An Analysis of Mental Health and 

Substance Abuse Disparities & 

Access to Treatment Services in 

the Appalachian Region 

Final Report 

August 2008

Presented to: 

Appalachian Regional Commission 

Presented by: 

Zhiwei Zhang, Ph.D. 

Alycia Infante, M.P.A. 

Michael Meit, M.A., M.P.H. 

Ned English, M.S.

National Opinion Research Center (NORC) 

at the University of Chicago 

 & 

Michael Dunn, Ph.D. 

Kristine Harper Bowers 

East Tennessee State University 

 
You can view and download this report by visiting www.arc.gov or www.norc.org. 

For more information about the report, please contact either Gregory Bischak, Ph.D. of the 

Appalachian Regional Commission (202-884-7790, gbischak@arc.gov) or Michael Meit, M.A., 

M.P.H. of NORC (301-634-9324, meit-michael@norc.org) 

The authors wish to thank the Appalachian Regional Commission for providing the funding for the 

report. 

Appalachian Regional Commission 

1666 Connecticut Avenue, NW, Suite 700 

Washington, DC 20009-1068 

The Appalachian Regional Commission’s mission is to be an advocate for and partner with the 

people of Appalachia to create opportunities for self-sustaining economic development and 

improved quality of life. 

National Opinion Research Center 

4250 East-West Highway, Suite 800 

Bethesda, MD 20814 

NORC’s mission is to conduct high quality social science research in the public interest. We 

conduct research in health, economics, demographics, education and child development, substance 

abuse, mental health, justice, and survey quality both in the U.S. and internationally. NORC 

supports the research needs of governments in the U.S. and abroad, international donor agencies, 

foundations, academic researchers, and private organizations. NORC has offices in Chicago, IL, 

Bethesda, MD, and Berkeley, CA. 

East Tennessee State University 

© 2008 by the Appalachian Regional Commission and the National Opinion Research Center 

Reproduction of this document is permitted and encouraged, with credit given to the Appalachian 

Regional Commission and the National Opinion Research Center. 
Acknowledgments 

This report was funded and prepared for the Appalachian Regional Commission (ARC). It was 

commissioned by the ARC to study the disparities in mental health status and substance abuse 

prevalence and access to treatment services in the Appalachian Region. 

The National Opinion Research Center (NORC) at the University of Chicago, in partnership with 

East Tennessee State University (ETSU), conducted this study. Zhiwei Zhang, Ph.D. is the lead 

author and Principal Investigator and Michael Meit, M.A., M.P.H. is the Project Manager. 

Contributing authors to this report were Alycia Infante, M.P.A. and Ned English, M.S. from NORC, 

and Michael Dunn, Ph.D. and Kristine Harper Bowers from East Tennessee State University 

(ETSU). 

The research, analysis, and report development were guided by Dr. Gregory Bischak, Senior 

Economist with the ARC. We would like to acknowledge the important contributions of Randall 

Jessee, Ph.D. and the members of the Center for Appalachian Substance Abuse Policy (CASAP) for 

their initial project guidance and review of draft findings, and the members of the Appalachian 

Health Policy Advisory Council (AHPAC) for their ongoing project guidance and support. We also 

thank Bruce Behringer, M.P.H. at East Tennessee State University for his guidance and 

contributions. We appreciate the assistance provided by Katherine Locke, M.P.H., Emily 

Shortridge, Ph.D., Jacob Feldman, Ph.D., and Sam Schildhaus, Ph.D. from NORC. We thank Art 

Hughes at the Office of Applied Studies (OAS) of the Substance Abuse and Mental Health Services 

Administration (SAMHSA) and staff at Research Triangle Institute International Inc. for running 

data on the National Survey on Drug Use and Health (NSDUH). We thank Deborah Trunzo at 

OAS/SAMHSA and Leigh Henderson at the Synectics for Management Decisions, Inc for 

providing the Treatment Episode Data Sets (TEDS) submitted by Appalachian states and 

jurisdictions. 

The data collection in the field for the case study part of this project was approved by the East 

Tennessee State University’s Institutional Review Board. All the data collection, analysis, reporting, 

and subsequent publications were approved by NORC’s Institutional Review Board. 

The views expressed are those of the authors and not necessarily those of ARC, NORC, or the East 

Tennessee State University. 
TABLE OF CONTENTS 

Executive Summary ............................................................................................................................ 1

CHAPTER 1: Introduction ................................................................................................................ 7

1.1 Substance Abuse and Mental Health Disorders in Appalachia .................................................. 7 

1.2 Key Research Questions and Methodology ............................................................................... 8 

1.3 Importance of the Current Study ................................................................................................ 9 

1.4 Structure of the Report ............................................................................................................. 11 

CHAPTER 2: Substance Use, Mental Disorders, and Access to Treatment Services in 

Household Surveys, 2002 – 2005 ...................................................................................................... 19

2.1 Introduction ................................................................................................................................. 19

2.2 Data ............................................................................................................................................... 19

2.2.1 Overview ................................................................................................................................ 19 

2.2.2 Limitations of the NSDUH .................................................................................................... 20 

2.3 Methods ........................................................................................................................................ 21

2.3.1 Analytic Sample ..................................................................................................................... 21 

2.3.2 Measures ................................................................................................................................. 21 

2.3.3 Statistical Methods ................................................................................................................. 23 

2.4 Results ......................................................................................................................................... 24

2.4.1 Tables ..................................................................................................................................... 29 

2.4.2 Maps ....................................................................................................................................... 54 

2.5 Discussion ..................................................................................................................................... 75

CHAPTER 3: Patient Admissions to Treatment for Abuse of Alcohol and Drugs in 

Appalachia, 2000 – 2004 ................................................................................................................... 78

3.1 Introduction ................................................................................................................................. 78

3.2 Data ............................................................................................................................................... 78

3.2.1 Overview ................................................................................................................................ 78 

3.2.2 Uses of TEDS ......................................................................................................................... 80 

3.2.3 TEDS Measures Used in this Study ....................................................................................... 80 

3.2.4 Limitations of the TEDS Series ............................................................................................. 83 

3.3 Methods ........................................................................................................................................ 83

3.3.1 Study Sample .......................................................................................................................... 83 

3.3.2 Statistical Methods ................................................................................................................. 84 

3.4 Results .......................................................................................................................................... 84

3.4.1 Tables ..................................................................................................................................... 85 

3.4.2. Figures ................................................................................................................................. 104 

3.4.3. Maps .................................................................................................................................... 110 
3.5 Discussion ................................................................................................................................... 121

CHAPTER 4: Substance Use and Mental Health Disorder Discharges from Appalachian and 

Other Community Hospitals in 2004 ............................................................................................. 124

4.1 Introduction .............................................................................................................................. 124

4.2 Data ............................................................................................................................................ 125

4.2.1 Overview .............................................................................................................................. 125 

4.2.2 Sample Design ...................................................................................................................... 125 

4.2.3 Uses of the HCUP Nationwide Inpatient Sample ................................................................ 126 

4.2.4 HCUP Measures Used in this Study .................................................................................... 126

4.2.5 Limitations of HCUP NIS Data ........................................................................................... 128 

4.3 Methods ...................................................................................................................................... 129

4.3.1 Study Sample ........................................................................................................................ 129 

4.3.2 Statistical Methods ............................................................................................................... 129 

4.4 Results ....................................................................................................................................... 130

4.4.1 Tables ................................................................................................................................... 130 

4.5 Discussion ................................................................................................................................... 150

CHAPTER 5: Substance Abuse Treatment Services in the Appalachian Region, 2005 .......... 152

5.1 Introduction ............................................................................................................................... 152

5.2 Data ............................................................................................................................................. 152

5.2.1 Overview .............................................................................................................................. 152 

5.2.2 Sample Design ...................................................................................................................... 153 

5.2.3 Uses of the N-SSATS ........................................................................................................... 154 

5.2.4 N-SSATS Measures Used in this Study ............................................................................... 154 

5.2.5 Limitations of the N-SSATS ................................................................................................ 155 

5.3 Methods ...................................................................................................................................... 156

5.3.1 Study Sample ........................................................................................................................ 156 

5.3.2 Statistical Methods ............................................................................................................... 156 

5.4 Results ........................................................................................................................................ 156

5.4.1 Tables ................................................................................................................................... 157 

5.4.2 Figures .................................................................................................................................. 162 

5.5 Discussion ................................................................................................................................... 166

CHAPTER 6: Substance Abuse and Mental Health – A Comparison of Appalachian Coal 

Mining Areas to Other Areas within the Appalachian Region ................................................... 168

6.1 Introduction ............................................................................................................................... 168

6.2 Data and Analytic Samples ...................................................................................................... 168

6.3 Results ........................................................................................................................................ 170

6.4 Conclusion .................................................................................................................................. 173
CHAPTER 7: Case Study Analysis of Disparities in Mental Health Status and Substance 

Abuse Prevalence in the Appalachian Region and Access to Mental Health and Substance 

Abuse Treatment Services .............................................................................................................. 181

7.1 Introduction .............................................................................................................................. 182

7.2 Case Study Process .................................................................................................................... 182

7.3 Phase 1: Identification of Potential Data Sets/Sources ........................................................ 183

7.4 Phase 2: Selection of Pairs of Counties for Case Study ....................................................... 184

Data Sources .................................................................................................................................. 184 

Measuring the Similarities of County Pairs .................................................................................. 185 

Composite Ranking Scale and Selection of Final Pairs ................................................................ 186 

Site Descriptions ........................................................................................................................... 188 

7.5 Phase 3: Onsite Focus Group and Key Informant Interviews ............................................ 193

7.6 Phase 4: Development of Community Resource Inventory ................................................... 198

7.7 Phase 5: Key Findings ............................................................................................................... 201

7.8 Discussion and Conclusions ...................................................................................................... 206

Case Study Appendix of Model Programs .................................................................................... 210

County Profiles .............................................................................................................................. 214 

CHAPTER 8: Conclusions ............................................................................................................. 215

APPENDIX A: Data Sources ......................................................................................................... 223

APPENDIX B: Literature Review of the Prevalence of Substance Abuse and Mental Health 

Disorders, Access to Treatment Services, and Disparities in Appalachia .................................. 225

APPENDIX C: Results from the 2005 National Survey on Drug Use and Health: National 

Findings ............................................................................................................................................ 235

APPENDIX D: County-Level Data Profiles for Appalachian Case Studies ............................. 274

References ........................................................................................................................................ 287

TABLES 

Table 1.1 Overview of the Data Sets: Data Coverage, Data Reliability, and Characteristics ............ 12 

Table 2.1 Sample Sizes of the Pooled National Surveys on Drug Use and Health, by Age Group, 

Survey Year, and Appalachian Region Status ........................................................................... 21 

Table 2.2 Demographic Characteristics and Health Insurance among Persons Aged 12 or Older, by 

Age Group and Appalachian Region Status: Percentages, Annual Averages Based on 2002-

2005 ............................................................................................................................................ 29 

Table 2.3 Lifetime, Past Year, and Past Month Substance Use among Persons Aged 12 or Older, by 

Substance, Age Group, and Appalachian Region Status: Percentages, Annual Averages Based 

on 2002-2005 .............................................................................................................................. 30 
Table 2.4 Substance Dependence or Abuse, Mental Health Measures, and Receipt of Substance 

Use Treatment in the Past Year among Persons Aged 12 or Older, by Age Group and 

Appalachian Region Status: Percentages, Annual Averages Based on 2002-2005 ................... 31 

Table 2.5 Demographic Characteristics and Health Insurance among Persons Aged 12 or Older 

Residing in Appalachian Region, by Age Group and Appalachian Sub-Region: Percentages, 

Annual Averages Based on 2002-2005 ...................................................................................... 32 

Table 2.6 Lifetime, Past Year, and Past Month Substance Use among Persons Aged 12 or Older 

Residing in Appalachian Region, by Substance, Age Group, and Appalachian Sub-Region: 

Percentages, Annual Averages Based on 2002-2005 ................................................................. 33 

Table 2.7 Substance Dependence or Abuse, Mental Health Measures, and Receipt of Substance 

Use Treatment in the Past Year among Persons Aged 12 or Older Residing in Appalachian 

Region, by Age Group and Appalachian Sub-Region: Percentages, Annual Averages Based on 

2002-2005 ................................................................................................................................... 34 

Table 2.8 Demographic Characteristics and Health Insurance among Persons Aged 12 or Older 

Residing in Appalachian Region, by Age Group and Appalachian Socioeconomic Status: 

Percentages, Annual Averages Based on 2002-2005 ................................................................. 36 

Table 2.9 Lifetime, Past Year, and Past Month Substance Use among Persons Aged 12 or Older 

Residing in Appalachian Region, by Substance, Age Group, and Appalachian Socioeconomic 

Status: Percentages, 2002-2005 .................................................................................................. 38 

Table 2.10 Substance Dependence or Abuse, Mental Health Measures, and Receipt of Substance 

Use Treatment in the Past Year among Persons Aged 12 or Older Residing in Appalachian 

Region, by Age Group and Appalachian Socioeconomic Status: Percentages, Annual Averages 

Based on 2002-2005 ................................................................................................................... 39 

Table 2.11 Access to Alcohol Treatment among Persons Aged 12 or Older, by Age Group and 

Appalachian Region Status: Percentages, Annual Averages Based on 2002-2005 ................... 44 

Table 2.12 Access to Drug Treatment among Persons Aged 12 or Older, by Age Group and 

Appalachian Region Status: Percentages, Annual Averages Based on 2002-2005 ................... 45 

Table 2.13 Reasons for Not Receiving Substance Use Treatment and Locations of Treatment 

among Persons Aged 12 or Older, by Age Group and Appalachian Region Status: 

Percentages, Annual Averages Based on 2002-2005 ................................................................. 46 

Table 2.14 Reasons for Not Receiving Mental Health Treatment among Persons Aged 12 or 

Older, by Age Group and Appalachian Region Status: Percentages, Annual Averages Based on 

2002-2005 ................................................................................................................................... 47 

Table 2.15 Access to Alcohol Use Treatment among Persons Aged 12 or Older, by Age Group 

and Appalachian Sub-Region: Percentages, Annual Averages Based on 2002-2005 ................ 48 

Table 2.16 Access to Drug Use Treatment among Persons Aged 12 or Older, by Age Group and 

Appalachian Sub-Region: Percentages, Annual Averages Based on 2002-2005 ...................... 49 

Table 2.17 Reasons for Not Receiving Mental Health Treatment among Persons Aged 12 or 

Older, by Age Group and Appalachian Sub-Region: Percentages, Annual Averages Based on 

2002-2005 ................................................................................................................................... 50 

Table 2.18 Access to Alcohol Use Treatment among Persons Aged 12 or Older, by Age Group 

and Appalachian Socioeconomic Status: Percentages, Annual Averages Based on 2002-200551 

Table 2.19 Access to Drug Treatment among Persons Aged 12 or Older, by Age Group and 

Appalachian Socioeconomic Status: Percentages, Annual Averages Based on 2002-2005 ...... 52 

Table 2.20 Reasons for Not Receiving Mental Health Treatment/Counseling among Persons Aged 

12 or Older, by Age Group and Appalachian Socioeconomic Status: Percentages, Annual 

Averages Based on 2002-2005 ................................................................................................... 53 
Table 3.1: Sub-regional Differences of Admissions to Substance Abuse Treatment in the 

Appalachian Region, By Demographics .................................................................................... 86 

Table 3.2: Sub-regional Differences of Admissions to Substance Abuse Treatment in the 

Appalachian Region, By Employment Status, Marital Status, and Pregnancy Status ............... 88 

Table 3.3: Sub-regional Differences of Admissions to Substance Abuse Treatment in the 

Appalachian Region, By Health Insurance and Source of Referral ........................................... 91 

Table 3.4: Sub-regional Differences of Admissions to Substance Abuse Treatment in the 

Appalachian Region, By Service Setting ................................................................................... 93 

Table 3.5: Sub-regional Differences of Admissions to Substance Abuse Treatment in the 

Appalachian Region, By Types of Services and Methadone Use As Part of Treatment ........... 95 

Table 3.6: Sub-regional Differences of Admissions to Substance Abuse Treatment in the 

Appalachian Region, By Prior Treatment Episodes and Expected Source of Payment ............. 97 

Table 3.7: Sub-regional Differences of Admissions to Substance Abuse Treatment in the 

Appalachian Region, By Use as a Primary Reason for Admission ........................................... 99 

Table 3.8: Sub-regional Differences of Admissions to Substance Abuse Treatment in the 

Appalachian Region, By One Major Reason for Admission ................................................... 101 

Table 3.9: Sub-regional Differences of Admissions to Substance Abuse Treatment in the 

Appalachian Region, By Psychological Problem and Mood Disorder Upon Admission ........ 103 

Table 4.1. AHRQ-developed Mental Health and Substance Abuse Clinical Classification Software 

(CCS-MHSA) ........................................................................................................................... 129 

Table 4.2a: Demographics of Community Hospital Discharges in the Appalachian Region 

(Unweighted) ............................................................................................................................ 132 

Table 4.2b: Demographics of Community Hospital Discharges in the Appalachian Region 

(Unweighted) by County Economic Development Status, 2004 ............................................. 133 

Table 4.3a: Admission Source, Type, and Expected Payment for Community Hospital Discharges in 

Appalachia (Unweighted), 2004 .............................................................................................. 136 

Table 4.3b: Admission Source, Type, and Expected Payment for Community Hospital Discharges in 

Appalachia (Unweighted) by County Economic Development Status, 2004 .......................... 137 

Table 4.4a: Hospital Stay Characteristics for Community Hospital Discharges in Appalachia 

(Unweighted), 2004 .................................................................................................................. 138 

Table 4.4b: Hospital Stay Characteristics for Community Hospital Discharges in Appalachia by 

County Economic Development Status (Unweighted), 2004 .................................................. 139 

Table 4.5a: Diagnoses and Principal Reason for Hospitalization for Community Hospital 

Discharges in Appalachia (Unweighted), 2004 ........................................................................ 141 

Table 4.5b: Diagnoses and Principal Reason for Hospitalization for Community Hospital 

Discharges in Appalachia (Unweighted), by County Economic Development Status, 2004 .. 142 

Table 4.6a: Differences Among All Principal and Secondary Mental Health or Substance Abuse 

Diagnoses for Discharges from Community Hospitals, 2004 .................................................. 144 

Table 4.6b: Differences Among All Principal and Secondary Mental Health or Substance Abuse 

Diagnoses Discharged from Community Hospitals, by County Economic Development Status, 

2004 .......................................................................................................................................... 145 

Table 4.7a: Differences Among Community Hospital Discharges by Substance Abuse and Mental 

Health Diagnoses as the Major Reason for Hospitalization, 2004 ........................................... 147 

Table 4.7b: Differences Among Community Hospital Discharges by Substance Abuse and Mental 

Health Diagnoses as the Major Reason for Hospitalization by County Economic Development 

Status, 2004 .............................................................................................................................. 148 

Table 4.8: Adult Patients Diagnosed with Mental Health Disorders in Community Hospitals, 2004

 .................................................................................................................................................. 149 
Table 5.1: Ownership and Other Characteristics of Substance Abuse Treatment Facilities, 2005 .. 157 

Table 5.2 Characteristics of Substance Abuse Treatment Facilities, 2005 ...................................... 158 

Table 5.3: Inpatient, Outpatient, and Non-Hospital Residential Care Offered at Substance Abuse 

Treatment Facilities, 2005 ........................................................................................................ 159 

Table 5.4 Counseling and Pharacotherapies Available at Treatment Facilities, 2005 ..................... 160 

Table 5.5 Services Available at Treatment Facilities, 2005 ............................................................. 161 

Table 6.1: Trend of Heroin Use as Primary, Secondary, or Tertiary Reason for Treatment, by Coal 

Mining Status of Patient Location ............................................................................................ 172 

Table 6.2: Trend of Other Opiates or Synthetics Use as Primary, Secondary, or Tertiary Reason for 

Treatment, by Coal Mining Status of Patient Location ............................................................ 173 

Table 6.3: Characteristics of Hospital Stays in Community Hospitals in the Appalachian Region, 

Adults Aged 18 or Older, by County Coal Mine Status ........................................................... 175 

Table 6.4: Characteristics of Admissions to Substance Abuse Specialty Treatment in the 

Appalachian Region, by County Coal Mine Status, 2000-2004 .............................................. 176 

Table 6.5: Treatment-Related Characteristics of Admissions to Substance Abuse Treatment in the 

Appalachian Region, by County Coal Mine Status, 2000-2004 .............................................. 178 

Table 6.6: Substance Abuse Characteristics of Admissions to Substance Abuse Treatment in the 

Appalachian Region, by County Coal Mine Status, 2000-2004 .............................................. 180 

Table 7.1. Selected Four Pairs of Counties Per State in the Appalachian Region Based on the 

Composite Ranking Score ........................................................................................................ 187 

Table 7.2. Model Programs (Best Practices) from Appalachian Twinned-County Focus Groups . 207 

Table 7.3. Strengths and Treatment Gaps for Twinned Counties Study ......................................... 208 

Table 7.4. Gaps In Available Data For Planning At the Local Level ............................................. 209 

APPENDIX C TABLES 

Table 2.1A Demographic Characteristics and Health Insurance among Persons Aged 12 or 

Older, by Age Group and Appalachian Region Status: Numbers in Thousands, Annual 

Averages Based on 2002-2005 ................................................................................................. 235 

Table 2.2A Lifetime, Past Year, and Past Month Substance Use among Persons Aged 12 or 

Older, by Substance, Age Group, and Appalachian Region Status: Numbers in Thousands, 

Annual Averages Based on 2002-2005 .................................................................................... 236 

Table 2.3A Substance Dependence or Abuse, Mental Health Measures, and Receipt of Substance 

Use Treatment in the Past Year among Persons Aged 12 or Older, by Age Group and 

Appalachian Region Status ...................................................................................................... 237 

Table 2.4A Demographic Characteristics and Health Insurance among Persons Aged 12 or Older 

Residing in Appalachian Region, by Age Group and Appalachian Sub-region ...................... 238 

Table 2.5A Lifetime, Past Year, and Past Month Substance Use among Persons Aged 12 or Older 

Residing in Appalachian Region, by Substance, Age Group, and Appalachian Sub-region ... 239 

Table 2.6A Substance Dependence or Abuse, Mental Health Measures, and Receipt of Substance 

Use Treatment in the Past Year among Persons Aged 12 or Older Residing in Appalachian 

Region, by Age Group and Appalachian Sub-region ............................................................... 240 

Table 2.7A Demographic Characteristics and Health Insurance among Persons Aged 12 or Older 

Residing in Appalachian Region, by Age Group and Appalachian Socioeconomic Status .... 241 

Table 2.8A Lifetime, Past Year, and Past Month Substance Use among Persons Aged 12 or Older 

Residing in Appalachian Region, by Substance, Age Group, and Appalachian Socioeconomic 

Status ........................................................................................................................................ 242 
Table 2.9A Substance Dependence or Abuse, Mental Health Measures, and Receipt of 

Substance Use Treatment in the Past Year among Persons Aged 12 or Older Residing in 

Appalachian Region, by Age Group and Appalachian Socioeconomic Status ........................ 243 

Table 2.10A Access to Alcohol Treatment among Persons Aged 12 or Older, by Age Group 

and Appalachian Region Status: Numbers in Thousands ........................................................ 244 

Table 2.11A Access to Drug Treatment among Persons Aged 12 or Older, by Age Group and 

Appalachian Region Status: Numbers in Thousands ............................................................... 245 

Table 2.12A Reasons for Not Receiving Substance Use Treatment and Locations of Treatment 

by Age Group and Appalachian Region Status ........................................................................ 246 

Table 2.13A Reasons for Not Receiving Mental Health Treatment among Persons Aged 12 or 

Older, by Age Group and Appalachian Region Status: Numbers in Thousands ..................... 247 

Table 2.14A Access to Alcohol Use Treatment among Persons Aged 12 or Older, by Age 

Group and Appalachian Sub-Region: Numbers in Thousands ................................................ 248 

Table 2.15A Access to Drug Use Treatment among Persons Aged 12 or Older, by Age Group 

and Appalachian Sub-Region: Numbers in Thousands ............................................................ 249 

Table 2.16A Reasons for Not Receiving Mental Health Treatment among Persons Aged 12 or 

Older, by Age Group and Appalachian Sub-Region: Numbers in Thousands ......................... 250 

Table 2.17A Access to Alcohol Use Treatment among Persons Aged 12 or Older, by Age 

Group and Appalachian Socioeconomic Status: Numbers in Thousands ................................ 251 

Table 2.18A Access to Drug Treatment among Persons Aged 12 or Older, by Age Group and 

Appalachian Socioeconomic Status: Numbers in Thousands .................................................. 252 

Table 2.19A Reasons for Not Receiving Mental Health Treatment/Counseling among Persons 

Aged 12 or Older, by Age Group and Appalachian Socioeconomic Status: Numbers in 

Thousands, Annual Averages Based on 2002-2005 ................................................................. 253 

Table 2.1B Demographic Characteristics and Health Insurance among Persons Aged 12 or 

Older, by Age Group and Appalachian Region Status: Standard Errors of Percentages, Annual 

Averages Based on 2002-2005 ................................................................................................. 254 

Table 2.2B Lifetime, Past Year, and Past Month Substance Use among Persons Aged 12 or 

Older, by Substance, Age Group, and Appalachian Region Status: Standard Errors of 

Percentages, Annual Averages Based on 2002-2005 ............................................................... 255 

Table 2.3B Substance Dependence or Abuse, Mental Health Measures, and Receipt of Substance 

Use Treatment in the Past Year among Persons Aged 12 or Older, by Age Group and 

Appalachian Region Status ...................................................................................................... 256 

Table 2.4B Demographic Characteristics and Health Insurance among Persons Aged 12 or Older 

Residing in Appalachian Region, by Age Group and Appalachian Subregion: Standard Errors 

of Percentages, Annual Averages Based on 2002-2005 .......................................................... 257 

Table 2.5B Lifetime, Past Year, and Past Month Substance Use among Persons Aged 12 or 

Older Residing in Appalachian Region, by Substance, Age Group, and Appalachian 

Subregion... ............................................................................................................................. 258 

Table 2.6B Substance Dependence or Abuse, Mental Health Measures, and Receipt of Substance 

Use Treatment in the Past Year among Persons Aged 12 or Older Residing in Appalachian 

Region, by Age Group and Appalachian Subregion: Standard Errors of Percentages, Annual 

Averages Based on 2002-2005 ................................................................................................. 259 

Table 2.7B Demographic Characteristics and Health Insurance among Persons Aged 12 or Older 

Residing in Appalachian Region, by Age Group and Appalachian Socioeconomic Status: 

Standard Errors of Percentages, Annual Averages Based on 2002-2005 ................................ 260 
Table 2.8B Lifetime, Past Year, and Past Month Substance Use among Persons Aged 12 or 

Older Residing in Appalachian Region, by Substance, Age Group, and Appalachian 

Socioeconomic Status, 2002 - 2005 ......................................................................................... 261

Table 2.9B Substance Dependence or Abuse, Mental Health Measures, and Receipt of Substance 

Use Treatment in the Past Year among Persons Aged 12 or Older Residing in Appalachian 

Region, by Age Group and Appalachian Socioeconomic Status: Standard Errors of 

Percentages, Annual Averages Based on 2002-2005 ............................................................... 263 

Table 2.10B Access to Alcohol Treatment among Persons Aged 12 or Older, by Age Group and 

Appalachian Region Status: Standard Errors of Percentages, Annual Averages Based on 2002-

2005...... .................................................................................................................................. 264 

Table 2.11B Access to Drug Treatment among Persons Aged 12 or Older, by Age Group and 

Appalachian Region Status: Standard Errors of Percentages, Annual Averages Based on 2002-

2005...... .................................................................................................................................. 265 

Table 2.12B Reasons for Not Receiving Substance Use Treatment and Locations of Treatment 

among Persons Aged 12 or Older, by Age Group and Appalachian Region Status: Standard 

Errors of Percentages, Annual Averages Based on 2002-2005................................................ 266 

Table 2.13B Reasons for Not Receiving Mental Health Treatment among Persons Aged 12 or 

Older, by Age Group and Appalachian Region Status: Standard Errors of Percentages, Annual 

Averages Based on 2002-2005 ................................................................................................. 267 

Table 2.14B Access to Alcohol Use Treatment among Persons Aged 12 or Older, by Age Group 

and Appalachian Sub-Region: Standard Errors of Percentages, Annual Averages Based on 

2002-2005 ................................................................................................................................. 268 

Table 2.15B Access to Drug Use Treatment among Persons Aged 12 or Older, by Age Group and 

Appalachian Sub-Region: Standard Errors of Percentages, Annual Averages Based on 2002-

2005...... .................................................................................................................................. 269 

Table 2.16B Reasons for Not Receiving Mental Health Treatment among Persons Aged 12 or 

Older, by Age Group and Appalachian Sub-Region: Standard Errors of Percentages, Annual 

Averages Based on 2002-2005 ................................................................................................. 270 

Table 2.17B Access to Alcohol Use Treatment among Persons Aged 12 or Older, by Age Group 

and Appalachian Socioeconomic Status: Standard Errors of Percentages, Annual Averages 

Based on 2002-2005 ................................................................................................................. 271 

Table 2.18B Access to Drug Treatment among Persons Aged 12 or Older, by Age Group and 

Appalachian Socioeconomic Status: Standard Errors of Percentages, Annual Averages Based 

on 2002-2005 ............................................................................................................................ 272 

Table 2.19B Reasons for Not Receiving Mental Health Treatment/Counseling for Persons with an 

Unmet Need for Mental Health Treatment, by Age Group and Appalachian Socioeconomic 

Status: Based on 2002-2005 ..................................................................................................... 273 

FIGURES 

Figure 2.1. Geographic Variation in Individuals’ Health Insurance: Adolescents and Adults ......... 40 

Figure 2.2. Geographic Variation in Individuals’ Health Insurance: Adolescents and Adults ......... 41 

Figure 2.3. Non-Medical Use of Prescription Drugs Among Adolescents Aged 12 to 17 ............... 42 

Figure 2.4. Mental Disorders Among Adults Aged 18 and Older in Appalachian Sub-Regions ..... 43 

Figure 3.1 Primary Substance of Abuse at Admission, Aged 12 and Older, in the U.S., TEDS 

2000-2004 ................................................................................................................................. 106 
Figure 3.2 Primary Substance of Abuse at Admission, Aged 12 and Older, in the Appalachian 

Region, TEDS 2000-2004 ........................................................................................................ 106 

Figure 3.3 Admissions Aged 12 and Over for Primary Alcohol Abuse, in the U.S. and Appalachia, 

TEDS 2000 – 2004 ................................................................................................................... 107 

Figure 3.4 Admissions Aged 12 and Over for Primary Marijuana/Hashish Abuse, in the U.S. and 

Appalachia, TEDS 2000 – 2004 ............................................................................................... 107 

Figure 3.5 Admissions Aged 12 and Over for Primary Cocaine Abuse, in the U.S. and Appalachia, 

TEDS 2000 – 2004 ................................................................................................................... 108 

Figure 3.6 Admissions Aged 12 and Over for Primary Heroin Abuse, in the U.S. and Appalachia, 

TEDS 2000 – 2004 ................................................................................................................... 108 

Figure 3.7 Admissions Aged 12 and Over for Primary Abuse of Other Opiates/Synthetics, in the 

U.S. and Appalachia, TEDS 2000 – 2004 ................................................................................ 109 

Figure 3.8 Admissions Aged 12 and Over for Primary Methamphetamine Abuse, in the U.S. and 

Appalachia, TEDS 2000 – 2004 ............................................................................................... 109 

Figure 4.1 Admission Source by Appalachian County Economic Development Status ................. 134 

Figure 4.2 Primary Expected Payer By Appalachian County Economic Development Status ....... 135 

Figure 5.1: Facilities Offering Inpatient Detoxification Services .................................................... 162 

Figure 5.2: Primary Focus of Substance Abuse Facilities ............................................................... 162 

Figure 5.3: Facilities Using a Sliding Fee Scale .............................................................................. 163 

Figure 5.4: Facilities Offering Free or No Charge Treatment .......................................................... 163 

Figure 5.5: Facilities that Accept Medicare ..................................................................................... 164 

Figure 5.6: Facilities that Accept Medicaid ..................................................................................... 164 

Figure 5.7: Facilities that Accept State Financed Health Insurance ................................................ 165 

Figure 5.8: Facilities that Accept Private Health Insurance ............................................................. 165 

Figure 6.1 Coal Mining Area in the Appalachian Region ................................................................ 169 

Figure 6.2 Coal Mining Appalachian Sub-Regions ......................................................................... 174 

Figure 7.1 Map of Case Study Counties .......................................................................................... 189 

MAPS 

Map 2.1 Average Population 2002-2005, in the Appalachian Region by County ............................. 55 

Map 2.2 Number of Sampled Adults Age 18 or older in NSDUH 2002-2005, in the Appalachian 

Region by County ....................................................................................................................... 56 

Map 2.3 Number of Sampled Adolescents Age 12 – 17 in NSDUH 2002-2005, in the Appalachian 

Region by County ....................................................................................................................... 57 

Map 2.4 Perception of Great Risk of Binge Drinking, by NSDUH Sub-Region ............................... 58 

Map 2.5 Alcohol Use in Past Month, by NSDUH Sub-Region ......................................................... 59 

Map 2.6 Binge Alcohol Use in Past Month, by NSDUH Sub-Region ............................................... 60 

Map 2.7 Alcohol Use in Past Month Among Persons Aged 12-20, by NSDUH Sub-Region ........... 61 

Map 2.8 Binge Alcohol Use in Past Month, Persons Aged 12-20, by NSDUH Sub-Region ............ 62 

Map 2.9 Alcohol Dependence in Past Year, by NSDUH Sub-Region .............................................. 63 

Map 2.10 Needing But Not Receiving Treatment in Past Year for Alcohol Use, by NSDUH SubRegion ........................................................................................................................................ 64 

Map 2.11 Perception of Great Risk of Smoking One or More Packs of Cigarettes Everyday, by 

NSDUH Sub-Region .................................................................................................................. 65 

Map 2.12 Cigarette Use in Past Month, by NSDUH Sub-Region ..................................................... 66 

Map 2.13 Marijuana Use in Past Month, by NSDUH Sub-Region .................................................... 67 
Map 2.14 Marijuana Use in Past Year, by NSDUH Sub-Region ...................................................... 68 

Map 2.15 Cocaine Use in Past Year, by NSDUH Sub-Region .......................................................... 69 

Map 2.16 Any Use of Illicit Drugs Other Than Marijuana, Past Month, by NSDUH Sub-Region ... 70 

Map 2.17 Any Drug Dependence in Past Year, by NSDUH Sub-Region ......................................... 71 

Map 2.18 Needing But Not Receiving Treatment for Drug Use in Past Year, by NSDUH SubRegion ........................................................................................................................................ 72 

Map 2.19 Painkiller Use in Past Year, by NSDUH Sub-Region ....................................................... 73 

Map 2.20 Serious Psychological Distress in Past Year, by NSDUH Sub-Region ............................. 74 

Map 3.1. Percentage of Persons with Three or More Prior Treatment Episodes ............................ 110 

Map 3.2. Percentage of Persons with No Prior Treatment Episodes .............................................. 111 

Map 3.3. Percentage of Persons Who Had an Alcohol and Drug or Health Provider Referral ...... 112 

Map 3.4. Percentage of Persons Who Had a Court or Criminal Justice Referral ........................... 113 

Map 3.5. Percentage of Persons Who Had an Individual Referral (Including Self-Referral) ......... 114 

Map 3.6. Percentage of Persons Admitted to Treatment for Alcohol Use ...................................... 115 

Map 3.7. Percentage of Persons Admitted to Treatment for Cocaine Use ...................................... 116 

Map 3.8. Percentage of Persons Admitted to Treatment for Heroin Use ........................................ 117 

Map 3.9. Percentage of Persons Admitted to Treatment for Methamphetamine Use ..................... 118 

Map 3.10. Percentage of Persons Admitted to Treatment for Primary Methamphetamine Abuse .. 119 

Map 3.11. Percentage of Persons Admitted to Treatment for Psychiatric Problems ...................... 120 
1 

Executive Summary 

This report presents an analysis of disparities in mental health status and substance abuse 

prevalence, as well as access to treatment services, in the 410 county Appalachian region 

comprising all or parts of 13 states. 

Aim and Objectives

The aim of this research is to assist regional policy makers and public health practitioners in 

improving surveillance, research and health education, as well as to more effectively target 

investments designed to improve the delivery of substance abuse and mental health treatment and 

treatment outcomes. The specific objectives of this study are to: 

Identify whether there are specific disparities in mental health and substance abuse 

diagnoses within the region, and any apparent incidence clusters within the region; 

Identify and analyze available data to measure the accessibility of mental health services and 

substance abuse treatment services within the region and compare the region to other parts 

of the nation; and 

Develop a set of criteria and protocols to identify relevant case study communities within 

the Appalachian region and conduct case study analyses accordingly. 

Data and Analyses

This study utilizes state, sub-state, and county level data on diagnoses and treatment of mental 

health and substance abuse conditions. These data are used to analyze potential disparities across 

Appalachian sub-regions and economic development levels defined by the Appalachian Regional 

Commission (ARC). The analyses draw on four major sources of public information on mental 

health and substance abuse diagnoses and treatment: 

National household survey of mental health and substance abuse (2002-2005); 

Treatment episode data on admissions to substance abuse specialty treatment facilities 

(2000-2004); 

Community hospital discharge reports of diagnoses and treatment of mental health 

conditions and substance abuse (2004); and 

National survey of treatment services reported by participating substance abuse treatment 

facilities regarding mental health and substance abuse services (2005). 

To supplement quantitative data sources, a series of case studies were also conducted in partnership 

with East Tennessee State University (ETSU). The purpose of these case studies was to gather 

additional information on how data are used to target mental health and substance abuse prevention 

and treatment resources, and to identify needed information to improve “on the ground” delivery of 

services. 
2 

Findings 

Mental Health 

There appears to be a higher prevalence of mental health disorders in the Appalachian region as 

compared to the rest of the nation, with proportionately more Appalachian adults reporting serious 

psychological distress and major depressive disorder. 

Mental health problems are not equally distributed across the region, with higher rates of serious 

psychological stress and major depressive episodes in central, as compared to northern and 

southern, Appalachia. 

Notably, mental health diagnoses for serious psychological distress and major depressive disorder 

are proportionately higher in Appalachia than in the rest of the nation, independent from substance 

abuse. That is, Appalachian disparities in mental health status do not appear to arise as a result of 

higher levels of co-occurrence with substance abuse. Community hospital discharge data, national 

household survey data, and treatment episode data all indicate this regional mental health disparity, 

independent of substance abuse. This disparity is particularly acute in more economically 

distressed areas of Appalachia. 

While this mental health disparity is an important finding, the case studies and discussions with 

members of the Coalition on Appalachian Substance Abuse Policy (CASAP) provide additional 

depth to our analyses that may help to explain the apparent lack of co-occurring disorders in the 

region. These sources suggest that there could be biases in the medical care system within the 

region that encourage under-reporting of comorbidity rates for mental health and substance abuse 

diagnoses. For example, facilities may under-report comorbidities to ensure optimal 

reimbursement. This study has not identified any evidence that suggests that under-reporting of 

comorbidities happens more often in Appalachia than in other regions, however. Future work 

should explore whether there is any systematic bias in the way mental health care payment and 

coverage is managed within the Appalachian Region, and whether such a bias may lead to 

underreporting of co-occurring substance abuse and mental health illnesses. 

Substance Use Problems

Alcohol is the predominant substance of abuse upon admission to treatment, nationally and in 

Appalachia. However, hospital discharge data show that Appalachian residents have a lower 

proportion of diagnoses for substance abuse only, and for co-occurring substance abuse and mental 

health problems, as compared to the rest of the nation. 

Findings related to specific substances demonstrate the following: 

This study does not support the belief that methamphetamine use is higher in Appalachia 

than elsewhere in the nation. Rather, methamphetamine use and admission rates are lower 

across Appalachia than in the rest of the nation. While regional trends show that 

methamphetamine use is rising, the rate of increase is similar to that of the rest of the nation 

so that rates in Appalachia remain lower. While there are likely to be “pockets of abuse” 

within the region, rates are lower within the region as a whole. 
3 

 

Other opiates and synthetics1 admission rates for primary abuse are higher in Appalachia 

than the rest of the nation, especially in coal-mining areas. The trend is rising across the 

nation and in Appalachia, but at a faster pace in Appalachia. This is particularly the case in 

Appalachian coal mining areas. 

Cigarette use rates2 are higher in Appalachia than in the rest of the nation among both 

adolescents and adults. 

Marijuana use rates are lower in Appalachian than in the rest of the nation among adults. 

Cocaine use rates are lower in Appalachia than in the rest of the nation among adults. 

Heroin admission rates are lower in Appalachia than in the rest of the nation, but the trend is 

rising, especially in coal-mining areas. 

Proportionately fewer Appalachian adults than adults outside the region are classified as 

having alcohol abuse or dependence, or both alcohol and illicit drug abuse or dependence 

according to household survey responses.3

Proportionately more Appalachian adolescents report nonmedical use of psychotherapeutics4

than adolescents in the rest of nation. 

Treatment of Substance Use and Mental Health Disorders

Overall, access to substance use and mental health treatment within the Appalachian region 

compares favorably to the United States as a whole. Overall, proportionately more adults in the 

Appalachian region with mental health problems received outpatient mental health treatment 

counseling services and prescription medical services in the past year, as compared to adults outside 

the Appalachian region. There is no significant difference between Appalachian adolescents and 

adults and adolescents and adults outside of the region in terms of the proportion of persons who 

need but do not receive treatment for an illicit drug problem. 

Proportionately more patients entered community hospitals for substance abuse or mental health 

treatment via the emergency room in the Appalachian region. This was particularly the case in 

more economically distressed counties and in coal mining areas. This may be an indicator of fear or 

stigma associated with mental health and substance use treatment, which is consistent with findings 

from the national household survey. 

In looking at treatment related to specific substances of abuse, findings related to other opiates or 

synthetics and alcohol are noteworthy: 

The percentage of people in the Appalachian region admitted to treatment for the primary 

abuse of other opiates or synthetics is significantly higher than in other regions of the United 

 

1

 These drugs include codeine, hydrocodone, hydromorphone, meperidine, morphine, opium, oxycodone, pentazocine, 

propoxyphene, tramadol, and any other drug with morphine-like effects except methadone. 2

 The rates cover the lifetime, past year, and past month use respectively. 

3

 The illicit drug abuse or dependence rate is also lower among Appalachian adults than adults outside the region, but 

the difference is not statistically significant. 

4

 Nonmedical use of prescription-type psychotherapeutics includes the nonmedical use of pain relievers, tranquilizers, 

stimulants, or sedatives and does not include over-the-counter drugs. 
4 

States. Within the Appalachian region, rates are highest in the central part of the Region and 

in coal mining areas. 

Proportionately more Appalachian adults in need of alcohol treatment receive treatment, as 

compared to adults in the rest of nation. 

When looking at services offered in substance abuse treatment facilities, findings demonstrate that: 

Outpatient rehabilitation is the most common setting for substance abuse treatment in 

Appalachia. 

Proportionately more Appalachian treatment facilities offer intensive outpatient care when 

compared to facilities outside of Appalachia. 

In Appalachia, proportionately fewer facilities offer outpatient detoxification when 

compared to facilities outside of Appalachia. 

Short-term non-hospital residential treatment is offered in proportionately fewer facilities in 

Appalachia than outside of Appalachia. 

Long-term non-hospital residential treatment is offered in proportionately fewer facilities in 

Appalachia than outside of Appalachia. 

Proportionately more treatment facilities in Appalachia offer services such as substance 

abuse family counseling and mental health assessment when compared to facilities outside 

of Appalachia. 

In Appalachia, proportionately more treatment facilities accept Medicare, Medicaid, state 

financed insurance, and private insurance as payment when compared to facilities outside of 

Appalachia. 

Case Study Findings 

Case study findings in six Appalachian counties provide additional depth to quantitative findings 

showing a lack of access to inpatient treatment for both substance abuse and mental illnesses. The 

case studies revealed a number of specific barriers in to accessing treatment for substance abuse and 

mental health illnesses, including: 

Stigma; 

Transportation; 

Payment options; 

Privacy issues; 

Choice of facilities; and 

Cultural or family barriers. 
5 

The case study counties reported difficulties in getting access to inpatient and residential treatment 

facilities. No case study county had inpatient facilities for either substance abuse or mental health 

and most reported difficulty placing those needing long term outpatient treatment. 

Recognizing the challenges confronting their communities, focus group participants noted the 

development of school-based prevention activities, after-school youth activities, anti-drug coalition 

activities, mentoring programs, parenting classes, agricultural extension programs, wellness classes, 

health camps, mentoring programs, sports, and recreational activities. Focus groups revealed a need 

for additional school-based interventions and prevention programs. 

Findings from the case studies also showed that community-level substance abuse and mental health 

leaders do not generally use nationally-available data sets to make decisions about local response to 

substance abuse and mental health issues, nor do they have uniformly available county and state 

data from which to draw conclusions about the magnitude of substance abuse and mental health 

issues within their communities. While they may use state data, especially when it supports 

applications for grant funding for prevention programs, more often than not, anecdotal evidence is 

used as the basis for informing local decision making. These findings do not suggest a disregard for 

the data, but rather the lack of utility in how data are presented and a disconnect between the levels 

of analysis (generally state or regional) and the level of service delivery (local). 

Conclusions 

Overall, the findings from this study suggest that disparities do exist in the Appalachian region for 

specific substance use and mental health disorders. While some of these disparities exist across the 

Appalachian region, even more can be learned by looking at a more granular level. Specifically, 

findings demonstrate particular disparities related to Appalachian sub-region, county economic 

distress level, and within coal-mining areas. These findings are consistent across data sets and, 

when taken with region-wide findings, demonstrate the presence of place-based disparities. Key 

region-wide findings are that: 

Mental health is a major area for concern in Appalachia, independent from substance abuse; 

Alcohol is the predominant substance of abuse upon admission to treatment, nationally and 

in Appalachia; 

Methamphetamine is not as large of a problem across Appalachia as is widely reported, 

although regional trends show that methamphetamine use is rising. The rate of increase, 

however, is similar to that of the rest of the nation so that rates in Appalachia remain lower 

when compared to the United States as a whole; 

Primary abuse of other opiates and synthetics is a key issue in Appalachia. Admission rates 

for primary abuse of other opiates and synthetics are higher in Appalachia than the rest of 

the nation, and rates are increasing within the region at a faster pace when compared to the 

United States as a whole; 

Outpatient rehabilitation is the most common setting for substance abuse treatment in 

Appalachia; 
6 

Access to inpatient treatment, and short and long-term non-hospital residential treatment for 

substance abuse or mental health illnesses, is less common within the Appalachian region; 

and 

Access to treatment is better in Appalachia when compared to the rest of the nation in terms 

of accepted forms of payment, and the provision of services such as substance abuse family 

counseling and mental health assessment. 

Whereas region-wide findings suggest opportunities to target resources across the Appalachian 

region, sub-regional findings suggest opportunities for states and communities to target resources to 

address more localized disparities. This point is noteworthy given case study findings 

demonstrating that community-level substance abuse and mental health leaders generally use 

anecdotal information in determining program priorities and resource allocation, due to a lack of 

uniformly available county and state data. 

Key findings from the case studies revealed that: 

There are regional difficulties in accessing inpatient facilities for substance abuse or mental 

health; 

There are regional difficulties in accessing long-term outpatient treatment; 

There are barriers to treatment for substance abuse and mental illnesses such as 

transportation, cultural factors, and stigma; 

Communities in Appalachia are targeting resources to prevent substance abuse and mental 

health illness; and 

Additional school-based interventions and prevention programs are needed in Appalachian 

communities. 

The case study counties are currently using an array of prevention programs and activities – such as 

The Beginning Alcohol and Addictions Basic Education Studies (BABES), Too Good For DrugsTM 

(K–8), and D.A.R.E. (Drug Abuse Resistance Education), LifeSkills4Kids, among others – to 

educate children and adolescents about the personal and social consequences of substance abuse, 

and to reduce risk factors and enhance protective factors related to alcohol, tobacco and other drug 

use. Prevention programs are offered in a variety of settings such as schools, youth organizations, 

and the workplace. Anti-drug coalitions are also present in the case study counties. 

The wide array of community programs available in Appalachian communities shows an 

appropriate recognition of, and focus on, the problems of substance abuse and mental illness. 

Future work should further explore community best practices in the prevention of substance abuse 

and mental health illness to address and prevent these problems in Appalachia. 
7 

CHAPTER 1: Introduction 

NORC at the University of Chicago was commissioned by the Appalachian Regional Commission 

(ARC) to analyze disparities in substance abuse, mental health status, and access to treatment 

services in the Appalachian region.5

 The Appalachian region is comprised of West Virginia and 

parts of 12 states: Alabama; Georgia; Kentucky; Maryland; Mississippi; New York; North Carolina; 

Ohio; Pennsylvania; South Carolina; Tennessee; and Virginia. Over four decades ago, the United 

States Congress established the ARC to facilitate economic development efforts in the Appalachian 

region in response to persistent issues of poverty, economic distress, joblessness, poor physical 

infrastructure, and cultural isolation. While some Appalachian communities have experienced 

economic and infrastructural improvements,1

 research has shown that disparities in health status 

exist between the Appalachian region and non-Appalachian U.S., with Appalachia experiencing 

more adverse health outcomes.2

 Through the current study we will determine the extent to which 

these disparities also exist relative to substance abuse and mental health status, and access to 

treatment services. 

This is the first effort to study substance abuse and mental health issues and access to treatment 

services within Appalachia, and between Appalachia and the rest of the United States. The study 

draws upon data from a variety of government sources and information from local communities 

with the goal of providing health care researchers, practitioners, and policy makers with a detailed 

understanding of substance abuse and mental health issues and access to treatment services in 

Appalachia, including patterns across Appalachian sub-regions, across levels of economic 

development, and between Appalachia and the rest of the United States. The qualitative and 

quantitative results from this study augment the scant body of literature on substance abuse 

disorders and mental health status, and access to treatment services in Appalachia. 

1.1 Substance Abuse and Mental Health Disorders in Appalachia 

Research to date does not provide a comprehensive understanding of substance abuse prevalence 

and mental health status, and access to treatment services in Appalachia. While a body of research 

has explored the prevalence of substance abuse and mental health disorders in rural 

communities,3,4,5,6,7,8 little research has explored these issues in Appalachian communities 

specifically. Studies suggest that disparities in access to and utilization of treatment for substance 

abuse and mental health disorders result from a complex interplay of socioeconomic, cultural, and 

health system factors. Race and ethnicity may also play a role in driving disparities within certain 

Appalachian sub-regions and communities. 

Research has identified some mechanisms to reduce treatment disparities in Appalachia, including 

cultural competency training for mental health and social service professionals9

 and enhanced 

surveillance systems.10 Studies have explored the potential for health care system changes to reduce 

disparities in rural America, though not in Appalachia specifically. Such changes include mental 

health staff in rural health centers;11 health care service delivery via telemedicine;12 and self help 

groups.13 Additional research is necessary to explore disparities specific to the Appalachian Region 

and inform cost-effective ways to combat disparities related to treatment access for mental health 

 

5

 The Appalachian region is home to more than 23 million people, extending from southern New York to northeast 

Mississippi and covering over 200,000 square miles of 410 counties in 13 states. 
8 

and substance abuse disorders in the region. Further study is needed to inform policy makers in the 

design of targeted interventions to reduce disparities in Appalachia. Specifically, it will be 

necessary to have a better understanding of the prevalence and geographic distribution of substance 

abuse and mental health disorders at the sub-regional level within Appalachian states – ideally at the 

county level. 

In order for policy makers to design targeted policy interventions to reduce disparities in 

Appalachia, it will be necessary to have a better understanding of the prevalence and geographic 

distribution of substance abuse and mental health disorders within the region. 

1.2 Key Research Questions and Methodology 

Recognizing the current gaps in the literature to date, this study strives to augment the body of 

literature on substance abuse and mental health issues and access to treatment services in 

Appalachia. Our study addresses four key research questions: 

1. Are there disparities in mental health status and substance abuse prevalence, and access to 

treatment services, in the Appalachian region as compared to the rest of the United States? 

2. Does socio-economic status, as measured by county economic development status, matter 

with respect to substance abuse and mental health issues and access to treatment services 

within Appalachia, and between Appalachia and areas outside of Appalachia? 

3. Are there notable patterns or trends across the northern, central or southern Appalachian 

sub-regions for different mental health status and substance abuse indicators? 

4. To the extent possible, can we identify county-level patterns in substance abuse prevalence 

and mental health status, and access to treatment services? 

To investigate our research questions, we utilized the largest and most up-to-date survey and 

administrative record data available from several Federal government sources. We analyzed data 

from the National Survey on Drug Use and Health (NSDUH), the Treatment Episode Data Set 

(TEDS), the Healthcare Cost and Utilization Project (HCUP), and the National Survey of Substance 

Abuse Treatment Services (N-SSATS). This study also incorporates a qualitative component to 

augment our quantitative findings; we include case studies based on paired Appalachian counties 

that are closely matched based on socioeconomic indicators yet demonstrate differences in mental 

health and substance abuse status. The case studies were conducted as a pilot effort to develop and 

test a methodology for gathering qualitative substance abuse and mental health status information 

across Appalachian states. 

Overall, our study incorporates the following data: 

19,416,000 Appalachian household residents age 12 or older as represented by 22,000 

Appalachian survey respondents (NSDUH); 

500,000 Appalachian admissions to substance abuse treatment (TEDS); 
9 

8,000,000 community hospital inpatient discharges, including 168,000 Appalachian 

discharge records (HCUP); 

980 Appalachian substance abuse treatment facilities (N-SSATS); and 

Six qualitative community case studies in three of the 13 Appalachian states. 

1.3 Importance of the Current Study 

This study is unique for three key reasons. First, we explore a variety of mental health and 

substance abuse indicators, and other demographic and socio-economic variables, based on data 

from four different federal sources. In addition, NORC partnered with East Tennessee State 

University (ETSU) to conduct a complementary qualitative component of the study. Specifically, a 

pilot set of focus groups were conducted in six Appalachian counties in three states with county 

officials and stakeholders about mental health and substance abuse issues in their communities. 

Second, as part of our process for conducting the study, we sought ongoing input and feedback from 

practitioners in the field. Specifically, we met with the Coalition on Appalachian Substance Abuse 

Policy (CASAP) – a leading group of mental health and substance abuse professionals in Central 

Appalachia – regarding their insights into the data sets, analyses, and findings.6

 The feedback that 

was generated through discussions with CASAP is presented in each chapter in a section entitled 

“reflections from practitioners.” It is important to note that the information presented in these 

sections is based on the reflections, insights, and opinions of the CASAP members, based upon their 

experiences in the field. 

Third, wherever possible, analytic results are broken down by sub-region (northern, central, 

southern) and county economic development level (distressed, at-risk, transitional, competitive, and 

attainment) to identify patterns and trends across different geographic areas. Additionally, some 

data sets also allow results to be presented graphically through a series of maps, demonstrating 

differences across counties. 

ARC divides the Appalachian region into three sub-regions – the northern, central, and southern 

sub-regions. Each region has relatively homogenous characteristics. 

Map 1.1 shows the Appalachian sub-regions as defined by ARC. The northern region includes 

parts of New York, Pennsylvania, Ohio, Maryland, and West Virginia. The central region is 

comprised of counties within Kentucky, Virginia, West Virginia, and Tennessee. The southern 

region is comprised of parts of Tennessee, North Carolina, South Carolina, Georgia, Alabama, and 

Mississippi. Our research explores substance abuse and mental health indicators at the sub-regional 

level when possible to identify patterns and trends. 

 

6

 CASAP was established by the ARC via a Kentucky Flex-E-Grant. 
10 

In order to better understand needs of the Appalachian counties, and decide on spending and project 

activities for each fiscal year, the ARC determines the economic development status of each county. 

The ARC uses a structured process to designate county economic status. In short, economic 

indicators such as the three-year average unemployment rate, per capita market income, and poverty 

rate are used to assign all U.S. counties into economic development quartiles. Status is then 

assigned by comparing individual county performance to all other counties in the U.S. on these 

indicators.14 More information on the process for determining county economic development 

status can be found on the Appalachian Regional Commission’s website at www.arc.gov. 

Map 1.2 below illustrates the economic development status for counties in Appalachia, based on 

ARC’s index-based county economic classification system. In FY 2007, seventy-eight of the 410 

Appalachian counties are categorized as “distressed.” These counties (in red) rank among the 

lowest 10 percent of the nation’s counties on economic status indicators. Distressed counties have 

high poverty and unemployment rates and low per capita income rates in comparison to other 

counties. Another 78 counties are categorized as “at-risk.” At-risk counties (in orange) are at risk 

of becoming distressed counties. Over half of the counties (221) are characterized as transitional 

counties. These counties (in white) are areas transitioning between weak and strong economies. 

Twenty-six counties are “competitive.” These counties (in light blue) are competitive with counties 

nationally. Finally, a small number of counties are identified as “attainment counties.” Seven 

counties (in dark blue) are attainment counties, and considered among the strongest counties in the 

nation relative to economic development indicators. 

Map 1.1. Appalachian Subregions 
11 

1.4 Structure of the Report 

The remaining eight chapters of the report are structured to explore each of our research questions. 

Chapters 2 through Chapter 5 detail four independent but related studies, focusing on a variety of 

issues related to substance abuse, mental health status, and access to treatment services in the 

Appalachian region. Specifically, Chapter 2 presents estimates of substance use, mental disorder, 

and access to treatment services from household surveys conducted from 2001-2005. Chapter 3 

provides findings on patient admissions to specialty treatment for abuse of alcohol and drugs in the 

Appalachian region during the period from 2000-2004. Chapter 4 discusses findings on health care 

access and service utilization for substance use and mental disorders by examining community 

hospital discharges in both the Appalachian region and elsewhere in the United States. Chapter 5 

presents key features of substance abuse treatment services in the Appalachian region, using the 

most recent treatment facility survey data. In Chapter 6, we focus exclusively on the Appalachian 

region with the objective of comparing coal mining areas and other areas with respect to substance 

abuse and mental health status and access to the treatment services. In Chapter 7, we present a 

complementary qualitative study comprised of six community case studies in three Appalachian 

states. In Chapter 8, we offer conclusions resulting from this study. Appendix A at the end of the 

report provides detailed information about the data sources. Appendix B is a literature review about 

substance abuse and mental health issues, with a concentration on Appalachia and rural America. 

Appendix C provides additional data tables based on the National Survey on Drug Use and Health. 

Appendix D provides a series of county-level data profiles on key substance abuse and mental 

health indicators that were used during the qualitative study. Immediately following this 

introduction, we provide an overview of the data sources used to conduct this study, and short 

abstracts of Chapters 2 through 7 to help the reader to navigate this report. 

Map 1.2 Appalachian County Economic Development Level 
12 

Table 1.1 Overview of the Data Sets: Data Coverage, Data Reliability, and 

Characteristics 

Overview of Data Sets 

NSDUH 

TEDS 

N-SSATS 

HCUP 

Data Coverage

Coverage of mental health issues z z z z 

Coverage of substance abuse issues z z z z 

Survey addresses co-occurring MH/SA disorders z z z z 

Survey excludes some populations z z z z 

Survey excludes some SM or MH treatment facilities z z z z 

Reporting to the survey is limited to facilities that are funded and 

licensed by the state z z z 

State accreditation and certification requirements, and state systems of 

licensure may contribute to exclusion of certain facilities z z 

Survey excludes some Appalachian counties z z z z 

Survey was not designed to provide regional estimates z z z z 

Confidentiality concerns that prohibit the state from releasing data on 

certain Appalachian counties z z z z 

Private for-profit facilities, hospitals, and state correctional facilities may 

be excluded from the survey z 

Data Reliability

Due to institutional budgetary and reimbursement issues, MH/SA 

diagnoses may be under-coded or miscoded* z z 

Data availability varies from state to state z z z 

Data Set Characteristics 

Annual survey z z z z 

Pooled data from multiple annual surveys z z 

Survey is voluntary z z 

Survey is self-report z z z z 

This table provides a high-level overview of the characteristics of each data set that readers should be 

aware of in three areas: data coverage; data reliability; and survey design. Each data set offers a 

different set of strengths and limitations. We recognize the limitations to using the various available 

data sets to explore our research questions, and acknowledge these limitations in each chapter, as 

appropriate. 

NOTE: Issues with an asterisk (*) were mentioned by the Coalition on Appalachian Substance Abuse Policy (CASAP) as a 

data limitation. 
13 

Chapter Overview – The National Survey on Drug Use and Health (NSDUH) 

Overview. Chapter 2 presents the comparative Appalachian regional analyses of substance abuse, 

mental health and related treatment access among the general population. The National Survey on 

Drug Use and Health (NSDUH) provides data on drug, alcohol, and tobacco use in the civilian, noninstitutionalized population aged 12 or older in the U.S. While substance use (both alcohol and 

illicit drugs) and dependence are a key focus of the survey, NSDUH also provides self-reported 

information leading to the identification of serious psychological disorders and major depressive 

episodes as well as information about the receipt of specialty treatment for illicit drug or alcohol 

use, and mental health treatment/counseling in various settings. 

Key Research Questions. Chapter 2 explores the following key research questions: (1) What 

proportions of people report substance use, abuse, or dependence in the Appalachian region as 

compared to outside of Appalachia? (2) What proportions of people in need of addiction or mental 

health treatment report having received treatment for substance abuse or mental health problems in 

the Appalachian region as compared to outside of Appalachia? (3) Are there patterns with respect to 

substance use or abuse and access to treatment across different sub-groups, depending on 

demographics, socio-economic characteristics, or age of population (age 12 to 17 versus age 18 and 

older)? (4) Are there patterns with respect to substance use or abuse and access to treatment across 

Appalachian sub-regions and/or by Appalachian county economic development status? 

Sample. The survey is based on a random sample of households in the nation. The sample design 

includes the 50 states and the District of Columbia. The four most recent NSDUH surveys, 2002-

2005, are pooled together to study substance abuse, mental disorders, and access to treatment by 

persons in the general population in Appalachia, as compared to the rest of the U.S., and to provide 

sufficient sample sizes for sub-regional analyses. A total of 271,978 respondents were included in 

the data (91,145 adolescents aged 12-17 and 180,833 adults aged 18 or older). 

Limitations. The primary limitation of NSDUH is that it has been designed to provide national, 

and, more recently, state-level estimates on drug use. The survey was not designed to provide 

special regional estimates, and thus estimated totals, and weighted percentages to a lesser degree, 

for groupings of counties should be interpreted with caution. The NSDUH also only targets the 

civilian, non-institutionalized population aged 12 or older, potentially excluding other populations 

that may have different substance abuse patterns. 

Findings. Non-medical use of psychotherapeutics was higher among adolescents than among adults 

overall; adolescents in the Appalachian region had even higher prevalence rates than adolescents 

outside of the Appalachian region. Both geographic variation and county economic status 

differences are observed in adolescents’ non-medical use of prescription drugs – with the southern 

part of Appalachia, “distressed and at-risk,” and “transitional” counties having higher rates. The 

percentages of current or recent methamphetamine use for adults are similar between Appalachia 

and elsewhere, but the lifetime use of methamphetamine rate is lower in Appalachian than outside 

of Appalachia. For adolescents, the methamphetamine use prevalence rates are generally similar, 

although the rates in Appalachia for lifetime use and past month use are slightly higher in 

Appalachia than outside of Appalachia. Finally, those who receive substance abuse treatment in the 

Appalachian region are less likely to utilize inpatient rehabilitation than people outside of the 

Appalachian region. 
14 

Chapter Overview – Treatment Episode Data Set (TEDS) 

Overview. We use the Treatment Episode Data Set (TEDS) to examine admissions to substance 

abuse treatment. Cross-tabulations are used to examine differences in admissions to substance 

abuse treatment within the Appalachian region. Analyses are conducted across subgroups based on 

Appalachian geographic sub-regions (Northern, Central, and Southern) and the ARC-defined 

economic development level of the counties where the admissions took place. 

Research Questions. Key research questions explored include: (1) Are there regional and subregional differences in admissions to substance abuse treatment in Appalachia as compared to 

admissions to treatment outside of Appalachia? (2) Are there regional and sub-regional patterns in 

admissions to treatment across different socio-economic and demographic variables such as age, 

education, type of health insurance, etc? and (3) Are there regional and sub-regional patterns in 

admissions to treatment with respect to other variables, such as source of referral, number of prior 

treatment episodes, and primary reason for admission? 

Sample. Chapter 3 provides an overview of the pooled annual admissions to treatment facilities in 

the Appalachian region, and in other regions nationally, during the 2000 – 2004 period. TEDS is 

based on over two million admissions reported by over 10,000 facilities to the 50 States, District of 

Columbia, and Puerto Rico, over a calendar year. Among the 410 Appalachian counties, 195 

counties were in the pooled 2000-2004 TEDS data set, comprising 511,217 total admissions to 

treatment for abuse of alcohol and drugs in facilities that report to individual State administrative 

data systems. Twelve of the 13 Appalachian states were included in the data (excluding West 

Virginia). 

Limitations. There are several limitations in using TEDS to explore substance abuse treatment 

issues in Appalachian counties as compared to other counties nationally. TEDS does not capture all 

of the substance abuse treatment facilities in the U.S., and the scope of facilities included differs 

from state to state. Second, states may vary in how they define an admission; thus, the absolute 

number of admissions may not be a valid measure for comparing states. Finally, different criminal 

justice practices at the state level may affect the way clients are referred to admission. 

Findings. The central Appalachian region had the highest proportion of admissions with other 

opiates or synthetics as the primary reason for admission among Appalachian sub-regions. In 

addition, about two-thirds of admissions in Appalachia were associated with mood disorders – both 

those that were substance-related and non-substance-related. Finally, the highest prevalence of 

mood disorders occurs in “transitional” counties and in the northern Appalachian sub-region; the 

central sub-region of Appalachia has the greatest density of admissions for psychiatric problems 

(both substance-related and non-substance-related). 
15 

Chapter Overview – The Healthcare Cost and Utilization Project (HCUP) 

Overview. Chapter 4 provides an overview of substance abuse and mental disorder discharges from 

Appalachian and other community hospitals. Analyses of the encounter-level administrative data 

for inpatient hospital stays are performed using the Healthcare Cost and Utilization Project (HCUP), 

the largest collection of longitudinal hospital care data in the United States. 

Research Questions. In Chapter 4 we investigate the following key research questions: (1) Are 

there differences in substance abuse and mental disorder diagnoses among patients discharged from 

community hospitals in Appalachia, as compared to discharges from community hospitals outside 

of Appalachia? (2) Are there differences in discharges from community hospitals in Appalachia 

versus outside of Appalachia when taking county economic status into account? and (3) Do subregional differences exist across socio-economic status, health diagnoses, and other dimensions of 

hospital stays? 

Sample. This study uses HCUP’s Nationwide Inpatient Sample (NIS) collected in 2004 to examine 

substance abuse and mental disorder discharges from community hospitals. The NIS is a stratified 

probability sample of non-rehabilitation, community hospitals in the United States. All U.S. 

community hospitals in the American Hospital Association’s hospital file are included in the 

hospital universe, except short-term rehabilitation hospitals. HCUP provides data that address both 

substance abuse and mental health issues. Given the NIS’s large sample size – 8,004,571 hospital 

discharges from 1,004 U.S. community hospitals – the NIS is ideal for exploring trends nationally 

and in the Appalachian region. The NIS sampling frame is representative of all U.S hospitals and 

includes data from 37 states, including ten of the 13 Appalachian states. Pennsylvania, Alabama, 

and Mississippi are excluded. 

Limitations. The HCUP data is limited to only 37 states. In 2004, HCUP NIS data were only 

available in 10 of the 13 Appalachian states, excluding Pennsylvania, Mississippi, and Alabama. 

Missing data is a clear limitation, given that it would be ideal to make comparisons between 

Appalachian community hospitals and other community hospitals nationally based on data for all 13 

Appalachian states and the rest of the nation. Also, the NIS includes general and specialty 

hospitals (e.g., pediatric, obstetrics-gynecology, short-term rehabilitation, and oncology), but 

excludes long-term care and psychiatric hospitals. 

Findings. Findings include that patients in the Appalachian region are more likely to be admitted 

through the emergency department than patients outside of the Appalachian region. This disparity 

appears to be concentrated in “at-risk” and “transitional” counties as compared to other counties. In 

addition, over 67 percent of adult hospital stays in Appalachia were billed to the government in 

2004, with Medicare being billed for the majority of stays. Finally, the percentage of admissions in 

Appalachia for patients with principal and/or secondary MH/SA diagnoses is higher than the 

percentage outside of Appalachia. The vast majority of the hospital stays with MH/SA diagnoses 

are mental health related, and the rate is higher in Appalachia than outside of Appalachia. 
16 

Chapter Overview – The National Survey of Substance Abuse Treatment Services (N-SSATS) 

Overview. Chapter 5 examines the facility and services characteristics of the substance abuse 

treatment programs inside and outside of Appalachia. We use the National Survey of Substance 

Abuse Treatment Services (N-SSATS) collected in 2005 to obtain a snapshot of the character and 

composition of the substance abuse treatment delivery system in the United States. N-SSATS 

allows us to make comparisons across geographic areas and among different populations with 

substance abuse issues. 

Research Questions. This chapter explores the following key research questions for facilities in 

Appalachia and facilities outside of Appalachia: (1) Do substance abuse facilities in Appalachia 

offer inpatient detoxification services? (2) What are the ownership structures for the Appalachian 

treatment facilities and how do they compare to those of other facilities? (3) What is the primary 

focus of Appalachian substance abuse facilities (e.g., substance abuse services, mental health 

services, general health care services, etc.)? (4) What types of health insurance do facilities accept 

(e.g., Medicare, Medicaid, state financed insurance, private health insurance)? 

Sample. The sample analyzed in this study includes 13,367 substance abuse treatment facilities 

from which data were collected in 2005. Of all these facilities, 980 (7.3%) were from the 

Appalachian region, and 12,391 (92.7%), were from the rest of the country. 

Limitations. There are several limitations with respect to using N-SSATS to explore the 

composition and characteristics of substance abuse treatment facilities in Appalachian counties as 

compared to other counties nationally. One serious limitation is that N-SSATS does not capture 

data from all of the substance abuse treatment facilities that may be relevant to this study. A second 

limitation is that N-SSATS is a point-prevalence survey, and as such, only reflects treatment facility 

composition and status at a single point in time. Additionally, there are limitations related to the 

survey’s design and content that will be presented in more detail in the chapter. Finally, some 

financial data originally collected through the survey have been omitted from the public use file for 

confidentiality reasons. Despite these limitations, we view the N-SSATS as a limited, yet important 

data source for this study of substance abuse and mental health issues, and access to treatment 

services in Appalachia. 

Findings. In Appalachia, proportionately more treatment facilities had a primary focus of 

providing mental health services, a mix of mental health services, and general health care services 

than treatment facilities outside of Appalachia. Non-hospital residential substance abuse care is 

provided in proportionately fewer facilities in Appalachia than outside of Appalachian. Long-term 

non-hospital residential treatment is offered in proportionately fewer facilities in Appalachia than 

outside of Appalachia. Analyses also show a significantly greater acceptance of government 

financed payment sources including Medicare, Medicaid, and state financed insurance. While 

proportionately more facilities accept these payment sources, we do not know the breadth of 

coverage within the region. Similarly, proportionately more Appalachian facilities accept private 

health insurance, but the breadth of coverage is also unknown. Future studies analyzing cost and 

insurance issues within the Appalachian region could provide more specificity in terms of facility 

rationale, breadth of coverage, and service implications. 
17 

Chapter Overview – Special Analysis: Substance Abuse and Mental Health – A Comparison of 

Appalachian Coal Mining Areas to Other Areas within the Appalachian Region 

Overview. The coal mining industry has long been a vital part of the economy of Appalachia and 

remains a major industry within the region. Popular media has cited an increase in drug use in coal 

mining areas. This chapter is based on statistical analyses of data systematically collected by two 

agencies within the U.S. Department of Health and Human Services – the Substance Abuse and 

Mental Health Services Administration (SAMHSA) and the Agency for Healthcare Research and 

Quality (AHRQ). We focus exclusively on the Appalachian region with the objective of comparing 

coal mining areas and other areas with respect to substance abuse and mental health status and 

access to the treatment services. 

Research Question. The key research question in Chapter 6 is: Do coal mining areas within 

Appalachia differ from other Appalachian areas in terms of the composition of patients admitted to 

specialty treatment services or discharged from community hospitals?

