Repeated measures latent class analysis of daily smoking in three smoking cessation studies

High-dose benzodiazepine use and QTc interval prolongation, a latent class analysis study

Benzodiazepine (BDZ) addiction is a widespread and multifaceted phenomenon. For many patients, especially females, the concomitant use of other drugs also increases their risk of QTc prolongation, possibly leading to complications such as seizures and even sudden death. However, the relationship between BDZ use and QTc prolongation is currently unclear. The present study aims to examine patterns of polysubstance use among a sample of Italian adults with BDZ dependence in relation with their QTc prolongation risk. We used Latent Class Analysis (LCA) on data collected from 251 inpatients of the Addiction Medicine Unit in Verona to group patients into three classes according to their substance use and their QTc prolongation risk. Results showed no significant relationship between QTc prolongation and BDZ use in any of the classes considered. We conclude that BDZs, even if used long-term and at high dosages, can be considered safe in terms of cardiovascular complications for patients.

Longitudinal latent polysubstance use patterns among a cohort of people who use opioids in Vancouver, Canada

INTRODUCTION

Polysubstance use (PSU) practices are increasing among people who use opioids (PWUO). However, several aspects of longitudinal PSU patterns among PWUO remain understudied. This study aims to identify person-centred longitudinal patterns of PSU among a cohort of PWUO.

METHODS

Using longitudinal data (2005-2018) from three prospective cohort studies including people who use drugs in Vancouver, Canada, we used repeated measures latent class analysis to identify different PSU classes among PWUO. Multivariable generalised estimating equations models weighted by the respective posterior membership probabilities were applied to identify covariates of membership in different PSU classes over time.

RESULTS

Overall, 2627 PWUO (median age at baseline: 36 [quartile 1-3: 25-45]) were included between 2005 and 2018. We found five distinct PSU patterns, including low/infrequent probability of regular substance use (Class 1; 30%), primarily opioid and methamphetamine use (Class 2; 22%), primarily cannabis use (Class 3; 15%), primarily opioid and crack use (Class 4; 29%) and frequent PSU (Class 5; 4%). Membership in Class 2, 4 and 5 was positively associated with several behavioural and socio-structural adversities.

DISCUSSION AND CONCLUSIONS

Findings of this longitudinal study suggest PSU is the norm among PWUO and highlights the heterogeneous characteristics of PWUO. The diversities within the population of PWUO need to be recognised in addiction care and treatment as well as optimising resource allocation in the response to the overdose crisis.

Polysubstance Use Patterns Among High Dose Benzodiazepine Users: A Latent Class Analysis and Differences Between Male and Female Use

Benzodiazepines (BZDs) represent one of the most widely used groups of pharmaceuticals, but if used for long periods of time they are associated with dependence and an increased risk of harmful effects. High-dose (HD) BZD dependence is a specific substance use disorder associated with a poor quality of life. It is especially important to pinpoint differences in HD BZD addict subgroups in order to tailor treatment to the individual's specific needs, also considering possible comorbidities with other substance use disorders. We conducted a study to evaluate HD BZD dependence (converted doses to diazepam equivalents, mg) in an Italian sample of 1,354 participants. We also investigated if and to which extent participants co-used other substances (alcohol, tobacco, cannabis/cannabinoids, cocaine, and heroin). We then performed latent class analysis (LCA) to identify the use patterns of these substances, finding three classes: participants in Class 1 (4.3% of the sample) had the highest probability of also using cocaine and alcohol (Polysubstance BZD users); Class 2 comprised subjects with the highest probability of being former heroin, cocaine, THC, and alcohol users (Former polysubstance BZD users); Class 3 represented mono-dependence BZD users (78.5% of the sample) and was the most prevalent among women, while young men were most prevalent in Class 1. The present study underlines different characteristics in HD BZD users both concerning other addictions and sex, and also highlights the need for a stricter control of BZD use, ranging from prescriptions to sales.

Trend in the Prevalence of Non-Daily Smoking and Their Relationship with Mental Health Using the Korea Health and Nutrition Examination Survey

Introduction: Non-Daily Smoking (NDS), which is increasingly prevalent worldwide, has not yet attracted as much attention as has daily smoking in Asia. The aims of this study were to identify trends in the prevalence of NDS and to compare characteristics by age, gender, and mental health indicators such as depression, suicidality, and alcohol consumption in South Korea. Methods: We included 33,806 adults (aged ≥ 19 years) who participated in the Korean National Health and Nutrition Examination Survey (KNHNES) from 2010 to 2015. The dataset includes self-reported medical history and questionnaires that explore depression, suicidality, and alcohol use, which are known to be highly related to smoking. We divided the respondents into four groups according to smoking status: Never Smoking (NS, N = 20,270); Past Smoking (PS = 6835); Daily Smoking (DS = 5927), who reported smoking every day; and Non-Daily Smoking (NDS = 774), who reported that they sometimes smoke. Results: Increased NDS prevalence is observed in most age groups in both male and female adults despite the prevalence of total smoking and daily smoking gradually decreasing. Depression and suicidality were significantly more prevalent in the NDS than the NS group (Depression Odds ratio, OR = 1.72, 95% Confidence interval, CI = 1.31–2.26; Suicidality OR = 3.14, 95% CI = 1.40–7.02). NDS is also associated with a higher frequency of binge drinking and alcohol use disorder than NS (OR = 4.17, 95% CI = 3.49–4.99). Conclusions: This study suggests that more concern is warranted for NDS given the increasing prevalence and characteristics of poor mental health in NDS respondents.

