Despite steadily declining rates of tobacco use in the United States, individuals suffering from substance use disorders (SUD) and other mental illnesses continue to use tobacco at alarmingly high rates, resulting in increased mortality. Given the synergistic consequences to those who suffer from both tobacco use disorders (TUD) and other SUD, embedding tobacco treatment into structured SUD programs using an opt-out approach may yield a greater impact. The current study compares clinical outcomes (ie, quit attempts and prescription of tobacco cessation medications) for an opt-out versus opt-in approach to tobacco treatment.

Tobacco use information was collected prior to and after implementation of an opt-out, eight-session, tobacco group treatment intervention. Patient self-report and medical chart review were utilized to identify individuals who began a tobacco cessation medication during treatment as well as those who reported quitting tobacco, defined as sustained tobacco abstinence for at least 7 days. The analysis includes a total of N = 332 Veterans who enrolled in the intensive outpatient program.

Those enrolled in the opt-out tobacco treatment group reported a significantly higher rate of quitting tobacco (24.57%) than those in the opt-in group (2.55%; p < .001). Likewise, the opt-out group was prescribed tobacco cessation medications at a significantly higher rate than the opt-in group (55.00% compared to 14.65%; p < .001).

An opt-out treatment approach to TUD in SUD treatment settings produced improved outcomes, including significantly more patients engaged in TUD treatment and a higher overall rate of SUD treatment completion.

Given the disproportionately high rate of tobacco use among those seeking treatment for SUD, enhanced tobacco cessation interventions could result in both improved tobacco as well as other substance use outcomes. The implementation of an opt-out tobacco treatment intervention embedded into SUD programming is supported by our findings of reduced tobacco use among patients.

Alcohol use disorder (AUD) is common and may complicate type 2 diabetes (T2DM) management. Little research has examined diabetes outcomes for people with T2DM and AUD, including during the window when patients start specialty addiction treatment.

To examine diabetes-related health monitoring, clinical outcomes, and acute health care use among patients with T2DM and AUD newly accessing specialty addiction treatment.

This retrospective cohort study included electronic health record data from a large, integrated health care delivery system.

Adults with T2DM and an index outpatient health care visit during 2016-2021 were included. Patients whose index visit was an initial AUD-related visit in specialty addiction treatment were in the AUD group. The comparison group had no AUD or addiction medicine visits.

Outcomes were diabetes-related health monitoring, achievement of treatment targets, complications, and acute health care use during the 12 months post-index visit.

The study included 222,334 adults with T2DM, 1,998 with AUD. Relative to the comparison group, participants with AUD had elevated risk for hypoglycemia (adjusted risk ratio [aRR] = 2.14; 95% confidence interval [CI] = 1.49, 3.08), cardiovascular complications (aRR = 1.43; 95% CI = 1.34, 1.53), and neuropathy (aRR = 1.26; 95% CI = 1.14, 1.41), and were less likely to be non-smokers (aRR = 0.88; 95% CI = 0.86, 0.90), after adjusting for confounding factors. In adjusted models, the AUD versus comparison group had similar or higher rates of diabetes monitoring (e.g., any glycemic test, aRR = 1.19; 95% CI = 1.17, 1.22) and metabolic control (e.g., hemoglobin A1c < 8.0%, aRR = 1.14; 95% CI = 1.11, 1.18).

Patients with co-occurring T2DM and AUD in an integrated health care delivery system are vulnerable to diabetes complications that could be addressed during the early phase of specialty addiction treatment.

A mathematical model of the dual addiction dissemination dynamics of alcoholism and smoking was created and examined in this work, along with cost-effectiveness and optimal control techniques. The primary goal of the research is to determine which cost-efficient management techniques are most helpful in lowering the problem of dual addiction dispersion in the community. The smoking addiction sub-model, the alcohol addiction sub-model, and the dual addiction model between alcohol and smoking were all calculated, and their stability was examined in this study. The effective reproduction numbers of the models are computed using the next-generation operator technique. When the model's effective reproduction number is smaller than one, the backward bifurcation phenomenon is seen. Six time-dependent control measures are taken into consideration when formulating and analyzing the optimum control issue. Utilizing and applying the parameter values and using MATLAB ode45 solver we performed numerical simulations for both the dual addiction model and its optimal control problem. Furthermore, using the incremental cost-effectiveness ratio (ICER), we carried out the cost-effectiveness analyses. The cost-effectiveness analysis shows that implementing all the protection (education) control measures simultaneously (i.e., implementing Strategy A) is the most cost-effective strategy. Finally, we recommend that the public health stakeholders must put great effort into the implementation of Strategy A to reduce the smoking and alcoholism dual addiction dissemination problem in the community.

The prevalence of combustible cigarette smoking in populations experiencing homelessness in the United States is five times that of the general population. The psychosocial well-being of persons who smoke and experience homelessness is poorer if such persons also use alcohol heavily. The PTQ2 study was a randomized clinical trial among persons experiencing homelessness who were also current smokers and heavy alcohol consumers. Secondary data analysis of the PTQ2 baseline data was conducted to examine associations among psychosocial variables (anxiety, depression, hopelessness, social network size), heaviness of smoking (cigarettes/day) and alcohol consumption (drinking days/month), and duration and frequency of homelessness. Among the 420 participants, the majority were male (75%), black (70%) and non-Hispanic (94%) with a mean age of 46.6 years (SD = 11.6).  Bivariate analyses show that heaviness of smoking was positively correlated with social network size (r = 0.16, p = .001). Heaviness of drinking was positively correlated with the MINI anxiety score (r = 0.13, p = .009) and marijuana use (median total number of drinks in past 30 days among those who used marijuana in past 30 days vs. did not use: 50 vs. 24, p < .0001), and associated with frequency of homelessness (median total number of drinks in past 30 days among those experiencing homelessness once vs. >1 time: 30 vs. 44, p = .022). The findings highlight the psychosocial factors that warrant consideration when addressing heavy smoking and alcohol consumption in persons experiencing homelessness.