Sample. We merged the coal mining area coverage data from the National Coal Resources Data 

System (NCRDS) with the list of the Appalachian counties described by the Appalachian Region 

Commission (ARC) as of 2006. Among the 410 Appalachian counties, 176 counties were identified 

as being located in the coal mining area. The first analytic sample for this chapter includes all adult 

discharges from community hospitals within the Appalachian Region from the Healthcare Cost and 

Utilization Project (HCUP). There are a total of 167,957 admissions included in the analytic sample, 

including 76,083 (45.3%) from 25 coal mining counties and 91,874 (54.7%) from 20 other counties 

in the Appalachian region. The second analytic sample for this chapter includes all admissions to 

substance abuse treatment services in the Appalachian Region from the Treatment Episode Data Set 

(TEDS) from 2000-2004. Among the 195 counties covered by the Treatment Episode Dataset 

(TEDS) in 2000-2004, 86 counties were located in the coal mining area. Overall there were 211,380 

admissions from the coal mining area and 299,837 admissions from other areas in the Appalachian 

region. 

Limitations. Our coal mining area was defined as the area with the subsurface filled with coal 

instead of the actual coal-producing counties. The results should also be interpreted with caution 

because the units of analyses were admissions to treatment or hospital discharges made by people 

living in this area rather than actual coal miners.

Findings. The study in this chapter demonstrates that coal mining areas within the Appalachian 

region demonstrate higher rates of both heroin use and other opiates or synthetics use as the 

primary, secondary or tertiary reason for treatment, as compared to other areas within the region. 

Furthermore, while studies in previous chapters show that rates of both heroin and other opiates and 

synthetics as primary reasons for coming to treatment increased over the 2000-2004 period, the pace 

of these rate increases is even faster in coal mining areas than in other areas within the Appalachian 

region. Other illicit drug use and non-medical use of prescription drugs are also cited more as the 

primary, secondary or tertiary reasons for treatment in coal mining areas than in other areas. 
18 

Chapter Overview – Case Study of Disparities in Mental Health Status and Substance Abuse 

Prevalence in the Appalachian Region and Access to Mental Health and Substance Abuse 

Treatment Services 

Overview. To supplement the quantitative findings presented in the previous chapters, NORC and 

East Tennessee State University conducted case studies using a “Socioeconomic Twins” 

methodology. The purpose of the study was to determine the extent of local assessments of the 

mental health and substance abuse situation as well as the perceived validity of nationally available 

quantitative data to serve as an index of the severity of local substance abuse prevalence, mental 

health status and access to treatment services. 

Research Questions. Research questions for Chapter 7 include: Do community perceptions of 

mental health/substance abuse (MH/SA) issues match available data? What additional data sources 

are used at the community level? What has been the community’s response to substance abuse and 

mental health concerns? And, are there potential explanations for variance in community MH/SA 

indicators?

Sample. Statistical procedures were performed and matrices developed to calculate sociodemographic similarity/dissimilarity and MH/SA similarity/dissimilarity for all possible pairs of 

Appalachian counties within each state. Then, these “distance matrices” were transformed into 

pairs which were subsequently ranked and sorted based on the distance values. The twinned county 

sites were selected based upon the statistically twinned rankings produced by NORC and by 

consensus among ETSU, CASAP, and NORC, and modified by local/regional knowledge of local 

situations. Case studies were conducted with the six counties in Kentucky, Virginia, and West 

Virginia respectively. 

Limitations. This study employed a case study methodology, which has inherent limitations. 

While we conducted discussions with a variety of stakeholders in each of the case study 

communities, these findings are not meant to provide a comprehensive understanding of every 

substance abuse and mental health issue and perception in every community

Findings. The case studies revealed that Appalachian communities have a sense of regional 

awareness of mental health and substance abuse issues and express willingness to share facilities 

and solutions. Local data sets are essential to understanding the depth of the substance use and 

mental health issues faced by residents at the county level, though better coordinated data 

collection, documentation and analysis are needed to access resources at state and federal levels. 

Barriers to the use of treatment services include social stigma for those who seek care, lack of 

transportation, non-recognition of the root causes of substance use behaviors, multi-generational 

patterns of substance abuse behaviors, and erosion of the power of family and community networks 

to assist in personal coping skills. Community leaders want better conditions for all citizens of their 

counties regardless of social class. The well-being of youth is of paramount importance to rural 

counties evidenced by the emphasis on prevention and awareness of substance abuse in schools and 

youth-programs settings. 
19 

CHAPTER 2: Substance Use, Mental Disorders, and Access to 

Treatment Services in Household Surveys, 2002 – 2005 

2.1 Introduction 

Drug misuse and abuse, and mental health disorders are major health and social issues in the United 

States. In Chapter 2, we provide our findings related to substance abuse, mental health problems, 

and access to treatment services among the general population in the Appalachian region, as 

compared to other parts of the United States. Where possible, findings are also presented by 

Appalachian sub-region and county economic development status. Data are from the National 

Survey on Drug Use and Health (NSDUH), the largest nationwide survey of the U.S. civilian noninstitutionalized population. While substance use (both alcohol and illicit drugs) and dependence 

are a key focus of the survey, NSDUH also explores the prevalence and treatment of serious 

psychological disorders and major depressive episodes. NSDUH also provides data about health 

and emotional problems associated with substance use. Finally, NSDUH provides information 

about the receipt of specialty treatment for illicit drug or alcohol use, and mental health 

treatment/counseling in various settings. 

This chapter explores the following key research questions: 

What proportions of people report substance use, abuse, or dependence in the Appalachian 

region as compared to outside of Appalachia? 

What proportions of people in need of addiction or mental health treatment report having 

received treatment for substance abuse or mental health problems in the Appalachian region 

as compared to outside of Appalachia? 

Are there patterns with respect to substance use or abuse and access to treatment across 

different sub-groups, depending on demographics, socio-economic characteristics, or age of 

population (age 12 to 17 versus age 18 and older)? 

Are there patterns with respect to substance use or abuse and access to treatment across 

Appalachian sub-regions and/or by Appalachian county economic development status? 

An overview of data sources is presented in Section 2.2, including a description of the targeted 

population. General limitations and major data gaps specifically related to exploring substance use 

and mental health problems in the Appalachian region are also included in this section. Section 2.3 

discusses the methods, including the analytic sample, measurement, and statistical methods. 

Section 2.4 contains the results of the analysis. Finally, Section 2.5 provides a discussion of key 

findings. 

2.2 Data 

2.2.1 Overview 

The data used for this chapter is from the National Survey on Drug Use and Health (NSDUH). 

NSDUH is the largest nationwide survey of the U.S. civilian non-institutionalized population. 

Excluded from the sample are individuals with no household address (e.g., homeless and/or 

transient persons not in shelters), active duty military personnel, and residents of jails and 
20 

hospitals.7

 Initiated in 1971 and authorized by the Public Health Service Act to collect data on 

substance abuse trends and patterns, NSDUH is the Federal government’s primary source of 

national data on substance abuse issues related to alcohol, tobacco, and other illicit substances. 

NSDUH is funded and overseen by the Substance Abuse and Mental Health Services 

Administration (SAMHSA) to collect data about the status of the nation’s drug usage. 

The survey is based on a random sample of households in the nation. Households that have been 

randomly selected are visited by a NSDUH field representative. The sample design includes the 50 

states and the District of Columbia. States designated as large sample states had sample sizes that 

ranged from 3,562 to 3,699 people.15 The large sample states – California, Florida, Illinois, 

Michigan, New York, Ohio, Pennsylvania, and Texas – were large enough to support direct state 

estimates (includes three Appalachian states). The other 42 states, including 10 of the 13 

Appalachian states, were designated as small sample states; sample sizes for small sample states 

ranged from 840 to 978 people. One or two residents aged 12 or older from each household may be 

asked to complete an interview for the survey. Each individual selected to participate in the survey 

represents about 3,000 other residents in the United States.16 

To provide a sufficient sample for analysis, we used pooled data from the four most recent National 

Surveys on Drug Use and Health (NSDUH), 2002-2005. In 2002-2005, NSDUH collected data 

from approximately 272,000 respondents aged 12 or older. A stratified sample was used to obtain 

sufficient representation from all 50 States and the District of Columbia. The survey was planned 

and managed by SAMHSA's Office of Applied Studies (OAS). In each year during 2002-2005, the 

nationwide surveys included close to 70,000 individuals. 

2.2.2 Limitations of the NSDUH 

The primary limitation of NSDUH is that it has been designed to provide national, and, more 

recently, state-level estimates on drug use. The survey was not designed to provide special regional 

estimates. As the Appalachian region is not part of the primary sampling unit or the sampling 

segment, the weights used for the national and state estimates are not ideal for a study of the 

Appalachian region. In addition, the NSDUH weighting process does not post-stratify at the county 

level; post-stratification of results involves weighting the data after collection when certain stratum 

may be over or under-represented. As a result, the estimated totals, and weighted percentages to a 

lesser degree, for groupings of counties – such as the 410 counties in the Appalachia region – 

should be interpreted with caution. 

Another limitation of using the NSDUH survey for this study is that it only targets the civilian, noninstitutionalized population aged 12 or older, potentially excluding other populations that may have 

different substance abuse patterns.17 For example, research shows that runaways have higher rates 

of drug abuse than their peers that live at home.18,19 Also, the NSDUH survey does not include 

people who are not in a homeless shelter on the survey date, potentially missing this population. 

Additionally, NSDUH excludes active military personnel and persons in institutional group quarters 

(e.g., prisons, long-term hospitals, residential drug treatment centers, etc.). 

 

7

 It is important to note that because this sample frame, persons who were residing in long-term psychiatric or other 

institutions at the time of interview were excluded from the NSDUH sample. 
21 

Third, NSDUH relies on people self-reporting their behavior with respect to drug use. Thus, data 

may be biased by interviewees either under-reporting or over-reporting their drug use. To mitigate 

this problem, NSDUH’s estimates are determined by interviewees’ responses to multiple questions 

about substance abuse. However, self-reporting may bias response tendencies, given that 

inconsistent responses for drug use questions are common in the survey.20

Finally, although data from four consecutive annual surveys were pooled to conduct this study, no 

county-level estimations are produced because of the small sample sizes and related confidentiality 

concerns. This also remains a concern when conducting state level analyses, as noted in the 

literature.21 

2.3 Methods 

2.3.1 Analytic Sample 

The data used for this study are the pooled cross-sectional annual National Surveys on Drug Use 

and Health (NSDUH) for the 2002-2005 period. As shown in Table 2.1, a total of 271,978 

respondents were included in the pooled data, including 91,145 adolescents aged 12-17 and 180,833 

adults aged 18 or older. 

About 8.13% (n=22,109) of the total respondents were from the 410-county Appalachian region 

when the surveys were conducted during the 2002-2005 period. Of the 22,109 respondents from the 

Appalachian region, 7,336 were adolescents age 12 -17, and 14,833 were adults age 18 or older. 

Table 2.1 Sample Sizes of the Pooled National Surveys on Drug Use and Health, by Age 

Group, Survey Year, and Appalachian Region Status 

Age Group 

Year of Data Collection All 

 

2002-2005 

Region of Data Collection 

2002 2003 2004 2005 

Appalachian 

Region* 

Non-Appalachian 

Region 

12-17 23,645 22,665 22,301 22,534 91,145 7,336 83,809 

18 or older 44,481 45,119 45,459 45,774 180,833 14,833 166,000 

Total 68,126 67,784 67,760 68,308 271,978 22,109 249,809 

Note: The Appalachian Region is comprised of the 410 counties located in 13 states -- Alabama, Georgia, 

Kentucky, Maryland, Mississippi, New York, North Carolina, Ohio, Pennsylvania, South Carolina, 

Tennessee, Virginia, and West Virginia. The only state located fully within the Appalachian region is West 

Virginia. 

2.3.2 Measures 

Tables and maps present population prevalence measures for the use of illicit drugs, alcohol, and 

tobacco products, as well as measures that indicate mental health issues and access to treatment 

services. Tables show estimates of drug use prevalence by lifetime (e.g., ever used), past year, and 

past month use. Prevalence measures showing the number of substance users are included in tables 

in Appendix C. Measures are analyzed across socio-demographic characteristics, including age, 

race/ethnicity, education, employment status, and health insurance status. 
22 

Substance Use 

Substances studied here include alcohol and illicit drugs, such as marijuana, cocaine, heroin, 

methamphetamine, and non-medical use of prescription-type drugs. Respondents are classified as 

dependent on or abusing specific substances based on criteria specified in the Diagnostic and 

Statistical Manual of Mental Disorders, 4th edition (DSM-IV) (American Psychiatric Association, 

1994). The questions on dependence ask about health and emotional problems associated with 

substance use, unsuccessful attempts to reduce use, tolerance, withdrawal, and other symptoms 

related to substance use. The questions on abuse ask about problems at work, home, and school; 

problems with family and friends; physical danger; and trouble with the law due to substance use. 

The survey also asks about treatment for substance use problems. Specialty treatment is defined as 

treatment received at drug or alcohol rehabilitation facilities, hospitals (inpatient only), or mental 

health centers. 

Mental Disorders 

Mental disorders studied here include the prevalence and treatment of serious psychological distress 

(SPD) and major depressive episodes (MDE). Past year SPD is an overall indicator of nonspecific 

psychological distress that is constructed from the K6 scale administered to adults aged 19 or older 

in the NSDUH. The K6 scale consists of six questions that gather information on how frequently a 

respondent experienced symptoms of psychological distress during the one month in the past year 

when he or she was at his or her worst emotionally. Responses to these six questions are combined 

to produce a score ranging from 0 to 24, where a score of 13 or greater is considered SPD.8 This 

cutoff is based on research suggesting that scores above this threshold provides an indicator of 

serious mental illness. MDE is defined as a period of at least two weeks when a person experienced 

a depressed mood or loss of interest or pleasure in daily activities and had symptoms that met the 

criteria for major depressive disorder as described in the 4th edition of the Diagnostic and Statistical 

Manual of Mental Disorders (DSM-IV) (American Psychiatric Association, 1994)9

. MDE, as 

defined here, can be caused by mental illness, bereavement, or substance use disorders. 

Access to Treatment 

Access to treatment measures studied here are past year receipt of specialty treatment for illicit drug 

or alcohol use, and mental health treatment/counseling in various settings. Received Treatment at a 

Specialty Facility refers to treatment received at a hospital (inpatient), alcohol or drug rehabilitation 

facility (inpatient or outpatient), or mental health center in order to reduce or stop alcohol or drug 

 

8

 The Serious Psychological Distress (SPD) measure reflects only 2004 and 2005 (unadjusted, Sample B) data, as 2002 

and 2003 (long form) SPD measures are not comparable to 2005 (short form) SPD measures. This information is 

footnoted in the tables. Similarly, the Major Depressive Episode measure reflects only 2004 and 2005 data, as this 

measure was not available prior to 2004. 

9

 Although there is significant overlap between those meeting the criteria of SPD and MDE, there are important 

distinctions between the two. Meeting the criteria for SPD indicates that the respondent exhibited a high level of distress 

due to any type of mental problem, which may include general symptoms related to phobia, anxiety, or depression. 

However, meeting the criteria for MDE indicates that the respondent had the specific physical and emotional symptom 

profile indicative of major depression. 
23 

use, or for medical problems associated with alcohol use. It excludes treatment at an emergency 

room, private doctor’s office, self-help groups, prison or jail, or hospital as an outpatient. 

Respondents were classified as Needing Treatment for an Illicit Drug or Alcohol Problem if they 

met at least one of three criteria during the past year: (1) dependent on illicit drugs or alcohol; 

(2) abuse of illicit drugs or alcohol; or (3) received treatment for an illicit drug or alcohol problem 

at a specialty facility (i.e., drug and alcohol rehabilitation facilities [inpatient or outpatient], 

hospitals [inpatient only], and mental health centers). Illicit drugs include marijuana/hashish, 

cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics 

used nonmedically. 

An individual defined as Needing But Not Receiving Treatment refers to respondents who are 

classified as needing treatment, but not receiving treatment for a problem at a specialty facility (e.g., 

drug and alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and 

mental health centers). 

An individual defined as Felt Need for Treatment includes persons who did not receive but felt they 

needed treatment, as well as persons who received treatment at a location other than a specialty 

facility but felt they needed additional treatment. 

2.3.3 Statistical Methods 

Two major types of analyses were conducted. First, analyses were conducted to identify disparities 

on substance abuse and mental disorder measures: (a) between Appalachia and non-Appalachia; (b) 

within Appalachian sub-regions (northern, central, and southern); and (c) across Appalachian 

Regional Commission (ARC) defined economic development level domains in the Appalachian 

region (distressed, at-risk, transitional, competitive, attainment). Second, analyses were conducted 

to identify patterns of more detailed geographic variations across counties. For the first type of 

analyses, we combine the 2002-2005 NSDUH data and estimate across the regional, sub-regional, 

and economic development domain groups. Analytic results from these analyses are presented in a 

series of analytic tables and bar charts, along with descriptions of the findings. For the second type 

of analyses, we use the 2002-2004 combined data and present estimates of the prevalence of 

substance use or mental health problems using regional maps. 

Type 1 Analysis 

Regional estimates, along with the associated variance components, were calculated by SAMHSA’s 

survey contractor using the SUDAAN software based on a request from NORC to SAMHSA’s 

Office of Applied Studies (OAS). SUDAAN was designed for the statistical analysis of data 

collected using stratified, multistage cluster sampling designs, as well as other observational and 

experimental studies involving repeated measures or studies subject to cluster correlation effects 

(RTI International, 2004). Although weights are used in the analyses, it is important to note that 

they were neither post-stratified at the county-level nor by Appalachian region. As such, drug use 

estimates could be biased. 

The standard NSDUH suppression rules have been applied to the analytic tables in this 

chapter. Additionally, the NSDUH weighting process does not post-stratify at the county level; thus, 
24 

these estimated totals (and weighted percentages, to a lesser degree) should be interpreted with 

caution. 

An adaptive analytic approach was used in the type 1 analyses. Adaptive analysis, a term used here 

that is similar to the concept of adaptive sampling technique in statistics, involves conducting 

appropriate analyses based on the analytic results at the prior stage. In this study, first, the numbers 

of respondents in each of the counties included in NSDUH were obtained and examined. Second, a 

set of demographics and substance use and mental disorder measures are estimated. Finally, 

selected measures on need for treatment and access to treatment are estimated. Note that in the first 

step, our analysis of county-level sample sizes indicated that, even with the combined four year 

data, response numbers are too small to produce useful county-level estimations of substance use 

and mental disorder prevalence. 

Type 2 Analysis 

SAMHSA, in collaboration with State treatment representatives, developed substate areas for each 

State in late 2005 and early 2006. The purpose of developing these substate areas was to provide 

substate-level estimates showing the geographic distribution of substance use prevalence for areas 

that States would find useful for treatment planning purposes.10 The final substate area boundaries 

were based on the recommendations of each State's staff, assuming the NSDUH sample sizes 

provided adequate precision. Most States defined areas in terms of counties or groups of counties. 

We present estimated values for all selected substance use and serious psychological distress 

measures using the NSDUH defined sub-state area as the unit of analysis. As such, all counties 

within those NSDUH sub-state areas are applied the same estimate as generated by SAMHSA’s 

Office of Applied Studies (OAS, 200622). These estimates are then mapped showing the full 

NSDUH sub-state areas, the ARC boundary, and state and county boundaries within Appalachia, to 

assist in pattern detection. Note that results from the type 2 analyses are only represented by maps 

shown in this chapter. All tables and their descriptions come from type 1 analysis. 

2.4 Results 

Demographic Characteristics of the NSDUH Population 

Adolescents 

Non-Hispanic whites accounted for more than four-fifths of the adolescents in Appalachia 

but less than two-thirds of the adolescents outside of Appalachia. Overall, adolescent 

minorities in Appalachia accounted for a larger percentage of the adolescent population than 

adult minorities accounted for in the adult population. 

 

10 These areas were defined by officials from each state, typically based on the substance abuse treatment planning areas 

specified by states in their applications for a SAPT Block Grant administered by SAMHSA. There is extensive variation 

in treatment planning areas across states. In some, the planning areas are used more for administrative purposes rather 

than for planning purposes. In a number of states, the designated planning areas changed frequently in recent years. 

Because the estimation method required a minimum NSDUH sample size of 200 to provide adequate precision, 

planning areas with insufficient sample size were collapsed with adjacent areas until the minimum was obtained. 
25 

Most of the adolescents had private insurance (68%) in both Appalachia and outside of 

Appalachia. Proportionately, more adolescents in Appalachia had Medicaid/CHIP (26.8%) 

than adolescents outside of Appalachia (23.5%). 

Adults 

On average, 88.4% of adults in the Appalachian region and 69% of adults outside the 

Appalachian region are non-Hispanic/non-Latino whites. Non-Hispanic blacks account for 

7.4% of the Appalachian population, and 11.5% of the population outside of Appalachia. 

Non-Hispanic Asians, American Indians, and Pacific Islanders accounted for 2.3% of the 

Appalachian population and 6.2 percent of the population outside the Appalachian region. 

Overall, only 2% of Appalachian residents are of Hispanic origin, while 13.3% of the 

residents outside of the Appalachian region are of Hispanic origin. 

The educational backgrounds of adults were quite different between the Appalachian region 

and outside of Appalachia. Most of the adult residents in the Appalachian region (58.8%) 

had a high school education or less, while most of the residents outside the Appalachian 

region (51.9%) had attended some college or were college graduates. 

About 51% of adult residents in Appalachia and 56% of adult residents outside of 

Appalachia had full-time jobs. Proportions of adults having private health insurance were 

similar between Appalachian and non-Appalachian regions (71.6% and 71.4% respectively), 

although more Appalachian adults received Medicare than other adults (21.6% vs. 17.6%). 

Substance Use 

Marijuana Use 

The average of marijuana use was lower for adults in Appalachia than outside of Appalachia 

regardless of length of use – lifetime use (38.2% vs. 43.2%); past year use (8.4% vs. 10.3%); 

and past month use (4.9% vs. 6.8%). 

The average of marijuana use among adolescents was only slightly lower in Appalachia than 

outside of Appalachia (14.4% vs. 14.7% for past year use; 7.0% vs. 7.7% for past month 

use). 

Cocaine Use 

Adult residents in Appalachia had lower rates of cocaine use as compared to adult residents 

outside of Appalachia, regardless of length of use – 11.7% vs. 16.0% for lifetime use; 2.2% 

vs. 2.5% for past year use; 0.8% vs. 1.0% for past month use. 

The percentages of adolescents who had ever used cocaine in their lifetime were the same 

(2.5%) inside of Appalachia and outside of Appalachia. 
26 

Methamphetamine Use 

Proportionately, fewer adults used methamphetamine in Appalachia than outside of 

Appalachia (lifetime: 4.0% vs. 5.4%; past year: 0.4% vs. 0.6%). The current use rates, 

however, were the same (0.2%). 

The percentages of having ever used methamphetamine by adolescents were 1.4% in 

Appalachia and 1.3% outside of Appalachia. 

For adults, the southern Appalachian sub-region had a higher current methamphetamine use 

rate (0.3%) than both the northern and central sub-regions (0.1%). 

For adolescents, both the central (0.4%) and southern (0.5%) sub-regions had higher current 

methamphetamine use rates than northern sub-region (0.1%). 

To assure an adequate sample size, results were compared across county economic 

development status using merged categories: “distressed/at-risk;” “transitional;” and 

“competitive/attainment.” For adults, the highest prevalence rate for current 

methamphetamine use was in the “competitive/attainment” counties (0.3%); for adolescents, 

the highest prevalence rate for current methamphetamine use was in the “distressed/at-risk” 

counties (0.6%). 

Alcohol Use 

Proportionately fewer Appalachian adults used alcohol in the past year compared to adults 

elsewhere (61.0% vs. 70.2%). Additionally, 20.6% of Appalachian adults were binge 

alcohol users in the past year as compared to 24.5% of non-Appalachia adults. In addition, 

6.8% of Appalachian adults were heavy alcohol users in the past year compared to 7.3% of 

non-Appalachian adults. 

The reporting of heavy alcohol use by adolescents was higher inside Appalachia (2.9%) than 

outside of Appalachia (2.5%). 

Cigarette Use 

Proportionately more adults used cigarettes in Appalachia than outside of Appalachia 

(lifetime use: 75.8% vs. 72.0%; past year use: 34.5% vs. 30.4%; past-month use: 30.9% vs. 

26.5%). 

 

Similarly, proportionately more adolescents used cigarettes in Appalachia than outside of 

Appalachia (lifetime use: 36.8% vs. 29.5%; past year use: 23.8% vs. 18.3%; past-month use: 

16.3% vs. 11.6%).

Non-Medical Use of Psychotherapeutics 

Among adults, the prevalence of the non-medical use of psychotherapeutics was slightly 

lower in the Appalachian region (5.6%) than outside of the Appalachian region (5.9%). 
27 

Among adolescents, however, the prevalence of the non-medical use of psychotherapeutics 

was higher in the Appalachian region (10.6%) than outside of the Appalachian region 

(8.7%). 

Alcohol and Drug Dependence or Abuse 

Proportionately, fewer adults in the Appalachian region had dependence or abuse problems 

as compared to adults outside of the Appalachian region: illicit drug dependence or abuse 

(2.5% vs. 2.7%), alcohol dependence or abuse (6.4% vs. 8.0%), both illicit drug and alcohol 

dependence or abuse (1.0% vs. 1.3%), and illicit drug or alcohol dependence or abuse (7.9% 

vs. 9.4%). 

Access to Treatment

Access to Alcohol Treatment 

During 2002-2005, the estimated percentage of persons age 18 or older needing but not 

receiving alcohol treatment in the Appalachian region was 6.1 percent; the estimated 

percentage of persons age 18 or older needing but not receiving alcohol treatment outside of 

the Appalachian region was 7.6 percent. 

During 2002-2005, the estimated percentage of persons age 12-17 needing but not receiving 

alcohol treatment in the Appalachian region was 5.6 percent; the estimated percentage of 

persons age 12-17 needing but not receiving alcohol treatment outside of the Appalachian 

region was 5.5 percent. 

Access to Drug Treatment 

During 2002-2005, the estimated percentage of persons age 18 or older needing but not 

receiving drug treatment in the Appalachian region was 2.2 percent; the estimated 

percentage of persons age 18 or older needing but not receiving drug treatment outside of 

the Appalachian region was 2.4 percent. 

During 2002-2005, the estimated percentage of persons age 12-17 needing but not receiving 

drug treatment in both the Appalachian region and outside of the Appalachian region was 

4.8 percent. 

Locations Where Substance Abuse Treatment Was Received 

Among persons who received substance abuse treatment at a specialty facility, the most 

frequently reported locations are outpatient rehabilitation facilities (68%) for both the 

Appalachian region and outside of the region. 

Among persons who received treatment at a specialty facility, the percentage being treated 

at inpatient rehabilitation facilities was 37% in the Appalachian region and 45% outside of 

the Appalachian region. 
28 

Mental Health 

Mental Health Problems 

Proportionately more adults in the Appalachian region (13.5%) encountered a serious 

psychological distress problem than adults outside of Appalachia (11.6%). 

Proportionately more adults in the Appalachian region (8.2%) had a major depressive 

episode in the past year than adults outside of Appalachia (7.6%). 

Access to Mental Health Treatment / Counseling 

Receiving mental health treatment. In general, adults in the Appalachian region with mental 

health problems reported a somewhat greater likelihood of having received outpatient 

mental health treatment or counseling in the past year (13.6%) as compared to adults outside 

the Appalachian region (12.9%). This was seen in both the receipt of outpatient counseling 

services (7.3% vs. 7.1%) and prescription medication services (12.0% vs. 10.5%). The 

percentage of adults with mental health problems having ever received inpatient mental 

health treatment was the same in both the Appalachian region and outside of Appalachia. 

Reasons for not receiving mental health treatment / counseling. Cost or insurance barriers 

were the primary self-reported reason why people did not receive mental health treatment or 

counseling. The percentage of persons reporting these barriers was slightly lower in the 

Appalachian region (44%) than outside of the region (48%). The second most frequently 

cited reason for not receiving mental health treatment or counseling was that people did not 

feel that it was needed and, rather, believed that they could handle the problem without 

treatment – proportionately more respondents in the Appalachian region (37%) than outside 

of the Appalachian region (33%) stated this reason. The third mostly reported reason for not 

receiving mental health treatment or counseling was stigma. The percentage of people 

reporting stigma as a reason for not receiving treatment/counseling was 28% in the 

Appalachian region, compared to 22% outside of the Appalachian region. 
29 

2.4.1 Tables 

Table 2.2 Demographic Characteristics and Health Insurance among Persons Aged 12 or Older, by Age Appalachian Region Status: Percentages, Annual Averages Based on 2002-2005 

Demographic Characteristic/ Health Insurance 

AGE GROUP 

12-17 18 or Olde

Appalachian Region1 Outside Appalachia Appalachian Region1 

HISPANIC ORIGIN AND RACE

 Not Hispanic or Latino 97.4 82.3 98.0  White 84.2 60.0 88.4  Black or African American 11.3 15.3 7.4  Other2 1.8 7.0 2.3  Hispanic or Latino 2.6 17.7 2.0 EDUCATION < High School N/A N/A 20.4  High School Graduate N/A N/A 38.4  Some College N/A N/A 22.8  College Graduate N/A N/A 18.4 CURRENT EMPLOYMENT Full-Time N/A N/A 51.1  Part-Time N/A N/A 11.9  Unemployed N/A N/A 3.4  Other3 N/A N/A 33.6 HEALTH INSURANCE  Private 67.6 68.0 71.6  Medicare 0.8 0.9 21.9  Medicaid/CHIP4 26.8 23.5 9.0 

*Low precision; no estimate reported. N/A: Not applicable. 1Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. 2 Includes respondents reporting American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, Asian, and Two or More Races.

3 The Other Employment category includes retired persons, disabled persons, homemakers, students, or other persons not in the labor force. 

4 CHIP is the Children's Health Insurance Program. Individuals aged 19 or younger are eligible for this plan. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
30 

Table 2.3 Lifetime, Past Year, and Past Month Substance Use among Persons Aged 12 or Older, by Substand Appalachian Region Status: Percentages, Annual Averages Based on 2002-2005 

Substance

AGE GROUP

12-17 18 or Old

Appalachian Region1 Outside Appalachia Appalachian Region1 

MARIJUANA USE Lifetime 19.0 19.1 38.2  Past Year 14.4 14.7 8.4  Past Month 7.0 7.7 4.9 COCAINE USE Lifetime 2.5 2.5 11.7  Past Year 1.9 1.8 2.2  Past Month 0.6 0.6 0.8 METHAMPHETAMINE USE Lifetime 1.4 1.3 4.0  Past Year 0.7 0.7 0.4  Past Month 0.3 0.2 0.2 ALCOHOL USE  Past Year 33.8 34.0 61.0  Binge Alcohol Use2 10.5 10.6 20.6  Heavy Alcohol Use2 2.9 2.5 6.8 CIGARETTE USE  Lifetime 36.8 29.5 75.8  Past Year 23.8 18.3 34.5  Past Month 16.3 11.6 30.9 PAST YEAR NONMEDICAL USE OF PSYCHOTHERAPEUTICS3

10.6 8.7 5.6 

*Low precision; no estimate reported. 1 Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. 2 Binge Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) on 

days. Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion on each of 5 or more days in the past 30 days; all heavy alco

alcohol users. 

3 Nonmedical use of prescription-type psychotherapeutics includes the nonmedical use of pain relievers, tranquilizers, stimulants, or sedatives and does 

counter drugs. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
31 

Table 2.4 Substance Dependence or Abuse, Mental Health Measures, and Receipt of Substance Use TreYear among Persons Aged 12 or Older, by Age Group and Appalachian Region Status: Percentages, AnnBased on 2002-2005 

Dependence or Abuse/Mental Health/Receipt of Treatment AGE GROUP 12-17 18 

Appalachian 

Region1 

Outside 

Appalachia 

Appalachian 

Region1 

DEPENDENCE OR ABUSE2  Illicit Drugs3 5.2 5.2 2.5  Alcohol 5.9 5.8 6.4  Both Illicit Drugs and Alcohol3 2.5 2.3 1.0 

Illicit Drugs or Alcohol3 8.6 8.7 7.9 

PAST YEAR SERIOUS PSYCHOLOGICAL DISTRESS4 N/A N/A 13.5 PAST YEAR MAJOR DEPRESSIVE EPISODE5 8.8 8.9 8.2 PAST YEAR RECEIPT OF SPECIALTY TREATMENT FOR ILLICIT DRUG OR ALCOHOL USE3,6 

0.9 0.7 0.9 

MENTAL HEALTH TREATMENT/COUNSELING7 N/A N/A 13.6  Inpatient N/A N/A 0.9  Outpatient N/A N/A 7.3  Prescription Medication N/A N/A 12.0 

*Low precision; no estimate reported. N/A: Not applicable. 1 Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. 2 Dependence or abuse is based on definitions found in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). 3 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used non-medically

4 Serious Psychological Distress (SPD) is defined as having a score of 13 or higher on the K6 scale. Due to questionnaire changes, these combined 2004 and 200

comparable with 2004 and earlier estimates published in prior NSDUH reports. See Section B.4.4 in Appendix C of the Results from the 2005 National Survey National Findings. Estimates are based on combined 2004-2005 data. 5 Major Depressive Episode (MDE) is defined as a period of at least 2 weeks when a person experienced a depressed mood or loss of interest or pleasure in daily 

of the symptoms for depression as described in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). Estimates are based on 

6 Received Substance Use Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or outpatient), or 

to reduce or stop illicit drug or alcohol use, or for medical problems associated with illicit drug or alcohol use. Estimates include persons who received treatmen

or alcohol, as well as persons who received treatment but did not specify for what substance(s). 7 Mental Health Treatment/Counseling is defined as having received inpatient care or outpatient care or having used prescription medication for problems with em

health. Respondents were not to include treatment for drug or alcohol use. Respondents with unknown treatment/counseling information were excluded. Estima

responses to items in the Adult Mental Health Service Utilization module. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
32 

Table 2.5 Demographic Characteristics and Health Insurance among Persons Aged 12 or Older Residing Region, by Age Group and Appalachian Sub-Region: Percentages, Annual Averages Based on 2002-2005 

Demographic Characteristic/Health Insurance 

AGE GROUP 

12-17 18 or Olde

Northern Central Southern Northern Central 

HISPANIC ORIGIN AND RACE Not Hispanic or Latino 97.9 98.0 96.8 98.9 98.7  White 91.1 94.7 75.2 93.7 95.5  Black or African American 4.5 1.1 20.2 3.4 1.7  Other1 2.3 2.1 1.4 1.8 1.5  Hispanic or Latino 2.1 2.0 3.2 1.1 1.3 EDUCATION < High School N/A N/A N/A 16.3 30.7  High School Graduate N/A N/A N/A 42.1 40.0  Some College N/A N/A N/A 22.7 18.9  College Graduate N/A N/A N/A 18.9 10.4 CURRENT EMPLOYMENT Full-Time N/A N/A N/A 49.1 43.1  Part-Time N/A N/A N/A 12.8 9.0  Unemployed N/A N/A N/A 3.6 3.8  Other2 N/A N/A N/A 34.4 44.1 HEALTH INSURANCE  Private 72.3 50.1 66.3 74.0 63.8  Medicare 0.5 0.6 1.1 22.3 27.8  Medicaid/CHIP3 22.4 42.2 28.0 8.1 14.4 

*Low precision; no estimate reported. 

NOTE: Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. N/A: Not applicable. 1 Includes respondents reporting American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, Asian, and Two or More Races.

2 The Other Employment category includes retired persons, disabled persons, homemakers, students, or other persons not in the labor force. 

3 CHIP is the Children's Health Insurance Program. Individuals aged 19 or younger are eligible for this plan. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
33 

Table 2.6 Lifetime, Past Year, and Past Month Substance Use among Persons Aged 12 or Older Residin

Region, by Substance, Age Group, and Appalachian Sub-Region: Percentages, Annual Averages Based on 

Substance AGE GROUP

12-17 18 or Old

Northern Central Southern Northern Centr

MARIJUANA USE Lifetime 19.2 17.5 18.9 38.9 33.0  Past Year 15.1 12.5 14.1 9.0 6.6  Past Month 7.5 4.3 7.0 5.5 3.7 COCAINE USE Lifetime 2.2 2.3 2.9 11.8 7.7  Past Year 1.7 1.9 2.2 2.3 1.6  Past Month 0.6 0.5 0.5 0.8 0.4 METHAMPHETAMINE USE Lifetime 1.2 1.7 1.5 4.0 2.1  Past Year 0.5 0.6 0.9 0.3 0.3  Past Month 0.1 0.4 0.5 0.1 0.1 ALCOHOL USE  Past Year 36.7 28.8 31.8 69.3 43.5  Binge Alcohol Use1 12.3 8.1 9.3 24.6 14.0  Heavy Alcohol Use1 3.3 2.4 2.5 8.2 4.1 CIGARETTE USE  Lifetime 35.6 42.0 36.9 76.9 75.3  Past Year 23.8 24.3 23.7 35.2 37.0  Past Month 16.5 17.2 15.9 31.5 33.2 PAST YEAR NONMEDICAL USE OF PSYCHOTHERAPEUTICS2 9.1 10.4 12.1 5.0 6.4 

*Low precision; no estimate reported. NOTE: Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. 1Binge Alcohol Use is defined as drinking five or m(i.e., at the same time or within a couple of hours of each other) on at least 1 day in the past 30 days. Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion on each of days; all heavy alcohol users are also binge alcohol users. 2 Nonmedical use of prescription-type psychotherapeutics includes the nonmedical use of pain relievers, tranquilizers, stimulants, or sedat

the-counter drugs. Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
34 

Table 2.7 Substance Dependence or Abuse, Mental Health Measures, and Receipt of Substance Use TreYear among Persons Aged 12 or Older Residing in Appalachian Region, by Age Group and Appalachian Percentages, Annual Averages Based on 2002-2005 

Dependence or Abuse/Mental Health/Receipt of Treatment 

AGE GROUP 

12-17 18 or Old

Northern Central Southern Northern Central 

DEPENDENCE OR ABUSE1  Illicit Drugs2 5.3 3.1 5.5 2.4 3.1  Alcohol 6.5 4.3 5.6 7.2 4.8  Both Illicit Drugs and Alcohol2 2.8 1.7 2.3 1.1 1.2 

Illicit Drugs or Alcohol2 9.0 5.7 8.8 8.5 6.7 

PAST YEAR SERIOUS PSYCHOLOGICAL DISTRESS3 

N/A N/A N/A 13.8 16.1 

PAST YEAR MAJOR DEPRESSIVE EPISODE4 

8.8 9.1 8.8 7.9 10.6 

PAST YEAR RECEIPT OF SPECIALTY TREATMENT FOR ILLICIT DRUG OR ALCOHOL USE2,5 

0.8 0.7 1.0 1.0 0.5 

MENTAL HEALTH TREATMENT/COUNSELING6 

N/A N/A N/A 13.7 15.4 

 Inpatient N/A N/A N/A 0.7 1.0  Outpatient N/A N/A N/A 7.0 7.4  Prescription Medication N/A N/A N/A 11.9 14.4 

Table is continued on the next page 
35 

Table 2.7 Substance Dependence or Abuse, Mental Health Measures, and Receipt of Substance Use TreYear among Persons Aged 12 or Older Residing in Appalachian Region, by Age Group and Appalachian Percentages, Annual Averages Based on 2002-2005 

NOTES: 

*Low precision; no estimate reported. 

 NOTE: Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. 

N/A: Not applicable. 

1 Dependence or abuse is based on definitions found in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). 2 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used non-m3 Serious Psychological Distress (SPD) is defined as having a score of 13 or higher on the K6 scale. Due to questionnaire changes, these combined 2004 

comparable with 2004 and earlier estimates published in prior NSDUH reports. See Section B.4.4 in Appendix C of the Results from the 2005 Nationa

Health: National Findings. Estimates are based on combined 2004-2005 data. 4 Major Depressive Episode (MDE) is defined as a period of at least 2 weeks when a person experienced a depressed mood or loss of interest or pleasure a majority of the symptoms for depression as described in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). Esti

combined 2004-2005 data. 

5 Received Substance Use Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or outpa

center in order to reduce or stop illicit drug or alcohol use, or for medical problems associated with illicit drug or alcohol use. Estimates include personspecifically for illicit drugs or alcohol, as well as persons who received treatment but did not specify for what substance(s). 6 Mental Health Treatment/Counseling is defined as having received inpatient care or outpatient care or having used prescription medication for problem

mental health. Respondents were not to include treatment for drug or alcohol use. Respondents with unknown treatment/counseling information were ebased only on responses to items in the Adult Mental Health Service Utilization module. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005. 
36 

Table 2.8 Demographic Characteristics and Health Insurance among Persons Aged 12 or Older Residin

Region, by Age Group and Appalachian Socioeconomic Status: Percentages, Annual Averages Based on 2

Demographic Characteristic/Health Insurance 

AGE GROUP 

12-17 18 or Olde

At-Risk or 

Distressed 

Transitional Competitive 

or 

Attainment 

At-Risk or 

Distressed 

Transition

HISPANIC ORIGIN AND RACE Not Hispanic or Latino 98.9 97.4 96.3 98.9 98.6  White 88.3 87.5 73.7 89.0 91.1  Black or African American 9.5 8.1 20.3 8.6 5.5  Other1 1.1 1.8 2.4 1.3 2.0  Hispanic or Latino 1.1 2.6 3.7 1.1 1.4 EDUCATION < High School N/A N/A N/A 28.9 20.2  High School Graduate N/A N/A N/A 41.8 39.5  Some College N/A N/A N/A 18.4 23.7  College Graduate N/A N/A N/A 10.9 16.7 CURRENT EMPLOYMENT Full-Time N/A N/A N/A 43.8 51.3  Part-Time N/A N/A N/A 9.7 12.3  Unemployed N/A N/A N/A 4.5 3.3  Other2 N/A N/A N/A 42.0 33.1 

*Low precision; no estimate reported. 

 NOTE: Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. 

N/A: Not applicable. 

1 Includes respondents reporting American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, Asian, and Two or More Races.

2 The Other Employment category includes retired persons, disabled persons, homemakers, students, or other persons not in the labor force.

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.

***Table is continued on the next page*** 
37 

Table 2.8 Demographic Characteristics and Health Insurance among Persons Aged 12 or Older Residin

Region, by Age Group and Appalachian Socioeconomic Status: Percentages, Annual Averages Based on 2

HEALTH INSURANCE 

 Private 52.4 69.4 73.5 63.2 72.8  Medicare 1.0 0.6 1.0 25.4 22.2  Medicaid/CHIP3 40.4 25.4 20.8 14.1 8.6 

*Low precision; no estimate reported. 

 NOTE: Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. 

N/A: Not applicable. 

3 CHIP is the Children's Health Insurance Program. Individuals aged 19 or younger are eligible for this plan. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
38 

Table 2.9 Lifetime, Past Year, and Past Month Substance Use among Persons Aged 12 or Older ResidinRegion, by Substance, Age Group, and Appalachian Socioeconomic Status: Percentages, 2002-2005 

Substance AGE GROUP

12-17 18 or Olde

At-Risk or 

Distressed

Transitional Competitive or 

Attainment

At-Risk or 

Distressed

Transitiona

MARIJUANA USE Lifetime 19.6 19.1 18.2 32.6 38.3  Past Year 13.8 14.8 14.0 5.9 8.9  Past Month 5.8 7.3 7.1 3.0 5.3 COCAINE USE Lifetime 3.1 2.8 1.5 8.2 11.6  Past Year 2.2 2.2 1.2 1.3 2.4  Past Month 0.9 0.5 0.4 0.4 0.9 METHAMPHETAMINE USE Lifetime 2.1 1.4 0.9 1.9 4.2  Past Year 0.9 0.7 0.4 0.4 0.5  Past Month 0.6 0.3 0.2 0.1 0.2 ALCOHOL USE  Past Year 31.4 34.8 33.0 43.6 62.1  Binge Alcohol Use1 10.1 11.4 8.8 15.3 21.9  Heavy Alcohol Use2 2.8 3.1 2.4 4.8 7.5 CIGARETTE USE  Lifetime 43.6 37.8 30.0 75.0 76.1  Past Year 25.7 24.7 20.3 37.4 35.3  Past Month 18.9 16.8 13.4 33.8 31.6 PAST YEAR NONMEDICAL USE OF PSYCHOTHERAPEUTICS2 

11.4 11.3 8.4 5.5 6.0 

 NOTES: 

*Low precision; no estimate reported. Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. 

1 Binge Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) on 

days. Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion on each of 5 or more days in the past 30 days; all heavy alco

alcohol users. 

2 Nonmedical use of prescription-type psychotherapeutics includes the nonmedical use of pain relievers, tranquilizers, stimulants, or sedatives and does 

counter drugs. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
39 

Table 2.10 Substance Dependence or Abuse, Mental Health Measures, and Receipt of Substance Use TreYear among Persons Aged 12 or Older Residing in Appalachian Region, by Age Group and Appalachian Status: Percentages, Annual Averages Based on 2002-2005 

Dependence or Abuse/Mental Health/Receipt of Treatment 

AGE GROUP 

12-17 18 or Olde

At-Risk or 

Distressed 

Transitional Competitive or 

Attainment 

At-Risk or 

Distressed 

Transition

DEPENDENCE OR ABUSE1  Illicit Drugs2 5.1 5.6 4.3 2.5 2.6  Alcohol 5.3 6.6 4.7 4.7 6.8  Both Illicit Drugs and Alcohol2 2.0 3.0 1.7 0.9 1.2 

Illicit Drugs or Alcohol2 8.4 9.2 7.4 6.3 8.2 

PAST YEAR SERIOUS PSYCHOLOGICAL DISTRESS3 N/A N/A N/A 17.4 11.8 PAST YEAR MAJOR DEPRESSIVE EPISODE4 9.9 8.3 9.5 10.5 6.9 PAST YEAR RECEIPT OF SPECIALTY TREATMENT FOR ILLICIT DRUG OR ALCOHOL USE2,5 

1.1 1.0 0.6 0.6 1.0 

MENTAL HEALTH TREATMENT/COUNSELING6 N/A N/A N/A 16.0 13.1  Inpatient N/A N/A N/A 1.1 0.8  Outpatient N/A N/A N/A 8.6 7.2  Prescription Medication N/A N/A N/A 14.2 11.6 

*Low precision; no estimate reported. 

 NOTE: Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. 

N/A: Not applicable. 1 Dependence or abuse is based on definitions found in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). 2 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used non-medically. 3 Serious Psychological Distress (SPD) is defined as having a score of 13 or higher on the K6 scale. Due to questionnaire changes, these combined 2004 and 2005 estimate

2004 and earlier estimates published in prior NSDUH reports. See Section B.4.4 in Appendix C of the Results from the 2005 National Survey on Drug Use and Health: Nare based on combined 2004-2005 data. 

4 Major Depressive Episode (MDE) is defined as a period of at least 2 weeks when a person experienced a depressed mood or loss of interest or pleasure in daily activities 

symptoms for depression as described in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). Estimates are based on combined 2004-

5 Received Substance Use Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or outpatient), or mental he

or stop illicit drug or alcohol use, or for medical problems associated with illicit drug or alcohol use. Estimates include persons who received treatment specifically for illipersons who received treatment but did not specify for what substance(s). 

6 Mental Health Treatment/Counseling is defined as having received inpatient care or outpatient care or having used prescription medication for problems with emotions, n

Respondents were not to include treatment for drug or alcohol use. Respondents with unknown treatment/counseling information were excluded. Estimates were based only 

Adult Mental Health Service Utilization module. Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
40 

Figure 2.1. Geographic Variation in Individuals’ Health Insurance: Adolescents and Adults 

Figure 2.1 shows geographic variation in health insurance status among adolescents aged 12 to 17 and adults aged 

private health insurance, the northern Appalachian sub-region has the highest rate of insurance for adolescents (72

while the central Appalachian sub-region has the lowest rates of insurance for adolescents (50.1%) and adults (63.

CHIP, the northern sub-region has the lowest rates of insurance in adolescents (22.4%) and adults (8.1%). The cenlargest proportion of adults with Medicare (27.8%) followed by the northern sub-region (22.3%). 

Geographic Variation in Individual's He

Insurance in Appalachia, Adults 18 and 

8.1

27.8

22.3

74

63.8

20.4

70.8

0

102030405060708090

100

Private Medicare Medic

Percent 

NCS

Geographic Variation in Individual's Health 

Insurance in Appalachia, 

Adolescents Aged 12 to 17

66.3

22.4

72.3

50.1 42.2

28

0

102030405060708090

100

Private Medicaid/ CHIP

Percent 

NorthCentralSouth
41 

Figure 2.2. Geographic Variation in Individuals’ Health Insurance: Adolescents and Adults 

Figure 2.2 shows individual health insurance by county economic development level in Appalachia. There is a lin

between economic development level and insurance, and the directions of these relationships are different for each There is a positive relationship between economic development level and private insurance; distressed or at-risk co

rates of private insurance for adolescents (52.4%) and adults (63.2%), and competitive or attainment counties have private insurance for adolescent (73.5%) and adults (74.4%). The trend for Medicaid/ CHIP is also linear, though inversely related. At-risk or distressed counties have the highest rates of Medicaid/ CHIP for adolescents (40.4%) and Medicare for adults (25.4%). Conversely, rates for Medicaid/ CHIP and Medicare are lowest in competitive o

County Economic Development Level and 

Individuals' Health Insurance in Appalachia, 

Adolescents Aged 12 to 17

40.4

69.4

52.4

25.4

20.8

73.5

0

102030405060708090

100

Private Medicaid/ CHIP

Percent

Distressed orAt-RiskTransitionalCompetitive orAttainment

County Economic Developme

Individuals' Health Insurance in 

Adults Aged 18 and O

63.2

25.4

72.8

22.2 1

74.4

0

102030405060708090

100

Private Medicare 

Percent
42 

Figure 2.3. Non-Medical Use of Prescription Drugs Among Adolescents Aged 12 to 17 Figure 2.3 presents non-medical use of prescription drugs among adolescents age 12 to 17 by county economic deAppalachian sub-region. Non-medical use of prescription drugs among adolescents is higher in the central (10.4%

regions (12.1%) of Appalachia, as compared to the northern sub-region (9.1%). Across economic development stacompetitive or attainment counties have the lowest rate of non-medical use of prescription drugs among adolescen

transitional counties (11.3%) and distressed or at-risk counties (11.4%). 

Past Year Nonmedical Use of Psychotherapeutics in 

Appalachia, Adolescents Aged 12 to 17

12.1

9.1 10.4

05

1015202530

North Central South

Sub-Region

Percent

Past Year Nonmedical Use of Psychotherapeutics in 

Appalachia, Adolescents Age 12 to 1711.4 11.3

8.4

05

1015202530

At-Risk or

Distressed

Transitional Competitive or

Attainment 

County Economic Development Status

Percent
43 

Figure 2.4. Mental Disorders Among Adults Aged 18 and Older in Appalachian Sub-Regions 

Mental Health Disorders Among Adults in 

Appalachian Sub-Regions

13.8

7.9

16.1

8

10.6

12.7

0

2

4

6

8

10

12

14

16

18

Past Year Serious

Pyschological Distress

Past Year Major Depressive

Episode

Percent

North

Central

South

 

Figure 2.4 shows mental health disorders among adults aged 18 and older in Appalachia. The 

prevalence rates for serious psychological distress in the past year and major depressive episode in 

the past year are high across all sub-regions. The highest prevalence rates for both serious 

psychological distress and major depressive episode are in the central sub-region (16.1% and 

10.6%, respectively). For the variable, serious psychological distress in the past year, the northern 

sub-region has a rate of 13.8%, and the southern sub-region has a rate of 12.7%. For the variable, 

major depressive episode in the past year, the northern and southern sub-regions have a prevalence 

rate of approximately 8%. 
44 

Table 2.11 Access to Alcohol Treatment among Persons Aged 12 or Older, by Age Group and Appalachian Percentages, Annual Averages Based on 2002-2005 

Age 12-17 Age 18 or 

Appalachian 

Region Outside Appalachia Appalachian Region 

Access to Alcohol Treatment1,2 

 Needed But Not Received Alcohol Treatment 5.6 5.5 6.1  Felt Need for Alcohol Treatment 0.2 0.2 0.3  Felt Need for Alcohol Treatment  and Made No Effort 0.1 0.1 0.2 

*Low precision; no estimate reported. NOTE: Received Alcohol Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or outp

center in order to reduce or stop alcohol use, or for medical problems associated with alcohol use. 

1 Needing But Not Receiving Treatment refers to respondents classified as needing treatment for alcohol, but have not received treatment for an alcohol 

facility (i.e., drug and alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and mental health centers). 

2 Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an alcohol problem, as well as persons who received tr

than a specialty facility but felt they needed additional treatment. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
45 

Table 2.12 Access to Drug Treatment among Persons Aged 12 or Older, by Age Group and Appalachian RPercentages, Annual Averages Based on 2002-2005 

Age 12-17 Age 18 or 

Appalachian Region Outside Appalachia Appalachian Region O

Access to Drug Treatment1,2 

 Needed But Not Received Treatment for an  Illicit Drug Problem 4.8 4.8 2.2  Felt Need for Treatment for an Illicit Drug  Problem 0.3 0.3 0.3  Felt Need for Treatment for an Illicit Drug  Problem and Made No Effort 0.2 0.2 0.2 

*Low precision; no estimate reported. NOTE: Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type pychotherapeutics used NOTE: Received Illicit Drug Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or o

center in order to reduce or stop illicit drug use, or for medical problems associated with illicit drug use. 

1 Needing But Not Receiving Treatment refers to respondents classified as needing treatment for illicit drugs, but have not received treatment for an illic

specialty facility (i.e., drug and alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and mental health centers. 

2 Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an illicit drug problem, as well as persons who receive

other than a specialty facility but felt they needed additional treatment. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
46 

 Table 2.13 Reasons for Not Receiving Substance Use Treatment and Locations of Treatment among Persons 

Age Group and Appalachian Region Status: Percentages, Annual Averages Based on 2002-2005 

Age 12-17 Age 

Appalachian 

Region

Outside Appalachia Appalachian Regio

Reasons for Not Receiving Drug or Alcohol Treatment among Persons Who Needed But Did Not Receive Treatment at a Specialty Facility1  Cost/Insurance Barriers2 * 16.3 *  Not Ready to Stop Using * 34.5 *  Stigma3,7 * 26.5 *  Did Not Know Where to Go for Treatment * 12.4 *  Did Not Feel Need for Treatment/Could Handle the Problem  Without Treatment4,7 

* 17.4 * 

 Did Not Have Time7 * 6.1 *  Treatment Would Not Help7 * 6.5 *  Other Access Barriers5 * 16.1 * Locations Where Past Year Substance Treatment was Received among Persons Who Received Treatment at a Specialty Facility6 Self-Help Group * 51.0 57.5  Outpatient Rehabilitation * 67.0 68.4  Inpatient Rehabilitation * 41.2 37.1  Mental Health Center * 42.1 48.2  Hospital Inpatient * 36.0 34.9  Private Doctor's Office * 15.8 19.3  Emergency Room * 20.4 18.3  Prison or Jail * 13.0 8.0 

NOTES: *Low precision; no estimate reported. 

Needing But Not Receiving Treatment refers to respondents classified as needing treatment for illicit drugs or alcohol, but have not received treatment for an illicit drug or alcohol problem at a specialty facility. 

Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an illicit drug or alcohol problem, as well as persons who received treatment at a location other than a specialty facility but felt they need

1 Respondents could indicate multiple reasons; thus, these response categories are not mutually exclusive. 2 Includes reasons of "No health coverage and could not afford cost," "Had health coverage but did not cover treatment or did not cover cost," and other-specify responses of "Could not afford cost; health coverage not indicated." 3 Includes reasons of "Might cause neighbors/community to have negative opinion," "Might have negative effect on job," "Did not want others to find out," and other-specify responses of "Ashamed/embarrassed/afraid" and "Afra

services." 

4 Includes reasons of "Did not feel need for treatment," "Could handle the problem without treatment," and other-specify responses of "Could do it with support of family/friends/ others," and "Could do it through religion/spiritua5 Includes reasons of "No transportation/inconvenient," "No program having type of treatment," "No openings in a program," and other-specify responses of "No program had counselor/doctors with whom you were comfortable,

were currently ineligible," and "Attempted to get treatment but encountered delays." 

6 Respondents could indicate multiple locations of treatment; thus, these response categories are not mutually exclusive. 7 Estimates are based only on combined 2003-2005 data. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
47 

Table 2.14 Reasons for Not Receiving Mental Health Treatment among Persons Aged 12 or Older, by Age GAppalachian Region Status: Percentages, Annual Averages Based on 2002-2005 

Age 12-17 Age 18 or O

Appalachian 

Region Outside Appalachia Appalachian Region O

 Reasons for Not Receiving Mental Health Treatment/Counseling among Persons with an Unmet Need for Mental Health Treatm

 Cost/Insurance Barriers2 N/A N/A 44.1  Did Not Feel Need for Treatment/Could Handle  the Problem Without Treatment3,7 N/A N/A 37.1  Stigma4,7 N/A N/A 27.6  Did not Know Where to Go for Services N/A N/A 12.4  Did Not Have Time7 N/A N/A 13.3  Treatment Would Not Help5,7 N/A N/A 9.4  Fear of Being Committed/Have to Take Medicine N/A N/A 11.6  Other Access Barriers6,7 N/A N/A 4.0 

*Low precision; no estimate reported. N/A: Not applicable. NOTE: Unmet Need for Mental Health Treatment/Counseling is defined as a perceived need for treatment that was not received. NOTE: Estimates represent reasons for not receiving mental health treatment/counseling for all persons aged 18 or older with an unmet need for treatm

unknown mental health treatment/counseling information. 

NOTE: Mental Health Treatment/Counseling is defined as having received inpatient care or outpatient care or having used prescription medication for p

nerves, or mental health. Respondents were not to include treatment for drug or alcohol use. Respondents with unknown treatment/counseling i

Estimates were based only on responses to items in the Adult Mental Health Service Utilization module. 1 Respondents could indicate multiple reasons; thus, these response categories are not mutually exclusive. 2 Includes reasons of "Could not afford," "Health insurance does not pay enough," "Health insurance does not cover mental health treatment," and other-

health insurance." 

 3 Includes reasons of "Did not feel need for treatment," "Could handle problem without treatment," and other responses of "Work on problems with fami

problems through religion/spirituality." 

 4 Includes reasons of "Might cause neighbors/community to have negative opinion," "Might have negative effect on job," "Concerned about confidential

to find out," and other-specify responses of "Ashamed/embarrassed/afraid," "Concerned how court system would treat me," and "Concerned how it woinsurability." 

 5 Includes reasons of "Did not feel need for treatment," "Could handle problem without treatment," and other-specify responses of "Work on problems w

"Work on problems through religion/spirituality." 

 6 Includes reasons of "No transportation/inconvenient" and other-specify responses of "Too much red tape/hassle to get services," "No openings/long wa

"Services unavailable/limited in area," "Attempted to get treatment but unsuccessful in finding help," and "Could not find program/counselor comforta

 7 Estimates are based only on combined 2003-2005 data.  Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005. 
48 

Table 2.15 Access to Alcohol Use Treatment among Persons Aged 12 or Older, by Age Group and Appalac

Percentages, Annual Averages Based on 2002-2005 

Age 12-17 Age 18 or 

Northern Central Southern Northern Cent

Access to Alcohol Treatment1,2 

 Needed But Not Received Alcohol Treatment 6.2 4.2 5.3 6.8 4.6  Felt Need for Alcohol Treatment 0.2 0.5 0.1 0.4 0.5  Felt Need for Alcohol Treatment and Made  No Effort 0.1 0.3 0.1 0.2 0.5 

*Low precision; no estimate reported. NOTE: Received Alcohol Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or outp

center in order to reduce or stop alcohol use, or for medical problems associated with alcohol use. 

1 Needing But Not Receiving Treatment refers to respondents classified as needing treatment for alcohol, but have not received treatment for an alcohol 

facility (i.e., drug and alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and mental health centers). 

2 Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an alcohol problem, as well as persons who received tr

than a specialty facility but felt they needed additional treatment. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
49 

 Table 2.16 Access to Drug Use Treatment among Persons Aged 12 or Older, by Age Group and AppalachiPercentages, Annual Averages Based on 2002-2005 

Age 12-17 Age 18 o

Northern Central Southern Northern Cen

Access to Drug Treatment1,2 

 Needed But Not Received Treatment for an  Illicit Drug Problem 5.1 3.1 5.0 2.1 2.9  Felt Need for Treatment for an Illicit Drug  Problem 0.3 0.3 0.2 0.2 0.5  Felt Need for Treatment for an Illicit Drug  Problem and Made No Effort 0.1 0.2 0.2 0.2 0.5 

*Low precision; no estimate reported. NOTE: Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type pychotherapeutics used NOTE: Received Illicit Drug Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or o

center in order to reduce or stop illicit drug use, or for medical problems associated with illicit drug use. 

1 Needing But Not Receiving Treatment refers to respondents classified as needing treatment for illicit drugs, but have not received treatment for an illic

specialty facility (i.e., drug and alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and mental health centers. 

2 Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an illicit drug problem, as well as persons who receive

other than a specialty facility but felt they needed additional treatment. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
50 

Table 2.17 Reasons for Not Receiving Mental Health Treatment among Persons Aged 12 or Older, by Age Appalachian Sub-Region: Percentages, Annual Averages Based on 2002-2005 

Age 12-17 Age 18 or 

Northern Central Southern Northern Cent

 Reasons for Not Receiving Mental Health Treatment/Counseling among Persons with an Unmet Need for Mental Health Treatm

 Cost/Insurance Barriers2 N/A N/A N/A 41.4 *  Did Not Feel Need for Treatment/Could  Handle the Problem Without Treatment3,7 N/A N/A N/A 37.5 *  Stigma4,7 N/A N/A N/A 28.5 *  Did not Know Where to Go for Services N/A N/A N/A 12.2 *  Did Not Have Time7 N/A N/A N/A 12.3 *  Treatment Would Not Help5,7 N/A N/A N/A 12.6 *  Fear of Being Committed/Have to Take  Medicine N/A N/A N/A 9.9 8.2  Other Access Barriers6,7 N/A N/A N/A 4.9 * 

*Low precision; no estimate reported. N/A: Not applicable. NOTE: Unmet Need for Mental Health Treatment/Counseling is defined as a perceived need for treatment that was not received. NOTE: Estimates represent reasons for not receiving mental health treatment/counseling for all persons aged 18 or older with an unmet need for treatm

unknown mental health treatment/counseling information. 

NOTE: Mental Health Treatment/Counseling is defined as having received inpatient care or outpatient care or having used prescription medication for 

nerves, or mental health. Respondents were not to include treatment for drug or alcohol use. Respondents with unknown treatment/counseling 

Estimates were based only on responses to items in the Adult Mental Health Service Utilization module. 1 Respondents could indicate multiple reasons; thus, these response categories are not mutually exclusive. 2 Includes reasons of "Could not afford," "Health insurance does not pay enough," "Health insurance does not cover mental health treatment," and other

health insurance." 

3 Includes reasons of "Did not feel need for treatment," "Could handle problem without treatment," and other-specify responses of "Work on problems w

"Work on problems through religion/spirituality." 

4 Includes reasons of "Might cause neighbors/community to have negative opinion," "Might have negative effect on job," "Concerned about confidentia

to find out," and other-specify responses of "Ashamed/embarrassed/afraid," "Concerned how court system would treat me," and "Concerned how it woinsurability." 

5 Includes reasons of "Did not feel need for treatment," "Could handle problem without treatment," and other-specify responses of "Work on problems w

"Work on problems through religion/spirituality." 

6 Includes reasons of "No transportation/inconvenient" and other-specify responses of "Too much red tape/hassle to get services," "No openings/long w

"Services unavailable/limited in area," "Attempted to get treatment but unsuccessful in finding help," and "Could not find program/counselor comforta

7 Estimates are based only on combined 2003-2005 data. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
51 

 Table 2.18 Access to Alcohol Use Treatment among Persons Aged 12 or Older, by Age Group and AppalaSocioeconomic Status: Percentages, Annual Averages Based on 2002-2005 

Age 12-17 Age 18 or 

At-Risk or 

Distressed Transitional

Competitive or 

Attainment 

At-Risk or 

Distressed Transitio

Access to Alcohol Treatment1,2 

 Needed But Not Received Alcohol Treatment 4.9 6.3 4.5 4.5 6.4  Felt Need for Alcohol Treatment 0.6 0.1 0.1 0.4 0.3  Felt Need for Alcohol Treatment and Made  No Effort 0.3 0.1 0.0 0.3 0.2 

*Low precision; no estimate reported. NOTE: Received Alcohol Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or outp

center in order to reduce or stop alcohol use, or for medical problems associated with alcohol use. 

1 Needing But Not Receiving Treatment refers to respondents classified as needing treatment for alcohol, but have not received treatment for an alcohol 

facility (i.e., drug and alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and mental health centers). 

2 Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an alcohol problem, as well as persons who received t

than a specialty facility but felt they needed additional treatment. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
52 

Table 2.19 Access to Drug Treatment among Persons Aged 12 or Older, by Age Group and Appalachian SStatus: Percentages, Annual Averages Based on 2002-2005 

Age 12-17 Age 18 o

At-Risk or 

Distressed Transitional

Competitive or 

Attainment

At-Risk or 

Distressed Transit

Access to Drug Treatment1,2 

 Needed But Not Received Treatment for an  Illicit Drug Problem 4.7 5.3 4.0 2.3 2.3  Felt Need for Treatment for an Illicit Drug  Problem 0.5 0.2 0.3 0.3 0.3  Felt Need for Treatment for an Illicit Drug  Problem and Made No Effort 0.3 0.1 0.2 0.3 0.2 

*Low precision; no estimate reported. NOTE: Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type pychotherapeutics used NOTE: Received Illicit Drug Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or o

center in order to reduce or stop illicit drug use, or for medical problems associated with illicit drug use. 

1 Needing But Not Receiving Treatment refers to respondents classified as needing treatment for illicit drugs, but have not received treatment for an illic

specialty facility (i.e., drug and alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and mental health centers. 

2 Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an illicit drug problem, as well as persons who receive

other than a specialty facility but felt they needed additional treatment. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
53 

Table 2.20 Reasons for Not Receiving Mental Health Treatment/Counseling among Persons Aged 12 or Oland Appalachian Socioeconomic Status: Percentages, Annual Averages Based on 2002-2005 

Age 12-17 Age 18 or 

At-Risk or 

Distressed Transitional

Competitive or 

Attainment 

At-Risk or 

Distressed Transitio

Reasons for Not Receiving Mental Health Treatment/Counseling among Persons with an Unmet Need for Mental Health Treatm

 Cost/Insurance Barriers2 N/A N/A N/A 37.0 49.1  Did Not Feel Need for Treatment /Could  Handle the Problem Without Treatment3,7 N/A N/A N/A 34.2 30.4  Stigma4,7 N/A N/A N/A 30.6 27.0  Did not Know Where to Go for Services N/A N/A N/A 10.3 14.1  Did Not Have Time7 N/A N/A N/A 11.5 13.8  Treatment Would Not Help5,7 N/A N/A N/A 5.6 8.7  Fear of Being Committed/Have to Take  Medicine N/A N/A N/A 15.0 10.7  Other Access Barriers6,7 N/A N/A N/A 2.1 5.0 

*Low precision; no estimate reported. N/A: Not applicable. NOTE: Unmet Need for Mental Health Treatment/Counseling is defined as a perceived need for treatment that was not received. NOTE: Estimates represent reasons for not receiving mental health treatment/counseling for all persons aged 18 or older with an unmet need for treatm

unknown mental health treatment/counseling information. 

NOTE: Mental Health Treatment/Counseling is defined as having received inpatient care or outpatient care or having used prescription medication for 

nerves, or mental health. Respondents were not to include treatment for drug or alcohol use. Respondents with unknown treatment/counseling 

Estimates were based only on responses to items in the Adult Mental Health Service Utilization module. 1 Respondents could indicate multiple reasons; thus, these response categories are not mutually exclusive. 2 Includes reasons of "Could not afford," "Health insurance does not pay enough," "Health insurance does not cover mental health treatment," and other

health insurance." 

3 Includes reasons of "Did not feel need for treatment," "Could handle problem without treatment," and other-specify responses of "Work on problems w

"Work on problems through religion/spirituality." 

4 Includes reasons of "Might cause neighbors/community to have negative opinion," "Might have negative effect on job," "Concerned about confidentia

to find out," and other-specify responses of "Ashamed/embarrassed/afraid," "Concerned how court system would treat me," and "Concerned how it woinsurability." 

5 Includes reasons of "Did not feel need for treatment," "Could handle problem without treatment," and other-specify responses of "Work on problems w

"Work on problems through religion/spirituality." 

6 Includes reasons of "No transportation/inconvenient" and other-specify responses of "Too much red tape/hassle to get services," "No openings/long w

"Services unavailable/limited in area," "Attempted to get treatment but unsuccessful in finding help," and "Could not find program/counselor comforta

7 Estimates are based only on combined 2003-2005 data. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
54 

2.4.2 Maps 

The first maps in this section present information relative to the county-level population of the 410 

Appalachian counties, and the NSDUH sample sizes for each county for both adults and 

adolescents. Map 2.1 shows the average population for each of the 410 counties within the 

Appalachian region for the years 2002 to 2005. Maps 2.2 and 2.3 show the number of individuals 

sampled as part of the NSDUH survey for those same years; Map 2.2 shows the numbers of adults 

age 18 and over by county, and Map 2.3 shows the number of adolescents sampled by county. As 

would be expected, areas with higher populations are more likely to have residents included in the 

NSDUH sample. Note that several counties (58 among adult sample; 10 among adolescent sample) 

have zero respondents, and many others have between only 1 and 5 respondents (31 among adult 

sample; 76 among adolescent sample). The small sample sizes make county-level analyses 

impossible. To address this issue, and with the help of the SAMHSA Office of Applied Studies, we 

were provided with aggregated data based on Appalachian sub-region (northern, central, and 

southern) and ARC designated economic development status (distressed, at-risk, transitional, 

competitive, and attainment), and analyses were conducted accordingly, as presented earlier in this 

chapter. Also note that three Appalachian states, New York, Pennsylvania, and Ohio, are among 

the NSDUH large sample states, so that county samples in these states are higher. 

NORC was not provided with data for individual counties, however, so we are unable to map results 

using ARC-defined categories. Rather, the remaining maps in this section present data according to 

NSDUH-defined sub-regions (described earlier in the chapter), which do not perfectly correspond to 

the ARC region. To accurately portray these maps, we present estimated values for all selected 

substance use and serious psychological distress measures using the NSDUH defined region as the 

unit of analysis. As such, all counties within those regions are applied the same estimate as 

generated by SAMHSA’s Office of Applied Studies (OAS, 200623). These estimates are then 

mapped showing the full NSDUH sub-state areas, the ARC boundary, and state and county 

boundaries within Appalachia, to assist in pattern detection. Readers should be cautious in 

generalizing regional estimates to the county level.
55 

Population & Sample

Map 2.1 Average Population 2002-2005, in the Appalachian Region by County 
56 

Map 2.2 Number of Sampled Adults Age 18 or older in NSDUH 2002-2005, in the 

Appalachian Region by County 
57 

Map 2.3 Number of Sampled Adolescents Age 12 – 17 in NSDUH 2002-2005, in the 

Appalachian Region by County 
58 

Alcohol Use

Map 2.4 Perception of Great Risk of Binge Drinking, by NSDUH Sub-Region, 2002-2005 

Map 2.4 shows the percentage distributions among persons age 12 or older who perceived the risk 

of binge drinking as a ‘great risk.’ NSDUH respondents were asked how much they thought people 

risk harming themselves by binge drinking (great risk, moderate risk, slight risk, no risk). 

