National and State Estimates of Drug Abuse Treatment Gap

Chapter 3. Estimates of the Treatment Gap, by State

This chapter presents State estimates of the percentages and numbers of persons needing but not receiving treatment for illicit drug use (see Tables 6 to 9 at the end of the chapter). The following discusses how the State estimates of the treatment gap are calculated. A more detailed discussion of this process is provided in Appendix B of this report.

For each respondent in the sample, one can determine whether a person needed but did not receive treatment for an illicit drug problem based on the following definition: An individual was counted in the treatment gap if he or she was dependent on or had abused an illicit drug but had not received treatment for his or her illicit drug problem at a "specialty" substance abuse facility in the past 12 months (i.e., in the 12 months before being interviewed). "Specialty" substance abuse facilities include drug and alcohol rehabilitation facilities (inpatient or outpatient), hospitals (inpatient only), and mental health centers.

The State estimates are based on a model that has essentially two components. One component is a national model using data from the 2000 National Household Survey on Drug Abuse (NHSDA). The national model includes demographic information (such as age and race), socioeconomic information on the local area (such as the percentage below the poverty level), and information specific to drug use (such as the marijuana possession arrest rate for the county). The information used in the national model is available at the Census block, Census tract, or county level.

The second component of the model is the information collected from the NHSDA respondents in each State. This direct sample component adjusts the results to reflect State- and local-level differences. These two components together produce the final estimate. In effect, for each State, two estimates of the treatment gap—one from a national model and one from just the sample data from the State—are combined to make the best estimate for the State. If a State is represented in the survey by a relatively small sample, and the direct sample estimate from the State is subject to significant sampling variation, more weight is given to the national component.

When the process is complete, the results are validated by comparing the estimates produced by the model with estimates based entirely on the sample data. This is done for areas having very large samples that can be assumed to produce "accurate" estimates without the need for models. The validation results showed that the model-based estimates for all persons aged 12 or older were quite accurate compared with the true (gold standard) State value—on average,within about 4 percent of the true value. For example, if the true value in a State was 2 percent, the estimate would typically be within 0.08 of a percent of the true value.

The final set of State estimates also comes with a corresponding set of interval estimates within which the true State value will fall 95 percent of the time. For example, the estimate of the percentage treatment gap for the State of Idaho, for persons aged 12 or older, is 1.81 percent, with a prediction interval of (1.41, 2.28). Therefore, the probability is 95 percent that the true value for Idaho lies between 1.41 and 2.28 percent. The model-based estimates were also more precise than the corresponding survey-based estimates based on the sample only. The prediction intervals were on average 45 percent smaller (better) than the corresponding confidence intervals (CIs) around the strictly sample-based estimates. This superior precision is equivalent to an effective sample size of 3,300 as opposed to the true design-based sample size of 1,000. Comparisons for the specific age groups are provided in Appendix B.

A national map (Figure 3) illustrates the distribution of State estimates of the percentage treatment gap into "fifths" from lowest to highest. States with the highest treatment gap as a percentage of their population fall into the top quintile and are in red. States with the lowest treatment gaps are in the bottom quintile and are in white.¹ Typically, most States cluster around the national average, and some may only differ by a fraction of a percent. Therefore, it is important to consider the interval in determining the relative ranking of States.

Nationally, 1.74 percent of persons aged 12 or older needed treatment but did not receive it in the past year.²

• Of the 10 States with the highest percentage treatment gaps, 6 were Western States and 3 were Northeastern States. Arizona had the highest percentage treatment gap of 2.29 percent.

Figure 3 Percentages of Persons Aged 12 or Older Needing But Not Receiving Treatment for an Illicit Drug Problem in the Past Year, by State: 2000

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 2000.

Figure 4 Numbers of Persons Aged 12 or Older Needing But Not Receiving Treatment for an Illicit Drug Problem in the Past Year, by State: 2000

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 2000.

