A Tutorial for Propensity Score Weighting for Moderation Analysis With Categorical Variables: An Application Examining Smoking Disparities Among Sexual Minority Adults.

OBJECTIVE: To provide step-by-step guidance and STATA and R code for using propensity score (PS) weighting to estimate moderation effects with categorical variables. RESEARCH DESIGN: Tutorial illustrating the key steps for estimating and testing moderation using observational data. Steps include: (1) examining covariate overlap across treatment groups within levels of the moderator; (2) estimating the PS weights; (3) evaluating whether PS weights improved covariate balance; (4) estimating moderated treatment effects; and (5) assessing the sensitivity of findings to unobserved confounding. Our illustrative case study uses data from 41,832 adults from the 2019 National Survey on Drug Use and Health to examine if gender moderates the association between sexual minority status (eg, lesbian, gay, or bisexual [LGB] identity) and adult smoking prevalence. RESULTS: For our case study, there were no noted concerns about covariate overlap, and we were able to successfully estimate the PS weights within each level of the moderator. Moreover, balance criteria indicated that PS weights successfully achieved covariate balance for both moderator groups. PS-weighted results indicated there was significant evidence of moderation for the case study, and sensitivity analyses demonstrated that results were highly robust for one level of the moderator but not the other. CONCLUSIONS: When conducting moderation analyses, covariate imbalances across levels of the moderator can cause biased estimates. As demonstrated in this tutorial, PS weighting within each level of the moderator can improve the estimated moderation effects by minimizing bias from imbalance within the moderator subgroups.

A Causal Approach to Functional Mediation Analysis with Application to a Smoking Cessation Intervention.

The increase in the use of mobile and wearable devices now allows dense assessment of mediating processes over time. For example, a pharmacological intervention may have an effect on smoking cessation via reductions in momentary withdrawal symptoms. We define and identify the causal direct and indirect effects in terms of potential outcomes on the mean difference and odds ratio scales, and present a method for estimating and testing the indirect effect of a randomized treatment on a distal binary variable as mediated by the nonparametric trajectory of an intensively measured longitudinal variable (e.g., from ecological momentary assessment). Coverage of a bootstrap test for the indirect effect is demonstrated via simulation. An empirical example is presented based on estimating later smoking abstinence from patterns of craving during smoking cessation treatment. We provide an R package, funmediation, available on CRAN at https://cran.r-project.org/web/packages/funmediation/index.html, to conveniently apply this technique. We conclude by discussing possible extensions to multiple mediators and directions for future research.

The Impact of Smoking Status and Smoking-Related Comorbidities on Coronavirus Disease 2019 Patient Outcomes: A Causal Mediation Analysis.

INTRODUCTION: Smoking history is a known risk factor for significant chronic diseases as well as pulmonary infections; however, the impact of smoking status on coronavirus disease 2019 (COVID-19) outcomes has not been conclusively characterized. This study aims to evaluate the association of smoking status on COVID-19 outcomes, and to explore the mechanism by which smoking and smoking-related comorbidities relate to COVID-19 outcomes. AIMS AND METHODS: Patients admitted with SARS-CoV-2 infection from November 2020 through January 2021 were included in this study. Causal mediation models investigating the associations between smoking status and the outcomes of mortality, intensive care unit (ICU) admission, advanced respiratory support, mechanical ventilation, ICU length of stay, and hospital length of stay, through mediation via smoking-related comorbidities, were examined. RESULTS: Active smokers did not experience worse COVID-19 outcomes once hospitalized. Former smokers had a higher odds of mortality (total effect OR 1.59, 95% CI 1.07 to 2.38, p = .01; indirect effect OR 1.45, 95% CI 1.09 to 1.93, p < .001), and advanced respiratory support (total effect OR 1.31, 95% CI 1.04 to 1.67, p = .02; indirect effect OR 1.26, 95% CI 1.03 to 1.54, p = .02), which were mediated by smoking-related comorbidities. While there was a nonsignificant increase in the total effect for mechanical ventilation, smoking-related comorbidities were significant mediators for their increased need (total effect OR 1.40, 95% CI 0.92 to 2.14, p = .13; indirect effect OR 1.47, 95% CI 1.10 to 1.87, p < .001). CONCLUSIONS: Although active smokers did not experience worse COVID-19 outcomes compared to never smokers, these results should be interpreted with caution. Compared to never smokers, former smokers had greater odds of mortality, advanced respiratory support, and mechanical ventilation which was significantly mediated through smoking-related comorbidities. IMPLICATIONS: Previous studies have linked smoking status with worse COVID-19 outcomes, and have inferred that smoking-related comorbidities may play a role in these findings. This causal mediation analysis provides statistical evidence supporting this hypothesis, clarifying the risk that smoking-related comorbidities impart on COVID-19 outcomes in those with a smoking history.