Perceived great risk of binge drinking is higher in the NSDUH sub-state areas corresponding to 

central Appalachia, and highest in the NSDUH sub-state areas corresponding to southern 

Appalachia. Perception of great risk of binge drinking appears to be lowest for NSDUH sub-state 

areas that include northern Pennsylvania and the southern tier of New York State. 
59 

Map 2.5 Alcohol Use in Past Month, by NSDUH Sub-Region, 2002-2005 

Map 2.5 shows the percentages of alcohol use in the past month among all persons age 12 or older, 

which appears highest in the NSDUH sub-state areas that include the Appalachian portions of 

Pennsylvania and New York. 
60 

Map 2.6 Binge Alcohol Use in Past Month, by NSDUH Sub-Region, 2002-2005 

Map 2.6 shows binge drinking percentages among people age 12 or older in the past month. Rates 

are highest in the NSDUH sub-state areas corresponding to northern Appalachia, with particularly 

high rates in the southern tier of New York, northern Pennsylvania, and eastern Ohio. Notably, 

rates appear highest in those areas where perception of risk was lowest (i.e., northern Appalachia), 

and lowest in those areas where perception of risk as highest (i.e., southern Appalachia) (see Map 

2.4). 
61 

Map 2.7 Alcohol Use in Past Month Among Persons Aged 12-20, by NSDUH Sub-Region, 

2002-2005 

Map 2.7 shows percentages of alcohol use in the past month among youth or young adults age 12-

20, which, as with those among all persons age 12 or older, appears highest in the NSDUH sub-state 

areas that include the Appalachian portions of Pennsylvania and New York. Additionally, rates 

appear higher among adolescents in NSDUH sub-state areas corresponding to central Appalachia as 

compared to adults, and somewhat lower in NSDUH sub-state areas corresponding to southern 

Appalachia as compared to adults. 
62 

Map 2.8 Binge Alcohol Use in Past Month, Persons Aged 12-20, by NSDUH Sub-Region, 2002-

2005 

Map 2.8 shows binge drinking in the past month, among adolescents or young adults age 12-20 

however. As before, rates are highest in the NSDUH sub-state areas corresponding to northern 

Appalachia, with particularly high rates in the southern tier of New York, northern Pennsylvania, 

and eastern Ohio. As compared to adults, however, rates also appear higher in NSDUH sub-state 

areas corresponding to central Appalachia. Also as before, rates appear highest in those areas where 

perception of risk was lowest (i.e., northern Appalachia), and lowest in those areas where 

perception of risk as highest (i.e., southern Appalachia) (see Map 2.4). 
63 

Map 2.9 Alcohol Dependence in Past Year, by NSDUH Sub-Region, 2002-2005 

Map 2.9 shows alcohol dependence in the past year among persons age 12 or older. Rates fluctuate 

across the region, but appear highest in the NSDUH sub-state areas corresponding to northeast 

Pennsylvania, the Appalachian portions of Virginia and South Carolina, as well as areas within 

Ohio and West Virginia, and Georgia. 
64 

Map 2.10 Needing But Not Receiving Treatment in Past Year for Alcohol Use, by NSDUH 

Sub-Region, 2002-2005 

Map 2.10 shows rates of individuals needing but not receiving treatment for alcohol in the past year 

among adults. Rates are highest in NSDUH sub-state areas corresponding to northern Appalachia, 

with particularly high rates in the northern portion of Pennsylvania, the southern tier of New York, 

and portions of Ohio and West Virginia. Rates appear low in most NSDUH sub-state areas 

corresponding to southern Appalachia, as well as eastern Kentucky. 
65 

Cigarette Use

Map 2.11 Perception of Great Risk of Smoking One or More Packs of Cigarettes Everyday, by 

NSDUH Sub-Region, 2002-2005 

Map 2.11 shows the percentages of persons age 12 or older who perceived ‘great risk’ of smoking 

one more packs of cigarettes per day. NSDUH respondents were asked how much they thought 

people risk harming themselves by smoking one or more packs of cigarettes per day (great risk, 

moderate risk, slight risk, no risk). Perceived risk is highest in NSDUH sub-state areas 

corresponding to the far southern portions of Appalachia, as well in the far northeastern portion of 

Appalachia. Perceived risk is low in the NSDUH sub-state areas corresponding to the Appalachian 

region of Ohio, eastern Kentucky, as well as in areas of Tennessee and North Carolina. 
66 

Map 2.12 Cigarette Use in Past Month, by NSDUH Sub-Region, 2002-2005 

Map 2.12 presents actual cigarette use in the past month, which contrasts noticeably from the prior 

map. For areas where Map 2.11 shows low perceived risk, rates appear to actually be highest. This 

includes the Appalachian portions of Ohio, eastern Kentucky, eastern Tennessee, and western North 

Carolina. 
67 

Marijuana Use

Map 2.13 Marijuana Use in Past Month, by NSDUH Sub-Region, 2002-2005 

Map 2.13 shows past month marijuana use among persons age 12 or older, which appears highest in 

NSDUH sub-state areas corresponding to northern and central Appalachia. Highest rates appear in 

NSDUH sub-state areas corresponding to western North Carolina and the southern tier of New 

York. 
68 

Map 2.14 Marijuana Use in Past Year, by NSDUH Sub-Region, 2002-2005 

Map 2.14 shows past year marijuana use among persons age 12 or older. Patterns are similar to past 

month use, with additional high rate pockets in NSDUH sub-state areas corresponding to 

northwestern Georgia and northeastern Pennsylvania. 
69 

Cocaine Use

Map 2.15 Cocaine Use in Past Year, by NSDUH Sub-Region, 2002-2005 

Map 2.15 shows past year cocaine use among persons age 12 or older. Rates appear highest in 

NSDUH sub-state areas corresponding to northern and central Appalachia, with particularly high 

rates in the southern tier of New York, northeastern Pennsylvania, northern West Virginia. 
70 

Illicit Drug Use Other Than Marijuana

Map 2.16 Any Use of Illicit Drugs Other Than Marijuana, Past Month, by NSDUH SubRegion, 2002-2005 

Map 2.16 shows rates of any use of illicit drugs other than marijuana over the past month among 

persons age 12 or older. Noticeably, the patterns change as compared to alcohol and marijuana use, 

with the highest rates in NSDUH sub-state areas corresponding to central and southern Appalachia. 

Rates are highest in NSDUH sub-state areas corresponding to eastern Kentucky, eastern Tennessee, 

western North Carolina, southern West Virginia, the Appalachian portion of South Carolina, and 

portions of Georgia and Alabama. Rates are lowest in the NSDUH sub-state areas corresponding to 

western Pennsylvania. 
71 

Map 2.17 Any Drug Dependence in Past Year, by NSDUH Sub-Region, 2002-2005 

Map 2.17 shows any reported drug dependence in the past year among persons age 12 or older. 

Rates appear highest in NSDUH sub-state areas corresponding to central Appalachia, with 

particularly high rates in eastern Kentucky and southern West Virginia. Rates are also high in 

NSDUH sub-state areas corresponding to portions of Appalachian Ohio, North Carolina, along the 

southern tier of New York, and in northern West Virginia. 
72 

Map 2.18 Needing But Not Receiving Treatment for Drug Use in Past Year, by NSDUH SubRegion, 2002-2005 

Map 2.18 shows rates of individuals age 12 or older reporting needing but not receiving treatment 

for drug abuse in the past year. Rates appear highest in the NSDUH sub-state areas corresponding 

to eastern Kentucky, southern and northern West Virginia, eastern Tennessee, western North 

Carolina, and along the southern tier of New York. Rates appear lowest in Pennsylvania and areas 

corresponding to southern Appalachia, including portions of Mississippi, Alabama, and Georgia. 

Non-Medical Use of Prescription Drugs
73 

Map 2.19 Painkiller Use in Past Year, by NSDUH Sub-Region, 2002-2005 

Map 2.19 shows the use of painkillers over the past year among persons age 12 or older. Rates are 

noticeably higher in the NSDUH sub-state areas corresponding to central Appalachia, with 

particularly high rates in eastern Kentucky and southern West Virginia. High rates are also seen in 

the easternmost portion of Tennessee, northeastern Georgia, and northern West Virginia. Rates 

appear lowest in NSDUH sub-state areas corresponding to southwestern and south central 

Pennsylvania. 
74 

Mental Health

Map 2.20 Serious Psychological Distress in Past Year, by NSDUH Sub-Region, 2002-2005 

Map 2.20 shows serious psychological distress in the past year among persons age 12 or older. 

Rates are particularly high in the NSDUH sub-state areas corresponding to central Appalachia, 

including eastern Kentucky and southern West Virginia. Rates are also high in NSDUH sub-state 

areas adjacent to central Appalachia, including areas of Tennessee, West Virginia, and Ohio. Rates 

appear lowest in NSDUH sub-state areas corresponding to southwest and northeast Pennsylvania. 
75 

2.5 Discussion 

This is the first time that a large-scale national household survey has been used to specifically 

address substance abuse and mental health problems at a regional level. The findings not only 

provide an overall and much needed contemporary view of the status of substance abuse and mental 

health within the Appalachian region, but they also highlight potential disparities when compared 

nationally. 

This chapter reveals several noteworthy findings. First, regardless of age or the length of use, 

smoking is more prevalent in the Appalachian region than outside of Appalachia. Second, while the 

prevalence of the non-medical use of psychotherapeutics was higher among adolescents than among 

adults overall, adolescents in the Appalachian region had even higher prevalence rates than 

adolescents outside of the Appalachian region. Both geographic variation and economic level 

differences are observed in adolescents’ non-medical use of prescription drugs – with the southern 

part of Appalachia, “distressed and at-risk,” and “transitional” counties having higher rates. In 

addition, evidence suggests that adolescents in Appalachia tend to engage in heavy alcohol use 

more than adolescents elsewhere. 

This study also reveals that, proportionately, there are more severe mental health problems in the 

Appalachian region than outside of Appalachia. Further, the central Appalachian sub-region is 

found to have the highest prevalence rates of both serious psychological distress and major 

depressive episode. 

Methamphetamine use has been of particular interest among news media and policy makers. The 

current study, however, does not support that methamphetamine use prevalence is higher in 

Appalachia than outside of Appalachia overall. Among adults, the percentages of current (past 

month) or recent (past year) methamphetamine use are similar between Appalachia and elsewhere, 

but the lifetime use of methamphetamine rate is lower in Appalachia than outside of Appalachia. 

For adolescents, the methamphetamine use prevalence rates are generally similar, although the rates 

in Appalachia for lifetime use and past month use are slightly higher as compared to rates outside of 

Appalachia. This finding should not minimize the issue of methamphetamine abuse within 

Appalachia, however. Rather, this may be a reflection of the granularity of the available data, 

which cannot be analyzed at the individual county level. We would expect, based on anecdotal 

evidence, that there are particular “hotspots” within Appalachia that cannot be gleaned from the 

NSDUH data set. Overall, however, the magnitude of methamphetamine use appears small across 

the region as compared to other substance use issues such as the non-medical use of prescriptiontype psychotherapeutics. 

Inasmuch as the findings appear to suggest greater problems among Appalachian adolescents than 

among Appalachian adults, policy makers and community members should take notice. 

Adolescents grow into adults, and communities will need to be prepared to address the fact that 

smoking rates and extensive non-prescription drug use will be ongoing challenges. The 

implementation of effective prevention measures is recommended within schools and communities 

to mitigate these challenges in the future. 

Although the findings also demonstrate that opportunities for outpatient mental health treatment and 

counseling comparable, or even slightly higher, within Appalachia as compared to areas outside of 
76 

Appalachia, determining the quality of care provided and the overall effectiveness of the treatment 

are beyond the scope of this project and are worthwhile areas to study further. 

This study finds that outpatient rehabilitation is the most common setting for substance abuse 

treatment both in and outside of Appalachia. In addition, this study finds that, of the people seeking 

substance abuse treatment at a specialty facility, proportionately fewer people utilize inpatient 

rehabilitation services in Appalachia than people outside of the Appalachian region. At the same 

time, utilization rates of hospital inpatient services, the private doctor’s office, and emergency room 

services are all higher in the Appalachian region than outside of the Appalachian region. The exact 

reasons behind this pattern need further study, but two possible explanations are: (1) those clients 

who could benefit more from inpatient rehabilitation do not get this treatment or substitute inpatient 

with outpatient services; or (2) those who have severe substance abuse problems have not received 

appropriate outpatient treatment or regular inpatient services, and as a result, use more expensive 

emergency room services. 

This study shows that the negative 

perceptions about treatment appear to be 

more pronounced within the 

Appalachian region among those who 

need mental health treatment but have 

not received treatment. Education, 

communications, and special 

intervention methods and programs 

should be considered as ways to modify 

the perceptions of the people with 

mental illness needing treatment. 

Efforts should also be made in 

Appalachian communities to reduce 

stigma arising from concerns such as 

“might cause neighborhood/community 

to have negative opinion,” “might have 

negative effect on job,” “someone may 

find out,” “ashamed, embarrassed, or 

afraid,” etc. 

Regardless of substance abuse or mental 

disorders, the top reason for people who needed treatment but did not receive treatment was due to 

the absence of insurance or external payment methods. Followed by this extrinsic reason are two 

intrinsic reasons – people did not think they needed treatment, or were obstructed by the stigma 

attached, especially for the Appalachian patients accessing the mental health services. Assuming 

that the boundary between perception of no need for treatment and the fear of stigma was blurred, 

these intrinsic reasons would even surpass the insurance issue and become the number one hurdle 

for why people who need treatment do not actually receive treatment. Behind these intrinsic 

reasons, it is possible that mistrust of the treatment system would be another important issue, though 

this would need future study and is beyond the scope of our current investigation. 
77 

It should be recognized that cost of treatment issues may be relatively more or less important 

depending on the economic status of the county. Poor counties could likely have access to 

governmental insurance (Medicaid, Medicare, CHIP), while well-off counties probably have higher 

rates of private insurance. “Transitional” counties may fall through the cracks. 

As noted previously, this study has limitations and as such, should be interpreted with caution. The 

NSDUH was designed for national and state estimates and not for any specific user-defined region. 

Neither the counties, nor the Appalachian region, were part of the primary sampling unit (PSU) or 

stratification unit. Estimates across state boundaries are inefficient, involving highly variable 

weights.24 In addition, the total weighted estimated numbers of persons for various measures may 

not be precise. For reference purpose or getting approximate estimates of the numbers of persons 

included, the weighted estimated totals using the existing weights are provided in Appendix C. 

However, since the Appalachian region is comprised of 13 states, and the sub-regions we 

investigated are also large domains, the biases caused by the innovative use of the NSDUH should 

not be a major concern. 
78 

CHAPTER 3: Patient Admissions to Treatment for Abuse of Alcohol and 

Drugs in Appalachia, 2000 – 2004 

3.1 Introduction 

Thousands of public and private treatment facilities are available across the United States to treat 

people with substance abuse and mental health disorders. Exploring data at the treatment facility 

level provides a unique opportunity to better understand populations with substance abuse and 

mental health disorders and to explore trends across geographic areas. 

One of the data sets used to explore admissions to and discharges from substance abuse treatment is 

the Treatment Episode Data Set (TEDS), an annual national flow of information on the 

demographic and characteristics of admissions to (and more recently discharges from) treatment. 

TEDS provides highly specific data on treatment type and demographic data for patients, making 

this dataset particularly important to understanding the trends of patient admissions for substance 

abuse treatment. TEDS captures data on admissions that report use of the following substances: 

marijuana; cocaine; other opiates or synthetics which includes codeine, Dilaudid, morphine, 

Demerol, opium, oxycodone, and any other drug with morphine-like effects; heroin; 

methamphetamine or other stimulants which includes non-amphetamine stimulants; tranquilizers; 

other substances; sedatives; and inhalants. TEDS also includes data on admissions with 

psychological problems or mood disorders, and captures whether admissions have a psychiatric 

problem in addition to an alcohol or drug problem. 

Chapter 3 provides an overview of the pooled annual admissions to treatment facilities in the 

Appalachian region, and in other regions nationally, during the 2000 – 2004 period. All analyses in 

this chapter are based on the TEDS series. Key research questions explored include: 

Are there sub-regional differences of admissions to substance abuse treatment in Appalachia 

as compared to admissions to treatment outside of Appalachia? 

What do the sub-regional differences of admissions to treatment look like across different 

socio-economic and demographic variables such as age, education, type of health insurance, 

etc? 

What do the sub-regional differences of admissions to treatment look like with respect to 

other variables, such as source of referral, number of prior treatment episodes, and primary 

reason for admission? 

In Section 3.2, we provide an overview of the TEDS series, its uses, the measures relevant to this 

study, and any limitations specifically related to exploring admissions to treatment of substance 

abuse in the Appalachian region. In Section 3.3, we discuss our methods. Section 3.4 contains the 

results of the analysis. Finally, Section 3.5 provides a discussion of key findings. 

3.2 Data 

3.2.1 Overview 
79 

The Treatment Episode Data Set (TEDS) is an administrative data system providing information on 

the demographic and substance abuse characteristics of admissions to and discharges from 

substance abuse treatment. The primary goal of this data set is to monitor and report treatment 

episodes for substance abusers.25 While the TEDS Admissions Data Set has been operational for 15 

years, the TEDS Discharge Data Set is new, reporting data for the first time in 2000. TEDS is 

sponsored by the Substance Abuse and Mental Health Services Administration (SAMHSA)’s Office 

of Applied Studies (OAS) at the U.S. Department of Health and Human Services. Collected since 

1992, the TEDS series was designed to provide annual data on persons admitted to public and 

private substance abuse treatment facilities that are licensed or certified by state substance abuse 

agencies to provide treatment. Generally, the facilities reporting to state substance abuse agencies 

are those that receive public funds. 

TEDS is one component of the Drug and Alcohol Services Information System (DASIS).26 The 

DASIS is the primary source of national data on substance abuse treatment and includes TEDS as 

well as two other components, the National Survey of Substance Abuse Treatment Services (NSSATS) and the Inventory of Substance Abuse Treatment Services (I-SATS).27

TEDS data are collected by publicly financed substance abuse treatment programs from the 50 

states, the District of Columbia, and Puerto Rico. State substance abuse agencies collect the 

administrative records from substance abuse treatment programs from states and jurisdictions and 

prepare the data in a standardized format. Data are then submitted to SAMHSA, which uses the 

data to report aggregated information on substance abuse treatment. The unit of analysis for the 

TEDS series is treatment admissions.28 

States vary in terms of the latest year for which they have complete data and the type of data they 

have submitted. Substance abuse treatment programs are required to report the Minimum Data Set 

(MDS) to their respective state substance abuse agency, but are not required to report data for the 

Supplemental Data Set (SuDS). 

The MDS contains data on 19 items that include characteristics of clients admitted for substance 

abuse treatment, as well as the characteristics of the treatment episodes. Specifically, the data 

elements from the MDS include: transaction type; admission date; type of service at admission; 

number of (previous) treatment episodes; client age; sex; race; ethnicity; education; employment 

status; principal source of referral; substance problem; usual route of administration; frequency of 

use; age of first use; and whether medication-assisted opioid therapy is part of the client’s treatment 

plan. Additional variables, such as calculated age and census region, are added to the state data. 

Substances abused include alcohol, marijuana and hashish, cocaine and crack, heroin, 

hallucinogens, nonprescription methadone, other opiates and synthetics, phencyclidine (PCP), 

methamphetamine, other amphetamines, other stimulants, benzodiazepines, other tranquilizers, 

barbiturates, other sedatives or hypnotics, inhalants, over-the-counter medications, and other 

substances. 

SuDS data is optional for treatment programs to report. SuDS data include: whether the client is 

pregnant at time of admission; veteran status; whether the patient has a psychiatric problem in 

addition to alcohol or drug problem; the diagnosis of the substance abuse problem from the 

American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders; 

marital status; living arrangement; source of income support; health insurance; expected/ actual 
80 

primary source of payment; detailed information about those clients who are coded as "Not in labor 

force" in the MDS; detailed information related to criminal justice referrals; number of days waiting 

to enter treatment; and detailed drug code. 

TEDS is based on over 2 million admissions reported by over 10,000 facilities to the 50 States, 

District of Columbia, and Puerto Rico, over a calendar year. 

3.2.2 Uses of TEDS 

TEDS enables researchers to explore the demographic and substance abuse characteristics of 

admissions to and discharges from substance abuse treatment. TEDS data has been used to explore 

a number of research questions related to substance abuse issues. Recent studies have focused on 

abuse of opioid analgesics and methamphetamine,29,30 heroin use, changes in use over time, and the 

economic costs of heroin addiction,31,32,33 misuse of prescription drugs,34 substance abuse during 

pregnancy,35 and trends in methamphetamine and amphetamine use.36 Researchers have also used 

TEDS data to explore characteristics of primary heroin injection and inhalation admissions and 

primary phencyclidine admissions.37,38 

A large body of research has applied TEDS data to study treatment for marijuana use disorders and 

methadone,39 substance abuse prevention and treatment activities at the state level,40 treatment 

trends,41 and treatment policy, more generally.42 

Given that TEDS data can be analyzed using geographic identifiers (e.g., metropolitan area, State, 

Census Region, Census Division, one State to all others), researchers have analyzed trends in 

treatment admissions in specific geographic areas.43,44 For example, recent studies have explored 

treatment admissions in urban and rural areas involving the abuse of narcotic painkillers45 and 

substance abuse in mid-size cities and rural areas.46

3.2.3 TEDS Measures Used in this Study 

Next, we define the measures used from the TEDS dataset of pooled admissions from 2000 – 2004 

period. We explore the following sets of variables: gender, race, education, and age; employment 

status, marital status, and pregnancy status upon admission; health insurance and primary source of 

referral; service setting; types of services and whether methadone was prescribed during treatment; 

number of prior treatment episodes and expected source of payment; substances abused as primary 

reason for admission; substances abused as one major reason for admission; and presence of 

psychological problems and mood disorders. We briefly describe each variable below. 

The gender of the client admitted for treatment in a drug or alcohol program is described as male or 

female. 

The race of the client is described as one of the following: Alaska Native (Aleut, Eskimo, Indian); 

American Indian (people of North, Central and South America who maintain cultural identification 

through tribal affiliation or community attachment); Asian or Pacific Islander (people of the Far 

East, the Indian subcontinent, Southeast Asia, or the Pacific Islands); Black or African American 

(any of the black racial groups of Africa); White (people of Europe, North Africa, or the Middle 

East); and Other (a default category for use in instances in which the client is not classified above). 
81 

The education of the client specifies the highest grade of school completed by the client admitted 

for treatment: less than high school; high school; and more than high school. 

The age of the admission is specified as one of the following categories: 17 years old or younger; 

18 to 24 years old; 25 to 34 years old; 35 to 44 years old; and 45 or older. 

The employment status of the admission is specified as: full time (working 35 hours or more each 

week - includes members of the uniformed services); part time (working fewer than 35 hours each 

week); unemployed (looking for work during the past 30 days or a homemaker, student, disabled, 

retired, or an inmate of an institution); not in the labor force; or unknown. 

The marital status of the admission is recorded as one of the following: never married; now 

married; separated; divorced/ widowed; and unknown. 

The pregnancy status of the admission is recorded as yes or no at the time of admission. 

The health insurance status of the admission is specified as one of the following: private health 

insurance; Blue Cross Blue Shield; Medicare; Medicaid; coverage by a health maintenance 

organization; other insurance; no insurance; or unknown. 

The primary source of referral for the admission is recorded as: “individual,” which includes the 

client, a family member, friend, self-referral due to DWI/DUI, or another individual not included in 

other categories; “Alcohol or Drug Abuse (ADA) care provider,” which includes any program, 

clinic, or other health care provider whose activities are related to alcohol or other drug abuse 

prevention or treatment; “other health care provider,” which includes a physician, psychiatrist, 

licensed health care professional, general hospital, psychiatric hospital, mental health program, or 

nursing home; “school,” which includes a school principal, counselor, teacher, a student assistance 

program, the school system, or educational agency; “employer/ employee assistance program 

(EAP),” which includes a supervisor or employee counselor; “other community referral,” which 

includes community and religious organizations, Federal, State, or local agencies that provides aid 

in the areas of poverty relief, unemployment, shelter, or social welfare, self-help groups and defense 

attorneys; and “court/ criminal justice,” which includes any police official, judge, prosecutor, 

probation officer, or other person affiliated with a Federal, State, or county judicial system. 

The service setting is specified as the type of treatment to which the client was admitted. “Hospital 

inpatient detoxification” is a 24 hour per day acute care service in a hospital setting for 

detoxification of persons with severe medical complications associated with withdrawal. 

“Detoxification at a free-standing residential facility” is defined as a 24 hour per day service in nonhospital setting providing for safe withdrawal and transition to ongoing treatment. “Rehabilitation/ 

Residential at a hospital” is defined as 24 hour per day medical care in a hospital facility in 

conjunction with treatment services for alcohol and other drug abuse and dependency. A “shortterm rehabilitation/ residential setting” is defined as typically 30 days or less of non-acute care in a 

setting with treatment services for alcohol and other drug abuse and dependency. A “long-term 

rehabilitation/ residential setting” is defined as typically more than 30 days of non-acute care in a 

setting with treatment services for alcohol and other drug abuse and dependency (this may include 

transitional living situations such as halfway houses). “Intensive outpatient ambulatory care” is 

defined as, at minimum, the client must receive treatment lasting two or more hours per day for 

three or more days per week. The “non-intensive outpatient ambulatory care setting” is defined as a 
82 

setting where ambulatory treatment services include individual, family, and/or group services (these 

may include pharmacological therapies). Finally, the “ambulatory detoxification setting” is defined 

as a setting where outpatient treatment services (pharmacological or non-pharmacological) are 

delivered. 

The types of services variable specifies the services that the admission will receive during 

treatment including: ambulatory health care services; detoxification services; and 

rehabilitation/residential services. 

 

Methadone use (planned as part of treatment) is a variable that specifies whether methadone is 

planned as part of the client’s treatment. 

The number of prior treatment episodes indicates the number of previous treatment episodes the 

client has received in any drug or alcohol program. Categories include: no prior treatment episodes; 

1 – 2 treatment episodes; 3 or more treatment episodes; or unknown. 

The expected source of payment for the treatment episode is specified as one of the following 

(whether it is the expected or actual source of payment): other government payments; self-pay; 

Medicaid; Blue Cross Blue Shield and other health insurance; no charge; Medicare/ Workman’s 

Compensation; other; and unknown. For this variable, states operating under a split payment fee 

arrangement between multiple payment sources must default to the payment source with the largest 

percentage; if the payment percentages are equal, the state can choose either source. 47

The primary substance of abuse at the time of admission is defined as one of the following: 

alcohol; marijuana; cocaine; heroin; other opiates or synthetics (which includes codeine, Dilaudid, 

morphine, Demerol, opium, oxycodone, and any other drug with morphine-like effects); 

methamphetamine or other stimulants (which includes non-amphetamine stimulants); other 

substances; tranquilizers; sedatives; and inhalants. 

The substance of abuse as one major reason for admission can be the following: alcohol; 

marijuana; cocaine; heroin; other opiates or synthetics (which includes codeine, Dilaudid, 

morphine, Demerol, opium, oxycodone, and any other drug with morphine-like effects); 

methamphetamine or other stimulants (which includes non-amphetamine stimulants); other 

substances; tranquilizers; sedatives; and inhalants. TEDS reports different types of substances as 

the primary, secondary, or tertiary substance of abuse at the time of admission. If the substance was 

mentioned as either the primary, secondary, or tertiary substance of abuse at the time of admission, 

this substance was then regarded as one major reason for admission into substance abuse treatment. 

The presence of psychological problems indicates whether there is a psychological problem 

present in addition to an alcohol or drug problem upon admission. 

The presence of mood disorders was derived from either the third edition revised or the fourth 

edition of the American Psychiatric Association's Diagnostic and Statistical Manual of Mental 

Disorders. This variable tells whether a mood disorder was present upon admission in addition to 

an alcohol or drug problem. However, due to reporting issues related to different types of drug 

abuse and dependence, the absence of a mood disorder in the data record upon admission may not 

necessarily mean the actual absence of mood disorder. 
83 

3.2.4 Limitations of the TEDS Series 

There are several limitations with respect to using TEDS to explore substance abuse treatment 

issues in Appalachian counties as compared to other counties nationally. One critical limitation is 

that TEDS does not capture all of the substance abuse treatment facilities in the U.S., and the scope 

of facilities included differs from state to state. Facilities reporting into TEDS are generally those 

that receive State substance abuse treatment funds, including Federal Block Grant funds. To be 

included in TEDS, facilities must be licensed through the state substance abuse treatment agency. 

As a result, private-for-profit facilities, hospitals, and state correctional facilities may be excluded 

from TEDS. In addition, TEDS does not include data from facilities operated by Federal agencies. 

Finally, states have different certification and accreditation requirements and different state systems 

of licensure which may contribute to the exclusion of certain facilities. 

The unit of measure in TEDS is the initial admission to treatment. Therefore, TEDS data may 

reflect multiple admissions for the same client in the same state or treatment site. In addition, one 

client could account for multiple admissions at multiple treatment sites in one state.48 Another 

limitation is that states may vary in how they define an admission; thus, the absolute number of 

admissions may not be a valid measure for comparing states. 

Next, public funding is a key external factor that affects the client mix at substance abuse programs. 

States that have more public funding may be able to accept more economically disadvantaged 

populations than states with limited public funding. In addition, public funding may also cause 

states to focus on a particular subset of the population, like pregnant women, for example. 

Different criminal justice practices at the state level may affect the manner in which clients are 

referred to admission. 

Another limitation to note is that there is a delay in the availability of the entire national TEDS data 

set for publication.49 Results for each calendar year may be incomplete, and states can revise or 

replace historical data files. In addition, since states rely on substance abuse facilities to report the 

data, completeness may vary on a state by state basis.50 Finally, direct identifiers have been 

removed in the TEDS public use file and disclosure analysis has been applied to remove the 

uniqueness of individual records within a file to prevent the identification of any individual.51 It is 

not possible to link variables between the TEDS and National Survey of Substance Abuse 

Treatment Services (N-SSATS) public-use files. 

3.3 Methods 

3.3.1 Study Sample 

The data used for this study were pooled data for 2000-2004 provided under a data use agreement 

with the Office of Applied Study (OAS) of the Substance Abuse and Mental Health Services 

Administration (SAMHSA). The data were provided by SAMHSA contractor, Synectics for 

Management Decisions, Inc. Only admissions in the 410 Appalachian counties were included in the 

data. Data are entered based on county of admission rather than county of residence. Overall, 12 of 

the 13 Appalachian states were included in the data. The only state which was missing was West 

Virginia. Among the 410 Appalachian counties, 195 counties were in the pooled 2000-2004 TEDS 
84 

data set, comprising 511,217 total admissions to treatment for abuse of alcohol and drugs in 

facilities that report to individual State administrative data systems. 

3.3.2 Statistical Methods 

We use cross-tabulations to examine differences of admissions to substance abuse treatment within 

the Appalachian region. Various aspects of the admissions are analyzed including: 

Demographic information; 

Primary, secondary, and tertiary substances; 

Source of referral to treatment; 

Number of prior treatment episodes; and 

Service type, including planned use of methadone. 

These are examined across admission subgroups based on Appalachian geographic sub-regions 

(Northern, Central, and Southern) and the economic development level of the counties where the 

admissions took place, as defined by the Appalachian Regional Commission (ARC). 

ARC uses a county economic classification system to target counties in need of special economic 

assistance. The system classifies counties into five economic status designations—distressed, atrisk, transitional, competitive, and attainment—based on a comparison of county and national 

averages for three economic indicators: three-year average unemployment rate; per capita market 

income; and poverty rate. The economic status designations change from year to year. Among the 

511,217 admissions analyzed, 48,684 (9.5%) were from the “Distressed” counties; 30,356 (5.9%) 

were from the “At-risk” counties; 6311,644 (61%) were from the “Transitional” counties; 67,383 

(13.2%) were from the “Competitive” counties; and 53,150 (10.4%) were from the “Attainment” 

counties. In terms of geographic locations, about half (N=254,675, 49.8%) were in the Northern 

Appalachia, about two-fifths (N=195,289, 38.2%) were from the Southern Appalachia, and slightly 

more than one-tenth (N=61,253, 12.0%) were from the Central Appalachia.

3.4 Results 

In Section 3.4, we present comparisons in admissions to substance abuse treatment within subsets of 

Appalachian counties defined by geographic sub-region (northern, central and southern) and 

economic status (distressed, at-risk, transitional, competitive, and attainment). 

Data are presented in a series of tables that show differences in admissions by demographic factors 

such as gender, race, education, and age; employment status, marital status, and pregnancy status 

upon admission; health insurance and primary source of referral; service setting; types of services 

and whether methadone was prescribed during treatment; number of prior treatment episodes and 

expected source of payment; substances abused as primary reason for admission; substances abused 

as one major reason for admission; and presence of psychological problems and mood disorders. 

After presenting the tables, we provide a series of figures that discuss trends in primary substance of 

abuse at admission. Finally, we provide a number of maps which offer a visual representation of 

our findings across sub-regions in Appalachia. 
85 

3.4.1 Tables 

Table 3.1 below demonstrates differences in admissions by economic status and sub-region across 

demographic variables. Approximately 69% of admissions in Appalachia are male, while only 

about 31% are female. This finding is consistent across economic status levels and sub-regions. 

Overall, about 83% of admissions were white, 15% were black, and 1.8% were defined as being of 

a race other than white or black. The “other” category includes the following races: Alaskan 

Native; American Indian; and Asian or Pacific Islander. The percentage of admissions that are white 

is the highest in distressed counties and in the central sub-region of Appalachia, while it is the 

lowest in attainment counties and the southern sub-region. In contrast, the percentage of admissions 

that are black or of another race is the lowest in distressed counties and the highest in attainment 

counties. Approximately 23% of admissions in the southern sub-region of Appalachia are black, a 

stark contrast to the 3% of admissions that are black in the central sub-region. 

In terms of educational attainment, overall, approximately 45% of clients admitted to treatment in 

Appalachia have a high school education, 36% have less than a high school education, and 19% 

have more than a high school education. Educational status tends to correspond with county 

economic status. Admissions with more than a high school education are higher in attainment 

counties versus distressed counties (22% versus 14%), while admissions with less than a high 

school education are higher in distressed counties versus attainment counties (48% versus 35%). 

Overall, 49% of admissions in the northern region have a high school education, followed by 41% 

of admissions in the southern region, and 38% in the central region. Admissions with a high school 

education comprise the greatest proportion of those receiving treatment in the northern and southern 

regions (49% and 41%), while admissions with less than a high school education comprise the 

greatest proportion of those receiving treatment in the central region (47%). 

In terms of age, overall, about 29% of admitted clients are between 35 and 44 years of age, followed 

by 28% in the 25 to 34 age bracket, 22% in the 18 to 24 age bracket, 16% age 45 and older, and 4% 

age 17 and younger. By economic status, the majority of those admitted to treatment from 

distressed and at-risk counties are between the ages of 25 to 34, whereas the majority of those 

admitted in transitional, competitive, or attainment counties are between the ages of 35 to 44. 

Approximately 29% of admissions in the northern sub-region and 31% of admissions in the 

southern sub-region are between 35 and 44 years of age; the majority of admissions in the central 

region are between the ages of 25 and 34. 
86 

Table 3.1: Sub-regional Differences of Admissions to Substance Abuse Treatment in the Appalachian Region, 

All Economic Level 

Distressed At-Risk Transitional Competitive Attainment Northern 

N % N % N % N % N % N % N % 

Gender Male 300,926 69.26 20,916 68.33 17,327 70.90 190,213 69.43 41,974 69.23 30,496 68.01 163,159 70.18 Female 133,555 30.74 9,693 31.67 7,113 29.10 83,742 30.57 18,660 30.77 14,347 31.99 69,342 29.82 All 434,481 100.00 30,609 100.00 24,440 100.00 273,955 100.00 60,634 100.00 44,843 100.00 232,501 100.00 Race White 360,881 83.06 29,533 96.48 22,126 90.53 230,175 84.02 49,454 81.56 29,593 65.99 199,792 85.93 Black 65,794 15.14 877 2.87 2,171 8.88 38,792 14.16 10,033 16.55 13,921 31.04 27,823 11.97 Other 7,806 1.80 199 0.65 143 0.59 4,988 1.82 1,147 1.89 1,329 2.96 4,886 2.10 All 434,481 100.00 30,609 100.00 24,440 100.00 273,955 100.00 60,634 100.00 44,843 100.00 232,501 100.00 Education Less than High School 

156,520 36.02 14,578 47.63 10,233 41.87 93,403 34.09 22,777 37.56 15,529 34.63 72,349 31.12 

High School 197,059 45.36 11,606 37.92 10,009 40.95 129,374 47.22 26,624 43.91 19,446 43.36 114,968 49.45 More than High School 

80,902 18.62 4,425 14.46 4,198 17.18 51,178 18.68 11,233 18.53 9,868 22.01 45,184 19.43 

All 434,481 100.00 30,609 100.00 24,440 100.00 273,955 100.00 60,634 100.00 44,843 100.00 232,501 100.00 Age 17 or younger 18,641 4.29 1,328 4.34 1,922 7.86 12,387 4.52 1,394 2.30 1,610 3.59 11,093 4.77 18-24 95,942 22.08 6,690 21.86 5,771 23.61 64,437 23.52 11,430 18.85 7,614 16.98 56,450 24.28 25-34 121,637 28.00 9,088 29.69 6,790 27.78 76,637 27.97 16,495 27.20 12,627 28.16 61,951 26.65 35-44 127,511 29.35 8,521 27.84 6,375 26.08 78,200 28.54 19,756 32.58 14,659 32.69 67,043 28.84 45 or older 70,750 16.28 4,982 16.28 3,582 14.66 42,294 15.44 11,559 19.06 8,333 18.58 35,964 15.47 All 434,481 100.00 30,609 100.00 24,440 100.00 273,955 100.00 60,634 100.00 44,843 100.00 232,501 100.00 Source: Treatment Episode Data Set (TEDS) 2000-2004. Office of Applied Studies, Substance Abuse and Mental Health Services Adminis
87 

Table 3.2 below demonstrates differences in admissions by economic status and sub-region for 

employment status, marital status, and pregnancy status upon admission. Overall, approximately 

33% of admissions are unemployed, meaning that they have been looking for work during the past 

30 days or a homemaker, student, disabled, retired, or an inmate of an institution. About 28% are 

not in the labor force, 24% work full time (35 hours or more each week), and 6% work part time 

(fewer than 35 hours each week). 

Approximately 19% of admissions in distressed counties work full time as compared to more than 

25% of admissions in attainment counties. In the northern and southern sub-regions, about 25% of 

admissions are full time workers, as compared to slightly less than 20% in the central sub-region. 

About 36% of admissions in at-risk counties and 35% in transitional counties are unemployed. 

Surprisingly, approximately 36% of admissions in attainment counties are unemployed. In the 

northern sub-region, about 40% of admissions are unemployed, while only about 25% of 

admissions are unemployed in the central and southern sub-regions. About 40% of admissions in 

distressed counties are not in the labor force while only 16% of admissions in attainment counties 

are not in the labor force. 

In terms of marital status, overall, 49% of admissions have never been married, 20% are divorced or 

widowed, 18% are now married, 8% are separated, and 5% are unknown. The majority of 

admissions in transitional (51%) and attainment counties (54%) have never been married. Across 

the sub-regions, 56% of admissions in the northern region have never been married, followed by 

43% of admissions in the southern region, and 29% of admissions in the central region. In 

distressed counties, 22% of admissions are divorced/widowed, slightly more than the 21% in 

competitive counties and 20% in attainment counties. 

Overall, less than 1% of clients were pregnant at the time of admission. Slightly more than 1% of 

admissions were pregnant in distressed, competitive, and attainment counties. Only 0.66% of 

admissions were pregnant in at-risk counties. Across the Appalachian region, 1.25% of admissions 

were pregnant in the southern sub-region, followed by 0.79% in the central sub-region and 0.74% in 

the northern sub-region. 
88 

Table 3.2: Sub-regional Differences of Admissions to Substance Abuse Treatment in the Appalachian RegionMarital Status, and Pregnancy Status 

All Economic Level 

Distressed At-Risk Transitional Competitive Attainment Northern 

N % N % N % N % N % N % N % 

Employment Status Full-timea 106,250 24.45 5,884 19.22 5,689 23.28 68,213 24.90 14,761 24.34 11,703 26.10 58,529 25Part-timeb 25,303 5.82 1,936 6.32 1,600 6.55 16,143 5.89 3,061 5.05 2,563 5.72 14,777 6.3Unemployedc 141,577 32.59 8,282 27.06 8,695 35.58 94,701 34.57 13,704 22.60 16,195 36.11 90,502 38Not in labor force 122,112 28.11 12,407 40.53 7,963 32.58 77,203 28.18 17,532 28.91 7,007 15.63 66,231 28Unknown 39,239 9.03 2,100 6.86 493 2.02 17,695 6.46 11,576 19.09 7,375 16.45 2,462 1.0All 434,481 100.00 30,609 100.00 24,440 100.00 273,955 100.00 60,634 100.00 44,843 100.00 232,501 100Marital Status Never married 211,320 48.64 11,208 36.62 9,426 38.57 140,348 51.23 26,296 43.37 24,042 53.61 130,304 56Now married 78,710 18.12 7,538 24.63 3,993 16.34 48,734 17.79 10,853 17.90 7,592 16.93 37,467 16Separated 35,042 8.07 2,494 8.15 1,193 4.88 22,966 8.38 4,398 7.25 3,991 8.90 15,880 6.8Divorced/widowed 85,752 19.74 6,778 22.14 4,005 16.39 53,021 19.35 12,804 21.12 9,144 20.39 39,755 17Unknown 23,657 5.44 2,591 8.46 5,823 23.83 8,886 3.24 6,283 10.36 74 0.17 9,095 3.9All 434,481 100.00 30,609 100.00 24,440 100.00 273,955 100.00 60,634 100.00 44,843 100.00 232,501 100Pregnant At Admission Yes 4,054 0.93 336 1.10 162 0.66 2,390 0.87 704 1.16 462 1.03 1,709 0.7No 125,745 28.94 8,993 29.38 5,665 23.18 80,486 29.38 16,719 27.57 13,882 30.96 66,074 28Not applicable 300,929 69.26 20,916 68.33 17,327 70.90 190,214 69.43 41,975 69.23 30,497 68.01 163,159 70Unknown 3,753 0.86 364 1.19 1,286 5.26 865 0.32 1,236 2.04 2 0.00 1,559 0.6All 434,481 100.00 30,609 100.00 24,440 100.00 273,955 100.00 60,634 100.00 44,843 100.00 232,501 100a Working 35 hours or more each week; includes members of the uniformed services. b Working fewer than 35 hours each week. c Looking for work during the past 30 days or a homemaker, student, disabled, retired, or an inmate of an institution. Source: Treatment Episode Data Set (TEDS) 2000-2004. Office of Applied Studies, Substance Abuse and Mental Health Services Administration.
89 

In Table 3.3, we provide differences in health insurance for admissions across economic status 

levels and sub-regions in Appalachia. The variable, health insurance, specifies the type of insurance 

a client possesses, if any. However, the insurance may or may not cover the alcohol or drug 

treatment. Overall, approximately 8% of admissions have Medicaid, 5% have private insurance 

(other than Blue Cross/ Blue Shield insurance or a health maintenance organization (HMO)), 3% 

have Blue Cross/ Blue Shield insurance, 2% are covered by an HMO, and less than 1% have 

Medicare. About 10.75% of admissions have some other type of insurance. Almost a quarter of 

admissions were uninsured and insurance status was unknown for 47% of admissions. 

While only 3% of admissions in distressed counties were uninsured, 39% of admissions were 

uninsured in attainment counties. Private insurance was most common for admissions in distressed 

counties (13%) and least common in attainment counties (3%). Medicaid was most common for 

admissions in transitional counties (8%). Medicare was most common among admissions in 

competitive (0.92%) and attainment counties (0.96%), as compared to distressed, at-risk, and 

transitional counties. 

Looking across the Appalachian region, more than a quarter of admissions in the northern and 

southern sub-regions had no insurance. In the central sub-region, 45% admissions had some other 

type of health insurance, followed by 15% of admissions with private insurance. About 2% of 

admissions in the central sub-region reported Medicare as their insurer, as compared to less than 1% 

of admissions in the northern and southern sub-regions. About 10% of admissions in the northern 

sub-region were on Medicaid, followed by 7% of admissions in the central sub-region and 5% in the 

southern sub-region. 

Next, we explore the primary source of referral – the person or agency referring the client to the 

alcohol or drug abuse treatment program. Overall, 37% of admissions were referred by the court or 

criminal justice system. This includes referrals from those affiliated with a Federal, State, or county 

judicial system, and referrals from DWI/DUI court. Clients referred in lieu of or for deferred 

prosecution, during pretrial release, or prior to or following official adjudication are also included. 

Finally, this figure also includes admissions on pre-parole, pre-release, work or home furlough, or 

in Treatment Alternatives for Safe Communities (TASC) programs. Next, about 23% of admissions 

were referred from an individual, which includes the client, a family member, friend, self-referral 

due to DWI/DUI, or other. 

About 16% of admissions were from an alcohol/drug abuse (ADA) care provider, which includes 

any program, clinic, or other health care provider whose activities are related to alcohol or other 

drug abuse prevention, or treatment. About 10% of admissions were described as being referred by 

“other community referral,” which includes community and religious organizations or any Federal, 

State, or local agency that provides assistance in the areas of poverty relief, unemployment, shelter, 

or social welfare. This 10% also includes self-help groups such as Alcoholics Anonymous (AA), 

Al-Anon, and Narcotics Anonymous (NA), and defense attorneys. Another 10% of admissions 

were described as being referred by “other health care provider,” including a physician, psychiatrist, 

other licensed health care professional, general hospital, psychiatric hospital, mental health 

program, or nursing home. Slightly more than 1% were referred by someone at school, such as a 

school principal, counselor, teacher or from a student assistance program (SAP), the school system, 

or educational agency. Finally, slightly less than 1% of people were referred by an employer or 

employee counselor. 
90 

The court/criminal justice system was the common primary source of referral across all counties, 

regardless of economic status. Slightly less than 50% of admissions in distressed counties and 

slightly more than 50% of admissions in at-risk counties were referred by court/criminal justice 

systems. Referrals by court/criminal justice systems were lower in transitional (36%), competitive 

(32%), and attainment counties (27%). 

Across sub-regions, the court/criminal justice system is the most common primary source of referral 

with the employer/ employee assistance program (EAP) being the least common. Around 31% of 

admissions in both the central and sub-regions were referred by an individual. 
91 

Table 3.3: Sub-regional Differences of Admissions to Substance Abuse Treatment in the Appalachian RegionSource of Referral

All Economic Level 

Distressed At-Risk Transitional Competitive Attainment Northern 

N % N % N % N % N % N % N % 

Health Insurance Private 20,987 4.83 3,901 12.74 1,152 4.71 12,131 4.43 2,438 4.02 1,365 3.04 10,223 4.40 BC/BS 13,059 3.01 238 0.78 75 0.31 10,483 3.83 904 1.49 1,359 3.03 10,363 4.46 Medicare/ Other 3,314 0.76 773 2.53 80 0.33 1,474 0.54 557 0.92 430 0.96 1,228 0.53 Medicaid 33,551 7.72 2,152 7.03 755 3.09 24,108 8.80 3,313 5.46 3,223 7.19 22,979 9.88 HMO 6,896 1.59 . . 951 3.89 3,314 1.21 1,297 2.14 1,334 2.97 5,970 2.57 Other 46,758 10.76 13,322 43.52 832 3.40 26,717 9.75 1,699 2.80 4,188 9.34 25,662 11.04 None 104,132 23.97 1,000 3.27 2,566 10.50 63,920 23.33 19,179 31.63 17,467 38.95 61,124 26.29 Unknown 205,784 47.36 9,223 30.13 18,029 73.77 131,808 48.11 31,247 51.53 15,477 34.51 94,952 40.84 All 434,481 100.00 30,609 100.00 24,440 100.00 273,955 100.00 60,634 100.00 44,843 100.00 232,501 100.00 Primary Source of Referral Individual a 103,634 23.85 8,471 27.67 4,733 19.37 56,684 20.69 16,957 27.97 16,789 37.44 40,646 17.48 ADA care provider b

70,727 16.28 512 1.67 2,772 11.34 57,141 20.86 7,084 11.68 3,218 7.18 62,904 27.06 

Other health care provider c

42,165 9.70 3,042 9.94 2,176 8.90 21,741 7.94 8,503 14.02 6,703 14.95 12,560 5.40 

School d 4,585 1.06 479 1.56 468 1.91 3,017 1.10 322 0.53 299 0.67 2,434 1.05 Employer/EAP e 3,650 0.84 186 0.61 145 0.59 2,663 0.97 451 0.74 205 0.46 2,277 0.98 Other community referral f

43,194 9.94 2,786 9.10 1,473 6.03 28,721 10.48 6,223 10.26 3,991 8.90 26,689 11.48 

Court/criminal justice g

158,826 36.56 14,710 48.06 12,533 51.28 99,410 36.29 19,646 32.40 12,527 27.94 83,859 36.07 

Unknown 7,700 1.77 423 1.38 140 0.57 4,578 1.67 1,448 2.39 1,111 2.48 1,132 0.49 All 434,481 100.00 30,609 100.00 24,440 100.00 273,955 100.00 60,634 100.00 44,843 100.00 232,501 100.00 a Includes the client, a family member, friend, self-referral due to DWU/DUI, or another individual not included in other categories; b Any program, clinic, or other health care provider whose activitiprevention, or treatment; c A physician, psychiatrist, licensed health care professional, general hospital, psychiatric hospital, mental health program, or nursing home; d A school principal, counselor, school system, or educational agency; e A supervisor or employee counselor; f Community and religious organizations or any Federal, State, or local agency that provides aid in the areas of poverty reSelf-help groups and defense attorneys are included; g Any police official, judge, prosecutor, probation officer, or other person affiliated with a Federal, State, or county judicial system. Source: Treatment Episode Data Set (TEDS) 2000-2004. Office of Applied Studies, Substance Abuse and Mental Health Services Administration.
92 

In Table 3.4, we provide sub-regional differences to substance abuse treatment in the Appalachian 

region by service setting. First, we explore the type of treatment into which the client was admitted. 

Overall, approximately 13% of admissions were for detoxification services in a 24-hour per day, 

non-hospital setting that provides safe withdrawal and transition to ongoing treatment. Only about 

2% of admissions were into 24-hour per day acute care services in a hospital setting for 

detoxification of persons with severe medical complications associated with withdrawal. 

About 0.2% of admissions were for 24-hour per day medical care (but not detoxification services) 

in a hospital facility in conjunction with treatment services for alcohol and other drug abuse and 

dependency. About 10% of admissions were into a short-term (typically for 30 days or less) nonacute care setting with treatment services for alcohol and other drug abuse and dependency. 

Slightly less than 5% of admissions were for long-term non-acute care (more than 30 days) in a 

setting with treatment services for alcohol, drug abuse and dependency (this figure may also include 

transitional living situations such as halfway houses, etc.). 

In the ambulatory care setting, about 15% of admissions were into an intensive outpatient setting 

where at a minimum the client must receive treatment for two or more hours per day for three or 

more days per week. About 57% of admissions were into the non-intensive outpatient ambulatory 

care setting; such admissions were for services including individual, family and/or group services 

and pharmacological therapies. Only about 0.10% of admissions were for outpatient treatment 

services providing detoxification in the ambulatory care setting (both pharmacological and nonpharmacological). 

Admissions for inpatient detoxification tend to be in the competitive (2.92%) and attainment 

counties (2.15%) rather than the at-risk (0.01%) and transitional counties (0.71%). About 24% of 

admissions to free-standing residential facilities were in competitive counties and 16% in attainment 

counties. Admissions for short-term detoxification in a rehabilitation/residential setting were 

highest in at-risk (11%) and transitional counties (13%). Admissions to a long-term non-acute care 

setting were highest in competitive and attainment counties (approximately 5% for both). 91% of 

admissions to non-intensive outpatient ambulatory care were in distressed counties. 

Across the sub-regions, the majority of admissions in the northern (61%) and central sub-regions 

(80%) were to non-intensive outpatient care settings. Admissions to a short-term or long-term 

rehabilitation/ residential care setting were much higher in the northern region (15%) than in the 

central and southern sub-regions (3% for both). Admissions to a free-standing residential setting 

were highest in the southern sub-region (16%), followed by the central (15%) and northern subregions (10%), respectively. 
93 

Table 3.4: Sub-regional Differences of Admissions to Substance Abuse Treatment in the Appalachian Region, 

All Economic Level 

Distressed At-Risk Transitional Competitive Attainment Northern 

N % N % N % N % N % N % N % 

Service Setting Detoxification Hospital Inpatient a

4,672 1.08 . . 3 0.01 1,932 0.71 1,771 2.92 966 2.15 3,916 1.68 

Free-standing Residential b 55,267 12.72 616 2.01 3,210 13.13 29,533 10.78 14,712 24.26 7,196 16.05 23,830 10.25 Rehabilitation/ Residential  Hospital c 663 0.15 . . . . 651 0.24 3 0.00 9 0.02 252 0.11  Short d 42,296 9.73 401 1.31 2,621 10.72 34,564 12.62 2,693 4.44 2,017 4.50 35,783 15.39  Long e 19,059 4.39 754 2.46 441 1.80 12,694 4.63 2,849 4.70 2,321 5.18 15,455 6.65 Ambulatory Intensive outpatient f

65,593 15.10 756 2.47 7,129 29.17 46,820 17.09 5,897 9.73 4,991 11.13 11,102 4.78 

Non-intensive Outpatient g 246,517 56.74 28,082 91.74 11,028 45.12 147,492 53.84 32,679 53.90 27,236 60.74 142,019 61.08 Detoxification h 414 0.10 . . 8 0.03 269 0.10 30 0.05 107 0.24 144 0.06 All 434,481 100.00 30,609 100.0 24,440 100.00 273,955 100.00 60,634 100.00 44,843 100.00 232,501 100.00 NOTES a 24 hour per day acute care services in a hospital setting for detoxification of persons with severe medical complications associated with withdrawal. b 24 hour per day services in non-hospital setting providing for safe withdrawal and transition to ongoing treatment. c 24 hour per day medical care in a hospital facility in conjunction with treatment services for alcohol and other drug abuse and dependency. d Typically 30 days or less of non-acute care in a setting with treatment services for alcohol and other drug abuse and dependency. e Typically more than 30 days of non-acute care in a setting with treatment services for alcohol and other drug abuse and dependency; this may include transitional living sucf At minimum, the client must receive treatment lasting two or more hours per day for three or more days per week. g Ambulatory treatment services including individual, family, and/or group services; these may include pharmacological therapies. h Outpatient treatment services providing for safe withdrawal in an ambulatory setting (pharmacological or non-pharmacological). Source: Treatment Episode Data Set (TEDS) 2000-2004. Office of Applied Studies, Substance Abuse and Mental Health Services Administration.
94 

In Table 3.5, we provide sub-regional differences to substance abuse treatment in the Appalachian 

region by types of service and methadone use. Overall, approximately 72% of admissions received 

ambulatory care services, 14% received rehabilitational services, and 14% received detoxification 

services. 94% of admissions in distressed counties received ambulatory care services. The majority of 

at-risk, transitional, competitive, and attainment counties also received ambulatory care services. This 

finding was consistent across sub-regions as well. Admissions for detoxification services were most 

common in competitive counties (27%) and least common in distressed counties (2%). Rehabilitation 

and residential services were most common for admissions in at-risk (13%) and transitional counties 

(17%); these services were also five times more common in the northern region than in the central 

region, and four times more common in the northern region than in the southern region. 

Next, we look at methadone use. Overall, methadone was specified as part of treatment for 

approximately 1.2% of admissions. For competitive and attainment counties, the percentages are 

larger, at 3% and 5% of admissions, respectively. Distressed counties are fairly consistent with the 

average across all Appalachian counties, at 1.44% of admissions. Methadone was specified as part of 

the treatment plan for less than 1% of admissions in at-risk counties and less than half a percent of 

admissions in transitional counties. Across Appalachia, methadone use was specified as part of the 

treatment plan for between 1 and 1.5% of admissions, with the smallest percentage of admissions in 

the northern sub-region and the greatest percentage of admissions in the southern sub-region. 
95 

Table 3.5: Sub-regional Differences of Admissions to Substance Abuse Treatment in the Appalachian Regioand Methadone Use As Part of Treatment 

All Economic Level 

Distressed At-Risk Transitional Competitive Attainment Northern 

N % N % N % N % N % N % N % 

Types of Services Ambulatory 312,524 71.93 28,838 94.21 18,165 74.32 194,581 71.03 38,606 63.67 32,334 72.10 153,265 65.92 Detoxification 59,939 13.80 616 2.01 3,213 13.15 31,465 11.49 16,483 27.18 8,162 18.20 27,746 11.93 Rehabilitation/ Residential 

62,018 14.27 1,155 3.77 3,062 12.53 47,909 17.49 5,545 9.15 4,347 9.69 51,490 22.15 

All 434,481 100.00 30,609 100.00 24,440 100.00 273,955 100.00 60,634 100.00 44,843 100.00 232,501 100.00 Methadone Use Yes 5,308 1.22 444 1.45 176 0.72 619 0.23 1,845 3.04 2,224 4.96 2,413 1.04 No 400,729 92.23 26,889 87.85 18,386 75.23 257,678 94.06 57,690 95.14 40,086 89.39 230,063 98.95 Unknown 28,444 6.55 3,276 10.70 5,878 24.05 15,658 5.72 1,099 1.81 2,533 5.65 25 0.01 All 434,481 100.00 30,609 100.00 24,440 100.00 273,955 100.00 60,634 100.00 44,843 100.00 232,501 100.00 Source: Treatment Episode Data Set (TEDS) 2000-2004. Office of Applied Studies, Substance Abuse and Mental Health Services Administration.
96 

Table 3.6 focuses on sub-regional differences in the number of previous treatment episodes that admissions 

received in any drug or alcohol program as well as the primary source of expected/ actual payment for this 

treatment episode. Overall, in Appalachia, approximately 37% of admissions had no prior treatment 

episodes in a drug or alcohol program, 30% had 1 or 2 prior treatments, and 18% had 3 or more prior 

treatments. The previous treatment for about 15% of admissions was unknown. This distribution is 

consistent across Appalachia regardless of county economic status with the exception of distressed counties. 

In distressed counties, we see that the majority of admissions had no prior treatment episodes and only 8% of 

admissions had three or more treatment episodes. 

Looking across geographic sub-regions, we see that 67% of admissions in the central sub-region had no prior 

treatment episodes, followed by the northern (37%) and southern sub-regions (30%), respectively. About 

26% of admissions with three or more treatment episodes are into programs in the northern sub-region, as 

opposed to the southern (9%) and central (7%) sub-regions. 

Next, we review our findings for the primary source of payment (expected/actual) for the treatment episode. 

Note that for this variable, states operating under a split payment fee arrangement between multiple payment 

sources must default to the payment source with the largest percentage; if the payment percentages are equal, 

the state can choose either source.52 In Table 3.6, we see that overall, the primary source of payment is 

unknown for almost 30% of admissions. Other government payments are the primary source of payment for 

about 22% of admissions, followed by self-pay (20%), Medicaid (10%), other (8%), Blue Cross Blue Shield 

and other health insurance (7%), no charge (3%), and Medicare/ Workman’s Compensation (1%). 

The primary payer in distressed counties is other government payments for about 35% of admissions, while 

in attainment counties approximately 40% of admissions are self-pay. No charge admissions are more 

common in distressed (5%) and at-risk counties (6%) than in competitive (0.19%) and attainment counties 

(0.36%). Across the sub-regions, we see that 40% of admissions are self-pay in the southern sub-region as 

opposed to 16% of admissions in the northern and 6% in the central sub-regions. The primary source of 

payment for about 11% of admissions in the northern sub-region is Blue Cross Blue Shield and other types 

of health insurance, compared to slightly more than 2% of admissions in the southern sub-region and 0.17% 

of admissions in the central sub-region. 
97 

Table 3.6: Sub-regional Differences of Admissions to Substance Abuse Treatment in the Appalachian RegioEpisodes and Expected Source of Payment 

All Economic Level 

Distressed At-Risk Transitional Competitive Attainment Northern 

N % N % N % N % N % N % N % 

Number of Prior Treatment Episodes No prior treatment 

161,910 37.27 19,139 62.53 8,473 34.67 99,789 36.43 18,550 30.59 15,959 35.59 86,631 37.26 

1-2 prior treatments 

129,057 29.70 7,781 25.42 7,856 32.14 86,226 31.47 15,803 26.06 11,391 25.40 78,866 33.92 

3 or more treatments 

77,473 17.83 2,446 7.99 3,860 15.79 56,369 20.58 8,989 14.83 5,809 12.95 59,647 25.65 

Unknown 66,041 15.20 1,243 4.06 4,251 17.39 31,571 11.52 17,292 28.52 11,684 26.06 7,357 3.16 All 434,481 100.00 30,609 100.00 24,440 100.00 273,955 100.00 60,634 100.00 44,843 100.00 232,501 100.00 Expected Source of Payment Self pay 84,876 19.54 3,463 11.31 6,222 25.46 40,154 14.66 17,003 28.04 18,034 40.22 14,266 6.14 BC/BS/ Other health insurance 

30,423 7.00 720 2.35 519 2.12 25,374 9.26 1,882 3.10 1,928 4.30 26,618 11.45 

Medicare/Workman’s Comp 

3,280 0.75 929 3.04 109 0.45 1,593 0.58 409 0.67 240 0.54 1,250 0.54 

Medicaid 43,738 10.07 4,854 15.86 1,753 7.17 29,734 10.85 2,895 4.77 4,502 10.04 31,215 13.43 Other government payments1

92,343 21.25 10,795 35.27 2,474 10.12 68,489 25.00 6,737 11.11 3,848 8.58 53,040 22.81 

No charge 12,992 2.99 1,556 5.08 1,558 6.37 9,604 3.51 114 0.19 160 0.36 12,255 5.27 Other 32,814 7.55 5,601 18.30 927 3.79 20,920 7.64 1,641 2.71 3,725 8.31 21,949 9.44 Unknown 134,015 30.84 2,691 879 10,878 44.51 78,087 28.50 29,953 49.40 12,406 27.67 71,908 30.93 All 434,481 100.00 30,609 100.00 24,440 100.00 273,955 100.00 60,634 100.00 44,843 100.00 232,501 100.00 1 Progams other than Medicare and Medicaid. Source: Treatment Episode Data Set (TEDS) 2000-2004. Office of Applied Studies, Substance Abuse and Mental Health Services Administration.
98 

Table 3.7 shows the primary substance of abuse at the time of admission across sub-regions. We 

see that alcohol was the primary substance of abuse at the time of admission for 52% of admissions, 

followed by: marijuana (14%); cocaine (13%); heroin (7%); other opiates or synthetics (6%) which 

includes codeine, Dilaudid, morphine, Demerol, opium, oxycodone, and any other drug with 

morphine-like effects; methamphetamine or other stimulants (3%) which includes nonamphetamine stimulants; other substances (1.50%); tranquilizers (1%); sedatives (0.35%); and 

inhalants (0.12%). 

For 50% or more of admissions, the primary substance of abuse at the time of admission was 

alcohol for all Appalachian counties, across all economic status levels. 

The second most common primary substance of abuse was marijuana for distressed (14%), at-risk 

(16%), and transitional counties (14%), and cocaine for competitive (15%) and attainment counties 

(18%). Across the Appalachian sub-regions, alcohol is the most common primary substance of 

abuse at the time of admission, followed by cocaine in the southern sub-region (16%), other opiates 

and synthetics in the central sub-region (14%), and marijuana in the northern sub-region (13%). 
99 

Table 3.7: Sub-regional Differences of Admissions to Substance Abuse Treatment in the Appalachian RegioReason for Admission 

All Economic Level 

Distressed At-Risk Transitional Competitive Attainment Northern 

N % N % N % N % N % N % N % 

Use as Primary Reason for Admission Alcohol 225,032 51.79 15,221 49.73 12,160 49.75 141,656 51.71 32,864 54.20 23,131 51.58 126,994 54.62 Cocaine/ Crack 56,447 12.99 1,481 4.84 1,826 7.47 36,083 13.17 9,200 15.17 7,857 17.52 27,903 12.00 Marijuana/ Hashish 

62,649 14.42 4,785 15.63 4,081 16.70 39,593 14.45 7,913 13.05 6,277 14.00 31,372 13.49 

Heroin 31,770 7.31 597 1.95 522 2.14 23,723 8.66 3,197 5.27 3,731 8.32 29,439 12.66 Other Opiates or Synthetics1

25,211 5.80 3,068 10.02 2,903 11.88 15,329 5.60 2,319 3.82 1,592 3.55 9,680 4.16 

Methamphetamine/ Other stimulants2

11,496 2.65 352 1.15 1,128 4.62 6,452 2.36 2,839 4.68 725 1.62 1,384 0.60 

Tranquilizers3 4,139 0.95 984 3.21 400 1.64 2,037 0.74 485 0.80 233 0.52 892 0.38 Sedatives4 1,505 0.35 194 0.63 82 0.34 979 0.36 134 0.22 116 0.26 576 0.25 Inhalants5 509 0.12 45 0.15 36 0.15 322 0.12 79 0.13 27 0.06 280 0.12 Other6 6,519 1.50 464 1.52 82 0.34 3,435 1.25 1,451 2.39 1,087 2.42 879 0.38 1 Includes codeine, Dilaudid, morphine, Demerol, opium, oxycodone, and any other drug with morphine-like effects. 2 Includes amphetamines, MDMA, phenmetrazine, and other unspecified amines and related drugs. 3 Includes meprobamate and other non-benzodiazepine tranquilizers. 4 Includes chloral hydrate, ethchlorvynol, glutethimide, methaqualone, and other non-barbiturate sedative or hyphotics. 5 Includes chloroform, ether, gasoline, glue, nitrous oxide, paint thinner, etc. 6 Includes diphenylhydantoin/phenytoin, GHB/GBL, ketamine, etc. Source: Treatment Episode Data Set (TEDS) 2000-2004. Office of Applied Studies, Substance Abuse and Mental Health Services Administration. 
100 

Table 3.8 presents data on “one major reason for admission to substance abuse programs” for 

Appalachia by economic level and sub-region. TEDS reports different types of substances as the 

primary, secondary, or tertiary substance of abuse at the time of admission. If the substance was 

mentioned as either the primary, secondary, or tertiary substance of abuse at the time of admission, 

this substance was then regarded as one major reason for admission into substance abuse treatment. 

We see that, overall, the substances included as one major reason for admission are alcohol (68%), 

followed by: marijuana (36%); cocaine (26%); other opiates or synthetics (10%) which includes 

codeine, Dilaudid, morphine, Demerol, opium, oxycodone, and any other drug with morphine-like 

effects; heroin (9%); methamphetamine or other stimulants (5%) which includes non-amphetamine 

stimulants; tranquilizers (4%); other substances (3%); sedatives (1%); and inhalants (1%). 

Alcohol was most commonly one major reason for admission to substance abuse programs in 

Appalachia, regardless of county economic status. The second substance most commonly cited as 

one major reason for admission was marijuana for all counties, with the exception of attainment 

counties where cocaine was second to alcohol as one major reason for admission. Similarly, 

looking across sub-regions, alcohol was one major reason for admission for almost three-quarters of 

admissions in the northern sub-region, followed by 64% of admissions in the southern sub-region, 

and 59% of admissions in the central sub-region. 
101 

Table 3.8: Sub-regional Differences of Admissions to Substance Abuse Treatment in the Appalachian RegiReason for Admission 

All Economic Level 

Distressed At-Risk Transitional Competitive Attainment Northern 

N % N % N % N % N % N % N % 

Use as One Major Reason for Admission Alcohol 296,266 68.19 19,298 63.05 16,192 66.25 188,032 68.64 42,734 70.48 30,010 66.92 168,726 72.57 Cocaine/ Crack 112,250 25.84 3,501 11.44 3,947 16.15 72,474 26.45 17,668 29.14 14,660 32.69 63,504 27.31 Marijuana/ Hashish 

155,934 35.89 10,516 34.36 9,316 38.12 102,069 37.26 20,492 33.80 13,541 30.20 88,790 38.19 

Heroin 39,309 9.05 862 2.82 729 2.98 28,921 10.56 4,144 6.83 4,653 10.38 35,740 15.37 Other Opiates or Synthetics1

43,412 9.99 4,923 16.08 4,478 18.32 27,359 9.99 3,994 6.59 2,658 5.93 19,192 8.25 

Methamphetamine/ Other stimulants2

20,631 4.75 791 2.58 1,830 7.49 12,426 4.54 4,131 6.81 1,453 3.24 4,335 1.86 

Tranquilizers3 18,186 4.19 3,327 10.87 2,366 9.68 9,445 3.45 1,975 3.26 1,073 2.39 5,032 2.16 Sedatives4 4,801 1.1 448 1.46 293 1.2 3263 1.19 535 0.88 262 0.58 2,879 1.24 Inhalants5 3,833 0.88 316 1.03 247 1.01 2617 0.96 481 0.79 172 0.38 2,584 1.11 Other6 11,250 2.59 848 2.77 201 0.82 6,500 2.37 2,421 3.99 1,280 2.85 2,976 1.28 1 Includes codeine, Dilaudid, morphine, Demerol, opium, oxycodone, and any other drug with morphine-like effects. 2 Includes amphetamines, MDMA, phenmetrazine, and other unspecified amines and related drugs. 3 Includes meprobamate and other non-benzodiazepine tranquilizers. 4 Includes chloral hydrate, ethchlorvynol, glutethimide, methaqualone, and other non-barbiturate sedative or hyphotics. 5 Includes chloroform, ether, gasoline, glue, nitrous oxide, paint thinner, etc. 6 Includes diphenylhydantoin/phenytoin, GHB/GBL, ketamine, etc. Source: Treatment Episode Data Set (TEDS) 2000-2004. Office of Applied Studies, Substance Abuse and Mental Health Services Adm
102 

Table 3.9 shows sub-regional differences for psychological problems or mood disorder upon 

admission. First, we explore whether there is a psychological problem present in addition to an 

alcohol or drug problem upon admission. Approximately 15% of admissions had a psychological 

problem present upon admission. In distressed counties, we see that 36% of admissions had a 

psychological problem, followed by 17% of admissions in attainment counties, 16% in at-risk 

counties, 13% in competitive counties, and 12% in transitional counties. In the central sub-region 

of Appalachia, more than 34% of admissions had a psychological problem, followed by northern 

and southern sub-regions with approximately 13% of admissions. 

The mood disorder variable was derived from either the third edition revised or the fourth edition of 

the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders. 

Our findings show whether a mood disorder was present upon admission in addition to an alcohol 

or drug problem. However, due to mutually-exclusive reporting of different types of drug abuse 

and dependence, the absence of mood disorder upon admission in the data record may not 

necessarily mean the actual absence of mood disorder. Therefore, these should be seen as 

conservative estimates. Overall, approximately 62% of admissions had a mood disorder (substancerelated or non-substance-related) present upon admission. More than 70% of admissions had a 

mood disorder in transition counties, followed by 59% in competitive counties, 47% in attainment 

counties, 53% in at-risk counties, and 35% in distressed counties. In the central sub-region of 

Appalachia, almost 90% of admissions had a mood disorder.
103 

Table 3.9: Sub-regional Differences of Admissions to Substance Abuse Treatment in the Appalachian ReProblem and Mood Disorder Upon Admission 

All Economic Level S

Distressed At-Risk Transitional Competitive Attainment Northern 

N % N % N % N % N % N % N % N 

Psychological Problem Yes 64,018 14.73 11,072 36.17 3,913 16.01 33,573 12.25 7,651 12.62 7,809 17.41 29,503 12.69 13No 190,377 43.82 14,637 47.82 9,980 40.83 101,682 37.12 42,585 70.23 21,493 47.93 54,986 23.65 16Unknown 180,086 41.45 4,900 16.01 10,547 43.15 138,700 50.63 10,398 17.15 15,541 34.66 148,012 63.66 9,0All 434,481 100.00 30,609 100.00 24,440 100.00 273,955 100.00 60,634 100.00 44,843 100.00 232,501 100.00 38Mood Disorder Yes 273,061 62.85 10,998 35.93 13,046 53.38 192,236 70.17 35,715 58.90 21,066 46.98 208,662 89.75 14No 161,420 37.15 19,611 64.07 11,394 46.62 81,719 29.83 24,919 41.10 23,777 53.02 23,839 10.25 24All 434,481 100.00 30,609 100.00 24,440 100.00 273,955 100.00 60,634 100.00 44,843 100.00 232,501 100.00 38Note: Mood disorders represented here are substance-related and non-substance-related. Source: Treatment Episode Data Set (TEDS) 2000-2004. Office of Applied Studies, Substance Abuse and Mental Health Services Administration.
104 

3.4.2. Figures 

Trends in Primary Substance of Abuse in Appalachia and the United States 

This section provides TEDS data on the primary substance of abuse at the time of admission to 

treatment between 2000 and 2004, both in Appalachia and nationally. We provide results for all 

TEDS treatment admissions aged 12 and older for 11 substances: alcohol; marijuana/hashish; 

cocaine; heroin; other opiates/synthetics; phencyclidine (PCP); hallucinogens; amphetamines; 

tranquilizers; sedatives; and inhalants. In Figure 3.1 and Figure 3.2 we illustrate the trends of 

primary substance of abuse at the time of admission for the years 2000 through 2004 in the U.S. and 

the Appalachian region, respectively. Figures 3.3 through 3.8 illustrate trends for the primary 

abuse of alcohol, marijuana/hashish, cocaine, heroin, other opiates/synthetics, and 

methamphetamine.11 Key findings include the following:. 

Alcohol as a primary substance accounted for 45% of all TEDS admissions in the 

Appalachian region in 2004, down from more than 56% in 2000. Between 2000 and 2004, 

the percentage of total admissions with alcohol as the primary substance of abuse also 

declined in United States as a whole, accounting for almost 26% of all TEDS admissions in 

2000, declining to 22% of admissions in 2004. Figure 3.3 illustrates this trend. 

The proportion of admissions for primary marijuana/hashish abuse as the primary 

substance increased steadily from 14.2% of all TEDS admissions in the U.S. in 2000 to 

15.5% of admissions in 2004. In Appalachia, admissions increased from 15.1% of all TEDS 

admissions in 2000 to 16.28% of admissions in 2002, and then declined to 14.24% of 

admissions in 2004. Figure 3.4 illustrates this trend. 

