2014-2015 National Survey on Drug Use and Health:
Other Sources of State-Level Data

 

Introduction

A variety of surveys and data systems other than the National Survey on Drug Use and Health (NSDUH) collect data on substance use problems and mental disorders. It is useful to consider the results of these other studies when discussing NSDUH data. This document briefly describes one of these other data systems that publish state estimates and presents selected comparisons with NSDUH results. The state-level survey that collects data on substance use discussed in this document is the Behavioral Risk Factor Surveillance System (BRFSS), sponsored by the Centers for Disease Control and Prevention (CDC). Another CDC data system that provides state-level substance use estimates for most but not all states is the Youth Risk Behavior Survey (YRBS). Differences between the YRBS and NSDUH sampling designs, as well as the wider range of age groups used in NSDUH small area estimates, imply that comparisons of estimates are not straightforward. However, ignoring these differences and examining estimates at a national level, the YRBS has been generally shown to have higher estimates but similar long-term trends compared with NSDUH (Center for Behavioral Health Statistics and Quality, 2014, 2015, 2016).1

When considering the information presented in this document, it is important to understand the methodological differences between these surveys and the impact that these differences could have on estimates of substance use and mental health. Several studies have compared NSDUH estimates with estimates from other studies and have evaluated how differences may have been affected by differences in survey methodology (Brener et al., 2006; Gfroerer, Wright, & Kopstein, 1997; Grucza, Abbacchi, Przybeck, & Gfroerer, 2007; Hennessy & Ginsberg, 2001; Miller et al., 2004). These studies suggest that the goals and approaches of surveys are often different, making comparisons between them difficult. Some methodological differences that have been identified as affecting comparisons include populations covered, sampling methods, mode of data collection, survey setting, questionnaires, and estimation methods.

BRFSS is a state-based system of health surveys that collect information on health risk behaviors (including cigarette and alcohol use), preventive health practices, and health care access primarily related to chronic disease, injuries, and preventable infectious diseases. BRFSS is an annual, state-based telephone (landline and cellular telephone) survey of the civilian, noninstitutionalized adult population aged 18 or older and is sponsored by the CDC. In 2014 and 2015, BRFSS collected data from all 50 states, the District of Columbia, Puerto Rico, the U.S. Virgin Islands, American Samoa, Palau, and Guam using a computer-assisted telephone interviewing design. More than 400,000 adults are interviewed each year, and state estimates are presented annually.

In 2011, BRFSS introduced two methodological changes: (1) the inclusion of cellular telephone-only households in the sample, and (2) the incorporation of iterative proportional fitting (also referred to as "raking") in the production of the final BRFSS weights, replacing the use of poststratification. Cellular telephone-only households were added to improve survey coverage of the telephone population and addressed differences in characteristics found between the cellular telephone-only and landline populations. In 2014 and 2015, BRFSS respondents who had a cellular telephone were eligible for participation in the cellular telephone survey. In 2013, on the other hand, in order to be eligible to participate in the cellular telephone survey, respondents had to be in either a cellular telephone-only household or a household where 90 percent or more of their calls were received on cellular telephones. Because state-level demographic characteristics of cellular telephone-only households are not available, weighting with the previous method of poststratification was no longer feasible. As a result of these methodological changes in 2014, the CDC reported small increases in various health risk indicators, including tobacco use and binge drinking.2 The pooled 2014-2015 BRFSS state estimates and confidence intervals are weighted design-based estimates (i.e., each respondent is weighted in a way that accounts for the survey design).3

Also in 2011, the BRFSS questionnaire underwent some changes in the alcohol consumption and tobacco use sections. In 2010, BRFSS respondents were asked, "During the past 30 days, have you had at least one drink of any alcoholic beverage such as beer, wine, a malt beverage or liquor?" The response to this question was used to route respondents to the next question regarding the frequency of alcohol use in the past 30 days. However, only the responses to the first question were used to determine past month alcohol use. In the 2011 BRFSS questionnaire, this question was dropped, and respondents were directly asked, "During the past 30 days, how many days per week or per month did you have at least one drink of any alcoholic beverage such as beer, wine, a malt beverage or liquor?" If a respondent answered "1" or higher to this question, he or she was considered a past month user of alcohol. In spite of the questionnaire changes, BRFSS is still producing an estimate of past month alcohol use that can be compared with the NSDUH estimate. Also, minor wording changes were made in one question in the tobacco use section, but none of these would affect current cigarette use estimates. These newly worded questions were used in the 2012 to the 2015 BRFSS surveys as well.

In both BRFSS and NSDUH, data are collected on the following four substance use and mental health measures in each of the 50 states and the District of Columbia:4

Note that only estimates for the first two of these four measures are compared here because the binge alcohol definition differs in BRFSS and NSDUH and small area estimates of lifetime doctor-diagnosed depression were not produced for NSDUH. The BRFSS and NSDUH questions that were used for the first two measures are shown in the next section.

