2014-2016 National Surveys on Drug Use and Health:
Guide to Substate Tables and Summary of Small Area Estimation Methodology

Section A: Overview

A.1. Introduction

This document provides information on the model-based small area estimates of substance use and mental disorders in substate regions based on data from the combined 2014-2016 National Surveys on Drug Use and Health (NSDUHs). The estimates along with other related information are available at https://www.samhsa.gov/data/.

NSDUH is an annual survey conducted from January through December of the civilian, noninstitutionalized population aged 12 or older and is sponsored by the Substance Abuse and Mental Health Services Administration (SAMHSA), U.S. Department of Health and Human Services. NSDUH is planned and managed by SAMHSA's Center for Behavioral Health Statistics and Quality (CBHSQ). Data collection and analysis are conducted under contract with RTI International.1

NSDUH is the primary source of statistical information on the use of illicit drugs, alcohol, and tobacco by the U.S. civilian, noninstitutionalized population aged 12 or older. The survey also includes several series of questions that focus on mental health issues. Conducted by the federal government since 1971, NSDUH collects data through face-to-face interviews with a representative sample of the population at the respondent's place of residence.

In 2014-2016, the survey collected data from 203,916 respondents aged 12 or older and was designed to obtain representative samples from the 50 states and the District of Columbia. It covers residents of households and noninstitutional group quarters (e.g., shelters, rooming houses, dormitories) and from civilians living on military bases. NSDUH excludes homeless people who do not use shelters, military personnel on active duty, and residents of institutional group quarters, such as jails and hospitals.

The 1999 survey marked the first year in which the national sample was interviewed using a computer-assisted interviewing (CAI) method. The survey used a combination of computer-assisted personal interviewing (CAPI) conducted by an interviewer and audio computer-assisted self-interviewing (ACASI). Use of ACASI is designed to provide the respondent with a highly private and confidential means of responding to questions and increases the level of honest reporting of illicit drug use and other sensitive behaviors. For further details on the development of the CAI procedures for the 1999 National Household Survey on Drug Abuse (NHSDA),2 see the Office of Applied Studies (OAS, 2001).3

The 1999 through 2001 NHSDAs and the 2002 through 2013 NSDUHs employed an independent, multistage area probability sample for each of the 50 states and the District of Columbia. For this design, eight states were designated as large sample states (California, Florida, Illinois, Michigan, New York, Ohio, Pennsylvania, and Texas) with target sample sizes of 3,600 per year. For the remaining 42 states and the District of Columbia, the target sample size was 900 per year. This approach ensured that there was sufficient sample in every state to support small area estimation (SAE) production at the state and substate level, while at the same time maintaining efficiency for national estimates. The design also oversampled youths aged 12 to 17 and young adults aged 18 to 25 so that each state's sample was approximately equally distributed among three major age groups: 12 to 17 years, 18 to 25 years, and 26 years or older.

A coordinated design was developed for the 2014 through 2017 NSDUHs. Similar to the 1999 through 2013 surveys, the coordinated 4-year design is state-based with an independent, multistage area probability sample within each state and the District of Columbia. This design designates 12 states as large sample states that have the following target sample sizes per year: 4,560 completed interviews in California; 3,300 completed interviews each in Florida, New York, and Texas; 2,400 completed interviews each in Illinois, Michigan, Ohio, and Pennsylvania; and 1,500 completed interviews each in Georgia, New Jersey, North Carolina, and Virginia. Making the sample sizes more proportional to the state population sizes improves the precision of national NSDUH estimates. This change also allows for a more cost-efficient sample allocation to the 12 large sample states while slightly increasing the sample sizes in the 38 remaining smaller states and the District of Columbia to improve the precision of state and substate estimates.4

Starting in 2014, the allocation of the NSDUH sample is 25 percent for adolescents aged 12 to 17, 25 percent for adults aged 18 to 25, and 50 percent for adults aged 26 or older. The sample of adults aged 26 or older is further divided into three subgroups: aged 26 to 34 (15 percent), aged 35 to 49 (20 percent), and aged 50 or older (15 percent). For more information on the 2014 through the 2017 NSDUH sample design and for differences between the 2013 and 2014 surveys, refer to the 2014 NSDUH sample design report (CBHSQ, 2015a).

This marks the eighth time5 that estimates for substate regions (also referred to as planning regions or substate areas) in all 50 states and the District of Columbia have been presented by SAMHSA. Here, substate-level small area estimates are provided for 14 binary (0, 1) substance use or mental health measures using combined data from the 2014-2016 NSDUHs for individuals aged 12 or older (or adults 18 or older for the five mental health outcomes, and individuals aged 12 to 20 for underage alcohol use). For a list of outcomes for which substate-level estimates are available, refer to Table A1 at the end of this section. These substate estimates are available at https://www.samhsa.gov/data/. The list of products (e.g., tables, maps, substate region definitions) related to the 2014-2016 substate estimates is provided in Section A.2.

Estimates for 406 substate regions were generated using the 2014-2016 NSDUH data. These substate regions were defined by government officials from each of the 50 states and the District of Columbia and were typically based on the substance abuse treatment planning regions specified by the states in their applications for the Substance Abuse Prevention and Treatment Block Grant (SABG) administered by SAMHSA. The SABG program provides financial and technical assistance to the 50 states, the District of Columbia, and other jurisdictions to support substance abuse prevention and treatment programs and to promote public health. States use NSDUH substate estimates for a variety of purposes, including strategic planning and program development, production of epidemiological profiles for briefing state legislatures and informing the public, allocating funds to substate areas based on the need for services, and other uses. More information on defining these regions is available in Section A.3.

Section A.4 discusses the methodological changes that were introduced in the 2002 NSDUH. An unanticipated result of these changes was that the prevalence rates for 2002 were in general substantially higher than those for 2001. As a result, the 1999-2001 substate estimates are not comparable with the other substate estimates. Additionally, this section discusses NSDUH questionnaire changes from 2015 and how these changes affect the small area estimates. Section A.5 discussed related substance use measures and warns users about not drawing conclusions by subtracting small area estimates from two different measures.

Section B provides information on the SAE methodology used to produce substate estimates. Section C includes the population estimates and the combined 2014, 2015, and 2016 NSDUH sample sizes and response rates for each substate region. Users may find the population estimates helpful in calculating the prevalence estimate for any combination of substate regions or to determine the number of people using a particular substance in a substate region. For example, the number of individuals aged 12 or older who used marijuana in the past month in Alabama's Region 1 (58,320 individuals) can be obtained by multiplying the prevalence rate (5.10 percent) from Table 2 in the "2014-2016 NSDUH Substate Regions: Excel Tables" (see https://www.samhsa.gov/data/) and the population estimate from Table C1 (1,143,525) in this document. Section D lists the references cited in this document, and Section E provides a list of contributors to the production of the 2014-2016 substate estimates.

A.2. Presentation of Findings

In addition to this methodology document for the 2014-2016 substate SAE results, the following files are available at https://www.samhsa.gov/data/:

Note that other products may be added to the 2014-2016 NSDUH substate homepage at a later date.

A.3. Formation and Ranking of Substate Regions

The substate regions for each state were developed in a series of communications during the fall of 2017 between SAMHSA staff and state officials responsible for the SABG application. There is extensive variation in the size and use of substate regions across the states. In some states, the substate regions are used more for administrative purposes rather than for planning purposes. The goal of the project was to provide substate-level estimates showing the geographic distribution of substance use prevalence for regions that states would find useful for planning and reporting purposes. The final substate region boundaries were based on the state's recommendations, assuming that the NSDUH sample sizes were large enough to provide estimates with adequate precision.

Most states defined regions in terms of counties or groups of counties. A few states defined the regions in terms of census tracts. Several states also requested estimates for aggregate substate regions, along with the estimates for their substate regions. An aggregate substate region is made up of two or more substate regions. These substate region definitions are available in a document titled "2014-2016 NSDUH Substate Region Definitions" (see https://www.samhsa.gov/data/ as listed in Section A.2). Some of the states (specifically, New Hampshire, Texas, and Washington) wanted the maps to be produced only for the aggregate regions. For example, Washington has eight substate regions, and those eight regions were combined to create three aggregate regions that are used in the maps. Hence, for each measure, maps were produced for 395 regions and not for 406 regions.

The 395 substate regions used in the maps were ranked from lowest to highest for each measure and were divided into seven categories (based on estimates rounded to two decimals) designed to represent distributions that are somewhat symmetric, as in a normal distribution. Colors were assigned to all substate regions such that the third having the lowest prevalence are in blue (132 substate regions), the middle third are in white (131 substate regions), and the third with the highest prevalence are in red (132 substate regions). To further distinguish among the substate regions that display relatively higher prevalence, the "highest" third in red has been subdivided into (a) dark red for the 18 substate regions with the highest estimates, (b) medium red for the 37 substate regions with the next highest estimates, and (c) light red for the 77 substate regions in the third highest group. The "lowest" third is categorized in a similar way using three distinct shades of blue. In some cases, a group (or category) could have more or fewer substate regions because two (or more) substate regions have the same estimate (to two decimal places). When such ties occurred at the "boundary" between two groups, all substate regions with the same estimate (to two decimal places) were assigned to the lower group. The upper and lower limits of each of the seven categories shown in the map legend collectively define a continuum and are not necessarily the actual values of a particular substate region.

For example, in Figure 6 (national map showing alcohol use in the past month among persons aged 12 or older) (see the "2014-2016 NSDUH National Maps of Prevalence Estimates, by Substate Region" at https://www.samhsa.gov/data/ as listed in Section A.2), the values on the boundary in the lowest category (group 1) correspond to Utah County in Utah (21.10 percent) and Salt Lake County in Utah (35.81 percent) and are displayed in the legend. In the next to lowest category, Region 2 in Mississippi (36.10 percent) and Region 3 in South Carolina (42.36 percent) are the regions with the lowest and highest values; however, in the continuum of the legend, the lower limit for group 2 was assigned a value of 35.82 percent because the upper limit of group 1 is 35.81 percent.

The 2014-2016 substate estimates and corresponding Bayesian CIs are available in the "2014-2016 NSDUH Substate Region Estimates: Excel Tables and CSV Files" (as mentioned in Section A.2, see https://www.samhsa.gov/data/). These tables also contain a sort order number and a map group indicator (= 1 for the national estimate, = 2 for census region estimates, = 3 for state-level estimates, = 4 if a region is part of the 395 substate/aggregate region-level estimates included in the maps, and = 5 for all other substate/aggregate region-level estimates not included in the maps).

In addition to the substate region estimates, comparable estimates are provided for the 50 states and the District of Columbia and also for the four census regions. Design-based estimates and corresponding CIs for the nation are also included. Because these estimates are based on 3 consecutive years of data, they are not directly comparable with the annually published state, census region, or national estimates that are based on only 2 consecutive years of NSDUH data. The U.S. Census Bureau defines the census regions as follows:

Northeast Region - Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and Vermont.

Midwest Region - Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin.

South Region - Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia.

West Region - Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming.

A.4. Comparability with Past Estimates

For the 2002 NSDUH, a number of methodological changes were introduced, including a $30 incentive for participating in the survey, additional training for interviewers to encourage adherence to survey protocols, a change in the survey name, and a shift to the 2000 decennial census (from the 1990 census) as a basis for population counts used in sample selection, weighting, and estimation. Additional information on these methodological changes is available in a report by the OAS (2005). An unanticipated result of these changes was that the prevalence rates for 2002 were in general substantially higher than the 2001 prevalence rates. The jump in the prevalence rates between 2001 and 2002 was more than the usual year-to-year change. Because of the changes in the survey that took place in 2002, substate estimates for 1999-2001 are not comparable with the other substate estimates. It is not possible to separate the effect of the methodological changes from the true trends in substance use.

However, estimates from 2002-2004, 2004-2006, 2006-2008, 2008-2010, 2010-2012, 2012-2014, and 2014-2016 are comparable for outcome measures that were defined in a similar manner and for substate regions defined consistently across these time periods. Table A1 at the end of this section lists the outcome measures for which substate estimates were produced using 2014-2016 NSDUH data and shows the outcome measures that remained comparable over time (indicated with an "X" in the table) since 2002-2004.

It is useful to note that the 2002-2004 to 2008-2010 substate estimates were produced using predictors from the 2000 census; also, the survey weights used population projections from the 2000 census. The 2010-2012, 2012-2014, and 2014-2016 estimates, on the other hand, were produced using 2010 census data. Hence, when reviewing changes between 2008-2010 and 2014-2016, it is important to note that they may be confounded with changes due to differences in the source of the predictors and the population projections (referred to as "census effects"). The impact of such census effects on national and state estimates is discussed in Section B.4.3 in Appendix B of the 2011 NSDUH national findings report (CBHSQ, 2012) and the "2011-2012 NSDUH: Impact of Using 2010 Census Data on 2010-2011 Small Area Estimates" at https://www.samhsa.gov/data/.

During regular data collection and processing checks for the 2011 NSDUH, data errors were identified. These errors were falsified cases submitted by field interviewers that affected the data for Pennsylvania (2006 to 2010) and Maryland (2008 and 2009). Cases with erroneous data were removed from the data files, and the remaining cases were reweighted to provide representative estimates (for more details on this data error, refer to Section A.7 of the "2011-2012 NSDUH Guide to State Tables and Summary of Small Area Estimation Methodology" at https://www.samhsa.gov/data/). The 2006-2008, 2008-2010, and the 2010-2012 substate estimates exclude data based on falsified cases.

In 2015, a number of changes were made to the NSDUH questionnaire and data collection procedures. These changes were intended to improve the quality of the data that were collected and to address the changing needs of substance use and mental health policy and research.7 Discussed here briefly is the effect of the redesign on the comparability between the 2015 NSDUH and earlier NSDUHs, specifically related to the SAE outcomes. For a more detailed discussion of the questionnaire redesign and its effect, see Section C of the 2015 NSDUH's methodological summary and definitions report (CBHSQ, 2016a) and a brief report summarizing the implications of the changes for data users (CBHSQ, 2016b).

In the alcohol section of the questionnaire, the threshold for defining binge alcohol use among females was revised from five or more drinks on an occasion to four or more drinks on an occasion to ensure consistency with federal definitions.8 The threshold for males in 2015 remained at five or more drinks on an occasion. Consequently, a new baseline was established in 2015 for estimates of binge alcohol for the overall population. Thus, substate small area estimates for past month binge alcohol use using combined 2014, 2015, and 2016 data were not produced. Note that this change did not affect estimates for alcohol use or alcohol use disorder.

Several changes were made to the various illicit drug modules. Specifically, changes were made to the hallucinogen, inhalant, methamphetamine, and prescription psychotherapeutic modules. For details on these specific changes, see Section C.1 of the 2015 NSDUH methodological summary and definitions report (CBHSQ, 2016a). These changes resulted in the need to revise the baseline for the following SAE outcomes: illicit drug use in the past month, nonmedical use of pain reliever in the past year,9 illicit drug use disorder, and needing but not receiving treatment for illicit drugs.

Additionally, changes to some of the drug modules might have affected the set of respondents in 2015 who were eligible to be asked questions about treatment for substance use. Hence, SAE outcomes on needing but not receiving treatment (for illicit drugs and alcohol) were potentially affected. Thus, substance use treatment estimates were not produced using combined 2014, 2015, and 2016 NSDUH data.

Finally, although questions on the perceptions of risk of harm from using different substances did not change in 2015, data quality checks on preliminary data and the full 2015 data showed deviations from the expected trends for these measures. A survey redesign carries the risk that preceding changes to the questionnaire will affect how respondents answer later questions (e.g., context effects). A context effect may be said to take place when the response to a question is affected by information that is not part of the question itself. For example, the content of a preceding question may affect the interpretation of a subsequent question. Or a respondent may answer a subsequent question in a manner that is consistent with responses to a preceding question if the two questions are closely related to each other. The set of questions preceding the risk and availability module in the 2015 questionnaire had undergone a number of significant changes that could have affected the way in which respondents answered the perceived risk and availability questions. Because of these deviations, the perception of risk estimates were not produced using the combined 2014, 2015, and 2016 NSDUH data.

To summarize, several changes in the 2015 questionnaire had impacts on the comparability of the 2014 and 2015 NSDUH data. It was decided, therefore, that for those measures data across those 2 years could not be pooled, and estimates for those measures could not be produced using 2014-2016 NSDUH data. For a complete list of outcomes for which substate small area estimates are available using the 2014-2016 NSDUH data, refer to Table A1.

A.5. 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 cigarettes in the past month from the percentage who used tobacco products in the past month to find the percentage who used tobacco other than cigarettes 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 substate region, 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.