Admissions for primary abuse of cocaine in the U.S. declined from 13.5% of all admissions 

in 2000 to 12.9% in 2001 and 2002, and then increased to 13.8% by 2004. In Appalachia, 

admissions for primary cocaine abuse followed a similar trend, declining from 12.95% in 

2000 to 11.78% in 2001, and then increasing to 12.45% in 2002. Admissions for primary 

cocaine abuse sharply increased between 2002 and 2004 to 13.66%. Figure 3.5 illustrates 

this trend. 

TEDS admissions for primary heroin abuse in the U.S. hovered around 15% of all 

admissions between 2000 and 2002, with a slight decrease to 14.1% in 2004. In Appalachia, 

admissions have increased steadily from 4.39% in 2000 to 10.19% in 2004. Figure 3.6

illustrates this trend. 

Admissions for primary abuse of other opiates and synthetics12 more than doubled between 

2000 and 2004 from 1.5% to 3.2% of all admissions in the U.S. In Appalachia, the 

proportion of admissions for primary abuse of other opiates and synthetics is considerably 

higher than in the U.S. between 2000 and 2004, and also more than doubled from 3.49% in 

2000 to 7.54% in 2004. Figure 3.7 illustrates this trend. 

 

11 Charts depicting the trends over the 2000 – 2004 period are not included below because admissions for primary abuse 

of PCP, hallucinogens, tranquilizers, sedatives, and inhalants were relatively stable. 

12 These drugs include codeine, hydrocodone, hydromorphone, meperidine, morphine, opium, oxycodone, pentazocine, 

propoxyphene, tramadol, and any other drug with morphine-like effects. These drugs exclude methadone. 
105 

The proportion of admissions for primary abuse of methamphetamine increased in both the 

U.S. and Appalachia between 2000 and 2004. In the U.S., primary methamphetamine abuse 

accounted for 3.8% of all admissions in 2000, and then rose steadily to almost 7% of 

admissions in 2004. In Appalachia, the proportion of admissions rose from 1.3% in 2000 to 

4.25% in 2004. Figure 3.8 illustrates this trend. 

Phencyclidine (PCP) as a primary substance of abuse accounted for 0.2% of all admissions 

in the U.S. between 2000 and 2004. The proportion of admissions for PCP abuse in 

Appalachia has also remained fairly stable over the 2000 to 2004 time period at 0.02 to 

0.03%. 

Admissions for primary abuse of hallucinogens remained fairly stable in the U.S. over this 

time period, accounting for less than 0.2% of all TEDS admissions between 2000 and 2002, 

and 0.1% in 2003 and 2004. In Appalachia, admissions were approximately 0.2% in 2000 

and 2001, declined to 0.15% in 2002, and then rose slightly to 0.18% in 2004. 

Admissions for primary abuse of tranquilizers remained fairly consistent over the time 

period, accounting for 0.4% to 0.5% of all US admissions between 2000 and 2004. In 

Appalachia, primary abuse of tranquilizers accounted for 0.95% of all admissions in 2004, 

up from 0.88% of admissions in 2000. 

TEDS admissions for primary abuse of sedatives remained at 0.2% between 2000 and 2004 

in the U.S. In Appalachia, the proportion of admissions hovered around 0.39% in 2004, up 

from 0.33% in 2000.

The proportion of TEDS admissions for primary abuse of inhalants was approximately 

0.1% between 2000 and 2004 in the U.S., and the Appalachian region. 
106 

Figure 3.1 Primary Substance of Abuse at Admission, Aged 12 and Older, in the U.S., TEDS 

2000-2004 

Primary Substance of Abuse At Admission, Aged 12 and Older,in the US, 

TEDS 2000-2004

0

5

10

15

20

25

30

2000 2001 2002 2003 2004

Percentage of Total Admissions

Alcohol 

Marijuana/Hashish

Cocaine

Heroin 

Other Opiates 

PCP 

Hallucinogens 

Methamphetamine

Tranquilizers 

Sedatives 

Inhalants 

SOURCE: "Treatment Episode Data Set (TEDS) 1995 - 2005: National Admissions to Substance Abuse 

Treatment Services." Office of Applied Studies, Substance Abuse and M ental Health Services 

Administration.

Figure 3.2 Primary Substance of Abuse at Admission, Aged 12 and Older, in the Appalachian 

Region, TEDS 2000-2004 

Primary Substance of Abuse At Admission, Aged 12 and Older, 

In the Appalachian Region, TEDS 2000-2004

0

10

20

30

40

50

60

2000 2001 2002 2003 2004

Percentage of Total Admissions

Alcohol 

Marijuana/Hashish

Cocaine

Heroin 

Other Opiates 

PCP 

Hallucinogens 

Methamphetamine

Tranquilizers 

Sedatives 

Inhalants 

SOURCE: "Treatment Episode Data Set (TEDS) 1995 - 2005: National Admissions to Substance Abuse 

Treatment Services." Office of Applied Studies, Substance Abuse and M ental Health Services 

Administration.
107 

Figure 3.3 Admissions Aged 12 and Over for Primary Alcohol Abuse, in the U.S. and 

Appalachia, TEDS 2000 – 2004 

Admissions Aged 12 and Over for Primary Alcohol Abuse, 

TEDS 2000 - 2004

0

10

20

30

40

50

60

2000 2001 2002 2003 2004

Percentage of All TEDS Admissions

US Appalachia

SOURCE: "Treatment Episode Data Set (TEDS) 1995 - 2005: National Admissions to Substance Abuse 

Treatment Services." Office of Applied Studies, Substance Abuse and M ental Health Services 

Administration.

Figure 3.4 Admissions Aged 12 and Over for Primary Marijuana/Hashish Abuse, in the U.S. 

and Appalachia, TEDS 2000 – 2004 

Admissions Aged 12 and Over for Primary Marijuana/Hashish Abuse, 

TEDS 2000 - 2004

13

13.5

14

14.5

15

15.5

16

16.5

2000 2001 2002 2003 2004

Percentage of All TEDS Admissions

US Appalachia

SOURCE: "Treatment Episode Data Set (TEDS) 1995 - 2005: National Admissions to Substance Abuse 

Treatment Services." Office of Applied Studies, Substance Abuse and M ental Health Services 

Administration.
108 

Figure 3.5 Admissions Aged 12 and Over for Primary Cocaine Abuse, in the U.S. and 

Appalachia, TEDS 2000 – 2004 

Admissions Aged 12 and Over for Primary Cocaine Abuse, 

TEDS 2000 - 2004

10.5

11

11.5

12

12.5

13

13.5

14

2000 2001 2002 2003 2004

Percentage of All TEDS Admissions

US Appalachia

SOURCE: "Treatment Episode Data Set (TEDS) 1995 - 2005: National Admissions to Substance Abuse 

Treatment Services." Office of Applied Studies, Substance Abuse and M ental Health Services 

Administration.

Figure 3.6 Admissions Aged 12 and Over for Primary Heroin Abuse, in the U.S. and 

Appalachia, TEDS 2000 – 2004 

Admissions Aged 12 and Over for Primary Heroin Abuse, 

TEDS 2000 - 2004

0

2

4

6

8

10

12

14

16

18

2000 2001 2002 2003 2004

Percentage of All TEDS Admissions

US Appalachia

SOURCE: "Treatment Episode Data Set (TEDS) 1995 - 2005: National Admissions to Substance Abuse 

Treatment Services." Office of Applied Studies, Substance Abuse and M ental Health Services 

Administration.
109 

Figure 3.7 Admissions Aged 12 and Over for Primary Abuse of Other Opiates/Synthetics, in 

the U.S. and Appalachia, TEDS 2000 – 2004 

Admissions Aged 12 and Over for Primary Abuse of Other 

Opiates/Synthetics, TEDS 2000 - 2004

0

1

2

3

4

5

6

7

8

2000 2001 2002 2003 2004

Percentage of All TEDS Admissions

US Appalachia

SOURCE: "Treatment Episode Data Set (TEDS) 1995 - 2005: National Admissions to Substance Abuse 

Treatment Services." Office of Applied Studies, Substance Abuse and M ental Health Services 

Administration.

 Figure 3.8 Admissions Aged 12 and Over for Primary Methamphetamine Abuse, in the U.S. 

and Appalachia, TEDS 2000 – 2004 

Admissions Aged 12 and Over for Primary Methamphetamine Abuse, 

TEDS 2000 - 2004

0

1

2

3

4

5

6

7

8

2000 2001 2002 2003 2004

Percentage of All TEDS Admissions

US Appalachia

SOURCE: "Treatment Episode Data Set (TEDS) 1995 - 2005: National Admissions to Substance Abuse 

Treatment Services." Office of Applied Studies, Substance Abuse and M ental Health Services 

Administration.
110 

3.4.3. Maps 

Map 3.1, below, shows the geographical distribution of TEDS admissions with three or more prior 

treatment episodes for substance abuse. Counties with higher proportions of admissions with three 

or more treatments are concentrated in northern Appalachia, from the southern border of New York 

to Maryland. High levels of three or more admissions are also seen in southern Appalachia, 

particularly in South Carolina and Alabama. There are relatively few admissions with three or more 

prior treatments in central Appalachia. 

Map 3.1. Percentage of Persons with Three or More Prior Treatment Episodes 

 

SOURCE: "Treatment Episode Data Set (TEDS) 2000 - 2004: National Admissions to Substance Abuse Treatment 

Services." Office of Applied Studies, Substance Abuse and Mental Health Services Administration. 
111 

Map 3.2, below, presents the distribution of admissions to substance abuse treatment in the 

Appalachian region with no prior treatment episodes. In contrast to Map 3.1, the highest 

distribution of new admissions is in central Appalachia, with the greatest concentration of 

admissions with no prior treatment in eastern Kentucky. Counties reporting TEDS data in western 

North Carolina and in Mississippi also show high levels of admissions with no prior treatment, 

while counties in Alabama and South Carolina show relatively lower levels of admissions with no 

prior treatment. 

Map 3.2. Percentage of Persons with No Prior Treatment Episodes 

SOURCE: "Treatment Episode Data Set (TEDS) 2000 - 2004: National Admissions to Substance Abuse 

Treatment Services." Office of Applied Studies, Substance Abuse and Mental Health Services 

Administration. 
112 

Map 3.3, below, shows patterns of referrals to substance abuse treatment. Northern Appalachia has 

the greatest concentration of referrals to treatment from health providers or substance abuse 

specialists, especially along the southern New York border and in central Pennsylvania. There are 

relatively fewer referrals from the central sub-region. Within the southern sub-region, there are 

relatively high referral levels among counties reporting TEDS data in Georgia, North Carolina and 

Mississippi. 

Map 3.3. Percentage of Persons Who Had an Alcohol and Drug or Health Provider Referral 

SOURCE: "Treatment Episode Data Set (TEDS) 2000 - 2004: National Admissions to Substance Abuse 

Treatment Services." Office of Applied Studies, Substance Abuse and Mental Health Services 

Administration. 
113 

Map 3.4, below, shows the geographical patterns of criminal justice referrals to substance abuse 

treatment, and, for the most part, the distribution is not unlike the distribution presented in Map 3.3. 

The majority of criminal justice referrals to treatment are in the northern sub-region, especially in 

sections of Ohio and Pennsylvania. There is a small pocket of criminal justice referrals in the 

central sub-region, especially in eastern Kentucky. Finally, northern and central Alabama counties 

also show a number of counties with high levels of criminal justice referrals to treatment. 

Map 3.4. Percentage of Persons Who Had a Court or Criminal Justice Referral 

SOURCE: "Treatment Episode Data Set (TEDS) 2000 - 2004: National Admissions to Substance Abuse 

Treatment Services." Office of Applied Studies, Substance Abuse and Mental Health Services 

Administration. 
114 

Map 3.5, below, shows the distribution of individual and self-referrals to substance abuse treatment. 

The greatest density of individual referrals within Appalachia is found in the central sub-region, 

centering around eastern Kentucky and including counties in Tennessee. Counties reporting TEDS 

data in the southern sub-region, especially in the Carolinas and Mississippi, also show high levels of 

individual referrals. There is a lower concentration of individual referrals in the northern subregion.

Map 3.5. Percentage of Persons Who Had an Individual Referral (Including Self-Referral) 

SOURCE: "Treatment Episode Data Set (TEDS) 2000 - 2004: National Admissions to Substance Abuse 

Treatment Services." Office of Applied Studies, Substance Abuse and Mental Health Services 

Administration. 
115 

Map 3.6, below, shows the geographical distribution of substance abuse admissions for alcohol use. 

The greatest density of admissions for alcohol use is in the northern sub-region, especially along the 

southern New York border and into northern Pennsylvania. There are small pockets in the central 

sub-region. 

Map 3.6. Percentage of Persons Admitted to Treatment for Alcohol Use 

SOURCE: "Treatment Episode Data Set (TEDS) 2000 - 2004: National Admissions to Substance Abuse 

Treatment Services." Office of Applied Studies, Substance Abuse and Mental Health Services 

Administration. 
116 

Map 3.7, below, presents the geographical distribution of substance abuse treatment admissions for 

cocaine use. Unlike Map 3.6, there are several pockets of high levels of admission for cocaine use 

in the southern sub-region, especially in Mississippi, Alabama, and the Carolinas. There are very 

few admissions for cocaine use in the central sub-region. In the northern sub-region, there are many 

pockets of high levels of admissions for cocaine use, especially in western and central 

Pennsylvania. 

Map 3.7. Percentage of Persons Admitted to Treatment for Cocaine Use 

SOURCE: "Treatment Episode Data Set (TEDS) 2000 - 2004: National Admissions to Substance Abuse 

Treatment Services." Office of Applied Studies, Substance Abuse and Mental Health Services 

Administration. 
117 

Map 3.8, below, depicts the geographical distribution of substance abuse admissions for heroin use. 

There are large areas of admission for heroin use in the northern sub-region in western and eastern 

Pennsylvania, as well as in the central region, in eastern Kentucky. 

Map 3.8. Percentage of Persons Admitted to Treatment for Heroin Use 

SOURCE: "Treatment Episode Data Set (TEDS) 2000 - 2004: National Admissions to Substance Abuse 

Treatment Services." Office of Applied Studies, Substance Abuse and Mental Health Services 

Administration. 
118 

Map 3.9, below, presents the geographical distribution of substance abuse admissions for 

methamphetamine use. Most admissions for methamphetamine use are clustered in the southern 

sub-region in Mississippi, Alabama, and Georgia. There are lower levels of admissions in the 

central region, as well as in the northern region, especially in western Pennsylvania. 

Map 3.9. Percentage of Persons Admitted to Treatment for Methamphetamine Use 

SOURCE: "Treatment Episode Data Set (TEDS) 2000 - 2004: National Admissions to Substance Abuse 

Treatment Services." Office of Applied Studies, Substance Abuse and Mental Health Services 

Administration. 
119 

Map 3.10, below, shows the geographical distribution of substance abuse admissions by primary 

methamphetamine abuse. This map is quite similar to Map 3.9, with the highest concentration of 

admissions in the southern sub-region of Appalachia. Besides the concentration in Mississippi, 

Alabama, and Georgia, the Carolinas present a greater concentration of admissions by primary 

methamphetamine abuse. 

Map 3.10. Percentage of Persons Admitted to Treatment for Primary Methamphetamine 

Abuse 

SOURCE: "Treatment Episode Data Set (TEDS) 2000 - 2004: National Admissions to Substance Abuse 

Treatment Services." Office of Applied Studies, Substance Abuse and Mental Health Services 

Administration. 
120 

Map 3.11, below, presents the geographical distribution of admission for psychiatric problems 

(both substance-related and non-substance-related). The central sub-region has the greatest density 

of admissions for psychiatric problems. Other pockets are seen in New York, Ohio and North 

Carolina. 

Map 3.11. Percentage of Persons Admitted to Treatment for Psychiatric Problems 

SOURCE: "Treatment Episode Data Set (TEDS) 2000 - 2004: National Admissions to Substance Abuse 

Treatment Services." Office of Applied Studies, Substance Abuse and Mental Health Services 

Administration. 
121 

3.5 Discussion 

Consistent with estimations at the national level and with prior research findings, alcohol use stands 

as the most-cited primary reason for treatment in Appalachia at the time of admission to treatment.53 

This is followed by marijuana use, cocaine use, heroin use, and the use of other opiates or 

synthetics. This is not the case across counties when analyzing the data by economic development 

status, however. For counties at lower economic development status levels (“distressed” and “at 

risk”), other opiates or synthetics are the most-cited primary reason for admission after alcohol and 

marijuana use. Despite relatively low overall prevalence, the proportions of admissions citing 

tranquilizer and sedative use were also the highest in the “distressed” counties. 

It is noteworthy that admissions to treatment for “other opiates or synthetics” include people using 

OxyContin. This finding supports recent media reports and other anecdotal evidence that 

OxyContin and non-medical use of prescription drugs have become serious problems in certain 

rural areas and within the Appalachian region.54,55,56 Furthermore, according to the Coalition on 

Appalachian Substance Abuse Policy (CASAP), TEDS data may actually understate the nonmedical use of prescription drugs in Appalachia. CASAP noted that methadone treatment for 

prescription drug abuse is likely underreported in Appalachia because most methadone treatment is 

provided by private facilities. However, private facilities do not submit TEDS data. In the case of 

Kentucky, for example, CASAP indicated that there are nine facilities that offer methadone 

treatment – two of which are publicly funded. However, only one of the two publicly funded 

facilities submits TEDS data. As a result, TEDS data may not provide a comprehensive picture of 

the prescription drug problem in Appalachia due to the facility’s funding stream and/or reporting 

practices. 

The TEDS data also show that the central Appalachian region had the highest proportion of 

admissions with other opiates or synthetics as the primary reason for admission among Appalachian 

sub-regions. This finding is also consistent with recent media reports.57 TEDS data also showed 

that the proportion of adult admissions for primary abuse of other opiates and synthetics is 

considerably higher than in the U.S. between 2000 and 2004, and also more than doubled from 

3.49% to 7.54% during this time period. 

About two-thirds of admissions in Appalachia were associated with mood disorders – both those 

substance-related and non-substance-related – based on either the third edition revised or the fourth 

edition of the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental 

Disorders (DSM-IIIR or DSM-IV). The highest prevalence of mood disorders occurs in 

“transitional” counties and in the northern Appalachian sub-region. The reasons for this pattern of 

comorbidity require further study. Furthermore, we also see that the central sub-region of 

Appalachia has the greatest density of admissions for psychiatric problems (both substance-related 

and non-substance-related). Other pockets are seen in New York, Ohio and North Carolina. 

Treatment referral by the criminal justice system or the courts was more common in the “distressed” 

and “at-risk” counties than in the “transitional” and “competitive” counties, and least likely in 

“attainment” counties. In contrast, the “attainment” counties had the highest proportion of 

admissions referred by individual clients (e.g., self-referral). Additionally, the proportion of 

admissions that were referred from health care providers was considerably lower in “distressed” 

counties. Although different criminal justice practices at the state level may affect the ways in 

which clients are referred to admission, it appears that the economic development status of the 
122 

counties where the facilities were located may also impact how substance abuse clients come to be 

admitted to treatment. 

The vast majority (94.21%) of the admissions in “distressed” counties were made into ambulatory 

care settings. Interestingly, while 14% of admissions across the Appalachian region were to 

rehabilitation or residential settings, only about 4% of admissions in “distressed” counties were to 

such settings. Future research should evaluate the effect of treatment settings on treatment 

outcomes by combining admissions and discharge data for the same clients. 

About one-third of the admissions in distressed counties were clients who had previously accessed 

treatment at the facility. In contrast, about two-thirds of admissions across Appalachian counties 

were clients who had previously sought treatment. Drug users who have been in and out of 

treatment programs multiple times are of particular concern. Past research has suggested that 

multiple prior treatment episodes might be indicative of less effective current treatment, everything 

REFLECTIONS FROM PRACTITIONERS 

 From the Coalition on Appalachian Substance Abuse Policy 

Challenges Associated with Using the Treatment Episode Data Set (TEDS) 

to Explore Substance Abuse and Mental Health in Appalachia •  The drug indicated as the “primary reason for admission” may not be the most relevant

drug to the client’s treatment.  The counselor selects the “primary” drug upon admission –

not the client. This is an important distinction.   If the counselor believes that heroin is the

most important drug, he/she may designate heroin as the primary drug upon admission.

•  Criminal justice clients and clients with multiple prior treatment episodes tend to do as

well if not better in terms of treatment outcomes than their counterparts.   CASAP noted

that criminal justice clients do well in treatment, if not better than clients who are not coming

from the criminal justice system.   In addition, CASAP noted that clients with multiple prior

treatment episodes tend to have better outcomes in treatment, than clients with zero prior

treatment episodes.  Most clients have had a previous treatment episode.   

•  TEDS may be missing important subgroups of the population.  For a client to qualify as a

TEDS admission, he/she must meet certain required criteria. If certain peak fields in TEDS are

missing, the client is not a TEDS admission. For example, court referred people are not

counted because they have a limited number of treatment visits, and do not receive a

treatment plan.   

•  Facility reporting practices are often affected by payment.  Facilities may underreport or

over‐report specific conditions to secure payment. In Virginia, if a client is admitted with a co‐

occurring disorder, the facility may choose to report that he/she has a mental health

condition to secure payment, although the client is receiving treatment for substance abuse

issues as well.   According to CASAP, the federal government should recognize co‐occurring

disorders to ameliorate payment concerns at treatment facilities.

REFLECTIONS FROM PRACTITIONERS 

 From the Coalition on Appalachian Substance Abuse Policy 

Challenges Associated with Using the Treatment Episode Data Set (TEDS) to 

Explore Substance Abuse and Mental Health in Appalachia 
123 

else being equal.58,59,60 Interestingly, CASAP suggested that clients with multiple prior treatment 

episodes do well, if not better than clients with zero prior treatment episodes. Given the special 

geographic and economic contexts of the Appalachian region, future studies may examine the 

outcome of new treatments in economically distressed areas. 

Item non-responses should be taken into consideration when interpreting admissions data. For 

example, unknown status of health insurance is quite common in TEDS. Health insurance is 

regarded as a key treatment access enabling factor and non-response to this item may affect overall 

admissions.61 Overall, the health insurance status was unknown for almost half of the admissions 

during the 2000-2004 period. Importantly, the distribution of this unknown status was uneven 

across sub-regions – while nearly two-thirds of admissions had unknown health insurance status in 

the southern Appalachian region, slightly less than one-third of admissions in the central 

Appalachian region had unknown health insurance status. Future data collection efforts should 

attempt to determine the reasons for the missing health insurance information and consistent 

patterns that may influence data interpretation. 

Finally, it is important to note that TEDS data do not provide a comprehensive understanding of all 

of the facility-level factors that may affect access to and utilization of treatment services. Additional 

data elements that would be useful to collect through TEDS in future years include staff turnover 

rates at substance abuse and mental health treatment facilities, and staff shortages at the facilitylevel. Such information may reveal other important deficiencies and disparities in access to 

treatment across Appalachia. 
124 

CHAPTER 4: Substance Use and Mental Health Disorder Discharges 

from Appalachian and Other Community Hospitals in 2004 

4.1 Introduction 

In the United States, community hospitals provide treatment services for adolescents and adults 

with mental health and/or substance abuse disorders. Community hospitals are non-Federal, acute 

care hospitals that provide general and specialty care. Excluded from this definition are federal, 

rehabilitation, and psychiatric hospitals as well as alcoholism/chemical dependency treatment 

facilities. In 2004, adults diagnosed with mental health and/or substance abuse disorders accounted 

for approximately 7.6 million stays – 1 out of every 4 – at community hospitals in the U.S.62

Given that community hospitals provide treatment for a large number of people with mental health 

and/or substance abuse disorders in the U.S., discharge data are a rich data source. Exploring the 

clinical and nonclinical data available at the community hospital-level provides an opportunity to 

better understand the demographics of patients with mental health and substance abuse disorders as 

well as other important characteristics such as their diagnoses, expected payment sources, and total 

charges. 

Chapter 4 provides an overview of substance abuse and mental disorder discharges from 

Appalachian and other community hospitals in 2004. Analyses are based on data from the 

Healthcare Cost and Utilization Project (HCUP)’s 2004 Nationwide Inpatient Sample (NIS). The 

HCUP databases contain information on the vast majority of all hospital discharges in U.S. 

community hospitals, making them a powerful tool for exploring substance abuse and mental health 

issues in Appalachia and nationally. HCUP provides data that address both substance abuse and 

mental health issues. Specifically, we explore the following data elements from HCUP: client 

demographics; admission source and type; primary expected payer and secondary expected payer; 

presence of mental health and/or substance abuse (MHSA) disorder; subtype of MHSA disorder; 

comorbidity status; whether the diagnosis contains alcohol use disorder, drug use disorder, or 

mental health disorder; whether the principal reason for hospitalization was alcohol use; and 

whether the principal reason for hospitalization was drug use. 

Chapter 4 will investigate the following key research questions: 

Are there differences in discharges from community hospitals in Appalachia, as compared to 

discharges from community hospitals outside of Appalachia? 

Are there differences in discharges from community hospitals in Appalachia versus outside 

of Appalachia when taking county economic status into account? 

What do sub-regional differences look like across socio-economic status, health diagnoses, 

and other variables? 

In Section 4.2, we provide an overview of the HCUP NIS, including its objectives, sampling design, 

uses, relevant measures, and limitations specifically related to exploring mental health and 

substance abuse issues in the Appalachian region. In Section 4.3, we discuss our methods. Section 

4.4 contains the results of the analysis. Finally, Section 4.5 provides a discussion of key findings. 
125 

4.2 Data 

4.2.1 Overview 

The Healthcare Cost and Utilization Project (HCUP) is the largest collection of longitudinal hospital 

care data in the United States, providing encounter-level administrative data for inpatient hospital 

stays. HCUP is comprised of a variety of databases, software tools, and products that provide data 

on an array of clinical and non-clinical information from patient hospital discharge abstracts. 

Sponsored by the Agency for Healthcare Research and Quality (AHRQ), and supported by a 

number of partnerships at the federal, state, and industry levels, HCUP was designed to support 

health care research and decision making in the U.S. 

According to AHRQ, the objectives of HCUP are three-fold: 1) to obtain data from state-wide 

information sources; 2) to design and develop multi-state health care databases for health services 

research and health policy analysis; and 3) to make data available to a broad set of public and 

private users.63 

AHRQ works closely with state data organizations in participating states to obtain data for the 

HCUP databases. A number of hospital associations and private organizations contribute to the 

development of these databases. HCUP is comprised of five databases: the State Inpatient 

Databases (SID); State Ambulatory Surgery Databases (SASD); State Emergency Department 

Databases (SEDD); the Nationwide Inpatient Sample (NIS); and the Kids’ Inpatient Database 

(KID). For all of these databases, the unit of analysis is the inpatient stay in a community hospital – 

not an individual patient or medical procedure.64 

This study uses HCUP’s Nationwide Inpatient Sample (NIS) to explore substance abuse and mental 

disorder discharges from community hospitals. Given the NIS’s large sample size – 8,004,571 

hospital discharges from 1,004 U.S. community hospitals – the NIS is ideal for exploring trends 

nationally and in the Appalachian region. As the largest all-payer inpatient care database in the 

U.S., the NIS affords researchers a unique opportunity to explore complex health policy issues such 

as access to care, medical practice patterns, cost and quality issues, and health care outcomes. 

4.2.2 Sample Design 

The NIS is a stratified probability sample of non-rehabilitation, community hospitals in the United 

States. All U.S. community hospitals in the American Hospital Association (AHA)’s hospital file 

are included in the hospital universe, except short-term rehabilitation hospitals. The sampling frame 

is constructed from the subset of universe hospitals that released data to AHRQ for the NIS. The 

sampling frame includes all AHA community hospitals that could be matched to discharge data 

provided to AHRQ. The objective of the NIS sampling design was to select a sample of hospitals 

that accurately represent the universe of hospitals and are geographically dispersed. 

The NIS uses five characteristics to create a sample from the AHA’s hospital files: 1) geographic 

region (Northeast, Midwest, West, and South); 2) control of hospital (public, private, not-for-profit, 

and proprietary); 3) location (urban or rural); 4) teaching status (teaching or non-teaching); and 5) 

bed size (small, medium, large).65 Each year, no more than 20% of the total number of U.S. 

hospitals within each of the five categories above are randomly selected. 
126 

The NIS sampling frame is representative of all U.S hospitals. Over 75% of all U.S. hospitals and 

87.5% of the U.S. population are accounted for in the NIS sampling frame. In 2004, the sampling 

frame contained data on 3,705 hospitals. The sample size for the 2004 survey was 1,004 hospitals – 

approximately 20.5% of 4,906 hospitals included in the total universe of U.S. community 

hospitals.66 The NIS includes data on 37 states; ten of the 13 Appalachian states are included in the 

NIS. Pennsylvania, Alabama, and Mississippi are excluded. 

4.2.3 Uses of the HCUP Nationwide Inpatient Sample 

The NIS enables researchers to answer questions about the use and cost of hospital services, 

medical practice variation, health care cost inflation, hospital financial distress, analyses at the State 

and community levels, medical treatment effectiveness, quality of care, impact of health policy 

changes, access to care, diffusion of medical technology, and utilization of health services by 

special populations.67 

HCUP’s databases have been used to explore research questions related to mental health and 

substance abuse issues. In July 2006, HCUP’s NIS 2004 data was used as the basis for a fact book 

on care of adults with mental health and substance abuse disorders.68 This fact book explored issues 

such as: what are the common reasons for hospitalization by type and diagnoses; how do hospital 

stays for this population vary by gender and age; how are patients admitted to the hospital; what is 

the mean length of stay; what is the cost of hospital stays; who is billed for hospital stays; where do 

patients go after they are discharged; and what percentage of hospital resource use is attributable to 

mental health and substance abuse disorders? Researchers have also used HCUP data to study 

psychiatric diagnoses,69 trends in substance abuse detoxification,70 and hospitalizations for alcohol 

abuse disorders,71 among other issues. 

In addition, a large body of research has applied HCUP data to study racial and ethnic disparities in 

the inpatient setting,72,73,74 as well as hospitalization and treatment for health care problems.75,76,77,78 

Finally, researchers have utilized HCUP hospital discharge data to study health care issues in 

specific geographic areas.79,80 

4.2.4 HCUP Measures Used in this Study 

Next, we define the measures used from the 2004 HCUP NIS data set, and explore the potential 

limitations with respect to using these measures for our purpose – to explore substance abuse and 

mental health disorder discharges in Appalachian community hospitals and other community 

hospitals nationally. We explore the following variables: expected primary payer; total and average 

charges; length of stay; race; admission source; alcohol, drug, and mental health disorder status; 

teaching hospital status; and death during hospitalization. We provide a brief discussion of each of 

these variables. 

Gender of the client discharged from a community hospital is described as male or female. 

Age of the client discharged from a community hospital is specified as one of the following 

categories: 18 to 44 years old; 45 to 64 years old; 65 to 79 years old; and 80 or older. 

Median household income quartile for the client’s zip code is specified as one of the following 

categories: $1 - $35,999; $36,000 - $44,999; $45,000 - $58,999; and $59,000 or more. 
127 

Patient location of discharges is described by a four category urban-rural designation for the 

patient’s county of residence: (1) large metropolitan; (2) small metropolitan; (3) micropolitan; and 

(4) non-core. The categorization is a simplified adaptation of the 2003 version of the Urban 

Influence Codes (UIC). The 12 categories of the UIC are combined into four broader categories that 

differentiate between large and small metropolitan, micropolitan, and a non-urban residual as 

follows. A large metro area is defined as an area of 1 million residents or more. A small metro area 

is defined as an area of less than 1 million residents. A micropolitan area is adjacent to a large 

metro, small metro, or not adjacent to a metro area. A noncore area is defined as one of the 

following: adjacent to a small metropolitan area with its own town; adjacent to a small metropolitan 

area without its own town; adjacent to a micropolitan area with its own town; adjacent to 

micropolitan area without its own town; not adjacent to a metropolitan or micropolitan area with its 

own town; and not adjacent to a metropolitan or micropolitan area without its own town.

Admission source indicates the source of the hospital admission: the emergency department; 

transfer from another hospital (includes transfers within the same hospital and transfers between 

hospitals); from another health facility including long term care; court or law enforcement; and 

routine, birth and other (includes referrals from physicians, clinics, and HMOs). 

Admission type indicates the type of hospital admission. Admission types are described as 

emergency or routine/ other (e.g., urgent, elective, newborn, trauma center, and other). 

The variables, primary expected payer and secondary expected payer, identify who the hospital 

expects will be the primary and secondary payer of the hospital bill for patients with substance 

abuse and mental health disorders. While each hospitalization and related hospital bill is associated 

with an expected primary payer, the expected primary payer may not be the ultimate payer. The 

expected primary payer can be: Medicaid (includes fee-for-service and managed care Medicaid 

patients); Medicare (includes fee-for-service and managed care Medicare patients); Private 

Insurance (includes Blue Cross, commercial carriers, and private HMOs and PPOs); Other (includes 

Workers' Compensation, TRICARE/VA, Title V, and other government programs); Self Pay 

(uninsured); and No Charge (uninsured). A noteworthy limitation of this variable is that it does not 

capture dual-eligible patients. 

Presence of mental health and/or substance abuse (MHSA) disorder indicates whether the 

discharge was diagnosed with at least one MHSA disorder or zero MHSA disorders. 

Presence of any secondary mental health and/or substance abuse (MHSA) disorder indicates 

whether or not the discharge was diagnosed with any secondary MHSA diagnosis. 

Subtype of mental health and/or substance abuse (MHSA) disorder indicates the client’s 

diagnosis. Categories for this variable include: principal MHSA diagnosis only; principal and 

secondary MHSA diagnosis; secondary MHSA only; any principal MHSA diagnoses; and at least 

one principal MHSA diagnosis. 

Comorbidity status indicates whether the client has a non-substance abuse and mental health 

diagnosis, a substance abuse diagnosis only, a mental health diagnosis only, or a comorbidity. 
128 

Diagnosis contains alcohol use disorder indicates that the client’s diagnosis contains an alcohol 

use disorder. 

Diagnosis contains drug use disorder indicates that the client’s diagnosis contains a drug use 

disorder.

Diagnosis contains mental health disorder indicates that the client’s diagnosis contains a mental 

health disorder.

Principal reason for hospitalization was alcohol use indicates that the principal reason for the 

client’s hospitalization was alcohol use.

Principal reason for hospitalization was drug use indicates that the principal reason for the 

client’s hospitalization was drug use.

4.2.5 Limitations of HCUP NIS Data 

There are a few critical limitations that may affect the quality of the findings when using HCUP 

NIS data to explore substance abuse and mental health issues in Appalachia and nationally. 

One obvious limitation is that HCUP data is only available for 37 states. Ideally, data would be 

available from every state in the U.S. Additionally, in 2004, HCUP NIS data were only available in 

10 of the 13 Appalachian states, excluding Pennsylvania, Mississippi, and Alabama. Missing data 

is one clear limitation, given that it would be ideal to make comparisons between Appalachian 

community hospitals and other community hospitals nationally based on data for all 13 Appalachian 

states and the rest of the nation. 

A second limitation is that the NIS is designed as a nationwide representation of inpatient hospital 

care. Most variables in the NIS are standardized to allow for national estimates. The NIS sampling 

frame is not designed with “county” or “state” as a stratification variable and therefore state and/or 

county-level analyses cannot be conducted. 

It is also important to note that while the NIS includes general and specialty hosptials (e.g., 

pediatric, obstetrics-gynecology, short-term rehabilitation, and oncology), the survey excludes longterm care and psychiatric hospitals. Given that the NIS does not include data on patients in 

psychiatric hospitals, the data should not be perceived as a comprehensive picture of mental health 

issues associated with inpatient care in the U.S. Findings from this chapter likely provide an underestimation of mental health problems in the U.S. Further exacerbating this problem, it is likely that 

MHSA diagnoses are under-coded at hospitals due to concerns regarding reimbursement and stigma 

associated with mental health and substance abuse (MHSA) diagnoses. 

Finally, due to confidentiality laws and other reasons, some states that contributed data to the NIS 

imposed restrictions on the release of certain data elements or on the number and types of hospitals 

that could be included in the database. 81 Other states prohibited the release of certain data 

elements. In Virginia, data may not include more than 50% of hospitals. Georgia requested that 

patient race be set to missing in the NIS. To further secure confidentiality, Georgia, Ohio, and 

Tennessee did not report data on the teaching status of hospitals.82 
129 

4.3 Methods 

4.3.1 Study Sample 

This study uses the 2004 HCUP Nationwide Inpatient Sample (NIS) database to analyze substance 

use and mental disorders in the Appalachian region. Because the NIS is limited to community 

hospital data, disorders treated in outpatient or ambulatory care settings, long-term care facilities, 

psychiatric hospitals, and substance abuse treatment facilities are not reflected in this report. Only 

adults age 18 or older were included; newborns, children, and adolescents were excluded. 

Due to confidentiality concerns and the manner in which state data are submitted to the central 

distributor of HCUP National Inpatient Stay files, 11 states did not include county identifiers for the 

hospitals where patient discharge information were provided. Among these 11 states, four are 

associated with the Appalachian region – Ohio, South Carolina, Tennessee, and Georgia. These 

four Appalachian states were excluded from the analysis because the Appalachian region portion of 

these states could not be determined due to the absence of county identifiers. 

4.3.2 Statistical Methods 

Unit of Analysis 

For this study, the unit of analysis is the inpatient stay in a community hospital rather than the 

patient or the procedure. For example, a patient admitted three times to a hospital is included three 

times in the NIS data. Thus, the same individual can account for more than one hospital stay. 

Measure 

Diagnoses are recorded within the NIS using the International Classification of Diseases, Ninth 

Revision, Clinical Modification (ICD-9-CM). We apply the AHRQ-developed Mental Health and 

Substance Abuse Clinical Classification Software (CCS-MHSA) to aggregate ICD-9_CD MHSA 

diagnostic codes into a limited number of clinically meaningful categories. The CCS-MHSA, 

derived primarily from the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, 

assigns mental and substance-use ICD-9-CM codes to 1 of the 14 categories. 

Table 4.1. AHRQ-developed Mental Health and Substance Abuse Clinical Classification 

Software (CCS-MHSA) 

CCSMHSA 

Code 

Mental Health or Substance Abuse Disorders 

650 Adjustment disorders

651 Anxiety disorders

652 Disruptive behavior disorders including conduct disorder, oppositional defiant disorder, attentiondeficit disorder and attention-deficit/hyperactivity disorder

653 Delirium, dementia, and amnestic and other cognitive disorders

654 Developmental disorders including communication disorders, developmental disabilities, intellectual 

disabilities, learning disorders and motor skills disorders*

655 Disorders usually diagnosed in infancy, childhood, or adolescence such as elimination disorders, 
130 

CCSMHSA 

Code 

Mental Health or Substance Abuse Disorders 

separation anxiety disorders, pervasive developmental disorders, and tic disorders

656 Impulse control disorders

657 Mood disorders including bipolar disorders and depressive disorders

658 Personality disorders

659 Schizophrenia and other psychotic disorders

660 Substance-related disorders including alcohol-related disorders and substance-related disorders (e.g., 

amphetamine-related disorders; cannabis-related disorders; cocaine-related disorders; hallucinogenrelated disorders; inhalant-related disorders; opioid-related disorders; phencyclidine-related disorders; 

sedative-, hypnotic-, or anxiolytic-related disorders; poly-substance-related disorders)

661 Miscellaneous mental disorders including dissociative disorders, eating disorders, factitious disorders, 

psychogenic disorders, sexual and gender identity disorders, sleep disorders, somatoform disorders, 

mental disorders due to general medical conditions not elsewhere classified, and other miscellaneous 

mental conditions

662 Suicide and intentional self-inflicted injury*

663 Screening and history of mental health and substance-related conditions*

* Suicide and intentional self-inflicted injury, as defined in the CCS-MHSA, is examined as a co-occurring condition 

with mental health and substance-related disorders. 

* Both unweighted and weighted estimations are calculated. For draft report, only the unweighted estimates are 

presented. 

4.4 Results 

In Section 4.4, we present subregional differences for community hospital discharges in Appalachia 

and outside of Appalachia in 2004. In Section 4.4.1, we show a series of tables and charts that 

explore the following variables: the client’s gender and age; median household income quartile for 

the client’s zip code; patient location; admission source; admission type; primary expected payer 

and secondary expected payer; presence of mental health and/or substance abuse (MHSA) disorder; 

presence of any MHSA abuse disorder; subtype of MHSA abuse disorder; comorbidity status; 

whether the diagnosis contains alcohol use disorder, drug use disorder, or mental health disorder; 

whether the principal reason for hospitalization was alcohol use; and whether the principal reason 

for hospitalization was drug use. We also present a table of mental health diagnoses. 

4.4.1 Tables 

Tables 4.2a and 4.2b, below, present subregional differences in hospital discharges for community 

hospitals in the Appalachian region and outside of Appalachia for demographic variables among 

patients over 18 years of age. Table 4.2a shows the differences in discharges from community 

hospitals in Appalachian counties and outside of Appalachia, overall. Table 4.2b depicts 

differences in discharges from community hospitals by county economic development status. In 

Appalachia, about 60% of women are discharged from community hospitals in both the 

Appalachian region and outside of the Appalachian region (61.1%) as compared to about 40% of 

men in Appalachia and 39% of men outside of Appalachia. This result is consistent across county 

economic development status with the exception of attainment counties, where 50.0% of discharges 

from community hospitals are male. 
131 

Overall, patients discharged from community hospitals outside of Appalachia are slightly younger 

than patients discharged in the Appalachian region. Outside the Appalachian region, 32.7% of 

patients are between the ages of 18 and 44, compared to 26.4% within the Appalachian region. 

These results are consistent across levels of economic development, although the distribution shifts 

slightly. For example, overall 28.2% of patients in the Appalachian region are 45 to 64 years of 

age, while in attainment counties, 37.6% of patients are in this age range. 

 

Overall, more patients discharged from community hospitals in the Appalachian region are in the 

lowest income category when compared to patients discharged from community hospitals outside of 

Appalachia (64.1% versus 26.5%). Furthermore, less than 10% of patients discharged from 

community hospitals in the Appalachian region have a median income over $45,000, compared with 

46% in the rest of the country. These results are even more pronounced in distressed and at-risk 

Appalachian counties. In distressed counties, nearly 90% of patients are in the lowest income 

quartile, while in at-risk counties, 83.7% of patients are in the lowest income bracket. By contrast, 

in attainment counties, only 36.6% of patients are in the lowest income bracket. 

Less than 1% of patients discharged from hospitals in the Appalachian region are from large 

metropolitan areas as compared to patients outside of Appalachia (57.5%). Instead, 34.5% of 

patients are from small metropolitan areas in Appalachia (compared to 25.9% outside of 

Appalachia), 29.2% are from micropolitan areas (compared to 9.7% outside of Appalachia), and 

31% of patients are from non-core areas (as compared to 6.5% outside of Appalachia). These 

results are consistent across counties, regardless of economic status. 
132 

Table 4.2a: Demographics of Community Hospital Discharges in the Appalachian Region 

(Unweighted) 

 

 

All 

Appalachian Region Outside of Appalachia 

N % N % 

Gender 

 Male 67,258 40.04 2,133,917 38.73 

 Female 100,696 59.95 3,364,470 61.07 

Age 

 18-44 44,338 26.4 1,804,197 32.75 

 45-64 47,290 28.16 1,456,348 26.43 

 65-79 45,564 27.13 1,327,258 24.09 

 80 or older 30,765 18.32 921,743 16.73 

Median Household Income Quartile for Patient's Zip Code 

 $1-$35,999 107,695 64.12 1,461,759 26.53 

 $36,000- $44,999 36,641 21.82 1,400,755 25.42 

 $45,000-$58,999 13,548 8.07 1,208,375 21.93 

 $59,000 or more 2,001 1.19 1,322,096 24 

Patient Location 

 Large metropolitan 1,322 0.79 3,167,482 57.49 

 Small metropolitan 58,014 34.54 1,425,579 25.87 

 Micropolitan 49,113 29.24 534,492 9.7 

 Non-core 59,000 35.13 358,486 6.51 
133 

Table 4.2b: Demographics of Community Hospital Discharges in the Appalachian Region (Unweighted) by Development Status, 2004 

County Economic Development Status 

Adults Age 18 or Older 

Distressed At-Risk Transitional Competitive 

Appalachian 

Region 

Outside of 

Appalachia 

Appalachian 

Region 

Outside of 

Appalachia 

Appalachian 

Region 

Outside of 

Appalachia 

Appalachian 

Region 

Outside of 

Appalachia 

N % N % N % N % N % N % N % N % 

Gender Male 12,958 40.3 63,210 40.4 9,834 37.8 17,089 37.2 26,192 36.6 644,486 40.7 3,066 39.1 185,050 3Female 19,216 59.7 93,408 59.6 16,151 62.2 28,809 62.8 45,365 63.4 939,653 59.3 4,778 60.9 292,107 6Age 18-44 

7,416 23.1 54,932 35.1 6,940 26.7 13,896 30.3 20,374 28.5 471,843 29.8 1,792 22.9 153,013 3

45-64 

9,775 30.4 46,438 29.7 6,626 25.5 10,973 23.9 17,663 24.7 423,146 26.7 1,786 22.8 122,098 2

65-79 

9,054 28.1 33,531 21.4 7,086 27.3 11,803 25.7 18,967 26.5 406,659 25.7 2,358 30.1 118,369 24

80 or older 

5,930 18.4 21,720 13.9 5,333 20.5 9,226 20.1 14,554 20.3 282,508 17.8 1,908 24.3 83,679 17

Median Household Income Quartile for Patient's Zip Code $1-$35,999 28,823 89.6 102,659 65.6 21,753 83.7 35,822 78.1 43,500 60.8 497,929 31.4 2,487 31.7 88,079 1$36,000- $44,999 

479 1.49 39,706 25.4 1,668 6.42 7,605 16.6 19,626 27.4 506,152 32 4,107 52.4 162,643 34

$45,000-$58,999 

116 0.36 7,110 4.54 856 3.29 1,135 2.47 5,698 7.96 317,716 20.1 518 6.6 141,613 2

$59,000 or more 

38 0.12 6,268 4 50 0.19 187 0.41 491 0.69 229,717 14.5 59 0.75 73,909 1

Patient Location Large metroplitan 101 0.31 134,446 85.8 119 0.46 623 1.36 528 0.74 787,722 49.7 73 0.93 226,573 47Small metropolitan 997 3.1 4,133 2.64 876 3.37 3,128 6.82 30,621 42.8 445,733 28.1 6,893 87.9 149,744 3Micropolitan 6,516 20.3 8,964 5.72 9,999 38.5 28,988 63.2 23,174 32.4 205,718 13 459 5.85 67,263 14Non-core 24,190 75.2 8,806 5.62 14,954 58 13,129 28.6 17,136 24 138,420 8.74 419 5.34 30,759 6SOURCE: Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS), 2004. 
134 

Tables 4.3a and 4.3b, below, present differences in community hospital discharges by admission 

source, admission type, and expected payment for admissions over 18 years of age. In Table 4.3a, 

we provide findings overall for community hospitals in Appalachia and outside of Appalachia. 

Table 4.4b shows findings by economic county development status. The percentage of discharges 

from community hospitals that entered into hospitals via the emergency department was higher in 

the Appalachian region (53.7%) than in hospitals outside of Appalachia (48.8%). Results vary, 

however, based on economic development level. Figure 4.1 visually shows these trends in 

Appalachia only. As the figure demonstrates, the emergency room is the most common source of 

admission to the hospital for patients in distressed counties in Appalachia, followed by at-risk, 

transitional, competitive, and attainment counties. 

Figure 4.1 Admission Source by Appalachian County Economic Development Status 

 SOURCE: Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS), 2004. 

Overall, more patients in economically distressed counties enter the hospital through the emergency 

department, with 73.3% of patients in non-Appalachian counties entering the hospital in this manner 

and 62.1% of patients from the Appalachian region entering the hospital in this manner. In at-risk 

counties, 58.2% of patients in the Appalachian region enter the hospital through the emergency 

department, while 50.5% of patients in non-Appalachian counties enter in this way. There is little 

difference between Appalachian and non-Appalachian admission types for transitional and 

competitive counties, with approximately 50% of patients entering the hospital through the 

emergency department. Finally, in attainment counties, 39.8% of patients from the Appalachian 

region and 49.3% of non-Appalachian patients entered the hospital through the emergency 

department. 

Medicare is the key primary expected payer in both Appalachian and non-Appalachian counties 

(51.9% versus 43.3%), followed by private insurance (24.4% in Appalachia and 33.7% outside of 

Appalachia), Medicaid (14.5% in Appalachia and 14.0% outside of Appalachia), self pay (5.1% in 

Appalachia and 5.2% outside of Appalachia), other forms of primary payment (3.8% in Appalachia 

and 3.2% outside of Appalachia), and, finally, no charge (0.03% in Appalachia and 0.5% outside of 

Appalachia). When the economic development level is taken into account, the profile changes 

slightly. Figure 4.2 below highlights these trends. 

Admission Source by Appalachian

County Economic Development Status

0

10

20

30

40

50

60

70

Dist ressed At -Risk Transit ional Compet it ive At t ainment

Count y E conomi c Devel opment St at us

 Emergency Room

 Routine/Other
135 

Figure 4.2 Primary Expected Payer By Appalachian County Economic Development Status 

 SOURCE: Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS), 2004. 

Medicare continues to be the dominant primary expected form of payment in the Appalachian 

region, hovering around 50% of expected payments in the less economically developed counties 

(distressed, at-risk, and transitional), increasing to 61.1% of expected payments in competitive 

counties, and falling to 46.5% of expected payments in attainment counties. Less economically 

developed counties in Appalachia report a greater percentage of Medicaid expected payers than 

more economically developed counties. In distressed counties, 21.7% of expected payers utilized 

Medicaid, while 15.2% report utilizing Medicaid in at-risk counties. Around 12.5% of payers in 

transitional and competitive counties expect to use Medicaid, and 11.7% of payers in attainment 

counties expect to use Medicaid. In contrast, 35.8% of patients from economically distressed 

counties outside of Appalachia use Medicaid, while counties with higher levels of economic 

development report similar rates of coverage to their Appalachian counterparts. 

The Appalachian region reports lower levels of private insurance coverage than their nonAppalachian counterparts at all levels of economic development, except in at-risk and transitional 

counties. Appalachian distressed counties report 11.9% private insurance coverage compared with 

19.3% for non-Appalachian distressed counties. Appalachian competitive counties report 17.8% 

private insurance coverage, while non-Appalachian competitive counties report coverage rates of 

33.9%. Finally, Appalachian attainment counties report private insurance coverage of 32.7%, while 

non-Appalachian attainment counties report coverage rates of 39.7%. 

Primary Expected Payer by Appalachian County 

Economic Development Status

0

10

20

30

40

50

60

70

Distressed At-Risk Transitional Competitive Attainment

County Economic Development Status

Percent

 Medicare

 Medicaid

 Private including HMO

 Self-pay
136 

Table 4.3a: Admission Source, Type, and Expected Payment for Community Hospital 

Discharges in Appalachia (Unweighted), 2004 

 

 

 

Adults Age 18 or Older 

Appalachian Region Outside of Appalachia 

N % N % 

Admission Source 

 Emergency Room 90,158 53.68 2,688,219 48.79 

 Routine/Other 77,402 46.08 2,805,904 50.93 

Admission Type 

 Emergency Room 85,906 51.19 2,383,357 48.92 

 Routine/Other 81,925 48.81 2,488,366 51.08 

Primary Expected Payer (uniform) 

 Medicare 87,260 51.95 2,386,065 43.31 

 Medicaid 24,406 14.53 770,870 13.99 

 Private including 

 HMO 

41,042 24.44 1,856,881 33.7 

 Self-pay 8,644 5.15 287,340 5.22 

 No charge 48 0.03 29,195 0.53 

 Other 6,373 3.79 173,969 3.16 

Secondary Expected Payer (uniform) 

 Medicare 25,197 29.47 336,954 16.17 

 Medicaid 16,351 19.12 395,946 19 

 Private including 

 HMO 

25,581 29.92 857,683 4.11 

 Self-pay 11,601 13.57 405,953 19.48 

 No charge 46 0.05 7,373 0.35 

 Other 6,776 7.92 80,360 3.85 

SOURCE: Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS), 2004. 
137 

Table 4.3b: Admission Source, Type, and Expected Payment for Community Hospital Discharges in AppalaCounty Economic Development Status, 2004 

County Economic Development Status Adults Age 18 or Older

Distressed At-Risk Transitional Competitive 

Appalachian 

Region 

Outside of 

Appalachia 

Appalachian 

Region 

Outside of 

Appalachia 

Appalachian 

Region 

Outside of 

Appalachia 

Appalachian 

Region 

Outside of 

Appalachia 

N % N % N % N % N % N % N % N % 

Admission Source Emergency Room 19,988 62.12 114,818 73.31 15,118 58.18 23,202 50.55 39,087 54.62 805,370 50.84 3,855 49.15 241,069 50.52 Routine/Other 12,169 37.82 41,748 26.66 10,865 41.81 22,689 49.43 32,094 44.85 774,422 48.89 3,989 50.85 235,955 49.45 Admission Type Emergency Room 

17,035 52.99 116,763 74.6 15,822 60.89 22,625 49.47 36,870 51.55 784,108 49.58 2,116 27.01 201,416 42.7 

Routine/Other 

15,111 47.01 39,747 25.4 10,162 39.11 23,106 50.53 34,649 48.45 797,496 50.42 5,717 72.99 270,310 57.3 

Primary Expected Payer (uniform) Medicare 

17,045 52.98 56,476 36.06 13,452 51.77 24,385 53.13 37,827 52.86 731,421 46.17 4,796 61.14 217,745 45.63 

Medicaid 

6,990 21.72 56,033 35.78 3,945 15.18 8,133 17.72 8,915 12.46 222,512 14.05 1,010 12.88 50,585 10.6 

Private including HMO 

3,818 11.87 30,249 19.31 6,469 24.9 7,551 16.45 19,420 27.14 480,661 30.34 1,400 17.85 161,855 33.92 

Self-pay 1,893 5.88 12,839 8.2 1,229 4.73 2,754 6 2,840 3.97 80,338 5.07 468 5.97 20,570 4.31 No charge 6 0.02 54 0.03 . . 77 0.17 42 0.06 16,320 1.03 . . 6,076 1.27  Other 

2,382 7.4 968 0.62 872 3.36 2,997 6.53 2,389 3.34 52,201 3.3 170 2.17 19,610 4.11 

Secondary Expected Payer (uniform) Medicare 

974 12.51 30,258 27.85 4,634 35.36 2,209 9.89 6,184 15.22 108,043 14.69 105 1.54 20,307 18.09 

Medicaid 

3,726 47.85 37,289 34.32 4,195 32.01 6,088 27.25 6,474 15.94 141,152 19.2 803 11.77 19,113 17.03 

Private including HMO 

2,183 28.04 8,669 7.98 4,275 32.62 10,346 46.32 14,373 35.39 286,765 39 2,775 40.69 58,247 51.89 

Self-pay 1 0 30,985 28.52 2 0.01 374 1.67 11,598 28.56 164,666 22.39 . . 10,225 9.11 No charge 

. . 5 0 . . 0 . 46 0.11 3,566 0.48 . . 150 0.13 

Other 

902 11.58 1,446 1.33 498 3.8 3,694 16.54 1,979 4.87 31,101 4.23 3,137 46 4,200 3.74 

SOURCE: Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS), 2004.
138 

Tables 4.4a and 4.4b, below, presents differences in community hospital discharges based on 

hospital stay characteristics for community hospital discharges in Appalachia and outside of 

Appalachia. Table 4.4a presents the findings overall, and Table 4.4b presents findings by county 

economic development status. Overall, 27.1% of inpatient hospital stays in the Appalachian region 

report mental health or substance abuse diagnoses, compared with 23.6% of inpatient hospital stays 

outside of Appalachia. The differences are most pronounced in distressed counties, where 26.6% of 

hospital stays in the Appalachian region report mental health or substance abuse diagnoses 

compared with 30.5% outside of Appalachia, and in competitive counties where 36.7% of hospital 

stays in the Appalachian region report mental health and substance abuse diagnoses compared with 

22.3% of hospital stays outside of Appalachia. 

Overall, among inpatient hospital stays with a substance abuse or mental health diagnosis, the 

majority had a mental health diagnosis only (77.96% in the Appalachian region; 69.23% outside of 

Appalachia). 

Table 4.4a: Hospital Stay Characteristics for Community Hospital Discharges in Appalachia 

(Unweighted), 2004 

 Adults Age 18 or Older 

Appalachian Region Outside of Appalachia 

N % N % 

Presence of MHSA 

 No MHSA diagnosis 122,401 72.88 4,211,090 76.43 

 At least one MHSA 

 diagnosis 45,556 27.12 1,298,456 23.57 

Subtype of MHSA Stays 

 Principal MHSA only 2,476 5.44 98,803 7.61 

 Principal and secondary 

 MHSA 6,357 13.95 224,415 17.28 

 Secondary MHSA only 36,723 80.61 975,238 75.11% 

At Least One Principal MHSA 

 Yes 8,833 5.26 323,218 5.87 

 No 159,124 94.74 5,186,328 94.13 

Any Secondary MHSA` 

 Yes 43,080 25.65 1,199,653 21.77 

 No 124,877 74.35 4,309,893 78.23 

Coborbidity Status 

 SA Diagnosis Only 5,113 11.22 189,006 14.56 

 MH Diagnosis Only 35,515 77.96 898,948 69.23 

 Comorbidity 4,928 10.82 210,502 16.21 

SOURCE: Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS) 
139 

Table 4.4b: Hospital Stay Characteristics for Community Hospital Discharges in Appalachia by County EcoStatus (Unweighted), 2004 

County Economic Development Status 

Adults Age 18 or Older

Distressed At-Risk Transitional Competitive 

Appalachian 

Region 

Outside of 

Appalachia 

Appalachian 

Region 

Outside of 

Appalachia 

Appalachian 

Region 

Outside of 

Appalachia 

Appalachian 

Region 

Outside of 

Appalachia 

N % N % N % N % N % N % N % N % 

Presence of MHSA No MHSA diagnosis 23,605 73.36 108,879 69.52 19,312 74.32 33,505 73 51,388 71.81 1,191,445 75.21 4,964 63.28 370,658 77At least one MHSA diagnosis 

8,570 26.64 47,742 30.48 6,673 25.68 12,393 27 20,170 28.19 392,711 24.79 2,880 36.72 106,501 22

Subtype of MHSA Stays Principal MHSA only 377 4.6 6,139 12.86 623 9.34 723 5.83 906 4.7 33,667 8.57 137 4.76 6792 6Principal and secondary MHSA 

828 10.11 10,974 22.99 1,205 18.06 2,221 17.92 2,902 15.06 74,780 19.04 848 29.44 17,102 17

Secondary MHSA only 7,365 89.89 30,629 64.16 4,845 72.61 9,449 76.24 16,362 84.94 284,264 72.39 1,895 65.7986 82,607 82At Least One Principal MHSA Yes 1,205 3.75 17,113 10.93 1,828 7.03 2,944 6.41 3,808 5.32 108,447 6.85 985 12.56 23,894 5No 30,970 96.25 139,508 89.07 24,157 92.97 42,954 93.59 67,750 94.68 1,475,709 93.15 6,859 87.44 453,265 94Any Secondary MHSA Yes 8,193 25.46 41,603 26.56 6,050 23.28 11,670 25.43 19,264 26.92 359,044 22.66 2,743 34.97 99,709 20No 23,982 74.54 115,018 73.44 19,935 76.72 34,228 74.57 52,294 73.08 1,225,112 77.34 5,101 65.03 377,450 7Coborbidity Status SA Diagnosis Only 

988 11.53 10,215 21.4 916 13.73 1,480 11.94 1,983 9.83 57,384 14.61 254 8.82 14,434 13

MH Diagnosis Only 

6,943 81.02 25,661 53.75 4,926 73.82 8,993 72.57 15,889 78.78 269,795 68.7 2,061 71.56 76,431 71

Comorbidity 639 7.46 11,866 24.85 831 12.45 1,920 15.49 2,298 11.39 65,532 16.69 565 19.62 15,636 14SOURCE: Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS) 
140 

Tables 4.5a and 4.5b below show findings for diagnoses and principal reason for hospitalization 

for community hospital discharges in Appalachia and outside of Appalachia. Table 4.5a provides 

findings overall, while Table 4.5b shows findings by county economic development status. 

Approximately 4% of hospital discharges in Appalachian counties and outside of Appalachia 

involve an alcohol use disorder diagnosis. Non-Appalachian distressed counties report 8.9% of 

diagnoses containing an alcohol use disorder, compared with 3.0% in Appalachian distressed 

counties. For competitive counties, conversely, 6.3% of diagnoses in the Appalachian region 

involve an alcohol use disorder compared with 4.1% outside of Appalachia. 

Approximately 3% of hospital discharges in Appalachia and 4% of discharges outside of 

Appalachia involve a drug use disorder diagnosis. These findings are consistent across economic 

development levels, with the exception of distressed counties. Non-Appalachian distressed counties 

report that 9.9% of discharges involve a drug use disorder, compared with 2.4% of discharges in 

Appalachian distressed counties. 

Overall, 23.7% of discharges in the Appalachian region involve diagnoses of a mental health 

disorder, compared with 19.5% of discharges outside of Appalachia. For most economic 

development levels, both Appalachian and non-Appalachian counties report about 20% of 

diagnoses as having mental health disorders. However, Appalachian competitive counties report 

33.2% of discharges as having a mental health disorder diagnosis, compared with 18.9% outside of 

Appalachia. 

Overall, alcohol and drug use are reported minimally as principal causes of hospitalization. In the 

Appalachian region, 0.7% of hospitalizations are principally due to alcohol or drug use, compared 

to 0.8% outside the Appalachian region. Differences in hospitalizations principally due to alcohol 

use are most apparent in distressed and attainment counties, where rates of 2.0% and 0.9%, 

respectively are seen outside of Appalachia, compared with Appalachian rates of 0.4% and 0.2%. 

In competitive counties, on the other hand, the Appalachian region reports slightly higher 

percentages of alcohol-related hospitalizations at 0.8% compared to 0.6%. The greatest gap for 

drug-related hospitalizations is in distressed counties, where 2.8% of hospitalizations outside of 

Appalachia are principally due to drug use, compared with 0.5% within Appalachia. 
141 

Table 4.5a: Diagnoses and Principal Reason for Hospitalization for Community Hospital 

Discharges in Appalachia (Unweighted), 2004 

Adults Age 18 or Older 

 Appalachian Region Outside of Appalachia 

 N % N % 

Diagnoses Contain Alcohol Use Disorder 

 Yes 6,358 3.79 247,550 4.49 

 No 6,495 3.87 226,276 4.11 

Diagnoses Contain Drug Use Disorder 

 Yes 5,159 3.07 224,855 4.08 

 No 6,471 3.85 221,578 4.02 

Diagnoses Contain Mental Health Disorder 

 Yes 39,784 23.69 1,075,012 19.51 

 No 1,749 1.04 64,130 1.16 

Principal Reason for Hospitalization was Alcohol Use 

 Yes 1,227 0.73 41,684 0.76 

 No 166,730 99.27 5,467,862 99.24 

Principal Reason for Hospitalization was Drug Use 

 Yes 1,176 0.7 45,888 0.83 

 No 166,781 99.3 5,463,658 99.17 

SOURCE: Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS), 2004. 
142 

Table 4.5b: Diagnoses and Principal Reason for Hospitalization for Community Hospital Discharges in App(Unweighted), by County Economic Development Status, 2004 

County Economic Development Status 

Adults Age 18 or Older 

Distressed At-Risk Transitional Competitive 

Appalachian 

Region 

Outside of 

Appalachia 

Appalachian 

Region 

Outside of 

Appalachia 

Appalachian 

Region 

Outside of 

Appalachia 

Appalachian 

Region 

Outside of 

Appalachia 

N % N % N % N % N % N % N % N % 

Diagnoses Contain Alcohol Use Disorder Yes 956 2.97 13,883 8.86 978 3.76 2,147 4.68 2,963 4.14 75,250 4.75 492 6.27 19,686 4.13 No 978 3.04 9,218 5.89 1,281 4.93 1,801 3.92 2,606 3.64 74,577 4.71 738 9.41 17,017 3.57 Diagnoses Contain Drug Use Disorder Yes 780 2.42 15,443 9.86 1,016 3.91 1,951 4.25 2,129 2.98 71,589 4.52 455 5.8 15,191 3.18 No 950 2.95 8,514 5.44 1,104 4.25 1,719 3.75 2,796 3.91 71,002 4.48 729 9.29 17,896 3.75 Diagnoses Contain Mental Health Disorder Yes 7,517 23.4 32,908 21 5,634 21.7 10,625 23.2 17,866 25 323,434 20.4 2,602 33.2 90,279 18.9 6No 266 0.83 6,470 4.13 588 2.26 716 1.56 687 0.96 25,100 1.58 61 0.78 3,329 0.7 Principal Reason for Hospitalization was Alcohol Use Yes 140 0.44 3,212 2.05 301 1.16 681 1.48 644 0.9 15,490 0.98 66 0.84 3,101 0.65 No 32,035 99.6 153,409 98 25,684 98.8 45,217 98.5 70,914 99.1 1,568,666 99 7,778 99.2 474,058 99.4 30Principal Reason for Hospitalization was Drug Use Yes 176 0.55 4,402 2.81 510 1.96 705 1.54 356 0.5 19,293 1.22 47 0.6 2,033 0.43 No 31,999 99.5 152,219 97.2 25,475 98 45,193 98.5 71,202 99.5 1,564,863 98.8 7,797 99.4 475,126 99.6 30SOURCE: Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS), 2004. 
143 

Tables 4.6a and 4.6b below present differences in community hospital discharges for all principal 

and secondary mental health or substance abuse diagnoses. Results are for adults age 18 and older. 

Table 4.6a provides findings overall, while Table 4.6b provides specific findings by county 

economic development status. Diagnoses cover all principal and secondary mental health or 

substance abuse diagnoses. Overall, 10.6% of discharges in the Appalachian region and 13.7% of 

discharges outside of Appalachia were screened for mental health problems. Screening for mental 

health problems constitutes the majority of discharge diagnoses outside of Appalachia. The gap 

between Appalachia and areas outside of Appalachia is largest in the two most economically 

developed categories, with approximately 8% of discharges in competitive and attainment counties 

in Appalachia being attributed to screening, compared to 14.5% in non-Appalachian counties. 

Overall, 5.6% of discharges in the Appalachian region are attributed to anxiety disorders, compared 

with 3.5% outside of Appalachia. No distinct pattern emerges based on the economic development 

status, with the largest gaps between Appalachian and non-Appalachian counties occurring in 

distressed counties (7.4% of discharges in the Appalachian region compared with 2.1% outside of 

Appalachia), and competitive counties (7.7% of discharges in the Appalachian region compared 

with 3.7% outside of Appalachia). 

Overall, 5.9% of discharges in the Appalachian region are due to delirium, dementia, and amnestic 

and other cognitive disorders, compared with 5.2% outside of Appalachia. In less economically 

developed counties, there is little regional difference in rates of these diagnoses. In competitive 

counties, however, 7.2% of discharges in the Appalachian region are due to this type of diagnosis, 

compared with 4.9% outside of Appalachia. In attainment counties, conversely, 3.0% of diagnoses 

in the Appalachian region are due to delirium and other cognitive disorders, compared with 5.2% 

outside of Appalachia. 

Overall, 12.3% of diagnoses in the Appalachian region and 10.1% of diagnoses outside of 

Appalachia are due to mood disorders. Mood disorders constitute the majority of diagnoses, 

overall, in Appalachia. The most striking regional difference occurs in competitive counties, where 

20.1% of mental health and substance abuse diagnoses in the Appalachian region are due to mood 

disorders, compared to 10% outside of Appalachia. 

Overall, 6.0% of discharges in the Appalachian region, and 7.2% of discharges outside of 

Appalachia are due to substance-related disorders. Strikingly, in non-Appalachian distressed 

counties, substance-related disorders constitute the predominant mental health diagnosis, 

comprising 14.1% of diagnoses. In contrast, only 5.1% of diagnoses in distressed Appalachian 

counties are attributed to substance-related disorders. 
144 

Table 4.6a: Differences Among All Principal and Secondary Mental Health or Substance 

Abuse Diagnoses for Discharges from Community Hospitals, 2004 

Adults Age 18 or Older

Appalachian Region Outside of Appalachia 

 N % N % 

Adjustment disorders 384 0.23 21,318 0.39 

Anxiety disorders 9,369 5.58 191,077 3.47 

Attention-deficit, conduct, and disruptive 

behavior disorders 291 0.17 8,837 0.16 

Delirium, dementia, and amnestic and other 

cognitive disorders 9,962 5.93 287,877 5.23 

Developmental disorders 1,386 0.83 31,533 0.57 

Disorders usually diagnosed in infancy, 

childhood, adolescence 54 0.03 1,927 0.03 

Impulse control disorders, NEC 247 0.15 4,023 0.07 

Mood disorders 20,718 12.34 556,748 10.11 

Personality disorders 1,572 0.94 42,250 0.77 

Schizophrenia, other psychotic disorders 3,480 2.07 143,039 2.6 

Substance-related disorders 10,041 5.98 399,508 7.25 

Miscellaneous mental disorders 1,612 0.96 56,812 1.03 

Screening and history of mental health and 

substance abuse codes 17,742 10.56 755,481 13.71 

SOURCE: Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS), 2004.
145 

Table 4.6b: Differences Among All Principal and Secondary Mental Health or Substance Abuse Diagnoses DCommunity Hospitals, by County Economic Development Status, 2004 

County Economic Development Status Adults Age 18 or Older

Distressed At-Risk Transitional Competitive 

Appalachian 

Region 

Outside of 

Appalachia 

Appalachian 

Region 

Outside of 

Appalachia 

Appalachian 

Region 

Outside of 

Appalachia 

Appalachian 

Region 

Outside of 

Appalachia 

 N % N % N % N % N % N % N % N % 

Adjustment disorders 57 0.18 868 0.55 54 0.21 92 0.2 177 0.25 7,561 0.48 19 0.24 2,107 0.4 Anxiety disorders 2,394 7.44 3,269 2.09 1,159 4.46 2,242 4.88 3,860 5.39 58,425 3.69 604 7.7 17,517 3.7 Attention-deficit, conduct, and disruptive behavior disorders 24 0.07 78 0.05 24 0.09 71 0.15 136 0.19 2,677 0.17 36 0.46 769 0.2 Delirium, dementia, and amnestic and other cognitive disorders 2,030 6.31 9,802 6.26 1,522 5.86 2,928 6.38 4,939 6.9 83,306 5.26 568 7.24 23,263 4.9 Developmental disorders 248 0.77 1,092 0.7 198 0.76 380 0.83 698 0.98 9,550 0.6 27 0.34 2,531 0.5 Disorders usually diagnosed in infancy, childhood, adolescence 3 0.01 61 0.04 6 0.02 8 0.02 24 0.03 549 0.03 4 0.05 164 0 Impulse control disorders, NEC 25 0.08 201 0.13 60 0.23 61 0.13 138 0.19 1,362 0.09 15 0.19 469 0.1 Mood disorders 3,074 9.55 12,903 8.24 2,858 11 5,481 11.94 9,324 13.03 164,347 10.37 1,576 20.1 47,578 10 Personality disorders 27 0.08 841 0.54 150 0.58 453 0.99 703 0.98 13,437 0.85 596 7.6 4,789 1 Schizophrenia, other psychotic disorders 762 2.37 9,084 5.8 519 2 1,046 2.28 1,463 2.04 45,583 2.88 273 3.48 9,070 1.9 Substance-related disorders 1,627 5.06 22,081 14.1 1,747 6.72 3,400 7.41 4,281 5.98 122,916 7.76 819 10.4 30,070 6.3 Miscellaneous mental disorders 239 0.74 694 0.44 192 0.74 278 0.61 941 1.32 16,994 1.07 102 1.3 6,417 1.3 Screening and history of mental health and substance abuse codes 3,184 9.9 12,299 7.85 2,234 8.6 6,031 13.14 9,650 13.49 199,570 12.6 694 8.85 69,182 15 SOURCE: Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS), 2004. 
146 

Tables 4.7a and 4.7b, below, show sub-regional differences among community hospital discharges 

by substance abuse and mental health diagnoses as the major reason for hospitalization for adults 

over age 18. Table 4.7a provides findings overall for admissions from Appalachian community 

hospitals versus non-Appalachian community hospitals. Table 4.7b provides findings by county 

economic development status. Overall, 5.4% of all hospitalizations in the Appalachian region, and 

6.1% of hospitalizations outside of Appalachia are attributed to mental health or substance abuse 

diagnoses. In Appalachia and outside of Appalachia, 0.2% of hospitalizations are attributed to 

screening for mental health disorders. There is little variation based on the level of economic 

development in the region. 

