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Appendix A: State Estimation Methodology

This report includes estimates of 22 substance use and mental health measures (see Section A.1) using the combined data from the 2007 and 2008 National Surveys on Drug Use and Health (NSDUHs). Also included in this report are comparisons between the 2006-2007 and the 2007-2008 State estimates and comparisons between the 2002-2003 and the 2007-2008 State estimates. As discussed in Chapter 1 (Section 1.1), several changes were introduced to the survey in 2002; thus, estimates for 2001 and prior years are not comparable with estimates from 2002 and later years.

The survey-weighted hierarchical Bayes (SWHB) methodology used in the production of State estimates from the 1999-2007 surveys also was used in the production of the 2007-2008 State estimates. The SWHB methodology is described in Appendix E of the 2001 State report (Wright, 2003b) and by Folsom, Shah, and Vaish (1999). The list of predictors used in the 2007-2008 small area estimation (SAE) modeling is given in Section A.2. In the production of the 2007-2008 small area estimates, new population projections (obtained from Claritas) were used. Information on the new projections and how they were used to create SAE model predictors is given in Section A.3. No new variable selection was done for the 2007-2008 data (as discussed in Section A.4). The goals of SAE modeling, general model description, and the implementation of SAE modeling remain the same and are described in Appendix E of the 2001 State report (Wright, 2003b). At the end of this appendix, tables showing the 2006, 2007, 2008, pooled 2006-2007, and pooled 2007-2008 survey sample sizes, population estimates, and response rates are included (Tables A.1 to A.12).

Small area estimates obtained using the SWHB methodology are design consistent (i.e., for States with large sample sizes, the small area estimates are close to the robust design-based estimates). The State small area estimates when aggregated using the appropriate population totals result in national small area estimates that are very close to the national design-based estimates. However, for numerous reasons (including internal consistency), it is desirable to have national small area estimates exactly match the national design-based estimates. Beginning in 2002, exact benchmarking was introduced as described in Section A.5. Tables of estimated numbers of persons associated with each outcome (in thousands) are available on the Web in the form of HTML tables (see http://www.samhsa.gov/data/2k8State/toc.htm). An explanation of how these counts and their respective prediction intervals (PIs) are calculated can be found in Section A.6. The definition and explanation of the formula used in estimating the marijuana incidence rate is given in Section A.7.

For all outcomes except major depressive episode (MDE), the age groups for which estimates are provided in this report are 12 to 17, 18 to 25, and 26 or older. Estimates for those aged 12 or older also are provided in this report. Because it was determined that States may find estimates for persons aged 18 or older useful, estimates for that age group will be available on the Web in the form of HTML tables (see http://www.samhsa.gov/data/2k8State/toc.htm). Note that for MDE, tables are included only for youths aged 12 to 17. For details, refer to Section A.10.

Also included in this report are estimates of underage (aged 12 to 20) alcohol use and binge alcohol use. Alcohol consumption is expected to differ significantly across the 18 to 25 age group because of the legalization of alcohol at age 21. Therefore, it was decided that it would be useful to produce small area estimates for persons aged 12 to 20. A short description of the methodology used to produce underage drinking estimates is provided in Section A.8.

Section A.9 discusses the criteria used to define dependence on and abuse of illicit drugs and alcohol. Section A.10 discusses the production of MDE estimates. Section A.11 discusses the method to compare prevalence rates of a particular outcome between two States. The methodology used to compare the 2006-2007 and the 2007-2008 State estimates and the 2002-2003 and the 2007-2008 State estimates is described in Section A.12.

A.1 Variables Modeled

The 2008 NSDUH data were pooled with the 2007 NSDUH data, and age group-specific State prevalence estimates for 22 binary (0, 1) outcome variables were produced and presented in this report in Appendix B. Note that serious psychological distress (SPD) is not included in this list as discussed in Chapter 1. Estimates were produced for the following outcomes:

  1. past month use of illicit drugs,

  2. past year use of marijuana,

  3. past month use of marijuana,

  4. perception of great risk of smoking marijuana once a month,

  5. average annual rate of first use of marijuana,

  6. past month use of illicit drugs other than marijuana,

  7. past year use of cocaine,

  8. past year nonmedical use of pain relievers,

  9. past month use of alcohol,

  10. past month binge alcohol use,

  11. perception of great risk of having five or more drinks of an alcoholic beverage once or twice a week,

  12. past month use of tobacco products,

  13. past month use of cigarettes,

  14. perception of great risk of smoking one or more packs of cigarettes per day,

  15. past year alcohol dependence or abuse,

  16. past year alcohol dependence,

  17. past year illicit drug dependence or abuse,

  18. past year illicit drug dependence,

  19. past year dependence on or abuse of illicit drugs or alcohol,

  20. needing but not receiving treatment for illicit drug use in the past year,

  21. needing but not receiving treatment for alcohol use in the past year, and

  22. past year major depressive episode (MDE).

Comparisons between the 2006-2007 and the 2007-2008 State estimates were produced for all of these outcomes and are included in this report in Appendix C. In addition, tests of change between the 2002-2003 and the 2007-2008 State estimates were produced for all outcomes except MDE and are included in this report in Appendix D. Also included at the end of this appendix is a table listing all outcomes and the years for which small area estimates were produced going back to the 2002 NSDUH (Table A.13).

A.2 Predictors Used in Mixed Logistic Regression Models

Local area data used as potential predictor variables in the mixed logistic regression models were obtained from several sources, including Claritas Inc., the U.S. Census Bureau, the Federal Bureau of Investigation (FBI) (Uniform Crime Reports), Health Resources and Services Administration (Area Resource File), the Bureau of Labor Statistics, the Bureau of Economic Analysis, the Substance Abuse and Mental Health Services Administration (SAMHSA) (National Survey of Substance Abuse Treatment Services [N-SSATS]), and the National Center for Health Statistics (mortality data). The values of these predictor variables are updated every year (when possible). Major sources and potential data items used in the modeling are provided in the following text and lists.

The following lists provide the specific independent variables that were potential predictors in the models.

Claritas Data (Description) Claritas Data (Level)
% Population aged 0-19 in block group Block group
% Population aged 20-24 in block group Block group
% Population aged 25-34 in block group Block group
% Population aged 35-44 in block group Block group
% Population aged 45-54 in block group Block group
% Population aged 55-64 in block group Block group
% Population aged 65+ in block group Block group
% Non-Hispanic Blacks in block group Block group
% Hispanics in block group Block group
% Non-Hispanic Other race in block group Block group
% Non-Hispanic Whites in block group Block group
% Males in block group Block group
% Females in block group Block group
% American Indian, Eskimo, Aleut in tract Tract
% Asian, Pacific Islander in tract Tract
% Population aged 0-19 in tract Tract
% Population aged 20-24 in tract Tract
% Population aged 25-34 in tract Tract
% Population aged 35-44 in tract Tract
% Population aged 45-54 in tract Tract
% Population aged 55-64 in tract Tract
% Population aged 65+ in tract Tract
% Non-Hispanic Blacks in tract Tract
% Hispanics in tract Tract
% Non-Hispanic Other race in tract Tract
% Non-Hispanic Whites in tract Tract
% Males in tract Tract
% Females in tract Tract
% Population aged 0-19 in county County
% Population aged 20-24 in county County
% Population aged 25-34 in county County
% Population aged 35-44 in county County
% Population aged 45-54 in county County
% Population aged 55-64 in county County
% Population aged 65+ in county County
% Non-Hispanic Blacks in county County
% Hispanics in county County
% Non-Hispanic Other race in county County
% Non-Hispanic Whites in county County
% Males in county County
% Females in county County

2000 Census Data (Description) 2000 Census Data (Level)
% Population who dropped out of high school Tract
% Housing units built in 1940-1949 Tract
% Persons aged 16-64 with a work disability Tract
% Hispanics who are Cuban Tract
% Females 16 years or older in labor force Tract
% Females never married Tract
% Females separated/divorced/widowed/other Tract
% One-person households Tract
% Female head of household, no spouse, child #under 18 Tract
% Males 16 years or older in labor force Tract
% Males never married Tract
% Males separated/divorced/widowed/other Tract
% Housing units built in 1939 or earlier Tract
Average persons per room Tract
% Families below poverty level Tract
% Households with public assistance income Tract
% Housing units rented Tract
% Population with 9-12 years of school, no high school diploma Tract
% Population with 0-8 years of school Tract
% Population with associate's degree Tract
% Population with some college and no degree Tract
% Population with bachelor's, graduate, professional degree Tract
Median rents for rental units Tract
Median value of owner-occupied housing units Tract
Median household income Tract

Uniform Crime Report Data (Description) Uniform Crime Report Data (Level)
Drug possession arrest rate County
Drug sale/manufacture arrest rate County
Drug violations' arrest rate County
Marijuana possession arrest rate County
Marijuana sale/manufacture arrest rate County
Opium or cocaine possession arrest rate County
Opium or cocaine sale/manufacture arrest rate County
Other drug possession arrest rate County
Other dangerous non-narcotics arrest rate County
Serious crime arrest rate County
Violent crime arrest rate County
Driving under influence arrest rate County

Other Categorical Data (Description) Other Categorical Data (Source) Other Categorical Data (Level)
=1 if Hispanic, =0 otherwise NSDUH sample Person
=1 if non-Hispanic black, =0 otherwise NSDUH sample Person
=1 if non-Hispanic other, =0 otherwise NSDUH sample Person
=1 if male, =0 if female NSDUH sample Person
=1 if MSA with ≥1 million, =0 otherwise 2000 Census County
=1 if MSA with <1 million, =0 otherwise 2000 Census County
=1 if non-MSA urban, =0 otherwise 2000 Census Tract
=1 if urban area, =0 if rural area 2000 Census Tract
=1 if no Cubans in tract, =0 otherwise 2000 Census Tract
=1 if no arrests for dangerous non-narcotics,
=0 otherwise
UCR County

Miscellaneous Data (Variable Description) Miscellaneous Data (Source) Miscellaneous Data (Level)
Alcohol death rate, underlying cause NCHS-ICD-10 County
Cigarettes death rate, underlying cause NCHS-ICD-10 County
Drug death rate, underlying cause NCHS-ICD-10 County
Alcohol treatment rate N-SSATS (formerly called UFDS) County
Alcohol and drug treatment rate N-SSATS (formerly called UFDS) County
Drug treatment rate N-SSATS (formerly called UFDS) County
% Families below poverty level ARF County
Unemployment rate BLS County
Per capita income (in thousands) BEA County
Average suicide rate (per 10,000) NCHS-ICD-10 County
Food stamp participation rate Census Bureau County
Single State agency maintenance of effort National Association of State Alcohol and Drug Abuse Directors (NASADAD) State
Block grant awards SAMHSA State
Cost of Services Factor Index SAMHSA State
Total Taxable Resources Per Capita Index U.S. Department of Treasury State

A.3 Updated Claritas Data

For the previously published State and substate reports using the 2002 to 2007 NSDUH data, Claritas data obtained in 2002 were used to produce the small area estimates. The 2002 Claritas data had 2000 and 2002 population counts, as well as 2007 population projections. Claritas data were used for the following in the NSDUH SAE process:

  1. Creating demographic predictor variables (age group, race × ethnicity, and gender) at the block group, tract, and county levels (predictors such as percentage of the population aged 0 to 19 in a block group, percentage of population who are males in a tract). There are 13 such variables defined for each of the census geographies (block group, tract, and county). See Section A.2 for a complete list of these predictors.

  2. Creating census block group-level population projections at the age group × race/ethnicity × gender level (4 age groups, 4 races/ethnicities, and 2 genders = 32 cells) that are used in producing aggregate State-level small area estimates.8
  1. In the 2008 SAE process, new Claritas data with 2008 population counts and 2012 population projections were used. The new Claritas data will be henceforth referred to as the 2008-2012 Claritas data, and the 2002 Claritas data will be referred to as the 2002-2007 Claritas data. After doing some data exploration on the 2008-2012 Claritas data and comparing them with the 2002-2007 Claritas data, some differences were observed when comparing the 2007 population counts (from the 2002-2007 Claritas data) with the 2008 population counts (from the 2008-2012 Claritas data). For example, the distributions of the population aged 20 to 24 in block groups were very different for the two datasets. Another difference was that there were more block groups that had a 0 population count for some of the 32 cells in 2008 as compared with the 32 cells in 2007.

  2. The format of the race/ethnicity data was also different for the two sets of Claritas data. To generate age group × race × Hispanicity × gender population counts at the block group level using the 2002-2007 Claritas data, two separate population distributions (age × gender × race and race × Hispanicity) at the block group level had to be used. The assumption that each of the age × gender cells within a race group had the same Hispanicity distribution was made. So, the data were manipulated to get the desired four-way cross of demographic domains. The 2008-2012 Claritas data have age group × race × Hispanicity × gender population distributions, so no assumptions or manipulations to the data had to be made.
  1. In prior State reports when creating the 32 cells using the 2002-2007 Claritas data, the population from the 2 or more races category was distributed among the black, white, and other race categories. Starting in 2008 and subsequent years, a decision was made to merge the two or more races category with the other race category. This was based on a decision to discontinue creating a NSDUH sample variable that split the two or more races respondents into black, white, or other. Because NSDUH respondents with 2 or more races were now being grouped into the other category, the same technique was used to produce the 32 cell counts.

Some of the data differences can be attributed to reasons (2b) and (3), and the rest are most likely attributed to the fact that the 2008-2012 Claritas projections are based on updated population information. Because of these differences in the 2007 population projections based on 2002-2007 Claritas data and the 2008 population counts based on 2008-2012 Claritas data, it was decided that "new" 2007 population projections would be obtained by "projecting back" the 2008-2012 Claritas data. Population projections for 2006 also would be obtained in the same manner, so that they could be used in the upcoming 2006-2008 substate SAE report and in the simultaneous modeling of 2006-2008 data to test for change between 2006-2007 and 2007-2008 in this report.

In summary, based on the information above, the following steps were taken for the current (2007-2008) SAE analysis:

  1. For the predictors created using the Claritas data, linear extrapolations of the 2008-2012 Claritas data were done to get the 2006 and 2007 populations, and each of the 13 block group, tract, and county-level predictors was recreated and merged onto the 2006 and 2007 sample and universe files (the universe file is a block group-level file for the entire Nation).

  2. The 2007 and 2008 sample files (with the updated Claritas predictors) were pooled and used to create new decile cutoffs for categorical variables (and subsequently used to produce orthogonal polynomials) for all the predictors. These new cutoffs were also used to create updated 2006 sample files. Additionally, they were used to create updated categorical variables for all predictors on the 2006, 2007, and 2008 universe files.

  3. The updated population counts for the 32 cells (age group × race/ethnicity × gender population counts) and the new deciles were used to create the updated universe files for all 3 years (2006, 2007, and 2008).

  4. For any analysis using 2002 through 2005 NSDUH data, the old projections based on the 2002-2007 Claritas data were used (i.e., for the 2002-2003 vs. 2007-2008 comparisons, the 2002-2007 Claritas projections were used on the 2002-2003 sample and universe files, whereas the 2008-2012 Claritas projections were used on the 2007-2008 sample and universe files).

Hence, the 2007-2008 small area estimates presented in this report are produced using the updated Claritas predictors for both years of data. For producing the change estimates between the 2006-2007 and 2007-2008 small area estimates, the correlations were based on the updated Claritas predictors (however, the 2006-2007 small area estimates were not reproduced based on the new data).

Note that these population projections needed to be updated to guarantee that the most up-to-date population counts were being used. However, it was decided not to reproduce the 2006-2007 small area estimates using the new counts to be consistent with the current practice of not updating previously published estimates. Despite not knowing the exact impact of using new population counts to calculate the correlation between 2006-2007 and 2007-2008 estimates, it is reasonable to expect that this should have minimal impact on the variances of change estimates (and consequently the p values).