Past month alcohol use is defined consistently in both BRFSS and NSDUH as having an alcoholic beverage in the past month. In NSDUH, past month cigarette use is defined as having smoked part or all of a cigarette during the past 30 days (i.e., the 30 days prior to the interview). In BRFSS, the cigarette use measure reported is current cigarette use, which is defined as having smoked at least 100 cigarettes during the lifetime and indicating smoking every day or some days at the time of the survey. Because of these subtle but present differences in definitions, the NSDUH cigarette use estimates tend to be higher in that they cover two groups of people that the BRFSS estimates would not: (1) respondents who have not smoked 100 cigarettes in their lifetime but had smoked in the past month, and (2) respondents who had smoked a cigarette earlier in the month but were not smoking at the time of the survey. Both surveys ask about binge alcohol use in the past month; however, as noted earlier, each survey defines it differently. In 2014 and prior years, NSDUH's binge alcohol use definition for males and females was having had five or more drinks of an alcoholic beverage on the same occasion (i.e., at the same time or within a couple hours of each other) on at least 1 day in the past 30 days. Starting in 2015, the NSDUH definition for binge drinking for females changed to four or more drinks instead of five or more drinks. Because of this change in definition, 2014-2015 NSDUH state estimates were not produced for past month binge alcohol use. In BRFSS, females are asked about drinking four or more drinks on one occasion, whereas males are asked about drinking five or more drinks on one occasion. Because of the difference in definitions in 2014 and prior years, NSDUH's small area estimates and BRFSS's estimates of binge alcohol use are not considered comparable, and no comparisons are included here. Starting with the 2015-2016 NSDUH state estimation, binge alcohol use estimates will be compared because both BRFSS and NSDUH will define binge drinking in a similar manner.

Beginning in 2011, the question assessing lifetime diagnosed depression was removed from the BRFSS optional anxiety and depression module and placed in the core section of the questionnaire within a group of questions inquiring about various chronic health conditions, such as coronary heart disease and diabetes. Thus, BRFSS estimates for lifetime diagnosed depression are now available for all states. In BRFSS, respondents are simply asked if a doctor, nurse, or other health professional has ever told them that they had a depressive disorder, including depression, major depression, dysthymia, or minor depression. In NSDUH, respondents are considered to have had depression in their lifetime if they answered that a doctor or medical professional has ever told them that they had depression. In the same group of questions asking about depression in both the BRFSS questionnaire and the NSDUH questionnaire, respondents are also asked about heart disease, diabetes, strokes, and asthma. However, because NSDUH's state-level small area estimates are not produced for lifetime diagnosed depression or any of these other health conditions, comparisons with BRFSS data cannot be made. Although state small area estimates have not been produced in NSDUH for these measures, direct estimates of these health measures could be generated using NSDUH data at the state level and compared with BRFSS estimates. Because the focus here is on model-based small area estimates, however, such comparisons with BRFSS data have not been made. Note that NSDUH's state small area estimates are produced for individuals having had a major depressive episode (MDE) in the past year. However, this MDE measure is unrelated to the NSDUH question about being diagnosed with lifetime depression. Instead, NSDUH includes a separate set of questions to assess depression symptoms that are used to measure MDE. Thus, NSDUH's small area estimates for MDE would not be comparable with estimates of the BRFSS depression measure discussed here.

This document presents the findings of the combined 2014-2015 BRFSS state estimates and the combined 2014-2015 NSDUH state estimates for past month alcohol use and cigarette use ("past month" use for NSDUH and "current" use for BRFSS). In Tables 1 and 2 (shown after this text discussion), the pooled 2014-2015 BRFSS state estimates for adults aged 18 or older are shown alongside the pooled 2014-2015 NSDUH small area estimates for the same age group. Table 1 also includes p values that indicate whether the BRFSS and NSDUH alcohol use estimates are significantly different from each other for a given state using an exact test as described in the next section. Due to definitional differences in the cigarette use measure, no tests of differences between NSDUH and BRFSS estimates were produced.

NSDUH and BRFSS Questions

The 2015 NSDUH questions that were used to determine past month alcohol use and when alcohol was last used were worded as follows:6

AL01
Have you ever, even once, had a drink of any type of alcoholic beverage? Please do not include times when you only had a sip or two from a drink.

1   Yes
2   No
DK/REF7

ALLAST3
[IF AL01 = 1 OR ALREF = 1] How long has it been since you last drank an alcoholic beverage?

1   Within the past 30 days – that is, since [DATEFILL]
2   More than 30 days ago but within the past 12 months
3   More than 12 months ago
DK/REF
PROGRAMMER: SHOW 12 MONTH CALENDAR

The 2015 BRFSS question that was used to determine past month alcohol use was worded as follows:8

9.1 During the past 30 days, how many days per week or per month did you have at least one drink of any alcoholic beverage such as beer, wine, a malt beverage or liquor?

1 _ _   Days per week
2 _ _   Days in past 30 days
8 8 8   No drinks in past 30 days
7 7 7   Don't know / Not sure
9 9 9   Refused

The 2015 NSDUH questions that were used to determine past month cigarette use were worded as follows:

CG01
Have you ever smoked part or all of a cigarette?

1   Yes
2   No
DK/REF

CG05
[IF CG01 = 1 OR CGREF1 = 1] Now think about the past 30 days, that is, from [DATEFILL] up to and including today. During the past 30 days, have you smoked part or all of a cigarette?