Table A1. – Outcomes, by Survey Year, for Which Substate Small Area Estimates Are Available
Measure 2002-2004 2004-2006 2006-2008 2008-2010 2010-2012 2012-2014 2014-2016
Illicit Drug Use in the Past Month X X X X X X --
Marijuana Use in the Past Year X X X X X X X
Marijuana Use in the Past Month X X X X X X X
Perceptions of Great Risk from Smoking Marijuana Once a Month X X X X X X --
First Use of Marijuana1 X X X X X X X
Illicit Drug Use Other Than Marijuana in the Past Month X X X X X X --
Cocaine Use in the Past Year X X X X X X X
Heroin Use in the Past Year -- -- -- -- -- -- X
Nonmedical Use of Pain Relievers in the Past Year X X X X X X --
Alcohol Use in the Past Month X X X X X X X
Underage Past Month Use of Alcohol (among Individuals Aged 12 to 20) X X X X X X X
Binge Alcohol Use in the Past Month X X X X X X --
Underage Past Month Binge Alcohol Use (among Individuals Aged 12 to 20) X X X X X X --
Perceptions of Great Risk from Having Five or More Drinks of an Alcoholic
   Beverage Once or Twice a Week
X X X X X X --
Tobacco Product Use in the Past Month X X X X X X X
Cigarette Use in the Past Month X X X X X X X
Perceptions of Great Risk from Smoking One or More Packs of Cigarettes
   per Day
X X X X X X --
Alcohol Use Disorder in the Past Year2 X X X X X X X
Alcohol Dependence in the Past Year2 X X X X X X --
Illicit Drug Use Disorder in the Past Year2 X X X X X X --
Illicit Drug Dependence in the Past Year2 X X X X X X --
Substance Use Disorder in the Past Year2 X X X X X X --
Needing But Not Receiving Treatment for Illicit Drug Use in the Past Year X X X X X X --
Needing But Not Receiving Treatment for Alcohol Use in the Past Year X X X X X X --
Serious Psychological Distress (SPD) in the Past Year3 X X -- -- -- -- --
Had at Least One Major Depressive Episode (MDE) in the Past Year4 -- X X X X X X
Serious Mental Illness (SMI) in the Past Year5 -- -- -- X X X X
Any Mental Illness (AMI) in the Past Year5 -- -- -- X X X X
Received Mental Health Services in the Past Year -- -- -- -- -- -- X
Had Serious Thoughts of Suicide in the Past Year -- -- -- X X X X
X = available; -- = not available.
NOTE: The measures included in the 1999-2001 substate small area estimation (SAE) report are not included here. Because of the changes in the survey that took place in 2002, the 1999-2001 estimates are not comparable with the 2002-2004 or subsequent year estimates. Estimates using the combined 2002-2004, 2004-2006, and 2006-2008 data can be found at https://www.samhsa.gov/data/. Estimates using the combined 2008-2010, 2010-2012, and 2012-2014 data can also be found at https://www.samhsa.gov/data/.
1 The marijuana incidence definition used here employs a simpler form of the at-risk population based on the model-based methodology. This model-based average annual incidence rate for first use of marijuana is defined as follows: Average annual initiation of marijuana (%) = 100 × {[X1 ÷ (0.5 × X1 + X2)] ÷ 2}, where X1 is the number of marijuana initiates in the past 24 months and X2 is the number of individuals who never used marijuana (with the at-risk population defined as 0.5 × X1 + X2). Both X1 and X2 are based on binary measures that correspond to questions with a "yes" or "no" response option. For details on calculating the average annual rate of first use of marijuana from NSDUH data, see Section B of the "2015–2016 NSDUH: Guide to State Tables and Summary of Small Area Estimation Methodology" at https://www.samhsa.gov/data/.
2 Substance use disorder is defined as meeting the criteria for illicit drug or alcohol dependence or abuse. Dependence or abuse is based on definitions found in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) (American Psychiatric Association, 1994). For more details, see Section B.4.2 in Appendix B of the 2012 NSDUH national findings report (Center for Behavioral Health Statistics and Quality [CBHSQ], 2013b).
3 Because of questionnaire changes, SPD estimates in 2002-2004 are not comparable with the 2004-2006 SPD estimates. For details, see Section B.7 of the report on Substate Estimates from the 2004-2006 National Surveys on Drug Use and Health (Office of Applied Studies [OAS], 2008). Additional questionnaire changes were made in 2008 that affected past year SPD trends. However, revised past year SPD measures were created for 2005 through 2007 that are comparable with the 2008 through 2016 past year SPD measure. Substate small area estimates for 2006-2008, 2008-2010, 2010-2012, 2012-2014, and 2014-2016 were not created for this measure.
4 Questions used to determine MDE were added in 2004. The 2004-2006 MDE estimates are not comparable with the 2006-2008 and subsequent year estimates. For details on MDE, see Sections B.4.2 and B.4.4 in Appendix B of the 2012 NSDUH mental health findings report (CBHSQ, 2013a).
5 The mental illness measures are based on a predictive model and are not direct measures of diagnostic status (i.e., a small subsample of the respondents received a clinical follow-up, and these responses along with questionnaire data were used to create predictive models for all of the respondents). For details about these measures and the predictive models, see Section B.4.3 in Appendix B of the 2012 NSDUH mental health findings report (CBHSQ, 2013a).
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Surveys on Drug Use and Health, 2002–2016.
Table A2. – NSDUH Substate Region Counts and Overlap, by State and Estimation Period
State 2008-2010 2012-2014 2014-2016
Number
of
Substate
Regions1
Number
of Map
Regions2
Number
of
Substate
Regions1
Number
of Map
Regions2
Number
of
Substate
Regions1
Number
of Map
Regions2
Number of
Substate
Regions
Overlapping
with 2008–
20103
Number of
Substate
Regions
Overlapping
with 2012–
20143
Total U.S. 383 362 384 362 406 395 304 345
Alabama 4 4 4 4 4 4 4 4
Alaska 4 4 4 4 4 4 4 4
Arizona 4 4 4 4 4 4 2 2
Arkansas 8 8 8 8 8 8 8 8
California 27 27 26 26 26 26 25 26
Colorado 5 5 5 5 7 7 0 0
Connecticut 5 5 5 5 5 5 5 5
Delaware 4 4 4 4 4 4 4 4
District of Columbia 8 8 8 8 8 8 8 8
Florida 18 18 18 18 18 18 16 18
Georgia 6 6 6 6 6 6 6 6
Hawaii 4 4 4 4 4 4 4 4
Idaho 7 7 7 7 7 7 5 7
Illinois 5 5 5 5 17 17 0 0
Indiana 8 8 8 8 8 8 8 8
Iowa 6 6 6 6 6 6 6 6
Kansas 6 6 6 6 5 5 0 0
Kentucky 6 6 6 6 6 6 6 6
Louisiana 5 5 6 6 6 6 4 6
Maine 7 7 8 8 8 8 6 8
Maryland 9 9 9 9 9 9 9 9
Massachusetts 6 6 6 6 6 6 6 6
Michigan 15 15 10 10 10 10 3 10
Minnesota 6 6 6 6 9 9 3 3
Mississippi 7 7 7 7 7 7 7 7
Missouri 7 7 7 7 7 7 7 7
Montana 5 5 5 5 5 5 5 5
Nebraska 6 6 6 6 6 6 6 6
Nevada 3 3 4 4 4 4 2 4
New Hampshire 5 3 5 3 5 3 5 5
New Jersey 4 4 4 4 4 4 4 4
New Mexico 5 5 5 5 6 6 4 4
New York 15 4 15 4 15 15 4 4
North Carolina 12 11 14 14 14 14 10 14
North Dakota 5 5 7 7 8 8 2 6
Ohio 21 21 21 21 21 21 21 21
Oklahoma 7 7 7 7 7 7 7 7
Oregon 6 6 6 6 6 6 6 6
Pennsylvania 13 13 13 13 13 13 13 13
Rhode Island 4 4 4 4 7 7 0 0
South Carolina 4 4 4 4 4 4 2 4
South Dakota 7 7 5 5 5 5 0 5
Tennessee 7 7 7 7 7 7 5 7
Texas 15 11 15 11 15 11 15 15
Utah 6 6 6 6 7 7 5 5
Vermont 4 4 4 4 4 4 4 4
Virginia 5 5 5 5 5 5 5 5
Washington 6 3 8 3 8 3 2 8
West Virginia 6 6 6 6 6 6 6 6
Wisconsin 6 6 6 6 6 6 6 6
Wyoming 9 9 9 9 9 9 9 9
1 Number of regions only include the main substate regions and not the aggregate regions.
2 More information on the map regions can be found in Section A.3.
3 The names of some of the substate regions have changed across the time periods. However, as long as the two regions are made of the same counties or tracts, they are included in the count of overlapping regions.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Surveys on Drug Use and Health, 2008–2016.

Section B: Substate Region Estimation Methodology

The survey-weighted hierarchical Bayes (SWHB) methodology used in the production of state estimates from the 1999 to 2016 National Surveys on Drug Use and Health (NSDUHs) also was used in the production of the 2014-2016 substate estimates. The SWHB methodology is described by Folsom, Shah, and Vaish (1999). A general model description is given in Section B.1. A brief discussion of the precision of the estimates and interpretation of the Bayesian confidence intervals (CIs) is given in Section B.2. The goals of the small area estimation (SAE) modeling, the general model description, and the implementation of SAE modeling remain the same and are described in Appendix E of the 2001 state report (Wright, 2003).

Small area estimates obtained using the SWHB methodology are design consistent (i.e., for states or substate areas with large sample sizes, the small area estimates are close to the corresponding robust design-based estimates). The substate 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 many reasons, including internal consistency, it is desirable to have the national small area estimates exactly match the national design-based estimates. Beginning in 2002, exact benchmarking was introduced (see Appendix A, Section A.4, in Wright & Sathe, 2005). The 2014-2016 substate small area estimates have been benchmarked to the national design-based estimates.

B.1. General SAE Model Description

The model can be characterized as a complex mixed10 model (including both fixed and random effects) of the following form:

Equation 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 substate region-j of state-i.

Let x sub a, i, j, k denote a  p sub a times 1 vector of the 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 the regression parameters. The age group-specific vectors of the 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 auxiliary variables include block group, census tract, county, and state-level data. These predictor variables include demographic and socioeconomic data from the American Community Survey (ACS), population projections obtained from Claritas,11 food stamp participation rates from the U.S. Census Bureau, Uniform Crime Report (UCR) arrest totals from the Federal Bureau of Investigation (FBI), per capita income from the Bureau of Economic Analysis (BEA), unemployment rates from the Bureau of Labor Statistics (BLS), mortality rates from the National Center for Health Statistics (NCHS), treatment rates from the National Survey of Substance Abuse Treatment Services (N-SSATS), and Block Grant awards, cost of services, and total taxable resources from the Substance Abuse and Mental Health Services Administration (SAMHSA). For a complete list of predictors, refer to Section B of the "2015-2016 NSDUH Guide to State Tables and Summary of Small Area Estimation Methodology" at https://www.samhsa.gov/data/.

The vectors An eta sub i is a transposed vector of values eta sub 1, i and so on until eta sub capital A, i. and 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., defined as state- and substate-level random effects, respectively, 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 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 distribution12 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 distribution. The basic process is described in Folsom et al. (1999), Shah, Barnwell, Folsom, and Vaish (2000), and Wright (2003). Once the required number of MCMC samples 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 projections to form substate- and state-level small area estimates for the desired age group(s). These small area estimates then are benchmarked to the national design-based estimates (for details on exact benchmarking, see Section B.5 of the "2015-2016 NSDUH Guide to State Tables and Summary of Small Area Estimation Methodology" at https://www.samhsa.gov/data/).

Because the objective here was to produce small area estimates for substate regions, it was decided to ratio adjust the person-level sampling weights to match population projections available from Claritas at the substate × age group × gender level. These adjusted sampling weights are used in the estimation because they reflect the demography of the substate regions better than the unadjusted weights. This ratio adjustment was done at the substate region (406 regions) × age group (12 to 17, 18 to 25, 26 to 34, and 35 or older) × gender (male and female) level collectively over 3 years (2014, 2015, and 2016) of data.

The SAE methodology used here tends to borrow strength from both the national model and the state-level random effects. Estimates for substate regions with smaller sample sizes tend to be shrunk more toward the corresponding state and national prevalence estimates than substate regions with larger sample sizes. This methodology tends to cluster the small sample substate estimates around their state prevalence estimates. Thus, relatively high estimates for substate regions with small sample sizes tend to shrink toward the state prevalence estimates, while relatively low estimates tend to increase toward the state prevalence estimates. On the other hand, for substate regions with large sample sizes, the methodology produces estimates that are close to the weighted average of the sample data in that substate region. In addition, these estimates are design consistent so that, as the sample size for a substate region increases, the estimate approaches the corresponding design-based estimate.

B.2. Precision Validation of the Estimates

The primary purpose of producing substate estimates is to give policy officials and data users a better perspective on the range of prevalence estimates within and across states. Because the data were collected in a consistent manner by field interviewers who adhered to the same procedures and administered the same questions across all states and substate regions, the results are comparable within and across the 50 states and the District of Columbia.

The 95 percent Bayesian CI associated with each estimate provides a measure of the accuracy of the estimate. It defines the range within which the true value can be expected to fall 95 percent of the time. For example, the estimated prevalence of past month use of marijuana in Region 1 in Alabama is 5.1 percent, and the 95 percent CI ranges from 4.0 to 6.5 percent.13 Therefore, the probability is 0.95 that the true value is within that range. The CI indicates the uncertainty due to both sampling variability and model bias. The key assumption underlying the validity of the CIs is that the state- and substate-level error (or bias correction) terms in the models behave like random effects with zero means and common variance components.

A comparison of the standard errors (SEs) among substate regions with small (n ≤ 500), medium (500 < n ≤ 1,000), and large (n > 1,000) sample sizes for certain measures shows that the small area estimates behave in predictable ways. Regardless of whether the substate region is from a state with a larger annual sample size or one of the other states, the sizes of the CIs are very similar and are primarily a function of the sample size of the substate region and the prevalence estimate of the measure. Substate regions with large sample sizes had the smallest SEs. For past month use of alcohol, where the national prevalence for all individuals aged 12 or older was 51.7 percent (for 2014-2016), the average relative standard error (RSE)14 was about 4.6 percent, and the RSE for substate regions with a large sample size was about 3.0 percent. For substate regions with a medium sample size, the average RSE was 3.9 percent; for small sample sizes, the average RSE was 5.2 percent. For past month use of marijuana (with a national prevalence of 8.5 percent), the average RSE was 9.1 percent for substate regions with large samples. For medium sample sizes, the average RSE was 11.2 percent, and for small samples, the RSE was 13.7 percent, whereas the overall national average RSE was 12.7 percent. Substance use measures with lower prevalence rates, such as past year use of cocaine (1.8 percent nationally), displayed larger average RSEs. For substate regions with large sample sizes, the average RSE was 18.5 percent. For those with medium sample sizes, the average RSE was 22.3 percent, and for those with small sample sizes, the average RSE was 26.4 percent. The overall national RSE for past year use of cocaine was 24.6 percent.

