Vulnerability to smokeless tobacco use among those dependent on alcohol or illicit drugs

Changes in Substance Use Treatment Providers' Delivery of the 5A's for Non-Cigarette Tobacco Use in the Context of a Comprehensive Tobacco-Free Workplace Program Implementation

Tobacco use treatment is not prioritized in substance use treatment centers (SUTCs), leading to tobacco-related health inequities for patients with substance use disorders (SUDs) and necessitating efforts to enhance providers' care provision. Training providers on how to treat tobacco use increases their intervention on patients' smoking, but limited work addresses its effects on their non-cigarette tobacco use intervention provision. This study redressed this gap using data from 15 unaffiliated SUTCs in Texas (serving 82,927 patients/year) participating in a tobacco-free workplace program (TFWP) that included provider education on treating tobacco use, including non-cigarette tobacco use. SUTC providers completed surveys before (n = 259) and after (n = 194) TFWP implementation. Past-month screening/intervention provision for non-cigarette tobacco use (the 5A's; ask, advise, assess, assist, arrange) and provider factors theoretically and practically presumed to underlie change [i.e., beliefs about concurrently treating tobacco use disorder (TUD) and other SUDs, self-efficacy for tobacco use assessment (TUA) delivery, barriers to treating tobacco dependence, receipt of tobacco intervention training] were assessed. Generalized linear or linear mixed models assessed changes over time from before to after TFWP implementation; low vs. high SUTC-level changes in provider factors were examined as moderators of changes in 5A's delivery. Results indicated significant improvement in each provider factor and increases in providers' asking, assisting, and arranging for non-cigarette tobacco use over time (ps < 0.04). Relative to their counterparts, SUTCs with high changes in providers' beliefs in favor of treating patients' tobacco use had greater odds of advising, assessing, assisting, and arranging patients, and SUTCs with greater barrier reductions had greater odds of advising and assisting patients. Results suggest that TFWPs can address training deficits and alter providers' beliefs about treating non-tobacco TUD during SUD care, improve their TUA delivery self-efficacy, and reduce intervention barriers, ultimately increasing intervention provision for patients' non-cigarette tobacco use. SUTCs with the greatest room for improvement in provider beliefs and barriers to care provision seem excellent candidates for TFWP implementation aimed at increasing non-cigarette tobacco use care delivery.

Internalizing problems are associated with initiation and past 30-Day use of flavored tobacco products

OBJECTIVE

Tobacco use remains disproportionately common among adults with internalizing problems. The rising prevalence of flavored tobacco use among this population may be a contributing factor. Using data from Wave 4 of the Population Assessment of Tobacco and Health Study, this study examined differences across adult ever tobacco users by severity of internalizing problems, in initiation of tobacco use with a flavored product and past 30-day (current) flavored tobacco use (n = 27,425). Severity of internalizing problems was measured using the Global Appraisal of Individual Needs-Short Screener Internalizing Disorder Screener. Tobacco use variables included initiation with or current use of a flavored product, assessed separately for each product. Weighted chi-square tests and multivariable modified Poisson regression models were used to examine the associations between severity of internalizing problems and each outcome.

RESULTS

Controlling for covariates, ever users with severe internalizing problems were more likely to have initiated with flavors for cigarettes (adjusted prevalence ratio [aPR]: 1.16, 95% confidence interval [CI]: 1.09,1.24), cigarillos (aPR: 1.09, 95% CI: 1.03, 1.16), electronic nicotine products (aPR: 1.08, 95% CI: 1.03, 1.13) and smokeless tobacco (aPR: 1.15, 95% CI: 1.04, 1.27), relative to those with low internalizing problems. Ever users with severe internalizing problems were more likely to currently use a flavored tobacco product for cigarettes (aPR: 1.15, 95% CI: 1.07, 1.24) and cigarillos (aPR: 1.15, 95% CI: 1.04, 1.28).

CONCLUSIONS

Flavored tobacco use seems disproportionately common among tobacco users with severe internalizing problems, across a variety of measures.

Association of Smokeless Tobacco Use With the Use of Other Illicit Drugs in the United States

BACKGROUND

There has been an increase in the use of smokeless tobacco recently. Whether smokeless tobacco use may predispose individuals to use other addictive substances is unknown. The use of multiple addictive substances may compound an individual's adverse health effects.