Overall, 0.5% of diagnoses in the Appalachian region and 0.4% of diagnoses outside of Appalachia 

are due to delirium, dementia, and amnestic and other cognitive disorders. Appalachian transitional 

and competitive counties report around 0.7% of hospitalizations due to delirium and other cognitive 

disorders, compared with about 0.4% outside of Appalachia. Conversely, in attainment counties, 

only about 0.2% of diagnoses in the Appalachian region are related to cognitive disorders, 

compared with 0.4% outside of Appalachia. 

Overall, 2.1% of hospitalizations in Appalachia and outside of Appalachia are due to mood 

disorders. Mood disorders, overall, are the leading mental health or substance abuse diagnosis 

associated with hospitalizations in Appalachia and outside of Appalachia. In Appalachian 

distressed counties, 1.1% of hospitalizations are due to mood disorders, compared with 2.0% in 

non-Appalachian distressed counties. Mood disorders are the leading mental health or substance 

abuse diagnosis associated with hospitalizations among distressed counties in Appalachia. Mood 

disorders are also the leading mental health or substance abuse diagnosis associated with 

hospitalization in transitional counties in Appalachia and outside of Appalachia (2.1% and 2.3% of 

hospitalizations, respectively). In competitive counties in the Appalachian region, 7.6% of 

hospitalizations are due to mood disorders, compared with 2.1% in competitive counties outside of 

Appalachia. Despite this gap, mood disorders constitute the main mental health or substance abuse 

diagnosis linked to hospitalizations in competitive counties both in Appalachian and outside of 

Appalachia. Mood disorders are also the main diagnosis associated with hospitalizations for 

attainment counties in Appalachia and outside of Appalachia. 

Overall, 0.8% of hospitalizations in the Appalachian region and 1.3% of hospitalizations outside of 

Appalachia are associated with a diagnosis of schizophrenia and other psychotic disorders. There 

are no discernable patterns associated with level of economic development around this diagnosis. 

In distressed counties, 0.9% of diagnoses in the Appalachian region and 3.3% of hospitalizations 

outside of Appalachia are linked to this diagnosis. In competitive counties, on the other hand, these 

values are switched. 

Overall, about 1.5% of hospitalizations in Appalachia and outside of Appalachia are due to 

substance-related disorders. In distressed counties, 1.0% of Appalachian and 4.9% of nonAppalachian hospitalizations are due to substance-related disorders. Outside of Appalachia, this 

constitutes the largest source of mental health or substance abuse diagnoses. Substance-related 

disorders also constitute the most frequent diagnosis associated with hospitalizations among mental 

health or substance abuse diagnoses in at-risk counties within Appalachia and outside of Appalachia 

(3.1% and 3.0% of hospitalizations, respectively). 
147 

Table 4.7a: Differences Among Community Hospital Discharges by Substance Abuse and 

Mental Health Diagnoses as the Major Reason for Hospitalization, 2004 

Adults Age 18 or Older

Appalachian Region Outside of Appalachia 

N % N % 

Adjustment disorders 92 0.05 6,637 0.12 

Anxiety Disorders 248 0.15 6,664 0.12 

Attention-deficit, conduct, and 

disruptive behavior disorders 

3 0 186 0 

Delirium, dementia, and amnestic and 

other cognitive disorders 915 0.54 22,526 0.41 

Developmental disorders 12 0.01 267 0 

Disorders usually diagnosed in infancy, 

childhood, adolescence 

4 0 133 0 

Impulse control disorders, NEC 38 0.02 1,268 0.02 

Mood disorders 3,519 2.1 117,444 2.13 

Personality disorders 17 0.01 790 0.01 

Schizophrenia and other psychotic 

disorders 

1,319 0.79 72,713 1.32 

 Substance-related disorders 2,403 1.43 87,572 1.59 

Miscellaneous mental disorders 

275 0.16 7,285 0.13 

Screening and history of mental health 

and substance abuse codes 306 0.18 12,789 0.23 

 SOURCE: Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS), 2004.
148 

Table 4.7b: Differences Among Community Hospital Discharges by Substance Abuse and Mental Health DiReason for Hospitalization by County Economic Development Status, 2004 

County Economic Development Status 

Adults Age 18 or Older

Distressed At-Risk Transitional Competitive 

Appalachian 

Region 

Outside of 

Appalachia 

Appalachian 

Region 

Outside of 

Appalachia 

Appalachian 

Region 

Outside of 

Appalachia 

Appalachian 

Region 

Outside o

Appalach

N % N % N % N % N % N % N % N 

Adjustment disorders 13 0.04 349 0.22 21 0.08 48 0.1 43 0.06 2,752 0.17 1 0.01 580 0Anxiety Disorders 34 0.11 108 0.07 70 0.27 83 0.2 97 0.14 2,135 0.13 18 0.23 830 0Attention-deficit, conduct, and disruptive behavior disorders 

. . 7 0 2 0.01 1 0 . . 75 0 . . 19 

Delirium, dementia, and amnestic and other cognitive disorders 

139 0.43 482 0.31 105 0.4 147 0.3 560 0.78 6,563 0.41 50 0.64 1,698 0

Developmental disorders 

1 0 19 0.01 . . 1 0 7 0.01 99 0.01 1 0.01 32 0

Disorders usually diagnosed in infancy, childhood, adolescence 

1 0 5 0 . . 1 0 1 0 40 0 1 0.01 11 

Impulse control disorders, NEC 

6 0.02 94 0.06 22 0.08 18 0 7 0.01 440 0.03 1 0.01 184 0

Mood disorders 345 1.07 3,161 2.02 513 1.97 815 1.8 1,510 2.11 36,314 2.29 595 7.59 10,134 2Personality disorders . . 27 0.02 1 0 1 0 10 0.01 252 0.02 4 0.05 74 0Schizophrenia and other psychotic disorders 

296 0.92 5,143 3.28 237 0.91 382 0.8 465 0.65 22,914 1.45 176 2.24 4,459 0

 Substance-related disorders 

316 0.98 7,614 4.86 811 3.12 1,386 3 1,000 1.4 34,783 2.2 113 1.44 5,134 1

Miscellaneous mental disorders 

55 0.17 123 0.08 46 0.18 62 0.1 115 0.16 2,179 0.14 26 0.33 771 0

Screening and history of mental health and substance abuse codes 

49 0.15 361 0.23 34 0.13 87 0.2 129 0.18 3,399 0.21 26 0.33 1,027 0

SOURCE: Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS), 2004.
149 

Table 4.8: Adult Patients Diagnosed with Mental Health Disorders in Community Hospitals, 

2004 

Table 4.8 above provides data on adult patients diagnosed with mental health disorders in 

community hospitals in Appalachia and outside of Appalachia. More adults in Appalachian 

community hospitals were diagnosed with the following disorders than their non-Appalachian 

counterparts: anxiety disorders; delirium, dementia, and amnestic and other cognitive disorders; 

developmental disorders (includes communication disorders, developmental disabilities, intellectual 

disabilities, learning disorders, and motor skill disorders); impulse control disorders; and personality 

disorders. Results are statistically significant (p<0.01). 

Age 18 and older 

Appalachian Region Outside of Appalachia 

 N=794,546 

Count (Percent) 

N=31,930,000 

Count (Percent) 

Adjustment disorders 1,862 (0.23%)*** 121,197 (0.39%)*** 

Anxiety disorders 43,996 (5.54%)*** 1,108,665 (3.56%)*** 

Attention-deficit, conduct, and disruptive 

behavior disorders 

1,320 (0.17%) 50,105 (0.16%) 

Delirium, dementia, and amnestic and other 

cognitive disorders 

47,016 (5.92%)*** 1,643,622 (5.28%)*** 

Developmental disorders 6,523 (0.82%)*** 181,070 (0.58%)*** 

Disorders usually diagnosed in infancy, 

childhood, or adolescence 

247 (0.03%) 10,786 (0.03%) 

Impulse control disorders 1,196 (0.15%)*** 24,056 (0.08%)*** 

Personality disorders 7,145 (0.90%)*** 246,001 (0.79%)*** 

Schizophrenia and other psychotic disorders 16,368 (2.06%)*** 804,620 (2.58%)*** 

Substance-related disorders 47,251 (5.95%)*** 2,205,822 (7.08%)*** 

Miscellaneous mental disorders 7,887 (0.99%)*** 326,184 (1.05%)*** 

Screening and history of mental health and 

substance abuse codes 

83,813 (10.55%)*** 4,368,709 (14.03%)*** 

SOURCE: Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS), 2004. 

Notes: 

1

 Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. 2

 Analysis is limited to hospital discharges with patients age 18-59; Weighted length and charge estimates are presented. 3

 ***The individual coefficient is statistically significant at the 1% level using a two-sided test. 

4

 **The individual coefficient is statistically significant at the 5% level using a two-sided test. 

5

 *The individual coefficient is statistically significant at the 10% level using a two-sided test.
150 

4.5 Discussion 

The Nationwide Inpatient Sample (NIS) data of the Healthcare Cost and Utilization Project (HCUP) 

provide important and unique information to understand the extent of substance use and mental 

disorders among patients discharged from the community hospitals. Findings described in this 

chapter point to several disparities between Appalachian and non-Appalachian community hospital 

discharges, as well as discharges across Appalachian sub-regions and county economic 

development levels. In addition, findings from this chapter emphasize that mental health problems 

are paramount in the Appalachian region. 

Path to admission 

Patients in the Appalachian region are more likely to be admitted through the emergency 

department (ED) than patients outside of the Appalachian region. This disparity appears to 

concentrate in “At-Risk” and “Transitional” counties as compared to other counties. Economic 

disadvantage is a likely factor in limiting people’s tendency to seek preventive care or get low cost, 

non-emergency health care. 

Payment for services 

In Appalachia, over 67 percent of adult hospital stays were billed to the government in 2004; 

Medicaid was billed for 15% of all stays and Medicare was billed for 52% of all stays. In 

comparison, 57 percent of adult hospital stays outside of Appalachia were billed to the government; 

Medicaid was billed for 14% of all stays and Medicare was billed for 43% of all stays. The 

percentages of inpatient hospital stays billed to Medicaid overall are almost the same between 

Appalachia and non-Appalachia counties. As expected, less economically developed counties in 

Appalachia report a greater percentage of Medicaid expected payers than more economically 

developed counties. However, fewer stays in Appalachian community hospitals in “Distressed,” 

“At-Risk,” and “Transitional” counties were billed to Medicaid than in non-Appalachian counties of 

similar economic development status. It appears that the delivery or utilization of government 

support across communities with differing economic development levels is uneven. It is notable that 

individuals in the most disadvantaged communities are actually less likely to benefit from 

government support. 

Substance abuse and/or mental disorder diagnoses 

 

Community hospitals play an important role in identifying and treating individuals with MHSA 

disorders, even when MHSA disorders are not the primary reason for an individual’s hospital visit. 

Overall, the percentage of admissions in Appalachia for patients with principal and/or secondary 

MHSA diagnoses is higher than the percentage outside of Appalachia. 

This study also reveals that the vast majority of hospital stays with MHSA diagnoses are mental 

health related; and the rate is higher in Appalachia than outside of Appalachia. The rate of cooccurrence of substance abuse and mental disorders, however, is lower in Appalachia than outside 

of Appalachia, especially in economically-distressed areas. The high presence of admissions with 

mental health disorders in Appalachia is a likely challenge to Appalachian community hospitals as 

these facilities, by definition, are not mental health hospitals. 
151 

REFLECTIONS FROM PRACTITIONERS 

 From the Coalition on Appalachian Substance Abuse Policy 

Challenges Associated with Using the Health Care Cost and Utilization 

Project (HCUP) National Inpatient Survey to Explore Substance Abuse and 

Mental Health in Appalachia 

• HCUP provides an underestimation of the mental health problems in

Appalachia and nationally because mental health hospitals are not

included in the data set.   

• Facility reporting practices are often affected by payment. CASAP noted

that hospitals participating in HCUP are likely to underreport substance

abuse issues for admissions.  Hospitals are not paid if the primary reason for

admission is related to a substance abuse problem.    According to CASAP,

hospitals may code the client’s reason for admission as a physical or mental

health problem, if possible, to secure payment.  As a result, the HCUP data

may significantly understate substance abuse problems.

• CASAP noted that the findings from the HCUP data set were more

consistent with their experiences than findings from TEDS, N‐SSATS, and

NSDUH.
152 

CHAPTER 5: Substance Abuse Treatment Services in the Appalachian 

Region, 2005 

5.1 Introduction 

The National Survey of Substance Abuse Treatment Services (N-SSATS) enables researchers to 

view an annual snapshot of the character and composition of the substance abuse treatment delivery 

system in the United States. N-SSATS allows us to make comparisons across geographic areas and 

among different populations with substance abuse issues. Chapter 5 provides an overview of 

substance abuse treatment services in and outside of Appalachia on the reference date of March 31, 

2005. The sample analyzed in this study includes 13,367 substance abuse treatment facilities from 

which data were collected in 2005. Of all these facilities, 980 (7.3%) were from the Appalachian 

region,13 and 12,391 (92.7%), were from the rest of the country.14 All analyses in this chapter are 

based on N-SSATS data. 

We explore the following key research questions for facilities in Appalachia and facilities outside of 

Appalachia: 

Do substance abuse facilities in Appalachia offer inpatient detoxification services? 

What are the ownership structures for the Appalachian treatment facilities and how do they 

compare to those of other facilities? 

What is the primary focus of Appalachian substance abuse facilities (e.g., substance abuse 

services, mental health services, general health care services, etc.)? 

What types of health insurance do facilities accept (e.g., Medicare, Medicaid, state financed 

insurance, private health insurance)? 

In Section 5.2, we provide an overview of the N-SSATS series, its uses, the measures relevant to 

this study, and any limitations specifically related to exploring admissions to substance abuse 

treatment in the Appalachian region. In Section 5.3, we discuss our methods. Section 5.4 contains 

the results of the analysis. Finally, Section 5.5 provides a discussion of key findings. 

5.2 Data 

5.2.1 Overview 

The National Survey of Substance Abuse Treatment Services (N-SSATS) collects data from public 

and private substance abuse treatment facilities in the United States. The term “facility” represents 

program-level, clinic-level, or multi-site respondents.83 N-SSATS provides information such as 

substance abuse treatment facility characteristics and key characteristics of clients receiving 

substance abuse treatment or services.84 

 

13 The Appalachian region is defined as the 410 designated counties in all of West Virginia and parts of 12 other states: 

Alabama; Georgia; Kentucky; Maryland; Mississippi; New York; North Carolina; Ohio; Pennsylvania; South Carolina; 

Tennessee; and Virginia 

14 The data description from the user’s guide showed 13,367 in-scope cases and our total analytic sample has 13,371 

cases. 
153 

The objective of N-SSATS is to collect data that can be used by the Substance Abuse and Mental 

Health Services Administration (SAMHSA) and state and local governments to: (1) assist 

SAMHSA in assessing the nature and extent of services provided and in forecasting treatment 

resource requirements; (2) update SAMHSA's Inventory of Substance Abuse Treatment Services (ISATS); (3) analyze general treatment services trends; and (4) generate the National Directory of 

Drug and Alcohol Abuse Treatment Programs and its online Abuse Treatment Facility Locator 

equivalent, the Substance Abuse Treatment Facility Locator.85

Planned and directed by SAMHSA, N-SSATS was originally launched in the 1970s to collect 

information on the characteristics of treatment facilities, including their location and utilization of 

treatment facilities and services. N-SSATS collects data from the 50 states, the District of 

Columbia, and other U.S. jurisdictions (including the territories of American Samoa and Guam, the 

Federated States of Micronesia, the Republic of Palau, the Commonwealth of Puerto Rico, and the 

Virgin Islands of the United States). Data are collected on the following topics: 

ownership/operation; primary focus (substance abuse, mental health, both, general health, other); 

organizational setting; services offered; languages spoken other than English; programs or groups 

for special populations; type of treatment provided; types of payment accepted; managed care 

agreements; sources and amounts of revenue; number of clients under age 18; number of clients by 

age, sex, race and ethnicity; client substance abuse problem treated; and licensure/ certification of 

facility and staff. 

The 2005 N-SSATS was conducted between March and October 2005. In 2005, a total of 13,371 

substance abuse treatment facilities responded to N-SSATS.86 

5.2.2 Sample Design 

N-SSATS is a point-prevalence survey, meaning that it provides information about the substance 

abuse treatment facilities on a particular reference date. For the 2005 N-SSATS, the reference date 

was March 31, 2005. The N-SSATS provides a snapshot of the substance abuse delivery system on 

this reference date. 

The Inventory of Substance Abuse Treatment Services (I-SATS) provides the sampling frame for 

N-SSATS. The survey universe contains treatment facilities listed on the I-SATS six weeks prior to 

the reference data and those added by state substance abuse agencies or discovered during the first 

three weeks of the survey. The treatment facilities included are licensed, certified, or approved by 

the state substance abuse agency and facilities that state substance abuse agencies do not license or 

certify (e.g., private, for-profit, small group practices, or hospital-based programs). 

Several features of N-SSATS are important to note. First, the total number of patients treated does 

not represent the annual total number of clients at these facilities. This is because N-SSATS 

provides a snapshot of treatment facilities on a single day. As a result, we do not have information 

about the annual number of clients treated, nor can we assume that facilities were treating clients at 

their full capacity. Second, N-SSATS collects data about substance abuse treatment facilities, 

rather than individual clients. Third, N-SSATS does not include treatment programs in jails or 

prisons. Finally, client data are aggregated for each facility that reports to N-SSATS.87

Data for N-SSATS are collected by Mathematica Policy Research, Inc. For 2005, N-SSATS 

questionnaires were distributed via mail to 16,418 facilities.88 The facilities that received the mail 
154 

questionnaire were believed to offer substance abuse treatment services. Approximately 10 percent 

of these facilities had closed or were not providing substance abuse treatment on the reference date, 

and were therefore deemed ineligible to participate. Of the remaining 14,747 facilities, 95.3% 

completed the survey.89 Of these, an additional 680 facilities were considered out of scope or had 

no facility information. The final sample size was 13,367 (90.6 percent of the survey universe). 

The response rate was 44.5 percent for the mail survey.90 The same survey was offered in telephone 

and Web-based formats. The response rate for the telephone survey was 22.1 percent, slightly 

lower than the 33.4 percent response rate for the Web-based questionnaire.91 Upon completion of 

data collection, Synectics for Management Decisions, Inc., prepares the file for release. 

5.2.3 Uses of the N-SSATS 

N-SSATS enables researchers to explore the demographic and substance abuse characteristics of 

admissions to and discharges from substance abuse treatment. SAMSHA releases an annual report 

based on the N-SSATS data as well as a national profile.92,93 The annual report explores trends in 

facility characteristics, client characteristics, and facility services. The national profile provides a 

high level overview of the N-SSATS data. N-SSATS data were also used to develop The National 

Directory of Drug and Alcohol Abuse Treatment Programs 2005, a searchable directory of 10,000 

drug and alcohol treatment programs across the country.94

N-SSATS data have been used to explore a number of research questions related to substance abuse 

treatment. A recent study used N-SSATS data to examine the relationships between state 

authorization type (certification/accreditation versus licensure with and without deemed status) and 

outpatient treatment program practices, for example.95 

N-SSATS has also been used to explore the distribution of specialized programs or groups in 

substance abuse treatment facilities across the United States. Studies have examined services and 

programs available for adolescents, criminal justice clients, and pregnant or postpartum 

women.96,97,98,99 Research has also focused on the availability of the treatment services (including 

clinical, social, and health services) for clients with co-occurring mental health and substance abuse 

disorders at these facilities.100

Other studies that have applied N-SSATS data have explored profit status and the effects on the 

provision of drug treatment services,101 opioid treatment programs,102 and the role of state policies 

in the adoption of naltrexone for substance abuse treatment.103 

The Office of Applied Studies (OAS) at SAMHSA also releases the Drug and Alcohol Services 

Information System (DASIS) Series report annually on drug and alcohol services. The DASIS is 

the primary source of national data on substance abuse treatment, developed from N-SSATS, the 

Treatment Episode Data Set (TEDS), and the Inventory of Substance Abuse Treatment Services (ISATS). 

5.2.4 N-SSATS Measures Used in this Study 

Next, we define the measures used from the 2005 N-SSATS, and explore the potential limitations 

with respect to using these measures for our purpose – exploring the characteristics of and services 

provided by substance abuse treatment facilities in the Appalachian region and other regions 
155 

nationally. We explore a number of variables related to services offered, groups treated, and 

payment/ insurance options. 

We explored measures indicating which substance abuse treatment facilities offer inpatient 

detoxification and looked at the primary focus of facilities – specifically, whether they offered 

substance abuse services, mental health services, a mix of mental health and substance abuse 

services, or general health care services. Next, we looked at which facilities accept adolescents for 

treatment. In terms of payment, we examined which facilities use a sliding fee scale and which 

facilities offer free or no charge treatment. Finally, we provide N-SSATS data on facilities that 

accept Medicare, Medicaid, state financed health insurance, and private insurance. 

5.2.5 Limitations of the N-SSATS 

There are several limitations with respect to using N-SSATS to explore the composition and 

characteristics of substance abuse treatment facilities in Appalachian counties as compared to other 

counties nationally. 

One serious limitation is that N-SSATS does not capture data from all of the substance abuse 

treatment facilities that may be relevant to this study. Several types of facilities were excluded from 

the 2005 N-SSATS analyses, including: halfway houses that do not provide substance abuse 

treatment; jails, prisons, or other organizations that treat incarcerated patients only; individual 

practitioners that were not recommended by the State substance abuse agency for inclusion; and 

other facilities whose client counts were included within the counts of other facilities.104 In addition 

to excluding certain facilities, state licensure and certification policies also may affect which 

facilities are in the N-SSATS survey universe.15 Finally, N-SSATS is a voluntary survey, and thus, 

does not reflect all substance abuse treatment facilities in the United States. The response rate is 

very high overall (about 95%), however. In this study, no adjustments have been made for facility 

non-response (approximately 5%) so non-response bias may affect results.105 

For these reasons, it is important to note that the N-SSATS does not capture data from all of the 

facilities that may be relevant to this study. This limitation is particularly problematic for this study 

because we are making comparisons between the Appalachian counties and all other counties 

nationally. If facilities in states in the Appalachian region submit data less often than other states, 

then our findings may be skewed. 

A second limitation is that N-SSATS is a point-prevalence survey. Thus, the data do not reflect the 

annual total number of clients receiving treatment at substance abuse facilities, but rather they 

provide a snapshot based on a single reference date. 

There are several limitations related to the survey’s design and content. For certain variables (e.g., 

services provided and specialized programs), facilities can enter multiple responses. However, the 

data only reflect the total number of treatment facilities that entered each response. In addition, NSSATS only reports that a service, such as inpatient detoxification, is offered. The data do not in 

 

15 According to project staff at the Office of Applied Studies, which funded and governed the data collection, the state 

licensure policies are not an important data concern. While the state is charged with helping to identify substance 

abuse treatment facilities, encouraging facilities to respond to the survey, and determining eligibility for inclusion in the 

published directory, they do not determine which agencies are actually surveyed. 
156 

any way reflect the quality of the service delivered, or whether the service has been received by the 

patient. Thus, our findings cannot speak to the quality of care received in Appalachian treatment 

facilities versus other facilities nationwide. One last limitation to note is that some financial data 

originally collected through the survey have been omitted from the public use file for confidentiality 

reasons. 

5.3 Methods 

5.3.1 Study Sample 

The sample analyzed in this study includes 13,371 substance abuse treatment facilities from which 

data were collected in 2005. Of all these facilities, 891 (7.3%) were from the 318 counties in the 

Appalachian region,16 and 12,391 (92.7%), were from the rest of the country.17

5.3.2 Statistical Methods 

 

Appalachian Regional Status. A key purpose of analyzing the N-SSATS is to obtain an overview of 

the characteristics of the substance abuse treatment facilities in the Appalachian region, as 

compared to substance abuse treatment facilities located outside of the Appalachian region. Our 

first step of the analysis is to match the census county FIPS codes in the 2005 N-SSATS with the 

FIPS codes of the 410 Appalachian counties as defined by the Appalachian Regional Commission. 

This creates a regional status flag variable to group all substance abuse treatment facilities into one 

of two groups – facilities located in the Appalachian region and facilities outside of the Appalachian 

region. 

Research Variables. Research variables for the analysis covered the following characteristics of the 

substance abuse treatment facilities: availability of inpatient detoxification services; primary 

substance abuse treatment facility focus areas; provision of services for adolescents; availability of a 

sliding fee scale; availability of no-cost treatment; acceptance of Medicare; acceptance of Medicaid; 

acceptance of state financed health insurance; and acceptance of private health insurance. 

Analysis. Data were analyzed using descriptive statistics. Cross-tabulations were examined to assess 

the distribution of aggregated frequencies and proportions of various facility characteristics between 

facilities in the Appalachian region and those outside of the Appalachian region. Chi-square tests 

were performed for tabulations to test for statistical significance of the differences. Data were 

compiled and analyzed with SPSS statistical software version 14.0 (SPSS Inc., Chicago, IL). 

5.4 Results 

Next, we present our results for substance abuse treatment facilities in Appalachia and outside of 

Appalachia. We present other findings in Section 5.4.1 about the ownership of substance abuse 

treatment facilities, characteristics of these facilities; a comparison of services offered in the 

 

16 The Appalachian region is defined as the 410 designated counties in all of West Virginia and parts of 12 other states: 

Alabama; Georgia; Kentucky; Maryland; Mississippi; New York; North Carolina; Ohio; Pennsylvania; South Carolina; 

Tennessee; and Virginia 

17 The data description from the user’s guide showed 13,367 in-scope cases and our total analytic sample has 13,371 

cases. 
157 

inpatient, outpatient, and non-hospital residential care settings; pharmacotherapies provided; and 

types of services offered at facilities, generally. In Section 5.4.2, we describe a series of figures that 

illustrate comparisons between Appalachian treatment facilities and non-Appalachian treatment 

facilities. We provide figures showing our findings related to inpatient detoxification services, the 

primary focus of facilities; and health insurance and payment options available at the treatment 

facilities (e.g., free or no charge, Medicare, Medicaid, state financed health insurance, and private 

health insurance). 

5.4.1 Tables 

Table 5.1: Ownership and Other Characteristics of Substance Abuse Treatment Facilities, 

2005

 Region 

Appalachia 

N=891 

Non-Appalachia 

N=12,480 

p-value 

N % N %

Ownership 

Private for-profit organization 204 22.90 3,367 26.98 

<0.0001 

Private non-profit organization 557 62.51 7,355 58.93 

State government 40 4.49 413 3.31 

Local, county, or community government 65 7.30 882 7.07 

Tribal government 3 0.34 167 1.34 

Federal government 22 2.47 296 2.37 

Other Characteristics 

 Receives public funds1 868 70.05 12,480 65.32 0.0046 

 Arrangements/contracts with managed care 

 organizations2

842 58.08 11,869 49.10 <0.0001 

NOTES: 

1 Public funds include federal, state, county, or local government funds for substance abuse treatment programs. 

2

 Managed care organizations have agreements with certain health care providers who provide services to plan members (e.g., 

managed behavioral health care organizations, health maintenance organizations, and preferred provider organizations). 

SOURCE: U.S. Dept. of Health and Human Services, Substance Abuse and Mental Health Services Administration, Office of 

Applied Studies. National Survey of Substance Abuse Treatment Services (N-SSATS), 2005. 

Table 5.1 describes the ownership and other characteristics of substance abuse treatment facilities 

in the Appalachian region and in the non-Appalachian region in 2005. The majority of substance 

abuse treatment facilities in Appalachia (62.51%) and outside of Appalachia (58.93%) are owned by 

private non-profit organizations. Proportionately, more Appalachian facilities are owned by the 

federal government (2.47%) than facilities outside of the Appalachian region (2.37%). 

Proportionately more Appalachian facilities are owned by a state government (4.49%) or a local, 

county or community government (7.30%) than treatment facilities outside of Appalachia (3.31% 

and 7.07%, respectively). Fewer Appalachian facilities than non-Appalachian facilities are owned 

by a private-for-profit organization (22.90% vs. 26.98%) or tribal government (0.34% vs. 1.34%). 

Results are statistically significant at the 99% confidence level. 
158 

Proportionately more treatment facilities in Appalachia than outside of Appalachia receive public 

funds for their treatment programs, though more Appalachian facilities than non-Appalachian 

facilities receive these funds; results are statistically significant at the 95% confidence level. 

Proportionately more facilities in Appalachia have contracts or arrangements with managed care 

organizations (58.08%) than facilities outside of Appalachia (49.10%); results are statistically 

significant (p<0.0001). 

Table 5.2 Characteristics of Substance Abuse Treatment Facilities, 2005 

 Region 

Appalachia Non-Appalachia p-value 

N % N % 

Accredited by the Joint Commission on the 

Accreditation of Healthcare Organizations (JCAHO) 1

891 27.38 12,480 22.92 0.0023 

Accredited by Commission on Accreditation of 

Rehabilitation Facilities (CARF) 2

891 13.69 12,480 16.51 0.0277 

Licensed/certified by public health department 891 44.78 12,480 38.65 0.0003 

Licensed/certified by state mental health department 891 44.00 12,480 29.78 <0.0001 

Licensed/certified by state substance abuse agency 891 69.14 12,480 81.35 <0.0001 

NOTES: 

1 JCAHO sets standards for healthcare organizations and issues accreditation to organizations that meet those standards. 

2 CARF is an independent, non-profit organization that reviews and grants accreditation services nationally and internationally per 

the request of facilities or programs. 

SOURCE: U.S. Dept. of Health and Human Services, Substance Abuse and Mental Health Services Administration, Office of 

Applied Studies. National Survey of Substance Abuse Treatment Services (N-SSATS), 2005. 

Table 5.2 describes the characteristics of substance abuse treatment facilities in the Appalachian 

region and outside of Appalachia in 2005. Proportionately more Appalachian than nonAppalachian treatment facilities are accredited by the Joint Commission on the Accreditation of 

Healthcare Organizations (JCAHO) (27.38% vs. 22.92%) (p<0.05). Proportionately less 

Appalachian facilities (13.6%) than non-Appalachian facilities (16.51%) are accredited by the 

Commission on Accreditation of Rehabilitation Facilities (CARF) (p<0.05). Approximately 45% of 

Appalachian treatment facilities are licensed or certified by a public health department as compared 

to 38.65% of facilities outside of Appalachia (p<0.001). Forty-four percent of Appalachian 

facilities are licensed or certified by the state mental health department, as opposed to 29.78% of 

non-Appalachian facilities (p<0.0001). Proportionately fewer Appalachian facilities (69.14%) are 

licensed or certified by the state substance abuse agency than non-Appalachian facilities (81.35%); 

results are statistically significant (p<0.0001). 
159 

Table 5.3: Inpatient, Outpatient, and Non-Hospital Residential Care Offered at Substance 

Abuse Treatment Facilities, 2005 

 Region 

Appalachia Non-Appalachia p-value 

N % N % 

Hospital Inpatient Care 

Inpatient care located in or operated by a hospital 890 14.16 12,456 13.18 0.407 

Inpatient substance abuse care offered 891 8.53 12,480 7.29 0.172 

Inpatient detoxification care offered 891 7.74 12,480 6.13 0.0542 

Outpatient Care

Any outpatient substance abuse care offered currently 891 83.28 12,479 80.66 0.0548 

Outpatient detoxification offered 891 7.41 12,478 11.13 0.0006 

Regular outpatient care offered 891 72.36 12,479 72.49 0.93 

Intensive outpatient care offered 891 38.95 12,479 42.88 0.0217 

Non-Hospital Residential Care

Non-hospital residential substance abuse care 891 21.66 12,480 27.92 <0.0001 

Non-hospital residential short-term treatment 891 8.19 12,480 12.07 0.0005 

Non-hospital residential long-term treatment 891 16.05 12,480 23.17 <0.0001 

SOURCE: U.S. Dept. of Health and Human Services, Substance Abuse and Mental Health Services Administration, Office of 

Applied Studies. National Survey of Substance Abuse Treatment Services (N-SSATS), 2005. 

Table 5.3 describes the inpatient, outpatient, and non-hospital residential care services offered by 

substance abuse treatment facilities in the Appalachian region and outside of Appalachia in 2005. 

In Appalachia, proportionately fewer facilities offer outpatient detoxification (7.41%) as opposed to 

facilities outside of Appalachia (11.13%). Approximately 38.95% of treatment facilities in 

Appalachia and 42.88% of facilities outside of Appalachia offer intensive outpatient care. Results 

are statistically significant (p<0.05). Non-hospital residential substance abuse care is provided in 

proportionately fewer facilities in Appalachia (21.66%) than outside of Appalachian (27.92%). 

About 8% of facilities in Appalachia offer non-hospital short-term residential treatment, less than 

the 12% of facilities that offer this service outside of Appalachia. Long-term treatment is also 

offered in proportionately fewer facilities in Appalachia (16.05%) than outside of Appalachia 

(23.17%). Results are statistically significant (p<0.001). 
160 

Table 5.4 Counseling and Pharacotherapies Available at Treatment Facilities, 2005 

 Region 

Appalachia Non-Appalachia p-value 

N % N % 

Pharmacotherapies Provided by Facility

Antabase 876 18.49 12,293 15.88 0.0417 

Naltrexone 874 16.59 12,233 12.07 <0.0001 

Campral 874 13.73 12,185 7.96 <0.0001 

Methadone 874 8.24 12,270 9.94 0.103 

Buprenorphine-Suboxone 871 8.15 12,190 7.85 0.75 

Buprenorphine-Subutex 863 5.10 12,160 5.25 0.85 

SOURCE: U.S. Dept. of Health and Human Services, Substance Abuse and Mental Health Services Administration, Office of 

Applied Studies. National Survey of Substance Abuse Treatment Services (N-SSATS), 2005. 

Table 5.4 describes the pharmacotherapies provided by substance abuse treatment facilities in the 

Appalachian region and outside of Appalachia in 2005. Naltrexone is provided at 16.59% in 

Appalachian and 12.07% of facilities outside of Appalachia (p<0.0001). Almost 14% of 

Appalachian treatment facilities provide Campral, compared to just under 8% of facilities outside of 

Appalachia (p<0.0001). 
161 

Table 5.5 Services Available at Treatment Facilities, 2005 

 Region 

Appalachia Non-Appalachia p-value 

N % N % 

Substance abuse treatment 891 98.3 12480 98.2 0.719 

Intake/ assessment/ referral 891 94.28 12,478 93.56 0.397 

Assessment of mental health 847 51.59 11,918 44.66 <0.0001 

Comprehensive substance abuse assessment 890 93.3 12434 93.0 0.793 

After care counseling 875 80.3 12311 78.5 0.191 

Substance abuse relapse prevention therapy 875 78.9 12325 81.4 0.062 

Substance abuse individual therapy 888 95.6 12436 94.8 0.291 

Substance abuse family counseling 886 83.07 12,309 76.19 <0.0001 

Substance abuse group therapy 887 90.5 12403 90.3 0.842 

SOURCE: U.S. Dept. of Health and Human Services, Substance Abuse and Mental Health Services Administration, Office of 

Applied Studies. National Survey of Substance Abuse Treatment Services (N-SSATS), 2005. 

As depicted in Table 5.5, there were statistically significant differences between Appalachian and 

non-Appalachian facilities in terms of whether they offered assessment of mental health and 

substance abuse family counseling (p<0.0001). 
162 

5.4.2 Figures 

Figure 5.1: Facilities Offering 

Inpatient Detoxification Services 

Figure 5.1 shows that 19% of the 891 

substance abuse treatment facilities in 

Appalachian counties offered inpatient 

detoxification services, as compared to 

21.4% of the 12,480 substance abuse 

treatment facilities in all other counties 

nationally. 

The 2.4% difference between 

Appalachian facilities and nonAppalachian facilities is not statistically 

significant (p<0.085). 

SOURCE: National Survey of Substance Abuse Treatment Services, 2005. 

Figure 5.2: Primary Focus of Substance Abuse Facilities 

Figure 5.2 shows the primary focus of 

substance abuse treatment facilities in 

Appalachian counties versus all other 

counties in the U.S. Treatment facilities 

were asked: “What is the primary focus of 

this facility?” 

 

In Appalachia, proportionately more 

treatment facilities had a primary focus of 

providing mental health services, a mix of 

mental health services, and general health 

care services than treatment facilities 

outside of Appalachia. Fewer facilities in 

Appalachia had a primary focus of 

providing substance abuse treatment 

services than outside of Appalachia. SOURCE: National Survey of Substance Abuse Treatment Services, 2005. 

About 2% of facilities in Appalachia and other counties nationally reported general health care 

services as their primary focus. Results are statistically significant (p<0.0001). 

Facilities Offering Intpatient Detoxification 

Services in Appalachia and Nationally

19 21.4

0

10

20

30

40

50

60

70

80

90

100

Appalachian Counties Other Counties Nationally

Percentage of Facilities 

Primary Focus of Facility in Appalachia and Nationally 

55.3%

10.0%

31.8%

2.4%

62.6%

7.8%

26.3%

1.8%

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Substance

Abuse Treatment

Services

Mental Health

Services

Mix of Mental

Health and

Substance

Abuse Services

General Health

Care Services

Percentage of Facilities

Appalachian Counties

Other Counties
163 

Figure 5.3: Facilities Using a Sliding Fee Scale 

Figure 5.3 shows that proportionately 

fewer Appalachian substance abuse 

treatment facilities (59.6%) offered a 

sliding fee scale to clients than facilities 

outside of Appalachia (64%). 

The total number of Appalachian 

facilities for this variable was 979. The 

total number for facilities outside of 

Appalachia was 12,343. 

The difference between Appalachian 

facilities and non-Appalachian facilities 

is statistically significant (p<0.05). 

SOURCE: National Survey of Substance Abuse Treatment Services, 2005. 

Figure 5.4: Facilities Offering Free or No Charge Treatment 

Figure 5.4 indicates that proportionately 

more substance abuse treatment facilities 

in Appalachian counties offered free or no 

charge treatment to clients who cannot 

afford to pay, in comparison to facilities 

in counties outside of Appalachia. 

Slightly more than half of the facilities 

(56.5% in Appalachia and 53.9% in other 

counties nationally) offered free or no 

charge treatment. Results were not 

statistically significant at the 95% 

confidence level. 

SOURCE: National Survey of Substance Abuse Treatment Services, 2005. 

Facilities Offering Free or No Charge Treatment in 

Appalachia and Nationally

56.5% 53.9%

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Appalachian Counties Other Counties Nationally

Percentage of Facilities

Facilities Using a Sliding Fee Scale 

in Appalachia and Nationally 

59.6%

64.0%

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Appalachian Counties Other Counties Nationally

Percentage of Facilities
164 

Figure 5.5: Facilities that Accept 

Medicare 

Figure 5.5 indicates that proportionately 

more treatment facilities in Appalachian 

counties accepted Medicare as payment 

than facilities in other counties 

nationally. 

Of the 848 Appalachian facilities 

responding to this item, approximately 

47% reported accepting Medicare for 

payment. About 35% of the 11,818 

facilities in all other counties nationally 

accepted Medicare. 

The difference is statistically significant 

at the 99% confidence level. 

 

 SOURCE: National Survey of Substance Abuse Treatment Services, 2005. 

Figure 5.6: Facilities that Accept Medicaid 

Figure 5.7 shows that proportionately 

more substance abuse treatment 

facilities in Appalachian counties 

accepted Medicaid than treatment 

facilities in other counties nationally. 

Of the 861 Appalachian facilities 

responding to this item, approximately 

70% reported accepting Medicaid for 

payment. About 54% of the 12,027 

facilities in all other counties 

nationally accepted Medicaid. 

The difference is statistically 

significant at the 99% confidence 

level. 

SOURCE: National Survey of Substance Abuse Treatment Services, 2005. 

Facilities that Accept Medicare in 

Appalachia and Nationally

34.8%

46.7%

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Appalachian Counties Other Counties Nationally

Percentage of Facilities

Facilities that Accept Medicaid 

in Appalachia and Nationally

53.8%

69.6%

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Appalachian Counties Other Counties Nationally

Percentage of Facilities
165 

Figure 5.7: Facilities that Accept State Financed Health Insurance 

Figure 5.7 demonstrates that 

proportionately more substance abuse 

treatment facilities in Appalachian 

counties accepted state financed health 

insurance than facilities in other counties 

nationally. For this variable, a state 

financed health insurance plan does not 

include Medicaid. Examples of state 

financed plans are the State Children's 

Health Insurance Program and other 

state financed high risk insurance pools. 

Of the 809 Appalachian facilities 

responding to this item, approximately 

57% reported accepting state financed 

health insurance for payment. About 

39% of the 11,278 facilities in all other 

counties nationally accepted state 

financed health insurance. The 

difference is statistically significant 

(p<0.01). SOURCE: National Survey of Substance Abuse Treatment Services, 2005. 

Figure 5.8: Facilities that Accept 

Private Health Insurance 

Figure 5.8 shows that more substance 

abuse treatment facilities in 

Appalachian counties accepted private 

health insurance than facilities in other 

counties nationally. 

Of the 870 Appalachian facilities 

responding to this item, approximately 

79.08% reported accepting private 

health insurance for payment. About 

67.5% of the 12,123 facilities in all 

other counties nationally accepted 

private health insurance. The difference 

is statistically significant (p<0.01). 

SOURCE: National Survey of Substance Abuse Treatment Services, 2005. 

Facilities that Accept State Financed Health 

Insurance in Appalachia and Nationally 

38.87%

56.98%

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Appalachian Counties Other Counties Nationally

Percentage of Facilities

Facilities that Accept Private Health Insurance in 

Appalachia and Nationally

67.5%

79.08%

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Appalachian Counties Other Counties Nationally

Percentage of Facilities
166 

5.5 Discussion 

In presenting our discussion of the findings for this chapter, we again want to recognize that the NSSATS has limitations as a data source for this study. Due to the voluntary nature of the survey and 

differences in reporting practices within states, it is difficult to ascertain the reliability of the data. 

Despite the limitations of the survey, the N-SSATS is the only survey that explores substance abuse 

treatment services and practices at the facility level. Thus, we view the N-SSATS as a limited, yet 

important data source for this study of substance abuse and mental health issues, and access to 

treatment in Appalachia. 

Our study found that the primary focus area of the majority of substance abuse treatment facilities 

was providing substance abuse treatment services only, rather than a mix of services. Even so, this 

was less likely to be the case among Appalachian facilities, with 55% listing substance abuse 

treatment only as their primary focus area, compared to approximately 63% for facilities nationally. 

In contrast, Appalachian substance abuse treatment facilities were more likely to list mental health 

treatment and a mix of substance abuse treatment and mental health treatment as the primary focus. 

Unique barriers to accessing treatment in the Appalachian region, such as distance and lack of 

public transportation, may provide the impetus for facilities to offer a broader array of co-located 

services. 

A consistent finding from this chapter is that Appalachian facilities are significantly less likely than 

non-Appalachian facilities to use a sliding fee scale (p<0.01). However, analyses also show a 

significantly greater acceptance of government financed payment sources including Medicare, 

Medicaid, and state financed insurance (p<0.01). While proportionately more facilities accept these 

payment sources, we do not know the breadth of coverage within the region. Similarly, 

proportionately more Appalachian facilities accept private health insurance (p<0.05), but the 

breadth of coverage is also unknown. Future studies analyzing cost and insurance issues within the 

Appalachian region could provide more specificity in terms of facility rationale, breadth of 

coverage, and service implications. 

In terms of facility ownership, we found that the majority of substance abuse treatment facilities in 

Appalachia and outside of Appalachia are owned by private non-profit organizations. 

Proportionately, more Appalachian facilities are owned by the local, county or community 

government, state government, or federal government than facilities outside of Appalachia. 

Of our findings related to the characteristics of services provided at treatment facilities, we found 

that more Appalachian treatment facilities are licensed or certified by a public health department 

than non-Appalachian treatment facilities (p<0.001), and more Appalachian facilities receive public 

funds than non-Appalachian facilities (p<0.01). 

More than 98% of Appalachian facilities offered substance abuse treatment. More Appalachian 

facilities offered assessment of mental health and substance abuse family counseling than nonAppalachian facilities, and the differences are statistically significant (p<0.01). 
167 

Future studies on substance abuse 

and mental health issues in 

Appalachia would benefit from 

better data at the substance abuse 

treatment facility level. The NSSATS does provide important 

information about the types of 

services offered in facilities – for 

example, that Appalachian facilities 

are more likely to accept payment 

from Medicare, Medicaid, state 

financed health insurance, and 

private insurance. However, the NSSATS does not provide data on 

other potentially useful topics such 

as wait-listing practices at different 

types of substance abuse facilities 

(residential, inpatient, and 

outpatient), cost of different services, 

and expected source of payment. 

Upon review of our findings for this 

chapter, the Coalition on Appalachian Substance Abuse Policy (CASAP) suggested a brief 

consumer-oriented telephone survey of facilities within Appalachia in order to gather some of these 

data elements. While the suggested survey activity is outside the scope of this study, such an effort 

would be beneficial to future studies of substance abuse at the facility level. Furthermore, efforts to 

augment the data available at the substance abuse treatment facility level would provide new 

opportunities to explore trends within the Appalachian region, and across the nation. 

Contrary to feedback from CASAP, according to staff at the Office of Applied Studies (OAS) 

(Alderks, 2008: through personal communication), the completeness of coverage of N-SSATS 

should have very little to do with state registration policies. Each year OAS and its data contractor 

perform augmentation activities using various directories such as the American Business Index and 

the American Hospital Association survey files in an effort to locate any unknown substance abuse 

treatment facilities. All identified and known facilities are then sent a survey at the location level. 

For example, a network of 15 facilities would receive 15 questionnaires, one for each facility 

location. In some cases, client count numbers may be combined for a few facilities, but it is known 

which facilities are included in those combined numbers. This would affect only information 

determining size of facility, not characteristics about services provided by the facility. 
CHAPTER 6: Substance Abuse and Mental Health – A Comparison of Appalachian Coal 

Mining Areas to Other Areas within the Appalachian Region 

6.1 Introduction 

A key geographic and economic feature of the Appalachian region is that a large proportion of the 

region is coal producing. The coal mining industry has long been a vital part of the economy of 

Appalachia and remains a major industry within the region. Many residents of the Appalachian region 

are employed in the coal mining industry or are employed in other industries that depend upon coal 

mining for their business.106 It has been reported in major news media that, with per-ton prices 

doubling in the past six years, mining is currently more profitable than any other time in the past 

generation. This has led to a coal boom, which has provided economic opportunity for many workers 

within the region, but has also been clouded by an increase in drug use, as reported by the media. The 

media’s poignant stories about drug use in coal mining areas have cited abuse of painkillers, 

methadone overdoses, and addiction OxyContin107 as major problems. Standard national estimates 

comparing major occupational groups indicate that people in occupations involving heavy physical 

labor tend to use substances more,108,109 yet workers in the coal mining industry have been reported as 

having only average prevalence of past month illicit drug use among major occupational groups.110 In 

addition to these seemingly contradictory results in media reporting and available research, questions 

also remain as to whether mining-concentrated areas feature differently in terms of treatment services 

access and health care utilization. This is an area in need of further study. 

“The abuse and misuse of painkillers is the worst I have seen in the 16 years I have worked 

narcotics in this area,” said Lt. Richard Stallard of the Big Stone Gap police department, director 

of the Southwest Virginia Drug Task Force.111

Experts say that whatever ground was gained against the illegal use of OxyContin is being lost, 

engulfed in a widening cycle of abuse that extends to pain-killers, antidepressants and other 

prescription drugs. 

Washington Post, January 13, 2008

In this chapter, we conduct statistical analyses of data systematically collected by two agencies within 

the U.S. Department of Health and Human Services – the Substance Abuse and Mental Health 

Services Administration (SAMHSA) and the Agency for Healthcare Research and Quality (AHRQ). 

We focus exclusively on the Appalachian region with the objective of comparing coal mining areas 

and other areas with respect to substance abuse and mental health status and access to the treatment 

services. The key research question for this chapter is: Do coal mining areas within Appalachia differ 

from other Appalachian areas in terms of the composition of patients admitted to specialty treatment 

services or discharged from community hospitals? 

6.2 Data and Analytic Samples 

Data sources utilized in this chapter are the current National Coal Resources Data System (NCRDS) 

from the U.S. Geological Survey, the Health Care Utilization Project’s (HCUP) National Inpatient Stay 

(NIS) data set from AHRQ, and the Treatment Episode Data Set (TEDS). 
169 

Coal Mining Counties 

We first identified the coal mining counties within the Appalachian Region by merging the coal 

mining area coverage data from the NCRDS with the list of the Appalachian counties described by the 

Appalachian Region Commission (ARC) as of 2006. Among the 410 Appalachian counties, 176 

counties were identified as being located in the coal mining area (see Figure 6.1). 

Figure 6.1 Coal Mining Area in the Appalachian Region 

Source: National Coal Resources Data System, U.S. Geological Survey. 

Community Hospital Discharges 

The first analytic sample for this chapter includes all adult discharges from community hospitals within 

the Appalachian Region. There are a total of 167,957 admissions included in the analytic sample, 

including 76,083 (45.3%) from 25 coal mining counties and 91,874 (54.7%) from 20 other counties in 

the Appalachian region.18 

Admissions to Substance Abuse Treatment Services 

The second analytic sample for this chapter includes all admissions to substance abuse treatment 

services in Appalachian Region from 2000-2004. Among the 195 counties covered by the Treatment 

Episode Dataset (TEDS) in 2000-2004, 86 counties were located in the coal mining area. Overall there 

were 211,380 admissions from the coal mining area and 299,837 admissions from other areas in the 

Appalachian region. 

 

18 Hospitals in five states with unknown county locations are excluded. 
170 

6.3 Results 

A series of univariate and bivariate analyses were performed. Chi-square statistics were used to assess 

the statistical significance of the associations. Major findings from the HCUP NIS community hospital 

discharge sample are listed below (see Table 6.3): 

Proportionately, there were more females among admissions in the coal mining area of 

Appalachia (62.4%) than in other areas of Appalachia (57.9%). 

Patients admitted to coal mining area hospitals were older that patients elsewhere. 

More than four-fifths of the admissions in the coal mining areas were among patients whose 

household incomes were less than $35,000, while only slightly more than half of the 

admissions in other areas were from this income group. 

While less than 10 percent of admissions (7.34%) from non-coal-mining areas were in 

distressed or at-risk counties, more than two-thirds (67.59%) of admissions from the coalmining areas were in distressed or at-risk counties. None of the coal-mining area in Appalachia 

included competitive or attainment counties. 

Proportionately more admissions in coal mining areas (56.82%) than admissions in other areas 

(51.35%) came through the Emergency Room (ER). 

In 2004, 26.84 percent of hospital stays for adults in Appalachian coal mining area community 

hospitals and 27.36 percent in community hospitals located in other Appalachian areas were 

related to MH/SA disorders. 

The rate of substance abuse-related disorders among all diagnoses was lower in community 

hospitals in coal mining areas (5.80%) than in other areas (6.13%). 

The most common MH/SA disorders seen among hospital stays in coal mining area community 

hospitals were mood disorders (11.15%), delirium/dementia (6.28%), substance-related 

disorders (5.80%), anxiety disorders (5.72%), and schizophrenia (1.89%). The most common 

MH/SA disorders seen in hospital stays in non-coal mining area community hospitals were 

mood disorders (13.32%), substance-related disorders (6.13%), delirium/dementia (5.64%), 

anxiety disorders (5.46%), and schizophrenia (2.23%). 

Among the MH/SA diagnoses, about 10 percent were co-occurring SA and MH diagnoses, 

accounting for 9.46% of diagnoses in coal mining areas and 13.32% of diagnoses in non-coal 

mining areas. 

Major findings from the Substance Abuse Treatment Services Sample from TEDS are listed 

below: 

Demographic Characteristics (see Table 6.4)
171 

Females made up 32.48 percent of admissions in coal mining areas and 29.94 percent of 

admissions in other areas. 

Overall, people less than 24 years of age accounted for more admissions in coal mining areas 

(32.89%) than other areas (29.59%). 

Proportionately, fewer admissions were made by full-time employed workers in coal mining 

areas (19.67%) than other areas (29.21%). Conversely, more admissions were made by 

unemployed persons in coal mining areas (39.28%) than other areas (29.98%). 

The majority of admissions were in transitional counties (59.1% in coal mining areas; 62.27% 

in other areas). Coal mining areas had proportionately more admissions (29.42%) in distressed 

or at-risk counties than other areas (5.62%), and fewer admissions (11.48%) in competitive or 

attainment counties than other areas (32.1%). 

Treatment Service Related Characteristics (see Table 6.5)

There were no significant differences between coal mining area admissions and admissions in 

other areas related to most types of insurance coverage; rates of private health insurance, Blue 

Cross/Blue Shield, Medicare, Medicaid, and Health Maintenance Organization (HMO) 

coverage were all similar. However, while 30.47 percent of admissions in the coal mining area 

were made by people without any health insurance, more than half (52.36%) of the admissions 

were made by people without any health insurance in other areas of Appalachia. 

Proportionately, more admissions were paid by “other” insurances in coal mining areas 

(33.01%) than other areas (12.01%). 

The most prevalent service setting for substance abuse treatment was non-intensive outpatient 

ambulatory services in both the coal mining areas (57.53%) and other areas (60.01%). 

Proportionately, fewer admissions were self-referrals in coal mining areas (22.12%) than other 

areas (26.41%); proportionately more admissions were referred by court/criminal justice 

systems in coal mining areas (39.73%) than other areas (35.07%). 

Less than 15% of coal mining area admissions were paid by individuals themselves, while fourfifths of the admissions in other areas were paid by individuals themselves; proportionately 

more admissions in coal mining areas were made by government payments other than Medicaid 

and Medicare (36.40%) than admissions in other areas (22.46%). 

Primary, Secondary, and Tertiary Reasons for Substance Abuse Treatment Services (see Table 6.6)

The primary reason for seeking substance abuse treatment in Appalachia was alcohol use, 

although less so in coal mining areas (45.58%) than other areas within Appalachia (53.01%). 

Heroin use as a primary, secondary, or tertiary reason for treatment accounted for 

proportionately more admissions in coal mining areas (10.34%) than for other areas within 

Appalachia (7.04%). 
172 

Trends of Heroin Use and Other Opiates or Synthetics Use in Appalachian Coal Mining Areas and 

Other Areas within the Region 

In 2000, admissions for heroin use represent 5.84 percent of TEDS admissions in the coal 

mining area in Appalachia and 5.71 percent of TEDS admissions in other Appalachian areas. 

While admissions rates increased steadily over the 2000-2004 period for both the coal mining 

and non-coal mining areas, admissions rates in coal mining areas increased to a proportionately 

higher level. By 2004, heroin admissions accounted for 14.59 percent of the TEDS admissions 

in coal mining areas and 9.25 percent in other areas (see Table 6.1). 

Table 6.1: Trend of Heroin Use as Primary, Secondary, or Tertiary Reason for Treatment, by Coal 

Mining Status of Patient Location 

 2000 2001 2002 2003 2004 p-value 

Coal Mining Area 5.84 7.16 9.43 12.95 14.59 <.0001 

Other Area 5.71 6.07 6.66 7.76 9.25 <.0001 

0

2

4

6

8

10

12

14

16

2000 2001 2002 2003 2004

Coal Mining Area

Other Area

Source: Office of Applied Studies, Substance Abuse and Mental Health Services Administration, Treatment Episode Data 

Set (TEDS), 2000 – 2004. 

In 2000, admissions for other opiates or synthetics use represented 8.41 percent of TEDS 

admissions in the coal mining area of Appalachia and 4.50 percent of TEDS admissions in 

other Appalachian areas. These percentages increased steadily over the 2000-2004 period for 

both coal mining and non-coal mining areas. By 2004, admissions for other opiates or 

synthetics accounted for 15.67 percent of the TEDS admissions in coal mining areas and 9.94 

percent in the other areas (see Table 6.2). 
173 

Table 6.2: Trend of Other Opiates or Synthetics Use as Primary, Secondary, or Tertiary Reason for 

Treatment, by Coal Mining Status of Patient Location 

 2000 2001 2002 2003 2004 p-value 

Coal Mining Area 8.41 11.64 12.37 15.23 15.67 <.0001 

Other Area 4.50 6.28 7.21 8.63 9.94 <.0001 

0

2

4

6

8

10

12

14

16

18

2000 2001 2002 2003 2004

Coal Mining Area

Other Area

Source: Office of Applied Studies, Substance Abuse and Mental Health Services Administration, Treatment Episode Data 

Set (TEDS), 2000 – 2004. 

6.4 Conclusion 

Our studies in previous chapters find that the percentage of admissions with heroin use and other 

opiates or synthetics use as the primary, secondary or tertiary reason for treatment is significantly 

higher in the Appalachian region, as compared to the rest of the nation. The study in this chapter adds 

granularity to these findings by demonstrating that coal mining areas within the Appalachian region 

demonstrate higher rates of both heroin use and other opiates or synthetics use as the primary, 

secondary or tertiary reason for treatment, as compared to other areas within the region. Furthermore, 

while studies in previous chapters show that rates of both heroin and other opiates and synthetics as 

primary reasons of coming to treatment increased over the 2000-2004 period, the pace of these rate 

increases is even faster in coal mining areas than in other areas within the Appalachian region. 

Other illicit drug use and non-medical use of prescription drugs are also cited more as the primary, 

secondary or tertiary reasons for treatment in coal mining areas than in other areas. As coal mining 

areas have been found also to have a higher proportion of admissions paid for by government sources 

instead of self-payment, substance abuse problems have likely required more government resource 

investment in these areas as compared to elsewhere within the Appalachian region. 
174 

Our coal mining area was defined as the area with subsurface filled with coal instead of the actual coalproducing counties. The 176 coal mining counties retrieved thus covered not only the 118 coalproducing counties defined by the Appalachian Regional Commission in 2001 but also some closelyadjacent lands with coal mines as located by the National Coal Resource Data System.112 The results 

should also be interpreted with caution because the units of analyses were admissions to treatment or 

hospital discharges made by people living in this area rather than actual coal miners. 

In this study, we compared the coal mining area with other areas in Appalachia overall. Future studies 

could explore the coal mining area further by studying patterns across groups of similar counties. For 

example, analyses could focus on patterns in the northern, central and southern regions of Appalachia. 

These geographic sub-regions, used by the Appalachian Regional Commission, were employed in the 

previous analytic chapters to investigate patterns in Appalachia. Analyses based on the Appalachian 

sub-regions may be of special benefit to analysis of coal mining areas since the northern, central, and 

southern regions of Appalachia had, notably, different levels of production for different types of coal, 

both in the past and, predictably, will in the future as well.113 

Figure 6.2 Coal Mining Appalachian Sub-Regions 

SOURCE: Berge, M. and Thompson, E. (2001). 

A Study on the Current Economic Impacts of the 

Appalachian Coal Industry and Its Future in the 

Region. Washington, D.C.: Appalachian 

Regional Commission. 
175 

Table 6.3: Characteristics of Hospital Stays in Community Hospitals in the Appalachian Region, 

Adults Aged 18 or Older, by County Coal Mine Status 

Characteristics of Hospital Stays (N=167,95719) in 

Community Hospitals, Adults, Aged 18 or older 

Appalachian Coal 

Mining Counties 

Other 

Appalachian 

Counties 

p-value 

Number of hospital stays 76,083 91,874 

Female (%) 62.42 57.91 <0.0001 

Age (%) 

 18 – 44 28.22 24.89 <0.0001 

 45 – 64 27.48 26.71 

 65 – 79 26.43 27.71 

 80 or older 17.87 18.69 

Household Income (%) 

 $1 - $35,999 87.36 51.63 <0.0001 

 $36,000 - $44,999 9.01 33.86 

 $45,000 - $58,999 3.24 12.59 

 $59,000 or more 0.40 1.92 

Economic Development Level (%) 

 Distressed 38.47 3.17 <0.0001 

 At-Risk 29.12 4.17 

 Transitional 32.41 51.05 

 Competitive 0 8.54 

 Attainment 0 33.08 

Patient Location (%) 

 Large metropolitan 0.38 1.13 <0.0001 

 Small metropolitan 26.95 40.98 

 Micropolitan 21.25 35.99 

 Non-core 51.42 21.90 

ER as Admission Source (%) 56.82 51.30 <0.0001 

At least one MHSA Diagnosis (%) 26.84 27.36 0.0186 

Substance-related disorders (%) 5.80 6.13 0.0045 

Mental Health20 (%) 

 Anxiety disorders 5.72 5.46 0.02 

 

19 The following five Appalachian states were not included due to the lack of the county identifiers in the data: Ohio, 

Tennessee, Georgia, Kansas, South Carolina. 

20 Only selected diagnoses are included. Multiple diagnoses can be marked for the same admission. 
176 

Characteristics of Hospital Stays (N=167,95719) in 

Community Hospitals, Adults, Aged 18 or older 

Appalachian Coal 

Mining Counties 

Other 

Appalachian 

Counties 

p-value 

Delirium, dementia, and amnestic and other 

cognitive disorders 

6.28 5.64 <0.0001 

 Development disorders 0.72 0.92 <0.0001 

 Mood disorders 11.15 13.32 <0.0001 

 Personality disorders 0.23 1.52 

Schizophrenia and other psychotic disorders 1.89 2.23 <0.0001 

Screening and history of mental health and 

substance abuse disorders 

11.01 10.20 <0.0001 

Comorbidity among MHSA admissions 9.46 11.89 <0.0001 

Table 6.4: Characteristics of Admissions to Substance Abuse Specialty Treatment in the 

Appalachian Region, by County Coal Mine Status, 2000-2004 

Characteristics of Admissions to Substance Abuse 

Specialty Treatment (N=511,217) 

Appalachian Coal 

Mining Counties 

Other 

Appalachian 

Counties 

p-value 

Number of Admissions 211,380 299,837 

Female (%) 32.48 29.94 <0.0001 

Age (%) 

 17 or younger 11.33 9.86 <0.0001 

 18 – 24 21.56 19.73 

 25 – 34 26.08 26.24 

 35 – 44 26.37 28.05 

 45 or older 14.66 161.2 

Education (%) 

 Less than High School 39.95 40.50 <0.0001 

 High School 43.32 41.82 

 More than High School 16.72 17.68 

Employment Status 

 Full-time 19.67 29.21 <0.0001 

 Part-time 6.23 6.26 

 Unemployed 39.28 28.98 

 Not in labor force 34.81 35.54 
177 

Characteristics of Admissions to Substance Abuse 

Specialty Treatment (N=511,217) 

Appalachian Coal 

Mining Counties 

Other 

Appalachian 

Counties 

p-value 

Race 

 White 84.27 83.43 <0.0001 

 Black 14.94 14.12 

 Other 0.79 2.45 

Marital Status 

 Never married 55.68 52.83 <0.0001 

 Now married 17.34 19.14 

 Separated 7.88 8.07 

 Divorced/widowed 19.10 19.96 

Sub-Region (%) 

 Northern 55.80 45.60 <0.0001 

 Central 22.82 4.34 

 Southern 21.38 50.06 

Economic Development (%) 

 Distressed 18.65 3.09 <0.0001 

 At-risk 10.77 2.53 

 Transitional 59.10 62.27 

 Competitive 2.27 20.87 

 Attainment 9.21 11.23 

Source: Office of Applied Studies, Substance Abuse and Mental Health Services Administration, Treatment Episode Data 

Set (TEDS), 2000 – 2004. 
178 

Table 6.5: Treatment-Related Characteristics of Admissions to Substance Abuse Treatment in 

the Appalachian Region, by County Coal Mine Status, 2000-2004 

Treatment-Related Characteristics of Admissions to 

Substance Abuse Treatment 

Appalachian 

Coal Mining 

Counties 

Other 

Appalachian 

Counties 

p-value 

Health Insurance21 

 Private 9.58 10.35 <0.0001 

 BC/BS 5.57 5.64 

 Medicare 2.03 1.38 

 Medicaid 16.15 15.51 

 HMO 3.19 2.76 

 Other 33.01 12.01 

 None 30.47 52.36 

Service Setting 

 Detoxification: Hospital inpatient 0.79 1.75 <0.0001 

 Detoxification: Freestanding residential 6.98 14.83 

 Rehabilitation/residential: Hospital 0.27 0.05 

 Rehabilitation/residential: Short-term 9.24 9.04 

 Rehabilitation/residential: Long-term 5.36 3.96 

 Ambulatory: Intensive outpatient 19.76 10.26 

 Ambulatory: Non-intensive outpatient 57.53 60.01 

 Ambulatory Detoxification 0.08 0.10 

Primary Source of Referral 

 Individual 22.12 26.41 <0.0001 

 ADA care provider 14.66 15.86 

 Other health care provider 8.29 11.28 

 School 1.75 1.81 

 Employer/EAP 0.67 0.93 

 Other community reference 12.77 8.64 

 Court/criminal justice 39.73 35.07 

Number of Prior Treatment (%) 

 No prior treatment 44.21 48.76 <0.0001 

 1 -2 prior treatment 32.71 32.75 

 3 or more prior treatment 19.08 18.49 

 

21 A total of 236,800 records in the Appalachian Region during the 2000-2000.274 did not have the insurance information. 
179 

Treatment-Related Characteristics of Admissions to 

Substance Abuse Treatment 

Appalachian 

Coal Mining 

Counties 

Other 

Appalachian 

Counties 

p-value 

Primary Source of Payment (%) 

 Self pay 14.44 40.96 <0.0001 

 B/BS/Other health insurance 10.14 10.14 

 Medicare/Workmans Comp 1.53 1.06 

 Medicaid 17.72 13.22 

 Other government payments 36.40 22.46 

 No charge 4.10 4.12 

 Other 15.66 8.03 

Source: Office of Applied Studies, Substance Abuse and Mental Health Services Administration, Treatment Episode Data 

Set (TEDS), 2000 – 2004. 
180 

Table 6.6: Substance Abuse Characteristics of Admissions to Substance Abuse Treatment in the 

Appalachian Region, by County Coal Mine Status, 2000-2004 

Substance Abuse Characteristics of Admissions to 

Substance Abuse Treatment22

Appalachian 

Coal Mining 

Counties 

Other 

Appalachian 

Counties 

p-value 

Number of admissions 195,409 291,553 

Primary Reason for Admission to Treatment (%) 

 Alcohol use 45.58 53.01 <0.0001 

 Marijuana use 17.78 16.49 <0.0001 

 Cocaine use 13.17 11.62 <0.0001 

 Heroin use 8.62 5.56 <0.0001 

 Other opiates or synthetic drug use 7.49 4.19 <0.0001 

 Methamphetamine/other stimulant use 2.08 3.19 <0.0001 

 Tranquilizers use 1.23 0.75 <0.0001 

 Sedatives use 0.44 0.32 <0.0001 

 Other hallucinogens use 0.26 0.16 <0.0001 

 Inhalants use 0.14 0.13 =0.403 

 Phencyclidine use 0.04 0.02 =.0004 

 Other 0.74 2.82 <.0001 

Primary, Secondary, or Tertiary Reason for Admission to Treatment (%) 

 Alcohol use 63.98 67.87 <0.0001 

 Marijuana use 39.45 36.59 <0.0001 

 Cocaine use 25.47 23.26 <0.0001 

 Heroin use 10.34 7.04 <0.0001 

 Other opiates or synthetic drug use 12.92 7.25 <0.0001 

 Methamphetamine/other stimulant use 4.18 5.40 <0.0001 

 Tranquilizers use 5.47 3.16 <0.0001 

 Sedatives use 1.45 1.10 <0.0001 

 Other hallucinogens use 1.29 0.95 <0.0001 

 Inhalants use 1.17 0.93 <0.0001 

 Phencyclidine use 0.15 0.09 <0.0001 

 Other 1.82 3.93 <0.0001 

Source: Office of Applied Studies, Substance Abuse and Mental Health Services Administration, Treatment Episode 

Data Set (TEDS), 2000 – 2004. 

 

22 Analyses in this table are based on 486,962 admissions because of the missing information on substance abuse for 24,255 

cases. 
181 

CHAPTER 7: Case Study Analysis of Disparities in Mental Health Status 

and Substance Abuse Prevalence in the Appalachian Region and Access 

to Mental Health and Substance Abuse Treatment Services 

 

 

Prepared By: 

Michael S. Dunn, PhD 

Department of Public Health 

East Tennessee State University 

& 

Kristine Harper Bowers 

Office of Rural and Community Health 

and Community Partnerships 

East Tennessee State University 
182 

7.1 Introduction 

To supplement the quantitative findings presented in the previous chapters, NORC and East Tennessee 

State University conducted case studies using a “Socioeconomic Twins” methodology. The studies 

were purposively selected and bracketed with “twin” counties in Kentucky, Virginia, and West 

Virginia. Two counties in each state were selected that were socioeconomically similar, yet varied on 

measures of substance abuse and mental health. An in-depth discussion of the selection process is 

provided below. The case study approach provides for a comprehensive understanding of a complex 

instance or instances that is acquired by extensive description and analysis. Appropriate selection is 

crucial to internal consistency and the plausible comparison of the evidence in context. One unique 

feature of case studies is that data is concurrently collected and analyzed leading to “thick” 

descriptions from multiple data sources, particularly first hand observations. 

The goals of the case studies were to: 

 Determine if community perceptions of substance abuse/mental health (MH/SA) issues match 

available data; 

 Identify additional data sources used at the community level; 

 Learn first hand about the community’s response to substance abuse and mental health 

concerns including statistical presentations of local data; and 

 Identify potential explanations for variance in community MH/SA indicators. 

The purpose of the study was to determine the extent of local assessments of the mental health and 

substance abuse situation as well as the perceived validity of nationally available quantitative data to 

serve as an index of the severity of local substance abuse prevalence, mental health status and access to 

treatment services. 

7.2 Case Study Process 

ETSU and NORC developed and piloted a five phase process for the socioeconomic twins case study: 

1. Identification of potential data sets/sources using a Dephi process. 

2. Selection of the 6 paired Appalachian counties using a socio-economic twins methodology. 

3. On-site focus group and key informant interviews with community leaders to: 

o Respond to secondary data identified by NORC that led to the initial selection of the 

county with respect to accuracy, reliability and validity of how the standard measures 

reflected the nature of the community’s issues; and 

o Assess overall impressions of substance abuse and mental health problems including 

community issues, systems capacities, recent incidents and community reaction and 

response to the research issues. 

4. Development of a community resource inventory to identify available services for prevention 

and treatment. 

5. Development of key findings based on an analysis of the textural data derived from the 

interviews and focus groups. Using an induction method the analysis focused on the 

organization of broad conceptual categories and then more refined coding for underlying 

themes. Finally, the textural data was triangulated with secondary data profiles, and county 

descriptors with researcher’s field notes to produce an understanding of the incidence of and 
183 

explanation for disparities in mental health status, substance abuse prevalence and access to 

treatment services in these Appalachian communities. 

The following sections describe the identification of potential data sources, selection of the pairs of 

counties for the case study, descriptions of each pair of case study sites, the community responses to 

the county data profiles and focus group/key informant interview questions, and conclusions. The 

tables include county model programs, strength and treatment gaps, and in-depth descriptions of the 

model programs listed. 

7.3 Phase 1: Identification of Potential Data Sets/Sources 

A Delphi process with an expert panel was used to identify the data elements they considered to be 

most useful as key indicators in differentiating levels of substance use/abuse in Appalachian 

communities. The Delphi process created another tier of possible or ideal data sources. 

In late spring of 2007, the following two questions were emailed to members of the Coalition on 

Appalachian Substance Abuse Policy (CASAP), a regional coalition of substance abuse practitioners, 

educators and researchers: 

 

1. What do you believe are the most critical data elements (indicators) needed in determining 

high/low substance use/abuse in a community (list as many as appropriate)? 

2. How readily available and reliable are these data elements (indicators)? 

CASAP members were given two weeks to reply to Round One of the Delphi process. Round Two 

consisted of CASAP members ranking each data element received in Round One as: 1 = very 

important; 2 = somewhat important; or 3 = not important. From the Delphi process, the following 

substance use/abuse indicators were identified. 

Socio-economic status 

Poverty rates 

Per capita incarceration rate for drug offense 

Substance abuse related arrests per capita/1,000 

Drunk & impaired driving arrests 

Suicide rate 

Overdose death rates 

Child abuse and neglect reports 

Drug related child protective services interventions/ social service investigations 

Birth certificate data on maternal smoking and substance abuse 

Prescription rates of abused drugs 

Service utilization rates for substance abuse /mental health treatment 

Mortality from alcohol or drug related causes 

Accident rates from AOD related causes 

Substance abuse screening tests conducted by schools and employers 

Behavioral Risk Factor Survey 
184 

Once identified, data sets and elements were analyzed by the NORC team to assess sources available 

across the Appalachian region that could be integrated into community profiles for use in case study 

analyses. 

7.4 Phase 2: Selection of Pairs of Counties for Case Study 

This section describes the process used to select pairs of counties for inclusion in the qualitative 

component of this study. Counties were ranked in terms of socio-demographic characteristics and 

substance abuse and mental health characteristics. Databases of counties were developed accordingly. 

