Suchergebnisse

INTRODUCTION: The use of electronic vapor products (EVPs) among youth has increased significantly in recent years, yet little is known about factors associated with initiation of EVPs during early adolescence. The purpose of this study was to explore the relationship between chronic exposure to adverse childhood experiences (ACEs) and early initiation of EVPs in a representative sample of middle school students. METHODS: 5,464 students from 113 middle schools (grades 6–8) completed the Nevada Youth Risk Behavior Survey (YRBS) in the spring of 2017. Six abuse and household dysfunction measures were used to calculate a cumulative ACE score (range 0–6). Initiation of EVPs (e-cigarettes, e-cigars, e-pipes, vape pipes, vaping pens, e-hookahs, and hookah pens) before age 11 was considered early initiation. Weighted logistic regression was used to assess the relationship between cumulative ACE exposure and early initiation of EVPs after controlling for sex, age, race/ethnicity, rurality, free or reduced lunch status, and military family involvement. RESULTS: Nearly 1 in 5 middle school students (18.6%) reported using EVPs, 6.7% had used EVPs during the past 30 days, and 5.1% started using EVPs before age 11. After controlling for sociodemographics, a strong graded relationship between cumulative ACE exposure and early initiation of EVPs was observed: 1 ACE (AOR = 1.60; 95% CI = 0.99–2.59), 2 ACEs (AOR = 2.29; 95% CI = 1.33–3.93), and 3–6 ACEs (AOR = 3.43, 95% CI = 2.20–5.36) compared to no ACEs. CONCLUSIONS: Screening for ACEs in school-based settings may be a feasible approach for identifying students who may be at-risk for early initiation of EVPs.

Purpose: Substantial research has demonstrated that assets (eg, family communication, school connectedness) protect youth from participation in numerous risk behaviors. However, very few studies have explored the relationship between assets and positive health behaviors. This study investigated prospective associations among assets and physical activity (PA) and body mass index (BMI). Design: Longitudinal design with 5 waves of data collected annually over a 4-year period. Setting: Community-based setting with participants recruited via door-to-door canvasing of homes located in stratified (by race and income) randomly selected census tracts and blocks. Participants: Participants were 1111 youth (baseline mean age = 14.3 years [SD = 1.6]; 53% female; 40.6% white, 28.6% Hispanic, 24.4% black, 6.4% other) and their parents. Measures: Weekly participation in PA, BMI, and 14 youth assets representing multiple levels of influence (individual, family, and community). Analysis: Generalized linear mixed models assessed associations among the assets and PA and BMI over the 5 waves of data. Results: There was a significant and graded relationship between assets and weekly participation in PA. For example, at the community-asset level, PA minutes were higher among youth with 2 assets ( P = .006), 3 assets ( P = .0006), and 4 to 5 assets ( P < .0001) compared to youth with 0 to 1 assets. No effects were found for BMI. Conclusion: Asset-based health promotion programs for youth may promote positive health behaviors and prevent participation in risk behaviors.

Purpose: The study's purpose was to improve the psychometric properties of the Youth Asset Survey (YAS). Design: Longitudinal cohort study with youth and parents recruited via door-to-door canvassing to participate in a 5-wave, 4-year study that assessed prospective associations among youth assets and youth health-related behaviors. Additional test items were added in the last 2 waves of a study to improve the YAS. Setting: Households in randomly selected census tracts located in the Oklahoma City metropolitan area. Participants: Youth and their parents (N = 1111 parent/child dyads). Youth demographic characteristics at wave 4 were mean age = 17.3 (standard deviation = 1.62) years; 53% female, 41% white, 28% Hispanic, 24% African American, and 6% other. Measures: Sixty-eight items assessing 17 youth asset constructs and 8 single items assessing youth risk behaviors. Analysis: Confirmatory factor analysis and generalized linear models were conducted to assess construct reliability and predictive validity, respectively. Results: Cronbach α for the revised asset constructs ranged from .72 to .82, predictive validity was strong, and all revised asset constructs were assessed via 4 items. Conclusions: Researchers and practitioners have an improved 68-item YAS-Revised, freely available for their use, which measures 17 youth assets with good reliability, validity, and functionality.