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2004 State Estimates of Substance Use and Mental Health
(from the 2003-2004 National Surveys on Drug Use & Health)

bulletNational data      bulletState level data       bulletMetropolitan and other subState area data

Appendix A: State Estimation Methodology

This report includes estimates of 22 substance use measures (see Section A.1) using the combined data from the 2003 and 2004 National Surveys on Drug Use and Health (NSDUHs). In addition to the 21 substance use measures for which age group–specific State estimates were produced and documented in the 2003 State report (Wright & Sathe, 2005), there is a new measure, past year nonmedical pain reliever use, introduced in this report. Also included in this report are estimates of change between 2002-2003 and 2003-2004 State estimates. This report is similar to the 2000 and 2001 State reports (Wright, 2002a, 2002b, 2003a, 2003b) that contained age group–specific State estimates obtained by pooling 1999–2000 and 2000–2001 National Household Survey on Drug Abuse (NHSDA)8 data, respectively. The 2001 State report also contained estimates of change between the 1999–2000 and 2000–2001 data for the 12 common substance use measures. As discussed in Chapter 1 (Section 1.1), several changes were introduced to the survey in 2002; thus, estimates for 2001 and prior years are not comparable with estimates from 2002 and later years.

The survey-weighted hierarchical Bayes (SWHB) methodology used in the production of State estimates from the 1999–2003 surveys also was used in the production of the 2003-2004 State estimates. The SWHB methodology is described in Appendix E of the 2001 State report (Wright, 2003b) and by Folsom, Shah, and Vaish (1999). The list of predictors used in the 2003-2004 small area estimation (SAE) modeling is given in Section A.2. The methodology used to select relevant predictors remains similar to the one used in prior years and is described in brief in Section A.3. The goals of SAE modeling, general model description, and the implementation of SAE modeling remain the same and are described in Appendix E of the 2001 State report (Wright, 2003b). At the end of this appendix, tables showing the 2002, 2003, 2004, pooled 2002-2003, and pooled 2003-2004 survey response rates are included (Table s A.1 to A.12).

Small area estimates obtained using the SWHB methodology are design consistent (i.e., for States with large sample sizes, the small area estimates are close to the robust design-based estimates). The State small area estimates when aggregated by using the appropriate population totals result in national small area estimates that are very close to the national design-based estimates. However, for numerous reasons (including internal consistency), it is desirable to have national small area estimates exactly match the national design-based estimates. Beginning in 2002, exact benchmarking was introduced as described in Section A.4. The definition and explanation of the formula used in estimating the marijuana incidence rate is given in Section A.5.

Included in this report for the first time are estimates of underage (ages 12 to 20) alcohol use and binge alcohol use. For all other outcomes the age groups of interest were 12 to 17, 18 to 25, and 26 or older. As alcohol consumption is expected to differ significantly across the 18 to 25 age group due to the legalization of alcohol at age 21, it was decided that it would be useful to produce small area estimates for persons aged 12 to 20. A short description of methodology used to produce underage drinking estimates is described in Section A.6.

Section A.7 discusses how serious psychological distress (SPD) estimates were produced. The methodology used to produce estimates of change between the 2002-2003 and the 2003-2004 State estimates is described in Section A.8.

A.1 Variables Modeled

The 2004 NSDUH data were pooled with the 2003 NSDUH data, and age group–specific State estimates for 22 binary (0,1) outcome variables were produced and presented in this report. The estimates of change between the 2002-2003 and 2003-2004 State estimates also were produced for the following outcomes:

  1. past month use of any illicit drug,
  2. past year use of marijuana,
  3. past month use of marijuana,
  4. perception of great risk of smoking marijuana once a month,
  5. average annual rate of first use of marijuana,
  6. past month use of any illicit drug 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 any tobacco product,
  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 any illicit drug dependence or abuse,
  18. past year any illicit drug dependence,
  19. past year dependence on or abuse of any illicit drug or alcohol,
  20. needing but not receiving treatment for illicit drug problems in the past year,
  21. needing but not receiving treatment for alcohol problems in the past year, and
  22. past year serious psychological distress (SPD).

A.2 Predictors Used in Mixed Logistic Regression Models

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

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

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

2000 Census Data
Description Level
% Population who dropped out of high school Tract
% Housing units built in 1940–1949 Tract
% Persons 16–64 with a work disability Tract
% Hispanics who are Cuban Tract
% Females 16 years or older in labor force Tract
% Females never married Tract
% Females separated/divorced/widowed/other Tract
% One-person households Tract
% Female head of household, no spouse, child less than equal to symbol18 Tract
% Males 16 years or older in labor force Tract
% Males never married Tract
% Males separated/divorced/widowed/other Tract
% Housing units built in 1939 or earlier Tract
Average persons per room Tract
% Families below poverty level Tract
% Households with public assistance income Tract
% Housing units rented Tract
% Population 9–12 years of school, no high school diploma Tract
% Population 0–8 years of school Tract
% Population with associate's degree Tract
% Population some college and no degree Tract
% Population with bachelor's, graduate, professional degree Tract
Median rents for rental units Tract
Median value of owner-occupied housing units Tract
Median household income Tract

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

Other Categorical Data
Description Source Level
=1 if Hispanic, =0 otherwise Sample Person
=1 if non-Hispanic Black, =0 otherwise Sample Person
=1 if non-Hispanic Other, =0 otherwise Sample Person
=1 if male, =0 if female Sample Person
=1 if MSA with 1 million +, =0 otherwise 2000 Census County
=1 if MSA with <1 million, =0 otherwise 2000 Census County
=1 if Non-MSA Urban, =0 otherwise 2000 Census Tract
=1 if Urban Area, =0 if Rural Area 2000 Census Tract
=1 if no Cubans in tract, =0 otherwise 2000 Census Tract
=1 if no arrests for dangerous non-narcotics,
=0 otherwise
UCR County

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

A.3 Selection of Independent Variables for the Models

The State estimates for past year nonmedical use of pain relievers (ANLYR) were not produced in prior years. Hence, in order to be consistent with the other set of outcomes, the fixed-effect predictors for ANLYR were selected using the pooled 2002-2003 NSDUH data. These fixed-effect predictors were selected based on the steps detailed in Section A.3 of Wright and Sathe (2005), and their updated versions were used to produce 2003-2004 State estimates for ANLYR. For all the other outcome variables, no new variable selection was done. The updated versions of fixed-effect predictors that were used in modeling the 2002-2003 data were used to model the 2003-2004 data. Because the interest was to estimate change between the 2002-2003 and 2003-2004 State estimates, the same set of fixed-effect predictors was used for producing both sets of estimates.

A.4 Benchmarking the Age Group–Specific Small Area Estimates

The self-calibration built into the SWHB solution ensures that the population-weighted average of the State small area estimates will closely match the national design-based estimates. Given the self-calibration ensured by the SWHB solution, for State reports prior to 2002, the standard Bayes prescription was followed; specifically, the posterior mean was used for the SAE point estimate, and the tail percentiles of the posterior distribution were used for the prediction 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 State-by-age group small area estimates (for 2003-2004) is adjusted by adding the common factor image representing deltaa = (Da - Pa), where Da is the design-based national prevalence estimate and Pa is the population-weighted mean of the State small area estimates (Psa) for age group-a. The exactly benchmarked State-s and age group-a small area estimates then are given by image representing thetasa = Psa + image representing deltaa. Experience with such additive adjustments suggests that the resulting exactly benchmarked State small area estimates always will be between 0 and 100 percent because the SWHB self-calibration ensures that the adjustment factor is small relative to the size of the State-level small area estimates.

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

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

where

Lsa = log[image representing thetasa/(1 - image representing thetasa)] - 1.96 * image representing the square root of M S E sub s a,

Usa = log[image representing thetasa/(1 - image representing thetasa)] + 1.96 * image representing the square root of M S E sub s a, and

MSEsa = (log[Psa/(1 - Psa)]- log[image representing thetasa/(1 - image representing thetasa)])2 + posterior variance of log[Psa/(1 - Psa)].

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

A.5 Calculation of Average Annual Incidence of Marijuana Use

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

Average annual incidence rate = {(Number of marijuana initiates in past 24 months) /
[(Number of marijuana initiates in past 24 months * 0.5) +
Number of persons who never used marijuana
]} / 2.

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

The count of persons who first used marijuana in the past 2 years is based on a "moving" 2–year period that ranges over 3 calendar years. Subjects were asked when they first used marijuana. If a person indicated first use of marijuana between the day of the interview and 2 years prior, the person was included in the count. Thus, it is possible for a person interviewed in the first part of 2004 to indicate first use as early as the first part of 2002 or as late as the first part of 2004. Similarly, a subject interviewed in the last part of 2004 could indicate first use as early as the last part of 2002 or as late as the last part of 2004. Therefore, in the 2004 survey, the reported period of first use ranged from early 2002 to late 2004 and was "centered" in 2003. About half of the 12 to 17 year olds who reported first use in the past 24 months reported first use in 2003, while a quarter each reported first use in 2002 and 2004. Persons who responded in 2004 that they had never used marijuana were included in the count of "never used." Similarly, reports of first use in past 24 months from the 2003 survey ranged from early 2000 to late 2003 and were centered in 2002. Half of the 12 to 17 year olds who reported first use in the past 24 months reported first use in 2002, while a quarter each reported first use in 2000 and 2003. Note that only incidence rates for marijuana use are provided in this report.

A.6 Underage Drinking

To obtain small area estimates for persons aged 12 to 20 for past month alcohol and binge alcohol use, a separate set of models was fit for these two outcomes for the 12 to 17 age group and the 18 to 20 age group. New variable selection (using the same methodology as described in Section A.3) was done for the 18 to 20 age group. Even though separate models were fit for the 12 to 17 age group along with the 18 to 20 year olds, no new variable selection was done for the 12 to 17 age group. Model-based estimates for persons aged 12 to 20 were produced by taking the population-weighted average of the individual age group (12 to 17 and 18 to 20) estimates. Estimates for underage drinking for past month alcohol and binge alcohol use were benchmarked to match national design-based estimates for that age group using the process described in Section A.4. Estimates of change between 2002-2003 and 2003-2004 underage drinking State estimates also are presented in this report.

A.7 Serious Psychological Distress

In 2004, SPD was measured using the K6 screening instrument for nonspecific psychological distress (Furukawa, Kessler, Slade, & Andrews, 2003; Kessler et al., 2003). In previous NSDUH reports, the K6 scale was referred to as a measure of serious mental illness (SMI). SMI was first measured by the National Household Survey on Drug Abuse (NHSDA) in 2001 for all persons aged 18 or older. SAMHSA's official definition of adults with SMI, based on a notice published in the Federal Register (SAMHSA, Center for Mental Health Services, 1993), is as follows:

Pursuant to section 1912(c) of the Public Health Service Act, adults with serious mental illness (SMI) are persons: (1) age 18 and over and (2) who currently have, or at any time during the past year, had a diagnosable mental, behavioral, or emotional disorder of sufficient duration to meet diagnostic criteria specified within DSM-IV or their ICD-9-CM equivalent (and subsequent revisions) with the exception of DSM-IV "V" codes, substance use disorders, and developmental disorders, which are excluded, unless they co-occur with another diagnosable serious mental illness. (3) That has resulted in functional impairment which substantially interferes with or limits one or more major life activities.

In prior NSDUH reports, the K6 scale was used to measure SMI according to the above definition. The K6 consists of six questions that ask respondents how frequently they experienced symptoms of psychological distress during the 1 month in the past year when they were at their worst emotionally. The use of this scale for SMI was based on a methodological study designed to evaluate several screening scales for measuring SMI in NSDUH. These scales consisted of a truncated version of the World Health Organization (WHO) Composite International Diagnostic Interview Short Form (CIDI-SF) scale (Kessler, Andrews, Mroczek, Üstün, & Wittchen, 1998), the K10/K6 scale of nonspecific psychological distress (Furukawa et al., 2003), and the WHO Disability Assessment Schedule (WHO-DAS) (Rehm et al., 1999).