1   Yes
2   No
DK/REF
PROGRAMMER: SHOW 30 DAY CALENDAR

The 2015 BRFSS questions that were used to determine current cigarette use were worded as follows:

8.1 Have you smoked at least 100 cigarettes in your entire life?

NOTE: 5 packs = 100 cigarettes

1   Yes
2   No
7   Don't know / Not sure
9   Refused

INTERVIEWER NOTE: "For cigarettes, do not include: electronic cigarettes (e cigarettes, NJOY, Bluetip), herbal cigarettes, cigars, cigarillos, little cigars, pipes, bidis, kreteks, water pipes (hookahs), or marijuana."

8.2 Do you now smoke cigarettes every day, some days, or not at all?

1   Every day
2   Some days
3   Not at all
7   Don't know / Not sure
9   Refused

Note that these 2015 NSDUH and 2015 BRFSS questions were the same as the questions used in the 2014 NSDUH and the 2014 BRFSS.

Methodology for Comparing BRFSS and NSDUH Estimates

The methodology used to compare BRFSS and NSDUH estimates is similar to what is described in Section B.7 of the "2014-2015 NSDUH: Guide to State Tables and Summary of Small Area Estimation Methodology."9 Here, the null hypothesis of no difference is tested, that is, pi sub b is equal to pi sub n (where pi sub b is the expected value10 of the BRFSS estimate and pi sub n is the expected value of the NSDUH estimate) or equivalently that the logs-odds ratio is zero, that is, Log-odds ratio lor is equal to zero, where log-odds ratio lor is defined as The log-odds ratio, lor, is defined as the natural logarithm of the ratio of two quantities. The numerator of the ratio is pi sub b divided by 1 minus pi sub b. The denominator of the ratio is pi sub n divided by 1 minus pi sub n., and where ln denotes the natural logarithm. An estimate of log-odds ratio lor is given by The estimate of the log-odds ratio, lor hat, is defined as the natural logarithm of the ratio of two quantities. The numerator of the ratio is p sub b divided by 1 minus p sub b. The denominator of the ratio is p sub n divided by 1 minus p sub n., where p sub b and p sub n are the 2014-2015 BRFSS state-level design-based estimates and the 2014-2015 NSDUH state model-based estimates, respectively (as given in Tables 1 and 2). To compute the variance of the estimate of the log-odds ratio, lor hat, that is, variance v of the estimate of the log-odds ratio, lor hat, let Theta sub b hat be defined as the ratio of p sub b and 1 minus p sub b and Theta sub n hat be defined as the ratio of p sub n and 1 minus p sub n, then Variance v of the estimate of the log-odds ratio, lor hat, is a function of three quantities: q1, q2, and q3. It is expressed as the sum of q1 and q2 minus q3. Quantity q1 is the variance v of the natural logarithm of Theta sub b hat, quantity q2 is the variance v of the natural logarithm of Theta sub n hat, and quantity q3 is 2 times the covariance between the natural logarithm of Theta sub b hat and the natural logarithm of Theta sub n hat.. The covariance term can be assumed to be zero because the BRFSS and NSDUH samples are independent.

The quantity variance v of the natural logarithm of Theta sub n hat can be obtained by using the 95 percent Bayesian confidence intervals in Tables 1 and 2. For this purpose, let lower sub n and upper sub n denote the 95 percent Bayesian confidence interval11 for a given state-s:

Equation 1,     D

where Capital U sub n is the natural logarithm of upper sub n divided by 1 minus upper sub n, and capital L sub n is the natural logarithm of lower sub n divided by 1 minus lower sub n. .

The quantity variance v of the natural logarithm of Theta hat sub b can be obtained by using the 95 percent confidence intervals in Tables 1 and 2. For this purpose, let lower sub b and upper sub b denote the 95 percent BRFSS confidence interval for a given state-s, then variance v of p sub b is given by

Equation 2.     D

Now, using the first-order Taylor series approximation,12 variance v of the natural logarithm of Theta hat sub b can be calculated from variance v of p sub b as follows: Variance v of the natural logarithm of Theta sub b hat is equal to the variance v of the natural logarithm of p sub b divided by 1 minus p sub b, which is then approximately equal to variance v of p sub b multiplied by the square of quantity q. Quantity q is the reciprocal of p sub b multiplied by 1 minus p sub b..

The p value that is given in Tables 1 and 2 for testing the null hypothesis of no difference (Log-odds ratio lor is equal to zero) is provided by the p value, which is equal to 2 times the probability of realizing a standard normal variate capital Z greater than or equal to the absolute value of a quantity z., where capital Z is a standard normal random variate, Quantity z is the estimate of the log-odds ratio, lor hat, divided by the square root of the sum of the variance v of the natural logarithm of Theta sub b hat and the variance v of the natural logarithm of Theta sub n hat., and absolute value of quantity z denotes the absolute value of quantity z.

Alcohol Use

As can be seen in Table 1, for past month alcohol use, the NSDUH estimates and the BRFSS estimates for more than half of the states were different (i.e., at the 5 percent level of significance, 37 of 51 states had different estimates). However, these two sets of estimates were highly correlated (correlation coefficient = 0.96). Figures 1 and 2, which follow the tables, were created by using state estimates from both BRFSS and NSDUH and categorizing the states into five quintiles similar to the process described on the title page of the "2014-2015 NSDUH National Maps of Prevalence Estimates, by State."13

As can be seen in Figures 1 and 2, eight states with the highest estimates of alcohol use (states shown in red) were the same in the two surveys: Colorado, Connecticut, the District of Columbia, Minnesota, New Hampshire, Rhode Island, Vermont, and Wisconsin. Note that Massachusetts and North Dakota were the other two states in the top BRFSS group and that Maine and Oregon were the other two states in the top NSDUH group. Nine states with the lowest estimates of alcohol use were the same in the two surveys: Alabama, Arkansas, Idaho, Kentucky, Mississippi, North Carolina, Tennessee, Utah, and West Virginia. Note that Oklahoma rounded out the bottom BRFSS group and that South Carolina was the other state in the bottom NSDUH group. The lowest estimate of past month alcohol use was in Utah for both BRFSS and NSDUH (see Table 1 and Figures 1 and 2).

