Full length articleSmoking-related outcomes and associations with tobacco-free policy in addiction treatment, 2015–2016
Introduction
The Centers for Disease Control and Prevention (CDC) recently reported that cigarette smoking among adults in the United States (U.S.) had decreased from 20.9% in 2005–15.1% in 2015 (Jamal et al., 2016). During this time, smoking prevalence decreased in every age group, in every racial/ethnic group, in nearly all educational attainment groups, and in all Census Regions. Although some have commented that decrease in U.S. smoking prevalence has slowed or stopped (King et al., 2011, Mendez and Warner, 2004), Jamal et al. (2016) report a statistically significant decrease from 16.8% in 2014–15.1% in 2015.
As smoking prevalence declines overall, smoking in subgroups becomes increasingly important in terms of tobacco control, health disparities (Okuyemi et al., 2015) and social justice (Healton and Nelson, 2004). Compared to 15.1% in the general population, smoking prevalence was 40.6% among persons with serious psychological distress (Jamal et al., 2016), a category that combines a number of risk groups. Smoking prevalence is 25% for persons with anxiety disorders, 30% for those with depressive disorders (Grant et al., 2004), and 50–80% for those with schizophrenia (Prochaska et al., 2008, Schroeder, 2009). Lasser et al. (2000) estimated that 44% of all cigarettes smoked in the U.S. were consumed by persons with mental health diagnoses, and Higgins et al. (2016) estimated that 14% of all U.S. smokers are persons with drug and/or alcohol abuse problems.
A review of smoking prevalence in U.S. addiction treatment programs, from 1987 to 2009, found a median annual smoking prevalence of 76.3% (Guydish et al., 2011a). Among all admissions to addiction treatment in New York State, annual smoking rates ranged from 69.5% in 2007–71.2% in 2012 (Guydish et al., 2015). A 2015 survey of persons enrolled in 24 addiction treatment programs reported a smoking rate of 77.9% (Guydish et al., 2016b). These studies show no observable decrease in smoking prevalence among persons enrolled in addiction treatment, from 1987 to 2015, and highlight the need for innovative approaches to smoking in this population.
There are, however, reasons to expect that smoking could decrease among those enrolled in addiction treatment. First is the continuing decline in population smoking prevalence (Jamal et al., 2016). Second, access to tobacco cessation services should be expanding, based on U.S. mental health parity legislation (Garcia, 2010), because the 2010 Affordable Care Act (ACA) was expected to in increase the numbers of persons who receive addiction treatment (Buck, 2011), and because the ACA required coverage of smoking cessation intervention. Third, the 2009 Family Smoking Prevention and Tobacco Control Act placed regulatory authority over tobacco products into the hands of the Food and Drug Administration (FDA), with the mandate to protect public health (National Institutes of Health, 2012).
The addiction treatment field has also noted the high rates of smoking among clients (Guydish et al., 2011a), the excess tobacco-related mortality in this population (Bandiera et al., 2015, Hser et al., 1994, Hurt et al., 1996), and the impact of smoking cessation on other treatment outcomes (McKelvey et al., 2017, Prochaska et al., 2004, Thurgood et al., 2016). Some have called for tobacco policies in state-level treatment systems (Krauth and Apollonio, 2015), and some states have implemented such policies, including tobacco-free grounds. (Brown et al., 2012, Drach et al., 2012, Williams et al., 2005).
Tobacco-free grounds policies include complete smoking bans on all program grounds (CDC, 2015), and may offer a policy approach to epidemic smoking in addiction treatment. Workplace smoking bans increase smoking cessation and reduce cigarette consumption (Bauer et al., 2005, Fichtenberg and Glantz, 2002), and complete bans reduce smoking more than partial bans (Tabuchi et al., 2016). Around one third of U.S. addiction treatment facilities had smoking bans on program property (Muilenburg et al., 2016, Shi and Cummins, 2015, Substance Abuse and Mental Health Services Administration, 2017) and 7 states required comprehensive indoor and outdoor smoking bans in treatment programs (National Association of State Alcohol and Drug Abuse Directors, 2010). One review of mental health and addiction treatment centers found that smoking restrictions had little effect on clients quitting smoking (el-Guebaly et al., 2002). However, pre-post assessments of the New York State tobacco-free grounds policy found that client smoking prevalence decreased significantly from 69.4% to 62.8% (Guydish et al., 2012), and that screening for smoking and use of cessation services increased post policy (Brown et al., 2012). Eby and Laschober (2013) found greater clinician support for smoking cessation in New York programs, compared to programs in other states that had not implemented tobacco-free grounds policies. Staff smoking prevalence and client cigarette consumption declined, and client attitudes toward quitting were more positive five years after policy implementation (Pagano et al., 2016a). Apart from New York State studies, Knudsen et al. (2010) found that programs with tobacco-free grounds policies reported lower smoking prevalence among counselors than those with indoor-only policies, and Richey et al. (2017) found that tobacco-free grounds implementation was not accompanied by a decrease in client census.
The current paper asks, first, whether any changes in smoking behavior were observed among clients enrolled in addiction treatment programs from 2015 to 2016 and, second, whether tobacco-free grounds policies were associated with differences in smoking-related measures.
Section snippets
Sampling design
We recruited a random sample of addiction treatment programs through the National Institute on Drug Abuse (NIDA) Clinical Trials Network (CTN) in 2013. We first identified CTN-affiliated programs meeting these inclusion criteria: publicly-funded, had at least 60 active clients, and the program director would designate a staff liaison to coordinate with the research team. From 48 programs meeting these criteria, 33 were randomly selected and contacted. Six programs were no longer eligible, two
Smoking behavior among clients enrolled in addiction treatment programs, 2015–2016
Clients recruited in 2015 had a mean age of 38.5 (SD = 11.87), nearly half were women (48.1%), and 44% had some education beyond high school (Table 1). The 2015 sample was 56% White, 17% African American, 13.6% Hispanic, 4.5% American Indian or Alaska Native, and 2.2% Asian/Pacific Islander. Participants were recruited from outpatient (29.3%), methadone (29.9%), and residential (40.7%) programs. Most (77.4%) smoked cigarettes at least weekly, 82% used at least one tobacco product on a weekly
Discussion
In 25 addiction treatment programs, and comparing annual cross-sectional samples of clients recruited in 2015 and 2016, we observed no difference over time for smoking prevalence, staff and clients smoking together, and CPD, or for the rates of thinking of quitting, making quit attempts. We saw no difference over time for client attitudes toward quitting smoking, and a small increase for program services related to tobacco. While there is a continuing decline in smoking in the U.S. general
Role of funding source
This work was supported by grant number R01 DA036066 from the National Institute on Drug Abuse (NIDA) and the Food and Drug Administration Center for Tobacco Products, and by NIDA Center Grant P50 DA009253. The content is solely the responsibility of the authors and does not represent the official views of the NIH or the Food and Drug Administration.
Contributors
Joseph Guydish conceived the study, had oversight of all implementation and analysis and drafted the paper. Deborah Yip executed data collection, developed literature review, drafted sections of the manuscript, and interpreted qualitative data regarding program policies. Thao Le managed data, conducted analyses presented, and contributed to data interpretation. Noah Gubner executed data collection and contributed to literature review and data interpretation. Kevin Delucchi provided consulting
Conflict of interest
No conflict declared.
Acknowledgements
The authors gratefully acknowledge the support of Directors who agreed that their program could participate in the study, the program staff who coordinated site visits and data collection, and the clients who gave their time to complete study surveys.
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