• Although the 12 to 25 age group represented only about 23 percent of the total population aged 12 or older, nationally it constituted the majority of the treatment gap. About 62 percent of all persons in the gap were in this age group. The 12 to 25 age group constituted anywhere from 51 percent (Washington) to 73 percent (Idaho) of the total number of persons in the treatment gap, depending on the State. Most of the States in the highest group for the treatment gap percentage had proportions of 12 to 25 year olds comprising their treatment gap that were lower than the national average.

• In the lowest fifth, five States were Southern States, and four were Midwestern. The State with the lowest treatment gap for ages 12 or older was Iowa with an estimate of 1.37 percent of the population.

• Generally, as might be expected, States with larger populations had the largest estimated number of persons in the treatment gap. California had the largest number of persons in the gap, approximately 564,000, representing 14.1 percent of the national gap for persons 12 or older. The other States with large treatment gap counts were Texas (288,000), New York (285,000), Florida (196,000), Illinois (164,000), Pennsylvania (160,000), Ohio (150,000), Michigan (138,000), New Jersey (110,000), and Georgia (110,000).

• Because the range in State population sizes was larger than the range in the estimated State treatment gap percentages, the population size had a dominant impact on the treatment gap counts. Variations in the State percentage gap, however, resulted in significant differences among States of a similar size. For example, Arizona and Alabama had similar population sizes in 2000; however, for persons aged 12 or older, Arizona had a larger treatment gap (89,000) than Alabama (61,000) because of its higher treatment gap percentage (2.29 vs. 1.66 percent).

These State-level estimates of the drug abuse treatment gap provide an important tool for treatment planners and policymakers at the Federal, State, and local levels. They represent the first available State estimates of the gap using a consistent methodology to allow valid comparisons across States. Although it is difficult to accurately measure characteristics affecting less than 2 percent of the population, the methodology used was able to identify significant variation in the treatment gap by State. The estimates ranged from as low as 1.37 percent up to 2.29 percent of the States' populations aged 12 or older, indicating very real differences in the unmet treatment need across States. In an average-sized State, such as Maryland, this size difference represents tens of thousands of persons.

The treatment gap estimates give a single measure of the illicit drug problem in each State. More detailed assessments of problems at the State level, such as analysis of demographic differences and access to care, are not possible with these data. These issues can only be studied with the NHSDA at the national level. Interpretation of State-level patterns in the treatment gap can also be aided by using these estimates in conjunction with other measures produced at the State level from the NHSDA, such as rates of current use, initiation, and perceived risk of harm for illicit drugs and also for alcohol and tobacco.

Table 6. Percentages of Persons Aged 12 or Older Needing But Not Receiving Treatment for an Illicit Drug Problem in the Past Year, by State, Ranked from Highest to Lowest: 2000

Note: Estimates are based on a survey-weighted hierarchical Bayes estimation approach, and the prediction (credible) intervals are generated by Markov Chain Monte Carlo techniques. Horizontal rules refer to quintile divisions shown in Figure 3.

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 2000.

Table 7. Estimated Numbers of Persons Aged 12 or Older Needing But Not Receiving Treatment for an Illicit Drug Problem in the Past Year, by State, Ranked from Highest to Lowest: 2000

Note: Estimates are based on a survey-weighted hierarchical Bayes estimation approach, and the prediction (credible) intervals are generated by Markov Chain Monte Carlo techniques. Horizontal rules refer to quintile divisions shown in Figure 4.

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 2000.