A.4 Selection of Independent Variables for the Models

No new variable selection was done for any outcome variables in 2007-2008. The updated versions of fixed-effect predictors that were used in modeling the 2006-2007 data were used to model the 2007-2008 data. Because the interest was to estimate change between the 2006-2007 and 2007-2008 State estimates, the same set of fixed-effect predictors was used for producing both sets of estimates.

A.5 Benchmarking the Age group-specific Small Area Estimates

The self-calibration built into the SWHB solution ensures that the population-weighted average of the State small area estimates will closely match the national design-based estimates. Given the self-calibration ensured by the SWHB solution, for State reports prior to 2002, the standard Bayes prescription was followed; specifically, the posterior mean was used for the point estimate, and the tail percentiles of the posterior distribution were used for the prediction interval (PI) limits.

Singh and Folsom (2001) extended Ghosh's (1992) results on constrained Bayes estimation to include exact benchmarking to design-based national estimates. In the simplest version of this constrained Bayes solution where only the design-based mean is imposed as a benchmarking constraint, each of the State-by-age group small area estimates (for 2007-2008) is adjusted by adding the common factor Δa = (Da - Pa), where Da is the design-based national prevalence estimate and Pa is the population-weighted mean of the State small area estimates (Psa) for age group-a. The exactly benchmarked State-s and age group-a small area estimates then are given by θsa = Psa+ Δa. Experience with such additive adjustments suggests that the resulting exactly benchmarked State small area estimates will always be between 0 and 100 percent because the SWHB self-calibration ensures that the adjustment factor is small relative to the size of the State-level small area estimates.

Relative to the Bayes posterior mean, these benchmark-constrained State small area estimates are biased by the common additive adjustment factor. Therefore, the posterior mean-squared error for each benchmarked State small area estimate has the square of this adjustment factor added to its posterior variance. To achieve the desirable feature of exact benchmarking, this constrained Bayes adjustment factor was implemented for the State-by-age group small area estimates. The associated credible intervals can be recentered at the benchmarked small area estimates on the logit scale with the symmetric interval end points based on the posterior root mean-squared errors. The adjusted 95 percent PIs (Lowersa , Uppersa) are defined below:

Lowersa = exp(Lsa) / [1 + exp(Lsa)] and Uppersa = exp(Usa) / [1 + exp(Usa)],     D

where

Lsa = ln[θsa / (1 - θsa)] - 1.96 * The square root of M S E sub s a,     D

Usa = ln[θsa / (1 - θsa)] + 1.96 * The square root of M S E sub s a, and      D

MSEsa = (ln[Psa / (1 - Psa)] - ln[θsa / (1 - θsa)])2 + posterior variance of ln[Psa / (1 - Psa)].     D

The associated posterior coverage probabilities for these benchmarked intervals are very close to the prescribed 0.95 value because the State small area estimates have posterior distributions that can be approximated exceptionally well by a Gaussian distribution.

A.6 Calculation of Estimated Number of Persons Associated with Each Outcome

Tables 1 to 23, available at http://www.samhsa.gov/data/2k8State/toc.htm, show the estimated numbers of persons (in thousands) associated with each of the 22 outcomes of interest. To calculate these estimated numbers of persons, the benchmarked small area estimates and the associated 95 percent PIs are multiplied by the average population across the 2 years (in this case, 2007 and 2008) of the State by age group of interest.

For example, past month use of alcohol among 18 to 25 year olds in Alabama was 52.32 percent (see Table B.9 in Appendix B). The corresponding PIs ranged from 48.45 to 56.17 percent. The population count for 18 to 25 year olds averaged across 2007-2008 in Alabama was 499,641 (see Table A.10). Hence, the estimated number of 18 to 25 year olds using alcohol in the past month in Alabama was 0.5232 * 499,641, which is 261,412 (see Table 9). The associated PIs ranged from 0.4845 * 499,641 (i.e., 242,076) to 0.5617 * 499,641 (i.e., 280,648). Note that when estimates of the number of persons are calculated for Tables 1 to 23, the unrounded prevalence estimates and population counts are used. Hence, the number obtained by multiplying the published prevalence rate with the published population estimate may not exactly match the counts that are published in these tables due to rounding differences.

A.7 Calculation of Average Annual Incidence of Marijuana Use

Incidence rates typically are calculated as the number of new initiates of a substance during a period of time (such as in the past year) divided by an estimate of the number of person years of exposure (in thousands). The incidence definition used in this report employs a simpler form of the at-risk population based on the model-based methodology. This model-based average annual incidence rate is defined as follows:

Average annual rate = 100*{[X1 ÷ (0.5 * X1 + X2)] ÷ 2},     D

where X1 is the number of marijuana initiates in the past 24 months and X2 is the number of persons who never used marijuana.

In this report, the incidence rate is expressed as a percentage or rate per 100 person years of exposure. Note that this estimate uses a 2-year time period to accumulate incidence cases from each annual survey. By assuming further that the distribution of first use for the incidence cases is uniform across the 2-year interval, the total number of person years of exposure is 1 year on average for the incidence cases plus 2 years for all the "never users" at the end of the time period. This approximation to the person years of exposure permits one to recast the incidence rate as a function of two population prevalence rates, namely, the fraction of persons who first used marijuana in the past 2 years and the fraction who had never used marijuana. Both of these prevalence estimates were estimated using the SWHB estimation approach.

The count of persons who first used marijuana in the past 2 years is based on a "moving" 2-year period that ranges over 3 calendar years. Subjects were asked when they first used marijuana. If a person indicated first use of marijuana between the day of the interview and 2 years prior, the person was included in the count. Thus, it is possible for a person interviewed in the first part of 2008 to indicate first use as early as the first part of 2006 or as late as the first part of 2008. Similarly, a subject interviewed in the last part of 2008 could indicate first use as early as the last part of 2006 or as late as the last part of 2008. Therefore, in the 2008 survey, the reported period of first use ranged from early 2006 to late 2008 and was "centered" in 2007. About half of the 12 to 17 year olds who reported first use in the past 24 months reported first use in 2007, while a quarter each reported first use in 2006 and 2008. Persons who responded in 2008 that they had never used marijuana were included in the count of "never used." Similarly, reports of first use in the past 24 months from the 2007 survey ranged from early 2005 to late 2007 and were centered in 2006. Half of the 12 to 17 year olds who reported first use in the past 24 months reported first use in 2006, while a quarter each reported first use in 2005 and 2007. Note that only incidence rates for marijuana use are provided in this report.

A.8 Underage Drinking

To obtain small area estimates for persons aged 12 to 20 for past month alcohol and binge alcohol use, a separate set of models was fit for these two outcomes for the 12 to 17 age group and the 18 to 20 age group. For the 2007-2008 models, no new variable selection was done. Updated versions of the predictors were used to produce the small area estimates.

Model-based estimates for persons aged 12 to 20 were produced by taking the population-weighted average of the individual age group (12 to 17 and 18 to 20) estimates. Estimates for underage drinking for past month alcohol and binge alcohol use were benchmarked to match national design-based estimates for that age group using the process described in Section A.5. Comparisons between the 2006-2007 and the 2007-2008 small area estimates for underage drinking in the States also are presented in this report.

A.9 Illicit Drug and Alcohol Dependence and Abuse

The NSDUH computer-assisted interviewing (CAI) instrumentation includes questions that are designed to measure dependence on and abuse of illicit drugs and alcohol. For these substances,9 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.

For additional details on how respondents were classified as being dependent on or having abused illicit drugs and alcohol, see Section B.4.3 in Appendix B of the 2008 NSDUH national findings report (OAS, 2009, pp. 140-142).

A.10 Major Depressive Episode

Beginning in 2004, a module was included in the questionnaire that was related to having a major depressive episode (MDE); it was derived from the criteria specified for major depression in the DSM-IV (APA, 1994). These questions permit estimates to be calculated for lifetime and past year prevalence of MDE, treatment for MDE, and role impairment resulting from MDE. In this report, estimates of having at least one MDE in the past year are reported.

In 2004, a split-sample design was implemented where adults aged 18 or older in half of the sample received the depression module while adult respondents in the other half did not. All adolescents aged 12 to 17 were administered the adolescent depression module that year. In 2005, 2006, 2007, and 2008 all adult and adolescent respondents were administered their respective depression modules. Separate modules were administered to adults 18 or older and youths aged 12 to 17. To make the modules developmentally appropriate for youths, there are minor wording differences in a few questions between the adult and youth modules. Since 2004, the NSDUH questions that determine MDE have remained unchanged. However, because of changes to other mental health items that precede the adult MDE questions (K6, suicide, and impairment) in the 2008 questionnaire, the reporting on MDE questions among adults appears to have been affected. Thus, MDE small area estimates for adults were not produced for 2007-2008 because the 2008 MDE estimates are not comparable with those for 2007. Hence, only MDE estimates for youths aged 12 to 17 are produced for this report because youth estimates were not affected by the questionnaire change. Comparisons between 2006-2007 and 2007-2008 MDE estimates for youths also are included in this report. For more details on the effects of the questionnaire changes to the MDE estimates, see Section B.4.4 in Appendix B of the 2008 NSDUH national findings report (OAS, 2009, pp. 142-145).

According to DSM-IV, a person is defined as having had MDE in his or her lifetime if he or she has had at least five or more of the following nine symptoms nearly every day in the same 2-week period, where at least one of the symptoms is a depressed mood or loss of interest or pleasure in daily activities (APA, 1994): (1) depressed mood most of the day; (2) markedly diminished interest or pleasure in all or almost all activities most of the day; (3) significant weight loss when not sick or dieting, or weight gain when not pregnant or growing, or decrease or increase in appetite; (4) insomnia or hypersomnia; (5) psychomotor agitation or retardation; (6) fatigue or loss of energy; (7) feelings of worthlessness; (8) diminished ability to think or concentrate or indecisiveness; and (9) recurrent thoughts of death or suicidal ideation. Respondents who have had MDE in their lifetime are asked if, during the past 12 months, they had a period of depression lasting 2 weeks or longer while also having some of the other symptoms mentioned. Those reporting that they have are defined as having had MDE in the past year.

For details on the adult and adolescent modules for MDE, see Section B.4.7 in Appendix B of the 2008 NSDUH national findings report (OAS, 2009, pp. 152-155).

A.11 Method for Determining Differences between Two State Estimates for 2007-2008

This section describes a method for determining whether differences between two 2007-2008 State estimates are statistically significant. This procedure can be used for any two State estimates representing the same age group (e.g., young adults aged 18 to 25) and time period (e.g., 2007-2008).

Let π1a and π2a denote the 2007-2008 age group-a specific prevalence rates for two different States, s1 and s2, respectively. The null hypothesis of no difference, that is, π1a = π2a, is equivalent to the log-odds ratio equal to zero, that is, lora = 0, where lora is defined as The log-odds ratio, lor sub a, is defined as the natural logarithm of the ratio of two quantities. The numerator of the ratio is Pi 2 sub a, divided by 1 minus Pi 2 sub a. The denominator of the ratio is Pi 1 sub a, divided by 1 minus Pi 1 sub a., where ln denotes the natural logarithm. An estimate of lora is given by The estimate of the log-odds ratio, lor hat sub a, is defined as the natural logarithm of the ratio of two quantities. The numerator of the ratio is p 2 sub a, divided by 1 minus p 2 sub a. The denominator of the ratio is p 1 sub a, divided by 1 minus p 1 sub a, where p 1 sub a is the 2006-2007 State estimate for State s1 and age group a and p 2 sub a is the 2006-2007 State estimate for State s2 and age group a for a particular outcome of interest., where p1a and p2a are the 2007-2008 State estimates given in Appendix B. To compute the variance of estimate of the log-odds ratio, lor hat sub a, that is, variance of the estimate of the log-odds ratio, lor hat sub a, let Theta 1 hat is defined as the ratio of p 1 sub a and 1 minus p 1 sub a and Theta 2 hat is defined as the ratio of p 2 sub a and 1 minus p 2 sub a., then Variance v of the estimate of the log-odds ratio, lor hat sub a, is a function of three quantities: q1, q2, and q3. It is expressed as the sum of q1 and q2 minus q3. Quantity q1 is the variance of the natural logarithm of Theta 1 hat, quantity q2 is the variance of the natural logarithm of Theta 2 hat, and quantity q3 is 2 times the covariance between the natural logarithm of Theta 1 hat and the natural logarithm of Theta 2 hat,

where covariance between the natural logarithm of Theta 1 hat and the natural logarithm of Theta 2 hat denotes the covariance between image represents the natural logarithm of Theta 1 hat and image represents the natural logarithm of Theta 2 hat. This covariance is defined in terms of the associated correlation as follows:

Equation A-5.     D

The quantities variance of the natural logarithm of Theta 1 hat and variance of the natural logarithm of Theta 2 hat can be obtained by using the 95 percent PIs given in Appendix B. For this purpose, let (lower1,upper1) and (lower2,upper2) denote the 95 percent PIs for the two States, s1 and s2, respectively. Then

Equation A-7     D

where U sub i is the natural logarithm of upper sub i divided by 1 minus upper sub i, and L sub i is the natural logarithm of lower sub i divided by 1 minus lower sub i.

For all practical purposes, the correlation between image represents the natural logarithm of Theta 1 hat and image represents the natural logarithm of Theta 2 hat is assumed to be negligible; hence, variance of the estimate of the log-odds ratio, lor hat sub a can be approximated by Variance v of the estimate of the log-odds ratio, lor hat sub a, is approximated by the sum of the variance of the natural logarithm of Theta 1 hat and the variance of the natural logarithm of Theta 2 hat.. The correlation is assumed to be negligible because each State was a stratum in the first level of stratification; therefore, each State sample is selected independently. However, the correlation between the two State estimates is theoretically nonzero because State estimates share common fixed-effect parameters in the SAE models. Hence, the test statistic z (defined below) might result in a different conclusion in a few cases when the correlation between the State estimates is incorporated in calculating variance v of the estimate of the log-odds ratio, lor hat sub a. To calculate the p value for testing the null hypothesis of no difference (lora = 0), it is assumed that the posterior distribution of lora is normal with Mean is equal to estimate of the log-odds ratio, lor hat sub a and Variance is equal to variance v of the estimate of the log-odds ratio, lor hat sub a. With the null value of lora = 0, the Bayes p value or posterior probability of no difference is p value = 2*P [Zabs(z)], where Z is a standard normal random variate, Quantity z is the estimate of the log-odds ratio, lor hat sub a, divided by the square root of the sum of the variance of the natural logarithm of Theta 1 hat and the variance of the natural logarithm of Theta 2 hat, and abs (z) denotes the absolute value of z.


When comparing prevalence rates for two States, it is tempting and often convenient to look at their 95 percent PIs to decide whether the difference in the State prevalence rates is significant. If the two PIs overlap, one would conclude that the difference is not statistically significant. If the two PIs do not overlap, it implies that the State prevalence rates are significantly different from each other. However, the type-I error for the overlapping 95 percent PIs test is 0.6 percent (assuming that the two State estimates are uncorrelated and have the same variances) as compared with the 5 percent type-I error of the test based on the z statistics defined above (Payton, Greenstone, & Schenker, 2003). Thus, using the overlap method with 95 percent PIs implies a type-I error that is much less than the 5 percent level that is typically prescribed for such tests.

As discussed in Schenker and Gentleman (2001), the method of overlapping PIs is more conservative (i.e., it rejects the null hypothesis of no difference less often) than the standard method based on z statistics when the null hypothesis is true. Even if PIs for two States overlap, the two prevalence rates may be declared significantly different by the test based on z statistics. Hence, the method of overlapping PIs is not recommended to test the equivalence of two State prevalence rates. A detailed description of the method of overlapping confidence intervals (CIs) and its comparison with the standard methods for testing of a hypothesis is given in Schenker and Gentleman (2001) and Payton et al. (2003).