Cigarette Use

As can be seen in Table 2, the NSDUH estimates of past month cigarette use were always larger than the BRFSS estimates of current cigarette use. Some of this difference is the result of the differences in definitions as discussed earlier in this document; thus, exact tests to examine significant differences between the NSDUH and BRFSS cigarette use estimates are not included. Although the NSDUH estimates tended to be larger, these two sets of estimates were highly correlated (correlation coefficient = 0.93).

Figures 3 and 4 were created using the same method used to produce Figures 1 and 2. As can be seen in Figures 3 and 4, nine states with the highest estimates of cigarette use (states shown in red) were the same in the two surveys: Arkansas, Indiana, Kentucky, Louisiana, Mississippi, Missouri, Ohio, and Oklahoma, and West Virginia. Rounding out the top BRFSS group was Tennessee, while Alaska rounded out the top NSDUH group. Seven states with the lowest estimates of cigarette use were the same in the two surveys: California, Connecticut, Hawaii, Idaho, Massachusetts, New Jersey, and Utah. Note that the other three states in the bottom BRFSS group were Maryland, New York, and Texas and that the other three states in the bottom NSDUH group were Florida, Oregon, and Washington.

Sample Size Comparisons

The BRFSS estimates are design based, while the NSDUH estimates are model based. Both sets of estimates are based on 2 years of pooled data (2014-2015) The BRFSS sample sizes for a given state were in general much larger than the sample sizes for NSDUH (both over 2 years). In the 2014-2015 NSDUH, the 18 or older sample sizes in the states ranged from 1,383 to 7,072 respondents, with a median sample size of 1,452.14 For the 2014-2015 BRFSS, all of the states had larger sample sizes as compared with their counterparts in NSDUH. Overall, the BRFSS sample sizes over 2 years for the states varied from a low of 6,689 to a high of 39,981 respondents, with a median sample size of 15,391.15 Sample size differences of this magnitude explain why the NSDUH Bayesian confidence intervals were generally wider than the corresponding BRFSS design-based confidence intervals.

References

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

Brener, N. D., Eaton, D. K., Kann, L., Grunbaum, J. A., Gross, L. A., Kyle, T. M., & Ross, J. G. (2006). The association of survey setting and mode with self-reported health risk behaviors among high school students. Public Opinion Quarterly, 70, 354-374. https://doi.org/10.1093/poq/nfl003

Center for Behavioral Health Statistics and Quality. (2014). Results from the 2013 National Survey on Drug Use and Health: Summary of national findings (HHS Publication No. SMA 14 4863, NSDUH Series H-48). Rockville, MD: Substance Abuse and Mental Health Services Administration.

Center for Behavioral Health Statistics and Quality. (2015). Section D: Other sources of data. In 2014 National Survey on Drug Use and Health: Methodological summary and definitions. Retrieved from http://www.samhsa.gov/data/

Center for Behavioral Health Statistics and Quality. (2016). Section E: Other sources of data. In 2015 National Survey on Drug Use and Health: Methodological summary and definitions. Retrieved from http://www.samhsa.gov/data/

Centers for Disease Control and Prevention. (2015, September). Behavioral Risk Factor Surveillance System: Comparability of data BRFSS 2014 (Version #1–Revised). Retrieved from http://www.cdc.gov/brfss/annual_data/2014/pdf/compare_2014.pdf

Gfroerer, J., Wright, D., & Kopstein, A. (1997). Prevalence of youth substance use: The impact of methodological differences between two national surveys. Drug and Alcohol Dependence, 47, 19-30. https://doi.org/10.1016/s0376-8716(97)00063-x

Grucza, R. A., Abbacchi, A. M., Przybeck, T. R., & Gfroerer, J. C. (2007). Discrepancies in estimates of prevalence and correlates of substance use and disorders between two national surveys. Addiction, 102, 623-629. https://doi.org/10.1111/j.1360-0443.2007.01745.x

Hennessy, K. H., & Ginsberg, C. (Eds.). (2001). Substance use survey data collection methodologies and selected papers [Special issue]. Journal of Drug Issues, 31(3), 595-808. https://doi.org/10.1177/002204260103100301

Miller, J. W., Gfroerer, J. C., Brewer, R. D., Naimi, T. S., Mokdad, A., & Giles, W. H. (2004). Prevalence of adult binge drinking: A comparison of two national surveys. American Journal of Preventive Medicine, 27, 197-204. https://doi.org/10.1016/s0749-3797(04)00121-7