BACKGROUNDAlcohol use disorder has a detrimental impact on global health and new treatment targets are needed. Preclinical studies show attenuating effects of glucagon-like peptide-1 (GLP-1) agonists on addiction-related behaviors in rodents and nonhuman primates. Some trials have shown an effect of GLP-1 agonism on reward processes in humans; however, results from clinical studies remain inconclusive.METHODSThis is a predefined secondary analysis of a double-blind, randomized, placebo-controlled trial evaluating the GLP-1 agonist dulaglutide as a therapy for smoking cessation. The main objective was to assess differences in alcohol consumption after 12 weeks of treatment with dulaglutide compared to placebo. The effect of dulaglutide on alcohol consumption was analyzed using a multivariable generalized linear model.RESULTSIn the primary analysis, participants out of the cohort (n = 255) who reported drinking alcohol at baseline and who completed 12 weeks of treatment (n = 151; placebo n = 75, dulaglutide n = 76) were included. The median age was 42 (IQR 33-53) with 61% (n = 92) females. At week 12, participants receiving dulaglutide drank 29% less (relative effect = 0.71, 95% CI 0.52-0.97, P = 0.04) than participants receiving placebo. Changes in alcohol consumption were not correlated with smoking status at week 12.CONCLUSIONThese results provide evidence that dulaglutide reduces alcohol intake in humans and contribute to the growing body of literature promoting the use of GLP-1 agonists in treatment of substance use disorders.TRIAL REGISTRATIONClinicalTrials.gov NCT03204396.FUNDINGSwiss National Foundation, Gottfried Julia Bangerter-Rhyner Foundation, Goldschmidt-Jacobson Foundation, Hemmi Foundation, University of Basel, University Hospital Basel, Swiss Academy of Medical Science.

At-risk alcohol use and tobacco smoking often co-occur. We investigated whether brief alcohol interventions (BAIs) among general hospital patients with at-risk alcohol use may also reduce tobacco smoking over 2 years. We also investigated whether such effects vary by delivery mode; i.e. in-person versus computer-based BAI.

A proactively recruited sample of 961 general hospital patients with at-risk alcohol use aged 18 to 64 years was allocated to three BAI study groups: in-person BAI, computer-based BAI, and assessment only. In-person- and computer-based BAI included motivation-enhancing intervention contacts to reduce alcohol use at baseline and 1 and 3 months later. Follow-ups were conducted after 6, 12, 18 and 24 months. A two-part latent growth model, with self-reported smoking status (current smoking: yes/no) and number of cigarettes in smoking participants as outcomes, was estimated.

Smoking participants in computer-based BAI smoked fewer cigarettes per day than those assigned to assessment only at month 6 (meannet change = - 0.02; 95% confidence interval = - 0.08-0.00). After 2 years, neither in-person- nor computer-based BAI significantly changed smoking status or number of cigarettes per day in comparison to assessment only or to each other (ps ≥ 0.23).

While computer-based BAI also resulted in short-term reductions of number of cigarettes in smoking participants, none of the two BAIs were sufficient to evoke spill-over effects on tobacco smoking over 2 years. For long-term smoking cessation effects, multibehavioural interventions simultaneously targeting tobacco smoking along with at-risk alcohol use may be more effective.

NCT01291693.

Cigarette smoking is believed to accelerate age-related neurodegeneration. Despite significant sex differences in both smoking behaviors and brain structures, the active literature is equivocal in parsing out a sex difference in smoking-associated brain structural changes.

The current study examined subcortical and lateral ventricle gray matter (GM) volume differences among smokers, active, past, and never-smokers, stratified by sex.

The current study data included 1959 Dallas Heart Study (DHS) participants with valid brain imaging data. Stratified by gender, multiple-group comparisons of three cigarette-smoking groups were conducted to test whether there is any cigarette-smoking group differences in GM volumes of the selected regions of interest (ROIs).

The largest subcortical GM volumetric loss and enlargement of the lateral ventricle were observed among past smokers for both females and males. However, these observed group differences in GM volumetric changes were statistically significant only among males after adjusting for age and intracranial volumes.

The study findings suggest a sex difference in lifetime-smoking-associated GM volumetric changes, even after controlling for aging and intracranial volumes.

The remarkable decline in cigarette smoking since 1964 has plateaued; approximately 12.5% of Americans still smoke. People who continue to smoke are largely members of marginalized groups, such as people with behavioral health conditions (BHC), encompassing both mental health and substance use disorders. Certified smoking cessation interventions can increase smoking abstinence in trials in people with BHC, yet smoking rates remain markedly increased, leading to increased mortality from smoking-related diseases, and worsening health disparities. A novel approach tailored to the unique needs, characteristics, and circumstances of people with BHC is mandated. One promising approach, the electronic cigarette, has not been embraced in the USA, likely due to an understandable concern for non-smoking young people among whom electronic cigarettes have been popular. Recent data confirm that electronic cigarette use is declining among young people, yet cigarette smoking is not declining among people with BHC. We propose smoking cessation trials utilizing electronic cigarettes in people with BHC. To this goal, the UK has already begun allowing companies to submit their products for approval as medically licensed electronic cigarettes that can be prescribed as smoking cessation aids. Our proposal is timely, backed by evidence, and aims to save hundreds of thousands of American lives.

Growing evidence suggests that intervention for smoking cessation enhances alcohol abstinence in treatment settings for alcohol dependence. However, research in this field is rare in Asians.

We prospectively investigated the association of smoking status with drinking status using 9 surveys mailed during a 12-month period in 198 Japanese alcohol-dependent men (70 never/ex-smokers and 128 smokers) who admitted for the first time and completed a 3-month inpatient program for simultaneous alcohol abstinence and smoking cessation.

Nonsmoking during the first month after discharge and at the end of follow-up was reported in 28.9% and 25.0% of the baseline smokers, respectively. Kaplan-Meier estimates showed that a 12-month alcohol abstinence and heavy-drinking-free status were more frequent among never/ex-smokers (45.1% and 59.8%, respectively) and baseline smokers who quit smoking during the first month after discharge (59.0% and 60.8%, respectively), compared with sustained smokers (30.0% and 41.2%, respectively). Among the baseline smokers, the multivariate odds ratio (95% confidence interval) for smoking cessation during the first month were 2.77 (1.01-7.61) for alcohol abstinence during the period and 2.50 (1.00-6.25) for use of varenicline, a smoking cessation agent, during the inpatient program. After adjusting for age, drinking profile, lifestyle, family history of heavy or problem drinking, lifetime episodes of other major psychiatric disorders, and medications at discharge, the multivariate hazard ratios (HRs) for drinking lapse were 0.57 (0.37-0.89) for the never/ex-smoking and 0.41 (0.23-0.75) for new smoking cessation groups, respectively, compared with sustained smoking, while the corresponding HRs for heavy-drinking lapse were 0.55 (0.33-0.90) and 0.47 (0.25-0.88), respectively. The HR for drinking lapse was 0.63 (0.42-0.95) for the nonsmoking group (vs. smoking) during the observation period, while the HR for heavy-drinking lapse was 0.58 (0.37-0.91) for the nonsmoking group (vs. smoking) during the observation period. Other significant variables that worsened drinking outcomes were higher daily alcohol intake prior to hospitalization, family history of heavy or problem drinking and psychiatric medications at discharge.

Nonsmoking was associated with better outcomes on the drinking status of Japanese alcohol-dependent men, and a smoking cessation program may be recommended to be integrated into alcohol abstinence programs.

