Long-Term Outcomes From Repeated Smoking Cessation Assistance in Routine Primary Care.

PURPOSE: To test the association between repeated clinical smoking cessation support and long-term cessation. DESIGN: Retrospective, observational cohort study using structured and free-text data from electronic health records. SETTING: Six diverse health systems in the United States. PARTICIPANTS: Patients aged ≥18 years who were smokers in 2007 and had ≥1 primary care visit in each of the following 4 years (N = 33 691). MEASURES: Primary exposure was a composite categorical variable (comprised of documentation of smoking cessation medication, counseling, or referral) classifying the proportions of visits for which patients received any cessation assistance (<25% (reference), 25%-49%, 50%-74%, and ≥75% of visits). The dependent variable was long-term quit (LTQ; yes/no), defined as no indication of being a current smoker for ≥365 days following a visit where nonsmoker or former smoker was indicated. ANALYSIS: Mixed effects logistic regression analysis adjusted for age, sex, race, and comorbidities, with robust standard error estimation to account for within site correlation. RESULTS: Overall, 20% of the cohort achieved LTQ status. Patients with ≥75% of visits with any assistance had almost 3 times the odds of achieving LTQ status compared to those with <25% visits with assistance (odds ratio = 2.84; 95% confidence interval: 1.50-5.37). Results were similar for specific assistance types. CONCLUSIONS: These findings provide support for the importance of repeated assistance at primary care visits to increase long-term smoking cessation.

E-cigarette use and asthma in a multiethnic sample of adolescents.

There is minimal evidence from epidemiological studies on how e-cigarette use is related to health indices in adolescence. We hypothesized that e-cigarette use would be associated with asthma, controlling for demographics and cigarette smoking. The hypothesis was tested with cross-sectional data from a statewide sample of school students. Surveys were administered in classrooms in 2015 to adolescents in 33 high schools throughout the State of Hawaii. The sample (N=6089) was 50% female and mean age was 15.8years. Data were obtained on demographics; ever use and current (past 30days) use of e-cigarettes, combustible cigarettes, and marijuana; ever being diagnosed with asthma; and currently having asthma. Multinomial regression examined the association between e-cigarette use and asthma controlling for cigarette smoking, marijuana use, and six demographic covariates. Current e-cigarette use was associated with currently having (vs. never having) asthma (adjusted odds ratio [aOR]=1.48, CI 1.26-1.74) and with previously having (vs. never having) asthma (aOR=1.22, CI 1.07-1.40). This was independent of cigarette smoking, marijuana use, and other covariates. Smoking and marijuana were nonsignificant in the multivariate analysis. Blacks, Native Hawaiians, other Pacific Islanders, and Filipinos had higher rates of asthma compared with Asian Americans and Caucasians. We conclude that e-cigarette use by adolescents is independently associated with asthma. This finding is consistent with recent laboratory research on pulmonary effects from e-cigarette vapor. Implications for public health should be considered.

How is the effect of adolescent e-cigarette use on smoking onset mediated: A longitudinal analysis.

E-cigarette use by adolescents has been related to onset of cigarette smoking but there is little knowledge about the process(es) through which this occurs. Accordingly, we tested the role of cognitive and social factors for mediating the relation between e-cigarette use and smoking onset. A school-based survey was conducted with a baseline sample of 2,338 students in Hawaii (9th and 10th graders, mean age 14.7 years) who were surveyed in 2013 (Time 1, T1) and followed up 1 year later (Time 2, T2). We assessed e-cigarette use, cigarette smoking, demographic covariates, and 4 hypothesized mediators: smoking-related expectancies, prototypes, and peer affiliations as well as marijuana use. The primary structural modeling analysis, based on initial never-smokers, used an autoregressive model (entering T2 mediator values adjusted for T1 values) to test for mediational pathways in the relation between e-cigarette use at T1 and cigarette smoking status at T2. Results showed that e-cigarette use was related to all of the mediators. Tests of indirect effects indicated that changes in expectancies, affiliations, and marijuana use were significant pathways in the relation between e-cigarette use and smoking onset. A direct effect from e-cigarette use to smoking onset was nonsignificant. Findings were replicated across autoregressive and prospective models. We conclude that the relation between adolescent e-cigarette use and smoking onset is in part attributable to cognitive and social processes that follow from e-cigarette use. Further research is needed to understand the relative role of nicotine and psychosocial factors in smoking onset. (PsycINFO Database Record

E-cigarette use is differentially related to smoking onset among lower risk adolescents.

OBJECTIVE: E-cigarette use has been linked to onset of cigarette smoking among adolescents, but some commentators have suggested that this simply reflects high-risk adolescents being more likely to use e-cigarettes and to smoke. We tested whether the effect of e-cigarette use for smoking onset differs for youth who are lower versus higher on propensity to smoke. METHODS: School-based survey with a longitudinal sample of 1136 students (9th-11th graders, mean age 14.7 years) in Hawaii, initially surveyed in 2013 (T1) and followed up 1 year later (T2). We assessed e-cigarette use, propensity to smoke based on 3 psychosocial factors known to predict smoking (rebelliousness, parental support and willingness to smoke), and cigarette smoking status. Analyses based on T1 never-smokers tested the relation of T1 e-cigarette use to T2 smoking status for participants lower versus higher on T1 propensity to smoke. RESULTS: The relation between T1 e-cigarette use and T2 smoking onset was stronger among participants with lower levels of rebelliousness and willingness and higher levels of parental support. A multiple logistic regression analysis with T2 smoking as the criterion tested the cross-product of T1 e-cigarette use and T1 smoking propensity score; the interaction (OR=0.88, p=0.01) indicated a significantly larger effect for smoking onset among lower risk youth. CONCLUSIONS: The results indicate e-cigarette use is a risk factor for smoking onset, not just a marker of high risk for smoking. This study provides evidence that e-cigarettes are recruiting lower risk adolescents to smoking, which has public health implications.