Estimation and inference for the mediation effect in a time-varying mediation model.

BACKGROUND: Traditional mediation analysis typically examines the relations among an intervention, a time-invariant mediator, and a time-invariant outcome variable. Although there may be a total effect of the intervention on the outcome, there is a need to understand the process by which the intervention affects the outcome (i.e., the indirect effect through the mediator). This indirect effect is frequently assumed to be time-invariant. With improvements in data collection technology, it is possible to obtain repeated assessments over time resulting in intensive longitudinal data. This calls for an extension of traditional mediation analysis to incorporate time-varying variables as well as time-varying effects. METHODS: We focus on estimation and inference for the time-varying mediation model, which allows mediation effects to vary as a function of time. We propose a two-step approach to estimate the time-varying mediation effect. Moreover, we use a simulation-based approach to derive the corresponding point-wise confidence band for the time-varying mediation effect. RESULTS: Simulation studies show that the proposed procedures perform well when comparing the confidence band and the true underlying model. We further apply the proposed model and the statistical inference procedure to data collected from a smoking cessation study. CONCLUSIONS: We present a model for estimating time-varying mediation effects that allows both time-varying outcomes and mediators. Simulation-based inference is also proposed and implemented in a user-friendly R package.

Time-Varying Mediation of Pharmacological Smoking Cessation Treatments on Smoking Lapse via Craving, Cessation Fatigue, and Negative Mood.

INTRODUCTION: The addictive nature of nicotine makes smoking cessation an extremely challenging process. With prolonged exposure, tobacco smoking transforms from being a positive reinforcer to a negative one, as smoking is used to mitigate aversive withdrawal symptoms. Studying the variations in withdrawal symptoms, especially during their peak in the first week of a quit attempt, could help improve cessation treatment for the future. The time-varying mediation model effectively studies whether altering withdrawal symptoms act as mediators in the pathway between treatment and cessation. AIMS AND METHODS: This secondary data analysis of a randomized clinical smoking cessation trial of three pharmacotherapy regimens (nicotine patch, varenicline, and nicotine patch + mini-lozenge) analyzes ecological momentary assessment (EMA) data from the first 4 weeks post-target quit day (TQD). We assess whether withdrawal symptoms (eg, negative mood, cessation fatigue, and craving) mediate the pathway between pharmacotherapy and daily smoking status and whether this effect varies over time. RESULTS: We found a statistically significant time-varying mediation effect of varenicline on smoking status through craving, which shows decreasing risk of lapse via reduction in craving. We did not find significant time-varying mediation effects through negative mood and cessation fatigue. CONCLUSIONS: This study supports the importance of craving suppression in the smoking cessation process. It also helped identify specific timepoints when withdrawal symptoms increased that would likely benefit from targeted cessation intervention strategies. IMPLICATIONS: This study aimed to understand the underlying dynamic mechanisms of the smoking cessation process using a new analytical approach that capitalizes on the intensive longitudinal data collected via EMAs. The findings from this study further elucidate the smoking cessation process and provide insight into behavioral intervention targets and the timing of such interventions through the estimation of time-varying mediation effects.

Relationships Between E-cigarette Use and Subsequent Cigarette Initiation Among Adolescents in the PATH Study: an Entropy Balancing Propensity Score Analysis.

This study aimed to examine the relationship between electronic cigarette use and subsequent combustible cigarette use, controlling for confounding by using a propensity score method approach. Data from the first three annual waves of the Population Assessment of Tobacco and Health study were analyzed (n = 6309). Participants were tobacco-naïve at Wave 1; used e-cigarettes exclusively (n = 414), used combustible cigarettes exclusively (n = 46), or not used any tobacco products (n = 5849) at Wave 2. We conducted entropy balancing propensity score analysis to examine the association between exclusive e-cigarette or cigarette initiation and subsequent cigarette use at Wave 3, adjusting for non-response bias, sampling bias, and confounding. Among tobacco-naïve youth, exclusive e-cigarette use was associated with greater risk for subsequent combustible cigarette smoking initiation (OR = 3.42, 95% CI = (1.99, 5.93)) and past 30-day combustible cigarette use (OR = 2.88, 95% CI = (1.22, 6.86)) in the following year. However, the latter risk was comparatively lower than the risk if youth started with a combustible cigarette (OR = 25.79, 95% CI = (9.68, 68.72)). Results of sensitivity analyses indicated that estimated effects were robust to unmeasured confounding. Use of e-cigarettes in tobacco-naïve youth is associated with increased risk of subsequent past 30-day combustible cigarette use but the risk is an order of magnitude higher if they start with a combustible cigarette.

Impact of topical budesonide on prevention of esophageal stricture after mucosal resection.