In the 2003 NSDUH, the mental health module contained a truncated version of the CIDI-SF scale, the K10/K6 scale, and the WHO-DAS scale to mirror the questions used by Kessler et al. (2003). Thus, the module contained a broad array of questions about mental health (i.e., panic attacks, depression, mania, phobias, generalized anxiety, posttraumatic stress disorder, and use of mental health services) that preceded the K6 items, and the four extra questions in the K10 scale were interspersed among the items in the K6 scale. To create a score, the responses to six items on the K6 scales were coded from 0 to 4. Summing across all the responses resulted in a score with a range from 0 to 24. Respondents with a total score of 13 or greater were classified as having a past year SMI. This cutpoint was chosen to equalize false positives and false negatives.

In the 2004 NSDUH, however, the sample of respondents aged 18 or older was split evenly between the "long-form" module, which included all items in the mental health module used in the 2003 NSDUH (sample A), and a "short-form" module consisting only of the K6 items (sample B). The short-form version was introduced to reduce interview time, removing questions that were not needed for estimation of SMI, and to provide space for a new module on depression. Inclusion of the long-form version in half of the sample was to measure the impact on the K6 responses of changing the context of the K6.

Results from the 2004 NSDUH showed large differences at the national level between the two samples in both the K6 total score and the proportion of respondents with a K6 total score of 13 or greater. These differences were most pronounced in the 18 to 25 age group. These differences suggested that the K6 scale was not context-independent; that is, respondents appeared to respond to the K6 items differently depending on whether the scale was preceded by a broad array of other mental health questions. There were other concerns as well. For example, the face validity of the K6 scale suggests that it may be more useful as a measure of psychological distress or of affective-mood and anxiety-type disorders. A direct consequence of these concerns was that a decision was made that the K6 would no longer be used to measure SMI. However, the K6 data are still useful as an indicator of psychological distress (see Section B.4.4 of OAS, 2005c).

The 2004 national SPD estimates therefore were based only on data from sample A (respondents who got the long-form module). For the purpose of producing State-level estimates for this report, however, an adjusted measure of SPD, which was produced for the entire sample of respondents aged 18 or older in 2004, was used, and SMI data from 2003 were pooled with data using this adjusted measure of SPD from 2004. The adjustment made to the SPD score on the short-form module is described in brief here.

A logistic regression model was used to estimate differences between the short- and long-form SPD prevalence rates (i.e., propensities). Several demographic and drug use covariates were included in the model, and it was found that the propensities varied according to race/ethnicity and age group. Five propensity strata based on race/ethnicity and age group were constructed from the results of this analysis. Tests suggested that a gross adjustment approach might be more appropriate than an item-based adjustment approach. As a consequence, the cumulative distribution function (CDF) (gross) adjustment method was applied within each of the five propensity strata, and the method appeared to work quite well in adjusting the marginal estimates of a number of important demographic and drug use variables. This method also was shown to be fairly robust to the way the propensity strata were defined.

Consideration also was given to the use of this logistic regression model to provide adjustments, as well as to provide propensity estimates. However, although this approach was useful for estimating propensities, it was not useful in determining how to adjust individual short-form respondents' SPD prevalence rates to match those of long-form respondents within covariate profiles. Using this approach, the only way to match prevalence rates would be to use long-form prevalence estimates in place of short-form prevalence estimates within covariate profiles. This is equivalent to discarding all short-form data after the logistic regression model has been fitted. A similar argument applies to the use of polytomous logistic regression models to estimate differences between short- and long-form SPD scores.

Before the CDF adjustment method was developed, consideration also was given to ad hoc adjustments to differences between short- and long-form SPD scores within covariate profiles, estimated from, say, polytomous regression models. For example, if the average difference between short- and long-form SPD scores for a particular covariate profile (e.g., white females aged 12 to 17 in the West) was 1.7, then all short-form SPD scores would be reduced by that amount in the profile. However, there are a couple of problems with this ad hoc approach. First, this approach is equivalent to shifting the entire distribution of short-form scores to the left, creating a set of adjusted values ranging from –1.7 to 22.3 instead of 0 to 24. Second, although this approach might force SPD scores to match on average within a profile, there is no guarantee that they would match at the SPD cutpoint of 13, which defines prevalence rates. A variation to this approach would be to multiply short-form scores by a factor that forced the scores to match on average, but this is equivalent to rescaling the short-form distribution so that all scores are shrunk toward zero. Neither of these ad hoc methods was optimal. Hence, the CDF adjustment method was used to transform the distribution of scores obtained from the short-form module to match that of the long-form module such that the distributional properties of the SPD scores from the short-form module matched the distributional properties of the SPD scores from the long-form module, without the scores matching exactly.

Adjusted short-form SPD scores and prevalence rates (based on the CDF adjustment method) were not used to derive national estimates for the 2004 survey. National estimates used a much finer categorization for some of the demographic and substance use variables than were used in the creation of the adjusted SPD outcome, and at these finer categorizations some notable discrepancies were observed between adjusted short-form and corresponding long-form prevalence rates. For this reason, national estimates of SPD scores and prevalence rates were derived from only long-form data.

Adjusted short-form SPD scores and prevalence rates were used to derive State-level estimates based on pooled 2003 and 2004 survey data. Because State-level estimates used a much coarser categorization of demographic and substance use variables than national estimates, the problem of discrepancies observed at the finer categorization of national estimates did not occur. In addition, unlike national estimates, which were based on large sample sizes, State-level estimates were typically based on small sample sizes. Hence, it was necessary to use all the data available, including the adjusted short-form data. For details on how the CDF adjustment was implemented, see Aldworth, Chromy, Foster, Heller, and Novak (2005).

A.8 Measuring Change in State Estimates between 2002-2003 and 2003-2004

The estimates of change between State estimates displayed in Appendix C are based on the 2002 through 2004 NSDUHs. The State estimates for 2002-2003 are the previously published model-based small area estimates (see Wright & Sathe, 2005). The State estimates for 2003-2004 are the small area estimates given in Appendix B. The moving average State prevalence estimates for the overlapping 2002-2003 and 2003-2004 time periods were obtained from independent applications of RTI's SWHB methodology; that is, the 2003-2004 models were fit independently of the previously fitted 2002-2003 models. This independent analysis approach was followed because there was no desire to revise the previously published estimates. Moreover, the same fixed predictor variables were used in the 2002-2003 and 2003-2004 models, but annual updates were made when more current versions became available. The age group–specific fixed predictor variables were defined at five levels (namely, person-level, 2000 decennial census block group-level, tract-level, county-level, and State-level). Also, each age group model had 51 State-level random effects and 300 substate region–level random effects.

To estimate change in State estimates, let image representing pisa(1) and image representing pisa(2) denote 2002-2003 and 2003-2004 prevalence rates, respectively, for State-s and age group-a. The change between image representing pisa(1) and image representing pisa(2) is defined in terms of the log-odds ratio (lorsa) as opposed to the simple difference because the posterior distribution of the lorsa is closer to Gaussian than the posterior distribution of the simple difference (image representing pisa(2)image representing pisa(1)). The lorsa is defined as

Equation A-1.     D

The p value given in the Appendix C tables is computed to test the null hypothesis of no change (i.e., image representing pisa(2) = image representing pisa(1) or equivalently lorsa = 0. An estimate of lorsa is given by

Equation A-2,     D

where the psa(1) are previously published 2002-2003 State estimates and the psa(2) are the 2003-2004 State estimates presented in this report (see Appendix B). To compute the variance of The estimate of the log-odds ratio, lor hat, sub s and a, i.e., Variance v of the estimate of the log-odds ratio, lor hat, sub s and a, let Theta 1 hat is defined as the ratio of p 1 sub s and a and 1 minus p 1 sub s and a and Theta 2 hat is defined as the ratio of p 2 sub s and a and 1 minus  p 2 sub s and a, then

Equation A-7,     D

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

Equation A-11.     D

Note that the variance of the logarithm of Theta 1 hat and variance of the logarithm of Theta 2 hat used here to calculate Variance v of the estimate of the log-odds ratio, lor hat, sub s and a are the same variances used in calculating the previously published 2002-2003 prediction intervals (PIs) and the 2003-2004 PIs given in this report, respectively.

The correlation between logarithm of Theta 1 hat and logarithm of Theta 2 hat was obtained by simultaneously modeling the 2002, 2003, and 2004 NSDUH data. This simultaneous modeling approach was adopted based on the results of the validation study (see Appendix E, Section E.2., of Wright, 2003b) conducted for measuring change in 1999–2000 and 2000-2001 State estimates. For this simultaneous model, four age groups by 3 years (i.e., 12 subpopulation–specific models) were fitted, each with its own set of fixed and random effects. In this case, the general covariance matrices for the State and substate random effects were 12 by 12 matrices corresponding to the 12 element (age group by year) vectors of random effects. Note that the survey-weighted Bernoulli-type log likelihood employed in SWHB methodology was appropriate for this simultaneous model because the 12 age group by year subpopulations were nonoverlapping. The correlation [logarithm of Theta 1 hat, logarithm of Theta 2 hat] was approximated by the correlation calculated using the posterior distributions of log[image representing pisa(1) /(1 - image representing pisa(1))] and log[image representing pisa(2) /(1 - image representing pisa(2))] from the simultaneous model.

To calculate the p value for testing the null hypothesis of no change (lorsa = 0), it was assumed that The estimate of the log-odds ratio, lor hat, sub s and a, is assumed to follow a normal distribution with mean zero and variance v of the estimate of the log-odds ratio, lor hat, sub s and a.. Then, the p value = P[Z greater than or equal to symbol abs(z)], where Z is a standard normal random variate, Quantity z is the estimate of the log-odds ratio, lor hat, sub s and a, divided by the square root of the variance v of the estimate of the log-odds ratio, lor hat, sub s and a., and abs(z) denotes the absolute value of Z.