The objective was to select pairs of counties that are similar in terms of socio-demographic 

characteristics, but relatively dissimilar overall in terms of their mental illness and substance abuse 

indicators, medical care, and mental health professional shortage area statuses, using existing or 

derived measures. Selection involved a three step process: 

1. Pertinent measures were identified and retrieved as the source variables; 

2. Statistical procedures were performed and matrices developed to calculate socio-demographic 

similarity/dissimilarity and MH/SA similarity/dissimilarity for all Appalachian counties within 

each state. Then, these “distance matrices” were transformed into pairs which were 

subsequently ranked and sorted based on the distance values; and 

3. Selection criteria were set up to identify pairs that were socio-demographically similar, but 

dissimilar on MH/SA indicators, and the final pairs were selected accordingly. 

Data Sources 

Measures utilized for the case study analyses were primarily from three major sources: the 

Appalachian Regional Commission (ARC); the Area Resource File (ARF); and the National Survey on 

Drug Use and Health (NSDUH). 

1. County-level Socio-demographic Characteristics 

The following county-level measures of socio-demographic characteristics are selected as the basis 

upon which to compare the similarities among counties. 

a. The 2003 population size estimates are from the 7/1/2003 County Population Estimates File 

for Internet Display from the U.S. Bureau of the Census. 

b. The 2000 population density per square mile estimates are from the 2000 Census. 

c. The 2000 percentage of urban population is from the 2000 Census. 

d. The 2003 Urban Influence Codes divide the counties, county equivalents, and the 

independent cities in the U.S. into 12 groups based on population and commuting data from 

the 2000 Census of the population, in the case of Metropolitan counties, and adjacency to 

metro area in the case of non-metropolitan counties. 23

e. The 2000 median home value is from the 2000 census. 

f. The 2004 economic development level codes are provided by the Appalachian Regional 

Commission. 

 

23 The codes were originally from the U.S. Department of Agriculture’s Economic Research Service (ERS) website at 

http://www.ers.usda.gov/Data/UrbanInfluenceCodes/ . 
185 

2. County-level Substance Abuse, Mental Health, and Service Delivery Statuses 

The selected measures24 and their original sources are listed in the following: 

a. Alcohol abuse or dependence in past year is from the 2002-2004 pooled National Survey on 

Drug Use and Health. 

b. Abuse or dependence of any illicit drugs in past year is from the 2002-2004 pooled National 

Survey on Drug Use and Health. 

c. Non-prescription use of painkillers in past year is from the 2002-2004 pooled National Survey 

on Drug Use and Health. 

d. The percentage of persons having serious psychological distress problems in past year is from 

the 2002-2004 pooled National Survey on Drug Use and Health. 

e. The percentage of persons in correctional or juvenile institutions in past year is calculated 

using measures from the Area Resource File 

f. The percentage of persons in mental health hospitals or institutions is calculated using 

measures from the Area Resource File 

g. The suicide rate is calculated using the average numbers of suicides in the past three years and 

population size from the Area Resource File. 

h. An index on the Health Professional Shortage Area status is created based on two measures – 

the 2003 codes for Health Professional Shortage Area (HPSA) for Primary Medical Care114 and 

the 2003 codes for Health Professional Shortage Area (HPSA) for Mental Health.115 Both were 

originally from the Bureau of Primary Health Care (BPHC) and are available in the Area 

Resource File. 

Measuring the Similarities of County Pairs 

The similarities between counties in terms of various pertinent county-level characteristics are 

measured quantitatively using the DISTANCE procedure in the Statistical Analysis System (SAS). 

Distance matrices are constructed to list the degree of similarity among all possible pairs of counties 

within each state116 based on source variables listed earlier. To address the potential issue that variables 

with large variances tend to have more of an effect than those with small variances, input variables 

with different measurement levels (interval, ordinal) have been taken into account through 

standardization before the similarity measures are computed. In order to rank the pairs of counties, the 

matrices are then transformed into a rectangular data structure in which all county-pairs are listed one 

by one within each state. The distance matrices were obtained separately through socio-demographic 

characteristics and through the substance abuse, mental health and service coverage measures. As a 

result of this procedure, two ranking indexes were created, namely, soc_rank and samh_rank, 

indicating the socio-demographic and substance abuse and mental health related similarities, 

separately. The lower the value from the ranking index, the more similarities the pair of counties 

shared. 

 

24 More measures were considered, including: cigarettes use, binge drinking, past month marijuana use, perceptions of risks 

of drinking and smoking from household surveys. After preliminary statistical analyses to identify patterns of variations 

(i.e., via factor analysis), these variables were dropped from being used to construct the similarity matrices. 
186 

Composite Ranking Scale and Selection of Final Pairs 

We calculated a composite ranking scale by subtracting soc_rank from samh_rank. The resulting value 

was used to rank pairs of counties in such a way that the higher value would indicate greater 

dissimilarity on substance abuse and mental health related measures and greater similarity on sociodemographic characteristics. Through the composite ranking scale, three or four pairs of counties from 

each of the Appalachian states were selected as the candidates of case study sites (see Table 7.1). 

After conferring among all NORC team partners, the top three pairs from Kentucky, Virginia, and 

West Virginia, with each pair having the highest composite ranking scale score in the corresponding 

state, were selected as the final sites for the case studies. Counties ultimately selected for inclusion in 

the study were: 

Monroe County and Hardy County from West Virginia; 

Bland County and Bath County from Virginia; and 

Wayne County and Morgan County from Kentucky. 
187 

The detailed county-pairs selected at the final stage from the 11 Appalachian States are listed in the 

following. 25

Table 7.1. Selected Four Pairs of Counties Per State in the Appalachian Region 

Based on the Composite Ranking Score 

County Pairs Distance Index Rank Composite 

County 1 County 2 Soc- Rank 

demo 

SAMH Socdemo SAMH 

Alabama 

Tallapoosa Talladega 0.09399 0.63828 58 662 604 

Talladega Marshall 0.10589 0.60212 75 651 576 

Lawrence Chilton 0.07074 0.53362 25 575 550 

Georgia 

Stephens Chattooga 0.086763 0.60025 76 654 578 

Jackson Gilmer 0.061062 0.46431 34 579 545 

Jackson Fannin 0.091484 0.52175 86 617 531 

Kentucky 

Wayne Morgan 0.041546 0.52521 23 1206 1183 

Morgan Monroe 0.059565 0.50804 42 1172 1130 

Morgan Adair 0.037319 0.48774 19 1115 1096 

Mississippi 

Montgomery Chickasaw 0.09058 0.64941 11 266 255 

Winston Montgomery 0.08435 0.49241 10 245 235 

Noxubee Montgomery 0.12209 0.4788 22 242 220 

Winston Tippah 0.12187 0.46412 21 240 219 

New York 

Chautauqua Allegany 0.56845 0.15715 84 14 70 

Tioga Steuben 0.19801 0.60495 21 87 66 

Cattaraugus Allegany 0.41395 0.0828 68 4 64 

Tioga Cattaraugus 0.17875 0.53048 16 73 57 

North Carolina 

Surry Rutherford 0.04658 0.65497 10 386 376 

Yadkin Madison 0.05974 0.64618 14 377 363 

Davie Alexander 0.06306 0.62176 16 366 350 

Surry McDowell 0.10259 0.67956 48 395 347 

Ohio 

Morgan Meigs 0.09381 0.41246 25 367 342 

Noble Monroe 0.09847 0.41375 28 368 340 

Washington Hocking 0.11086 0.40282 39 359 320 

Ross Hocking 0.11931 0.41563 50 369 319 

Pennsylvania 

 

25 As there are only 3 Appalachian counties in Maryland and 6 Appalachian counties in South Carolina, the “distance” 

values are not calculated and thus no county pairs are set up for these two states.
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Table 7.1. Selected Four Pairs of Counties Per State in the Appalachian Region 

Based on the Composite Ranking Score 

County Pairs Distance Index Rank Composite 

County 1 County 2 Soc- Rank 

demo 

SAMH Socdemo SAMH 

Somerset Crawford 0.024427 0.44986 14 1294 1280 

Snyder Juniata 0.045775 0.48158 39 1311 1272 

Somerset Bradford 0.01667 0.42379 6 1263 1257 

Huntingdon Crawford 0.016052 0.41279 5 1246 1241 

Tennessee 

Franklin Claiborne 0.055416 0.58012 32 1123 1091 

Overton Morgan 0.066463 0.58349 56 1130 1074 

Scott Grundy 0.070694 0.58661 64 1136 1072 

Roane Putnam 0.070714 0.58204 65 1126 1061 

Virginia 

Bland Bath 0.06587 0.78649 14 259 245 

Highland Bland 0.08249 0.72867 17 256 239 

Highland Floyd 0.0928 0.65025 20 240 220 

Floyd Bath 0.07618 0.61837 15 231 216 

West Virginia 

Monroe Hardy 0.043199 0.60952 23 1472 1449 

Pendleton Monroe 0.054856 0.61336 35 1475 1440 

Lewis Barbour 0.043253 0.54555 24 1416 1392 

Wyoming Barbour 0.045604 0.53389 26 1402 1376 

Site Descriptions 

The twinned county sites were selected from the lists above by consensus among ETSU, CASAP and 

NORC based upon the statistically twinned rankings produced by NORC and modified by 

local/regional knowledge of local situations. 

The following brief descriptions paint a picture of each selected county that accents its uniqueness 

while illustrating the commonalities among the locations. Information about each county was procured 

from the County Profiles prepared by NORC (See Appendix D) from Epodunk.com and from maps 

and other county data available on-line. Figure 7.1 shows the geographic placement of the case study 

counties in Appalachia. 
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Figure 7.1 Map of Case Study Counties 

MORGAN and WAYNE COUNTIES, KENTUCKY 

Of the three sets of county twins selected, the two Kentucky counties, Morgan and Wayne were 

farthest apart geographically – one in the north central part of the state and one bordering Tennessee. 

Despite the relative distance, both contain portions of the Daniel Boone National Forest, part of a 

designated High Intensity Drug Trafficking Area by the Office of National Drug Control Policy. Both 

counties are non-metropolitan counties, not adjacent to a metropolitan area. Both are classified as 

economically distressed by the Appalachian Regional Commission. Morgan County is the location of 

a state medium/minimum correctional facility with a population of 1690 males and staff of 377, with 

another large facility in neighboring Elliott County. 

Wayne County has a larger available labor force (8,767 vs. 5,043 persons) than Morgan County with 

manufacturing as the largest employment sector and lower unemployment for 2006 (6.7 vs. 8.8). Both 

Wayne County and Morgan County have a higher unemployment rate than the state rate of 5.7, with 

higher personal income and almost two thirds as many households. The high school graduation rates 

and median household income in Wayne County are nearly the same as in Morgan County. Both 

counties have lower graduation rates (Wayne County at 57.8% and Morgan at 56.4%) than the 74.1% 

state average in 2000. Both counties have experienced below average population growth (2.9% for 
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Wayne County and 2.6% for Morgan County) compared to the state of Kentucky. The percentage of 

persons below the poverty level for 2004 was 27.0% for Morgan County, compared to 24.3 % for 

Wayne County contrasting with 16.3 for the state. 

Neither county is crossed by an interstate highway; transportation into and out of each county is 

through a rural landscape primarily via state or federal roads. Each county is served by a branch 

campus of state higher education and counts the local technical facility as a community center for 

training and education. Monroe County’s facility, run by Morehead State University, also houses the 

public library. Wayne County’s ASPIRE Center is a multipurpose community program center. 

The state does not report crime on a county-by-county basis but Morgan County had almost twice as 

many juvenile court referrals in 2005 (33 vs.15). Morgan County has fewer low birth weight babies 

(7% vs. 10%). The 2004 Area Resource file data on the County Profile listed 11.93% of Morgan 

County’s population in correctional or juvenile institutions vs. 0.1410% for Wayne County. In 

addition 0.0208% of Morgan County’s population was reported to have used mental health hospitals or 

institutions while Wayne County’s rate was 0.0251% contrasting with 0.0485% for the state. All of 

Morgan County is designated as both a mental health professional shortage area and a primary care 

health professional shortage area. Wayne County has no mental health professional shortage area 

designation. Both counties have only outpatient mental health or substance abuse treatment facilities 

within the county, and both have access to the same number of regional facilities. 

Although Wayne County reported slightly more alcohol use or dependence (6.03% vs. 5.95%), both 

reported rates lower than the state average of 6.47%. Morgan County had greater abuse or dependence 

of any illicit drugs (3.37% vs. 2.74%), non-prescription use of painkillers (6.83% vs. 5.85%), serious 

psychological distress problems (12.61% vs. 11.49%) and a higher suicide rate (0.0215 vs. 0.0153) as 

compared to Wayne County. Morgan County also demonstrated higher rates of tobacco use and 

cigarette smoking, alcohol use in the past month by 12-20 year olds, binge alcohol use, and illicit drug 

use including marijuana and cocaine use. Both counties have active federally funded anti-drug 

coalitions and local programs targeting youth in the schools and community, though impressions from 

Wayne County indicated fewer extracurricular programs. Morgan County planned to host a rotating 

regional drug court by the end of the 2007. 

BLAND and BATH COUNTIES, VIRGINIA

Bath County is located along the northern portion of Virginia’s border with West Virginia. Bland 

County occupies a similar position on the border about three hours south. In 2003, the USDA 

classified Bath County as a non-metro, completely rural county with less than 2,500 urban population. 

Neither county has more than 7,000 people according to 2006 U.S. Census estimates. The 

Appalachian Regional Commission classifies Bland County as economically transitional and Bath 

County as competitive. Bland is bisected by I-77 which brackets access to the county by tunnels. Bath 

is served by one U.S. highway intersecting a state highway. Both counties contain portions of national 

forests and much forested recreational land. The Appalachian Trail crosses Bland County. 

Personal income appears higher in Bath County ($31,520 vs. $22,200) with a greater proportion of the 

public with high school diplomas (74% v. 70.9%) and college degrees (11.1% vs. 9.2%) than Bland 

County. Poverty levels were higher in Bland County (11.9% vs. 7.3%). Bath County reported a 

population change of 4.6% in the 2000-2006 period while Bland had a slight change of 0.5%. Median 

home values in 2000 in Bath County were $79,700 vs. $71,500 in Bland County. There were slightly 
191 

more households in Bland County (2,568 vs. 2,053) and the labor force was larger (3,211 vs. 2,935) 

than in Bath County in 2006. USDA 2006 unemployment figures are similar at 3.6 for Bland County 

and 3.2 for Bath County compared to 3.0 for Virginia. Employment is mostly in the light 

manufacturing sector in Bland County and in the construction sector in Bath County, boosted by new 

luxury homes building. A major employer in the county is a nationally known luxury resort that 

provides high-end tourism activities. 

The County Profile shows that Bland County has a greater percentage of its population in 

correctional/juvenile institutions (8.59% vs. 0.12% for Bath County), but neither county records 

anyone being treated in mental health institutions. Bland County is also the home of the Bland 

Correctional Center, a level 2, male-only prison. Bland County is wholly designated as both a mental 

health shortage area and a primary care health professional shortage area; Bath County has no 

designated mental health professional shortage areas, though it is wholly designated as a primary care 

health professional shortage area. There are over 100 substance abuse treatment facilities within a 100 

mile radius of Bland County, but only 42 within 100 miles of Bath County. Bath County is served by 

two substance abuse out-patient offices, while Bland County has four. 

Alcohol abuse or dependence rates are similar at 7.82% for Bath County and 7.52% for Bland County 

(7.67% is the average for Virginia). Rates are also similar for abuse or dependence of any illicit drugs 

(3.06% for Bath County vs. 2.95% for Bland County) and for the nonprescription use of painkillers 

(5.16% for Bath County vs. 4.94% for Bland County). Rates of serious psychological distress, 

however, are higher for Bland County (9.22%) versus Bath County (8.59%). Bath County shows 

slightly more people needing but not receiving treatment for alcohol use (7.36% vs. 7.05%) and 

needing but not receiving treatment for drug use (2.61% vs. 2.57%) than Bland County. Bland County 

residents used more past month tobacco (33.43% vs. 31.67%) and cigarettes (28.22% vs. 26.61%) as 

reported in 2002-2004, but Bath County showed more alcohol use (50.48% vs. 42.15%) though Bland 

was a little higher on past month binge drinking by 12-20 year olds at (23.61% vs. 23.22%). Bland 

County had slightly more past month marijuana use (5.84% vs. 5.65%), past year use (10.06% vs. 

9.58%), and first use (2.14% vs. 1.82%). Cocaine use was also slightly higher in Bland County (2.37% 

vs. 2.31%). Bath County had a greater use of any illicit drug other than marijuana (3.92% vs. 3.79%). 

Bath County reports some in-school drug prevention programs and the support of churches. The 

county administration, schools, the National Guard and the community services board have taken the 

lead in Bland County to provide in-school and after school programs. Bland County schools have an 

assigned sheriff’s officer while Bath County schools are actively served by the sheriff’s department. 

Bland County has a drug prevention coalition. Efforts to pull Bath County into the Rockbridge Area 

Community Service Board’s Prevention Services have not been successful to date, especially since it is 

administered from an office over an hour away. Neither county has inpatient mental health or 

residential treatment facilities. Long term residential treatment is located 29 miles from Bland County 

and over 53 miles away for Bath residents. Both counties are served by regional community services 

offices which supply outpatient treatment and referrals. 

MONROE and HARDY COUNTIES, WEST VIRGINIA 

Hardy and Monroe Counties occupy comparable positions on the West Virginia border to the Virginia 

counties, also within national forest land. Neither is served by a limited access interstate highway, but 

Hardy County is well-linked about an hour each way to I-68 and I-81. Hardy County has a large 

proportion of residents of German ancestry and occupies a broad fertile swath of agricultural land in 
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the valley of the South Branch of the Potomac River. Monroe County is located only a half hour south 

from I-64 and the Greenbrier resort area. 

While both counties have agricultural bases, Monroe County counts the public administration sector as 

its chief employer. Hardy County has several retail and natural resource production and processing 

plants, resulting in a larger labor force (7,271 persons vs. 5,962 persons) and a lower rate of 

unemployment for 2006 (3.9 vs. 5.5) compared to Monroe County. Virginia’s unemployment rate is 

4.9% by comparison. The poverty rate in Monroe County is higher at 14.3% vs. 12.5% for Hardy 

County. The counties have nearly identical populations (13,420-13,510), and are classified as 

economically transitional by the Appalachian Regional Commission. 

Hardy County exhibits greater overall median home value ($74,700 vs. $64,700 for Monroe County) 

and median household income ($35,361 vs. $31,069 for Monroe County). While Hardy County 

experienced a 5.9% change in population, Monroe grew at 2.4%, both below the average for West 

Virginia as a whole in the 2000-2006 period. Monroe County has a greater percentage of high school 

graduates (73.7% vs. 70.3%), but Hardy County has a higher percentage of college graduates (9.4% vs. 

8.2%). Representatives from Hardy County reported a growing influx of retirees and second home 

builders on its eastern border which is within two hours of Washington, D.C. 

Monroe County’s Profile reported that 9.53% of its population was housed in correctional or juvenile 

institutions while Hardy County showed no figures in that category according to the 2004 Area 

Resource File. Neither county reported any residents in mental health hospitals. Hardy County is 

wholly designated as mental health professional shortage area and partially designated as a primary 

care professional shortage area. Monroe County is wholly designated as primary care professional 

shortage area, but has no mental health professional shortage designation. More Monroe County 

residents needed but did not receive treatment for alcohol use (6.53% vs. 6.0%) and needed but did not 

receive treatment for drug use (2.91% vs. 2.35%) according to the National Survey on Drug Use and 

Health, 2002-2004. Monroe County had a greater proportion of residents reporting serious 

psychological problems (13.66% vs. 11.07%) and a greater suicide rate (0.014% vs. 0.0079%) than 

Hardy County. Hardy County has 135 substance abuse treatment facilities within a 100 mile radius 

while Monroe County has about 52. Neither has an in-patient facility located in the county though 

Monroe County’s out-patient facility treats co-occurring mental health and substance abuse disorders 

and offers detoxification. Both counties have programs that treat adolescents. 

Data for Monroe County show that 6.88% of residents exhibit alcohol abuse or dependence vs. 6.39% 

for Hardy County, both less than the 6.93% for the state. Monroe County has a 3.33% rate of abuse or 

dependence on any illicit drugs (compared to 2.77% for Hardy), which is greater than the state average 

of 3.08%. Monroe County also has a higher rate of past month nonprescription painkiller use (6.58% 

vs. 4.54%), past month tobacco use (39.45% vs. 37.88%) and past month cigarette smoking (31.58% 

vs. 29.74%) than Hardy County. However, Hardy County showed greater past month use of alcohol 

(39.05% vs. 28.58%) and past month binge alcohol use (19.65% vs. 17.39%). Monroe County had 

more past month use of marijuana (5.08% vs. 4.83%), greater past year use of marijuana (10.01% vs. 

9.26%), greater past month use of illicit drugs (7.08% vs. 6.51%), greater past month illicit drug use 

other than marijuana (4.04% vs. 3.48%) and greater past year cocaine use (2.48% vs. 2.05%) than 

Hardy County. 

Both counties have prevention coalitions and applied for funds through the state’s Substance Abuse 

and Mental Health Services Administration Strategic Prevention Framework-State Incentive Grant 
193 

(SPF-SIG) initial planning program, though neither county was selected to receive funding for 2007-

2008. Hardy County has a dedicated sheriff’s deputy present in its schools. The 4-H program through 

the county extension offices organizes activities for youth in both counties. Both counties indicate that 

the faith community also provides support for prevention of substance abuse. 

7.5 Phase 3: Onsite Focus Group and Key Informant Interviews 

Community members were identified in the target counties using key leaders or contacts. Key contacts 

were the researcher’s essential link “inside” the population of interest and were used to facilitate the 

recruitment of participants who could provide meaningful data. Identities of key leaders in each 

community were provided by members of the Coalition on Appalachian Substance Abuse Policy 

(CASAP). These leaders were asked to provide contact information for community members who 

were associated with substance abuse and mental health education, prevention, treatment, etc. as well 

as concerned citizens. All community members lived and/or worked in the targeted county and 

represented at least one predetermined stakeholder group. Multiple stakeholders are essential to 

integrating a broad-based coalition with values diversity for long-term effectiveness. Seeking out 

multiple community stakeholders was a condition of the methodology to ensure depth of data. 

Focus groups were comprised of a diverse set of community members, including representatives of 

multiple stakeholder groups such as law enforcement, medical and mental health practitioners, school 

personnel, business representatives, county extension agents, social service providers and county 

administrators. These stakeholders were presumed to be aware of the county’s substance abuse and 

mental health issues. Participants were contacted initially by mail. The letter was followed within a 

week by a personal telephone confirmation. In a few instances, email was used for contact when no 

address or phone number were supplied. 

Six focus group interviews were conducted between July and September of 2007 in Kentucky, 

Virginia, and West Virginia. The six focus groups were conducted at neutral sites in the selected 

counties including county libraries, community colleges and, in one case, the county courthouse. Prior 

to data collection, the focus group moderator explained the purpose of session, ground rules for 

confidentiality, and conduct and methods that would assure anonymity of the participants. Each focus 

group discussion was audio-taped and transcribed with identifiers removed prior to analysis. Trained 

facilitators used structured focus group moderator guides that were developed specifically for the 

study. All discussions followed the predetermined format of the guides. Each of the focus groups 

lasted between 45 and 75 minutes with an average of 5.5 participants (range 4 to 7 persons). 

Following focus group interviews, key informant interviews were conducted by phone with selected 

members from each of the six counties. Key informant interviews were conducted with representatives 

of stakeholder groups that were underrepresented at the county’s focus group. Key informant 

interviews also followed a structured interview guide and lasted between 25-35 minutes. The 

methodology was reviewed and approved by the ETSU Institutional Review Board to assure 

appropriate informed consent for participation. 

The sections below provide a composite of the responses to questions from the focus group interview 

guides, supplemented by responses from the key informant interviews. Themes were captured around 

each question discussed in the focus group interviews. Each of the focus groups’ notes was also 

classified and compared according to general themes within each state and between all the states. The 

concept of community dialog was incorporated into the focus group reports. The discussion among 

focus group participants who were deeply involved in the life of the communities indicated their 
194 

firsthand knowledge of the issues. Descriptions of the substance abuse or mental health issues or 

“themes” in the counties demonstrated familiarity with the topics. Key informant interviews reiterated 

many of these themes. 

Prior to focus group and key informant interviews, county data profile sheets prepared by NORC (see 

Appendix D) were provided to each participating individual. The county profile sheet provided data 

on socio-economic characteristics, substance abuse and mental health problems, access to treatment, 

institutional characteristics (i.e., mental health institutions, correctional facility, etc), cigarette smoking 

and tobacco use, alcohol use and binge drinking, and marijuana and other illicit drug use. 

Reactions to Secondary Data in County Profiles Provided by NORC 

Four out of the six counties said the profiles (see Appendix D) were fairly accurate, but all expressed 

uncertainty about the definitions and data collection methods used. Both West Virginia counties noted 

inaccuracies in the population and population density numbers and raised questions about these 

specific numbers. The following are comments from the groups about the data profiles that were 

distributed and discussed. 

Item #1: Socio-demographic characteristics 

 Median home value may not be a good indicator in rural counties with relative proximity to large 

urban areas (e. g., Washington DC) because of the influx of new residents for retirement or a 

second home. These individuals tend to be older, more educated and more affluent. Some may 

build homes with higher property values. One county representative noted: “People who retire 

here skew the county income data. The true local residents are poor.” Another person suggested 

that a different poverty indicator may provide a more reliable picture, such as the percentage of 

county students participating in the free lunch program at school: “Fifty percent of all students in 

the county are on the free or reduced school lunch program.” The high school graduation rate was 

questioned in two counties because the inclusion of individuals receiving a GED was not known. 

Item #2: Overview of substance abuse and mental health 

 Some county representatives had questions about where and how the data were obtained for the 

county profiles. Some people expressed concern over how the measures were defined. For 

example, one measure looks at alcohol abuse and dependence as a single data element. One 

respondent mentioned that these are two distinctively different measures: “Alcohol abuse and 

alcohol dependence are two different things, so the data doesn’t reflect that.” 

Item #3: Access to treatment 

 Questions were raised about how the access to treatment data was procured and the sources of the 

data. Sources for this item were not identified on the profiles. The difference between those 

needing help and those seeking help were stated as a simple percentage of the total population. 

Item #4: Institutional characteristics 

 Representatives from each of the counties expressed confusion about what was meant by 

“institutional characteristics.” The presence of a correctional facility is a local determinant that 
195 

does not indicate if persons were incarcerated outside the county, and thus may have 

disproportionately increased the county percentage of persons in correctional/juvenile institutions 

when a correctional facility was located within county borders. The designation “health 

professional shortage area” was not understood by most respondents. 

Item #5: Cigarette smoking and tobacco use/ Items #6: Alcohol use and binge drinking/ and Item 

#7: Marijuana and other illicit drug use 

Respondents from most of the counties indicated that the data were fairly accurate, and the high 

perceived great risk of tobacco use was not a surprise. One respondent asked if the numbers 

included smokeless tobacco use. Some respondents questioned the data collection methods, citing 

the unreliability of self reporting known to be used in some data sources. 

 

Most counties expressed a desire to be compared to other Appalachian counties in their states or to 

regional data. 

Overall Impressions of Substance Abuse and Mental Health Problems in their Communities

All communities indicated that prescription drug abuse was prevalent. The use, acquisition, and 

distribution of the non-prescribed pain relievers contributed to criminal behavior and involved 

community social networks and created an alternative economic layer to the community. In addition, 

most communities believed that prescription drug use was a result of the relative ease of access to 

dealers or other procurement methods. One respondent noted that drugs are acquired or stolen from 

family members: “Prescription abusers first deplete the family. They empty out the medicine cabinets 

before seeking other sources for drugs.” Other common drugs of choice included alcohol, tobacco, 

marijuana, inhalants, and methamphetamine. Law enforcement officers and counselors confirmed a 

smaller presence for heroin, cocaine, ecstasy, and other illegal drugs but said use and choice was a 

function of ease of access, cost, and cultural preference. 

Respondents from most of the communities indicated that drugs were easy to obtain and could be 

obtained locally. Participants reported that students seem to have a great deal of knowledge regarding 

drugs and many could identify local drug dealers. People from all of the communities indicated that in 

a small county “everyone knows everyone,” and as such, discretion was difficult. One respondent 

noted: “Drug dealers are on every street corner and we tend to know who they are.” 

Some people discussed the procurement of drugs out-of-county and out-of-state. People from all of the 

counties reported that their emergency rooms, pharmacies, dentists and doctors have experienced 

people with habitual and extensive drug-seeking behaviors. Some counties’ offices and institutions 

have taken steps to curb this behavior through specific prescription dispensing management practices. 

The Kentucky counties were somewhat familiar with the Kentucky All Schedule Electronic Reporting 

System (KASPER) procedures. KASPER tracks controlled substance prescriptions dispensed within 

the state and shows all scheduled prescriptions for an individual over a specified time period, the 

prescriber, and the dispenser. Designed to be a source of information for practitioners and 

pharmacists, and an investigative tool for law enforcement, KASPER has some lag (real time) between 

filing and access by other system users that has been initially exploited by drug seekers.
196 

Some community leaders indicated that substance abuse was underreported. Participants perceived a 

collective denial of substance abuse, contrasted with individual awareness of specific dealers, users, 

habits and behaviors. Multiple factors were identified that influence this finding: 

Cultural and family factors contribute to the denial of the existence of substance abuse and its 

severity. 

Small communities reported the existence of stigma for seeking help and that many parents 

reject complicity or accountability for the behavior of children or other family members. 

Substance use is often seen as a coping mechanism and is sometimes accepted as a normal 

behavior in many communities. 

Substance use is often not acknowledged as abuse until the behavior becomes harmful or 

criminal. As indicated by one focus group participant: “Substance abuse is significantly 

underreported and indication of abuse comes out in different kinds of ways such as 

unemployment.” 

All counties expressed knowledge of regional substance use problems and knew that other nearby 

counties experienced similar issues. Participants from counties were aware of national trends and 

noted that their area mirrored what was happening in the nation. The regional news media reach across 

state boundaries in most cases so that rural and urban people receive and share the same information. 

No community was informed in advance of its status of being selected because of high or low county 

substance abuse indicators. Interestingly, all communities perceived that their own substance abuse 

was high. The following is a list of factors contributing to substance abuse cited by communities: 

Substance abuse can often be the result of self-medication for underlying factors such as 

depression, anxiety, and deeper psychological trauma, such as child abuse; 

Geographical isolation (limited transportation, rurality) and distance from services; 

Societal and cultural factors like stoicism, self-reliance or pride; 

Economic stressors like loss of community resources and scarcity of worthwhile employment; 

The use of substances to escape from problems; 

Intergenerational modeling of substance use behavior by parents engaging in the behavior, 

having a positive attitude towards the behavior, and/or allowing child substance use; 

Societal factors including peer pressure, poor family values, expectations, and media marketing 

of prescription drugs as a “cure all”; 

The break-down of family and community values; 

Boredom; 

Limited recreational opportunities for youth; and 

Few positive adult role models. 

Participants in one focus group noted that children today lack goal-setting skills and that hope is in 

short supply. One person noted: “Our kids have generational poverty and they don’t have a clue about 

how to achieve goals.” On the other hand, participants from a few communities indicated that residing 

in a small rural community can also serve as a protective factor against substance use and creates a 

cohesive, self-aware unit where people are likely to know and help each other. One community 

representative noted the “presence of a lot of traditional ‘moral people’” and that “families are close 

and churches are abundant.” These were factors thought to contribute to lower rates of substance use. 

Conversely “poor moral fiber” was believed to be a factor that promotes substance abuse and 
197 

addiction. The availability of fulfilling employment and greater relative wealth was thought to be a 

deterrent in a few of the communities. Communities that reported broader educational opportunities, 

more after school programs (including sports and music), and awareness of the consequences of drug 

abuse were less likely to indicate higher levels of substance abuse. 

Some state and local data are collected by counties or entities within counties, especially in preparing 

funding applications. Purchased or state-provided school youth surveys are primary sources of data 

that communities can use to gauge local situations and benchmark to national trends. The following is 

a list of surveys being used to collect primary data on substance use, as well as personal factors 

affecting substance use. 

Parents' Resource Institute for Drug Education (PRIDE) Survey from National Survey 

Associates - the PRIDE survey measures the prevalence of alcohol, tobacco, and drug use by 

students in grades 6-12 and was reportedly used by one county in West Virginia and both 

Virginia counties in the last two years. Available at: http://www.pridesurveys.com 

Kentucky Incentive for Prevention Survey (KIPS) - KIPS measures substance use among 6th, 8th, 

10th, and 12th grade students. School specific data is provided to local school administrators 

and is publicly available in regional aggregated data sets. Available at: 

http://mhmr.ky.gov/MHSAS/sa_kipsurvey.asp 

Search Institute’s 40 Developmental Assets Survey - this survey measures such factors as 

positive relationships, skills enhancement, and health promoting activities among school aged 

children and was used by one county in West Virginia within the past four years. Available at: 

http://www.search-institute.org 

In addition to surveys, some communities rely on other secondary data. The following are additional 

data items that were suggested. 

Emergency Management Services - overdose response calls, overdose deaths. 

Local Police Reports - DUI arrests, drug related arrests. 

In most cases, the case study counties did not seem to seek out and use locally available data. While 

communities presumed a problem with substance abuse, additional data did not seem to be a valuable 

resource except for grant application purposes. One person from a Department of Social Services 

summarized this attitude, saying: “We need to get away from wasting money collecting and looking at 

data, and use this money on prevention.” 

 

In looking at mental health problems in their communities, most county groups observed that 

preexisting mental health issues often manifest as substance abuse problems; that is, people often 

abuse substances as a way to cope with a mental health issue. One focus group participant noted: 

“Mental health problems are often a result of a situation in one’s life that results in substance use and 

abuse as a way to cope with one’s problems.” This “self-medication” is perceived to occur especially 

when depression and anxiety are the underlying issues. In one county, a treatment specialist reported 

that the majority of people seen for addiction have underlying depression. This complex relationship 

is seen to be affected both by the long term and often severe economic issues faced by mountain 
198 

communities and their resident families, and the documented prevailing Appalachian cultural attitudes 

of self-reliance. 

Individuals from most counties indicated that they lacked adequate mental health services and that 

access to care was a contributing problem to the prevalence of mental health issues. None of the 

counties had inpatient treatment and most reported a limited scope of mental health services. Often 

treatment was provided by psychologists/psychiatrists practicing in the county for a few days per 

week. One individual noted: “For every 1,000 people who have trouble with alcohol, we have one 

bed. Their insurance card will tell you how long it will take to detox because that is how long they can 

stay.” 

According to focus group participants, a cultural stigma is attached to seeking mental health care. 

Some people would not seek treatment even if the services were available because of fear of being 

observed, and judged, by family and peers. One person noted: “We are a proud people and do not 

typically ask for help.” Treatment costs were also reported to be a major barrier in most counties. 

Many Appalachian communities have large numbers of residents with no insurance or limited 

insurance benefit packages that prevent them from seeking or receiving services. One best practice 

strategy was identified in Kentucky: some anti-drug coalition groups provide one-time referrals and 

payment for substance abuse treatment with funding from federal sources. Transportation issues, 

parental denial of children’s mental health conditions, and multi-generational acceptance of mental 

health issues were mentioned as barriers in all counties. 

Among mental health and substance abuse treatment services most often cited as missing was a lack of 

residential treatment facilities within the counties. Residential placement in other counties was 

difficult but was the typical avenue for people requiring residential treatment. Additionally, counties 

indicated that additional school prevention programs would be desirable. Only two of the six counties 

had well developed prevention programs. These counties were using nationally based model programs 

such as “Lifeskills Training” by Gilbert Botvin. Other counties had limited programs which were more 

modest in scope. Dearth of funding or state restrictions sometimes limited the institutional purchases 

of science-based classroom prevention packages. 

The need for greater law enforcement resources was cited in several counties. Individuals across 

counties perceived that in rural areas, local, county and even state police presence are overwhelmed 

with day to day operations. Specifically, it was noted that police have insufficient funding for 

adequate law enforcement to address and control criminal activities related to substance use and 

distribution. For example, one county had two officers to patrol 575 square miles. Additionally, law 

enforcement professionals acknowledged that only a small percentage of criminal activity due to 

substance use was curbed due to their efforts. One individual noted: “We can’t keep up with the calls 

we do get, let alone prevent anything.” In one county, law enforcement facilities were used as a last 

resort for mental health emergencies (i.e., holding an individual in a county jail) when appropriate 

treatment was not immediately available. 

7.6 Phase 4: Development of Community Resource Inventory 

As part of the case study process, each county was asked to identify existing community programs that 

it considered “exceptional” or “best practices.” Existing research defines best practices as a technique, 

activity or methodology that, through research, experience and replication, reliably provides: 
199 

Effective and desired result(s); 

Ethical and equitable outcome(s); 

Adaptability to similar environments; and 

Opportunities for innovation. 

While few counties felt they provided adequate services to their communities, all were able to list 

mental health and substance abuse programs and services in their counties that met these criteria for 

“best practices.” However, some respondents noted that the use of best practice programs and services 

is limited by financial and other constraints. 

Model services and program activities varied due to state and local financial and human resources. All 

counties but one had some form of anti-drug coalition comprised of concerned stakeholders. The 

presence of program activities by churches, schools and community groups also contributed to a sense 

that positive alternatives to substance abuse were available. Treatment services varied, but all counties 

had access to outpatient treatment. However, the degree of community utilization and perceived 

competence varied (see Tables 7.2 and 7.3). 

The following programs were mentioned as available within the participating counties: 

Mental Health 

All counties in the study have access to outpatient treatment facilities within the county. However, 

individuals felt these facilities were underused and that the drug problem within the county was greater 

than reported. Only two counties (Wayne County, KY and Bland County, VA) had additional 

independent substance abuse/mental health providers within the county. No county had inpatient 

facilities for either substance abuse or mental health and most reported difficulty placing those needing 

long term outpatient treatment. Special programs include the Rockbridge Community Services Board 

PACE (Parenting Assessment Consultation and Education), which models appropriate parenting. The 

FMRS Health System in Monroe County (WV), a not-for-profit behavioral health organization, offers 

the Mother Program, a women’s substance abuse treatment program and ADAPT for adolescents. 

Schools 

Individuals across counties noted that the schools were integral to the dissemination of prevention 

programs and activities. In some counties, adolescent and family outpatient counseling took place at 

the schools because it was the most accessible environment for students and parents. Most school 

systems are bound to use evidence-based, proven prevention programs that may be purchased if funds 

are available. Only one school system reported using the DARE activities. Wayne County (KY) and 

Bland County (VA) were using LifeSkills4Kids. Beginning Alcohol and Addictions Basic Education 

Studies (BABES) is a classroom-based primary alcohol prevention program for children 5-8 years of 

age that is being implemented in Wayne County (KY). Other counties use Protecting Me/Protecting 

You from the Mothers Against Drunk Driving (MADD), a 5-year classroom alcohol prevention 

program for grades 1-5. Too Good for Drugs (Wayne County, KY) for elementary and middle school 

students and Parenting Wisely (Bland County, VA), for children 9-18 years, are both science-based, 

field-tested SAMHSA model programs. Monroe County (WV) touted having a school-based wellness 

center in each county school. 
200 

Justice and Law Enforcement 

One county (Morgan County, KY) anticipated a drug court which will rotate regionally to ameliorate 

judicial overload. Wayne County also participates in the Kentucky Drug Court Program. Bath County 

(VA) combines its family and juvenile courts and Bland County (VA) has a youth case management 

worker. Bland County (VA) and Hardy County (WV) have had representatives of the sheriff’s 

department in the schools; individuals in both counties indicated that they made a substantial 

contribution with respect to providing a needed law enforcement presence. 

Faith Community Programs 

Representatives from all counties said that church and faith-based programs were important to the 

quality of life and health in the community. Morgan County (KY) has an after school program called 

Lifeline that was considered an outstanding contribution, as was Bath County’s (VA) Camp 

ACCOVAC, administered by the Adventist Christian church. Morgan County (KY) respondents said 

that the many vacation bible schools were a deterrent to drug activity. Both West Virginia counties 

actively use their ministerial association for referrals. Bland County (VA) worked with Hope 

Ministries Center, a Southern Baptist mission which provides some health and dental care. 

Other Community Programs 

Youth mentoring programs were present in all communities, provided by local community agencies 

and organizations such as Kiwanis clubs and county extension service 4-H programs. These programs 

often work through the schools or offer summer and weekend programs to alleviate boredom and 

provide esteem-building activities for youth. In Hardy County (WV), the school counselors actively 

partnered with county extension agencies involved extensively in youth programs to provide wellness 

activities including substance use prevention, wellness, health, and self-esteem activities. 

Drug coalitions also play a visible role in attracting attention and money to address substance use 

issues and provide a focus for program activities in communities. Kentucky has received federal 

money to organize Operation UNITE anti-drug coalitions through the efforts of Congressman Hal 

Rogers. These coalitions are well-supported in the state and work closely with law enforcement 

agencies. In Virginia, Bland County has the advantage of a progressive county administration that has 

been assertive in organizing and seeking funding for prevention activities, while Bath County has 

relied on prevention efforts through the schools. The Hardy County (WV) Prevention Partnership and 

the Monroe County (WV) Prevention Coalition include tobacco, alcohol, and drug use prevention as 

part of their agendas, with funding from the West Virginia Tobacco Settlement Foundation. Wayne 

County (KY) and Bath County (VA) mentioned the presence of Assistance for Alcohol and Substance 

Abuse Prevention (ASAP) programs, a workplace education, prevention and testing service offered 

through employers, though only Virginia offers workmen’s compensation for ASAP program use. The 

presence of an active multi-stakeholder prevention coalition is a function of community interest in the 

issues, but acquires significance and weight through state and federal recognition and funding. The 

degree of prevention awareness and treatment availability may be functions of that recognition (see 

Tables 7.2 and 7.3). 
201 

7.7 Phase 5: Key Findings 

Key findings were developed based on an analysis of the textural data derived from the interviews and 

focus groups. Using an induction method, the analysis focused on the organization of broad 

conceptual categories and then more refined coding for underlying themes. Finally, the textural data 

was triangulated with secondary data profiles, and county descriptors with the researcher’s field notes 

to produce an understanding of the incidence of and explanation for disparities in mental health status, 

substance abuse prevalence and access to treatment services in these Appalachian communities. 

Key Findings 

The national data sets used in the County Profiles painted a different picture of county 

problems than county representatives felt were important because the profiles did not clearly 

illustrate local factors. Local data sets are essential to understanding the depth of the substance 

use and mental health issues faced by residents at the county level. However, focus groups 

stated that local data is not always sought or used effectively in education or planning. Some 

stakeholders said that local data collection is not as important or useful as other applications 

because the issues are assumed to be well-understood and money used for data collection is 

more urgently needed for basic services. With better coordinated data collection, 

documentation and analysis, localities may be better equipped to access resources at state and 

federal levels. 

Several common themes emerged from the case studies regarding barriers to use of services 

including social stigma for those who seek care, lack of transportation, non-recognition of 

roots of substance use behaviors, multi-generational patterns of substance abuse behaviors, and 

erosion of the power of family and community networks to assist in personal coping skills. 

These multiple factors must be taken into account when prescribing ways to increase access to 

mental health treatment and reduce the prevalence of substance abuse in Appalachia. 

Appalachian communities have a sense of regional awareness of mental health and substance 

abuse issues and express willingness to share facilities and solutions. None of the six focus 

group sites had residential treatment facilities and those seeking treatment had to travel over 30 

miles to receive even short term residential treatment. Individuals in these communities felt 

that substance use and mental health disparities were issues not only in their community but 

also throughout the rest of the state, and region. 

Focus groups members were concerned with destruction of community social infrastructure, 

family values and workforce viability due to substance abuse, and wanted better conditions for 

all citizens of their counties. The well being of youth was of paramount importance to rural 

counties as evidenced by the emphasis on prevention and awareness of substance abuse in 

schools and youth-programs settings. 

Solutions to mental health and substance use issues were understood by communities to be 

community-based and family-based; solutions were thought to be more effective when actively 

supported by other local institutions like schools, churches and courts. Communities with more 

diverse programs to address substance abuse and mental health seemed more confident that 

they were able to have a positive impact on their citizens. 

Moral and cultural decline in general was noted most often as the reason for substance use. 

Factors such as irresponsible parenting, effects of the media, two-income families, decreased 

personal expectations, poverty, poor job prospects, easy access to prescription drugs, peer 

pressure, boredom and curiosity about drugs were cited as causes of this decline. Communities 
202 

saw solutions to substance use in programs or activities that addressed one or more of these 

issues. 

Each of the sites reported that substance use and mental health problems were the result of cooccurrence and not the result of a single cause. 

The following are some of the limitations or special considerations related to the case studies. 

Respondents 

The respondents who participated in the focus groups and key informant interviews were provided by 

contacts within the substance abuse/mental health arena in each county. Most respondents were 

members of local antidrug coalitions, treatment facilities or other public figures in the county. Focus 

groups met during the work day. Some potential respondents were unable to participate because of the 

time or personal schedules. While a comparable representation was sought from similar stakeholders 

or constituents in each county, not every stakeholder group was represented. 

Counties 

In this report the terms “county” and “community” are often used interchangeably. Both terms refer an 

Appalachian concept of cultural identity which defines the parameters of place identity. A community 

exhibits membership boundaries within a pattern of beliefs and behavior for the dominant cultural 

group. The unit of identity in a rural setting is the county where the largest “urban area” may be the 

county seat. In this study, all county seats were towns of fewer than 6,000. In Appalachian counties, 

the social constructs of a county seat seem to be representative of the county as a whole. The 

attachment is to the county “community.” Attachment to the Appalachian portion of the state or 

surrounding counties and to regional Appalachian affiliations which may cross state lines was evident 

in the focus groups when participants mentioned the desire for comparison to other counties in the 

region. 

Though the counties selected for inclusion in the case study pilot were based on objective rankings, in 

fact, the four counties on the border of Virginia and West Virginia were close in geographic proximity 

and had similar demographic profiles with similarities in attitudes, concerns, issues, barriers, and 

services. The two Kentucky counties were farther apart in geographic proximity. Individuals from all 

counties expressed the desire to be measured against comparable rural Appalachian counties. 

Individuals from all six counties felt that the uniqueness of the Appalachian region made an accurate 

comparison of an Appalachian region to a non-Appalachian region difficult. 

Substance abuse concentration 

The problems associated with substance use seemed to be of greater importance to focus group 

participants than did problems associated with mental health. Substance abuse was the opening topic 

of discussion and featured in seven of the twelve survey protocol questions. It was a problem that 

touched more stakeholders in the community notwithstanding the interrelatedness of the issues. 

Data sets comparison 
203 

Three sources of potential data emerged from the study: The data sets used by NORC to compile the 

County Profiles, the sets suggested by CASAP through a Delphi Process, and the data used by the 

counties in the case studies. NORC used nationally available, proven and accessible data sets to 

prepare the county profiles. Some of these numbers were calculated based on county population size. 

Not all of the data sets suggested by CASAP through the Delphi process are available nationally or 

state by state at the county level. Data is also not collected or reported consistently from state to state. 

However, these suggestions – gathered from Appalachian researchers, educators and practitioners – 

were examples of ideal data to use to measure high/low substance abuse prevalence and mental health 

access. 

The county/community data postulated by local decision makers was reported in focus groups and key 

information interviews in the six Appalachian county case studies. While other data sets may also be 

used by counties, these were reported as being useful or desirable. Some data sets corresponded to sets 

from other sources and are grouped on the same line. 

The use of secondary data, collected at state and local levels, is being encouraged by the Community 

Anti-Drug Coalitions of America (CADCA), the Robert Wood Johnson Foundation, Join Together, 

and Substance Abuse and Mental Health Services Administration’s Strategic Prevention FrameworkState Incentive Grant program as the most reliable way for local agencies to assess current need and 

project the scope of substance abuse issues and treatments. The reality is that finding and using local 

data in a coherent way is difficult for some local groups because of cost, cooperation, presumptions of 

knowledge and small sample size. Table 7.4 below also demonstrates the gaps in available data for 

planning at the local level. 

Researchers from ETSU drew the following conclusions about the case studies data: 

Regional substance abuse and mental health leaders do not have uniformly available county 

and state data sets from which to draw conclusive measurements, but they do know what types 

of data would be useful to formulate a local response to the issues. 

National researchers do not have enough reliable county-level data from which to draw 

conclusive analyses. This conclusion is based on questions and reactions to county profiles in 

the case study. 

Appalachian counties and communities do not report using nationally-available data sets to 

make decisions about local responses to substance abuse and mental health issues. They may 

use state data, especially when it supports applications for grant funding of prevention 

programs, but anecdotal evidence informs decision making. 

Assessing the Communities’ Dialogues: Strengths and Gaps in Prevention and Treatment 

Each of the six focus groups and sets of key informant interviews represents a community’s dialogue 

about its substance abuse and mental health issues. Profiled below is the commentary regarding 

community perceptions of their own strengths and treatment gaps with regard to substance abuse and 

mental health needs and services. The final section summarizes elements of the six separate dialogues 

and offers conclusions. 

In relation to prevention and treatment services available to address substance abuse and mental health 

issues, the counties chosen for this case study exhibited many strengths. These strengths are 
204 

characteristics of the counties that can be seen as deterrents to substance abuse behavior or those that 

promote local treatment options. These strengths are essentially features that contribute to preventive 

and protective factors in the community. The model programs listed in Table 7.2 represent some of 

these strengths. Additionally, a listing of strengths is provided in Table 7.3. The focus groups, 

informants and the inventories also identified areas of need and gaps in the prevention and treatment 

continuum. In Table 7.3, the gaps in the prevention/treatment continuum are concentrated under the 

“gaps identified from the interviews” and “gaps identified from the focus groups.” 

Each community discussion demonstrated cognizance of both the protective factors and the disposition 

to risk associated with rurality and the Appalachian culture. Small town culture was mentioned as an 

asset by people representing each of the case study counties. One individual described the benefits of a 

rural community: “We look out for each other.” Another individual noted the close-knit nature of the 

community: “If you do something, [your] parents will know before you get home.” Additionally, 

focus group participants noted that other factors may affect a community’s disposition to risk, 

including the demands of single-parent households, dual-income families, poor parental examples, and 

normative risk behaviors in the media, music, films and television. Others noted that the propensity 

for youth to use drugs was exacerbated by the small town atmosphere, moral decline, peer pressure and 

proliferation of outside influences like television and the internet. According to participants, 

individuals and the community face internal and external realities that create tension and uncertainty, 

and may contribute to the use of drugs and alcohol. 

Distance between the county and illicit drug distribution sources was not always seen as a protective 

factor, as the nearest medicine cabinet could be a pharmacopeia of useable or saleable drugs. 

Poverty in rural areas was discussed as a potential protective factor to substance abuse. One focus 

group participant commented that relative rural poverty was a protective factor because it limited the 

purchase of drugs. 

All communities saw a relationship between employment and substance abuse, whether the use was 

caused by addiction to painkillers resulting from job-related injury, recreational habituation, or the 

numbing depression from a dead end job. In one community with adequate employment opportunities, 

county officials said that employers learned to look the other way and only required drug testing when 

a safety violation or accident occurred, preferring a workforce that was functional regardless of 

substance use. 

The risks posed by place are related to the perception of relative isolation from legal consequences, 

covert use of substances, lack of a range of activities for youth, and diminished employment 

opportunities. These risks were not listed as gaps but were seen as a conditional quality of the nature 

of the rural setting. 

Common strengths among all the counties surveyed were the state-supported networks of behavioral 

health treatments services. These multi-county agencies furnish both mental health and substance 

abuse treatment on an outpatient basis. No county had any in-county residential treatment facility and 

relied on referrals to residential facilities at distances of at least 30 to 50 miles. Transportation to 

treatment on a sustainable basis was difficult for those with limited means. 

Faith-based prevention activities and some informal counseling for substance abuse and mental health 

were provided in each of the counties. Stakeholders from each county mentioned that the presence of 
205 

churches, youth programs, a strong faith community, and positive adult and family models were 

factors that contributed to the moral fiber of the community and offered protective qualities. 

The presence of school-based prevention activities, curriculum, after-school youth activities, and 

multi-generational events were central to the perception of a positive community atmosphere. 

Stakeholders from counties that had such activities noted that they felt the community was committed 

to creating a positive environment where drugs are not the answer to boredom, lack of jobs, and 

despair. Parenting classes, agricultural extension programs, wellness classes, health camps, mentoring 

programs, sports, and recreation were some ways that communities worked to prevent drug use and 

promote mental health. 

The array of anti-drug coalition activities is an important strength of the rural communities surveyed. 

Operation UNITE, an organization that is active in both Kentucky counties, seeks to prevent illegal 

drug use, coordinate treatment, provide support to families and friends of substance abusers, and 

educate the public about the dangers of drugs. UNITE was started with federal funding. Bland, Hardy 

and Monroe Counties each had multi-stakeholder coalitions supported by state and regional agencies 

that functioned to raise awareness about the dangers of drug use. 

Outstanding local leadership was a positive asset in several communities. Local “champions” 

mobilized action and coordinated prevention activities. Individuals working in the school systems, 

county governance, and public health noted that local leadership was a positive asset to their 

communities. Leaders became apparent as participants talked about the issues and solutions in their 

communities. These individuals could be a local county extension agent, the county executive, the 

school resource officer, a concerned counselor, or a public health official. Common to these 

individuals was recognition of the necessity to involve others from all parts of the community to tackle 

the problem on many fronts. 

Access to treatment, including transportation, payment options, privacy issues, stigma, choice of 

facilities and cultural or family bias, were uniformly identified as gaps in the continuum of care for 

substance abuse and mental health. The paucity of long term care residential treatment facilities and 

after-care programs was also discovered. The continuity of treatment modalities was a concern. 

Counties recognized that treatment constituted a long term commitment to recovery and recovery 

maintenance. Some modalities are provided in volunteer settings (e.g. Alcoholics Anonymous and 

Narcotics Anonymous and local drop in centers). Counties lacked reliable volunteers and locations for 

the groups to meet, and experienced cultural barriers for women and youth. 

The need for treatment options for women was suggested in two county focus groups, while the need 

for more school intervention and action prevention programs was mentioned in three county focus 

groups. Individuals from both Virginia counties noted the need for better emergency mental health 

plans because their counties are geographically situated far from appropriate emergency mental health 

care; county providers were often forced to improvise in emergency mental health situations. One 

county said that another access to treatment issue was that employed individuals had difficulty 

securing time off during work hours which added to the stigma attached to seeking care; thus, another 

gap to mental health treatment are the service hours available for treatment. 

These Appalachian communities have strengths and assets within their counties and some gaps in 

services that are not evident from national data sets. Generalizing strengths and gaps in treatment and 

prevention from these six counties to other Appalachian counties may be speculative at this time. 
206 

Definitive descriptions can only be made through individual assessments of each Appalachian county’s 

response to the substance abuse and mental health issues. However, we recognized from these 

communities that: 

Substance abuse resulting from the distribution of prescription drugs as much or more than 

alcohol and tobacco is a prime concern to government officials, law enforcement and 

justice personnel, health departments, educators and the public. 

Nearly every person interviewed admitted they had been touched in some way by substance 

abuse issues among family and friends. 

Socioeconomic realities and community culture are two factors that affect substance abuse 

and mental health issues. 

Individuals from case study communities indicated the need to address local problems 

locally. They are trying to implement successful new strategies to restore their 

communities and to help individuals to engage in healthy behaviors and lead productive 

lives. 

7.8 Discussion and Conclusions 

The case studies revealed that the deeper story about Appalachian substance abuse and mental health 

disparities cannot be captured using nationally available data sets only. Analyses of substance use 

prevalence and mental health status using national data must be supplemented by additional local data 

that contains information about the institutional populations, law enforcement, EMS, etc. 

Through direct participation in focus groups and interviews, key respondents described the diversity of 

the rural Appalachian counties – despite their similarities across socio-economic indicators. The onsite visits to the six counties were important to understanding the variety of local substance abuse and 

mental health issues found in each county. Some leaders acknowledged that there are insufficient 

resources to cope with the effects of substance distribution, abuse, and addiction. Other leaders 

appeared to be in denial of the substance abuse and mental health issues in their communities. 

Findings from the focus groups revealed that the steps needed to ameliorate substance use and mental 

health treatment access issues are largely dependent on the local community’s recognition of these 

problems. In addition, other factors that also have an influence on access to treatment include state 

resources, local economic conditions, the community’s culture and commitment to resolving the 

issues, transportation options, viable payment alternatives, and mobilization of key community 

members. 

Individuals from each of the county sites reported that substance abuse and mental health issues are 

often co-occurring. These issues are complex and any approach must consider the relationship 

between mental health and substance abuse, as some people may abuse substances to deal with anxiety 

or other serious mental health problems. In other situations, substance abuse may precipitate or 

exacerbate mental health issues. Policy makers must address prevention and access to treatment issues 

as well. This research suggests that substance abuse and mental health issues are typically cooccurring disorders that impact the community at large. Additional research in other areas of 

Appalachia should be conducted to test the reliability of these results. 
207 

Table 7.2. Model Programs (Best Practices) from Appalachian Twinned-County Focus Groups 

 Kentucky Virginia West Virginia 

Morgan Wayne Bath Bland Hardy Monroe 

School Champions for 

Drug-Free 

Kentucky 

Too Good for 

Drugs 

LifeSkills4Kids 

BABES 

Second Step 

Too Good for 

Drugs 

 Champions 

Against Drugs 

Safe and Drug 

Free Schools 

program 

After Prom 

activities 

LifeSkills4Kids 

Parenting 

Wisely 

DARE 

Protecting 

Me/Protecting 

You 

Character 

Education 

Tobacco 

Prevention 

Health 

Choices Camp 

Drug and 

alcohol 

education K12 

Tobacco 

programs 

School Partnerships 

School-based 

wellness center 

Sports 

After school 

activities 

Tobacco programs 

Faith-based Lifeline after 

school program 

Ministerial 

Association 

Church VBS 

programs 

Church 

activities 

Camp Kovacs 

Churches 

Hope Ministries 

Churches 

Ministerial 

Association 

Churches 

Ministerial 

Association 

Churches 

Law 

Enforcement 

 ACCESS 

emergency 

mental health 

care 

School 

Enforcement 

Officer 

Officer in 

Schools 

Community 

Prevention 

Operation 

UNITE 

 Hooked on 

Fishing 

 School 

programs and 

clubs 

 Summer 

activities 

Morgan Co. 

ASAP 

Operation 

UNITE – 

DAAD 

 Hooked on 

Fishing 

 Celebrate 

Recovery 

 Neighbors 

United 

Wayne Co. 

ASAP 

Prevention 

Task Force 

ASAP alcohol 

prevention 

Operation 

CADDY 

Family 

Resource 

Center 

Strengthening 

Families 

program 

Hardy Co. 

Prevention 

Partnership 

Family 

Resource 

Center 

Community 

Action 

Monroe Co. 

Prevention Coalition 

Medical 

Mental 

Health 

Pathways, Inc. Adanta 

Behavioral 

Health Services 

Phoenix 

Preferred 

Health Care 

 

Narcotics 

Anonymous 

AA 

Rockbridge 

Community 

Services Board: 

 PEPPACE 

Mt. Rogers 

Community 

Services Board. 

AA 

Potomac 

Highlands 

Guild 

AA 

FRMS Health 

Systems: 

 Mother Program 

 ADAPT for 

adolescents 

 AA 

Judicial Drug court 

(rotating) 

Drug Court Bath Co. 

Combined 

Courts 

Mt. Rogers 

Youth Case 

Mgt. 

 

Other Kiwanis Club Wayne Co. 

Hotline 

Youth 

Empowerment 

Network 

4-H clubs 

Kiwanis Club 

Parks and 

outdoor 

recreation 

4-H 

Virginia 

National Guard 

activities 

4-H 

Parks 

4-H 

4-H 

Summer programs 

West Virginia 

Prevention 

Resource 
208 

Table 7.3. Strengths and Treatment Gaps for Twinned Counties Study 

Kentucky Virginia West Virginia 

Wayne Morgan Bath Bland Hardy Monroe

Strengths 

(See also 

Model 

programs) 

Strong faith 

community; 

school drug 

testing; nuclear 

families; small 

town culture 

Church programs; 

positive adult and 

family models; 

after school 

programs; 

publicizing drug 

mortalities 

Recreation 

opportunities; 

churches; youth 

programs; 

rurality; lack of 

jobs(income to 

buy drugs) 

Parental 

involvement; 

churches; outreach 

programs; teachers 

who listen; lack of 

gang activity; 

small town 

atmosphere 

Relative wealth; 

employment 

opportunities; 

education; strong 

rural families; 

churches; small 

community 

culture; 

mandatory 

employee drug 

screening 

Summer youth 

programs; 

strict 

medication 

controls at 

health centers 

and mental 

health 

facilities; 

ruralness; 

small 

community 

setting and 

culture 

Strengths 

from 

Inventories 

Adanta Behavior 

Health Services 

including 

adolescent and 

female 

treatment; 

Phoenix 

Preferred Care 

services; UNITE 

coalition 

activities; inschool 

prevention 

programs; AA; 

county extension 

youth programs; 

community 

center; state 

Champions 

program 

Pathways, Inc. 

mental health and 

counseling 

services, 

drug court; church 

involvement; state 

Champions 

program; UNITE 

coalition activities; 

school prevention 

programs; after 

school care; 

Kiwanis 

community 

programs 

Rockbridge 

Community 

Services Board 

services; school 

prevention 

efforts; 

knowledgeable 

sheriff’s drug 

officer; 

recreation 

facilities; 

concerned DHS 

personnel 

Mt. Rogers 

Community 

Services Board 

services; school 

enforcement 

officer; classroom 

prevention 

programs; VA 

National Guard 

programs; 

vigorous county 

administration 

involvement; drug 

coalition activities 

Potomac 

Highlands Guild 

services including 

adolescent 

treatment; sheriff 

officer in schools; 

Making Healthy 

Choices 4-H/ 

school camp; AA, 

county extension 

youth programs 

FRMS Health 

System 

Mother 

program and 

adolescent 

program; 

school 

partnerships; 

school-based 

wellness 

centers; after 

school 

activities; 

concerned 

county health 

department; 

county 

extension 

youth 

programs 

Profiles: 

Needing but 

not receiving 

treatment for 

alcohol use 

5.81% of 

population 

5.67% of 

population 

7.36% of 

population 

7.05% of 

population 

6.00% of 

population 

6.35% of 

population 

Profiles: 

Needing but 

not receiving 

treatment for 

drug use 

2.45% of 

population 

2.91% of 

population 

2.61% of 

population 

2.575% of 

population 

2.35% of 

population 

2.91% of 

population 

Gaps 

identified 

from focus 

groups 

Residential 

treatment; more 

school 

prevention 

programs 

30-day + 

Residential 

treatment; faithbased youth 

residence; half-way 

houses; treatment 

for women; Action 

programs in 

schools; more state 

involvement 

Drug coalition; 

Prevention 

programs in 

schools; local 

residential 

beds; adequate 

emergency 

mental health 

plan 

Local hot line that 

is not tied to 911; 

better total health 

care 

More AA 

programs, more 

law enforcement; 

prevention 

programs for 

adults; treatment 

options for women 

More 

treatment 

facilities; 

specific local 

data 

Gaps 

identified 

from 

Inventories 

Access* to 

residential 

treatment 

Access* to 

residential 

treatment 

Access* to 

residential and 

outpatient 

treatment; 

school 

prevention 

programs 

Access* to 

treatment, 

residential 

treatment 

Access* to 

treatment, 

residential 

treatment 

Access* to 

treatment, 

residential 

treatment 

*Access to treatment: transportation, payment options, privacy issues in rural community, and treatment choice within the 

community. 
209 

Table 7.4. Gaps In Available Data For Planning At the Local Level 

NORC** DATA 

SOURCES Used for Preparation of County 

Profiles and as measure of high/low 

substance abuse prevalence/mental health 

status in Appalachian counties 

CASAP* DELPHI PROCESS DATA 

SETS suggested as measures of high/low 

substance abuse prevalence/mental health 

status in Appalachian counties 

COMMUNITY/COUNTY DATA 

(from case studies) as measure of 

county level substance abuse 

prevalence/mental health status 

2000 median home value from US 

Census* 

Socio-economic status 

 Poverty rates 

Percentage of persons in correctional or 

juvenile institutions from Area Resource 

file (calculated)* 

Per capita incarceration rate for drug 

offense 

 Substance abuse related arrests per 

capita/1,000 

 Drunk & impaired driving arrests 

Area Resource File (calculated from past 

3 years and population size) 

Suicide rate 

 Overdose death Rates (Partial correlation) local EMS 

data (response calls, ODs) 

 Child Abuse and Neglect reports 

 Drug related Child Protective Services 

interventions/ Social Service 

investigations 

 Birth Certificate data on maternal 

smoking and substance abuse 

 Prescription rates of abused drugs 

 Service utilization rates for Substance 

Abuse /Mental Health treatment 

 Mortality from alcohol or drug related 

causes 

 Accident rates from AOD related causes 

 Substance abuse screening tests 

conducted by schools and employers 

 Behavioral Risk Factor Survey 

Alcohol abuse or dependence in past year 

from 2002-2004 National Survey on Drug 

Use and Health (pooled) 

 

Abuse or dependence of any illicit drugs 

in past year from 2002-2004 National 

Survey on Drug Use and Health(pooled) 

 

Non-prescription use of pain killers in 

past year from 2002-2004 National 

Survey on Drug Use and Health(pooled) 

 

Percentage of persons having serious 

psychological distress problems in past 

year from 2002-2004 National Survey on 

Drug Use and Health (pooled) 

 
210 

Table 7.4. Gaps In Available Data For Planning At the Local Level 

NORC** DATA 

SOURCES Used for Preparation of County 

Profiles and as measure of high/low 

substance abuse prevalence/mental health 

status in Appalachian counties 

CASAP* DELPHI PROCESS DATA 

SETS suggested as measures of high/low 

substance abuse prevalence/mental health 

status in Appalachian counties 

COMMUNITY/COUNTY DATA 

(from case studies) as measure of 

county level substance abuse 

prevalence/mental health status 

Percentage of persons in mental health 

hospitals or institutions from Area 

Resource file (calculated) 

 

Index on Health Professional Shortage 

Area status from 2003 codes of HPSA for 

Primary Medical Care and for Mental 

Health from the Area Resource file 

 

 School Surveys: KIPS, PRIDE, 

Search Institute’s 40 

Developmental Assets 

 Community Planning 

Assessments 

 Local Police Reports 

 Anecdotal information from 

teachers, churches, community 

members 

Note: Variables marked with an asterix (*) indicate that the variable used is a proxy for the variable suggested by CASAP 

through the Delphi process. 

Case Study Appendix of Model Programs 

Model programs or best practices demonstrate a technique, activity or methodology that through 

research, experience and replication, reliably provides: 

Effective and desired result(s); 

Ethical and equitable outcome(s); 

Adaptability to similar environments; and 

Opportunities for innovation. 

Through the National Registry of Evidence-based Programs and Practices (NREPP) 

(http://nrepp.samhsa.gov), the Substance Abuse and Mental Health Services Administration 

(SAMHSA) has designated the following programs as effective models to address substance abuse and 

mental health: Too Good for Drugs; Parenting Wisely; Life Skills Training; Protecting Me/Protecting 

You; and Strengthening Families. 

The following are examples of programs being used in the focus group counties: 

KY-ASAP (Agency for Substance Abuse Policy)

KY-ASAP was created in 2000 by the Kentucky General Assembly to promote the reduction of 

alcohol, tobacco and other drug use in Kentucky by working with communities to help them identify 
211 

existing needs and resources. There are currently 72 local ASAP boards that cover 111 of 120 counties 

in the Commonwealth. The local boards consist of stakeholders in each county or multi-county 

jurisdiction. ASAP has become a vital part of substance abuse prevention and treatment efforts in 

many of Kentucky’s communities. http://odcp.ky.gov/kyasap.htm 

Champions for a Drug Free Kentucky – Kentucky Office of Drug Control Policy

Champions for a Drug-Free Kentucky was established in 1986. The Champions coalitions promote the 

prevention of alcohol, tobacco and other drugs along with the reduction of violence in Kentucky 

communities. The Champions program provides assistance for communities desiring to form a 

coalition and provides state oversight and funding opportunities for established coalitions. Ninety-five 

Champions coalitions have been established in 104 counties throughout the state. Champions 

coalitions function as a substance abuse prevention catalyst. The coalitions are comprised of people 

who care about the quality of life in their communities. http://odcp.ky.gov/champions.htm 

 Life Skills 4 Kids

Life Skills 4 Kids from The Million Dollar Machine (MDM) is a comprehensive Life Skills 

Enrichment Program designed to benefit children in grades K-6 with Robot-Taught Assembly 

Programs. The program includes major components that also address the learning objectives of 

Character Education, Health Education and Drug Prevention. http://www.lifeskills4kids.com

BABES

The Beginning Alcohol and Addictions Basic Education Studies (BABES) is a primary prevention 

program designed to teach children how to live a happy, healthy, drug and tobacco free life. Trained 

volunteers using puppets impart information designed to enable children to grasp the importance of 

good decision making skills. This program is designed to help children understand and develop skills 

necessary to cope with unhappy situations, promote self-esteem, define peer pressure and make good 

choices. http://www.aodc.org/BABES.html 

Second Step

Based on more than 15 years of classroom application and the most current academic, social, and 

emotional research, the Second Step curriculum focuses on three essential competencies: empathy, 

impulse control and problem solving, and anger management. The Second Step program teaches 

Elementary students how to deal with emotions, resist impulsive behavior, resolve conflict, solve 

problems and understand the consequences of their actions. Teachers model and reinforce the skills 

taught in the lesson. http://www.cfchildren.org/programs/ssp/overview 

Too Good for Drugs

Too Good For DrugsTM (K–8) is a school-based prevention program designed to reduce risk factors 

and enhance protective factors related to alcohol, tobacco and other drug (ATOD) use among students. 

Too Good For DrugsTM (K-8) has a separate, developmentally-appropriate curriculum for each grade 

level. Each curriculum builds on earlier grade levels with an instructional design to enable students to 

learn and retain skills. http://www.mendezfoundation.org/educationcenter/tgfd/index.htm 
212 

Safe and Drug Free Schools

The Office of Safe and Drug-Free Schools (OSDFS) administers, coordinates, and recommends policy 

for improving quality and excellence of programs and activities that are designed to provide financial 

assistance for drug and violence prevention activities and activities that promote the health and well 

being of students in elementary and secondary schools, and institutions of higher education. 

http://www.ed.gov/about/offices/list/osdfs/index.html 

D.A.R.E.

D.A.R.E. (Drug Abuse Resistance Education) is a collaborative program between local law 

enforcement and local schools to educate students about the personal and social consequences of 

substance abuse and violence. D.A.R.E.'s primary mission is to provide children with the information 

and skills they need to live drug-and-violence-free lives, to equip them with tools to enable children to 

avoid negative influences, and to allow them to focus on their strengths. It seeks to establish positive 

relationships between students and law enforcement, teachers, parents, and other community leaders. 

http://www.dare.com 

Parenting Wisely

Parenting Wisely is a self-administered, interactive, multimedia CD-ROM program that reduces family 

conflict and child behavior problems by improving parenting skills and enhancing family 

communication and mutual support, supervision, and discipline. Parents can use it alone, in a group, or 

with a practitioner. The program targets parents with children 9 to 18 years of age. 

Parenting Wisely, developed at Ohio University, is an alternative or complement to existing family 

interventions. The developer used his knowledge of the Functional Family Therapy model and 

experience with program dissemination to create a program that would reduce or eliminate many of the 

barriers that keep at-risk families from receiving good family interventions. The resulting prototype, an 

interactive computer disk, was field-tested in 11 southern (Appalachia) Ohio counties under an Office 

of Juvenile Justice and Delinquency Prevention Formula Grant. http://www.familyworksinc.com/ 

Protecting Me/Protecting You

Protecting You/Protecting Me® (PY/PM®) is an alcohol use prevention curriculum for children in 

grades 1-5. PY/PM works to reach children before they have fully shaped their attitudes and opinions 

about alcohol use and educates them about their role in preventing it. The curriculum focuses on the 

effects of alcohol on the developing brain during the first 21 years of life. http://www.pypm.org 

Virginia Tobacco Settlement 

Funds from the Virginia Tobacco Settlement Foundation fund programs like All Stars, Al’s Pals, 

Creating Lasting Families, Not On tobacco, Positive Action, Project Alert, Project EX, Project Toward 

No Tobacco Use, Ending Nicotine Dependence, Helping Teens Stop Using Tobacco (TAP), 
213 

Intervening with Teen Tobacco Users (TEG), Know Your Body, Life Skills Training, Project Toward 

No Drug Use, Skills for Adolescence, and Too Good for Drugs. http://www.vtsf.org 

Virginia National Guard Drug Demand Reduction Program (DDRP)

The Virginia National Guard supports coordinated community education and prevention programs and 

works with at-risk youth to develop values, skills and self discipline. 

http://vko.va.ngb.army.mil/VirginiaGuard

Drug Coalitions

Operation UNITE

Launched in April 2003 by Fifth District Congressman Harold “Hal” Rogers, Operation UNITE serves 

29 counties in southern and eastern Kentucky. It is divided into five coalition service regions. Every 

county has at least one UNITE coalition and conducts its own program activities. Morgan and Wayne 

Counties each have a volunteer coalition. Operation UNITE’s mission is to rid communities of illegal 

drug use through undercover narcotics investigations and the coordination of treatment for substance 

abusers; the goal is to provide support to families and friends of substance abusers and public 

education about the dangers of drug use. UNITE educates and activates individuals by developing and 

empowering community coalitions to refuse to accept or tolerate drug culture. 

