2012-2013
National Survey on Drug Use and Health:
Guide to State Tables and Summary of Small
Area Estimation Methodology

Section A: Overview of NSDUH and Model-Based State Estimates

A.1 Introduction

This document provides information on the model-based small area estimates of substance use and mental disorders in States based on data from the combined 2012-2013 National Surveys on Drug Use and Health (NSDUHs). These estimates are available online along with other related information.1 An annual survey of the civilian, noninstitutionalized population aged 12 or older, NSDUH is sponsored by the Substance Abuse and Mental Health Services Administration (SAMHSA). It collects information from individuals residing in households, noninstitutionalized group quarters (e.g., shelters, rooming houses, dormitories), and civilians living on military bases.

In 2012-2013, NSDUH collected data from 136,147 respondents aged 12 or older and was designed to obtain representative samples from the 50 States and the District of Columbia.2 The survey is planned and managed by SAMHSA's Center for Behavioral Health Statistics and Quality (CBHSQ). Data collection and analysis were conducted under contract with RTI International.3 Nationally in 2012-2013, 314,198 addresses were screened, and 136,147 individuals responded within the screened addresses (see Table C.9). The survey is conducted from January through December each year. The screening response rate (SRR) for 2012-2013 combined averaged 85.0 percent, and the interview response rate (IRR) averaged 72.4 percent, for an overall response rate (ORR) of 61.5 percent (Table C.9). The ORRs for 2012-2013 ranged from 45.8 percent in New York to 75.2 percent in Utah. Estimates have been adjusted to reflect the probability of selection, unit nonresponse, poststratification to known census population estimates, item imputation, and other aspects of the estimation process. These procedures are described in the 2011, 2012, and 2013 NSDUH's methodological resource books (MRBs) (CBHSQ, 2013, 2014, in press). For additional details on NSDUH's methodology, see Section A.2 of the 2011-2012 State small area estimation (SAE) methodology document.4

Section A.2 of this document lists all of the tables and files associated with the 2012-2013 State small area estimates and when and where they can be found. Information is given in Section A.3 on the confidence intervals and margins of error and how to make interpretations with respect to the small area estimates. Section A.4 discusses related substance use measures and warns users about not drawing conclusions by subtracting small area estimates from two different measures.

The survey-weighted hierarchical Bayes (SWHB) estimation methodology used in the production of State estimates from the 1999 to 2012 surveys also was used in the production of the 2012-2013 State estimates. The SWHB methodology is described in Appendix E of the 2001 State report (Wright, 2003b) and in Folsom, Shah, and Vaish (1999). The goals of SAE modeling and the implementation of SAE modeling remain the same and are described in Appendix E of the 2001 State report (Wright, 2003b). A general model description is given in Section B.1 of this document. A list of measures for which small area estimates are produced is given in Section B.2. Predictors used in the 2012-2013 SAE modeling are listed and described in Section B.3.

Small area estimates obtained using the SWHB methodology are design consistent (i.e., the small area estimates for States with large sample sizes 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, to ensure internal consistency, it is desirable to have national small area estimates5 exactly match the national design-based estimates. The benchmarked State-level estimates are also potentially less biased than the unbenchmarked State-level estimates. Beginning in 2002, exact benchmarking was introduced, as described in Section B.4.6 Tables of the estimated numbers of individuals associated with each measure are available online,7 and an explanation of how these counts and their respective Bayesian confidence intervals8 are calculated can be found in Section B.5. Section B.6 discusses the method to compare the estimates of a particular measure between two States. For all measures except major depressive episode (MDE, i.e., depression), serious mental illness (SMI), any mental illness (AMI), and past year serious thoughts of suicide, the age groups for which estimates are provided are 12 to 17, 18 to 25, 26 or older, 18 or older, and 12 or older.9 Estimates of underage (aged 12 to 20) alcohol use and binge alcohol use were also produced. 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 individuals aged 12 to 20.

In Section C, the 2011, 2012, 2013, pooled 2011-2012, and pooled 2012-2013 survey sample sizes, population estimates, and response rates are included in Tables C.1 to C.14, respectively. Table C.15 lists all of the measures and the years for which small area estimates were produced going back to the 2002 NSDUH, and Table C.16 lists all of the measures by age groups for which small area estimates were produced. In addition, Table C.17 provides a summary of milestones implemented in the SAE production process from 2002 to 2013.

A.2 Presentation of Data

In addition to this methodology document, the following files are also available at http://www.samhsa.gov/data/population-data-nsduh/reports?tab=33:

A.3 Confidence Intervals and Margins of Error

At the top of each of the 26 State model-based estimate tables11 is the design-based national estimate along with a 95 percent design-based confidence interval, all of which are based on survey weights and the reported data. The State and regional estimates are model-based statistics (using SAE methodology) that have been adjusted such that the population-weighted mean of the estimates across the 50 States and the District of Columbia equals the design-based national estimate. For more details on this benchmarking, see Section B.4. Associated with each State and regional estimate is a 95 percent Bayesian confidence interval. These intervals indicate the uncertainty in the estimate due to both sampling variability and model bias. For example, the State with the highest estimate of past month use of marijuana for young adults aged 18 to 25 was Rhode Island, with an estimate of 29.8 percent and a 95 percent confidence interval that ranged from 26.3 to 33.5 percent (Table 3 of the State model-based estimates' tables). Therefore, the probability is 0.95 that the true percentage of past month marijuana use in Rhode Island for young adults aged 18 to 25 is between 26.3 and 33.5 percent. As noted earlier in a Section A.1 footnote, the term "prediction interval" (PI) was used in the 2004-2005 NSDUH State report and prior reports to represent uncertainty in the State and regional estimates. However, that term also is used in other applications to estimate future values of a parameter of interest. That interpretation does not apply to NSDUH State model-based estimates, so PI was replaced with "Bayesian confidence interval."

Margin of error is another term used to describe uncertainty in the estimates. For example, if lower interval l comma and upper interval u is a 95 percent symmetric confidence interval for the population proportion (p) and p hat is an estimate of p obtained from the survey data, then the margin of error of p hat is given by u minus p hat or p hat minus l. Because lower interval l comma and upper interval u is a symmetric confidence interval, u minus p hat will be the same as p hat minus l. In this case, the probability is 0.95 that the true population value (p) is within ±u minus p hat or ±p hat minus l of the survey estimate (p hat). The margin of error defined above will vary for each estimate and will be affected not only by the sample size (e.g., the larger the sample, the smaller the margin of error), but also by the sample design (e.g., telephone surveys using random digit dialing and surveys employing a stratified multistage cluster design will, more than likely, produce a different margin of error) (Scheuren, 2004).

The confidence intervals shown in NSDUH reports are asymmetric, meaning that the distance between the estimate and the lower confidence limit will not be the same as the distance between the upper confidence limit and the estimate. For example, Utah's past month marijuana use estimate of 10.9 percent for adults aged 18 to 25 years with a 95 percent confidence interval equal to (8.7, 13.5) (see Table 3 of the State model-based estimates' tables). Therefore Utah's estimate is 2.2 (i.e., 10.9 − 8.7) percentage points from the lower 95 percent confidence limit and 2.6 (i.e., 13.5 − 10.9) percentage points from the upper limit. These asymmetric confidence intervals work well for small percentages often found in NSDUH tables and reports while still being appropriate for larger percentages. Some surveys or polls provide only one margin of error for all reported percentages. This single number is usually calculated by setting the sample percentage estimate (p hat) equal to 50 percent, which will produce an upper bound or maximum margin of error. Such an approach would not be feasible in NSDUH because the estimates vary from less than 1 percent to over 75 percent; hence, applying a single margin of error to these estimates could significantly overstate or understate the actual precision levels. Therefore, given the differences mentioned above, it is more useful and informative to report the confidence interval for each estimate instead of a margin of error.

When it is indicated that a State has the highest or lowest estimate, it does not imply that the State's estimate is significantly higher or lower than the next highest or lowest State. When comparing two State estimates, two overlapping 95 percent confidence intervals do not imply that their State estimates are statistically equivalent at the 5 percent level of significance. For details on a more accurate test to compare State estimates, see Section B.6.

A.4 Related Substance Use Measures

Small area estimates are produced for a number of related drug measures, such as marijuana use and illicit drug use. It might appear that one could draw conclusions by subtracting one from the other (e.g., subtracting the percentage who used illicit drugs other than marijuana in the past month from the percentage who used illicit drugs in the past month to find the percentage who only used marijuana in the past month). Because related measures have been estimated with different models (i.e., separate models by age group and outcome), subtracting one measure from another related measure at the State or census region level can give misleading results, perhaps even a "negative" estimate, and should be avoided. However, these comparisons can be made at the national level because these estimates are design-based estimates. For example, at the national level, subtracting cigarette use estimates from tobacco use estimates will give the estimate of individuals who did not use cigarettes, but used other forms of tobacco.

Section B: State Model-Based Estimation Methodology

B.1 General Model Description

The model can be characterized as a complex mixed12 model (including both fixed and random effects) of the following form:

Equation B.1-1,     D

where pi sub a, i, j, k is the probability of engaging in the behavior of interest (e.g., using marijuana in the past month) for person-k belonging to age group-a in grouped State sampling region (SSR)-j of State-i.13 Let x sub a, i, j, k denote a p sub a times 1 vector of auxiliary (predictor) variables associated with age group-a (12 to 17, 18 to 25, 26 to 34, and 35 or older) and beta sub a denote the associated vector of regression parameters. The age group-specific vectors of auxiliary variables are defined for every block group in the Nation and also include person-level demographic variables, such as race/ethnicity and gender. The vectors of State-level random effects An eta sub i is a transposed vector of values eta sub 1, i and so on until eta sub capital A, i. and grouped SSR-level random effects A nu sub i, j is a vector of transposed values nu sub 1, i, j and so on until nu sub capital A, i, j. are assumed to be mutually independent with An eta sub i is normally distributed with mean 0 and variance denoted by matrix capital D sub eta. and A nu sub i, j is normally distributed with mean 0 and variance denoted by matrix capital D sub nu., where capital A is the total number of individual age groups modeled (generally, Capital A equals 4.). For hierarchical Bayes (HB) estimation purposes, an improper uniform prior distribution is assumed for beta sub a, and proper Wishart prior distributions are assumed for inverse of capital D sub eta and inverse of capital D sub nu. The HB solution for pi sub a, i, j, k involves a series of complex Markov Chain Monte Carlo (MCMC) steps to generate values of the desired fixed and random effects from the underlying joint posterior distribution. The basic process is described in Folsom et al. (1999), Shah, Barnwell, Folsom, and Vaish (2000), and Wright (2003a, 2003b).

Once the required number of MCMC samples (1,250 in all) for the parameters of interest are generated and tested for convergence properties (see Raftery & Lewis, 1992), the small area estimates for each age group × race/ethnicity × gender cell within a block group can be obtained. These block group-level small area estimates then can be aggregated using the appropriate population count projections to form State-level small area estimates for the desired age group(s). These State-level small area estimates are benchmarked to the national design-based estimates as described in Section B.4.

B.2 Variables Modeled

The 2013 NSDUH data were pooled with the 2012 NSDUH data, and age group-specific State estimates for 25 binary (0, 1) measures 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,14
  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 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,
  22. serious mental illness (SMI) in the past year,
  23. any mental illness (AMI) in the past year,
  24. serious thoughts of suicide in the past year, and
  25. past year major depressive episode (MDE, i.e., depression).

Estimates of underage (aged 12 to 20) alcohol use and binge alcohol use were also produced. Comparisons between the 2011-2012 and the 2012-2013 State estimates were produced for all of these measures as well. For details on how measures such as AMI, SMI, MDE, illicit drugs, dependence or abuse, and average annual rate of first use of marijuana are defined, see "2011-2012 National Surveys on Drug Use and Health: Guide to State Tables and Summary of Small Area Estimation Methodology" at http://www.samhsa.gov/data/population-data-nsduh/reports?tab=33.

Illicit drug use includes the use of methamphetamines. NSDUH questions on methamphetamine use are asked in the stimulant module of the core section of the questionnaire in the context of questions about the nonmedical use of prescription stimulants. Beginning in 2005, new questions were added to the special drug module in the noncore section of the NSDUH questionnaire to capture information from respondents who may have used methamphetamines but did not recognize it as a prescription drug and therefore did not report use in the core stimulant module. However, the illicit drug estimates (including dependence, abuse, and treatment of illicit drugs) shown in the 2012-2013 SAE documents include data from the original methamphetamine questions, but they do not include the new methamphetamine items added in 2005 and 2006 (i.e., the responses to the noncore questions). For more information on these new methamphetamine questions, see the findings from the methamphetamine analysis section of the 2005 NSDUH Methodological Resource Book (Center for Behavioral Health Statistics and Quality [CBHSQ], 2007).

B.3 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 [UCRs]), 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). Note that the predictors used to produce the 2012-2013 State small area estimates are the same as the predictors used to produce the 2011-2012 State small area estimates (however, values of the data were updated when possible). That is, no new variable selection was done for 2012-2013.

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.

Nielsen Claritas Data (Description) Nielsen Claritas Data (Level)
% Population Aged 0 to 19 in Block Group Block Group
% Population Aged 20 to 24 in Block Group Block Group
% Population Aged 25 to 34 in Block Group Block Group
% Population Aged 35 to 44 in Block Group Block Group
% Population Aged 45 to 54 in Block Group Block Group
% Population Aged 55 to 64 in Block Group Block Group
% Population Aged 65 or Older in Block Group Block Group
% Non-Hispanic Blacks in Block Group Block Group
% Hispanics in Block Group Block Group
% Non-Hispanic Other Races in Block Group Block Group
% Non-Hispanic Whites in Block Group Block Group
% Males in Block Group Block Group
% American Indians, Eskimos, Aleuts in Tract Tract
% Asians, Pacific Islanders in Tract Tract
% Population Aged 0 to 19 in Tract Tract
% Population Aged 20 to 24 in Tract Tract
% Population Aged 25 to 34 in Tract Tract
% Population Aged 35 to 44 in Tract Tract
% Population Aged 45 to 54 in Tract Tract
% Population Aged 55 to 64 in Tract Tract
% Population Aged 65 or Older in Tract Tract
% Non-Hispanic Blacks in Tract Tract
% Hispanics in Tract Tract
% Non-Hispanic Other Races in Tract Tract
% Non-Hispanic Whites in Tract Tract
% Males in Tract Tract
% Population Aged 0 to 19 in County County
% Population Aged 20 to 24 in County County
% Population Aged 25 to 34 in County County
% Population Aged 35 to 44 in County County
% Population Aged 45 to 54 in County County
% Population Aged 55 to 64 in County County
% Population Aged 65 or Older in County County
% Non-Hispanic Blacks in County County
% Hispanics in County County
% Non-Hispanic Other Races in County County
% Non-Hispanic Whites in County County
% Males in County County

2010 Census Data (Description) 2010 Census Data (Level)
% Hispanics Who Are Cuban Tract

American Community Survey (ACS) (Description) ACS Data (Level)
% Population Who Dropped Out of High School Tract
% Housing Units Built in 1940 to 1949 Tract
% Females 16 Years or Older in Labor Force Tract
% Females Never Married Tract
% Females Separated, Divorced, Widowed, or Other Tract
% One-Person Households Tract
% Males 16 Years or Older in Labor Force Tract
% Males Never Married Tract
% Males Separated, Divorced, Widowed, or Other Tract
% Housing Units Built in 1939 or Earlier Tract
Average Number of Persons per Room Tract
% Families below Poverty Level Tract
% Households with Public Assistance Income Tract
% Housing Units Rented Tract
% Population with 9 to 12 Years of School, No High School Diploma Tract
% Population with 0 to 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
% Housing Units with No Telephone Service Available Tract
% Households with No Vehicle Available Tract
Median Rents for Rental Units Tract
Median Value of Owner-Occupied Housing Units Tract
Median Household Income Tract
% Families below the Poverty Level County

Uniform Crime Report (UCR) Data (Description) UCR Data (Level)
Drug Possession Arrest Rate County
Drug Sale or Manufacture Arrest Rate County
Drug Violations' Arrest Rate County
Marijuana Possession Arrest Rate County
Marijuana Sale or Manufacture Arrest Rate County
Opium or Cocaine Possession Arrest Rate County
Opium or Cocaine Sale or 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 National Survey on Drug Use
and Health (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 Metropolitan Statistical Area (MSA) with ≥ 1 Million, = 0 Otherwise 2010 Census County
= 1 if MSA with < 1 Million, = 0 Otherwise 2010 Census County
= 1 if Non-MSA Urban, = 0 Otherwise 2010 Census Tract
= 1 if Urban Area, = 0 if Rural Area 2010 Census Tract
= 1 if No Cubans in Tract, = 0 Otherwise 2010 Census Tract
= 1 if No Arrests for Dangerous Non-Narcotics, = 0 Otherwise Uniform Crime Report (UCR) County
= 1 if No Arrests for Opium or Cocaine Possession = 0 Otherwise UCR County
= 1 if No Housing Units Built in 1939 or Earlier, = 0 Otherwise American Community Survey (ACS) Tract
=1 if No Housing Units Built in 1940 to 1949, = 0 Otherwise ACS Tract
= 1 if No Households with Public Assistance Income, = 0 Otherwise ACS Tract

Miscellaneous Data (Description) Miscellaneous Data (Source) Miscellaneous Data (Level)
Alcohol Death Rate, Underlying Cause National Center for Health Statistics (NCHS)
International Classification of Diseases, 10th
revision (NCHS-ICD-10)
County
Cigarette Death Rate, Underlying Cause NCHS-ICD-10 County
Drug Death Rate, Underlying Cause NCHS-ICD-10 County
Alcohol Treatment Rate National Survey of Substance Abuse Treatment
Services (N–SSATS) (Formerly Called Uniform
Facility Data Set [UFDS])
County
Alcohol and Drug Treatment Rate N-SSATS (Formerly Called UFDS) County
Drug Treatment Rate N-SSATS (Formerly Called UFDS) County
Unemployment Rate Bureau of Labor Statistics (BLS) County
Per Capita Income (in Thousands) Bureau of Economic Analysis (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 Substance Abuse and Mental Health Services
Administration (SAMHSA)
State
Cost of Services Factor Index SAMHSA State
Total Taxable Resources per Capita
Index
U.S. Department of Treasury State

B.4 Benchmarking the Age Group-Specific Small Area Estimates

The self-calibration built into the survey-weighted hierarchical Bayes (SWHB) solution ensures that the population-weighted average of the State small area estimates will closely match the national design-based estimates. The national design-based estimates in NSDUH are based entirely on survey-weighted data using a direct estimation approach, whereas the State and census region estimates are model-based. 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 Bayesian confidence interval 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 2012-2013 State-by-age group small area estimates is adjusted by adding the common factor Delta sub a is defined as the national design-based estimate, capital D sub a, minus the national model-based small area estimate, capital P sub a. where capital D sub a is the design-based national estimate and capital P sub a is the population-weighted mean of the State small area estimates capital P sub s and a for age group-a. The exactly benchmarked State-s and age group-a small area estimates then are given by The benchmarked State-s and age group-a small area estimate, Theta sub s and a, is defined as the sum of capital P sub s and a and Delta sub a.. Experience with such additive adjustments suggests that the resulting exactly benchmarked State small area estimates will always be between 0 percent 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 Bayesian confidence (credible) intervals can be re-centered 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 Bayesian confidence intervals Lower sub s and a is the lower bound of the 95 percent Bayesian confidence interval of Theta sub s and a; upper sub s and a is the upper bound of the 95 confidence interval of Theta sub s and a. are defined below:

Equation B.4-1 ,     D

where

Equation B.4-2 ,     D

Equation B.4-3 ,     D     and

Equation B.4-4 .     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.