Example. The prevalence rates for past month alcohol use among 12 to 17 year olds in Arkansas and Montana are shown in the exhibit below and also in Table B.9 in Appendix B. Looking at the two 95 percent PIs, it would appear that the Arkansas and Montana prevalence rates for past month alcohol use are not statistically different at the 5 percent level of significance because the two PIs overlap:

State Point Estimate (%) 95% PI (%)
Arkansas 14.74 (12.71, 17.02)
Montana 18.74 (16.33, 21.41)

However, in the following example, the test based on the z statistic described earlier concludes that they are significantly different at the 5 percent level of significance.

Let p1a = 0.1474, lower1 = 0.1271, upper1 = 0.1702, p2a = 0.1874, lower2 = 0.1633, and upper2 = 0.2141. Then,

Equation A-10     D

Equation A-11     D

Equation A-12     D

Equation A-13     D

Because the computed absolute value of z is greater than or equal to 1.96 (the critical value of the z statistic), then at the 5 percent level of significance, the hypothesis of no difference (Arkansas prevalence rate = Montana prevalence rate) is rejected. Thus, the two State prevalence rates are statistically different. The Bayes p value or posterior probability of no difference is p value = 2*P [Z ≥ 2.362] = 0.018.

A.12 Measuring Change in State Estimates

A.12.1 Change between 2006-2007 and 2007-2008 Small Area Estimates

Comparisons between State small area estimates displayed in Appendix C are based on the 2006 through 2008 NSDUHs. The State estimates for 2006-2007 are the previously published model-based small area estimates (Hughes et al., 2009). The State estimates for 2007-2008 are the small area estimates given in Appendix B. The moving average State prevalence estimates for the overlapping 2006-2007 and 2007-2008 time periods were obtained from independent applications of RTI's SWHB methodology; that is, the 2007-2008 models were fit independently of the previously fitted 2006-2007 models. This independent analysis approach was followed because there was no desire to revise the previously published 2006-2007 estimates. Moreover, the same fixed predictor variables were used in the 2006-2007 and 2007-2008 models, but annual updates were made when more current versions became available (refer to Section A.3 for details). The age group-specific fixed predictor variables were defined at five levels (namely, person-level, census block group-level, tract-level, county-level, and State-level). Also, each age group model had 51 State-level random effects and 300 "within-State" area-level random effects.

To estimate change in State estimates, let πsa(1) and πsa(2) denote 2006-2007 and 2007-2008 prevalence rates, respectively, for State-s and age group-a. The change between πsa(1) and πsa(2) is defined in terms of the log-odds ratio (lorsa) as opposed to the simple difference because the posterior distribution of the lorsa is closer to Gaussian than the posterior distribution of the simple difference (πsa(2) – πsa(1)). The lorsa is defined as

Equation A-14,     D


where ln denotes the natural logarithm. The p value given in the Appendix C tables is computed to test the null hypothesis of no change (i.e., πsa(2) = πsa(1) or equivalently lorsa = 0). An estimate of lorsa is given by

Equation A-15,     D


where the Psa(1) are previously published 2006-2007 State estimates and the Psa(2) are the 2007-2008 State estimates presented in this report (see Appendix B). To compute the variance of The estimate of the log-odds ratio, lor hat sub s and a, that is, variance of the estimate of the log-odds ratio, lor hat sub s and a, let Theta 1 hat is defined as the ratio of p 1 sub s and a and 1 minus p 1 sub s and a and Theta 2 hat is defined as the ratio of p 2 sub s and a and 1 minus p 2 sub s and a, then


Equation A-17,     D

where covariance between the natural logarithm of Theta 1 hat and the natural logarithm of Theta 2 hat denotes the covariance between image represents the natural logarithm of Theta 1 hat and image represents the natural logarithm of Theta 2 hat. This covariance is defined in terms of the associated correlation as follows:

Equation A-19.     D

Note that variance of the natural logarithm of Theta 1 hat and variance of the natural logarithm of Theta 2 hat used here to calculate variance of the estimate of the log-odds ratio, lor hat sub s and a are the same variances used in calculating the previously published 2006-2007 PIs and the 2007-2008 PIs given in this report, respectively.

The correlation between [image represents the natural logarithm of Theta 1 hat and image represents the natural logarithm of Theta 2 hat] was obtained by simultaneously modeling the 2006, 2007, and 2008 NSDUH data. This simultaneous modeling approach was adopted based on the results of the validation study (see Appendix E, Section E.2, of Wright, 2003b) conducted for measuring change in the 1999-2000 and 2000-2001 State estimates. For this simultaneous model, 4 age groups (12 to 17, 18 to 25, 26 to 34, and 35 or older) by 3 years (2006, 2007, and 2008), that is, 12 subpopulation-specific models, were fitted, each with its own set of fixed and random effects. In this case, the general covariance matrices for the State and within-State random effects were 12 × 12 matrices corresponding to the 12 element (age group × year) vectors of random effects. Note that the survey-weighted, Bernoulli-type log likelihood employed in the SWHB methodology was appropriate for this simultaneous model because the 12 age group × year subpopulations were nonoverlapping. The correlation [image represents the natural logarithm of Theta 1 hat, image represents the natural logarithm of Theta 2 hat] was approximated by the correlation calculated using the posterior distributions of ln[πsa(1) / (1 – πsa(1))] and ln[πsa(2) / (1 – πsa(2))] from the simultaneous model.

To calculate the p value for testing the null hypothesis of no difference (lor = 0), it is assumed that the posterior distribution of lor is normal with Mean is equal to estimate of the log-odds ratio, lor hat sub s and a and Variance is equal to variance v of the estimate of the log-odds ratio, lor hat sub s and a. With the null value of (lor = 0), the Bayes p value or posterior probability of no difference is p value = 2*P [Zabs(z)], where Z is a standard normal random variate, Quantity z is the estimate of the log-odds ratio, lor hat sub s and a, divided by the square root of the variance v of the estimate of the log-odds ratio, lor hat sub s and a, and abs (z) denotes the absolute value of z.


A.12.2 Change between 2002-2003 and 2007-2008 Small Area Estimates

Estimates of the posterior probability of no difference in estimates between the two nonoverlapping periods, 2002-2003 and 2007-2008, were calculated in a very similar manner to the method described in Section A.12.1. Borrowing from the notation above, let Psa(1) refer to the previously published 2002-2003 State estimates (Wright & Sathe, 2005), and let Psa(2) denote the 2007-2008 State estimates presented in this report (see Appendix B). The change between the two estimates is defined in terms of the log-odds ratio as discussed in the prior section. The p value given in the Appendix D tables is computed to test the null hypothesis of no change, that is, to test lorsa = 0. An estimate of lorsa is given by

Equation A-21,     D


To compute the variance of The estimate of the log-odds ratio, lor hat sub s and a that is, variance of the estimate of the log-odds ratio, lor hat sub s and a let Theta 1 hat is defined as the ratio of p 1 sub s and a and 1 minus p 1 sub s and a and Theta 2 hat is defined as the ratio of p 2 sub s and a and 1 minus p 2 sub s and a then


Equation A-22,     D

where covariance between the natural logarithm of Theta 1 hat and the natural logarithm of Theta 2 hat denotes the covariance between image represents the natural logarithm of Theta 1 hat and image represents the natural logarithm of Theta 2 hat. This covariance is defined in terms of the associated correlation as follows:

Equation A-23.     D

Note that variance of the natural logarithm of Theta 1 hat and variance of the natural logarithm of Theta 2 hat used here to calculate variance of the estimate of the log-odds ratio, lor hat sub s and a are the same posterior variances used in calculating the previously published 2002-2003 PIs and the 2007-2008 PIs given in this report, respectively.

The difference in the method discussed in Section A.12.1 and the method discussed here is in the model that was fit to find the correlation between image represents the natural logarithm of Theta 1 hat and image represents the natural logarithm of Theta 2 hat. Here, the correlation between image represents the natural logarithm of Theta 1 hat and image represents the natural logarithm of Theta 2 hat was obtained by simultaneously modeling the pooled 2002-2003 and pooled 2007-2008 NSDUH data. For this simultaneous model, four age groups (12 to 17, 18 to 25, 26 to 34, and 35 or older) by two time periods (2002-2003 and 2007-2008), that is, eight subpopulation-specific models, were fitted, each with its own set of fixed and random effects. In this case, the general covariance matrices for the State and substate random effects were 8 × 8 matrices corresponding to the eight element (age group × time period) vectors of random effects.

The Bayes p value or posterior probability of no difference was calculated in a manner similar to that described in Section A.12.1.

