Role transitions in emerging adulthood are associated with smoking among Hispanics in Southern California

Abstract

Introduction: Smoking initiation seldom occurs after emerging adulthood, making prevention critical during this phase of the life course. Among emerging adults, Hispanics have an especially high risk for cigarette use. Emerging adulthood scholars suggest role transitions commonly experienced by this age group may lead to substance use including cigarette experimentation and/or progression, contributing to the high smoking rates exhibited by Hispanics.

Methods: Hispanic emerging adults (aged 18-24) completed surveys indicating which of a comprehensive list of role transitions they had experienced in the past year. Separate logistic regression models explored the association between each individual role transition and smoking in the past 30 days, controlling for age and gender and using a Bonferonni correction.

Results: Among the sample of emerging adults (n = 1,390), 41% were male, the average age was 21, and about 21% reported cigarette use in the past 30 days. Losing a job, becoming a family member's caregiver, starting to date someone new, experiencing a breakup, being arrested, and becoming addicted to illicit drugs and/or alcohol were all associated with smoking.

Conclusions: The stress associated with navigating through changes in critical periods of the life course may lead some emerging adults to smoke. Future research should be directed toward determining what specific mechanisms make these transitional processes risk factors for smoking. These determinations could prove critical if effective prevention programs are to be designed that lead to a decrease in the smoking prevalence among Hispanic emerging adults.

Figure 1.

Transitions and smoking show the change in predicted probability of smoking in the past 30 days with 95% CIs. An overlapping CI with zero would have indicated a null result with alpha = .002. Estimates were calculated by simulating the first difference in the transition, for example, lost job changing from 0 to 1. Each estimate was arrived by the use of 1,000 randomly drawn sets of estimates from each respective coefficient covariance matrix with control variables held at their mean values.