B.5 Calculation of Estimated Number of Individuals Associated with Each Outcome

Tables 1 to 26 of "2012-2013 NSDUHs: Model-Based Estimated Totals (in Thousands) (50 States and the District of Columbia)" show the estimated numbers of individuals associated with each of the 25 outcomes of interest.15 To calculate these numbers, the benchmarked small area estimates and the associated 95 percent Bayesian confidence intervals are multiplied by the average population across the 2 years (in this case, 2012 and 2013) of the State by the age group of interest.

For example, past month use of alcohol among 18 to 25 year olds in Alabama was 50.89 percent.16 The corresponding Bayesian confidence intervals ranged from 47.07 to 54.71 percent. The population count for 18 to 25 year olds averaged across 2012 and 2013 in Alabama was 536,933 (see Table C.10 in Section C of this methodology document). Hence, the estimated number of 18 to 25 year olds using alcohol in the past month in Alabama was 0.5089 × 536,933, which is 273,245.17 The associated Bayesian confidence intervals ranged from 0.4707 × 536,933 (i.e., 252,734) to 0.5471 × 536,933 (i.e., 293,756). Note that when estimates of the number of individuals are calculated for Tables 1 to 26 in "2012-2013 NSDUHs: Model-Based Estimated Totals (in Thousands) (50 States and the District of Columbia)" (follow the link in footnote 17), the unrounded percentages and population counts are used, then the numbers are reported to the nearest thousand. Hence, the number obtained by multiplying the published estimate with the published population estimate may not exactly match the counts that are published in these tables because of rounding differences.

The only exception to this calculation is the production of the estimated numbers of marijuana initiates. Those estimates cannot be directly calculated as the product of the percentage estimate of first use of marijuana and the population counts available in Section C. That is because the denominator of that percentage estimate is defined as the number of person years at risk for marijuana initiation, which is a combination of individuals who never used marijuana and one half of the individuals who initiated in the past 24 months.

B.6 Comparison of Two 2012-2013 Small Area Estimates

This section describes a method for determining whether differences between two 2012-2013 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., 2012-2013).

Let pi 1 sub a and pi 2 sub a denote the 2012-2013 age group-a specific prevalence rates for two different States, State 1 and State 2, respectively. The null hypothesis of no difference, that is, Pi 1 sub a is equal to pi 2 sub a. , is equivalent to the log-odds ratio equal to zero, that is, Log-odds ratio lor sub a is equal to zero., where Log-odds ratio lor sub a 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 lor sub a 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 and p 2 sub a are the 2012-2013 State estimates given in the "2012-2013 NSDUH: Model-Based Prevalence Estimates (50 States and the District of Columbia) (Tables 1 to 26, by Age Group)" (follow the link in footnote 16). To compute the variance of the estimate of the log-odds ratio, lor hat sub a, that is, variance v 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 v of the natural logarithm of Theta 1 hat, quantity q2 is the variance v 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 the covariance between the natural logarithm of Theta 1 hat and the natural logarithm of Theta 2 hat denotes the covariance between the natural logarithm of Theta 1 hat and the natural logarithm of Theta 2 hat. This covariance is defined in terms of the associated correlation as follows:

Equation B.6-1.     D

The quantities variance v of the natural logarithm of Theta 1 hat and variance v of the natural logarithm of Theta 2 hat can be obtained by using the 95 percent Bayesian confidence intervals given in the "2012-2013 NSDUH: Model-Based Prevalence Estimates (50 States and the District of Columbia) (Tables 1 to 26, by Age Group)" (follow the link in footnote 16). For this purpose, let lower sub 1 and upper sub 1 and lower sub 2 and upper sub 2 denote the 95 percent Bayesian confidence intervals for the two States, State 1 and State 2, respectively. Then

Equation B.6-2     D

where Capital U sub i is the natural logarithm of upper sub i divided by 1 minus upper sub i, and capital 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 the natural logarithm of Theta 1 hat and the natural logarithm of Theta 2 hat is assumed to be negligible; hence, variance v of the estimate of the log-odds ratio, lor hat sub a can be approximated by the sum of the variance v of the natural logarithm of Theta 1 hat and the variance v 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 quantity 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 (Log-odds ratio, lor sub a, is equal to zero.), it is assumed that the posterior distribution of log-odds ratio, lor sub a is normal with Mean is equal to the estimate of the log-odds ratio, lor hat sub a. and Variance is equal to the variance v of the estimate of the log-odds ratio, lor hat sub a.. With the null value of Log-odds ratio, lor sub a, is equal to zero., the Bayes p value or posterior probability of no difference is The p value is equal to 2 times the probability of realizing a standard normal variate greater than or equal to the absolute value of a quantity z., where capital 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 v of the natural logarithm of Theta 1 hat and the variance v of the natural logarithm of Theta 2 hat., and absolute value of quantity z denotes the absolute value of quantity z.

Hence, to test whether differences between two 2012-2013 State estimates are statistically significant, the test statistic quantity z and the associated p value can be used. If p ≤ 0.05, then the two State estimates can be considered different at the 5 percent level of significance.

When comparing estimates for two States, it is tempting and often convenient to look at their 95 percent Bayesian confidence intervals to decide whether the difference in the State estimates is significant. If the two Bayesian confidence intervals overlap, one would conclude that the difference is not statistically significant. If the two Bayesian confidence intervals do not overlap, it implies that the State estimates are significantly different from each other. However, the type-I error for the overlapping 95 percent Bayesian confidence intervals 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 quantity z statistics defined above (Payton, Greenstone, & Schenker, 2003). Thus, using the overlap method with 95 percent Bayesian confidence intervals 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 Bayesian confidence intervals 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 Bayesian confidence intervals for two States overlap, the two estimates may be declared significantly different by the test based on z statistics. Hence, the method of overlapping Bayesian confidence intervals is not recommended to test the equivalence of two State estimates. A detailed description of the method of overlapping confidence intervals 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 percentages for past month alcohol use among 12 to 17 year olds in New Jersey and Oklahoma are shown in the following exhibit and also in Table 9 of the "2012-2013 NSDUH: Model-Based Prevalence Estimates (50 States and the District of Columbia)" at http://www.samhsa.gov/data/population-data-nsduh/reports?tab=33. Looking at the two 95 percent Bayesian confidence intervals, it would appear that the Oklahoma and New Jersey percentages for past month alcohol use are not statistically different at the 5 percent level of significance because the two Bayesian confidence intervals overlap:

State Point Estimate (%) 95% Bayesian Confidence Interval (%)
New Jersey 13.64 (11.44, 16.18)
Oklahoma 10.00 (8.33, 11.97)

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

Let p 1 sub a equal 0.1364, lower sub 1 equal 0.1144, upper sub 1 equal 0.1618, p 2 sub a equal 0.1000, lower sub 2 equal 0.0833, upper sub 2 equal 0.1197. Then,

Equation B.6-3,     D

Equation B.6-4,     D

Equation B.6-5,     D

Equation B.6-6,     D

Equation B.6-7,     D     and

Equation B.6-8.     D


Because the computed absolute value of quantity z is greater than or equal to 1.96 (the critical value of the quantity z statistic), then at the 5 percent level of significance, the hypothesis of no difference (Oklahoma estimate = New Jersey estimate) is rejected. Thus, the two State estimates are statistically different. The Bayes p value or posterior probability of no difference is The Bayes p value or posterior probability of no difference is calculated as 2 times the probability that capital Z is greater than or equal to the absolute value of negative 2.4229. The p value is equal to 0.0154..

