Discrete time measures versus trajectories of drinking frequency across adolescence as predictors of binge drinking in young adulthood: a longitudinal investigation
Objectives We compared discrete time measures with trajectories of adolescent drinking frequency as predictors of sustained binge drinking in young adulthood.Design Prospective longitudinal study.Setting 10 high schools in Montréal, Canada.Participants 1293 high-school students followed from mean (S...
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2020-09-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/10/9/e035939.full |
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| author | Marie-Pierre Sylvestre Robert J Wellman Marilyn N Ahun Geetanjali Datta Didier Jutras-Aswad Jennifer O Loughlin |
| author_facet | Marie-Pierre Sylvestre Robert J Wellman Marilyn N Ahun Geetanjali Datta Didier Jutras-Aswad Jennifer O Loughlin |
| author_sort | Marie-Pierre Sylvestre |
| collection | DOAJ |
| description | Objectives We compared discrete time measures with trajectories of adolescent drinking frequency as predictors of sustained binge drinking in young adulthood.Design Prospective longitudinal study.Setting 10 high schools in Montréal, Canada.Participants 1293 high-school students followed from mean (SD) age 12 (0.6) to 24 (0.7) years.Primary outcome measures Patterns of drinking frequency (self-reports every 3 months from ages 12 to 17) identified using group-based trajectory modelling. Sustained binge drinking was defined as binging monthly or more often at both ages 20 and 24.Analyses Using logistic regression, sustained binge drinking was regressed on trajectory group membership and on four discrete time measures (frequency of drinking at age 12; frequency of drinking at age 17; age at drinking onset; age at onset of drinking monthly or more often).Results We identified seven drinking trajectories: late triers (15.2%), decreasers (9.5%), late escalators (10.4%), early slow escalators (16.5%), steady drinkers (14.4%), early rapid escalators (15.8%) and early frequent drinkers (18.2%). Sustained binge drinking was reported by 260 of 787 participants (33.0%) with complete data at both ages 20 and 24. Decreasers did not differ from late triers; all other patterns were associated with higher odds of sustained binge drinking (adjusted ORs: AORs=1.4–17.0). All discrete time measures were associated with sustained binge drinking, notably frequency at age 12 (a bit to try and drinking monthly: (AORs=2.6 (1.7; 3.9) and 2.8 (1.3; 6.1), respectively), age of drinking onset <13 years (AOR=7.6 (3.0; 24.1)), and any age of onset of drinking monthly or more often (AORs=5.1–8.2).Conclusion Youth at risk of sustained binge drinking as young adults can be identified with indicators of early drinking as early as 7th grade (aged 12–13 years). Identification of easy-to-obtain indicators can facilitate screening and intervention efforts. |
| format | Article |
| id | doaj-art-6d30f730cc0c4fe4b6ada11fa6918f12 |
| institution | Kabale University |
| issn | 2044-6055 |
| language | English |
| publishDate | 2020-09-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open |
| spelling | doaj-art-6d30f730cc0c4fe4b6ada11fa6918f122025-01-08T08:30:09ZengBMJ Publishing GroupBMJ Open2044-60552020-09-0110910.1136/bmjopen-2019-035939Discrete time measures versus trajectories of drinking frequency across adolescence as predictors of binge drinking in young adulthood: a longitudinal investigationMarie-Pierre Sylvestre0Robert J Wellman1Marilyn N Ahun2Geetanjali Datta3Didier Jutras-Aswad4Jennifer O Loughlin5Department of Social and Preventive Medicine, Université de Montréal, Montreal, Quebec, CanadaDepartment of Population and Quantitative Health Sciences, Division of Preventive and Behavioral Medicine, University of Massachusetts Medical School, Worcester, Massachusetts, USADepartment of Global Health and Population, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USASchool of Public Health, Université de Montréal, Montreal, Québec, Canada4 Department of Psychiatry and Addiction, Université de Montréal, Montreal, Quebec, CanadaSchool of Public Health, Université de Montréal, Montreal, Québec, CanadaObjectives We compared discrete time measures with trajectories of adolescent drinking frequency as predictors of sustained binge drinking in young adulthood.Design Prospective longitudinal study.Setting 10 high schools in Montréal, Canada.Participants 1293 high-school students followed from mean (SD) age 12 (0.6) to 24 (0.7) years.Primary outcome measures Patterns of drinking frequency (self-reports every 3 months from ages 12 to 17) identified using group-based trajectory modelling. Sustained binge drinking was defined as binging monthly or more often at both ages 20 and 24.Analyses Using logistic regression, sustained binge drinking was regressed on trajectory group membership and on four discrete time measures (frequency of drinking at age 12; frequency of drinking at age 17; age at drinking onset; age at onset of drinking monthly or more often).Results We identified seven drinking trajectories: late triers (15.2%), decreasers (9.5%), late escalators (10.4%), early slow escalators (16.5%), steady drinkers (14.4%), early rapid escalators (15.8%) and early frequent drinkers (18.2%). Sustained binge drinking was reported by 260 of 787 participants (33.0%) with complete data at both ages 20 and 24. Decreasers did not differ from late triers; all other patterns were associated with higher odds of sustained binge drinking (adjusted ORs: AORs=1.4–17.0). All discrete time measures were associated with sustained binge drinking, notably frequency at age 12 (a bit to try and drinking monthly: (AORs=2.6 (1.7; 3.9) and 2.8 (1.3; 6.1), respectively), age of drinking onset <13 years (AOR=7.6 (3.0; 24.1)), and any age of onset of drinking monthly or more often (AORs=5.1–8.2).Conclusion Youth at risk of sustained binge drinking as young adults can be identified with indicators of early drinking as early as 7th grade (aged 12–13 years). Identification of easy-to-obtain indicators can facilitate screening and intervention efforts.https://bmjopen.bmj.com/content/10/9/e035939.full |
| spellingShingle | Marie-Pierre Sylvestre Robert J Wellman Marilyn N Ahun Geetanjali Datta Didier Jutras-Aswad Jennifer O Loughlin Discrete time measures versus trajectories of drinking frequency across adolescence as predictors of binge drinking in young adulthood: a longitudinal investigation BMJ Open |
| title | Discrete time measures versus trajectories of drinking frequency across adolescence as predictors of binge drinking in young adulthood: a longitudinal investigation |
| title_full | Discrete time measures versus trajectories of drinking frequency across adolescence as predictors of binge drinking in young adulthood: a longitudinal investigation |
| title_fullStr | Discrete time measures versus trajectories of drinking frequency across adolescence as predictors of binge drinking in young adulthood: a longitudinal investigation |
| title_full_unstemmed | Discrete time measures versus trajectories of drinking frequency across adolescence as predictors of binge drinking in young adulthood: a longitudinal investigation |
| title_short | Discrete time measures versus trajectories of drinking frequency across adolescence as predictors of binge drinking in young adulthood: a longitudinal investigation |
| title_sort | discrete time measures versus trajectories of drinking frequency across adolescence as predictors of binge drinking in young adulthood a longitudinal investigation |
| url | https://bmjopen.bmj.com/content/10/9/e035939.full |
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