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Table 8. Percentages of Persons Aged 12 or Older Needing But Not Receiving Treatment for an Illicit Drug Problem in the Past Year, by State: 2000

State	Total				Age Group (Years)
					12-17				18-25				26 or Older
	Estimate	Prediction Interval			Estimate	Prediction Interval			Estimate	Prediction Interval			Estimate	Prediction Interval
Total1	1.79				4.12				5.22				0.89
Alabama	1.66	(1.26	-	2.15)	3.52	(2.32	-	5.13)	5.64	(3.94	-	7.79)	0.75	(0.41	-	1.25)
Alaska	2.12	(1.56	-	2.80)	4.60	(2.91	-	6.90)	4.83	(3.26	-	6.86)	1.14	(0.59	-	1.98)
Arizona	2.29	(1.60	-	3.18)	4.50	(3.06	-	6.36)	5.02	(3.49	-	6.96)	1.48	(0.74	-	2.65)
Arkansas	1.58	(1.22	-	2.00)	4.23	(2.94	-	5.88)	5.15	(3.65	-	7.04)	0.62	(0.33	-	1.07)
California	2.19	(1.79	-	2.65)	5.16	(4.29	-	6.15)	4.90	(3.92	-	6.04)	1.26	(0.82	-	1.86)
Colorado	2.09	(1.55	-	2.75)	4.52	(3.08	-	6.36)	5.36	(3.71	-	7.45)	1.18	(0.64	-	2.00)
Connecticut	1.92	(1.45	-	2.49)	5.28	(3.54	-	7.54)	6.54	(4.54	-	9.06)	0.86	(0.47	-	1.45)
Delaware	1.76	(1.30	-	2.31)	4.24	(2.95	-	5.88)	4.73	(3.23	-	6.66)	0.95	(0.52	-	1.61)
District of Columbia	2.08	(1.53	-	2.78)	4.21	(2.69	-	6.27)	4.84	(3.27	-	6.88)	1.29	(0.71	-	2.15)
Florida	1.55	(1.26	-	1.87)	4.04	(3.14	-	5.11)	5.21	(4.14	-	6.47)	0.76	(0.48	-	1.15)
Georgia	1.73	(1.31	-	2.23)	4.01	(2.83	-	5.50)	4.86	(3.40	-	6.72)	0.85	(0.46	-	1.44)
Hawaii	1.73	(1.15	-	2.48)	5.29	(3.40	-	7.82)	3.80	(2.45	-	5.60)	0.97	(0.41	-	1.95)
Idaho	1.81	(1.41	-	2.28)	4.17	(2.82	-	5.93)	5.48	(3.91	-	7.44)	0.67	(0.38	-	1.09)
Illinois	1.68	(1.38	-	2.03)	3.51	(2.72	-	4.44)	5.00	(3.99	-	6.18)	0.86	(0.55	-	1.27)
Indiana	1.66	(1.28	-	2.10)	3.75	(2.56	-	5.30)	5.40	(3.86	-	7.32)	0.71	(0.41	-	1.17)
Iowa	1.37	(1.02	-	1.82)	3.20	(2.04	-	4.77)	4.42	(2.94	-	6.36)	0.59	(0.32	-	1.01)
Kansas	1.63	(1.20	-	2.16)	3.01	(1.88	-	4.57)	4.58	(3.14	-	6.44)	0.90	(0.50	-	1.51)
Kentucky	1.63	(1.26	-	2.07)	4.00	(2.76	-	5.59)	5.24	(3.68	-	7.22)	0.70	(0.39	-	1.15)
Louisiana	1.83	(1.44	-	2.31)	3.99	(2.73	-	5.61)	5.57	(3.95	-	7.61)	0.75	(0.41	-	1.25)
Maine	1.80	(1.38	-	2.29)	5.31	(3.57	-	7.58)	6.23	(4.32	-	8.65)	0.70	(0.38	-	1.18)
Maryland	1.89	(1.40	-	2.48)	4.71	(3.25	-	6.59)	5.26	(3.65	-	7.31)	1.02	(0.54	-	1.75)
Massachusetts	2.11	(1.56	-	2.79)	5.59	(3.87	-	7.79)	6.00	(4.23	-	8.23)	1.09	(0.58	-	1.88)
Michigan	1.74	(1.46	-	2.05)	4.14	(3.27	-	5.15)	6.00	(4.82	-	7.36)	0.68	(0.43	-	1.02)