BACKGROUND AND AIMS: EMR and endoscopic submucosal dissection (ESD) are treatment modalities for Barrett's esophagus involving high-grade dysplasia or early cancer. Injectional corticosteroid therapy decreases the risk of procedure-related esophageal stricture (ES) formation. Our aim was to assess the efficacy of topical budesonide on the rate of ES formation after EMR or ESD. METHODS: Patients included prospectively from 3 tertiary endoscopy centers received 3 mg budesonide orally twice a day for 8 weeks after esophageal EMR or ESD of 50% or more of the esophageal circumference between January 1, 2014 and June 30, 2018. These patients were matched (1:3 ratio) retrospectively with a consecutive patient cohort who underwent EMR or ESD of 50% or more of the esophageal circumference without concomitant corticosteroid therapy. The primary endpoint was the presence of ES at the 12-week follow-up. RESULTS: Twenty-five patients (budesonide) were matched with 75 patients (no budesonide). Most underwent EMR for Barrett's esophagus with biopsy-proven high-grade dysplasia or suspected T1a cancer. Although most baseline characteristics did not differ significantly, patients in the budesonide cohort tended to have a higher proportion of circumferential EMR. The proportion of patients with ES was not significantly lower in the budesonide cohort (16% vs 28%). On logistic regression analysis, budesonide remained associated with a lower incidence of ES (P = .023); however, when controlling for baseline characteristics with a propensity score weighted logistic regression model, there was no significant effect on ES formation (P = .176). CONCLUSIONS: Topical budesonide might be associated with a reduction of ES after EMR or ESD; however, further studies are needed to verify our results.

Scalar-on-function regression for predicting distal outcomes from intensively gathered longitudinal data: Interpretability for applied scientists.

Researchers are sometimes interested in predicting a distal or external outcome (such as smoking cessation at follow-up) from the trajectory of an intensively recorded longitudinal variable (such as urge to smoke). This can be done in a semiparametric way via scalar-on-function regression. However, the resulting fitted coefficient regression function requires special care for correct interpretation, as it represents the joint relationship of time points to the outcome, rather than a marginal or cross-sectional relationship. We provide practical guidelines, based on experience with scientific applications, for helping practitioners interpret their results and illustrate these ideas using data from a smoking cessation study.

Kids Safe and Smokefree (KiSS) Multilevel Intervention to Reduce Child Tobacco Smoke Exposure: Long-Term Results of a Randomized Controlled Trial.

BACKGROUND: Pediatricians following clinical practice guidelines for tobacco intervention (“Ask, Advise, and Refer” [AAR]) can motivate parents to reduce child tobacco smoke exposure (TSE). However, brief clinic interventions are unable to provide the more intensive, evidence-based behavioral treatments that facilitate the knowledge, skills, and confidence that parents need to both reduce child TSE and quit smoking. We hypothesized that a multilevel treatment model integrating pediatric clinic-level AAR with individual-level, telephone counseling would promote greater long-term (12-month) child TSE reduction and parent smoking cessation than clinic-level AAR alone. METHODS: Pediatricians were trained to implement AAR with parents during clinic visits and reminded via prompts embedded in electronic health records. Following AAR, parents were randomized to intervention (AAR + counseling) or nutrition education attention control (AAR + control). Child TSE and parent quit status were bioverified. RESULTS: Participants (n = 327) were 83% female, 83% African American, and 79% below the poverty level. Child TSE (urine cotinine) declined significantly in both conditions from baseline to 12 months (p = 0.001), with no between-group differences. The intervention had a statistically significant effect on 12-month bioverified quit status (p = 0.029): those in the intervention group were 2.47 times more likely to quit smoking than those in the control. Child age was negatively associated with 12-month log-cotinine (p = 0.01), whereas nicotine dependence was positively associated with 12-month log-cotinine levels (p = 0.001) and negatively associated with bioverified quit status (p = 0.006). CONCLUSIONS: Pediatrician advice alone may be sufficient to increase parent protections of children from TSE. Integrating clinic-level intervention with more intensive individual-level smoking intervention is necessary to promote parent cessation.

Dietary energy density is positively associated with breast density among young women.