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

180126
Table C1. – Sample Sizes, Weighted Screening and Interview Response Rates, and Population Estimates, by Substate Region, for Individuals Aged 12 or Older: 2014, 2015, and 2016 NSDUHs
State/Substate Region Total
Selected DUs
Total Eligible
DUs
Total
Completed
Screeners
Weighted DU
Screening
Response
Rate
(Percentage)
Total
Selected
Total
Responded
Population
Estimate
Weighted
Interview
Response
Rate
(Percentage)
Weighted
Overall
Response
Rate
(Percentage)
Total United States 588,564 493,010 395,003 79.83% 281,746 203,916 267,494,781 69.62% 55.58%
Northeast 130,212 109,845 83,084 73.82% 55,945 38,736 47,754,274 65.92% 48.66%
Midwest 135,800 114,520 94,528 81.59% 66,524 47,738 56,630,386 69.19% 56.45%
South 192,981 159,911 130,205 82.66% 92,574 68,382 100,115,205 71.32% 58.96%
West 129,571 108,734 87,186 78.16% 66,703 49,060 62,994,916 70.12% 54.80%
Alabama 8,433 6,746 5,587 82.74% 3,992 2,900 4,066,740 68.88% 56.99%
Region 1 2,309 1,923 1,643 84.67% 1,167 844 1,143,525 68.33% 57.85%
Region 2 2,693 2,201 1,687 76.94% 1,245 855 1,300,200 64.48% 49.61%
Region 3 1,623 1,174 1,020 86.70% 728 545 727,198 72.93% 63.23%
Region 4 1,808 1,448 1,237 85.70% 852 656 895,817 73.18% 62.71%
Alaska 9,546 7,113 5,743 80.61% 4,084 2,888 583,292 69.48% 56.01%
Anchorage 3,829 3,059 2,448 79.97% 1,748 1,275 239,206 70.37% 56.27%
Northern 2,197 1,464 1,172 79.95% 855 592 129,318 67.55% 54.01%
South Central 2,508 1,903 1,534 80.95% 1,083 762 153,717 70.79% 57.30%
Southeast 1,012 687 589 83.66% 398 259 61,051 65.96% 55.18%
Arizona 8,457 6,429 5,443 84.88% 3,945 2,949 5,644,790 73.47% 62.36%
Central 5,037 3,991 3,348 84.27% 2,501 1,860 3,371,572 72.65% 61.22%
North 901 712 616 86.59% 393 284 681,935 72.39% 62.68%
South 2,519 1,726 1,479 85.59% 1,051 805 1,591,283 75.90% 64.97%
South A 1,574 1,101 954 86.75% 602 465 870,076 77.03% 66.82%
South B 945 625 525 83.53% 449 340 721,207 74.34% 62.10%
Arkansas 8,585 7,050 5,992 85.13% 3,986 2,937 2,459,210 70.42% 59.94%
Catchment Area 1 1,329 1,126 913 81.39% 655 464 405,083 67.96% 55.31%
Catchment Area 2 1,158 900 738 82.45% 473 359 297,808 74.71% 61.60%
Catchment Area 3 1,131 922 829 89.59% 575 442 326,336 76.04% 68.13%
Catchment Area 4 812 707 605 85.84% 421 313 216,727 70.69% 60.68%
Catchment Area 5 1,313 1,052 923 87.54% 633 454 367,776 66.57% 58.27%
Catchment Area 6 749 597 522 87.76% 315 251 171,970 74.05% 64.99%
Catchment Area 7 555 437 403 92.54% 234 185 189,124 75.72% 70.07%
Catchment Area 8 1,538 1,309 1,059 81.08% 680 469 484,385 65.16% 52.83%
California 33,713 30,426 22,640 74.04% 19,568 13,954 32,482,792 67.98% 50.34%
Region 1R 1,011 866 729 84.55% 520 394 817,672 74.77% 63.22%
Region 2R 996 845 668 79.21% 553 421 877,839 72.74% 57.62%
Region 3R (Sacramento) 1,500 1,371 967 70.62% 767 580 1,229,336 72.19% 50.98%
Region 4R 1,275 1,153 915 79.80% 691 489 1,127,236 68.12% 54.36%
Region 5R (San Francisco) 978 842 552 66.40% 380 231 766,151 56.74% 37.68%
Region 6 (Santa Clara) 1,666 1,537 1,205 78.54% 1,065 761 1,578,447 68.44% 53.75%
Region 7R (Contra Costa) 1,010 945 732 77.56% 615 456 930,884 71.67% 55.59%
Region 8R (Alameda) 1,267 1,148 936 81.34% 735 535 1,344,459 71.07% 57.81%
Region 9R (San Mateo) 623 572 479 83.73% 372 263 637,069 69.06% 57.82%
Region 10 980 864 639 74.65% 557 374 1,078,944 64.83% 48.40%
Region 11 (Los Angeles) 8,376 7,815 5,656 72.73% 5,106 3,443 8,495,997 63.21% 45.97%
LA SPA 1 and 5 873 818 491 61.58% 451 319 916,998 66.96% 41.23%
LA SPA 2 1,878 1,766 1,253 71.08% 1,170 748 1,870,818 60.16% 42.76%
LA SPA 3 1,351 1,271 898 71.16% 797 547 1,514,521 64.79% 46.11%
LA SPA 4 1,052 947 686 72.66% 499 295 994,517 53.76% 39.06%
LA SPA 6 737 686 571 83.83% 591 438 816,244 71.13% 59.63%
LA SPA 7 914 870 667 76.51% 702 465 1,075,611 63.29% 48.42%
LA SPA 8 1,571 1,457 1,090 74.74% 896 631 1,307,289 64.23% 48.01%
Region 12R 699 603 495 82.07% 413 314 716,288 70.62% 57.96%
Regions 13 and 19R 2,037 1,781 1,304 66.66% 1,249 942 2,065,736 72.47% 48.31%
Region 14 (Orange) 2,629 2,431 1,555 62.95% 1,432 937 2,678,523 60.92% 38.35%
Region 15R (Fresno) 768 697 535 76.75% 500 362 781,651 69.67% 53.47%
Region 16R (San Diego) 3,124 2,871 1,930 67.16% 1,530 1,111 2,747,477 70.22% 47.16%
Region 17R 1,571 1,358 1,132 83.71% 1,012 801 1,208,114 75.20% 62.95%
Region 18R (San Bernardino) 1,580 1,426 1,113 78.48% 1,138 837 1,735,180 70.87% 55.61%
Region 20R 661 596 516 86.51% 474 364 787,695 75.78% 65.56%
Region 21R 962 705 582 82.68% 459 339 878,093 70.69% 58.45%
Colorado 7,814 6,657 5,395 80.86% 4,009 2,922 4,525,628 70.75% 57.21%
Region 1 1,539 1,137 932 80.96% 632 441 751,752 70.62% 57.18%
Region 2 574 486 399 82.03% 288 205 349,899 62.59% 51.35%
Region 3 1,905 1,716 1,372 80.00% 1,155 844 1,177,330 69.67% 55.74%
Region 4 588 446 385 86.34% 241 190 308,602 77.30% 66.75%
Region 5 908 822 656 79.44% 504 376 568,069 73.84% 58.66%
Region 6 1,332 1,233 949 76.98% 692 500 769,114 70.38% 54.17%
Region 7 968 817 702 86.20% 497 366 600,861 72.82% 62.76%
Connecticut 8,642 7,561 5,864 77.60% 4,241 2,881 3,055,203 65.36% 50.72%
Eastern 1,185 965 788 81.97% 529 377 371,164 68.06% 55.79%
North Central 2,497 2,217 1,726 77.56% 1,183 822 854,958 66.84% 51.84%
Northwestern 1,477 1,329 1,039 78.28% 781 535 526,857 69.98% 54.78%
South Central 2,058 1,763 1,419 80.49% 1,018 687 713,696 63.77% 51.33%
Southwest 1,425 1,287 892 69.63% 730 460 588,528 58.68% 40.86%
Delaware 8,426 7,199 5,491 76.48% 3,917 2,824 793,943 70.82% 54.16%
Kent 1,517 1,326 1,067 80.49% 758 563 143,583 71.22% 57.32%
New Castle (excluding Wilmington City) 4,264 3,887 2,842 73.30% 2,177 1,539 406,917 70.31% 51.53%
Sussex 2,104 1,522 1,226 80.72% 734 518 179,873 69.42% 56.03%
Wilmington City 541 464 356 77.29% 248 204 63,569 79.71% 61.60%
District of Columbia 15,447 13,166 9,321 70.65% 3,710 2,826 573,161 73.82% 52.15%
Ward 1 1,748 1,463 1,088 75.26% 411 300 71,811 68.08% 51.24%
Ward 2 2,493 2,137 1,238 57.97% 404 292 76,179 70.10% 40.64%
Ward 3 1,877 1,424 1,018 71.57% 411 293 73,589 72.68% 52.02%
Ward 4 1,888 1,707 1,286 75.24% 530 395 70,867 73.58% 55.36%
Ward 5 1,677 1,486 1,053 69.88% 430 334 72,601 74.76% 52.25%
Ward 6 2,505 2,140 1,568 73.29% 569 455 74,876 76.52% 56.08%
Ward 7 1,598 1,423 1,020 70.70% 451 362 66,937 77.99% 55.14%
Ward 8 1,661 1,386 1,050 75.71% 504 395 66,301 75.82% 57.40%
Florida 32,081 25,876 20,751 80.02% 13,844 10,152 17,242,820 69.51% 55.62%
Broward (Circuit 17) 2,647 2,056 1,544 74.58% 1,052 772 1,594,764 70.64% 52.69%
Central I 3,856 3,402 2,916 85.80% 2,173 1,627 2,176,032 72.24% 61.98%
Circuit 9 2,154 1,946 1,684 86.75% 1,395 1,066 1,296,722 73.81% 64.03%
Circuit 18 1,702 1,456 1,232 84.65% 778 561 879,310 70.25% 59.47%
Central II 9,941 7,712 6,115 78.96% 3,796 2,777 4,831,147 69.43% 54.82%
Circuit 6 2,549 2,103 1,596 74.85% 1,004 686 1,266,166 65.47% 49.00%
Circuit 10 1,351 1,130 976 86.63% 642 520 650,370 79.61% 68.97%
Circuit 12 1,514 977 773 79.64% 434 324 691,693 75.57% 60.18%
Circuit 13 (Hillsborough) 2,516 2,168 1,715 79.04% 1,119 820 1,138,621 68.02% 53.76%
Circuit 20 2,011 1,334 1,055 78.60% 597 427 1,084,296 65.07% 51.14%
Northeast 5,866 4,727 3,894 82.62% 2,310 1,614 3,221,106 66.12% 54.63%
Circuit 4 1,929 1,595 1,262 79.22% 761 530 993,903 65.14% 51.60%
Circuit 5 1,830 1,394 1,152 82.89% 655 448 965,790 68.46% 56.75%
Circuit 7 1,342 1,105 927 84.31% 577 397 788,951 61.15% 51.55%
Circuit 8 plus Columbia, Dixie, Hamilton,
   Lafayette, and Suwannee
765 633 553 87.24% 317 239 472,462 72.45% 63.21%
Northwest 2,470 2,032 1,738 85.63% 1,205 927 1,275,635 73.94% 63.31%
Circuit 1 1,183 1,034 886 85.81% 603 454 624,250 71.06% 60.97%
Circuit 2 plus Madison and Taylor 849 668 567 85.28% 422 334 388,803 76.66% 65.37%
Circuit 14 438 330 285 85.75% 180 139 262,582 77.04% 66.06%
South (Circuits 11 and 16) 3,853 3,253 2,494 76.30% 1,900 1,422 2,378,649 70.75% 53.99%
Southeast 3,448 2,694 2,050 76.45% 1,408 1,013 1,765,488 66.15% 50.58%
Circuit 15 (Palm Beach) 2,294 1,802 1,328 74.30% 954 667 1,213,150 63.74% 47.36%
Circuit 19 1,154 892 722 80.89% 454 346 552,337 71.18% 57.58%
Georgia 11,327 9,535 7,613 79.83% 6,019 4,555 8,354,200 72.40% 57.80%
Region 1 2,724 2,365 1,990 84.12% 1,547 1,119 2,154,037 69.26% 58.27%
Region 2 1,633 1,376 1,137 82.85% 870 676 1,069,386 73.31% 60.74%
Region 3 3,536 3,019 2,195 72.66% 1,887 1,407 2,498,830 71.14% 51.69%
Region 4 681 568 497 87.43% 337 285 515,403 83.94% 73.39%
Region 5 1,257 961 789 81.95% 620 489 949,323 76.48% 62.68%
Region 6 1,496 1,246 1,005 80.42% 758 579 1,167,221 73.09% 58.78%
Hawaii 10,030 8,428 6,371 75.28% 4,186 2,992 1,162,034 69.58% 52.38%
Hawaii Island 1,512 1,227 1,069 86.51% 640 476 155,455 73.18% 63.31%
Honolulu 6,745 5,691 4,045 71.05% 2,740 1,956 818,697 68.81% 48.89%
Kauai 638 544 468 86.15% 317 230 56,499 74.09% 63.83%
Maui 1,135 966 789 81.69% 489 330 131,383 67.37% 55.03%
Idaho 6,605 5,654 4,849 85.84% 3,973 3,024 1,351,967 74.17% 63.67%
Region 1 1,047 817 633 78.61% 463 305 189,702 64.11% 50.39%
Region 2 441 380 315 82.90% 231 180 94,958 77.36% 64.13%
Region 3 1,056 949 821 86.25% 731 566 213,811 75.76% 65.35%
Region 4 1,815 1,652 1,427 86.46% 1,121 866 389,716 75.90% 65.62%
Region 5 880 715 638 88.72% 529 421 155,306 77.97% 69.17%
Region 6 438 352 308 87.65% 259 186 100,522 69.16% 60.62%
Region 7 928 789 707 89.89% 639 500 207,951 75.13% 67.54%
Illinois 21,229 18,462 13,547 73.46% 10,869 7,229 10,726,139 64.08% 47.08%
Region 1 (Cook) 8,592 7,394 4,692 63.86% 3,936 2,539 4,372,169 62.36% 39.83%
Region 1.1 (Far North Side) 771 702 433 61.82% 284 172 401,000 62.16% 38.43%
Region 1.2 (Northwest Side) 463 402 281 70.43% 266 156 226,723 56.71% 39.95%
Region 1.3 (North Central Side) 923 784 300 38.96% 234 133 401,961 57.82% 22.52%
Region 1.4 (West Side) 938 787 353 43.97% 315 222 392,394 65.81% 28.94%
Region 1.5 (South Side) 822 675 413 61.82% 372 251 551,374 69.79% 43.15%
Region 1.6 (Southwest Side) 821 688 424 61.81% 434 273 303,419 59.90% 37.03%
Region 1.7 (Suburban Cook) 3,854 3,356 2,488 74.38% 2,031 1,332 2,095,299 62.15% 46.23%
Region 2 6,289 5,758 4,386 75.95% 3,697 2,449 3,393,930 63.84% 48.49%
Region 2a (DuPage) 1,502 1,403 991 70.74% 833 518 782,530 59.24% 41.91%
Region 2b 3,183 2,914 2,312 79.33% 2,057 1,375 1,820,605 64.45% 51.13%
Region 2c (Winnebago) 559 502 364 70.06% 231 166 239,220 73.71% 51.64%
Region 2d 1,045 939 719 76.59% 576 390 551,575 65.16% 49.90%
Region 3 2,596 2,210 1,881 85.11% 1,419 960 1,208,296 64.79% 55.15%
Region 3a (Champaign) 357 322 276 85.31% 229 154 172,198 64.26% 54.82%
Region 3b 2,239 1,888 1,605 85.08% 1,190 806 1,036,097 64.89% 55.21%
Region 4 1,639 1,393 1,208 86.82% 820 584 753,290 69.65% 60.46%
Region 4a (Sangamon) 369 324 277 85.76% 190 138 167,678 72.32% 62.02%
Region 4b 1,270 1,069 931 87.14% 630 446 585,612 68.91% 60.05%
Region 5 2,113 1,707 1,380 81.11% 997 697 998,455 67.52% 54.76%
Region 5a 875 684 539 78.80% 382 274 444,704 69.76% 54.97%
Region 5b 1,238 1,023 841 82.64% 615 423 553,751 66.19% 54.70%
Indiana 7,793 6,519 5,266 80.79% 3,956 2,873 5,483,151 69.99% 56.55%
Central 2,193 1,972 1,480 75.15% 1,194 856 1,455,692 70.38% 52.89%
East 644 485 426 87.89% 314 232 459,504 72.55% 63.77%
North Central 1,089 907 752 82.61% 519 391 769,741 72.96% 60.28%
Northeast 752 653 552 84.38% 415 304 540,515 70.62% 59.59%
Northwest 799 677 556 81.93% 471 332 620,599 62.56% 51.26%
Southeast 840 706 603 85.56% 425 305 588,921 70.81% 60.58%
Southwest 604 529 411 78.03% 274 206 428,875 71.73% 55.97%
West 872 590 486 82.17% 344 247 619,304 67.81% 55.72%
Iowa 8,457 7,230 6,192 85.61% 4,011 2,902 2,597,970 70.57% 60.41%
Central 1,557 1,374 1,121 81.57% 765 529 472,094 66.89% 54.57%
North Central 978 799 686 85.80% 438 320 287,303 70.40% 60.40%
Northeast 1,979 1,746 1,515 86.75% 1,016 734 631,363 71.09% 61.67%
Northwest 1,318 1,101 1,010 91.80% 602 445 394,239 69.87% 64.15%
Southeast 1,881 1,620 1,336 82.25% 854 625 551,512 72.10% 59.31%
Southwest 744 590 524 89.00% 336 249 261,459 74.40% 66.22%
Kansas 7,466 6,477 5,515 85.10% 4,010 2,964 2,364,482 72.14% 61.39%
Northeast 3,697 3,312 2,673 80.50% 2,026 1,485 1,182,405 71.29% 57.39%
Northwest and North Central 551 457 407 89.17% 243 168 188,357 69.46% 61.94%
South Central 2,249 1,912 1,713 89.72% 1,225 928 681,690 74.69% 67.01%
Southeast 510 415 375 90.32% 252 182 175,731 65.82% 59.44%
Southwest 459 381 347 91.30% 264 201 136,298 76.56% 69.90%
Kentucky 8,187 6,666 5,626 84.54% 4,000 2,837 3,668,395 67.98% 57.47%
Adanta, Cumberland River, and Lifeskills 1,413 1,088 942 87.04% 641 438 614,496 66.01% 57.46%
Bluegrass, Comprehend, and North Key 2,408 1,992 1,707 85.86% 1,249 874 1,078,518 67.22% 57.71%
Centerstone 1,805 1,532 1,294 84.31% 905 706 814,353 72.59% 61.20%
Communicare and River Valley 723 609 531 87.29% 397 263 408,784 61.58% 53.75%
Four Rivers and Pennyroyal 834 693 553 79.51% 366 257 343,762 69.32% 55.12%
Kentucky River, Mountain, and Pathways 1,004 752 599 80.33% 442 299 408,482 68.42% 54.96%
Louisiana 7,999 6,538 5,480 84.25% 3,912 2,908 3,816,673 72.37% 60.97%
Regions 1 and 10 1,541 1,311 1,083 83.26% 776 568 746,613 70.59% 58.77%
Region 1 657 527 446 85.04% 319 244 389,722 76.99% 65.47%
Region 10 (Jefferson) 884 784 637 82.44% 457 324 356,891 67.17% 55.37%
Regions 2 and 9 2,163 1,809 1,519 84.62% 1,105 816 1,013,680 75.82% 64.16%
Region 3 744 637 563 88.53% 410 328 327,511 77.86% 68.93%
Regions 4, 5, and 6 2,038 1,572 1,267 80.71% 897 629 979,634 66.21% 53.44%
Regions 7 and 8 1,513 1,209 1,048 87.24% 724 567 749,235 73.89% 64.46%
