yoga

Nicotine & Tobacco Research, 2019, 1517–1523 doi:10.1093/ntr/nty212 Original investigation

Received June 18, 2018; Editorial Decision September 26, 2018; Accepted October 4, 2018

© The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: [email protected].

1517

Original investigation

Yoga as a Complementary Therapy for Smoking Cessation: Results From BreathEasy, a Randomized Clinical Trial Beth C. Bock PhD1–3, Shira I. Dunsiger PhD1–3, Rochelle K. Rosen PhD1–3, Herpreet Thind PhD4, Ernestine Jennings PhD1–3, Joseph L. Fava PhD3, Bruce M. Becker MD1,2,5, James Carmody PhD6, Bess H. Marcus PhD2

1Department of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University, Providence, RI; 2Brown School of Public Health, Brown University, Providence, RI; 3Centers for Behavioral and Preventive Medicine, The Miriam Hospital, Providence, RI; 4Department of Public Health, Zuckerberg College of Health Sciences, University of Massachusetts Lowell, Lowell, MA; 5Rhode Island Hospital, Providence, RI; 6Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA

Corresponding Author: Beth C. Bock, PhD. The Miriam Hospital, Coro West, Suite 309, 164 Summit Ave, Providence, RI 02906, USA. E-mail: [email protected]

Abstract

Introduction: There is evidence that Yoga may be helpful as an aid for smoking cessation. Yoga has been shown to reduce stress and negative mood and may aid weight control, all of which have proven to be barriers to quitting smoking. This study is the first rigorous, randomized clinical trial of Yoga as a complementary therapy for smokers attempting to quit. Methods: Adult smokers (N  =  227; 55.5% women) were randomized to an 8-week program of cognitive-behavioral smoking cessation and either twice-weekly Iyengar Yoga or general Wellness classes (control). Assessments included cotinine-verified 7-day point prevalence abstinence at week 8, 3-month, and 6-month follow-ups. Results: At baseline, participants’ mean age was 46.2 (SD  =  12.0) years and smoking rate was 17.3 (SD  =  7.6) cigarettes/day. Longitudinally adjusted models of abstinence outcomes demonstrated sig- nificant group effects favoring Yoga. Yoga participants had 37% greater odds of achieving abstinence than Wellness participants at the end of treatment (EOT). Lower baseline smoking rates (≤10 cigarettes/ day) were also associated with higher likelihood of quitting if given Yoga versus Wellness (OR = 2.43, 95% CI = 1.09% to 6.30%) classes at EOT. A significant dose effect was observed for Yoga (OR = 1.12, 95% CI = 1.09% to 1.26%), but not Wellness, such that each Yoga class attended increased quitting odds at EOT by 12%. Latent Class Modeling revealed a 4-class model of distinct quitting patterns among participants. Conclusions: Yoga appears to increase the odds of successful smoking abstinence, particularly among light smokers. Additional work is needed to identify predictors of quitting patterns and inform adjustments to therapy needed to achieve cessation and prevent relapse. Implications: This study adds to our knowledge of the types of physical activity that aid smok- ing cessation. Yoga increases the odds of successful smoking abstinence, and does so in a dose- response manner. This study also revealed four distinct patterns of smoking behavior among participants relevant to quitting smoking. Additional work is needed to determine whether vari- ables that are predictive of these quitting patterns can be identified, which might suggest modifica- tions to therapy for those who are unable to quit.

Introduction

Vigorous, aerobic exercise is an effective aid for smoking cessa- tion as it reduces postcessation weight gain,1,2 improves mood, and reduces cigarette cravings and withdrawal symptoms,3–7 offering sig- nificant benefits for smokers trying to quit by directly addressing fears of weight gain and ameliorating the physiological and affective symptoms of nicotine withdrawal.7,8

Yoga may offer additional benefits beyond those seen for stand- ard aerobic exercise. Yoga has been shown to improve mood and reduce stress through the practice of asanas (Yoga postures), pra- nayama (breathing exercises), and seated meditation.9,10 Yoga also enhances mindfulness11—the purposeful direction of attention to present-moment experiences (sensations, perceptions, and thoughts) in a nonjudgmental way.12 Increases in mindfulness are associated with reductions in perceived stress, psychological distress, and cogni- tive reactivity.13,14 Mindfulness may also reduce symptoms of nicotine withdrawal, improve coping with cravings, and increase the cogni- tive deliberation needed to make effective choices to avoid smoking in tempting situations.11,15,16 Thus, Yoga may have special relevance for smokers who are trying to quit.9,15,16 Yoga practice also improves weight control.17–22 By addressing barriers such as stress, cravings, and weight concerns, and improving mindfulness, Yoga has some potential as an effective complementary therapy for smoking cessa- tion. This study investigates the efficacy of Yoga as a complementary therapy for smoking cessation in a rigorously designed randomized prospective clinical trial. We hypothesized that participants given the Yoga intervention would show a significantly higher abstinence rates compared to a control condition.

