Harmonizing Cigar Survey Data Across Tobacco Centers of Regulatory Science, Center for Tobacco Products, and Population Assessment of Tobacco and Health Studies: The Cigar Collaborative Research Group.

INTRODUCTION: Cigars are a popular tobacco product of choice for youth and young adults. Despite growing interest in cigar research, there are gaps in the available literature limiting an ability to set evidence-based policies. Too small research samples, the heterogeneity of types of cigars when asking a single question about use, makes analyzing data difficult. Given the Food and Drug Administration's (FDA's) authority granted in 2016 to regulate cigars, and its popularity, data to better understand use and preference for cigars will help FDA set appropriate regulatory policies. METHODS: We harmonized cigar survey data previously collected by five independent tobacco regulatory science survey research projects. Data supplying participants included three Tobacco Centers of Regulatory Science, one Center for Tobacco Products grantee, and data from Population Assessment of Tobacco and Health (PATH) study's public use dataset. RESULTS: Analyzing 92 data variables from across five studies, and applying a rigorous data harmonization protocol, we report findings on 24 key cigar use variables. The step by step protocol for harmonizing is presented. Selected findings showing strict reproducibility across all five studies reveal youth 17-19 years at highest risk for cigar initiation; relative reproducibility shows males more likely to try cigars than females but with significant differences in magnitude across studies; and areas of inconsistent reproducibility are revealed when evaluating brand preferences. CONCLUSION: Harmonizing data from multiple sources fosters a broader view of the robustness and generalizability of survey data than that from a single source. These observations raise awareness to look for the highest degree of reproducibility among and across data sources to inform policy. IMPLICATIONS: Harmonizing data from discrete datasets provides insights into cigar initiation and use and is presented showing opportunities, challenges, and solutions. Comparing observational data from PATH and four independent research studies provides a best-practices approach and example of data synthesis for the tobacco research community. The dataset of five studies offers a look at the degree of confidence in analyzing harmonized survey results. Variable conclusions raise the need to strive for the highest degree of reproducibility, to best understand the behaviors of cigar users, and allow for the future development of the most effective interventions to alter tobacco use patterns.

Psychometric Evaluation of the E-cigarette Dependence Scale.

INTRODUCTION: Psychometrically sound measures of e-cigarette dependence are lacking. METHODS: We modified the PROMIS Item Bank v1.0-Smoking: Nicotine Dependence for All Smokers for use with e-cigarettes and evaluated the psychometrics of the 22-, 8-, and 4-item adapted versions, referred to as The E-cigarette dependence scale (EDS). Adults (1009) who reported using e-cigarettes at least weekly completed an anonymous survey in summer 2016 (50.2% male, 77.1% White, mean age 35.81 [10.71], 66.4% daily e-cigarette users, 72.6% current cigarette smokers). Psychometric analyses included confirmatory factor analysis, internal consistency, measurement invariance, examination of mean-level differences, convergent validity, and test-criterion relationships with e-cigarette use outcomes. RESULTS: All EDS versions had confirmable, internally consistent latent structures that were scalar invariant by sex, race, e-cigarette use (nondaily/daily), e-liquid nicotine content (no/yes), and current cigarette smoking status (no/yes). Daily e-cigarette users, nicotine e-liquid users, and cigarette smokers reported being more dependent on e-cigarettes than their counterparts. All EDS versions correlated strongly with one another, evidenced convergent validity with the Penn State E-cigarette Dependence Index and time to first e-cigarette use in the morning, and evidenced test-criterion relationships with vaping frequency, e-liquid nicotine concentration, and e-cigarette quit attempts. Similar results were observed when analyses were conducted within subsamples of exclusive e-cigarette users and duals-users of cigarettes and e-cigarettes. CONCLUSIONS: Each EDS version evidenced strong psychometric properties for assessing e-cigarette dependence in adults who either use e-cigarette exclusively or who are dual-users of cigarettes and e-cigarettes. However, results indicated little benefit of the longer versions over the 4-item EDS, which provides an efficient assessment of e-cigarette dependence. IMPLICATIONS: The availability of the novel, psychometrically sound EDS can further research on a wide range of questions related to e-cigarette use and dependence. In addition, the overlap between the EDS and the original PROMIS that was developed for assessing nicotine dependence to cigarettes provides consistency within the field.

Use and Impact of Type 2 Diabetes Prevention Interventions.