Minnesota	1.90	(1.43	-	2.49)	4.29	(2.99	-	5.94)	4.97	(3.46	-	6.91)	1.02	(0.54	-	1.74)
Mississippi	1.63	(1.25	-	2.09)	3.27	(2.16	-	4.75)	5.12	(3.56	-	7.10)	0.72	(0.41	-	1.18)
Missouri	1.48	(1.11	-	1.94)	3.16	(2.03	-	4.68)	4.61	(3.17	-	6.47)	0.72	(0.38	-	1.24)
Montana	1.60	(1.22	-	2.05)	4.68	(3.07	-	6.79)	4.63	(3.21	-	6.43)	0.65	(0.35	-	1.09)
Nebraska	1.61	(1.23	-	2.06)	3.38	(2.20	-	4.95)	5.15	(3.64	-	7.05)	0.71	(0.38	-	1.20)
Nevada	1.81	(1.36	-	2.35)	4.65	(3.09	-	6.70)	5.27	(3.64	-	7.35)	0.94	(0.54	-	1.53)
New Hampshire	1.97	(1.52	-	2.51)	6.25	(4.19	-	8.94)	5.82	(4.08	-	8.01)	0.81	(0.45	-	1.35)
New Jersey	1.64	(1.24	-	2.13)	3.48	(2.35	-	4.94)	5.70	(3.99	-	7.85)	0.82	(0.45	-	1.39)
New Mexico	1.73	(1.31	-	2.24)	4.33	(2.86	-	6.28)	4.20	(2.88	-	5.89)	0.85	(0.47	-	1.42)
New York	1.93	(1.58	-	2.33)	3.34	(2.52	-	4.34)	6.89	(5.54	-	8.44)	0.96	(0.61	-	1.42)
North Carolina	1.55	(1.17	-	2.02)	3.05	(2.03	-	4.40)	5.02	(3.58	-	6.83)	0.81	(0.44	-	1.36)
North Dakota	1.49	(1.14	-	1.92)	3.64	(2.39	-	5.29)	4.09	(2.76	-	5.83)	0.66	(0.35	-	1.12)
Ohio	1.62	(1.33	-	1.94)	3.62	(2.80	-	4.60)	5.11	(4.09	-	6.28)	0.76	(0.48	-	1.13)
Oklahoma	1.58	(1.20	-	2.06)	3.31	(2.15	-	4.86)	4.81	(3.34	-	6.69)	0.76	(0.42	-	1.27)
Oregon	1.92	(1.42	-	2.54)	5.03	(3.46	-	7.04)	5.52	(3.87	-	7.61)	0.98	(0.50	-	1.72)
Pennsylvania	1.58	(1.32	-	1.88)	3.05	(2.33	-	3.93)	6.13	(4.94	-	7.49)	0.72	(0.47	-	1.07)
Rhode Island	1.70	(1.29	-	2.19)	4.08	(2.75	-	5.81)	5.58	(3.88	-	7.75)	0.82	(0.47	-	1.34)
South Carolina	1.54	(1.16	-	2.01)	4.11	(2.73	-	5.93)	4.48	(3.05	-	6.34)	0.73	(0.40	-	1.23)
South Dakota	1.49	(1.13	-	1.92)	3.79	(2.40	-	5.68)	4.27	(2.93	-	5.99)	0.60	(0.32	-	1.02)
Tennessee	1.69	(1.29	-	2.17)	4.76	(3.29	-	6.64)	5.10	(3.52	-	7.11)	0.74	(0.40	-	1.24)
Texas	1.79	(1.49	-	2.14)	4.72	(3.78	-	5.82)	4.50	(3.55	-	5.61)	0.78	(0.47	-	1.23)
Utah	2.11	(1.59	-	2.75)	3.38	(2.22	-	4.92)	4.91	(3.38	-	6.87)	1.06	(0.57	-	1.81)
Vermont	1.92	(1.48	-	2.44)	4.56	(2.98	-	6.65)	6.34	(4.62	-	8.46)	0.84	(0.48	-	1.38)
Virginia	1.55	(1.16	-	2.04)	3.54	(2.47	-	4.91)	4.37	(2.97	-	6.19)	0.86	(0.47	-	1.44)
Washington	1.97	(1.39	-	2.71)	4.39	(2.98	-	6.21)	4.37	(2.87	-	6.34)	1.26	(0.62	-	2.26)
West Virginia	1.47	(1.10	-	1.92)	3.96	(2.70	-	5.60)	4.58	(3.10	-	6.49)	0.69	(0.38	-	1.16)
Wisconsin	1.71	(1.34	-	2.15)	4.44	(3.13	-	6.11)	5.30	(3.75	-	7.25)	0.71	(0.39	-	1.17)
Wyoming	1.61	(1.22	-	2.10)	3.12	(1.94	-	4.75)	5.03	(3.48	-	7.00)	0.72	(0.39	-	1.22)