Section C: Sample Sizes, Response Rates, and Population Estimates

Table C.1 Sample Sizes, Weighted Screening and Interview Response Rates, and Population Estimates, by State, for Persons Aged 12 or Older: 2011
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, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2011.
Total U.S. 216,521 179,293 156,048 86.98% 88,536 70,109 257,598,945 74.38% 64.69%
Northeast 46,446 38,803 31,569 80.08% 17,251 13,090 46,891,412 69.86% 55.94%
Midwest 58,190 48,817 42,805 88.19% 24,570 19,258 55,687,448 73.92% 65.18%
South 70,821 57,462 51,276 89.47% 28,122 22,980 95,181,797 76.88% 68.78%
West 41,064 34,211 30,398 87.20% 18,593 14,781 59,838,287 74.41% 64.88%
Alabama 4,338 3,360 3,032 89.89% 1,708 1,383 3,985,593 74.64% 67.09%
Alaska 2,459 1,911 1,700 88.87% 1,121 905 569,155 79.52% 70.67%
Arizona 2,731 2,149 1,915 89.43% 1,126 928 5,285,358 82.24% 73.55%
Arkansas 2,687 2,180 2,008 92.12% 1,160 919 2,411,125 72.47% 66.76%
California 9,464 8,223 6,869 83.58% 4,692 3,640 31,060,033 72.25% 60.39%
Colorado 3,127 2,571 2,300 88.95% 1,153 921 4,187,811 76.05% 67.64%
Connecticut 2,805 2,398 2,025 84.35% 1,200 951 3,015,283 72.47% 61.13%
Delaware 2,845 2,334 2,054 87.89% 1,109 900 756,390 76.51% 67.24%
District of Columbia 4,627 3,808 3,119 80.97% 1,067 900 534,393 83.28% 67.43%
Florida 13,954 10,951 9,602 86.92% 4,941 4,029 16,131,977 74.96% 65.16%
Georgia 2,255 1,909 1,745 91.50% 1,082 878 7,928,493 77.49% 70.91%
Hawaii 2,835 2,470 2,015 81.14% 1,260 950 1,116,660 72.08% 58.49%
Idaho 2,237 1,842 1,735 94.05% 1,124 916 1,274,823 76.97% 72.39%
Illinois 11,772 10,195 7,912 77.53% 4,929 3,655 10,652,220 68.90% 53.41%
Indiana 2,475 2,015 1,875 93.20% 1,104 896 5,365,682 73.89% 68.86%
Iowa 2,659 2,295 2,137 93.15% 1,137 933 2,537,918 78.95% 73.54%
Kansas 2,579 2,243 2,043 91.08% 1,164 915 2,323,751 75.45% 68.71%
Kentucky 2,619 2,188 2,048 93.62% 1,113 899 3,597,429 76.19% 71.33%
Louisiana 5,114 4,039 3,768 93.48% 2,126 1,746 3,719,351 77.92% 72.83%
Maine 3,568 2,517 2,313 91.74% 1,039 865 1,142,856 79.50% 72.93%
Maryland 2,587 2,290 1,842 80.47% 1,121 924 4,849,618 77.62% 62.47%
Massachusetts 3,419 2,941 2,518 85.24% 1,230 975 5,601,752 74.44% 63.45%
Michigan 11,276 9,000 7,698 85.60% 4,667 3,685 8,291,125 74.32% 63.62%
Minnesota 2,723 2,369 2,135 90.09% 1,160 940 4,434,303 79.23% 71.38%
Mississippi 3,478 2,708 2,504 92.66% 1,462 1,226 2,408,918 77.57% 71.88%
Missouri 2,501 2,073 1,925 92.84% 1,127 912 4,967,492 73.10% 67.86%
Montana 3,075 2,483 2,340 94.29% 1,194 956 835,577 76.54% 72.17%
Nebraska 2,547 2,123 1,956 91.82% 1,178 908 1,500,994 71.98% 66.10%
Nevada 2,125 1,680 1,584 95.22% 1,125 907 2,241,024 74.26% 70.71%
New Hampshire 3,003 2,402 2,099 87.19% 1,228 945 1,127,509 72.59% 63.29%
New Jersey 2,534 2,163 1,898 87.73% 1,129 894 7,385,619 71.57% 62.79%
New Mexico 2,478 1,876 1,769 94.23% 1,134 938 1,695,728 79.87% 75.26%
New York 14,528 12,454 9,093 72.46% 5,123 3,531 16,423,062 63.90% 46.31%
North Carolina 2,843 2,319 2,112 90.63% 1,103 935 7,910,951 80.92% 73.34%
North Dakota 3,321 2,629 2,476 94.18% 1,133 904 565,372 74.23% 69.91%
Ohio 11,134 9,463 8,496 89.29% 4,697 3,695 9,616,044 74.43% 66.45%
Oklahoma 2,614 2,068 1,895 91.72% 1,128 890 3,073,328 76.09% 69.79%
Oregon 2,729 2,389 2,171 90.89% 1,190 951 3,261,406 76.65% 69.66%
Pennsylvania 10,738 9,207 7,401 79.86% 4,011 3,074 10,760,673 72.87% 58.19%
Rhode Island 2,634 2,140 1,896 88.56% 1,155 930 893,903 73.56% 65.14%
South Carolina 2,978 2,441 2,205 90.33% 1,143 927 3,853,142 74.53% 67.32%
South Dakota 2,495 2,128 2,027 95.23% 1,107 913 667,896 77.20% 73.52%
Tennessee 2,590 2,149 1,914 89.19% 1,110 911 5,312,944 77.92% 69.50%
Texas 9,328 7,741 7,096 91.51% 4,478 3,636 20,486,703 75.86% 69.43%
Utah 1,797 1,590 1,505 94.62% 1,125 918 2,176,506 77.23% 73.08%
Vermont 3,217 2,581 2,326 90.14% 1,136 925 540,755 78.83% 71.06%
Virginia 2,726 2,431 2,074 85.29% 1,105 939 6,647,559 81.71% 69.69%
Washington 2,950 2,586 2,298 88.23% 1,254 959 5,668,143 72.78% 64.22%
West Virginia 3,238 2,546 2,258 87.80% 1,166 938 1,573,884 75.61% 66.39%
Wisconsin 2,708 2,284 2,125 92.73% 1,167 902 4,764,652 75.45% 69.97%
Wyoming 3,057 2,441 2,197 89.85% 1,095 892 466,065 78.14% 70.21%
Table C.2 Sample Sizes, Weighted Interview Response Rates, and Population Estimates, by State and Three Age Groups: 2011
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: Computations in this table are based on a respondent's age at screening. Thus, the data in the Total Responded column(s) could differ from data in other NSDUH tables that use the respondent's age recorded during the interview.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2011.
Total U.S. 27,911 23,549 24,973,646 84.95% 28,589 23,083 34,301,730 80.48% 32,036 23,477 198,323,568 71.96%
Northeast 5,443 4,425 4,277,870 82.07% 5,465 4,270 6,120,583 77.18% 6,343 4,395 36,492,959 67.15%
Midwest 7,649 6,388 5,445,784 83.26% 7,982 6,373 7,340,274 80.46% 8,939 6,497 42,901,391 71.62%
South 9,087 7,870 9,256,114 87.02% 9,028 7,542 12,610,321 83.06% 10,007 7,568 73,315,362 74.47%
West 5,732 4,866 5,993,878 85.37% 6,114 4,898 8,230,553 78.93% 6,747 5,017 45,613,857 72.13%
Alabama 529 452 385,875 85.66% 577 486 536,911 83.41% 602 445 3,062,807 71.72%
Alaska 392 333 60,921 85.33% 368 284 79,374 77.63% 361 288 428,860 79.00%
Arizona 363 308 535,373 86.03% 375 308 705,171 83.29% 388 312 4,044,814 81.51%
Arkansas 351 296 234,612 84.34% 431 352 316,930 81.16% 378 271 1,859,582 69.15%
California 1,403 1,181 3,173,750 84.94% 1,562 1,230 4,401,989 78.04% 1,727 1,229 23,484,294 69.41%
Colorado 376 326 395,811 84.87% 361 290 552,881 80.31% 416 305 3,239,119 74.43%
Connecticut 361 309 292,050 86.67% 389 320 366,697 83.62% 450 322 2,356,536 68.68%
Delaware 347 292 69,137 84.31% 349 295 100,448 82.88% 413 313 586,805 74.47%
District of Columbia 343 304 31,407 88.80% 408 339 97,511 82.66% 316 257 405,475 83.00%
Florida 1,649 1,440 1,380,074 87.03% 1,466 1,222 1,947,535 82.91% 1,826 1,367 12,804,369 72.50%
Georgia 360 312 821,078 87.30% 309 254 1,073,944 81.77% 413 312 6,033,471 75.45%
Hawaii 395 303 98,668 74.86% 412 329 135,970 82.72% 453 318 882,022 70.07%
Idaho 382 331 138,364 87.43% 326 269 173,071 83.08% 416 316 963,388 74.47%
Illinois 1,547 1,254 1,063,049 81.28% 1,630 1,207 1,394,519 73.93% 1,752 1,194 8,194,652 66.32%
Indiana 336 292 540,048 86.96% 374 315 728,277 84.58% 394 289 4,097,357 70.25%
Iowa 395 332 241,080 85.04% 320 273 344,974 84.99% 422 328 1,951,863 77.28%
Kansas 338 279 235,652 82.61% 394 321 320,124 82.19% 432 315 1,767,975 73.31%
Kentucky 359 297 339,927 83.56% 355 300 457,966 84.54% 399 302 2,799,536 73.80%
Louisiana 671 588 367,017 88.27% 666 567 525,065 87.75% 789 591 2,827,268 74.55%
Maine 350 300 97,195 85.41% 348 296 129,785 84.83% 341 269 915,876 77.99%
Maryland 370 324 460,905 87.15% 368 303 624,724 82.56% 383 297 3,763,989 75.67%
Massachusetts 461 384 495,429 83.49% 410 330 765,174 79.20% 359 261 4,341,149 72.35%
Michigan 1,420 1,195 819,033 84.29% 1,569 1,261 1,094,805 80.72% 1,678 1,229 6,377,287 71.97%
Minnesota 370 315 425,134 85.39% 339 274 570,169 81.72% 451 351 3,439,001 78.13%
Mississippi 452 410 248,626 91.19% 453 390 335,084 85.87% 557 426 1,825,208 74.15%
Missouri 338 293 476,256 82.39% 359 304 654,304 84.44% 430 315 3,836,932 70.24%
Montana 352 299 74,309 83.99% 396 326 106,543 82.17% 446 331 654,725 74.87%
Nebraska 342 298 146,677 87.64% 418 315 205,271 76.00% 418 295 1,149,047 69.10%
Nevada 239 204 218,674 89.40% 446 381 280,630 88.39% 440 322 1,741,720 70.36%
New Hampshire 407 324 103,573 79.53% 404 327 138,419 81.88% 417 294 885,517 70.19%
New Jersey 350 301 712,565 87.81% 360 295 870,975 84.31% 419 298 5,802,078 67.72%
New Mexico 319 280 169,846 87.11% 393 326 226,296 80.21% 422 332 1,299,586 78.88%
New York 1,537 1,180 1,482,881 76.97% 1,702 1,176 2,238,168 68.70% 1,884 1,175 12,702,014 61.53%
North Carolina 379 339 754,179 89.13% 339 282 1,016,089 81.19% 385 314 6,140,683 79.89%
North Dakota 334 291 48,835 87.85% 398 325 89,850 81.27% 401 288 426,688 71.23%
Ohio 1,491 1,220 932,467 81.91% 1,462 1,184 1,228,851 80.53% 1,744 1,291 7,454,725 72.47%
Oklahoma 322 264 302,691 82.91% 389 311 421,806 81.30% 417 315 2,348,831 74.21%
Oregon 414 355 291,549 86.35% 373 286 409,460 76.97% 403 310 2,560,397 75.46%
Pennsylvania 1,252 1,023 969,456 83.05% 1,105 889 1,406,406 81.30% 1,654 1,162 8,384,811 70.33%
Rhode Island 356 301 78,432 84.88% 372 324 132,407 87.65% 427 305 683,065 69.48%
South Carolina 348 302 356,131 86.42% 392 331 511,928 84.82% 403 294 2,985,082 71.06%
South Dakota 363 317 64,382 86.27% 340 295 90,856 85.84% 404 301 512,659 74.58%
Tennessee 336 293 503,104 88.26% 358 297 679,027 82.54% 416 321 4,130,814 75.89%
Texas 1,516 1,314 2,251,878 87.02% 1,426 1,180 2,896,598 82.35% 1,536 1,142 15,338,228 72.77%
Utah 350 317 264,830 90.99% 350 278 362,847 77.60% 425 323 1,548,828 74.74%
Vermont 369 303 46,290 83.39% 375 313 72,552 84.62% 392 309 421,913 77.36%
Virginia 378 332 618,074 87.87% 354 307 879,583 85.65% 373 300 5,149,902 80.14%
Washington 367 309 529,144 83.87% 447 339 733,670 74.35% 440 311 4,405,329 71.11%
West Virginia 377 311 131,399 82.69% 388 326 189,172 84.72% 401 301 1,253,313 73.59%
Wisconsin 375 302 453,172 80.52% 379 299 618,275 81.47% 413 301 3,693,206 73.70%
Wyoming 380 320 42,640 84.62% 305 252 62,649 83.42% 410 320 360,775 76.42%
Table C.3 Sample Sizes, Weighted Screening and Interview Response Rates, and Population Estimates, by State, for Persons Aged 12 or Older: 2012
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, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2012.
Total U.S. 214,274 178,586 153,873 86.07% 87,656 68,309 260,057,325 73.04% 62.87%
Northeast 47,763 40,410 32,868 79.93% 18,301 13,773 47,174,958 69.59% 55.62%
Midwest 58,534 49,381 43,010 87.61% 24,499 19,142 55,924,697 74.27% 65.06%
South 66,141 54,110 47,494 88.15% 26,279 20,886 96,373,144 74.22% 65.42%
West 41,836 34,685 30,501 86.04% 18,577 14,508 60,584,526 72.75% 62.59%
Alabama 3,012 2,372 2,141 90.30% 1,145 901 4,005,432 74.57% 67.34%
Alaska 2,424 1,869 1,642 87.82% 1,076 829 577,147 73.34% 64.40%
Arizona 2,771 2,143 1,928 90.16% 1,139 922 5,362,657 77.11% 69.52%
Arkansas 2,776 2,292 2,090 90.92% 1,212 913 2,422,926 69.77% 63.43%
California 9,489 8,314 6,852 82.37% 4,779 3,608 31,424,054 70.20% 57.82%
Colorado 3,071 2,579 2,201 85.23% 1,188 927 4,260,412 74.95% 63.88%
Connecticut 2,855 2,535 2,107 82.76% 1,261 964 3,034,241 72.36% 59.88%
Delaware 2,847 2,292 2,008 87.57% 1,110 893 765,733 79.90% 69.97%
District of Columbia 5,055 4,104 3,327 80.90% 1,125 962 544,627 80.64% 65.24%
Florida 12,768 10,055 8,516 84.67% 4,579 3,544 16,382,543 70.57% 59.75%
Georgia 2,365 2,042 1,796 87.94% 1,144 885 8,040,955 73.07% 64.26%
Hawaii 3,212 2,761 2,239 80.80% 1,285 938 1,130,820 68.98% 55.73%
Idaho 2,300 1,939 1,821 93.92% 1,136 921 1,288,271 78.38% 73.61%
Illinois 11,385 9,964 7,678 77.04% 4,871 3,672 10,680,769 70.95% 54.66%
Indiana 2,491 2,110 1,921 91.01% 1,171 911 5,391,372 72.95% 66.39%
Iowa 2,529 2,199 2,022 91.72% 1,137 900 2,550,660 74.74% 68.55%
Kansas 2,598 2,198 1,977 89.98% 1,109 912 2,336,047 77.88% 70.07%
Kentucky 2,852 2,407 2,202 91.46% 1,184 927 3,607,428 73.49% 67.21%
Louisiana 2,741 2,143 1,977 92.28% 1,100 901 3,745,460 77.61% 71.63%
Maine 3,866 2,858 2,585 90.56% 1,134 938 1,145,565 79.20% 71.72%
Maryland 2,680 2,308 1,802 78.13% 1,074 874 4,905,827 75.90% 59.30%
Massachusetts 3,064 2,653 2,208 83.22% 1,253 955 5,661,530 71.52% 59.52%
Michigan 11,441 9,207 7,826 85.05% 4,606 3,655 8,319,227 75.75% 64.43%
Minnesota 2,483 2,160 1,975 91.57% 1,092 902 4,470,679 81.16% 74.32%
Mississippi 2,553 2,087 1,951 93.50% 1,100 901 2,419,811 78.58% 73.48%
Missouri 2,879 2,409 2,188 90.88% 1,149 915 4,985,565 74.36% 67.58%
Montana 3,295 2,610 2,415 92.62% 1,109 876 842,009 77.46% 71.74%
Nebraska 2,556 2,175 2,018 92.74% 1,170 940 1,511,302 73.14% 67.83%
Nevada 2,354 1,879 1,721 91.75% 1,134 903 2,278,656 75.62% 69.38%
New Hampshire 2,990 2,507 2,191 87.40% 1,259 950 1,133,661 73.08% 63.87%
New Jersey 2,622 2,227 1,935 86.87% 1,155 898 7,440,994 73.64% 63.97%
New Mexico 2,771 2,052 1,889 92.22% 1,101 879 1,702,667 74.17% 68.39%
New York 14,547 12,547 9,115 71.89% 5,267 3,680 16,532,006 64.38% 46.28%
North Carolina 2,848 2,246 1,990 88.48% 1,117 917 8,007,328 75.46% 66.77%
North Dakota 3,374 2,633 2,461 93.42% 1,156 895 577,526 73.47% 68.64%
Ohio 11,722 10,122 9,023 89.14% 4,827 3,687 9,638,652 72.73% 64.84%
Oklahoma 2,960 2,382 2,173 91.22% 1,189 908 3,099,247 72.38% 66.03%
Oregon 2,547 2,250 2,019 89.57% 1,165 923 3,293,097 76.48% 68.51%
Pennsylvania 11,907 10,256 8,453 82.09% 4,705 3,580 10,790,033 70.67% 58.02%
Rhode Island 2,620 2,190 1,957 89.37% 1,131 923 895,345 77.76% 69.50%
South Carolina 3,306 2,666 2,374 88.97% 1,171 938 3,900,041 75.13% 66.85%
South Dakota 2,636 2,163 2,031 93.92% 1,113 878 676,283 76.12% 71.49%
Tennessee 2,532 2,095 1,929 91.91% 1,105 927 5,363,074 81.06% 74.50%
Texas 9,048 7,651 6,792 88.52% 4,612 3,625 20,852,844 73.36% 64.94%
Utah 1,793 1,558 1,474 94.67% 1,099 926 2,214,352 83.26% 78.83%
Vermont 3,292 2,637 2,317 87.81% 1,136 885 541,583 73.81% 64.82%
Virginia 2,576 2,293 2,027 88.47% 1,095 894 6,735,698 76.50% 67.68%
Washington 2,700 2,306 2,078 90.10% 1,218 928 5,736,136 71.82% 64.71%
West Virginia 3,222 2,675 2,399 89.39% 1,217 976 1,574,171 74.07% 66.21%
Wisconsin 2,440 2,041 1,890 92.37% 1,098 875 4,786,617 75.55% 69.79%
Wyoming 3,109 2,425 2,222 91.72% 1,148 928 474,248 77.48% 71.07%
Table C.4 Sample Sizes, Weighted Interview Response Rates, and Population Estimates, by State and Three Age Groups: 2012
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: Computations in this table are based on a respondent's age at screening. Thus, the data in the Total Responded column(s) could differ from data in other NSDUH tables that use the respondent's age recorded during the interview.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2012.
Total U.S. 27,147 22,492 24,933,051 82.84% 28,639 22,762 34,589,953 79.26% 31,870 23,055 200,534,321 70.76%
Northeast 5,513 4,421 4,237,419 79.81% 6,114 4,720 6,153,492 76.54% 6,674 4,632 36,784,047 67.26%
Midwest 7,733 6,399 5,416,148 83.34% 7,891 6,270 7,361,823 79.64% 8,875 6,473 43,146,726 72.22%
South 8,292 6,973 9,305,299 83.52% 8,583 7,012 12,758,779 81.70% 9,404 6,901 74,309,066 71.75%
West 5,609 4,699 5,974,186 83.44% 6,051 4,760 8,315,859 77.22% 6,917 5,049 46,294,482 70.61%
Alabama 342 278 384,244 80.41% 383 312 536,932 80.90% 420 311 3,084,257 72.65%
Alaska 304 233 60,308 76.07% 348 286 81,619 82.25% 424 310 435,220 71.44%
Arizona 366 312 539,163 85.61% 371 293 713,584 74.97% 402 317 4,109,911 76.39%
Arkansas 394 312 236,048 78.13% 404 310 317,735 75.45% 414 291 1,869,143 67.71%
California 1,409 1,159 3,139,169 81.82% 1,584 1,216 4,452,711 76.51% 1,786 1,233 23,832,173 67.51%
Colorado 376 319 399,087 86.13% 390 301 560,123 78.11% 422 307 3,301,202 73.13%
Connecticut 361 288 289,862 79.74% 426 339 373,279 80.56% 474 337 2,371,100 70.39%
Delaware 376 307 68,973 82.59% 305 246 102,090 83.85% 429 340 594,670 79.02%
District of Columbia 362 329 31,338 91.77% 398 344 95,556 87.06% 365 289 417,734 78.39%
Florida 1,419 1,193 1,383,312 83.48% 1,535 1,222 1,970,724 79.16% 1,625 1,129 13,028,506 67.81%
Georgia 344 287 828,383 81.72% 360 284 1,096,583 79.58% 440 314 6,115,989 70.82%