Table A.1 Sample Sizes, Weighted Screening and Interview Response Rates, and Population Estimates, by State, for Persons Aged 12 or Older: 2002
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
Overall 178,013 150,162 136,349 90.72% 80,581 68,126 235,143,245 78.56% 71.27%
Alabama 2,403 2,028 1,852 91.31% 1,103 960 3,686,602 81.85% 74.74%
Alaska 2,408 1,898 1,751 92.13% 1,067 915 496,025 82.05% 75.59%
Arizona 2,346 1,908 1,770 92.66% 1,078 924 4,361,020 79.66% 73.81%
Arkansas 2,540 2,102 2,005 95.28% 1,054 877 2,216,033 76.09% 72.50%
California 8,425 7,601 6,816 89.60% 4,363 3,599 28,231,483 74.93% 67.14%
Colorado 2,099 1,827 1,664 91.01% 1,087 914 3,655,496 81.67% 74.32%
Connecticut 2,718 2,440 2,227 91.44% 1,188 977 2,827,588 76.73% 70.16%
Delaware 2,585 2,116 1,908 89.64% 1,159 964 665,926 78.55% 70.42%
District of Columbia 3,701 3,100 2,608 84.08% 979 864 482,635 84.79% 71.29%
Florida 10,742 8,622 7,723 89.47% 4,340 3,653 13,832,088 77.23% 69.10%
Georgia 2,206 1,896 1,660 87.50% 1,066 897 6,842,168 77.76% 68.04%
Hawaii 2,276 1,942 1,759 90.38% 1,111 925 962,485 76.50% 69.14%
Idaho 2,033 1,634 1,515 92.80% 1,052 907 1,074,515 82.81% 76.86%
Illinois 9,263 8,181 6,986 85.45% 4,613 3,729 10,258,735 75.32% 64.36%
Indiana 2,261 1,961 1,856 94.61% 1,123 945 5,019,711 77.60% 73.42%
Iowa 2,252 1,939 1,835 94.68% 1,028 894 2,440,614 84.42% 79.93%
Kansas 1,933 1,683 1,579 93.86% 1,041 898 2,202,285 81.96% 76.92%
Kentucky 2,641 2,273 2,155 94.79% 1,098 909 3,395,143 79.55% 75.41%
Louisiana 2,189 1,816 1,701 93.64% 1,070 930 3,607,669 84.44% 79.07%
Maine 2,828 2,290 2,082 90.85% 1,017 906 1,104,764 87.35% 79.36%
Maryland 1,984 1,801 1,610 89.42% 1,039 919 4,449,299 81.71% 73.07%
Massachusetts 2,567 2,216 1,930 86.95% 1,142 916 5,387,071 71.93% 62.55%
Michigan 9,820 8,073 7,414 91.75% 4,432 3,792 8,255,399 81.82% 75.06%
Minnesota 2,173 1,895 1,765 93.09% 996 873 4,154,504 83.23% 77.48%
Mississippi1 2,261 1,750 1,508 86.58% 988 839 2,307,320 77.37% 66.99%
Missouri 2,725 2,236 2,098 93.87% 1,039 890 4,656,459 82.05% 77.02%
Montana 2,772 2,174 2,057 94.64% 1,075 914 759,543 81.98% 77.58%
Nebraska 1,954 1,746 1,652 94.59% 1,042 891 1,411,983 82.01% 77.57%
Nevada1 2,534 2,069 1,956 94.67% 1,147 954 1,742,004 73.54% 69.62%
New Hampshire 2,597 2,154 1,966 91.27% 1,092 910 1,065,165 78.10% 71.28%
New Jersey 2,554 2,290 2,042 89.28% 1,065 854 7,075,581 74.61% 66.61%
New Mexico1 1,950 1,586 1,236 77.38% 794 674 1,500,281 81.83% 63.32%
New York 10,480 9,032 7,516 83.31% 4,615 3,716 15,882,822 73.14% 60.94%
North Carolina 2,289 1,940 1,792 92.57% 1,046 902 6,726,205 80.99% 74.98%
North Dakota 2,307 1,873 1,770 94.52% 1,011 913 527,574 84.91% 80.26%
Ohio 9,194 7,970 7,476 93.76% 4,221 3,554 9,369,125 78.58% 73.68%
Oklahoma 2,300 1,932 1,791 92.64% 1,100 922 2,822,615 78.63% 72.84%
Oregon 2,456 2,158 2,019 93.43% 1,071 917 2,916,974 80.74% 75.44%
Pennsylvania 10,104 8,482 7,710 90.86% 4,251 3,606 10,298,942 79.56% 72.29%
Rhode Island 2,458 2,117 1,883 89.14% 1,107 925 896,699 74.12% 66.07%
South Carolina 2,332 1,824 1,729 94.77% 1,091 913 3,371,646 80.90% 76.67%
South Dakota 2,053 1,717 1,632 95.03% 1,013 914 619,768 86.83% 82.52%
Tennessee 2,732 2,357 2,212 92.82% 1,057 920 4,766,688 83.26% 77.28%
Texas 7,730 6,408 5,960 93.05% 4,212 3,649 17,207,615 82.73% 76.98%
Utah 1,487 1,336 1,264 94.52% 990 889 1,807,003 84.94% 80.29%
Vermont 2,410 1,914 1,803 94.36% 1,013 896 525,061 88.02% 83.06%
Virginia 2,426 2,104 1,873 89.03% 1,069 884 5,862,299 75.20% 66.95%
Washington 2,454 2,002 1,832 91.35% 1,079 901 4,962,300 78.20% 71.44%
West Virginia 2,763 2,299 2,169 94.33% 1,059 898 1,527,885 79.91% 75.38%
Wisconsin 2,152 1,709 1,587 92.87% 1,029 887 4,511,335 82.44% 76.56%
Wyoming 2,146 1,741 1,645 94.49% 1,059 907 413,099 79.40% 75.02%

Table A.2 Sample Sizes, Weighted Interview Response Rates, and Population Estimates, by State and Three Age Groups: 2002
State 12–17 18–25 26+
Total Selected Total Responded Population Estimate Weighted Interview Response Rate Total Selected Total Responded Population Estimate Weighted Interview Response Rate Total Selected Total Responded Population Estimate Weighted Interview Response Rate
Overall 26,230 23,659 24,753,586 89.99% 27,216 23,271 31,024,280 85.16% 27,135 21,196 179,365,379 75.81%
Alabama 361 331 378,922 92.11% 370 324 497,362 86.86% 372 305 2,810,318 79.54%
Alaska 393 353 70,050 90.00% 353 305 58,061 85.24% 321 257 367,914 79.65%
Arizona 360 330 477,791 91.87% 346 303 593,368 86.21% 372 291 3,289,861 76.81%
Arkansas 385 340 232,228 88.68% 287 256 299,329 89.70% 382 281 1,684,476 71.97%
California 1,439 1,304 3,119,651 90.54% 1,459 1,224 3,910,445 83.32% 1,465 1,071 21,201,387 70.93%
Colorado 349 309 386,275 88.67% 380 317 488,328 82.92% 358 288 2,780,893 80.55%
Connecticut 369 335 297,332 90.70% 423 341 314,467 82.08% 396 301 2,215,789 74.39%
Delaware 392 350 64,655 88.74% 344 285 87,670 83.05% 423 329 513,601 76.54%
District of Columbia 354 326 33,553 91.52% 284 256 73,858 89.63% 341 282 375,224 83.16%
Florida 1,335 1,213 1,332,058 91.10% 1,523 1,317 1,526,407 86.35% 1,482 1,123 10,973,623 74.40%
Georgia 339 309 740,287 91.81% 332 281 931,197 85.79% 395 307 5,170,684 74.28%
Hawaii 337 306 106,624 92.14% 351 300 123,983 85.94% 423 319 731,877 72.94%
Idaho 346 314 128,019 89.27% 348 302 162,155 87.73% 358 291 784,341 80.82%
Illinois 1,475 1,304 1,081,426 88.16% 1,620 1,301 1,366,021 79.82% 1,518 1,124 7,811,288 72.73%
Indiana 351 323 537,937 90.92% 415 346 699,137 84.53% 357 276 3,782,636 74.38%
Iowa 343 312 247,154 91.07% 315 278 348,675 89.36% 370 304 1,844,784 82.50%
Kansas 324 301 242,248 93.27% 374 321 316,706 86.26% 343 276 1,643,332 79.59%
Kentucky 376 325 317,845 84.53% 342 288 457,462 84.10% 380 296 2,619,836 78.11%
Louisiana 344 311 408,864 91.56% 359 310 533,943 86.92% 367 309 2,664,863 82.83%
Maine 337 310 107,138 92.04% 336 295 128,854 88.23% 344 301 868,772 86.65%
Maryland 376 346 472,125 91.83% 331 302 525,127 90.68% 332 271 3,452,047 78.58%
Massachusetts 402 353 502,081 87.86% 350 285 670,475 84.04% 390 278 4,214,516 68.13%
Michigan 1,458 1,301 892,683 89.81% 1,570 1,371 1,078,221 87.65% 1,404 1,120 6,284,494 79.57%
Minnesota 318 289 447,909 90.45% 352 317 564,444 90.66% 326 267 3,142,151 80.71%
Mississippi1 342 312 257,043 91.28% 314 274 346,485 87.36% 332 253 1,703,792 72.96%
Missouri 364 328 489,034 90.34% 335 289 621,802 85.99% 340 273 3,545,624 80.20%
Montana 383 348 82,057 91.77% 309 262 101,662 85.48% 383 304 575,825 80.05%
Nebraska 353 317 152,803 90.07% 327 280 202,014 86.69% 362 294 1,057,166 79.90%
Nevada1 396 359 182,000 91.12% 356 308 208,607 86.18% 395 287 1,351,398 69.19%
New Hampshire 344 300 112,627 88.19% 405 343 126,521 84.89% 343 267 826,017 75.60%
New Jersey 324 290 712,611 89.35% 383 308 775,060 79.98% 358 256 5,587,910 71.75%
New Mexico1 235 213 176,221 89.25% 296 250 207,372 85.15% 263 211 1,116,688 80.02%
New York 1,426 1,241 1,564,858 86.12% 1,649 1,344 2,026,299 80.59% 1,540 1,131 12,291,665 70.20%
North Carolina 354 325 677,525 89.91% 341 292 866,820 84.88% 351 285 5,181,860 79.25%
North Dakota 357 337 54,725 94.54% 332 307 81,994 92.38% 322 269 390,856 81.86%
Ohio 1,358 1,221 991,716 89.83% 1,429 1,224 1,217,589 85.83% 1,434 1,109 7,159,820 75.66%
Oklahoma 362 308 305,129 84.00% 385 333 408,904 85.11% 353 281 2,108,583 76.37%
Oregon 354 322 297,634 90.31% 361 308 379,401 85.13% 356 287 2,239,939 78.69%
Pennsylvania 1,395 1,243 1,025,357 89.15% 1,489 1,293 1,270,338 86.58% 1,367 1,070 8,003,247 77.15%
Rhode Island 365 334 83,814 91.12% 357 306 124,681 84.64% 385 285 688,204 70.20%
South Carolina 339 304 336,271 90.47% 412 343 458,511 82.93% 340 266 2,576,865 79.24%
South Dakota 359 343 70,145 95.94% 320 286 89,870 89.15% 334 285 459,753 85.02%
Tennessee 381 352 472,625 91.52% 260 228 610,807 87.69% 416 340 3,683,257 81.42%
Texas 1,347 1,224 2,004,787 90.81% 1,427 1,251 2,477,451 87.79% 1,438 1,174 12,725,377 80.50%
Utah 316 309 227,575 97.46% 324 289 363,300 88.95% 350 291 1,216,128 81.15%
Vermont 339 312 53,892 92.84% 367 314 68,583 86.88% 307 270 402,586 87.51%
Virginia 297 278 600,443 93.43% 412 341 728,869 83.24% 360 265 4,532,987 71.75%
Washington 298 264 530,187 86.66% 361 304 640,479 84.62% 420 333 3,791,634 76.00%
West Virginia 339 305 139,243 89.85% 336 292 193,439 87.55% 384 301 1,195,204 77.58%
Wisconsin 317 280 482,456 87.97% 380 338 613,508 87.26% 332 269 3,415,371 80.85%
Wyoming 323 295 45,958 91.71% 385 339 58,222 88.37% 351 273 308,919 75.91%