Maine 11,560 8,526 7,222 84.98% 4,024 2,926 1,155,877 71.91% 61.10%
Aroostook/Downeast 1,528 1,036 937 90.88% 520 407 138,205 79.60% 72.34%
Aroostook 740 547 490 90.10% 294 240 61,755 83.31% 75.07%
Downeast 788 489 447 91.70% 226 167 76,450 74.61% 68.41%
Central 1,382 1,038 854 82.70% 445 340 150,204 76.56% 63.31%
Cumberland 2,435 1,943 1,596 82.49% 975 654 248,377 68.13% 56.20%
Midcoast 1,210 883 756 85.86% 396 294 128,172 72.63% 62.36%
Penquis 1,435 1,083 965 89.42% 473 359 149,029 75.37% 67.39%
Western 1,869 1,292 1,087 84.54% 615 454 167,659 71.38% 60.34%
York 1,701 1,251 1,027 81.81% 600 418 174,230 65.35% 53.46%
Maryland 7,209 6,389 4,820 74.94% 3,904 2,907 5,011,465 71.70% 53.73%
Anne Arundel 658 609 450 72.95% 372 278 471,453 73.44% 53.58%
Baltimore City 982 812 633 77.89% 495 388 518,452 76.60% 59.67%
Baltimore County 934 831 554 65.85% 401 292 698,887 70.41% 46.37%
Montgomery 1,194 1,115 834 73.77% 706 534 860,532 73.79% 54.44%
North Central 609 566 442 77.93% 351 255 402,195 68.74% 53.56%
Northeast 594 520 413 78.91% 325 224 419,191 67.23% 53.05%
Prince George's 942 870 603 69.42% 540 385 736,311 67.62% 46.94%
South 638 558 463 82.87% 357 278 480,838 74.88% 62.05%
West 658 508 428 84.22% 357 273 423,607 70.79% 59.62%
Massachusetts 10,014 8,753 6,564 75.36% 4,624 2,936 5,813,831 62.04% 46.75%
Boston 1,201 1,056 694 66.34% 540 336 730,029 59.66% 39.58%
Central 1,235 1,137 867 76.34% 618 390 749,026 62.50% 47.72%
Metrowest 2,203 2,033 1,514 74.74% 1,036 643 1,352,593 60.69% 45.35%
Northeast 2,016 1,898 1,474 78.00% 1,095 706 1,144,574 62.23% 48.54%
Southeast 2,049 1,508 1,180 77.94% 778 498 1,109,094 63.59% 49.56%
Western 1,310 1,121 835 75.43% 557 363 728,515 63.44% 47.86%
Michigan 20,865 17,084 14,160 82.78% 9,963 7,279 8,390,651 70.32% 58.22%
Region 1 913 625 541 86.61% 332 245 273,965 71.09% 61.57%
Region 2 1,086 733 612 83.58% 350 244 439,495 70.09% 58.59%
Region 3 2,268 1,983 1,676 84.38% 1,336 1,013 1,033,763 73.73% 62.21%
Region 4 1,888 1,603 1,359 84.13% 952 727 708,970 74.97% 63.06%
Region 5 3,920 3,013 2,585 85.82% 1,747 1,365 1,408,645 76.76% 65.88%
Region 6 1,346 1,191 981 82.47% 746 562 680,057 72.11% 59.47%
Region 7 3,627 2,865 2,236 77.84% 1,661 1,160 1,471,779 65.75% 51.18%
Region 8 2,540 2,316 1,847 79.75% 1,257 860 1,056,401 66.75% 53.23%
Region 9 1,690 1,556 1,279 81.99% 908 600 724,098 61.26% 50.23%
Region 10 1,587 1,199 1,044 87.13% 674 503 593,478 71.10% 61.95%
Minnesota 7,461 6,538 5,446 83.28% 3,927 2,880 4,574,972 72.39% 60.29%
Regions 1 and 2 959 730 601 82.13% 375 256 454,682 67.60% 55.52%
Region 1 402 333 258 76.79% 162 106 171,843 65.83% 50.55%
Region 2 557 397 343 86.45% 213 150 282,840 68.82% 59.50%
Regions 3 and 4 1,435 1,170 998 85.32% 714 529 778,084 74.61% 63.66%
Region 3 339 259 215 83.06% 161 118 271,946 74.14% 61.58%
Region 4 1,096 911 783 86.00% 553 411 506,138 74.75% 64.28%
Regions 5 and 6 1,191 1,032 913 88.51% 699 490 847,281 68.01% 60.20%
Region 5 589 501 450 89.83% 377 272 428,215 68.62% 61.64%
Region 6 602 531 463 87.27% 322 218 419,066 67.29% 58.72%
Region 7 3,876 3,606 2,934 81.34% 2,139 1,605 2,494,926 73.80% 60.03%
Region 7A (Hennepin) 1,624 1,534 1,230 80.19% 925 690 1,023,049 75.17% 60.28%
Region 7B (Ramsey) 742 661 548 82.89% 395 305 447,005 77.22% 64.00%
Region 7C 1,510 1,411 1,156 81.84% 819 610 1,024,872 70.98% 58.09%
Mississippi 7,135 5,723 4,856 84.99% 3,710 2,764 2,447,101 72.55% 61.66%
Region 1 1,587 1,328 1,160 87.49% 925 692 556,236 73.32% 64.14%
Region 2 900 648 518 79.86% 385 316 298,326 76.60% 61.17%
Region 3 998 793 704 88.90% 526 393 341,474 71.21% 63.30%
Region 4 1,230 1,077 851 79.03% 688 507 454,881 73.95% 58.44%
Region 5 436 292 261 90.09% 189 137 147,446 71.48% 64.39%
Region 6 906 717 659 91.99% 479 364 253,078 73.75% 67.85%
Region 7 1,078 868 703 81.37% 518 355 395,660 66.70% 54.27%
Missouri 7,772 6,457 5,611 86.84% 3,894 2,858 5,053,610 70.60% 61.31%
Central 1,066 840 746 88.85% 498 361 686,509 70.27% 62.43%
Eastern 2,690 2,327 2,043 87.77% 1,382 1,018 1,756,158 70.85% 62.18%
Eastern (St. Louis City and County) 1,606 1,328 1,160 87.33% 768 580 1,104,367 73.46% 64.16%
Eastern (excluding St. Louis) 1,084 999 883 88.34% 614 438 651,791 67.84% 59.93%
Northwest 1,891 1,598 1,358 84.83% 966 722 1,224,829 72.21% 61.26%
Northwest (Jackson) 957 822 681 82.47% 509 391 559,340 73.19% 60.37%
Northwest (excluding Jackson) 934 776 677 87.31% 457 331 665,490 71.19% 62.16%
Southeast 848 685 606 88.51% 441 343 598,268 75.10% 66.48%
Southwest 1,277 1,007 858 85.15% 607 414 787,845 65.23% 55.54%
Montana 9,241 7,400 6,442 87.27% 4,049 2,972 867,472 71.00% 61.96%
Region 1 658 412 389 94.67% 271 209 68,591 76.91% 72.82%
Region 2 1,409 1,145 1,019 88.97% 629 471 122,807 70.77% 62.97%
Region 3 2,005 1,728 1,468 85.09% 905 651 179,688 71.84% 61.14%
Region 4 2,380 1,874 1,613 86.41% 1,049 748 230,640 69.56% 60.10%
Region 5 2,789 2,241 1,953 87.42% 1,195 893 265,746 70.66% 61.77%
Nebraska 7,665 6,608 5,517 83.50% 3,933 2,847 1,547,666 71.18% 59.44%
Regions 1 and 2 808 653 576 88.40% 328 235 156,621 70.52% 62.34%
Region 1 406 318 277 86.98% 168 121 73,417 70.53% 61.34%
Region 2 402 335 299 89.84% 160 114 83,205 70.51% 63.35%
Region 3 1,072 912 815 89.43% 553 418 190,009 74.54% 66.66%
Region 4 798 669 616 92.09% 430 307 170,599 66.68% 61.40%
Region 5 1,831 1,576 1,324 84.29% 866 639 383,101 72.61% 61.21%
Region 6 3,156 2,798 2,186 77.86% 1,756 1,248 647,336 70.54% 54.92%
Nevada 7,476 6,429 4,864 75.54% 3,864 2,924 2,405,650 71.78% 54.23%
Clark – Region 1 5,321 4,622 3,443 74.34% 2,794 2,128 1,735,247 71.81% 53.38%
Region 3 939 732 588 80.28% 388 272 294,972 66.88% 53.69%
Capital District 304 264 200 75.15% 136 97 140,001 64.62% 48.56%
Rural/Frontier 635 468 388 83.41% 252 175 154,971 68.57% 57.19%
Washoe – Region 2 1,216 1,075 833 77.48% 682 524 375,432 74.86% 58.00%
New Hampshire 9,612 7,965 6,394 80.22% 4,078 2,863 1,151,028 68.07% 54.61%
Central 2,965 2,506 2,098 83.73% 1,396 1,011 326,910 69.81% 58.45%
Central 1 1,373 1,124 952 84.79% 642 463 161,866 69.43% 58.87%
Central 2 1,592 1,382 1,146 82.86% 754 548 165,044 70.15% 58.12%
Northern 1,677 1,012 825 80.84% 442 333 148,941 71.43% 57.74%
Southern 4,970 4,447 3,471 78.13% 2,240 1,519 675,177 66.38% 51.86%
Southern 1 (Rockingham) 1,812 1,653 1,262 76.66% 793 521 260,103 66.55% 51.01%
Southern 2 3,158 2,794 2,209 78.98% 1,447 998 415,074 66.28% 52.35%
New Jersey 12,849 11,258 8,549 75.30% 6,563 4,486 7,541,739 66.11% 49.78%
Central 2,964 2,620 1,951 72.13% 1,492 976 1,730,180 64.23% 46.33%
Metropolitan 3,130 2,696 2,004 74.27% 1,506 1,015 1,820,453 64.98% 48.27%
Northern 4,212 3,743 2,880 76.81% 2,249 1,556 2,426,107 65.18% 50.06%
Southern 2,543 2,199 1,714 77.96% 1,316 939 1,565,000 71.26% 55.56%
New Mexico 7,788 5,622 4,919 87.64% 3,647 2,898 1,721,763 77.80% 68.18%
Region 1 1,344 1,047 918 87.94% 731 594 358,976 78.36% 68.91%
Region 2 976 664 581 87.98% 414 347 248,007 80.11% 70.47%
Region 3 (Bernalillo) 2,520 1,991 1,700 85.29% 1,254 971 559,940 77.19% 65.83%
Region 4 872 675 615 91.31% 479 378 214,196 74.48% 68.01%
Region 5 2,076 1,245 1,105 88.91% 769 608 340,644 78.81% 70.07%
Region 5a 1,378 693 612 88.69% 378 301 161,878 77.95% 69.13%
Region 5b (Dona Ana) 698 552 493 89.21% 391 307 178,766 79.92% 71.29%
New York 35,578 30,774 20,398 65.88% 14,732 9,826 16,748,149 63.04% 41.53%
Region 1: Long Island 4,668 4,134 2,799 67.65% 2,266 1,369 2,434,332 57.39% 38.83%
Region 2: New York City 14,905 13,215 7,850 58.74% 6,058 3,742 7,202,566 57.98% 34.06%
Region 2A: Bronx 2,292 2,137 1,517 71.00% 1,197 885 1,171,688 71.88% 51.03%
Region 2B: Kings 4,226 3,659 2,313 63.32% 1,785 1,035 2,180,764 54.68% 34.62%
Region 2C: New York 3,998 3,431 1,709 48.01% 1,171 744 1,467,390 61.25% 29.40%
Region 2D: Queens 3,614 3,297 1,843 55.96% 1,537 846 1,981,210 51.51% 28.82%
Region 2E: Richmond 775 691 468 68.15% 368 232 401,513 59.45% 40.52%
Region 3: Mid-Hudson 4,331 3,705 2,359 63.52% 1,646 1,071 1,955,838 61.75% 39.22%
Region 4: Capital Region 1,519 1,276 925 72.78% 641 474 812,980 74.06% 53.90%
Region 5: Mohawk Valley 367 251 207 82.61% 153 116 222,088 78.03% 64.47%
Region 6: North Country 673 472 382 79.94% 213 166 263,280 77.23% 61.74%
Region 7: Tug Hill Seaway 691 489 419 85.71% 275 216 214,345 75.50% 64.72%
Region 8: Central 2,008 1,647 1,239 75.35% 807 636 866,864 77.11% 58.10%
Region 9: Southern Tier 860 693 553 79.56% 341 287 382,701 81.89% 65.15%
Region 10: Finger Lakes 2,328 2,058 1,525 73.93% 971 722 1,085,658 71.52% 52.87%
Region 11: Western 3,228 2,834 2,140 75.64% 1,361 1,027 1,307,498 71.36% 53.98%
North Carolina 12,558 10,519 8,794 83.54% 6,170 4,617 8,318,964 72.62% 60.67%
Alliance Behavioral Healthcare 1 1,261 1,054 911 86.33% 655 500 657,907 73.18% 63.18%
Alliance Behavioral Healthcare 2 1,015 898 755 84.15% 549 416 820,197 73.50% 61.85%
Cardinal Innovations Healthcare Solutions 1 944 840 683 81.08% 500 340 632,700 66.16% 53.64%
Cardinal Innovations Healthcare Solutions 2 742 623 543 87.15% 376 283 568,160 73.41% 63.98%
Cardinal Innovations Healthcare Solutions 3 1,224 1,064 842 79.09% 612 447 822,355 70.22% 55.54%
CenterPoint Human Services 817 679 555 81.70% 380 295 459,622 76.49% 62.49%
Eastpointe 1,244 1,095 920 84.21% 649 493 691,059 73.60% 61.98%
Partners Behavioral Health Management 914 785 665 84.66% 465 355 768,880 71.83% 60.81%
Sandhills Center 1 519 439 367 83.59% 253 191 479,961 76.22% 63.71%
Sandhills Center 2 680 597 480 80.56% 355 264 432,615 71.90% 57.92%
Smoky Mountain Center 1 881 641 546 85.21% 370 269 460,631 71.51% 60.93%
Smoky Mountain Center 2 773 644 545 84.57% 313 228 458,990 72.78% 61.55%
Trillium Health Resources 1 949 704 588 82.90% 443 361 524,436 78.10% 64.75%
Trillium Health Resources 2 595 456 394 86.16% 250 175 541,448 68.82% 59.30%
North Dakota 9,979 8,003 7,141 89.28% 3,926 2,917 617,037 72.96% 65.14%
Badlands and West Central 2,704 2,129 2,001 94.05% 1,090 807 165,469 72.78% 68.45%
Badlands 567 389 368 94.52% 181 132 37,436 73.69% 69.65%
West Central 2,137 1,740 1,633 93.94% 909 675 128,033 72.59% 68.19%
Lake Region 681 500 447 89.34% 224 172 34,469 78.01% 69.69%
North Central 1,267 963 854 88.47% 460 347 86,655 73.46% 65.00%
Northeast 1,403 1,178 1,014 86.31% 574 426 77,789 71.56% 61.77%
Northwest 448 301 266 88.77% 171 111 33,304 60.87% 54.03%
South Central 842 600 539 89.37% 241 173 48,790 75.08% 67.10%
Southeast 2,634 2,332 2,020 86.73% 1,166 881 170,560 73.92% 64.11%
Ohio 20,158 17,139 14,004 81.70% 10,158 7,220 9,725,850 68.62% 56.06%
Boards 2, 46, 55, and 68 674 588 492 83.62% 376 256 428,775 64.61% 54.03%
Boards 3, 52, and 85 527 488 397 81.47% 309 219 320,796 73.43% 59.83%
Boards 4 and 78 602 502 437 87.11% 297 226 261,594 76.24% 66.42%
Boards 5 and 60 495 427 388 90.75% 297 213 287,227 70.42% 63.91%
Boards 7, 15, 41, 79, and 84 839 713 555 77.51% 369 238 390,557 62.26% 48.25%
Boards 8, 13, and 83 628 576 456 79.05% 332 230 422,162 64.41% 50.92%
Board 9 (Butler) 660 584 475 81.39% 356 229 310,689 62.01% 50.47%
Board 12 721 570 405 71.43% 305 213 293,200 68.71% 49.08%
Boards 18 and 47 2,791 2,357 1,849 78.39% 1,275 923 1,315,794 70.35% 55.15%
Boards 20, 32, 54, and 69 762 672 619 91.97% 426 311 286,136 71.80% 66.03%
Boards 21, 39, 51, 70, and 80 640 559 493 88.22% 426 315 468,487 71.65% 63.21%
Boards 22, 74, and 87 897 607 537 88.37% 401 301 328,042 71.24% 62.95%
Boards 23 and 45 736 629 542 86.28% 465 324 317,970 65.97% 56.92%
Board 25 (Franklin) 2,115 1,867 1,441 77.42% 1,118 790 1,007,348 68.67% 53.16%
Boards 27, 71, and 73 917 706 572 80.78% 412 275 414,284 62.10% 50.16%
Boards 28, 43, and 67 897 780 686 88.05% 496 344 415,913 67.49% 59.43%
Board 31 (Hamilton) 1,595 1,321 1,041 78.64% 716 500 663,396 66.98% 52.68%
Board 48 (Lucas) 670 590 502 85.08% 342 254 363,436 66.86% 56.88%
Boards 50 and 76 1,163 1,029 894 86.84% 604 433 517,995 70.08% 60.86%
Board 57 (Montgomery) 996 839 639 76.43% 410 313 456,829 74.09% 56.63%
Board 77 (Summit) 833 735 584 79.63% 426 313 455,218 68.66% 54.67%
Oklahoma 7,770 6,311 5,321 84.55% 4,017 2,873 3,180,210 68.10% 57.58%
Central 929 816 661 81.31% 560 395 406,362 65.73% 53.45%
East Central 795 633 563 89.34% 435 310 363,907 69.08% 61.72%
Northeast 954 765 684 89.42% 493 349 403,170 68.38% 61.15%
Northwest and Southwest 1,250 901 797 88.79% 542 411 452,073 70.67% 62.75%
Oklahoma County 1,426 1,198 957 79.85% 690 493 616,207 67.01% 53.51%
Southeast 1,085 853 727 85.88% 553 397 429,603 69.98% 60.10%
Tulsa County 1,331 1,145 932 81.70% 744 518 508,888 66.86% 54.63%
Oregon 8,215 7,167 5,904 82.57% 4,042 2,958 3,424,658 71.66% 59.17%
Region 1 (Multnomah) 1,633 1,481 1,221 82.69% 852 599 676,840 69.74% 57.67%
Region 2 1,867 1,725 1,429 83.19% 1,096 817 811,991 73.03% 60.75%
Region 3 2,379 2,058 1,647 80.00% 1,132 835 1,063,850 72.54% 58.03%
Region 4 1,455 1,198 979 81.90% 549 415 483,699 71.40% 58.47%
Region 5 (Central) 299 265 236 89.31% 155 103 178,587 70.50% 62.97%
Region 6 (Eastern) 582 440 392 89.38% 258 189 209,690 69.97% 62.54%
Pennsylvania 22,355 18,950 15,206 80.16% 9,726 7,122 10,839,410 71.00% 56.92%
Region 1 (Allegheny) 2,263 1,993 1,555 78.17% 907 611 1,059,578 67.40% 52.68%
Regions 3, 8, 9, and 51 1,470 1,250 1,035 82.91% 638 475 597,776 72.05% 59.74%
Regions 4, 11, 37, and 49 1,652 1,247 1,017 81.69% 621 437 767,695 70.32% 57.44%
Regions 5, 18, 23, 24, and 46 1,400 1,217 1,019 83.60% 650 497 633,833 73.21% 61.20%
Regions 6, 12, 16, 31, 35, 45, and 47 1,051 854 698 81.83% 500 383 608,238 72.53% 59.35%
Regions 7, 13, 20, and 33 4,176 3,801 2,845 73.95% 1,908 1,356 2,117,660 68.44% 50.61%