INTRODUCTION: RCTs have found that type 2 diabetes can be prevented among high-risk individuals by metformin medication and evidence-based lifestyle change programs. The purpose of this study is to estimate the use of interventions to prevent type 2 diabetes in real-world clinical practice settings and determine the impact on diabetes-related clinical outcomes. METHODS: The analysis performed in 2020 used 2010‒2018 electronic health record data from 69,434 patients aged ≥18 years at high risk for type 2 diabetes in 2 health systems. The use and impact of prescribed metformin, lifestyle change program, bariatric surgery, and combinations of the 3 were examined. A subanalysis was performed to examine uptake and retention among patients referred to the National Diabetes Prevention Program. RESULTS: Mean HbA1c values declined from before to after intervention for patients who were prescribed metformin (-0.067%; p<0.001) or had bariatric surgery (-0.318%; p<0.001). Among patients referred to the National Diabetes Prevention Program lifestyle change program, the type 2 diabetes postintervention incidence proportion was 14.0% for nonattendees, 12.8% for some attendance, and 7.5% for those who attended ≥4 sessions (p<0.001). Among referred patients to the National Diabetes Prevention Program lifestyle change program, uptake was low (13% for 1‒3 sessions, 15% for ≥4 sessions), especially among males and Hispanic patients. CONCLUSIONS: Findings suggest that metformin and bariatric surgery may improve HbA1c levels and that participation in the National Diabetes Prevention Program may reduce type 2 diabetes incidence. Efforts to increase the use of these interventions may have positive impacts on diabetes-related health outcomes.

The Longitudinal Epidemiologic Assessment of Diabetes Risk (LEADR): Unique 1.4 M patient Electronic Health Record cohort.

BACKGROUND: The Longitudinal Epidemiologic Assessment of Diabetes Risk (LEADR) study uses a novel Electronic Health Record (EHR) data approach as a tool to assess the epidemiology of known and new risk factors for type 2 diabetes mellitus (T2DM) and study how prevention interventions affect progression to and onset of T2DM. We created an electronic cohort of 1.4 million patients having had at least 4 encounters with a healthcare organization for at least 24-months; were aged ≥18 years in 2010; and had no diabetes (i.e., T1DM or T2DM) at cohort entry or in the 12 months following entry. EHR data came from patients at nine healthcare organizations across the U.S. between January 1, 2010-December 31, 2016. RESULTS: Approximately 5.9% of the LEADR cohort (82,922 patients) developed T2DM, providing opportunities to explore longitudinal clinical care, medication use, risk factor trajectories, and diagnoses for these patients, compared with patients similarly matched prior to disease onset. CONCLUSIONS: LEADR represents one of the largest EHR databases to have repurposed EHR data to examine patients' T2DM risk. This paper is first in a series demonstrating this novel approach to studying T2DM. IMPLICATIONS: Chronic conditions that often take years to develop can be studied efficiently using EHR data in a retrospective design. LEVEL OF EVIDENCE: While much is already known about T2DM risk, this EHR's cohort's 160 M data points for 1.4 M people over six years, provides opportunities to investigate new unique risk factors and evaluate research hypotheses where results could modify public health practice for preventing T2DM.

Systematic review of cigars, cigarillos, and little cigars among adolescents: Setting research agenda to inform tobacco control policy.

INTRODUCTION: We conducted a systematic review of the literature on cigar research on youth to identify potential future research agenda to generate evidence to inform cigar regulations to prevent cigar use among youth. METHODS: We searched articles on Medline, EMBASE, and PsycINFO in April 2017 to identify articles relevant to cigars and adolescents. Two independent coders examined 48 articles to determine eligibility: (1) published between 2000-April 2017; (2) published in English; (3) conducted in the United States; (4) published in a peer-review journal; (5) examined cigars, cigarillos, or little cigars; (6) included youth (12-18 years old); and (7) included empirical data. Three independent coders reviewed the included articles (n = 48) to identify whether the studies addressed FDA's Research Priorities. RESULTS: The studies addressed FDA's Research Priorities of "behavior" (n = 48), "communications" (n = 4), "marketing influences" (n = 1), and "impact analysis" (n = 1). Studies on "behavior" underscored the need for improvements in measurement, such as using brand names and distinguishing cigar products. The review revealed the need for restrictions on cigar flavors, development of media campaigns and interventions, increasing the cost (via taxation), and evaluating the impact of cigar policies. CONCLUSIONS: The studies mostly focused on surveillance of behaviors and use patterns, which revealed cigar specific issues to address in policies to decrease cigar use among youth. The lack of studies addressing other FDA's research priorities highlighted the critical need for future studies that inform prevention of youth cigar use.

Development and psychometric validation of a novel measure of sensory expectancies associated with E-cigarette use.