Note: Estimates are based on a survey-weighted hierarchical Bayes estimation approach, and the prediction (credible) intervals are generated by Markov Chain Monte Carlo techniques.

¹ This estimate is the sum of the hierarchical Bayes estimates across all States and the District of Columbia and typically is not equal to the direct sample-weighted estimate for the Nation.

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 2000.

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Table 9. Estimated Numbers of Persons Aged 12 or Older Needing But Not Receiving Treatment for an Illicit Drug Problem in the Past Year, by State: 2000

State	Total				Age Group (Years)
					12-17				18-25				26 or Older
	Estimate	Prediction Interval			Estimate	Prediction Interval			Estimate	Prediction Interval			Estimate	Prediction Interval
Total1	3,994,321				963,682				1,511,823				1,518,816
Alabama	60,846	(46,033	-	78,487)	13,085	(8,602	-	19,040)	26,845	(18,767	-	37,074)	20,916	(11,533	-	34,964)
Alaska	10,381	(7,654	-	13,748)	2,879	(1,819	-	4,316)	3,451	(2,332	-	4,904)	4,051	(2,101	-	7,079)
Arizona	88,686	(61,861	-	122,928)	19,499	(13,259	-	27,571)	25,902	(18,035	-	35,909)	43,284	(21,685	-	77,124)
Arkansas	34,202	(26,365	-	43,209)	9,509	(6,605	-	13,217)	14,384	(10,201	-	19,640)	10,309	(5,505	-	17,675)
California	563,676	(461,420	-	681,354)	147,129	(122,173	-	175,448)	172,043	(137,555	-	212,195)	244,504	(158,079	-	361,194)
Colorado	71,131	(52,786	-	93,664)	16,164	(11,034	-	22,779)	24,240	(16,801	-	33,714)	30,727	(16,590	-	52,052)
Connecticut	52,010	(39,045	-	67,330)	13,550	(9,089	-	19,348)	20,130	(13,989	-	27,911)	18,329	(9,975	-	30,890)
Delaware	11,100	(8,216	-	14,555)	2,743	(1,910	-	3,807)	3,719	(2,539	-	5,241)	4,637	(2,513	-	7,823)
District of Columbia	8,820	(6,463	-	11,764)	1,852	(1,181	-	2,757)	2,820	(1,903	-	4,009)	4,148	(2,288	-	6,926)
Florida	196,128	(160,449	-	237,262)	47,578	(36,955	-	60,209)	71,294	(56,572	-	88,505)	77,256	(48,883	-	116,233)
Georgia	110,012	(83,253	-	141,784)	27,273	(19,260	-	37,405)	41,947	(29,324	-	57,986)	40,792	(22,069	-	69,160)
Hawaii	16,838	(11,247	-	24,197)	5,034	(3,235	-	7,439)	4,375	(2,823	-	6,453)	7,429	(3,144	-	14,895)
Idaho	19,700	(15,320	-	24,692)	5,408	(3,654	-	7,689)	9,029	(6,443	-	12,264)	5,263	(2,998	-	8,588)
Illinois	164,309	(134,517	-	198,622)	34,985	(27,164	-	44,296)	65,356	(52,140	-	80,766)	63,967	(41,229	-	94,762)
Indiana	82,093	(63,426	-	104,093)	19,227	(13,104	-	27,157)	35,911	(25,685	-	48,693)	26,955	(15,344	-	44,012)