Table 1 – Alcohol Use in the Past Month among Adults Aged 18 or Older, by State: Percentages, Annual Averages Based on 2014-2015 BRFSS and 2014-2015 NSDUH
State 2014-2015
BRFSS
(Estimate)
2014-2015 BRFSS
(95% Confidence
Interval)
2014-2015
NSDUH
(Estimate)
2014-2015 NSDUH
(95% Confidence
Interval)
P Value
NOTE: NSDUH estimates along with 95 percent Bayesian confidence (credible) intervals are based on a survey-weighted hierarchical Bayes estimation approach and are generated by Markov Chain Monte Carlo techniques. BRFSS estimates are based on a survey-weighted direct estimation approach.
NOTE: The p value is the probability of no difference between the BRFSS and NSDUH estimates.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2014-2015; Centers for Disease Control and Prevention (CDC), Behavioral Risk Factor Surveillance System, 2014-2015.
Alabama 40.38 (39.29 - 41.48) 47.57 (44.63 - 50.53) 0.000
Alaska 56.28 (54.54 - 58.01) 59.95 (57.08 - 62.76) 0.032
Arizona 50.30 (49.20 - 51.40) 55.60 (52.59 - 58.57) 0.001
Arkansas 40.99 (39.35 - 42.63) 45.26 (42.21 - 48.35) 0.016
California 53.82 (52.88 - 54.76) 55.77 (54.32 - 57.21) 0.028
Colorado 61.07 (60.18 - 61.95) 63.99 (60.92 - 66.96) 0.073
Connecticut 61.68 (60.63 - 62.73) 65.09 (61.94 - 68.13) 0.044
Delaware 52.97 (51.38 - 54.55) 57.99 (54.93 - 60.99) 0.004
District of Columbia 67.08 (65.17 - 68.98) 72.27 (69.65 - 74.74) 0.002
Florida 53.97 (52.94 - 55.00) 58.77 (56.99 - 60.53) 0.000
Georgia 47.96 (46.61 - 49.30) 53.43 (51.06 - 55.79) 0.000
Hawaii 51.41 (50.22 - 52.60) 49.91 (46.83 - 52.99) 0.373
Idaho 47.51 (46.12 - 48.90) 48.72 (45.72 - 51.72) 0.474
Illinois 57.72 (56.43 - 59.01) 58.93 (57.04 - 60.79) 0.300
Indiana 48.63 (47.47 - 49.78) 54.87 (51.85 - 57.86) 0.000
Iowa 58.32 (57.21 - 59.42) 60.75 (57.67 - 63.74) 0.144
Kansas 51.79 (51.11 - 52.46) 57.26 (54.22 - 60.24) 0.001
Kentucky 39.03 (37.84 - 40.21) 46.14 (43.03 - 49.29) 0.000
Louisiana 49.00 (47.75 - 50.25) 54.22 (51.15 - 57.26) 0.002
Maine 59.07 (58.05 - 60.09) 64.62 (61.44 - 67.67) 0.001
Maryland 53.97 (52.70 - 55.24) 63.01 (60.03 - 65.89) 0.000
Massachusetts 61.15 (60.18 - 62.12) 62.11 (59.12 - 65.02) 0.545
Michigan 56.96 (56.01 - 57.91) 58.37 (56.40 - 60.32) 0.206
Minnesota 61.67 (60.98 - 62.35) 64.42 (61.51 - 67.23) 0.070
Mississippi 38.53 (37.09 - 39.97) 42.94 (39.85 - 46.09) 0.011
Missouri 48.41 (47.19 - 49.64) 54.99 (51.82 - 58.12) 0.000
Montana 58.79 (57.55 - 60.03) 62.47 (59.25 - 65.58) 0.036
Nebraska 58.41 (57.60 - 59.21) 62.70 (59.62 - 65.68) 0.008
Nevada 50.66 (48.68 - 52.63) 56.84 (53.60 - 60.03) 0.001
New Hampshire 63.12 (61.88 - 64.37) 68.36 (65.34 - 71.22) 0.002
New Jersey 56.41 (55.40 - 57.42) 61.03 (58.45 - 63.56) 0.001
New Mexico 47.64 (46.36 - 48.92) 51.06 (47.93 - 54.18) 0.047
New York 54.80 (53.78 - 55.81) 58.51 (56.80 - 60.21) 0.000
North Carolina 46.16 (45.12 - 47.20) 49.74 (47.24 - 52.25) 0.009
North Dakota 61.10 (59.80 - 62.39) 63.11 (60.26 - 65.86) 0.206
Ohio 53.00 (51.92 - 54.08) 56.97 (55.06 - 58.85) 0.000
Oklahoma 41.79 (40.66 - 42.92) 49.95 (46.75 - 53.14) 0.000
Oregon 59.21 (57.92 - 60.50) 63.28 (60.24 - 66.21) 0.016
Pennsylvania 54.66 (53.54 - 55.78) 60.82 (58.80 - 62.81) 0.000
Rhode Island 61.79 (60.49 - 63.10) 63.56 (60.37 - 66.64) 0.312
South Carolina 47.71 (46.79 - 48.64) 49.88 (46.91 - 52.85) 0.172
South Dakota 55.95 (54.49 - 57.41) 63.02 (59.98 - 65.96) 0.000
Tennessee 40.58 (39.15 - 42.01) 47.04 (43.89 - 50.20) 0.000
Texas 48.90 (47.83 - 49.96) 52.48 (50.84 - 54.11) 0.000
Utah 30.12 (29.39 - 30.85) 34.99 (32.25 - 37.83) 0.001
Vermont 62.52 (61.43 - 63.61) 64.82 (61.59 - 67.92) 0.183
Virginia 52.88 (51.85 - 53.90) 55.86 (53.47 - 58.22) 0.025
Washington 58.90 (58.01 - 59.78) 61.84 (58.71 - 64.89) 0.076
West Virginia 33.35 (32.33 - 34.38) 44.08 (40.84 - 47.36) 0.000
Wisconsin 63.97 (62.75 - 65.20) 65.34 (62.27 - 68.29) 0.413