INTRODUCTION: E-cigarette dependence measures largely focus on e-cigarette use ("vaping") that is linked to nicotine use, and measures assessing sensory aspects of vaping that may influence use (e.g., taste) are limited in scope. Thus, we developed the novel Sensory E-cigarette Expectancies Scale (SEES). METHODS: In Summer 2017, 610 adult e-cigarette users (48.7% male, 84.9% White, 37.41[±12.15] years old) completed an online survey that included 23 SEES items. Psychometric analyses included evaluating latent structure, internal consistency, measurement invariance, mean differences, and test-criterion relationships. RESULTS: Factor analyses supported a 9-item, 3-subscale structure (taste/smell, pleasure/satisfaction, vapor cloud production). Subscales evidenced internal consistency and scalar invariance by sex, race, smoking status (current/not), vaping status (daily/not), e-liquid nicotine content (yes/no), and device type (cig-a-likes/vape-pens/Advanced Personal Vaporizers [APVs]/Mods). Women and daily e-cigarette users reported stronger SEEs for taste/smell and pleasure than their counterparts. Non-white participants reported stronger SEEs for cloud production than White participants. Cig-a-like users reported the weakest SEEs for taste/smell and weaker SEEs linked to cloud production than APV/mod users. SEES scores evidenced convergence with nicotine dependence (mean r = .36). Finally, SEES scores predicted vaping frequency and habitual vaping concurrently and incrementally beyond nicotine dependence. CONCLUSIONS: The SEES evidenced good psychometric properties, suggesting that the measure can be used to assess sensory vaping expectancies in adults. Importantly, SEES scores indicated that sensory expectancies are related, yet distinct, from nicotine dependence. Future research should evaluate how SEEs relate to product characteristic preferences and patterns of vaping including the development and maintenance of addiction.

Measuring E-cigarette dependence: Initial guidance.

E-cigarette use rates are increasing among youth and adults, despite limited knowledge about the safety, risks, and potential for this product in substituting for or reducing other tobacco use. Understanding how to characterize and assess e-cigarette dependence will be important for evaluating the public health impact of e-cigarettes and considering prevention and intervention strategies. To provide an initial review of constructs to consider when assessing e-cigarette dependence, a content expert group within the Tobacco Center for Regulatory Science (TCORS) Measurement Workgroup engaged in a review of published manuscripts and 12 tobacco dependence measures, followed by review of suggested dependence domains by a 10-person external subject-matter expert panel. The final domains selected to be considered in the development of a measure of e-cigarette dependence included: 1) Quantity and frequency of use, 2) Tolerance, 3) Perceived benefits, 4) Withdrawal symptoms, 5) Craving/urge to use, 6) Use despite harm, 7) Impaired control, 8) Automaticity, 9) Preferred over competing rewards, and 10) Sensory dependence. Similarities and differences in potential features of e-cigarette dependence compared with dependence on other tobacco products is discussed. Future work will evaluate these dependence items and constructs in a sample of e-cigarette users with a goal of developing a valid, brief, standardized measure of e-cigarette dependence.

The Healthy Communities Study: Its Rationale, Aims, and Approach.

Communities across the U.S. are implementing programs and policies designed to address the epidemic of childhood obesity. These programs vary widely in their approaches, including the intensity level, duration, funding, target population, and implementation techniques. However, no previous studies have examined these variations and determined how such aspects of community programs and policies are related to childhood obesity outcomes. The Healthy Communities Study is an observational study that is assessing the associations between characteristics of community programs and policies and BMI, nutrition, and physical activity in children. The Healthy Communities Study was funded in 2010, field data collection and medical record abstraction will be completed in 2015, and data cleaning and analyses will be completed by mid-year 2016. One-hundred and thirty communities (defined as a high school catchment area) and approximately 5,000 children in kindergarten through eighth grade and their parents have been recruited from public elementary and middle schools across the country. The study is examining quantitative and qualitative information obtained from community-based initiatives; measures of community characteristics (e.g., school environment); and child and parent measures, including children's physical activity levels and dietary practices and children's and parents' BMI. The Healthy Communities Study employs a complex study design that includes a diverse sample of communities across the country and combines current/cross-sectional and retrospective data (abstracted from children's medical records). This paper describes the rationale for the Healthy Communities Study, the study aims and logic model, and a brief overview of the study design.

Statistical Design Features of the Healthy Communities Study.