Regions 10, 15, 27, 32, 43, and 44 908 665 588 88.57% 359 279 436,103 73.91% 65.46%
Regions 17 and 21 674 518 449 86.64% 287 213 311,440 74.36% 64.42%
Regions 19, 26, 28, and 42 2,341 2,121 1,848 87.12% 1,186 887 1,233,033 72.54% 63.20%
Regions 22, 38, 40, 41, and 48 1,458 1,237 1,044 84.39% 618 445 708,013 69.50% 58.66%
Regions 29 and 34 1,117 918 793 86.85% 461 316 558,238 66.20% 57.49%
Regions 30 and 50 1,127 946 791 83.87% 510 392 518,639 76.89% 64.49%
Region 36 (Philadelphia) 2,718 2,183 1,524 69.95% 1,081 831 1,289,164 74.37% 52.02%
Rhode Island 8,654 7,365 5,817 79.21% 4,044 2,892 903,919 69.62% 55.14%
Region 1: Southern Providence County 1,353 1,242 950 76.88% 672 442 165,030 66.75% 51.32%
Region 2: Northern Providence County/
   Blackstone Valley
1,913 1,708 1,407 82.38% 1,010 737 181,461 69.45% 57.22%
Region 3: Providence 1,236 985 718 73.32% 608 470 150,431 75.50% 55.35%
Region 4: Kent County 1,248 1,136 908 80.50% 592 432 147,798 71.13% 57.26%
Region 5: East Bay 809 727 568 78.42% 390 287 83,752 70.49% 55.28%
Region 6: Newport County 843 648 525 81.07% 326 202 71,293 63.81% 51.73%
Region 7: South County 1,252 919 741 80.77% 446 322 104,153 69.89% 56.45%
South Carolina 8,619 6,994 5,847 83.46% 3,938 2,955 4,071,052 73.37% 61.24%
Region 1 2,608 2,133 1,756 82.11% 1,155 849 1,274,110 70.05% 57.52%
Region 2 2,108 1,768 1,480 83.57% 1,089 796 1,001,686 71.17% 59.48%
Region 3 1,571 1,279 1,105 86.33% 714 536 705,283 74.78% 64.56%
Region 4 2,332 1,814 1,506 82.99% 980 774 1,089,973 78.16% 64.86%
South Dakota 7,330 6,085 5,515 90.96% 3,812 2,845 698,307 73.62% 66.97%
Region 1 1,750 1,476 1,338 90.89% 901 687 172,217 74.65% 67.85%
Region 2 661 552 499 90.69% 332 254 64,285 77.26% 70.07%
Region 3 1,844 1,429 1,322 92.80% 886 661 164,858 74.42% 69.07%
Region 4 1,087 897 812 90.98% 545 409 98,178 71.61% 65.16%
Region 5 1,988 1,731 1,544 89.57% 1,148 834 198,769 71.98% 64.47%
Tennessee 8,030 6,527 5,524 84.75% 3,929 2,943 5,508,015 72.95% 61.82%
Region 1 685 584 500 85.10% 364 272 445,617 70.25% 59.78%
Region 2 1,461 1,167 997 85.50% 649 503 1,031,340 77.28% 66.08%
Region 3 1,352 1,054 941 89.39% 642 488 825,704 76.10% 68.03%
Region 4 (Davidson) 790 684 507 74.74% 382 260 545,915 66.00% 49.32%
Region 5 1,704 1,475 1,247 84.81% 943 681 1,340,254 73.03% 61.93%
Region 6 905 658 607 92.26% 381 285 535,742 66.41% 61.27%
Region 7 (Shelby) 1,133 905 725 80.36% 568 454 783,443 75.29% 60.50%
Texas 20,024 16,766 14,481 86.18% 13,194 9,984 22,110,904 72.80% 62.73%
Region 1 717 597 505 84.48% 412 296 720,872 70.41% 59.48%
Region 2 609 478 439 92.00% 325 254 464,435 76.34% 70.23%
Region 3 5,079 4,532 4,069 89.79% 3,823 3,002 5,965,536 76.39% 68.59%
Region 3a 3,184 2,876 2,522 87.71% 2,430 1,835 3,811,325 72.96% 64.00%
Region 3bc 1,895 1,656 1,547 93.46% 1,393 1,167 2,154,212 82.46% 77.07%
Region 4 1,171 806 736 91.15% 580 486 960,048 81.68% 74.45%
Region 5 666 471 447 95.18% 326 265 661,439 78.95% 75.14%
Region 6 4,665 3,960 3,194 80.59% 3,051 2,116 5,368,072 65.03% 52.41%
Region 6a 4,157 3,604 2,881 79.84% 2,750 1,906 4,805,141 65.08% 51.96%
Region 6bc 508 356 313 87.61% 301 210 562,931 64.54% 56.54%
Region 7 2,537 2,146 1,848 86.23% 1,651 1,221 2,685,359 71.80% 61.91%
Region 7a 1,552 1,335 1,148 86.23% 1,007 715 1,714,533 69.64% 60.05%
Region 7bcd 985 811 700 86.23% 644 506 970,827 75.53% 65.13%
Region 8 2,134 1,737 1,455 83.88% 1,310 1,016 2,305,620 75.07% 62.97%
Region 9 451 365 327 89.26% 291 189 494,537 61.94% 55.28%
Region 10 511 451 399 88.52% 380 294 718,969 75.50% 66.83%
Region 11 1,484 1,223 1,062 84.23% 1,045 845 1,766,017 76.63% 64.55%
Region 11abd 898 808 707 87.65% 679 535 1,113,103 74.45% 65.25%
Region 11c (Hidalgo) 586 415 355 79.20% 366 310 652,914 80.24% 63.54%
Utah 4,523 3,991 3,589 89.98% 3,605 2,876 2,359,519 77.60% 69.82%
Bear River, Northeastern, Summit, Tooele,
   and Wasatch
400 346 322 93.13% 311 251 284,421 79.58% 74.11%
Central, Four Corners, San Juan, and
   Southwest
660 478 424 88.56% 380 282 285,613 72.46% 64.18%
Central, Four Corners, and San Juan 306 204 184 89.83% 160 116 109,353 73.52% 66.05%
Southwest 354 274 240 87.66% 220 166 176,260 71.62% 62.79%
Davis County 415 389 338 86.36% 323 252 255,266 76.18% 65.79%
Salt Lake County 1,869 1,716 1,529 89.28% 1,575 1,279 895,778 79.06% 70.58%
Utah County 748 682 621 91.15% 656 518 434,211 76.49% 69.72%
Weber, Morgan 431 380 355 93.72% 360 294 204,230 78.41% 73.49%
Vermont 10,948 8,693 7,070 81.26% 3,913 2,804 545,119 71.25% 57.90%
Champlain Valley 3,984 3,489 2,824 80.89% 1,743 1,237 219,413 69.19% 55.97%
Rural Northeast 2,453 1,869 1,389 74.09% 768 552 128,344 72.28% 53.55%
Rural Southeast 2,593 1,930 1,639 84.98% 806 583 112,629 73.11% 62.13%
Rural Southwest 1,918 1,405 1,218 86.81% 596 432 84,734 73.18% 63.53%
Virginia 11,525 10,047 8,175 81.46% 6,210 4,558 6,920,132 70.57% 57.49%
Region 1 1,573 1,365 1,167 85.39% 858 666 1,075,646 74.06% 63.24%
Region 2 3,000 2,753 2,151 78.36% 1,859 1,285 1,969,310 65.75% 51.52%
Region 3 2,221 1,817 1,573 86.48% 1,035 793 1,159,100 74.24% 64.21%
Region 4 1,948 1,725 1,389 80.54% 1,056 774 1,178,568 71.25% 57.39%
Region 5 2,783 2,387 1,895 79.51% 1,402 1,040 1,537,508 71.21% 56.62%
Washington 7,920 7,017 5,483 78.16% 3,909 2,813 5,983,711 70.11% 54.79%
Region 1 1,587 1,320 1,108 83.99% 881 639 1,297,892 70.82% 59.48%
Greater Columbia and North Central 972 809 676 83.66% 580 417 772,866 69.21% 57.90%
Spokane 615 511 432 84.53% 301 222 525,025 73.58% 62.19%
Region 2 3,778 3,425 2,571 74.98% 1,794 1,243 2,757,283 67.05% 50.28%
King 2,524 2,310 1,658 71.54% 1,175 806 1,761,061 66.40% 47.50%
North Sound 1,254 1,115 913 82.24% 619 437 996,223 68.34% 56.21%
Region 3 2,555 2,272 1,804 79.59% 1,234 931 1,928,536 74.43% 59.24%
Pierce 1,255 1,130 875 77.61% 619 485 704,398 78.28% 60.76%
Salish 381 334 278 82.82% 175 121 320,556 68.65% 56.86%
SW WA and Great Rivers 628 572 450 79.14% 317 239 621,859 73.54% 58.20%
Thurston-Mason 291 236 201 85.41% 123 86 281,722 66.98% 57.21%
West Virginia 9,626 7,859 6,526 83.15% 4,122 2,842 1,572,220 66.11% 54.97%
Region I 679 596 500 84.07% 285 190 124,260 62.73% 52.74%
Region II 1,188 1,026 867 84.54% 584 434 223,897 73.35% 62.01%
Region III 895 712 614 86.38% 376 261 144,615 64.86% 56.02%
Region IV 2,075 1,744 1,441 82.54% 995 657 347,400 65.47% 54.04%
Region V 2,672 2,127 1,759 82.81% 1,062 693 445,709 61.18% 50.67%
Region VI 2,117 1,654 1,345 81.62% 820 607 286,339 70.09% 57.21%
Wisconsin 9,625 7,918 6,614 83.55% 4,065 2,924 4,850,551 70.47% 58.88%
Milwaukee 1,610 1,462 1,153 78.70% 705 490 783,239 67.91% 53.44%
Northeastern 1,876 1,677 1,386 82.42% 779 573 1,052,103 74.47% 61.38%
Northern 1,316 719 616 85.90% 326 256 417,435 78.72% 67.62%
Southeastern 1,837 1,645 1,350 82.27% 921 626 985,969 66.92% 55.06%
Southern 1,925 1,606 1,393 86.47% 874 640 949,286 68.58% 59.30%
Western 1,061 809 716 88.64% 460 339 662,520 71.40% 63.29%
Wyoming 8,243 6,401 5,544 86.57% 3,822 2,890 481,640 73.85% 63.93%
Judicial District 1 (Laramie) 1,383 1,160 972 83.75% 631 460 79,139 69.94% 58.58%
Judicial District 2 853 633 545 85.74% 433 347 46,291 79.51% 68.18%
Judicial District 3 1,167 818 733 89.09% 530 412 67,465 77.26% 68.83%
Judicial District 4 456 349 300 85.97% 190 134 32,153 67.00% 57.60%
Judicial District 5 864 679 574 84.64% 333 259 46,042 80.30% 67.96%
Judicial District 6 918 719 623 87.04% 441 350 50,169 78.56% 68.38%
Judicial District 7 (Natrona) 1,014 879 756 86.35% 541 430 65,305 78.62% 67.89%
Judicial District 8 632 484 432 89.22% 293 195 33,622 63.32% 56.50%
Judicial District 9 956 680 609 89.25% 430 303 61,452 67.29% 60.06%
DU = dwelling unit; SPA = service planning area.
NOTE: For substate region definitions, see the "2014-2016 National Survey on Drug Use and Health Substate Region Definitions" at https://www.samhsa.gov/data.
NOTE: To compute the pooled 2014-2016 weighted response rates, the three samples were combined, and the individual-year weights were used for the pooled sample. Thus, the response rates presented here are weighted across 3 years of data rather than being a simple average of the 2014, 2015, and 2016 individual response rates.
NOTE: The total responded column represents the combined sample size from the 2014, 2015, and 2016 NSDUHs.
NOTE: The population estimate is the simple average of the 2014, 2015, and 2016 population counts for individuals aged 12 or older. Because of rounding, the sum of the substate region population counts within a state may not exactly match the state population count listed in the table.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2014, 2015, and 2016.
180126
Table C2. – Sample Sizes, Weighted Interview Response Rates, and Population Estimates, by Substate Region, for Individuals Aged 12 to 20 and Adults Aged 18 or Older: 2014, 2015, and 2016 NSDUHs
State/Substate Region 12–20
Total
Selected
12–20
Total
Responded
12–20
Population
Estimate
12–20
Weighted
Interview
Response Rate
(Percentage)
18+
Total
Selected
18+
Total
Responded
18+
Population
Estimate
18+
Weighted
Interview
Response Rate
(Percentage)
Total United States 88,841 69,151 37,874,213 78.03% 216,172 152,806 242,602,294 68.74%
Northeast 17,552 13,182 6,446,688 74.02% 43,015 29,039 43,627,889 65.16%
Midwest 21,201 16,233 8,084,417 76.11% 50,884 35,759 51,280,094 68.46%
South 29,207 23,163 14,215,451 79.70% 70,878 51,166 90,640,312 70.44%
West 20,881 16,573 9,127,658 79.93% 51,395 36,842 57,053,999 69.03%
Alabama 1,222 964 583,463 80.07% 3,117 2,206 3,687,329 67.70%
Region 1 363 277 159,857 76.89% 899 635 1,035,597 67.25%
Region 2 364 275 187,245 75.93% 990 657 1,180,600 63.17%
Region 3 246 204 110,798 87.01% 565 417 660,982 71.82%
Region 4 249 208 125,563 83.91% 663 497 810,150 72.08%
Alaska 1,351 985 90,578 72.89% 3,080 2,172 524,044 69.33%
Anchorage 551 422 36,804 75.30% 1,349 975 215,449 70.10%
Northern 292 208 21,871 69.89% 642 441 115,457 67.40%
South Central 382 277 23,681 74.46% 783 551 137,679 70.52%
Southeast 126 78 8,222 63.31% 306 205 55,458 66.73%
Arizona 1,176 929 792,006 79.61% 3,063 2,246 5,097,411 72.70%
Central 723 574 483,793 79.84% 1,970 1,435 3,031,603 71.82%
North 117 84 89,562 72.73% 305 219 621,983 72.00%
South 336 271 218,652 81.54% 788 592 1,443,826 75.14%
South A 170 138 114,084 82.50% 473 359 795,469 76.32%
South B 166 133 104,567 80.63% 315 233 648,357 73.39%
Arkansas 1,254 990 345,621 78.49% 3,048 2,197 2,222,652 69.59%
Catchment Area 1 193 158 63,385 81.56% 516 348 362,320 66.60%
Catchment Area 2 133 111 36,724 83.18% 405 304 272,510 74.16%
Catchment Area 3 187 146 47,299 78.80% 431 326 293,789 75.45%
Catchment Area 4 143 116 31,108 83.17% 307 222 194,739 69.35%
Catchment Area 5 201 154 52,306 74.81% 485 342 334,562 65.76%
Catchment Area 6 108 90 23,726 81.57% 233 180 156,218 72.88%
Catchment Area 7 76 66 26,194 87.45% 171 130 170,946 74.41%
Catchment Area 8 213 149 64,878 69.34% 500 345 437,568 64.87%
California 5,967 4,775 4,784,400 79.99% 15,275 10,504 29,434,856 66.70%
Region 1R 180 136 107,076 76.15% 395 302 750,574 74.93%
Region 2R 184 154 127,834 83.69% 415 307 796,588 71.53%
Region 3R (Sacramento) 215 176 178,714 80.39% 623 460 1,111,600 71.28%
Region 4R 200 158 148,314 78.36% 531 360 1,029,401 66.96%
Region 5R (San Francisco) 51 38 57,099 68.06% 340 200 731,968 56.12%
Region 6 (Santa Clara) 292 230 212,871 79.69% 844 589 1,436,324 67.42%
Region 7R (Contra Costa) 182 147 132,712 80.94% 485 350 841,324 70.70%
Region 8R (Alameda) 192 152 176,169 79.00% 608 435 1,233,116 70.51%
Region 9R (San Mateo) 89 72 76,639 81.86% 303 205 583,830 67.61%
Region 10 179 129 167,426 70.32% 428 280 977,787 64.17%
Region 11 (Los Angeles) 1,557 1,227 1,227,942 78.95% 4,015 2,580 7,724,963 61.64%
LA SPA 1 and 5 138 112 124,934 82.35% 353 241 843,590 65.43%
LA SPA 2 382 292 253,028 75.69% 905 542 1,706,615 58.38%
LA SPA 3 236 175 216,070 74.04% 625 420 1,378,551 63.99%
LA SPA 4 99 82 111,247 83.44% 430 237 925,724 51.90%
LA SPA 6 197 162 156,949 82.92% 457 324 720,942 69.59%
LA SPA 7 231 173 180,454 75.58% 539 345 961,561 62.09%
LA SPA 8 274 231 185,260 84.61% 706 471 1,187,980 62.33%
Region 12R 143 120 115,900 85.79% 306 224 640,601 68.66%
Regions 13 and 19R 435 361 354,924 83.42% 956 703 1,837,605 71.41%
Region 14 (Orange) 446 343 383,565 76.57% 1,105 680 2,430,400 58.81%
Region 15R (Fresno) 160 126 138,530 76.44% 392 277 693,102 68.70%
Region 16R (San Diego) 452 383 386,786 84.96% 1,208 836 2,508,452 68.74%
Region 17R 325 277 214,799 83.14% 759 582 1,068,543 73.88%
Region 18R (San Bernardino) 385 303 307,658 80.74% 843 603 1,537,109 69.50%
Region 20R 162 131 136,808 83.31% 368 279 699,336 74.90%
Region 21R 138 112 132,631 78.49% 351 252 802,232 69.94%
Colorado 1,303 1,042 650,188 79.85% 3,060 2,154 4,107,426 69.62%
Region 1 167 118 102,188 70.29% 508 353 688,644 70.63%
Region 2 95 82 56,080 87.02% 221 147 314,026 59.43%
Region 3 398 332 181,725 84.07% 853 594 1,051,515 67.86%
Region 4 90 71 42,196 73.42% 179 142 281,980 78.05%
Region 5 173 142 69,054 80.55% 406 290 525,296 72.62%
Region 6 213 169 104,856 78.36% 522 361 704,640 69.26%
Region 7 167 128 94,088 78.22% 371 267 541,324 71.88%
Connecticut 1,308 999 440,718 77.32% 3,298 2,160 2,773,834 64.11%
Eastern 149 121 59,284 83.78% 423 293 340,079 66.69%
North Central 333 259 118,873 77.95% 923 617 776,864 65.53%
Northwestern 243 178 74,892 74.40% 589 395 475,800 69.51%
South Central 319 240 99,699 77.15% 784 509 652,746 62.21%
Southwest 264 201 87,971 75.68% 579 346 528,345 57.41%
