One Drink to a Lifetime of Drinking: Temporal Structures of Drinking Patterns (original) (raw)
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Individual patterns of alcohol use
Addictive Behaviors, 2014
Individual alcohol use trajectories were analyzed from time series of daily reports. • A novel methodology was developed to identify statistically distinct use patterns. • Patterns were classified into mutually exclusive categories. • Patterns were used to monitor transitions between recreational and problem use.
Addictive Behaviors, 1995
Steady (daily, continuous) versus nonsteady (binge, episodic, bout, intermittent) drinking pattern have been influential Jellinek's (1960) formulation of delta and gamma drinkers, and are used as variables in various typological systems and drinker profiles. However, definitions of drinking patterns vary widely across studies, and most studies rely on one self-report item to establish a subject's pattern. To systematize and empirically test drinking-pattern schemas, we developed detailed definitions of binge, episodic, sporadic, and steady drinking patterns. A computer algorithm was written in SAS to classify 94 male alcoholics participating in outpatient conjoint therapy, using 6-month pretreatment drinking data from the Timeline Followback Interview. The final classification was: 3 (3%) binge, 33 (35%) episodic, 12 (13%) sporadic, and 40 (43%) steady drinkers. Six (6%) were unclassifiable (due to too few drinking days or too many interruptions to the pattern) by the computer. Episodic, sporadic, and steady drinkers did not differ in demographics, alcohol-related consequences, global psychological distress. or marital satisfaction. Steady drinking was associated with later onset of drinking problems (>25), while episodic and sporadic drinking were associated with earlier onset. These results are contrary to current use of "binge drinking" as a variable associated with Type 1 alcoholism. Predictive validity analyses indicated that steady drinkers continued to drink more frequently than episodic and sporadic drinkers during treatment and 6 months posttreatment. Also, preliminary data indicate that pretreatment drinking pattern may be predictive of similar within-treatment urge-to-drink patterns. Implications for research and treatment are discussed.
Addiction, 2009
Aims This paper examines the relationship between frequency of drinking, usual daily consumption and frequency of binge drinking, taking into consideration possible age and gender differences. Participants and design Subjects were 10 466 current drinkers (5743 women and 4723 men) aged between 18 and 76 years, who participated in the GENACIS Canada (GENder Alcohol and Culture: an International Study) study. Setting Canada. Measurements The independent variable was the annual drinking frequency. The dependent variables were the usual daily quantity consumed, annual, monthly and weekly frequency of binge drinking (five drinks or more on one occasion). Findings Logistic regressions show (i) that those who drink less than once a week are less likely than weekly drinkers to take more than two drinks when they do drink; (ii) that the usual daily quantity consumed by weekly drinkers is not related to their frequency of drinking; but that (iii) the risk and frequency of binge drinking increase with the frequency of drinking. Conclusions Given that risk and frequency of binge drinking among Canadians increases with their frequency of drinking, any public recommendation to drink moderately should be made with great caution.
