.80 0.86 2,087 2,287 8.16 8.94 0 0 0.00 0.00
91 - Fraudulent Case 6 21 0.01 0.03 1 1 0.01 0.00 5 20 0.01 0.04
Other1 661 700 0.67 0.72 115 109 0.46 0.43 546 591 0.69 0.76

Table B.5 Response Rates and Sample Sizes for 2009 and 2010 NSDUHs, by Demographic Characteristics
Demographic Characteristic Selected Persons
2009
Selected Persons
2010
Completed
Interviews
2009
Completed
Interviews
2010
Weighted
Response Rate
2009
Weighted
Response Rate
2010
NOTE: Estimates are based on demographic information obtained from screener data and are not consistent with estimates on demographic characteristics presented in the 2009 and 2010 sets of detailed tables.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2009 and 2010.
TOTAL 85,429 85,668 68,700 68,487 75.68% 74.66%
AGE IN YEARS            
12-17 26,377 26,157 22,644 22,246 85.73% 84.79%
18-25 28,444 28,447 23,248 23,322 81.70% 81.39%
26 or Older 30,608 31,064 22,808 22,919 73.34% 72.21%
GENDER            
Male 42,008 42,116 33,282 33,164 74.21% 73.20%
Female 43,421 43,552 35,418 35,323 77.07% 76.03%
RACE/ETHNICITY            
Hispanic 12,779 13,003 10,502 10,715 78.70% 78.29%
White 56,052 55,890 44,601 44,005 75.14% 73.65%
Black 9,804 9,990 8,315 8,507 80.70% 80.25%
All Other Races 6,794 6,785 5,282 5,260 65.91% 67.14%
REGION            
Northeast 17,503 17,453 13,772 13,700 73.44% 73.29%
Midwest 23,827 24,139 19,133 19,301 75.97% 74.81%
South 25,560 25,597 20,976 20,769 77.39% 76.24%
West 18,539 18,479 14,819 14,717 74.50% 73.17%
COUNTY TYPE            
Large Metropolitan 38,216 38,141 30,160 29,831 73.97% 73.33%
Small Metropolitan 29,404 29,972 23,926 24,261 77.55% 75.94%
Nonmetropolitan 17,809 17,555 14,614 14,395 77.92% 76.72%

Table B.6 Past Year Initiates of Marijuana and Any Illicit Drug among Persons Aged 26 or Older or Aged 26 to 49: Numbers in Thousands, 2002-2010
Drug/Age Group 2002 2003 2004 2005 2006 2007 2008 2009 2010
*Low precision; no estimate reported.
a Difference between estimate and 2010 estimate is statistically significant at the .05 level.
b Difference between estimate and 2010 estimate is statistically significant at the .01 level.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2002-2010.
Marijuana, Aged 26 or Older 90a 88a 176 252 126 134 159 49b 247
Marijuana, Aged 26 to 49 90a 56b 127 122 126 121 155 49b 210
Any Illicit Drug, Aged 26 or Older 268a 324 479 579 414 326 419 430 458
Any Illicit Drug, Aged 26 to 49 251 209a 333 379 405 250 350 201a 366

Table B.7 Mean Age at First Use of Marijuana and Any Illicit Drug among Past Year Initiates Aged 26 to 49, 2002-2010
Drug 2002 2003 2004 2005 2006 2007 2008 2009 2010
*Low precision; no estimate reported.
a Difference between estimate and 2010 estimate is statistically significant at the .05 level.
b Difference between estimate and 2010 estimate is statistically significant at the .01 level.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2002-2010.
Marijuana 31.2a 29.6b 29.5b 30.4b 29.1b 32.4 32.6 32.1 36.3
Any Illicit Drug 34.8 32.8a 31.6b 34.0 33.9 32.9 35.1 31.7b 37.2

Appendix C: Other Sources of Data

A variety of surveys and data systems other than the National Survey on Drug Use and Health (NSDUH) collect data on substance use. It is useful to consider the results of these other studies when discussing NSDUH data. This appendix briefly describes several of these other data systems and presents selected comparisons with NSDUH results. In addition, this appendix describes surveys on substance use of populations not covered by NSDUH. Descriptions of these surveys are presented in alphabetical order.

When considering the information presented here, it is important to understand the methodological differences between the different surveys and the impact that these differences could have on estimates of the presence of substance use. Several studies have compared NSDUH estimates with estimates from other studies and have evaluated how differences may have been affected by differences in survey methodology (Gfroerer, Wright, & Kopstein, 1997b; Grucza, Abbacchi, Przybeck, & Gfroerer, 2007; Hennessy & Ginsberg, 2001; Miller et al., 2004). These comparisons suggest that the goals and approaches of surveys are often different, making comparisons between them difficult. Some methodological differences that have been identified as affecting comparisons include populations covered, sampling methods, modes of data collection, questionnaires, and estimation methods.

C.1 Other National Surveys of Substance Use

Behavioral Risk Factor Surveillance System (BRFSS)

The Behavioral Risk Factor Surveillance System (BRFSS)—a State-based system of health surveys—collects information on health risk behaviors, preventive health practices, and health care access primarily related to chronic disease and injury. The BRFSS surveys are cross-sectional telephone surveys conducted by State health departments with technical and methodological assistance from the Centers for Disease Control and Prevention (CDC). Every year, States conduct monthly telephone surveys of noninstitutionalized adults (aged 18 or older) using random-digit-dialing methods. Since 1994, BRFSS has collected data from all 50 States, the District of Columbia, Puerto Rico, the U.S. Virgin Islands, and Guam using a computer-assisted telephone interviewing (CATI) design. More than 350,000 adults are interviewed each year. National estimates typically are presented as medians. BRFSS includes questions on alcohol consumption and tobacco use.

NSDUH and BRFSS rates of current alcohol use have been generally similar, but NSDUH has shown consistently higher rates of binge drinking than BRFSS. The use of audio computer-assisted self-interviewing (ACASI) in NSDUH, which is considered to be more anonymous and yields higher reporting of sensitive behaviors, was offered as an explanation for the lower binge rates in BRFSS (Miller et al., 2004).

Because BRFSS uses CATI, it may yield lower reports of some sensitive behaviors than NSDUH, which employs face-to-face data collection with ACASI for questions about these behaviors. Response rates also are higher in NSDUH than BRFSS, which could have resulted in differential nonresponse bias patterns in the two surveys.

For further details, see the CDC Web site at http://www.cdc.gov/brfss/.

Harvard School of Public Health's College Alcohol Study (CAS)

The Harvard School of Public Health's College Alcohol Study (CAS) is a survey of students at 4-year colleges and universities in 40 States. It examined various issues, including heavy drinking on college campuses, the role of fraternities and sororities and athletics, the relationship of State alcohol control measures and college policies to this behavior, and the roles that access to alcohol and alcohol prices play in college alcohol use. The study also examined other high-risk behaviors among college students, including tobacco and illicit drug use, unsafe sex, and violence. Supported by The Robert Wood Johnson Foundation, CAS surveyed a random sample of students at the same colleges in 1993, 1997, 1999, and 2001. The schools and students were selected to provide nationally representative samples of schools and students. In 1993, a national sample of 195 colleges was selected from the American Council on Education's list of accredited 4-year colleges by using probability proportionate to size of enrollment; of the 195 colleges, 140 agreed to participate, for an unweighted school-level response rate of 72 percent (Wechsler, Dowdall, Davenport, & Castillo, 1995). Of these 140 colleges, 130 participated in 1997, 128 in 1999, and 120 in 2001. Student-level response rates to the two-stage mail survey were 70 percent in 1993, 59 percent in 1997 and 1999, and 52 percent in 2001. The researchers provided a short survey to nonrespondents in order to better weight the data (Wechsler et al., 2002). In 2005, sampled colleges with high levels of heavy alcohol use were surveyed again.

For further details, see the CAS Web site at http://www.hsph.harvard.edu/cas/.

Monitoring the Future (MTF)

The Monitoring the Future (MTF) study is an ongoing study of substance use trends and related attitudes among America's secondary school students, college students, and adults through age 50. The study is conducted annually by the Institute for Social Research at the University of Michigan through grants awarded by the National Institute on Drug Abuse (NIDA). The MTF and NSDUH are the Federal Government's largest and primary tools for tracking youth substance use. The MTF is composed of three substudies: (a) an annual survey of high school seniors initiated in 1975; (b) ongoing panel studies of representative samples from each graduating class that have been conducted by mail since 1976; and (c) annual surveys of 8th and 10th graders initiated in 1991. Each spring, students in the 8th, 10th, and 12th grades complete a self-administered, machine-readable questionnaire during a regular class period. Approximately 50,000 students in about 420 public and private secondary schools are surveyed annually for the cross-sectional study, and approximately 2,400 persons who participated in the survey of 12th graders are followed longitudinally. The latest MTF was conducted in 2010. The MTF provides information on the use of alcohol, illicit drugs, and tobacco.

Comparisons between the MTF estimates and estimates based on students sampled in NSDUH generally have shown NSDUH substance use prevalence levels to be lower than MTF estimates (Table C.1).14 The lower prevalences in NSDUH may be due to more underreporting in the household setting as compared with the MTF school setting. However, the MTF does not survey dropouts or include students who were absent from school on the day of the survey. NSDUH has shown dropouts to have higher rates of illicit drug use (Gfroerer et al., 1997b). Findings presented in Chapter 8 of this report generally show parallel trends in the prevalence of substance use in NSDUH and MTF for both youths and young adults.

For further details, see the MTF Web site at http://www.monitoringthefuture.org/.

National Comorbidity Survey (NCS)

The National Comorbidity Survey (NCS) was sponsored by the National Institute of Mental Health (NIMH), NIDA, and the W.T. Grant Foundation. It was designed to measure in the general population the prevalence of the illnesses described in the Diagnostic and Statistical Manual of Mental Disorders, 3rd edition revised (DSM-III-R) (American Psychiatric Association [APA], 1987). The first wave of the NCS was a household survey collecting data from 8,098 respondents aged 15 to 54 in a face-to-face interview using paper-and-pencil interviewing (PAPI). These responses were weighted to produce nationally representative estimates. A random sample of 4,414 respondents also was administered an additional module that captured information on nicotine dependence. The interviews took place between 1990 and 1992. The NCS used a modified version of the Composite International Diagnostic Interview (the University of Michigan [UM]-CIDI) to generate DSM-III-R diagnoses.

There have been several recent follow-ups to and replications of the original NCS, including a 10-year follow-up of the baseline sample (NCS-2), a replication study conducted in 2001 and 2002 with a newly recruited nationally representative sample of 9,282 respondents aged 18 or older (NCS-R), and an adolescent sample with a targeted recruitment of more than 10,000 adolescents aged 13 to 17 (NCS-A) along with their parents.

The NCS provides information on the use of alcohol, illicit drugs, and tobacco and on substance dependence or abuse. The NCS-R used an updated version of the CIDI that was designed to capture diagnoses of substance abuse or dependence using current DSM-IV criteria (APA, 1994). Interviews were conducted using computer-assisted personal interviewing (CAPI). It should be noted that in several NCS-R studies (Kessler et al., 2005a; Kessler, Chiu, Demler, Merikangas, & Walters, 2005b), the diagnosis for abuse also includes those who meet the diagnosis for dependence. In contrast, NSDUH follows DSM-IV guidelines and measures abuse and dependence separately. To make the NCS definition of abuse comparable with that of NSDUH, the rate for dependence must be subtracted from the rate for abuse. Rates of alcohol dependence or abuse and rates of illicit drug dependence or abuse were generally lower in NCS-R than in NSDUH (Kessler et al., 2003a, 2003b).

For further details, see the NCS Web site at http://www.hcp.med.harvard.edu/ncs/.

National Health Interview Survey (NHIS)

The National Health Interview Survey (NHIS) is a continuous nationwide sample survey that collects data using personal household interviews through an interviewer-administered CAPI system. The survey is sponsored by the National Center for Health Statistics (NCHS) and provides national estimates of the health status and behaviors of the civilian, noninstitutionalized population, including cigarette smoking and alcohol use among persons aged 18 or older. NHIS data have been collected since 1957. In 2009, data were derived from three core components of the survey: the Family Core, which collects information from all family members aged 18 or older in each household; the Sample Adult Core, which collects information from one adult aged 18 or older in each family; and the Sample Child Core, which collects information on youths under age 18 from a knowledgeable family member in households with a child, usually a parent. In 2009, NHIS data were based on 88,446 persons in the Family Core, 27,731 adults in the Sample Adult Core, and 11,156 children in the Sample Child Core (NCHS, Division of Health Interview Statistics, 2010).

For further details, see the NCHS Web site at http://www.cdc.gov/nchs/nhis.htm.

National Longitudinal Alcohol Epidemiologic Survey (NLAES) and National Epidemiologic Survey on Alcohol and Related Conditions (NESARC)

The National Longitudinal Alcohol Epidemiologic Survey (NLAES) was conducted in 1991 and 1992 by the U.S. Bureau of the Census for the National Institute on Alcohol Abuse and Alcoholism (NIAAA). Face-to-face, interviewer-administered interviews were conducted with 42,862 respondents aged 18 or older in the contiguous United States. Despite the survey name, the design was cross-sectional.

The National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) was conducted in 2001 and 2002, also by the U.S. Bureau of the Census for NIAAA, using a computerized interviewer-administered interview. The NESARC sample was designed to make inferences for persons aged 18 or older in the civilian, noninstitutionalized population of the United States, including Alaska, Hawaii, and the District of Columbia, and including persons living in noninstitutional group quarters. NESARC was designed to be a longitudinal survey. The first wave was conducted in 2001 and 2002, with a final sample size of 43,093 respondents aged 18 or older. The second wave was conducted in 2004 and 2005 (Grant & Dawson, 2006).

The study contains comprehensive assessments of drug use, dependence, and abuse and associated mental disorders. NESARC included an extensive set of questions, based on DSM-IV criteria (APA, 1994), designed to assess the presence of symptoms of alcohol and drug dependence and abuse in persons' lifetimes and during the prior 12 months. In addition, DSM-IV diagnoses of major mental disorders were generated using the Alcohol Use Disorder and Associated Disabilities Interview Schedule-version 4 (AUDADIS-IV), which is a structured diagnostic interview that captures major DSM-IV axis I and axis II disorders.

Research indicates that (a) prevalence estimates for substance use were generally higher in NSDUH than in NESARC; (b) rates of past year substance use disorder (SUD) for cocaine and heroin use were higher in NSDUH than in NESARC; (c) rates of past year SUD for use of alcohol, marijuana, and hallucinogens were similar between NSDUH and NESARC; and (d) prevalence estimates for past year SUD conditional on past year use were substantially lower in NSDUH for the use of marijuana, hallucinogens, and cocaine (Grucza et al., 2007). A number of methodological factors might have contributed to such discrepancies, including privacy and anonymity (questions about sensitive topics in NSDUH are self-administered, while similar questions are interviewer administered in NESARC, which may have resulted in higher use estimates in NSDUH) and differences in SUD diagnostic instrumentation (which may have resulted in higher SUD prevalence among past year substance users in NESARC).

For further details about NLAES, see Stinson et al. (1998). For an overview of NESARC findings, see Caetano (2006).

National Longitudinal Study of Adolescent Health (Add Health)

The National Longitudinal Study of Adolescent Health (Add Health) was conducted to measure the effects of family, peer group, school, neighborhood, religious institution, and community influences on health risks, such as tobacco, drug, and alcohol use. Initiated in 1994 and supported by grants from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) with cofunding from 21 other Federal agencies and foundations, Add Health is the largest, most comprehensive survey of adolescents ever undertaken.

The study began in 1994-1995 (Wave I) with an in-school questionnaire administered to a nationally representative sample of students in grades 7 to 12 and followed up with an in-home interview. In Wave I, about 90,000 students in grades 7 to 12 were surveyed at 144 schools around the United States using brief, machine-readable questionnaires during a regular class period. Interviews also were conducted with about 20,000 students and their parents in the students' homes using a combined CAPI and ACASI design. In Wave II, conducted in 1996, about 15,000 students in grades 8 to 12 were interviewed a second time in their homes. In Wave III in 2001-2002, about 15,000 of the original Add Health respondents, then aged 18 to 26, were reinterviewed to investigate how adolescent experiences and behaviors are related to outcomes during the transition to adulthood. Wave IV was conducted in 2007-2008 when the approximately 15,000 respondents were aged 24 to 32. The study provides information on the use of alcohol, illicit drugs, and tobacco.

For further details, see the Add Health Web site at http://www.cpc.unc.edu/projects/addhealth.

National Survey of Parents and Youth (NSPY)

The National Survey of Parents and Youth (NSPY) was sponsored by NIDA to evaluate the Office of National Drug Control Policy's (ONDCP's) National Youth Anti-Drug Media Campaign. NSPY was a national, household-based survey of youths aged 9 to 18 years old and their parents. Data were collected using a combination of computer-assisted interviewing technologies, including CAPI for nonsensitive portions of the survey and ACASI for the sensitive portions. The study provides information on the use of alcohol, illicit drugs, and tobacco.