Table A.1 Sample Sizes, Weighted Screening and Interview Response Rates, and Population Estimates, by State, for Persons Aged 12 or Older: 2006
State Total
Selected
DUs
Total
Eligible
DUs
Total
Completed
Screeners
Weighted DU
Screening
Response Rate
Total
Selected
Total
Responded
Population
Estimate
Weighted
Interview
Response Rate
Weighted
Overall
Response Rate
DU = dwelling unit.
Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2006.
Total U.S. 182,459 151,288 137,057 90.55% 85,034 67,802 246,021,656 74.24% 67.23%
Northeast 39,736 33,247 28,846 85.62% 17,201 13,499 45,851,360 71.96% 61.61%
Midwest 49,110 41,548 37,705 90.73% 23,766 18,988 54,699,857 75.39% 68.40%
South 57,646 46,460 42,682 92.21% 25,848 20,841 88,990,723 75.13% 69.27%
West 35,967 30,033 27,824 91.93% 18,219 14,474 56,479,716 73.60% 67.66%
Alabama 2,246 1,784 1,633 91.49% 1,130 912 3,801,084 73.90% 67.61%
Alaska 2,248 1,696 1,522 89.74% 1,131 910 527,233 76.21% 68.39%
Arizona 2,300 1,761 1,663 94.43% 1,105 880 4,984,110 73.31% 69.23%
Arkansas 2,378 1,904 1,793 94.04% 1,042 862 2,305,283 80.15% 75.37%
California 8,239 7,385 6,670 90.35% 4,753 3,657 29,636,814 71.87% 64.93%
Colorado 2,508 2,070 1,894 91.48% 1,101 899 3,889,399 78.63% 71.93%
Connecticut 2,347 2,004 1,791 89.26% 1,133 891 2,926,648 73.70% 65.79%
Delaware 2,413 1,930 1,716 88.96% 1,109 897 705,945 77.29% 68.76%
District of Columbia 3,804 3,161 2,735 86.54% 1,083 880 493,946 77.31% 66.91%
Florida 10,538 8,351 7,544 90.29% 4,627 3,671 15,151,767 72.71% 65.65%
Georgia 2,277 1,830 1,686 92.20% 1,146 925 7,529,337 72.96% 67.27%
Hawaii 2,399 2,024 1,845 91.04% 1,190 889 1,037,510 68.48% 62.34%
Idaho 2,252 1,883 1,777 94.37% 1,113 901 1,181,617 77.42% 73.06%
Illinois 9,769 8,514 7,002 82.14% 4,679 3,512 10,533,040 68.44% 56.21%
Indiana 2,337 1,951 1,775 90.97% 1,197 970 5,191,139 79.02% 71.89%
Iowa 2,288 1,975 1,825 92.71% 1,091 893 2,474,784 79.65% 73.84%
Kansas 2,202 1,872 1,765 94.27% 1,129 900 2,246,155 78.55% 74.05%
Kentucky 2,441 2,061 1,939 94.05% 1,141 913 3,469,472 73.33% 68.97%
Louisiana 2,438 1,691 1,599 94.69% 1,086 869 3,478,296 72.91% 69.04%
Maine 3,204 2,234 2,059 92.16% 1,087 903 1,130,632 80.38% 74.08%
Maryland 2,326 2,022 1,749 86.61% 1,154 927 4,638,342 77.05% 66.73%
Massachusetts 2,605 2,248 1,944 86.52% 1,169 910 5,415,211 75.56% 65.38%
Michigan 8,665 7,274 6,580 90.48% 4,463 3,625 8,389,088 76.56% 69.28%
Minnesota 2,242 1,921 1,751 91.20% 1,057 872 4,286,476 80.23% 73.17%
Mississippi 2,391 1,795 1,714 95.46% 1,086 887 2,349,616 74.33% 70.96%
Missouri 2,265 1,855 1,751 94.41% 1,133 924 4,819,013 75.20% 70.99%
Montana 2,474 2,053 1,935 94.26% 1,122 909 790,600 77.58% 73.12%
Nebraska 2,367 2,054 1,933 94.12% 1,096 890 1,442,619 78.21% 73.61%
Nevada 2,280 1,862 1,756 94.30% 1,100 876 2,039,509 74.25% 70.02%
New Hampshire 2,730 2,224 2,008 90.17% 1,104 903 1,114,761 77.94% 70.28%
New Jersey 2,692 2,336 2,009 85.99% 1,251 899 7,254,664 67.07% 57.67%
New Mexico 2,208 1,818 1,716 94.37% 1,065 884 1,589,217 77.04% 72.71%
New York 11,412 9,696 7,825 80.73% 4,871 3,584 16,122,190 68.59% 55.37%
North Carolina 3,004 2,413 2,275 94.31% 1,218 1,000 7,218,540 78.71% 74.23%
North Dakota 2,572 2,074 1,962 94.54% 1,123 934 526,510 79.51% 75.17%
Ohio 9,607 8,178 7,711 94.24% 4,549 3,627 9,518,947 74.67% 70.36%
Oklahoma 2,915 2,305 2,088 90.20% 1,160 925 2,899,366 76.11% 68.66%
Oregon 2,545 2,122 1,985 93.56% 1,101 882 3,103,344 73.51% 68.78%
Pennsylvania 9,946 8,540 7,659 89.70% 4,374 3,574 10,451,936 75.67% 67.88%
Rhode Island 2,417 2,095 1,837 87.53% 1,130 919 899,026 77.77% 68.08%
South Carolina 2,653 2,076 1,968 94.76% 1,127 921 3,551,269 76.20% 72.20%
South Dakota 2,367 1,902 1,802 94.74% 1,104 926 637,001 80.79% 76.54%
Tennessee 2,211 1,875 1,746 92.96% 1,071 904 4,994,197 80.24% 74.59%
Texas 8,291 6,761 6,367 94.14% 4,383 3,537 18,644,278 75.48% 71.05%
Utah 1,559 1,340 1,272 94.89% 1,074 912 1,975,874 81.08% 76.94%
Vermont 2,383 1,870 1,714 91.60% 1,082 916 536,292 83.30% 76.30%
Virginia 2,630 2,223 1,972 88.62% 1,157 906 6,216,707 73.39% 65.04%
Washington 2,432 2,011 1,892 94.10% 1,183 929 5,297,005 75.07% 70.64%
West Virginia 2,690 2,278 2,158 94.72% 1,128 905 1,543,277 74.23% 70.31%
Wisconsin 2,429 1,978 1,848 93.25% 1,145 915 4,635,085 76.48% 71.31%
Wyoming 2,523 2,008 1,897 94.47% 1,181 946 427,484 77.01% 72.75%
Table A.2 Sample Sizes, Weighted Interview Response Rates, and Population Estimates, by State and Three Age Groups: 2006
State 12-17
Total
Selected
12-17
Total
Responded
12-17
Population
Estimate
12-17
Weighted
Interview
Response
Rate
18-25
Total
Selected
18-25
Total
Responded
18-25
Population
Estimate
18-25
Weighted
Interview
Response
Rate
26+
Total
Selected
26+
Total
Responded
26+
Population
Estimate
26+
Weighted
Interview
Response
Rate
Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2006.
Total U.S. 26,702 22,912 25,391,932 85.46% 27,303 22,152 32,739,870 80.96% 31,029 22,738 187,889,854 71.54%
Northeast 5,428 4,613 4,513,132 83.38% 5,505 4,365 5,862,816 78.29% 6,268 4,521 35,475,412 69.47%
Midwest 7,453 6,383 5,670,639 85.90% 7,543 6,106 7,383,772 80.18% 8,770 6,499 41,645,446 73.12%
South 8,261 7,155 9,151,832 86.29% 8,267 6,836 11,681,799 82.94% 9,320 6,850 68,157,092 72.23%
West 5,560 4,761 6,056,330 85.33% 5,988 4,845 7,811,483 80.74% 6,671 4,868 42,611,904 70.65%
Alabama 342 301 388,190 88.02% 377 318 502,446 83.46% 411 293 2,910,448 70.56%
Alaska 342 293 64,608 84.11% 383 310 73,165 81.05% 406 307 389,461 74.24%
Arizona 315 279 528,141 87.82% 386 307 666,453 80.26% 404 294 3,789,516 70.18%
Arkansas 330 285 235,092 86.02% 339 284 301,916 85.42% 373 293 1,768,276 78.43%
California 1,462 1,226 3,262,489 84.06% 1,504 1,196 4,193,216 80.41% 1,787 1,235 22,181,109 68.53%
Colorado 326 281 386,045 84.43% 363 300 515,619 83.75% 412 318 2,987,735 77.04%
Connecticut 386 332 298,079 86.83% 312 245 350,601 80.33% 435 314 2,277,969 70.92%
Delaware 342 304 70,313 90.08% 324 259 92,101 79.78% 443 334 543,531 75.22%
District of Columbia 332 279 38,255 85.09% 303 270 79,730 88.36% 448 331 375,961 74.51%
Florida 1,459 1,272 1,395,023 86.59% 1,519 1,239 1,782,136 81.74% 1,649 1,160 11,974,608 69.68%
Georgia 422 354 819,555 84.12% 360 304 1,007,678 83.87% 364 267 5,702,105 69.24%
Hawaii 357 281 101,375 76.37% 380 300 124,757 80.54% 453 308 811,378 65.46%
Idaho 353 296 132,682 85.06% 377 313 167,260 83.76% 383 292 881,675 75.05%
Illinois 1,426 1,205 1,098,090 84.31% 1,431 1,081 1,437,196 74.29% 1,822 1,226 7,997,754 65.25%
Indiana 372 309 541,262 83.88% 408 330 698,732 82.18% 417 331 3,951,146 77.79%
Iowa 334 291 249,631 87.29% 355 283 345,578 80.00% 402 319 1,879,576 78.59%
Kansas 391 318 236,905 79.95% 319 256 321,520 79.97% 419 326 1,687,729 78.10%
Kentucky 374 320 342,465 85.48% 354 292 435,107 83.95% 413 301 2,691,900 70.03%
Louisiana 321 289 375,058 89.85% 367 304 502,102 83.34% 398 276 2,601,136 68.39%
Maine 371 323 106,794 86.33% 358 297 129,749 82.70% 358 283 894,089 79.24%
Maryland 374 313 481,655 83.37% 329 272 586,086 83.45% 451 342 3,570,602 75.38%
Massachusetts 349 286 510,401 80.94% 386 303 711,915 81.01% 434 321 4,192,896 73.94%
Michigan 1,384 1,210 893,293 87.84% 1,368 1,132 1,100,817 82.82% 1,711 1,283 6,394,978 74.01%
Minnesota 294 265 439,635 91.20% 395 322 586,082 82.52% 368 285 3,260,759 78.21%
Mississippi 367 325 260,500 89.49% 316 273 332,010 86.91% 403 289 1,757,106 69.46%
Missouri 342 298 495,519 86.51% 377 317 640,870 83.30% 414 309 3,682,625 72.30%
Montana 353 305 79,182 86.38% 354 280 105,427 79.46% 415 324 605,992 76.04%
Nebraska 362 297 150,353 82.68% 371 323 208,596 87.29% 363 270 1,083,670 75.65%
Nevada 334 297 208,358 87.57% 352 286 246,826 81.66% 414 293 1,584,326 71.32%
New Hampshire 352 314 111,999 88.93% 386 308 135,850 81.12% 366 281 866,912 76.19%
New Jersey 384 311 732,339 81.49% 381 274 848,461 73.38% 486 314 5,673,865 64.25%
New Mexico 333 287 175,349 84.76% 357 308 226,384 86.93% 375 289 1,187,485 73.96%
New York 1,498 1,208 1,589,881 79.72% 1,574 1,164 2,161,472 73.93% 1,799 1,212 12,370,837 66.28%
North Carolina 372 320 725,554 86.48% 442 378 898,015 85.45% 404 302 5,594,971 76.37%
North Dakota 338 292 51,433 86.06% 374 319 86,938 85.62% 411 323 388,139 77.42%
Ohio 1,479 1,258 977,863 85.70% 1,482 1,206 1,241,401 81.47% 1,588 1,163 7,299,683 71.98%
Oklahoma 382 323 301,174 85.10% 380 303 410,515 79.86% 398 299 2,187,677 74.02%
Oregon 350 311 297,252 88.86% 344 275 391,117 78.86% 407 296 2,414,975 70.76%
Pennsylvania 1,410 1,252 1,026,320 89.06% 1,329 1,121 1,327,163 84.86% 1,635 1,201 8,098,453 72.46%
Rhode Island 340 296 85,962 88.97% 399 325 128,023 81.31% 391 298 685,041 75.77%
South Carolina 332 294 363,760 86.88% 415 345 458,602 83.68% 380 282 2,728,907 73.45%
South Dakota 358 318 66,755 88.92% 326 277 91,245 86.76% 420 331 479,000 78.48%
Tennessee 343 309 494,906 89.65% 368 307 624,639 83.20% 360 288 3,874,652 78.43%
Texas 1,421 1,224 2,105,384 86.54% 1,331 1,101 2,700,676 82.99% 1,631 1,212 13,838,219 72.31%
Utah 283 259 240,594 92.82% 395 338 367,883 83.36% 396 315 1,367,397 78.40%
Vermont 338 291 51,357 85.02% 380 328 69,584 87.19% 364 297 415,351 82.43%
Virginia 383 324 617,449 82.64% 374 292 782,870 78.98% 400 290 4,816,388 71.25%
Washington 379 330 537,185 86.79% 397 309 673,599 77.70% 407 290 4,086,221 72.89%
West Virginia 365 319 137,499 87.61% 369 295 185,171 79.30% 394 291 1,220,607 71.86%
Wisconsin 373 322 469,901 85.72% 337 260 624,798 75.17% 435 333 3,540,386 75.54%
Wyoming 373 316 43,070 85.88% 396 323 59,780 81.42% 412 307 324,634 75.09%
Table A.3 Sample Sizes, Weighted Screening and Interview Response Rates, and Population Estimates, by State, for Persons Aged 12 or Older: 2007
State Total
Selected
DUs
Total
Eligible
DUs
Total
Completed
Screeners
Weighted DU
Screening
Response Rate
Total
Selected
Total
Responded
Population
Estimate
Weighted
Interview
Response Rate
Weighted
Overall
Response Rate
DU = dwelling unit.
Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2007.
Total U.S. 192,092 158,411 141,487 89.45% 85,774 67,870 247,845,207 73.94% 66.14%
Northeast 42,071 35,148 29,843 83.68% 17,486 13,642 45,877,579 71.65% 59.96%
Midwest 52,386 44,279 39,697 90.07% 24,150 19,110 54,799,063 74.34% 66.96%
South 58,260 46,564 42,423 91.72% 25,737 20,683 89,939,563 75.75% 69.47%
West 39,375 32,420 29,524 90.01% 18,401 14,435 57,229,003 72.52% 65.27%
Alabama 2,375 1,914 1,794 93.71% 1,152 899 3,811,968 71.76% 67.25%
Alaska 2,419 1,682 1,520 90.41% 1,066 852 541,042 77.92% 70.45%
Arizona 2,745 2,059 1,828 88.61% 1,157 885 5,120,090 70.49% 62.46%
Arkansas 2,556 2,001 1,875 93.72% 1,115 912 2,316,670 79.93% 74.91%
California 8,737 7,799 6,888 88.34% 4,835 3,652 29,849,097 70.68% 62.44%
Colorado 2,648 2,176 1,989 91.29% 1,121 889 3,976,785 74.46% 67.97%
Connecticut 2,903 2,594 2,292 88.24% 1,166 920 2,917,789 76.99% 67.94%
Delaware 2,335 1,929 1,729 89.74% 1,102 883 714,649 77.05% 69.15%
District of Columbia 4,265 3,339 2,782 83.14% 1,044 824 501,857 75.29% 62.60%
Florida 10,898 8,452 7,543 89.21% 4,576 3,585 15,266,862 71.81% 64.06%
Georgia 2,201 1,720 1,608 93.55% 1,083 891 7,642,504 78.31% 73.26%
Hawaii 2,912 2,406 2,021 82.95% 1,179 849 1,053,117 64.34% 53.37%
Idaho 2,420 2,015 1,901 94.35% 1,160 943 1,200,903 78.11% 73.70%
Illinois 11,061 9,611 7,472 77.47% 4,984 3,634 10,545,802 67.57% 52.34%
Indiana 2,412 2,018 1,885 93.37% 1,160 921 5,201,443 74.01% 69.11%
Iowa 2,449 2,098 1,960 93.32% 1,110 920 2,475,077 77.20% 72.04%
Kansas 2,184 1,849 1,745 94.39% 1,107 890 2,255,504 79.65% 75.18%
Kentucky 2,335 1,970 1,855 94.13% 1,107 888 3,496,061 77.47% 72.92%
Louisiana 2,521 1,765 1,662 94.20% 1,094 901 3,484,871 74.17% 69.86%
Maine 3,196 2,350 2,144 91.28% 1,119 917 1,126,007 76.43% 69.77%
Maryland 2,346 2,017 1,681 83.23% 1,119 888 4,639,855 76.47% 63.65%
Massachusetts 2,818 2,382 2,078 87.07% 1,143 899 5,441,203 72.84% 63.42%
Michigan 9,220 7,622 6,826 89.55% 4,439 3,566 8,380,042 74.36% 66.59%
Minnesota 2,465 2,107 1,977 93.75% 1,132 925 4,305,593 78.89% 73.96%
Mississippi 2,279 1,692 1,599 94.19% 1,081 899 2,343,924 78.12% 73.58%
Missouri 2,490 2,072 1,953 94.26% 1,129 916 4,837,421 73.73% 69.49%
Montana 2,823 2,195 2,071 94.34% 1,080 891 801,167 78.25% 73.82%
Nebraska 2,391 2,013 1,899 94.34% 1,123 917 1,445,813 77.32% 72.94%
Nevada 2,413 1,996 1,883 94.54% 1,100 890 2,088,962 76.83% 72.64%