Methods

Study Design Overview Adult smokers were randomly assigned in a 1:1 ratio to an 8-week program of either (1) Yoga or (2) general Wellness, which controlled for contact time and participant burden. In both programs, partici- pants met for 1 hour, twice weekly. Participants also attended 1-hour weekly of group-based smoking cessation counseling. Smoking abstinence was measured at the end of treatment (EOT), and at 3- and 6-month follow-ups. A detailed description of the study design and procedures has been published elsewhere.23 Recruitment and follow-up retention are presented in the consort diagram (Figure 1). All sessions were conducted at a university-affiliated hospital in New England.

Interventions Smoking Cessation Counseling This intervention consisted of group-based cognitive-behavioral therapy for smoking cessation delivered by PhD-level psychologists.23 Session content was similar to that used in our previous studies1,4,24 and included planning for the program’s targeted quit day (week 4), handling smoking triggers, coping with cravings, and managing withdrawal. A  study manual was used to ensure that topics were covered consistently across study arms and multiple cohorts. All ses- sions were audio-recorded and coded to ensure treatment fidelity.

Yoga Intervention This study used Iyengar Yoga25 because it emphasizes postural alignment and the use of props (eg, blocks and straps) to facilitate learning and reduce injury risk. Classes included 5 minutes of pra- nayama, 45 minutes of dynamically linked asanas, and 5–10 minutes

of resting meditation. Classes were conducted by certified Iyengar instructors with more than 15 years’ experience. A manual was used to ensure consistent program delivery. Handouts showing the asanas and sequence used for the current week’s practice were given to par- ticipants weekly to encourage home practice.

Wellness Control Group Wellness classes followed a format used in previous studies1,24 and consisted of videos, lectures, and demonstrations on a variety of health topics (eg, cancer screenings, sleep hygiene, and healthy diet) followed by a discussion guided by the study Wellness counselor or other health care professional (eg, sleep expert).

Recruitment, Screening, and Randomization Procedures Advertisements were placed on local radio stations and Web sites. Flyers were posted at physician’s offices and retail outlets. Advertisements emphasized the smoking cessation program and explained that participants would also be randomized to a Wellness or Yoga program. Callers were screened for eligibility by research assistants and were excluded if they were pregnant, had a body mass index of more than 40 kg/m2, smoked less than 5 cigarettes/day, were currently enrolled in a quit-smoking program, were using medica- tions to quit smoking, or had a medical condition that might make participation in Yoga difficult or potentially hazardous (eg, heart failure, ischemia, and hypertension).

Eligible individuals attended an orientation session to learn about study details and expectations. After providing written consent and completing baseline assessments, participants were randomized using a permuted block randomization stratified on gender and level of nicotine dependence (procedural details described elsewhere).23 All procedures and materials were approved by the Miriam Hospital Clinical Research Review Board (IRB registration no.0000482).

Assessments Assessments were obtained by research assistants blind to random- ization assignment. Participants were compensated $30 and $50 for completing the 3- and 6-month follow-ups, respectively.

Smoking Outcomes Research assistants collected data weekly on participant class attend- ance, smoking rate (cigarettes per day), quit status, quit attempts, and use of medications. Self-reports of 7 days of nonsmoking were verified weekly by exhaled carbon monoxide (<10  ppm indicates abstinence for the previous 12–24 hours)26 and by saliva cotinine (<15  mg/mL) at EOT (week 8)  and all follow-ups.27 Participants reporting 7-day point prevalence abstinence (7PPA) at EOT and follow-up were considered continuously abstinent.

Smoking-Related Covariates At baseline, participants completed a 25-item questionnaire con- cerning their smoking history, including smoking rate, previous quit attempts, and use of medications. At baseline and all follow-ups, participants were assessed for nicotine dependence (Fagerström Test for Nicotine Dependence),28 and motivation to quit smoking, confi- dence in quitting, and readiness to quit using three items answered on a 10-point Likert scale from “not at all” to “extremely.”29

Other Covariates Demographic information (eg, age, gender, and ethnicity) was col- lected at baseline along with measurements of height and weight.