Wayne County Operation UNITE: Sponsors Neighbors UNITED, a community watch activity; 

Celebrate Recovery, a faith-based support program; Hooked on Fishing Not on Drugs and Kid’s 

Fishing Derby (http://www.futurefisherman.org ), a copyrighted program of the Future Fisherman 

Organization; three school anti-drug clubs; Red Ribbon Week at the schools; a Back-to-School Bash 

fair; the safe and drug-free graduation bowling activity; safe Halloween activities; and a Christmas 

parade. 

Morgan County UNITE: Sponsors six school anti-drug clubs; Hooked on Fishing; various speakers; 

joint activities with other community groups and schools and the Kentucky Drug Endangered Children 

network; EMT training about drugs; neighborhood watch training; Red Ribbon Week activities; and 

safe Halloween activities. Morgan County UNITE also helps to fund a local adult circuit drug court. 

http://www.operationunite.org 

Bland County (VA) CADDY: Organized in 2006 with help from a matching grant from the 

Appalachian Regional Commission as a result of participation in a regional Appalachian substance 

abuse conference, Operation CADDY (Coalition Against Drugs Destroying Youth) in Bland County 

(VA) seeks to increase the knowledge of community leaders about the importance of providing 

positive alternatives and protective factors for youth, young adults and their families and effective 

implementation of comprehensive prevention programs. 

Hardy County (WV) Prevention Partnership: A function of the West Virginia Prevention Resource 

Center Office community development initiative, the partnership counts over 50 stakeholders from 

education, medicine, law enforcement, county extension offices, the media, mental and behavioral 

treatment, churches, and government as members. 
214 

Monroe County (WV) Prevention Coalition: A community wide partnership dedicated to reducing 

substance abuse, underage use, and associated risky behaviors through effective prevention strategies 

that include: policy setting; education; communication; programming; mentoring; and role modeling. 

Community Services 

ASAP programs

Alcohol and Substance Abuse Prevention (ASAP), a workplace substance abuse and prevention 

program available in Kentucky and Virginia, was developed to implement and maintain programs 

which aim to reduce the incidence of drug and alcohol abuse in the workplace and deter drug and 

alcohol use. http://www.asap-programs.com

County Extension Services

State county extension services with offices in each U.S. county function as agencies within the U.S. 

Department of Agriculture through state land grant colleges. Children and families at risk for negative 

outcomes such as infant mortality, malnourishment, child abuse and neglect, poor health, substance 

abuse, teenage pregnancy, crime, violence, and academic underachievement are served by these 

agencies. 4-H clubs and activities are youth organizations administered by the Cooperative Extension 

System with the mission of "engaging youth to reach their fullest potential while advancing the field of 

youth development." 

While all counties in the study have active cooperative extension services, Hardy County (WV) 

cooperative extension co-sponsors a Health Choices camp for elementary and middle school youth 

during the school day, in conjunction with school staff, that reinforces healthy behaviors including 

alcohol, substance use and tobacco prevention activities. http://www.csrees.usda.gov/Extension 

Alcoholics Anonymous (AA)

Alcoholics Anonymous® groups are locally organized and based on a fellowship of men and women 

who share experiences to support each other to solve common problems and help others recover from 

alcoholism. Bath, Bland, Hardy, Monroe, and Wayne counties all have active AA meetings. Narcotics 

Anonymous is a similarly organized community-based association of recovering drug addicts. Only 

Wayne County (KY) has meetings of Narcotics Anonymous. 

http://www.alcoholics-anonymous.org 

County Profiles 

The county profiles used during the site visits are included as Appendix D at the end of this report.
215 

CHAPTER 8: Conclusions 

As the first effort to explore substance abuse and mental health issues and access to treatment 

services within Appalachia, and between Appalachia and the rest of the United States, this report 

augments the scant body of literature in these areas. In doing so, we hope to inform the direction of 

substance abuse and mental health research and policy in Appalachia, and provide information to 

better allocate and target resources to eliminate substance use and mental health disparities within 

the region. Analyses included in this report explore patterns across Appalachian sub-regions, across 

levels of economic development within the region, within Appalachian coal-mining areas, and 

between Appalachia and the rest of the United States. 

Overall Conclusions 

This study provides an in-depth synthesis of the available data on substance abuse and mental health 

disorders, and access to treatment services, in Appalachia. There are several findings worthy of 

emphasis given their consistency across the Appalachian region, and across data sets. The 

consistency of these findings suggests possible areas of focus for targeting region-wide resources to 

eliminate Appalachian mental health and substance use disparities. Findings demonstrate that: 

Mental health is a key area of concern in Appalachia. Independent from substance abuse, mental 

health diagnoses for serious psychological distress and major depressive disorder are 

proportionately higher in Appalachia than in the rest of the nation. This is an important finding in 

that it suggests that Appalachian disparities in mental health status do not appear to arise as a result 

of higher levels of co-occurrence with substance abuse. Consistent with this finding, hospital 

discharge data show that Appalachian residents have a lower proportion of diagnoses for substance 

abuse only, and for co-occurring substance abuse and mental health problems, as compared to the 

rest of the nation. 

It is important to note, however, that findings from the case studies and from discussions with 

members of the Coalition on Appalachian Substance Abuse Policy (CASAP) suggest that medical 

care system factors related to reimbursement could encourage under-reporting of comorbidity rates 

within the region. While this study has not identified any evidence that suggests that underreporting happens more often in Appalachia than in other regions, future work should explore this 

issue. Specifically, studies should investigate whether any systematic bias exists in the way mental 

health and substance abuse coverage and payment is managed within the Appalachian Region. 

While alcohol is the predominant substance of abuse both nationally and within Appalachia, use 

patterns differ. Proportionately fewer Appalachian adults used alcohol in the past year, as 

compared to adults nationally. Among those who did use alcohol, proportionately fewer 

Appalachian adults reported binge alcohol use and heavy alcohol use in the past year as compared 

to adults nationally. Among adolescents, however, heavy alcohol use was a greater problem within 

Appalachia than outside of Appalachia. For Appalachian coal mining areas, the proportion of 

people entering treatment for alcohol abuse is lower than in other areas of Appalachia. 

Methamphetamine is not as large of a problem within Appalachia as is widely believed. Findings 

do not support that methamphetamine use is higher in Appalachia than elsewhere in the nation. 
216 

Rather, methamphetamine use and admission rates are demonstrably lower across Appalachia. 

While regional trends show that methamphetamine use is rising, the rate of increase is similar to 

that of the rest of the nation. While there are likely to be “pockets of abuse” within the region, 

rates are lower within the region as a whole. 

The growing proportion of admissions for primary abuse of other opiates and synthetics is a key 

issue in Appalachia. Admission rates for the primary abuse of other opiates and synthetics26 are 

higher in Appalachia than in the rest of the nation. Further, while rates are rising both across the 

nation and in Appalachia, the rate of increase in Appalachia is greater. This is particularly the case 

in Appalachian coal mining areas. 

In many ways, access to treatment is better in Appalachia when compared to the rest of the 

nation. In terms of accepted forms of payment, and availability of substance abuse family 

counseling and mental health assessment upon admission, we see that access to treatment is better 

in Appalachia when compared to the rest of the U.S. Overall, proportionately more adults in the 

Appalachian region with mental health problems received outpatient mental health treatment 

counseling services and prescription medical services in the past year, as compared to adults outside 

the Appalachian region. There is no significant difference between Appalachian adolescents and 

adults and adolescents and adults outside of the region in terms of the proportion of persons who 

need but do not receive treatment for an illicit drug problem. 

Outpatient rehabilitation is the most common setting for substance abuse treatment in 

Appalachia. Access to inpatient treatment, and short and long-term non-hospital residential 

treatment for substance abuse or mental health illnesses, is less common within the Appalachian 

region. Findings from the national household survey indicate that outpatient rehabilitation is the 

most common setting for substance abuse treatment in Appalachia. Of the people over age 18 who 

received substance abuse treatment at a specialty facility in the past year, proportionately fewer 

people in Appalachia received treatment at an inpatient rehabilitation facility than people outside of 

Appalachia. At the same time, utilization rates of hospital inpatient services, the private doctor’s 

office, and emergency room services are all higher in the Appalachian region than outside of the 

Appalachian region. One interpretation of this finding is that people who have severe substance 

abuse problems have not received appropriate outpatient treatment or regular inpatient services, and 

as a result, use more expensive emergency room services. The case study counties also reported 

having access to outpatient treatment, but difficulties in getting access to inpatient and long-term 

residential treatment facilities. In fact, no case study county had inpatient facilities for either 

substance abuse or mental health and most reported difficulty placing those needing long term 

outpatient treatment. Results from the survey of substance abuse treatment facilities indicate that 

significantly fewer Appalachian facilities offer short term and long-term non-hospital residential 

substance abuse treatment when compared to facilities outside the Appalachian region. 

Barriers to treatment for substance abuse and mental illnesses exist within the Appalachian 

region, including transportation issues, cultural factors, and stigma. The case studies revealed a 

number of specific barriers to accessing treatment for substance abuse and mental health illnesses, 

including: stigma; transportation availability; limited payment options; privacy issues; choice of 

facilities; and cultural and family barriers. 

 

26 These drugs include codeine, hydrocodone, hydromorphone, meperidine, morphine, opium, oxycodone, pentazocine, 

propoxyphene, tramadol, and any other drug with morphine-like effects except methadone. 
217 

Better data are needed at the local level to inform policy and allocate resources to more 

effectively address substance abuse and mental health problems in the Appalachian region. 

Findings from the case studies showed that community-level substance abuse treatment and mental 

health leaders do not have uniformly available county and state data from which to draw 

conclusions about the magnitude of substance abuse and mental health issues within their 

communities. Additionally, they do not generally use nationally-available data sets to make 

decisions about local response to substance abuse and mental health issues. While they may use 

state data, especially when it supports applications for grant funding for prevention programs, more 

often than not, anecdotal evidence is most often used as the basis for informing local decision 

making. These findings do not suggest a disregard for the data, but rather the lack of utility in how 

data are presented and a disconnect between the levels of analysis (generally state or regional) and 

the level of service delivery (local). Improved data collection at the national, state and local levels, 

including larger sample sizes, may lead to more informed community-level decision making with 

respect to resource allocation and program development. 

Taken together, these findings suggest that disparities do exist in the Appalachian region for 

specific substance use and mental health disorders. While some of these disparities exist across the 

Appalachian region, even more can be learned by looking at a more granular level. Specifically, 

findings demonstrate particular disparities related to Appalachian sub-region, county economic 

distress level, and within coal-mining areas. A sampling of these findings is highlighted below: 

Findings Across Appalachian Sub-Regions (Northern; Central; Southern) 

The central Appalachian region had the highest proportion of admissions with other opiates 

or synthetics as the primary reason for admission. 

The highest prevalence of mood disorders occurs in the northern Appalachian sub-region. 

The central sub-region of Appalachia has the greatest density of admissions for psychiatric 

problems – both substance-related and non-substance-related. 

Non-medical use of prescription drugs among adolescents is higher in the central and 

southern sub-regions of Appalachia, as compared to the northern sub-region. 

Findings Across Economic Status Levels (Attainment; Competitive; Transitional; At-Risk; 

Distressed) 

There is a positive relationship between the economic development levels and private 

insurance for both adults and adolescents; distressed and at-risk counties have the lowest 

rates of private insurance, and competitive and attainment counties have the highest rates of 

private insurance. 

Medicare and Medicaid/CHIP payments are highest in at-risk and distressed counties and 

lowest in competitive and attainment counties. 

Competitive and attainment counties have the lowest rates of non-medical use of 

prescription drugs among adolescents, followed by transitional counties and distressed and 

at-risk counties. 
218 

Patients in the Appalachian region are more likely to be admitted through the emergency 

department than patients outside of the Appalachian region. This disparity appears to be 

concentrated in at-risk and transitional counties, as compared to other counties. 

Findings for the Appalachian Coal Mining Region 

Proportionately more females than males were admitted to treatment in coal mining areas 

than in other areas of Appalachia. 

People less than 24 years of age accounted for more admissions in coal mining areas than in 

other areas. 

The percentage of admissions with heroin use and other opiates or synthetics use as the 

primary, secondary or tertiary reason for treatment is significantly higher in coal mining 

areas than in other parts of the Appalachian region. 

Other illicit drug use and non-medical use of prescription drugs are also cited more as the 

primary, secondary or tertiary reasons for treatment in coal mining areas than in other areas. 

Implications for Policy Interventions 

Among the notable findings from this study were differences in patterns of substance use and 

mental health status among adolescents as compared to adults. This suggests that targeted 

interventions are needed for the prevention and treatment of both substance abuse and mental health 

concerns. 

Adolescents

While Appalachian adolescents demonstrate similar substance use patterns for cocaine, marijuana, 

and methamphetamine, rates of non-medical use of psychotherapeutics, cigarettes, and heavy 

alcohol use are higher as compared to adolescents across the United States. Non-medical use of 

psychotherapeutics is a problem for adolescents nationwide, with rates exceeding those of adults. 

Rates for Appalachian adolescents are even higher. Similarly, for adolescents, rates of heavy 

alcohol use were higher in Appalachia than outside of Appalachia. 

The picture of substance use and mental health concerns among Appalachian adolescents becomes 

even clearer when analyses are conducted by county economic status level, suggesting that 

economic status plays a key role in mental health and substance abuse issues. Findings demonstrate 

that adolescents in distressed and at-risk Appalachian counties – compared to adolescents in other 

Appalachian counties – have the highest rate of non-medical use of psychotherapeutics. Cigarette 

and alcohol use are also key concerns for adolescents in Appalachia. Proportionately more 

adolescents reported heavy alcohol use inside Appalachia than outside of Appalachia. Similarly, 

proportionately more adolescents used cigarettes in Appalachia than outside of Appalachia; usage 

was higher for lifetime use, past year use, and past-month use. 

On the positive side, proportionately more treatment facilities in Appalachia offer substance abuse 

family counseling than in facilities outside of Appalachia. This suggests a regional understanding of 

the need for treatment services for adolescents and their families. While adolescents in at-risk and 
219 

distressed counties have the lowest rate of private health insurance, we see that across Appalachia, 

more adolescents have Medicaid/ CHIP coverage than adolescents in other areas of the country. 

Several federally-commissioned nationwide efforts are underway to explore substance use and 

mental health challenges facing adolescents, and to raise awareness about mental health, and 

alcohol and drug abuse.27 Such efforts are needed, and should be expanded/targeted toward at-risk 

and distressed areas in Appalachia. Both quantitative and qualitative findings from this study 

suggest that preventive measures are needed to address substance abuse and mental health issues 

among Appalachian adolescents. While treatment is important, there is a clear need for an 

“upstream” approach focused on prevention. Given that our case study findings suggest that 

problems often arise due to issues such as boredom and lack of hope, community interventions may 

appropriately focus on school/after-school settings. 

This is not to say that medical treatment is unimportant, however. Given the magnitude of many of 

the problems seen among Appalachian adolescents, treatment is clearly needed. While many 

Appalachian facilities do treat adolescents, there still remain cost/insurance barriers that need to be 

addressed. It is essential that policymakers and community leaders consider both treatment and 

prevention measures as they craft interventions to reduce the burden of substance use and mental 

health concerns among Appalachian adolescents. 

Many Appalachian communities are clearly doing their part in working to prevent drug use and 

promote mental health. Case study communities report active school-based prevention activities, 

after-school youth activities, anti-drug coalition activities, mentoring programs, wellness classes, 

health camps, mentoring programs, sports, and recreational activities. Community representatives 

from the case study counties have described the utility of and growing demand for programs such as 

Beginning Alcohol and Addictions Basic Education Studies (BABES), Too Good For DrugsTM (K–

8), D.A.R.E. (Drug Abuse Resistance Education), LifeSkills4Kids, and others. Future work should 

explore the effectiveness of community-based prevention programs in Appalachia. 

Adults 

Whereas substance abuse issues are of primary concern among Appalachian adolescents, overall 

substance abuse rates among Appalachian adults are proportionately lower as compared to adults 

nationally. This is true across substances, including alcohol, non-medical use of 

psychotherapeutics, marijuana, methamphetamine, and cocaine. While substance use rates are 

lower, however, we see proportionately higher rates of serious psychological distress and major 

depressive episodes as compared to adults nationally, suggesting that mental health concerns may 

be of primary interest when targeting efforts towards Appalachian adults. Importantly, these mental 

health concerns occur independent from substance use, rather than as a result of co-occurring 

disorders. 

A look at hospital discharge data shows specific mental health conditions that appear more 

prevalent within the Appalachian region, with significantly more Appalachian adults having 

diagnoses of: anxiety disorders; delirium, dementia, and amnesic and other cognitive disorders; 

developmental disorders (includes communication disorders, developmental disabilities, intellectual 

 

27 http://www.helpingamericasyouth.gov/conf-tsu.cfm 
220 

disabilities, learning disorders, and motor skill disorders); impulse control disorders; and personality 

disorders. 

In looking at treatment, an important finding is that Appalachian adults are more likely to access 

treatment through the emergency room, especially in distressed and at-risk counties. This suggests 

that Appalachian adults are more likely to seek treatment later, and may be less likely to recognize 

the magnitude of their mental health and substance use issues. This is consistent with findings that 

Appalachian residents are more likely to report stigma, not feeling the need for treatment, and fear 

of commitment, as reasons for not seeking treatment. Similar findings are also reflected in the case 

studies, where community participants reported cultural barriers, stigma, and stoicism as reasons for 

Appalachian residents not seeking treatment. 

Among substances of abuse, alcohol remains the predominant concern among Appalachian adults. 

While overall use rates, heavy use rates and binge drinking rates are all lower as compared to adults 

nationally, alcohol is the mostly widely used and abused substance within the region, and the 

primary reason for Appalachian adults seeking substance abuse treatment. Interestingly, the 

dynamics of substance use and abuse differ within the coal mining region of Appalachia, with 

treatment rates for alcohol use being lower than in other parts of the region. The percentage of 

admissions for heroin use and other opiates or synthetics use as the primary, secondary or tertiary 

reason for treatment is significantly higher in coal mining areas than in other parts of the 

Appalachian region, however. 

As with adolescents, these findings suggest the need for targeted initiatives to address mental health 

and substance abuse issues among Appalachian adults. The nature of these issues differs among 

adolescents and adults, however, with mental health concerns rising as a primary area of concern 

among adults. Perhaps the most critical finding relative to Appalachian adults is the need to focus 

on these mental health concerns, independent from substance abuse, and to develop programs to 

overcome cultural barriers to treatment and issues of stigma that may result in more admissions 

occurring through emergency room settings. 

One caveat to this recommendation is the finding that, within the coal mining region of Appalachia, 

abuse of heroin and other opiates and synthetics appears to be a primary substance abuse concern. 

Targeted prevention and treatment efforts are needed to address these concerns. 

Key Recommendations to Guide Future Policy and Research Efforts 

This study is the first effort to investigate the state of mental health status and substance abuse 

prevalence at the most granular level possible across Appalachia. While our research has provided 

a picture of the state of the region, much remains to be learned about mental health status and 

substance abuse prevalence in Appalachia, and access to treatment services. 

We believe there are any number of recommendations that could be offered to guide future policy 

and research efforts. We offer four key recommendations to stimulate and improve future research 

efforts, and thereby inform mental health and substance abuse policy and community-level 

programs: 
221 

 

Recognizing that interventions take place at the community level, and that substance use and 

mental health patterns differ from community to community, local-level data are clearly needed 

to most appropriately target initiatives and ensure the optimal use of limited resources. While 

our findings are instructive in guiding the allocation of region-wide resources, and targeting 

resources based on factors such as Appalachian sub-region and county economic development 

level, local-level data are needed to inform local interventions. Our case study findings also 

revealed that better coordinated data collection, documentation and analysis are needed for 

Appalachian communities to access resources at state and federal levels. This study serves as a 

call to action to improve primary data collection with representative sampling in and for the 

Appalachian region. Leadership from the federal, regional, and local levels is needed to ensure 

that researchers and practitioners have access to more comprehensive data sets to explore these 

issues across the Appalachian region. 

Studies are needed to determine the quality of services being delivered in Appalachian treatment 

facilities. The data only tell us that a service, such as inpatient detoxification, is offered; we do 

not know about the quality of the service delivered, or whether the service has been received by 

the patient. Thus, our findings cannot speak to the quality of care received in Appalachian 

treatment facilities versus other facilities nationwide. Such studies would answer questions such 

as: 

How do we measure the quality of services delivered across the region? 

Do patients perceive the services they receive to be of a high quality? 

Are there differences in the quality of services being delivered for co-occurring and nonco-occurring disorders? 

We know little about the effectiveness of clinical treatments and community-based prevention 

programs and interventions in Appalachia. Outcome assessments and evaluations of the 

1. Richer data are needed to enable analyses at the county and community levels to fully 

understand the extent of substance abuse and mental health problems in Appalachia. 

2. Studies are needed to determine the quality of substance abuse and mental health 

services being delivered in Appalachian treatment facilities. 

3. Future work should include outcome assessments and other evaluations of the 

effectiveness of clinical and community-based mental health and substance abuse 

interventions in Appalachia. 
222 

effectiveness of mental health and substance abuse interventions in Appalachia are needed. 

Studies are needed to address the following questions: 

Are interventions perceived as effective in treating mental health and substance abuse 

disorders in the region? 

Are community-based interventions effective in preventing illness? 

Are patients placed on waiting lists for certain services? 

What are the clinical outcomes of specific interventions? 

Findings indicate that there are regional difficulties in accessing inpatient treatment services. At 

the same time, the data show that utilization rates of hospital inpatient services, private 

physicians, and emergency room services are all higher in the Appalachian region than outside 

of the Appalachian region. One possible interpretation of these finding is that people who have 

severe substance abuse problems have not received appropriate outpatient treatment and may 

not have access to inpatient services at drug treatment facilities, and as a result, use more 

expensive hospital inpatient and emergency room services. The case study findings were 

consistent with this interpretation, as counties reported difficulties in accessing inpatient 

facilities for either substance abuse or mental health, and difficulties in placing those needing 

long term outpatient treatment. One possible cost effective way to create an inpatient treatment 

infrastructure in the Appalachian region may be to pool resources across counties and develop 

regional inpatient treatment units. 

By providing an in-depth analysis and synthesis of available data on substance abuse and mental 

health disorders, and access to treatment services in Appalachia, we believe this study can be useful 

in targeting region-wide resources to eliminate Appalachian mental health and substance abuse 

disparities. At the same time, however, we recognize that more work needs to be done to promote 

community level analyses. Only then will Appalachian communities have sufficient understanding 

of the nature of the substance use and mental health issues within their communities to address these 

concerns effectively. A major finding of this study is that data collection efforts should be 

strengthened to encourage such granular analyses at the county and community levels. When 

supplemented with studies exploring the quality of services being delivered and the effectiveness of 

both medical and community-based interventions in Appalachia, communities will be fully 

empowered to make effective decisions on resource allocation and develop both prevention and 

treatment initiatives responsive to the unique and complex interplay of socioeconomic, cultural, and 

health system factors in the Appalachian region. 

4. Creative solutions should be explored to address concerns over the lack of available 

inpatient care. 
APPENDIX A: Data Sources 

Source Information Population and 

Contents of 

Investigation 

Characteristics of the Data Comparing Regional Data 

to the U.S. 

CHAPTER 2: 

National Survey on Drug 

Use and Health 

(NSDUH), Substance 

Abuse and Mental Health 

Services Administration 

(SAMHSA) 

Years: 2002 – 2005 

Type of source: Household 

survey data 

Substance use and 

mental disorders 

among civilian, noninstitutionalized 

population of the 

U.S., age 12 or older. 

Number of Appalachian States 

Included: 13 

Number of Appalachian Counties 

Included: 352 

Number of Appalachian Facilities 

Included: N/A 

Sample Size: 217,978 respondents 

Appalachian counties are compared to 

non-Appalachian counties for the 

following variables: demographic 

characteristics; health insurance status; 

lifetime, past year, and past month 

substance use; substance dependence or 

abuse, mental health measures, and 

receipt of substance use treatment; access 

to alcohol treatment; access to drug 

treatment; reasons for not receiving 

substance use treatment; and reasons for 

not receiving mental health treatment. 

CHAPTER 3: 

Treatment Episode Data 

Set (TEDS), Substance 

Abuse and Mental Health 

Services Administration 

(SAMHSA) 

Years: 2000 – 2004 

Type of source: Data from 

treatment facilities 

Location, 

characteristics, and 

utilization of all 

alcohol and drug 

treatment facilities 

and services, both 

public and private, 

throughout the 50 

States, the District of 

Columbia, and other 

U.S. jurisdictions. 

Number of Appalachian States 

Included: 12 (Excludes WV)

Number of Appalachian Counties 

Included: 195 

Number of Appalachian Facilities 

Included: N/A 

Sample Size: 511,217 total 

admissions 

Data from Appalachia is compared to 

U.S. data for the primary substance of 

abuse at the time of admission to 

treatment between 2000 and 2004. 

CHAPTER 4: 

Healthcare Cost and 

Utilization Project, 

(HCUP), Nationwide 

Inpatient Sample, Agency 

for Healthcare Research 

and Quality (AHRQ) 

Years: 2004 

Type of source: Discharge 

data from community 

hospitals 

Substance abuse and 

mental disorder 

related clinical and 

resource use 

information available 

from discharge 

abstracts of records 

of hospital stays from 

about 1,000 hospitals 

sampled to 

approximate a 20 

percent stratified 

sample of U.S. 

community hospitals. 

Number of Appalachian States 

Included: 6 (Includes NC, KY, VA, 

WV, NY, MD)

Number of Appalachian Counties 

Included: 45 

Number of Appalachian Hospitals 

Included: 52 

Sample Size: 5,666,341 inpatient 

stays total 

Appalachian counties are compared to 

non-Appalachian counties for the 

following variables: demographic 

characteristics across economic 

development status level; hospital stay 

characteristics; presence of MHSA; 

subtype of MHSA stays; comorbidity 

status; diagnoses contain alcohol use 

disorder; diagnoses contain mental health 

disorder; principal reason for 

hospitalization was alcohol use; principal 

reason for hospitalization was drug use; 

and types of SAMH diagnoses for 

adolescents and adults. 

CHAPTER 5: 

National Survey of 

Substance Abuse 

Treatment Services (NSSATS), Substance Abuse 

and Mental Health Services 

Administration 

(SAMHSA) 

Demographic and 

substance abuse 

characteristics of 

annual admissions to 

treatment for abuse 

of alcohol and drugs 

in facilities that 

report to individual 

State administrative 

data systems. 

Number of Appalachian States 

Included: 13 

Number of Appalachian Counties 

Included: 318 

Number of Appalachian Facilities 

Included: 891 

Appalachian counties are compared to 

non-Appalachian counties for the 

following variables: Ownership of 

substance abuse treatment facilities; 

characteristics of substance abuse 

treatment facilities (accredited by 

Commission on Accreditation of 

Rehabilitation Facilities, licensed/ 

certified by public health department, 

arrangements/ contracts with managed 
224 

Source Information Population and 

Contents of 

Investigation 

Characteristics of the Data Comparing Regional Data 

to the U.S. 

Years: 2005 

Type of source: Data on 

admissions to substance 

abuse treatment services 

Sample Size: 13,367 substance 

abuse treatment facilities 

care organizations, receives public 

funds); services offered at substance 

abuse treatment cacilities, facilities 

offering inpatient detoxification services; 

primary focus of substance abuse 

facilities; facilities accepting adolescents; 

facilities using a sliding fee scale; 

facilities offering free or no charge 

treatment; facilities that accept Medicare; 

facilities that accept Medicaid; facilities 

that accept state financed health 

insurance; and facilities that accept 

private health insurance. 

CHAPTER 6: 

Coal Mining Data from 

HCUP and TEDS 

Years: 2004, 2005 

Type of source: Data from 

HCUP and TEDS, see 

above

See above in HCUP 

and TEDS. 

HCUP

Number of Appalachian Counties 

Included: 45 (25 coal mining, 20 

non-coal mining)

Sample Size: 167,957 total 

hospital admissions (76,083 

admissions from coal mining 

Appalachian counties; 91,874 

from non-coal mining 

Appalachian counties)

TEDS

Number of Appalachian Counties 

Included: (86 coal mining)

Sample Size: 511,317 total 

hospital admissions (211,380 

admissions from coal mining 

Appalachian counties; 299,837 

from non-coal mining 

Appalachian counties)

No comparisons are made between the 

Appalachian region and the U.S., as this 

was not the scope of this chapter. Rather, 

we compare coal-producing Appalachian 

counties to non-coal producing 

Appalachian counties for the following 

variables: heroin use as primary, 

secondary, or tertiary reason for 

treatment; other opiates or synthetics use 

as primary, secondary, or tertiary reason 

for treatment; characteristics of hospital 

stays; characteristics of admissions to 

substance abuse specialty treatment; 

treatment-related characteristics of 

admissions to substance abuse treatment; 

and substance abuse characteristics of 

admissions to substance abuse treatment. 

CHAPTER 7: 

Case Studies with 

Twinned Appalachian 

Counties

Six counties were 

selected using a 

‘socioeconomic 

twinning’ 

methodology, and 

community 

stakeholders 

participated in 

discussions about 

perceptions of mental 

health and substance 

abuse issues in their 

communities. 

Number of Appalachian Counties 

Included: 6 

Number of Appalachian States 

Included: 3 

While this chapter was qualitative in 

nature, NORC produced county profiles 

of substance abuse and mental health 

characteristics that compared countylevel data for six Appalachian counties in 

three states to state-level data. 
225 

APPENDIX B: Literature Review of the Prevalence of Substance Abuse 

and Mental Health Disorders, Access to Treatment Services, and 

Disparities in Appalachia 

Introduction 

In Appendix B, we provide a review of the literature related to substance abuse and mental health 

disorders in Appalachia, access to treatment services, and related disparities in Appalachia. When 

Appalachia-specific literature has not been available, we have referenced literature on rural 

substance abuse and mental health disparities as a proxy for Appalachia. 

Methods 

In order to obtain the most relevant articles for this review, we conducted extensive searches using 

PubMed, Sociological Abstracts, Lexis/Nexis and Google Scholar. We also used articles cited in 

relevant journals as sources of information and drew upon reports commissioned by government 

agencies such as ARC and SAMHSA. Finally, we obtained recommended literature sources from 

experts in Appalachian research, rural research, and mental health and substance abuse research. A 

special focus was placed on articles with an Appalachia-wide focus, articles with county-level data 

obtained from nationally-representative datasets, and articles that offered potential solutions for 

reducing mental health and substance abuse disparities. 

We have organized our findings using Kilbourne et al’s conceptual framework for advancing health 

disparities research (Kilbourne et al, 2006). Using an epidemiological framework, Kilbourne et al 

divided disparities research into three phases: detection (defining disparities and identifying 

vulnerable populations), understanding (identifying the causes and contributing factors of 

disparities), and reducing disparities (identifying successful interventions and policies which lead 

to a reduction in disparities). 

DETECTION 

Overall Prevalence of Substance Abuse and Mental Health Disorders 

Though substance abuse is often assumed to be an urban problem, data have consistently shown no 

significant difference in rates of mental health disorders and drug and alcohol abuse between rural 

and non-rural areas (Hartley, Bird and Dempsey 1999, Robertson and Donnermeyer 1998, 

Leuekefeld et al 2002). These findings have also been supported by large national surveys: data 

from the 2004 National Survey on Drug Use and Health found that 8.2% of those living in nonmetropolitan areas met criteria for past year alcohol and/or drug abuse, compared to 9.6% in 

metropolitan areas (SAMHSA Office of Applied Studies, 2005) and the 1991 Comorbidity Survey 

found no statistical difference in the prevalence of mental health or substance use disorders between 

urban and rural residents (Simmons and Havens 2006). 

Differences in prevalence do exist based on type of substance used, however. For example, many 

states in the Appalachian region have smoking rates that are higher than the national average 

(Doescher et al 2006) and women in West Virginia were found to have the highest rate of pre-natal 
226 

smoking (Song and Fish 2006). OxyContin® has been mentioned frequently in the media as a major 

problem in Appalachia and rural areas, and the data, while scant, support that contention. 

Leukenfeld et al (2005) explored prescription drug use, health services utilization, and health 

problems in rural Appalachian Kentucky. As part of a larger project designed to examine the 

effectiveness of two HIV/AIDS risk reduction interventions, Leukenfeld et al studied 295 subjects 

on felony probation from one of 30 Appalachian counties in Eastern Kentucky. Subjects were 

divided into two groups: those who had ever used OxyContin and those who had never used 

OxyContin. Findings suggested statistical differences between the OxyContin-using and non-using 

subjects. OxyContin users reported greater use of other substances and more emergency room 

treatments for drug overdose more often than the non-users. Additionally, OxyContin users sought 

detoxification and self-help more often than the non-users.

In addition, research conducted by the Maine Rural Health Research Center has demonstrated that 

2.8% of young adults in the smallest rural areas use OxyContin® as compared to 1.7% of urban 

young adults, and similarly that young adults in the smallest rural areas report methamphetamine 

use at nearly twice the rate of urban young adults (2.9% vs. 1.5%). Differences for both OxyContin 

and methamphetamine, while appearing small, were in fact statistically significant (Maine Rural 

Health Research Center, June 2007). 

Findings from the Maine Rural Health Research Center also noted that while OxyContin and 

methamphetamine rates were higher in small rural areas, the rates of alcohol abuse were particularly 

striking. Children aged 12-17 from the smallest rural areas are more likely to have used alcohol, 

engaged in binge drinking (defined as having 5 or more drinks on a single occasion), heavy drinking 

(defined as binge drinking on 5 or more occasions within a month) and driving under the influence 

(DUI) than urban children. Among young adults, the highest rates of binge drinking, heavy 

drinking, and DUI are seen in larger, non-adjacent rural areas. Findings demonstrated that fortyeight percent of young adults in larger rural areas have engaged in binge drinking in the past month 

(Maine Rural Health Research Center, 2007). 

Though there are many nationally representative surveys that provide insight into the prevalence of 

mental health and substance use disorders in Appalachia and rural areas, it is important to 

understand the limitations of these data. Hartley et al (2002) suggest that survey data based on self 

report may represent an underestimation of true mental health and substance use disorder 

prevalence. For example, rural areas have higher suicide rates which may be indicative of greater 

unreported prevalence of depressive disorders. Furthermore, hospital based data may under-report 

drug and alcohol related injury due to the restrictions of laws that allow insurers to refuse payment 

for services rendered due to drug or alcohol use. Prescription drug data may also be problematic. 

For example, Anglin and White’s 1999 study of prescription drug problems in Eastern Kentucky 

describe a scenario where Eastern Kentucky clinics were chastised for seemingly over prescribing 

Tylenol Three (a specific dosage of Tylenol with Codeine), when in reality, they had a majority of 

patients who were insured through Medicaid and Tylenol Three was the only pain medicine on the 

formulary. It appeared that they were over-prescribing this medication, but in fact, they were underprescribing the wider variety of painkillers. 

Disparities in Treatment Utilization and Access 

Kilbourne et al define disparities as “observed clinically and statistically significant differences in 

health outcomes or health care use between socially distinct vulnerable and less vulnerable 
227 

populations that are not explained by the effect of selection bias.” The authors identify vulnerable 

populations as people who face physical, psychological and/or social health risks because of 

“differences in underlying social status” due to multiple factors such as race/ethnicity, gender, rural 

residence and Appalachian residence. Rurality is likely a key factor driving disparities in treatment 

access and utilization for Appalachian residents, and race/ethnicity may also play a role in driving 

disparities within certain Appalachian sub-regions. 

Several studies have found that compared to urban residents, rural individuals are less likely to 

utilize drug and alcohol treatment (Warner and Leukefeld 2001, Simmons and Havens 2006). This 

is likely at least partially attributable to the availability of specialty mental health treatment and 

substance abuse treatment, which has been shown to be significantly lower in rural areas (Hartley et 

al 1999, SAMHSA 2003). Further, Fortnay et al found that increased travel time, a common rural 

concern, was associated with poor treatment compliance and health outcomes regarding chronic 

conditions (Fortnay et al 1999). However, distance from treatment services may be a less important 

factor than access to a car for personal use or having a friend or relative willing to provide 

transportation (Arcury et al 2005). 

Disparities in treatment utilization may be higher among nonwhite Appalachian residents. The 

Great Smoky Mountains Study, which compared white and Native American Appalachian youth in 

Western North Carolina, found similar opportunities to access treatment among white and Native 

American children, but that Native American children utilized fewer services (Costello et al 1997). 

They also found that Native American children had higher rates of substance abuse and co-morbid 

substance abuse and mental health disorders. Another study, based on the Great Smoky Mountains 

study, compared white children with African-American children (Angold et al 2002), finding that 

despite similar prevalence of mental health and substance use disorders and no difference in ability 

to access treatment, African-American youth had lower usage of specialty mental health services. 

UNDERSTANDING 

The Relationship Between Rural Residence and Disparities in Treatment Access in 

Appalachia 

We have described above that despite having similar prevalence of mental health and substance use 

disorders, rural residents experience disparities in treatment utilization and access. Socioeconomic 

conditions as well as cultural factors serve as barriers to treatment utilization in Appalachia. Factors 

relating to the health care system also contribute to the problems of substance abuse and lack of 

treatment. 

It is impossible to discuss disparities in Appalachia without a discussion of socioeconomic 

conditions. Economic decline based on struggles in the mining and farming industries have resulted 

in out-migration and dismantling of kinship networks (Goodrum et al 2004). Recently, researchers 

have drawn comparisons between these rural areas and highly distressed urban ghettos, describing 

their similar problems of economic deprivation, lack of opportunity, social isolation and 

disintegrating kinship networks (Schoenberger et al 2006). 

Cultural factors also contribute to the disparities in treatment utilization and access among rural and 

Appalachian people. Multiple authors have cited the rural values of individualism and self reliance 

as a barrier to treatment utilization (Leukefeld et al 2002, Schoenberger et al 2006). For example, 
228 

Warner and Leukefeld’s study of rural-urban differences in substance abuse treatment utilization 

among prisoners in Kentucky found that the most common reason that rural prisoners did not seek 

substance abuse treatment was because they did not think they had a problem. This was the key 

determinant of lower rates of treatment utilization among rural prisoners, even though rural 

prisoners indicated higher rates of substance use than urban prisoners. Data from the Treatment 

Episode Data Set (TEDS) found that people in rural treatment centers were more likely to have been 

referred to treatment through the criminal justice system than people in urban treatment centers 

(SAMHSA, 2005), indicating that those attending rural treatment centers may have not recognized 

that they had a substance abuse problem. High rates of co-morbid substance abuse and mental 

health disorders can also be explained by the problem of lack of recognition of a need for treatment. 

Simmons and Havens have suggested that these high rates of co-morbid conditions are caused by 

people with mental health disorders not knowing to seek treatment for their mental health 

conditions, and instead, medicating with drugs and alcohol. 

Lack of adequate insurance and other health care system issues also contribute to both the 

prevalence of substance use disorders and access/utilization. Anglin and White’s study of an 

Eastern Kentucky community clinic serving a distressed uninsured and under-insured Appalachian 

area identified various problems with prescription drug misuse. They found that due to financial 

constraints, informal networks of prescription sharing develop, causing prescription misuse. This 

misuse is not due to patients wanting to abuse drugs, but because patients are unable to afford 

appropriate supplies of their medications and have to pool their resources within their communities. 

They also state that some who become reliant on pain medication did so because they were unable 

to afford treatment for the chronic condition causing their pain. Havens et al (2006) found that the 

highest rates of OxyContin® prescribing among Kentucky Medicaid recipients occurred in the 

ARC-designated distressed Appalachian counties as opposed to non-Appalachian counties and nondistressed Appalachian counties and called for further research into the cause of this overprescribing. 

Clearly, disparities in treatment access and utilization in Appalachia result from a complex interplay 

of rurality, socioeconomic, cultural, and health system factors. 

REDUCING DISPARITIES 

Key strategies for reducing disparities are education (both geared towards prevention and treatment 

options), improved surveillance tools, criminal justice system issues (treatment in prison, drug 

courts) and heath system issues (culturally-competent healthcare delivery and increased staffing in 

rural areas). The literature related to substance abuse and mental health disparities in Appalachia 

suggests several methods to reduce disparities related to prevalence and treatment. 

Education is a critical method for overcoming disparities in both prevalence and treatment access. 

Leukefeld et al found that rural substance abusers in a Kentucky prison had a much later onset of 

drug and alcohol use than urban prisoners. This indicates that there is a greater window of 

opportunity for rural young people and that preventive efforts may be a good option for 

Appalachian youth. This becomes especially critical because rates of methamphetamine and 

OxyContin® use are higher among rural youth, as described above. Educating both providers and 

consumers regarding signs of a substance abuse or mental health disorder is also critical because of 

the lack of recognition of having a substance abuse problem described above. Community-level 
229 

education about the benefits of treatment would provide a great benefit in rural and Appalachian 

areas. Mental health-related education may also be helpful for African-American and Native 

American parents due to the lower rates of mental health services utilization among AfricanAmerican and Native American children with mental health disorders. 

Improved surveillance systems are also needed to allow policymakers and stakeholders to better 

understand of the impact of substance abuse in Appalachia. Cicero et al describe a surveillance 

system set up to detect high rates of OxyContin® and other prescription drug diversion. Using a 

network of key informants, the authors developed a surveillance system to show when an area is 

having an increased problem, allowing stakeholders to know when a particular diverted drug is 

becoming a problem in their community. Leukefeld et al used a unique method to improve 

estimation of drug injection prevalence in rural Kentucky (2002) which also provided insight 

regarding the numbers of injection drug users who are not in treatment. This type of data will allow 

state and local governments to more effectively allocate resources and address disparities. 

A best practice to reduce the impact of substance abuse (and especially methamphetamine abuse) in 

Appalachia may be the use of drug courts. This recommendation was generated through a meeting 

of Appalachian stakeholders organized by East Tennessee State University in 2005. The potential 

benefits of this strategy can be seen based on the TEDS data described above, which found that 

people in rural treatment centers were more likely in treatment as a result of a court order. Other 

authors (Kubiak et al 2006, Mateyoke-Schrivner et al 2004, Warner and Leukefeld 2001) found the 

usage of drug courts and/or treatment within prisons and jails to be a key opportunity for reducing 

disparities in treatment utilization among rural and Appalachian substance abusers. Given that a 

lack of recognition of a substance abuse problem is a key barrier to treatment entry, drug courts and 

prison/jail in-house treatment offer a unique opportunity to ensure treatment access for a population 

that is hard to identify and unlikely to self-select into treatment. 

Finally, the health care system also can provide opportunities to address substance use and mental 

health disparities in the Appalachian region. Rural areas have fewer available treatment facilities 

and those that do exist are often understaffed. Mental health staff in rural health centers can access a 

large number of vulnerable patients and are essential to improving access to mental health services 

(Van Hook and Ford 1998). Telemedicine and self help groups may also reduce these disparities, 

although transportation may be a problem in accessing self-help groups in rural areas (Ralph in 

Hartley, 1999). 

Health care providers in Appalachia, especially when providing information about sensitive topics 

such as mental health and substance abuse, should be trained in effective communication and 

culturally competent healthcare delivery (Behringer and Friedell 2006, Anglin and White 1999). 

Clinicians who are able to gain the trust of patients can be more effective in increasing awareness of 

these issues. Furthermore, clinicians who are more familiar with Appalachian cultural norms will be 

better equipped to understand their patient’s struggles. Anglin and White also call for greater 

oversight regarding written prescriptions of commonly diverted drugs so that providers who are 

over prescribing for financial benefit are identified, a key issue in areas with high rates of 

prescription drug diversion. 
230 

WHAT HAVE WE LEARNED? 

Much remains to be learned about mental health status and substance abuse prevalence in 

Appalachia. Studies have found that substance use is higher in Appalachia than the rest of the 

nation for certain types of substances. While a body of research has explored mental health status 

in rural communities, few studies have explored mental health status in Appalachian communities 

specifically. Future research should explore geographic and demographic trends across 

Appalachian sub-regions and states, and within Appalachian counties. 

The literature also suggests that disparities in access to and utilization of treatment for substance 

abuse and mental health disorders in Appalachia result from a complex interplay of socioeconomic, 

cultural, and health system factors. Some studies indicate that there is a relationship between rural 

residence and disparities in treatment access in Appalachia, but further research must be done on 

this topic. Research should also investigate the impact of socioeconomic, cultural and health 

system factors on treatment access and utilization at the state and county levels in Appalachia. 

Studies have suggested that race and ethnicity may play a role in driving disparities within certain 

Appalachian sub-regions. Specifically, studies have demonstrated that non-white Appalachian 

residents have lower utilization of treatment services, including specialty mental health services, 

and higher rates of substance abuse and co-morbid substance abuse and mental health disorders. 

Literature has identified various mechanisms to reduce disparities related to treatment access and 

utilization in Appalachia – methods include education, cultural competency training for providers, 

surveillance systems, and changes to the health care system (e.g., more mental health staff in rural 

health centers, health care via telemedicine, and treatment via self help groups). Future research 

should explore the effectiveness of these methods in specific Appalachian communities. 

Overall, research to date does not provide a comprehensive understanding of substance abuse 

prevalence and mental health status, and disparities in access to and utilization of treatment services 

in Appalachia. Moving forward, research should investigate more granular patterns and trends 

related to substance abuse prevalence and mental health status in Appalachia. The identification of 

geographic and demographic patterns within specific sub-regions, counties, and communities will 

enable policy makers to design targeted policy interventions to reduce disparities and improve 

access to treatment services. 
231 

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http://oas.samhsa.gov/HSR/ch2.htm 
235 

APPENDIX C: Results from the 2005 National Survey on Drug Use and 

Health: National Findings 

Note: Estimates are based on combined 2004 – 2005 data. 

Table 2.1A Demographic Characteristics and Health Insurance among Persons Aged 12 or 

Older, by Age Group and Appalachian Region Status: Numbers in Thousands, Annual 

Averages Based on 2002-2005 

Demographic 

Characteristic/Health 

Insurance 

AGE GROUP 

12-17 18 or Older 

Appalachian 

Region1 

Outside 

Appalachia 

Appalachian 

Region1 

Outside 

Appalachia 

HISPANIC ORIGIN 

AND RACE

 

 Not Hispanic or 

 Latino 

1,826 19,099 17,590 170,094 

 White 1,579 13,922 15,851 135,270 

 Black or African 

 American 

212 3,545 1,330 22,629 

 Other2 34 1,632 408 12,195 

 Hispanic or Latino 49 4,106 351 26,025 

EDUCATION 

 < High School N/A N/A 3,653 33,182 

 High School 

 Graduate 

N/A N/A 6,889 61,045 

 Some College N/A N/A 4,090 49,674 

 College Graduate N/A N/A 3,308 52,219 

CURRENT 

EMPLOYMENT 

 Full-Time N/A N/A 9,161 109,116 

 Part-Time N/A N/A 2,144 25,854 

 Unemployed N/A N/A 616 7,047 

 Other3 N/A N/A 6,020 54,103 

HEALTH 

INSURANCE 

 

 Private 1,268 15,771 12,844 140,071 

 Medicare 14 202 3,928 34,575 

 Medicaid/CHIP4 502 5,442 1,607 15,331 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005. 

*Low precision; no estimate reported. 

N/A: Not applicable. 

1 Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. 2 Includes respondents reporting American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, Asian, and Two or 

More Races.

3

 The Other Employment category includes retired persons, disabled persons, homemakers, students, or other persons not in the labor 

force. 

4 CHIP is the Children's Health Insurance Program. Individuals aged 19 or younger are eligible for this plan. 
236 

Table 2.2A Lifetime, Past Year, and Past Month Substance Use among Persons Aged 12 or 

Older, by Substance, Age Group, and Appalachian Region Status: Numbers in Thousands, 

Annual Averages Based on 2002-2005 

Substance AGE GROUP

12-17 18 or Older

Appalachian 

Region1 Outside Appalachia

Appalachian 

Region1 Outside 

Appalachia

MARIJUANA USE 

 Lifetime 355 4,440 6,855 84,818

 Past Year 270 3,402 1,498 20,283

 Past Month 131 1,777 878 11,820

COCAINE USE

 Lifetime 47 581 2,097 31,432

 Past Year 36 409 389 4,913

 Past Month 10 131 139 1,899

METHAMPHETAMINE 

USE

 

 Lifetime 26 296 714 10,656

 Past Year 13 170 75 1,140

 Past Month 6 58 32 479

ALCOHOL USE 

 Past Year 633 7,897 10,948 137,605

 Binge Alcohol Use2 198 2,454 3,697 47,995

 Heavy Alcohol Use2 54 588 1,216 14,326

CIGARETTE USE 

 Lifetime 690 6,844 13,606 141,234

 Past Year 446 4,256 6,191 59,583

 Past Month 306 2,690 5,543 51,961

PAST YEAR NONMEDICAL 

USE OF 

PSYCHOTHERAPEUTICS3

198 2,027 1,013 11,632 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005. 

*Low precision; no estimate reported. 

1 Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. 2

 Binge Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of 

hours of each other) on at least 1 day in the past 30 days. Heavy Alcohol Use is defined as drinking five or more drinks on the same 

occasion on each of 5 or more days in the past 30 days; all heavy alcohol users are also binge alcohol users. 3 Nonmedical use of prescription-type psychotherapeutics includes the nonmedical use of pain relievers, tranquilizers, stimulants, or 

sedatives and does not include over-the-counter drugs. 
237 

Table 2.3A Substance Dependence or Abuse, Mental Health Measures, and Receipt of 

Substance Use Treatment in the Past Year among Persons Aged 12 or Older, by Age Group 

and Appalachian Region Status 

Dependence or Abuse/Mental 

Health/Receipt of Treatment 

AGE GROUP 

Numbers in Thousands, Annual Averages Based on 2002-2005

12-17 18 or Older 

Appalachian 

Region1 

Outside 

Appalachia 

Appalachian 

Region1 

Outside 

Appalachia 

DEPENDENCE OR ABUSE2 

 Illicit Drugs3 97 1,202 444 5,277

 Alcohol 111 1,351 1,156 15,686

 Both Illicit Drugs and 

 Alcohol3 

47 542 187 2,470 

 Illicit Drugs or Alcohol3 162 2,010 1,414 18,493

PAST YEAR SERIOUS 

PSYCHOLOGICAL DISTRESS4 N/A N/A 2,426 22,999 

PAST YEAR MAJOR 

DEPRESSIVE EPISODE5 165 2,043 1,460 14,970 

PAST YEAR RECEIPT OF 

SPECIALTY TREATMENT 

FOR ILLICIT DRUG OR 

ALCOHOL USE3,6 

17 163 155 1,879 

MENTAL HEALTH 

TREATMENT/COUNSELING7 N/A N/A 2,429 25,304 

 Inpatient N/A N/A 160 1,668 

 Outpatient N/A N/A 1,303 13,891 

 Prescription Medication N/A N/A 2,155 20,645 

*Low precision; no estimate reported. 

N/A: Not applicable. 1 Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. 2 Dependence or abuse is based on definitions found in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). 3

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

non-medically. 4 Serious Psychological Distress (SPD) is defined as having a score of 13 or higher on the K6 scale. Due to questionnaire changes, these combined 

2004 and 2005 estimates are not comparable with 2004 and earlier estimates published in prior NSDUH reports. See Section B.4.4 in Appendix B of 

the Results from the 2005 National Survey on Drug Use and Health: National Findings. Estimates are based on combined 2004-2005 data. 5 Major Depressive Episode (MDE) is defined as a period of at least 2 weeks when a person experienced a depressed mood or loss of interest or 

pleasure in daily activities and had a majority of the symptoms for depression as described in the 4th edition of the Diagnostic and Statistical Manual 

of Mental Disorders (DSM-IV). Estimates are based on combined 2004-2005 data. 6

 Received Substance Use Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or 

outpatient), or mental health center in order to reduce or stop illicit drug or alcohol use, or for medical problems associated with illicit drug or 

alcohol use. Estimates include persons who received treatment specifically for illicit drugs or alcohol, as well as persons who received treatment but 

did not specify for what substance(s). 7 Mental Health Treatment/Counseling is defined as having received inpatient care or outpatient care or having used prescription medication for 

problems with emotions, nerves, or mental health. Respondents were not to include treatment for drug or alcohol use. Respondents with unknown 

treatment/counseling information were excluded. Estimates were based only on responses to items in the Adult Mental Health Service Utilization 

module. 

 Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
238 

Table 2.4A Demographic Characteristics and Health Insurance among Persons Aged 12 or 

Older Residing in Appalachian Region, by Age Group and Appalachian Sub-region 

Demographic 

Characteristic/Health 

Insurance 

AGE GROUP 

Numbers in Thousands, Annual Averages Based on 2002-2005

12-17 18 or Older 

Northern Central Southern Northern Central Southern 

HISPANIC ORIGIN 

AND RACE

 

 Not Hispanic or 

 Latino 

835 165 826 7,875 1,597 8,117 

 White 777 160 642 7,463 1,546 6,842 

 Black or African 

 American 

38 2 172 269 28 1,034 

 Other1 19 4 12 143 24 242 

 Hispanic or Latino 18 3 28 86 21 243 

EDUCATION 

 < High School N/A N/A N/A 1,296 497 1,861 

 High School 

 Graduate 

N/A N/A N/A 3,352 648 2,889 

 Some College N/A N/A N/A 1,806 306 1,978 

 College Graduate N/A N/A N/A 1,507 169 1,633 

CURRENT 

EMPLOYMENT 

 Full-Time N/A N/A N/A 3,911 698 4,552 

 Part-Time N/A N/A N/A 1,023 146 975 

 Unemployed N/A N/A N/A 288 62 266 

 Other2 N/A N/A N/A 2,739 713 2,568 

HEALTH 

INSURANCE 

 

 Private 617 84 566 5,893 1,032 5,918 

 Medicare 4 1 9 1,775 451 1,702 

 Medicaid/CHIP3 191 71 239 647 233 727 

*Low precision; no estimate reported. 

 NOTE: Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. 

N/A: Not applicable. 1 Includes respondents reporting American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, Asian, and Two or More Races. 2

 The Other Employment category includes retired persons, disabled persons, homemakers, students, or other persons not in the labor force. 3 CHIP is the Children's Health Insurance Program. Individuals aged 19 or younger are eligible for this plan. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
239 

Table 2.5A Lifetime, Past Year, and Past Month Substance Use among Persons Aged 12 or 

Older Residing in Appalachian Region, by Substance, Age Group, and Appalachian Sub-region 

Substance AGE GROUP

Numbers in Thousands, Annual Averages Based on 2002-2005

12-17 18 or Older

Northern Central Southern Northern Central Southern 

MARIJUANA USE 

 Lifetime 164 30 162 3,094 535 3,226

 Past Year 128 21 121 713 107 678

 Past Month 64 7 59 438 61 379

COCAINE USE 

 Lifetime 19 4 25 937 125 1,035

 Past Year 15 3 19 181 27 181

 Past Month 5 1 4 65 7 67

METHAMPHETAMINE 

USE 

 Lifetime 10 3 13 315 34 365

 Past Year 4 1 8 21 5 50

 Past Month 1 1 4 5 1 26

ALCOHOL USE 

 Past Year 313 49 272 5,515 705 4,727

 Binge Alcohol Use1 105 14 79 1,958 226 1,513

 Heavy Alcohol Use1 28 4 21 654 66 496

CIGARETTE USE 

 Lifetime 304 71 315 6,125 1,219 6,262

 Past Year 203 41 202 2,799 598 2,794

 Past Month 141 29 136 2,511 537 2,495

PAST YEAR 

NONMEDICAL USE OF 

PSYCHOTHERAPEUTICS2

77 18 103 395 104 514 

*Low precision; no estimate reported. 

NOTE: Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. 

1

 Binge Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of 

each other) on at least 1 day in the past 30 days. Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion on 

each of 5 or more days in the past 30 days; all heavy alcohol users are also binge alcohol users. 

2 Nonmedical use of prescription-type psychotherapeutics includes the nonmedical use of pain relievers, tranquilizers, stimulants, or 

sedatives and does not include over-the-counter drugs. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
240 

Table 2.6A Substance Dependence or Abuse, Mental Health Measures, and Receipt of Substance Use Treathe Past Year among Persons Aged 12 or Older Residing in Appalachian Region, by Age Group and AppalacSub-region 

Dependence or Abuse/Mental Health/Receipt of Treatment 

AGE GROUP 

Numbers in Thousands, Annual Averages Based on 2002-2005

12-17 18 or Older 

Northern Central Southern Northern Central S

DEPENDENCE OR ABUSE1  Illicit Drugs2 46 5 47 192 50  Alcohol 56 7 48 574 78  Both Illicit Drugs and  Alcohol2 

24 3 19 87 20 

Illicit Drugs or Alcohol2 77 10 75 680 108 

PAST YEAR SERIOUS PSYCHOLOGICAL DISTRESS3 N/A N/A N/A 1,123 270 PAST YEAR MAJOR DEPRESSIVE EPISODE4 

74 15 76 638 177 

PAST YEAR RECEIPT OF SPECIALTY TREATMENT FOR ILLICIT DRUG OR ALCOHOL USE2,5 

7 1 9 79 9 

MENTAL HEALTH TREATMENT/COUNSELING6 N/A N/A N/A 1,085 248  Inpatient N/A N/A N/A 57 16  Outpatient N/A N/A N/A 554 120  Prescription Medication N/A N/A N/A 946 232 

*Low precision; no estimate reported. NOTE: Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. N/A: Not applicable. 1 Dependence or abuse is based on definitions found in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). 2 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used non-medically. 3 Serious Psychological Distress (SPD) is defined as having a score of 13 or higher on the K6 scale. Due to questionnaire changes, these combined 2004 and 2005 estimates a

comparable with 2004 and earlier estimates published in prior NSDUH reports. See Section B.4.4 in Appendix B of the Results from the 2005 National Survey on Drug Use National Findings. Estimates are based on combined 2004-2005 data. 4 Major Depressive Episode (MDE) is defined as a period of at least 2 weeks when a person experienced a depressed mood or loss of interest or pleasure in daily activities and 

majority of the symptoms for depression as described in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). Estimates are based on com

2005 data. 

5 Received Substance Use Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or outpatient), or mental healt

order to reduce or stop illicit drug or alcohol use, or for medical problems associated with illicit drug or alcohol use. Estimates include persons who received treatment speciillicit drugs or alcohol, as well as persons who received treatment but did not specify for what substance(s). 6 Mental Health Treatment/Counseling is defined as having received inpatient care or outpatient care or having used prescription medication for problems with emotions, nervhealth. Respondents were not to include treatment for drug or alcohol use. Respondents with unknown treatment/counseling information were excluded. Estimates were base

responses to items in the Adult Mental Health Service Utilization module. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
241 

Table 2.7A Demographic Characteristics and Health Insurance among Persons Aged 12 or Older Residing Region, by Age Group and Appalachian Socioeconomic Status 

Demographic Characteristic/ Health Insurance 

AGE GROUP 

Numbers in Thousands, Annual Averages Based on 2002-2

12-17 18 or O

At-Risk or 

Distressed 

Transitional Competitive or 

Attainment 

At-Risk or 

Distressed 

Transition

HISPANIC ORIGIN AND RACE Not Hispanic or Latino 306 1,073 446 2,981 10,463  White 273 964 341 2,683 9,665  Black or African American 29 89 94 258 586  Other1 3 20 11 40 211  Hispanic or Latino 3 29 17 33 148 EDUCATION < High School N/A N/A N/A 871 2,142  High School  Graduate 

N/A N/A N/A 1,261 4,186 

 Some College N/A N/A N/A 554 2,511  College Graduate N/A N/A N/A 329 1,771 CURRENT EMPLOYMENT Full-Time N/A N/A N/A 1,321 5,445  Part-Time N/A N/A N/A 292 1,305  Unemployed N/A N/A N/A 137 346  Other2 N/A N/A N/A 1,265 3,514 HEALTH INSURANCE  Private 162 765 341 1,906 7,725  Medicare 3 6 5 765 2,352  Medicaid/CHIP3 125 280 96 426 911 

*Low precision; no estimate reported. NOTE: Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. N/A: Not applicable. 1 Includes respondents reporting American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, Asian, and Two or More Races.

2 The Other Employment category includes retired persons, disabled persons, homemakers, students, or other persons not in the labor force. 

3 CHIP is the Children's Health Insurance Program. Individuals aged 19 or younger are eligible for this plan. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
242 

Table 2.8A Lifetime, Past Year, and Past Month Substance Use among Persons Aged 12 or Older Residing Region, by Substance, Age Group, and Appalachian Socioeconomic Status 

Substance AGE GROUP

Numbers in Thousands, Annual Averages Based on 2002-2005

12-17 18 or Older

At-Risk or 

Distressed

Transitional Competitive 

or Attainment

At-Risk or 

Distressed

Transitional 

MARIJUANA USE Lifetime 61 210 84 983 4,065  Past Year 43 163 65 178 945  Past Month 18 80 33 91 566 COCAINE USE Lifetime 9 31 7 248 1,233  Past Year 7 24 6 40 258  Past Month 3 6 2 13 94 METHAMPHETAMINE USE Lifetime 6 16 4 59 448  Past Year 3 8 2 12 50  Past Month 2 3 1 4 16 ALCOHOL USE  Past Year 97 383 153 1,314 6,586  Binge Alcohol Use1 31 126 41 462 2,324  Heavy Alcohol Use1 9 34 11 144 800 CIGARETTE USE  Lifetime 135 416 139 2,260 8,079  Past Year 79 272 94 1,127 3,746  Past Month 58 186 62 1,018 3,357 PAST YEAR NONMEDICAL USE OF PSYCHOTHERAPEUTICS2

35 124 39 166 636 

*Low precision; no estimate reported. 

NOTE: Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. \ 1 Binge Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) on 

30 days. Heavy Alcohol Use is defined as drinking five or more drinks on the same occasion on each of 5 or more days in the past 30 days; all heavy abinge alcohol users. 2 Nonmedical use of prescription-type psychotherapeutics includes the nonmedical use of pain relievers, tranquilizers, stimulants, or sedatives and does 

counter drugs. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
243 

Table 2.9A Substance Dependence or Abuse, Mental Health Measures, and Receipt of Substance Use TreaYear among Persons Aged 12 or Older Residing in Appalachian Region, by Age Group and Appalachian SoStatus 

Dependence or Abuse/Mental Health/Receipt of Treatment Numbers in Thousands, Annual Averages Based on 2002-2005

AGE GROUP 

12-17 18 or Older 

At-Risk or 

Distressed 

Transitional Competitive 

or Attainment 

At-Risk or 

Distressed 

Transitional 

DEPENDENCE OR ABUSE1  Illicit Drugs2 16 62 20 77 279  Alcohol 16 73 22 142 717  Both Illicit Drugs and  Alcohol2 

6 33 8 28 123 

Illicit Drugs or Alcohol2 26 102 34 191 873 

PAST YEAR SERIOUS PSYCHOLOGICAL DISTRESS3 

N/A N/A N/A 521 1,265 

PAST YEAR MAJOR DEPRESSIVE EPISODE4 

28 93 45 313 745 

PAST YEAR RECEIPT OF SPECIALTY TREATMENT FOR ILLICIT DRUG OR ALCOHOL USE2,5 

3 11 3 17 102 

MENTAL HEALTH TREATMENT/COUNSELING6 

N/A N/A N/A 480 1,392 

 Inpatient N/A N/A N/A 34 83  Outpatient N/A N/A N/A 258 761  Prescription Medication N/A N/A N/A 427 1,229 

*Low precision; no estimate reported. 

NOTE: Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. N/A: Not applicable. 1 Dependence or abuse is based on definitions found in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). 2 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used nonmedically. 3 Serious Psychological Distress (SPD) is defined as having a score of 13 or higher on the K6 scale. Due to questionnaire changes, these combined 2004 and 2005 estimates are not comparable wit

published in prior NSDUH reports. See Section B.4.4 in Appendix B of the Results from the 2005 National Survey on Drug Use and Health: National Findings. Estimates are based on combined 

4 Major Depressive Episode (MDE) is defined as a period of at least 2 weeks when a person experienced a depressed mood or loss of interest or pleasure in daily activities and had a majority of th

described in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). Estimates are based on combined 2004-2005 data. 5 Received Substance Use Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or outpatient), or mental health center in order to re

alcohol use, or for medical problems associated with illicit drug or alcohol use. Estimates include persons who received treatment specifically for illicit drugs or alcohol, as well as persons who r

specify for what substance(s). 6 Mental Health Treatment/Counseling is defined as having received inpatient care or outpatient care or having used prescription medication for problems with emotions, nerves, or mental health. 

treatment for drug or alcohol use. Respondents with unknown treatment/counseling information were excluded. Estimates were based only on responses to items in the Adult Mental Health Serv

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
244 

Table 2.10A Access to Alcohol Treatment among Persons Aged 12 or Older, by Age Group and AppalachiNumbers in Thousands Annual Averages Based on 2002-2005

Age 12-17 Age 18 

Appalachian Region Outside Appalachia Appalachian Region 

Access to Alcohol Treatment1,2

 Needed But Not Received Alcohol Treatment 105 1,286 1,103  Felt Need for Alcohol Treatment 4 42 63  Felt Need for Alcohol Treatment and Made No  Effort 2 28 41 

*Low precision; no estimate reported. NOTE: Received Alcohol Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or outp

in order to reduce or stop alcohol use, or for medical problems associated with alcohol use. 

1 Needing But Not Receiving Treatment refers to respondents classified as needing treatment for alcohol, but have not received treatment for an alcohol 

(i.e., drug and alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and mental health centers). 

2 Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an alcohol problem, as well as persons who received tr

than a specialty facility but felt they needed additional treatment. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005. 
245 

Table 2.11A Access to Drug Treatment among Persons Aged 12 or Older, by Age Group and Appalachian Numbers in Thousands Annual Averages Based on 2002-2005

Age 12-17 Age 18 or 

Appalachian Region Outside Appalachia Appalachian Region O

Access to Drug Treatment1,2

 Needed But Not Received Treatment for an  Illicit Drug Problem 91 1,124 388  Felt Need for Treatment for an Illicit Drug  Problem 5 72 51 

 Felt Need for Treatment for an Illicit Drug  Problem and Made No Effort 3 55 43 *Low precision; no estimate reported. NOTE: Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type pychotherapeutics used NOTE: Received Illicit Drug Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or o

center in order to reduce or stop illicit drug use, or for medical problems associated with illicit drug use. 

1 Needing But Not Receiving Treatment refers to respondents classified as needing treatment for illicit drugs, but have not received treatment for an illic

specialty facility (i.e., drug and alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and mental health centers. 

2 Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an illicit drug problem, as well as persons who receive

other than a specialty facility but felt they needed additional treatment. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
246 

Table 2.12A Reasons for Not Receiving Substance Use Treatment and Locations of Treatment by Age GroRegion Status 

Numbers in Thousands, Annual Averages Based on 2002-2005 Age 12-17 

Appalachian Region Outside 

Appalachia 

Appalach

Regio

Reasons for Not Receiving Drug or Alcohol Treatment among Persons Who Needed But Did Not Receive Treatment at a Specialty Facility1  Cost/Insurance Barriers2 * 11 *  Not Ready to Stop Using * 24 *  Stigma3,7 * 18 *  Did Not Know Where to Go for Treatment * 9 *  Did Not Feel Need for Treatment/Could Handle the Problem  Without Treatment4,7 

* 11 * 

 Did Not Have Time7 * 4 *  Treatment Would Not Help7 * 4 *  Other Access Barriers5 * 11 * Locations Where Past Year Substance Treatment was Received among Persons Who Received Treatment at a Specialty Facility6 Self-Help Group * 83 89  Outpatient Rehabilitation * 109 106  Inpatient Rehabilitation * 67 57  Mental Health Center * 69 75  Hospital Inpatient * 59 54  Private Doctor's Office * 26 30  Emergency Room * 33 28  Prison or Jail * 21 12 

*Low precision; no estimate reported. - Needing But Not Receiving Treatment refers to respondents classified as needing treatment for illicit drugs or alcohol, but have not received treatment for an illicit drug o

- Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an illicit drug or alcohol problem, as well as persons who received treatm

facility but felt they needed additional treatment. 1 Respondents could indicate multiple reasons; thus, these response categories are not mutually exclusive. 2 Includes reasons of "No health coverage and could not afford cost," "Had health coverage but did not cover treatment or did not cover cost," and other-specify responses 

not indicated." 

3 Includes reasons of "Might cause neighbors/community to have negative opinion," "Might have negative effect on job," "Did not want others to find out," and other-speci

"Ashamed/embarrassed/afraid" and "Afraid would have trouble with the police/social services." 4 Includes reasons of "Did not feel need for treatment," "Could handle the problem without treatment," and other-specify responses of "Could do it with support of family/f

religion/spirituality." 5 Includes reasons of "No transportation/inconvenient," "No program having type of treatment," "No openings in a program," and other-specify responses of "No program h

were comfortable," "Services desired were unavailable or you were currently ineligible," and "Attempted to get treatment but encountered delays." 6 Respondents could indicate multiple locations of treatment; thus, these response categories are not mutually exclusive. 

7 Estimates are based only on combined 2003-2005 data. Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 
247 

Table 2.13A Reasons for Not Receiving Mental Health Treatment among Persons Aged 12 or Older, by AgAppalachian Region Status: Numbers in Thousands 

Annual Averages Based on 2002-2005 

Age 12-17 

Appalachian Region Outside Appalachia Appalachian 

Reasons for Not Receiving Mental Health Treatment/Counseling among Persons with an Unmet Need for Mental Health Treatment1,2 

 Cost/Insurance Barriers2 N/A N/A 406  Did Not Feel Need for Treatment/Could Handle the Problem Without Treatment3,7 N/A N/A 339  Stigma4,7 N/A N/A 253  Did not Know Where to Go for Services N/A N/A 114  Did Not Have Time7 N/A N/A 122  Treatment Would Not Help5,7 N/A N/A 86  Fear of Being Committed/Have to Take Medicine N/A N/A 107  Other Access Barriers6,7 N/A N/A 37 

*Low precision; no estimate reported. N/A: Not applicable. NOTE: Unmet Need for Mental Health Treatment/Counseling is defined as a perceived need for treatment that was not received. NOTE: Estimates represent reasons for not receiving mental health treatment/counseling for all persons aged 18 or older with an unmet need for treatm

mental health treatment/counseling information. 

NOTE: Mental Health Treatment/Counseling is defined as having received inpatient care or outpatient care or having used prescription medication for p

mental health. Respondents were not to include treatment for drug or alcohol use. Respondents with unknown treatment/counseling information based only on responses to items in the Adult Mental Health Service Utilization module. 

1 Respondents could indicate multiple reasons; thus, these response categories are not mutually exclusive. 2 Includes reasons of "Could not afford," "Health insurance does not pay enough," "Health insurance does not cover mental health treatment," and other-

insurance." 

3 Includes reasons of "Did not feel need for treatment," "Could handle problem without treatment," and other-specify responses of "Work on problems w

problems through religion/spirituality." 

4 Includes reasons of "Might cause neighbors/community to have negative opinion," "Might have negative effect on job," "Concerned about confidential

out," and other-specify responses of "Ashamed/embarrassed/afraid," "Concerned how court system would treat me," and "Concerned how it would affe

5 Includes reasons of "Did not feel need for treatment," "Could handle problem without treatment," and other-specify responses of "Work on problems w

problems through religion/spirituality." 

6 Includes reasons of "No transportation/inconvenient" and other-specify responses of "Too much red tape/hassle to get services," "No openings/long wa

unavailable/limited in area," "Attempted to get treatment but unsuccessful in finding help," and "Could not find program/counselor comfortable with." 

7 Estimates are based only on combined 2003-2005 data. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005. 
248 

Table 2.14A Access to Alcohol Use Treatment among Persons Aged 12 or Older, by Age Group and Appa

Region: Numbers in Thousands 

 Annual Averages Based on 2002-2005

Age 12-17 Age 18 or Old

Northern Central Southern Northern Centr

Access to Alcohol Treatment1,2

 Needed But Not Received Alcohol Treatment 53 7 46 541 74  Felt Need for Alcohol Treatment 2 1 1 28 9  Felt Need for Alcohol Treatment and Made  No Effort 1 1 0 12 8 

*Low precision; no estimate reported. NOTE: Received Alcohol Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or outp

health center in order to reduce or stop alcohol use, or for medical problems associated with alcohol use. 

