AIM: To test whether intrapersonal growth in e-cigarette advertising exposure over time is associated with growth in e-cigarette use and/or cigarette smoking. DESIGN: Longitudinal study using four waves of data were collected in 6-month intervals between 2018 and 2020. SETTING AND PARTICIPANTS: Participants were 2327 young adults recruited from colleges in Hawaii, USA. MEASUREMENTS: Data were collected on demographics, e-cigarette advertising exposure measured using the cued- recall method and recent (past 30-day) cigarette and e-cigarette use. FINDINGS: The average trajectory for e-cigarette advertising exposure over time was significant and upward [M slope = 0.18 (0.14-0.22), P < 0.0001]. However, average trajectories for e-cigarette [M slope = -0.08 (-0.18 to 0.02), P = 0.09] and cigarette [M slope = -0.14 (-0.30 to 0.02), P = 0.07] use were not. There were significant differences in individual level trajectories across participants for advertising exposure [σ2 = 0.12 (0.10-0.14), P < 0.0001], e-cigarette use [σ2 = 0.22 (0.14-0.30), and cigarette smoking (σ2 = 0.17 [0.09-0.25], P < 0.0001). Individuals with an increasing rate of advertising exposure showed an increasing rate of e-cigarette use [B = 0.63 (0.36-0.90), P < 0.0001). Neither initial level of, nor rate of change in, advertising exposure was significantly associated with cigarette smoking growth factors (P > 0.05). Higher initial level of e-cigarette use was associated with higher initial level of cigarette smoking [B = 0.89 (0.69-1.09), P < 0.0001] but decreased rate of cigarette smoking over time [B = -0.12 (-0.20 to -0.04) P = 0.003]. Rate of change in e-cigarette use was not associated with the rate of change in cigarette smoking (P > 0.05). CONCLUSIONS: Increased exposure to e-cigarette advertising appears to be associated with increased e-cigarette use but not with increased cigarette smoking. Higher initial level of e-cigarette use appears to be associated with higher initial level of cigarette smoking but may be associated with a decreasing rate of cigarette smoking over time.
AIM: To test whether intrapersonal growth in e-cigarette advertising exposure over time is associated with growth in e-cigarette use and/or cigarette smoking. DESIGN: Longitudinal study using four waves of data were collected in 6-month intervals between 2018 and 2020. SETTING AND PARTICIPANTS: Participants were 2327 young adults recruited from colleges in Hawaii, USA. MEASUREMENTS: Data were collected on demographics, e-cigarette advertising exposure measured using the cued- recall method and recent (past 30-day) cigarette and e-cigarette use. FINDINGS: The average trajectory for e-cigarette advertising exposure over time was significant and upward [M slope = 0.18 (0.14-0.22), P < 0.0001]. However, average trajectories for e-cigarette [M slope = -0.08 (-0.18 to 0.02), P = 0.09] and cigarette [M slope = -0.14 (-0.30 to 0.02), P = 0.07] use were not. There were significant differences in individual level trajectories across participants for advertising exposure [σ2 = 0.12 (0.10-0.14), P < 0.0001], e-cigarette use [σ2 = 0.22 (0.14-0.30), and cigarette smoking (σ2 = 0.17 [0.09-0.25], P < 0.0001). Individuals with an increasing rate of advertising exposure showed an increasing rate of e-cigarette use [B = 0.63 (0.36-0.90), P < 0.0001). Neither initial level of, nor rate of change in, advertising exposure was significantly associated with cigarette smoking growth factors (P > 0.05). Higher initial level of e-cigarette use was associated with higher initial level of cigarette smoking [B = 0.89 (0.69-1.09), P < 0.0001] but decreased rate of cigarette smoking over time [B = -0.12 (-0.20 to -0.04) P = 0.003]. Rate of change in e-cigarette use was not associated with the rate of change in cigarette smoking (P > 0.05). CONCLUSIONS: Increased exposure to e-cigarette advertising appears to be associated with increased e-cigarette use but not with increased cigarette smoking. Higher initial level of e-cigarette use appears to be associated with higher initial level of cigarette smoking but may be associated with a decreasing rate of cigarette smoking over time.
Authors: Erin L Sutfin; Beth A Reboussin; Beata Debinski; Kimberly G Wagoner; John Spangler; Mark Wolfson Journal: Am J Public Health Date: 2015-06-11 Impact factor: 9.308
Authors: Matthew C Farrelly; Jennifer C Duke; Erik C Crankshaw; Matthew E Eggers; Youn O Lee; James M Nonnemaker; Annice E Kim; Lauren Porter Journal: Am J Prev Med Date: 2015-07-07 Impact factor: 5.043
Authors: Gary C K Chan; Daniel Stjepanović; Carmen Lim; Tianze Sun; Aathavan Shanmuga Anandan; Jason P Connor; Coral Gartner; Wayne D Hall; Janni Leung Journal: Addiction Date: 2020-10-05 Impact factor: 6.526
Authors: Dale S Mantey; Maria R Cooper; Stephanie L Clendennen; Keryn E Pasch; Cheryl L Perry Journal: J Adolesc Health Date: 2016-04-12 Impact factor: 5.012
Authors: Samir Soneji; Jessica L Barrington-Trimis; Thomas A Wills; Adam M Leventhal; Jennifer B Unger; Laura A Gibson; JaeWon Yang; Brian A Primack; Judy A Andrews; Richard A Miech; Tory R Spindle; Danielle M Dick; Thomas Eissenberg; Robert C Hornik; Rui Dang; James D Sargent Journal: JAMA Pediatr Date: 2017-08-01 Impact factor: 16.193
Authors: Julia Cen Chen-Sankey; Jennifer B Unger; Maansi Bansal-Travers; Jeff Niederdeppe; Edward Bernat; Kelvin Choi Journal: Pediatrics Date: 2019-11 Impact factor: 7.124