Hawaii 377 284 96,933 75.93% 382 308 140,267 80.83% 526 346 893,621 66.50%
Idaho 389 345 139,664 88.85% 334 262 173,325 80.12% 413 314 975,282 76.28%
Illinois 1,517 1,234 1,051,880 81.95% 1,562 1,190 1,393,334 76.45% 1,792 1,248 8,235,555 68.62%
Indiana 330 271 540,535 82.24% 408 328 731,531 80.64% 433 312 4,119,306 70.63%
Iowa 373 314 241,376 82.15% 362 287 347,524 79.41% 402 299 1,961,760 72.90%
Kansas 388 343 236,447 88.15% 318 265 322,233 84.49% 403 304 1,777,368 75.30%
Kentucky 384 318 339,442 81.85% 380 302 461,441 80.21% 420 307 2,806,546 71.39%
Louisiana 330 292 367,661 88.75% 364 303 523,034 82.65% 406 306 2,854,766 75.23%
Maine 359 305 95,666 85.30% 387 325 129,416 84.13% 388 308 920,484 77.79%
Maryland 330 282 458,368 85.48% 363 306 631,975 83.31% 381 286 3,815,483 73.39%
Massachusetts 380 309 493,395 81.19% 408 312 772,360 77.20% 465 334 4,395,776 69.50%
Michigan 1,445 1,178 809,401 81.72% 1,508 1,231 1,101,787 81.78% 1,653 1,246 6,408,038 73.97%
Minnesota 363 324 424,357 89.54% 339 272 571,203 79.91% 390 306 3,475,119 80.32%
Mississippi 384 313 248,208 80.62% 338 297 336,270 88.22% 378 291 1,835,332 76.36%
Missouri 367 312 474,059 85.89% 356 290 654,819 82.34% 426 313 3,856,687 71.53%
Montana 388 316 73,775 81.81% 350 279 107,843 78.48% 371 281 660,391 76.71%
Nebraska 322 278 147,378 86.79% 433 365 205,771 84.84% 415 297 1,158,152 69.50%
Nevada 333 290 220,899 86.58% 368 289 284,532 79.10% 433 324 1,773,226 73.75%
New Hampshire 405 305 102,103 75.51% 417 324 139,482 78.95% 437 321 892,076 71.84%
New Jersey 349 291 708,659 83.09% 378 292 881,583 78.25% 428 315 5,850,752 71.73%
New Mexico 332 290 168,839 87.22% 369 303 226,708 81.39% 400 286 1,307,120 71.17%
New York 1,564 1,193 1,466,519 75.84% 1,778 1,266 2,246,785 71.75% 1,925 1,221 12,818,701 61.76%
North Carolina 354 298 760,601 83.53% 382 337 1,033,454 87.89% 381 282 6,213,274 72.36%
North Dakota 371 309 48,912 83.61% 339 268 93,645 79.86% 446 318 434,970 70.99%
Ohio 1,628 1,297 926,791 79.72% 1,475 1,148 1,232,694 77.78% 1,724 1,242 7,479,167 71.02%
Oklahoma 385 303 305,458 78.05% 383 297 424,952 76.87% 421 308 2,368,838 70.82%
Oregon 311 270 292,395 87.03% 407 318 409,756 79.10% 447 335 2,590,946 75.05%
Pennsylvania 1,425 1,169 958,552 82.15% 1,536 1,218 1,404,841 79.74% 1,744 1,193 8,426,641 67.91%
Rhode Island 320 276 77,245 86.40% 391 329 132,691 84.47% 420 318 685,409 75.55%
South Carolina 385 317 358,471 81.59% 349 295 515,765 84.67% 437 326 3,025,806 72.71%
South Dakota 316 265 64,543 84.11% 371 300 91,525 82.83% 426 313 520,215 74.13%
Tennessee 299 261 505,108 85.96% 419 352 688,253 83.32% 387 314 4,169,713 80.11%
Texas 1,472 1,246 2,279,511 84.37% 1,471 1,183 2,943,283 80.38% 1,669 1,196 15,630,050 70.45%
Utah 319 287 272,004 90.49% 384 310 363,798 81.78% 396 329 1,578,549 82.34%
Vermont 350 285 45,420 80.52% 393 315 73,055 80.92% 393 285 423,108 71.93%
Virginia 373 322 619,042 85.05% 316 270 891,542 85.19% 406 302 5,225,114 73.95%
Washington 368 301 528,812 81.58% 406 310 737,911 75.50% 444 317 4,469,414 70.24%
West Virginia 359 315 131,131 87.64% 433 352 189,192 81.40% 425 309 1,253,848 71.61%
Wisconsin 313 274 450,470 86.72% 420 326 615,758 77.80% 365 275 3,720,389 73.85%
Wyoming 337 293 43,140 85.79% 358 285 63,681 78.58% 453 350 367,427 76.36%
Table C.5 Sample Sizes, Weighted Screening and Interview Response Rates, and Population Estimates, by State, for Persons Aged 12 or Older: 2013
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, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2013.
Total U.S. 227,075 190,067 160,325 83.93% 88,742 67,838 262,391,455 71.69% 60.18%
Northeast 51,312 43,608 34,787 78.54% 18,334 13,661 47,388,235 68.75% 54.00%
Midwest 61,705 51,906 44,380 85.68% 24,842 18,822 56,214,652 71.54% 61.30%
South 69,936 57,463 49,288 85.67% 26,758 20,782 97,513,014 73.32% 62.81%
West 44,122 37,090 31,870 83.74% 18,808 14,573 61,275,553 71.48% 59.86%
Alabama 3,110 2,522 2,141 84.04% 1,156 900 4,025,044 69.26% 58.21%
Alaska 3,177 2,347 2,044 87.05% 1,122 863 577,309 74.91% 65.21%
Arizona 3,013 2,324 1,991 85.43% 1,170 882 5,443,545 69.25% 59.16%
Arkansas 2,721 2,189 1,984 90.66% 1,193 908 2,435,182 73.21% 66.38%
California 9,994 8,965 7,211 80.33% 4,864 3,729 31,739,919 70.45% 56.60%
Colorado 2,790 2,436 2,016 82.93% 1,173 885 4,339,337 71.19% 59.04%
Connecticut 2,989 2,691 2,294 85.25% 1,198 893 3,045,630 70.24% 59.88%
Delaware 3,042 2,485 2,073 83.64% 1,113 862 774,640 72.21% 60.40%
District of Columbia 5,466 4,554 3,700 80.83% 1,142 907 555,335 75.40% 60.95%
Florida 14,174 11,056 9,176 81.41% 4,792 3,649 16,599,656 71.63% 58.31%
Georgia 2,660 2,218 1,836 82.63% 1,093 852 8,133,541 73.03% 60.34%
Hawaii 3,294 2,861 2,235 77.45% 1,240 924 1,135,919 66.79% 51.73%
Idaho 2,388 2,020 1,863 92.19% 1,163 907 1,305,833 75.66% 69.75%
Illinois 11,767 10,379 7,912 76.19% 4,935 3,503 10,713,667 65.98% 50.27%
Indiana 2,992 2,513 2,182 86.71% 1,165 894 5,430,975 71.51% 62.00%
Iowa 2,700 2,318 2,120 91.46% 1,164 900 2,566,989 71.34% 65.25%
Kansas 2,608 2,191 1,944 88.60% 1,165 887 2,344,171 73.15% 64.81%
Kentucky 3,085 2,556 2,341 91.53% 1,160 904 3,633,237 73.51% 67.28%
Louisiana 2,877 2,321 2,096 90.32% 1,160 903 3,774,189 73.28% 66.19%
Maine 3,624 2,708 2,444 90.02% 1,125 926 1,147,984 78.25% 70.44%
Maryland 2,759 2,430 1,919 79.18% 1,183 925 4,947,041 76.85% 60.85%
Massachusetts 3,007 2,692 2,189 80.96% 1,240 897 5,711,595 69.49% 56.26%
Michigan 12,080 9,938 8,310 83.39% 4,716 3,636 8,346,148 72.79% 60.70%
Minnesota 2,595 2,272 2,056 90.74% 1,126 906 4,509,704 77.38% 70.21%
Mississippi 2,441 2,019 1,829 90.55% 1,088 918 2,428,802 79.27% 71.77%
Missouri 3,144 2,586 2,330 89.93% 1,183 917 5,009,791 73.20% 65.83%
Montana 2,991 2,429 2,251 92.54% 1,177 910 850,469 74.42% 68.87%
Nebraska 3,052 2,500 2,279 91.03% 1,146 910 1,524,399 74.27% 67.61%
Nevada 2,753 2,285 2,004 87.68% 1,137 932 2,312,257 74.64% 65.44%
New Hampshire 3,488 2,919 2,498 85.43% 1,243 953 1,137,904 76.03% 64.95%
New Jersey 3,164 2,774 2,281 82.31% 1,238 913 7,476,944 68.88% 56.70%
New Mexico 2,868 2,254 2,038 90.20% 1,168 922 1,707,564 73.84% 66.60%
New York 15,157 12,992 9,243 71.27% 5,248 3,637 16,619,482 63.66% 45.36%
North Carolina 2,872 2,382 2,090 87.63% 1,103 880 8,114,142 75.94% 66.55%
North Dakota 3,634 2,767 2,562 92.58% 1,257 945 593,987 68.81% 63.71%
Ohio 11,540 9,824 8,450 85.92% 4,734 3,568 9,677,958 71.01% 61.01%
Oklahoma 2,830 2,326 2,100 90.39% 1,250 950 3,130,656 68.89% 62.27%
Oregon 2,770 2,458 2,153 87.44% 1,093 861 3,327,918 76.84% 67.19%
Pennsylvania 13,292 11,490 9,213 80.00% 4,760 3,663 10,808,879 73.13% 58.50%
Rhode Island 2,969 2,515 2,205 87.59% 1,167 904 897,301 71.97% 63.04%
South Carolina 3,291 2,763 2,308 83.36% 1,134 908 3,952,463 76.40% 63.69%
South Dakota 2,728 2,204 2,059 93.35% 1,106 889 685,112 76.78% 71.68%
Tennessee 2,967 2,431 2,152 88.53% 1,121 894 5,407,982 73.11% 64.72%
Texas 9,323 7,887 6,873 87.12% 4,743 3,604 21,223,105 72.07% 62.79%
Utah 2,032 1,771 1,678 95.05% 1,150 930 2,258,561 75.09% 71.37%
Vermont 3,622 2,827 2,420 85.51% 1,115 875 542,516 76.92% 65.78%
Virginia 2,792 2,413 2,072 85.14% 1,148 902 6,803,508 76.51% 65.15%
Washington 2,598 2,235 1,937 86.55% 1,175 900 5,797,644 71.56% 61.93%
West Virginia 3,526 2,911 2,598 89.32% 1,179 916 1,574,493 76.28% 68.13%
Wisconsin 2,865 2,414 2,176 90.41% 1,145 867 4,811,751 73.66% 66.60%
Wyoming 3,454 2,705 2,449 90.40% 1,176 928 479,279 78.69% 71.14%
Table C.6 Sample Sizes, Weighted Interview Response Rates, and Population Estimates, by State and Three Age Groups: 2013
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: Computations in this table are based on a respondent's age at screening. Thus, the data in the Total Responded column(s) could differ from data in other NSDUH tables that use the respondent's age recorded during the interview.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2013.
Total U.S. 27,630 22,532 24,892,618 81.95% 28,921 22,458 34,785,501 77.34% 32,191 22,848 202,713,336 69.45%
Northeast 5,700 4,561 4,187,318 79.38% 5,915 4,465 6,149,025 74.20% 6,719 4,635 37,051,892 66.60%
Midwest 7,730 6,220 5,398,028 80.27% 8,236 6,328 7,406,554 76.24% 8,876 6,274 43,410,071 69.65%
South 8,368 6,904 9,356,405 82.51% 8,566 6,762 12,857,518 78.55% 9,824 7,116 75,299,092 71.29%
West 5,832 4,847 5,950,868 84.38% 6,204 4,903 8,372,403 78.74% 6,772 4,823 46,952,282 68.53%
Alabama 381 322 382,694 82.54% 377 304 536,933 78.79% 398 274 3,105,417 66.03%
Alaska 364 276 60,220 76.37% 380 301 83,264 77.91% 378 286 433,826 74.16%
Arizona 396 323 541,841 81.38% 385 293 727,937 76.31% 389 266 4,173,767 66.25%
Arkansas 327 255 236,968 78.23% 454 350 319,725 76.45% 412 303 1,878,489 72.01%
California 1,490 1,263 3,095,715 85.24% 1,571 1,236 4,464,898 78.73% 1,803 1,230 24,179,306 66.97%
Colorado 322 259 405,187 80.90% 399 304 570,429 75.38% 452 322 3,363,721 69.41%
Connecticut 391 316 287,546 82.74% 351 271 378,789 78.01% 456 306 2,379,294 67.41%
Delaware 334 281 67,694 82.04% 396 309 102,069 78.44% 383 272 604,877 70.04%
District of Columbia 374 327 30,375 88.49% 304 237 93,799 80.28% 464 343 431,161 73.41%
Florida 1,407 1,156 1,387,520 82.81% 1,513 1,184 1,973,936 77.89% 1,872 1,309 13,238,200 69.64%
Georgia 358 291 834,836 82.28% 384 306 1,103,523 79.41% 351 255 6,195,182 70.39%
Hawaii 368 306 97,238 81.23% 417 321 140,183 75.08% 455 297 898,498 64.16%
Idaho 337 280 142,022 84.51% 429 341 172,682 82.06% 397 286 991,129 73.13%
Illinois 1,460 1,145 1,039,658 79.14% 1,661 1,201 1,395,665 71.65% 1,814 1,157 8,278,344 63.39%
Indiana 366 292 541,496 78.05% 365 288 738,003 77.25% 434 314 4,151,475 69.66%
Iowa 357 287 242,247 79.14% 395 315 350,483 80.07% 412 298 1,974,259 68.83%
Kansas 369 296 237,924 80.42% 386 295 324,627 77.64% 410 296 1,781,619 71.39%
Kentucky 366 300 340,478 82.34% 365 296 468,033 81.37% 429 308 2,824,726 71.05%
Louisiana 370 297 367,993 78.65% 340 276 520,801 79.72% 450 330 2,885,395 71.59%
Maine 390 328 94,311 82.76% 361 306 127,972 84.65% 374 292 925,702 76.97%
Maryland 375 302 455,935 81.11% 389 306 630,762 76.22% 419 317 3,860,344 76.45%
Massachusetts 370 285 489,152 76.58% 427 311 777,767 73.11% 443 301 4,444,677 68.04%
Michigan 1,488 1,194 802,126 80.07% 1,550 1,220 1,112,833 78.07% 1,678 1,222 6,431,190 70.93%
Minnesota 335 287 424,921 87.36% 391 307 571,675 76.12% 400 312 3,513,108 76.46%
Mississippi 377 337 246,305 88.95% 328 287 338,137 87.14% 383 294 1,844,359 76.42%
Missouri 358 302 471,719 82.66% 381 292 655,369 76.22% 444 323 3,882,703 71.61%
Montana 394 314 74,018 79.63% 397 309 110,155 77.44% 386 287 666,296 73.30%
Nebraska 390 321 148,681 80.79% 371 309 208,331 82.84% 385 280 1,167,387 71.59%
Nevada 355 310 221,435 88.57% 351 314 286,394 87.34% 431 308 1,804,427 70.98%
New Hampshire 393 304 100,312 76.63% 414 319 140,525 77.94% 436 330 897,067 75.64%
New Jersey 380 293 703,594 78.88% 404 313 887,966 77.36% 454 307 5,885,384 66.32%
New Mexico 340 297 167,385 87.52% 378 297 229,365 77.50% 450 328 1,310,813 71.52%
New York 1,685 1,303 1,446,714 77.33% 1,649 1,136 2,239,850 68.87% 1,914 1,198 12,932,918 61.18%
North Carolina 310 266 768,619 87.00% 368 290 1,050,264 77.57% 425 324 6,295,258 74.28%
North Dakota 368 297 50,250 78.97% 402 315 99,046 78.91% 487 333 444,691 65.58%
Ohio 1,542 1,220 924,863 78.72% 1,525 1,173 1,238,671 78.36% 1,667 1,175 7,514,424 68.82%
Oklahoma 423 346 308,182 82.96% 412 319 428,032 77.07% 415 285 2,394,443 65.70%
Oregon 321 263 291,705 80.87% 361 289 413,732 79.98% 411 309 2,622,480 75.89%
Pennsylvania 1,383 1,146 945,209 82.78% 1,575 1,220 1,391,012 77.81% 1,802 1,297 8,472,657 71.23%
Rhode Island 372 312 75,840 84.51% 360 289 131,461 79.12% 435 303 690,001 69.39%
South Carolina 392 319 360,578 80.86% 345 285 522,722 82.89% 397 304 3,069,164 74.75%
South Dakota 359 304 65,259 84.23% 361 286 93,194 78.68% 386 299 526,659 75.61%
Tennessee 371 317 505,527 85.19% 359 292 697,396 81.65% 391 285 4,205,059 70.31%
Texas 1,404 1,139 2,311,623 80.63% 1,588 1,219 2,985,606 76.39% 1,751 1,246 15,925,876 70.06%
Utah 371 318 279,317 86.38% 419 340 370,856 81.41% 360 272 1,608,388 71.37%
Vermont 336 274 44,641 81.36% 374 300 73,683 80.65% 405 301 424,193 75.81%
Virginia 394 331 620,869 85.27% 322 247 895,156 79.29% 432 324 5,287,483 74.84%
Washington 353 297 530,892 85.62% 365 289 738,379 78.95% 457 314 4,528,373 68.85%
West Virginia 405 318 130,210 78.65% 322 255 190,624 79.31% 452 343 1,253,658 75.55%
Wisconsin 338 275 448,884 80.11% 448 327 618,657 71.94% 359 265 3,744,210 73.13%
Wyoming 421 341 43,892 80.89% 352 269 64,129 78.38% 403 318 371,258 78.50%
Table C.7 Sample Sizes, Weighted Screening and Interview Response Rates, and Population Estimates, by State, for Persons Aged 12 or Older: 2011 and 2012
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 2011-2012 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 2011 and 2012 individual response rates. The 2011-2012 population estimate is the average of the 2011 and the 2012 population.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2011 and 2012.
Total U.S. 430,795 357,879 309,921 86.53% 176,192 138,418 258,828,135 73.70% 63.77%
Northeast 94,209 79,213 64,437 80.01% 35,552 26,863 47,033,185 69.72% 55.78%
Midwest 116,724 98,198 85,815 87.90% 49,069 38,400 55,806,073 74.09% 65.12%
South 136,962 111,572 98,770 88.81% 54,401 43,866 95,777,470 75.54% 67.08%
West 82,900 68,896 60,899 86.64% 37,170 29,289 60,211,407 73.56% 63.73%
Alabama 7,350 5,732 5,173 90.09% 2,853 2,284 3,995,513 74.60% 67.21%
Alaska 4,883 3,780 3,342 88.34% 2,197 1,734 573,151 76.26% 67.37%
Arizona 5,502 4,292 3,843 89.78% 2,265 1,850 5,324,007 79.55% 71.42%
Arkansas 5,463 4,472 4,098 91.51% 2,372 1,832 2,417,026 71.09% 65.05%
California 18,953 16,537 13,721 82.98% 9,471 7,248 31,242,043 71.20% 59.09%
Colorado 6,198 5,150 4,501 87.22% 2,341 1,848 4,224,111 75.50% 65.85%
Connecticut 5,660 4,933 4,132 83.54% 2,461 1,915 3,024,762 72.41% 60.49%
Delaware 5,692 4,626 4,062 87.74% 2,219 1,793 761,061 78.28% 68.68%
District of Columbia 9,682 7,912 6,446 80.94% 2,192 1,862 539,510 81.91% 66.29%
Florida 26,722 21,006 18,118 85.78% 9,520 7,573 16,257,260 72.77% 62.42%
Georgia 4,620 3,951 3,541 89.79% 2,226 1,763 7,984,724 75.23% 67.55%
Hawaii 6,047 5,231 4,254 80.97% 2,545 1,888 1,123,740 70.47% 57.06%
Idaho 4,537 3,781 3,556 93.99% 2,260 1,837 1,281,547 77.64% 72.97%
Illinois 23,157 20,159 15,590 77.28% 9,800 7,327 10,666,494 69.94% 54.05%
Indiana 4,966 4,125 3,796 92.12% 2,275 1,807 5,378,527 73.40% 67.61%
Iowa 5,188 4,494 4,159 92.40% 2,274 1,833 2,544,289 76.95% 71.10%
Kansas 5,177 4,441 4,020 90.55% 2,273 1,827 2,329,899 76.66% 69.41%
Kentucky 5,471 4,595 4,250 92.49% 2,297 1,826 3,602,428 74.81% 69.19%
Louisiana 7,855 6,182 5,745 92.89% 3,226 2,647 3,732,406 77.76% 72.23%
Maine 7,434 5,375 4,898 91.15% 2,173 1,803 1,144,211 79.35% 72.33%
Maryland 5,267 4,598 3,644 79.32% 2,195 1,798 4,877,722 76.79% 60.91%
Massachusetts 6,483 5,594 4,726 84.24% 2,483 1,930 5,631,641 72.92% 61.43%
Michigan 22,717 18,207 15,524 85.33% 9,273 7,340 8,305,176 75.03% 64.02%
Minnesota 5,206 4,529 4,110 90.85% 2,252 1,842 4,452,491 80.17% 72.84%
Mississippi 6,031 4,795 4,455 93.10% 2,562 2,127 2,414,364 78.07% 72.68%
Missouri 5,380 4,482 4,113 91.84% 2,276 1,827 4,976,528 73.71% 67.69%
Montana 6,370 5,093 4,755 93.46% 2,303 1,832 838,793 76.96% 71.93%