NSPY employed a panel survey design with four rounds consisting of nine waves of data collection for youths between November 1999 and June 2004. Round 1 was conducted in three waves between November 1999 and June 2001 and included 8,117 youths aged 9 to 18 and 7,620 of their parents (Waves 1-3). Rounds 2, 3, and 4 were follow-up data collections, each of which was conducted in two waves. Round 2 was conducted from July 2001 to June 2002 (Waves 4-5); Round 3 was conducted from July 2002 to June 2003 (Waves 6-7); and Round 4 was conducted from July 2003 to June 2004 (Waves 8-9). Wave 9 from Round 4 was conducted between January and June 2004 with 3,143 youths and 2,381 parents.

Data from NSPY and NSDUH produced similar estimates of marijuana use for youths. For example, Wave 9 of NSPY data indicated that 16.7 percent of youths aged 12 to 18 had used marijuana in the past year, and the 2004 NSDUH yielded an estimate of 17.1 percent among this age group for this time period (Orwin et al., 2006). One explanation for the similarity in estimates is that both surveys used ACASI.

For further details about NSPY, see http://archives.drugabuse.gov/initiatives/westat/.

Partnership Attitude Tracking Study (PATS)

The Partnership Attitude Tracking Study (PATS), an annual national research study that tracks attitudes about illegal drugs, is sponsored by the Partnership for a Drug-Free America (PDFA). PATS consists of two nationally representative samples—a teenage sample for students in grades 9 through 12 and a parent sample. Adolescents complete self-administered, machine-readable questionnaires during a regular class period with their teacher remaining in the room. The latest PATS surveys of teenagers and parents were conducted in 2010. The 2010 survey of adolescents included questions about use of cigarettes, alcohol, and illicit drugs. In 2010, 2,544 teenagers were surveyed nationwide in the 22nd wave of the survey conducted since 1987, and 831 parents or caregivers of children in grades 9 to 12 were surveyed (PDFA, 2011).

In general, NSDUH estimates of substance use prevalence for adolescents are lower than PATS estimates for youths in that age group. The differences in prevalence estimates are likely to be due to the different study designs. The youth portion of PATS is a school-based survey, which may elicit more reporting of sensitive behaviors than the home-based NSDUH. In addition, the most recent PATS survey was conducted with a sample of students in the 9th through 12th grades, which was an older sample than that of the NSDUH 12- to 17-year-old sample.

For further details, see the PDFA Web site at http://www.drugfree.org/.

Youth Risk Behavior Survey (YRBS)

The Youth Risk Behavior Survey (YRBS) is a component of the CDC's Youth Risk Behavior Surveillance System (YRBSS), which measures the prevalence of six priority health risk behavior categories: (a) behaviors that contribute to unintentional injuries and violence; (b) tobacco use; (c) alcohol and other drug use; (d) sexual behaviors that contribute to unintended pregnancy and sexually transmitted diseases (STDs), including human immunodeficiency virus (HIV) infection; (e) unhealthy dietary behaviors; and (f) physical inactivity. The YRBSS includes national, State, territorial, tribal, and local school-based surveys of high school students conducted every 2 years. The national school-based survey uses a three-stage cluster sample design to produce a nationally representative sample of students in grades 9 through 12 who attend public and private schools. The State and local surveys use a two-stage cluster sample design to produce representative samples of public school students in grades 9 through 12 in their jurisdictions. The YRBS is conducted during the spring, with students completing a self-administered, machine-readable questionnaire during a regular class period. The latest YRBS was conducted in 2009. For the 2009 national YRBS, 16,410 usable questionnaires were obtained in 158 schools.

In general, the YRBS school-based survey has found higher rates of substance use for youths than those found in NSDUH (Table C.2).15 The lower prevalence rates in NSDUH are likely due to the differences in study design; specifically, the YRBS is school-based, which likely has resulted in higher rates of reported use as compared with the home-based NSDUH.

For further details, see the CDC Web site at http://www.cdc.gov/HealthyYouth/yrbs/.

C.2 Surveys of Populations Not Covered by NSDUH

Department of Defense (DoD) Survey of Health Related Behaviors Among Active Duty Military Personnel

The 2008 Department of Defense (DoD) Survey of Health Related Behaviors Among Active Duty Military Personnel was the 10th in a series of studies conducted since 1980. The sample consisted of 28,546 active-duty Armed Forces personnel worldwide who anonymously completed self-administered questionnaires that assessed substance use and other health behaviors. Members of the Coast Guard were included for the first time in the 2008 survey. (Bray et al., 2009). The survey provides information about the use of alcohol, illicit drugs, and tobacco.

In recent administrations of this survey, comparisons with NSDUH data have consistently shown that, even after accounting for demographic differences between the military and civilian populations, the military personnel had higher rates of heavy alcohol use than their civilian counterparts, similar rates of cigarette use, and lower rates of illicit drug use.

For further details, see the DoD Lifestyle Assessment Program (DLAP) Web site at https://dlap.rti.org/.

Surveys of Inmates in State and Federal Correctional Facilities (SISCF, SIFCF)

The Survey of Inmates in State Correctional Facilities (SISCF) and the Survey of Inmates in Federal Correctional Facilities (SIFCF) are conducted regularly using the same data collection instrument. The two surveys provide nationally representative data on State prison inmates and sentenced Federal inmates held in federally owned and operated facilities. The Survey of State Inmates was conducted in 1974, 1979, 1986, 1991, 1997, and 2004, and the Survey of Federal Inmates in 1991, 1997, and 2004. The 2004 SISCF was conducted for the Bureau of Justice Statistics (BJS) by the U.S. Census Bureau, which also conducted the SIFCF for the BJS and the Federal Bureau of Prisons (FBOP). Both surveys provide information about current offense and criminal history, family background and personal characteristics, prior drug and alcohol use and treatment, gun possession, and prison treatment, programs, and services. The surveys are the only national source of detailed information on criminal offenders, particularly special populations such as drug and alcohol users and offenders who have mental health problems. Systematic random sampling was used to select the inmates, and the 2004 surveys of State and Federal inmates were administered through CAPI. In 2004, 14,499 State prisoners in 287 State prisons and 3,686 Federal prisoners in 39 Federal prisons were interviewed.

Prior drug use among State prisoners remained stable on all measures between 1997 and 2004, while the percentage of Federal inmates who reported prior drug use rose on most measures (Mumola & Karberg, 2006). For the first time, half of Federal inmates reported drug use in the month before their offense. In 2004, measures of drug dependence and abuse based on criteria in DSM-IV (APA, 1994) were introduced, and 53 percent of the State and 45 percent of Federal prisoners met the DSM-IV criteria for drug abuse or dependence. The survey results indicate substantially higher rates of drug use among State and Federal prisoners as compared with NSDUH's rates for the general household population.

For further details, see BJS's "All Data Collections" Web page at http://bjs.ojp.usdoj.gov/index.cfm?ty=dca.

Table C.1 Use of Specific Substances in Lifetime, Past Year, and Past Month among 8th, 10th, and 12th Graders in MTF and NSDUH: Percentages, 2009 and 2010
Drug/Current Grade Level MTF
Lifetime
(2009)
MTF
Lifetime
(2010)
MTF
Past Year
(2009)
MTF
Past Year
(2010)
MTF
Past
Month
(2009)
MTF
Past
Month
(2010)
NSDUH
Lifetime
(2009)
NSDUH
Lifetime
(2010)
NSDUH
Past Year
(2009)
NSDUH
Past Year
(2010)
NSDUH
Past
Month
(2009)
NSDUH
Past
Month
(2010)
MTF = Monitoring the Future; NSDUH = National Survey on Drug Use and Health.
-- Not available.
NOTE: NSDUH data have been drawn from January to June of each survey year and subset to persons aged 12 to 20 to be more comparable with MTF data.
a Difference between estimate and 2010 estimate is statistically significant at the .05 level.
b Difference between estimate and 2010 estimate is statistically significant at the .01 level.
Sources: National Institute on Drug Abuse, Monitoring the Future Study, University of Michigan, 2009 and 2010. SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2009 and 2010 (January-June).
Marijuana                        
8th Grade 15.7 17.3 11.8b 13.7 6.5b 8.0 7.4 8.3 6.0 7.0 2.9 3.0
10th Grade 32.3 33.4 26.7 27.5 15.9 16.7 24.0 27.2 18.8 21.9 10.1 10.9
12th Grade 42.0 43.8 32.8 34.8 20.6 21.4 37.3 37.6 28.9 29.9 15.9 17.1
Cocaine                        
8th Grade 2.6 2.6 1.6 1.6 0.8 0.6 0.5 0.8 0.3 0.4 0.1 0.1
10th Grade 4.6 3.7 2.7 2.2 0.9 0.9 2.1 2.7 1.1 2.0 0.3 0.3
12th Grade 6.0 5.5 3.4 2.9 1.3 1.3 5.1 3.8 3.1 2.6 1.0 0.6
Inhalants                        
8th Grade 14.9 14.5 8.1 8.1 3.8 3.6 10.1 10.1 4.5 4.8 1.0 1.4
10th Grade 12.3 12.0 6.1 5.7 2.2 2.0 9.9 9.3 3.3 3.9 0.6 0.7
12th Grade 9.5 9.0 3.4 3.6 1.2 1.4 8.6 7.5 2.3 3.1 0.5 0.6
Cigarettes                        
8th Grade 20.1 20.0 -- -- 6.5 7.1 13.4 13.4 8.5 8.4 4.6 4.2
10th Grade 32.7 33.0 -- -- 13.1 13.6 28.5 29.6 19.4 21.4 11.5 12.1
12th Grade 43.6 42.2 -- -- 20.1 19.2 43.7 42.1 32.2 31.6 21.4 21.9
Alcohol                        
8th Grade 36.6 35.8 30.3 29.3 14.9 13.8 26.4 23.3 18.7 17.3 7.0 6.8
10th Grade 59.1 58.2 52.8 52.1 30.4 28.9 52.9 49.8 44.0 41.7 21.1 18.6
12th Grade 72.3 71.0 66.2 65.2 43.5a 41.2 67.9 69.2 59.4 60.2 36.7 33.8

Table C.2 Lifetime and Past Month Substance Use among Students in Grades 9 to 12 in YRBS and NSDUH: Percentages, 2005, 2007, and 2009
Substance/
Period of Use
YRBS
(2005)
YRBS
(2007)
YRBS
(2009)
NSDUH
(2005)
NSDUH
(2007)
NSDUH
(2009)
NSDUH = National Survey on Drug Use and Health; YRBS = Youth Risk Behavior Survey.
-- Not available.
NOTE: NSDUH data have been drawn from January to June of each survey year and subset to persons aged 12 to 20 to be more comparable with YRBS data. Statistical tests for the YRBS were conducted using the "Youth Online" tool (see http://www.cdc.gov/HealthyYouth/yrbs/). Results of testing for statistical significance in this table may differ from published YRBS reports of change.
a Difference between estimate and 2009 estimate is statistically significant at the .05 level.
b Difference between estimate and 2009 estimate is statistically significant at the .01 level.
Sources: Centers for Disease Control and Prevention, Youth Risk Behavior Survey, 2005, 2007, and 2009. SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, January-June for 2005, 2007, and 2009.
Marijuana            
Lifetime Use 38.4 38.1 36.8 28.1 26.3 27.6
Past Month Use 20.2 19.7 20.8 11.2 10.9 11.9
Cocaine            
Lifetime Use 7.6a 7.2 6.4 3.8a 3.8b 2.8
Past Month Use 3.4 3.3 2.8 0.8a 0.6 0.4
Ecstasy            
Lifetime Use 6.3 5.8 6.7 2.8 2.9 3.2
Past Month Use -- -- -- 0.4a 0.4a 0.8
Inhalants            
Lifetime Use 12.4 13.3a 11.7 12.0a 10.7 10.1
Past Month Use -- -- -- 1.1a 1.1b 0.6
Cigarettes            
Lifetime Use 54.3b 50.3a 46.3 39.0b 35.1 33.5
Past Month Use 23.0a 20.0 19.5 17.0b 15.4 14.7
Alcohol            
Lifetime Use 74.3 75.0 72.5 57.5 57.5 56.1
Past Month Use 43.3 44.7a 41.8 26.0 26.3 25.7

Appendix D: References

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Bray, R. M., Pemberton, M. R., Hourani, L. L., Witt, M., Rae Olmsted, K. L., Brown, J. M., Weimer, B. J., Lane, M. E., Marsden, M. E., Scheffler, S. A., Vandermaas-Peeler, R., Aspinwall, K. R., Anderson, E. M., Spagnola, K., Close, K. L., Gratton, J. L., Calvin, S. L., & Bradshaw, M. R. (2009, September). 2008 Department of Defense Survey of Health Related Behaviors Among Active Duty Military Personnel: A component of the Defense Lifestyle Assessment Program (DLAP) (RTI/10940-FR, prepared under Contract No. GS-10F-0097L, Task Order No. W81XWH-07-F-0538, for the Assistant Secretary of Defense (Health Affairs) and Task Order No. HSCG23-07-F-PMD047 for the U.S. Coast Guard). Research Triangle Park, NC: RTI International. [Available as a PDF at http://www.tricare.mil/tma/studiesEval.aspx]

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Gfroerer, J., Hughes, A., Chromy, J., Heller, D., & Packer, L. (2004, July). Estimating trends in substance use based on reports of prior use in a cross-sectional survey. In S. B. Cohen & J. M. Lepkowski (Eds.), Eighth Conference on Health Survey Research Methods: Conference proceedings [Peachtree City, GA] (HHS Publication No. PHS 04-1013, pp. 29-34). Hyattsville, MD: U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Center for Health Statistics. [Available as a PDF at http://www.cdc.gov/nchs/data/misc/proceedings_hsrm2004.pdf]

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Gfroerer, J., Wright, D., & Kopstein, A. (1997b). Prevalence of youth substance use: The impact of methodological differences between two national surveys. Drug and Alcohol Dependence, 47, 19-30.

Grant, B. F., & Dawson, D. A. (2006). Introduction to the National Epidemiologic Survey on Alcohol and Related Conditions. Alcohol Research & Health, 29, 74-78.

Grucza, R. A., Abbacchi, A. M., Przybeck, T. R., & Gfroerer, J. C. (2007). Discrepancies in estimates of prevalence and correlates of substance use and disorders between two national surveys. Addiction, 102, 623-629.

Grunbaum, J. A., Kann, L., Kinchen, S. A., Williams, B., Ross, J. G., Lowry, R., & Kolbe, L. (2002, June 28). Youth risk behavior surveillance—United States, 2001. Morbidity and Mortality Weekly Report CDC Surveillance Summaries, 51(4), 1-62. [Available at http://www.cdc.gov/mmwr/preview/mmwrhtml/ss5104a1.htm]

Han, B., Gfroerer, J., & Colliver, J. (2009, August). An examination of trends in illicit drug use among adults aged 50 to 59 in the United States: An OAS Data Review. Rockville, MD: U.S. Department of Health and Human Services, Substance Abuse and Mental Health Services Administration, Office of Applied Studies.

Harrison, L., & Hughes, A. (Eds.). (1997). The validity of self-reported drug use: Improving the accuracy of survey estimates (NIH Publication No. 97-4147, NIDA Research Monograph 167). Rockville, MD: National Institute on Drug Abuse. [Available as a PDF at http://www.drugabuse.gov/pdf/monographs/monograph167/download167.html]

Harrison, L. D., Martin, S. S., Enev, T., & Harrington, D. (2007). Comparing drug testing and self-report of drug use among youths and young adults in the general population (HHS Publication No. SMA 07-4249, Methodology Series M-7). Rockville, MD: Substance Abuse and Mental Health Services Administration, Office of Applied Studies.

Hawkins, J. D., Catalano, R. F., & Miller, J. Y. (1992). Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: Implications for substance abuse prevention. Psychological Bulletin, 112(1), 64-105.

Hennessy, K. H., & Ginsberg, C. (Eds.). (2001). Substance use survey data collection methodologies and selected papers [Special issue]. Journal of Drug Issues, 31(3), 595-808.

Hughes, A., Muhuri, P., Sathe, N., & Spagnola, K. (2011). State estimates of substance use and mental disorders from the 2008-2009 National Surveys on Drug Use and Health (HHS Publication No. SMA 11-4641, NSDUH Series H-40). Rockville, MD: Substance Abuse and Mental Health Services Administration, Center for Behavioral Health Statistics and Quality.

Johnston, L. D., O'Malley, P. M., Bachman, J. G., & Schulenberg, J. E. (2010). Monitoring the Future national survey results on drug use, 1975-2009: Secondary school students (NIH Publication No. 10-7584, Vol. I). Bethesda, MD: National Institute on Drug Abuse.

Johnston, L. D., O'Malley, P. M., Bachman, J. G., & Schulenberg, J. E. (2011a). Monitoring the Future national results on adolescent drug use: Overview of key findings, 2010. Bethesda, MD: National Institute on Drug Abuse.

Johnston, L. D., O'Malley, P. M., Bachman, J. G., & Schulenberg, J. E. (2011b). Monitoring the Future national survey results on drug use, 1975-2010: Secondary school students (Vol. I). Bethesda, MD: National Institute on Drug Abuse.

Kessler, R. C., Barker, P. R., Colpe, L. J., Epstein, J. F., Gfroerer, J. C., Hiripi, E., Howes, M. J., Normand, S. L., Manderscheid, R. W., Walters, E. E., & Zaslavsky, A. M. (2003a). Screening for serious mental illness in the general population. Archives of General Psychiatry, 60, 184-189.