Table A.3 Sample Sizes, Weighted Screening and Interview Response Rates, and Population Estimates, by State, for Persons Aged 12 or Older: 2003
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
Overall 170,762 143,485 130,605 90.72% 81,631 67,784 237,682,009 77.39% 70.21%
Alabama 2,071 1,712 1,558 91.14% 1,029 879 3,699,723 79.60% 72.55%
Alaska 2,314 1,814 1,666 91.97% 1,098 883 505,278 75.00% 68.98%
Arizona 2,159 1,757 1,662 94.64% 1,057 897 4,473,518 81.20% 76.85%
Arkansas 2,258 1,850 1,767 95.53% 1,092 922 2,228,670 79.84% 76.27%
California 7,687 6,858 6,015 86.86% 4,471 3,600 28,673,990 73.76% 64.07%
Colorado 2,225 1,855 1,709 92.06% 1,103 911 3,701,560 78.79% 72.53%
Connecticut 2,623 2,288 2,073 90.56% 1,128 933 2,880,493 76.25% 69.06%
Delaware 2,419 1,936 1,774 91.59% 1,105 911 671,922 75.12% 68.80%
District of Columbia 3,692 3,078 2,576 83.69% 1,116 949 476,873 80.38% 67.27%
Florida 10,451 8,453 7,575 89.77% 4,414 3,541 14,145,707 73.68% 66.14%
Georgia 2,112 1,734 1,612 92.81% 1,088 902 6,951,437 79.46% 73.74%
Hawaii 2,259 1,953 1,767 90.25% 1,142 928 1,013,259 73.21% 66.07%
Idaho 1,998 1,596 1,509 94.45% 1,112 912 1,099,895 77.63% 73.32%
Illinois 9,163 8,128 6,803 83.45% 4,652 3,711 10,319,948 74.36% 62.05%
Indiana 2,046 1,741 1,637 94.11% 1,082 903 5,049,910 79.37% 74.69%
Iowa 2,035 1,829 1,721 94.16% 993 884 2,448,928 85.81% 80.79%
Kansas 2,042 1,744 1,638 93.94% 1,041 875 2,209,221 81.11% 76.20%
Kentucky 2,266 1,991 1,878 94.25% 1,102 908 3,381,254 75.69% 71.34%
Louisiana 2,084 1,757 1,637 93.12% 1,095 943 3,618,197 81.80% 76.17%
Maine 2,827 2,240 2,045 91.21% 1,094 928 1,113,100 82.07% 74.86%
Maryland 1,899 1,673 1,475 88.04% 1,000 863 4,510,290 82.58% 72.70%
Massachusetts 2,413 2,129 1,878 88.16% 1,220 964 5,377,359 75.04% 66.16%
Michigan 9,000 7,447 6,709 90.14% 4,353 3,667 8,316,442 79.06% 71.26%
Minnesota 2,029 1,801 1,673 92.73% 1,052 909 4,193,331 82.14% 76.17%
Mississippi 2,196 1,732 1,650 95.33% 1,078 899 2,311,859 78.81% 75.13%
Missouri 2,495 2,042 1,912 93.64% 1,105 932 4,683,914 81.99% 76.77%
Montana 2,384 1,871 1,766 94.40% 1,068 911 767,946 79.57% 75.12%
Nebraska 1,996 1,716 1,622 94.51% 1,071 918 1,418,952 79.62% 75.25%
Nevada 2,071 1,751 1,663 94.91% 1,072 902 1,818,116 79.78% 75.71%
New Hampshire 2,015 1,688 1,568 92.94% 1,112 910 1,082,138 76.29% 70.90%
New Jersey 2,564 2,287 1,981 86.56% 1,126 883 7,118,305 72.97% 63.17%
New Mexico 2,260 1,822 1,740 95.42% 1,132 944 1,520,180 77.03% 73.50%
New York 9,973 8,575 7,205 83.97% 4,609 3,634 15,948,708 71.96% 60.42%
North Carolina 2,239 1,852 1,753 94.65% 1,086 904 6,805,722 79.21% 74.98%
North Dakota 2,072 1,714 1,619 94.57% 977 867 525,140 87.43% 82.69%
Ohio 8,874 7,690 7,246 94.17% 4,313 3,559 9,433,820 75.91% 71.49%
Oklahoma 2,455 1,972 1,812 91.80% 1,042 871 2,846,785 78.62% 72.17%
Oregon 2,102 1,853 1,760 94.94% 1,095 912 2,970,969 79.79% 75.75%
Pennsylvania 9,866 8,252 7,482 90.76% 4,214 3,572 10,356,055 80.56% 73.12%
Rhode Island 2,255 1,991 1,772 88.58% 1,141 914 903,348 75.20% 66.61%
South Carolina 2,205 1,807 1,723 95.45% 1,109 920 3,384,520 79.64% 76.02%
South Dakota 2,154 1,749 1,660 94.78% 980 881 621,498 86.26% 81.76%
Tennessee 2,290 1,978 1,864 94.27% 1,004 856 4,823,157 79.89% 75.32%
Texas 7,901 6,466 6,079 94.03% 4,231 3,566 17,432,369 79.14% 74.42%
Utah 1,623 1,392 1,325 95.14% 995 898 1,816,737 87.98% 83.71%
Vermont 2,638 2,047 1,909 93.19% 1,092 917 530,133 79.87% 74.43%
Virginia 2,168 1,908 1,667 87.33% 1,076 907 5,951,031 78.61% 68.65%
Washington 2,475 2,033 1,920 94.43% 1,128 941 5,053,331 78.65% 74.28%
West Virginia 2,923 2,384 2,236 93.83% 1,058 871 1,534,650 78.86% 74.00%
Wisconsin 2,282 1,793 1,655 92.28% 1,046 887 4,546,217 77.76% 71.76%
Wyoming 2,214 1,756 1,659 94.48% 1,032 885 416,105 84.33% 79.67%

Table A.4 Sample Sizes, Weighted Interview Response Rates, and Population Estimates, by State and Three Age Groups: 2003
State 12–17 18–25 26+
Total Selected Total Responded Population Estimate Weighted Interview Response Rate Total Selected Total Responded Population Estimate Weighted Interview Response Rate Total Selected Total Responded Population Estimate Weighted Interview Response Rate
Overall 25,387 22,696 24,995,357 89.57% 27,259 22,941 31,728,286 83.47% 28,985 22,147 180,958,366 74.63%
Alabama 324 297 382,688 92.61% 394 340 501,543 86.10% 311 242 2,815,492 76.33%
Alaska 348 298 68,750 86.80% 378 314 67,522 82.66% 372 271 369,006 71.30%
Arizona 346 314 493,252 91.48% 377 317 611,163 84.15% 334 266 3,369,104 78.82%
Arkansas 352 320 233,744 91.18% 356 301 304,728 85.42% 384 301 1,690,198 77.24%
California 1,381 1,236 3,161,827 89.71% 1,463 1,195 3,928,708 81.65% 1,627 1,169 21,583,456 69.91%
Colorado 327 292 385,020 88.53% 379 305 499,513 79.29% 397 314 2,817,027 77.43%
Connecticut 313 279 292,982 88.47% 423 353 331,774 83.64% 392 301 2,255,738 73.62%
Delaware 344 305 68,298 88.69% 373 315 89,106 84.55% 388 291 514,518 71.54%
District of Columbia 370 326 32,832 88.64% 373 326 73,453 87.28% 373 297 370,589 78.33%
Florida 1,377 1,203 1,360,537 87.23% 1,418 1,171 1,626,149 81.73% 1,619 1,167 11,159,021 71.02%
Georgia 342 308 756,648 88.43% 323 267 959,782 84.93% 423 327 5,235,007 77.32%
Hawaii 388 353 100,981 90.91% 329 275 121,594 83.63% 425 300 790,684 69.33%
Idaho 331 299 128,037 90.50% 348 287 166,977 81.40% 433 326 804,881 74.87%
Illinois 1,423 1,238 1,083,365 86.69% 1,537 1,242 1,395,959 81.48% 1,692 1,231 7,840,623 71.43%
Indiana 338 308 545,217 90.65% 365 292 710,330 79.87% 379 303 3,794,364 77.73%
Iowa 329 304 245,539 89.91% 333 292 353,759 87.71% 331 288 1,849,631 84.81%
Kansas 317 280 240,109 87.93% 363 309 322,145 84.48% 361 286 1,646,967 79.40%
Kentucky 349 306 337,609 86.98% 349 293 451,685 83.75% 404 309 2,591,960 72.97%
Louisiana 353 321 405,066 92.36% 382 335 541,507 86.50% 360 287 2,671,623 79.32%
Maine 345 304 110,584 87.73% 388 330 132,168 86.27% 361 294 870,349 80.84%
Maryland 318 292 481,268 90.86% 280 237 547,577 83.87% 402 334 3,481,445 81.21%
Massachusetts 344 303 514,569 88.08% 414 324 674,611 76.98% 462 337 4,188,180 73.23%
Michigan 1,336 1,196 898,823 89.25% 1,536 1,323 1,104,530 86.20% 1,481 1,148 6,313,089 76.36%
Minnesota 393 357 445,182 91.19% 311 270 581,147 85.52% 348 282 3,167,002 80.08%
Mississippi 310 284 257,972 93.11% 347 293 348,335 85.15% 421 322 1,705,552 75.67%
Missouri 363 312 493,755 86.13% 385 329 635,283 85.62% 357 291 3,554,877 80.74%
Montana 308 272 81,338 88.05% 395 350 105,014 88.66% 365 289 581,594 76.60%
Nebraska 325 295 152,127 91.02% 404 351 207,187 86.79% 342 272 1,059,638 76.51%
Nevada 306 278 187,341 90.35% 364 312 222,655 86.49% 402 312 1,408,120 77.26%
New Hampshire 328 288 114,288 88.06% 399 332 132,490 83.61% 385 290 835,361 73.63%
New Jersey 326 288 726,704 88.67% 373 287 807,111 75.67% 427 308 5,584,490 70.62%
New Mexico 354 319 177,001 90.44% 365 316 213,899 87.67% 413 309 1,129,280 73.13%
New York 1,392 1,232 1,559,994 88.11% 1,534 1,227 2,046,657 80.51% 1,683 1,175 12,342,057 68.43%
North Carolina 324 285 693,740 88.12% 420 352 884,534 84.21% 342 267 5,227,448 77.02%
North Dakota 285 259 54,050 91.09% 309 276 82,629 89.55% 383 332 388,461 86.51%
Ohio 1,356 1,199 984,255 88.08% 1,435 1,229 1,244,999 85.43% 1,522 1,131 7,204,566 72.56%
Oklahoma 374 329 300,218 88.45% 316 272 413,370 84.45% 352 270 2,133,197 75.75%
Oregon 345 313 296,519 90.45% 377 309 390,879 82.15% 373 290 2,283,571 78.02%
Pennsylvania 1,367 1,232 1,030,859 90.72% 1,350 1,160 1,309,752 85.92% 1,497 1,180 8,015,444 78.25%
Rhode Island 361 308 86,777 85.36% 375 313 127,775 84.68% 405 293 688,797 71.97%
South Carolina 343 307 354,988 89.36% 373 311 458,297 82.69% 393 302 2,571,235 77.80%
South Dakota 301 281 69,339 94.03% 344 315 92,111 92.37% 335 285 460,048 83.73%
Tennessee 346 324 474,491 93.33% 270 223 632,850 80.82% 388 309 3,715,817 77.93%
Texas 1,279 1,153 2,033,118 90.38% 1,414 1,222 2,546,961 86.63% 1,538 1,191 12,852,291 75.82%
Utah 304 286 231,320 94.61% 321 301 357,456 94.31% 370 311 1,227,961 85.08%
Vermont 351 306 53,957 87.12% 355 306 71,119 85.94% 386 305 405,058 77.88%
Virginia 324 298 614,433 91.96% 368 311 749,393 82.44% 384 298 4,587,205 76.33%
Washington 369 344 527,057 93.61% 390 321 666,923 82.04% 369 276 3,859,351 75.89%
West Virginia 324 281 139,083 86.58% 371 306 195,671 82.42% 363 284 1,199,896 77.34%
Wisconsin 291 271 482,916 92.43% 405 349 627,502 85.36% 350 267 3,435,798 74.33%
Wyoming 343 313 44,796 92.11% 308 255 60,007 84.13% 381 317 311,302 83.18%