Nicotine & Tobacco Research, 2019, Vol. 21, No. 111518

Analyses Baseline measures were summarized using descriptive statistics, and between-group differences in baseline characteristics were tested.30 Potential differences between cohorts in baseline characteristics were explored using parametric (analysis of variance) and nonparametric (chi-square) tests as appropriate.

Using a series of longitudinal models implemented with gener- alized estimating equations with robust standard errors, we tested the effect of randomization on binary smoking outcomes (7PPA and continuous abstinence) over time (smoking status at week 5 through follow-up) controlling for potential confounders including contam- ination risk (defined as any Wellness participant who reported par- ticipation in Yoga during the 8-week treatment). Models included effects of intervention, time, time × intervention, as well as potential confounders. Data were clustered within participant within cohort, and standard errors were adjusted accordingly. We explored poten- tial moderating effects of smoking rate at baseline by including main effects of smoking rate, and all two- and three-way interactions between smoking rate, time, and treatment group.

We tested the effects of randomization on mean smoking rate over time using a longitudinal mixed effects model in which smok- ing rates postquit date (week 5)  through follow-up were regressed

on time, group, and time × group. Models adjusted for confound- ers including contamination risk and baseline smoking rate, and included a subject-specific intercept to adjust for repeated measures of the outcome within participant. Potential cohort effects were also explored. As with our primary outcomes, we explored potential moderating effects of baseline smoking rate on treatment effects.

Using Latent Class Models (LCMs), we sought to identify smok- ing patterns during the treatment period (exploratory analysis). The outcome of interest was self-reported 7PPA from quit date through EOT, with cotinine validation at week 8. LCMs assume the popula- tion is made up of a finite number of patterns (smoking patterns in this case). This technique reduces participant-level data from a vec- tor of up to 8 weeks of data to a single class, corresponding to their most likely pattern of smoking behavior. Class (pattern) provides an objective grouping that can be used as a predictor or outcome in subsequent analyses. To identify the number of classes supported by the data, we fit a series of LCMs ranging from 2 to 6 classes and identified the model that minimized the Bayesian information criteria value (which maximizes fit). The optimal solution was a 4-class model (significant model fit and significantly lowest Bayesian information criteria), which is presented later. Classes were com- pared based on baseline characteristics, randomized group, smoking

Figure 1. Consort diagram.

Nicotine & Tobacco Research, 2019, Vol. 21, No. 11 1519

rates at 3- and 6-month follow-up, and baseline motivational vari- ables (ie, motivation, readiness, and confidence) using chi-square tests and analysis of variance as appropriate. Finally, we explored potential dose effects both within and across groups using a similar modeling strategy.

All analyses were conducted on the intent-to-treat sample (N = 227). Models used likelihood-based approaches to estimation and thus made use of all available data without directly imputing missing data. Results were compared to the conservative assumption that missing equals smoking (in the case of binary outcomes) and did not differ substan- tially from the maximum likelihood estimation. All analyses were run using SAS v. 9.3 and R, and significance value was set at α = .05 a priori.

Results

Sample Among participants (N = 227) randomized at baseline, 55.5% were women, 72.3% had attended at least some college, 42.3% were mar- ried or partnered, and 55.9% were employed full time. Mean age was 46.2 (SD = 12.0) years. Mean smoking rate at baseline was 17.0 (SD = 7.8) cigarettes/day. There were no significant between-group differences in baseline characteristics (Table  1), and no differences between study cohorts. Overall, the study retention rate was 94.7% through final follow-up with no difference between groups (p > .05).

Smoking Outcomes Longitudinal adjusted models indicate significant group effects favoring Yoga with respect to 7PPA at EOT (odds ratio [OR] = 1.37, 95% confidence interval [CI] = 1.07% to 2.79%). The odds of 7PPA at EOT were 37% higher for Yoga versus Wellness participants. Effects were no longer significant at 3- and 6- month follow-up (ps > .05). There were no significant effects of group on continuous abstin- ence (p = .52). Overall, 11.2% of participants had prolonged abstin- ence at 6 months, with no significant group effect (p = .92).

Moderating Effects Exploration of the moderating effects of baseline smoking rate sug- gests there were significant effects of group on 7PPA at EOT among those with low smoking rates at baseline (≤10 cigarettes/day = 25th percentile; OR  =  2.43, 95% CI  =  1.09% to 6.30%). Among light smokers at baseline, the odds of 7PPA at EOT for Yoga were 2.43 times that of Wellness. There were no moderating effects of baseline smoking rate on continuous abstinence (p > .05).