Iowa	32,845	(24,272	-	43,409)	7,980	(5,092	-	11,892)	14,102	(9,375	-	20,312)	10,764	(5,795	-	18,339)
Kansas	35,310	(25,915	-	46,538)	7,244	(4,526	-	10,977)	13,406	(9,189	-	18,833)	14,661	(8,086	-	24,443)
Kentucky	53,647	(41,501	-	67,985)	13,165	(9,088	-	18,395)	22,798	(16,010	-	31,378)	17,684	(9,940	-	29,135)
Louisiana	65,208	(51,141	-	82,168)	16,667	(11,418	-	23,435)	28,934	(20,515	-	39,500)	19,607	(10,779	-	32,892)
Maine	18,817	(14,469	-	24,008)	5,463	(3,668	-	7,796)	7,565	(5,244	-	10,516)	5,789	(3,164	-	9,736)
Maryland	80,734	(59,889	-	106,368)	19,869	(13,686	-	27,791)	26,850	(18,617	-	37,333)	34,014	(17,947	-	58,740)
Massachusetts	108,669	(79,822	-	142,946)	28,215	(19,513	-	39,308)	36,641	(25,823	-	50,255)	43,812	(23,113	-	75,335)
Michigan	137,607	(115,803	-	162,255)	34,424	(27,201	-	42,911)	61,890	(49,773	-	75,909)	41,293	(26,205	-	62,041)
Minnesota	75,663	(56,404	-	98,355)	18,474	(12,874	-	25,610)	26,808	(18,635	-	37,236)	30,382	(16,197	-	51,990)
Mississippi	37,181	(28,302	-	47,497)	8,488	(5,598	-	12,320)	16,533	(11,495	-	22,948)	12,160	(6,858	-	19,973)
Missouri	67,487	(50,268	-	88,011)	15,037	(9,666	-	22,287)	27,465	(18,862	-	38,532)	24,985	(13,270	-	42,967)
Montana	12,396	(9,491	-	15,863)	3,955	(2,599	-	5,745)	4,616	(3,207	-	6,415)	3,825	(2,080	-	6,462)
Nebraska	22,267	(16,953	-	28,303)	5,205	(3,390	-	7,627)	9,747	(6,885	-	13,352)	7,315	(3,948	-	12,421)
Nevada	27,941	(21,071	-	36,296)	6,816	(4,533	-	9,808)	9,672	(6,679	-	13,493)	11,453	(6,581	-	18,540)
New Hampshire	19,883	(15,317	-	25,333)	6,566	(4,397	-	9,381)	7,006	(4,918	-	9,640)	6,310	(3,487	-	10,532)
New Jersey	110,186	(83,020	-	143,273)	21,851	(14,783	-	31,061)	44,599	(31,248	-	61,478)	43,737	(23,831	-	73,748)
New Mexico	25,748	(19,531	-	33,350)	7,533	(4,968	-	10,914)	8,854	(6,078	-	12,426)	9,362	(5,161	-	15,649)
New York	285,054	(233,386	-	344,527)	49,307	(37,179	-	64,032)	125,708	(101,175	-	154,035)	110,039	(70,584	-	163,580)
North Carolina	98,671	(74,303	-	128,412)	19,877	(13,217	-	28,668)	39,033	(27,845	-	53,051)	39,762	(21,745	-	66,937)
North Dakota	8,019	(6,077	-	10,276)	2,259	(1,484	-	3,287)	3,162	(2,132	-	4,506)	2,598	(1,399	-	4,431)
Ohio	150,150	(123,896	-	180,234)	34,443	(26,622	-	43,776)	61,867	(49,588	-	76,133)	53,840	(34,325	-	80,494)
Oklahoma	43,449	(32,808	-	56,404)	10,098	(6,561	-	14,836)	17,632	(12,228	-	24,530)	15,719	(8,643	-	26,320)
Oregon	54,906	(40,135	-	71,855)	13,900	(9,562	-	19,455)	19,589	(13,730	-	26,996)	21,417	(10,890	-	37,856)