This study investigated whether tobacco smoking affected outcomes of brief alcohol interventions (BAIs) in at-risk alcohol-drinking general hospital patients. Between 2011 and 2012 among patients aged 18−64 years, 961 patients were allocated to in-person counseling (PE), computer-based BAI containing computer-generated individual feedback letters (CO), and assessment only. PE and CO included contacts at baseline, 1, and 3 months. After 6, 12, 18, and 24 months, self-reported reduction of alcohol use per day was assessed as an outcome. By using latent growth curve models, self-reported smoking status, and number of cigarettes per day were tested as moderators. In PE and CO, alcohol use was reduced independently of smoking status (IRRs ≤ 0.61, ps < 0.005). At month 24, neither smoking status nor number of cigarettes per day moderated the efficacy of PE (IRR = 0.69, ps > 0.05) and CO (IRR = 0.85, ps > 0.05). Up to month 12, among persons smoking ≤ 19 cigarettes per day, the efficacy of CO increased with an increasing number of cigarettes (ps < 0.05). After 24 months, the efficacy of PE and CO that have been shown to reduce drinking did not differ by smoking status or number of cigarettes per day. Findings indicate that efficacy may differ by the number of cigarettes in the short term.

In the midst of the COVID-19 pandemic, many research and clinical teams have transitioned their projects to a remote-based format, weighing the pros and cons of making such a potentially disruptive decision. One key aspect of this decision is related to the patient population, with underserved populations possibly benefiting from the increased reach of telehealth, while also encountering technology barriers that may limit accessibility. Early in the pandemic, our team shifted a group-based, smoking cessation and alcohol modification treatment trial to a remote-based format. Our population included individuals who concurrently wanted to quit smoking and modify their alcohol use. This paper describes technical and logistical considerations of transitioning from in-person to remote-based delivery for group-based treatment, including the impact upon study staff, group facilitators, participants, and the institution. Remotely-delivered group treatment may be valuable not only in response to pandemic-related restrictions, but it may also offer an alternative treatment-delivery modality with independent benefits in terms of population reach, costs, and pragmatics for clients, staff, and institutions.

Cigarette smoking induces a profound transcriptomic and systemic inflammatory response. Previous studies have focused on gene level differential expression of smoking, but the genome-wide effects of smoking on alternative isoform regulation have not yet been described. We conducted RNA sequencing in whole-blood samples of 454 current and 767 former smokers in the COPDGene Study, and we analyzed the effects of smoking on differential usage of isoforms and exons. At 10% FDR, we detected 3167 differentially expressed genes, 945 differentially used isoforms and 160 differentially used exons. Isoform switch analysis revealed widespread 3' UTR lengthening associated with cigarette smoking. The lengthening of these 3' UTRs was consistent with alternative usage of distal polyadenylation sites, and these extended 3' UTR regions were significantly enriched with functional sequence elements including microRNA and RNA-protein binding sites. These findings warrant further studies on alternative polyadenylation events as potential biomarkers and novel therapeutic targets for smoking-related diseases.

Despite an overall decline in tobacco use in the United States, secular trends of smoking and nicotine dependence with co-occurring substance use are not well characterized.

We examined self-reported tobacco and other substance use in 22,245 participants age 21-59 in the United States from six waves of the National Health and Nutrition Examination Survey (NHANES). Using Joinpoint regression, we assessed secular trends of smoking and nicotine dependence as a function of co-occurring use of alcohol, prescription opioids, marijuana/hashish, cocaine/heroin/methamphetamine, or other injection drug use. Multivariable logistic regressions were fitted to identify the potential risk factors.

During 2005-2016, the prevalence of current smoking decreased (without co-occurring substance use: 17.0 %-12.7 %; with co-occurring use of one substance: 35.3 % to 24.6 %; with co-occurring use of two or more substances: 53.8 %-42.2 %), and moderate-to-severe nicotine dependence decreased as well (8.0 %-4.2 %, 16.0 %-8.8 %, and 23.9 %-15.7 %, respectively). Smoking and nicotine dependence were more likely in those with co-occurring use of one substance (current smoking: odds ratio [OR] = 2.22, 95 % confidence interval [CI] = 2.01-2.45); nicotine dependence: OR = 1.88, 95 % CI = 1.63-2.17) and in those with co-occurring use of two or more substances (current smoking: OR = 5.25, 95 % CI = 4.63-5.95; nicotine dependence: OR = 3.24, 95 % CI = 2.72-3.87).

Co-occurring substance use was associated with smaller reductions in tobacco use, over time, and with increased odds of nicotine dependence. This suggests that co-occurring substance users should be regarded as a tobacco-related disparity group and prioritized for tobacco control interventions.

Among people with cancer, dual alcohol and tobacco use increases risk for morbidity and mortality. Most smoking cessation clinical trials with this patient population have excluded individuals with problematic alcohol use. This investigation examined whether problematic alcohol use affects smoking cessation in cancer patients.

Mixed-methods secondary analysis of data from the Smokefree Support Study, a randomized-controlled trial examining the efficacy of Intensive (IT; n = 153) vs. Standard Treatment (ST; n = 150) for smoking cessation in newly diagnosed cancer patients. Problematic alcohol use was assessed at enrollment using the Cut-Down-Annoyed-Guilty-Eye-Opener (CAGE), weekly frequency of alcohol use and binge drinking measures. Alcohol use was categorized as: no current alcohol use, moderate and problematic use. The primary outcome was biochemically-confirmed cigarette abstinence at 6-months. A subset of patients (n = 72) completed qualitative exit-interviews.

Among all participants, biochemically-confirmed cigarette abstinence rates were 25% (n = 32), 28% (n = 27), and 36% (n = 20) for participants reporting no current alcohol use, moderate use, and problematic use, respectively (p = 0.33). In logistic regression analysis, neither problematic alcohol use (AOR = 0.96, 95% CI = 0.35-2.67, p = .94) nor the problematic use by study arm interaction (AOR = 2.22, 95% CI = 0.59-8.39, p = .24) were associated with biochemically-confirmed 6-month abstinence. Qualitatively, participants reported that drinking alcohol triggers urges to smoke.

Newly diagnosed cancer patients reporting problematic alcohol use were not less likely to quit smoking than those without. Additional research is needed to investigate whether problematic alcohol users may benefit from smoking and alcohol behavior change interventions at the time of cancer diagnosis.