Nebraska 5,103 4,298 3,974 92.27% 2,348 1,848 1,506,148 72.57% 66.96%
Nevada 4,479 3,559 3,305 94.07% 2,259 1,810 2,259,840 74.94% 70.50%
New Hampshire 5,993 4,909 4,290 87.29% 2,487 1,895 1,130,585 72.84% 63.58%
New Jersey 5,156 4,390 3,833 87.30% 2,284 1,792 7,413,306 72.59% 63.37%
New Mexico 5,249 3,928 3,658 93.26% 2,235 1,817 1,699,198 77.04% 71.84%
New York 29,075 25,001 18,208 72.18% 10,390 7,211 16,477,534 64.14% 46.29%
North Carolina 5,691 4,565 4,102 89.63% 2,220 1,852 7,959,139 78.20% 70.09%
North Dakota 6,695 5,262 4,937 93.80% 2,289 1,799 571,449 73.84% 69.26%
Ohio 22,856 19,585 17,519 89.22% 9,524 7,382 9,627,348 73.58% 65.65%
Oklahoma 5,574 4,450 4,068 91.46% 2,317 1,798 3,086,287 74.22% 67.88%
Oregon 5,276 4,639 4,190 90.22% 2,355 1,874 3,277,252 76.56% 69.07%
Pennsylvania 22,645 19,463 15,854 80.97% 8,716 6,654 10,775,353 71.76% 58.11%
Rhode Island 5,254 4,330 3,853 88.96% 2,286 1,853 894,624 75.65% 67.30%
South Carolina 6,284 5,107 4,579 89.63% 2,314 1,865 3,876,591 74.84% 67.08%
South Dakota 5,131 4,291 4,058 94.58% 2,220 1,791 672,090 76.65% 72.49%
Tennessee 5,122 4,244 3,843 90.53% 2,215 1,838 5,338,009 79.50% 71.97%
Texas 18,376 15,392 13,888 89.98% 9,090 7,261 20,669,774 74.57% 67.10%
Utah 3,590 3,148 2,979 94.65% 2,224 1,844 2,195,429 80.29% 75.99%
Vermont 6,509 5,218 4,643 89.01% 2,272 1,810 541,169 76.27% 67.88%
Virginia 5,302 4,724 4,101 86.82% 2,200 1,833 6,691,628 79.04% 68.63%
Washington 5,650 4,892 4,376 89.16% 2,472 1,887 5,702,140 72.27% 64.44%
West Virginia 6,460 5,221 4,657 88.63% 2,383 1,914 1,574,028 74.85% 66.34%
Wisconsin 5,148 4,325 4,015 92.56% 2,265 1,777 4,775,635 75.50% 69.89%
Wyoming 6,166 4,866 4,419 90.79% 2,243 1,820 470,156 77.80% 70.63%
Table C.8 Sample Sizes, Weighted Interview Response Rates, and Population Estimates, by State and Three Age Groups: 2011 and 2012
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: Computations in this table are based on a respondent's age at screening. Thus, the data in the Total Responded column(s) could differ from data in other NSDUH tables that use the respondent's age recorded during the interview.
NOTE: To compute the pooled 2011-2012 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 2011 and 2012 individual response rates. The 2011-2012 population estimate is the average of the 2011 and the 2012 population.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2011 and 2012.
Total U.S. 55,058 46,041 24,953,349 83.90% 57,228 45,845 34,445,842 79.86% 63,906 46,532 199,428,944 71.35%
Northeast 10,956 8,846 4,257,645 80.95% 11,579 8,990 6,137,038 76.86% 13,017 9,027 36,638,503 67.21%
Midwest 15,382 12,787 5,430,966 83.30% 15,873 12,643 7,351,049 80.05% 17,814 12,970 43,024,058 71.92%
South 17,379 14,843 9,280,706 85.27% 17,611 14,554 12,684,550 82.38% 19,411 14,469 73,812,214 73.09%
West 11,341 9,565 5,984,032 84.40% 12,165 9,658 8,273,206 78.06% 13,664 10,066 45,954,169 71.35%
Alabama 871 730 385,060 83.04% 960 798 536,921 82.17% 1,022 756 3,073,532 72.17%
Alaska 696 566 60,614 80.86% 716 570 80,497 79.96% 785 598 432,040 74.94%
Arizona 729 620 537,268 85.82% 746 601 709,377 79.02% 790 629 4,077,362 78.80%
Arkansas 745 608 235,330 81.32% 835 662 317,333 78.29% 792 562 1,864,363 68.41%
California 2,812 2,340 3,156,459 83.38% 3,146 2,446 4,427,350 77.27% 3,513 2,462 23,658,234 68.44%
Colorado 752 645 397,449 85.51% 751 591 556,502 79.14% 838 612 3,270,160 73.78%
Connecticut 722 597 290,956 83.31% 815 659 369,988 82.08% 924 659 2,363,818 69.61%
Delaware 723 599 69,055 83.47% 654 541 101,269 83.37% 842 653 590,737 76.88%
District of Columbia 705 633 31,373 90.29% 806 683 96,533 84.87% 681 546 411,604 80.57%
Florida 3,068 2,633 1,381,693 85.23% 3,001 2,444 1,959,129 81.01% 3,451 2,496 12,916,437 70.17%
Georgia 704 599 824,731 84.45% 669 538 1,085,263 80.65% 853 626 6,074,730 73.07%
Hawaii 772 587 97,800 75.39% 794 637 138,119 81.76% 979 664 887,821 68.20%
Idaho 771 676 139,014 88.14% 660 531 173,198 81.56% 829 630 969,335 75.31%
Illinois 3,064 2,488 1,057,464 81.61% 3,192 2,397 1,393,927 75.19% 3,544 2,442 8,215,103 67.50%
Indiana 666 563 540,292 84.57% 782 643 729,904 82.60% 827 601 4,108,332 70.45%
Iowa 768 646 241,228 83.57% 682 560 346,249 82.22% 824 627 1,956,812 75.23%
Kansas 726 622 236,049 85.41% 712 586 321,178 83.34% 835 619 1,772,671 74.30%
Kentucky 743 615 339,685 82.71% 735 602 459,703 82.38% 819 609 2,803,041 72.56%
Louisiana 1,001 880 367,339 88.51% 1,030 870 524,049 85.18% 1,195 897 2,841,017 74.90%
Maine 709 605 96,430 85.36% 735 621 129,601 84.48% 729 577 918,180 77.89%
Maryland 700 606 459,636 86.32% 731 609 628,350 82.93% 764 583 3,789,736 74.57%
Massachusetts 841 693 494,412 82.35% 818 642 768,767 78.23% 824 595 4,368,462 70.85%
Michigan 2,865 2,373 814,217 83.01% 3,077 2,492 1,098,296 81.24% 3,331 2,475 6,392,662 72.96%
Minnesota 733 639 424,745 87.45% 678 546 570,686 80.80% 841 657 3,457,060 79.18%
Mississippi 836 723 248,417 85.92% 791 687 335,677 87.06% 935 717 1,830,270 75.23%
Missouri 705 605 475,157 84.15% 715 594 654,561 83.39% 856 628 3,846,810 70.85%
Montana 740 615 74,042 82.91% 746 605 107,193 80.32% 817 612 657,558 75.70%
Nebraska 664 576 147,027 87.22% 851 680 205,521 80.34% 833 592 1,153,600 69.30%
Nevada 572 494 219,786 87.94% 814 670 282,581 83.77% 873 646 1,757,473 72.05%
New Hampshire 812 629 102,838 77.50% 821 651 138,951 80.42% 854 615 888,797 71.03%
New Jersey 699 592 710,612 85.48% 738 587 876,279 81.17% 847 613 5,826,415 69.69%
New Mexico 651 570 169,342 87.16% 762 629 226,502 80.79% 822 618 1,303,353 75.06%
New York 3,101 2,373 1,474,700 76.41% 3,480 2,442 2,242,476 70.22% 3,809 2,396 12,760,358 61.64%
North Carolina 733 637 757,390 86.25% 721 619 1,024,771 84.52% 766 596 6,176,978 76.15%
North Dakota 705 600 48,873 85.72% 737 593 91,747 80.54% 847 606 430,829 71.11%
Ohio 3,119 2,517 929,629 80.81% 2,937 2,332 1,230,773 79.16% 3,468 2,533 7,466,946 71.75%
Oklahoma 707 567 304,074 80.48% 772 608 423,379 79.07% 838 623 2,358,834 72.49%
Oregon 725 625 291,972 86.68% 780 604 409,608 78.02% 850 645 2,575,672 75.24%
Pennsylvania 2,677 2,192 964,004 82.60% 2,641 2,107 1,405,623 80.50% 3,398 2,355 8,405,726 69.11%
Rhode Island 676 577 77,839 85.62% 763 653 132,549 86.08% 847 623 684,237 72.52%
South Carolina 733 619 357,301 83.98% 741 626 513,846 84.74% 840 620 3,005,444 71.92%
South Dakota 679 582 64,463 85.20% 711 595 91,190 84.33% 830 614 516,437 74.34%
Tennessee 635 554 504,106 87.13% 777 649 683,640 82.94% 803 635 4,150,263 78.02%
Texas 2,988 2,560 2,265,694 85.69% 2,897 2,363 2,919,940 81.38% 3,205 2,338 15,484,139 71.56%
Utah 669 604 268,417 90.74% 734 588 363,323 79.82% 821 652 1,563,689 78.55%
Vermont 719 588 45,855 81.98% 768 628 72,804 82.71% 785 594 422,511 74.58%
Virginia 751 654 618,558 86.47% 670 577 885,563 85.42% 779 602 5,187,508 76.94%
Washington 735 610 528,978 82.76% 853 649 735,790 74.94% 884 628 4,437,371 70.65%
West Virginia 736 626 131,265 85.18% 821 678 189,182 83.12% 826 610 1,253,581 72.62%
Wisconsin 688 576 451,821 83.56% 799 625 617,016 79.62% 778 576 3,706,797 73.78%
Wyoming 717 613 42,890 85.21% 663 537 63,165 81.03% 863 670 364,101 76.39%
Table C.9 Sample Sizes, Weighted Screening and Interview Response Rates, and Population Estimates, by State, for Persons Aged 12 or Older: 2012 and 2013
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 2012-2013 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 2012 and 2013 individual response rates. The 2012-2013 population estimate is the average of the 2012 and the 2013 population.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2012 and 2013.
Total U.S. 441,349 368,653 314,198 85.00% 176,398 136,147 261,224,390 72.37% 61.51%
Northeast 99,075 84,018 67,655 79.23% 36,635 27,434 47,281,597 69.17% 54.80%
Midwest 120,239 101,287 87,390 86.65% 49,341 37,964 56,069,675 72.91% 63.17%
South 136,077 111,573 96,782 86.90% 53,037 41,668 96,943,079 73.77% 64.11%
West 85,958 71,775 62,371 84.88% 37,385 29,081 60,930,039 72.12% 61.22%
Alabama 6,122 4,894 4,282 87.14% 2,301 1,801 4,015,238 71.81% 62.58%
Alaska 5,601 4,216 3,686 87.42% 2,198 1,692 577,228 74.10% 64.78%
Arizona 5,784 4,467 3,919 87.78% 2,309 1,804 5,403,101 73.26% 64.31%
Arkansas 5,497 4,481 4,074 90.79% 2,405 1,821 2,429,054 71.52% 64.93%
California 19,483 17,279 14,063 81.35% 9,643 7,337 31,581,986 70.32% 57.21%
Colorado 5,861 5,015 4,217 84.13% 2,361 1,812 4,299,874 73.07% 61.47%
Connecticut 5,844 5,226 4,401 84.03% 2,459 1,857 3,039,935 71.34% 59.95%
Delaware 5,889 4,777 4,081 85.61% 2,223 1,755 770,186 76.17% 65.21%
District of Columbia 10,521 8,658 7,027 80.87% 2,267 1,869 549,981 78.06% 63.13%
Florida 26,942 21,111 17,692 82.98% 9,371 7,193 16,491,099 71.12% 59.02%
Georgia 5,025 4,260 3,632 85.39% 2,237 1,737 8,087,248 73.06% 62.38%
Hawaii 6,506 5,622 4,474 79.11% 2,525 1,862 1,133,370 67.89% 53.71%
Idaho 4,688 3,959 3,684 93.03% 2,299 1,828 1,297,052 76.96% 71.59%
Illinois 23,152 20,343 15,590 76.61% 9,806 7,175 10,697,218 68.46% 52.45%
Indiana 5,483 4,623 4,103 88.87% 2,336 1,805 5,411,173 72.26% 64.22%
Iowa 5,229 4,517 4,142 91.59% 2,301 1,800 2,558,825 73.00% 66.86%
Kansas 5,206 4,389 3,921 89.29% 2,274 1,799 2,340,109 75.50% 67.41%
Kentucky 5,937 4,963 4,543 91.49% 2,344 1,831 3,620,332 73.50% 67.25%
Louisiana 5,618 4,464 4,073 91.33% 2,260 1,804 3,759,825 75.38% 68.85%
Maine 7,490 5,566 5,029 90.29% 2,259 1,864 1,146,775 78.71% 71.07%
Maryland 5,439 4,738 3,721 78.66% 2,257 1,799 4,926,434 76.39% 60.09%
Massachusetts 6,071 5,345 4,397 82.04% 2,493 1,852 5,686,563 70.51% 57.85%
Michigan 23,521 19,145 16,136 84.20% 9,322 7,291 8,332,687 74.28% 62.54%
Minnesota 5,078 4,432 4,031 91.15% 2,218 1,808 4,490,191 79.20% 72.19%
Mississippi 4,994 4,106 3,780 92.05% 2,188 1,819 2,424,306 78.93% 72.65%
Missouri 6,023 4,995 4,518 90.41% 2,332 1,832 4,997,678 73.77% 66.69%
Montana 6,286 5,039 4,666 92.58% 2,286 1,786 846,239 75.85% 70.22%
Nebraska 5,608 4,675 4,297 91.86% 2,316 1,850 1,517,851 73.67% 67.68%
Nevada 5,107 4,164 3,725 89.51% 2,271 1,835 2,295,456 75.13% 67.25%
New Hampshire 6,478 5,426 4,689 86.38% 2,502 1,903 1,135,783 74.56% 64.40%
New Jersey 5,786 5,001 4,216 84.47% 2,393 1,811 7,458,969 71.25% 60.18%
New Mexico 5,639 4,306 3,927 91.19% 2,269 1,801 1,705,115 74.00% 67.48%
New York 29,704 25,539 18,358 71.58% 10,515 7,317 16,575,744 64.02% 45.83%
North Carolina 5,720 4,628 4,080 88.05% 2,220 1,797 8,060,735 75.70% 66.66%
North Dakota 7,008 5,400 5,023 92.99% 2,413 1,840 585,756 71.05% 66.07%
Ohio 23,262 19,946 17,473 87.57% 9,561 7,255 9,658,305 71.87% 62.94%
Oklahoma 5,790 4,708 4,273 90.80% 2,439 1,858 3,114,952 70.60% 64.10%
Oregon 5,317 4,708 4,172 88.54% 2,258 1,784 3,310,508 76.65% 67.87%
Pennsylvania 25,199 21,746 17,666 81.03% 9,465 7,243 10,799,456 71.88% 58.25%
Rhode Island 5,589 4,705 4,162 88.48% 2,298 1,827 896,323 74.83% 66.20%
South Carolina 6,597 5,429 4,682 86.09% 2,305 1,846 3,926,252 75.78% 65.23%
South Dakota 5,364 4,367 4,090 93.65% 2,219 1,767 680,698 76.45% 71.60%
Tennessee 5,499 4,526 4,081 90.21% 2,226 1,821 5,385,528 77.01% 69.47%
Texas 18,371 15,538 13,665 87.82% 9,355 7,229 21,037,974 72.71% 63.86%
Utah 3,825 3,329 3,152 94.88% 2,249 1,856 2,236,456 79.22% 75.17%
Vermont 6,914 5,464 4,737 86.66% 2,251 1,760 542,049 75.33% 65.28%
Virginia 5,368 4,706 4,099 86.82% 2,243 1,796 6,769,603 76.51% 66.43%
Washington 5,298 4,541 4,015 88.37% 2,393 1,828 5,766,890 71.69% 63.35%
West Virginia 6,748 5,586 4,997 89.36% 2,396 1,892 1,574,332 75.15% 67.15%
Wisconsin 5,305 4,455 4,066 91.41% 2,243 1,742 4,799,184 74.64% 68.23%
Wyoming 6,563 5,130 4,671 91.06% 2,324 1,856 476,764 78.09% 71.10%
Table C.10 Sample Sizes, Weighted Interview Response Rates, and Population Estimates, by State and Three Age Groups: 2012 and 2013
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: Computations in this table are based on a respondent's age at screening. Thus, the data in the Total Responded column(s) could differ from data in other NSDUH tables that use the respondent's age recorded during the interview.
NOTE: To compute the pooled 2012-2013 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 2012 and 2013 individual response rates. The 2012-2013 population estimate is the average of the 2012 and the 2013 population.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2012 and 2013.
Total U.S. 54,777 45,024 24,912,835 82.39% 57,560 45,220 34,687,727 78.30% 64,061 45,903 201,623,828 70.10%
Northeast 11,213 8,982 4,212,368 79.60% 12,029 9,185 6,151,259 75.38% 13,393 9,267 36,917,970 66.93%
Midwest 15,463 12,619 5,407,088 81.81% 16,127 12,598 7,384,188 77.93% 17,751 12,747 43,278,398 70.94%
South 16,660 13,877 9,330,852 83.02% 17,149 13,774 12,808,148 80.11% 19,228 14,017 74,804,079 71.51%
West 11,441 9,546 5,962,527 83.91% 12,255 9,663 8,344,131 77.98% 13,689 9,872 46,623,382 69.58%
Alabama 723 600 383,469 81.47% 760 616 536,933 79.81% 818 585 3,094,837 69.18%
Alaska 668 509 60,264 76.22% 728 587 82,442 80.12% 802 596 434,523 72.75%
Arizona 762 635 540,502 83.49% 756 586 720,761 75.65% 791 583 4,141,839 71.47%
Arkansas 721 567 236,508 78.18% 858 660 318,730 75.95% 826 594 1,873,816 69.89%
California 2,899 2,422 3,117,442 83.51% 3,155 2,452 4,458,805 77.62% 3,589 2,463 24,005,740 67.24%
Colorado 698 578 402,137 83.52% 789 605 565,276 76.77% 874 629 3,332,461 71.26%
Connecticut 752 604 288,704 81.26% 777 610 376,034 79.25% 930 643 2,375,197 68.98%
Delaware 710 588 68,333 82.31% 701 555 102,080 81.10% 812 612 599,773 74.72%
District of Columbia 736 656 30,856 90.16% 702 581 94,677 83.79% 829 632 424,447 75.93%
Florida 2,826 2,349 1,385,416 83.15% 3,048 2,406 1,972,330 78.53% 3,497 2,438 13,133,353 68.77%
Georgia 702 578 831,609 82.00% 744 590 1,100,053 79.50% 791 569 6,155,586 70.62%
Hawaii 745 590 97,086 78.59% 799 629 140,225 78.05% 981 643 896,059 65.33%
Idaho 726 625 140,843 86.67% 763 603 173,004 81.11% 810 600 983,206 74.62%
Illinois 2,977 2,379 1,045,769 80.56% 3,223 2,391 1,394,500 74.06% 3,606 2,405 8,256,950 66.00%
Indiana 696 563 541,016 80.14% 773 616 734,767 78.96% 867 626 4,135,390 70.17%
Iowa 730 601 241,811 80.67% 757 602 349,004 79.74% 814 597 1,968,010 70.80%
Kansas 757 639 237,185 84.32% 704 560 323,430 81.02% 813 600 1,779,494 73.33%
Kentucky 750 618 339,960 82.10% 745 598 464,737 80.80% 849 615 2,815,636 71.22%
Louisiana 700 589 367,827 83.68% 704 579 521,917 81.23% 856 636 2,870,080 73.33%
Maine 749 633 94,988 84.06% 748 631 128,694 84.38% 762 600 923,093 77.36%
Maryland 705 584 457,152 83.28% 752 612 631,368 79.76% 800 603 3,837,914 74.99%
Massachusetts 750 594 491,273 78.88% 835 623 775,063 75.12% 908 635 4,420,226 68.78%
Michigan 2,933 2,372 805,764 80.89% 3,058 2,451 1,107,310 79.91% 3,331 2,468 6,419,614 72.46%
Minnesota 698 611 424,639 88.46% 730 579 571,439 78.02% 790 618 3,494,114 78.30%
Mississippi 761 650 247,257 84.79% 666 584 337,204 87.67% 761 585 1,839,846 76.40%
Missouri 725 614 472,889 84.31% 737 582 655,094 79.29% 870 636 3,869,695 71.57%
Montana 782 630 73,896 80.70% 747 588 108,999 77.95% 757 568 663,344 74.89%
Nebraska 712 599 148,030 83.78% 804 674 207,051 83.81% 800 577 1,162,770 70.47%
Nevada 688 600 221,167 87.57% 719 603 285,463 83.25% 864 632 1,788,826 72.37%
New Hampshire 798 609 101,207 76.06% 831 643 140,004 78.44% 873 651 894,572 73.74%
New Jersey 729 584 706,126 81.00% 782 605 884,775 77.80% 882 622 5,868,068 69.01%