Table A.5 Sample Sizes, Weighted Screening and Interview Response Rates, and Population Estimates, by State, for Persons Aged 12 or Older: 2004
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
Overall 169,514 142,612 130,130 90.92% 81,973 67,760 240,514,815 77.00% 70.01%
Alabama 1,991 1,611 1,477 91.72% 1,055 880 3,740,924 74.76% 68.57%
Alaska 1,902 1,525 1,399 91.61% 1,078 894 511,059 79.21% 72.57%
Arizona 2,226 1,858 1,750 94.21% 1,119 903 4,616,821 77.92% 73.41%
Arkansas 2,369 1,933 1,833 94.83% 1,062 900 2,259,150 80.09% 75.95%
California 7,911 6,957 6,192 88.60% 4,631 3,725 29,016,735 72.88% 64.57%
Colorado 2,207 1,822 1,712 93.92% 1,135 934 3,735,710 77.90% 73.17%
Connecticut 2,493 2,209 2,013 90.99% 1,098 897 2,901,872 75.85% 69.02%
Delaware 2,253 1,954 1,794 91.90% 1,144 932 688,666 77.70% 71.41%
District of Columbia 3,155 2,606 2,242 86.24% 1,041 903 466,433 82.55% 71.19%
Florida 10,456 8,488 7,581 88.99% 4,526 3,662 14,478,448 73.89% 65.75%
Georgia 2,141 1,752 1,597 91.32% 1,054 890 7,063,198 80.38% 73.41%
Hawaii 1,959 1,715 1,575 91.94% 1,088 903 1,014,184 77.42% 71.18%
Idaho 2,015 1,704 1,607 94.31% 1,051 902 1,125,089 82.42% 77.74%
Illinois 8,457 7,458 6,342 85.01% 4,444 3,575 10,387,581 75.12% 63.86%
Indiana 2,176 1,833 1,742 95.05% 1,085 891 5,098,367 77.64% 73.79%
Iowa 1,990 1,745 1,641 94.14% 1,039 890 2,468,073 81.10% 76.35%
Kansas 2,294 1,953 1,841 94.22% 993 828 2,226,734 78.58% 74.04%
Kentucky 2,372 2,059 1,949 94.67% 1,144 933 3,421,489 73.82% 69.88%
Louisiana 2,106 1,713 1,614 94.17% 1,082 933 3,646,863 81.16% 76.43%
Maine 2,731 2,168 2,025 93.40% 1,064 896 1,127,062 81.46% 76.08%
Maryland 2,122 1,855 1,617 86.77% 1,039 901 4,557,984 81.39% 70.63%
Massachusetts 2,218 1,895 1,686 89.13% 1,087 877 5,380,703 76.92% 68.56%
Michigan 9,530 7,969 7,155 89.78% 4,490 3,670 8,364,197 75.61% 67.88%
Minnesota 2,001 1,714 1,578 91.98% 1,066 907 4,237,627 83.72% 77.00%
Mississippi 1,931 1,549 1,482 95.71% 1,053 914 2,341,802 80.45% 77.00%
Missouri 2,190 1,872 1,764 94.23% 1,104 897 4,751,346 77.96% 73.46%
Montana 2,511 1,990 1,874 94.18% 1,080 907 781,536 79.58% 74.95%
Nebraska 2,044 1,729 1,629 94.21% 1,072 897 1,430,465 80.70% 76.03%
Nevada 1,903 1,641 1,552 93.71% 1,053 888 1,898,843 78.32% 73.39%
New Hampshire 2,348 1,908 1,765 92.38% 1,114 904 1,095,589 76.40% 70.58%
New Jersey 2,764 2,359 2,033 85.50% 1,153 886 7,172,774 72.04% 61.60%
New Mexico 2,190 1,799 1,719 95.54% 1,072 922 1,552,672 80.98% 77.37%
New York 10,475 8,940 7,372 82.28% 4,585 3,638 15,978,304 73.79% 60.72%
North Carolina 2,185 1,733 1,635 94.33% 1,029 869 6,927,805 79.39% 74.89%
North Dakota 2,576 2,128 2,020 94.95% 1,071 911 530,030 81.21% 77.11%
Ohio 8,599 7,463 7,026 94.14% 4,404 3,613 9,489,788 76.91% 72.40%
Oklahoma 2,382 1,889 1,769 93.71% 1,054 867 2,867,524 76.21% 71.42%
Oregon 2,234 1,931 1,825 94.50% 1,108 910 3,001,872 76.30% 72.10%
Pennsylvania 9,599 8,236 7,448 90.44% 4,360 3,590 10,399,693 77.05% 69.68%
Rhode Island 2,030 1,785 1,588 89.11% 1,126 911 907,154 76.31% 68.00%
South Carolina 2,392 1,946 1,844 94.73% 1,042 885 3,437,860 81.78% 77.47%
South Dakota 2,024 1,674 1,594 95.24% 1,034 893 630,156 82.20% 78.30%
Tennessee 2,387 2,049 1,933 94.37% 1,023 896 4,888,070 85.51% 80.70%
Texas 7,923 6,599 6,254 94.72% 4,334 3,631 17,783,855 79.21% 75.03%
Utah 1,718 1,464 1,389 94.70% 1,040 910 1,851,896 83.73% 79.28%
Vermont 2,689 1,954 1,820 93.02% 1,087 924 534,195 81.75% 76.04%
Virginia 2,060 1,773 1,587 89.40% 1,080 902 6,027,395 79.88% 71.41%
Washington 1,998 1,769 1,677 94.81% 1,086 886 5,134,850 75.97% 72.03%
West Virginia 2,721 2,173 2,049 94.31% 1,058 909 1,543,726 79.17% 74.67%
Wisconsin 2,338 1,944 1,805 92.86% 1,118 917 4,597,266 77.89% 72.33%
Wyoming 2,228 1,819 1,715 94.28% 1,018 857 423,382 81.54% 76.88%

Table A.6 Sample Sizes, Weighted Interview Response Rates, and Population Estimates, by State and Three Age Groups: 2004
State 12–17 18–25 26+
Total Selected Total Responded Population Estimate Weighted Interview Response Rate Total Selected Total Responded Population Estimate Weighted Interview Response Rate Total Selected Total Responded Population Estimate Weighted Interview Response Rate
Overall 25,141 22,309 25,214,390 88.56% 27,408 23,075 32,193,946 83.87% 29,424 22,376 183,106,479 74.22%
Alabama 335 300 380,438 88.15% 317 277 506,024 87.42% 403 303 2,854,462 70.97%
Alaska 343 301 68,234 87.37% 376 308 71,635 80.38% 359 285 371,190 77.66%
Arizona 355 307 504,134 86.71% 356 280 632,441 79.72% 408 316 3,480,247 76.36%
Arkansas 336 301 232,624 89.62% 372 312 309,270 83.12% 354 287 1,717,256 78.00%
California 1,408 1,251 3,256,862 88.81% 1,523 1,259 3,971,071 82.89% 1,700 1,215 21,788,802 68.82%
Colorado 339 309 392,567 92.63% 435 358 502,509 81.78% 361 267 2,840,634 75.05%
Connecticut 351 310 297,475 88.74% 341 290 340,627 82.95% 406 297 2,263,770 72.90%
Delaware 344 296 67,017 86.70% 402 330 91,920 81.90% 398 306 529,729 75.84%
District of Columbia 324 291 33,936 90.50% 369 328 67,513 88.13% 348 284 364,984 80.63%
Florida 1,422 1,248 1,392,381 88.13% 1,426 1,197 1,690,586 83.29% 1,678 1,217 11,395,480 70.76%
Georgia 310 281 770,391 90.24% 384 325 974,428 85.42% 360 284 5,318,379 77.85%
Hawaii 314 290 100,117 92.32% 374 313 121,874 84.55% 400 300 792,193 74.27%
Idaho 310 279 127,641 90.53% 362 318 170,720 87.99% 379 305 826,729 80.03%
Illinois 1,316 1,166 1,096,436 89.10% 1,483 1,214 1,405,081 81.40% 1,645 1,195 7,886,063 72.15%
Indiana 339 284 547,820 80.66% 370 321 712,431 87.14% 376 286 3,838,117 75.51%
Iowa 354 319 241,677 90.80% 322 283 354,834 89.24% 363 288 1,871,562 78.38%
Kansas 309 279 235,602 90.08% 331 278 326,635 84.04% 353 271 1,664,497 75.58%
Kentucky 338 297 336,208 88.01% 379 324 454,337 85.35% 427 312 2,630,944 70.36%
Louisiana 315 288 401,563 91.61% 384 345 546,374 89.71% 383 300 2,698,926 77.88%
Maine 325 292 109,324 88.79% 378 310 136,314 82.23% 361 294 881,424 80.39%
Maryland 331 311 490,535 94.06% 350 299 564,517 86.07% 358 291 3,502,932 78.60%
Massachusetts 320 280 511,108 87.59% 372 304 678,194 81.46% 395 293 4,191,401 74.97%
Michigan 1,441 1,273 906,283 88.40% 1,503 1,266 1,113,043 83.80% 1,546 1,131 6,344,871 72.25%
Minnesota 346 305 440,475 87.61% 333 280 594,051 85.11% 387 322 3,203,101 82.96%
Mississippi 292 276 255,992 94.84% 415 367 350,329 88.32% 346 271 1,735,480 76.64%
Missouri 349 296 488,189 84.08% 355 293 650,694 81.04% 400 308 3,612,463 76.59%
Montana 320 277 78,581 87.14% 373 324 108,216 85.88% 387 306 594,739 77.30%
Nebraska 266 236 149,210 88.31% 413 342 210,327 82.97% 393 319 1,070,927 79.27%
Nevada 307 281 197,330 89.52% 356 307 234,194 87.69% 390 300 1,467,319 75.18%
New Hampshire 340 292 115,175 86.06% 335 285 136,081 83.41% 439 327 844,334 74.06%
New Jersey 308 265 741,001 83.21% 393 297 825,494 76.88% 452 324 5,606,279 70.03%
New Mexico 341 315 173,978 91.56% 333 296 222,316 88.48% 398 311 1,156,379 77.93%
New York 1,345 1,144 1,583,424 85.11% 1,564 1,275 2,048,409 81.31% 1,676 1,219 12,346,471 71.15%
North Carolina 336 307 710,225 91.75% 338 285 893,651 84.47% 355 277 5,323,929 76.67%
North Dakota 350 314 51,236 89.71% 368 315 83,256 84.18% 353 282 395,539 79.50%
Ohio 1,418 1,243 982,106 87.60% 1,428 1,186 1,258,053 83.17% 1,558 1,184 7,249,629 74.37%
Oklahoma 325 288 293,667 89.22% 386 324 417,990 85.22% 343 255 2,155,867 72.18%
Oregon 349 311 297,975 88.86% 365 309 394,016 85.49% 394 290 2,309,881 72.97%
Pennsylvania 1,314 1,177 1,037,595 89.81% 1,433 1,197 1,321,982 84.56% 1,613 1,216 8,040,116 74.30%
Rhode Island 342 285 87,882 85.57% 377 326 127,105 86.38% 407 300 692,166 73.19%
South Carolina 349 307 357,948 87.80% 292 258 463,134 89.41% 401 320 2,616,779 79.59%
South Dakota 277 257 67,385 91.02% 387 346 94,182 89.49% 370 290 468,590 79.79%
Tennessee 295 273 476,738 91.61% 341 298 640,352 88.72% 387 325 3,770,980 84.21%
Texas 1,350 1,205 2,044,166 89.33% 1,444 1,236 2,607,359 85.92% 1,540 1,190 13,132,330 76.31%
Utah 348 324 227,860 93.80% 343 301 354,811 86.85% 349 285 1,269,225 80.91%
Vermont 354 318 53,165 89.86% 350 295 70,039 87.11% 383 311 410,991 79.80%
Virginia 296 268 619,572 89.10% 374 310 765,684 80.74% 410 324 4,642,140 78.68%
Washington 345 301 527,781 86.17% 378 311 685,109 80.79% 363 274 3,921,960 73.76%
West Virginia 313 285 137,455 91.56% 355 319 194,513 90.54% 390 305 1,211,758 76.03%
Wisconsin 382 339 474,936 89.82% 342 273 638,512 80.49% 394 305 3,483,818 75.77%
Wyoming 305 267 42,970 89.29% 328 281 61,714 86.59% 385 309 318,699 79.61%