Addiction is a chronic disorder that consists of a three-stage cycle of binge/intoxication, withdrawal/negative affect, and preoccupation/anticipation. These stages involve, respectively, neuroadaptations in brain circuits involved in incentive salience and habit formation, stress surfeit and reward deficit, and executive function. Much research on addiction focuses on the neurobiology underlying single drug use. However, alcohol use disorder (AUD) can be co-morbid with substance use disorder (SUD), called dual dependence. The limited epidemiological data on dual dependence indicates that there is a large population of individuals suffering from addiction who are dependent on more than one drug and/or alcohol, yet dual dependence remains understudied in addiction research. Here, we review neurobiological data on neurotransmitter and neuropeptide systems that are known to contribute to addiction pathology and how the involvement of these systems is consistent or divergent across drug classes. In particular, we highlight the dopamine, opioid, corticotropin-releasing factor, norepinephrine, hypocretin/orexin, glucocorticoid, neuroimmune signaling, endocannabinoid, glutamate, and GABA systems. We also discuss the limited research on these systems in dual dependence. Collectively, these studies demonstrate that the use of multiple drugs can produce neuroadaptations that are distinct from single drug use. Further investigation into the neurobiology of dual dependence is necessary to develop effective treatments for addiction to multiple drugs.

The combined use of cigarettes and alcohol is associated with an increased risk of morbidity and mortality. Yet, efficacious interventions that address both behaviors concurrently are lacking. Smoking cessation and alcohol modification not only garner health benefits, but there is also value in addressing alcohol use in the context of smoking cessation to reduce the risk for smoking relapse. In this paper we describe the development of mindfulness-based relapse prevention for smoking cessation and alcohol modification (MBRP-SA) and pilot study findings (Phase 1). Next, details regarding the methods and design of an ongoing, randomized controlled trial, Project RISE (Phase 2), are described. MBRP-SA is a group-based intervention that consists of eight weekly treatment sessions. Results from the Phase 1 pilot study (N = 21 enrolled) indicated that participants planned to use the skills learned in their everyday activities and to address their smoking and alcohol goals. Based on the progression of Phase 1 cohorts, modifications were made to the inclusion/exclusion criteria and recruitment methods that will be implemented in Phase 2. Phase 2 will assess the feasibility and acceptability of MBRP-SA, delivered via live online groups, as a primary treatment option for smoking cessation and alcohol use modification.

Combined smoking and heavy drinking is a significant health burden. Varenicline, an efficacious tobacco pharmacotherapy that also shows promise for drinking, has yielded mixed results among heavy-drinking smokers. This pilot study investigated integrated tobacco and alcohol counselling plus varenicline for this vulnerable group.

Twelve-week parallel, randomized controlled pilot trial of two behavioural interventions in combination with open-label varenicline. Participants were randomized using computer-generated tables, stratified by sex.

Outpatient academic medical centre research clinic.

Volunteers who reported smoking and heavy drinking and sought tobacco or alcohol treatment (N = 26). Intervention. (1) Integrated tobacco + alcohol counselling (INT; n = 13) or (2) counselling focused on their presenting concern (i.e., tobacco or alcohol) (SINGLE; n = 13), plus varenicline (2 mg) for 12 weeks.

Feasibility/acceptability, smoking quit rates and heavy drinking.

INT feasibility/acceptability was high among men but not women. More participants quit smoking in INT than SINGLE. This outcome was only in men, not significant, but had a medium effect size. Both conditions yielded significant drinking reductions.

Integrated tobacco and alcohol behavioural counselling plus varenicline may be feasible and promote smoking cessation among men who smoke and drink heavily, but a larger sample is needed to replicate this finding.

Tobacco use has been steadily increasing among the females in developing countries. It has led to rise in tobacco-related morbidity and mortality among females. Knowing the geographic distribution of the habit is essential to identify high-priority areas and direct the healthcare intervention. Hence, this study was done to assess the spatial patterns and determinants of tobacco consumption among females in India.

Univariate and bivariate Moran's I statistic and local indicators for spatial association maps were generated to determine the spatial clustering of tobacco consumption (smoked and smokeless form). Ordinary least-square regression, spatial-lag and spatial-error models were performed to assess the determinants. Poverty (belonging to poorest and poorer quintile of wealth index), illiteracy (no formal education), marital status, ST population, tobacco use by family members, and alcohol use were the explanatory variables.

Univariate Moran's I was .691 suggesting positive spatial autocorrelation. High-prevalence clustering (hotspots) was maximum in the central, eastern, and northeastern states such as Chhattisgarh, Madhya Pradesh, Odisha, Bihar, Manipur, Tripura, Meghalaya, Mizoram, and Assam. This pattern was similar for both smokeless and smoked form. Results of spatial-lag and spatial-error model suggested that alcohol use, scheduled tribes, illiteracy, poverty, marital status, and tobacco use by family members were significant determinants of female tobacco consumption. The coefficient of spatial association was maximum for alcohol use (β = .20, p < .001) followed by widowed/separated/divorced (β = .12, p < .001).

Tobacco consumption among females in India is spatially clustered. Multisectoral coordination and targeted interventions are required in the geographical hotspots of tobacco consumption.

This is the first study to explore the geospatial pattern of tobacco consumption among females in India. We found that the pattern of tobacco use among females is spatially clustered in India. Clustering was predominantly found in central, eastern, and northeastern regions of the country. Tribal population in these areas and complementarities between alcohol and tobacco use contributed significantly to the high-prevalence clustering. These findings will be helpful for policymakers and planners to devise specific intervention package targeting the high-risk regions.

Tobacco use may deteriorate mental health and increase health risk behaviours.

The aim of this investigation was to identify associations between tobacco use and mental illness symptoms and health risk behaviours in individuals 15 years or older in South Africa.

Community-based national population sample in South Africa.

Cross-sectional data were analysed from the 'South African National Health and Nutrition Examination Survey (SANHANES-1) 2012', using a sample of 15 310 individuals 15 years or older (median age 33 years). Measures included information on tobacco use, sociodemographic factors, mental symptoms and health risk behaviour.

Compared to non-tobacco users, daily tobacco users were associated with psychological distress and post-traumatic stress disorder (PTSD) in adjusted logistic regression analysis, and with sleeping problems in unadjusted analysis. Past tobacco use, less than daily, and daily tobacco use were highly associated with a drinking problem. In terms of dietary variables, less than daily and daily tobacco use increased the odds of inadequate fruit intake and salty food intake, and daily tobacco use decreased the odds of fast food consumption. Past tobacco use, less than daily, and daily tobacco use were inversely associated with physical inactivity, and daily tobacco use was associated with not always washing hands before eating.

The study showed that compared to non-tobacco users, daily tobacco users had significantly poorer mental health (psychological distress and PTSD) and increased odds for several health risk behaviours (drinking problem, inadequate fruit intake, salty food consumption and not always washing hands before eating) as compared to non-tobacco users.

Polytobacco use is a growing concern; users are exposed to cumulatively more nicotine, increasing their risk for dependence and long-term use. More sexual minority (SM) young adults report polytobacco use than their heterosexual peers, yet no studies explore how their tobacco patterns vary across the diverse product landscape. The purpose of this study was to characterize SM young adults' patterns of tobacco use and nicotine dependence, and explore co-occurring risk factors for polytobacco use.