Kessler, R. C., Berglund, P., Demler, O., Jin, R., Koretz, D., Merikangas, K. R., Rush, A. J., Walters, E. E., & Wang, P. S. (2003b). The epidemiology of major depressive disorder: Results from the National Comorbidity Survey Replication (NCS-R). Journal of the American Medical Association, 289, 3095-3105.

Kessler, R. C., Berglund, P., Demler, O., Jin, R., Merikangas, K. R., & Walters, E. E. (2005a). Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry, 62, 593-602.

Kessler, R. C., Chiu, W. T., Demler, O., Merikangas, K. R., & Walters, E. E. (2005b). Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Archives of General Psychiatry, 62, 617-627.

Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33, 159-174.

Manly, B. F. J. (1986). Multivariate statistical methods: A primer. London, England: Chapman and Hall.

Miller, J. W., Gfroerer, J. C., Brewer, R. D., Naimi, T. S., Mokdad, A., & Giles, W. H. (2004). Prevalence of adult binge drinking: A comparison of two national surveys. American Journal of Preventive Medicine, 27, 197-204.

Morton, K. B., Martin, P. C., Chromy, J. R., Hirsch, E. L., & Ridenhour, J. L. (2011, January 31). Sample design report. In 2010 National Survey on Drug Use and Health: Methodological resource book (Section 2, prepared for the Substance Abuse and Mental Health Services Administration, Center for Behavioral Health Statistics and Quality, formerly the Office of Applied Studies, under Contract No. HHSS283200800004C, Phase I, Deliverable No. 8, RTI/0211838.103.004). Research Triangle Park, NC: RTI International.

Mumola, C. J., & Karberg, J. C. (2006, October [revised January 19, 2007]). Drug use and dependence, State and Federal prisoners, 2004 (NCJ 213530, BJS Special Report). Washington, DC: U.S. Department of Justice, Office of Justice Programs, Bureau of Justice Statistics. [Available as a PDF at http://bjs.ojp.usdoj.gov/index.cfm?ty=pbdetail&iid=778]

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Appendix E: List of Contributors

This National Survey on Drug Use and Health (NSDUH) report was prepared by the Center for Behavioral Health Statistics and Quality (CBHSQ), Substance Abuse and Mental Health Services Administration (SAMHSA), U.S. Department of Health and Human Services (HHS), and by RTI International (a trade name of Research Triangle Institute), Research Triangle Park, North Carolina. Work by RTI was performed under Contract No. HHSS283200800004C.

Contributors at SAMHSA listed alphabetically, with chapter authorship noted, include Peggy Barker, Jonaki Bose (Chapter 1), Joseph Gfroerer (Chapter 8), Beth Han (Chapter 7), Sarra L. Hedden, Arthur Hughes (Chapter 5), Michael Jones (Project Officer) (Chapter 4), Joel Kennet (Chapter 3), Pradip Muhuri (Chapter 6), Dicy Painter, and Peter Tice (Chapter 2).

Contributors and reviewers at RTI listed alphabetically include Jeremy Aldworth, Stephanie Barnett, Ellen Bishop, Patrick Chen, James R. Chromy, Elizabeth Copello, G. Lance Couzens, Devon S. Cribb, Christine Davies, Teresa R. Davis, Ralph E. Folsom, Jr., Misty Foster, Peter Frechtel, Julia Gable, Jennifer Gratton, Wafa Handley, David C. Heller, Erica Hirsch, David Cunningham Hunter, Ilona Johnson, Phillip S. Kott, Larry A. Kroutil, Mary Ellen Marsden, Martin Meyer, Andrew Moore, Katherine B. Morton, N. Ben Neely, Scott Novak, Lisa E. Packer, Michael Pemberton, Jeremy Porter, Harley Rohloff, Victoria Scott, Kathryn Spagnola, Thomas G. Virag (Project Director), Jiantong (Jean) Wang, Lauren Warren, and Ryan Whitworth.

Also at RTI, report and Web production staff listed alphabetically include Teresa G. Bass, Kimberly Cone, Valerie Garner, Richard Hair, Andrew Jessup, Shari B. Lambert, Farrah Bullock Mann, Brenda K. Porter, Pamela Couch Prevatt, Melissa Reid, Roxanne Snaauw, Richard S. Straw, Pamela Tuck, and Cheryl Velez. Final report production was managed by Christine Hager and Jane Feldman at SAMHSA.


End Notes

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

2 Prior to 2002, the survey was known as the National Household Survey on Drug Abuse (NHSDA).

3 SAE is a hierarchical Bayes modeling technique used to make State-level estimates for approximately 20 measures related to substance use. For more details, see the State Estimates of Substance Use and Mental Disorders from the 2008-2009 National Surveys on Drug Use and Health (Hughes, Muhuri, Sathe, & Spagnola, 2011).

4 Sampling areas were defined using 2000 census geography. Counts of dwelling units (DUs) and population totals were obtained from the 2000 census data supplemented with revised population counts from Nielsen Claritas.

5 Census tracts are relatively permanent statistical subdivisions of counties and provide a stable set of geographic units across decennial census periods.

6 Some census tracts had to be aggregated in order to meet the minimum DU requirement of 150 DUs in urban areas and 100 DUs in rural areas.

7 This comprehensive set of tables is available at http://www.samhsa.gov/data/population-data-nsduh.

8 Available at http://www.samhsa.gov/data/population-data-nsduh.

9 A successfully screened household is one in which all screening questionnaire items were answered by an adult resident of the household and either zero, one, or two household members were selected for the NSDUH interview.

10 The usable case rule requires that a respondent answer "yes" or "no" to the question on lifetime use of cigarettes and "yes" or "no" to at least nine additional lifetime use questions.

11 Prior to 2002, NSDUH was known as the National Household Survey on Drug Abuse (NHSDA).

12 Substances include alcohol, marijuana, cocaine, heroin, hallucinogens, inhalants, pain relievers, tranquilizers, stimulants, and sedatives.

13 See Section B.4.8 in the Results from the 2008 National Survey on Drug Use and Health: National Findings (OAS, 2009) for the methamphetamine analysis decisions.

14 To examine estimates that are comparable with MTF data, NSDUH estimates presented in Table C.1 are based on data collected in the first 6 months of the survey year and are subset to ages 12 to 20.

15 To examine estimates that are comparable with YRBS data, NSDUH estimates presented in Table C.2 are based on data collected in the first 6 months of the survey year and are subset to ages 12 to 20.


Long Descriptions – Figures and Equations

Figures

Chapter 1

Long description, Figure 1.1. Figure 1.1 is titled "U.S. Census Bureau Regions." It is map of the United States divided into the four U.S. Census Bureau regions: Northeast, South, Midwest, and West.

The Northeast region is made up of Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and Vermont.

The South region is made up of Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia.

The Midwest region is made up of Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin.

The West region is made up of Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming.

Long description end. Return to Figure 1.1.

Chapter 2

Long description, Figure 2.1. Figure 2.1 is titled "Past Month Illicit Drug Use among Persons Aged 12 or Older: 2010." It is a bar graph, where the numbers in millions of past month users are shown on the horizontal axis and seven drug categories (illicit drugs, marijuana, psychotherapeutics, cocaine, hallucinogens, inhalants, and heroin) are shown on the vertical axis. There is a footnote on the illicit drugs row that says, "Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used nonmedically."

The number of persons who used illicit drugs in the past month was 22.6 million.

The number of persons who used marijuana in the past month was 17.4 million.

The number of persons who used psychotherapeutics in the past month was 7.0 million.

The number of persons who used cocaine in the past month was 1.5 million.

The number of persons who used hallucinogens in the past month was 1.2 million.

The number of persons who used inhalants in the past month was 0.7 million.

The number of persons who used heroin in the past month was 0.2 million.

Long description end. Return to Figure 2.1.

Long description, Figure 2.2. Figure 2.2 is titled "Past Month Use of Selected Illicit Drugs among Persons Aged 12 or Older: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage using in the past month is shown on the vertical axis. For each of the five drug categories (illicit drugs, marijuana, psychotherapeutics, cocaine, and hallucinogens), there is a line showing use over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

The prevalence of past month illicit drug use was 8.3 percent in 2002, 8.2 percent in 2003, 7.9 percent in 2004, 8.1 percent in 2005, 8.3 percent in 2006, 8.0 percent in both 2007 and 2008, 8.7 percent in 2009, and 8.9 percent in 2010. The differences between the 2010 estimate and the 2002 through 2008 estimates were statistically significant.

The prevalence of past month marijuana use was 6.2 percent in both 2002 and 2003, 6.1 percent in 2004, 6.0 percent in both 2005 and 2006, 5.8 percent in 2007, 6.1 percent in 2008, 6.6 percent in 2009, and 6.9 percent in 2010. The differences between the 2010 estimate and the 2002 through 2008 estimates were statistically significant.

The prevalence of past month psychotherapeutic use was 2.7 percent in both 2002 and 2003, 2.5 percent in 2004, 2.7 percent in 2005, 2.9 percent in 2006, 2.8 percent in 2007, 2.5 percent in 2008, 2.8 percent in 2009, and 2.7 percent in 2010.

The prevalence of past month cocaine use was 0.9 percent in 2002, 1.0 percent in 2003, 0.8 percent in 2004, 1.0 percent in both 2005 and 2006, 0.8 percent in 2007, 0.7 percent in both 2008 and 2009, and 0.6 percent in 2010. The differences between the 2010 estimate and the 2002 through 2008 estimates were statistically significant.

The prevalence of past month hallucinogen use was 0.5 percent in 2002; 0.4 percent in 2003, 2004, 2005, 2006, 2007, and 2008; and 0.5 percent in both 2009 and 2010. The difference between the 2010 estimate and the 2004 estimate was statistically significant.

Long description end. Return to Figure 2.2.

Long description, Figure 2.3. Figure 2.3 is titled "Past Month Nonmedical Use of Types of Psychotherapeutic Drugs among Persons Aged 12 or Older: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage using in the past month is shown on the vertical axis. For each of the four psychotherapeutic drug categories (pain relievers, tranquilizers, stimulants, and sedatives), there is a line showing use over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

The prevalence of past month use of pain relievers was 1.9 percent in 2002, 2.0 percent in 2003, 1.8 percent in 2004, 1.9 percent in 2005, 2.1 percent in both 2006 and 2007, 1.9 percent in 2008, 2.1 percent in 2009, and 2.0 percent in 2010.

The prevalence of past month use of tranquilizers was 0.8 percent in both 2002 and 2003; 0.7 percent in 2004, 2005, 2006, 2007, and 2008; 0.8 percent in 2009; and 0.9 percent in 2010. The difference between the 2010 estimate and the 2004 estimate was statistically significant.

The prevalence of past month use of stimulants was 0.6 percent in both 2002 and 2003, 0.5 percent in both 2004 and 2005, 0.6 percent in 2006, 0.4 percent in both 2007 and 2008, 0.5 percent in 2009, and 0.4 percent in 2010. The differences between the 2010 estimate and the 2002, 2003, 2004, and 2006 estimates were statistically significant.

The prevalence of past month use of sedatives was 0.2 percent in 2002; 0.1 percent in 2003, 2004, and 2005; 0.2 percent in 2006; and 0.1 percent in 2007, 2008, 2009, and 2010.

Long description end. Return to Figure 2.3.

Long description, Figure 2.4. Figure 2.4 is titled "Past Month Illicit Drug Use among Persons Aged 12 or Older, by Age: 2009 and 2010." It is a bar graph, where survey years and 14 categories of age in years are shown on the horizontal axis and the percentage using illicit drugs in the past month is shown on the vertical axis. Tests of statistical significance at the .05 level were performed between 2010 and 2009; significant results are indicated where appropriate.

Among 12 or 13 year olds, the prevalence of past month illicit drug use was 3.6 percent in 2009 and 4.0 percent in 2010.

Among 14 or 15 year olds, the prevalence of past month illicit drug use was 9.0 percent in 2009 and 9.3 percent in 2010.

Among 16 or 17 year olds, the prevalence of past month illicit drug use was 16.7 percent in 2009 and 16.6 percent in 2010.

Among 18 to 20 year olds, the prevalence of past month illicit drug use was 22.2 percent in 2009 and 23.1 percent in 2010.

Among 21 to 25 year olds, the prevalence of past month illicit drug use was 20.5 percent in both 2009 and 2010.

Among 26 to 29 year olds, the prevalence of past month illicit drug use was 14.4 percent in 2009 and 14.8 percent in 2010.

Among 30 to 34 year olds, the prevalence of past month illicit drug use was 10.5 percent in 2009 and 12.9 percent in 2010. This difference was statistically significant.

Among 35 to 39 year olds, the prevalence of past month illicit drug use was 8.0 percent in 2009 and 8.1 percent in 2010.

Among 40 to 44 year olds, the prevalence of past month illicit drug use was 6.5 percent in 2009 and 6.9 percent in 2010.

Among 45 to 49 year olds, the prevalence of past month illicit drug use was 6.5 percent in 2009 and 7.2 percent in 2010.

Among 50 to 54 year olds, the prevalence of past month illicit drug use was 6.9 percent in 2009 and 7.2 percent in 2010.

Among 55 to 59 year olds, the prevalence of past month illicit drug use was 5.4 percent in 2009 and 4.1 percent in 2010.

Among 60 to 64 year olds, the prevalence of past month illicit drug use was 3.1 percent in 2009 and 2.7 percent in 2010.

Among persons aged 65 or older, the prevalence of past month illicit drug use was 0.9 percent in 2009 and 1.1 percent in 2010.

Long description end. Return to Figure 2.4.

Long description, Figure 2.5. Figure 2.5 is titled "Past Month Illicit Drug Use among Persons Aged 12 or Older, by Age: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage using in the past month is shown on the vertical axis. For each of the three age groups (12 to 17, 18 to 25, and 26 or older), there is a line showing use over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

The prevalence of youths aged 12 to 17 using illicit drugs in the past month was 11.6 percent in 2002, 11.2 percent in 2003, 10.6 percent in 2004, 9.9 percent in 2005, 9.8 percent in 2006, 9.5 percent in 2007, 9.3 percent in 2008, 10.0 percent in 2009, and 10.1 percent in 2010. The differences between the 2010 estimate and the 2002, 2003, and 2008 estimates were statistically significant.

The prevalence of past month illicit drug use among young adults aged 18 to 25 was 20.2 percent in 2002, 20.3 percent in 2003, 19.4 percent in 2004, 20.1 percent in 2005, 19.8 percent in 2006, 19.7 percent in 2007, 19.6 percent in 2008, 21.2 percent in 2009, and 21.5 percent in 2010. The differences between the 2010 estimate and the 2002 through 2008 estimates were statistically significant.

The prevalence of past month illicit drug use among adults aged 26 or older was  percent in 2002, 5.6 percent in 2003, 5.5 percent in 2004, 5.8 percent in 2005, 6.1 percent in 2006, 5.8 percent in 2007, 5.9 percent in 2008, 6.3 percent in 2009, and 6.6 percent in 2010. The differences between the 2010 estimate and the 2002, 2003, 2004, 2005, 2007, and 2008 estimates were statistically significant.

Long description end. Return to Figure 2.5.

Long description, Figure 2.6. Figure 2.6 is titled "Past Month Use of Selected Illicit Drugs among Youths Aged 12 to 17: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage using in the past month is shown on the vertical axis. For each of the five drug categories (illicit drugs, marijuana, psychotherapeutics, inhalants, and hallucinogens), there is a line showing use over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

The prevalence of youths aged 12 to 17 using illicit drugs in the past month was 11.6 percent in 2002, 11.2 percent in 2003, 10.6 percent in 2004, 9.9 percent in 2005, 9.8 percent in 2006, 9.5 percent in 2007, 9.3 percent in 2008, 10.0 percent in 2009, and 10.1 percent in 2010. The differences between the 2010 estimate and the 2002, 2003, and 2008 estimates were statistically significant.

The prevalence of youths aged 12 to 17 using marijuana in the past month was 8.2 percent in 2002; 7.9 percent in 2003; 7.6 percent in 2004; 6.8 percent in 2005; 6.7 percent in 2006, 2007, and 2008; 7.3 percent in 2009; and 7.4 percent in 2010. The differences between the 2010 estimate and the 2002, 2006, 2007, and 2008 estimates were statistically significant.

The prevalence of youths aged 12 to 17 using psychotherapeutics in the past month was 4.0 percent in both 2002 and 2003; 3.6 percent in 2004; 3.3 percent in 2005, 2006, and 2007; 2.9 percent in 2008; 3.1 percent in 2009; and 3.0 percent in 2010. The differences between the 2010 estimate and the 2002, 2003, and 2004 estimates were statistically significant.

The prevalence of youths aged 12 to 17 using inhalants in the past month was 1.2 percent in 2002, 1.3 percent in 2003, 1.2 percent in both 2004 and 2005, 1.3 percent in 2006, 1.2 percent in 2007, 1.1 percent in 2008, 1.0 percent in 2009, and 1.1 percent in 2010.

The prevalence of youths aged 12 to 17 using hallucinogens in the past month was 1.0 percent in both 2002 and 2003, 0.8 percent in both 2004 and 2005, 0.7 percent in both 2006 and 2007, 1.0 percent in 2008, and 0.9 percent in both 2009 and 2010.

Long description end. Return to Figure 2.6.