1 Needing But Not Receiving Treatment refers to respondents classified as needing treatment for alcohol, but have not received treatment for an alcohol 

specialty facility (i.e., drug and alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and mental health centers). 

2 Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an alcohol problem, as well as persons who received t

location 

 other than a specialty facility but felt they needed additional treatment. Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
249 

Table 2.15A Access to Drug Use Treatment among Persons Aged 12 or Older, by Age Group and Appalac

Numbers in Thousands 

Annual Averages Based on 2002-2005 

Age 12-17 Age 18 or 

Northern Central Southern Northern Cen

Access to Drug Treatment1,2 

 Needed But Not Received Treatment for an  Illicit Drug Problem 43 5 42 170 46  Felt Need for Treatment for an Illicit Drug  Problem 3 1 2 19 8  Felt Need for Treatment for an Illicit Drug  Problem and Made No Effort 1 0 1 13 8 

*Low precision; no estimate reported. NOTE: Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type pychotherapeutics used NOTE: Received Illicit Drug Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or o

health center in order to reduce or stop illicit drug use, or for medical problems associated with illicit drug use. 

1 Needing But Not Receiving Treatment refers to respondents classified as needing treatment for illicit drugs, but have not received treatment for an illic

specialty facility (i.e., drug and alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and mental health centers. 

2 Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an illicit drug problem, as well as persons who receive

other than a specialty facility but felt they needed additional treatment. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
250 

Table 2.16A Reasons for Not Receiving Mental Health Treatment among Persons Aged 12 or Older, by A

Appalachian Sub-Region: Numbers in Thousands 

Annual Averages Based on 2002-2005 

Age 12-17 Age 18 or 

Northern Central Southern Northern Cent

Reasons for Not Receiving Mental Health Treatment/Counseling among Persons with an Unmet Need for Mental Health Treatm

 Cost/Insurance Barriers2 N/A N/A N/A 172 *  Did Not Feel Need for Treatment/Could  Handle the Problem Without Treatment3,7 N/A N/A N/A 160 *  Stigma4,7 N/A N/A N/A 121 *  Did not Know Where to Go for Services N/A N/A N/A 51 *  Did Not Have Time7 N/A N/A N/A 53 *  Treatment Would Not Help5,7 N/A N/A N/A 54 *  Fear of Being Committed/Have to Take  Medicine N/A N/A N/A 41 8  Other Access Barriers6,7 N/A N/A N/A 21 * 

*Low precision; no estimate reported. N/A: Not applicable. NOTE: Unmet Need for Mental Health Treatment/Counseling is defined as a perceived need for treatment that was not received. NOTE: Estimates represent reasons for not receiving mental health treatment/counseling for all persons aged 18 or older with an unmet need for treatment, including tho

health treatment/counseling information. 

NOTE: Mental Health Treatment/Counseling is defined as having received inpatient care or outpatient care or having used prescription medication for problems with em

health. Respondents were not to include treatment for drug or alcohol use. Respondents with unknown treatment/counseling information were excluded. Estimatresponses to items in the Adult Mental Health Service Utilization module. 

1 Respondents could indicate multiple reasons; thus, these response categories are not mutually exclusive. 2 Includes reasons of "Could not afford," "Health insurance does not pay enough," "Health insurance does not cover mental health treatment," and other-specify responses 3 Includes reasons of "Did not feel need for treatment," "Could handle problem without treatment," and other-specify responses of "Work on problems with family/friends

through religion/spirituality." 

4 Includes reasons of "Might cause neighbors/community to have negative opinion," "Might have negative effect on job," "Concerned about confidentiality," "Did not wan

other-specify responses of "Ashamed/embarrassed/afraid," "Concerned how court system would treat me," and "Concerned how it would affect future insurability." 

5 Includes reasons of "Did not feel need for treatment," "Could handle problem without treatment," and other-specify responses of "Work on problems with family/friends

through religion/spirituality." 

6 Includes reasons of "No transportation/inconvenient" and other-specify responses of "Too much red tape/hassle to get services," "No openings/long waiting lists/delays," 

in area," "Attempted to get treatment but unsuccessful in finding help," and "Could not find program/counselor comfortable with." 

7 Estimates are based only on combined 2003-2005 data. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
251 

Table 2.17A Access to Alcohol Use Treatment among Persons Aged 12 or Older, by Age Group and AppaSocioeconomic Status: Numbers in Thousands 

Annual Averages Based on 2002-2005

Age 12-17 Age 18 or 

At-Risk or 

Distressed Transitional

Competitive or 

Attainment 

At-Risk or 

Distressed Transitio

Access to Alcohol Treatment1,2 

 Needed But Not Received Alcohol Treatment 15 69 21 135 681  Felt Need for Alcohol Treatment 2 1 0 13 31  Felt Need for Alcohol Treatment and Made  No Effort 1 1 0 9 24 

*Low precision; no estimate reported. NOTE: Received Alcohol Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or outpatient), or mental 

reduce or stop alcohol use, or for medical problems associated with alcohol use. 

1 Needing But Not Receiving Treatment refers to respondents classified as needing treatment for alcohol, but have not received treatment for an alcohol problem at a speci

alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and mental health centers). 

2 Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an alcohol problem, as well as persons who received treatment at a locat

facility but felt they needed additional treatment. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
252 

Table 2.18A Access to Drug Treatment among Persons Aged 12 or Older, by Age Group and Appalachian 

Status: Numbers in Thousands 

Annual Averages Based on 2002-2005 

Age 12-17 Age 18 o

At-Risk or 

Distressed Transitional

Competitive or 

Attainment

At-Risk or 

Distressed Transit

Access to Drug Treatment1,2

 Needed But Not Received Treatment for an  Illicit Drug Problem 14 58 18 68 240  Felt Need for Treatment for an Illicit Drug  Problem 1 2 1 9 29  Felt Need for Treatment for an Illicit Drug  Problem and Made No Effort 1 1 1 8 23 

*Low precision; no estimate reported. NOTE: Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type pychotherapeutics used NOTE: Received Illicit Drug Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or o

center in order to reduce or stop illicit drug use, or for medical problems associated with illicit drug use. 

1 Needing But Not Receiving Treatment refers to respondents classified as needing treatment for illicit drugs, but have not received treatment for an illic

specialty facility (i.e., drug and alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and mental health centers. 

2 Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an illicit drug problem, as well as persons who receive

other than a specialty facility but felt they needed additional treatment. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005. 
253 

Table 2.19A Reasons for Not Receiving Mental Health Treatment/Counseling among Persons Aged 12 or 

Group and Appalachian Socioeconomic Status: Numbers in Thousands, Annual Averages Based on 2002-2

Age 12-17 Age 18 or 

At-Risk or 

Distressed Transitional

Competitive or 

Attainment 

At-Risk or 

Distressed Transitio

Reasons for Not Receiving Mental Health Treatment/Counseling among Persons with an Unmet Need for Mental Health Treatm

 Cost/Insurance Barriers2 N/A N/A N/A 68 260  Did Not Feel Need for Treatment/Could  Handle the Problem Without Treatment3,7 N/A N/A N/A 67 152  Stigma4,7 N/A N/A N/A 60 135  Did not Know Where to Go for Services N/A N/A N/A 19 75  Did Not Have Time7 N/A N/A N/A 23 69  Treatment Would Not Help5,7 N/A N/A N/A 11 44  Fear of Being Committed/Have to Take  Medicine N/A N/A N/A 27 56  Other Access Barriers6,7 N/A N/A N/A 4 25 

*Low precision; no estimate reported. N/A: Not applicable. NOTE: Unmet Need for Mental Health Treatment/Counseling is defined as a perceived need for treatment that was not received. NOTE: Estimates represent reasons for not receiving mental health treatment/counseling for all persons aged 18 or older with an unmet need for treatment, including tho

health treatment/counseling information. 

NOTE: Mental Health Treatment/Counseling is defined as having received inpatient care or outpatient care or having used prescription medication for problems with em

health. Respondents were not to include treatment for drug or alcohol use. Respondents with unknown treatment/counseling information were excluded. Estimatresponses to items in the Adult Mental Health Service Utilization module. 

1 Respondents could indicate multiple reasons; thus, these response categories are not mutually exclusive. 2 Includes reasons of "Could not afford," "Health insurance does not pay enough," "Health insurance does not cover mental health treatment," and other-specify responses 3 Includes reasons of "Did not feel need for treatment," "Could handle problem without treatment," and other-specify responses of "Work on problems with family/friends

through religion/spirituality." 

4 Includes reasons of "Might cause neighbors/community to have negative opinion," "Might have negative effect on job," "Concerned about confidentiality," "Did not wan

other-specify responses of "Ashamed/embarrassed/afraid," "Concerned how court system would treat me," and "Concerned how it would affect future insurability." 

5 Includes reasons of "Did not feel need for treatment," "Could handle problem without treatment," and other-specify responses of "Work on problems with family/friends

through religion/spirituality." 

6 Includes reasons of "No transportation/inconvenient" and other-specify responses of "Too much red tape/hassle to get services," "No openings/long waiting lists/delays," 

in area," "Attempted to get treatment but unsuccessful in finding help," and "Could not find program/counselor comfortable with." 

7 Estimates are based only on combined 2003-2005 data. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005. 
254 

Table 2.1B Demographic Characteristics and Health Insurance among Persons Aged 12 or Older, by Age Appalachian Region Status: Standard Errors of Percentages, Annual Averages Based on 2002-2005 

Demographic Characteristic/Health Insurance 

AGE GROUP 

12-17 18 or Olde

Appalachian Region1 Outside Appalachia Appalachian Region1 Ou

HISPANIC ORIGIN AND RACE Not Hispanic or Latino 0.30 0.28 0.27  White 0.85 0.36 0.69  Black or African American 0.80 0.27 0.55  Other2 0.25 0.17 0.24  Hispanic or Latino 0.30 0.28 0.27 EDUCATION < High School N/A N/A 0.61  High School Graduate N/A N/A 0.68  Some College N/A N/A 0.54  College Graduate N/A N/A 0.71 CURRENT EMPLOYMENT Full-Time N/A N/A 0.73  Part-Time N/A N/A 0.39  Unemployed N/A N/A 0.20  Other3 N/A N/A 0.71 HEALTH INSURANCE  Private 0.92 0.32 0.68  Medicare 0.18 0.05 0.72  Medicaid/CHIP4 0.86 0.28 0.42 

*Low precision; no estimate reported. N/A: Not applicable. 1 Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. 2 Includes respondents reporting American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, Asian, and Two or More Races.

3 The Other Employment category includes retired persons, disabled persons, homemakers, students, or other persons not in the labor force. 

4 CHIP is the Children's Health Insurance Program. Individuals aged 19 or younger are eligible for this plan. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
255 

Table 2.2B Lifetime, Past Year, and Past Month Substance Use among Persons Aged 12 or Older, by SubsGroup, and Appalachian Region Status: Standard Errors of Percentages, Annual Averages Based on 2002-20

Substance AGE GROUP

12-17 18 or Older

Appalachian Region1 Outside Appalachia Appalachian Region1 Out

MARIJUANA USE Lifetime 0.60 0.18 0.64  Past Year 0.53 0.16 0.29  Past Month 0.38 0.12 0.21 COCAINE USE Lifetime 0.23 0.07 0.41  Past Year 0.20 0.06 0.14  Past Month 0.09 0.04 0.09 METHAMPHETAMINE USE Lifetime 0.17 0.05 0.25  Past Year 0.13 0.04 0.05  Past Month 0.12 0.02 0.04 ALCOHOL USE  Past Year 0.70 0.22 0.74  Binge Alcohol Use2 0.43 0.15 0.51  Heavy Alcohol Use2 0.22 0.07 0.29 CIGARETTE USE  Lifetime 0.70 0.22 0.61  Past Year 0.61 0.18 0.64  Past Month 0.55 0.15 0.61 PAST YEAR NONMEDICAL USE OF PSYCHOTHERAPEUTICS3

0.51 0.13 0.23 

*Low precision; no estimate reported. 1 Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. 2 Binge Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) on at least 1 day in the past 30 days

defined as drinking five or more drinks on the same occasion on each of 5 or more days in the past 30 days; all heavy alcohol users are also binge alcohol users. 3 Nonmedical use of prescription-type psychotherapeutics includes the nonmedical use of pain relievers, tranquilizers, stimulants, or sedatives and does not include over-the-counter drug

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
256 

Table 2.3B Substance Dependence or Abuse, Mental Health Measures, and Receipt of Substance Use TreaYear among Persons Aged 12 or Older, by Age Group and Appalachian Region Status 

Dependence or Abuse/Mental Health/Receipt of Treatment (Standard Errors of Percentages, Annual Averages Based on 2002-2005)

AGE GROUP 

12-17 18 or 

Appalachian 

Region1 

Outside 

Appalachia 

Appalachian 

Region1 

DEPENDENCE OR ABUSE2  Illicit Drugs3 0.32 0.10 0.16  Alcohol 0.37 0.11 0.26  Both Illicit Drugs and Alcohol3 0.23 0.07 0.08 

Illicit Drugs or Alcohol3 0.43 0.13 0.29 

PAST YEAR SERIOUS PSYCHOLOGICAL DISTRESS4 

N/A N/A 0.74 

PAST YEAR MAJOR DEPRESSIVE EPISODE5 0.61 0.19 0.57 PAST YEAR RECEIPT OF SPECIALTY TREATMENT FOR ILLICIT DRUG OR ALCOHOL USE3,6 

0.14 0.04 0.09 

MENTAL HEALTH TREATMENT/COUNSELING7 N/A N/A 0.43  Inpatient N/A N/A 0.13  Outpatient N/A N/A 0.33  Prescription Medication N/A N/A 0.41 

*Low precision; no estimate reported. N/A: Not applicable 1 Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. 2 Dependence or abuse is based on definitions found in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). 3 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used nonmedically. 4 Serious Psychological Distress (SPD) is defined as having a score of 13 or higher on the K6 scale. Due to questionnaire changes, these combined 2004 and 2005 estimates a

2004 and earlier estimates published in prior NSDUH reports. See Section B.4.4 in Appendix B of the Results from the 2005 National Survey on Drug Use and Health: Natare based on combined 2004-2005 data. 

5 Major Depressive Episode (MDE) is defined as a period of at least 2 weeks when a person experienced a depressed mood or loss of interest or pleasure in daily activities an

symptoms for depression as described in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). Estimates are based on combined 2004-20

6 Received Substance Use Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or outpatient), or mental heal

or stop illicit drug or alcohol use, or for medical problems associated with illicit drug or alcohol use. Estimates include persons who received treatment specifically for illicipersons who received treatment but did not specify for what substance(s). 7 Mental Health Treatment/Counseling is defined as having received inpatient care or outpatient care or having used prescription medication for problems with emotions, ner

Respondents were not to include treatment for drug or alcohol use. Respondents with unknown treatment/counseling information were excluded. Estimates were based only 

Adult Mental Health Service Utilization module. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005. 
257 

Table 2.4B Demographic Characteristics and Health Insurance among Persons Aged 12 or Older ResidinRegion, by Age Group and Appalachian Subregion: Standard Errors of Percentages, Annual Averages Bas

Demographic Characteristic/Health Insurance 

AGE GROUP 

12-17 18 or Olde

North Central South North Central 

HISPANIC ORIGIN AND RACE Not Hispanic or Latino 0.32 0.83 0.55 0.20 0.77  White 0.93 1.21 1.61 0.56 1.30  Black or African American 0.77 0.48 1.55 0.41 0.87  Other1 0.30 0.86 0.42 0.27 0.42  Hispanic or Latino 0.32 0.83 0.55 0.20 0.77 EDUCATION < High School N/A N/A N/A 0.71 2.26  High School Graduate N/A N/A N/A 0.83 2.52  Some College N/A N/A N/A 0.70 1.48  College Graduate N/A N/A N/A 0.75 1.80 CURRENT EMPLOYMENT Full-Time N/A N/A N/A 0.92 2.61  Part-Time N/A N/A N/A 0.48 1.15  Unemployed N/A N/A N/A 0.26 0.75  Other2 N/A N/A N/A 0.89 2.69 HEALTH INSURANCE  Private 0.99 2.90 1.66 0.76 2.34  Medicare 0.14 0.32 0.35 0.81 2.71  Medicaid/CHIP3 0.87 3.05 1.60 0.50 2.05 

*Low precision; no estimate reported. NOTE: Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. N/A: Not applicable. 1 Includes respondents reporting American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, Asian, and Two or More Races.

2 The Other Employment category includes retired persons, disabled persons, homemakers, students, or other persons not in the labor force. 

3 CHIP is the Children's Health Insurance Program. Individuals aged 19 or younger are eligible for this plan. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
258 

Table 2.5B Lifetime, Past Year, and Past Month Substance Use among Persons Aged 12 or Older ResidinRegion, by Substance, Age Group, and Appalachian Subregion 

Substance Standard Errors of Percentages, Annual Averages Based on 2002-2005

AGE GROUP

12-17 18 or Olde

North Central South North Central 

MARIJUANA USE Lifetime 0.75 1.75 1.01 0.84 1.90  Past Year 0.64 1.50 0.91 0.40 0.81  Past Month 0.50 0.70 0.66 0.29 0.60 COCAINE USE Lifetime 0.25 0.63 0.41 0.46 1.01  Past Year 0.23 0.61 0.36 0.19 0.36  Past Month 0.12 0.30 0.15 0.12 0.17 METHAMPHETAMINE USE Lifetime 0.20 0.57 0.29 0.30 0.52  Past Year 0.10 0.32 0.27 0.05 0.20  Past Month 0.06 0.28 0.24 0.03 0.04 ALCOHOL USE  Past Year 0.84 1.99 1.21 0.80 2.42  Binge Alcohol Use1 0.56 0.92 0.72 0.65 1.44  Heavy Alcohol Use1 0.33 0.63 0.36 0.42 0.71 CIGARETTE USE  Lifetime 0.85 2.39 1.19 0.66 1.70  Past Year 0.76 1.92 1.03 0.78 1.95  Past Month 0.69 1.47 0.92 0.76 1.90 PAST YEAR NONMEDICAL USE OF PSYCHOTHERAPEUTICS2 0.48 1.24 0.96 0.26 0.75 

*Low precision; no estimate reported. NOTE: Appalachian region is defined as all areas covered by the 410 designated counties in 13 states.1 Binge Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) on at least 1 day in the past 30 da

defined as drinking five or more drinks on the same occasion on each of 5 or more days in the past 30 days; all heavy alcohol users are also binge alcohol users. 2 Nonmedical use of prescription-type psychotherapeutics includes the nonmedical use of pain relievers, tranquilizers, stimulants, or sedatives and does not include over-the-counter d

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
259 

Table 2.6B Substance Dependence or Abuse, Mental Health Measures, and Receipt of Substance Use TreYear among Persons Aged 12 or Older Residing in Appalachian Region, by Age Group and Appalachian SuErrors of Percentages, Annual Averages Based on 2002-2005 

Dependence or Abuse/Mental Health/Receipt of Treatment 

AGE GROUP 

12-17 18 or Older 

North Central South North Central 

DEPENDENCE OR ABUSE1  Illicit Drugs2 0.39 0.64 0.56 0.19 0.50  Alcohol 0.45 0.88 0.67 0.38 0.54  Both Illicit Drugs and Alcohol2 0.27 0.50 0.40 0.11 0.28 

Illicit Drugs or Alcohol2 0.53 0.94 0.73 0.41 0.66 

PAST YEAR SERIOUS PSYCHOLOGICAL DISTRESS3 N/A N/A N/A 0.82 2.38 PAST YEAR MAJOR DEPRESSIVE EPISODE4 0.73 1.59 1.04 0.66 2.05 PAST YEAR RECEIPT OF SPECIALTY TREATMENT FOR ILLICIT DRUG OR ALCOHOL USE2,5 

0.13 0.35 0.26 0.12 0.14 

MENTAL HEALTH TREATMENT/COUNSELING6 N/A N/A N/A 0.52 1.48  Inpatient N/A N/A N/A 0.14 0.33  Outpatient N/A N/A N/A 0.38 0.98  Prescription Medication N/A N/A N/A 0.50 1.44 

*Low precision; no estimate reported. NOTE: Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. N/A: Not applicable. 1 Dependence or abuse is based on definitions found in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). 2 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used nonmedically. 3 Serious Psychological Distress (SPD) is defined as having a score of 13 or higher on the K6 scale. Due to questionnaire changes, these combined 2004 and 2005 estimate

2004 and earlier estimates published in prior NSDUH reports. See Section B.4.4 in Appendix B of the Results from the 2005 National Survey on Drug Use and Health: Nare based on combined 2004-2005 data. 

4 Major Depressive Episode (MDE) is defined as a period of at least 2 weeks when a person experienced a depressed mood or loss of interest or pleasure in daily activities 

symptoms for depression as described in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). Estimates are based on combined 2004-

5 Received Substance Use Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or outpatient), or mental he

or stop illicit drug or alcohol use, or for medical problems associated with illicit drug or alcohol use. Estimates include persons who received treatment specifically for illipersons who received treatment but did not specify for what substance(s). 6 Mental Health Treatment/Counseling is defined as having received inpatient care or outpatient care or having used prescription medication for problems with emotions, nRespondents were not to include treatment for drug or alcohol use. Respondents with unknown treatment/counseling information were excluded. Estimates were based on

Adult Mental Health Service Utilization module. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
260 

Table 2.7B Demographic Characteristics and Health Insurance among Persons Aged 12 or Older ResidinRegion, by Age Group and Appalachian Socioeconomic Status: Standard Errors of Percentages, Annual Av2002-2005 

Demographic Characteristic/Health Insurance 

AGE GROUP 

12-17 18 or Olde

At-Risk or 

Distressed 

Transitional Competitive or 

Attainment 

At-Risk or 

Distressed 

Transition

HISPANIC ORIGIN AND RACE Not Hispanic or Latino 0.37 0.40 0.57 0.44 0.25  White 1.40 0.88 2.48 1.63 0.67  Black or African  American 

1.35 0.76 2.44 1.39 0.55 

 Other1 0.30 0.27 0.73 0.37 0.29  Hispanic or Latino 0.37 0.40 0.57 0.44 0.25 EDUCATION < High School N/A N/A N/A 1.58 0.77  High School Graduate N/A N/A N/A 1.44 0.89  Some College N/A N/A N/A 1.06 0.75  College Graduate N/A N/A N/A 1.01 0.79 CURRENT EMPLOYMENT Full-Time N/A N/A N/A 1.83 0.90  Part-Time N/A N/A N/A 0.69 0.55  Unemployed N/A N/A N/A 0.52 0.26  Other2 N/A N/A N/A 1.97 0.86 HEALTH INSURANCE  Private 1.99 1.14 2.04 1.83 0.72  Medicare 0.33 0.15 0.57 1.70 0.91  Medicaid/CHIP3 1.88 1.14 1.73 1.21 0.51 

*Low precision; no estimate reported. NOTE: Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. N/A: Not applicable. 1 Includes respondents reporting American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, Asian, and Two or More Races.

2 The Other Employment category includes retired persons, disabled persons, homemakers, students, or other persons not in the labor force. 

3 CHIP is the Children's Health Insurance Program. Individuals aged 19 or younger are eligible for this plan. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
261 

Table 2.8B Lifetime, Past Year, and Past Month Substance Use among Persons Aged 12 or Older ResidinRegion, by Substance, Age Group, and Appalachian Socioeconomic Status, 2002 - 2005 

Substance AGE GROUP

12-17 18 or Older

At-Risk or 

Distressed

Transitional Competitive or 

Attainment

At-Risk or 

Distressed

Transitiona

MARIJUANA USE Lifetime 1.54 0.82 1.19 1.47 0.79  Past Year 1.25 0.72 1.13 0.50 0.39  Past Month 0.70 0.53 0.83 0.32 0.29 COCAINE USE Lifetime 0.51 0.33 0.31 0.72 0.50  Past Year 0.42 0.30 0.26 0.22 0.20  Past Month 0.29 0.12 0.14 0.14 0.13 METHAMPHETAMINE USE Lifetime 0.52 0.25 0.22 0.30 0.32  Past Year 0.31 0.20 0.12 0.14 0.07  Past Month 0.28 0.18 0.10 0.07 0.04 ALCOHOL USE  Past Year 1.61 0.91 1.78 1.71 0.86  Binge Alcohol Use1 0.97 0.58 0.79 1.08 0.66  Heavy Alcohol Use1 0.45 0.30 0.47 0.53 0.37 CIGARETTE USE  Lifetime 1.75 0.92 1.41 1.29 0.77  Past Year 1.56 0.85 1.13 1.51 0.78  Past Month 1.33 0.77 1.06 1.51 0.74 PAST YEAR NONMEDICAL USE OF PSYCHOTHERAPEUTICS2

1.00 0.70 0.86 0.47 0.30 

*Low precision; no estimate reported. Standard Errors of Percentages, Annual Averages Based on 2002-2005. NOTE: Appalachian region is defined as all areas covered by the 410 d1Binge Alcohol Use is defined as drinking five or more drinks on the same occasion (i.e., at the same time or within a couple of hours of each other) on at least 1 day in the past 30 day

as drinking five or more drinks on the same occasion on each of 5 or more days in the past 30 days; all heavy alcohol users are also binge alcohol users. 2 Nonmedical use of prescription-type psychotherapeutics includes the nonmedical use of pain relievers, tranquilizers, stimulants, or sedatives and does not include over-the-counter d

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
262 

Table 2.9B Substance Dependence or Abuse, Mental Health Measures, and Receipt of Substance Use TreYear among Persons Aged 12 or Older Residing in Appalachian Region, by Age Group and Appalachian SoStatus: Standard Errors of Percentages, Annual Averages Based on 2002-2005 

Dependence or Abuse/Mental Health/Receipt of Treatment 

AGE GROUP 

12-17 18 or O

At-Risk or 

Distressed 

Transitional Competitive 

or 

Attainment 

At-Risk or 

Distressed 

Transitio

DEPENDENCE OR ABUSE1  Illicit Drugs2 0.71 0.46 0.53 0.34 0.21  Alcohol 0.70 0.50 0.61 0.45 0.33  Both Illicit Drugs and Alcohol2 0.41 0.33 0.30 0.16 0.11 

Illicit Drugs or Alcohol2 0.88 0.58 0.73 0.56 0.36 

PAST YEAR SERIOUS PSYCHOLOGICAL DISTRESS3 

N/A N/A N/A 1.62 0.82 

PAST YEAR MAJOR DEPRESSIVE EPISODE4 

1.52 0.69 1.53 1.35 0.64 

PAST YEAR RECEIPT OF SPECIALTY TREATMENT FOR ILLICIT DRUG OR ALCOHOL USE2,5 

0.34 0.20 0.20 0.16 0.12 

MENTAL HEALTH TREATMENT/COUNSELING6 

N/A N/A N/A 1.19 0.54 

 Inpatient N/A N/A N/A 0.32 0.14  Outpatient N/A N/A N/A 0.94 0.42  Prescription Medication N/A N/A N/A 1.11 0.52 

NOTES: 

*Low precision; no estimate reported. NOTE:Appalachian region is defined as all areas covered by the 410 designated counties in 13 states. N/A: No

1 Dependence or abuse is based on definitions found in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). 2 Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type psychotherapeutics used nonm3 Serious Psychological Distress (SPD) is defined as having a score of 13 or higher on the K6 scale. Due to questionnaire changes, these combined 2004 

comparable with 2004 and earlier estimates published in prior NSDUH reports. See Section B.4.4 in Appendix B of the Results from the 2005 Nationa

Health: National Findings. Estimates are based on combined 2004-2005 data.
263 

Table 2.9B Substance Dependence or Abuse, Mental Health Measures, and Receipt of Substance Use TreYear among Persons Aged 12 or Older Residing in Appalachian Region, by Age Group and Appalachian SoStatus: Standard Errors of Percentages, Annual Averages Based on 2002-2005 4 Major Depressive Episode (MDE) is defined as a period of at least 2 weeks when a person experienced a depressed mood or loss of interest or pleasure 

majority of the symptoms for depression as described in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). Estim

2004-2005 data. 

NOTES (Cont): 5 Received Substance Use Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or outpa

center in order to reduce or stop illicit drug or alcohol use, or for medical problems associated with illicit drug or alcohol use. Estimates include personspecifically for illicit drugs or alcohol, as well as persons who received treatment but did not specify for what substance(s). 6 Mental Health Treatment/Counseling is defined as having received inpatient care or outpatient care or having used prescription medication for problem

mental health. Respondents were not to include treatment for drug or alcohol use. Respondents with unknown treatment/counseling information were ebased only on responses to items in the Adult Mental Health Service Utilization module. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
264 

Table 2.10B Access to Alcohol Treatment among Persons Aged 12 or Older, by Age Group and AppalachiStandard Errors of Percentages, Annual Averages Based on 2002-2005 

Age 12-17 Age 18 or 

Appalachian 

Region

Outside 

Appalachia 

Appalachian 

Region

Access to Alcohol Treatment1,2 Needed But Not Received Alcohol  Treatment 

0.37 0.11 0.26 

 Felt Need for Alcohol Treatment 0.05 0.02 0.07  Felt Need for Alcohol Treatment and  Made No Effort 

0.03 0.02 0.05 

*Low precision; no estimate reported. NOTE: Received Alcohol Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or outp

center in order to reduce or stop alcohol use, or for medical problems associated with alcohol use. 

1 Needing But Not Receiving Treatment refers to respondents classified as needing treatment for alcohol, but have not received treatment for an alcohol 

facility (i.e., drug and alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and mental health centers). 

2 Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an alcohol problem, as well as persons who received tr

than a specialty facility but felt they needed additional treatment. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
265 

Table 2.11B Access to Drug Treatment among Persons Aged 12 or Older, by Age Group and AppalachiaStandard Errors of Percentages, Annual Averages Based on 2002-2005 

Age 12-17 Age 18 or 

Appalachian 

Region

Outside 

Appalachia 

Appalachian 

Region

O

Access to Drug Treatment1,2 Needed But Not Received Treatment  for an Illicit Drug Problem 

0.32 0.10 0.15 

 Felt Need for Treatment for an Illicit  Drug Problem 

0.06 0.02 0.05 

 Felt Need for Treatment for an Illicit  Drug Problem and Made No Effort

0.05 0.02 0.05 

*Low precision; no estimate reported. NOTE: Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type pychotherapeutics usNOTE: Received Illicit Drug Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or 

center in order to reduce or stop illicit drug use, or for medical problems associated with illicit drug use. 

1 Needing But Not Receiving Treatment refers to respondents classified as needing treatment for illicit drugs, but have not received treatment for an ill

specialty facility (i.e., drug and alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and mental health centers. 

2 Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an illicit drug problem, as well as persons who recei

other than a specialty facility but felt they needed additional treatment. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
266 

Table 2.12B Reasons for Not Receiving Substance Use Treatment and Locations of Treatment among PeOlder, by Age Group and Appalachian Region Status: Standard Errors of Percentages, Annual Averages 

Age 12-17 A

Appalachian Region Outside Appalachia Appalachian Re

Reasons for Not Receiving Drug or Alcohol Treatment among Persons Who Needed But Did Not Receive Treatment at a Specialty Facility1  Cost/Insurance Barriers2 * 3.46 *  Not Ready to Stop Using * 4.21 *  Stigma3,7 * 4.55 *  Did Not Know Where to Go for Treatment * 2.35 *  Did Not Feel Need for Treatment/Could Handle the Problem Without 

 Treatment4,7 

* 3.77 * 

 Did Not Have Time7 * 2.00 *  Treatment Would Not Help7 * 2.23 *  Other Access Barriers5 * 3.09 * Locations Where Past Year Substance Treatment was Received among Persons Who Received Treatment at a Specialty Facility6 Self-Help Group * 2.54 4.88  Outpatient Rehabilitation * 2.20 4.46  Inpatient Rehabilitation * 2.62 4.65  Mental Health Center * 2.48 5.14  Hospital Inpatient * 2.48 4.95  Private Doctor's Office * 1.73 3.63  Emergency Room * 2.01 3.35  Prison or Jail * 1.75 1.96 

*Low precision; no estimate reported. NOTE: Respondents were classified as needing treatment for an illicit drug or alcohol problem if they met at least one of three criteria during the past year: (1) dependen

(2) abuse of illicit drugs or alcohol; or (3) received treatment for an illicit drug or alcohol problem at a specialty facility (i.e., drug and alcohol rehabilitation facilities 

[inpatient only], and mental health centers). Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type p

NOTE: Needing But Not Receiving Treatment refers to respondents classified as needing treatment for illicit drugs or alcohol, but have not received treatment for an illic

specialty facility. Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an illicit drug or alcohol problem, as well as personlocation other than a specialty facility but felt they needed additional treatment. 1 Respondents could indicate multiple reasons; thus, these response categories are not mutually exclusive. 2 Includes reasons of "No health coverage and could not afford cost," "Had health coverage but did not cover treatment or did not cover cost," and other-specify response

coverage not indicated." 3 Includes reasons of "Might cause neighbors/community to have negative opinion," "Might have negative effect on job," "Did not want others to find out," and other-spe

"Ashamed/embarrassed/afraid" and "Afraid would have trouble with the police/social services." 4 Includes reasons of "Did not feel need for treatment," "Could handle the problem without treatment," and other-specify responses of "Could do it with support of family

through religion/spirituality." 5 Includes reasons of "No transportation/inconvenient," "No program having type of treatment," "No openings in a program," and other-specify responses of "No program 

you were comfortable," "Services desired were unavailable or you were currently ineligible," and "Attempted to get treatment but encountered delays." 6 Respondents could indicate multiple locations of treatment; thus, these response categories are not mutually exclusive. 7 Estimates are based only on combined 2003-2005 data. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005. 
267 

Table 2.13B Reasons for Not Receiving Mental Health Treatment among Persons Aged 12 or Older, by AAppalachian Region Status: Standard Errors of Percentages, Annual Averages Based on 2002-2005 

Age 12-17 Age 18 or 

Appalachian 

Region

Outside Appalachia Appalachian Region 

Reasons for Not Receiving Mental Health Treatment/Counseling among Persons with an Unmet Need for Mental Health Treatment1,2Cost/Insurance Barriers2 N/A N/A 2.36 Did Not Feel Need for Treatment/Could Handle the Problem Without Treatment3,7

N/A N/A 2.89 

Stigma4,7 N/A N/A 2.35 Did not Know Where to Go for Services N/A N/A 1.40 Did Not Have Time7 N/A N/A 1.80 Treatment Would Not Help5,7 N/A N/A 1.79 Fear of Being Committed/Have to Take Medicine 

N/A N/A 1.44 

Other Access Barriers6,7 N/A N/A 0.93 

*Low precision; no estimate reported. N/A: Not applicable. NOTE: Unmet Need for Mental Health Treatment/Counseling is defined as a perceived need for treatment that was not received. NOTE: Estimates represent reasons for not receiving mental health treatment/counseling for all persons aged 18 or older with an unmet need for treatment, including th

treatment/counseling information.

NOTE: Mental Health Treatment/Counseling is defined as having received inpatient care or outpatient care or having used prescription medication for problems with e

health. Respondents were not to include treatment for drug or alcohol use. Respondents with unknown treatment/counseling information were excluded. Estimaresponses to items in the Adult Mental Health Service Utilization module. 

1 Respondents could indicate multiple reasons; thus, these response categories are not mutually exclusive. 2 Includes reasons of "Could not afford," "Health insurance does not pay enough," "Health insurance does not cover mental health treatment," and other-specify response3 Includes reasons of "Did not feel need for treatment," "Could handle problem without treatment," and other-specify responses of "Work on problems with family/friend

through religion/spirituality." 

4 Includes reasons of "Might cause neighbors/community to have negative opinion," "Might have negative effect on job," "Concerned about confidentiality," "Did not wa

specify responses of "Ashamed/embarrassed/afraid," "Concerned how court system would treat me," and "Concerned how it would affect future insurability." 

5 Includes reasons of "Did not feel need for treatment," "Could handle problem without treatment," and other-specify responses of "Work on problems with family/friend

through religion/spirituality." 

6 Includes reasons of "No transportation/inconvenient" and other-specify responses of "Too much red tape/hassle to get services," "No openings/long waiting lists/delays

in area," "Attempted to get treatment but unsuccessful in finding help," and "Could not find program/counselor comfortable with." 

7 Estimates are based only on combined 2003-2005 data. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
268 

Table 2.14B Access to Alcohol Use Treatment among Persons Aged 12 or Older, by Age Group and AppRegion: Standard Errors of Percentages, Annual Averages Based on 2002-2005 

Age 12-17 Age 18 o

North Central South North Cen

Access to Alcohol Treatment1,2Needed But Not Received Alcohol Treatment 

0.43 0.88 0.66 0.37 0.54 

Felt Need for Alcohol Treatment 0.07 0.27 0.07 0.11 0.21 Felt Need for Alcohol Treatment and Made No Effort 

0.05 0.20 0.04 0.05 0.21 

*Low precision; no estimate reported. NOTE: Received Alcohol Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or ou

center in order to reduce or stop alcohol use, or for medical problems associated with alcohol use. 

1 Needing But Not Receiving Treatment refers to respondents classified as needing treatment for alcohol, but have not received treatment for an alcoh

facility (i.e., drug and alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and mental health centers). 

2 Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an alcohol problem, as well as persons who receive

other than a specialty facility but felt they needed additional treatment. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005. 
269 

Table 2.15B Access to Drug Use Treatment among Persons Aged 12 or Older, by Age Group and AppalaStandard Errors of Percentages, Annual Averages Based on 2002-2005 

Age 12-17 Age 18 

North Central South North Cen

Access to Drug Treatment1,2Needed But Not Received Treatment for an Illicit Drug Problem 

0.38 0.64 0.55 0.18 0.49 

Felt Need for Treatment for an Illicit Drug Problem 

0.08 0.15 0.08 0.06 0.23 

Felt Need for Treatment for an Illicit Drug Problem and Made No Effort 

0.05 0.15 0.08 0.05 0.23 

*Low precision; no estimate reported. NOTE: Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type pychotherapeutics uNOTE: Received Illicit Drug Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient o

health center in order to reduce or stop illicit drug use, or for medical problems associated with illicit drug use. 

1 Needing But Not Receiving Treatment refers to respondents classified as needing treatment for illicit drugs, but have not received treatment for an i

specialty facility (i.e., drug and alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and mental health centers. 

2 Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an illicit drug problem, as well as persons who rece

other than a specialty facility but felt they needed additional treatment. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005. 
270 

Table 2.16B Reasons for Not Receiving Mental Health Treatment among Persons Aged 12 or Older, by A

Appalachian Sub-Region: Standard Errors of Percentages, Annual Averages Based on 2002-2005 

Age 12-17 Age 18 o

North Central South North Cen

Reasons for Not Receiving Mental Health Treatment/Counseling among Persons with an Unmet Need for Mental Health Treatment1,2 Cost/Insurance Barriers2 N/A N/A N/A 2.86 *  Did Not Feel Need for  Treatment/Could Handle the Problem  Without Treatment3,7

N/A N/A N/A 3.42 * 

 Stigma4,7 N/A N/A N/A 3.04 *  Did not Know Where to Go for  Services 

N/A N/A N/A 1.84 * 

 Did Not Have Time7 N/A N/A N/A 2.07 *  Treatment Would Not Help5,7 N/A N/A N/A 2.46 *  Fear of Being Committed/Have to  Take Medicine 

N/A N/A N/A 1.63 2.53 

 Other Access Barriers6,7 N/A N/A N/A 1.31 * 

*Low precision; no estimate reported. N/A: Not applicable. NOTE: Unmet Need for Mental Health Treatment/Counseling is defined as a perceived need for treatment that was not received. NOTE: Estimates represent reasons for not receiving mental health treatment/counseling for all persons aged 18 or older with an unmet need for treatment, including 

health treatment/counseling information.

NOTE: Mental Health Treatment/Counseling is defined as having received inpatient care or outpatient care or having used prescription medication for problems with 

health. Respondents were not to include treatment for drug or alcohol use. Respondents with unknown treatment/counseling information were excluded. Estimresponses to items in the Adult Mental Health Service Utilization module. 

1 Respondents could indicate multiple reasons; thus, these response categories are not mutually exclusive. 2 Includes reasons of "Could not afford," "Health insurance does not pay enough," "Health insurance does not cover mental health treatment," and other-specify respons3 Includes reasons of "Did not feel need for treatment," "Could handle problem without treatment," and other-specify responses of "Work on problems with family/frien

through religion/spirituality." 

4 Includes reasons of "Might cause neighbors/community to have negative opinion," "Might have negative effect on job," "Concerned about confidentiality," "Did not w

other-specify responses of "Ashamed/embarrassed/afraid," "Concerned how court system would treat me," and "Concerned how it would affect future insurability." 

5 Includes reasons of "Did not feel need for treatment," "Could handle problem without treatment," and other-specify responses of "Work on problems with family/frien

through religion/spirituality." 

6 Includes reasons of "No transportation/inconvenient" and other-specify responses of "Too much red tape/hassle to get services," "No openings/long waiting lists/delay

in area," "Attempted to get treatment but unsuccessful in finding help," and "Could not find program/counselor comfortable with." 

7 Estimates are based only on combined 2003-2005 data. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005. 
271 

Table 2.17B Access to Alcohol Use Treatment among Persons Aged 12 or Older, by Age Group and App

Socioeconomic Status: Standard Errors of Percentages, Annual Averages Based on 2002-2005 

Age 12-17 Age 18 o

At-Risk or 

Distressed 

Transitional Competitive 

or 

Attainment

At-Risk or 

Distressed 

Transi

Access to Alcohol Treatment1,2Needed But Not Received Alcohol Treatment 

0.67 0.49 0.61 0.44 0.33 

Felt Need for Alcohol Treatment 0.25 0.05 0.08 0.14 0.07 Felt Need for Alcohol Treatment and Made No Effort 

0.17 0.03 0.03 0.12 0.07 

*Low precision; no estimate reported. NOTE: Received Alcohol Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient or ou

center in order to reduce or stop alcohol use, or for medical problems associated with alcohol use. 

1 Needing But Not Receiving Treatment refers to respondents classified as needing treatment for alcohol, but have not received treatment for an alcoh

facility (i.e., drug and alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and mental health centers). 

2 Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an alcohol problem, as well as persons who receive

other than a specialty facility but felt they needed additional treatment. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005. 
272 

Table 2.18B Access to Drug Treatment among Persons Aged 12 or Older, by Age Group and Appalachia

Status: Standard Errors of Percentages, Annual Averages Based on 2002-2005 

Age 12-17 Age 18 o

At-Risk or 

Distressed 

Transitional Competitive 

or 

Attainment

At-Risk 

or 

Distressed

Transi

Access to Drug Treatment1,2Needed But Not Received Treatment for an Illicit Drug Problem 

0.69 0.46 0.50 0.32 0.20 

Felt Need for Treatment for an Illicit Drug Problem 

0.19 0.06 0.12 0.11 0.06 

Felt Need for Treatment for an Illicit Drug Problem and Made No Effort

0.15 0.05 0.09 0.11 0.05 

*Low precision; no estimate reported. NOTE: Illicit Drugs include marijuana/hashish, cocaine (including crack), heroin, hallucinogens, inhalants, or prescription-type pychotherapeutics uNOTE: Received Illicit Drug Treatment at a Specialty Facility refers to treatment received at a hospital (inpatient), rehabilitation facility (inpatient o

health center in order to reduce or stop illicit drug use, or for medical problems associated with illicit drug use. 

1 Needing But Not Receiving Treatment refers to respondents classified as needing treatment for illicit drugs, but have not received treatment for an i

specialty facility (i.e., drug and alcohol rehabilitation facilities [inpatient or outpatient], hospitals [inpatient only], and mental health centers. 

2 Felt Need for Treatment includes persons who did not receive but felt they needed treatment for an illicit drug problem, as well as persons who rece

other than a specialty facility but felt they needed additional treatment. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005. 
273 

Table 2.19B Reasons for Not Receiving Mental Health Treatment/Counseling for Persons with an Unmet Health Treatment, by Age Group and Appalachian Socioeconomic Status: Based on 2002-2005 

Age 12-17 Age 18 

At-Risk or 

Distressed 

Transitional Competitive 

or 

Attainment

At-Risk or 

Distressed 

Trans

Reasons for Not Receiving Mental Health Treatment/Counseling among Persons with an Unmet Need for Mental Health Treatment1,2 Cost/Insurance Barriers2 N/A N/A N/A 4.29 3.2 Did Not Feel Need for Treatment/Could  Handle the Problem Without  Treatment3,7

N/A N/A N/A 5.71 3.2

 Stigma4,7 N/A N/A N/A 4.66 2.9 Did not Know Where to Go for Services N/A N/A N/A 2.27 1.9 Did Not Have Time7 N/A N/A N/A 3.26 2.4 Treatment Would Not Help5,7 N/A N/A N/A 2.16 2.0 Fear of Being Committed/Have to Take  Medicine 

N/A N/A N/A 3.67 1.6

 Other Access Barriers6,7 N/A N/A N/A 1.34 1.3

*Low precision; no estimate reported. N/A: Not applicable. NOTE: Unmet Need for Mental Health Treatment/Counseling is defined as a perceived need for treatment that was not received. NOTE: Estimates represent reasons for not receiving mental health treatment/counseling for all persons aged 18 or older with an unmet need for treatment, including tho

treatment/counseling information.

NOTE: Mental Health Treatment/Counseling is defined as having received inpatient care or outpatient care or having used prescription medication for problems with em

Respondents were not to include treatment for drug or alcohol use. Respondents with unknown treatment/counseling information were excluded. Estimates were 

in the Adult Mental Health Service Utilization module.

1 Respondents could indicate multiple reasons; thus, these response categories are not mutually exclusive. 2 Includes reasons of "Could not afford," "Health insurance does not pay enough," "Health insurance does not cover mental health treatment," and other-specify responses 

3 Includes reasons of "Did not feel need for treatment," "Could handle problem without treatment," and other-specify responses of "Work on problems with family/friends

religion/spirituality." 

4 Includes reasons of "Might cause neighbors/community to have negative opinion," "Might have negative effect on job," "Concerned about confidentiality," "Did not wan

specify responses of "Ashamed/embarrassed/afraid," "Concerned how court system would treat me," and "Concerned how it would affect future insurability." 

5 Includes reasons of "Did not feel need for treatment," "Could handle problem without treatment," and other-specify responses of "Work on problems with family/friends

religion/spirituality." 

6 Includes reasons of "No transportation/inconvenient" and other-specify responses of "Too much red tape/hassle to get services," "No openings/long waiting lists/delays," 

area," "Attempted to get treatment but unsuccessful in finding help," and "Could not find program/counselor comfortable with." 

7 Estimates are based only on combined 2003-2005 data. 

Source: SAMHSA, Office of Applied Studies, National Survey on Drug Use and Health, 2002, 2003, 2004, and 2005.
APPENDIX D: County-Level Data Profiles for Appalachian Case Studies
275 

Profile of Bath County, VA 1. Sociodemographic Characteristics 3. Access to Treatm

012345678

Percentage of Bath County 

Population

Needing but not receivin

treatment for alcohol us

Socio-Demographics Treat

Bath County Virginia 

Population, 2006 estimate 4,814 7,642,884 Population density per square mile, 2000 

9.5 178.8 

Percentage of urban population, 2000 

0% 84.9% 

Median home value, dollars, 2000 

$79,700 $125,400 

Persons below poverty, percent, 2004 

7.3% 9.5% 

High school graduates, percent of persons age 25+, 2000 

 74% 81.5% 

Sources: Population estimates from U.S. Census Bureau State & County Facts. State-level urban population variable from U.S. Department of Agriculture. All other variables from the U.S. Census Bureau, 2000. Map from www.epodunk.com. 2. Overview of Substance Abuse and Mental Health Substance Abuse or Mental Health Problem in the Past Year 

Substance Abuse and Mental Health Problems 

in the Last Year

7.82

8.59

3.06

4.94

0123456789

10

Alcohol abuse or

dependence (%)

Abuse or

dependence of

any illicit drugs

(%)

Non-prescription

use of painkillers

(%)

Serious

psychological

distress problem

(%)

Percentage of Bath County Population Bath County Virginia Alcohol abuse or dependence (%) 7.82 7.67 Abuse or dependence of any illicit drugs (%) 3.06 3.01 Non-prescription use of painkillers (%) 4.94 5.05 Serious psychological distress problem (%) 8.59 8.91 

Suicide rate (%) 0 0.018 Sources: National Survey on Drug Use and Health, 2002-2004, and the Area Resource File, 2004. 

4. Institutional ChaInstitutional Characteristics 

B

C

 % In correctional/juvenile institutions  % In mental health hospitals/institutions Proportion of mental health professional shortage area Proportion of primary care health professional shortage area Source: Area Resource File, 2004. 

Source: National Survey on Drug Use 
276 

Prepared by Zhiwei Zhang, Ph.D., Alycia Infante, M.P.A., Michael Meit, M.A., M.P.H., NORC 

 Profile of Bath County, VA 5. Cigarette Smoking and Tobacco Use 6. Alcohol Use and Binge Drinking 

 7. Marijuana and O

Cigarette Smoking and Tobacco Use (% of Bath County population) Cigarette Smoking and Tobacco Use

70.11

26.61

31.67

0 10 20 30 40 50 60 70 80

Perception of

Smoking 1 or more

packs of

cigarettes/day

Cigarette smoking,

past month

Any tobacco use,

past month

Percent of Bath County Population

 Bath 

County 

Virginia 

Any tobacco use, past month 

31.67 32.55 

Cigarette smoking, past month 

26.61 27.42 

Perceived great risk of smoking 1 or more packs of cigarettes/day 

70.11 69.72 

Sources: National Survey on Drug Use and Health, 2002-2004.

% of Adults Age 12 or OldAny illicit drug use in the pmonth Any illicit drug use other tmarijuana in the past monCocaine use in the past yea% of Adults Age 12 or OldMarijuana use, past month Marijuana use, past year Annual rate of first use of marijuana Sources: National Survey on Drug 

50.48

23.22

0

102030405060

Percent of Bath County 

Population

Alcohol, past

month

Alcohol, past

month, ages 12 - 20

Alcohol Use in Bath County Alcohol Use and Binge Drinking, 

% of Adults 12 or Older Bath County Virginia Binge D

22.9

05

1015202530354045

Binge alcohol, pas

month

Percent of Bath County Population Alcohol, past month 50.48 46.32 Alcohol, past month, ages 12 - 20 31.93 31.31 Binge alcohol, past month 22.90 22.11 Binge alcohol, past month, ages 12 - 20 23.22 23.42 Perceived great risk of binge drinking 41.18 43.07 

Sources: National Survey on Drug Use and Health, 2002-2004.
277 Pre

pared b

y Zhiwei Zhang, Ph.D., Al

ycia Infante, M.P.A., Michael Meit, M.A., M.P.H., NORC 

Profile of Bland County, VA 1. Socio-demographic Characteristics 2. Overview of Substance Abuse and Mental Health 

3.

 3. Access to Treatm

012345678

Percentage of Bland County 

Population

Needing but not receiv

treatment for alcohol u

Trea

4. Institutional Cha

Socio-Demographics Bland County Virginia Population, 2006 estimate 6,903 7,642,884 Population density per square mile, 2000 

19.1 178.8 

Percentage of urban population, 2000 

0% 84.9% 

Median home value, dollars, 2000 

$71,500 $125,400 

Persons below poverty, percent, 2004 

11.9% 9.5% 

High school graduates, percent of persons age 25+, 2000 

70.9% 81.5% 

Sources: Population estimates from U.S. Census Bureau State & County Facts. State-level urban population variable from U.S. Department of Agriculture. All other variables from the U.S. Census Bureau, 2000. Map from www.epodunk.com. 

Institutional Characteristic % In correctional/juvenile institutions  % In mental health hospitals/institutions Proportion of mental health professional shortage area Proportion of primary care health professional shortage area Source: Area Resource File, 2004. 

Substance Abuse or Mental Health Problem in the Past Year 

Substance Abuse and Mental Health Problems 

in the Last Year

7.52

9.22

2.95

5.16

0123456789

10

Alcohol abuse or

dependence (%)

Abuse or

dependence of

any illicit drugs

(%)

Non-prescription

use of painkillers

(%)

Serious

psychological

distress problem

(%)

Percentage of Bland County Population Bland County Virginia Alcohol abuse or dependence (%) 7.52 7.67 Abuse or dependence of any illicit drugs (%) 2.95 3.01 Non-prescription use of painkillers (%) 5.16 5.05 Serious psychological 

distress problem (%) 

9.22 8.91 

Suicide rate (%) 0.029 0.018 Sources: National Survey on Drug Use and Health, 2002-2004, and the Area Resource File, 2004. 

Source: National Survey on Drug Use 
278 

Prepared by Zhiwei Zhang, Ph.D., Alycia Infante, M.P.A., Michael Meit, M.A., M.P.H., NORC 

Profile of Bland County, VA 5. Cigarette Smoking and Tobacco Use 6. Alcohol Use and Binge Drinking 

 7. Marijuana and O

Cigarette Smoking and Tobacco Use (% of Bland Co. population) Cigarette Smoking and Tobacco Use

69.32

33.43

28.22

0 10 20 30 40 50 60 70 80

Perception of

Smoking 1 or more

packs of

cigarettes/day

Cigarette smoking,

past month

Any tobacco use,

past month

Percent of Bland County Population

 Bland 

County 

Virginia 

Any tobacco use, past month 

33.43 32.55 

Cigarette smoking, past month 

28.22 27.42 

Perceived great risk of smoking 1 or more packs of cigarettes/day 

69.32 69.72 

Sources: National Survey on Drug Use and Health, 2002-2004.

% of Adults Age 12 or OldAny illicit drug use in the pmonth Any illicit drug use other tmarijuana in the past monCocaine use in the past yea% of Adults Age 12 or OldMarijuana use, past month Marijuana use, past year Annual rate of first use of marijuana Sources: National Survey on Drug 

42.15

30.69

05

1015202530354045

Percent of Bland County 

Population

Alcohol, past

month

Alcohol, past

month, ages 12 -

20

Alcohol Use in Bland County Alcohol Use and Binge Drinking, 

% of Adults 12 or Older Bland County Virginia Binge D

21.32 

05

101520253035404550

Binge alcohol, pas

month

Percent of Bland County Population Alcohol, past month 42.15 46.32 Alcohol, past month, ages 12 - 20 30.69 31.31 Binge alcohol, past month 21.32 22.11 Binge alcohol, past month, ages 12 - 20 23.61 23.42 Perceived great risk of binge 

drinking 

44.95 43.07 

Sources: National Survey on Drug Use and Health, 2002-2004.
279 

Pre

pared b

y Zhiwei Zhang, Ph.D., Al

ycia Infante, M.P.A., Michael Meit, M.A., M.P.H., NORC 

Profile of Hardy County, WV 1. Socio-demographic Characteristics 2. Overview of Substance Abuse and Mental Health 

3.

 3. Access to Treatm

-

1.002.003.004.005.006.00

Percentage of Hardy County 

Population

Needing but not rec

treatment for alcoho

Trea

4. Institutional Cha

Socio-Demographics Hardy County West Virginia Population, 2006 estimate 13,420 1,818,470 Population density per square mile, 2000 

21.7 75.1 

Percentage of urban population, 2000 

0% 55.18% 

Median home value, dollars, 2000 

$74,700 $ 72,800 

Persons below poverty, percent, 2004 

12.5% 16.2% 

High school graduates, percent of persons age 25+, 2000 

70.3% 75.2% 

Sources: Population estimates from U.S. Census Bureau State & County Facts. State-level urban population variable from U.S. Department of Agriculture. All other variables from the U.S. Census Bureau, 2000. Map from www.epodunk.com. 

Institutional Characteristic % In correctional/juvenile institutions  % In mental health hospitals/institutions Proportion of mental health professional shortage area Proportion of primary care health professional shortage area Source: Area Resource File, 2004. 

Substance Abuse or Mental Health Problem in the Past Year 

Substance Abuse and Mental Health Problems 

in the Last Year

6.39

11.07

2.77

4.54

02468

1012

Alcohol abuse or

dependence (%)

Abuse or

dependence of

any illicit drugs

(%)

Non-prescription

use of painkillers

(%)

Serious

psychological

distress problem

(%)

Percentage of Hardy County Population Hardy County West Virginia Alcohol abuse or dependence (%) 6.39 6.93 Abuse or dependence of any illicit drugs (%) 2.77 3.08 Non-prescription use of painkillers (%) 4.54 5.67 Serious psychological 

distress problem (%) 

11.07 12.26 

Suicide rate (%) 0.0079 0.013 Sources: National Survey on Drug Use and Health, 2002-2004, and the Area Resource File, 2004. 

Source: National Survey on Drug Use 
280 

Prepared by Zhiwei Zhang, Ph.D., Alycia Infante, M.P.A., Michael Meit, M.A., M.P.H., NORC 

Profile of Hardy County, WV 5. Cigarette Smoking and Tobacco Use 6. Alcohol Use and Binge Drinking 

 7. Marijuana and O

Cigarette Smoking and Tobacco Use (% of Hardy County population) Cigarette Smoking and Tobacco Use

29.74

37.88

67.73

0 10 20 30 40 50 60 70 80

Perception of

Smoking 1 or more

packs of

cigarettes/day

Cigarette smoking,

past month

Any tobacco use,

past month

Percent of Hardy County Population

 Hardy 

County 

West 

Virginia 

Any tobacco use, past month 

37.88 38.45 

Cigarette smoking, past month 

29.74 30.76 

Perceived great risk of smoking 1 or more packs of cigarettes/day 

67.73 67.36 

Sources: National Survey on Drug Use and Health, 2002-2004.

% of Adults Age 12 or OldAny illicit drug use in the pmonth Any illicit drug use other tmarijuana in the past monCocaine use in the past yea% of Adults Age 12 or OldMarijuana use, past month Marijuana use, past year Annual rate of first use of marijuana Sources: National Survey on Drug 

39.05

29.15

05

10152025303540

Percent of Hardy County 

Population

Alcohol, past

month

Alcohol, past

month, ages 12 -

20

Alcohol Use in Hardy County Alcohol Use and Binge Drinking, 

% of Adults 12 or Older Hardy County West Virginia Binge D

19.65 

05

1015202530354045

Binge alcohol, pas

month

Percent of Hardy County Population Alcohol, past month 39.05 36.00 Alcohol, past month, ages 12 - 20 29.15 28.14 Binge alcohol, past month 19.65 19.38 Binge alcohol, past month, ages 12 - 20 21.05 21.17 Perceived great risk of binge 

drinking 

41.64 41.51 

Sources: National Survey on Drug Use and Health, 2002-2004.
281 

Pre

pared b

y Zhiwei Zhang, Ph.D., Al

ycia Infante, M.P.A., Michael Meit, M.A., M.P.H., NORC 

Profile of Monroe County, WV 1. Socio-demographic Characteristics 2. Overview of Substance Abuse and Mental Health 

3.

 3. Access to Treatm

01234567

Percentage of Monroe County 

Population

Needing but not rece

treatment for alcoho

Tre

4. Institutional Cha

Socio-Demographics Monroe County West Virginia Population, 2006 estimate 13,510 1,818,470 Population density per square mile, 2000 

30.8 75.1 

Percentage of urban population, 2000 

 10.3% 55.18% 

Median home value, dollars, 2000 

$64,700 $72,800 

Persons below poverty, percent, 2004 

14.3% 16.2% 

High school graduates, percent of persons age 25+, 2000 

73.7% 75.2% 

Sources: Population estimates from U.S. Census Bureau State & County Facts. State-level urban population variable from U.S. Department of Agriculture. All other variables from the U.S. Census Bureau, 2000. Map from www.epodunk.com. 

Institutional Characteristic % In correctional/juvenile institutions  % In mental health hospitals/institutions Proportion of mental health professional shortage area Proportion of primary care health professional shortage area Source: Area Resource File, 2004. 

Substance Abuse or Mental Health Problem in the Past Year 

Substance Abuse and Mental Health Problems 

in the Last Year

6.88

13.66

3.33

6.58

02468

10121416

Alcohol abuse or

dependence (%)

Abuse or

dependence of

any illicit drugs

(%)

Non-prescription

use of painkillers

(%)

Serious

psychological

distress problem

(%)

Percentage of Monroe County Population Monroe County West Virginia Alcohol abuse or dependence (%) 6.88 6.93 Abuse or dependence of any illicit drugs (%) 3.33 3.08 Non-prescription use of painkillers (%) 6.58 5.67 Serious psychological distress problem (%) 13.66 12.26 

Suicide rate (%) 0.014 0.013 Sources: National Survey on Drug Use and Health, 2002-2004, and the Area Resource File, 2004. 

Source: National Survey on Drug Use 
282 

Prepared by Zhiwei Zhang, Ph.D., Alycia Infante, M.P.A., Michael Meit, M.A., M.P.H., NORC 

Profile of Monroe County, WV 5. Cigarette Smoking and Tobacco Use 6. Alcohol Use and Binge Drinking 

 7. Marijuana and O

Cigarette Smoking and Tobacco Use (% of Monroe County population) Cigarette Smoking and Tobacco Use

31.59

39.45

66.6

0 10 20 30 40 50 60 70

Perception of

Smoking 1 or more

packs of

cigarettes/day

Cigarette smoking,

past month

Any tobacco use,

past month

Percent of Monroe County Population

 Monroe 

County 

West 

Virginia 

Any tobacco use, past month 

39.45 38.45 

Cigarette smoking, past month 

31.59 30.76 

Perceived great risk of smoking 1 or more packs of cigarettes/day 

66.60 67.36 

Sources: National Survey on Drug Use and Health, 2002-2004.

% of Adults Age 12 or OldAny illicit drug use in the pmonth Any illicit drug use other tmarijuana in the past monCocaine use in the past yea% of Adults Age 12 or OldMarijuana use, past month Marijuana use, past year Annual rate of first use of marijuana Sources: National Survey on Drug 

28.58

24.73

2223242526272829

Percent of Monroe 

County Population

Alcohol, past

month

Alcohol, past

month, ages 12 -

20

Alcohol Use in Monroe County Alcohol Use and Binge Drinking, 

% of Adults 12 or Older Monroe County West Virginia Binge Dr

17.39 

05

101520253035404550

Binge alcohol, pas

month

Percent of Monroe County Population Alcohol, past month 28.58 36.00 Alcohol, past month, ages 12 - 20 24.73 28.14 Binge alcohol, past month 17.39 19.38 Binge alcohol, past month, ages 12 - 20 18.96 21.17 Perceived great risk of binge drinking 43.30 41.51 

Sources: National Survey on Drug Use and Health, 2002-2004.
283 

Pre

pared b

y Zhiwei Zhang, Ph.D., Al

ycia Infante, M.P.A., Michael Meit, M.A., M.P.H., NORC 

Profile of Morgan County, KY 1. Socio-demographic Characteristics 2. Overview of Substance Abuse and Mental Health 

3. Access to Treat

0123456

Percent of Morgan County 

Population

Needing but n

receiving

treatment fo

alcohol use

Treatme

4. Institutional Cha

Socio-Demographics Morgan County Kentucky Population, 2006 estimate 14,306 4,206,074 Population density per square mile, 2000 

36.6 101.7 

Percentage of urban population, 2000 

20.7% 18.3% 

Median home value, dollars, 2000 

$55,400 $86,700 

Persons below poverty, percent, 2004 

27% 16.3% 

High school graduates, percent of persons age 25+, 2000 

56.4 74.1 

Sources: Population estimates from U.S. Census Bureau State & County Facts. All other variables from the U.S. Census Bureau, 2000, unless otherwise indicated. Map from www.epodunk.com. 

Institutional Characteristic % In correctional/juvenile institutions  % In mental health hospitals/institutions Proportion of mental health professional shortage area Proportion of primary care health professional shortage area Source: Area Resource File, 2004. 

Substance Abuse or Mental Health Problem in the Past Year Substance Abuse and Mental Health Problems in the Last Year

3.37

5.95 6.83

12.61

02468

101214

 % Alcohol

abuse or

dependence

 % Abuse or

dependence of

any illicit drugs

 % Nonprescription use

of painkillers

 % Serious

psychological

distressproblem

Percent of Morgan County Population

 Morgan 

County 

Kentucky 

Alcohol abuse or dependence (%) 

5.95 6.47 

Abuse or dependence of any illicit drugs (%) 

3.37 3.11 

Non-prescription use of painkillers (%) 

6.83 6.79 

Serious psychological distress problem (%) 

12.61 11.37 

Suicide rate 0.0215 0.0153 Sources: National Survey on Drug Use and Health, 2002-2004, and the Area Resource File, 2004. 

Source: National Survey on Drug Use 
284 

Prepared by Zhiwei Zhang, Ph.D., Alycia Infante, M.P.A., Michael Meit, M.A., M.P.H., NORC 

Profile of Morgan County, KY 5. Cigarette Smoking and Tobacco Use 6. Alcohol Use and Binge Drinking 

 7. Marijuana and O

Cigarette Smoking and Tobacco Use (% of Morgan Co. population) Cigarette Smoking and Tobacco Use

43.42

37.54

61.67

0 10 20 30 40 50 60 70

Perceived great risk of smoking 1 or

more packs of cigarettes/day

Cigarette smoking, past month

Any tobacco use, past month

Percent of Morgan County Population

 Morgan 

County 

Kentucky 

Any tobacco use, past month 

43.42 40.06 

Cigarette smoking, past month 

37.54 34.55 

Perceived great risk of smoking 1 or more packs of cigarettes/day 

61.67 62.15 

Sources: National Survey on Drug Use and Health, 2002-2004.

30.06

26.8

25

25.5

26

26.5

27

27.5

28

28.5

29

29.5

30

30.5

Percent of Morgan County 

Population

Alcohol, past month Alcohol, past month,

ages 12 - 20

Alcohol Use in Morgan County % of Adults 12 or Older Who Had 

Alcohol Use and Binge Drinking Morgan County Kentucky Binge Drin

18.75 

05

101520253035404550

Binge alcohol,

past month

Percent of Morgan County Population Alcohol, past month 30.06 36.15 Alcohol, past month, ages 12 - 20 26.80 27.60 Binge alcohol, past month 18.75 19.26 Binge alcohol, past month, ages 12 - 20 20.20 18.79 Perceived great risk of binge 

drinking 

43.92 42.85 

Sources: National Survey on Drug Use and Health, 2002-2004..

% of Adults Age 12 or OldAny illicit drug use in the pmonth Any illicit drug use other tmarijuana in the past monCocaine use in the past yea% of Adults Age 12 or OldMarijuana use, past month Marijuana use, past year Annual rate of first use of marijuana Sources: National Survey on Drug 
285 Pre

pared b

y Zhiwei Zhang, Ph.D., Al

ycia Infante, M.S., Michael Meit, M.S., NORC 

Profile of Wayne County, KY 1. Socio-demographic Characteristics 2. Overview of Substance Abuse and Mental Health 

3. Access to Treat

0123456

Percent of Wayne County 

Population

Needing but no

receiving

treatment for

alcohol use

Treatmen

4. Institutional Cha

Socio-Demographics Wayne 

County 

Kentucky 

Population, 2006 estimate 20,504 4,206,074 Population density per square mile, 2000 

43.4 101.7 

Percentage of urban population, 2000 

31.1% 18.3% 

Median home value, dollars, 2000 

$55,400 $86,700 

Persons below poverty, percent, 2004 

23.4% 16.3% 

High school graduates, percent of persons age 25+, 2000 

57.8% 74.1% 

Sources: Population estimates from U.S. Census Bureau State & County Facts. All other variables from the U.S. Census Bureau, 2000, unless otherwise indicated. Map from www.epodunk.com. Substance Abuse or Mental Health Problem in the Past Year Substance Abuse and Mental Health Problems in the Last Year

2.74

6.03

5.85

11.4

02468

1012

 % Alcohol

abuse or

dependence

 % Abuse or

dependence of

any illicit drugs

 % Nonprescription use

of painkillers

 % Serious

psychological

distressproblem

Percent of Wayne County Population

 Wayne 

County 

Kentucky 

Alcohol abuse or dependence (%) 

6.03 6.47 

Abuse or dependence of any illicit drugs (%) 

2.74 3.11 

Non-prescription use of painkillers (%) 

5.85 6.79 

Serious psychological distress problem (%) 

11.40 11.37 

Suicide rate 0.0100 0.0153 Sources: National Survey on Drug Use and Health, 2002-2004, and the Area Resource File, 2004. 

Institutional Characteristic% In correctional/ juvenile institutions % In mental health hospitals/institutions Proportion of mental health professional shortage area Proportion of primary care health professional shortage area Source: Area Resource File, 2004. 

Source: National Survey on Drug Use 
286 

Prepared by Zhiwei Zhang, Ph.D., Alycia Infante, M.S., Michael Meit, M.S., NORC 

Profile of Wayne County 5. Cigarette Smoking and Tobacco Use 6. Alcohol Use and Binge Drinking 

 7. Marijuana and 

Cigarette Smoking and Tobacco Use (% of Wayne Co. population) Cigarette Smoking and Tobacco Use

60.74

34.25

40.65

0 10 20 30 40 50 60 70

Perception of

Smoking 1 or more

packs of

cigarettes/day

Cigarette smoking,

past month

Any tobacco use,

past month

Percent of Wayne County Population

 Wayne 

County 

Kentucky 

Any tobacco use, past month 

 40.65 40.06 

Cigarette smoking, past month 

34.25 34.55 

Perceived great risk of smoking 1 or more packs of cigarettes/day 

60.74 62.15 

Sources: National Survey on Drug Use and Health, 2002-2004..

32.01

25.72

05

101520253035

Percent of Wayne County 

Population

Alcohol, past month Alcohol, past month,

ages 12 - 20

Alcohol Use in Wayne County % of Adults 12 or Older Who Had 

Alcohol Use and Binge Drinking Wayne County Kentucky Binge Drin

17.71 

05

101520253035404550

Binge alcohol,

past month

Percent of Wayne County Population Alcohol, past month 32.01 36.15 Alcohol, past month, age 12 - 20 25.72 27.60 Binge alcohol use in past month 17.71 19.26 Binge alcohol use in past month, age 12- 20 17.59 18.79 Perceived great risk of binge 

drinking 

43.89 42.85 

Sources: National Survey on Drug Use and Health, 2002-2004.

% of Adults Age 12 or OldAny illicit drug use in the pmonth Any illicit drug use other tmarijuana in the past monCocaine use in the past yea% of Adults Age 12 or OldMarijuana use, past month Marijuana use, past year Annual rate of first use of marijuana Sources: National Survey on Drug 
287 

 

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 Halverson JA, Byrd RC, Ma L, Harner EJ. November 2004. An Analysis of Disparities in Health Status and Access 

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 Maine Rural Health Research Center. June 2007. Substance Abuse Among Rural Youth: A Little Meth and a Lot of 

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 Robertson EB, Sloboda Z, Boyd GM, Beatty L and Kozel NJ, eds. 1997. Rural Substance Abuse: State of Knowledge 

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 Logan TK, Schenck JE, Leukefeld CG, Meyers J and Allen S. 1999. Rural Attitudes, Opinions and Drug Use. 

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 Keefe S. (2005). Appalachian Cultural Competency: A Guide For Medical, Mental Health, And Social Service 

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http://www.oas.samhsa.gov/nhsda/2k2nsduh/Results/appB.htm. 

18 Whitbeck K, Johnson D, HA Cauce. 1998. Mental disorder and comorbidity among runaway and homeless 

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19 Bailey SL, Camlin CS, Ennett ST. 1998. Substance use and risky behavior among homeless and runaway youth. 

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http://www.oas.samhsa.gov/nhsda/2k2nsduh/Results/appB.htm. 

21 Gfroerer J, Epstein J, Wright D. August 2004. Estimating substance abuse treatment need by state. Editorial in 

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23 Office of Applied Studies. 2006. Substate estimates from the 2002-2004 National Surveys on Drug Use and Health. 

Rockville, MD: Substance Abuse and Mental Health Services Administration. 

24 Marker D. 2001. Producing small area estimates from national surveys: methods for minimizing use of indirect 

estimators. Survey Methodology, 27, 2, 183-188. 
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 25 U.S. Dept. of Health and Human Services, Substance Abuse and Mental Health Services Administration, Office of 

Applied Studies. TREATMENT EPISODE DATA SET (TEDS), 2004, Chapter 1. Prepared by Synectics for 

Management Decisions, Incorporated. ICPSR04626-v1. Ann Arbor, MI: Inter-university Consortium for Political and 

Social Research [producer and distributor], 2007-02-22. 

http://www.oas.samhsa.gov/TEDSdischarges/2k4/TEDSD2k4Chp1.htm#limit 26 U.S. Dept. of Health and Human Services, Substance Abuse and Mental Health Services Administration, Office of 

Applied Studies. http://www.oas.samhsa.gov/dasis.htm. 

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28 Treatment Episode Data Set (TEDS), 2005. Substance Abuse and Mental Health Data Archive. Study No. 4626. 

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