Understanding quit patterns from a randomized clinical trial: Latent classes, predictors, and long-term abstinence

OBJECTIVE

Tobacco dependence treatment is recognized as a dynamic, chronic process comprised of several specific phases. Of these phases, the Cessation phase is the most critical as it has demonstrated the strongest relation to quit success. Yet, little is understood about smoking trajectories during this period. The current study aimed to address gaps in the smoking research literature and advance understanding of the dynamic quit process unique to completing an integrated smoking treatment by evaluating quit behavior during the Cessation phase.

METHOD

Two hundred and sixty-seven treatment seeking smokers enrolled in a clinical trial to evaluate the efficacy of a novel, integrated smoking cessation treatment (46.1% male; Mage = 39.25, SD = 13.70) were included in the present study. Repeated-measure latent class analysis was employed to evaluate quit patterns from quit day through day 14 post-quit.

RESULTS

Results supported a four-class solution: Consistent Quitters, Non-Quitters, Relapsers, and Delayed Quitters. Predictors of class membership included age, number of prior quit attempts, motivation to quit smoking, and quit day smoking urges. Moreover, class membership was significantly associated with 6-month abstinence.

CONCLUSION

Results suggest that there are four relevant classes of quit behavior, each with specific predictor variables including age, motivation to quit, smoking urges, and number of quit attempts, and that these classes relate to long-term abstinence. These results have the potential to inform manualized smoking cessation treatment interventions based on relevant subgroups of quit behavior.

Dynamic, data-driven typologies of long-term smoking, cessation, and their correlates: Findings from the International Tobacco Control (ITC) Netherlands Survey

RATIONALE

Efforts towards tobacco control are numerous, but relapse rates for smoking cessations remain high. Behavioral changes necessary for continuous cessation appear complex, variable and subject to social, biological, psychological and environmental determinants. Currently, most cessation studies concentrate on short-to midterm behavioral changes. Besides, they use fixed typologies, thereby failing to capture the temporal changes in smoking/cessation behaviors, and its determinants.

OBJECTIVE

To obtain long-term, data-driven longitudinal patterns or profiles of smoking, cessation, and related determinants in a cohort of adult smokers, and to investigate their dynamic links.

METHODS

The dataset originated from the International Tobacco Control (ITC) Netherlands Project, waves 2008 to 2016. Temporal dynamics of smoking/cessation, psychosocial constructs, and time-varying determinants of smoking were extracted with Group-Based Trajectory Modeling technique. Their associations were investigated via multiple regression models.

RESULTS

Substantial heterogeneity of smoking and cessation behaviors was unveiled. Most respondents were classified as persistent smokers, albeit with distinct levels of consumption. For a minority, cessation could be sustained between 1 and 8 years, while others showed relapsing or fluctuating smoking behavior. Links between smoking/cessation trajectories with those of psychosocial and sociodemographic variables were diverse. Notably, changes in two variables were aligned to behavioral changes towards cessation: decreasing number of smoking peers and attaining a higher self-perceived control.

CONCLUSION

The unveiled heterogeneity of smoking behavior over time and the varied cross-dependencies between smoking data-driven typologies and those of underlying risk factors underscore the need of individually tailored approaches for motivational quitting.

Evidence of subgroups in smokers as revealed in clinical measures and evaluated by neuroimaging data: a preliminary study

To date, fractionation of the nicotine addiction phenotype has been limited to that based primarily on characteristics of cigarette use, although it is widely appreciated that a variety of individual factors are associated with tobacco use disorder. Identifying subtypes of tobacco use disorder based on such factors may lead to better understanding of potential treatment targets, individualize treatments and improve outcomes. In this preliminary study, to identify potential subgroups, we applied hierarchical clustering to a broad range of assessments measuring personality, IQ and psychiatric symptoms, as well as various environmental and experiential characteristics from 102 otherwise healthy cigarette smokers. The identified subgroups were further compared on various resting-state fMRI measures from a subset (N = 65) of individuals who also underwent resting-state fMRI scanning. The clustering dendrogram indicated that smokers can be divided into three subgroups. Each subgroup had unique clinical assessment characteristics. The division yielded imaging differences between subgroups in the supplementary motor area/middle cingulate cortex and the cuneus. Regression analyses showed that amplitude of low frequency fluctuations in the supplementary motor area/middle cingulate cortex differed between groups and were negatively correlated with the Toronto Alexithymia Scale subscale Difficulty Describing Feelings.

Associations Between Timing of Meals, Physical Activity, Light Exposure, and Sleep With Body Mass Index in Free-Living Adults

BACKGROUND

This study tested if the timing of meals, physical activity, light exposure, and sleep cluster within individuals and are associated with body mass index (BMI) in a sample of free-living adults (N = 125).

METHODS

Data were collected between November 2015 and March 2016 at the University of California, San Diego, Children's Hospital of Philadelphia, and Washington University in St Louis. Height and weight were measured, and BMI (kg/m²) was calculated. Sleep timing was estimated using actigraphy, and timing of meals, physical activity, and light exposure were self-reported using a smartphone application. General linear models estimated the mean BMI across time categories of behaviors, adjusting for covariates. A latent class analysis was used to identify patterns of timing variables that clustered within individuals and test for associations between identified patterns and BMI.

RESULTS

Later exposure to outdoor light was associated with a lower BMI (P trend < .01). The timing of other behaviors was not independently associated with BMI. The latent class analysis identified 2 distinct groups related to behavioral timing, reflecting an "early bird" and "night owl" phenotype. These phenotypes were not associated with BMI (P > .05).

CONCLUSION

Timing of exposures to light, meals, sleep, and physical activity were not strongly associated with BMI in this sample.