Adjusted models indicate that Yoga participants were smoking significantly fewer cigarettes per day at EOT compared to Wellness (adjusting for baseline). Specifically, there was a 1.54 (standard error = 0.59, p = .01) difference in cigarettes per day favoring Yoga at EOT. This effect was most pronounced among those with higher smoking rates at baseline (≥20 cigarettes/day  =  75th percentile). Among these individuals, those in Yoga smoked 2.66 fewer ciga- rettes per day at EOT compared to Wellness (standard error = 1.33, p = .04).

Patterns of Quitting Behavior LCM analysis suggests a 4-class model is best supported by the data. Patterns show that 16% of participants quit by week 4 and had high probability of remaining quit through week 8 (Class 1: Quit Date Quitters). Most participants (71%) were not able to achieve abstinence (Class 2: Non-quitters), 5% of participants were slow and steady quitters such that the slope increased over time with

high probability of being quit by EOT (Class 3: Slow Quitters), and 8% of participants had high probability of quitting on or before week 4 with a decline in odds of remaining quit thereafter (Class 4: Relapsers). These patterns are depicted in Figure 2.

Participants randomized to Yoga were significantly more likely to be Quit Date Quitters or Slow Quitters compared to Wellness partic- ipants (p = .04). Both Quit Date Quitters and Slow Quitters (67.6% and 60%, respectively) were more likely to report 7PPA at 3 months than Non-quitters and Relapsers (2.2% and 14.3%, respectively). Although there were no significant between-class differences in base- line demographics (Table 2), there was a significant effect of baseline smoking rate on the distribution of classes. Specifically, light smok- ers (≤10 cigarettes/day) were significantly more likely to be Slow Quitters compared to other classes (p = .04).

There were significant between-class differences in readiness and confidence in quitting (and a trend for motivation to quit) at

Table 1. Participant Characteristics at Baseline by Intervention Group (N = 227)

Variable Overall, N = 227

Yoga, n = 113

Wellness, n = 114

Age, mean (SD), y 46.2 (12.0) 46.1 (12.0) 46.4 (12.0) Gender (female), No. (%) 126 (55.5) 67 (59.3) 59 (51.8) Race (white), No. (%) 195 (85.9) 102 (90.3) 93 (81.6) Hispanic/Latino, No. (%) 8 (3.5) 4 (3.5) 4 (3.5) Education level, No. (%) High school graduate

or less 63 (27.8) 31 (27.4) 32 (28.1)

At least some college 138 (60.8) 66 (58.4) 72 (63.2) At least some graduate

school 26 (11.5) 16 (14.2) 10 (8.8)

Income ($), No. (%) <11 500 32 (14.1) 12 (10.6) 20 (17.5) 11 501–50 000 91 (40.1) 45 (39.8) 46 (40.4) 50 001–100 000 71 (31.3) 40 (35.4) 31 (27.2) >100 000 19 (8.4) 11 (9.7) 8 (7.0) Don’t know/refuse 14 (6.2) 5 (4.4) 9 (7.9)20 Marital status, No. (%) Single 88 (38.8) 50 (44.2) 38 (33.3) Single, live with partner 34 (15.0) 11 (9.7) 23 (20.2) Married 62 (27.3) 33 (29.2) 29 (25.4) Separated, divorced,

widowed 43 (18.9) 19 (16.8) 24 (21.1)

Employment status, No. (%) Employed full time 127 (55.9) 66 (58.4) 61 (53.5) Employed part-time 22 (9.7) 15 (13.3) 7 (6.1) Unemployed 47 (20.7) 21 (18.6) 26 (22.8) Other 31 (13.7) 11 (9.7) 20 (17.5) BMI (baseline), mean (SD),

kg/m2 27.3 (5.0) 27.1 (4.7) 27.6 (5.3)

Cigarettes per day (baseline), mean (SD)

17.0 (7.8) 16.9 (7.5) 17.1 (8.1)

Readiness to quit, mean (SD)

7.9 (1.8) 8.0 (1.8) 7.8 (1.8)

Confidence to quit, mean (SD)

7.8 (1.9) 7.8 (1.9) 7.8 (1.9)

Motivated to quit, mean (SD)

8.7 (1.4) 8.7 (1.5) 8.7 (1.5)

Fagerström score, mean (SD)

4.9 (2.1) 4.9 (2.1) 4.9 (2.0)

BMI  =  body mass index; SD  =  standard deviation. No significant between- group differences.