The Healthy Communities Study is designed to assess relationships between characteristics of community programs and policies targeting childhood obesity and children's BMI, diet, and physical activity. The study involved a complex data collection protocol implemented over a 2-year period (2013-2015) across a diverse sample of 130 communities, defined as public high school catchment areas. The protocol involved baseline assessment within each community that included in-person or telephone interviews regarding community programs and policies and in-home collection of BMI, nutritional, and physical activity outcomes from a sample of up to 81 children enrolled in kindergarten through eighth grade in public schools. The protocol also involved medical record reviews to establish a longitudinal trajectory of BMI for an estimated 70% of participating children. Staged sampling was used to collect less detailed measures of physical activity and nutrition across the entire sample of children, with a subset assessed using more costly, burdensome, and detailed measures. Data from the Healthy Community Study will be analyzed using both cross-sectional and longitudinal models that account for the complex design and correct for measurement error and bias using a likelihood-based Markov-chain Monte Carlo methodology. This methods paper provides insights into the complex design features of the Healthy Communities Study and may serve as an example for future large-scale studies that assess the relationship between community-based programs and policies and health outcomes of community residents.

Operational Implementation of the Healthy Communities Study: How Communities Shape Children's Health.

The Healthy Communities Study (HCS) is examining how characteristics of community programs and policies targeting childhood obesity are related to childhood diet, physical activity, and obesity outcomes. The study involves selected districts and public schools in 130 communities; families recruited through schools; and data collected at the community, school, household, and child levels. Data collection took place in two waves-Wave 1 in Spring 2012 and Wave 2 from 2013 to 2015-with analysis to be completed by August 2016. This paper describes operational elements of the HCS, including recruitment activities, field operations, training of data collectors, human subjects protection, and quality assurance and quality control procedures. Experienced trainers oversaw and conducted all training, including training of (1) district and school recruitment staff; (2) telephone interviewers for household screening and recruitment; (3) field data collectors for conducting household data collection; and (4) community liaisons for conducting key informant interviews, document abstraction, and community observations. The study team developed quality assurance and quality control procedures that were implemented for all aspects of the study. Planning and operationalizing a study of this complexity and magnitude, with multiple functional teams, required frequent communication and strong collaboration among all study partners to ensure timely and effective decision making.

Independent evaluation of the California Tobacco Control Program: relationships between program exposure and outcomes, 1996-1998.

OBJECTIVES: This study sought to determine the effects of the California Tobacco Control Program on tobacco-related attitudes and behaviors. METHODS: In 1996 and 1998, a telephone survey was conducted among adults in randomly selected households in 18 California counties. Tenth-grade youths in 84 randomly selected high schools completed a written survey. In analyses conducted at the county level, differences in outcomes were regressed on an index of program exposure. RESULTS: Among adults, program exposure was associated with decreased smoking prevalence rates, increased no-smoking policies in homes, and decreased violations of workplace no-smoking policies. Among youths, there was no effect of program exposure on outcomes. CONCLUSIONS: These results suggest that the California Tobacco Control Program may have reduced adult smoking prevalence rates and exposure to environmental tobacco smoke.

Veteran identity and race/ethnicity: influences on VA outpatient care utilization.

BACKGROUND: "Veteran identity" is defined as veterans' self-concept that derives from his/her military experience within a sociohistorical context. Veteran identity may vary by race/ethnicity because the sociohistorical context of the military experience varies by race. OBJECTIVES: To explore veteran identity and how it varies by race/ethnicity, and to identify aspects of veteran identity that significantly influence preferences for, and use of, VA outpatient care. RESEARCH DESIGN: Focus groups were conducted at community sites to explore concepts related to veteran identity, race/ethnicity, military experience, and health services use. The focus groups informed the development of a telephone survey, which was administered to veterans of four racial/ethnic groups in Southern California and Southern Nevada. SUBJECTS: One hundred seventy-eight veterans participated in the focus groups, and 3,227 veterans completed the telephone survey. MEASURES: Dependent variables include: (1) preference for VA health services, (2) VA-only outpatient use, (3) Any VA outpatient use, and (4) number of outpatient visits within the previous 12 months. Independent variables include veteran identity, sociodemographic, and health-related characteristics. RESULTS: All veteran identity variables were significantly associated with race/ethnicity. Race/ethnicity, eg, being black or Hispanic, in addition to veteran identity factors, significantly influenced preferences for VA outpatient care. Veteran identity factors, however, had less influence on VA outpatient service utilization than socioeconomic factors. CONCLUSIONS: Minority veterans who highly identify with their veteran status may prefer the VA to other systems of care. Factors associated with veteran identity may be useful for incorporation into interventions to improve access to VA care.