New Hampshire 2,626 2,067 1,866 90.08% 1,105 876 1,112,661 76.93% 69.30%
New Jersey 2,568 2,227 1,942 87.15% 1,153 898 7,227,870 74.93% 65.30%
New Mexico 2,701 2,037 1,923 94.43% 1,151 956 1,606,155 76.31% 72.06%
New York 12,392 10,631 8,106 75.87% 5,130 3,699 16,191,334 65.11% 49.40%
North Carolina 2,942 2,434 2,251 92.46% 1,206 974 7,381,205 74.56% 68.94%
North Dakota 2,649 2,145 2,022 94.27% 1,106 905 530,226 79.91% 75.33%
Ohio 10,168 8,632 8,124 94.10% 4,530 3,626 9,508,750 75.26% 70.82%
Oklahoma 2,802 2,279 2,070 90.77% 1,204 952 2,927,119 75.67% 68.69%
Oregon 2,482 2,130 1,968 92.17% 1,160 916 3,138,875 73.88% 68.10%
Pennsylvania 10,437 8,853 7,765 87.48% 4,525 3,649 10,433,605 75.65% 66.18%
Rhode Island 2,535 2,165 1,933 89.31% 1,118 914 892,599 75.72% 67.62%
South Carolina 2,792 2,188 2,053 93.83% 1,129 925 3,607,724 78.53% 73.69%
South Dakota 2,201 1,783 1,693 94.94% 1,122 922 649,052 79.35% 75.34%
Tennessee 2,306 1,887 1,765 93.57% 1,101 896 5,082,082 75.51% 70.66%
Texas 7,818 6,413 6,054 94.35% 4,324 3,557 18,904,425 77.52% 73.15%
Utah 1,924 1,611 1,531 95.04% 1,083 900 2,049,189 79.63% 75.67%
Vermont 2,596 1,879 1,717 91.39% 1,027 870 534,511 81.75% 74.71%
Virginia 2,579 2,134 1,864 87.24% 1,187 924 6,282,584 76.23% 66.51%
Washington 2,476 2,129 1,963 92.08% 1,150 909 5,372,199 75.66% 69.66%
West Virginia 2,910 2,430 2,238 91.99% 1,113 885 1,535,205 76.20% 70.10%
Wisconsin 2,696 2,329 2,141 92.14% 1,208 968 4,664,339 78.09% 71.96%
Wyoming 2,675 2,185 2,038 93.30% 1,159 903 431,423 74.79% 69.78%
Table A.4 Sample Sizes, Weighted Interview Response Rates, and Population Estimates, by State and Three Age Groups: 2007
State 12-17
Total
Selected
12-17
Total
Responded
12-17
Population
Estimate
12-17
Weighted
Interview
Response
Rate
18-25
Total
Selected
18-25
Total
Responded
18-25
Population
Estimate
18-25
Weighted
Interview
Response
Rate
26+
Total
Selected
26+
Total
Responded
26+
Population
Estimate
26+
Weighted
Interview
Response
Rate
Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2007.
Total U.S. 26,191 22,475 25,241,088 85.35% 28,085 22,409 32,730,853 79.76% 31,498 22,986 189,873,266 71.42%
Northeast 5,317 4,496 4,458,471 82.32% 5,763 4,530 5,902,786 76.60% 6,406 4,616 35,516,321 69.50%
Midwest 7,415 6,364 5,614,954 85.94% 7,920 6,341 7,287,805 80.20% 8,815 6,405 41,896,304 71.79%
South 7,873 6,809 9,129,195 86.77% 8,322 6,765 11,686,936 81.75% 9,542 7,109 69,123,431 73.28%
West 5,586 4,806 6,038,467 84.85% 6,080 4,773 7,853,326 78.74% 6,735 4,856 43,337,209 69.62%
Alabama 333 276 385,087 82.86% 357 304 497,891 85.65% 462 319 2,928,991 68.12%
Alaska 366 318 64,158 88.19% 331 250 75,478 76.22% 369 284 401,406 76.40%
Arizona 332 288 535,271 85.60% 386 287 668,649 73.71% 439 310 3,916,169 67.83%
Arkansas 370 313 233,624 84.88% 325 259 294,086 81.27% 420 340 1,788,961 79.17%
California 1,461 1,221 3,239,651 83.14% 1,561 1,200 4,239,933 78.12% 1,813 1,231 22,369,512 67.39%
Colorado 364 315 388,527 88.00% 375 294 518,151 78.81% 382 280 3,070,107 71.99%
Connecticut 330 289 294,751 86.97% 411 310 354,623 75.78% 425 321 2,268,416 75.93%
Delaware 320 277 70,353 86.46% 404 324 91,857 82.64% 378 282 552,439 74.95%
District of Columbia 343 299 37,676 86.85% 324 256 84,330 78.90% 377 269 379,851 73.35%
Florida 1,285 1,101 1,383,657 85.40% 1,480 1,206 1,775,518 81.63% 1,811 1,278 12,107,687 68.84%
Georgia 328 290 825,764 88.73% 336 279 996,074 83.18% 419 322 5,820,666 75.88%
Hawaii 360 295 97,554 80.48% 375 272 127,524 73.01% 444 282 828,039 60.93%
Idaho 375 326 133,051 84.98% 379 305 163,370 80.51% 406 312 904,482 76.63%
Illinois 1,540 1,252 1,090,441 81.60% 1,591 1,172 1,430,266 73.58% 1,853 1,210 8,025,095 64.56%
Indiana 321 270 537,600 85.29% 439 361 680,319 81.32% 400 290 3,983,524 71.28%
Iowa 378 336 246,542 88.81% 327 279 342,411 85.30% 405 305 1,886,125 74.27%
Kansas 352 316 233,910 89.59% 339 254 322,756 74.27% 416 320 1,698,838 79.32%
Kentucky 337 286 341,080 85.06% 368 301 425,259 81.73% 402 301 2,729,722 75.71%
Louisiana 339 304 369,218 89.00% 351 299 508,682 85.81% 404 298 2,606,970 69.87%
Maine 342 301 104,509 87.63% 393 330 125,774 85.33% 384 286 895,724 73.67%
Maryland 316 271 475,278 85.07% 410 327 592,747 79.44% 393 290 3,571,831 75.05%
Massachusetts 364 303 511,379 79.34% 377 300 721,029 77.49% 402 296 4,208,794 71.11%
Michigan 1,317 1,132 882,825 85.67% 1,495 1,226 1,089,259 81.76% 1,627 1,208 6,407,959 71.52%
Minnesota 388 333 434,170 86.38% 344 282 579,707 82.49% 400 310 3,291,716 77.21%
Mississippi 325 288 258,825 88.59% 347 299 329,531 85.63% 409 312 1,755,568 75.06%
Missouri 348 305 492,534 87.89% 356 300 625,471 84.89% 425 311 3,719,416 70.31%
Montana 324 287 78,824 88.05% 357 292 105,687 80.10% 399 312 616,657 76.73%
Nebraska 378 330 148,560 88.07% 336 279 209,608 82.85% 409 308 1,087,646 74.48%
Nevada 301 267 213,775 90.01% 379 302 240,941 79.67% 420 321 1,634,245 74.87%
New Hampshire 339 282 110,622 82.17% 353 284 132,472 81.50% 413 310 869,567 75.67%
New Jersey 363 303 721,841 80.79% 358 276 855,683 75.53% 432 319 5,650,345 74.10%
New Mexico 373 340 169,013 91.93% 375 316 226,689 85.58% 403 300 1,210,452 72.06%
New York 1,541 1,240 1,569,950 79.78% 1,679 1,222 2,196,813 72.45% 1,910 1,237 12,424,572 62.09%
North Carolina 407 351 731,643 87.47% 385 312 916,505 82.26% 414 311 5,733,057 71.43%
North Dakota 372 313 50,461 84.21% 359 297 90,221 83.32% 375 295 389,544 78.44%
Ohio 1,343 1,173 965,669 87.49% 1,509 1,234 1,212,277 82.72% 1,678 1,219 7,330,804 72.44%
Oklahoma 429 360 298,069 84.23% 365 286 411,003 78.88% 410 306 2,218,047 73.84%
Oregon 319 274 297,399 85.62% 420 335 383,128 79.08% 421 307 2,458,349 71.81%
Pennsylvania 1,375 1,193 1,010,168 86.16% 1,521 1,231 1,322,592 80.95% 1,629 1,225 8,100,845 73.45%
Rhode Island 355 311 84,715 87.08% 336 288 126,010 87.70% 427 315 681,873 72.24%
South Carolina 319 281 362,012 88.01% 408 330 455,872 79.12% 402 314 2,789,840 77.27%
South Dakota 324 295 66,689 91.67% 355 294 91,410 84.11% 443 333 490,953 77.06%
Tennessee 360 316 498,268 88.15% 335 281 616,230 85.95% 406 299 3,967,584 72.28%
Texas 1,388 1,224 2,106,251 88.23% 1,398 1,151 2,698,089 82.21% 1,538 1,182 14,100,085 74.96%
Utah 349 311 245,792 90.52% 343 290 373,846 85.05% 391 299 1,429,552 76.08%
Vermont 308 274 50,535 89.07% 335 289 67,790 86.26% 384 307 416,186 80.25%
Virginia 347 294 617,259 84.79% 385 282 815,120 74.23% 455 348 4,850,205 75.53%
Washington 316 267 532,673 84.63% 401 324 670,845 82.14% 433 318 4,168,681 73.38%
West Virginia 327 278 135,134 83.98% 344 269 178,142 77.99% 442 338 1,221,929 75.12%
Wisconsin 354 309 465,555 87.02% 470 363 614,100 77.96% 384 296 3,584,684 76.95%
Wyoming 346 297 42,779 86.29% 398 306 59,086 77.75% 415 300 329,558 72.47%
Table A.5 Sample Sizes, Weighted Screening and Interview Response Rates, and Population Estimates, by State, for Persons Aged 12 or Older: 2008
State Total
Selected
DUs
Total
Eligible
DUs
Total
Completed
Screeners
Weighted DU
Screening
Response Rate
Total
Selected
Total
Responded
Population
Estimate
Weighted
Interview
Response Rate
Weighted
Overall
Response Rate
DU = dwelling unit.
Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2008.
Total U.S. 194,815 160,133 142,938 89.04% 86,435 68,736 249,815,089 74.45% 66.29%
Northeast 41,088 34,150 29,235 84.54% 17,336 13,594 46,098,527 72.48% 61.28%
Midwest 52,794 44,490 39,977 90.15% 24,383 19,314 54,957,186 74.93% 67.55%
South 59,559 47,794 43,312 91.24% 25,641 20,877 90,962,960 76.59% 69.88%
West 41,374 33,699 30,414 88.10% 19,075 14,951 57,796,416 72.24% 63.64%
Alabama 2,946 2,329 2,140 92.06% 1,173 929 3,843,374 71.78% 66.09%
Alaska 2,628 1,763 1,597 90.64% 1,147 908 541,167 76.32% 69.18%
Arizona 2,899 2,071 1,820 88.20% 1,131 908 5,239,324 76.87% 67.79%
Arkansas 2,699 2,130 2,000 93.82% 1,122 933 2,332,677 77.25% 72.48%
California 9,128 8,079 6,843 84.56% 5,036 3,830 30,012,612 69.66% 58.90%
Colorado 2,963 2,366 2,149 90.78% 1,195 949 4,035,628 76.15% 69.13%
Connecticut 2,744 2,426 2,158 88.84% 1,162 938 2,919,630 75.10% 66.72%
Delaware 2,547 2,123 1,858 87.67% 1,166 943 721,693 78.71% 69.01%
District of Columbia 4,070 3,307 2,720 82.08% 1,078 900 505,593 78.87% 64.74%
Florida 11,058 8,486 7,704 90.84% 4,388 3,590 15,343,888 76.52% 69.51%
Georgia 2,610 2,026 1,836 90.56% 1,089 877 7,753,524 73.73% 66.77%
Hawaii 3,047 2,373 2,038 84.44% 1,277 897 1,052,720 65.04% 54.92%
Idaho 2,393 1,943 1,842 94.82% 1,147 942 1,219,776 78.15% 74.11%
Illinois 10,542 9,213 7,350 79.73% 5,045 3,743 10,598,573 68.66% 54.74%
Indiana 2,314 1,947 1,815 93.21% 1,147 914 5,225,927 77.75% 72.47%
Iowa 2,470 2,154 2,004 92.98% 1,152 945 2,484,297 80.80% 75.12%
Kansas 2,163 1,864 1,746 93.67% 1,100 884 2,269,597 76.83% 71.97%
Kentucky 2,644 2,163 2,040 94.34% 1,097 884 3,524,562 73.21% 69.06%
Louisiana 2,414 1,820 1,717 94.31% 1,082 881 3,581,692 78.79% 74.30%
Maine 3,212 2,374 2,196 92.46% 1,102 915 1,126,276 77.15% 71.33%
Maryland 2,526 2,212 1,858 83.86% 1,181 981 4,660,360 77.55% 65.03%
Massachusetts 2,562 2,159 1,908 88.09% 1,112 897 5,476,618 76.63% 67.50%
Michigan 10,246 8,222 7,299 88.81% 4,587 3,675 8,341,138 75.18% 66.77%
Minnesota 2,238 1,918 1,805 94.08% 1,073 881 4,323,170 78.86% 74.19%
Mississippi 2,109 1,677 1,587 94.69% 1,074 883 2,358,646 78.01% 73.87%
Missouri 2,613 2,186 2,045 93.58% 1,131 914 4,864,752 76.30% 71.40%
Montana 2,869 2,340 2,211 94.50% 1,139 919 808,201 77.02% 72.78%
Nebraska 2,316 1,915 1,805 94.26% 1,105 888 1,451,290 76.82% 72.41%
Nevada 2,778 2,256 2,121 94.20% 1,124 887 2,115,107 74.07% 69.77%
New Hampshire 2,585 2,006 1,761 87.82% 1,113 904 1,115,443 79.14% 69.50%
New Jersey 2,757 2,336 2,054 88.06% 1,247 974 7,225,089 73.12% 64.39%
New Mexico 2,591 1,946 1,835 94.30% 1,073 876 1,616,007 79.35% 74.83%
New York 11,715 9,885 7,693 77.90% 4,928 3,570 16,365,125 66.90% 52.12%
North Carolina 2,433 2,039 1,874 92.06% 1,084 890 7,496,430 78.16% 71.95%
North Dakota 2,818 2,293 2,158 94.19% 1,142 932 530,391 78.87% 74.29%
Ohio 10,373 8,808 8,239 93.53% 4,641 3,692 9,526,405 73.94% 69.15%
Oklahoma 2,192 1,775 1,602 90.43% 1,117 897 2,941,713 78.99% 71.43%
Oregon 2,756 2,353 2,170 92.31% 1,242 1,011 3,173,495 71.54% 66.04%
Pennsylvania 10,033 8,623 7,521 86.90% 4,441 3,601 10,448,312 75.76% 65.84%
Rhode Island 2,653 2,197 1,966 89.44% 1,080 881 887,019 77.68% 69.48%
South Carolina 2,806 2,167 1,977 91.00% 1,113 938 3,667,059 82.06% 74.68%
South Dakota 2,297 1,907 1,821 95.55% 1,143 963 653,933 78.42% 74.93%
Tennessee 2,418 1,978 1,822 92.15% 1,181 937 5,136,799 75.26% 69.35%
Texas 8,122 6,682 6,215 93.03% 4,367 3,556 19,229,370 76.81% 71.45%
Utah 1,730 1,521 1,440 94.74% 1,155 961 2,113,331 78.29% 74.17%
Vermont 2,827 2,144 1,978 92.26% 1,151 914 535,016 75.19% 69.37%
Virginia 2,592 2,142 1,878 87.62% 1,152 926 6,328,752 75.92% 66.52%
Washington 2,758 2,397 2,213 92.43% 1,197 920 5,431,264 73.35% 67.79%
West Virginia 3,373 2,738 2,484 90.51% 1,177 932 1,536,829 76.20% 68.97%
Wisconsin 2,404 2,063 1,890 91.53% 1,117 883 4,687,712 76.91% 70.39%
Wyoming 2,834 2,291 2,135 93.20% 1,212 943 437,785 72.21% 67.30%
Table A.6 Sample Sizes, Weighted Interview Response Rates, and Population Estimates, by State and Three Age Groups: 2008
State 12-17
Total
Selected
12-17
Total
Responded
12-17
Population
Estimate
12-17
Weighted
Interview
Response
Rate
18-25
Total
Selected
18-25
Total
Responded
18-25
Population
Estimate
18-25
Weighted
Interview
Response
Rate
26+
Total
Selected
26+
Total
Responded
26+
Population
Estimate
26+
Weighted
Interview
Response
Rate
Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2008.
Total U.S. 26,501 22,559 24,892,326 84.73% 29,091 23,468 32,938,183 80.67% 30,843 22,709 191,984,580 72.00%
Northeast 5,245 4,437 4,374,575 83.22% 5,866 4,661 5,986,651 78.36% 6,225 4,496 35,737,300 70.21%
Midwest 7,439 6,305 5,508,681 84.56% 8,217 6,591 7,275,820 79.57% 8,727 6,418 42,172,686 72.85%
South 7,927 6,846 9,050,269 86.19% 8,663 7,169 11,764,906 83.27% 9,051 6,862 70,147,785 74.15%
West 5,890 4,971 5,958,801 83.78% 6,345 5,047 7,910,806 79.52% 6,840 4,933 43,926,809 69.31%
Alabama 340 292 380,937 86.23% 410 341 501,390 83.71% 423 296 2,961,047 67.68%
Alaska 370 300 61,212 80.19% 374 301 75,989 81.95% 403 307 403,966 74.55%
Arizona 352 307 538,925 87.29% 384 311 675,594 79.95% 395 290 4,024,805 74.78%
Arkansas 354 324 231,729 91.17% 398 328 293,143 84.25% 370 281 1,807,805 74.19%