Nicotine & Tobacco Research, 2019, Vol. 21, No. 111520

baseline. Relapsers had highest mean scores on readiness to quit (9.18, SD = 1.07), and Slow Quitters had the lowest mean readiness scores (7.50, SD  =  2.15) at baseline. However, Quit Date Quitters had significantly higher confidence to quit compared to other classes,

and Slow Quitters had the lowest mean confidence scores: Quit Date Quitters = 8.56 (SD = 1.46), Non-quitters = 7.62 (SD = 1.92), Slow Quitters  =  1.50 (SD  =  1.98), Relapsers  =  8.47 (SD  =  1.97). Slow quitters and Relapsers trended toward higher motivation scores at

Figure 2. Latent class Model (LCM) resulting patterns of quitting over time among all participants.

Table 2. Participant Demographics by Pattern

Variable Quit Date Quitters,

n = 36 Non-quitters, n = 162 Slow Quitters, n = 12 Relapsers, n = 17

Age, mean (SD), y 49.47 (12.50) 45.25 (11.41) 48.33 (11.84) 47.12 (15.48) Gender (female), No. (%) 18 (50.0) 94 (58.0) 6 (50.0) 8 (47.1) Race (white), No. (%) 34 (94.4) 147 (90.7) 10 (83.3) 15 (88.2) Hispanic/Latino, No. (%) 1 (2.8) 7 (4.3) 0 (0) 0 (0) Education level, No. (%) High school graduate or less 10 (27.8) 48 (29.6) 2 (16.7) 3 (17.6) At least some college 18 (50.0) 99 (61.1) 9 (75.0) 12 (70.6) At least some graduate school 8 (22.2) 15 (9.3) 1 (8.3) 2 (11.8) Income ($), No. (%) <11 500 2 (5.6) 25 (15.4) 3 (25.0) 2 (11.8) 11 501–50 000 16 (44.4) 62 (38.3) 6 (50.0) 7 (41.2) 50 001–100 000 12 (33.3) 50 (30.9) 2 (16.7) 7 (41.2) >100 000 5 (13.9) 12 (7.4) 1 (8.3) 1 (5.9) Don’t know/refuse 1 (2.8) 13 (8.0) 0 (0) 0 (0) Marital status, No. (%) Single 14 (38.9) 65 (40.1) 4 (33.3) 5 (29.4) Single, live with partner 3 (8.3) 16 (16.0) 2 (16.7) 3 (17.6) Married 11 (30.6) 43 (26.5) 2 (16.7) 6 (35.3) Separated, divorced, widowed 8 (22.2) 28 (17.3) 4 (33.3) 3 (17.6) Employment status, No. (%) Employed full time 23 (63.9) 87 (53.7) 7 (58.3) 10 (58.8) Employed part-time 3 (8.3) 14 (8.6) 2 (16.7) 3 (17.6) Unemployed 4 (11.1) 39 (24.1) 2 (16.7) 2 (11.8) Other 6 (16.7) 22 (13.6) 1 (8.3) 2 (11.8) BMI (baseline), mean (SD), kg/m2 27.54 (4.08) 27.40 (5.11) 28.88 (5.34) 25.46 (4.98) Cigarettes per day (baseline), mean (SD) 15.75 (7.99) 16.99 (7.81) 14.75 (7.03) 18.12 (8.28) Fagerström score, mean (SD) 4.69 (2.27) 4.94 (2.02) 5.17 (2.76) 5.18 (1.67)

BMI = body mass index; SD = standard deviation.

Nicotine & Tobacco Research, 2019, Vol. 21, No. 11 1521

baseline (9.25, SD  =  1.06 and 9.29, SD  =  1.05, respectively) com- pared to Quit Date Quitters (8.92, SD  =  1.27) and Non-quitters (8.54, SD = 1.52). There were no other differences in baseline vari- ables between classes (ps > .05).

Treatment Dose Effects There was no significant difference in the average number of classes attended (of possible 24)  during treatment between Yoga (mean = 16.49, SD = 5.92) and Wellness (mean = 16.61, SD = 7.42) participants (p > .05). Among Yoga participants, there was a signifi- cant association between total dose of treatment received and 7PPA (OR = 1.12, 95% CI = 1.09% to 1.26%), such that each additional session attended was associated with a 12% increase in the odds of being quit at EOT. There was no significant dose effect among Wellness participants (p > .05).