New Mexico 672 587 168,112 87.37% 747 600 228,037 79.38% 850 614 1,308,966 71.35%
New York 3,249 2,496 1,456,617 76.58% 3,427 2,402 2,243,318 70.34% 3,839 2,419 12,875,810 61.47%
North Carolina 664 564 764,610 85.24% 750 627 1,041,859 82.67% 806 606 6,254,266 73.32%
North Dakota 739 606 49,581 81.26% 741 583 96,345 79.36% 933 651 439,830 68.18%
Ohio 3,170 2,517 925,827 79.23% 3,000 2,321 1,235,683 78.07% 3,391 2,417 7,496,795 69.92%
Oklahoma 808 649 306,820 80.51% 795 616 426,492 76.97% 836 593 2,381,640 68.19%
Oregon 632 533 292,050 83.94% 768 607 411,744 79.54% 858 644 2,606,713 75.45%
Pennsylvania 2,808 2,315 951,880 82.46% 3,111 2,438 1,397,926 78.78% 3,546 2,490 8,449,649 69.54%
Rhode Island 692 588 76,543 85.46% 751 618 132,076 81.81% 855 621 687,705 72.40%
South Carolina 777 636 359,524 81.22% 694 580 519,243 83.75% 834 630 3,047,485 73.75%
South Dakota 675 569 64,901 84.17% 732 586 92,359 80.75% 812 612 523,437 74.88%
Tennessee 670 578 505,317 85.57% 778 644 692,825 82.46% 778 599 4,187,386 75.12%
Texas 2,876 2,385 2,295,567 82.49% 3,059 2,402 2,964,444 78.37% 3,420 2,442 15,777,963 70.25%
Utah 690 605 275,660 88.43% 803 650 367,327 81.59% 756 601 1,593,468 76.95%
Vermont 686 559 45,030 80.94% 767 615 73,369 80.79% 798 586 423,650 73.81%
Virginia 767 653 619,956 85.16% 638 517 893,349 82.17% 838 626 5,256,298 74.38%
Washington 721 598 529,852 83.62% 771 599 738,145 77.21% 901 631 4,498,893 69.56%
West Virginia 764 633 130,671 83.20% 755 607 189,908 80.33% 877 652 1,253,753 73.53%
Wisconsin 651 549 449,677 83.42% 868 653 617,207 74.83% 724 540 3,732,300 73.51%
Wyoming 758 634 43,516 83.37% 710 554 63,905 78.47% 856 668 369,343 77.41%
Table C.11 Sample Sizes, Weighted Interview Response Rates, and Population Estimates among Persons Aged 12 to 20, by State: 2011, 2012, and 2013
State 2011
Total
Selected
2011
Total
Responded
2011
Population
Estimate
2011
Weighted
Interview
Response
Rate
2012
Total
Selected
2012
Total
Responded
2012
Population
Estimate
2012
Weighted
Interview
Response
Rate
2013
Total
Selected
2013
Total
Responded
2013
Population
Estimate
2013
Weighted
Interview
Response
Rate
NOTE: Computations in this table are based on a respondent's age at screening. Thus, the data in the Total Responded column(s) could differ from data in other NSDUH tables that use the respondent's age recorded during the interview.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2011, 2012, and 2013.
Total U.S. 38,505 32,349 38,497,742 84.37% 37,391 30,912 38,205,953 82.59% 37,820 30,801 38,086,579 81.70%
Northeast 7,493 6,098 6,824,455 82.10% 7,735 6,239 6,646,927 80.21% 7,770 6,238 6,379,509 79.42%
Midwest 10,686 8,872 8,368,112 82.81% 10,454 8,616 8,152,530 82.67% 10,686 8,592 8,217,933 80.04%
South 12,390 10,682 14,024,266 86.28% 11,385 9,547 14,063,463 83.57% 11,306 9,274 14,070,964 81.83%
West 7,936 6,697 9,280,909 84.53% 7,817 6,510 9,343,033 82.70% 8,058 6,697 9,418,173 84.56%
Alabama 744 631 604,574 84.49% 469 384 584,363 81.07% 497 421 570,714 82.97%
Alaska 515 431 89,332 83.83% 441 352 95,819 80.24% 490 383 91,357 77.84%
Arizona 511 433 798,580 85.99% 503 424 816,941 83.45% 526 428 816,730 81.20%
Arkansas 528 442 374,992 83.30% 550 439 370,165 79.62% 457 357 334,342 77.85%
California 2,003 1,685 5,066,496 84.30% 2,016 1,646 5,018,845 81.44% 2,070 1,767 5,008,517 85.96%
Colorado 480 411 564,436 84.33% 501 421 594,406 85.04% 450 367 609,754 82.09%
Connecticut 516 441 436,152 86.19% 520 427 455,720 82.40% 534 431 421,506 81.80%
Delaware 465 393 105,240 84.25% 493 407 107,644 84.15% 460 379 99,907 80.87%
District of Columbia 487 422 65,173 83.44% 498 451 64,190 91.18% 452 387 54,486 84.22%
Florida 2,250 1,949 2,211,773 86.30% 1,980 1,649 2,109,563 82.68% 1,929 1,574 2,127,386 81.54%
Georgia 480 413 1,207,618 86.51% 478 397 1,309,366 82.78% 502 405 1,278,777 81.65%
Hawaii 541 424 149,682 78.74% 500 388 145,487 78.38% 508 416 146,388 80.45%
Idaho 493 422 205,495 85.84% 515 441 206,195 85.69% 483 398 202,212 84.41%
Illinois 2,144 1,711 1,619,137 79.79% 2,036 1,637 1,553,772 80.89% 2,048 1,582 1,571,014 77.50%
Indiana 489 424 852,672 85.97% 480 393 813,060 81.75% 490 392 794,141 77.86%
Iowa 523 443 382,062 85.81% 485 404 353,403 82.15% 484 396 365,893 81.48%
Kansas 484 398 344,035 82.51% 508 443 380,034 86.86% 499 404 360,191 81.57%
Kentucky 481 400 501,556 83.75% 511 422 505,420 82.23% 491 400 507,396 81.31%
Louisiana 918 804 573,374 88.93% 451 395 552,954 87.18% 487 399 574,885 80.70%
Maine 495 424 153,910 85.35% 504 433 145,895 86.56% 523 448 146,805 85.44%
Maryland 487 422 657,919 85.91% 438 372 655,351 84.43% 505 403 653,828 79.02%
Massachusetts 620 520 822,796 83.78% 520 420 763,162 80.74% 499 385 723,842 76.61%
Michigan 2,034 1,702 1,293,907 83.70% 1,992 1,638 1,251,079 82.84% 2,054 1,654 1,239,358 80.23%
Minnesota 488 411 622,236 84.21% 471 411 629,891 86.19% 456 393 626,747 86.71%
Mississippi 597 539 365,463 90.08% 517 426 376,196 82.30% 493 437 363,901 88.44%
Missouri 465 398 714,937 82.47% 486 407 700,548 84.33% 493 412 714,528 81.35%
Montana 491 411 112,790 82.79% 522 431 123,289 83.41% 550 440 120,530 79.55%
Nebraska 514 427 225,527 83.87% 475 413 228,674 87.51% 539 452 240,691 82.96%
Nevada 440 385 370,767 90.91% 474 403 339,091 85.10% 486 431 343,860 89.80%
New Hampshire 589 479 177,762 82.39% 599 472 181,715 80.39% 556 444 173,109 80.69%
New Jersey 494 424 1,119,943 88.15% 475 389 1,041,104 81.91% 506 400 1,028,297 80.63%
New Mexico 469 404 258,176 84.99% 459 396 247,385 86.18% 477 403 252,940 83.62%
New York 2,120 1,607 2,330,810 76.15% 2,182 1,674 2,352,294 76.70% 2,218 1,701 2,191,460 76.54%
North Carolina 487 433 1,114,423 88.06% 474 404 1,096,473 85.11% 438 365 1,101,838 83.46%
North Dakota 476 414 80,431 86.41% 495 415 90,131 84.87% 497 397 82,751 78.48%
Ohio 2,081 1,715 1,474,645 82.49% 2,134 1,696 1,382,707 79.58% 2,130 1,697 1,449,529 80.13%
Oklahoma 454 373 462,928 83.45% 523 407 474,162 76.65% 601 482 497,668 80.37%
Oregon 534 450 424,881 83.95% 457 391 462,560 85.86% 458 372 456,806 80.22%
Pennsylvania 1,677 1,377 1,583,008 83.76% 1,980 1,620 1,506,219 82.23% 1,967 1,623 1,484,560 82.08%
Rhode Island 483 413 126,155 85.65% 460 399 127,152 87.11% 508 430 139,658 85.71%
South Carolina 482 414 521,289 85.95% 496 414 537,771 83.64% 507 411 539,469 81.31%
South Dakota 470 411 87,535 86.40% 444 378 101,364 85.52% 506 425 103,606 82.80%
Tennessee 462 401 768,020 86.68% 439 378 731,381 84.81% 495 425 773,131 85.93%
Texas 2,010 1,738 3,303,733 86.40% 2,002 1,690 3,407,153 84.28% 1,968 1,591 3,455,065 80.21%
Utah 463 406 364,611 85.21% 434 386 396,005 88.78% 511 434 420,269 85.51%
Vermont 499 413 73,919 84.39% 495 405 73,666 81.68% 459 376 70,271 81.84%
Virginia 516 452 966,316 86.34% 484 416 952,855 85.21% 502 421 933,932 85.76%
Washington 510 424 809,041 82.70% 516 419 825,920 81.17% 503 417 880,808 84.01%
West Virginia 542 456 219,874 85.17% 582 496 228,456 84.92% 522 417 204,238 80.45%
Wisconsin 518 418 670,989 81.33% 448 381 667,867 84.74% 490 388 669,485 77.88%
Wyoming 486 411 66,621 85.07% 479 412 71,089 84.48% 546 441 68,002 81.58%
Table C.12 Sample Sizes, Weighted Interview Response Rates, and Population Estimates among Persons Aged 12 to 20, by State: 2011-2012 and 2012-2013
State 2011-2012
Total
Selected
2011-2012
Total
Responded
2011-2012
Population
Estimate
2011-2012
Weighted
Interview
Response
Rate
2012-2013
Total
Selected
2012-2013
Total
Responded
2012-2013
Population
Estimate
2012-2013
Weighted
Interview
Response
Rate
NOTE: Computations in this table are based on a respondent's age at screening. Thus, the data in the Total Responded column(s) could differ from data in other NSDUH tables that use the respondent's age recorded during the interview.
NOTE: 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. The population estimate is the average of the population across the 2 years.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2011, 2012, and 2013.
Total U.S. 75,896 63,261 38,351,848 83.48% 75,211 61,713 38,146,266 82.14%
Northeast 15,228 12,337 6,735,691 81.17% 15,505 12,477 6,513,218 79.82%
Midwest 21,140 17,488 8,260,321 82.74% 21,140 17,208 8,185,232 81.35%
South 23,775 20,229 14,043,864 84.93% 22,691 18,821 14,067,213 82.70%
West 15,753 13,207 9,311,971 83.61% 15,875 13,207 9,380,603 83.62%
Alabama 1,213 1,015 594,469 82.82% 966 805 577,538 82.00%
Alaska 956 783 92,576 82.01% 931 735 93,588 79.06%
Arizona 1,014 857 807,761 84.71% 1,029 852 816,835 82.33%
Arkansas 1,078 881 372,578 81.52% 1,007 796 352,254 78.75%
California 4,019 3,331 5,042,671 82.86% 4,086 3,413 5,013,681 83.66%
Colorado 981 832 579,421 84.71% 951 788 602,080 83.58%
Connecticut 1,036 868 445,936 84.34% 1,054 858 438,613 82.09%
Delaware 958 800 106,442 84.20% 953 786 103,775 82.52%
District of Columbia 985 873 64,681 87.24% 950 838 59,338 87.97%
Florida 4,230 3,598 2,160,668 84.51% 3,909 3,223 2,118,475 82.12%
Georgia 958 810 1,258,492 84.59% 980 802 1,294,072 82.22%
Hawaii 1,041 812 147,585 78.56% 1,008 804 145,938 79.41%
Idaho 1,008 863 205,845 85.76% 998 839 204,204 85.06%
Illinois 4,180 3,348 1,586,454 80.33% 4,084 3,219 1,562,393 79.19%
Indiana 969 817 832,866 83.88% 970 785 803,600 79.84%
Iowa 1,008 847 367,732 84.07% 969 800 359,648 81.81%
Kansas 992 841 362,035 84.71% 1,007 847 370,112 84.27%
Kentucky 992 822 503,488 83.00% 1,002 822 506,408 81.76%
Louisiana 1,369 1,199 563,164 88.07% 938 794 563,920 83.93%
Maine 999 857 149,902 85.94% 1,027 881 146,350 86.01%
Maryland 925 794 656,635 85.18% 943 775 654,590 81.68%
Massachusetts 1,140 940 792,979 82.34% 1,019 805 743,502 78.72%
Michigan 4,026 3,340 1,272,493 83.28% 4,046 3,292 1,245,219 81.54%
Minnesota 959 822 626,064 85.18% 927 804 628,319 86.44%
Mississippi 1,114 965 370,830 86.07% 1,010 863 370,048 85.31%
Missouri 951 805 707,743 83.39% 979 819 707,538 82.83%
Montana 1,013 842 118,039 83.11% 1,072 871 121,910 81.44%
Nebraska 989 840 227,100 85.62% 1,014 865 234,682 85.20%
Nevada 914 788 354,929 88.06% 960 834 341,475 87.42%
New Hampshire 1,188 951 179,739 81.37% 1,155 916 177,412 80.53%
New Jersey 969 813 1,080,523 85.12% 981 789 1,034,700 81.28%
New Mexico 928 800 252,781 85.58% 936 799 250,162 84.89%
New York 4,302 3,281 2,341,552 76.42% 4,400 3,375 2,271,877 76.62%
North Carolina 961 837 1,105,448 86.55% 912 769 1,099,156 84.28%
North Dakota 971 829 85,281 85.62% 992 812 86,441 81.66%
Ohio 4,215 3,411 1,428,676 81.08% 4,264 3,393 1,416,118 79.86%
Oklahoma 977 780 468,545 80.03% 1,124 889 485,915 78.58%
Oregon 991 841 443,721 84.92% 915 763 459,683 83.01%
Pennsylvania 3,657 2,997 1,544,613 83.01% 3,947 3,243 1,495,389 82.16%
Rhode Island 943 812 126,654 86.38% 968 829 133,405 86.40%
South Carolina 978 828 529,530 84.79% 1,003 825 538,620 82.45%
South Dakota 914 789 94,450 85.95% 950 803 102,485 84.13%
Tennessee 901 779 749,701 85.76% 934 803 752,256 85.38%
Texas 4,012 3,428 3,355,443 85.34% 3,970 3,281 3,431,109 82.24%
Utah 897 792 380,308 87.03% 945 820 408,137 87.10%
Vermont 994 818 73,792 83.04% 954 781 71,968 81.76%
Virginia 1,000 868 959,586 85.79% 986 837 943,393 85.48%
Washington 1,026 843 817,480 81.94% 1,019 836 853,364 82.64%
West Virginia 1,124 952 224,165 85.05% 1,104 913 216,347 82.84%
Wisconsin 966 799 669,428 83.00% 938 769 668,676 81.25%
Wyoming 965 823 68,855 84.76% 1,025 853 69,545 83.04%
Table C.13 Sample Sizes, Weighted Interview Response Rates, and Population Estimates among Persons Aged 18 or Older, by State: 2011, 2012, and 2013
State 2011
Total
Selected
2011
Total
Responded
2011
Population
Estimate
2011
Weighted
Interview
Response
Rate
2012
Total
Selected
2012
Total
Responded
2012
Population
Estimate
2012
Weighted
Interview
Response
Rate
2013
Total
Selected
2013
Total
Responded
2013
Population
Estimate
2013
Weighted
Interview
Response
Rate
NOTE: Computations in this table are based on a respondent's age at screening. Thus, the data in the Total Responded column(s) could differ from data in other NSDUH tables that use the respondent's age recorded during the interview.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2011, 2012, and 2013.
Total U.S. 60,625 46,560 232,625,299 73.22% 60,509 45,817 235,124,274 72.00% 61,112 45,306 237,498,837 70.61%
Northeast 11,808 8,665 42,613,542 68.62% 12,788 9,352 42,937,539 68.59% 12,634 9,100 43,200,918 67.70%
Midwest 16,921 12,870 50,241,664 72.89% 16,766 12,743 50,508,549 73.29% 17,112 12,602 50,816,624 70.61%
South 19,035 15,110 85,925,683 75.76% 17,987 13,913 87,067,845 73.21% 18,390 13,878 88,156,610 72.35%
West 12,861 9,915 53,844,410 73.17% 12,968 9,809 54,610,340 71.60% 12,976 9,726 55,324,685 70.09%
Alabama 1,179 931 3,599,718 73.44% 803 623 3,621,189 73.90% 775 578 3,642,350 67.91%
Alaska 729 572 508,235 78.77% 772 596 516,839 73.05% 758 587 517,089 74.74%
Arizona 763 620 4,749,984 81.79% 773 610 4,823,495 76.18% 774 559 4,901,704 67.86%
Arkansas 809 623 2,176,513 71.07% 818 601 2,186,878 68.89% 866 653 2,198,214 72.67%
California 3,289 2,459 27,886,283 70.78% 3,370 2,449 28,284,885 68.90% 3,374 2,466 28,644,204 68.82%
Colorado 777 595 3,792,000 75.18% 812 608 3,861,324 73.85% 851 626 3,934,150 70.24%
Connecticut 839 642 2,723,233 70.84% 900 676 2,744,379 71.67% 807 577 2,758,083 68.93%
Delaware 762 608 687,253 75.70% 734 586 696,760 79.66% 779 581 706,947 71.27%
District of Columbia 724 596 502,986 82.93% 763 633 513,289 79.99% 768 580 524,960 74.63%
Florida 3,292 2,589 14,751,904 73.85% 3,160 2,351 14,999,230 69.34% 3,385 2,493 15,212,136 70.67%
Georgia 722 566 7,107,414 76.39% 800 598 7,212,572 72.11% 735 561 7,298,705 71.87%
Hawaii 865 647 1,017,992 71.81% 908 654 1,033,888 68.36% 872 618 1,038,681 65.50%
Idaho 742 585 1,136,459 75.69% 747 576 1,148,607 76.93% 826 627 1,163,811 74.54%
Illinois 3,382 2,401 9,589,171 67.45% 3,354 2,438 9,628,889 69.74% 3,475 2,358 9,674,009 64.56%
Indiana 768 604 4,825,634 72.44% 841 640 4,850,837 72.01% 799 602 4,889,478 70.78%
Iowa 742 601 2,296,838 78.35% 764 586 2,309,284 73.90% 807 613 2,324,742 70.53%
Kansas 826 636 2,088,098 74.63% 721 569 2,099,601 76.67% 796 591 2,106,246 72.33%
Kentucky 754 602 3,257,502 75.37% 800 609 3,267,986 72.62% 794 604 3,292,759 72.57%
Louisiana 1,455 1,158 3,352,333 76.72% 770 609 3,377,799 76.40% 790 606 3,406,196 72.72%
Maine 689 565 1,045,661 78.89% 775 633 1,049,900 78.59% 735 598 1,053,674 77.84%
Maryland 751 600 4,388,713 76.64% 744 592 4,447,458 74.85% 808 623 4,491,106 76.42%
Massachusetts 769 591 5,106,323 73.51% 873 646 5,168,136 70.62% 870 612 5,222,444 68.82%
Michigan 3,247 2,490 7,472,092 73.25% 3,161 2,477 7,509,825 75.11% 3,228 2,442 7,544,022 72.00%
Minnesota 790 625 4,009,170 78.60% 729 578 4,046,322 80.26% 791 619 4,084,784 76.42%
Mississippi 1,010 816 2,160,292 75.97% 716 588 2,171,602 78.33% 711 581 2,182,497 78.14%
Missouri 789 619 4,491,236 72.16% 782 603 4,511,506 73.10% 825 615 4,538,072 72.25%
Montana 842 657 761,268 75.83% 721 560 768,234 76.98% 783 596 776,451 73.89%
Nebraska 836 610 1,354,318 70.17% 848 662 1,363,924 71.68% 756 589 1,375,718 73.48%
Nevada 886 703 2,022,350 72.78% 801 613 2,057,758 74.47% 782 622 2,090,821 73.20%
New Hampshire 821 621 1,023,936 71.86% 854 645 1,031,559 72.83% 850 649 1,037,592 75.97%
New Jersey 779 593 6,673,054 69.81% 806 607 6,732,336 72.63% 858 620 6,773,350 67.83%
New Mexico 815 658 1,525,882 79.08% 769 589 1,533,828 72.67% 828 625 1,540,178 72.40%
New York 3,586 2,351 14,940,181 62.61% 3,703 2,487 15,065,487 63.25% 3,563 2,334 15,172,768 62.31%
