OBJECTIVE: Although it has been recognized that the course of alcoholism may differ across individuals, little work has characterized drinking trajectories from drinking onset to midlife. METHOD: The current study examined trajectories of alcohol dependence from adolescence to the mid-50s in a sample of 420 men with a lifetime diagnosis of alcohol dependence. Men from the Vietnam Era Twin Registry were given the Lifetime Drinking History, which assesses the patterns of alcohol consumption and diagnostic symptoms for self-defined drinking phases. Phase data were converted into person-year data, with alcohol-dependence diagnosis coded as present or absent for each of 13 age groupings, starting with up to age 20 and ending with ages 54-56. RESULTS: Latent growth mixture modeling was used to define four drinking trajectories: young-adult, late-onset, severe-nonchronic, and severe-chronic alcoholics. Further analyses with other diagnostic variables, other drinking variables, alcohol expectancies, personality scales, and religiousness scores were completed to differentiate men best categorized by each trajectory. CONCLUSIONS: Extension of Latent Growth Mixture Modeling (LGMM) into the mid-50s revealed that, although some individuals remain chronic alcohol users, others decline in alcohol problem use. Differences seen among these groups may help in the treatment of alcohol dependence, such that more energy can be spent treating those likely to be in the more severe trajectories.
OBJECTIVE: Although it has been recognized that the course of alcoholism may differ across individuals, little work has characterized drinking trajectories from drinking onset to midlife. METHOD: The current study examined trajectories of alcohol dependence from adolescence to the mid-50s in a sample of 420 men with a lifetime diagnosis of alcohol dependence. Men from the Vietnam Era Twin Registry were given the Lifetime Drinking History, which assesses the patterns of alcohol consumption and diagnostic symptoms for self-defined drinking phases. Phase data were converted into person-year data, with alcohol-dependence diagnosis coded as present or absent for each of 13 age groupings, starting with up to age 20 and ending with ages 54-56. RESULTS: Latent growth mixture modeling was used to define four drinking trajectories: young-adult, late-onset, severe-nonchronic, and severe-chronic alcoholics. Further analyses with other diagnostic variables, other drinking variables, alcohol expectancies, personality scales, and religiousness scores were completed to differentiate men best categorized by each trajectory. CONCLUSIONS: Extension of Latent Growth Mixture Modeling (LGMM) into the mid-50s revealed that, although some individuals remain chronic alcohol users, others decline in alcohol problem use. Differences seen among these groups may help in the treatment of alcohol dependence, such that more energy can be spent treating those likely to be in the more severe trajectories.
Authors: Kenneth S Kendler; Xiao-Qing Liu; Charles O Gardner; Michael E McCullough; David Larson; Carol A Prescott Journal: Am J Psychiatry Date: 2003-03 Impact factor: 18.112
Authors: Theodore Jacob; Brian Waterman; Andrew Heath; William True; Kathleen K Bucholz; Randy Haber; Jeff Scherrer; Qiang Fu Journal: Arch Gen Psychiatry Date: 2003-12
Authors: Jeffrey F Scherrer; Brian M Waterman; Andrew C Heath; Kathleen K Bucholz; William R True; Theodore Jacob Journal: J Stud Alcohol Date: 2004-01
Authors: Richard F Farmer; John R Seeley; Derek B Kosty; Jeff M Gau; Susan C Duncan; Kenneth J Sher; Peter M Lewinsohn Journal: J Stud Alcohol Drugs Date: 2017-03 Impact factor: 2.582
Authors: Marc A Schuckit; Tom L Smith; George Danko; Robert Anthenelli; Lara Schoen; Mari Kawamura; John Kramer; Danielle M Dick; Zoe Neale; Samuel Kuperman; Vivia McCutcheon; Andrey P Anokhin; Victor Hesselbrock; Michie Hesselbrock; Kathleen Bucholz Journal: Alcohol Clin Exp Res Date: 2017-05-24 Impact factor: 3.455
Authors: Jungeun Olivia Lee; Karl G Hill; Katarina Guttmannova; Lacey A Hartigan; Richard F Catalano; J David Hawkins Journal: J Stud Alcohol Drugs Date: 2014-07 Impact factor: 2.582
Authors: Jon Randolph Haber; Julia D Grant; Carolyn E Sartor; Laura B Koenig; Andrew Heath; Theodore Jacob Journal: Psychol Addict Behav Date: 2013-03-25