Participants were 609 SM Texas college students. Latent class analysis identified subgroups of tobacco users based on their tobacco use behaviors and an indicator of nicotine dependence. Multinomial logistic regression identified associations between individual-level variables and the probability of membership in various user classes.

Tobacco use clustered in four classes: non-users, non-addicted cigarette users, non-addicted e-cigarette users, and addicted polytobacco users. Polytobacco users had an increased probability of depressive symptoms and cannabis use relative to non-users, and more binge alcohol use than all other groups. Non-addicted cigarette users had an increased probability of binge alcohol use, cannabis use, and being non-Hispanic White relative to non-users, and an increased likelihood of cannabis use relative to non-addicted e-cigarette users. Non-addicted e-cigarette users had an increased probability of binge alcohol use relative to non-users.

SM young adults' tobacco use varies across the diverse product landscape. Failing to account for a range of tobacco behaviors and nicotine dependence prevents tailoring interventions that should also address concerns such as depressive symptoms, cannabis use, and binge alcohol use.

On average, two-thirds of individuals treated for alcohol use disorder (AUD) relapse within six months. There is a critical need to identify modifiable risk factors associated with relapse that can be addressed during AUD treatment. Candidate factors include mood disorders and cigarette smoking, which frequently co-occur with AUD. We predicted that co-occurrence of mood disorders, cigarette smoking, and other modifiable conditions will predict relapse within six months of AUD treatment. Ninety-five Veterans, 23-91 years old, completed assessments of multiple characteristics including demographic information, co-occurring psychiatric disorders, and medical conditions during residential treatment for AUD. Participants' alcohol consumption was monitored over six months after participation. Logistic regression was used to determine if, mood disorders, cigarette smoking status, alcohol consumption, educational level, and comorbid general medical conditions are associated with relapse after AUD treatment. Sixty-nine percent of Veterans (n = 66) relapsed within six months of study while 31% remained abstinent (n = 29). While education, comorbid general medical conditions, and mood disorder diagnoses were not predictors of relapse, Veterans with greater symptoms of anhedonia, active smokers, and fewer days of abstinence prior to treatment showed significantly greater odds for relapse within six months. Anhedonia and cigarette smoking are modifiable risk factors, and effective treatment of underlying anhedonic symptoms and implementation of smoking cessation concurrent with AUD-focused interventions may decrease risk of relapse.

Understanding the association between smoking and alcohol use among women may help inform the delivery of targeted interventions to address both of these health behaviors.

This study analyzed data from N = 138 women enrolled in a randomized clinical trial comparing female-specific individual versus group cognitive-behavior therapy for alcohol use disorder (AUD). We assessed cigarette use patterns, participants' interest in quitting smoking and motivation to quit smoking during treatment for AUD, and examined the relationship between smoking and alcohol use before and during alcohol treatment.

Over a third of the sample reported smoking cigarettes at baseline (N = 47, 34.1%), with the majority of smokers reporting daily cigarette use. At baseline, those who smoked reported a high interest in quitting smoking M = 7.8 out of 10 (SD = 2.7), although most believed they should quit smoking only after achieving some success in quitting drinking (50.0%). However, participants who smoked cigarettes (compared to non-smokers) reported more alcohol abuse and dependence symptoms (p = .001), lower rates of completing the alcohol treatment (p = .03), attended significantly fewer treatment sessions (p = .008), and consumed significantly more drinks per day on average both at baseline (p = .002) and during the treatment period (p = .04).

Findings suggest that women with AUD who also smoke cigarettes have greater difficulty engaging in or responding to treatment for their alcohol use. However, these participants reported high interest in quitting smoking but low perceived readiness during AUD treatment, suggesting that motivational interventions should be considered that could take advantage of the opportunity to treat women for both of these co-occurring behaviors while in treatment.

Background: Justice-involved youth are at risk to become cigarette smokers as they age, leading to a variety of poor health outcomes. However, little is known about cigarette use among justice-involved youth, especially youth supervised in the community where there is ample opportunity to smoke. Objective: This study investigates the prevalence of cigarette smoking and the associations between cigarette smoking, emotional and behavioral functioning, and other substance use among a sample of first-time offending court-involved, non-incarcerated (FTO-CINI) youth. Methods: Youth were recruited from a family court in the Northeast (N = 423). Substance use was self-reported using the Adolescent Risk Behavior Assessment (ARBA). Emotional and behavioral functioning was measured using the Behavior Assessment Schedule for Children-Second Edition (BASC-2), the Affect Dysregulation Scale (ADS), National Stressful Events Survey PTSD Short Scale (NSESSS), and the National Survey of Self-Reported Delinquency (NYS-SRD). Results: About 9.9% of FTO-CINI youth had smoked cigarettes in the past 30 days. Compared with FTO-CINI youth who had not smoked recently, recent smokers endorsed more emotional and behavioral symptoms, such as school problems (p < .001), internalizing problems (p = .012), inattention/hyperactivity (p = .020), affect dysregulation (p = .044), PTSD symptoms (p = .006), and delinquent behavior (p < .001). Recent smokers were also more likely to use alcohol (OR = 5.61, p < .001), marijuana (OR = 11.27, p < .001), and other drugs (OR = 5.00, p < .001). Conclusions: Recent smoking was higher among FTO-CINI youth than youth in the general population. Findings underscore the need to incorporate nicotine into existing substance use prevention interventions for this population, who are at high risk to initiate cigarette use as they age.

Electronic cigarettes (e-cigarettes) are becoming popular and may be a potential harm reduction and quit smoking aid for people who use other drugs. Data on e-cigarette use and perceptions among people who use drugs is limited. The current study examines tobacco smoking status, use and attitudes towards e-cigarettes among people in drug and alcohol treatment.

Data were collected through a standardised Patient Experience Tracking System device installed in the waiting room of six drug and alcohol clinical service programs located within one area health service in New South Wales, Australia during April to June 2017. Participants were clients of participating services aged 18 years and older.

Five hundred and eleven participants completed the survey, 85% were current smokers, 9% were ex-smokers and 6% were non-smokers. Over half of all participants (53%) had tried e-cigarettes in their lifetime, 26% reported current use and 77% of those were using them with nicotine. Just less than half of all participants believed that e-cigarettes were helpful for quitting or cutting down smoking tobacco cigarettes (48%). More than half of all respondents (59%) believed that tobacco cigarettes were more harmful than e-cigarettes (59%) and believed that e-cigarettes were an acceptable quit smoking aid for patients of drug and alcohol services (64%).

Most participants were current tobacco smokers and had tried an e-cigarette though a minority were currently using e-cigarettes. Participant attitudes were favourable towards the use of e-cigarettes as quit smoking aids.

The prevalence of cigarette smoking among individuals with a history of substance use disorders (SUDs) remains up to four times higher than those without a history of SUDs. More than half of individuals who attain sustained remission from SUDs will die of tobacco-related diseases. The aim of this secondary data analysis was to compare the risk for smoking relapse among smokers with no history of SUDs and smokers in recovery from SUDs after multi-component, cognitive-behavioral treatment for tobacco dependence.