Delaware 1,274 986 107,615 77.92% 2,997 2,105 725,071 70.07%
Kent 257 200 21,087 79.12% 567 409 130,096 69.90%
New Castle (excluding Wilmington City) 718 552 58,594 77.12% 1,668 1,147 370,720 69.70%
Sussex 215 161 19,735 74.64% 579 403 166,287 69.11%
Wilmington City 84 73 8,199 87.93% 183 146 57,967 78.21%
District of Columbia 1,037 862 55,389 83.78% 2,881 2,143 542,377 73.29%
Ward 1 68 59 6,159 93.60% 368 266 69,188 67.86%
Ward 2 96 84 6,166 85.27% 368 260 75,103 69.74%
Ward 3 96 74 5,779 74.66% 327 226 70,331 72.23%
Ward 4 150 120 6,323 80.12% 400 291 66,071 73.08%
Ward 5 141 114 7,253 80.79% 308 236 68,569 74.33%
Ward 6 98 88 4,442 85.33% 479 372 71,791 75.88%
Ward 7 173 148 8,934 87.48% 316 249 61,385 77.52%
Ward 8 215 175 10,332 82.72% 315 243 59,938 75.17%
Florida 4,326 3,455 2,112,061 80.15% 10,605 7,580 15,841,372 68.63%
Broward (Circuit 17) 307 254 197,862 83.19% 825 583 1,457,063 69.54%
Central I 717 575 293,723 80.61% 1,631 1,192 1,984,893 71.46%
Circuit 9 465 384 186,420 82.45% 1,055 785 1,178,609 72.96%
Circuit 18 252 191 107,303 77.27% 576 407 806,284 69.59%
Central II 1,142 884 561,947 77.46% 2,902 2,094 4,448,834 68.88%
Circuit 6 307 220 134,463 73.69% 755 510 1,173,449 64.76%
Circuit 10 224 183 84,823 82.41% 475 385 592,906 79.41%
Circuit 12 126 93 70,017 71.88% 331 247 643,096 75.82%
Circuit 13 (Hillsborough) 328 266 157,368 81.22% 872 621 1,034,066 66.97%
Circuit 20 157 122 115,277 74.68% 469 331 1,005,318 64.75%
Northeast 728 551 391,607 76.42% 1,757 1,191 2,965,173 65.11%
Circuit 4 248 188 133,307 74.83% 574 383 903,630 63.80%
Circuit 5 198 136 98,470 70.27% 502 345 897,402 68.46%
Circuit 7 169 141 94,000 84.81% 453 289 726,193 58.86%
Circuit 8 plus Columbia, Dixie, Hamilton,
   Lafayette, and Suwannee
113 86 65,830 77.90% 228 174 437,948 72.19%
Northwest 393 326 171,408 84.85% 969 743 1,172,641 73.49%
Circuit 1 197 161 82,970 82.64% 477 354 571,015 70.21%
Circuit 2 plus Madison and Taylor 141 121 57,271 88.00% 349 278 360,226 76.61%
Circuit 14 55 44 31,167 83.74% 143 111 241,400 76.87%
South (Circuits 11 and 16) 614 511 292,977 83.47% 1,444 1,041 2,186,453 69.51%
Southeast 425 354 202,537 82.14% 1,077 736 1,626,314 64.80%
Circuit 15 (Palm Beach) 280 234 139,028 82.37% 739 487 1,118,123 62.19%
Circuit 19 145 120 63,509 81.65% 338 249 508,191 70.23%
Georgia 1,899 1,530 1,232,724 80.30% 4,571 3,398 7,503,516 71.61%
Region 1 505 397 321,545 79.61% 1,158 816 1,924,757 68.16%
Region 2 282 228 159,654 79.51% 668 510 966,011 72.68%
Region 3 574 453 357,533 78.61% 1,427 1,049 2,244,757 70.33%
Region 4 113 99 77,785 86.13% 252 210 464,512 83.71%
Region 5 199 169 139,210 85.63% 482 375 859,320 75.78%
Region 6 226 184 176,996 80.42% 584 438 1,044,159 72.42%
Hawaii 1,322 1,013 148,317 77.00% 3,200 2,235 1,064,978 68.94%
Hawaii Island 221 170 20,261 76.83% 474 349 141,904 72.78%
Honolulu 854 665 104,456 78.44% 2,112 1,468 751,659 68.04%
Kauai 105 75 6,993 74.47% 239 171 51,617 73.47%
Maui 142 103 16,607 69.14% 375 247 119,797 67.21%
Idaho 1,251 998 215,761 80.10% 3,082 2,301 1,205,453 73.27%
Region 1 132 88 26,535 72.29% 375 244 171,286 62.93%
Region 2 66 51 14,042 75.39% 199 154 87,499 77.49%
Region 3 247 201 36,934 82.39% 551 422 188,302 75.13%
Region 4 325 269 58,998 82.75% 892 673 348,081 74.92%
Region 5 175 143 25,199 76.66% 399 313 137,821 77.65%
Region 6 92 72 16,742 80.08% 189 128 89,142 67.01%
Region 7 214 174 37,311 82.42% 477 367 183,322 74.00%
Illinois 3,405 2,495 1,551,146 73.53% 8,349 5,382 9,706,617 63.14%
Region 1 (Cook) 1,163 832 591,721 72.80% 3,093 1,929 3,980,259 61.36%
Region 1.1 (Far North Side) 56 30 44,374 49.35% 245 147 372,698 62.28%
Region 1.2 (Northwest Side) 76 49 32,313 66.42% 215 119 205,023 55.03%
Region 1.3 (North Central Side) 42 26 29,875 64.55% 200 113 385,950 57.72%
Region 1.4 (West Side) 86 67 55,939 76.40% 255 174 357,461 64.75%
Region 1.5 (South Side) 136 98 79,398 74.26% 273 180 500,953 69.51%
Region 1.6 (Southwest Side) 146 105 54,572 72.39% 331 199 266,658 58.31%
Region 1.7 (Suburban Cook) 621 457 295,251 75.43% 1,574 997 1,891,516 60.99%
Region 2 1,245 914 538,068 72.83% 2,748 1,748 3,024,899 62.64%
Region 2a (DuPage) 260 188 113,613 71.18% 628 370 703,190 57.87%
Region 2b 739 537 304,544 72.96% 1,502 974 1,609,372 63.40%
Region 2c (Winnebago) 65 51 34,195 78.56% 182 123 215,957 72.43%
Region 2d 181 138 85,716 73.08% 436 281 496,380 63.66%
Region 3 460 340 182,612 74.78% 1,086 722 1,103,337 64.22%
Region 3a (Champaign) 68 54 32,778 81.67% 196 130 160,071 63.91%
Region 3b 392 286 149,834 73.33% 890 592 943,266 64.28%
Region 4 235 182 103,777 77.91% 634 443 686,609 69.13%
Region 4a (Sangamon) 55 42 22,724 79.55% 151 109 152,156 72.08%
Region 4b 180 140 81,053 77.43% 483 334 534,453 68.31%
Region 5 302 227 134,967 75.07% 788 540 911,513 66.91%
Region 5a 119 96 61,492 77.66% 299 204 403,887 68.49%
Region 5b 183 131 73,475 73.25% 489 336 507,626 66.00%
Indiana 1,243 966 827,225 77.35% 3,043 2,160 4,943,155 69.15%
Central 373 283 215,549 75.09% 919 645 1,303,238 69.76%
East 92 69 69,367 76.05% 254 184 418,618 71.66%
North Central 161 133 117,127 79.93% 400 289 691,621 71.75%
Northeast 140 110 84,822 81.11% 307 221 482,206 69.51%
Northwest 154 120 91,921 77.86% 347 236 557,453 61.01%
Southeast 156 119 83,081 75.23% 306 214 531,555 70.13%
Southwest 80 68 61,626 87.58% 225 166 388,847 70.89%
West 87 64 103,732 71.72% 285 205 569,618 67.77%
Iowa 1,295 980 371,555 76.09% 3,048 2,174 2,354,955 70.02%
Central 242 175 67,913 70.55% 575 389 425,237 66.39%
North Central 125 97 43,668 78.01% 347 249 262,901 69.78%
Northeast 329 243 90,132 73.88% 786 568 573,041 71.00%
Northwest 199 160 55,823 85.30% 450 325 356,506 68.51%
Southeast 295 225 77,907 73.86% 632 453 501,572 71.66%
Southwest 105 80 36,112 78.90% 258 190 235,697 73.82%
Kansas 1,323 1,015 366,159 76.97% 3,051 2,242 2,126,952 71.83%
Northeast 671 503 183,915 74.83% 1,548 1,138 1,064,841 71.24%
Northwest and North Central 73 54 26,141 75.31% 182 124 171,274 69.24%
South Central 400 316 106,068 79.81% 936 702 610,972 74.29%
Southeast 78 64 26,245 81.29% 197 137 159,519 64.24%
Southwest 101 78 23,790 78.11% 188 141 120,346 76.08%
Kentucky 1,295 987 511,359 75.60% 3,040 2,098 3,328,551 67.09%
Adanta, Cumberland River, and Lifeskills 213 156 86,520 73.92% 478 316 558,416 64.85%
Bluegrass, Comprehend, and North Key 378 290 154,669 76.29% 973 661 978,054 66.26%
Centerstone 309 261 111,337 83.52% 669 502 737,009 71.27%
Communicare and River Valley 129 99 58,440 76.29% 295 186 368,569 59.97%
Four Rivers and Pennyroyal 112 76 46,815 67.33% 292 207 313,333 69.48%
Kentucky River, Mountain, and Pathways 154 105 53,579 67.99% 333 226 373,169 68.66%
Louisiana 1,307 1,048 575,865 80.24% 2,964 2,160 3,449,120 71.65%
Regions 1 and 10 236 194 99,714 79.84% 599 420 683,376 69.54%
Region 1 105 89 53,766 84.81% 241 177 357,579 75.96%
Region 10 (Jefferson) 131 105 45,947 76.43% 358 243 325,798 66.22%
Regions 2 and 9 370 293 157,745 81.53% 869 639 913,889 75.66%
Region 3 150 126 50,616 85.33% 292 232 294,147 77.10%
Regions 4, 5, and 6 320 236 151,080 72.29% 645 441 880,787 65.24%
Regions 7 and 8 231 199 116,711 86.17% 559 428 676,921 72.93%
Maine 1,306 984 143,706 75.11% 3,070 2,210 1,063,424 71.65%
Aroostook/Downeast 168 125 15,867 75.42% 396 321 127,875 80.59%
Aroostook 103 79 7,418 77.65% 213 182 56,908 84.65%
Downeast 65 46 8,449 72.04% 183 139 70,966 75.25%
Central 161 123 18,581 77.42% 334 252 137,966 76.15%
Cumberland 300 207 31,674 68.21% 739 488 228,127 67.83%
Midcoast 119 95 14,344 79.70% 305 221 118,144 72.14%
Penquis 139 107 19,991 78.04% 371 282 137,992 75.26%
Western 219 171 21,938 75.97% 449 323 153,654 70.65%
York 200 156 21,312 78.44% 476 323 159,666 64.73%
Maryland 1,220 957 685,424 78.16% 3,003 2,198 4,557,206 70.96%
Anne Arundel 126 101 62,545 81.61% 277 203 429,327 72.71%
Baltimore City 120 98 66,395 79.98% 406 316 479,689 76.45%
Baltimore County 122 89 92,243 71.86% 306 220 640,187 69.90%
Montgomery 202 166 111,181 83.99% 543 401 777,360 72.83%
North Central 116 91 58,631 78.23% 263 188 359,790 67.92%
Northeast 105 72 58,037 68.22% 244 168 379,811 67.00%
Prince George's 180 138 106,281 74.36% 444 310 670,647 66.72%
South 121 101 71,086 84.33% 263 198 435,659 73.61%
West 128 101 59,026 80.06% 257 194 384,736 69.71%
Massachusetts 1,472 1,031 853,712 70.14% 3,582 2,212 5,326,206 61.37%
Boston 149 106 107,248 67.47% 449 268 685,461 58.75%
Central 198 132 116,835 66.83% 483 300 679,570 62.18%
Metrowest 315 214 190,911 66.01% 793 476 1,235,420 60.11%
Northeast 332 242 164,499 73.40% 835 516 1,042,578 61.07%
Southeast 256 177 153,576 70.41% 599 376 1,014,978 63.15%
Western 222 160 120,643 75.39% 423 276 668,199 63.13%
Michigan 3,143 2,445 1,182,347 77.30% 7,634 5,471 7,606,591 69.66%
Region 1 111 88 34,285 76.64% 249 180 252,982 70.66%
Region 2 111 73 51,706 63.99% 271 192 402,996 70.60%
Region 3 445 353 157,899 78.53% 1,007 748 928,432 73.01%
Region 4 284 231 101,098 82.97% 762 576 642,567 74.55%
Region 5 527 433 209,324 82.09% 1,361 1,052 1,283,845 76.42%
Region 6 248 199 101,086 80.54% 555 409 618,067 71.34%
Region 7 529 393 211,045 73.66% 1,257 861 1,327,476 65.00%
Region 8 404 310 138,708 76.92% 941 614 956,248 65.55%
Region 9 255 186 93,386 72.49% 726 467 658,476 60.20%
Region 10 229 179 83,809 76.22% 505 372 535,501 70.44%
Minnesota 1,264 982 635,000 77.54% 2,985 2,142 4,147,990 71.84%
Regions 1 and 2 132 97 59,516 74.51% 272 183 416,464 66.96%
Region 1 52 37 24,298 70.27% 122 79 155,492 65.49%
Region 2 80 60 35,219 77.19% 150 104 260,972 67.99%
Regions 3 and 4 250 196 111,319 76.67% 528 380 703,972 74.20%
Region 3 67 50 36,440 73.07% 103 73 248,519 73.82%
Region 4 183 146 74,878 77.82% 425 307 455,453 74.31%
Regions 5 and 6 227 170 119,724 75.89% 546 381 769,544 67.63%
Region 5 128 105 59,671 82.28% 299 212 389,634 67.93%
Region 6 99 65 60,053 66.09% 247 169 379,909 67.26%
Region 7 655 519 344,441 78.96% 1,639 1,198 2,258,010 73.18%
Region 7A (Hennepin) 290 220 131,150 76.10% 703 518 935,344 75.17%
Region 7B (Ramsey) 119 95 63,448 80.25% 315 236 407,727 76.25%
Region 7C 246 204 149,843 81.64% 621 444 914,939 69.90%
Mississippi 1,147 926 369,961 82.04% 2,856 2,082 2,202,655 71.69%
Region 1 296 234 86,983 81.11% 696 514 499,526 72.62%
Region 2 105 94 44,216 90.79% 308 247 268,417 75.20%
Region 3 154 132 53,466 84.73% 419 302 307,885 70.13%
Region 4 230 181 68,550 80.13% 519 378 407,947 73.73%
Region 5 65 53 20,773 83.46% 133 91 133,202 69.71%
Region 6 147 118 37,775 82.11% 370 281 228,576 73.44%
Region 7 150 114 58,198 76.24% 411 269 357,102 65.34%
Missouri 1,206 949 706,985 79.07% 3,008 2,159 4,583,870 69.77%
Central 156 118 105,002 77.78% 385 277 625,025 69.66%
Eastern 415 333 235,338 80.33% 1,069 762 1,593,064 69.81%
Eastern (St. Louis City and County) 214 174 139,938 81.30% 603 446 1,008,021 72.89%
Eastern (excluding St. Louis) 201 159 95,400 79.37% 466 316 585,043 66.22%
Northwest 294 233 171,888 78.90% 747 546 1,108,151 71.55%
Northwest (Jackson) 155 130 74,259 82.30% 398 296 507,830 72.12%
Northwest (excluding Jackson) 139 103 97,629 74.93% 349 250 600,321 70.95%
Southeast 148 121 82,570 82.05% 333 255 543,665 74.43%
Southwest 193 144 112,186 75.72% 474 319 713,965 64.43%
Montana 1,266 971 114,610 76.56% 3,132 2,262 792,939 70.36%
Region 1 104 79 9,166 72.98% 184 143 62,168 77.60%
Region 2 189 144 17,179 75.18% 479 354 111,316 69.95%
Region 3 270 189 23,676 71.17% 694 502 163,281 71.79%
Region 4 324 248 30,322 77.24% 851 593 212,218 68.83%
Region 5 379 311 34,268 81.35% 924 670 243,955 69.61%
Nebraska 1,251 969 230,669 77.60% 3,025 2,144 1,395,872 70.44%
Regions 1 and 2 90 71 22,455 78.61% 256 179 141,522 69.93%
Region 1 44 34 10,465 78.30% 131 93 66,553 70.01%
Region 2 46 37 11,990 78.86% 125 86 74,969 69.84%
Region 3 172 134 28,180 75.47% 415 310 171,343 74.46%
Region 4 156 117 25,578 72.88% 311 221 153,261 66.54%
Region 5 236 189 56,334 81.05% 681 487 349,383 71.64%
Region 6 597 458 98,121 77.83% 1,362 947 580,364 69.52%
Nevada 1,202 994 331,099 82.74% 2,979 2,180 2,182,228 70.50%
Clark – Region 1 894 745 240,327 83.08% 2,137 1,570 1,572,346 70.44%
Region 3 108 81 39,221 75.70% 307 210 267,727 65.92%
Capital District 37 28 17,612 75.18% 109 75 127,816 63.40%
Rural/Frontier 71 53 21,609 76.00% 198 135 139,910 67.87%
Washoe – Region 2 200 168 51,550 85.12% 535 400 342,155 73.77%
New Hampshire 1,312 983 154,875 76.07% 3,097 2,131 1,053,471 67.37%
Central 479 360 45,187 75.90% 1,053 755 300,402 69.36%
Central 1 238 178 23,712 76.54% 483 346 149,234 68.93%
Central 2 241 182 21,475 75.18% 570 409 151,168 69.75%
Northern 139 106 19,423 77.42% 352 267 138,182 71.16%
Southern 694 517 90,265 75.89% 1,692 1,109 614,887 65.43%
Southern 1 (Rockingham) 237 155 33,329 66.73% 600 394 236,373 66.51%
Southern 2 457 362 56,936 80.47% 1,092 715 378,514 64.84%
New Jersey 2,114 1,579 1,033,555 74.26% 5,036 3,339 6,845,720 65.22%
Central 510 357 239,285 70.29% 1,126 720 1,566,037 63.59%
Metropolitan 449 326 260,263 72.39% 1,183 777 1,649,807 64.05%
Northern 693 543 318,919 78.24% 1,754 1,169 2,209,141 63.93%
Southern 462 353 215,089 75.08% 973 673 1,420,735 70.81%
New Mexico 1,157 976 246,704 85.82% 2,769 2,155 1,555,252 76.92%
Region 1 245 210 54,806 86.60% 547 436 320,110 77.30%
Region 2 124 116 30,307 94.85% 310 250 227,155 78.76%
Region 3 (Bernalillo) 370 302 76,454 82.33% 991 755 508,712 76.71%
Region 4 158 133 34,203 85.42% 348 266 191,461 72.94%
Region 5 260 215 50,933 86.65% 573 448 307,815 78.10%
Region 5a 120 102 21,447 89.08% 286 225 147,310 77.09%
