Tobacco use trajectories among a large cohort of treated smokers with posttraumatic stress disorder

Tobacco use, trauma exposure and PTSD: a systematic review

Tobacco use remains one of the most significant preventable public health problems globally and is increasingly concentrated among vulnerable groups, including those with trauma exposure or diagnosed with PTSD. The goal of this systematic review was to update and extend previous reviews. Of the 7224 publications that met the initial criteria, 267 were included in the review. Summary topic areas include conceptual frameworks for the relation between trauma or PTSD and tobacco use; associations between trauma exposure or PTSD and tobacco use; number and type of trauma exposures and tobacco use; PTSD symptoms and tobacco use; Treatment-related studies; and the examination of causal relations. Evidence continues to indicate that individuals exposed to trauma or diagnosed with PTSD are more likely to use tobacco products, more nicotine dependent and less likely to abstain from tobacco even when provided evidence-based treatments than individuals without trauma. The most commonly cited causal association proposed was use of tobacco for self-regulation of negative affect associated with trauma. A small proportion of the studies addressed causality and mechanisms of action. Future work should incorporate methodological approaches and measures from which we can draw causal conclusions and mechanisms to support the development of viable therapeutic targets.

A scoping review of the clinical application of machine learning in data-driven population segmentation analysis

OBJECTIVE

Data-driven population segmentation is commonly used in clinical settings to separate the heterogeneous population into multiple relatively homogenous groups with similar healthcare features. In recent years, machine learning (ML) based segmentation algorithms have garnered interest for their potential to speed up and improve algorithm development across many phenotypes and healthcare situations. This study evaluates ML-based segmentation with respect to (1) the populations applied, (2) the segmentation details, and (3) the outcome evaluations.

MATERIALS AND METHODS

MEDLINE, Embase, Web of Science, and Scopus were used following the PRISMA-ScR criteria. Peer-reviewed studies in the English language that used data-driven population segmentation analysis on structured data from January 2000 to October 2022 were included.

RESULTS

We identified 6077 articles and included 79 for the final analysis. Data-driven population segmentation analysis was employed in various clinical settings. K-means clustering is the most prevalent unsupervised ML paradigm. The most common settings were healthcare institutions. The most common targeted population was the general population.

DISCUSSION

Although all the studies did internal validation, only 11 papers (13.9%) did external validation, and 23 papers (29.1%) conducted methods comparison. The existing papers discussed little validating the robustness of ML modeling.

CONCLUSION

Existing ML applications on population segmentation need more evaluations regarding giving tailored, efficient integrated healthcare solutions compared to traditional segmentation analysis. Future ML applications in the field should emphasize methods' comparisons and external validation and investigate approaches to evaluate individual consistency using different methods.

Lifelong smoking trajectories of Northern Finns are characterized by sociodemographic and lifestyle differences in a 46-year follow-up

Smoking remains among the leading causes of mortality worldwide. Obtaining a comprehensive understanding of a population’s smoking behaviour is essential for tobacco control. Here, we aim to characterize lifelong smoking patterns and explore underlying sociodemographic and lifestyle factors in a population-based birth cohort population followed up for 46 years. Our analysis is based on 5797 individuals from the Northern Finland Birth Cohort 1966 who self-reported their tobacco smoking behaviour at the ages of 14, 31 and 46. Data on sex, education, employment, body mass index, physical activity, alcohol consumption, and substance addiction were also collected at the follow-ups. We profile each individual’s annual smoking history from the age of 5 to 47, and conduct a latent class trajectory analysis on the data. We then characterize the identified smoking trajectory classes in terms of the background variables, and compare the heaviest smokers with other classes in order to reveal specific predictors of non-smoking and discontinued smoking. Six smoking trajectories are identified in our sample: never-smokers (class size 41.0%), youth smokers (12.6%), young adult quitters (10.8%), late adult quitters (10.5%), late starters (4.3%), and lifetime smokers (20.7%). Smoking is generally associated with male sex, lower socioeconomic status and unhealthier lifestyle. Multivariable between-class comparisons identify unemployment (odds ratio [OR] 1.28–1.45) and physical inactivity (OR 1.20–1.52) as significant predictors of lifetime smoking relative to any other class. Female sex increases the odds of never-smoking and youth smoking (OR 1.29–1.33), and male sex increases the odds of adult quitting (OR 1.30–1.41), relative to lifetime smoking. We expect future initiatives to benefit from our data by exploiting the identified predictors as direct targets of intervention, or as a means of identifying individuals who may benefit from such interventions.