Home Practice Home practice of Yoga was tracked weekly through 6-month follow-up. At EOT, 47% of Yoga participants reported practic- ing Yoga at home (an average of 2.56 days/week). At 3 months, Yoga participants reported an average of 90.00  min/week of Yoga (SD  =  50.90) and 75.36  min/week of Yoga (SD  =  74.25) at 6 months.

Discussion

This is the first large-scale randomized controlled trial to suc- cessfully recruit and retain adult smokers in the United States that examined Yoga as a complementary treatment for smok- ing cessation. This study compared Yoga to a Wellness control to complement standard smoking cessation counseling based on cognitive-behavioral therapy, a well-tested, effective intervention for tobacco cessation.31 The study design was stringent in that both groups were proved with a high-quality, intensive therapy for smoking cessation. Thus, we could test the relative efficacy of Yoga to a comparison arm that effectively controlled for contact time, attention, and subject burden.

Results indicated that in this sample, Iyengar Yoga was highly feasible and acceptable based on strong attendance and retention rates. Participation was enthusiastic as demonstrated by our 94.7% retention rate across both groups.

Longitudinally adjusted models showed significant results favor- ing Yoga. Participants in the Yoga group were 37% more likely to quit than those in Wellness group. Yoga also had differential effects between heavier and lighter smokers in that lighter smokers were over twice as likely to quit if given Yoga.

Although most participants did not achieve smoking abstinence, participants in both groups significantly decreased their daily cigar- ette consumption by the EOT. Yoga produced a greater reduction in smoking rate by EOT compared to Wellness, particularly among those who were heavier smokers at baseline. Thus, Yoga had a posi- tive effect on smoking among all participants compared to controls. Those who were smoking fewer cigarettes at baseline were more likely to quit if they received Yoga, and heavy smokers were more likely to cut down, a positive step on the path to improved health and eventual cessation.

LCM revealed 4 distinct patterns of quitting behavior that differed significantly between treatment arms. Yoga partici- pants were more likely to be represented in the two “successful”

patterns of quitting: either those able to quit on the designated quit day (week 4)  and remain quit, or those who experienced a gradual reduction in smoking rate leading to full abstinence by EOT. In contrast, Wellness participants were more likely to never achieve full abstinence or to quit early (before the designated quit day), and relapse to smoking before EOT. Future work is needed to identify whether these patterns can be predicted and treatment adjustments made for individuals likely to relapse early or never quit.

Results of this study also provide an intriguing hint that some variables or combination of variables may predict these patterns. Readiness, confidence, and motivation for quitting have been pre- dictive of successful smoking cessation in multiple studies.32,33 However, in this study we saw noteworthy differences in the dis- tribution of these constructs based on pattern of quitting. For example, Relapsers scored high on all three measures (readiness, confidence, and motivation), whereas Slow Quitters scored high on motivation, but lower on readiness and far lower in confi- dence. It is possible that other factors may predict which pattern an individual falls into and thus suggest options for enhanced treatment approaches. For example, it would be unsurpris- ing if Relapsers were relatively low on mindfulness and/or high on impulsivity at program entry. If supported, a Yoga program emphasizing mindfulness training might address these deficits more intensely at the beginning and perhaps reduce the likelihood of early quitting that leads to quick relapse. Similarly, there is a substantial literature showing that comorbid affective symptoms such as anxiety and depression are associated with smoking and predictive of postcessation relapse.34,35 It may be fruitful to iden- tify whether and how the patterns of quitting and non-quitting found in the present study may map onto these specific affective states as well as transdiagnostic markers of emotional vulnerabil- ity, such as anxiety sensitivity, low distress tolerance, and similar psycho-affective characteristics.

Limitations Both treatment arms were labor-intensive for participants, requir- ing 3 hours weekly for 8 weeks. To enhance potential dissem- ination, it would be valuable to test whether a home-delivered Yoga program would be effective. Both arms were provided with a strong well-validated cognitive-behavioral therapy smoking cessation program, leading to higher abstinence rates than might be the seen in less intensive programs. The Wellness program was not a real-world comparison, in that smoking cessation pro- grams are not typically paired with Wellness programs. However, this comparison was chosen to avoid any bias that might result from unequal subject burden between conditions. We did not use medications to aid smoking cessation although medications are the current standard of care.31 We were concerned that if Yoga produced a small positive effect on cessation, that effect might be effectively washed out by the addition of medications, which typically produce a doubling of effect size.31 To detect a poten- tially small intervention effect above and beyond the impact of medications would require a much larger sample. Individuals seeking a program like Yoga to aid them in quitting smoking may be disinclined to use medications, although there are cur- rently no data to support or refute this. Similarly, many individu- als cannot use or choose not to use quit-smoking medications because of cost, interactions with their other medications, or

Nicotine & Tobacco Research, 2019, Vol. 21, No. 111522

medical contraindications;36 therefore, we studied Yoga as a po- tential option for those who cannot or will not use medications for quitting.