Table A.7 Sample Sizes, Weighted Screening and Interview Response Rates, and Population Estimates, by State, for Persons Aged 12 or Older: 2002-2003
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
Overall 348,775 293,647 266,954 90.72% 162,212 135,910 236,412,627 77.97% 70.74%
Alabama 4,474 3,740 3,410 91.23% 2,132 1,839 3,693,162 80.75% 73.66%
Alaska 4,722 3,712 3,417 92.05% 2,165 1,798 500,651 78.39% 72.16%
Arizona 4,505 3,665 3,432 93.64% 2,135 1,821 4,417,269 80.40% 75.28%
Arkansas 4,798 3,952 3,772 95.40% 2,146 1,799 2,222,351 77.97% 74.38%
California 16,112 14,459 12,831 88.24% 8,834 7,199 28,452,737 74.34% 65.59%
Colorado 4,324 3,682 3,373 91.53% 2,190 1,825 3,678,528 80.24% 73.44%
Connecticut 5,341 4,728 4,300 90.97% 2,316 1,910 2,854,040 76.50% 69.60%
Delaware 5,004 4,052 3,682 90.65% 2,264 1,875 668,924 76.87% 69.69%
District of Columbia 7,393 6,178 5,184 83.89% 2,095 1,813 479,754 82.57% 69.27%
Florida 21,193 17,075 15,298 89.62% 8,754 7,194 13,988,898 75.42% 67.59%
Georgia 4,318 3,630 3,272 90.17% 2,154 1,799 6,896,803 78.64% 70.91%
Hawaii 4,535 3,895 3,526 90.31% 2,253 1,853 987,872 74.86% 67.61%
Idaho 4,031 3,230 3,024 93.67% 2,164 1,819 1,087,205 80.16% 75.08%
Illinois 18,426 16,309 13,789 84.44% 9,265 7,440 10,289,341 74.83% 63.19%
Indiana 4,307 3,702 3,493 94.36% 2,205 1,848 5,034,811 78.51% 74.08%
Iowa 4,287 3,768 3,556 94.41% 2,021 1,778 2,444,771 85.10% 80.35%
Kansas 3,975 3,427 3,217 93.90% 2,082 1,773 2,205,753 81.55% 76.58%
Kentucky 4,907 4,264 4,033 94.50% 2,200 1,817 3,388,199 77.58% 73.32%
Louisiana 4,273 3,573 3,338 93.37% 2,165 1,873 3,612,933 83.10% 77.59%
Maine 5,655 4,530 4,127 91.03% 2,111 1,834 1,108,932 84.60% 77.01%
Maryland 3,883 3,474 3,085 88.72% 2,039 1,782 4,479,795 82.16% 72.90%
Massachusetts 4,980 4,345 3,808 87.56% 2,362 1,880 5,382,215 73.50% 64.36%
Michigan 18,820 15,520 14,123 90.94% 8,785 7,459 8,285,920 80.41% 73.13%
Minnesota 4,202 3,696 3,438 92.92% 2,048 1,782 4,173,917 82.68% 76.83%
Mississippi1 4,457 3,482 3,158 91.05% 2,066 1,738 2,309,589 78.12% 71.13%
Missouri 5,220 4,278 4,010 93.76% 2,144 1,822 4,670,187 82.02% 76.90%
Montana 5,156 4,045 3,823 94.52% 2,143 1,825 763,745 80.81% 76.38%
Nebraska 3,950 3,462 3,274 94.55% 2,113 1,809 1,415,467 80.81% 76.40%
Nevada1 4,605 3,820 3,619 94.79% 2,219 1,856 1,780,060 76.75% 72.76%
New Hampshire 4,612 3,842 3,534 92.10% 2,204 1,820 1,073,652 77.14% 71.05%
New Jersey 5,118 4,577 4,023 87.85% 2,191 1,737 7,096,943 73.75% 64.79%
New Mexico1 4,210 3,408 2,976 86.36% 1,926 1,618 1,510,230 79.39% 68.56%
New York 20,453 17,607 14,721 83.66% 9,224 7,350 15,915,765 72.55% 60.70%
North Carolina 4,528 3,792 3,545 93.61% 2,132 1,806 6,765,963 80.14% 75.02%
North Dakota 4,379 3,587 3,389 94.55% 1,988 1,780 526,357 86.19% 81.49%
Ohio 18,068 15,660 14,722 93.97% 8,534 7,113 9,401,472 77.23% 72.57%
Oklahoma 4,755 3,904 3,603 92.22% 2,142 1,793 2,834,700 78.62% 72.51%
Oregon 4,558 4,011 3,779 94.16% 2,166 1,829 2,943,971 80.26% 75.57%
Pennsylvania 19,970 16,734 15,192 90.81% 8,465 7,178 10,327,498 80.06% 72.70%
Rhode Island 4,713 4,108 3,655 88.86% 2,248 1,839 900,023 74.65% 66.33%
South Carolina 4,537 3,631 3,452 95.11% 2,200 1,833 3,378,083 80.27% 76.34%
South Dakota 4,207 3,466 3,292 94.90% 1,993 1,795 620,633 86.56% 82.15%
Tennessee 5,022 4,335 4,076 93.47% 2,061 1,776 4,794,923 81.58% 76.25%
Texas 15,631 12,874 12,039 93.53% 8,443 7,215 17,319,992 80.94% 75.70%
Utah 3,110 2,728 2,589 94.83% 1,985 1,787 1,811,870 86.50% 82.03%
Vermont 5,048 3,961 3,712 93.78% 2,105 1,813 527,597 83.70% 78.49%
Virginia 4,594 4,012 3,540 88.20% 2,145 1,791 5,906,665 76.93% 67.85%
Washington 4,929 4,035 3,752 92.88% 2,207 1,842 5,007,815 78.42% 72.84%
West Virginia 5,686 4,683 4,405 94.09% 2,117 1,769 1,531,267 79.40% 74.70%
Wisconsin 4,434 3,502 3,242 92.57% 2,075 1,774 4,528,776 80.13% 74.18%
Wyoming 4,360 3,497 3,304 94.48% 2,091 1,792 414,602 81.81% 77.29%

Table A.8 Sample Sizes, Weighted Interview Response Rates, and Population Estimates, by State and Three Age Groups: 2002-2003
State 12–17 18–25 26+
Total Selected Total Responded Population Estimate Weighted Interview Response Rate Total Selected Total Responded Population Estimate Weighted Interview Response Rate Total Selected Total Responded Population Estimate Weighted Interview Response Rate
Overall 51,617 46,355 24,874,472 89.78% 54,475 46,212 31,376,283 84.31% 56,120 43,343 180,161,872 75.22%
Alabama 685 628 380,805 92.36% 764 664 499,453 86.47% 683 547 2,812,905 77.99%
Alaska 741 651 69,400 88.47% 731 619 62,791 83.85% 693 528 368,460 75.27%
Arizona 706 644 485,521 91.67% 723 620 602,265 85.15% 706 557 3,329,482 77.74%
Arkansas 737 660 232,986 89.91% 643 557 302,029 87.50% 766 582 1,687,337 74.60%
California 2,820 2,540 3,140,739 90.12% 2,922 2,419 3,919,577 82.48% 3,092 2,240 21,392,421 70.41%
Colorado 676 601 385,648 88.60% 759 622 493,921 81.06% 755 602 2,798,960 79.01%
Connecticut 682 614 295,157 89.62% 846 694 323,120 82.88% 788 602 2,235,763 74.02%
Delaware 736 655 66,477 88.72% 717 600 88,388 83.80% 811 620 514,059 74.11%
District of Columbia 724 652 33,192 90.09% 657 582 73,655 88.48% 714 579 372,907 80.72%
Florida 2,712 2,416 1,346,297 89.13% 2,941 2,488 1,576,278 83.99% 3,101 2,290 11,066,322 72.68%
Georgia 681 617 748,467 90.08% 655 548 945,489 85.36% 818 634 5,202,846 75.87%
Hawaii 725 659 103,803 91.52% 680 575 122,789 84.82% 848 619 761,280 71.13%
Idaho 677 613 128,028 89.90% 696 589 164,566 84.54% 791 617 794,611 77.77%
Illinois 2,898 2,542 1,082,396 87.42% 3,157 2,543 1,380,990 80.66% 3,210 2,355 7,825,956 72.07%
Indiana 689 631 541,577 90.78% 780 638 704,733 82.13% 736 579 3,788,500 76.11%
Iowa 672 616 246,347 90.49% 648 570 351,217 88.54% 701 592 1,847,207 83.63%
Kansas 641 581 241,178 90.61% 737 630 319,425 85.37% 704 562 1,645,149 79.50%
Kentucky 725 631 327,727 85.79% 691 581 454,574 83.93% 784 605 2,605,898 75.48%
Louisiana 697 632 406,965 91.95% 741 645 537,725 86.71% 727 596 2,668,243 81.04%
Maine 682 614 108,861 89.84% 724 625 130,511 87.24% 705 595 869,560 83.60%
Maryland 694 638 476,696 91.35% 611 539 536,352 87.15% 734 605 3,466,746 79.97%
Massachusetts 746 656 508,325 87.97% 764 609 672,543 80.52% 852 615 4,201,348 70.71%
Michigan 2,794 2,497 895,753 89.53% 3,106 2,694 1,091,376 86.92% 2,885 2,268 6,298,792 77.93%
Minnesota 711 646 446,545 90.82% 663 587 572,795 88.02% 674 549 3,154,577 80.40%
Mississippi1 652 596 257,508 92.18% 661 567 347,410 86.29% 753 575 1,704,672 74.39%
Missouri 727 640 491,394 88.24% 720 618 628,542 85.79% 697 564 3,550,250 80.48%
Montana 691 620 81,697 89.94% 704 612 103,338 87.09% 748 593 578,710 78.40%
Nebraska 678 612 152,465 90.55% 731 631 204,600 86.74% 704 566 1,058,402 78.19%
Nevada1 702 637 184,670 90.73% 720 620 215,631 86.34% 797 599 1,379,759 73.33%
New Hampshire 672 588 113,457 88.12% 804 675 129,505 84.22% 728 557 830,689 74.56%
New Jersey 650 578 719,658 89.01% 756 595 791,085 77.76% 785 564 5,586,200 71.15%
New Mexico1 589 532 176,611 89.85% 661 566 210,636 86.39% 676 520 1,122,984 76.48%
New York 2,818 2,473 1,562,426 87.12% 3,183 2,571 2,036,478 80.55% 3,223 2,306 12,316,861 69.31%
North Carolina 678 610 685,632 89.01% 761 644 875,677 84.54% 693 552 5,204,654 78.20%
North Dakota 642 596 54,387 92.84% 641 583 82,312 90.99% 705 601 389,658 84.24%
Ohio 2,714 2,420 987,986 88.97% 2,864 2,453 1,231,294 85.63% 2,956 2,240 7,182,193 74.08%
Oklahoma 736 637 302,673 86.17% 701 605 411,137 84.77% 705 551 2,120,890 76.06%
Oregon 699 635 297,076 90.38% 738 617 385,140 83.63% 729 577 2,261,755 78.35%
Pennsylvania 2,762 2,475 1,028,108 89.95% 2,839 2,453 1,290,045 86.25% 2,864 2,250 8,009,346 77.70%
Rhode Island 726 642 85,295 88.17% 732 619 126,228 84.66% 790 578 688,500 71.06%
South Carolina 682 611 345,629 89.90% 785 654 458,404 82.81% 733 568 2,574,050 78.51%
South Dakota 660 624 69,742 94.99% 664 601 90,990 90.77% 669 570 459,901 84.40%
Tennessee 727 676 473,558 92.42% 530 451 621,828 84.19% 804 649 3,699,537 79.69%
Texas 2,626 2,377 2,018,953 90.59% 2,841 2,473 2,512,206 87.21% 2,976 2,365 12,788,834 78.18%
Utah 620 595 229,447 96.01% 645 590 360,378 91.50% 720 602 1,222,045 83.21%
Vermont 690 618 53,924 90.00% 722 620 69,851 86.39% 693 575 403,822 82.35%
Virginia 621 576 607,438 92.67% 780 652 739,131 82.83% 744 563 4,560,096 74.06%
Washington 667 608 528,622 90.12% 751 625 653,701 83.29% 789 609 3,825,493 75.95%
West Virginia 663 586 139,163 88.23% 707 598 194,555 84.94% 747 585 1,197,550 77.47%
Wisconsin 608 551 482,686 90.21% 785 687 620,505 86.32% 682 536 3,425,585 77.65%
Wyoming 666 608 45,377 91.90% 693 594 59,114 86.23% 732 590 310,110 79.45%