California 1,471 1,223 3,178,553 82.21% 1,748 1,372 4,276,022 79.29% 1,817 1,235 22,558,037 66.03%
Colorado 398 341 385,509 85.87% 361 279 522,146 77.78% 436 329 3,127,973 74.54%
Connecticut 306 270 289,686 90.03% 443 359 358,342 79.84% 413 309 2,271,601 72.79%
Delaware 351 290 69,446 82.91% 437 354 92,890 81.55% 378 299 559,357 77.54%
District of Columbia 300 273 36,326 92.35% 398 336 84,963 84.30% 380 291 384,303 76.47%
Florida 1,383 1,197 1,353,763 86.91% 1,399 1,176 1,779,426 83.78% 1,606 1,217 12,210,699 74.30%
Georgia 364 313 823,565 85.83% 335 282 1,002,141 84.62% 390 282 5,927,818 69.89%
Hawaii 360 276 94,033 77.53% 431 317 130,031 72.11% 486 304 828,656 62.56%
Idaho 356 314 132,813 88.57% 360 301 163,669 82.85% 431 327 923,294 76.09%
Illinois 1,515 1,235 1,074,628 81.78% 1,689 1,272 1,455,604 74.87% 1,841 1,236 8,068,342 65.78%
Indiana 389 324 532,430 84.25% 370 289 675,007 78.93% 388 301 4,018,491 76.71%
Iowa 351 300 242,215 85.63% 372 304 339,024 82.29% 429 341 1,903,058 79.95%
Kansas 304 259 230,579 84.49% 395 317 320,106 82.00% 401 308 1,718,912 74.93%
Kentucky 361 314 338,183 85.31% 359 299 425,780 81.01% 377 271 2,760,600 70.28%
Louisiana 328 276 372,486 83.41% 361 301 519,209 84.62% 393 304 2,689,997 76.84%
Maine 321 286 101,011 88.64% 372 314 125,017 83.72% 409 315 900,248 75.00%
Maryland 380 332 463,837 86.83% 398 340 603,272 86.40% 403 309 3,593,251 74.53%
Massachusetts 352 301 501,071 85.22% 365 294 745,429 80.99% 395 302 4,230,117 74.93%
Michigan 1,381 1,192 855,511 86.10% 1,591 1,299 1,083,355 81.49% 1,615 1,184 6,402,273 72.60%
Minnesota 343 301 424,864 87.96% 360 290 572,788 80.73% 370 290 3,325,519 77.33%
Mississippi 330 289 254,843 87.98% 353 296 330,023 83.47% 391 298 1,773,779 75.80%
Missouri 358 315 484,594 85.58% 360 284 622,228 76.74% 413 315 3,757,931 74.90%
Montana 383 318 77,182 83.49% 371 312 105,186 84.56% 385 289 625,834 74.91%
Nebraska 346 299 145,878 86.01% 358 291 207,730 79.46% 401 298 1,097,683 75.01%
Nevada 367 320 213,611 87.72% 382 302 243,004 79.89% 375 265 1,658,492 71.42%
New Hampshire 336 285 107,937 84.98% 361 297 132,623 82.48% 416 322 874,884 78.02%
New Jersey 390 316 708,395 80.08% 488 394 861,235 80.20% 369 264 5,655,459 71.02%
New Mexico 316 281 165,144 87.61% 346 275 225,333 79.50% 411 320 1,225,529 78.27%
New York 1,418 1,155 1,548,677 80.19% 1,675 1,213 2,240,017 72.47% 1,835 1,202 12,576,431 64.26%
North Carolina 375 330 728,418 87.95% 312 256 936,723 83.17% 397 304 5,831,288 75.89%
North Dakota 346 296 49,073 85.02% 392 324 88,206 82.80% 404 312 393,112 77.23%
Ohio 1,498 1,262 948,248 84.14% 1,480 1,214 1,208,122 82.55% 1,663 1,216 7,370,036 71.18%
Oklahoma 324 276 293,748 84.67% 397 311 406,525 79.30% 396 310 2,241,440 78.22%
Oregon 369 312 293,880 84.04% 468 407 383,593 86.15% 405 292 2,496,022 67.47%
Pennsylvania 1,435 1,237 987,054 86.16% 1,440 1,203 1,329,112 83.43% 1,566 1,161 8,132,146 73.28%
Rhode Island 319 283 82,028 88.85% 354 289 126,487 82.24% 407 309 678,503 75.29%
South Carolina 350 302 357,713 86.20% 375 314 464,802 84.79% 388 322 2,844,544 81.14%
South Dakota 325 289 65,489 88.07% 399 351 90,410 87.27% 419 323 498,034 75.88%
Tennessee 316 263 495,488 83.78% 433 357 616,859 80.88% 432 317 4,024,452 73.37%
Texas 1,318 1,135 2,109,558 86.02% 1,475 1,232 2,706,388 83.77% 1,574 1,189 14,413,424 74.07%
Utah 378 337 251,154 86.62% 337 271 374,827 80.56% 440 353 1,487,351 76.52%
Vermont 368 304 48,716 81.63% 368 298 68,388 81.06% 415 312 417,912 73.53%
Virginia 360 307 607,065 85.38% 420 332 825,136 80.33% 372 287 4,896,552 73.98%
Washington 396 329 524,495 84.17% 383 290 675,978 77.04% 418 301 4,230,791 71.36%
West Virginia 393 333 133,164 85.61% 403 314 176,237 77.96% 381 285 1,227,428 74.83%
Wisconsin 283 233 455,175 83.70% 451 356 613,242 79.48% 383 294 3,619,295 75.54%
Wyoming 374 313 42,291 84.01% 400 309 59,434 76.96% 438 321 336,059 69.82%
Table A.7 Sample Sizes, Weighted Screening and Interview Response Rates, and Population Estimates, by State, for Persons Aged 12 or Older: 2006 and 2007
State Total
Selected
DUs
Total
Eligible
DUs
Total
Completed
Screeners
Weighted DU
Screening
Response Rate
Total
Selected
Total
Responded
Population
Estimate
Weighted
Interview
Response Rate
Weighted
Overall
Response Rate
DU = dwelling unit.
NOTE: To compute the pooled 2006-2007 weighted response rates, two samples were combined, and the individual year weights were used for the pooled sample. Thus, the response rates presented here are weighted across 2 years of data rather than being a simple average of the 2006 and 2007 individual response rates.
Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2006 and 2007.
Total U.S. 374,551 309,699 278,544 90.00% 170,808 135,672 246,933,431 74.09% 66.68%
Northeast 81,807 68,395 58,689 84.65% 34,687 27,141 45,864,469 71.80% 60.78%
Midwest 101,496 85,827 77,402 90.40% 47,916 38,098 54,749,460 74.87% 67.68%
South 115,906 93,024 85,105 91.96% 51,585 41,524 89,465,143 75.44% 69.38%
West 75,342 62,453 57,348 90.97% 36,620 28,909 56,854,360 73.06% 66.46%
Alabama 4,621 3,698 3,427 92.61% 2,282 1,811 3,806,526 72.84% 67.45%
Alaska 4,667 3,378 3,042 90.05% 2,197 1,762 534,137 77.02% 69.36%
Arizona 5,045 3,820 3,491 91.47% 2,262 1,765 5,052,100 71.90% 65.76%
Arkansas 4,934 3,905 3,668 93.89% 2,157 1,774 2,310,977 80.03% 75.14%
California 16,976 15,184 13,558 89.34% 9,588 7,309 29,742,955 71.28% 63.68%
Colorado 5,156 4,246 3,883 91.39% 2,222 1,788 3,933,092 76.56% 69.96%
Connecticut 5,250 4,598 4,083 88.73% 2,299 1,811 2,922,219 75.38% 66.88%
Delaware 4,748 3,859 3,445 89.35% 2,211 1,780 710,297 77.17% 68.95%
District of Columbia 8,069 6,500 5,517 84.90% 2,127 1,704 497,902 76.34% 64.81%
Florida 21,436 16,803 15,087 89.73% 9,203 7,256 15,209,315 72.25% 64.83%
Georgia 4,478 3,550 3,294 92.88% 2,229 1,816 7,585,920 75.64% 70.26%
Hawaii 5,311 4,430 3,866 86.83% 2,369 1,738 1,045,314 66.37% 57.63%
Idaho 4,672 3,898 3,678 94.36% 2,273 1,844 1,191,260 77.77% 73.38%
Illinois 20,830 18,125 14,474 79.80% 9,663 7,146 10,539,421 68.01% 54.27%
Indiana 4,749 3,969 3,660 92.15% 2,357 1,891 5,196,291 76.51% 70.50%
Iowa 4,737 4,073 3,785 93.02% 2,201 1,813 2,474,931 78.43% 72.95%
Kansas 4,386 3,721 3,510 94.33% 2,236 1,790 2,250,830 79.10% 74.62%
Kentucky 4,776 4,031 3,794 94.09% 2,248 1,801 3,482,766 75.36% 70.90%
Louisiana 4,959 3,456 3,261 94.45% 2,180 1,770 3,481,583 73.55% 69.47%
Maine 6,400 4,584 4,203 91.72% 2,206 1,820 1,128,319 78.38% 71.89%
Maryland 4,672 4,039 3,430 84.97% 2,273 1,815 4,639,099 76.76% 65.22%
Massachusetts 5,423 4,630 4,022 86.79% 2,312 1,809 5,428,207 74.23% 64.42%
Michigan 17,885 14,896 13,406 90.01% 8,902 7,191 8,384,565 75.48% 67.94%
Minnesota 4,707 4,028 3,728 92.47% 2,189 1,797 4,296,034 79.55% 73.57%
Mississippi 4,670 3,487 3,313 94.82% 2,167 1,786 2,346,770 76.28% 72.32%
Missouri 4,755 3,927 3,704 94.33% 2,262 1,840 4,828,217 74.46% 70.23%
Montana 5,297 4,248 4,006 94.30% 2,202 1,800 795,884 77.92% 73.48%
Nebraska 4,758 4,067 3,832 94.23% 2,219 1,807 1,444,216 77.76% 73.27%
Nevada 4,693 3,858 3,639 94.43% 2,200 1,766 2,064,235 75.60% 71.39%
New Hampshire 5,356 4,291 3,874 90.12% 2,209 1,779 1,113,711 77.43% 69.79%
New Jersey 5,260 4,563 3,951 86.58% 2,404 1,797 7,241,267 70.94% 61.42%
New Mexico 4,909 3,855 3,639 94.40% 2,216 1,840 1,597,686 76.68% 72.38%
New York 23,804 20,327 15,931 78.33% 10,001 7,283 16,156,762 66.84% 52.36%
North Carolina 5,946 4,847 4,526 93.37% 2,424 1,974 7,299,873 76.60% 71.52%
North Dakota 5,221 4,219 3,984 94.41% 2,229 1,839 528,368 79.70% 75.25%
Ohio 19,775 16,810 15,835 94.17% 9,079 7,253 9,513,849 74.97% 70.60%
Oklahoma 5,717 4,584 4,158 90.50% 2,364 1,877 2,913,243 75.89% 68.68%
Oregon 5,027 4,252 3,953 92.88% 2,261 1,798 3,121,110 73.70% 68.46%
Pennsylvania 20,383 17,393 15,424 88.60% 8,899 7,223 10,442,770 75.66% 67.03%
Rhode Island 4,952 4,260 3,770 88.43% 2,248 1,833 895,812 76.74% 67.86%
South Carolina 5,445 4,264 4,021 94.31% 2,256 1,846 3,579,496 77.40% 73.00%
South Dakota 4,568 3,685 3,495 94.84% 2,226 1,848 643,027 80.01% 75.89%
Tennessee 4,517 3,762 3,511 93.26% 2,172 1,800 5,038,139 77.76% 72.52%
Texas 16,109 13,174 12,421 94.25% 8,707 7,094 18,774,352 76.50% 72.10%
Utah 3,483 2,951 2,803 94.96% 2,157 1,812 2,012,531 80.36% 76.31%
Vermont 4,979 3,749 3,431 91.50% 2,109 1,786 535,402 82.50% 75.49%
Virginia 5,209 4,357 3,836 87.92% 2,344 1,830 6,249,645 74.88% 65.83%
Washington 4,908 4,140 3,855 93.08% 2,333 1,838 5,334,602 75.37% 70.15%
West Virginia 5,600 4,708 4,396 93.35% 2,241 1,790 1,539,241 75.24% 70.23%
Wisconsin 5,125 4,307 3,989 92.67% 2,353 1,883 4,649,712 77.27% 71.61%
Wyoming 5,198 4,193 3,935 93.87% 2,340 1,849 429,454 75.97% 71.31%
Table A.8 Sample Sizes, Weighted Interview Response Rates, and Population Estimates, by State and Three Age Groups: 2006 and 2007
State 12-17
Total
Selected
12-17
Total
Responded
12-17
Population
Estimate
12-17
Weighted
Interview
Response
Rate
18-25
Total
Selected
18-25
Total
Responded
18-25
Population
Estimate
18-25
Weighted
Interview
Response
Rate
26+
Total
Selected
26+
Total
Responded
26+
Population
Estimate
26+
Weighted
Interview
Response
Rate
NOTE: To compute the pooled 2006-2007 weighted response rates, two samples were combined, and the individual year weights were used for the pooled sample. Thus, the response rates presented here are weighted across 2 years of data rather than being a simple average of the 2006 and 2007 individual response rates.
Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2006 and 2007.
Total U.S. 52,893 45,387 25,316,510 85.40% 55,388 44,561 32,735,362 80.36% 62,527 45,724 188,881,560 71.48%
Northeast 10,745 9,109 4,485,801 82.85% 11,268 8,895 5,882,801 77.45% 12,674 9,137 35,495,867 69.48%
Midwest 14,868 12,747 5,642,796 85.92% 15,463 12,447 7,335,788 80.19% 17,585 12,904 41,770,875 72.45%
South 16,134 13,964 9,140,514 86.53% 16,589 13,601 11,684,367 82.34% 18,862 13,959 68,640,262 72.77%
West 11,146 9,567 6,047,398 85.09% 12,068 9,618 7,832,405 79.74% 13,406 9,724 42,974,556 70.13%
Alabama 675 577 386,639 85.40% 734 622 500,168 84.53% 873 612 2,919,719 69.34%
Alaska 708 611 64,383 86.18% 714 560 74,321 78.56% 775 591 395,433 75.24%
Arizona 647 567 531,706 86.70% 772 594 667,551 76.91% 843 604 3,852,843 69.01%
Arkansas 700 598 234,358 85.46% 664 543 298,001 83.34% 793 633 1,778,618 78.84%
California 2,923 2,447 3,251,070 83.60% 3,065 2,396 4,216,574 79.26% 3,600 2,466 22,275,311 67.97%
Colorado 690 596 387,286 86.20% 738 594 516,885 81.27% 794 598 3,028,921 74.53%
Connecticut 716 621 296,415 86.90% 723 555 352,612 78.03% 860 635 2,273,192 73.49%
Delaware 662 581 70,333 88.25% 728 583 91,979 81.20% 821 616 547,985 75.08%
District of Columbia 675 578 37,965 85.95% 627 526 82,030 83.48% 825 600 377,906 73.96%
Florida 2,744 2,373 1,389,340 86.00% 2,999 2,445 1,778,827 81.68% 3,460 2,438 12,041,147 69.25%
Georgia 750 644 822,659 86.45% 696 583 1,001,876 83.54% 783 589 5,761,385 72.58%
Hawaii 717 576 99,465 78.42% 755 572 126,140 76.75% 897 590 819,708 63.15%
Idaho 728 622 132,866 85.02% 756 618 165,315 82.16% 789 604 893,079 75.84%
Illinois 2,966 2,457 1,094,265 82.97% 3,022 2,253 1,433,731 73.93% 3,675 2,436 8,011,425 64.91%
Indiana 693 579 539,431 84.57% 847 691 689,525 81.76% 817 621 3,967,335 74.50%
Iowa 712 627 248,086 88.04% 682 562 343,994 82.68% 807 624 1,882,850 76.44%
Kansas 743 634 235,408 84.72% 658 510 322,138 77.17% 835 646 1,693,284 78.72%
Kentucky 711 606 341,772 85.27% 722 593 430,183 82.84% 815 602 2,710,811 72.80%
Louisiana 660 593 372,138 89.43% 718 603 505,392 84.61% 802 574 2,604,053 69.15%
Maine 713 624 105,652 86.98% 751 627 127,761 83.98% 742 569 894,906 76.40%
Maryland 690 584 478,466 84.21% 739 599 589,416 81.41% 844 632 3,571,216 75.22%
Massachusetts 713 589 510,890 80.12% 763 603 716,472 79.28% 836 617 4,200,845 72.56%
Michigan 2,701 2,342 888,059 86.76% 2,863 2,358 1,095,038 82.29% 3,338 2,491 6,401,469 72.79%
Minnesota 682 598 436,903 88.84% 739 604 582,894 82.51% 768 595 3,276,237 77.70%
Mississippi 692 613 259,663 89.04% 663 572 330,771 86.24% 812 601 1,756,337 72.34%
Missouri 690 603 494,026 87.20% 733 617 633,170 84.05% 839 620 3,701,021 71.28%
Montana 677 592 79,003 87.20% 711 572 105,557 79.78% 814 636 611,324 76.40%
Nebraska 740 627 149,456 85.41% 707 602 209,102 85.01% 772 578 1,085,658 75.06%
Nevada 635 564 211,067 88.78% 731 588 243,884 80.67% 834 614 1,609,285 73.19%