METHODS

In a cross-sectional analysis, we used the 2016-2017 Behavioral Risk Factor Surveillance System (BRFSS) survey database to identify all individuals who reported the use of smokeless tobacco and extracted data regarding baseline and demographic patterns, as well as information regarding the use of other addictive substances. Weighted multivariable logistic regression models adjusting for age, gender, race/ethnicity, poverty level, education, employment status, and marital status were used to determine the odds ratios (ORs) for use of alcohol, cigarettes, e-cigarettes, and marijuana among smokeless tobacco users.

RESULTS

We identified 30,395 (3.38%) individuals in our study population who reported smokeless tobacco use. Compared with non-users, smokeless tobacco users were more likely to be unmarried, male, Caucasian, belonging to the lower socioeconomic strata, and did not have a formal college education (P <0.01). In multivariable analyses, smokeless tobacco use was associated with a higher likelihood of cigarettes use (OR: 1.76 [95% confidence interval {CI}: 1.66-1.86, P <0.01]), e-cigarette use (OR: 1.61 [95% CI: 1.52-1.71, P <0.01]), and heavy alcohol consumption (OR:2.36 [95% CI: 2.17-2.56, P <0.01]) but not marijuana use (OR: 1.11 [95% CI: 0.90-1.38, P = 0.33]).

CONCLUSION

In a large, nationally representative sample, smokeless tobacco use was associated with the increased use of cigarettes, e-cigarettes, and alcohol. Simultaneous use of these substances may compound the adverse health effects of smokeless tobacco use. Public health interventions addressing this concerning trend are warranted.

Research on Youth and Young Adult Tobacco Use, 2013-2018, From the Food and Drug Administration-National Institutes of Health Tobacco Centers of Regulatory Science

The Tobacco Regulatory Science Program is a collaborative research effort between the National Institutes of Health (NIH) and the Food and Drug Administration (FDA). In 2013, the NIH funded 14 Tobacco Centers of Regulatory Science (TCORS), which serve as partners in establishing research, training, and professional development programs to guide FDA. Each of the fourteen TCORS, and two other NIH-funded research programs, the Center for the Evaluation of Nicotine in Cigarettes (CENIC) and the Consortium on Methods Evaluating Tobacco (COMET), pursued specific research themes relevant to FDA's priorities. A key mandate for FDA is to reduce tobacco use among young people. This article is a review of the peer-reviewed research, including published and in-press manuscripts, from the TCORS, CENIC, and COMET, which provides specific data or other findings on youth (ages 10-18 years) and/or young adults (ages 18-34 years), from 2013 to 2018. Citations of all TCORS, CENIC, and COMET articles from September 2013 to December 2017 were collected by the TCORS coordinating center, the Center for Evaluation and Coordination of Training and Research. Additional citations up to April 30, 2018 were requested from the principal investigators. A scoring rubric was developed and implemented to assess study type, primary theme, and FDA priority area addressed by each article. The major subareas and findings from each priority area are presented. There were 766 articles in total, with 258 (34%) focusing on youth and/or young adults. Findings relevant to FDA from this review concern impact analysis, toxicity, health effects, addiction, marketing influences, communications, and behavior.

IMPLICATIONS

The Tobacco Centers of Regulatory Science, CENIC, and COMET have had a high output of scientific articles since 2013. These Centers are unique in that the FDA supports science specifically to guide future regulatory actions. The 258 articles that have focused on youth and/or young adults are providing data for regulatory actions by the FDA related to the key priority areas such as the addictiveness of non-cigarette products, the effects of exposure to electronic cigarette marketing on initiation and cessation, and the impact of flavored products on youth and young adult tobacco use. Future regulations to reduce tobacco use will be guided by the cumulative evidence. These Centers are one innovative mechanism to promote important outcomes to advance tobacco regulatory science.

Is Cannabis Use Associated With Increased Risk of Cigarette Smoking Initiation, Persistence, and Relapse? Longitudinal Data From a Representative Sample of US Adults

OBJECTIVE

The current study prospectively investigated the relationship between cannabis use and cigarette smoking initiation, persistence, and relapse during a 3-year period among adults in the United States.

METHODS

Analyses included respondents who completed Waves 1 (2001-2002) and 2 (2004-2005) of the National Epidemiologic Survey on Alcohol and Related Conditions and responded to questions about cannabis use and smoking status (n = 34,639). Multivariable logistic regression models were used to calculate the odds of cigarette use at Wave 2 among Wave 1 daily smokers, nondaily smokers, former smokers, and nonsmokers by Wave 1 cannabis use.