Long description, Figure 2.7. Figure 2.7 is titled "Past Month Use of Selected Illicit Drugs among Young Adults Aged 18 to 25: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage using in the past month is shown on the vertical axis. For each of the five drug categories (illicit drugs, marijuana, psychotherapeutics, cocaine, and hallucinogens), there is a line showing use over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

The prevalence of past month illicit drug use among young adults aged 18 to 25 was 20.2 percent in 2002, 20.3 percent in 2003, 19.4 percent in 2004, 20.1 percent in 2005, 19.8 percent in 2006, 19.7 percent in 2007, 19.6 percent in 2008, 21.2 percent in 2009, and 21.5 percent in 2010. The differences between the 2010 estimate and the 2002 through 2008 estimates were statistically significant.

The prevalence of past month marijuana use among young adults aged 18 to 25 was 17.3 percent in 2002, 17.0 percent in 2003, 16.1 percent in 2004, 16.6 percent in 2005, 16.3 percent in 2006, 16.4 percent in 2007, 16.5 percent in 2008, 18.1 percent in 2009, and 18.5 percent in 2010. The differences between the 2010 estimate and the 2002 through 2008 estimates were statistically significant.

The prevalence of past month psychotherapeutic use among young adults aged 18 to 25 was 5.5 percent in 2002, 6.1 percent in both 2003 and 2004, 6.3 percent in 2005, 6.5 percent in 2006, 6.0 percent in 2007, 5.9 percent in 2008, 6.3 percent in 2009, and 5.9 percent in 2010.

The prevalence of past month cocaine use among young adults aged 18 to 25 was 2.0 percent in 2002, 2.2 percent in 2003, 2.1 percent in 2004, 2.6 percent in 2005, 2.2 percent in 2006, 1.7 percent in 2007, 1.5 percent in 2008, 1.4 percent in 2009, 1.5 percent in 2010. The differences between the 2010 estimate and the 2002 through 2006 estimates were statistically significant.

The prevalence of past month hallucinogen use among young adults aged 18 to 25 was 1.9 percent in 2002, 1.7 percent in 2003, 1.5 percent in both 2004 and 2005, 1.7 percent in 2006, 1.5 percent in 2007, 1.7 percent in 2008, 1.8 percent in 2009, and 2.0 percent in 2010. The differences between the 2010 estimate and the 2004, 2005, and 2007 estimates were statistically significant.

Long description end. Return to Figure 2.7.

Long description, Figure 2.8. Figure 2.8 is titled "Past Month Illicit Drug Use among Adults Aged 50 to 59: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage using in the past month is shown on the vertical axis. For each age group (50 to 59, 50 to 54, and 55 to 59), there is a line showing use over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

Among adults aged 50 to 59, the percentage using illicit drugs in the past month was 2.7 percent in 2002, 3.1 percent in 2003, 3.8 percent in 2004, 4.4 percent in 2005, 4.3 percent in 2006, 5.0 percent in 2007, 4.6 percent in 2008, 6.2 percent in 2009, and 5.8 percent in 2010. The differences between the 2010 estimate and the 2002, 2003, and 2004 estimates were statistically significant.

Among adults aged 50 to 54, the percentage using illicit drugs in the past month was 3.4 percent in 2002, 3.9 percent in 2003, 4.8 percent in 2004, 5.2 percent in 2005, 6.0 percent in 2006, 5.7 percent in 2007, 4.3 percent in 2008, 6.9 percent in 2009, and 7.2 percent in 2010. The differences between the 2010 estimate and the 2002, 2003, 2004, and 2008 estimates were statistically significant.

Among adults aged 55 to 59, the percentage using illicit drugs in the past month was 1.9 percent in 2002, 2.0 percent in 2003, 2.6 percent in 2004, 3.4 percent in 2005, 2.4 percent in 2006, 4.1 percent in 2007, 5.0 percent in 2008, 5.4 percent in 2009, and 4.1 percent in 2010. The differences between the 2010 estimate and the 2002, 2003, and 2006 estimates were statistically significant.

Long description end. Return to Figure 2.8.

Long description, Figure 2.9. Figure 2.9 is titled "Past Month Marijuana Use among Youths Aged 12 to 17, by Gender: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage using in the past month is shown on the vertical axis. For each gender, there is a line showing use over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

Among males aged 12 to 17, the percentage using marijuana in the past month was 9.1 percent in 2002, 8.6 percent in 2003, 8.1 percent in 2004, 7.5 percent in 2005, 6.8 percent in 2006, 7.5 percent in 2007, 7.3 percent in 2008, and 8.3 percent in both 2009 and 2010. The differences between the 2010 estimate and the 2006 and 2008 estimates were statistically significant.

Among females aged 12 to 17, the percentage using marijuana in the past month was 7.2 percent in both 2002 and 2003, 7.1 percent in 2004, 6.2 percent in 2005, 6.4 percent in 2006, 5.8 percent in 2007, 6.0 percent in 2008, 6.3 percent in 2009, and 6.4 percent in 2010.

Long description end. Return to Figure 2.9.

Long description, Figure 2.10. Figure 2.10 is titled "Past Month Illicit Drug Use among Persons Aged 12 or Older, by Race/Ethnicity: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage using in the past month is shown on the vertical axis. For each race/ethnicity category (black or African American, white, Hispanic or Latino, and Asian), there is a line showing use over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate. There is a note below the figure that says, "Sample sizes for American Indians or Alaska Natives and for persons of two or more races were too small for reliable trend presentation for these groups. Due to low precision, estimates for Native Hawaiians or Other Pacific Islanders are not shown."

Among blacks or African Americans, the percentage using illicit drugs in the past month was 9.7 percent in 2002, 8.7 percent in both 2003 and 2004, 9.7 percent in 2005, 9.8 percent in 2006, 9.5 percent in 2007, 10.1 percent in 2008, 9.6 percent in 2009, and 10.7 percent in 2010. The differences between the 2010 estimate and the 2003 and 2004 estimates were statistically significant.

Among whites, the percentage using illicit drugs in the past month was 8.5 percent in 2002, 8.3 percent in 2003, 8.1 percent in both 2004 and 2005, 8.5 percent in 2006, 8.2 percent in both 2007 and 2008, 8.8 percent in 2009, and 9.1 percent in 2010. The differences between the 2010 estimate and the 2003, 2004, 2005, 2007, and 2008 estimates were statistically significant.

Among Hispanics or Latinos, the percentage using illicit drugs in the past month was 7.2 percent in 2002, 8.0 percent in 2003, 7.2 percent in 2004, 7.6 percent in 2005, 6.9 percent in 2006, 6.6 percent in 2007, 6.2 percent in 2008, 7.9 percent in 2009, and 8.1 percent in 2010. The differences between the 2010 estimate and the 2007 and 2008 estimates were statistically significant.

Among Asians, the percentage using illicit drugs in the past month was 3.5 percent in 2002, 3.8 percent in 2003, 3.1 percent in both 2004 and 2005, 3.6 percent in 2006, 4.2 percent in 2007, 3.6 percent in 2008, 3.7 percent in 2009, and 3.5 percent in 2010.

Long description end. Return to Figure 2.10.

Long description, Figure 2.11. Figure 2.11 is titled "Past Month Illicit Drug Use among Persons Aged 18 or Older, by Employment Status: 2009 and 2010." There are two bar graphs, one for rates of use and one for the number of users. Employment status is shown on the horizontal axis in both graphs. The percentage using illicit drugs in the past month is shown on the vertical axis of the rates of use graph, and the number of users in millions is shown on the vertical axis of the number of users' graph. There is a separate bar for the 2009 and 2010 survey years within each employment status category. The four employment statuses are full time, part time, unemployed, and other. There is a footnote on the "Other" bar that says, "The Other Employment category includes retired persons, disabled persons, homemakers, students, or other persons not in the labor force." Tests of statistical significance at the .05 level were performed between 2010 and 2009; no differences were significant.

The prevalence of past month illicit drug use among those employed full time was 8.0 percent (9.2 million) in 2009 and 8.4 percent (9.6 million) in 2010.

The prevalence of past month illicit drug use among those employed part time was 11.5 percent (3.6 million) in 2009 and 11.2 percent (3.7 million) in 2010.

The prevalence of past month illicit drug use among those unemployed was 17.0 percent (2.5 million) in 2009 and 17.5 percent (2.6 million) in 2010.

The prevalence of past month illicit drug use among those with other employment status was 6.0 percent (4.0 million) in 2009 and 6.4 percent (4.3 million) in 2010.

Long description end. Return to Figure 2.11.

Long description, Figure 2.12. Figure 2.12 is titled "Past Month Illicit Drug Use among Persons Aged 12 or Older, by County Type: 2010." It is a bar graph, where county type is shown on the horizontal axis and the percentage using in the past month is shown on the vertical axis. The five county types are large metropolitan, small metropolitan, nonmetropolitan urbanized, nonmetropolitan less urbanized, and nonmetropolitan completely rural.

The percentage of persons aged 12 or older in the large metropolitan county type using illicit drugs in the past month was 9.4 percent.

The percentage of persons aged 12 or older in the small metropolitan county type using illicit drugs in the past month was 8.8 percent.

The percentage of persons aged 12 or older in the nonmetropolitan urbanized county type using illicit drugs in the past month was 8.7 percent.

The percentage of persons aged 12 or older in the nonmetropolitan less urbanized county type using illicit drugs in the past month was 7.1 percent.

The percentage of persons aged 12 or older in the nonmetropolitan completely rural county type using illicit drugs in the past month was 3.7 percent.

Long description end. Return to Figure 2.12.

Chapter 3

Long description, Figure 3.1. Figure 3.1 is titled "Current, Binge, and Heavy Alcohol Use among Persons Aged 12 or Older, by Age: 2010." It is a bar graph, where age in years is shown on the horizontal axis and the percentage using in the past month is shown on the vertical axis. There are 14 age categories, and for each age category, the bar is divided into three sections corresponding to three types of alcohol use: (1) current alcohol use, which does not include binge use or heavy use; (2) binge alcohol use, which does not include heavy use; and (3) heavy alcohol use. Individual estimates may not sum to the total due to rounding.

Among 12 or 13 year olds, 3.1 percent were past month alcohol users; of these, 2.1 percent were current alcohol users (non-binge and non-heavy use), 0.9 percent were binge alcohol users (non-heavy use), and 0.1 percent were heavy alcohol users.

Among 14 or 15 year olds, 12.4 percent were past month alcohol users; of these, 5.6 percent were current alcohol users (non-binge and non-heavy use), 5.5 percent were binge alcohol users (non-heavy use), and 1.2 percent were heavy alcohol users.

Among 16 or 17 year olds, 24.6 percent were past month alcohol users; of these, 9.3 percent were current alcohol users (non-binge and non-heavy use), 11.7 percent were binge alcohol users (non-heavy use), and 3.6 percent were heavy alcohol users.

Among 18 to 20 year olds, 48.9 percent were past month alcohol users; of these, 15.6 percent were current alcohol users (non-binge and non-heavy use), 22.0 percent were binge alcohol users (non-heavy use), and 11.3 percent were heavy alcohol users.

Among 21 to 25 year olds, 70.0 percent were past month alcohol users; of these, 24.5 percent were current alcohol users (non-binge and non-heavy use), 30.3 percent were binge alcohol users (non-heavy use), and 15.2 percent were heavy alcohol users.

Among 26 to 29 year olds, 65.3 percent were past month alcohol users; of these, 26.7 percent were current alcohol users (non-binge and non-heavy use), 27.2 percent were binge alcohol users (non-heavy use), and 11.4 percent were heavy alcohol users.

Among 30 to 34 year olds, 63.9 percent were past month alcohol users; of these, 29.3 percent were current alcohol users (non-binge and non-heavy use), 25.3 percent were binge alcohol users (non-heavy use), and 9.3 percent were heavy alcohol users.

Among 35 to 39 year olds, 60.5 percent were past month alcohol users; of these, 31.9 percent were current alcohol users (non-binge and non-heavy use), 20.8 percent were binge alcohol users (non-heavy use), and 7.8 percent were heavy alcohol users.

Among 40 to 44 year olds, 61.1 percent were past month alcohol users; of these, 34.6 percent were current alcohol users (non-binge and non-heavy use), 19.0 percent were binge alcohol users (non-heavy use), and 7.5 percent were heavy alcohol users.

Among 45 to 49 year olds, 58.9 percent were past month alcohol users; of these, 34.0 percent were current alcohol users (non-binge and non-heavy use), 17.7 percent were binge alcohol users (non-heavy use), and 7.2 percent were heavy alcohol users.

Among 50 to 54 year olds, 57.6 percent were past month alcohol users; of these, 37.0 percent were current alcohol users (non-binge and non-heavy use), 14.6 percent were binge alcohol users (non-heavy use), and 6.0 percent were heavy alcohol users.

Among 55 to 59 year olds, 52.7 percent were past month alcohol users; of these, 35.8 percent were current alcohol users (non-binge and non-heavy use), 11.7 percent were binge alcohol users (non-heavy use), and 5.2 percent were heavy alcohol users.

Among 60 to 64 year olds, 51.6 percent were past month alcohol users; of these, 37.8 percent were current alcohol users (non-binge and non-heavy use), 10.5 percent were binge alcohol users (non-heavy use), and 3.3 percent were heavy alcohol users.

Among persons aged 65 or older, 38.2 percent were past month alcohol users; of these, 30.7 percent were current alcohol users (non-binge and non-heavy use), 5.9 percent were binge alcohol users (non-heavy use), and 1.6 percent were heavy alcohol users.

Long description end. Return to Figure 3.1.

Long description, Figure 3.2. Figure 3.2 is titled "Current, Binge, and Heavy Alcohol Use among Persons Aged 12 or Older, by Race/Ethnicity: 2010." It is a bar graph, where race/ethnicity is shown on the horizontal axis and the percentage using in the past month is shown on the vertical axis. The six categories of race/ethnicity are (1) white, (2) black or African American, (3) American Indian or Alaska Native, (4) Asian, (5) two or more races, and (6) Hispanic or Latino. For each race/ethnicity category, the bar is divided into three sections corresponding to three types of alcohol use: (1) current alcohol use, which does not include binge use or heavy use; (2) binge alcohol use, which does not include heavy use; and (3) heavy alcohol use. Individual estimates may not sum to the total due to rounding. There is a note below the figure that says, "Due to low precision, estimates for Native Hawaiians or Other Pacific Islanders are not shown."

Among whites, 56.7 percent were past month alcohol users; of these, 32.8 percent were current alcohol users (non-binge and non-heavy use), 16.3 percent were binge alcohol users (non-heavy use), and 7.7 percent were heavy alcohol users.

Among blacks or African Americans, 42.8 percent were past month alcohol users; of these, 23.1 percent were current alcohol users (non-binge and non-heavy use), 15.3 percent were binge alcohol users (non-heavy use), and 4.5 percent were heavy alcohol users.

Among American Indians or Alaska Natives, 36.6 percent were past month alcohol users; of these, 11.8 percent were current alcohol users (non-binge and non-heavy use), 17.9 percent were binge alcohol users (non-heavy use), and 6.9 percent were heavy alcohol users.

Among Asians, 38.4 percent were past month alcohol users; of these, 26.0 percent were current alcohol users (non-binge and non-heavy use), 9.9 percent were binge alcohol users (non-heavy use), and 2.4 percent were heavy alcohol users.

Among persons of two or more races, 45.2 percent were past month alcohol users; of these, 23.7 percent were current alcohol users (non-binge and non-heavy use), 15.7 percent were binge alcohol users (non-heavy use), and 5.8 percent were heavy alcohol users.

Among Hispanics or Latinos, 41.8 percent were past month alcohol users; of these, 16.6 percent were current alcohol users (non-binge and non-heavy use), 20.0 percent were binge alcohol users (non-heavy use), and 5.1 percent were heavy alcohol users.

Long description end. Return to Figure 3.2.

Long description, Figure 3.3. Figure 3.3 is titled "Binge Alcohol Use among Adults Aged 18 to 22, by College Enrollment: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage using in the past month is shown on the vertical axis. For each college enrollment status (enrolled full time in college and not enrolled full time in college), there is a line showing use over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

Among adults aged 18 to 22 enrolled full time in college, 44.4 percent were past month binge alcohol users in 2002, 43.5 percent in 2003, 43.4 percent in 2004, 44.8 percent in 2005, 45.5 percent in 2006, 43.6 percent in 2007, 40.5 percent in 2008, 43.5 percent in 2009, and 42.2 percent in 2010. The difference between the 2010 estimate and the 2006 estimate was statistically significant.

Among adults aged 18 to 22 not enrolled full time in college, 38.9 percent were past month binge alcohol users in 2002, 38.7 percent in 2003, 39.4 percent in 2004, 38.3 percent in 2005, 38.4 percent in both 2006 and 2007, 38.1 percent in 2008, 37.8 percent in 2009, and 35.6 percent in 2010. The differences between the 2010 estimate and the 2002 through 2009 estimates were statistically significant.

Long description end. Return to Figure 3.3.

Long description, Figure 3.4. Figure 3.4 is titled "Driving Under the Influence of Alcohol in the Past Year among Persons Aged 12 or Older: 2002 through 2010." It is a bar graph, where the survey years are shown on the horizontal axis and the percentage driving under the influence of alcohol in the past year is shown on the vertical axis. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

The percentage of persons aged 12 or older driving under the influence of alcohol in the past year was 14.2 percent in 2002, 13.6 percent in 2003, 13.5 percent in 2004, 13.0 percent in 2005, 12.4 percent in 2006, 12.7 percent in 2007, 12.4 percent in 2008, 12.0 percent in 2009, and 11.4 percent in 2010. The differences between the 2010 estimate and the 2002 through 2008 estimates were statistically significant.