New Hampshire 691 596 111,310 85.49% 739 592 134,161 81.30% 779 591 868,239 75.93%
New Jersey 747 614 727,090 81.15% 739 550 852,072 74.47% 918 633 5,662,105 69.09%
New Mexico 706 627 172,181 88.27% 732 624 226,537 86.24% 778 589 1,198,968 73.02%
New York 3,039 2,448 1,579,916 79.75% 3,253 2,386 2,179,143 73.19% 3,709 2,449 12,397,704 64.17%
North Carolina 779 671 728,599 86.97% 827 690 907,260 83.84% 818 613 5,664,014 73.85%
North Dakota 710 605 50,947 85.12% 733 616 88,579 84.40% 786 618 388,842 77.91%
Ohio 2,822 2,431 971,766 86.58% 2,991 2,440 1,226,839 82.10% 3,266 2,382 7,315,244 72.22%
Oklahoma 811 683 299,621 84.65% 745 589 410,759 79.39% 808 605 2,202,862 73.93%
Oregon 669 585 297,325 87.23% 764 610 387,123 78.96% 828 603 2,436,662 71.31%
Pennsylvania 2,785 2,445 1,018,244 87.62% 2,850 2,352 1,324,878 82.93% 3,264 2,426 8,099,649 72.95%
Rhode Island 695 607 85,339 88.03% 735 613 127,016 84.47% 818 613 683,457 73.99%
South Carolina 651 575 362,886 87.44% 823 675 457,237 81.39% 782 596 2,759,373 75.44%
South Dakota 682 613 66,722 90.31% 681 571 91,328 85.40% 863 664 484,977 77.71%
Tennessee 703 625 496,587 88.89% 703 588 620,435 84.59% 766 587 3,921,118 75.17%
Texas 2,809 2,448 2,105,817 87.38% 2,729 2,252 2,699,382 82.61% 3,169 2,394 13,969,152 73.63%
Utah 632 570 243,193 91.64% 738 628 370,864 84.20% 787 614 1,398,474 77.25%
Vermont 646 565 50,946 86.99% 715 617 68,687 86.73% 748 604 415,768 81.29%
Virginia 730 618 617,354 83.71% 759 574 798,995 76.55% 855 638 4,833,297 73.50%
Washington 695 597 534,929 85.73% 798 633 672,222 79.93% 840 608 4,127,451 73.14%
West Virginia 692 597 136,317 85.82% 713 564 181,656 78.66% 836 629 1,221,268 73.55%
Wisconsin 727 631 467,728 86.37% 807 623 619,449 76.54% 819 629 3,562,535 76.23%
Wyoming 719 613 42,925 86.08% 794 629 59,433 79.60% 827 607 327,096 73.88%
Table A.9 Sample Sizes, Weighted Screening and Interview Response Rates, and Population Estimates, by State, for Persons Aged 12 or Older: 2007 and 2008
State Total
Selected
DUs
Total
Eligible
DUs
Total
Completed
Screeners
Weighted DU
Screening
Response Rate
Total
Selected
Total
Responded
Population
Estimate
Weighted
Interview
Response Rate
Weighted
Overall
Response Rate
DU = dwelling unit.
NOTE: To compute the pooled 2007-2008 weighted response rates, two samples were combined, and the individual year weights were used for the pooled sample. Thus, the response rates presented here are weighted across 2 years of data rather than being a simple average of the 2007 and 2008 individual response rates.
Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2007 and 2008.
Total U.S. 386,907 318,544 284,425 89.25% 172,209 136,606 248,830,148 74.19% 66.21%
Northeast 83,159 69,298 59,078 84.11% 34,822 27,236 45,988,053 72.07% 60.62%
Midwest 105,180 88,769 79,674 90.11% 48,533 38,424 54,878,124 74.64% 67.26%
South 117,819 94,358 85,735 91.48% 51,378 41,560 90,451,261 76.17% 69.67%
West 80,749 66,119 59,938 89.06% 37,476 29,386 57,512,709 72.38% 64.46%
Alabama 5,321 4,243 3,934 92.88% 2,325 1,828 3,827,671 71.77% 66.66%
Alaska 5,047 3,445 3,117 90.52% 2,213 1,760 541,104 77.11% 69.81%
Arizona 5,644 4,130 3,648 88.39% 2,288 1,793 5,179,707 73.62% 65.07%
Arkansas 5,255 4,131 3,875 93.77% 2,237 1,845 2,324,674 78.68% 73.78%
California 17,865 15,878 13,731 86.47% 9,871 7,482 29,930,854 70.17% 60.67%
Colorado 5,611 4,542 4,138 91.03% 2,316 1,838 4,006,207 75.29% 68.54%
Connecticut 5,647 5,020 4,450 88.55% 2,328 1,858 2,918,710 76.01% 67.31%
Delaware 4,882 4,052 3,587 88.73% 2,268 1,826 718,171 77.82% 69.05%
District of Columbia 8,335 6,646 5,502 82.59% 2,122 1,724 503,725 77.11% 63.69%
Florida 21,956 16,938 15,247 90.01% 8,964 7,175 15,305,375 74.13% 66.73%
Georgia 4,811 3,746 3,444 91.99% 2,172 1,768 7,698,014 76.04% 69.95%
Hawaii 5,959 4,779 4,059 83.67% 2,456 1,746 1,052,918 64.69% 54.13%
Idaho 4,813 3,958 3,743 94.60% 2,307 1,885 1,210,339 78.13% 73.91%
Illinois 21,603 18,824 14,822 78.60% 10,029 7,377 10,572,188 68.12% 53.54%
Indiana 4,726 3,965 3,700 93.29% 2,307 1,835 5,213,685 75.91% 70.81%
Iowa 4,919 4,252 3,964 93.15% 2,262 1,865 2,479,687 79.01% 73.60%
Kansas 4,347 3,713 3,491 94.01% 2,207 1,774 2,262,551 78.25% 73.57%
Kentucky 4,979 4,133 3,895 94.23% 2,204 1,772 3,510,312 75.33% 70.98%
Louisiana 4,935 3,585 3,379 94.26% 2,176 1,782 3,533,282 76.41% 72.02%
Maine 6,408 4,724 4,340 91.86% 2,221 1,832 1,126,141 76.80% 70.55%
Maryland 4,872 4,229 3,539 83.55% 2,300 1,869 4,650,108 76.96% 64.30%
Massachusetts 5,380 4,541 3,986 87.59% 2,255 1,796 5,458,910 74.84% 65.55%
Michigan 19,466 15,844 14,125 89.18% 9,026 7,241 8,360,590 74.77% 66.68%
Minnesota 4,703 4,025 3,782 93.92% 2,205 1,806 4,314,382 78.87% 74.07%
Mississippi 4,388 3,369 3,186 94.45% 2,155 1,782 2,351,285 78.06% 73.73%
Missouri 5,103 4,258 3,998 93.92% 2,260 1,830 4,851,087 74.94% 70.38%
Montana 5,692 4,535 4,282 94.42% 2,219 1,810 804,684 77.64% 73.31%
Nebraska 4,707 3,928 3,704 94.30% 2,228 1,805 1,448,552 77.06% 72.67%
Nevada 5,191 4,252 4,004 94.37% 2,224 1,777 2,102,034 75.51% 71.25%
New Hampshire 5,211 4,073 3,627 88.93% 2,218 1,780 1,114,052 78.04% 69.40%
New Jersey 5,325 4,563 3,996 87.60% 2,400 1,872 7,226,479 74.04% 64.85%
New Mexico 5,292 3,983 3,758 94.36% 2,224 1,832 1,611,081 77.88% 73.49%
New York 24,107 20,516 15,799 76.89% 10,058 7,269 16,278,230 66.00% 50.75%
North Carolina 5,375 4,473 4,125 92.26% 2,290 1,864 7,438,817 76.38% 70.47%
North Dakota 5,467 4,438 4,180 94.23% 2,248 1,837 530,308 79.38% 74.80%
Ohio 20,541 17,440 16,363 93.81% 9,171 7,318 9,517,578 74.60% 69.99%
Oklahoma 4,994 4,054 3,672 90.60% 2,321 1,849 2,934,416 77.39% 70.12%
Oregon 5,238 4,483 4,138 92.24% 2,402 1,927 3,156,185 72.78% 67.13%
Pennsylvania 20,470 17,476 15,286 87.18% 8,966 7,250 10,440,959 75.71% 66.00%
Rhode Island 5,188 4,362 3,899 89.38% 2,198 1,795 889,809 76.65% 68.51%
South Carolina 5,598 4,355 4,030 92.40% 2,242 1,863 3,637,391 80.33% 74.22%
South Dakota 4,498 3,690 3,514 95.24% 2,265 1,885 651,493 78.89% 75.14%
Tennessee 4,724 3,865 3,587 92.85% 2,282 1,833 5,109,440 75.38% 69.99%
Texas 15,940 13,095 12,269 93.69% 8,691 7,113 19,066,897 77.16% 72.29%
Utah 3,654 3,132 2,971 94.89% 2,238 1,861 2,081,260 78.91% 74.88%
Vermont 5,423 4,023 3,695 91.83% 2,178 1,784 534,763 78.54% 72.12%
Virginia 5,171 4,276 3,742 87.43% 2,339 1,850 6,305,668 76.08% 66.52%
Washington 5,234 4,526 4,176 92.25% 2,347 1,829 5,401,732 74.50% 68.72%
West Virginia 6,283 5,168 4,722 91.26% 2,290 1,817 1,536,017 76.20% 69.54%
Wisconsin 5,100 4,392 4,031 91.84% 2,325 1,851 4,676,025 77.50% 71.17%
Wyoming 5,509 4,476 4,173 93.25% 2,371 1,846 434,604 73.46% 68.50%
Table A.10 Sample Sizes, Weighted Interview Response Rates, and Population Estimates, by State and Three Age Groups: 2007 and 2008
State 12-17
Total
Selected
12-17
Total
Responded
12-17
Population
Estimate
12-17
Weighted
Interview
Response
Rate
18-25
Total
Selected
18-25
Total
Responded
18-25
Population
Estimate
18-25
Weighted
Interview
Response
Rate
26+
Total
Selected
26+
Total
Responded
26+
Population
Estimate
26+
Weighted
Interview
Response
Rate
NOTE: To compute the pooled 2007-2008 weighted response rates, two samples were combined, and the individual year weights were used for the pooled sample. Thus, the response rates presented here are weighted across 2 years of data rather than being a simple average of the 2007 and 2008 individual response rates.
Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2007 and 2008.
Total U.S. 52,692 45,034 25,066,707 85.04% 57,176 45,877 32,834,518 80.21% 62,341 45,695 190,928,923 71.71%
Northeast 10,562 8,933 4,416,523 82.77% 11,629 9,191 5,944,719 77.48% 12,631 9,112 35,626,811 69.86%
Midwest 14,854 12,669 5,561,817 85.25% 16,137 12,932 7,281,812 79.88% 17,542 12,823 42,034,495 72.32%
South 15,800 13,655 9,089,732 86.48% 16,985 13,934 11,725,921 82.51% 18,593 13,971 69,635,608 73.71%
West 11,476 9,777 5,998,634 84.32% 12,425 9,820 7,882,066 79.13% 13,575 9,789 43,632,009 69.46%
Alabama 673 568 383,012 84.53% 767 645 499,641 84.67% 885 615 2,945,019 67.91%
Alaska 736 618 62,685 84.26% 705 551 75,733 79.10% 772 591 402,686 75.46%
Arizona 684 595 537,098 86.45% 770 598 672,122 76.77% 834 600 3,970,487 71.23%
Arkansas 724 637 232,677 87.98% 723 587 293,615 82.78% 790 621 1,798,383 76.90%
California 2,932 2,444 3,209,102 82.68% 3,309 2,572 4,257,978 78.71% 3,630 2,466 22,463,775 66.70%
Colorado 762 656 387,018 86.93% 736 573 520,149 78.28% 818 609 3,099,040 73.24%
Connecticut 636 559 292,219 88.48% 854 669 356,482 77.81% 838 630 2,270,009 74.29%
Delaware 671 567 69,899 84.71% 841 678 92,374 82.10% 756 581 555,898 76.13%
District of Columbia 643 572 37,001 89.58% 722 592 84,647 81.59% 757 560 382,077 74.94%
Florida 2,668 2,298 1,368,710 86.14% 2,879 2,382 1,777,472 82.69% 3,417 2,495 12,159,193 71.54%
Georgia 692 603 824,664 87.31% 671 561 999,107 83.92% 809 604 5,874,242 72.93%
Hawaii 720 571 95,794 79.05% 806 589 128,777 72.56% 930 586 828,347 61.77%
Idaho 731 640 132,932 86.74% 739 606 163,520 81.70% 837 639 913,888 76.34%
Illinois 3,055 2,487 1,082,534 81.69% 3,280 2,444 1,442,935 74.22% 3,694 2,446 8,046,718 65.17%
Indiana 710 594 535,015 84.76% 809 650 677,663 80.14% 788 591 4,001,008 74.04%
Iowa 729 636 244,378 87.23% 699 583 340,717 83.81% 834 646 1,894,591 77.15%
Kansas 656 575 232,244 87.07% 734 571 321,431 78.18% 817 628 1,708,875 77.15%
Kentucky 698 600 339,631 85.18% 727 600 425,520 81.37% 779 572 2,745,161 72.98%
Louisiana 667 580 370,852 86.21% 712 600 513,946 85.21% 797 602 2,648,484 73.20%
Maine 663 587 102,760 88.12% 765 644 125,395 84.52% 793 601 897,986 74.37%
Maryland 696 603 469,557 85.96% 808 667 598,009 82.93% 796 599 3,582,541 74.82%
Massachusetts 716 604 506,225 82.21% 742 594 733,229 79.30% 797 598 4,219,456 73.16%
Michigan 2,698 2,324 869,168 85.88% 3,086 2,525 1,086,307 81.62% 3,242 2,392 6,405,116 72.06%
Minnesota 731 634 429,517 87.16% 704 572 576,248 81.62% 770 600 3,308,617 77.27%
Mississippi 655 577 256,834 88.29% 700 595 329,777 84.58% 800 610 1,764,673 75.45%
Missouri 706 620 488,564 86.73% 716 584 623,849 80.82% 838 626 3,738,674 72.43%
Montana 707 605 78,003 85.78% 728 604 105,436 82.32% 784 601 621,245 75.83%
Nebraska 724 629 147,219 87.06% 694 570 208,669 81.17% 810 606 1,092,664 74.76%
Nevada 668 587 213,693 88.88% 761 604 241,972 79.78% 795 586 1,646,368 73.23%
New Hampshire 675 567 109,279 83.54% 714 581 132,548 81.99% 829 632 872,225 76.86%
New Jersey 753 619 715,118 80.43% 846 670 858,459 77.88% 801 583 5,652,902 72.59%
New Mexico 689 621 167,079 89.82% 721 591 226,011 82.65% 814 620 1,217,991 75.34%
New York 2,959 2,395 1,559,314 79.99% 3,354 2,435 2,218,415 72.46% 3,745 2,439 12,500,501 63.16%
North Carolina 782 681 730,031 87.71% 697 568 926,614 82.72% 811 615 5,782,173 73.68%
North Dakota 718 609 49,767 84.60% 751 621 89,213 83.07% 779 607 391,328 77.81%
Ohio 2,841 2,435 956,958 85.82% 2,989 2,448 1,210,200 82.63% 3,341 2,435 7,350,420 71.82%
Oklahoma 753 636 295,908 84.45% 762 597 408,764 79.09% 806 616 2,229,744 76.13%
Oregon 688 586 295,639 84.84% 888 742 383,360 82.66% 826 599 2,477,185 69.80%
Pennsylvania 2,810 2,430 998,611 86.16% 2,961 2,434 1,325,852 82.19% 3,195 2,386 8,116,495 73.36%
Rhode Island 674 594 83,372 87.96% 690 577 126,249 85.00% 834 624 680,188 73.67%
South Carolina 669 583 359,862 87.10% 783 644 460,337 81.98% 790 636 2,817,192 79.25%
South Dakota 649 584 66,089 89.89% 754 645 90,910 85.62% 862 656 494,494 76.48%
Tennessee 676 579 496,878 85.98% 768 638 616,545 83.44% 838 616 3,996,018 72.83%
Texas 2,706 2,359 2,107,904 87.12% 2,873 2,383 2,702,238 82.99% 3,112 2,371 14,256,754 74.51%
Utah 727 648 248,473 88.58% 680 561 374,336 82.77% 831 652 1,458,451 76.32%
Vermont 676 578 49,626 85.41% 703 587 68,089 83.67% 799 619 417,049 76.97%
Virginia 707 601 612,162 85.08% 805 614 820,128 77.30% 827 635 4,873,378 74.79%
Washington 712 596 528,584 84.40% 784 614 673,412 79.67% 851 619 4,199,736 72.36%
West Virginia 720 611 134,149 84.80% 747 583 177,189 77.97% 823 623 1,224,679 74.98%
Wisconsin 637 542 460,365 85.33% 921 719 613,671 78.70% 767 590 3,601,989 76.25%
Wyoming 720 610 42,535 85.19% 798 615 59,260 77.35% 853 621 332,809 71.08%
Table A.11 Sample Sizes, Weighted Interview Response Rates, and Population Estimates among Persons Aged 12 to 20, by State: 2006, 2007, and 2008
State 2006
Total
Selected