A longitudinal analysis of tobacco use in younger and older U.S. veterans

United States (U.S.) veterans are prone to higher rates of smoking and smoking-related disease. We describe the prevalence of cigarette and non-cigarette product use and determine longitudinal predictors of tobacco use transitions in this vulnerable population.

Data are from Waves 1 (2013–2014) and 2 (2014–2015) of the adult cohort in the Population Assessment of Tobacco and Health. Wave 1 prevalence was calculated for past 30-day use of all queried tobacco products, and compared by veteran status. Weighted multinomial logistic regression was used to determine predictors—demographics, substance use, and physical and psychological comorbidities—of tobacco use transitions (continued use, initiation, and cessation) among veterans.

Compared to non-veterans, use of nearly all tobacco products was significantly higher among veterans and was highest among younger veterans. Compared to continued nonusers, continued users were more likely to: be of younger age (OR = 0.95, 95% CI: 0.95–0.96), have poorer physical health (OR = 1.58, 95% CI: 1.22–2.06) and mental health (OR = 1.48, 95% CI: 1.18–1.85), report substance use (OR = 1.79, 95% CI: 1.21–2.64), and report problematic alcohol use (OR = 4.23, 95% CI: 2.38–7.52) and were less likely to be female (OR = 0.57, 95% CI: 0.35–0.93). Compared to continued nonusers, initiators were more likely to report problematic alcohol use (OR = 8.63, 95% CI: 3.79–19.63), and those in the cessation category were more likely to be of younger age (OR = 0.97, 95% CI: 0.95–0.99).

Cigarette and non-cigarette use is especially prevalent among young veterans, so prevention should begin during military service. Tobacco cessation programs should be tailored for this population, incorporating aspects related to concomitant health conditions.

Posttraumatic stress disorder and tobacco use: A systematic review and meta-analysis

Posttraumatic stress disorder (PTSD) and tobacco use are prevalent conditions that co-occur at striking rates in the US. Previous reviews examined prevalence and factors associated with cigarette smoking among individuals with PTSD but have not been summarized since 2007. Moreover, none explored rates and factors associated with the use of other tobacco products. This study aimed to systematically review the most recent literature examining the comorbidity of PTSD and tobacco use to provide prevalence rates, as well as summarize the literature exploring other factors associated with tobacco use among individuals with PTSD. Studies were identified using a systematic search of keywords related to tobacco use and PTSD within the following databases: PubMed, PsycINFO, Web of Knowledge, CINAHL, PsycARTICLES, and Cochrane Clinical Trials Library. The studies included in this review (N = 66) showed that the prevalence of current use of tobacco products in individuals with PTSD was 24.0% and the rate of PTSD among users of tobacco products was 20.2%. Additionally, results demonstrated that individuals with PTSD present with high levels of nicotine dependence and heavy use of tobacco products, as well as underscore the importance of negative emotional states as a contributing factor to tobacco use among individuals with PTSD. It is imperative that future studies continue monitoring tobacco use among individuals with PTSD while also assessing factors identified as having a prominent role in tobacco use among individuals with PTSD. These findings also demonstrate the need for more innovative approaches to reduce the pervasive tobacco use among individuals with PTSD.

A Review of Impact of Tobacco Use on Patients with Co-occurring Psychiatric Disorders

Consumption of tobacco has been a worldwide problem over the past few decades due to the highly prevalent tobacco-attributable complications. Tobacco use has also been found to be more prevalent in patients with psychiatric disorders. Therefore, we conducted this review about the impact of tobacco use on co-occurring psychiatric disorders. Various facets of this interaction between tobacco use among those with co-occurring psychiatric disorders have been explored. It has been found that people with psychiatric disorders have a higher chance of currently smoking tobacco and lesser chance of cessation. Tobacco use and mental disorders continue to share a complex relationship that has been further evolving after the change in the pattern of tobacco use and also the advent of newer modalities of treatment. However, at the same time, it is believed that cessation of smoking may lead to improvement in the symptoms of mental illness.