Long description end. Return to Figure 3.4.

Long description, Figure 3.5. Figure 3.5 is titled "Driving Under the Influence of Alcohol in the Past Year among Persons Aged 16 or Older, by Age: 2010." It is a bar graph, where age in years is shown on the horizontal axis and the percentage driving under the influence of alcohol in the past year is shown on the vertical axis. There are 12 age categories.

The percentage of persons driving under the influence of alcohol in the past year was 5.8 percent among 16 or 17 year olds, 15.1 percent among 18 to 20 year olds, 23.4 percent among 21 to 25 year olds, 19.3 percent among 26 to 29 year olds, 18.0 percent among 30 to 34 year olds, 14.8 percent among 35 to 39 year olds, 13.4 percent among 40 to 44 year olds, 11.8 percent among 45 to 49 year olds, 10.5 percent among 50 to 54 year olds, 10.1 percent among 55 to 59 year olds, 6.4 percent among 60 to 64 year olds, and 2.7 percent among persons aged 65 or older.

Long description end. Return to Figure 3.5.

Long description, Figure 3.6. Figure 3.6 is titled "Current Alcohol Use among Persons Aged 12 to 20, by Age: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage using in the past month is shown on the vertical axis. For each of the four age groups (12 or 13 year olds, 14 or 15 year olds, 16 or 17 year olds, and 18 to 20 year olds), there is a line showing use over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

Among persons aged 12 or 13, the percentage using alcohol in the past month was 4.3 percent in 2002, 4.5 percent in 2003, 4.3 percent in 2004, 4.2 percent in 2005, 3.9 percent in 2006, 3.5 percent in 2007, 3.4 percent in 2008, 3.5 percent in 2009, and 3.1 percent in 2010. The differences between the 2010 estimate and the 2002 through 2005 estimates were statistically significant.

Among persons aged 14 or 15, the percentage using alcohol in the past month was 16.6 percent in 2002, 17.0 percent in 2003, 16.4 percent in 2004, 15.1 percent in 2005, 15.6 percent in 2006, 14.7 percent in 2007, 13.1 percent in 2008, 13.0 percent in 2009, and 12.4 percent in 2010. The differences between the 2010 estimate and the 2002 through 2007 estimates were statistically significant.

Among persons aged 16 or 17, the percentage using alcohol in the past month was 32.6 percent in 2002, 31.8 percent in 2003, 32.5 percent in 2004, 30.1 percent in 2005, 29.7 percent in 2006, 29.0 percent in 2007, 26.2 percent in 2008, 26.3 percent in 2009, and 24.6 percent in 2010. The differences between the 2009 estimate and the 2002 through 2007 estimates were statistically significant.

Among persons aged 18 to 20, the percentage using alcohol in the past month was 51.0 percent in 2002, 51.5 percent in 2003, 51.1 percent in both 2004 and 2005, 51.6 percent in 2006, 50.7 percent in 2007, 48.7 percent in 2008, 49.7 percent in 2009, and 48.9 percent in 2010. The differences between the 2010 estimate and the 2003 through 2006 estimates were statistically significant.

Long description end. Return to Figure 3.6.

Long description, Figure 3.7. Figure 3.7 is titled "Current, Binge, and Heavy Alcohol Use among Persons Aged 12 to 20, by Gender: 2010." It is a bar graph, where the levels of alcohol use (current, binge, and heavy) are shown on the horizontal axis and the percentage using in the past month is shown on the vertical axis. There is a bar for each gender at each alcohol use level.

The percentage of males aged 12 to 20 using alcohol in the past month was 28.3 percent. The percentage of females aged 12 to 20 using alcohol in the past month was 24.1 percent.

The percentage of males aged 12 to 20 reporting binge alcohol use in the past month was 19.8 percent. The percentages of females aged 12 to 20 reporting binge alcohol use in the past month was 14.0 percent.

The percentage of males aged 12 to 20 reporting heavy alcohol use in the past month was 6.7 percent. The percentage of females aged 12 to 20 reporting heavy alcohol use in the past month was 3.5 percent.

Long description end. Return to Figure 3.7.

Chapter 4

Long description, Figure 4.1. Figure 4.1 is titled "Past Month Tobacco Use among Persons Aged 12 or Older: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage using in the past month is shown on the vertical axis. There are five categories of tobacco use: tobacco products, cigarettes, cigars, smokeless tobacco, and pipe tobacco. For each type of tobacco use, there is a line showing use over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

Among persons aged 12 or older, 30.4 percent used tobacco products in the past month in 2002, 29.8 percent in 2003, 29.2 percent in 2004, 29.4 percent in 2005, 29.6 percent in 2006, 28.6 percent in 2007, 28.4 percent in 2008, 27.7 percent in 2009, and 27.4 percent in 2010. The differences between the 2010 estimate and the 2002 through 2007 estimates were statistically significant.

Among persons aged 12 or older, 26.0 percent used cigarettes in the past month in 2002, 25.4 percent in 2003, 24.9 percent in both 2004 and 2005, 25.0 percent in 2006, 24.2 percent in 2007, 23.9 percent in 2008, 23.3 percent in 2009, and 23.0 percent in 2010. The differences between the 2010 estimate and the 2002 through 2008 estimates were statistically significant.

Among persons aged 12 or older, 5.4 percent used cigars in the past month in both 2002 and 2003, 5.7 percent in 2004, 5.6 percent in both 2005 and 2006, 5.4 percent in 2007, 5.3 percent in both 2008 and 2009, and 5.2 percent in 2010. The differences between the 2010 estimate and the 2004 and 2005 estimates were statistically significant.

Among persons aged 12 or older, 3.3 percent used smokeless tobacco in the past month in both 2002 and 2003, 3.0 percent in 2004, 3.2 percent in 2005, 3.3 percent in 2006, 3.2 percent in 2007, 3.5 percent in 2008, 3.4 percent in 2009, and 3.5 percent in 2010. The differences between the 2010 estimate and the 2004 and 2005 estimates were statistically significant.

Among persons aged 12 or older, 0.8 percent used pipe tobacco in the past month in 2002, 0.7 percent in 2003, 0.8 percent in 2004, 0.9 percent in both 2005 and 2006, and 0.8 percent in 2007, 2008, 2009, and 2010.

Long description end. Return to Figure 4.1.

Long description, Figure 4.2. Figure 4.2 is titled "Past Month Tobacco Use among Youths Aged 12 to 17: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage using in the past month is shown on the vertical axis. There are five categories of tobacco use: tobacco products, cigarettes, cigars, smokeless tobacco, and pipe tobacco. For each type of tobacco use, there is a line showing use over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

Among youths aged 12 to 17, 15.2 percent used tobacco products in the past month in 2002, 14.4 percent in both 2003 and 2004, 13.1 percent in 2005, 12.9 percent in 2006, 12.4 percent in 2007, 11.4 percent in 2008, 11.6 percent in 2009, and 10.7 percent in 2010. The differences between the 2010 estimate and the 2002, 2003, 2004, 2005, 2006, 2007, and 2009 estimates were statistically significant.

Among youths aged 12 to 17, 13.0 percent used cigarettes in the past month in 2002, 12.2 percent in 2003, 11.9 percent in 2004, 10.8 percent in 2005, 10.4 percent in 2006, 9.8 percent in 2007, 9.1 percent in 2008, 8.9 percent in 2009, and 8.3 percent in 2010. The differences between the 2010 estimate and the 2002 through 2008 estimates were statistically significant.

Among youths aged 12 to 17, 4.5 percent used cigars in the past month in both 2002 and 2003, 4.8 percent in 2004, 4.2 percent in 2005, 4.1 percent in 2006, 4.2 percent in 2007, 3.8 percent in 2008, 4.0 percent in 2009, and 3.2 percent in 2010. The differences between the 2010 estimate and the 2002 through 2009 estimates were statistically significant.

Among youths aged 12 to 17, 2.0 percent used smokeless tobacco in the past month in both 2002 and 2003, 2.3 percent in 2004, 2.1 percent in 2005, 2.4 percent in both 2006 and 2007, 2.2 percent in 2008, and 2.3 percent in both 2009 and 2010. The difference between the 2010 estimate and the 2002 estimate was statistically significant.

Among youths aged 12 to 17, 0.6 percent used pipe tobacco in both 2002 and 2003; 0.7 percent in 2004; 0.6 percent in 2005; 0.7 percent in 2006, 2007, and 2008; 0.9 percent in 2009; and 0.6 percent in 2010. The difference between the 2010 estimate and the 2009 estimate was statistically significant.

Long description end. Return to Figure 4.2.

Long description, Figure 4.3. Figure 4.3 is titled "Past Month Cigarette Use among Persons Aged 12 or Older, by Age: 2010." It is a bar graph, where age in years is shown on the horizontal axis and the percentage smoking cigarettes in the past month is shown on the vertical axis. There are 14 age categories.

The percentage of past month cigarette smoking was 1.8 percent among 12 or 13 year olds, 7.4 percent among 14 or 15 year olds, 15.4 percent among 16 or 17 year olds, 31.9 percent among 18 to 20 year olds, 35.8 percent among 21 to 25 year olds, 36.8 percent among 26 to 29 year olds, 30.9 percent among 30 to 34 year olds, 24.7 percent among 35 to 39 year olds, 26.5 percent among 40 to 44 year olds, 26.2 percent among 45 to 49 year olds, 25.2 percent among 50 to 54 year olds, 22.8 percent among 55 to 59 year olds, 16.9 percent among 60 to 64 year olds, and 9.1 percent among persons aged 65 or older.

Long description end. Return to Figure 4.3.

Long description, Figure 4.4. Figure 4.4 is titled "Past Month Cigarette Use among Youths Aged 12 to 17, by Gender: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage smoking cigarettes in the past month is shown on the vertical axis. For each gender, there is a line showing use over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

Among male youths aged 12 to 17, the percentage smoking cigarettes in the past month was 12.3 percent in 2002, 11.9 percent in 2003, 11.3 percent in 2004, 10.7 percent in 2005, 10.0 percent in both 2006 and 2007, 9.0 percent in 2008, 9.2 percent in 2009, and 8.6 percent in 2010. The differences between the 2010 estimate and the 2002 through 2007 estimates were statistically significant.

Among female youths aged 12 to 17, the percentage smoking cigarettes in the past month was 13.6 percent in 2002, 12.5 percent in both 2003 and 2004, 10.8 percent in 2005, 10.7 percent in 2006, 9.7 percent in 2007, 9.2 percent in 2008, 8.6 percent in 2009, and 8.1 percent in 2010. The differences between the 2010 estimate and the 2002 through 2008 estimates were statistically significant.

Long description end. Return to Figure 4.4.

Long description, Figure 4.5. Figure 4.5 is titled "Past Month Cigarette Use among Women Aged 15 to 44, by Pregnancy Status: Combined Years 2002 and 2003 to Combined Years 2009 and 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage smoking cigarettes in the past month is shown on the vertical axis. There is a line representing women who are pregnant and a line representing women who are not pregnant. Tests of statistical significance at the .05 level were performed between 2009 and 2010 combined data and each of the previous combined years listed; significant results are indicated where appropriate.

Among pregnant women aged 15 to 44, the percentage smoking cigarettes in the past month was 18.0 percent in 2002 and 2003 combined, 18.0 percent in 2003 and 2004 combined, 16.6 percent in 2004 and 2005 combined, 16.5 percent in 2005 and 2006 combined, 16.4 percent in 2006 and 2007 combined, 16.4 percent in 2007 and 2008 combined, 15.3 percent in 2008 and 2009 combined, and 16.3 percent in 2009 and 2010 combined.

Among women aged 15 to 44 who were not pregnant, the percentage smoking cigarettes in the past month was 30.7 percent in 2002 and 2003 combined, 30.0 percent in 2003 and 2004 combined, 29.6 percent in 2004 and 2005 combined, 29.5 percent in 2005 and 2006 combined, 28.4 percent in 2006 and 2007 combined, 27.3 percent in 2007 and 2008 combined, 27.4 percent in 2008 and 2009 combined, and 26.7 percent in 2009 and 2010 combined. The differences between the 2009 and 2010 combined estimate and the 2002 and 2003 combined, 2003 and 2004 combined, 2004 and 2005 combined, 2005 and 2006 combined, and 2006 and 2007 combined estimates were statistically significant.

Long description end. Return to Figure 4.5.

Long description, Figure 4.6. Figure 4.6 is titled "Past Month Smokers of One or More Packs of Cigarettes per Day among Daily Smokers, by Age Group: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage smoking one or more packs per day in the past month is shown on the vertical axis. For each of the three age groups (12 to 17, 18 to 25, and 26 or older), there is a line showing use over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

Among youths aged 12 to 17, 21.7 percent smoked one or more packs of cigarettes per day in the past month in 2002, 22.0 percent in 2003, 19.3 percent in 2004, 20.1 percent in 2005, 17.7 percent in 2006, 18.5 percent in 2007, 18.4 percent in 2008, 17.9 percent in 2009, and 16.5 percent in 2010.

Among adults aged 18 to 25, 39.0 percent smoked one or more packs of cigarettes per day in the past month in 2002, 37.1 percent in 2003, 34.9 percent in 2004, 36.9 percent in 2005, 34.4 percent in 2006, 33.1 percent in 2007, 32.1 percent in 2008, 29.7 percent in 2009, and 27.8 percent in 2010. The differences between the 2010 estimate and the 2002 through 2008 estimates were statistically significant.

Among adults aged 26 or older, 56.9 percent smoked one or more packs of cigarettes per day in the past month in 2002, 57.9 percent in 2003, 59.1 percent in 2004, 55.0 percent in 2005, 54.7 percent in 2006, 55.0 percent in 2007, 52.8 percent in 2008, 49.3 percent in 2009, and 48.9 percent in 2010. The differences between the 2010 estimate and the 2002 through 2008 estimates were statistically significant.

Long description end. Return to Figure 4.6.

Chapter 5

Long description, Figure 5.1. Figure 5.1 is titled "First Specific Drug Associated with Initiation of Illicit Drug Use among Past Year Illicit Drug Initiates Aged 12 or Older: 2010." It is a pie chart with the following written below the chart: "3.0 million Initiates of Illicit Drugs." There is also a note at the bottom of the figure that says, "The percentages do not add up to 100 percent due to rounding or because a small number of respondents initiated multiple drugs on the same day. The first specific drug refers to the one that was used on the occasion of first-time use of any illicit drug."

The percentage of those who initiated illicit drug use with marijuana was 61.8 percent.

The percentage of those who initiated illicit drug use with pain relievers was 17.3 percent.

The percentage of those who initiated illicit drug use with inhalants was 9.0 percent.

The percentage of those who initiated illicit drug use with tranquilizers was 4.6 percent.

The percentage of those who initiated illicit drug use with hallucinogens was 3.0 percent.

The percentage of those who initiated illicit drug use with stimulants was 2.5 percent.

The percentage of those who initiated illicit drug use with sedatives was 1.9 percent.

The percentage of those who initiated illicit drug use with cocaine was 0.1 percent.

The percentage of those who initiated illicit drug use with heroin was 0.1 percent.

Long description end. Return to Figure 5.1.

Long description, Figure 5.2. Figure 5.2 is titled "Past Year Initiates of Specific Illicit Drugs among Persons Aged 12 or Older: 2010." It is a bar graph, where the specific illicit drugs (marijuana, pain relievers, tranquilizers, Ecstasy, inhalants, cocaine, stimulants, LSD, sedatives, heroin, and PCP) are shown on the horizontal axis and the numbers in thousands of past year initiates are shown on the vertical axis. There is a note at the bottom of the figure that says, "The specific drug refers to the one that was used for the first time, regardless of whether it was the first drug used or not."

The number of past year initiates among persons aged 12 or older in 2010 was 2,426,000 for marijuana; 2,004,000 for pain relievers; 1,238,000 for tranquilizers; 937,000 for Ecstasy; 793,000 for inhalants; 637,000 for cocaine; 624,000 for stimulants; 377,000 for LSD; 252,000 for sedatives; 140,000 for heroin; and 45,000 for PCP.

Long description end. Return to Figure 5.2.

Long description, Figure 5.3. Figure 5.3 is titled "Mean Age at First Use for Specific Illicit Drugs among Past Year Initiates Aged 12 to 49: 2010." It is a bar graph, where the specific illicit drugs (inhalants, PCP, marijuana, LSD, Ecstasy, pain relievers, cocaine, stimulants, heroin, sedatives, and tranquilizers) are shown on the horizontal axis and the mean age in years is shown on the vertical axis.

Among persons aged 12 to 49, the mean age at first use of past year initiates was 16.3 years for inhalants, 17.6 years for PCP, 18.4 years for marijuana, 19.1 years for LSD, 19.4 years for Ecstasy, 21.0 years for pain relievers, 21.2 years for cocaine, 21.2 years for stimulants, 21.3 years for heroin, 23.5 years for sedatives, and 24.6 years for tranquilizers.

Long description end. Return to Figure 5.3.

