Adolescent-to-young adulthood heavy drinking trajectories and their prospective predictors.

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ABSTRACT. Objective: The purpose of this three-wave longitudinal study was twofold. First, prevalence data on alcohol characteristics (e.g., drinks per day, heavy episodic drinking [HED]) were provided for a community sample of middle-aged adults. Aggregate (or group) and individual levels of stability of these characteristics across a 10-year interval were a major focus. Second, an actor-partner interdependence model (APIM) was used to test husbands' and wives' mutual infl uences on each other's alcohol use. Method: Prospective data were collected from the middle-aged parents of a cohort study that originally targeted adolescents. Three measurement occasions occurred at baseline, 5 years later, and an additional 5 years later. Data from 597 men and 847 women were used to derive prevalence data on alcohol use, and 489 intact marital dyads were used to test spouses' interdependence on alcohol use and HED in the APIMs. Results: The majority of men and women reported alcohol use at each measurement occasion, and the average number of drinks per day was highly similar across time, as was the percentage reporting HED. There was substantial stability at the individual level in the amount of alcohol consumed and HED between waves of measurement. Marital partners had signifi cant but modest effects on each other's alcohol use. Wives had a somewhat greater infl uence on their husbands' drinking than vice versa. Conclusions: The majority of middle-aged adults consumed alcohol at a low to moderate level. However, there is heterogeneity in alcohol use patterns, and a signifi cant minority reported at-risk levels of alcohol use and HED. (J. Stud. Alcohol Drugs, 75, 546-556, 2014)

Section: Participantsmentioning

confidence: 99%

A Prospective Study of Alcohol Use Among Middle-Aged Adults and Marital Partner Influences on Drinking

Windle

2014

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“…Rather, subgroups of alcohol users exist, including abstainers, moderate drinkers, and chronic heavy drinkers. However, most studies include limited, community-based samples of emerging adults, such as predominantly White, suburban youth (e.g., Windle et al, 2005). Even studies using the Monitoring the Future project (e.g., Schulenberg et al, 1996), which is a large, nationally representative sample, exclude youth who drop out of high school, who may be at highest risk for alcohol problems (Muthén and Muthén, 2000).…”

Section: Patterns Of Alcohol Use Among Emerging Adultsmentioning

confidence: 99%

Patterns of Alcohol Use and Related Consequences in Non-College-Attending Emerging Adults

Cleveland

Mallett

White

et al. 2013

ABSTRACT. Objective: Among emerging adults, those who do not attain postsecondary education are at highest risk for experiencing longterm problems related to alcohol use, including alcohol dependence. The purpose of the current study was to identify latent classes of alcohol users among non-college-attending youth and examine correlates of class membership. Method: Screening criteria were used to select emerging adults between ages 18 and 22 years with no postsecondary education (N = 264) from a prerecruited probability-based Web panel. Latent class analysis (LCA) was used to identify common patterns of alcohol use. Grouping variables and demographic variables were added to the LCA model, and rates of alcohol-related consequences across the LCA classes were compared. Results: Four classes of drinking patterns were identifi ed: (a) current nondrinkers (34%), (b) weekend light drinkers (38%), (c) weekend risky drinkers (23%), and (d) daily drinkers (5%). Class membership was associated with early onset of alcohol use (age 14 or younger), marital status, employment status, and urban residency (area populated by 50,000 or more people). The number of latent classes did not differ across sex and legal drinking age status, although proportions of subjects within classes varied by age. Weekend risky drinkers were most likely to report sickness and feelings of guilt because of drinking, whereas daily drinkers were most likely to report getting into fi ghts, driving a car after drinking, and missing work. Conclusions: Similar to college samples of emerging adults, most of this noncollege sample belonged to latent classes defi ned by rare or moderate alcohol use. Nevertheless, nearly a quarter of the sample reported high-risk drinking behaviors, and a small number reported drinking alcohol on a daily basis. Both of these classes were at elevated risk for experiencing a number of alcohol-related consequences. (J. Stud. Alcohol Drugs, 74, 84-93, 2013)

“…Stud. Alcohol Drugs 69: [866][867][868][869][870][871][872][873][874][875][876][877]2008) N UMEROUS STUDIES HAVE EXAMINED changes in volume and pattern of drinking over the life course, with most focusing on the heavy drinking trajectories from adolescence to early adulthood (Chassin et al, 2002;Hill et al, 2000;Oesterle et al, 2004;Schulenberg et al, 1996;Tucker et al, 2003;Windle et al, 2005). Within the developmental framework of this rich literature, numerous factors have discriminated among different drinking trajectories.…”

Section: Three-year Changes In Adult Risk Drinking Behavior Inmentioning

confidence: 99%

“…Virtually all studies have found male gender to be associated with higher baseline levels of heavy drinking and trajectories more indicative of increasing or continued heavy drinking. Other factors associated with change in drinking behavior over time have included baseline levels of alcohol and other substance use (Auerbach and Collins, 2006;Chassin et al, 2002;Hill et al, 2000;Sher and Rutledge, 2007;Windle et al, 2005); family history of alcoholism (Chassin et al, 2002(Chassin et al, , 2004Jackson et al, 2001;Timberlake et al, 2007); borderline personality disorder (PD) and/or behavioral undercontrol and impulsivity (Rohde et al, 2001;Rutledge and Sher, 2001); externalizing behavior, delinquency, conduct disorder, and antisocial PD (Bucholz et al, 2000;Chassin et al, 2002;Hill et al, 2000;Jackson and Sher, 2005;Tucker et al, 2003); and early initiation of drinking (Casswell et al, 2002;Goudriaan et al, 2007;Windle et al, 2005).…”

Section: Three-year Changes In Adult Risk Drinking Behavior Inmentioning

confidence: 99%

Three-Year Changes in Adult Risk Drinking Behavior in Relation to the Course of Alcohol-Use Disorders

Dawson

Stinson

Chou

et al. 2008

ABSTRACT. Objective: This study examines the associations between the course of alcohol-use disorder (AUD) and changes in average daily volume of ethanol intake, frequency of risk drinking, and maximum quantity of drinks consumed per day over a 3-year follow-up interval in a sample of U.S. adults. Method: Data were taken from a longitudinal study of a nationally representative sample of U.S. adults, who were 18 years of age and older (mean age = 46.4) when initially interviewed in 2001-2002 and successfully reinterviewed approximately 3 years later (n = 22,245 baseline drinkers). The time reference period for the drinking measures was the 12 months preceding the interview. Changes in consumption refl ect differences between Wave 1 and Wave 2 measures for individuals with nonmissing values at both Waves (n = 22,003 for volume of intake, 22,132 for frequency of risk drinking and 21,942 for maximum quantity of drinks). Results: There were positive changes in all consumption measures associated with developing an AUD and negative changes associated with remission of an AUD, even among individuals who continued to drink. Increases and decreases associated with onset and offset of dependence exceeded those associated with onset/offset of abuse only, and the decreases associated with full remission from dependence exceeded those associated with partial remission. There were few changes in consumption among individuals whose AUD status did not change. Interactions of AUD transitions with other factors indicate that development of an AUD is associated with a greater increase in consumption among men, possibly refl ecting their greater total body water and lower blood alcohol concentration in response to a given dose of ethanol, and among individuals with high baseline levels of consumption. Conclusions: Changes in consumption associated with onset and offset of AUD are substantial enough to have important implications for the risk of associated physical and psychological harm. (J. Stud. Alcohol Drugs 69: [866][867][868][869][870][871][872][873][874][875][876][877] 2008)