RESULTS

In unadjusted analyses, Wave 1 cannabis use was associated with increased odds of Wave 2 daily and nondaily smoking for Wave 1 nonsmokers (daily OR = 2.90; 95% CI, 2.10-4.00; nondaily OR = 4.45; 95% CI, 3.97-5.00) and Wave 2 relapse to daily and nondaily smoking for Wave 1 former smokers (daily OR = 4.18, 95% CI, 3.01-5.81; nondaily OR = 5.24; 95% CI, 3.74-7.34). Wave 1 cannabis use was associated with decreased odds of Wave 2 smoking cessation for Wave 1 daily cigarette smokers (OR = 0.57; 95% CI, 0.51-0.64). The associations remained significant for daily smoking initiation (OR = 1.43; 95% CI, 1.06-1.93), daily smoking relapse (OR = 1.47; 95% CI, 1.00-2.16), and smoking cessation (OR = 0.77; 95% CI, 0.69-0.87) after adjusting for demographics and psychiatric disorders. Associations remained significant for nondaily smoking initiation (OR = 1.85; 95% CI, 1.59-2.16) and nondaily smoking relapse (OR = 1.63; 95% CI, 1.05-2.54) after adjusting for these covariates as well as for alcohol and substance use disorders.

CONCLUSIONS

Cannabis use was associated with increased initiation of, persistence of, and relapse to cigarette smoking. Additional attention to cannabis use in tobacco control efforts and in clinical settings aimed at reducing cigarette smoking and smoking-related negative consequences may be warranted.

How far can you go? Association between illicit drug use and academic migration

ABSTRACT Objective: To measure the prevalence of illicit drugs use in the lifetime, last year and last month, as well as the factors associated to the last year's use and its association with academic migration, among undergraduate students of a university in southern Brazil. Methods: In this cross-sectional study, data were collected through self-administered questionnaire. It was conducted a clustered systematic sampling. For multivariate analyses, it was used Poisson regression. Results: 1,423 students participated. The prevalence of illicit drug use in the lifetime, last year and last month were 42.4%, 25.5% and 17.7%, respectively. Regarding illicit substances, marijuana use was the most prevalent. The variables independently associated with illicit drugs use in the last year were academic migration, being male, younger, single, high parent's educational level, living with peers, tobacco use in the last year, and having friend and relative that have used illicit drugs. Religious practice had a protective effect. Conclusion: Individuals who migrated from their cities to study at the university are more exposed to the main risk factors pointed out by this research and hence to the use of illicit drugs. Based on these results, we suggest that universities develop evaluation, prevention, treatment or referral strategies considering specific needs of this population

Relationships Among Chewing Tobacco, Cigarette Smoking, and Chronic Health Conditions in Males 18-44 Years of Age

As more public places are designated "non-smoking," chewing tobacco could be an alternative choice for tobacco use; however, controversy exists over the long-term health effects associated with it. This study assessed the relationship between chewing tobacco, cigarette smoking, and chronic health conditions in a representative sample of males 18-44 years of age, while controlling for other variables known to be related to tobacco use. This cross sectional analysis used 2013 data from the Behavioral Risk Factor Surveillance System (BRFSS). The results indicated that about 41% of males reported one or more chronic health conditions, and that about 15% used chewing tobacco only, 21% smoked cigarettes only, and 6% did both. From adjusted analyses, those who chewed tobacco only were 49% more likely to report one or more health conditions; those who smoked cigarettes only were 34% more likely to report one or more health conditions; and those who did both were 95% more likely to report at least one health condition. Overall, any combination of tobacco use was significantly and similarly related to the increased prevalence of chronic health conditions in males aged 18-44 years. Although chewing tobacco use may not be as prevalent in the general population as cigarette smoking, clinicians should be aware of the similar health risks associated with all tobacco use at ages younger than may be expected, and encourage cessation of any tobacco use.

Trends in Daily Cannabis Use Among Cigarette Smokers: United States, 2002-2014

OBJECTIVES

To estimate changes in the prevalence of daily cannabis use among current, former, and never cigarette smokers from 2002 to 2014 in the United States.

METHODS

The National Survey on Drug Use and Health is a nationally representative cross-sectional study conducted annually among persons aged 12 years and older in the United States.