Participants were randomized to receive 6 sessions of multicomponent cognitive-behavioral therapy (adapted for lower socioeconomic groups or standard), 8 weeks of nicotine patches, and were followed for 6 months in the parent randomized clinical trial. Participants passed a urine drug test prior to enrollment. Recovery was assessed at baseline by self-report to the question, "Do consider yourself in recovery from drugs or alcohol?" Relapse was defined as any smoking for 7 consecutive days.

Participants were primarily lower SES and identified as racial and/or ethnic minorities. Cox proportional hazards models revealed that the risk of smoking relapse following tobacco dependence treatment was greater among smokers in long-term (HR: 1.44; 95% CI: 1.01, 2.05) and short-term (HR: 1.98; 95% CI: 1.30, 3.03) recovery than for smokers with no history of SUDs.

Our findings indicate that smokers in recovery from SUDs have 1.5-2 times the risk of relapse than smokers with no history of SUDs. More effective relapse prevention interventions are needed for this vulnerable, high-risk group of smokers.

A relapsing-remitting course is very common in patients with an Alcohol Use Disorder (AUD). Understanding the determinants associated with alcohol resumption remains a formidable task. This paper examines relapse determinants based on a systematic review of recent alcohol literature (2000-2019). Relevant databases were consulted for articles that contained information about specific relapse determinants and reported statistical significance of each relapse determinant in predicting relapse. Relapse was broadly defined based on the characterization in the included articles. From the initial identified 4613 papers, a total of 321 articles were included. Results encompass multiple relapse determinants, which were ordered according to biopsychosocial and spiritual categories, and presented, using a descriptive methodology. Psychiatric co-morbidity, AUD severity, craving, use of other substances, health and social factors were consistently significantly associated with AUD relapse. Conversely, supportive social network factors, self efficacy, and factors related to purpose and meaning in life, were protective against AUD relapse. Despite heterogeneity in different methods, measures, and sample characteristics, these findings may contribute to a better therapeutic understanding in which specific factors are associated with relapse and those that prevent relapse. Such factors may have a role in a personalized medicine framework to improve patient outcomes.

Despite high rates of smoking (70-90%) and the severely negative impact of smoking on physical and mental health, only 12% of individuals receiving stimulant-use disorder treatment also receive smoking-cessation treatment. The aim of this investigation was to examine the effect of a contingency management (CM) intervention targeting methamphetamine (MA) use on cigarette smoking. Sixty-one adults with MA-use disorders who were smokers were assigned to CM or standard psychosocial treatment. Rates of smoking-negative breath samples (carbon monoxide <3 ppm) were compared between the two groups while controlling for baseline carbon monoxide level, marijuana use, MA use, and time. This subgroup of mostly male (59%) participants included 44 participants in the CM group and 17 participants in the standard psychosocial treatment. Tobacco smoking participants who received CM targeting MA use were 140% (odds ratio: 2.395; 95% confidence interval: 1.073-5.346) more likely to submit a smoking-negative breath sample relative to standard psychosocial treatment during the treatment period, holding constant several other prespecified covariates. This study provides evidence that a behavioral treatment for MA use results in reductions in cigarette smoking in adults with MA-use disorder.

Women who smoke during pregnancy face psychosocial barriers to cessation, and women with opioid use disorder (OUD) face amplified barriers. We pilot tested a Perinatal Wellness Navigator (PWN) program for a group of high-risk perinatal women (N = 50; n = 42 with OUD) that consisted of (a) one-on-one tobacco treatment, (b) comprehensive assessment of cessation barriers, and (c) linkage to clinical/social services. Outcome measures were assessed at baseline and postintervention. Participants smoked 10 fewer cigarettes per day (p = .05) at postintervention and were less dependent on nicotine (p < .01). Mean postnatal depression scores (p = .03) and perceived stress (p = .03) decreased postintervention. Participants received at least one referral at baseline (n = 106 total), and 10 participants received an additional 18 referrals at postintervention to address cessation barriers. The PWN program was minimally effective in promoting total tobacco abstinence in a high-risk group of perinatal women, but participants experienced reductions in cigarettes smoked per day, nicotine dependence, stress, and depression.

Tobacco smoking among those seeking treatment for cannabis use disorder (CUD) is common and is a negative predictor of cannabis outcomes. Quitting tobacco may be beneficial for those seeking to quit cannabis use. This initial proof of concept, controlled trial was designed to compare a simultaneous versus sequential tobacco intervention among those seeking treatment for CUD. Sixty-seven adults received either a simultaneous (SIM) or sequential (SEQ) approach to tobacco cessation in the context of outpatient treatment for CUD. A tobacco intervention (TI) that combined web-based counseling with nicotine replacement therapy (NRT) was provided during weeks 1-12 for SIM and was delayed until weeks 13-24 for SEQ. During weeks 1-12, no between-condition significant differences were observed on treatment participation or cannabis use outcomes. The majority of SIM participants initiated TI counseling (62%), 50% made at least one quit attempt and 41% initiated NRT. Interestingly, 39% in SEQ made tobacco quit attempts and 18% initiated NRT on their own before the TI was offered to them. However, only 30% of those in SEQ continued treatment during weeks 13-24, which compromised between-condition comparisons following the TI, but illustrated a potential clinical concern with delaying the TI. Tobacco cessation outcomes generally were poor and did not differ between conditions. This initial controlled trial suggests that addressing tobacco use during CUD treatment is acceptable and generates action towards tobacco cessation. Additional trials testing more intensive TI models may be necessary to identify more efficacious interventions for co-use of cannabis and tobacco.

Tobacco and alcohol are often used in tandem over time, but specific predictors of course and patterns of course over time need explication. We examined differences in alcohol and tobacco course among an adolescent population as they transitioned into young adulthood across a 17-year period. Data came from participants (n = 303 for ages 15-21, n = 196 for ages 21 to 32; 52% female and 54% female, respectively) enrolled in the Amsterdam Growth and Health Longitudinal Study, an epidemiologic investigation examining disease across the life span. We utilized parallel latent growth modeling to assess the impact of sex, personality traits, cholesterol, blood pressure, and body mass index (BMI), on initial status and linear change over time in course of tobacco and alcohol. Females reported less alcohol use at adolescent baseline (β = -21.79), less increase during adolescence (β = -7.92, p < .05), slower decrease during young adulthood (β = 4.67, p < .05), and more rapid decline in tobacco use during young adulthood (β = -70.85, p < .05), relative to males. Alcohol and tobacco use baseline status' and change over time were all significantly associated with one another during both adolescence and young adulthood (p < .05; aside from alcohol baseline and slope during young adulthood). Effects of BMI, cholesterol, blood pressure, and personality traits were also observed on tobacco and alcohol course. In light of the strong, but sex dependent relationship between alcohol and tobacco course, particularly from ages 15 to 21, prevention efforts to curb heavy alcohol and tobacco use should consider targeting course taking into account biological sex and other notable covariates. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

According to the World Health Organization (WHO), in 2015, over 1.1 billion people smoked tobacco, which represents around 15% of the global population. In Africa, around one in five adults smoke tobacco. The 2014 Kenya Global Adult Tobacco Survey reported that 2.5 million adults use tobacco products. The objective of our study was to describe patterns and determinants of tobacco use from the 2015 Kenya STEPS survey, including use of "smokeless" tobacco products and the more novel e-cigarettes.