2006
Total
Responded
2006
Population
Estimate
2006
Weighted
Interview
Response
Rate
2007
Total
Selected
2007
Total
Responded
2007
Population
Estimate
2007
Weighted
Interview
Response
Rate
2008
Total
Selected
2008
Total
Responded
2008
Population
Estimate
2008
Weighted
Interview
Response
Rate
Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2006, 2007, and 2008.
Total U.S. 36,754 31,342 38,184,777 84.92% 36,653 31,132 38,475,786 84.40% 37,414 31,691 38,109,092 84.54%
Northeast 7,559 6,357 6,808,407 82.53% 7,615 6,380 6,927,594 81.31% 7,483 6,306 6,735,784 83.15%
Midwest 10,179 8,666 8,488,925 85.03% 10,332 8,793 8,530,144 85.00% 10,526 8,854 8,356,484 83.74%
South 11,329 9,764 13,770,324 85.84% 10,913 9,344 13,726,139 85.74% 11,156 9,609 13,857,311 86.31%
West 7,687 6,555 9,117,121 85.21% 7,793 6,615 9,291,909 84.13% 8,249 6,922 9,159,513 83.60%
Alabama 499 439 612,196 87.37% 464 396 592,470 85.95% 493 427 581,262 86.76%
Alaska 499 416 95,199 82.41% 471 402 94,412 86.48% 515 414 92,180 80.10%
Arizona 465 399 801,413 85.79% 485 402 831,600 81.32% 481 413 810,336 85.49%
Arkansas 474 411 378,803 87.39% 491 415 355,964 85.69% 513 454 350,656 88.83%
California 2,007 1,681 4,883,362 84.24% 2,027 1,690 4,954,430 83.32% 2,120 1,761 4,938,568 82.75%
Colorado 436 375 562,030 85.25% 488 415 573,755 85.11% 530 444 568,813 83.19%
Connecticut 510 429 421,119 84.66% 490 413 435,326 84.09% 453 396 422,896 88.56%
Delaware 449 391 104,557 87.08% 481 407 108,201 84.53% 495 410 104,894 83.20%
District of Columbia 439 378 66,559 87.92% 449 393 72,337 88.36% 410 368 58,497 90.11%
Florida 2,034 1,757 2,127,307 85.94% 1,798 1,535 2,079,077 85.28% 1,953 1,691 2,132,876 86.69%
Georgia 572 490 1,254,765 85.97% 457 401 1,220,703 88.30% 512 438 1,242,605 84.97%
Hawaii 490 393 140,236 78.61% 475 379 136,591 78.91% 525 408 141,555 77.46%
Idaho 482 410 206,568 86.24% 496 418 186,618 82.46% 477 418 193,450 87.15%
Illinois 1,923 1,609 1,644,639 82.95% 2,097 1,691 1,668,918 80.25% 2,113 1,719 1,626,682 81.62%
Indiana 527 437 810,463 83.97% 482 403 802,712 83.83% 540 447 818,888 83.63%
Iowa 471 395 369,185 83.32% 510 450 385,713 87.80% 484 413 367,032 86.07%
Kansas 512 414 372,583 79.75% 463 406 349,573 86.16% 441 367 343,518 83.67%
Kentucky 506 429 509,169 85.20% 475 403 510,132 84.81% 486 423 515,913 86.34%
Louisiana 438 389 541,357 88.47% 477 420 565,529 87.27% 466 404 615,972 86.94%
Maine 526 455 165,874 85.39% 506 437 159,826 86.86% 484 423 154,462 86.37%
Maryland 492 411 704,270 82.90% 482 411 729,464 85.16% 538 474 707,164 88.35%
Massachusetts 492 400 797,860 81.53% 507 416 790,129 78.14% 475 405 783,464 85.33%
Michigan 1,868 1,629 1,304,963 87.43% 1,873 1,596 1,322,124 84.60% 2,027 1,730 1,325,437 84.95%
Minnesota 405 359 633,052 90.02% 485 418 621,993 86.66% 452 390 620,418 86.35%
Mississippi 502 448 416,500 90.49% 457 405 397,984 88.94% 464 401 385,041 86.31%
Missouri 481 419 753,996 86.35% 508 446 779,438 88.13% 483 410 713,872 82.22%
Montana 470 403 117,066 85.58% 453 392 119,194 84.79% 525 442 121,269 85.39%
Nebraska 497 418 233,340 85.09% 510 441 232,321 87.70% 483 417 225,154 85.63%
Nevada 441 384 296,994 86.24% 431 374 305,708 87.49% 490 423 301,339 86.56%
New Hampshire 508 439 172,530 86.47% 480 396 165,706 82.26% 494 418 172,605 84.97%
New Jersey 497 398 1,004,017 80.56% 480 397 1,053,380 79.84% 579 474 1,042,888 81.60%
New Mexico 463 407 262,895 87.53% 512 460 258,604 90.87% 442 382 252,364 85.83%
New York 2,058 1,624 2,426,076 78.10% 2,204 1,749 2,512,654 78.46% 2,028 1,630 2,425,431 79.44%
North Carolina 548 476 1,119,962 87.00% 588 493 1,178,490 84.57% 480 420 1,102,143 88.11%
North Dakota 496 427 90,517 86.25% 510 431 85,278 84.71% 494 417 83,543 83.50%
Ohio 2,035 1,725 1,475,834 85.27% 1,932 1,670 1,476,889 86.70% 2,087 1,757 1,463,023 84.33%
Oklahoma 520 432 450,592 83.44% 553 449 433,136 80.15% 457 385 440,291 84.06%
Oregon 480 422 445,510 87.89% 528 452 502,263 85.88% 583 507 481,595 86.18%
Pennsylvania 1,934 1,715 1,595,641 88.93% 1,987 1,712 1,586,861 85.71% 2,002 1,729 1,525,711 86.46%
Rhode Island 492 427 136,938 88.09% 488 432 138,232 88.96% 448 398 130,107 88.98%
South Carolina 474 416 535,586 86.48% 444 385 532,386 86.10% 488 422 547,282 86.74%
South Dakota 464 408 100,335 88.12% 435 391 98,754 90.55% 497 447 106,030 89.70%
Tennessee 485 425 735,982 86.63% 478 421 721,190 88.71% 456 378 699,714 82.76%
Texas 1,871 1,602 3,067,870 85.80% 1,861 1,619 3,108,430 86.89% 1,906 1,645 3,243,147 86.32%
Utah 410 375 380,898 91.75% 471 415 399,647 88.79% 501 434 395,972 84.14%
Vermont 542 470 88,350 86.19% 473 428 85,480 90.65% 520 433 78,221 82.77%
Virginia 522 432 930,209 81.32% 485 394 906,519 80.33% 502 428 931,139 86.21%
Washington 546 469 861,788 85.86% 494 420 864,704 85.28% 538 446 795,765 84.12%
West Virginia 504 438 214,640 86.71% 473 397 214,128 83.09% 537 441 198,715 82.69%
Wisconsin 500 426 700,020 83.19% 527 450 706,430 85.91% 425 340 662,888 81.80%
Wyoming 498 421 63,161 85.71% 462 396 64,382 86.06% 522 430 66,307 81.99%
Table A.12 Sample Sizes, Weighted Interview Response Rates, and Population Estimates among Persons Aged 12 to 20, by State: 2006-2007 and 2007-2008
State 2006-2007
Total
Selected
2006-2007
Total
Responded
2006-2007
Population
Estimate
2006-2007
Weighted
Interview
Response
Rate
2007-2008
Total
Selected
2007-2008
Total
Responded
2007-2008
Population
Estimate
2007-2008
Weighted
Interview
Response
Rate
To compute the pooled weighted response rates, the two samples were combined, and the individual-year weights were used for the pooled sample. Thus, the response rates presented here are weighted across 2 years of data rather than being a simple average of the individual response rates.
Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2006, 2007, and 2008.
Total U.S. 73,407 62,474 38,330,281 84.66% 74,067 62,823 38,292,439 84.47%
Northeast 15,174 12,737 6,868,000 81.92% 15,098 12,686 6,831,689 82.22%
Midwest 20,511 17,459 8,509,535 85.01% 20,858 17,647 8,443,314 84.37%
South 22,242 19,108 13,748,232 85.79% 22,069 18,953 13,791,725 86.03%
West 15,480 13,170 9,204,515 84.67% 16,042 13,537 9,225,711 83.87%
Alabama 963 835 602,333 86.66% 957 823 586,866 86.36%
Alaska 970 818 94,806 84.43% 986 816 93,296 83.28%
Arizona 950 801 816,507 83.49% 966 815 820,968 83.32%
Arkansas 965 826 367,383 86.58% 1,004 869 353,310 87.29%
California 4,034 3,371 4,918,896 83.77% 4,147 3,451 4,946,499 83.04%
Colorado 924 790 567,893 85.18% 1,018 859 571,284 84.12%
Connecticut 1,000 842 428,223 84.38% 943 809 429,111 86.26%
Delaware 930 798 106,379 85.76% 976 817 106,547 83.88%
District of Columbia 888 771 69,448 88.14% 859 761 65,417 89.17%
Florida 3,832 3,292 2,103,192 85.61% 3,751 3,226 2,105,976 85.99%
Georgia 1,029 891 1,237,734 87.12% 969 839 1,231,654 86.61%
Hawaii 965 772 138,414 78.76% 1,000 787 139,073 78.18%
Idaho 978 828 196,593 84.42% 973 836 190,034 84.80%
Illinois 4,020 3,300 1,656,778 81.59% 4,210 3,410 1,647,800 80.93%
Indiana 1,009 840 806,588 83.90% 1,022 850 810,800 83.73%
Iowa 981 845 377,449 85.58% 994 863 376,373 86.95%
Kansas 975 820 361,078 82.81% 904 773 346,546 84.90%
Kentucky 981 832 509,651 85.01% 961 826 513,022 85.56%
Louisiana 915 809 553,443 87.84% 943 824 590,750 87.10%
Maine 1,032 892 162,850 86.12% 990 860 157,144 86.62%
Maryland 974 822 716,867 84.04% 1,020 885 718,314 86.77%
Massachusetts 999 816 793,995 79.82% 982 821 786,797 81.69%
Michigan 3,741 3,225 1,313,543 86.00% 3,900 3,326 1,323,781 84.78%
Minnesota 890 777 627,522 88.38% 937 808 621,205 86.51%
Mississippi 959 853 407,242 89.71% 921 806 391,513 87.66%
Missouri 989 865 766,717 87.25% 991 856 746,655 85.28%
Montana 923 795 118,130 85.18% 978 834 120,231 85.09%
Nebraska 1,007 859 232,831 86.43% 993 858 228,738 86.69%
Nevada 872 758 301,351 86.87% 921 797 303,524 87.03%
New Hampshire 988 835 169,118 84.34% 974 814 169,156 83.62%
New Jersey 977 795 1,028,699 80.20% 1,059 871 1,048,134 80.74%
New Mexico 975 867 260,749 89.19% 954 842 255,484 88.43%
New York 4,262 3,373 2,469,365 78.28% 4,232 3,379 2,469,042 78.95%
North Carolina 1,136 969 1,149,226 85.75% 1,068 913 1,140,317 86.28%
North Dakota 1,006 858 87,898 85.48% 1,004 848 84,411 84.11%
Ohio 3,967 3,395 1,476,361 85.98% 4,019 3,427 1,469,956 85.51%
Oklahoma 1,073 881 441,864 81.83% 1,010 834 436,713 82.09%
Oregon 1,008 874 473,887 86.84% 1,111 959 491,929 86.03%
Pennsylvania 3,921 3,427 1,591,251 87.33% 3,989 3,441 1,556,286 86.08%
Rhode Island 980 859 137,585 88.53% 936 830 134,169 88.97%
South Carolina 918 801 533,986 86.29% 932 807 539,834 86.43%
South Dakota 899 799 99,545 89.36% 932 838 102,392 90.11%
Tennessee 963 846 728,586 87.67% 934 799 710,452 85.76%
Texas 3,732 3,221 3,088,150 86.35% 3,767 3,264 3,175,789 86.60%
Utah 881 790 390,273 90.23% 972 849 397,810 86.49%
Vermont 1,015 898 86,915 88.33% 993 861 81,850 86.82%
Virginia 1,007 826 918,364 80.82% 987 822 918,829 83.21%
Washington 1,040 889 863,246 85.57% 1,032 866 830,234 84.73%
West Virginia 977 835 214,384 84.90% 1,010 838 206,422 82.90%
Wisconsin 1,027 876 703,225 84.54% 952 790 684,659 83.84%
Wyoming 960 817 63,771 85.88% 984 826 65,344 84.01%
Table A.13 Outcomes, by Survey Year, for Which Small Area Estimates Are Available
Measure 2002-2003 2003-2004 2004-2005 2005-2006 2006-2007 2007-2008
1 Estimates for these outcomes were not included in the 2002-2003 State report (Wright & Sathe, 2005), but the 2002-2003 estimates are included in the 2003-2004 State report as part of the comparison tables (see Wright & Sathe, 2006). However, the prediction intervals (PIs) associated with these were not published.
2 Estimates for serious psychological distress (SPD) in the years 2002-2003 and 2003-2004 are not comparable with the 2004-2005 and subsequent SPD estimates. For more details, see Section A.8 in Appendix A of the 2005-2006 State report (Hughes et al., 2008). Estimates for SPD are not shown for 2007-2008; for more details, see Section 1.2 in Chapter 1 of this report.
3 Questions used to determine a major depressive episode (MDE) were added in 2004. Only estimates for youths aged 12 to 17 are shown for 2007-2008; for more details, see Section A.10 of this report.
Yes = available, No = not available.
Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, 2005, 2006, 2007, and 2008.
Illicit Drug Use in Past Month Yes Yes Yes Yes Yes Yes
Marijuana Use in Past Year Yes Yes Yes Yes Yes Yes
Marijuana Use in Past Month Yes Yes Yes Yes Yes Yes
Perceptions of Great Risk of Smoking Marijuana Once a Month Yes Yes Yes Yes Yes Yes
First Use of Marijuana Yes Yes Yes Yes Yes Yes
Illicit Drug Use Other Than Marijuana in Past Month Yes Yes Yes Yes Yes Yes
Cocaine Use in Past Year Yes Yes Yes Yes Yes Yes
Nonmedical Use of Pain Relievers in Past Year No1 Yes Yes Yes Yes Yes
Alcohol Use in Past Month Yes Yes Yes Yes Yes Yes
Underage Past Month Use of Alcohol No1 Yes Yes Yes Yes Yes
Binge Alcohol Use in Past Month Yes Yes Yes Yes Yes Yes
Underage Past Month Binge Alcohol Use No1 Yes Yes Yes Yes Yes
Perceptions of Great Risk of Having Five or More Drinks of an Alcoholic Beverage Once or Twice a Week Yes Yes Yes Yes Yes Yes
Tobacco Product Use in Past Month Yes Yes Yes Yes Yes Yes
Cigarette Use in Past Month Yes Yes Yes Yes Yes Yes
Perceptions of Great Risk of Smoking One or More Packs of Cigarettes Per Day Yes Yes Yes Yes Yes Yes
Alcohol Dependence or Abuse in Past Year Yes Yes Yes Yes Yes Yes
Alcohol Dependence in Past Year Yes Yes Yes Yes Yes Yes
Illicit Drug Dependence or Abuse in Past Year Yes Yes Yes Yes Yes Yes
Illicit Drug Dependence in Past Year Yes Yes Yes Yes Yes Yes
Dependence on or Abuse of Illicit Drugs or Alcohol in Past Year Yes Yes Yes Yes Yes Yes
Needing But Not Receiving Treatment for Illicit Drug Use in Past Year Yes Yes Yes Yes Yes Yes
Needing But Not Receiving Treatment for Alcohol Use in Past Year Yes Yes Yes Yes Yes Yes
Serious Psychological Distress in Past Year2 Yes Yes Yes Yes Yes No
Having at Least One Major Depressive Episode in Past Year3 No No Yes Yes Yes Yes


End Notes

8 The four age groups are 12 to 17, 18 to 25, 26 to 34, and 35 or older; the four race/ethnicity groups are non-Hispanic white, non-Hispanic black, non-Hispanic other, and Hispanic; and the two genders are male and female.

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

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