Table A.9 Sample Sizes, Weighted Screening and Interview Response Rates, and Population Estimates, by State, for Persons Aged 12 or Older: 2003-2004
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
Overall 340,276 286,097 260,735 90.82% 163,604 135,544 239,098,412 77.20% 70.11%
Alabama 4,062 3,323 3,035 91.42% 2,084 1,759 3,720,323 77.03% 70.43%
Alaska 4,216 3,339 3,065 91.79% 2,176 1,777 508,168 77.24% 70.89%
Arizona 4,385 3,615 3,412 94.42% 2,176 1,800 4,545,170 79.41% 74.98%
Arkansas 4,627 3,783 3,600 95.17% 2,154 1,822 2,243,910 79.96% 76.10%
California 15,598 13,815 12,207 87.73% 9,102 7,325 28,845,363 73.31% 64.32%
Colorado 4,432 3,677 3,421 93.00% 2,238 1,845 3,718,635 78.35% 72.87%
Connecticut 5,116 4,497 4,086 90.77% 2,226 1,830 2,891,183 76.05% 69.03%
Delaware 4,672 3,890 3,568 91.75% 2,249 1,843 680,294 76.44% 70.14%
District of Columbia 6,847 5,684 4,818 84.95% 2,157 1,852 471,653 81.43% 69.17%
Florida 20,907 16,941 15,156 89.38% 8,940 7,203 14,312,077 73.78% 65.94%
Georgia 4,253 3,486 3,209 92.03% 2,142 1,792 7,007,318 79.90% 73.53%
Hawaii 4,218 3,668 3,342 91.11% 2,230 1,831 1,013,721 75.27% 68.58%
Idaho 4,013 3,300 3,116 94.39% 2,163 1,814 1,112,492 80.00% 75.51%
Illinois 17,620 15,586 13,145 84.24% 9,096 7,286 10,353,764 74.75% 62.96%
Indiana 4,222 3,574 3,379 94.56% 2,167 1,794 5,074,139 78.51% 74.23%
Iowa 4,025 3,574 3,362 94.15% 2,032 1,774 2,458,501 83.32% 78.45%
Kansas 4,336 3,697 3,479 94.08% 2,034 1,703 2,217,978 79.89% 75.16%
Kentucky 4,638 4,050 3,827 94.45% 2,246 1,841 3,401,372 74.74% 70.59%
Louisiana 4,190 3,470 3,251 93.63% 2,177 1,876 3,632,530 81.48% 76.29%
Maine 5,558 4,408 4,070 92.33% 2,158 1,824 1,120,081 81.79% 75.51%
Maryland 4,021 3,528 3,092 87.38% 2,039 1,764 4,534,137 82.00% 71.65%
Massachusetts 4,631 4,024 3,564 88.65% 2,307 1,841 5,379,031 75.98% 67.36%
Michigan 18,530 15,416 13,864 89.96% 8,843 7,337 8,340,319 77.35% 69.58%
Minnesota 4,030 3,515 3,251 92.34% 2,118 1,816 4,215,479 82.97% 76.61%
Mississippi 4,127 3,281 3,132 95.52% 2,131 1,813 2,326,830 79.62% 76.05%
Missouri 4,685 3,914 3,676 93.94% 2,209 1,829 4,717,630 79.96% 75.11%
Montana 4,895 3,861 3,640 94.30% 2,148 1,818 774,741 79.58% 75.04%
Nebraska 4,040 3,445 3,251 94.36% 2,143 1,815 1,424,708 80.17% 75.65%
Nevada 3,974 3,392 3,215 94.25% 2,125 1,790 1,858,479 79.04% 74.50%
New Hampshire 4,363 3,596 3,333 92.67% 2,226 1,814 1,088,864 76.34% 70.75%
New Jersey 5,328 4,646 4,014 86.02% 2,279 1,769 7,145,540 72.50% 62.37%
New Mexico 4,450 3,621 3,459 95.48% 2,204 1,866 1,536,426 78.99% 75.41%
New York 20,448 17,515 14,577 83.10% 9,194 7,272 15,963,506 72.89% 60.57%
North Carolina 4,424 3,585 3,388 94.49% 2,115 1,773 6,866,763 79.31% 74.93%
North Dakota 4,648 3,842 3,639 94.76% 2,048 1,778 527,585 84.32% 79.91%
Ohio 17,473 15,153 14,272 94.16% 8,717 7,172 9,461,804 76.42% 71.95%
Oklahoma 4,837 3,861 3,581 92.75% 2,096 1,738 2,857,154 77.42% 71.81%
Oregon 4,336 3,784 3,585 94.72% 2,203 1,822 2,986,420 78.06% 73.94%
Pennsylvania 19,465 16,488 14,930 90.60% 8,574 7,162 10,377,874 78.74% 71.34%
Rhode Island 4,285 3,776 3,360 88.84% 2,267 1,825 905,251 75.76% 67.31%
South Carolina 4,597 3,753 3,567 95.09% 2,151 1,805 3,411,190 80.71% 76.75%
South Dakota 4,178 3,423 3,254 95.02% 2,014 1,774 625,827 84.08% 79.89%
Tennessee 4,677 4,027 3,797 94.32% 2,027 1,752 4,855,614 82.79% 78.09%
Texas 15,824 13,065 12,333 94.39% 8,565 7,197 17,608,112 79.18% 74.74%
Utah 3,341 2,856 2,714 94.92% 2,035 1,808 1,834,316 85.85% 81.49%
Vermont 5,327 4,001 3,729 93.10% 2,179 1,841 532,164 80.81% 75.24%
Virginia 4,228 3,681 3,254 88.40% 2,156 1,809 5,989,213 79.26% 70.06%
Washington 4,473 3,802 3,597 94.63% 2,214 1,827 5,094,091 77.29% 73.14%
West Virginia 5,644 4,557 4,285 94.08% 2,116 1,780 1,539,188 79.02% 74.34%
Wisconsin 4,620 3,737 3,460 92.59% 2,164 1,804 4,571,741 77.83% 72.06%
Wyoming 4,442 3,575 3,374 94.38% 2,050 1,742 419,744 82.88% 78.22%

Table A.10 Sample Sizes, Weighted Interview Response Rates, and Population Estimates, by State and Three Age Groups: 2003-2004
State 12–17 18–25 26+
Total Selected Total Responded Population Estimate Weighted Interview Response Rate Total Selected Total Responded Population Estimate Weighted Interview Response Rate Total Selected Total Responded Population Estimate Weighted Interview Response Rate
Overall 50,528 45,005 25,104,874 89.06% 54,667 46,016 31,961,116 83.67% 58,409 44,523 182,032,422 74.42%
Alabama 659 597 381,563 90.39% 711 617 503,783 86.75% 714 545 2,834,977 73.43%
Alaska 691 599 68,492 87.09% 754 622 69,578 81.47% 731 556 370,098 74.72%
Arizona 701 621 498,693 89.03% 733 597 621,802 81.91% 742 582 3,424,675 77.45%
Arkansas 688 621 233,184 90.40% 728 613 306,999 84.26% 738 588 1,703,727 77.60%
California 2,789 2,487 3,209,345 89.26% 2,986 2,454 3,949,889 82.27% 3,327 2,384 21,686,129 69.35%
Colorado 666 601 388,793 90.64% 814 663 501,011 80.53% 758 581 2,828,830 76.27%
Connecticut 664 589 295,229 88.61% 764 643 336,200 83.29% 798 598 2,259,754 73.26%
Delaware 688 601 67,658 87.73% 775 645 90,513 83.18% 786 597 522,123 73.76%
District of Columbia 694 617 33,384 89.56% 742 654 70,483 87.71% 721 581 367,787 79.44%
Florida 2,799 2,451 1,376,459 87.68% 2,844 2,368 1,658,368 82.54% 3,297 2,384 11,277,251 70.90%
Georgia 652 589 763,519 89.34% 707 592 967,105 85.19% 783 611 5,276,693 77.57%
Hawaii 702 643 100,549 91.59% 703 588 121,734 84.10% 825 600 791,438 71.73%
Idaho 641 578 127,839 90.51% 710 605 168,848 84.70% 812 631 815,805 77.42%
Illinois 2,739 2,404 1,089,901 87.90% 3,020 2,456 1,400,520 81.44% 3,337 2,426 7,863,343 71.80%
Indiana 677 592 546,518 85.62% 735 613 711,380 83.46% 755 589 3,816,240 76.63%
Iowa 683 623 243,608 90.35% 655 575 354,296 88.48% 694 576 1,860,596 81.36%
Kansas 626 559 237,856 88.99% 694 587 324,390 84.26% 714 557 1,655,732 77.57%
Kentucky 687 603 336,908 87.49% 728 617 453,011 84.56% 831 621 2,611,452 71.63%
Louisiana 668 609 403,315 91.98% 766 680 543,941 88.12% 743 587 2,685,275 78.60%
Maine 670 596 109,954 88.24% 766 640 134,241 84.18% 722 588 875,886 80.63%
Maryland 649 603 485,901 92.48% 630 536 556,047 84.99% 760 625 3,492,188 79.95%
Massachusetts 664 583 512,838 87.83% 786 628 676,402 79.19% 857 630 4,189,790 74.10%
Michigan 2,777 2,469 902,553 88.82% 3,039 2,589 1,108,787 84.99% 3,027 2,279 6,328,980 74.33%
Minnesota 739 662 442,828 89.42% 644 550 587,599 85.31% 735 604 3,185,052 81.61%
Mississippi 602 560 256,982 93.98% 762 660 349,332 86.79% 767 593 1,720,516 76.14%
Missouri 712 608 490,972 85.10% 740 622 642,988 83.36% 757 599 3,583,670 78.64%
Montana 628 549 79,960 87.61% 768 674 106,615 87.23% 752 595 588,167 76.95%
Nebraska 591 531 150,669 89.72% 817 693 208,757 84.88% 735 591 1,065,283 77.92%
Nevada 613 559 192,336 89.92% 720 619 228,424 87.10% 792 612 1,437,719 76.21%
New Hampshire 668 580 114,731 87.05% 734 617 134,285 83.51% 824 617 839,848 73.84%
New Jersey 634 553 733,853 85.94% 766 584 816,302 76.28% 879 632 5,595,385 70.32%
New Mexico 695 634 175,489 91.00% 698 612 218,107 88.08% 811 620 1,142,829 75.49%
New York 2,737 2,376 1,571,709 86.61% 3,098 2,502 2,047,533 80.91% 3,359 2,394 12,344,264 69.81%
North Carolina 660 592 701,982 89.97% 758 637 889,092 84.35% 697 544 5,275,688 76.84%
North Dakota 635 573 52,643 90.42% 677 591 82,943 86.83% 736 614 392,000 83.00%
Ohio 2,774 2,442 983,181 87.84% 2,863 2,415 1,251,526 84.30% 3,080 2,315 7,227,097 73.47%
Oklahoma 699 617 296,942 88.82% 702 596 415,680 84.83% 695 525 2,144,532 73.97%
Oregon 694 624 297,247 89.65% 742 618 392,447 83.82% 767 580 2,296,726 75.54%
Pennsylvania 2,681 2,409 1,034,227 90.27% 2,783 2,357 1,315,867 85.23% 3,110 2,396 8,027,780 76.17%
Rhode Island 703 593 87,330 85.47% 752 639 127,440 85.54% 812 593 690,482 72.59%
South Carolina 692 614 356,468 88.56% 665 569 460,716 86.06% 794 622 2,594,007 78.69%
South Dakota 578 538 68,362 92.54% 731 661 93,146 90.92% 705 575 464,319 81.56%
Tennessee 641 597 475,614 92.46% 611 521 636,601 84.82% 775 634 3,743,398 81.19%
Texas 2,629 2,358 2,038,642 89.85% 2,858 2,458 2,577,160 86.27% 3,078 2,381 12,992,311 76.07%
Utah 652 610 229,590 94.21% 664 602 356,134 90.37% 719 596 1,248,593 83.02%
Vermont 705 624 53,561 88.49% 705 601 70,579 86.53% 769 616 408,025 78.85%
Virginia 620 566 617,003 90.55% 742 621 757,538 81.59% 794 622 4,614,672 77.54%
Washington 714 645 527,419 89.87% 768 632 676,016 81.43% 732 550 3,890,656 74.79%
West Virginia 637 566 138,269 89.09% 726 625 195,092 86.36% 753 589 1,205,827 76.67%
Wisconsin 673 610 478,926 91.12% 747 622 633,007 82.89% 744 572 3,459,808 75.05%
Wyoming 648 580 43,883 90.73% 636 536 60,860 85.38% 766 626 315,000 81.30%