Long description, Figure 5.4. Figure 5.4 is titled "Past Year Marijuana Initiates among Persons Aged 12 or Older and Mean Age at First Use of Marijuana among Past Year Marijuana Initiates Aged 12 to 49: 2002 through 2010." There are two bar graphs, one for the number of past year initiates and one for the mean age at first use. The past year initiates' bar graph has the survey years on the horizontal axis and the numbers in millions of past year initiates on the vertical axis. The mean-age-at-first-use bar graph has the survey years on the horizontal axis and the mean age in years shown on the vertical axis. There is a footnote on the mean-age-at-first-use bar graph that states, "Mean-age-at-first-use estimates are for recent initiates aged 12 to 49." Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

There were 2.2 million persons aged 12 or older who used marijuana for the first time in the past 12 months in 2002; 2.0 million persons in 2003; 2.1 million persons each year in 2004, 2005, 2006, and 2007; 2.2 million persons in 2008; and 2.4 million in both 2009 and 2010. The differences between the 2010 estimate and the 2002 through 2007 estimates were statistically significant.

The mean age at first marijuana use among past year marijuana initiates aged 12 to 49 was 17.0 years in 2002, 16.8 years in 2003, 17.1 years in 2004, 17.4 years in both 2005 and 2006, 17.6 years in 2007, 17.8 years in 2008, 17.0 years in 2009, and 18.4 years in 2010. The differences between the 2010 estimate and the 2002, 2003, 2004, 2005, and 2009 estimates were statistically significant.

Long description end. Return to Figure 5.4.

Long description, Figure 5.5. Figure 5.5 is titled "Past Year Hallucinogen Initiates among Persons Aged 12 or Older: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the numbers in thousands of past year initiates are shown on the vertical axis. For each drug category (any hallucinogen, Ecstasy, LSD, and PCP), there is a line showing the number in thousands of past year initiates over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

Among persons aged 12 or older, the number of past year initiates of hallucinogens was 1,152,000 in 2002; 886,000 in 2003; 934,000 in 2004; 953,000 in 2005; 1,116,000 in 2006; 1,064,000 in 2007; 1,127,000 in 2008; 1,269,000 in 2009; and 1,229,000 in 2010. The differences between the 2010 estimate and the 2003, 2004, and 2005 estimates were statistically significant.

Among persons aged 12 or older, the number of past year initiates of Ecstasy was 1,206,000 in 2002; 642,000 in 2003; 607,000 in 2004; 615,000 in 2005; 860,000 in 2006; 781,000 in 2007; 894,000 in 2008; 1,110,000 in 2009; and 937,000 in 2010. The differences between the 2010 estimate and the 2003, 2004, 2005, and 2007 estimates were statistically significant.

Among persons aged 12 or older, the number of past year initiates of LSD was 338,000 in 2002; 200,000 in 2003; 235,000 in 2004; 243,000 in 2005; 264,000 in 2006; 270,000 in 2007; 394,000 in 2008; 337,000 in 2009; and 377,000 in 2010. The differences between the 2010 estimate and the 2003 through 2007 estimates were statistically significant.

Among persons aged 12 or older, the number of past year initiates of PCP was 123,000 in 2002; 105,000 in 2003; 106,000 in 2004; 77,000 in 2005; 69,000 in 2006; 58,000 in 2007; 53,000 in 2008; and 45,000 in both 2009 and 2010. The differences between the 2010 estimate and the 2002, 2003, and 2004 estimates were statistically significant.

Long description end. Return to Figure 5.5.

Long description, Figure 5.6. Figure 5.6 is titled "Past Year Methamphetamine Initiates among Persons Aged 12 or Older and Mean Age at First Use of Methamphetamine among Past Year Methamphetamine Initiates Aged 12 to 49: 2002 through 2010." There are two bar graphs, one for the number of past year initiates and one for mean age at first use. The past year initiates' bar graph has the survey years on the horizontal axis and the numbers in thousands of past year initiates shown on the vertical axis. The mean-age-at-first-use bar graph has the survey years on the horizontal axis and the mean age in years shown on the vertical axis. There is a footnote on the mean-age-at-first-use bar graph that says, "Mean-age-at-first-use estimates are for recent initiates aged 12 to 49." Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

There were 299,000 persons aged 12 or older who used methamphetamine for the first time in the past 12 months in 2002; 260,000 persons in 2003; 318,000 persons in 2004; 192,000 persons in 2005; 259,000 persons in 2006; 157,000 persons in 2007; 95,000 persons in 2008; 154,000 in 2009; and 105,000 in 2010. The differences between the 2010 estimate and the 2002 through 2007 estimates were statistically significant.

The mean age at first methamphetamine use among recent initiates aged 12 to 49 was 18.9 years in 2002, 20.4 years in 2003, 20.6 years in 2004, 18.6 years in 2005, 22.2 years in 2006, 19.1 years in 2007, 19.2 years in 2008, 19.3 years in 2009, and 18.8 years in 2010.

Long description end. Return to Figure 5.6.

Long description, Figure 5.7. Figure 5.7 is titled "Past Year Cigarette Initiates among Persons Aged 12 or Older, by Age at First Use: 2002 through 2010." It is a bar graph, where the survey years are shown on the horizontal axis and the numbers in millions of persons who initiated cigarette use in the past year are shown on the vertical axis. Each bar is divided into two sections representing age at first use: initiated use prior to age 18 and initiated use at age 18 or older. Due to rounding, the stacked bar totals may not add to the overall total. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

Of the 1.9 million persons in 2002 who smoked cigarettes for the first time in the past 12 months, 1.3 million initiated prior to age 18, and 0.6 million initiated at age 18 or older. The difference between the 2010 estimate for the number of persons who smoked cigarettes for the first time in the past 12 months and the 2002 estimate was statistically significant.

Of the 2.0 million persons in 2003 who smoked cigarettes for the first time in the past 12 months, 1.4 million initiated prior to age 18, and 0.6 million initiated at age 18 or older. The difference between the 2010 estimate for the number of persons who smoked cigarettes for the first time in the past 12 months and the 2003 estimate was statistically significant.

Of the 2.1 million persons in 2004 who smoked cigarettes for the first time in the past 12 months, 1.4 million initiated prior to age 18, and 0.7 million initiated at age 18 or older. The difference between the 2010 estimate for the number of persons who smoked cigarettes for the first time in the past 12 months and the 2004 estimate was statistically significant.

Of the 2.3 million persons in 2005 who smoked cigarettes for the first time in the past 12 months, 1.4 million initiated prior to age 18, and 0.8 million initiated at age 18 or older.

Of the 2.4 million persons in 2006 who smoked cigarettes for the first time in the past 12 months, 1.5 million initiated prior to age 18, and 0.9 million initiated at age 18 or older.

Of the 2.2 million persons in 2007 who smoked cigarettes for the first time in the past 12 months, 1.3 million initiated prior to age 18, and 0.9 million initiated at age 18 or older.

Of the 2.4 million persons in 2008 who smoked cigarettes for the first time in the past 12 months, 1.4 million initiated prior to age 18, and 1.0 million initiated at age 18 or older.

Of the 2.5 million persons in 2009 who smoked cigarettes for the first time in the past 12 months, 1.5 million initiated prior to age 18, and 1.0 million initiated at age 18 or older.

Of the 2.4 million persons in 2010 who smoked cigarettes for the first time in the past 12 months, 1.4 million initiated prior to age 18, and 1.0 million initiated at age 18 or older.

Long description end. Return to Figure 5.7.

Long description, Figure 5.8. Figure 5.8 is titled "Past Year Cigarette Initiation among Youths Aged 12 to 17 Who Had Never Smoked Prior to the Past Year, by Gender: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage initiating cigarettes in the past year is shown on the vertical axis. For each gender, there is a line showing use over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

Among males aged 12 to 17 who had never smoked prior to the past year, 6.1 percent reported cigarette use initiation in 2002, 5.8 percent in both 2003 and 2004, 6.0 percent in 2005, 6.3 percent in 2006, 5.7 percent in both 2007 and 2008, 6.2 percent in 2009, and 5.7 percent in 2010.

Among females aged 12 to 17 who had never smoked prior to the past year, 7.4 percent reported cigarette use initiation in 2002, 7.5 percent in 2003, 7.8 percent in 2004, 7.1 percent in 2005, 6.9 percent in 2006, 6.0 percent in 2007, 6.7 percent in 2008, 6.1 percent in 2009, and 6.0 percent in 2010. The differences between the 2010 estimate and the 2002 through 2006 estimates were statistically significant.

Long description end. Return to Figure 5.8.

Chapter 6

Long description, Figure 6.1. Figure 6.1 is titled "Past Month Binge Drinking and Marijuana Use among Youths Aged 12 to 17, by Perceptions of Risk: 2010." It is a bar graph, where alcohol and marijuana use behaviors are shown on the horizontal axis and the percentage using in the past month is shown on the vertical axis. For each of the two behavior categories, there is a bar representing perceived great risk and a bar representing perceived moderate, slight, or no risk.

Among youths aged 12 to 17 who perceived great risk in having five or more drinks of alcohol once or twice a week, 4.8 percent reported binge drinking in the past month.

Among youths aged 12 to 17 who perceived moderate, slight, or no risk in having five or more drinks of alcohol once or twice a week, 10.0 percent reported binge drinking in the past month.

Among youths aged 12 to 17 who perceived great risk in smoking marijuana once a month, 1.3 percent reported using marijuana in the past month.

Among youths aged 12 to 17 who perceived moderate, slight, or no risk in smoking marijuana once a month, 10.2 percent reported using marijuana in the past month.

Long description end. Return to Figure 6.1.

Long description, Figure 6.2. Figure 6.2 is titled "Perceived Great Risk of Cigarette and Alcohol Use among Youths Aged 12 to 17: 2002 through 2010." It is a line graph, where survey years are shown on the horizontal axis and the percentage perceiving great risk is shown on the vertical axis. For each of the three behavior categories (smoke one or more packs of cigarettes per day, have four or five drinks nearly every day, and have five or more drinks once or twice a week), there is a line showing perceived great risk over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

The percentage of youths aged 12 to 17 who perceived that smoking one or more packs of cigarettes per day is a great risk was 63.1 percent in 2002, 64.2 percent in 2003, 67.5 percent in 2004, 68.3 percent in 2005, 68.7 percent in 2006, 68.8 percent in 2007, 69.7 percent in 2008, 65.8 percent in 2009, and 65.5 percent in 2010. The differences between the 2010 estimate and the 2002 through 2008 estimates were statistically significant.

The percentage of youths aged 12 to 17 who perceived that having four or five drinks of alcohol nearly every day is a great risk was 62.2 percent in 2002, 61.6 percent in 2003, 61.8 percent in 2004, 63.8 percent in 2005, 64.6 percent in 2006, 65.2 percent in 2007, 65.9 percent in 2008, 64.3 percent in 2009, and 65.0 percent in 2010. The differences between the 2010 estimate and the 2002, 2003, and 2004 estimates were statistically significant.

The percentage of youths aged 12 to 17 who perceived that having five or more drinks of alcohol once or twice a week is a great risk was 38.2 percent in 2002, 38.5 percent in 2003, 38.1 percent in 2004, 38.4 percent in 2005, 39.4 percent in both 2006 and 2007, 40.5 percent in 2008, 39.9 percent in 2009, and 40.8 percent in 2010. The differences between the 2010 estimate and the 2002 through 2007 estimates were statistically significant.

Long description end. Return to Figure 6.2.

Long description, Figure 6.3. Figure 6.3 is titled "Perceived Great Risk of Marijuana Use among Youths Aged 12 to 17: 2002 through 2010." It is a line graph, where survey years are shown on the horizontal axis and the percentage perceiving great risk is shown on the vertical axis. For each of the two marijuana use behavior categories (smoke marijuana once or twice a week and smoke marijuana once a month), there is a line showing estimates for 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

The percentage of youths aged 12 to 17 who perceived that smoking marijuana once or twice a week is a great risk was 51.5 percent in 2002, 54.4 percent in 2003, 54.7 percent in 2004, 55.0 percent in 2005, 54.2 percent in 2006, 54.7 percent in 2007, 53.1 percent in 2008, 49.3 percent in 2009, and 47.5 percent in 2010. The differences between the 2010 estimate and the 2002 through 2009 estimates were statistically significant.

The percentage of youths aged 12 to 17 who perceived that smoking marijuana once a month is a great risk was 32.4 percent in 2002, 34.9 percent in 2003, 35.0 percent in 2004, 34.0 percent in 2005, 34.7 percent in 2006, 34.5 percent in 2007, 33.9 percent in 2008, 30.7 percent in 2009, and 30.1 percent in 2010. The differences between the 2010 estimate and the 2002 through 2008 estimates were statistically significant.

Long description end. Return to Figure 6.3.

Long description, Figure 6.4. Figure 6.4 is titled "Perceived Great Risk of Use of Selected Illicit Drugs Once or Twice a Week among Youths Aged 12 to 17: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage perceiving great risk is shown on the vertical axis. For each of the four behavior categories (once or twice a week use of heroin, cocaine, LSD, and marijuana), there is a line showing perceived risk over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

The percentage of youths aged 12 to 17 who perceived that using heroin once or twice a week is a great risk was 82.5 percent in 2002, 82.6 percent in 2003, 81.4 percent in 2004, 81.8 percent in 2005, 81.2 percent in 2006, 81.0 percent in 2007, 81.3 percent in 2008, 81.0 percent in 2009, and 80.5 percent in 2010. The differences between the 2010 estimate and the 2002, 2003, and 2005 estimates were statistically significant.

The percentage of youths aged 12 to 17 who perceived that using cocaine once or twice a week is a great risk was 79.8 percent in 2002, 80.7 percent in 2003, 79.8 percent in 2004, 79.9 percent in 2005, 79.2 percent in 2006, 78.9 percent in 2007, 79.2 percent in 2008, 78.5 percent in 2009, and 78.4 percent in 2010. The differences between the 2010 estimate and the 2002 through 2005 estimates were statistically significant.

The percentage of youths aged 12 to 17 who perceived that using LSD once or twice a week is a great risk was 76.2 percent in 2002, 76.9 percent in 2003, 76.4 percent in 2004, 76.1 percent in 2005, 74.7 percent in 2006, 74.2 percent in 2007, 73.9 percent in 2008, 71.8 percent in 2009, and 71.5 percent in 2010. The differences between the 2010 estimate and the 2002 through 2008 estimates were statistically significant.

The percentage of youths aged 12 to 17 who perceived that using marijuana once or twice a week is a great risk was 51.5 percent in 2002, 54.4 percent in 2003, 54.7 percent in 2004, 55.0 percent in 2005, 54.2 percent in 2006, 54.7 percent in 2007, 53.1 percent in 2008, 49.3 percent in 2009, and 47.5 percent in 2010. The differences between the 2010 estimate and the 2002 through 2009 estimates were statistically significant.

Long description end. Return to Figure 6.4.

Long description, Figure 6.5. Figure 6.5 is titled "Perceived Availability of Selected Illicit Drugs among Youths Aged 12 to 17: 2002 through 2010." It is a line graph, where survey years are shown on the horizontal axis and the percentage indicating it was fairly or very easy to obtain specific illicit drugs is shown on the vertical axis. For each of the four types of illicit drugs (marijuana, cocaine, LSD, and heroin), there is a line showing perceived availability over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

The percentage of youths aged 12 to 17 indicating that marijuana is fairly or very easy to obtain was 55.0 percent in 2002, 53.6 percent in 2003, 52.2 percent in 2004, 51.0 percent in 2005, 50.1 percent in 2006, 49.1 percent in 2007, 49.2 percent in 2008, 49.9 percent in 2009, and 48.6 percent in 2010. The differences between the 2010 estimate and the 2002 through 2006 estimates were statistically significant.

The percentage of youths aged 12 to 17 indicating that cocaine is fairly or very easy to obtain was 25.0 percent in both 2002 and 2003, 24.4 percent in 2004, 24.9 percent in 2005, 25.9 percent in 2006, 24.5 percent in 2007, 22.1 percent in 2008, 20.9 percent in 2009, and 19.0 percent in 2010. The differences between the 2010 estimate and the 2002 through 2009 estimates were statistically significant.

The percentage of youths aged 12 to 17 indicating that LSD is fairly or very easy to obtain was 19.4 percent in 2002, 17.6 percent in 2003, 16.9 percent in 2004, 15.7 percent in 2005, 14.0 percent in 2006, 14.4 percent in 2007, 13.8 percent in 2008, 13.5 percent in 2009, and 12.9 percent in 2010. The differences between the 2010 estimate and the 2002 through 2008 estimates were statistically significant.

The percentage of youths aged 12 to 17 indicating that heroin is fairly or very easy to obtain was 15.8 percent in 2002, 15.3 percent in 2003, 14.0 percent in both 2004 and 2005, 14.4 percent in 2006, 14.1 percent in 2007, 13.0 percent in 2008, 12.9 percent in 2009, and 11.6 percent in 2010. The differences between the 2010 estimate and the 2002 through 2009 estimates were statistically significant.

Long description end. Return to Figure 6.5.

