E-cigarette use and quantity of cigarette smoking among adolescent cigarette smokers: A finite mixture model analysis

Social media use and mental health indicators among US adolescents: A population-based study

Social media use among young people has raised concerns about its potential impact on mental health. However, research is limited regarding whether certain subgroups may be differently affected. This study uses data from the 2022 National Youth Tobacco Survey, a nationally representative sample of middle and high school students aged approximately 11-18 years (n = 23,366). Mental health conditions were assessed using the Patient Health Questionnaire-4, and social media use was categorized by frequency levels. We employed multinomial logistic regression and a finite mixture Poisson model to explore the relationship between social media use, sexual identity, and mental health status. The study found a consistent association between social media use and mental health conditions, particularly among frequent users. The finite mixture model revealed two latent groups based on mental health status: a 'better' group with minimal or no poor mental health indicators and a 'worse' group with more indicators. For both groups, social media use was associated with mental health conditions, with a stronger association among frequent users. Notably, sexual minorities, especially bisexual students, were more likely to report poor mental health indicators. This study suggests that frequent social media use may adversely affect young people's mental health and that different youth subgroups may respond differently to social media use and mental health conditions.

Disposable e-cigarette use: Factors, frequency and cigarette smoking among United States high school students

BACKGROUND AND AIMS

Disposable e-cigarette use has increased among United States (US) high school students in recent years. However, there is limited research on the profile of these users, how often they use these products, and whether they displace cigarette smoking. This study aimed to measure how disposable e-cigarette use among US youth varies according to demographic characteristics and whether there is any association between e-cigarette use and reduced use of traditional cigarettes.

DESIGN

We used cross-sectional data from the 2022 National Youth Tobacco Survey and conducted a multinomial logistic regression to examine factors associated with the types of e-cigarette devices used in the prior 30 days, adjusting for sex, sexual identity, grade level and race/ethnicity. We also used a finite mixture model to account for unobserved differences among users and identify e-cigarette use patterns in different subgroups of users.

SETTING

United States.

PARTICIPANTS

High school students in grades 9-12 (n = 14 389).

MEASUREMENTS

Survey participants self-reported the type of e-cigarette device used, the frequency of e-cigarettes used and cigarettes smoked over the past 30 days.

FINDINGS

Disposable e-cigarettes were the most popular e-cigarette type. Sex, sexual orientation, grade level and race/ethnicity were associated with disposable e-cigarette use. The odds of disposable e-cigarette use were lower in male students than in female students (odds ratio [OR] = 0.78, 95% confidence interval [CI] = [0.64-0.96]), and higher in students who identified as gay or lesbian (OR = 1.70, 95% CI = [1.11-2.61]) or bisexual (OR = 1.52, 95% CI = [1.16-1.99]) than in heterosexual students. The odds of disposable use were higher among students in higher grades (10th, 11th and 12th) than in 9th graders (OR = 1.71, 2.24 and 2.52, respectively). Disposable e-cigarette users had a lower frequency of traditional cigarette use than other e-cigarette users, both in the low-frequency class (incidence rate ratio [IRR] = 0.33, 95% CI = [0.12-0.92]) and the high-frequency class (IRR = 0.27, 95% CI = [0.08-0.92]).

CONCLUSIONS

Disposable e-cigarette use appears to be higher among United States high school students who are female, older and/or identify as gay, lesbian or bisexual. Disposable e-cigarettes appear to be associated with reduced traditional cigarette use.

Human insecurity and child deaths in conflict: evidence for improved response in Yemen

Background

Since the beginning of the ongoing conflict in Yemen, >23 000 air strikes and >100 000 fatalities have been recorded. Data from Yemen Data Project linked >1300 child fatalities and >900 child injuries to air raids. However, there is little literature on the effect of the protracted armed conflict on the pattern of child mortality using data from small-scale surveys. We aimed to identify the pattern of the death rate for children aged <5 years (‘under-5’) and its relationship with human insecurity in Yemen.

Methods

We created a human insecurity index (i.e. severely insecure vs insecure) for the 22 governorates in Yemen from 2015 to 2019, using data from the Armed Conflict Location and Event Database. We matched this insecurity index with the corresponding under-5 mortality data from the Complex Emergency Database. We analysed the relationship between the under-5 death rate (U5DR) and the insecurity level using a Bayesian finite mixture model in order to account for unobserved heterogeneity in clustered finite subsets of a population.

Results

We extracted 72 surveys and 77.8% (n = 56) were included in this study. The mean of the recall period for mortality was 106 days with a standard deviation of 93 days. We identified two subpopulations: Subpopulation I—high average number of child deaths and Subpopulation II—low average number of child deaths. The log posterior mean of the U5DR is 1.10 (95% credible intervals: 0.36, 1.82) in the severely insecure group in Subpopulation I and 3-fold the estimate in Subpopulation II. However, in Subpopulation II, we found no association between the insecurity level and the U5DR.

