Woo, Juhee (2018). Racial/ethnic differences in smoking trajectories from adolescence to mid-adulthood. 2018 Add Health Users Conference.
Cigarette smoking remains the leading cause of death in the United States, and racial/ethnic disparities in smoking exist. Studies find different smoking trajectories for different racial/ethnic groups, with later initiation of smoking among blacks and greater smoking cessation among whites at older ages. This study uses the most recent nationally representative data to follow U.S. adolescents for a longer period of time. Using the Add Health data (Waves I to V) and growth-curve modeling, I examine regular smoking trajectories for different racial/ethnic groups (whites, blacks, Hispanics), segregated by gender, from adolescence to mid-adulthood and identify variables that partly account for the racial/ethnic differences in smoking trajectories. Preliminary findings (descriptive statistics) suggest that while the smoking rates of whites and Hispanics increase until Wave III (ages 18 to 28) and declines thereafter, the smoking rates of blacks increase until Wave IV (ages 24 to 34) and persist (among males) or continue to rise (among females) at Wave V (ages 33 to 42). Respondents' demographic variables (e.g. age, gender, and nativity) as well as ascribed characteristics (parents' SES, parents' smoking status, and cigarette accessibility at home) are included as controls. Achieved characteristics, such as respondents' SES (personal earnings and education attainment), other substance use (alcohol, marijuana, other tobacco product), depression, and living arrangement (living with parents, spouse, or children) are used as mediators. I also explore whether the effect of achieved characteristics on smoking varies across different racial/ethnic groups, using interaction terms. I expect both ascribed and achieved characteristics will mediate the racial/ethnic differences in smoking trajectories (growth-curve analysis results will be ready later on). Findings from this study will help to determine which subpopulations in terms of race/ethnicity, gender, and age group should be targeted for public health interventions.
2018 Add Health Users Conference
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