Long description, Figure 6.6. Figure 6.6 is titled "Exposure to Substance Use Prevention Messages and Programs among Youths Aged 12 to 17: 2002 through 2010." It is a line graph, where survey years are shown on the horizontal axis and the percentage who had seen or heard substance use prevention messages is shown on the vertical axis. There are two categories: (1) seen or heard drug or alcohol prevention messages from sources outside of school, and (2) seen or heard drug or alcohol prevention messages at school. A footnote on the at-school label says, "Estimates are from youths aged 12 to 17 who were enrolled in school in the past year." For each of these categories, there is a line showing exposure to substance use prevention messages over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

Among youths aged 12 to 17, the percentage who had seen or heard drug or alcohol prevention messages from sources outside of school in the past year was 83.2 percent in 2002, 83.6 percent in 2003, 83.0 percent in 2004, 81.1 percent in 2005, 79.4 percent in 2006, 77.9 percent in 2007, 78.0 percent in 2008, 77.0 percent in 2009, and 75.9 percent in 2010. The differences between the 2010 estimate and the 2002 through 2009 estimates were statistically significant.

Among youths aged 12 to 17 enrolled in school, the percentage who had seen or heard drug or alcohol prevention messages at school in the past year was 78.8 percent in 2002, 78.1 percent in 2003, 78.2 percent in 2004, 77.9 percent in 2005, 76.9 percent in 2006, 75.8 percent in 2007, 75.9 percent in 2008, 74.9 percent in 2009, and 75.4 percent in 2010. The differences between the 2010 estimate and the 2002 through 2006 estimates were statistically significant.

Long description end. Return to Figure 6.6.

Chapter 7

Long description, Figure 7.1. Figure 7.1 is titled "Substance Dependence or Abuse in the Past Year among Persons Aged 12 or Older: 2002 through 2010." It is a bar graph, where the survey years are shown on the horizontal axis and the numbers in millions of persons with dependence or abuse are shown on the vertical axis. Each bar is divided into three sections representing (1) both alcohol and illicit drugs, (2) illicit drugs only, and (3) alcohol only. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate. Due to rounding, the stacked bar totals may not add to the overall total.

Of the 22.0 million persons with substance dependence or abuse in 2002, 3.2 million were dependent on or abused both alcohol and illicit drugs, 3.9 million were dependent on or abused illicit drugs only, and 14.9 million were dependent on or abused alcohol only.

Of the 21.6 million persons with substance dependence or abuse in 2003, 3.1 million were dependent on or abused both alcohol and illicit drugs, 3.8 million were dependent on or abused illicit drugs only, and 14.8 million were dependent on or abused alcohol only.

Of the 22.5 million persons with substance dependence or abuse in 2004, 3.4 million were dependent on or abused both alcohol and illicit drugs, 3.9 million were dependent on or abused illicit drugs only, and 15.2 million were dependent on or abused alcohol only. The difference between the 2010 estimate and the 2004 estimate for dependence or abuse of both alcohol and illicit drugs was statistically significant.

Of the 22.2 million persons with substance dependence or abuse in 2005, 3.3 million were dependent on or abused both alcohol and illicit drugs, 3.6 million were dependent on or abused illicit drugs only, and 15.4 million were dependent on or abused alcohol only. The differences between the 2010 estimate and the 2005 estimates for dependence or abuse of both alcohol and illicit drugs and for dependence or abuse of illicit drugs only were statistically significant.

Of the 22.6 million persons with substance dependence or abuse in 2006, 3.2 million were dependent on or abused both alcohol and illicit drugs, 3.8 million were dependent on or abused illicit drugs only, and 15.6 million were dependent on or abused alcohol only.

Of the 22.3 million persons with substance dependence or abuse in 2007, 3.2 million were dependent on or abused both alcohol and illicit drugs, 3.7 million were dependent on or abused illicit drugs only, and 15.5 million were dependent on or abused alcohol only. The difference between the 2010 estimate and the 2007 estimate for dependence or abuse of illicit drugs only was statistically significant.

Of the 22.2 million persons with substance dependence or abuse in 2008, 3.1 million were dependent on or abused both alcohol and illicit drugs, 3.9 million were dependent on or abused illicit drugs only, and 15.2 million were dependent on or abused alcohol only.

Of the 22.5 million persons with substance dependence or abuse in 2009, 3.2 million were dependent on or abused both alcohol and illicit drugs, 3.9 million were dependent on or abused illicit drugs only, and 15.4 million were dependent on or abused alcohol only.

Of the 22.1 million persons with substance dependence or abuse in 2010, 2.9 million were dependent on or abused both alcohol and illicit drugs, 4.2 million were dependent on or abused illicit drugs only, and 15.0 million were dependent on or abused alcohol only.

Long description end. Return to Figure 7.1.

Long description, Figure 7.2. Figure 7.2 is titled "Specific Illicit Drug Dependence or Abuse in the Past Year among Persons Aged 12 or Older: 2010." It is a bar graph, where the numbers in thousands of users with dependence or abuse are shown on the horizontal axis and nine specific illicit drugs (marijuana, pain relievers, cocaine, tranquilizers, hallucinogens, heroin, stimulants, sedatives, and inhalants) are shown on the vertical axis.

The number of persons aged 12 or older who had dependence or abuse of marijuana in the past year was 4,476,000.

The number of persons aged 12 or older who had dependence or abuse of pain relievers in the past year was 1,921,000.

The number of persons aged 12 or older who had dependence or abuse of cocaine in the past year was 1,003,000.

The number of persons aged 12 or older who had dependence or abuse of tranquilizers in the past year was 521,000.

The number of persons aged 12 or older who had dependence or abuse of hallucinogens in the past year was 397,000.

The number of persons aged 12 or older who had dependence or abuse of heroin in the past year was 359,000.

The number of persons aged 12 or older who had dependence or abuse of stimulants in the past year was 357,000.

The number of persons aged 12 or older who had dependence or abuse of sedatives in the past year was 162,000.

The number of persons aged 12 or older who had dependence or abuse of inhalants in the past year was 161,000.

Long description end. Return to Figure 7.2.

Long description, Figure 7.3. Figure 7.3 is titled "Illicit Drug Dependence or Abuse in the Past Year among Persons Aged 12 or Older: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the numbers in millions of users with dependence or abuse of specific illicit drugs is shown on the vertical axis. For each drug category (illicit drugs, marijuana, cocaine, and pain relievers), there is a line showing dependence or abuse over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

The number of persons aged 12 or older with dependence or abuse of illicit drugs in the past year was 7.1 million in 2002, 6.8 million in 2003, 7.3 million in 2004, 6.8 million in 2005, 7.0 million in 2006, 6.9 million in 2007, 7.0 million in 2008, and 7.1 million in both 2009 and 2010.

The number of persons aged 12 or older with dependence or abuse of marijuana in the past year was 4.3 million in 2002, 4.2 million in 2003, 4.5 million in 2004, 4.1 million in 2005, 4.2 million in 2006, 3.9 million in 2007, 4.2 million in 2008, 4.3 million in 2009, and 4.5 million in 2010. The difference between the 2010 estimate and the 2007 estimate was statistically significant.

The number of persons aged 12 or older with dependence or abuse of cocaine in the past year was 1.5 million in both 2002 and 2003, 1.6 million in 2004, 1.5 million in 2005, 1.7 million in 2006, 1.6 million in 2007, 1.4 million in 2008, 1.1 million in 2009, and 1.0 million in 2010. The differences between the 2010 estimate and the 2002, 2003, 2004, 2005, 2006, 2007, and 2008 estimates were statistically significant.

The number of persons aged 12 or older with dependence or abuse of pain relievers in the past year was 1.5 million in 2002, 1.4 million in both 2003 and 2004, 1.5 million in 2005, 1.6 million in 2006, 1.7 million in both 2007 and 2008, and 1.9 million in both 2009 and 2010. The differences between the 2010 estimate and the 2002, 2003, 2004, and 2005 estimates were statistically significant.

Long description end. Return to Figure 7.3.

Long description, Figure 7.4. Figure 7.4 is titled "Alcohol Dependence or Abuse in the Past Year among Adults Aged 21 or Older, by Age at First Use of Alcohol: 2010." It is a bar graph, where the age at first use of alcohol is shown on the horizontal axis and the percentage with alcohol dependence or abuse in the past year is shown on the vertical axis. Each bar is divided into two sections: (1) alcohol dependence and (2) alcohol abuse. Due to rounding, the stacked bar totals may not add to the overall total. Four groups of age at first use are shown: 14 or younger, 15 to 17, 18 to 20, and 21 or older.

Among adults aged 21 or older who first used alcohol at age 14 or younger, 15.1 percent had alcohol dependence or abuse in the past year; this can be further broken down as follows: 7.6 percent had alcohol dependence, and 7.5 percent had alcohol abuse.

Among adults aged 21 or older who first used alcohol at age 15 to 17, 9.1 percent had alcohol dependence or abuse in the past year; this can be further broken down as follows: 4.1 percent had alcohol dependence, and 5.1 percent had alcohol abuse.

Among adults aged 21 or older who first used alcohol at age 18 to 20, 4.4 percent had alcohol dependence or abuse in the past year; this can be further broken down as follows: 2.3 percent had alcohol dependence, and 2.0 percent had alcohol abuse.

Among adults aged 21 or older who first used alcohol at age 21 or older, 2.7 percent had alcohol dependence or abuse in the past year; this can be further broken down as follows: 1.2 percent had alcohol dependence, and 1.5 percent had alcohol abuse.

Long description end. Return to Figure 7.4.

Long description, Figure 7.5. Figure 7.5 is titled "Alcohol and Illicit Drug Dependence or Abuse among Youths Aged 12 to 17: 2002 through 2010." It is a line graph, where survey years are shown on the horizontal axis and the percentage with alcohol or illicit drug dependence or abuse in the past year is shown on the vertical axis. For each type of dependence or abuse (illicit drugs, alcohol, and alcohol or illicit drugs), there is a line showing dependence or abuse over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between the 2010 estimate and each of the previous years listed; significant results are indicated where appropriate.

Among youths aged 12 to 17, the percentage with illicit drug dependence or abuse in the past year was 5.6 percent in 2002, 5.1 percent in 2003, 5.3 percent in 2004, 4.7 percent in 2005, 4.6 percent in 2006, 4.3 percent in 2007, 4.6 percent in 2008, 4.3 percent in 2009, and 4.7 percent in 2010. The differences between the 2010 estimate and the 2002 and 2004 estimates were statistically significant.

Among youths aged 12 to 17, the percentage with alcohol dependence or abuse in the past year was 5.9 percent in both 2002 and 2003, 6.0 percent in 2004, 5.5 percent in 2005, 5.4 percent in both 2006 and 2007, 4.9 percent in 2008, 4.6 percent in 2009, and 4.5 percent in 2010. The differences between the 2010 estimate and the 2002, 2003, 2004, 2005, 2006, and 2007 estimates were statistically significant.

Among youths aged 12 to 17, the percentage with alcohol or illicit drug dependence or abuse in the past year was 8.9 percent in both 2002 and 2003, 8.8 percent in 2004, 8.0 percent in both 2005 and 2006, 7.7 percent in 2007, 7.6 percent in 2008, 7.0 percent in 2009, and 7.3 percent in 2010. The differences between the 2010 estimate and the 2002, 2003, 2004, 2005, and 2006 estimates were statistically significant.

Long description end. Return to Figure 7.5.

Long description, Figure 7.6. Figure 7.6 is titled "Substance Dependence or Abuse in the Past Year, by Age and Gender: 2010." It is a bar graph, where age categories are shown on the horizontal axis and the percentage dependent or abusing in the past year is shown on the vertical axis. There are three age categories: aged 12 or older, aged 12 to 17, and aged 18 or older. For each age category, there is a bar representing males and a bar representing females.

Among persons aged 12 or older, 11.6 percent of males and 5.9 percent of females had past year substance dependence or abuse.

Among persons aged 12 to 17, 6.9 percent of males and 7.7 percent of females had past year substance dependence or abuse.

Among persons aged 18 or older, 12.2 percent of males and 5.8 percent of females had past year substance dependence or abuse.

Long description end. Return to Figure 7.6.

Long description, Figure 7.7. Figure 7.7 is titled "Locations Where Past Year Substance Use Treatment Was Received among Persons Aged 12 or Older: 2010." It is a bar graph, where the numbers in thousands of persons receiving treatment are shown on the horizontal axis and the types of substance use treatment locations are shown on the vertical axis. There are eight types of substance use treatment locations: (1) self-help group, (2) outpatient rehabilitation, (3) outpatient mental health center, (4) inpatient rehabilitation, (5) hospital inpatient, (6) private doctor's office, (7) emergency room, and (8) prison or jail.

The number of persons aged 12 or older who received substance use treatment at a self-help group was 2,334,000.

The number of persons aged 12 or older who received substance use treatment at an outpatient rehabilitation facility was 1,689,000.

The number of persons aged 12 or older who received substance use treatment at an outpatient mental health center was 999,000.

The number of persons aged 12 or older who received substance use treatment at an inpatient rehabilitation facility was 986,000.

The number of persons aged 12 or older who received substance use treatment at a hospital as an inpatient was 731,000.

The number of persons aged 12 or older who received substance use treatment at a private doctor's office was 653,000.

The number of persons aged 12 or older who received substance use treatment at an emergency room was 467,000.

The number of persons aged 12 or older who received substance use treatment at a prison or jail was 342,000.

Long description end. Return to Figure 7.7.

Long description, Figure 7.8. Figure 7.8 is titled "Substances for Which Most Recent Treatment Was Received in the Past Year among Persons Aged 12 or Older: 2010." It is a bar graph, where the numbers in thousands of persons receiving their most recent treatment are shown on the horizontal axis and the substances for which the most recent treatment was received are shown on the vertical axis. There are eight substances: (1) alcohol, (2) marijuana, (3) pain relievers, (4) cocaine, (5) heroin, (6) tranquilizers, (7) stimulants, and (8) hallucinogens.

The number of persons aged 12 or older who reported that the most recent treatment they received in the past year was for alcohol was 2,596,000.

The number of persons aged 12 or older who reported that the most recent treatment they received in the past year was for marijuana was 1,021,000.

The number of persons aged 12 or older who reported that the most recent treatment they received in the past year was for pain relievers was 754,000.

The number of persons aged 12 or older who reported that the most recent treatment they received in the past year was for cocaine was 699,000.

The number of persons aged 12 or older who reported that the most recent treatment they received in the past year was for heroin was 417,000.

The number of persons aged 12 or older who reported that the most recent treatment they received in the past year was for tranquilizers was 350,000.

The number of persons aged 12 or older who reported that the most recent treatment they received in the past year was for stimulants was 343,000.

The number of persons aged 12 or older who reported that the most recent treatment they received in the past year was for hallucinogens was 333,000.

Long description end. Return to Figure 7.8.

Long description, Figure 7.9. Figure 7.9 is titled "Received Most Recent Treatment in the Past Year for the Use of Pain Relievers among Persons Aged 12 or Older: 2002 through 2010." It is a bar graph, where the survey years are shown on the horizontal axis and the numbers in thousands of persons whose most recent treatment was for the use of pain relievers are shown on the vertical axis. Bars are shown for 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

The number of persons aged 12 or older who reported that the most recent treatment they received in the past year was for pain relievers was 360,000 in 2002; 415,000 in 2003; 424,000 in 2004; 466,000 in 2005; 547,000 in 2006; 558,000 in 2007; 601,000 in 2008; 739,000 in 2009; and 754,000 in 2010. The differences between the 2010 estimate and the 2002, 2003, 2004, 2005, and 2006 estimates were statistically significant.

Long description end. Return to Figure 7.9.

Long description, Figure 7.10. Figure 7.10 is titled "Past Year Perceived Need for and Effort Made to Receive Specialty Treatment among Persons Aged 12 or Older Needing But Not Receiving Treatment for Illicit Drug or Alcohol Use: 2010." It is a pie chart, with the following written below the chart: "20.5 million Needing But Not Receiving Treatment for Illicit Drug or Alcohol Use." The pie chart shows the percentages of persons who did not feel the need for treatment, as well as the percentages of those who felt the need for treatment and made an effort and those who did not make an effort to get treatment.

Of the 20.5 million persons needing but not receiving treatment for illicit drug or alcohol use in the past year, 95.0 percent did not feel they needed treatment, 3.3 percent felt they needed treatment and did not make an effort to get it, and 1.7 percent felt they needed treatment and made an effort to get it.

Long description end. Return to Figure 7.10.

Long description, Figure 7.11. Figure 7.11 is titled "Reasons for Not Receiving Substance Use Treatment among Persons Aged 12 or Older Who Needed and Made an Effort to Get Treatment But Did Not Receive Treatment and Felt They Needed Treatment: 2007 through 2010 Combined." It is a bar graph, where the percentage reporting a particular reason is shown on the horizontal axis and the reasons for not receiving treatment are shown on the vertical axis. Eight reasons are shown: (1) no health coverage and could not afford cost, (2) not ready to stop using, (3) no transportation/inconvenient, (4) might have negative effect on job, (5) might cause neighbors/community to have negative opinion, (6) able to handle the problem without treatment, (7) had health coverage but did not cover treatment or did not cover cost, and (8) did not have time for treatment.

Among persons aged 12 or older who needed and made an effort to get treatment but did not receive treatment and felt they needed it, 38.8 percent indicated that they did not have health coverage and could not afford the cost, 30.2 percent indicated that they were not ready to stop using, 9.2 percent indicated that they had no transportation or it was inconvenient, 8.8 percent indicated that it might have a negative effect on their job, 8.5 percent indicated that it might cause neighbors/community to have a negative opinion of them, 8.0 percent indicated that they were able to handle the problem without treatment, 7.6 percent indicated that they had health coverage but it did not cover treatment or did not cover the cost, and 7.2 percent indicated that they did not have time for treatment.