Conclusion

The pattern of child deaths is crucial in understanding the relationship between human insecurity and the U5DR.

Latent Heterogeneity in the Impact of Financial Coaching on Delay Discounting among Low-Income Smokers: A Secondary Analysis of a Randomized Controlled Trial

Low-income adults are significantly more likely to smoke, and face more difficulty in quitting, than people with high income. High rates of delay discounting (DD) may be an important factor contributing to the high rates of tobacco use among low-income adults. Future-oriented financial coaching may offer a novel approach in the treatment of smoking cessation among low-income adults. This secondary analysis (N = 251) of data from a randomized controlled trial examined the integration of future-oriented financial coaching into smoking cessation treatment for low-income smokers. Linear regression and finite mixture models (FMM) estimated the overall and the latent heterogeneity of the impact of the intervention versus usual care control on DD rates 6 months after randomization. Though standard linear regression found no overall difference in DD between intervention and control (β = −0.23, p = 0.338), the FMM identified two latent subgroups with different responses to the intervention. Subgroup 1 (79% of the sample) showed no difference in DD between intervention and control (β = 0.25, p = 0.08). Subgroup 2 (21% of the sample) showed significantly lower DD (β = −2.06, p = 0.003) among intervention group participants versus control at 6 months. Participants were more likely to be a member of subgroup 2 if they had lower baseline DD rates, were living at or below 100% of federal poverty, or were married/living with a partner. This study identified a group of low-income adults seeking to quit smoking who responded to financial coaching with decreased DD rates. These results can be used to inform future targeting of the intervention to individuals who may benefit most, as well as inform future treatment adaptations to support the subgroup of low-income smokers, who did not benefit.

Trends and predictors of exclusive e-cigarette use, exclusive smoking and dual use among youth in Canada

BACKGROUND

Few studies have examined predictors of exclusive e-cigarette use, exclusive smoking and dual use among youth. We investigated whether frequency of e-cigarette use and cigarette smoking predicted involvement in different usage groups after a 1- and 2-year follow-up among a sample of Canadian youth.

METHODS

A longitudinal sample of youth who participated in three waves of COMPASS [Wave 1 (W₁) 2015/16, Wave 2 (W₂) 2016-17, Wave 3 (W₃) 2017/18] was identified (N = 5,704). Multinomial logistic regression was used to examine whether frequency of e-cigarette use and cigarette smoking at W₁ predicted involvement in different usage groups at W₂ and W₃. Similarly, we examined whether changes in frequency of e-cigarette use and cigarette smoking between W₁ and W₂ predicted involvement in different usage groups at W₃.

RESULTS

E-cigarette users reporting use on 4 or more days per month at W₁ had greater odds of dual use at W₂, compared to non-users (aOR = 11.22, p < 0.0001). Those who reduced their frequency of e-cigarette use between W₁ and W₂ had lower odds of exclusive e-cigarette use and dual use at W₃ (aOR = 0.18 and 0.17 respectively; both p < 0.05). Those who increased their frequency of cigarette smoking between W₁ and W₂ had higher odds of exclusive smoking and dual use at W₃ (aOR = 22.65 and aOR = 9.92 respectively; both p < 0.0001).

DISCUSSION

Reductions in frequency of e-cigarette use appeared to have a protective effect of reducing exclusive e-cigarette use and dual use at follow-up. Increases in frequency of cigarette smoking were a significant predictor of exclusive smoking and dual use.

E-Cigarette Use and Transition in Adult Smoking Frequency: A Longitudinal Study

INTRODUCTION

The relationship between e-cigarette use and cigarette smoking is the subject of ongoing debate. There is limited research on e-cigarette use and changes in the frequency of cigarette smoking. This study examines whether the frequency of e-cigarette use is associated with changes in cigarette smoking behavior among U.S. adults.

METHODS

The study used data (n=20,558) from Waves 1 (2013-2014) and 2 (2014-2015) of the Population Assessment of Tobacco and Health, analyzed in 2019. Multivariable multinomial logistic regression assessed the association between e-cigarette use at Wave 1 and change in cigarette smoking frequency between Waves 1 and 2.

RESULTS

Every day cigarette smokers who used e-cigarettes some days (OR=1.95, 95% CI=1.27, 2.98) and every day (OR=3.37, 95% CI=1.78, 6.36) in Wave 1 had significantly higher odds of switching to some days cigarette smoking in Wave 2. Every day smokers who used e-cigarettes every day in Wave 1 had higher odds of becoming former cigarette smokers in Wave 2. Likewise, e-cigarette use at baseline among former cigarette smokers was associated with higher odds of switching to some days cigarette smoking (experimental e-cigarette use: OR=5.43, 95% CI=2.13, 10.72; some days e-cigarette use: OR=4.78, 95% CI=2.13, 10.72). In addition, experimental smokers who were also some days e-cigarettes users in Wave 1 had significantly lower odds of switching to experimental former smokers.