RESULTS

Daily cannabis use occurs nearly exclusively among nondaily and daily cigarette smokers compared with former and never smokers (8.03%, 9.01%, 2.79%, 1.05%, respectively). Daily cannabis use increased over the past decade among both nondaily (8.03% [2014] vs 2.85% [2002]; linear trend P < .001) and daily smokers (9.01% [2014]; 4.92% [2002]; linear trend P < .001). Daily cannabis use increased most rapidly among former cigarette smokers (2.79% [2014] vs 0.98% [2002]; linear trend P < .001).

CONCLUSIONS

Daily cannabis use occurs predominantly among cigarette smokers in the United States. Daily cannabis use increased among current, former, and never smokers over the past decade, with particularly rapid increases among youth and female cigarette smokers. Future research is needed to monitor the observed increase in daily cannabis use, especially among youths and adults who smoke cigarettes.

Co-occurring risk factors for current cigarette smoking in a U.S. nationally representative sample

INTRODUCTION

Relatively little has been reported characterizing cumulative risk associated with co-occurring risk factors for cigarette smoking. The purpose of the present study was to address that knowledge gap in a U.S. nationally representative sample.

METHODS

Data were obtained from 114,426 adults (≥18years) in the U.S. National Survey on Drug Use and Health (years 2011-13). Multiple logistic regression and classification and regression tree (CART) modeling were used to examine risk of current smoking associated with eight co-occurring risk factors (age, gender, race/ethnicity, educational attainment, poverty, drug abuse/dependence, alcohol abuse/dependence, mental illness).

RESULTS

Each of these eight risk factors was independently associated with significant increases in the odds of smoking when concurrently present in a multiple logistic regression model. Effects of risk-factor combinations were typically summative. Exceptions to that pattern were in the direction of less-than-summative effects when one of the combined risk factors was associated with generally high or low rates of smoking (e.g., drug abuse/dependence, age ≥65). CART modeling identified subpopulation risk profiles wherein smoking prevalence varied from a low of 11% to a high of 74% depending on particular risk factor combinations. Being a college graduate was the strongest independent predictor of smoking status, classifying 30% of the adult population.

CONCLUSIONS

These results offer strong evidence that the effects associated with common risk factors for cigarette smoking are independent, cumulative, and generally summative. The results also offer potentially useful insights into national population risk profiles around which U.S. tobacco policies can be developed or refined.

A review of epidemiologic research on smoking behavior among persons with alcohol and illicit substance use disorders

Persons with alcohol use disorders (AUDs) and substance use disorders (SUDs) appear to be heavily affected by cigarette smoking. In order to address the consequences of smoking in this population, an understanding of the current state of knowledge is needed. Epidemiologic research provides the opportunity to obtain detailed information on smoking behaviors in large community samples. The aim of this paper was to synthesize the epidemiologic evidence on smoking among persons with AUDs/SUDs and suggest directions for future research. Literature searches of Medline and PubMed were used to identify articles and additional articles were elicited from publication reference lists. To be included in the review, papers had to be published in English, analyze epidemiologic data, and examine an aspect of smoking behavior in persons with AUDs/SUDs. Twenty-nine studies met inclusion criteria and were included in the review. In summary, epidemiologic evidence to date suggests greater lifetime and current smoking, nicotine dependence, and non-cigarette tobacco use; lower quitting; and differences in quit attempts and withdrawal symptoms for persons with AUDs/SUDs compared to other people. Most studies examined nationally representative data and were conducted on persons in the United States and Australia. Few publications examined outcomes by demographics (e.g., gender, age) but these studies suggested that specific patterns differ by demographic subgroups. More research is needed on persons with AUDs/SUDs in order to develop the most effective public health and clinical interventions to reduce smoking behaviors, improve cessation outcomes, and reduce the harmful consequences of smoking for those with AUDs/SUDs.

Do Socioeconomic Risk Factors for Cigarette Smoking Extend to Smokeless Tobacco Use?

INTRODUCTION

Individuals with lower socioeconomic status (SES) are at increased risk for cigarette smoking. Less research has been conducted characterizing the relationship between SES and risk of using of other tobacco products. The present study examined SES as a risk factor for smokeless tobacco (ST) use in a US nationally representative sample, utilizing data from the 2012 National Survey on Drug Use and Health.

METHODS

Odds were generated for current cigarette smoking and ST use among adults (≥18 years) based on SES markers (educational attainment, income, blue-collar employment, and unemployment) after controlling for the influence of demographics and other substance dependence.

RESULTS

Odds of current cigarette smoking increased as a graded, inverse function of educational attainment as well as lower income and being unemployed. Odds of current ST use also increased as a function of lower educational attainment, although not in the linear manner seen with cigarette smoking. Odds of ST use but not cigarette smoking also increased with blue-collar employment. In contrast to patterns seen with cigarette smoking, ST use did not change in relation to income or unemployment.