Long description end. Return to Figure 7.11.

Chapter 8

Long description, Figure 8.1. Figure 8.1 is titled "Past Month Alcohol Use among Youths in NSDUH and MTF: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage using alcohol in the past month is shown on the vertical axis. For each survey's youths (NSDUH youths aged 12 to 17 and MTF 8th and 10th graders combined), there is a line showing use over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. There is a note under the figure that says, "MTF = Monitoring the Future; NSDUH = National Survey on Drug Use and Health." Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

The percentage of 8th and 10th graders using alcohol (in MTF) in the past month was 27.5 percent in 2002, 27.6 percent in 2003, 26.9 percent in 2004, 25.2 percent in 2005, 25.5 percent in 2006, 24.7 percent in 2007, 22.4 percent in 2008, 22.7 percent in 2009, and 21.4 percent in 2010. The differences between the 2010 estimate and the 2002, 2003, 2004, 2005, 2006, 2007, and 2009 estimates were statistically significant.

The percentage of 12 to 17 year olds using alcohol (in NSDUH) in the past month was 17.6 percent in 2002, 17.7 percent in 2003, 17.6 percent in 2004, 16.5 percent in 2005, 16.6 percent in 2006, 15.9 percent in 2007, 14.6 percent in 2008, 14.7 percent in 2009, and 13.6 percent in 2010. The differences between the 2010 estimate and the 2002, 2003, 2004, 2005, 2006, 2007, 2008, and 2009 estimates were statistically significant.

Long description end. Return to Figure 8.1.

Long description, Figure 8.2. Figure 8.2 is titled "Past Month Cigarette Use among Youths in NSDUH and MTF: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage using cigarettes in the past month is shown on the vertical axis. For each survey's youths (NSDUH youths aged 12 to 17 and MTF 8th and 10th graders combined), there is a line showing use over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. There is a note under the figure that says, "MTF = Monitoring the Future; NSDUH = National Survey on Drug Use and Health." Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

The percentage of 8th and 10th graders using cigarettes (in MTF) in the past month was 14.2 percent in 2002, 13.5 percent in 2003, 12.6 percent in 2004, 12.1 percent in 2005, 11.6 percent in 2006, 10.6 percent in 2007, 9.6 percent in 2008, 9.8 percent in 2009, and 10.4 percent in 2010. The differences between the 2010 estimate and the 2002, 2003, 2004, 2005, and 2006 estimates were statistically significant.

The percentage of 12 to 17 year olds using cigarettes (in NSDUH) in the past month was 13.0 percent in 2002, 12.2 percent in 2003, 11.9 percent in 2004, 10.8 percent in 2005, 10.4 percent in 2006, 9.8 percent in 2007, 9.1 percent in 2008, 8.9 percent in 2009, and 8.3 percent in 2010. The differences between the 2010 estimate and the 2002, 2003, 2004, 2005, 2006, 2007, and 2008 estimates were statistically significant.

Long description end. Return to Figure 8.2.

Long description, Figure 8.3. Figure 8.3 is titled "Past Month Marijuana Use among Youths in NSDUH and MTF: 2002 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage using marijuana in the past month is shown on the vertical axis. For each survey's youths (NSDUH youths aged 12 to 17 and MTF 8th and 10th graders combined), there is a line showing use over the years 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, and 2010. There is a note under the figure that says, "MTF = Monitoring the Future; NSDUH = National Survey on Drug Use and Health." Tests of statistical significance at the .05 level were performed between 2010 and each of the previous years listed; significant results are indicated where appropriate.

The percentage of 8th and 10th graders using marijuana (in MTF) in the past month was 13.1 percent in 2002, 12.3 percent in 2003, 11.2 percent in 2004, 10.9 percent in 2005, 10.4 percent in 2006, 10.0 percent in 2007, 9.8 percent in 2008, 11.2 percent in 2009, and 12.4 percent in 2010. The differences between the 2010 estimate and the 2004, 2005, 2006, 2007, 2008, and 2009 estimates were statistically significant.

The percentage of 12 to 17 year olds using marijuana (in NSDUH) in the past month was 8.2 percent in 2002; 7.9 percent in 2003; 7.6 percent in 2004; 6.8 percent in 2005; 6.7 percent in 2006, 2007, and 2008; 7.3 percent in 2009; and 7.4 percent in 2010. The differences between the 2010 estimate and the 2002, 2006, 2007, and 2008 estimates were statistically significant.

Long description end. Return to Figure 8.3.

Long description, Figure 8.4. Figure 8.4 is titled "Past Month Marijuana Use among Youths in NSDUH, MTF, and YRBS: 1971 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage using marijuana in the past month is shown on the vertical axis. There is a note under the figure that says, "MTF = Monitoring the Future; NSDUH = National Survey on Drug Use and Health; YRBS = Youth Risk Behavior Survey." Another note says, "NSDUH data for youths aged 12 to 17 are not presented for 1999 to 2001 because of design changes in the survey. These design changes preclude direct comparisons of estimates from 2002 to 2010 with estimates prior to 1999." For each data source, there is a line representing the percentage using marijuana during the past month for the years shown.

According to the NSDUH data for youths aged 12 to 17, the percentage of youths reporting past month marijuana use was 5.1 percent in 1971; 6.0 percent in 1972; 10.2 percent in 1974; 10.5 percent in 1976; 14.1 percent in 1977; 14.2 percent in 1979; 9.9 percent in 1982; 10.2 percent in 1985; 5.4 percent in 1988; 4.4 percent in 1990; 3.6 percent in 1991; 3.4 percent in 1992; 4.0 percent in 1993; 6.0 percent in 1994; 8.2 percent in 1995; 7.1 percent in 1996; 9.4 percent in 1997; 8.3 percent in 1998; 8.2 percent in 2002; 7.9 percent in 2003; 7.6 percent in 2004; 6.8 percent in 2005, 6.7 percent in 2006, 2007, and 2008; 7.3 percent in 2009; and 7.4 percent in 2010.

According to the MTF data for 8th and 10th graders combined, the percentage reporting past month marijuana use was 6.0 percent in 1991, 5.9 percent in 1992, 8.0 percent in 1993, 11.8 percent in 1994, 13.2 percent in 1995, 15.9 percent in 1996, 15.4 percent in 1997, 14.2 percent in 1998, 14.6 percent in 1999, 14.4 percent in 2000, 14.5 percent in 2001, 13.1 percent in 2002, 12.3 percent in 2003, 11.2 percent in 2004, 10.9 percent in 2005, 10.4 percent in 2006, 10.0 percent in 2007, 9.8 percent in 2008, 11.2 percent in 2009, and 12.4 percent in 2010.

According to the MTF data for 12th graders, the percentage reporting past month marijuana use was 27.1 percent in 1975, 32.2 percent in 1976, 35.4 percent in 1977, 37.1 percent in 1978, 36.5 percent in 1979, 33.7 percent in 1980, 31.6 percent in 1981, 28.5 percent in 1982, 27.0 percent in 1983, 25.2 percent in 1984, 25.7 percent in 1985, 23.4 percent in 1986, 21.0 percent in 1987, 18.0 percent in 1988, 16.7 percent in 1989, 14.0 percent in 1990, 13.8 percent in 1991, 11.9 percent in 1992, 15.5 percent in 1993, 19.0 percent in 1994, 21.2 percent in 1995, 21.9 percent in 1996, 23.7 percent in 1997, 22.8 percent in 1998, 23.1 percent in 1999, 21.6 percent in 2000, 22.4 percent in 2001, 21.5 percent in 2002, 21.2 percent in 2003, 19.9 percent in 2004, 19.8 percent in 2005, 18.3 percent in 2006, 18.8 percent in 2007, 19.4 percent in 2008, 20.6 percent in 2009, and 21.4 percent in 2010.

According to the YRBS combined data for 9th through 12th graders, the percentage reporting past month marijuana use was 14.7 percent in 1991, 17.7 percent in 1993, 25.3 percent in 1995, 26.2 percent in 1997, 26.7 percent in 1999, 23.9 percent in 2001, 22.4 percent in 2003, 20.2 percent in 2005, 19.7 percent in 2007, and 20.8 percent in 2009.

Long description end. Return to Figure 8.4.

Long description, Figure 8.5. Figure 8.5 is titled "Past Year Nonmedical Pain Reliever Use among Youths and Young Adults in NSDUH and MTF: 1994 through 2010." It is a line graph, where the survey years are shown on the horizontal axis and the percentage using pain relievers nonmedically in the past year is shown on the vertical axis. There is a note under the figure that says, "MTF = Monitoring the Future; NSDUH = National Survey on Drug Use and Health." A second note says, "NSDUH data are not presented for 1999 to 2001 because of design changes in the survey. These design changes preclude direct comparisons of estimates from 2002 to 2010 with estimates prior to 1999." Another note says, "Data for MTF are for 'narcotics other than heroin.' MTF estimates from 1994 to 2001 are not comparable with MTF estimates for 2002 and later due to questionnaire changes." For each data source, there is a line representing the percentage using pain relievers nonmedically during the past year for the years shown.

According to the NSDUH data for youths aged 12 to 17, the percentage reporting past year nonmedical pain reliever use was 3.2 percent in 1994, 3.0 percent in 1995, 3.7 percent in 1996, 3.6 percent in 1997, 3.1 percent in 1998, 7.6 percent in 2002, 7.7 percent in 2003, 7.4 percent in 2004, 6.9 percent in 2005, 7.2 percent in 2006, 6.7 percent in 2007, 6.5 percent in 2008, 6.6 percent in 2009, and 6.2 percent in 2010.

According to the NSDUH data for young adults aged 18 to 25, the percentage of young adults reporting past year nonmedical pain reliever use was 4.7 percent in 1994, 4.2 percent in 1995, 4.9 percent in 1996, 3.8 percent in 1997, 4.4 percent in 1998, 11.4 percent in 2002, 12.0 percent in 2003, 11.9 percent in 2004, 12.4 percent in 2005 and 2006, 12.1 percent in 2007, 12.0 percent in 2008, 11.9 percent in 2009, and 11.1 percent in 2010.

According to the MTF data for 12th graders, the percentage reporting past year nonmedical pain reliever use was 3.8 percent in 1994, 4.7 percent in 1995, 5.4 percent in 1996, 6.2 percent in 1997, 6.3 percent in 1998, 6.7 percent in 1999, 7.0 percent in 2000, 6.7 percent in 2001, 9.4 percent in 2002, 9.3 percent in 2003, 9.5 percent in 2004, 9.0 percent in 2005 and 2006, 9.2 percent in 2007, 9.1 percent in 2008, 9.2 percent in 2009, and 8.7 percent in 2010.

Long description end. Return to Figure 8.5.

Appendix B Alternative Text for Figure

Long description, Figure B.1. Figure B.1 is titled "Required Effective Sample in the 2010 NSDUH as a Function of the Proportion Estimated." It is a graph of a function within a coordinate plane; the horizontal axis shows the proportion estimated, and the vertical axis shows the required effective sample size. A horizontal line through the graph indicates that an effective sample size of 68 is required for the current rule. The graph decreases from an infinitely large required effective sample size when the estimated proportion is close to zero and approaches a local minimum of 50 when the estimated proportion is 0.20. The graph increases for estimated proportions greater than 0.20 until a required effective sample size of 68 is reached for an estimated proportion of 0.50. The graph decreases for estimated proportions greater than 0.50 and approaches a local minimum of 50 for the required effective sample size when the estimated proportion is 0.80. The graph increases for estimated proportions greater than 0.80 and reaches an infinitely large required effective sample size when the estimated proportion is close to 1.

Long description end. Return to Figure B.1.

Equations

Appendix A

Equation A.1. The adjustment factor a sub k as a function of lambda is defined as the ratio of two quantities. The quantity in the numerator is defined as the sum of two terms. The first term is calculated as the product of l sub k and the difference between u sub k and c sub k. The second term is calculated as the product of u sub k, the difference between c sub k and l sub k, and the value of the exponential function evaluated as the following product: capital A sub k multiplied by the transpose of the vector x sub k, multiplied by lambda. The quantity in the denominator is defined as the sum of two terms. The first term is the difference between u sub k and c sub k. The second term is calculated as the product of the difference between c sub k and l sub k and the value of the exponential function evaluated as the following product: capital A sub k multiplied by the transpose of the vector x sub k, multiplied by lambda.

Long description end. Return to Equation A.1.

Equation A.2. The quantity of the summation over s of the product of (x sub k, d sub k, and a sub k as a function of lambda), minus the quantity capital T tilde sub x is equal to zero.

Long description end. Return to Equation A.2.

Equation A.3. Delta of the parameters w and d equals the summation over all k in s of the ratio of d sub k to capital A sub k multiplied by the sum of the following two quantities. The first quantity is calculated as the product of the difference between a sub k and l sub k and the logarithm of the ratio of the difference between a sub k and l sub k to the difference between c sub k and l sub k. The second quantity is defined as the product of the difference between u sub k and a sub k and the logarithm of the ratio of the difference between u sub k and a sub k to the difference between u sub k and c sub k.

Long description end. Return to Equation A.3.

Appendix B

Equation B.1. p hat sub d is equal to capital Y hat sub d divided by capital N hat sub d

Long description end. Return to Equation B.1.

Equation B.2. The standard error of capital Y hat sub d is equal to capital N hat sub d times the standard error of p hat sub d.

Long description end. Return to Equation B.2.

Equation B.3. Two suppression rules are shown. The first indicates that suppressions occurred when the relative standard error of the negative of the natural logarithm of p hat was greater than .175 and p hat was less than or equal to .5.

Long description end. Return to Equation B.3.

Equation B.4. The second suppression rule indicates that suppressions also occurred when the relative standard error of the negative of the natural logarithm of the difference 1 minus p hat was greater than .175 and p hat was greater than .5.

Long description end. Return to Equation B.4.

Equation B.5. Two computational forms of the suppression rule are presented. The first indicates that suppressions occurred when p hat was less than or equal to .5 and the following ratio was greater than .175: The numerator of the ratio is the standard error of p hat divided by p hat; the denominator is the negative of the natural logarithm of p hat.

Long description end. Return to Equation B.5.

Equation B.6. The second computational form of the suppression rule indicates that suppressions also occurred whenever p hat was greater than .5 and the following ratio was greater than .175: The numerator is the standard error of p hat divided by the difference 1 minus p hat; the denominator is the negative of the natural logarithm of the difference 1 minus p hat.

Long description end. Return to Equation B.6.

Equation B.7. Capital Z is equal to the ratio of two quantities. The numerator is p hat sub 1 minus p hat sub 2. The denominator is the square root of the following quantity: the variance of p hat sub1, plus the variance of p hat sub 2, minus twice the covariance of p hat sub 1 and p hat sub 2.

Long description end. Return to Equation B.7.

Equation B.8. p bar sub 2 minus p bar sub 1

Long description end. Return to Equation B.8.

Equation B.9. The variance of p hat is equal to the product of 1 divided by n, capital D, p hat, and the difference 1 minus p hat.

Long description end. Return to Equation B.9.

Equation B.10. The variance of the quantity p hat sub 2 i minus p hat sub 1 i is equal to capital D sub i times the sum of two quantities. The first quantity is the product of 1 over n sub 1 i times p hat sub 1 i times the difference 1 minus p hat sub 1 i. The second quantity is the product of 1 over n sub 2 i times p hat sub 2 i times the difference 1 minus p hat sub 2 i. The variable i can take on the values 1 and 2.

Long description end. Return to Equation B.10.

Equation B.11. The variance of the quantity p bar sub 2 minus p bar sub 1 is equal to one quarter of the sum of two quantities. The first quantity is the variance of the difference of p hat sub two one minus p hat sub one one. The second quantity is the variance of the difference p hat sub two two minus p hat sub one two.

Long description end. Return to Equation B.11.

Equation B.12. Capital Z is equal to the ratio of two quantities. The numerator is p bar sub 2 minus p bar sub 1. The denominator is the square root of the variance of the quantity p bar sub 2 minus p bar sub 1.

Long description end. Return to Equation B.12.

Equation B.13. Capital S R R is equal to the ratio of two quantities. The numerator is the summation of the product of w sub h h and complete sub h h. The denominator is the summation of the product of w sub h h and eligible sub h h.

Long description end. Return to Equation B.13.

Equation B.14. Capital I R R is equal to the ratio of two quantities. The numerator is the summation of the product of w sub i and complete sub i. The denominator is the summation of the product of w sub i and selected sub i

Long description end. Return to Equation B.14.

Equation B.15. Capital O R R is equal to the product of capital S R R and capital I R R.

Long description end. Return to Equation B.15.

Equation B.16. Capital I, which stands for "past year initiate," as a function of i is equal to 1 if the date of the interview minus the date of initiation (first use) is less than or equal to 365. Capital I is equal to 0 otherwise.

Long description end. Return to Equation B.16.

Equation B.17. Estimated Past Year Initiates Aged 11 in 2009 times the Estimated Lifetime Users Aged 12 to 17 in 2010 divided by the Estimated Lifetime Users Aged 12 to 17 in 2009

Long description end. Return to Equation B.17.

Equation B.18. 77,477 times 8,573,937 over 9,382,813 is equal to 70,798.

Long description end. Return to Equation B.18.

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