CONCLUSIONS

Although e-cigarette use may reduce cigarette smoking frequency among continuing smokers, findings suggest that e-cigarette use may be associated with cigarette smoking relapse among former smokers.

The Relationship Between Electronic Cigarette Use and Conventional Cigarette Smoking Is Largely Attributable to Shared Risk Factors

INTRODUCTION

The growing popularity of electronic cigarettes (e-cigarettes) among youth raises concerns about possible causal effects on conventional cigarette smoking. However, past research remains inconclusive due to heavy confounding between cigarette and e-cigarette use. This study uses propensity score methods to robustly adjust for shared risk in estimating the relationship between e-cigarette use and conventional smoking.

METHODS

Cross-sectional data from 8th and 10th graders were drawn from the 2015-2016 waves of Monitoring the Future (n = 12 421). The effects of (1) lifetime and (2) current e-cigarette use on (A) lifetime and (B) current conventional cigarette smoking were examined using logistic regression analyses with inverse propensity weighting based on 14 associated risk factors.

RESULTS

After accounting for the propensity for using e-cigarettes based on 14 risk factors, both lifetime and current e-cigarette use significantly increased the risk of ever smoking a conventional cigarette (OR = 2.49, 95% CI = 1.77 to 3.51; OR = 2.32, 95% CI = 1.66 to 3.25, respectively). However, lifetime (OR = 2.17, 95% CI = 0.62 to 7.63) and current e-cigarette use (OR = 0.95, 95% CI = 0.55 to 1.63) did not significantly increase the risk of current conventional cigarette smoking.

CONCLUSIONS

E-cigarette use does not appear to be associated with current, continued smoking. Instead, the apparent relationship between e-cigarette use and current conventional smoking is fully explained by shared risk factors, thus failing to support claims that e-cigarettes have a causal effect on concurrent conventional smoking among youth. E-cigarette use has a remaining association with lifetime cigarette smoking after propensity score adjustment; however, future research is needed to determine whether this is a causal relationship or merely reflects unmeasured confounding.

IMPLICATIONS

This study examines the relationship between e-cigarette use and conventional smoking using inverse propensity score weighting, an innovative statistical method that produces less-biased results in the presence of heavy confounding. Our findings show that the apparent relationship between e-cigarette use and current cigarette smoking is entirely attributable to shared risk factors for tobacco use. However, e-cigarette use is associated with lifetime cigarette smoking, though further research is needed to determine whether this is a causal relationship or merely reflects unaccounted-for confounding. Propensity score weighting produced significantly weaker effect estimations compared to conventional regression control.

Adolescent Dual Use Classification and Its Association With Nicotine Dependence and Quit Intentions

PURPOSE

Electronic cigarettes (e-cigarette) use is rapidly increasing in the U.S., especially among adolescents. A significant number of adolescents use both cigarettes and e-cigarettes, often referred to as dual use. We used a new classification of dual use, taking into account the frequency of use of both products. In addition, we examined the association between dual use with time to first cigarette after waking (a nicotine dependence measure) and quit intention.

METHODS

Data were drawn from the 2015-2018 National Youth Tobacco Survey. We grouped participants by dual use frequency. Multivariable logistic regression was used to examine the association of dual use frequency with nicotine dependence and quit intention.

RESULTS

Different categories of dual users varied in demographic characteristics and beliefs on the harms of cigarette smoking and e-cigarette use. Compared with cigarette-only smokers, significantly higher odds of nicotine dependence were found for high-frequency e-cigarette dual users (within 5 minutes of awakening, odds ratio [OR]: 1.67, 95% confidence interval [CI], 1.07-2.62; within 30 minutes, OR: 1.61, 95% CI, 1.15-2.27), high-frequency cigarette dual users (5 minutes, OR: 2.85, 95% CI, 1.76-4.63; within 30 minutes, OR: 4.14, 95% CI, 2.96-5.80), and high-frequency dual users (5 minutes, OR: 4.46, 95% CI, 2.88-6.91; 30 minutes, OR: 3.94, 95% CI, 2.43-6.42). In addition, high-frequency e-cigarette dual users had significantly lower quit intention compared with both cigarette-only smokers and low-frequency dual users.

CONCLUSIONS

Findings highlight the need for a standard, granulated classification of dual user, as important characteristics may vary between different categories. Future studies on dual use should consider categorizing dual use into the four classifications described in this study.