Federico E Vaca1, Kaigang Li1,2,3, Denise Haynie4, Xiang Gao2, Deepa R Camenga1, James Dziura1, Barbara Banz1, Leslie Curry5, Linda Mayes6, Niyousha Hosseinichimeh7, Rod MacDonald8, Ronald J Iannotti9, Bruce Simons-Morton4. 1. Department of Emergency Medicine, Developmental Neurocognitive Driving Simulation Research Center (DrivSim Lab), Yale University School of Medicine, New Haven, Connecticut. 2. Department of Health & Exercise Science, Colorado State University, Fort Collins, Colorado. 3. Colorado School of Public Health, Fort Collins, Colorado. 4. Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, Bethesda, Maryland. 5. Department of Health Policy & Management, Yale School of Public Health, New Haven, Connecticut. 6. Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut. 7. Department of Industrial and Systems Engineering, Virginia Tech, Blacksburg, Virginia. 8. School of Integrated Sciences, James Madison University, Harrisonburg, Virginia. 9. The CDM Group, Inc., Bethesda, Maryland.
Abstract
PURPOSE: The purpose of this study was to identify and characterize trajectory classes of adolescents who ride with an impaired driver (RWI) and drive while impaired (DWI). METHODS: We analyzed all 7 annual assessments (Waves W1-W7) of the NEXT Generation Health Study, a nationally representative longitudinal study starting with 10th grade (2009-2010 school year). Using all 7 waves, latent class analysis was used to identify trajectory classes with dichotomized RWI (last 12 months) and DWI (last 30 days; once or more = 1 vs. none = 0). Covariates were race/ethnicity, sex, parent education, urbanicity, and family affluence. RESULTS: Four RWI trajectories and 4 DWI trajectories were identified: abstainer, escalator, decliner, and persister. For RWI and DWI trajectories respectively, 45.0% (n = 647) and 76.2% (n = 1,657) were abstainers, 15.6% (n = 226) and 14.2% (n = 337) were escalators, 25.0% (n = 352) and 5.4% (n = 99) were decliners, and 14.4% (n = 197) and 3.8% (n = 83) persisters. Race/ethnicity (χ2 = 23.93, P = .004) was significantly associated with the RWI trajectory classes. Race/ethnicity (χ2 = 20.55, P = .02), sex (χ2 = 13.89, P = .003), parent highest education (χ2 = 12.49, P = .05), urbanicity (χ2 = 9.66, P = .02), and family affluence (χ2 = 12.88, P = .05) were significantly associated with DWI trajectory classes. CONCLUSIONS: Among adolescents transitioning into emerging adulthood, race/ethnicity is a common factor associated with RWI and DWI longitudinal trajectories. Our results suggest that adolescent RWI and DWI are complex behaviors warranting further detailed investigation of the respective trajectory classes. Our study findings can inform the tailoring of prevention and intervention efforts aimed at preventing illness/injury and preserving future opportunities for adolescents to thrive in emerging adulthood.
PURPOSE: The purpose of this study was to identify and characterize trajectory classes of adolescents who ride with an impaired driver (RWI) and drive while impaired (DWI). METHODS: We analyzed all 7 annual assessments (Waves W1-W7) of the NEXT Generation Health Study, a nationally representative longitudinal study starting with 10th grade (2009-2010 school year). Using all 7 waves, latent class analysis was used to identify trajectory classes with dichotomized RWI (last 12 months) and DWI (last 30 days; once or more = 1 vs. none = 0). Covariates were race/ethnicity, sex, parent education, urbanicity, and family affluence. RESULTS: Four RWI trajectories and 4 DWI trajectories were identified: abstainer, escalator, decliner, and persister. For RWI and DWI trajectories respectively, 45.0% (n = 647) and 76.2% (n = 1,657) were abstainers, 15.6% (n = 226) and 14.2% (n = 337) were escalators, 25.0% (n = 352) and 5.4% (n = 99) were decliners, and 14.4% (n = 197) and 3.8% (n = 83) persisters. Race/ethnicity (χ2 = 23.93, P = .004) was significantly associated with the RWI trajectory classes. Race/ethnicity (χ2 = 20.55, P = .02), sex (χ2 = 13.89, P = .003), parent highest education (χ2 = 12.49, P = .05), urbanicity (χ2 = 9.66, P = .02), and family affluence (χ2 = 12.88, P = .05) were significantly associated with DWI trajectory classes. CONCLUSIONS: Among adolescents transitioning into emerging adulthood, race/ethnicity is a common factor associated with RWI and DWI longitudinal trajectories. Our results suggest that adolescent RWI and DWI are complex behaviors warranting further detailed investigation of the respective trajectory classes. Our study findings can inform the tailoring of prevention and intervention efforts aimed at preventing illness/injury and preserving future opportunities for adolescents to thrive in emerging adulthood.
Entities:
Keywords:
Driving while impaired; riding with an impaired driver; trajectory classes; young drivers
Authors: Niyousha Hosseinichimeh; Rod MacDonald; Kaigang Li; James C Fell; Denise L Haynie; Bruce Simons-Morton; Barbara C Banz; Deepa R Camenga; Ronald J Iannotti; Leslie A Curry; James Dziura; Linda C Mayes; David F Andersen; Federico E Vaca Journal: Soc Sci Med Date: 2022-01-19 Impact factor: 4.634
Authors: Federico E Vaca; Kaigang Li; Denise L Haynie; Xiang Gao; Deepa R Camenga; James Dziura; Barbara C Banz; Leslie A Curry; Linda Mayes; Niyousha Hosseinichimeh; Rod MacDonald; Ronald J Iannotti; Bruce Simons-Morton Journal: J Transp Health Date: 2022-01-03