Conclusions

Yoga appears to aid some smokers during quit attempts. Yoga may be particularly effective for lighter smokers, and higher doses of Yoga (eg, more frequent classes or programs of longer duration) may be most effective. Additional work is needed to determine whether we can identify predictors of quitting patterns and use this informa- tion to make adjustments to therapy in order to maximize treatment efficacy for each smoker.

Funding Funding for this study was provided by a grant from the National Institutes of Health, National Center for Complementary and Integrative Health (R01 AT006948 to BB).

Declaration of Interests The authors have no competing financial interests to declare.

References 1. Marcus BH, Albrecht AE, King TK, et  al. The efficacy of exercise as an

aid for smoking cessation in women: a randomized controlled trial. Arch Intern Med. 1999;159(11):1229–1234.

2. Ussher MH, Taylor AH, Faulkner GE. Exercise interventions for smoking cessation. Cochrane Database Syst Rev. 2014;(4):CD002295.

3. Annesi JJ. Changes in depressed mood associated with 10 weeks of mod- erate cardiovascular exercise in formerly sedentary adults. Psychol Rep. 2005;96(3 Pt 1):855–862.

4. Bock BC, Marcus BH, King TK, Borrelli B, Roberts MR. Exercise effects on withdrawal and mood among women attempting smoking cessation. Addict Behav. 1999;24(3):399–410.

5. Dunn AL, Trivedi MH, O’Neal HA. Physical activity dose-response effects on outcomes of depression and anxiety. Med Sci Sports Exerc. 2001;33(suppl 6):S587–S597; discussion 609.

6. Matsouka O, Kabitsis C, Harahousou Y, Trigonis I. Mood alterations fol- lowing an indoor and outdoor exercise program in healthy elderly women. Percept Mot Skills. 2005;100(3 Pt 1):707–715.

7. Ussher M, Nunziata P, Cropley M, West R. Effect of a short bout of exercise on tobacco withdrawal symptoms and desire to smoke. Psychopharmacology (Berl). 2001;158(1):66–72.

8. Taylor AH, Katomeri M, Ussher M. Acute effects of self-paced walking on urges to smoke during temporary smoking abstinence. Psychopharmacology (Berl). 2005;181(1):1–7.

9. Li AW, Goldsmith CA. The effects of yoga on anxiety and stress. Altern Med Rev. 2012;17(1):21–35.

10. Shahab L, Sarkar BK, West R. The acute effects of yogic breathing exercises on craving and withdrawal symptoms in abstaining smokers. Psychopharmacology (Berl). 2013;225(4):875–882.

11. Gard T, Brach N, Hölzel BK, Noggle JJ, Conboy LA, Lazar SW. Effects of a yoga-based intervention for young adults on quality of life and perceived stress: the potential mediating roles of mindfulness and self-compassion. J Posit Psychol. 2012;7(3):165–175.

12. Kabat-Zinn J. Full Catastrophe Living: Using the Wisdom of Your Body and Mind to Face Stress, Pain, and Illness. New York, NY: Delta Trade; 2009.

13. Carmody J, Baer RA. Relationships between mindfulness practice and levels of mindfulness, medical and psychological symptoms and well-being in a mindfulness-based stress reduction program. J Behav Med. 2008;31(1):23–33.

14. Raes F, Dewulf D, Van Heeringen C, Williams JM. Mindfulness and reduced cognitive reactivity to sad mood: evidence from a correlational study and a non-randomized waiting list controlled study. Behav Res Ther. 2009;47(7):623–627.

15. McClernon FJ, Westman EC, Rose JE. The effects of controlled deep breathing on smoking withdrawal symptoms in dependent smokers. Addict Behav. 2004;29(4):765–772.

16. Ussher M, West R, Doshi R, Sampuran AK. Acute effect of isometric exercise on desire to smoke and tobacco withdrawal symptoms. Hum Psychopharmacol. 2006;21(1):39–46.