The WHO STEPwise approach to surveillance (STEPS) was completed in Kenya between April and June 2015. Logistic regression analyses was used to assess factors affecting prevalence and frequency of tobacco use. Sociodemographic variables associated with tobacco use were considered: age, sex, level of education, wealth quintile, and residence. The relationship with alcohol as an intervening risk factor was also assessed. Our main outcomes of interest were current tobacco use, daily tobacco use and use of smokeless tobacco products.

Of 4484 respondents, 605 (13.5%) reported being current tobacco users. Most active tobacco users were male (n = 507/605, 83.8%). Three out of four tobacco users (n = 468/605, 77.4%) reported being less than 50 years old, with the average start age being 21 (20.6, 95% CI 19.3-21.8) and the average quit age 27 (27.2, 95% CI 25.8-28.6). Most tobacco users had only ever attended up to primary school (n = 434/605, 71.7%). Men had nearly seven times higher odds of being tobacco users as compared to women (OR 7.63, 95% CI 5.63-10.33). Alcohol use had a positive effect on tobacco use. Finally, less than ten respondents reported having used e-cigarettes.

The 2015 Kenya WHO STEPS provided primary data on the status of tobacco use in the country and other leading NCD risk factors, such as alcohol, and associated diseases. Our findings highlight key target populations for tobacco cessation efforts: young people, men, those with lower levels of education, and alcohol consumers. Further data is needed on the use of smokeless tobacco, and its impact on smoked tobacco products, as well as on the novel use of e-cigarettes.

Resilience and recovery are of increasing importance in the field of alcohol dependence (AD). This paper describes how imaging studies in man can be used to assess the neurobiological correlates of resilience and, if longitudinal, of disease trajectories, progression rates and markers for recovery to inform treatment and prevention options.

Original papers on recovery and resilience in alcohol addiction and its neurobiological correlates were identified from PubMed and have been analyzed and condensed within a systematic literature review.

Findings deriving from functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) studies have identified links between increased resilience and less task-elicited neural activation within the basal ganglia, and benefits of heightened neural pre-frontal cortex (PFC) engagement regarding resilience in a broader sense; namely, resilience against relapse in early abstinence of AD. Furthermore, findings consistently propose at least partial recovery of brain glucose metabolism and executive and general cognitive functioning, as well as structural plasticity effects throughout the brain of alcohol-dependent patients during the course of short-, medium- and long-term abstinence, even when patients only lowered their alcohol consumption to a moderate level. Additionally, specific factors were found that appear to influence these observed brain recovery processes in AD, e.g. genotype-dependent neuronal (re)growth, gender-specific neural recovery effects, critical interfering effects of psychiatric comorbidities, additional smoking or marijuana influences or adolescent alcohol abuse.

Neuroimaging research has uncovered neurobiological markers that appear to be linked to resilience and improved recovery capacities that are furthermore influenced by various factors such as gender or genetics. Consequently, future system-oriented approaches may help to establish a broad neuroscience-based research framework for alcohol dependence.

This review of contingency management (CM; the behavior-modification method of providing reinforcement in exchange for objective evidence of a desired behavior) for the treatment of substance-use disorders (SUDs) begins by describing the origins of CM and how it has come to be most commonly used during the treatment of SUDs. Our core objective is to review, describe, and discuss three ongoing critical advancements in CM. We review key emerging areas wherein CM will likely have an impact. In total, we qualitatively reviewed 31 studies in a systematic fashion after searching PubMed and Google Scholar. We then describe and highlight CM investigations across three broad themes: adapting CM for underserved populations, CM with experimental technologies, and optimizing CM for personalized interventions. Technological innovations that allow for mobile delivery of reinforcers in exchange for objective evidence of a desired behavior will likely expand the possible applications of CM throughout the SUD-treatment domain and into therapeutically related areas (eg, serious mental illness). When this mobile technology is coupled with new, easy-to-utilize biomarkers, the adaptation for individual goal setting and delivery of CM-based SUD treatment in hard-to-reach places (eg, rural locations) can have a sustained impact on communities most affected by these disorders. In conclusion, there is still much to be done, not only technologically but also in convincing policy makers to adopt this well-established, cost-effective, and evidence-based method of behavior modification.

Contingency management (CM) is associated with decreases in off-target drug and alcohol use during primary target treatment. The primary hypothesis for this trial was that targeting alcohol use or tobacco smoking would yield increased abstinence in the opposite, nontargeted drug. We used a 2 [CM vs. noncontingent control (NC) for alcohol]×2 (CM vs. NC for smoking tobacco) factorial design, with alcohol intake (through urinary ethyl glucuronide) and tobacco smoking (through urinary cotinine) as the primary outcomes. Thirty-four heavy-drinking smokers were randomized into one of four groups, wherein they received CM, or equivalent NC reinforcement, for alcohol abstinence, smoking abstinence, both drugs, or neither drug. The CM for alcohol and tobacco group had only two participants and therefore was not included in analysis. Compared with the NC for alcohol and tobacco smoking group, both the CM for the tobacco smoking group [odds ratio (OR)=12.03; 95% confidence interval (CI): 1.50-96.31] and the CM for the alcohol group (OR=37.55; 95% CI: 4.86-290.17) submitted significantly more tobacco-abstinent urinalyses. Similarly, compared with the NC for the alcohol and tobacco group, both the CM for smoking (OR=2.57; 95% CI: 1.00-6.60) and the CM for alcohol groups (OR=3.96; 95% CI: 1.47-10.62) submitted significantly more alcohol-abstinent urinalyses. These data indicate cross-over effects of CM on indirect treatment targets. Although this is a pilot investigation, it could help to inform the design of novel treatments for alcohol and tobacco co-addiction.

The opioid antagonist naltrexone is not efficacious for every alcohol treatment seeker. However, various individual factors, such as genetic differences and nicotine-use/smoking status, have been suggested as predictors of naltrexone response. In a randomized clinical trial, we previously reported that nicotine-use/smoking status might be a stronger predictor of naltrexone efficacy than OPRM1 A118G single nucleotide polymorphism (SNP) genotype. In this report, we further characterize the nicotine-users in that trial, examine other drinking outcomes, examine the influence of smoking change on naltrexone effects on drinking, and validate the result in smokers with disialo carbohydrate-deficient transferrin (%dCDT) change as an independent biomarker of response.

