Intersectionality in cigarette smoking cessation: A latent class analysis to predict 12-month cessation in a...

Currently, smoking cessation intervention research on marginalized populations focuses on a single attribute (e.g. race). However, these attributes intersect and research on this intersectionality has been rare. This study applied latent class analysis (LCA) to examine how multiple theory-driven baseline factors interact and predict 12-month 30-day point prevalence abstinence from cigarette smoking in 2415 adult participants in a digital smoking cessation intervention.

Theory-based analysis of a randomized trial with 12-month smoking cessation follow-up.

United States (US).

A total of 2415 adults who smoke that were recruited from all 50 US states and enrolled in the trial between May 2017 and September 2018.

In the parent RCT, participants were randomized to receive iCanQuit, an Acceptance and Commitment Therapy-based smartphone smoking cessation app (n = 1214) or QuitGuide, a US Clinical Practice Guidelines-based smoking cessation app (n = 1201) for 12 months.

Guided by Sheffer et al.,six theory-based factors were examined, including social identities: gender, race and ethnicity, marital status, sexual and gender minority (SGM) identity and socio-economic status (SES; education, income, employment); and lived experiences: positive screen for experiencing depression symptoms. Social identity and lived experiences data were collected via baseline questionnaires. The primary smoking cessation outcome was self-reported complete-case 30-day point prevalence abstinence at 12 months. SAS PROC LCA was used to identify classes based on the six selected factors and to predict 12-month smoking cessation.

A 4-class model showed the best goodness-of-fit statistics and interpretability. Participants in class 1 (n = 352, 14.6%) were more likely to be women, individuals of Black race and those with single marital status. Participants in class 2 (n = 322, 13.3%) were more likely to be men, SGM individuals and socioeconomically advantaged, as indicated by higher education, higher income or employment. Participants in class 3 (n = 368, 15.2%) were socioeconomically disadvantaged and screened positive for experiencing depression symptoms at baseline (CES-D $\ge$ 16). Finally, participants in class 4 (n = 1373, 56.9%) were more likely to be women, individuals of White race and married. Class 2 had the highest smoking cessation rate (32.8%) at 12 months, followed by class 1 (27.3%), class 4 (24.2%) and class 3 (15.4%). Compared with class 2, class 3 had 63% lower odds of quitting smoking (odds ratio = 0.37; 95% confidence interval = 0.20-0.71, P = 0.016).

People with both socioeconomic disadvantage and symptoms of depression appear to have a harder time quitting smoking than other people who try to quit.