17. Bera TK, Rajapurkar MV. Body composition, cardiovascular endurance and anaerobic power of yogic practitioner. Indian J Physiol Pharmacol. 1993;37(3):225–228.

18. Emery CF, Blumenthal JA. Perceived change among participants in an exercise program for older adults. Gerontologist. 1990;30(4):516–521.

19. Kristal AR, Littman AJ, Benitez D, White E. Yoga practice is associated with attenuated weight gain in healthy, middle-aged men and women. Altern Ther Health Med. 2005;11(4):28–33.

20. Mahajan AS, Reddy KS, Sachdeva U. Lipid profile of coronary risk subjects following yogic lifestyle intervention. Indian Heart J. 1999;51(1):37–40.

21. Roland KP, Jakobi JM, Jones GR. Does yoga engender fitness in older adults? A critical review. J Aging Phys Act. 2011;19(1):62–79.

22. Schmidt T, Wijga A, Von Zur Mühlen A, Brabant G, Wagner TO. Changes in cardiovascular risk factors and hormones during a comprehensive resi- dential three month kriya yoga training and vegetarian nutrition. Acta Physiol Scand Suppl. 1997;640:158–162.

23. Bock BC, Rosen RK, Fava JL, et al. Testing the efficacy of yoga as a com- plementary therapy for smoking cessation: design and methods of the BreathEasy trial. Contemp Clin Trials. 2014;38(2):321–332.

24. Marcus BH, King TK, Albrecht AE, Parisi AF, Abrams DB. Rationale, de- sign, and baseline data for Commit to Quit: an exercise efficacy trial for smoking cessation among women. Prev Med. 1997;26(4):586–597.

25. Iyengar BKS. BKS Iyengar Yoga: The Path to Holistic Health. New York, NY: DK Publishing; 2007.

26. Hughes JR, Keely JP, Niaura RS, Ossip-klein DJ, Richmond RL, Swan GE. Measures of abstinence in clinical trials: issues and recommendations. Nicotine Tob Res. 2003;5(1):13–25.

27. Benowitz NL, Jacob P III, Ahijevych K, et  al.; SRNT Subcommittee on Biochemical Verification. Biochemical verification of tobacco use and ces- sation. Nicotine Tob Res. 2002;4(2).

28. Heatherton TF, Kozlowski LT, Frecker RC, Fagerström KO. The Fagerström test for nicotine dependence: a revision of the Fagerström tolerance ques- tionnaire. Br J Addict. 1991;86(9):1119–1127.

29. Bock BC, Morrow KM, Becker BM, et  al. Yoga as a complementary treatment for smoking cessation: rationale, study design and participant characteristics of the Quitting-in-Balance study. BMC Complement Altern Med. 2010;(10):14.

30. Bock BC, Thind H, Dunsiger S, et  al. Who Enrolls in a Quit Smoking Program with Yoga Therapy? Am J Health Behav. 2017;41(6):740–749.

31. Fiore MC, Jaen CR, Baker TB, et al. Treating Tobacco Use and Dependence: 2008 Update. Clinical Practice Guideline. Rockville, MD: US Department of Health and Human Services, Public Health Service; 2008.

32. Borland R, Yong HH, Balmford J, et al. Motivational factors predict quit attempts but not maintenance of smoking cessation: findings from the international tobacco control four country project. Nicotine Tob Res. 2010;12(suppl):S4–S11.

33. Boudreaux ED, Sullivan A, Abar B, Bernstein SL, Ginde AA, Camargo CA Jr. Motivation rulers for smoking cessation: a prospective observational exam- ination of construct and predictive validity. Addict Sci Clin Pract. 2012;7:8.

34. Leventhal AM, Zvolensky MJ. Anxiety, depression, and cigarette smok- ing: a transdiagnostic vulnerability framework to understanding emotion- smoking comorbidity. Psychol Bull. 2015;141(1):176–212.

35. Shiffman S, Paty JA, Gnys M, Kassel JA, Hickcox M. First lapses to smok- ing: within-subjects analysis of real-time reports. J Consult Clin Psychol. 1996;64(2):366–379.

36. Vogt F, Hall S, Marteau TM. Understanding why smokers do not want to use nicotine dependence medications to stop smoking: qualitative and quantitative studies. Nicotine Tob Res. 2008;10(8):1405–1413.

Nicotine & Tobacco Research, 2019, Vol. 21, No. 11 1523