BACKGROUND: Breast density is an established predictor of breast cancer risk, and there is considerable interest in associations of modifiable lifestyle factors, such as diet, with breast density. OBJECTIVE: To determine whether dietary energy density (ED) is associated with percent dense breast volume (%DBV) and absolute dense breast volume (ADBV) in young women. DESIGN: A cross-sectional analysis was conducted with women who participated in the Dietary Intervention Study in Children Follow-Up Study. %DBV and ADBV were measured by magnetic resonance imaging. Diet was assessed by three 24-hour recalls. Dietary ED (kilocalories/gram) was calculated using three methods: food only, food and caloric beverages, and food and all beverages. PARTICIPANTS/SETTING: One hundred seventy-two women (aged 25 to 29 years) who were enrolled in the Dietary Intervention Study in Children Follow-Up Study. Participants who reported breast augmentation or reduction surgery or were pregnant or lactating within 3 months before breast density assessment were excluded. MAIN OUTCOME MEASURES: ADBV and %DBV. STATISTICAL ANALYSES PERFORMED: Multivariable linear mixed effects models were used. Final models were adjusted for race, smoking status, education, parity, duration of sex hormone use, whole body percent fat, childhood body mass index z score, and energy from beverages. RESULTS: After adjustment, each 1 kcal/g unit increase in food-only ED was associated with a 25.9% (95% CI 6.2% to 56.8%) increase in %DBV (P=0.01). Childhood body mass index z score modified the association between food-only ED and %DBV such that a significant positive association was observed only in women who were heavier as children. Food-only ED was not associated with ADBV in all women, but a borderline significant positive association was observed in women who had higher childhood body mass index z scores. CONCLUSIONS: This is the first report to suggest a potential role for dietary ED in breast density; the effects of long-term exposure to high-ED diets on breast cancer risk remain unknown.

Diet-related practices and BMI are associated with diet quality in older adults.

OBJECTIVE: To assess the association of diet-related practices and BMI with diet quality in rural adults aged ≥74 years. DESIGN: Cross-sectional. Dietary quality was assessed by the twenty-five-item Dietary Screening Tool (DST). Diet-related practices were self-reported. Multivariate linear regression models were used to analyse associations of DST scores with BMI and diet-related practices after controlling for gender, age, education, smoking and self- v. proxy reporting. SETTING: Geisinger Rural Aging Study (GRAS) in Pennsylvania, USA. SUBJECTS: A total of 4009 (1722 males, 2287 females; mean age 81·5 years) participants aged ≥74 years. RESULTS: Individuals with BMI < 18·5 kg/m2 had a significantly lower DST score (mean 55·8, 95 % CI 52·9, 58·7) than those individuals with BMI = 18·5-24·9 kg/m2 (mean 60·7, 95 % CI 60·1, 61·5; P = 0·001). Older adults with higher, more favourable DST scores were significantly more likely to be food sufficient, report eating breakfast, have no chewing difficulties and report no decline in intake in the previous 6 months. CONCLUSIONS: The DST may identify potential targets for improving diet quality in older adults including promotion of healthy BMI, breakfast consumption, improving dentition and identifying strategies to decrease concern about food sufficiency.

Investigating the potential causal relationship between parental knowledge and youth risky behavior: a propensity score analysis.

This longitudinal study aims to explore the potential causal relationship between parental knowledge and youth risky behavior among a sample of rural, early adolescents (84 % White, 47 % male). Using inverse propensity weighting, the sample was adjusted by controlling for 33 potential confounding variables. Confounding variables include other aspects of the parent-child relationship, parental monitoring, demographic variables, and earlier levels of problem behavior. The effect of parental knowledge was significant for youth substance and polysubstance use initiation, alcohol and cigarette use, attitudes towards substance use, and delinquency. Our results suggest that parental knowledge may be causally related to substance use during middle school, as the relationship between knowledge and youth outcomes remained after controlling for 33 different confounding variables. The discussion focuses on understanding issues of causality in parenting and intervention implications.

Introducing the at-risk average causal effect with application to HealthWise South Africa.

Researchers often hypothesize that a causal variable, whether randomly assigned or not, has an effect on an outcome behavior and that this effect may vary across levels of initial risk of engaging in the outcome behavior. In this paper, we propose a method for quantifying initial risk status. We then illustrate the use of this risk-status variable as a moderator of the causal effect of leisure boredom, a non-randomized continuous variable, on cigarette smoking initiation. The data come from the HealthWise South Africa study. We define the causal effects using marginal structural models and estimate the causal effects using inverse propensity weights. Indeed, we found leisure boredom had a differential causal effect on smoking initiation across different risk statuses. The proposed method may be useful for prevention scientists evaluating causal effects that may vary across levels of initial risk.

Predicting substance use behavior among South African adolescents: The role of leisure experiences across time.

Using seven waves of data, collected twice a year from the 8th through the 11th grades in a low-resource community in Cape Town, South Africa, we aimed to describe the developmental trends in three specific leisure experiences (leisure boredom, new leisure interests, and healthy leisure) and substance use (cigarettes, alcohol, and marijuana) behaviors and to investigate the ways in which changes in leisure experiences predict changes in substance use behaviors over time. Results indicated that adolescents' substance use increased significantly across adolescence, but that leisure experiences remained fairly stable over time. We also found that adolescent leisure experiences predicted baseline substance use and that changes in leisure experiences predicted changes in substance use behaviors over time, with leisure boredom emerging as the most consistent and strongest predictor of alcohol, cigarette, and marijuana use. Implications for interventions that target time use and leisure experiences are discussed.