Relations among alcohol consumption measures derived from the Cognitive Lifetime Drinking History
Drug and Alcohol Review, 1998
Few studies have been conducted of chronic alcohol effects on health and social outcomes. To evaluate the utility and feasibility of such studies, correlations between lifetime and current measures of total alcohol consumption (ounces) and times intoxicated were examined to determine whether these dimensions of drinking are distinct. Studies were conducted in 2142 respondents ages 35 to 70 selected from lists of licensed drivers and individuals eligible for Medicare. Lifetime measures of alcohol consumption and times intoxicated were derived from the Cognitive Lifetime Drinking History (CLDH). Depending on age and sex of the subgroups examined, current consumption accounted for only about 10-25% of the variability in lifetime alcohol consumption; current and lifetime times intoxicated were even less highly correlated. Lifetime and current measures of alcohol consumption accounted for approximately 40-50% of the variability in corresponding lifetime and current measures of times intoxicated in younger cohorts, but this fell to 25% and less in older cohorts. These findings support the use of lifetime measures of alcohol consumption and times intoxicated based on the CLDH together with current measures to investigate chronic and acute alcohol effects on health and social outcomes. [Russell M, Peirce RS, Vana JE, Nochajski TH, Carosella AM, Muti P, Freudenheim J, Trevisan M. Relations among alcohol consumption measures derived from the Cognitive Lifetime Drinking History. Drug Alcohol Rev 1998;17:377-387]
A Comparison of Methods for Estimating Change in Drinking following Alcohol Treatment
Alcoholism: Clinical and Experimental Research, 2010
Background-The ultimate goal of alcohol treatment research is to develop interventions that help individuals reduce their alcohol use. To determine whether a treatment is effective researchers must then evaluate whether a particular treatment affects changes in drinking behavior after treatment. Importantly, drinking following treatment tends to be highly variable between individuals and within individuals across time. Method-Using data from the COMBINE study (COMBINE Study Research Group, 2003) the current study compared three commonly used and novel methods for analyzing changes in drinking over time: latent growth curve analysis, growth mixture models, and latent Markov models. Specifically, using self-reported drinking data from all participants (n = 1,383, 69% male) we were interested in examining how well the three estimated models were able to explain observed changes in percent heavy drinking days during the 52 weeks following treatment. Results-The results from all three models indicated that the majority of individuals were either abstinent or reported few heavy drinking days during the 52 week follow-up and only a minority of individuals (10% or fewer) reported consistently frequent heavy drinking following treatment. All three models provided a reasonably good fit to the observed data with the latent Markov models providing the closest fit. The observed drinking trajectories evinced discontinuity, whereby individuals seem to transition between drinking and non-drinking across adjacent followup assessment points. The latent growth curve and growth mixture models both assumed continuous change and could not explain this discontinuity in the observed drinking trajectories, whereas the latent Markov approach explicitly modeled transitions between drinking states. Conclusions-The three models tested in the current study provided a unique look at the observed drinking among individuals who received treatment for alcohol dependence. Latent Markov modeling may be a highly desirable methodology for gaining a better sense of transitions between positive and negative drinking outcomes.
Addictive behaviors, 2004
This study refines an empirically derived drinking pattern classification system [Addict. Behav. 20 (1995) 23] and assesses its concurrent and predictive validity in a new sample of alcohol-dependent adults in treatment. Drinking data were collected from 195 adults (133 men) at baseline and for 52 weeks postbaseline using the Timeline Follow-back (TLFB) method. Ninety-three percent of the sample were classified into one of four drinking patterns: binge (n=13, 6.5%), episodic (n=41, 21%), sporadic (n=17, 9%), or steady (n=111, 57%). The steady drinking group showed substantial variability in drinking intensity and was divided into steady/high intensity (n=67, 34%) and steady/low intensity (n=44, 23%) subgroups. With age and gender controlled, the five subgroups did not differ on baseline employment or marital status, but differed on a measure of relationship functioning. Binge and steady/high groups reported the most severe alcohol-use histories. Steady/low intensity drinkers had lat...
MODELLING OVER WEEK PATTERNS OF ALCOHOL CONSUMPTION
Aims: This study aims to analyze alcohol consumption patterns throughout a week, controlled by socio-demographic characteristics, and to discuss the adequacy of the complex models employed. Methods: The sample included 496 participants, from both sexes, 40 years old and with 7-day dietary records. Bayesian generalized additive mixed models (GAMM) were applied using two approaches: a multinomial model, with three categories of alcohol consumption behaviour including; non-drinkers, alcohol during meals only and alcohol at any time; and a gamma model for drinkers which considered the total amount of alcohol ingested per day. Results: The multinomial model captured two different patterns of alcohol consumption: a sharp increase in consumption on weekends for mealtime only drinkers, the dominant behaviour among drinkers and a linear increase from Monday towards Sunday for those who drank at anytime. The effect of higher education changed from slightly protective for mealtime only drinkers to risky for anytime drinkers. The amount of alcohol consumed presents a pattern similar to the meals-only drinking. Conclusions: Alcohol consumption increased during the week. Two different alcohol consumption patterns were identified according to drinking behaviours. The methodological approach utilized was essential in uncovering these patterns.