Region 5b (Dona Ana) 140 113 29,486 84.43% 287 223 160,505 79.43%
New York 4,482 3,270 2,180,289 71.18% 11,379 7,381 15,326,050 62.30%
Region 1: Long Island 745 515 331,745 67.95% 1,703 976 2,202,755 56.20%
Region 2: New York City 1,659 1,146 864,081 67.16% 4,880 2,938 6,646,216 57.38%
Region 2A: Bronx 411 323 179,377 79.68% 896 651 1,058,323 71.21%
Region 2B: Kings 506 314 278,589 60.32% 1,428 820 1,995,099 54.49%
Region 2C: New York 237 176 126,561 73.45% 1,016 630 1,393,420 60.76%
Region 2D: Queens 394 251 226,790 61.40% 1,252 665 1,833,734 50.74%
Region 2E: Richmond 111 82 52,765 75.94% 288 172 365,641 57.72%
Region 3: Mid-Hudson 560 391 281,749 66.27% 1,202 757 1,762,699 60.98%
Region 4: Capital Region 215 163 107,427 74.94% 476 350 744,482 74.10%
Region 5: Mohawk Valley 44 28 30,563 63.22% 123 98 203,261 80.09%
Region 6: North Country 55 45 32,025 82.32% 169 129 242,330 76.47%
Region 7: Tug Hill Seaway 78 67 31,381 89.56% 214 165 195,295 74.74%
Region 8: Central 298 240 123,819 81.40% 575 449 790,248 76.55%
Region 9: Southern Tier 112 94 56,956 83.66% 259 217 353,216 81.68%
Region 10: Finger Lakes 290 232 148,955 78.62% 738 539 989,065 70.99%
Region 11: Western 426 349 171,589 82.92% 1,040 763 1,196,482 70.17%
North Carolina 1,941 1,547 1,150,506 79.80% 4,707 3,449 7,538,179 71.86%
Alliance Behavioral Healthcare 1 219 179 95,410 80.43% 497 367 594,097 72.12%
Alliance Behavioral Healthcare 2 172 149 121,754 88.51% 411 296 734,002 71.64%
Cardinal Innovations Healthcare Solutions 1 189 138 93,454 71.16% 342 222 564,709 64.75%
Cardinal Innovations Healthcare Solutions 2 104 83 79,917 79.74% 296 220 517,054 73.01%
Cardinal Innovations Healthcare Solutions 3 165 129 113,890 78.57% 495 357 741,529 69.84%
CenterPoint Human Services 113 90 63,494 80.97% 286 219 416,164 75.84%
Eastpointe 231 183 96,546 78.18% 472 353 624,214 73.24%
Partners Behavioral Health Management 170 144 104,359 84.68% 341 250 695,496 70.35%
Sandhills Center 1 77 59 66,978 79.44% 198 149 432,349 75.93%
Sandhills Center 2 104 90 62,072 87.17% 269 187 392,881 69.96%
Smoky Mountain Center 1 112 79 58,490 70.06% 294 220 424,488 72.24%
Smoky Mountain Center 2 80 60 53,046 76.30% 258 190 421,844 72.96%
Trillium Health Resources 1 133 114 70,954 86.91% 348 280 480,390 77.32%
Trillium Health Resources 2 72 50 70,141 68.26% 200 139 498,965 68.46%
North Dakota 1,344 1,051 94,691 78.86% 2,966 2,181 565,225 72.57%
Badlands and West Central 352 276 23,558 79.11% 801 580 151,189 71.97%
Badlands 55 43 5,065 75.70% 135 97 34,418 73.39%
West Central 297 233 18,493 79.77% 666 483 116,771 71.68%
Lake Region 84 64 5,869 77.71% 155 122 30,711 78.69%
North Central 153 118 13,207 77.47% 328 244 79,334 72.92%
Northeast 212 173 13,362 83.55% 451 331 72,104 71.10%
Northwest 51 37 4,745 75.13% 128 81 30,311 60.12%
South Central 71 50 6,614 64.63% 182 131 44,857 75.51%
Southeast 421 333 27,336 79.49% 921 692 156,719 73.67%
Ohio 3,154 2,386 1,376,806 74.84% 7,820 5,442 8,812,617 67.93%
Boards 2, 46, 55, and 68 139 100 63,029 67.57% 271 179 386,190 63.74%
Boards 3, 52, and 85 111 80 49,596 68.14% 217 149 286,414 73.51%
Boards 4 and 78 82 63 33,999 78.08% 232 176 237,864 75.99%
Boards 5 and 60 94 66 45,267 72.30% 235 170 261,526 70.29%
Boards 7, 15, 41, 79, and 84 121 83 49,683 66.83% 274 171 356,695 61.28%
Boards 8, 13, and 83 123 95 63,145 74.47% 227 145 376,691 62.33%
Board 9 (Butler) 117 79 49,736 67.19% 265 167 279,429 61.40%
Board 12 116 83 43,151 66.46% 231 159 266,843 68.83%
Boards 18 and 47 369 282 176,770 75.67% 997 710 1,196,862 69.85%
Boards 20, 32, 54, and 69 138 112 41,741 82.42% 321 228 257,077 70.95%
Boards 21, 39, 51, 70, and 80 165 124 68,761 75.29% 292 212 419,629 70.63%
Boards 22, 74, and 87 140 113 47,843 79.51% 307 226 298,088 70.55%
Boards 23 and 45 145 109 48,559 74.14% 359 248 285,280 65.52%
Board 25 (Franklin) 324 249 142,114 78.26% 896 624 916,263 68.00%
Boards 27, 71, and 73 131 96 57,053 73.68% 322 209 375,064 60.95%
Boards 28, 43, and 67 137 101 59,784 73.17% 400 275 377,548 67.28%
Board 31 (Hamilton) 212 158 91,803 73.95% 562 384 603,424 66.29%
Board 48 (Lucas) 97 80 52,258 80.49% 272 192 329,959 64.89%
Boards 50 and 76 172 133 69,292 76.82% 475 333 471,711 69.46%
Board 57 (Montgomery) 107 94 61,962 89.26% 320 236 416,147 72.97%
Board 77 (Summit) 114 86 61,260 74.13% 345 249 413,912 67.86%
Oklahoma 1,247 944 461,843 75.12% 3,062 2,151 2,866,854 67.42%
Central 178 137 60,354 75.33% 427 293 366,536 64.66%
East Central 145 107 53,840 74.91% 324 229 327,085 68.66%
Northeast 147 109 59,763 72.74% 388 270 365,000 67.90%
Northwest and Southwest 193 156 66,323 78.70% 396 294 407,463 69.88%
Oklahoma County 186 148 87,083 76.73% 546 381 555,362 66.37%
Southeast 172 127 60,975 75.31% 412 290 388,160 69.04%
Tulsa County 226 160 73,505 72.22% 569 394 457,247 66.42%
Oregon 1,269 960 434,609 76.13% 3,078 2,216 3,133,289 71.13%
Region 1 (Multnomah) 235 171 73,920 71.04% 673 462 627,664 69.18%
Region 2 398 308 108,537 78.51% 773 568 734,104 72.48%
Region 3 340 253 145,315 75.21% 901 662 973,074 72.34%
Region 4 171 132 55,877 77.84% 420 313 445,555 70.76%
Region 5 (Central) 49 38 22,308 75.35% 116 70 162,608 69.35%
Region 6 (Eastern) 76 58 28,651 79.99% 195 141 190,283 69.13%
Pennsylvania 3,120 2,444 1,449,943 78.45% 7,432 5,326 9,908,218 70.32%
Region 1 (Allegheny) 229 171 125,049 75.62% 745 491 979,005 66.91%
Regions 3, 8, 9, and 51 215 172 78,431 80.39% 487 355 549,973 71.48%
Regions 4, 11, 37, and 49 206 149 106,827 73.36% 462 321 698,209 69.98%
Regions 5, 18, 23, 24, and 46 202 166 83,605 82.10% 489 366 579,877 72.57%
Regions 6, 12, 16, 31, 35, 45, and 47 182 147 89,248 81.95% 402 308 562,637 72.23%
Regions 7, 13, 20, and 33 616 482 291,035 78.26% 1,434 982 1,917,341 67.39%
Regions 10, 15, 27, 32, 43, and 44 102 83 53,882 81.33% 279 216 399,808 73.66%
Regions 17 and 21 88 63 44,957 71.72% 216 162 283,787 74.58%
Regions 19, 26, 28, and 42 395 301 170,669 77.05% 882 656 1,117,029 72.07%
Regions 22, 38, 40, 41, and 48 185 149 82,848 79.88% 482 336 652,080 68.71%
Regions 29 and 34 169 129 78,899 76.50% 329 213 507,199 64.86%
Regions 30 and 50 167 131 64,614 78.86% 377 286 477,374 76.63%
Region 36 (Philadelphia) 364 301 179,879 80.21% 848 634 1,183,899 73.46%
Rhode Island 1,211 947 120,526 78.46% 3,138 2,190 829,196 68.92%
Region 1: Southern Providence County 193 141 19,434 72.29% 521 330 152,440 66.27%
Region 2: Northern Providence County/
   Blackstone Valley
297 236 22,858 80.06% 782 559 165,039 68.55%
Region 3: Providence 180 151 27,596 82.54% 486 369 137,221 74.89%
Region 4: Kent County 187 150 16,574 81.34% 456 324 135,835 70.40%
Region 5: East Bay 116 95 10,232 82.32% 302 214 77,111 69.01%
Region 6: Newport County 96 65 8,633 68.82% 250 150 65,704 63.32%
Region 7: South County 142 109 15,200 77.48% 341 244 95,847 69.84%
South Carolina 1,238 998 554,493 80.82% 3,011 2,206 3,704,783 72.65%
Region 1 369 300 177,635 82.80% 889 633 1,156,520 68.79%
Region 2 377 301 143,058 80.20% 801 570 908,309 70.33%
Region 3 220 171 89,361 76.00% 539 398 644,968 74.52%
Region 4 272 226 144,440 82.39% 782 605 994,986 77.68%
South Dakota 1,278 1,007 103,486 79.11% 2,880 2,109 631,809 73.03%
Region 1 276 219 25,408 77.40% 691 519 155,569 74.44%
Region 2 120 96 10,026 81.25% 234 176 57,293 76.61%
Region 3 311 245 25,113 79.58% 664 483 150,285 73.70%
Region 4 215 170 14,744 79.57% 397 295 89,128 71.13%
Region 5 356 277 28,196 78.97% 894 636 179,535 71.17%
Tennessee 1,261 979 789,042 77.55% 3,024 2,240 4,999,822 72.48%
Region 1 140 109 57,411 76.58% 281 211 409,331 69.98%
Region 2 192 152 141,017 81.19% 510 391 941,367 76.89%
Region 3 197 148 114,695 75.94% 490 371 754,196 75.92%
Region 4 (Davidson) 105 73 72,028 73.61% 304 206 502,251 65.61%
Region 5 333 249 204,741 75.96% 698 499 1,202,771 72.79%
Region 6 101 80 77,846 78.39% 298 219 486,354 65.49%
Region 7 (Shelby) 193 168 121,305 80.47% 443 343 703,552 74.25%
Texas 4,241 3,448 3,549,733 81.00% 10,097 7,449 19,733,150 71.72%
Region 1 112 80 117,711 69.12% 329 237 647,431 70.71%
Region 2 105 89 70,068 82.59% 250 189 421,410 75.37%
Region 3 1,221 1,022 943,303 83.79% 2,924 2,252 5,312,787 75.45%
Region 3a 786 636 603,411 80.97% 1,850 1,366 3,392,041 71.83%
Region 3bc 435 386 339,892 89.11% 1,074 886 1,920,746 81.79%
Region 4 167 143 138,151 85.27% 458 379 867,534 81.06%
Region 5 100 85 95,784 85.98% 256 207 599,333 78.71%
Region 6 987 769 851,043 77.39% 2,324 1,540 4,783,998 63.33%
Region 6a 876 683 765,152 77.61% 2,100 1,387 4,280,533 63.28%
Region 6bc 111 86 85,891 75.63% 224 153 503,465 63.75%
Region 7 509 395 420,793 77.52% 1,283 931 2,425,665 71.05%
Region 7a 305 228 259,866 75.29% 797 561 1,546,425 69.30%
Region 7bcd 204 167 160,928 81.27% 486 370 879,240 74.18%
Region 8 406 344 369,937 84.52% 1,015 766 2,059,794 73.97%
Region 9 99 73 78,074 76.29% 225 139 443,839 59.71%
Region 10 138 107 131,965 76.66% 280 217 630,716 75.37%
Region 11 397 341 332,904 85.73% 753 592 1,540,643 75.08%
Region 11abd 256 213 201,000 82.11% 490 375 977,902 72.96%
Region 11c (Hidalgo) 141 128 131,904 92.37% 263 217 562,741 78.52%
Utah 1,139 977 426,435 85.30% 2,740 2,132 2,066,736 76.48%
Bear River, Northeastern, Summit, Tooele,
   and Wasatch
106 94 52,930 88.90% 229 179 247,427 78.30%
Central, Four Corners, San Juan, and
   Southwest
123 105 52,714 88.30% 287 206 250,047 70.58%
Central, Four Corners, and San Juan 49 38 20,887 83.59% 121 88 95,230 72.79%
Southwest 74 67 31,827 91.29% 166 118 154,816 68.81%
Davis County 116 93 47,892 77.18% 234 179 220,512 75.44%
Salt Lake County 476 413 147,675 85.78% 1,211 958 792,739 78.05%
Utah County 202 172 90,104 85.03% 507 391 376,232 75.16%
Weber, Morgan 116 100 35,120 85.29% 272 219 179,780 77.71%
Vermont 1,227 945 69,363 77.27% 2,983 2,090 501,770 70.75%
Champlain Valley 528 409 30,611 79.00% 1,372 956 201,776 68.55%
Rural Northeast 252 193 15,974 72.76% 564 393 117,817 71.96%
Rural Southeast 259 193 12,476 74.96% 608 435 103,906 72.97%
Rural Southwest 188 150 10,302 81.43% 439 306 78,272 72.45%
Virginia 1,960 1,559 925,947 79.75% 4,752 3,384 6,294,357 69.53%
Region 1 256 215 154,624 82.89% 676 510 975,404 73.10%
Region 2 558 428 252,543 78.09% 1,423 944 1,778,797 64.18%
Region 3 305 238 149,400 76.85% 815 618 1,066,498 73.86%
Region 4 338 273 159,366 81.77% 803 569 1,072,836 70.29%
Region 5 503 405 210,015 80.42% 1,035 743 1,400,823 70.13%
Washington 1,221 957 827,195 78.09% 3,028 2,119 5,452,060 69.24%
Region 1 317 259 206,611 81.16% 656 451 1,170,456 69.23%
Greater Columbia and North Central 224 183 131,248 81.85% 424 288 692,588 67.50%
Spokane 93 76 75,363 79.49% 232 163 477,868 72.11%
Region 2 500 373 353,258 74.01% 1,432 975 2,528,868 66.38%
King 303 221 216,593 71.78% 957 646 1,620,679 65.89%
North Sound 197 152 136,664 77.35% 475 329 908,189 67.38%
Region 3 404 325 267,326 81.03% 940 693 1,752,736 73.78%
Pierce 193 160 101,689 83.13% 478 369 638,133 77.89%
Salish 55 42 39,709 79.12% 135 89 295,141 67.36%
SW WA and Great Rivers 103 83 88,952 79.82% 245 180 562,027 72.97%
Thurston-Mason 53 40 36,976 78.18% 82 55 257,435 65.55%
West Virginia 1,338 983 204,404 74.37% 3,143 2,120 1,443,317 65.29%
Region I 86 59 15,563 68.08% 221 145 114,550 62.16%
Region II 195 155 32,297 80.41% 422 301 202,685 72.05%
Region III 121 82 18,102 65.29% 287 199 132,177 64.59%
Region IV 339 245 47,890 74.91% 776 501 321,732 64.77%
Region V 323 223 56,350 70.90% 819 527 408,659 60.44%
Region VI 274 219 34,201 79.23% 618 447 263,514 69.25%
Wisconsin 1,295 988 638,347 74.72% 3,075 2,153 4,404,440 69.75%
Milwaukee 199 155 112,040 78.31% 567 381 705,880 66.81%
Northeastern 233 168 133,164 68.08% 593 433 957,254 74.63%
Northern 113 94 50,016 83.67% 241 186 382,235 78.18%
Southeastern 337 238 134,304 69.59% 646 427 888,924 66.21%
Southern 268 216 120,564 77.59% 677 480 866,220 67.55%
Western 145 117 88,259 79.14% 351 246 603,927 70.02%
Wyoming 1,257 996 65,756 77.72% 2,909 2,166 437,329 73.44%
Judicial District 1 (Laramie) 184 135 10,616 73.10% 489 356 71,842 69.66%
Judicial District 2 156 130 7,082 81.05% 366 291 43,273 79.05%
Judicial District 3 188 150 10,180 77.41% 378 291 60,068 77.37%
Judicial District 4 76 56 4,066 76.94% 133 91 29,304 65.50%
Judicial District 5 104 82 6,142 81.64% 242 190 41,797 80.55%
Judicial District 6 149 123 7,097 80.23% 334 261 45,004 78.48%
Judicial District 7 (Natrona) 179 154 8,682 85.01% 406 314 59,360 77.94%
Judicial District 8 99 74 4,322 70.83% 216 138 30,658 62.61%
Judicial District 9 122 92 7,570 69.60% 345 234 56,024 66.53%
SPA = service planning area.
NOTE: For substate region definitions, see the "2014-2016 National Survey on Drug Use and Health Substate Region Definitions" at https://www.samhsa.gov/data.
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 2014-2016 weighted response rates, the three samples were combined, and the individual-year weights were used for the pooled sample. Thus, the response rates presented here are weighted across 3 years of data rather than being a simple average of the 2014, 2015, and 2016 individual response rates.
NOTE: The total responded column represents the combined sample size from the 2014, 2015, and 2016 NSDUHs.
NOTE: The population estimate is the simple average of the 2014, 2015, and 2016 population counts for individuals aged 12 to 20 and adults aged 18 or older. Because of rounding, the sum of the substate region population counts within a state may not exactly match the state population count listed in the table.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2014, 2015, and 2016.