CONCLUSIONS

Markers of SES are significantly associated with odds of cigarette smoking and ST use, but which indicators are predictive and the shape of their relationship to use differs across the two tobacco products.

Demographic and psychological factors associated with lifetime cocaine use: An exploratory factor analysis of baseline questionnaires

OBJECTIVES

Underlying heterogeneity among individuals with cocaine dependence is widely postulated in the literature, however, identification of a group of factors that explain risk of cocaine use severity has yet to be confirmed.

METHODS

Latent mixture modeling evaluated 338 cocaine-dependent individuals recruited from the community to assess the evidence for the presence of distinct subgroups. Variables included 5 baseline questionnaires measuring cognitive function (Shipley), impulsivity (BIS), mood (BDI), affective lability (ALS), and addiction severity (ASI). Results failed to suggest multiple subgroups. Given a lack of evidence for discrete latent classes, an exploratory factor analysis (EFA) followed by exploratory structural equation modeling (ESEM) was implemented to identify functional dimensions to enhance interpretation of these variables.

RESULTS

Findings from the EFA indicated a 3-factor model as the best fit, and the subsequent ESEM solution resulted in associations with lifetime cocaine use. Factor 1, best characterized by demographic factors (gender, age), is associated with less lifetime cocaine use. Psychological problems best characterize factor 2, which is associated with higher lifetime cocaine use. Finally, factor 3 is characterized by other substance use (alcohol and marijuana). Although this factor did not demonstrate a statistically reliable relation with self-reported, lifetime cocaine use, it did indicate a potentially meaningful positive association.

CONCLUSIONS

These 3 factors delineate dimensions of functioning that likewise help characterize the variability found in previously established associations with self-reported cocaine use.

Psychiatric disorders as vulnerability factors for nicotine addiction: what have we learned from animal models?

Epidemiological studies indicate a high prevalence of tobacco smoking in subjects with psychiatric disorders. Notably, there is a high prevalence of smoking among those with dependence to other substances, schizophrenia, mood, or anxiety disorders. It has been difficult to understand how these phenomena interact with clinical populations as it is unclear what preceded what in most of the studies. These comorbidities may be best understood by using experimental approaches in well-controlled conditions. Notably, animal models represent advantageous approaches as the parameters under study can be controlled perfectly. This review will focus on evidence collected so far exploring how behavioral effects of nicotine are modified in animal models of psychiatric conditions. Notably, we will focus on behavioral responses induced by nicotine that are relevant for its addictive potential. Despite the clinical relevance and frequency of the comorbidity between psychiatric issues and tobacco smoking, very few studies have been done to explore this issue in animals. The available data suggest that the behavioral and reinforcing effects of nicotine are enhanced in animal models of these comorbidities, although much more experimental work would be required to provide certainty in this domain.

Examining vulnerability to smokeless tobacco use among adolescents and adults meeting diagnostic criteria for major depressive disorder

Smoking prevalence is unevenly distributed in the U.S. population, with those with mental illness, other substance use disorders, and lower socioeconomic status being especially vulnerable. Less research has been conducted on the association between these same vulnerabilities and smokeless tobacco (ST) use. The present study examined cigarette and ST use among adolescents and adults who met diagnostic criteria for major depressive disorder in the National Survey on Drug Use and Health (NSDUH). Utilizing the most recent (2011) NSDUH, we compared odds for current cigarette smoking and ST use among adolescents and adults meeting criteria for past-year major depressive disorder to the general population, after adjusting for potential confounding influences of sociodemographic and other substance use characteristics. Analyses were conducted to examine sex as a moderator of the relation between major depressive disorder and tobacco use. Odds for current cigarette smoking among those classified with major depressive disorder were increased among adolescents (OR = 1.33, 95% CI [1.05, 1.69], p = .021) and adults (OR = 1.70, 95% CI [1.47, 1.97], p < .0005), and odds for current ST use did not differ among adolescents (OR = 0.90, 95% CI [0.54, 1.49], p = .678) and were lower among adults (OR = 0.68, 95% CI [0.51, 0.91], p = .010). Sex was not a significant moderator in adolescents or adults. Major depressive disorder is associated with increased risk for smoking but not ST use among adolescents and adults further demonstrating heterogeneity in predictors of vulnerability to use of different tobacco products.