Christina Marel1, Matthew Sunderland2, Katherine L Mills2, Tim Slade2, Maree Teesson2, Cath Chapman2. 1. National Drug and Alcohol Research Centre, University of New South Wales, NSW 2052, Sydney, Australia; NHMRC Centre of Research Excellence in Mental Health and Substance Use, University of New South Wales, NSW 2052, Sydney, Australia. Electronic address: c.marel@unsw.edu.au. 2. National Drug and Alcohol Research Centre, University of New South Wales, NSW 2052, Sydney, Australia; NHMRC Centre of Research Excellence in Mental Health and Substance Use, University of New South Wales, NSW 2052, Sydney, Australia.
Abstract
BACKGROUND: Relatively little is known about factors that may lead to the development of a substance use disorder (SUD), across a range of drug classes. This study aimed to identify factors that predict the likelihood of transition from use to SUD and the speed with which this may occur at the population level, with a focus on the impact of pre-existing mental disorders. METHODS: Data were collected as part of the 2007 Australian National Survey of Mental Health and Wellbeing, a nationally representative survey of 8841 Australian adults. A series of discrete time survival analyses were undertaken on data pertaining to the age of onset of use and symptoms of use disorder, for alcohol, cannabis, sedatives, stimulants, and opioids, as well as the impact of pre-existing mood and anxiety disorders on the likelihood of developing a SUD. RESULTS: Lifetime cumulative probability estimates indicated that 50.4% of stimulant, 46.6% of opioid, 39% of sedative, 37.5% of alcohol, and 34.1% of cannabis users would develop a SUD on those substances, within an estimated 14, 12, 8, 30, and 23 years after onset respectively. Pre-existing mental disorders were significantly associated with increased risk of developing a SUD for alcohol, cannabis and stimulant use disorder. CONCLUSION: The relative speed associated with the transition from use to SUD emphasizes the narrow window of time available to intervene, underscoring the urgency of early identification of mental health conditions and the timely provision of appropriate evidence-based interventions, which could potentially prevent the development of secondary SUDs.
BACKGROUND: Relatively little is known about factors that may lead to the development of a substance use disorder (SUD), across a range of drug classes. This study aimed to identify factors that predict the likelihood of transition from use to SUD and the speed with which this may occur at the population level, with a focus on the impact of pre-existing mental disorders. METHODS: Data were collected as part of the 2007 Australian National Survey of Mental Health and Wellbeing, a nationally representative survey of 8841 Australian adults. A series of discrete time survival analyses were undertaken on data pertaining to the age of onset of use and symptoms of use disorder, for alcohol, cannabis, sedatives, stimulants, and opioids, as well as the impact of pre-existing mood and anxiety disorders on the likelihood of developing a SUD. RESULTS: Lifetime cumulative probability estimates indicated that 50.4% of stimulant, 46.6% of opioid, 39% of sedative, 37.5% of alcohol, and 34.1% of cannabis users would develop a SUD on those substances, within an estimated 14, 12, 8, 30, and 23 years after onset respectively. Pre-existing mental disorders were significantly associated with increased risk of developing a SUD for alcohol, cannabis and stimulant use disorder. CONCLUSION: The relative speed associated with the transition from use to SUD emphasizes the narrow window of time available to intervene, underscoring the urgency of early identification of mental health conditions and the timely provision of appropriate evidence-based interventions, which could potentially prevent the development of secondary SUDs.
Authors: Jennifer E Lansford; Natalie Goulter; Jennifer Godwin; Max Crowley; Robert J McMahon; John E Bates; Gregory S Pettit; Mark Greenberg; John E Lochman; Kenneth A Dodge Journal: Addict Behav Date: 2021-04-20 Impact factor: 4.591
Authors: Christina Marel; Katherine Mills; Rachel Visontay; Jack Wilson; Shane Darke; Joanne Ross; Tim Slade; Paul S Haber; Katherine Haasnoot; Madeleine Keaveny; Chris Tremonti; Maree Teesson Journal: BMJ Open Date: 2020-07-12 Impact factor: 2.692
Authors: Charles M Cleland; Marya Gwadz; Linda M Collins; Leo Wilton; Dawa Sherpa; Caroline Dorsen; Noelle R Leonard; Sabrina R Cluesman; Belkis Y Martinez; Amanda S Ritchie; Mariam Ayvazyan Journal: AIDS Behav Date: 2021-03-08