Wyoming 52.44 (50.90 - 53.98) 58.73 (55.42 - 61.96) 0.001
Table 2 – Cigarette Use among Adults Aged 18 or Older, by State: Percentages, Annual Averages Based on 2014-2015 BRFSS and 2014-2015 NSDUH
State 2014-2015
BRFSS1
(Estimate)
2014-2015 BRFSS1
(95% Confidence
Interval)
2014-2015
NSDUH2
(Estimate)
2014-2015 NSDUH2
(95% Confidence
Interval)
NOTE: NSDUH estimates along with 95 percent Bayesian confidence (credible) intervals are based on a survey-weighted hierarchical Bayes estimation approach and are generated by Markov Chain Monte Carlo techniques. BRFSS estimates are based on a survey-weighted direct estimation approach.
1 BRFSS respondents were classified as current smokers if they reported having smoked at least 100 cigarettes during their lifetime and indicated that they smoked every day or some days at the time of the survey.
2 NSDUH respondents were classified as past month cigarette users if they smoked all or part of a cigarette during the past 30 days.
Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2014-2015; Centers for Disease Control and Prevention (CDC), Behavioral Risk Factor Surveillance System, 2014-2015.
Alabama 21.26 (20.29 - 22.22) 26.20 (23.78 - 28.78)
Alaska 19.49 (18.13 - 20.85) 26.74 (24.35 - 29.29)
Arizona 15.23 (14.41 - 16.06) 20.87 (18.75 - 23.15)
Arkansas 24.81 (23.28 - 26.33) 30.10 (27.66 - 32.64)
California 12.27 (11.66 - 12.87) 16.05 (15.06 - 17.08)
Colorado 15.68 (14.99 - 16.37) 21.23 (19.12 - 23.50)
Connecticut 14.44 (13.67 - 15.22) 18.89 (16.84 - 21.13)
Delaware 18.60 (17.30 - 19.91) 24.13 (21.82 - 26.61)
District of Columbia 16.18 (14.54 - 17.82) 20.83 (18.76 - 23.07)
Florida 16.71 (15.90 - 17.52) 20.26 (18.95 - 21.63)
Georgia 17.52 (16.45 - 18.60) 22.26 (20.51 - 24.11)
Hawaii 14.11 (13.25 - 14.98) 17.76 (15.76 - 19.95)
Idaho 14.87 (13.86 - 15.87) 19.26 (17.25 - 21.44)
Illinois 15.82 (14.82 - 16.81) 22.14 (20.65 - 23.69)
Indiana 21.73 (20.71 - 22.74) 28.01 (25.61 - 30.54)
Iowa 18.27 (17.34 - 19.20) 22.85 (20.69 - 25.16)
Kansas 17.90 (17.36 - 18.44) 20.52 (18.48 - 22.71)
Kentucky 26.06 (24.93 - 27.18) 30.94 (28.43 - 33.55)
Louisiana 22.94 (21.84 - 24.03) 28.65 (26.07 - 31.37)
Maine 19.39 (18.47 - 20.31) 21.99 (19.76 - 24.39)
Maryland 14.87 (13.91 - 15.84) 20.58 (18.44 - 22.90)
Massachusetts 14.35 (13.64 - 15.05) 17.81 (15.85 - 19.96)
Michigan 20.95 (20.10 - 21.81) 24.09 (22.59 - 25.65)
Minnesota 16.24 (15.71 - 16.78) 21.02 (18.95 - 23.26)
Mississippi 22.75 (21.47 - 24.03) 27.54 (25.10 - 30.13)
Missouri 21.45 (20.39 - 22.50) 26.96 (24.55 - 29.51)
Montana 19.42 (18.35 - 20.49) 20.92 (18.80 - 23.20)
Nebraska 17.22 (16.58 - 17.86) 23.78 (21.47 - 26.26)
Nevada 17.26 (15.72 - 18.80) 22.99 (20.61 - 25.56)
New Hampshire 16.71 (15.69 - 17.72) 20.99 (18.86 - 23.29)
New Jersey 14.32 (13.60 - 15.04) 18.03 (16.31 - 19.90)
New Mexico 18.32 (17.28 - 19.37) 22.05 (19.74 - 24.55)
New York 14.81 (14.08 - 15.55) 20.99 (19.67 - 22.37)
North Carolina 19.03 (18.18 - 19.88) 22.92 (21.06 - 24.88)
North Dakota 19.31 (18.20 - 20.42) 25.46 (23.34 - 27.69)
Ohio 21.28 (20.33 - 22.24) 27.27 (25.65 - 28.96)
Oklahoma 21.62 (20.61 - 22.62) 27.61 (25.16 - 30.22)
Oregon 17.04 (16.03 - 18.05) 19.20 (17.19 - 21.37)
Pennsylvania 19.03 (18.13 - 19.92) 23.11 (21.60 - 24.68)
Rhode Island 15.88 (14.83 - 16.93) 20.52 (18.23 - 23.02)
South Carolina 20.58 (19.78 - 21.38) 25.28 (23.06 - 27.64)
South Dakota 19.33 (18.12 - 20.54) 23.79 (21.55 - 26.19)
Tennessee 23.06 (21.79 - 24.32) 24.53 (22.21 - 26.99)
Texas 14.88 (14.13 - 15.64) 20.97 (19.73 - 22.27)
Utah   9.37   (8.89 -   9.84) 14.88 (13.04 - 16.94)
Vermont 16.19 (15.33 - 17.05) 23.36 (21.05 - 25.83)
Virginia 18.02 (17.21 - 18.83) 21.72 (20.01 - 23.54)
Washington 15.15 (14.46 - 15.84) 18.83 (16.77 - 21.08)
West Virginia 26.18 (25.19 - 27.17) 31.68 (29.08 - 34.40)
Wisconsin 17.35 (16.34 - 18.35) 22.10 (19.93 - 24.43)
Wyoming 19.27 (17.96 - 20.57) 25.90 (23.48 - 28.48)