Individuals (n = 146) meeting DSM-IV criteria for alcohol dependence who were genotyped for the OPRM1 A118G SNP and who did, or did not, use nicotine/cigarettes were randomized, in a balanced fashion, to naltrexone (50 mg/d) or placebo and provided medical management (MM) over a 16-week clinical trial. Alcohol use and smoking during the trial were assessed and analyzed.

Nicotine-use/smoking status significantly interacted with medication in reducing percent heavy drinking days (PHDD) during the trial (p = 0.003), such that nicotine-users/smokers showed significantly lower PHDD on naltrexone versus placebo (p = 0.0001, Cohen's d = 0.89), while nonusers showed no significant difference between naltrexone and placebo (p = 0.95, Cohen's d = 0.02). Similar effects were shown for drinks per day and percent days drinking. The superiority of naltrexone over placebo on PHDD reduction in nicotine-users/smokers was confirmed with %dCDT (Cohen's d range 0.3 to 0.9 over the study). Naltrexone did not significantly change cigarette use in smokers, and change in use did not influence naltrexone's effect on PHDD.

These data confirm past findings that naltrexone is more efficacious in those who use nicotine/cigarettes. Compared to previous work on the OPRM1 A118G SNP, it appears that nicotine-use might be a more salient predictor of naltrexone treatment response. While naltrexone did not change cigarette use during the study, and smoking change was not related to alcohol reduction, it should be noted that participants were not seeking smoking cessation and MM did not address this issue.

There is growing interest in applying the multimorbidity model for mental health disorders - i.e. the interactive effects of co-occurring diagnoses. Alcohol use disorder (AUD) and tobacco use disorder (TUD) often occur together, but distinctive correlates of their co-occurrence have not been studied. Veterans treated by the Veterans Health Administration (VHA) nationally in FY 2012 with diagnoses of both AUD and TUD were compared to those with only AUD or only TUD on socio-environmental factors, medical and psychiatric diagnoses, and service use. Multimorbid effects were defined as those in which patients with both AUD and TUD had more serious problems greater likelihood of specific co-occurring conditions than those with either AUD alone or TUD alone. Veterans with concurrent AUD and TUD (N=153,397), as compared to those with AUD only (N=191,900) or with TUD only (N=643,377), had significantly higher rates of homelessness [odd ratios (ORs)=1.24, 1.68], hepatic disease (ORs=1.11, 2.18), substance use disorders (ORs=1.42, 3.14), receipt of a VA disability pension (ORs=1.26, 1.30) and use of substance and mental health outpatient services (ORs=1.04, 1.12). Veterans with AUD and TUD appear to have more severe problems in some, but not all, socio-environmental, medical, psychiatric, and service use domains than veterans with either of these diagnoses alone. The combination of AUD and TUD yield generally more adverse effects in diverse areas and thus reflect an emergent phenomenon that may a require a distinctive treatment approach.

Babor's A/B typology characterizes alcohol-dependence subtypes, which differ across multiple defining variables; however, differences in cigarette smoking and cessation between these subtypes have not been previously investigated. Topiramate reduces heavy drinking and has separately been found to help non-alcohol-dependent individuals quit smoking. This study tested the hypothesis that topiramate's effects on smoking would be moderated by alcohol-dependence subtype, and explored craving as a mediator of this response.

One hundred twenty-nine abstinent alcohol-dependent outpatient male smokers participated in this 12-week, randomized controlled trial comparing topiramate (maximum dosage 200 mg/day) with placebo, both with brief counseling, for smoking cessation. Participants were followed for 24 weeks following end of treatment.

Of the 125 participants with sufficient subtyping data, k-means cluster analysis categorized 52 (42%) as Type A alcoholics and 73 (58%) as Type B. Types A and B did not differ on baseline smoking characteristics, urges to smoke, or smoking consequence scores. Longitudinal mixed-effects regression indicated that the effect of treatment on smoking was moderated by the Type × Time interaction. Specifically, during the nontreatment follow-up phase, Type B's treated with topiramate had relative suppressed levels of smoking compared with placebo-treated Type B's. This moderating effect of the Type × Time interaction was mediated by intention to smoke and craving related to relief of negative affect.

Type B alcoholics demonstrated suppressed levels of smoking in response to topiramate treatment as compared with placebo, but only during the nontreatment follow-up phase. This effect was mediated, in part, through intention to smoke and craving to smoke to relieve negative affect. Our findings extend other studies demonstrating a differential medication response by alcoholism subtype.

During the transition to adulthood, many unhealthy behaviors are developed that in turn shape behaviors, health, and mortality in later life. However, research on unhealthy behaviors and risky transitions has mostly focused on one health problem at a time. In this article, we examine variation in health behavior trajectories, how trajectories cluster together, and how the likelihood of experiencing different behavior trajectories varies by sociodemographic characteristics. We use the National Longitudinal Study of Adolescent Health (Add Health) Waves I to IV to chart the most common health behavior trajectories over the transition to adulthood for cigarette smoking, alcohol consumption, obesity, and sedentary behavior. We find that health behavior trajectories cluster together in seven joint classes and that sociodemographic factors (including gender, parental education, and race-ethnicity) significantly predict membership in these joint trajectories.

There is inconsistent evidence about the potential influence of smoking on recovery from alcohol dependence. Our study aimed at assessing the impact of smoking-behavior on relapse during a 12 months follow-up period following a detoxification in patients with Alcohol Use Disorder (AUD).

Three hundred Patients with AUD (74.9% smoking) were recruited from two inpatient detoxification units in psychiatric hospitals in Germany and their alcohol consumption was prospectively followed for 1 year. Data on different indicators of smoking behavior was gathered. Cox regression model was used to evaluate potential risk factors on time to relapse of alcohol consumption. Two hundred seventy-nine participants (n = 279) were included in the final analysis.

Smoking increased the risk for alcohol relapse (hazard ratio = 3.962, 95% CI 1.582-9.921). However, this increased risk is slightly reduced with higher numbers of daily consumed cigarettes (hazard ratio per cigarette = .986, 95% CI .976-.995).

Smoking reduced the probability of maintaining alcohol abstinence significantly, whereas higher number of cigarettes smoked daily diminished the increased risk of alcohol relapse in alcohol-dependent patients.

Coordinated psychiatric and substance abuse interventions for different subgroups of patients with AUD in the post-acute treatment phase are necessary. Individualized treatment planning is especially important in smoking patients with AUD who are vulnerable for a relapse to alcohol drinking and for somatic complications. Our findings might support individualized treatment plans. (Am J Addict 2017;26:366-373).