North Carolina 724 596 7,156,772 80.07% 763 619 7,246,727 74.56% 793 614 7,345,522 74.76%
North Dakota 799 613 516,537 72.93% 785 586 528,614 72.53% 889 648 543,737 67.93%
Ohio 3,206 2,475 8,683,577 73.60% 3,199 2,390 8,711,861 71.96% 3,192 2,348 8,753,095 70.18%
Oklahoma 806 626 2,770,637 75.32% 804 605 2,793,790 71.76% 827 604 2,822,475 67.42%
Oregon 776 596 2,969,857 75.67% 854 653 3,000,702 75.56% 772 598 3,036,213 76.46%
Pennsylvania 2,759 2,051 9,791,217 71.86% 3,280 2,411 9,831,482 69.58% 3,377 2,517 9,863,670 72.18%
Rhode Island 799 629 815,472 72.44% 811 647 818,100 76.97% 795 592 821,462 70.88%
South Carolina 795 625 3,497,010 73.23% 786 621 3,541,570 74.46% 742 589 3,591,886 75.96%
South Dakota 744 596 603,514 76.24% 797 613 611,740 75.34% 747 585 619,853 76.03%
Tennessee 774 618 4,809,840 76.82% 806 666 4,857,966 80.57% 750 577 4,902,455 71.95%
Texas 2,962 2,322 18,234,826 74.41% 3,140 2,379 18,573,333 72.01% 3,339 2,465 18,911,482 71.04%
Utah 775 601 1,911,676 75.26% 780 639 1,942,347 82.23% 779 612 1,979,244 73.43%
Vermont 767 622 494,466 78.40% 786 600 496,163 73.23% 779 601 497,875 76.52%
Virginia 727 607 6,029,485 81.02% 722 572 6,116,656 75.62% 754 571 6,182,639 75.56%
Washington 887 650 5,138,999 71.57% 850 627 5,207,324 70.94% 822 603 5,266,752 70.21%
West Virginia 789 627 1,442,485 75.00% 858 661 1,443,040 72.82% 774 598 1,444,283 76.05%
Wisconsin 792 600 4,311,481 74.87% 785 601 4,336,147 74.41% 807 592 4,362,867 72.94%
Wyoming 715 572 423,425 77.45% 811 635 431,108 76.66% 755 587 435,387 78.48%
Table C.14 Sample Sizes, Weighted Interview Response Rates, and Population Estimates among Persons Aged 18 or Older, by State: 2011-2012 and 2012-2013
State 2011-2012
Total
Selected
2011-2012
Total
Responded
2011-2012
Population
Estimate
2011-2012
Weighted
Interview
Response
Rate
2012-2013
Total
Selected
2012-2013
Total
Responded
2012-2013
Population
Estimate
2012-2013
Weighted
Interview
Response
Rate
NOTE: Computations in this table are based on a respondent's age at screening. Thus, the data in the Total Responded column(s) could differ from data in other NSDUH tables that use the respondent's age recorded during the interview.
NOTE: 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. The population estimate is the average of the population across the 2 years.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2011, 2012, and 2013.
Total U.S. 121,134 92,377 233,874,786 72.60% 121,621 91,123 236,311,555 71.31%
Northeast 24,596 18,017 42,775,541 68.60% 25,422 18,452 43,069,229 68.15%
Midwest 33,687 25,613 50,375,107 73.09% 33,878 25,345 50,662,587 71.95%
South 37,022 29,023 86,496,764 74.47% 36,377 27,791 87,612,227 72.78%
West 25,829 19,724 54,227,375 72.36% 25,944 19,535 54,967,513 70.85%
Alabama 1,982 1,554 3,610,453 73.67% 1,578 1,201 3,631,769 70.77%
Alaska 1,501 1,168 512,537 75.73% 1,530 1,183 516,964 73.87%
Arizona 1,536 1,230 4,786,739 78.83% 1,547 1,169 4,862,599 72.12%
Arkansas 1,627 1,224 2,181,695 69.95% 1,684 1,254 2,192,546 70.81%
California 6,659 4,908 28,085,584 69.82% 6,744 4,915 28,464,544 68.86%
Colorado 1,589 1,203 3,826,662 74.51% 1,663 1,234 3,897,737 72.04%
Connecticut 1,739 1,318 2,733,806 71.28% 1,707 1,253 2,751,231 70.35%
Delaware 1,496 1,194 692,007 77.78% 1,513 1,167 701,853 75.61%
District of Columbia 1,487 1,229 508,138 81.39% 1,531 1,213 519,124 77.35%
Florida 6,452 4,940 14,875,567 71.60% 6,545 4,844 15,105,683 70.03%
Georgia 1,522 1,164 7,159,993 74.20% 1,535 1,159 7,255,639 72.00%
Hawaii 1,773 1,301 1,025,940 70.01% 1,780 1,272 1,036,284 66.93%
Idaho 1,489 1,161 1,142,533 76.27% 1,573 1,203 1,156,209 75.67%
Illinois 6,736 4,839 9,609,030 68.62% 6,829 4,796 9,651,449 67.15%
Indiana 1,609 1,244 4,838,235 72.21% 1,640 1,242 4,870,158 71.43%
Iowa 1,506 1,187 2,303,061 76.26% 1,571 1,199 2,317,013 72.17%
Kansas 1,547 1,205 2,093,849 75.65% 1,517 1,160 2,102,923 74.48%
Kentucky 1,554 1,211 3,262,744 73.96% 1,594 1,213 3,280,373 72.59%
Louisiana 2,225 1,767 3,365,066 76.56% 1,560 1,215 3,391,997 74.50%
Maine 1,464 1,198 1,047,780 78.74% 1,510 1,231 1,051,787 78.21%
Maryland 1,495 1,192 4,418,086 75.78% 1,552 1,215 4,469,282 75.66%
Massachusetts 1,642 1,237 5,137,229 72.01% 1,743 1,258 5,195,290 69.73%
Michigan 6,408 4,967 7,490,959 74.17% 6,389 4,919 7,526,924 73.56%
Minnesota 1,519 1,203 4,027,746 79.41% 1,520 1,197 4,065,553 78.26%
Mississippi 1,726 1,404 2,165,947 77.12% 1,427 1,169 2,177,049 78.23%
Missouri 1,571 1,222 4,501,371 72.61% 1,607 1,218 4,524,789 72.67%
Montana 1,563 1,217 764,751 76.36% 1,504 1,156 772,343 75.34%
Nebraska 1,684 1,272 1,359,121 70.94% 1,604 1,251 1,369,821 72.53%
Nevada 1,687 1,316 2,040,054 73.62% 1,583 1,235 2,074,289 73.83%
New Hampshire 1,675 1,266 1,027,747 72.35% 1,704 1,294 1,034,575 74.40%
New Jersey 1,585 1,200 6,702,695 71.21% 1,664 1,227 6,752,843 70.22%
New Mexico 1,584 1,247 1,529,855 75.90% 1,597 1,214 1,537,003 72.53%
New York 7,289 4,838 15,002,834 62.93% 7,266 4,821 15,119,127 62.78%
North Carolina 1,487 1,215 7,201,750 77.34% 1,556 1,233 7,296,125 74.66%
North Dakota 1,584 1,199 522,576 72.73% 1,674 1,234 536,176 70.13%
Ohio 6,405 4,865 8,697,719 72.78% 6,391 4,738 8,732,478 71.07%
Oklahoma 1,610 1,231 2,782,213 73.52% 1,631 1,209 2,808,132 69.54%
Oregon 1,630 1,249 2,985,280 75.61% 1,626 1,251 3,018,457 75.99%
Pennsylvania 6,039 4,462 9,811,349 70.71% 6,657 4,928 9,847,576 70.86%
Rhode Island 1,610 1,276 816,786 74.71% 1,606 1,239 819,781 73.87%
South Carolina 1,581 1,246 3,519,290 73.86% 1,528 1,210 3,566,728 75.22%
South Dakota 1,541 1,209 607,627 75.78% 1,544 1,198 615,796 75.69%
Tennessee 1,580 1,284 4,833,903 78.71% 1,556 1,243 4,880,211 76.17%
Texas 6,102 4,701 18,404,079 73.17% 6,479 4,844 18,742,407 71.52%
Utah 1,555 1,240 1,927,012 78.79% 1,559 1,251 1,960,796 77.89%
Vermont 1,553 1,222 495,314 75.75% 1,565 1,201 497,019 74.82%
Virginia 1,449 1,179 6,073,071 78.24% 1,476 1,143 6,149,648 75.59%
Washington 1,737 1,277 5,173,161 71.23% 1,672 1,230 5,237,038 70.58%
West Virginia 1,647 1,288 1,442,762 73.94% 1,632 1,259 1,443,661 74.41%
Wisconsin 1,577 1,201 4,323,814 74.63% 1,592 1,193 4,349,507 73.71%
Wyoming 1,526 1,207 427,266 77.04% 1,566 1,222 433,248 77.56%
Table C.15 Outcomes, by Survey Year, for Which Small Area Estimates Are Available
Measure 2002-
2003
2003-
2004
2004-
2005
2005-
2006
2006-
2007
2007-
2008
2008-
2009
2009-
2010
2010-
2011
2011-
2012
2012-
2013
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 Bayesian confidence intervals associated with these were not published.
2 Estimates for SPD in the years 2002-2003 and 2003-2004 are not comparable with the 2004-2005 SPD estimates. For more details, see Section A.7 in Appendix A of the 2004-2005 State report (Wright et al., 2007). Note that, in 2002-2003, SPD was referred to as "serious mental illness."
3 Questions that were used to determine an MDE were added in 2004. Note that the adult MDE estimates shown in the 2004-2005 report are not comparable with the adult MDE estimates for later years.
Yes = available, No = not available.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2002-2013.
Illicit Drug Use in the Past Month Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Marijuana Use in the Past Year Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Marijuana Use in the Past Month Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Perceptions of Great Risk of Smoking Marijuana Once a Month Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
First Use of Marijuana (Marijuana Incidence) Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Illicit Drug Use Other Than Marijuana in the Past Month Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Cocaine Use in the Past Year Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Nonmedical Use of Pain Relievers in the Past Year No1 Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Alcohol Use in the Past Month Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Underage Past Month Use of Alcohol No1 Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Binge Alcohol Use in the Past Month Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Underage Past Month Binge Alcohol Use No1 Yes Yes Yes Yes Yes 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 Yes Yes Yes Yes Yes
Tobacco Product Use in the Past Month Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Cigarette Use in the Past Month Yes Yes Yes Yes Yes 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 Yes Yes Yes Yes Yes
Alcohol Dependence or Abuse in the Past Year Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Alcohol Dependence in the Past Year Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Illicit Drug Dependence or Abuse in the Past Year Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Illicit Drug Dependence in the Past Year Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Dependence or Abuse of Illicit Drugs or Alcohol in the Past Year Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Needing But Not Receiving Treatment for Illicit Drug Use in the Past Year Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Needing But Not Receiving Treatment for Alcohol Use in the Past Year Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
Serious Psychological Distress (SPD) in the Past Year2 Yes Yes Yes No No No No No No No No
Had at Least One Major Depressive Episode (MDE) in the Past Year3 No No Yes Yes Yes Yes Yes Yes Yes Yes Yes
Serious Mental Illness (SMI) in the Past Year No No No No No No Yes Yes Yes Yes Yes
Any Mental Illness (AMI) in the Past Year No No No No No No Yes Yes Yes Yes Yes
Had Serious Thoughts of Suicide in the Past Year No No No No No No Yes Yes Yes Yes Yes
Table C.16 Outcomes, by Age Groups, for Which Small Area Estimates Are Available
Measure Age Group
12+ 12-17 12-20 18-25 26+ 18+
NOTE: For details on which years small area estimates are available for these outcomes, see Table C.15.
NOTE: Tables containing 18 or older estimates were first presented with the 2005-2006 small area estimation (SAE) tables.
1 There are minor wording differences in the questions for the adult and adolescent MDE modules. Therefore, data from youths aged 12 to 17 were not combined with data from adults aged 18 or older to get an overall MDE estimate (12 or older).
Yes = available, No = not available.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2002-2013.
Illicit Drug Use in the Past Month Yes Yes No Yes Yes Yes
Marijuana Use in the Past Year Yes Yes No Yes Yes Yes
Marijuana Use in the Past Month Yes Yes No Yes Yes Yes
Perceptions of Great Risk of Smoking Marijuana Once a Month Yes Yes No Yes Yes Yes
First Use of Marijuana (Marijuana Incidence) Yes Yes No Yes Yes Yes
Illicit Drug Use Other Than Marijuana in the Past Month Yes Yes No Yes Yes Yes
Cocaine Use in the Past Year Yes Yes No Yes Yes Yes
Nonmedical Use of Pain Relievers in the Past Year Yes Yes No Yes Yes Yes
Alcohol Use in the Past Month Yes Yes Yes Yes Yes Yes
Binge Alcohol Use in the Past Month Yes 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 No Yes Yes Yes
Tobacco Product Use in the Past Month Yes Yes No Yes Yes Yes
Cigarette Use in the Past Month Yes Yes No Yes Yes Yes
Perceptions of Great Risk of Smoking One or More Packs of Cigarettes per Day Yes Yes No Yes Yes Yes
Alcohol Dependence or Abuse in the Past Year Yes Yes No Yes Yes Yes
Alcohol Dependence in the Past Year Yes Yes No Yes Yes Yes
Illicit Drug Dependence or Abuse in the Past Year Yes Yes No Yes Yes Yes
Illicit Drug Dependence in the Past Year Yes Yes No Yes Yes Yes
Dependence or Abuse of Illicit Drugs or Alcohol in the Past Year Yes Yes No Yes Yes Yes
Needing But Not Receiving Treatment for Illicit Drug Use in the Past Year Yes Yes No Yes Yes Yes
Needing But Not Receiving Treatment for Alcohol Use in the Past Year Yes Yes No Yes Yes Yes
Serious Psychological Distress (SPD) in the Past Year No No No Yes Yes Yes
Had at Least One Major Depressive Episode (MDE) in the Past Year1 No Yes No Yes Yes Yes
Serious Mental Illness (SMI) in the Past Year No No No Yes Yes Yes
Any Mental Illness (AMI) in the Past Year No No No Yes Yes Yes
Had Serious Thoughts of Suicide in the Past Year No No No Yes Yes Yes
Table C.17 Summary of Milestones Implemented in the SAE Production Process, 2002-2012
SAE Production Items Years for Which Pooled 2-Year Small Area Estimates Were Published
2002-
2003
2003-
2004
2004-
2005
2005-
2006
2006-
2007
2007-
2008
2008-
2009
2009-
2010
2010-
2011
2011-
2012
2012-
2013
AMI = any mental illness; MDE = major depressive episode; NSDUH = National Survey on Drug Use and Health; SAE = small area estimation; SMI = serious mental illness.
1 The weight used for 2010 was based on projections from the 2000 census control totals, and the 2011 weight was based on projections from the 2010 census control totals. For SMI and AMI, the weights used for both years were based on the 2010 census control totals.
2 Variable selection was done using 2002-2003 NSDUH data for all outcomes with the following exception: For SMI, AMI, suicidal thoughts in the past year, and MDE, variable selection was done using 2008-2009 NSDUH data. Note that the 2005-2006, 2006-2007, and 2007-2008 MDE small area estimates were based on the variable selection done in 2008-2009.
3 For all outcomes except SMI and AMI, the 2010-2011 small area estimates were produced based on 2002-2003 variable selection (see note 2 for an exception). For SMI and AMI, variable selection was done using 2010-2011 NSDUH data.
4 When new variable selection was done using 2010-2011 NSDUH data, one source of predictor data was revised: The American Community Survey (ACS) estimates were used in place of 2000 long-form census estimates, which resulted in dropping several predictors and adding several new predictors.
5 The 2005-2006 through 2008-2009 small area estimates were revised and republished with falsified data removed. For more information, see Section A.7 of "2011-2012 NSDUH: Guide to State Tables and Summary of Small Area Estimation Methodology" at http://www.samhsa.gov/data/population-data-nsduh/reports?tab=33.
6 The 2008-2009, 2009-2010, and 2010-2011 small area estimates were revised and republished based on the new SMI and AMI variables. These new variables will continue to be used to produce SMI and AMI small area estimates. For more information, see Section B.11.1 of the document mentioned in this table's footnote 5.
7 An adjusted MDE variable was created for 2005-2008 that is comparable with the 2009-2013 MDE variables. Hence, MDE small area estimates were produced using the adjusted variable. For more information, see Section B.11.3 of the document mentioned in this table's footnote 5.
Weights Based on Projections from 2000 Census Control Totals X X X X X X X X X1    
Weights Based on Projections from 2010 Census Control Totals                 X1 X X
Small Area Estimates Produced Based on Variable Selection Done Using
   2002-2003 Data2
X X X X X X X X X3    
Small Area Estimates Produced Based on Variable Selection Done Using
   2010-2011 Data4
                X3 X X
Small Area Estimates Reproduced Using Data Omitting Falsified Data5       X X X X        
SMI and AMI Small Area Estimates Based on Updated 2013 Model6             X X X X
MDE Small Area Estimates Based on Adjusted MDE Variable7       X X X X        