Table A.11 Sample Sizes, Weighted Interview Response Rates, and Population Estimates among Persons Aged 12 to 20, by State: 2002, 2003, and 2004
State 2002 2003 2004
Total Selected Total Responded Population Estimate Weighted Interview Response Rate Total Selected Total Responded Population Estimate Weighted Interview Response Rate Total Selected Total Responded Population Estimate Weighted Interview Response Rate
Overall 36,567 32,794 37,200,835 89.24% 35,468 31,493 37,517,008 88.54% 35,343 31,221 37,736,765 88.01%
Alabama 511 467 587,585 91.22% 491 448 624,780 91.36% 474 424 609,056 88.81%
Alaska 545 492 96,322 90.07% 490 419 97,543 86.51% 484 428 97,677 87.90%
Arizona 486 445 699,214 91.75% 467 419 709,434 90.17% 460 391 692,728 85.11%
Arkansas 492 436 350,404 89.04% 487 436 350,182 89.68% 483 425 360,424 87.61%
California 1,961 1,749 4,652,169 88.72% 1,945 1,712 4,793,532 87.79% 1,975 1,737 4,886,817 87.62%
Colorado 486 429 576,143 87.91% 457 403 562,345 86.11% 490 436 590,904 90.26%
Connecticut 513 460 422,161 89.91% 478 423 428,352 87.94% 482 427 429,774 88.45%
Delaware 536 474 105,693 87.77% 488 425 100,828 86.87% 492 425 103,646 86.64%
District of Columbia 464 432 64,106 93.65% 484 433 57,202 90.35% 439 393 55,748 90.02%
Florida 1,911 1,722 1,932,413 90.10% 1,910 1,658 2,048,669 86.55% 1,943 1,687 2,041,124 86.80%
Georgia 455 405 1,096,267 89.73% 450 402 1,116,747 88.69% 423 376 1,072,483 88.79%
Hawaii 469 419 155,358 90.41% 526 476 154,005 90.33% 434 395 146,333 91.25%
Idaho 465 421 186,467 89.74% 451 399 191,599 88.36% 457 417 208,478 91.75%
Illinois 2,038 1,780 1,606,101 87.07% 1,958 1,688 1,622,676 86.38% 1,880 1,655 1,658,743 88.14%
Indiana 527 477 856,119 88.82% 461 410 805,229 87.52% 479 406 821,329 82.80%
Iowa 472 433 407,912 92.58% 454 414 382,804 89.19% 479 430 387,153 90.72%
Kansas 469 429 370,727 91.68% 466 419 379,463 89.77% 412 369 357,889 90.00%
Kentucky 488 420 473,643 83.76% 487 424 517,645 86.09% 486 426 509,725 87.63%
Louisiana 481 434 628,050 91.33% 503 456 628,632 90.59% 469 434 638,363 93.03%
Maine 478 437 167,452 91.86% 487 427 165,367 87.61% 466 406 161,056 86.28%
Maryland 520 481 700,758 92.50% 412 373 696,774 89.12% 455 418 698,869 91.70%
Massachusetts 523 450 726,357 87.01% 473 406 726,797 85.32% 466 404 761,421 86.79%
Michigan 2,058 1,844 1,337,752 90.07% 1,961 1,750 1,369,113 89.03% 2,022 1,786 1,362,028 88.13%
Minnesota 443 405 660,986 91.01% 514 470 684,381 92.34% 466 410 647,035 87.57%
Mississippi1 460 418 396,888 90.35% 417 381 380,147 92.90% 434 403 377,607 92.62%
Missouri 487 435 741,043 89.39% 504 434 747,842 86.09% 482 407 739,176 82.71%
Montana 496 441 118,533 89.37% 462 412 124,324 89.19% 476 415 125,547 87.01%
Nebraska 486 436 240,071 90.37% 479 436 234,433 91.22% 398 349 214,257 87.57%
Nevada1 532 481 264,864 90.26% 427 385 263,304 90.22% 424 381 272,295 89.35%
New Hampshire 496 432 160,899 87.68% 511 452 180,199 88.79% 463 402 171,351 86.24%
New Jersey 489 428 1,060,363 87.68% 446 386 1,002,752 86.27% 446 373 1,040,817 81.91%
New Mexico1 363 326 270,071 89.22% 480 434 262,302 90.61% 477 437 267,026 90.81%
New York 2,031 1,753 2,337,270 85.37% 1,944 1,705 2,402,951 87.33% 1,923 1,643 2,386,440 85.64%
North Carolina 481 433 991,541 88.87% 479 422 1,041,193 87.77% 462 415 1,040,105 89.50%
North Dakota 497 466 91,095 93.68% 416 382 91,756 92.00% 515 464 91,193 89.71%
Ohio 1,845 1,653 1,441,043 89.37% 1,916 1,687 1,501,608 87.57% 1,965 1,712 1,477,159 86.84%
Oklahoma 514 443 479,049 84.54% 506 442 464,325 86.24% 468 416 451,625 89.08%
Oregon 503 448 458,891 88.35% 472 421 422,957 88.78% 487 425 448,317 87.18%
Pennsylvania 2,009 1,803 1,602,990 89.65% 1,889 1,691 1,560,665 89.95% 1,865 1,661 1,601,008 89.67%
Rhode Island 509 464 133,296 89.73% 490 419 133,702 85.96% 515 443 148,022 87.42%
South Carolina 486 431 533,703 88.60% 451 401 503,091 88.46% 431 384 503,928 89.79%
South Dakota 486 458 109,809 93.72% 436 403 105,738 92.98% 427 396 105,280 91.57%
Tennessee 503 467 797,436 93.05% 446 408 725,796 89.73% 408 379 687,831 92.64%
Texas 1,856 1,681 2,950,235 90.50% 1,773 1,594 2,986,183 90.10% 1,876 1,679 3,070,551 89.67%
Utah 428 413 378,829 95.69% 414 388 355,508 94.04% 466 430 360,286 92.16%
Vermont 480 439 82,118 92.35% 470 419 79,202 89.66% 473 418 79,607 88.84%
Virginia 450 413 864,521 92.09% 464 423 935,590 90.87% 434 389 915,164 87.44%
Washington 448 392 797,499 86.54% 517 466 809,829 90.25% 513 454 863,672 87.17%
West Virginia 470 425 225,498 90.34% 446 385 212,611 86.41% 467 426 227,229 91.82%
Wisconsin 474 421 738,285 87.31% 442 409 704,508 90.90% 503 440 704,083 88.50%
Wyoming 497 453 74,840 91.71% 471 418 70,394 89.10% 429 375 68,388 89.04%

Table A.12 Sample Sizes, Weighted Interview Response Rates, and Population Estimates among Persons Aged 12 to 20, by State: 2002-2003 and 2003-2004
State 2002-2003 2003-2004
Total Selected Total Responded Population Estimate Weighted Interview Response Rate Total Selected Total Responded Population Estimate Weighted Interview Response Rate
Overall 72,035 64,287 37,358,921 88.89% 70,811 62,714 37,626,886 88.27%
Alabama 1,002 915 606,182 91.29% 965 872 616,918 90.08%
Alaska 1,035 911 96,933 88.33% 974 847 97,610 87.21%
Arizona 953 864 704,324 90.94% 927 810 701,081 87.64%
Arkansas 979 872 350,293 89.36% 970 861 355,303 88.63%
California 3,906 3,461 4,722,850 88.25% 3,920 3,449 4,840,174 87.71%
Colorado 943 832 569,244 87.02% 947 839 576,625 88.22%
Connecticut 991 883 425,257 88.92% 960 850 429,063 88.20%
Delaware 1,024 899 103,260 87.32% 980 850 102,237 86.75%
District of Columbia 948 865 60,654 92.06% 923 826 56,475 90.19%
Florida 3,821 3,380 1,990,541 88.29% 3,853 3,345 2,044,897 86.68%
Georgia 905 807 1,106,507 89.21% 873 778 1,094,615 88.74%
Hawaii 995 895 154,682 90.37% 960 871 150,169 90.77%
Idaho 916 820 189,033 89.03% 908 816 200,038 90.11%
Illinois 3,996 3,468 1,614,389 86.72% 3,838 3,343 1,640,709 87.27%
Indiana 988 887 830,674 88.18% 940 816 813,279 85.13%
Iowa 926 847 395,358 90.92% 933 844 384,978 89.96%
Kansas 935 848 375,095 90.72% 878 788 368,676 89.88%
Kentucky 975 844 495,644 84.96% 973 850 513,685 86.86%
Louisiana 984 890 628,341 90.96% 972 890 633,497 91.81%
Maine 965 864 166,409 89.72% 953 833 163,212 86.95%
Maryland 932 854 698,766 90.86% 867 791 697,822 90.45%
Massachusetts 996 856 726,577 86.20% 939 810 744,109 86.08%
Michigan 4,019 3,594 1,353,433 89.55% 3,983 3,536 1,365,570 88.58%
Minnesota 957 875 672,684 91.68% 980 880 665,708 89.98%
Mississippi1 877 799 388,518 91.56% 851 784 378,877 92.76%
Missouri 991 869 744,442 87.70% 986 841 743,509 84.40%
Montana 958 853 121,428 89.28% 938 827 124,935 88.09%
Nebraska 965 872 237,252 90.80% 877 785 224,345 89.52%
Nevada1 959 866 264,084 90.24% 851 766 267,799 89.77%
New Hampshire 1,007 884 170,549 88.27% 974 854 175,775 87.56%
New Jersey 935 814 1,031,558 87.00% 892 759 1,021,785 84.06%
New Mexico1 843 760 266,187 89.88% 957 871 264,664 90.71%
New York 3,975 3,458 2,370,111 86.35% 3,867 3,348 2,394,695 86.48%
North Carolina 960 855 1,016,367 88.31% 941 837 1,040,649 88.66%
North Dakota 913 848 91,425 92.85% 931 846 91,474 90.84%
Ohio 3,761 3,340 1,471,325 88.45% 3,881 3,399 1,489,383 87.21%
Oklahoma 1,020 885 471,687 85.40% 974 858 457,975 87.60%
Oregon 975 869 440,924 88.56% 959 846 435,637 87.95%
Pennsylvania 3,898 3,494 1,581,827 89.80% 3,754 3,352 1,580,836 89.81%
Rhode Island 999 883 133,499 87.85% 1,005 862 140,862 86.72%
South Carolina 937 832 518,397 88.54% 882 785 503,509 89.14%
South Dakota 922 861 107,773 93.35% 863 799 105,509 92.27%
Tennessee 949 875 761,616 91.47% 854 787 706,814 91.17%
Texas 3,629 3,275 2,968,209 90.30% 3,649 3,273 3,028,367 89.89%
Utah 842 801 367,168 94.88% 880 818 357,897 93.10%
Vermont 950 858 80,660 91.03% 943 837 79,404 89.25%
Virginia 914 836 900,055 91.46% 898 812 925,377 89.17%
Washington 965 858 803,664 88.39% 1,030 920 836,750 88.70%
West Virginia 916 810 219,055 88.45% 913 811 219,920 89.25%
Wisconsin 916 830 721,396 89.06% 945 849 704,296 89.70%
Wyoming 968 871 72,617 90.45% 900 793 69,391 89.07%

End Note

8In 2002, the name of the survey was changed from the National Household Survey on Drug Abuse (NHSDA) to NSDUH.

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