Figure 1. Alcohol Use in the Past Month among Adults Aged 18 or Older, by State: Percentages, Annual Averages Based on 2014 and 2015 BRFSS

Figure 1. Follow the 'D' link at the right for the long description.     D

Source: Centers for Disease Control and Prevention (CDC), Behavioral Risk Factor Surveillance System Survey, 2014 and 2015.

Figure 2. Alcohol Use in the Past Month among Adults Aged 18 or Older, by State: Percentages, Annual Averages Based on 2014 and 2015 NSDUHs

Figure 2. Follow the 'D' link at the right for the long description.     D

Source: Center for Behavioral Health Statistics and Quality, NSDUH, 2014 and 2015

Figure 3. Current Cigarette Use among Adults Aged 18 or Older, by State: Percentages, Annual Averages Based on 2014 and 2015 BRFSS

Figure 3. Follow the 'D' link at the right for the long description.     D

Source: Centers for Disease Control and Prevention (CDC), Behavioral Risk Factor Surveillance System Survey, 2014 and 2015.

Figure 4. Cigarette Use in the Past Month among Adults Aged 18 or Older, by State: Percentages, Annual Averages Based on 2014 and 2015 NSDUHs

Figure 4. Follow the 'D' link at the right for the long description.     D

Source: SAMHSA, Center for Behavioral Health Statistics and Quality, NSDUH, 2014 and 2015.


End Notes

1 For further details about the YRBS and the Youth Risk Behavior Surveillance System (YRBSS), see http://www.cdc.gov/healthyyouth/data/yrbs/index.htm.

2 More detailed information about these methodological changes is available online at the 2014 BRFSS web page: http://www.cdc.gov/brfss/annual_data/annual_2014.html (specifically, see CDC, 2015).

3 For more details about BRFSS in general, along with information about the methodological changes introduced in 2011 and 2012 and their impact on BRFSS estimates, see the following two web pages: http://www.cdc.gov/brfss and http://www.cdc.gov/surveillancepractice/reports/brfss/brfss.html.

4 The District of Columbia is referred to as a "state" in this document.

5 The BRFSS doctor-diagnosed depression measure is based on a question that asks respondents if a doctor or other medical professional had ever told them they had depression. The NSDUH doctor-diagnosed depression measure is based on a similar question that is also asked directly of respondents. However, NSDUH also has a measure based on a series of questions that determines depression using diagnostic criteria defined in the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (American Psychiatric Association, 1994).

6 To search a PDF of the complete 2015 NSDUH questionnaire, see http://www.samhsa.gov/data/sites/default/files/NSDUH2015MRB/NSDUHmrbCAIquex2015.pdf.

7 "DK" = "don't know," and "REF" = "refused."

8 To search a PDF of the complete 2015 BRFSS questionnaire, see http://www.cdc.gov/brfss/questionnaires/pdf-ques/2015-brfss-questionnaire-12-29-14.pdf.

9 See http://www.samhsa.gov/data/.

10 The expected value of an estimate is defined as the mean of the observed values of the estimate over repeated samples.

11 For more information about NSDUH's small area estimation (SAE) confidence intervals, see Section B of the "2014-2015: Guide to State Tables and Summary of Small Area Estimation Methodology" at http://www.samhsa.gov/data/.

12 The first-order Taylor series approximation is defined as Variance v of function x is approximately equal to the variance v of x multiplied by the square of the first-order derivative of function x., where first-order derivative of function x is the first-order derivative of function x. If Function x equals the natural logarithm of x divided by 1 minus x., then The first-order derivative of function x is the reciprocal of x multiplied by 1 minus x..

13 See footnote 9.

14 See Table C.14 in the "2014-2015 NSDUH: Guide to State Tables and Summary of Small Area Estimation Methodology."

15 For more information, see http://www.cdc.gov/brfss/annual_data/annual_2015.html.


Long Descriptions—Equations and Figures

Long description, Equation 1. Variance v of the natural logarithm of Theta sub n hat is equal to the square of quantity q. Quantity q is the difference between capital U sub n and capital L sub n divided by 2 times 1.96.

Long description end. Return to Equation 1.