Section D: References

Center for Behavioral Health Statistics and Quality. (2007). 2005 National Survey on Drug Use and Health: Methodological Resource Book (Section 20, Methamphetamine analysis report). Rockville, MD: Substance Abuse and Mental Health Services Administration.

Center for Behavioral Health Statistics and Quality. (2013). 2011 National Survey on Drug Use and Health: Methodological Resource Book. Rockville, MD: Substance Abuse and Mental Health Services Administration.

Center for Behavioral Health Statistics and Quality. (2014). 2012 National Survey on Drug Use and Health: Methodological Resource Book. Rockville, MD: Substance Abuse and Mental Health Services Administration.

Center for Behavioral Health Statistics and Quality. (in press). 2013 National Survey on Drug Use and Health: Methodological Resource Book. Rockville, MD: Substance Abuse and Mental Health Services Administration.

Folsom, R. E., Shah, B., & Vaish, A. (1999). Substance abuse in states: A methodological report on model based estimates from the 1994-1996 National Household Surveys on Drug Abuse. In Proceedings of the 1999 Joint Statistical Meetings, American Statistical Association, Survey Research Methods Section, Baltimore, MD (pp. 371-375). Alexandria, VA: American Statistical Association.

Ghosh, M. (1992). Constrained Bayes estimation with applications. Journal of the American Statistical Association, 87, 533-540.

Payton, M. E., Greenstone, M. H., & Schenker, N. (2003). Overlapping confidence intervals or standard error intervals: What do they mean in terms of statistical significance? Journal of Insect Science, 3, 34.

Raftery, A. E., & Lewis, S. (1992). How many iterations in the Gibbs sampler? In J. M. Bernardo, J. O. Berger, A. P. Dawid, & A. F. M. Smith (Eds.), Bayesian statistics 4 (pp. 763-774). London, England: Oxford University Press.

Schenker, N., & Gentleman, J. F. (2001). On judging the significance of differences by examining the overlap between confidence intervals. American Statistician, 55(3), 182-186.

Scheuren, F. (2004, June). What is a survey (2nd ed.). Retrieved September 17, 2014, from https://www.whatisasurvey.info/overview.htm

Shah, B. V., Barnwell, B. G., Folsom, R., & Vaish, A. (2000). Design consistent small area estimates using Gibbs algorithm for logistic models. In Proceedings of the 2000 Joint Statistical Meetings, American Statistical Association, Survey Research Methods Section, Indianapolis, IN (pp. 105-111). Alexandria, VA: American Statistical Association.

Singh, A. C., & Folsom, R. E. (2001, April 11-14). Hierarchical Bayes calibrated domain estimation via Metropolis-Hastings Step in MCMC with application to small areas. Presented at the International Conference on Small Area Estimation and Related Topics, Potomac, MD.

Wright, D. (2003a). State estimates of substance use from the 2001 National Household Survey on Drug Abuse: Volume I. Findings (HHS Publication No. SMA 03-3775, NHSDA Series H-19). Rockville, MD: Substance Abuse and Mental Health Services Administration, Office of Applied Studies.

Wright, D. (2003b). State estimates of substance use from the 2001 National Household Survey on Drug Abuse: Volume II. Individual state tables and technical appendices (HHS Publication No. SMA 03-3826, NHSDA Series H-20). Rockville, MD: Substance Abuse and Mental Health Services Administration, Office of Applied Studies.

Wright, D., & Sathe, N. (2005). State estimates of substance use from the 2002-2003 National Surveys on Drug Use and Health (HHS Publication No. SMA 05-3989, NSDUH Series H-26). Rockville, MD: Substance Abuse and Mental Health Services Administration, Office of Applied Studies.

Wright, D., & Sathe, N. (2006). State estimates of substance use from the 2003-2004 National Surveys on Drug Use and Health (HHS Publication No. SMA 06-4142, NSDUH Series H-29). Rockville, MD: Substance Abuse and Mental Health Services Administration, Office of Applied Studies.

Wright, D., Sathe, N., & Spagnola, K. (2007). State estimates of substance use from the 2004-2005 National Surveys on Drug Use and Health (HHS Publication No. SMA 07-4235, NSDUH Series H-31). Rockville, MD: Substance Abuse and Mental Health Services Administration, Office of Applied Studies.

Section E: List of Contributors

This National Survey on Drug Use and Health (NSDUH) document was prepared by the Center for Behavioral Health Statistics and Quality (CBHSQ), Substance Abuse and Mental Health Services Administration (SAMHSA), U.S. Department of Health and Human Services (HHS), and by RTI International (a registered trademark and a trade name of Research Triangle Institute), Research Triangle Park, North Carolina. Work by RTI was performed under Contract No. HHSS283201000003C.

At SAMHSA, Arthur Hughes reviewed the document and provided substantive revisions. At RTI, Neeraja S. Sathe and Kathryn Spagnola were responsible for the writing of the document, and Ralph E. Folsom and Akhil K. Vaish were responsible for the overall methodology and estimation for the model-based Bayes estimates and confidence intervals.

The following staff were responsible for generating the estimates and providing other support and analysis: Akhil K. Vaish, Neeraja S. Sathe, Kathryn Spagnola, and Brenda K. Porter. Ms. Spagnola provided oversight for production of the document. Richard S. Straw edited it; Debbie Bond and Valerie Garner formatted its text and tables; and Teresa F. Bass, Kimberly Cone, Danny Occoquan, Margaret Smith, Pamela Tuck, and Cheryl Velez prepared the Web versions. Justine L. Allpress and E. Andrew Jessup prepared and processed the maps used in the associated files.



End Notes

1 See http://www.samhsa.gov/data/population-data-nsduh/reports?tab=33.

2 For the purposes of this document, the term "State" refers to all 50 States and the District of Columbia.

3 RTI International is a registered trademark and a trade name of Research Triangle Institute, Research Triangle Park, North Carolina.

4 At http://www.samhsa.gov/data/population-data-nsduh/reports?tab=33, see "2011-2012 National Surveys on Drug Use and Health: Guide to State Tables and Summary of Small Area Estimation Methodology."

5 National small area estimates = Population-weighted averages of State-level small area estimates.

6 The census region-level estimates in the tables are population-weighted aggregates of the State estimates. The national estimates, however, are benchmarked to exactly match the design-based estimates.

7 At http://www.samhsa.gov/data/population-data-nsduh/reports?tab=33, see Tables 1 to 26 in "2012-2013 NSDUHs: Model-Based Estimated Totals (in Thousands) (50 States and the District of Columbia)."

8 Note that in the 2004-2005 NSDUH State report and prior reports, the term "prediction interval" (PI) was used to represent uncertainty in the State and regional estimates. However, that term also is used in other applications to estimate future values of a parameter of interest. That interpretation does not apply to NSDUH State report estimates; thus, "prediction interval" was dropped and replaced with "Bayesian confidence interval."

9 For MDE, estimates for individuals 12 or older are not included. For AMI, SMI, and thoughts of suicide, estimates for youths aged 12 to17 and individuals aged 12 or older are not included.

10 The SAE expert panel, convened in April 2002, had six members: Dr. William Bell of the U.S. Bureau of the Census; Partha Lahiri, Professor of the Joint Program in Survey Methodology at the University of Maryland at College Park; Professor Balgobin Nandram of Worcester Polytechnic Institute; Wesley Schaible, formerly Associate Commissioner for Research and Evaluation at the Bureau of Labor Statistics; Professor J. N. K. Rao of Carleton University; and Professor Alan Zaslavsky of Harvard University.

11 At http://www.samhsa.gov/data/population-data-nsduh/reports?tab=33, see "2012-2013 NSDUH: Model-Based Prevalence Estimates (50 States and the District of Columbia)" (Tables 1 to 26, by Age Group).

12 The use of mixed models (fixed and random effects) allows additional error components (random effects) to be included. These account for differences between States and within-State variations that are not taken into account by the predictor variables (fixed effects) alone. These models produce estimates that are approximately represented by a weighted combination of the direct estimate from the State data and a regression estimate from the national model, where the weights are obtained by minimizing the mean squared error of the small area estimate. It is also difficult if not impossible to produce valid mean squared errors for small area estimates based solely on a fixed-effect national regression model.

13 To increase the precision of estimated random effects at the within-State level, three SSRs were grouped together. Each of the 8 large sample States (i.e., California, Florida, Illinois, Michigan, New York, Ohio, Pennsylvania, and Texas) consists of 16 grouped SSRs, and the rest of the States and the District of Columbia each has 4 grouped SSRs.

14 For details on how the average annual rate of marijuana (incidence of marijuana) is calculated, see Section B.8 of "2011-2012 National Surveys on Drug Use and Health: Guide to State Tables and Summary of Small Area Estimation Methodology" at http://www.samhsa.gov/data/population-data-nsduh/reports?tab=33.

15 This file is available at http://www.samhsa.gov/data/population-data-nsduh/reports?tab=33.

16 See Table 9 of the "2012-2013 NSDUH: Model-Based Prevalence Estimates (50 States and the District of Columbia)" at http://www.samhsa.gov/data/population-data-nsduh/reports?tab=33.

17 See Table 9 of "2012-2013 NSDUHs: Model-Based Estimated Totals (in Thousands) (50 States and the District of Columbia)" at http://www.samhsa.gov/data/population-data-nsduh/reports?tab=33.



Long Descriptions

Section B.1

Long description, Equation B.1-1. The model is given by the following equation: log of pi sub a, i, j, k divided by 1 minus pi sub a, i, j, k is equal to the sum of three terms. The first term is given by x transpose sub a, i, j, k times beta sub a. The second term is eta sub a, i. And the third term is nu sub a, i, j.

Long description end. Return to Equation B.1-1.

Section B.4

Long description, Equation B.4-1. Lower sub s and a is defined as the exponent of capital L sub s and a divided by the sum of 1 and the exponent of capital L sub s and a. And upper sub s and a is defined as the exponent of capital U sub s and a divided by the sum of 1 and the exponent of capital U sub s and a.

Long description end. Return to Equation B.4-1.

Long description, Equation B.4-2. Capital L sub s and a is defined as the difference of two quantities. The first quantity is the natural logarithm of the ratio of Theta sub s and a and 1 minus Theta sub s and a. The second quantity is the product of 1.96 and the square root of MSE sub s and a, which is the mean squared error for State-s and age group-a.

Long description end. Return to Equation B.4-2.

Long description, Equation B.4-3. Capital U sub s and a is defined as the sum of two quantities. The first quantity is the natural logarithm ofthe ratio of Theta sub s and a and 1 minus Theta sub s and a. The second quantity is the product of 1.96 and the square root of MSE sub s and a, which is the mean squared error for State-s and age group-a.

Long description end. Return to Equation B.4-3.

Long description, Equation B.4-4. The mean squared error, MSE sub s and a, is defined as the sum of two quantities. The first quantity is the square of the difference of two parts. Part 1 is defined as the natural logarithm of the ratio of capital P sub s and a and 1 minus capital P sub s and a. Part 2 is defined as the natural logarithm of the ratio of Theta sub s and a and 1 minus Theta sub s and a. The second quantity is the posterior variance of the natural logarithm of the ratio of capital P sub s and a and 1 minus capital P sub s and a.

Long description end. Return to Equation B.4-4.

Section B.6

Long description, Equation B.6-1. The covariance between the natural logarithm of Theta 1 hat and the natural logarithm of Theta 2 hat is equal to the correlation between the natural logarithm of Theta 1 hat and the natural logarithm of Theta 2 hat multiplied by the square root of the product of the variance v of the natural logarithm of Theta 1 hat and the variance v of the natural logarithm of Theta 2 hat.

Long description end. Return to Equation B.6-1.

Long description, Equation B.6-2. Variance v of the natural logarithm of Theta sub i is equal to the square of quantity q. Quantity q is calculated as the difference between capital U sub i and capital L sub i divided by 2 times 1.96, where i takes values 1 and 2.

Long description end. Return to Equation B.6-2.

Long description, Equation B.6-3. Capital U sub 1 is defined as the natural logarithm of the ratio of 0.1618 and 1 minus 0.1618, which is negative 1.6449.

Capital L sub 1 is defined as the natural logarithm of the ratio of 0.1144 and 1 minus 0.1144, which is negative 2.0466.

Long description end. Return to Equation B.6-3.

Long description, Equation B.6-4. Capital U sub 2 is defined as the natural logarithm of the ratio of 0.1197 and 1 minus 0.1197, which is negative 1.9953.

Capital L sub 2 is defined as the natural logarithm of the ratio of 0.0833 and 1 minus 0.0833, which is negative 2.3983.

Long description end. Return to Equation B.6-4.

Long description, Equation B.6-5. 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 p1 sub a is 0.1364 and p 2 sub a is 0.1000. The estimate lor hat sub a is calculated to be negative 0.3517.

Long description end. Return to Equation B.6-5.

Long description, Equation B.6-6. The variance v of the natural logarithm of Theta 1 hat is equal to the square of quantity q. Quantity q is calculated as the difference between capital U sub 1 and capital L sub 1 divided by the product of 2 and 1.96. Here, capital U sub 1 is negative 1.6449, and capital L sub 1 is negative 2.0466. Hence, the variance v of the natural logarithm of Theta 1 hat is calculated to be 0.01050.

Long description end. Return to Equation B.6-6.

Long description, Equation B.6-7. The variance v of the natural logarithm of Theta 2 hat is equal to the square of quantity q. Quantity q is calculated as the difference between capital U sub 2 and capital L sub 2 divided by the product of 2 and 1.96. Here, capital U sub 2 is negative 1.9953, and capital L sub 2 is negative 2.3983. Hence, the variance v of the natural logarithm of Theta 2 hat is calculated to be 0.01057.

Long description end. Return to Equation B.6-7.

Long description, Equation B.6-8. 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 v of the natural logarithm of Theta 1 hat and the variance v of the natural logarithm of Theta 2 hat, where lor hat sub a is negative 0.3517, the variance v of the natural logarithm of Theta 1 hat is 0.01050, and the variance v of the natural logarithm of Theta 2 hat is 0.01057. The statistic z is calculated to be negative 2.4229.

Long description end. Return to Equation B.6-8.

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