Dimensionality of lifetime alcohol abuse, dependence and binge drinking
Drug and Alcohol Dependence, 2009
Questions relevant to DSM-V alcohol use disorders (AUD) include whether dimensional measures provide more information than categorical diagnoses, whether to combine abuse and dependence criteria, and whether to add a new diagnostic criterion, binge drinking. Binary and dimensional models of three versions of AUD criteria were investigated: (1) dependence criteria; (2) abuse and dependence criteria combined; and (3) abuse and dependence criteria combined with a binge drinking criterion added. In a national sample of lifetime drinkers (N = 27,324), these models of AUD criteria were investigated in relation to two well-established risk factors for AUD, family history and early drinking onset. Logistic or Poisson regression modeled the relationships between the validating variables and dependence in categorical, dimensional and hybrid forms; Wald tests were used to assess differences between the dimensional, categorical and hybrid models. Alcohol dependence criteria represented a single continuum (family history Wald = 9.93, p = 0.13; early drinking Wald = 7.62, p = 0.27) with no support for a categorical or hybrid version of alcohol dependence. Adding four abuse criteria produced similar results for family history (Wald = 15.4, p = 0.12) although with early drinking, this model showed a trend towards deviating from the data (Wald = 16.7, p = 0.08). No support was found for any diagnostic threshold at 3, 4, 5, 6, or 7 criteria when abuse and dependence were combined. Adding binge drinking resulted in a significant departure from linearity for family history (Wald = 21.8, p = 0.03) and early drinking (Wald = 23.9, p = 0.01). The number of alcohol dependence and abuse criteria met should be explored further as a useful AUD severity indicator or phenotype.
Journal of studies on alcohol, 1998
This study was designed to compare the Timeline Follow-Back (TLFB) to daily and real-time assessments of drinking. Our purpose was to evaluate overall correspondence and day-today agreement between these two methods among both problem and moderate drinkers. Method: In Study 1, problem drinkers (n-20) reported their alcohol consumption daily during 28 days of brief treatment. In Study 2, moderate drinkers (n = 48), recruited from the community, used a palm-top computer to record their drinking for 30 days. In both studies participants completed the TLFB covering the recording period. Results: Participants in Study 1 reported fewer drinking days, fewer drinks per drinking day and fewer total drinks per day on the TLFB, and those in Study 2 reported fewer drinks per drinking day, fewer ounces per drinking day, fewer total drinks per day and fewer total ounces per day. The magnitude of the difference, however, was modest. There was considerable between-person variation in day-today correspondence of TLFB and the daily and real-time reports. Neither person characteristics (gender, education and income) nor the distributional characteristics of drinking (including average consumption, variation) predicted concordance between TLFB and real-time reports. Conclusions: The Timeline Follow-Back method captured overall levels of drinking quite well compared to a 28-day daily diary and a 30-day electronic interview. Vast individual differences in day-today correspondence suggest that the TLFB may be less useful for detecting patterns of consumption. (J. Stud. Alcohol 59: 447-454, 1998) HE ACCURACY with which people recall their alcohol consumption is critical to our understanding of the causes, correlates and consequences of alcohol use, abuse and dependence (Babor et al., 1987, 1990). Although individuals tend to underestimate their alcohol consumption, the extent of this underestimation and its potential moderators are not well understood. In this article we describe two studies designed to examine recall accuracy among moderate and heavy drinkers. One study used daily recording and the other "real time" recording using an "electronic interview." Recalled consumption was compared with these two methods using the Timeline Follow-Back procedure (Sobell et al., 1980; Sobell and Sobell, 1992). Three primary methods have been used to measure alcohol consumption in field settings: (1) quantity and frequency (Q/F) measures asking individuals to summarize or estimate their aggregate drinking over a specified period of time; (2) retrospective diaries; and (3) more recently, prospective diaries of daily drinking. In studies comparing Q/F methods to daily retrospective diaries (