Section D: References

American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (DSM-IV) (4th ed.). Washington, DC: Author.

Box, G. E. P., & Tiao, G. C. (1992). Bayesian inference in statistical analysis (Wiley Classics Library). Hoboken, NJ: John Wiley & Sons.

Center for Behavioral Health Statistics and Quality. (2012). Results from the 2011 National Survey on Drug Use and Health: Summary of national findings (HHS Publication No. SMA 12-4713, NSDUH Series H-44). Retrieved from https://www.samhsa.gov/data/

Center for Behavioral Health Statistics and Quality. (2013a). Results from the 2012 National Survey on Drug Use and Health: Mental health findings (HHS Publication No. SMA 13-4805, NSDUH Series H-47). Retrieved from https://www.samhsa.gov/data/

Center for Behavioral Health Statistics and Quality. (2013b). Results from the 2012 National Survey on Drug Use and Health: Summary of national findings (HHS Publication No. SMA 13-4795, NSDUH Series H-46). Retrieved from https://www.samhsa.gov/data/

Center for Behavioral Health Statistics and Quality. (2015a). 2014 National Survey on Drug Use and Health: Methodological resource book (Section 2, Sample design report). Retrieved from https://www.samhsa.gov/data/

Center for Behavioral Health Statistics and Quality. (2015b, August). National Survey on Drug Use and Health: 2014 and 2015 redesign changes. Retrieved from https://www.samhsa.gov/data/

Center for Behavioral Health Statistics and Quality. (2016a). 2015 National Survey on Drug Use and Health: Methodological summary and definitions. Retrieved from https://www.samhsa.gov/data/

Center for Behavioral Health Statistics and Quality. (2016b). 2015 National Survey on Drug Use and Health: Summary of the effects of the 2015 NSDUH questionnaire redesign: Implications for data users. Retrieved from https://www.samhsa.gov/data/

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.

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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.

Wright, D. (2003, July). 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). Retrieved from https://www.samhsa.gov/data/

Wright, D., & Sathe, N. (2005, January). 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). Retrieved from https://www.samhsa.gov/data/

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. HHSS283201300001C.

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

The following staff were responsible for generating the estimates: Akhil K. Vaish, Neeraja S. Sathe, and Kathryn Spagnola. The following staff provided other support: Brenda K. Porter and Ana Saravia. Ms. Spagnola also provided oversight for production of the document. Richard S. Straw edited it; Debbie F. Bond formatted its text and tables; and Teresa F. Bass, Kimberly Cone, Danny Occoquan, and Pamela Tuck prepared the web versions. Justine L. Allpress prepared the maps used in the associated files.

End Notes

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

2 In 2002, the survey's name changed from the National Household Survey on Drug Abuse (NHSDA) to the National Survey on Drug Use and Health (NSDUH).

3 The Office of Applied Studies (OAS) is the former name of the Center for Behavioral Health Statistics and Quality (CBHSQ).

4 The target sample size per year in each of the small sample states is 960 completed interviews, with the exception of Hawaii where the target sample size is 967 completed interviews.

5 Prior to this effort, substate small area estimates using combined 1999-2001, 2002-2004, 2004-2006, 2006-2008, 2008-2010, 2010-2012, and 2012-2014 data have been produced by SAMHSA. These estimates can be found at https://www.samhsa.gov/data/. (For 2006-2008 and earlier estimates, see https://archive.samhsa.gov/data/.)

6 Files with a comma separated value (*.csv) extension are in plain text. They contain characters stored in a flat, nonproprietary format and can be opened by most computer programs. Computers with Microsoft Excel installed open *.csv files in Excel by default, with the fields automatically arranged appropriately in columns. Other database programs also open *.csv files with the fields appropriately arranged.

7 The exact changes are documented in the 2015 NSDUH's Office of Management and Budget (OMB) clearance package and in a summary report (CBHSQ, 2015b). The summary report and the 2015 NSDUH questionnaire are available on the SAMHSA website at https://www.samhsa.gov/data/.

8 The National Institute on Alcohol Abuse and Alcoholism (NIAAA, 2016) defines binge drinking as a pattern of drinking that brings blood alcohol concentration (BAC) levels to 0.08 grams per deciliter (g/dL). This typically occurs after four drinks for women and five drinks for men in about 2 hours.

9 Prior to 2015, NSDUH referred to "nonmedical" use of prescription drugs. See Section C of the 2015 NSDUH methodological summary and definitions report (CBHSQ, 2016a) for further discussion about the change in terminology from nonmedical use to misuse of prescription drugs in 2015. Specifically, the approach and definition for measuring the misuse of prescription drugs were revised to include questions about any use of prescription drugs in addition to questions about misuse (previously called "nonmedical use"). Also, the definition for misuse was revised to focus on specific behaviors that indicate misuse (i.e., use in any way a doctor did not direct respondents to use prescription drugs, including use without a prescription of one's own; use in greater amounts, more often, or longer than told to take a drug; and use in any other way not directed by a doctor). Moreover, questions pertaining to specific prescription drugs focused on the past 12 months instead of the lifetime period that was used in the 2014 and prior questionnaires.

10 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. It is also difficult (if not impossible) to produce valid mean squared errors (MSEs) for small area estimates based solely on a fixed-effect national regression model (i.e., synthetic estimation) (Rao, 2003, p. 52). The mixed models produce estimates that are approximately represented by a weighted combination of the direct estimate from the substate data and a regression estimate from the national model. The regression coefficients of the national model are estimated using data from all of the substate areas (i.e., borrowing strength), and the regression estimate for a particular substate area is obtained by applying the national model to the substate-specific predictor data. The regression estimate for the substate area is then combined with the direct estimate from the substate data in a weighted combination where the weights are obtained by minimizing the MSE (variance + squared bias) of the small area estimate.

11 Claritas is a market research firm headquartered in Ithaca, New York (see https://www.claritas.com/). When the Claritas data were obtained for the 2014-2016 NSDUHs, Claritas was affiliated with Nielsen Holdings, from which they became independent in January 2017.

12 Improper noninformative priors were used for the fixed regression coefficients. Because NSDUH's sample size is very large (approximately 200,000 observations across 3 years), it can be said with certainty that the posterior distribution for the fixed regression coefficients will be proper. For the W1 and W2 matrices, noninformative proper inverse Wishart prior distributions were used so that proper posterior distributions are guaranteed. Noninformative priors are used so that the data speak for themselves and inferences are unaffected by information external to the current data. For further information on Bayesian inference and analysis, see Box and Tiao (1992) and Gelman, Carlin, Stern, and Rubin (2003).

13 See Table 2 in the "2014-2016 NSDUH Substate Region Estimates: Excel Tables and CSV Files" at https://www.samhsa.gov/data/.

14 The RSE of an estimate is the posterior SE divided by the estimate itself. Note that the RSEs have been calculated based on the unbenchmarked small area estimates.

Long Description

Long description, Equation 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 1.

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