Long description, Equation 2. Variance v of p sub b is equal to the square of quantity q. Quantity q is the difference between upper sub b and lower sub b divided by 2 times 1.96.

Long description end. Return to Equation 2.

Long description, Figure 1. Figure 1 is a U.S. map showing alcohol use in the past month among adults aged 18 or older, by State: Percentages, annual averages based on 2014 and 2015 BRFSS. States listed here in alphabetical order within each group were divided into five groups based on the magnitude of their percentages. States in the highest group (59.22 to 67.08 percent) were Colorado, Connecticut, District of Columbia, Massachusetts, Minnesota, New Hampshire, North Dakota, Rhode Island, Vermont, and Wisconsin. States in the next highest group (55.96 to 59.21 percent) were Alaska, Illinois, Iowa, Maine, Michigan, Montana, Nebraska, New Jersey, Oregon, and Washington. States in the midgroup (51.42 to 55.95 percent) were California, Delaware, Florida, Kansas, Maryland, New York, Ohio, Pennsylvania, South Dakota, Virginia, and Wyoming. States in the next lowest group (47.52 to 51.41 percent) were Arizona, Georgia, Hawaii, Indiana, Louisiana, Missouri, Nevada, New Mexico, South Carolina, and Texas. States in the lowest group (30.12 to 47.51 percent) were Alabama, Arkansas, Idaho, Kentucky, Mississippi, North Carolina, Oklahoma, Tennessee, Utah, and West Virginia.

Long description end. Return to Figure 1.

Long description, Figure 2. Figure 2 is a U.S. map showing alcohol use in the past month among adults aged 18 or older, by State: Percentages, annual averages based on 2014 and 2015 NSDUHs. States listed here in alphabetical order within each group were divided into five groups based on the magnitude of their percentages. States in the highest group (63.12 to 72.27 percent) were Colorado, Connecticut, District of Columbia, Maine, Minnesota, New Hampshire, Oregon, Rhode Island, Vermont, and Wisconsin. States in the next highest group (59.96 to 63.11 percent) were Iowa, Maryland, Massachusetts, Montana, Nebraska, New Jersey, North Dakota, Pennsylvania, South Dakota, and Washington. States in the midgroup (55.78 to 59.95 percent) were Alaska, Delaware, Florida, Illinois, Kansas, Michigan, Nevada, New York, Ohio, Virginia, and Wyoming. States in the next lowest group (49.89 to 55.77 percent) were Arizona, California, Georgia, Hawaii, Indiana, Louisiana, Missouri, New Mexico, Oklahoma, and Texas. States in the lowest group (34.99 to 49.88 percent) were Alabama, Arkansas, Idaho, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee, Utah, and West Virginia.

Long description end. Return to Figure 2.

Long description, Figure 3. Figure 3 is a U.S. map showing current cigarette use among adults aged 18 or older, by State: Percentages, annual averages based on 2014 and 2015 BRFSS. States listed here in alphabetical order within each group were divided into five groups based on the magnitude of their percentages. States in the highest group (21.27 to 26.18 percent) were Arkansas, Indiana, Kentucky, Louisiana, Mississippi, Missouri, Ohio, Oklahoma, Tennessee, and West Virginia. States in the next highest group (19.04 to 21.26 percent) were Alabama, Alaska, Maine, Michigan, Montana, North Dakota, South Carolina, South Dakota, and Wyoming. States in the midgroup (16.72 to 19.03 percent) were Delaware, Georgia, Iowa, Kansas, Nebraska, Nevada, New Mexico, North Carolina, Oregon, Pennsylvania, Virginia, and Wisconsin. States in the next lowest group (14.89 to 16.71 percent) were Arizona, Colorado, District of Columbia, Florida, Illinois, Minnesota, New Hampshire, Rhode Island, Vermont, and Washington. States in the lowest group (9.37 to 14.88 percent) were California, Connecticut, Hawaii, Idaho, Maryland, Massachusetts, New Jersey, New York, Texas, and Utah.

Long description end. Return to Figure 3.

Long description, Figure 4. Figure 4 is a U.S. map showing cigarette use in the past month among adults aged 18 or older, by State: Percentages, annual averages based on 2014 and 2015 NSDUHs. States listed here in alphabetical order within each group were divided into five groups based on the magnitude of their percentages. States in the highest group (26.21 to 31.68 percent) were Alaska, Arkansas, Indiana, Kentucky, Louisiana, Mississippi, Missouri, Ohio, Oklahoma, and West Virginia. States in the next highest group (23.12 to 26.20 percent) were Alabama, Delaware, Michigan, Nebraska, North Dakota, South Carolina, South Dakota, Tennessee, Vermont, and Wyoming. States in the midgroup (21.03 to 23.11 percent) were Colorado, Georgia, Illinois, Iowa, Maine, Nevada, New Mexico, North Carolina, Pennsylvania, Virginia, and Wisconsin. States in the next lowest group (20.27 to 21.02 percent) were Arizona, District of Columbia, Kansas, Maryland, Minnesota, Montana, New Hampshire, New York, Rhode Island, and Texas. States in the lowest group (14.88 to 20.26 percent) were California, Connecticut, Florida, Hawaii, Idaho, Massachusetts, New Jersey, Oregon, Utah, and Washington.

Long description end. Return to Figure 4.

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