Pennsylvania	160,117	(133,536	-	190,349)	30,162	(22,965	-	38,851)	72,657	(58,589	-	88,901)	57,298	(37,093	-	84,635)
Rhode Island	13,983	(10,600	-	17,959)	3,417	(2,304	-	4,866)	5,282	(3,671	-	7,329)	5,284	(3,007	-	8,625)
South Carolina	48,469	(36,463	-	62,805)	13,398	(8,892	-	19,324)	17,298	(11,753	-	24,479)	17,773	(9,780	-	29,812)
South Dakota	9,262	(7,010	-	11,863)	2,784	(1,762	-	4,171)	3,739	(2,567	-	5,248)	2,739	(1,477	-	4,668)
Tennessee	78,992	(60,266	-	101,055)	22,063	(15,248	-	30,779)	30,487	(21,077	-	42,515)	26,442	(14,397	-	44,653)
Texas	287,765	(238,763	-	343,704)	88,677	(70,975	-	109,278)	106,489	(84,048	-	132,855)	92,599	(55,613	-	145,327)
Utah	36,474	(27,201	-	47,167)	8,360	(5,490	-	12,177)	15,995	(11,017	-	22,379)	12,120	(6,473	-	20,701)
Vermont	9,810	(7,568	-	12,500)	2,511	(1,642	-	3,663)	3,980	(2,901	-	5,308)	3,320	(1,873	-	5,454)
Virginia	87,768	(65,335	-	115,360)	19,913	(13,884	-	27,610)	30,225	(20,550	-	42,761)	37,630	(20,613	-	63,304)
Washington	94,245	(66,323	-	129,778)	21,368	(14,517	-	30,240)	26,444	(17,403	-	38,417)	46,433	(23,048	-	83,569)
West Virginia	22,959	(17,142	-	29,879)	5,606	(3,816	-	7,922)	8,916	(6,041	-	12,647)	8,437	(4,621	-	14,135)
Wisconsin	75,832	(58,708	-	94,080)	21,142	(14,876	-	29,077)	31,298	(22,167	-	42,778)	23,392	(13,046	-	38,865)
Wyoming	6,872	(5,174	-	8,915)	1,531	(951	-	2,331)	3,089	(2,139	-	4,303)	2,252	(1,216	-	3,830)

Note: Estimates are based on a survey-weighted hierarchical Bayes estimation approach, and the prediction (credible) intervals are generated by Markov Chain Monte Carlo techniques.

¹ This estimate is the sum of the hierarchical Bayes estimates across all States and the District of Columbia and typically is not equal to the direct sample-weighted estimate for the Nation.

Source: SAMHSA, Office of Applied Studies, National Household Survey on Drug Abuse, 2000.

¹ States were ranked from lowest to highest based on the percentage gap to two decimals. Nine States were included in the third (middle) "fifth." Also see Figure 4 for the comparable numbers of persons.

² This is the national sample weighted estimate. Also, shown in Tables 8 and 9 are the corresponding "Totals" that represent the weighted average across States of the model-based estimates. The "Totals" are similar, but not identical, to the corresponding sample weighted national estimates.

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