Temporal progression of alcohol use disorder (AUD) symptoms has been studied among members of Alcoholics Anonymous and treatment samples since the 1940’s (see Nelson, Heath, & Kessler, 1998
for a comprehensive review of the history). In recent decades, this line of research has been extended to the general population (Nelson et al., 1998
; Nelson, Little, Heath, & Kessler, 1996
), adolescent drinkers (Martin, Langenbucher, Kaczynski, & Chung, 1996
), and community-residing older drinkers (Lemke, Schutte, Brennan, & Moos, 2005
). One common goal of these studies is to characterize AUD in terms of a disease-progression model
(Lemke et al., 2005
), which specifies a temporal ordering of clusters of symptoms that may indicate the stages of disease progression. Such a model has the potential to improve screening of early cases, designs of preventive intervention, allocation of treatment resources, and timing of treatment. However, different patterns of progression have been identified by existing studies depending on the statistical methods, characteristics of the samples and the different ways in which AUD symptoms were asked. In addition, because of the cross-sectional design of existing studies, the accuracy of retrospective data at the symptom level remains a major concern, especially for individuals who had been drinking for some years at the time the data were collected. Thus, a prospective longitudinal design that follows youth from drinking initiation to the onset of AUD symptoms is needed for a better understanding of the developmental emergence of AUD symptoms.
Symptom-specific progression patterns to date have only been examined by one prospective
study, the Early Developmental Stages of Psychopathology (EDSP) study, which followed 3021 community participants aged 14–24 (at baseline) in Germany across 4 waves over 10 years (Behrendt, Wittchen, Hofler, Lieb, Low, Rehm, et al., 2008
). The EDSP study showed that the distributions of the duration of progression from first alcohol use to first alcohol dependence symptom were different for the seven DSM-IV alcohol dependence symptoms (see for a comprehensive list of the AUD symptoms and acronyms). However, these curves may not be totally comparable because they were estimated with different levels of accuracy. In particular, the curves corresponding to the symptoms rarely endorsed as a first alcohol dependence symptom (e.g. AD2-withdrawal, AD6-activities given up) were based on only a handful of cases (range of 12 to 24). Moreover, the sample characteristics, involving a relatively high socioeconomic status region in Germany, may render the findings of only limited generalizability to the high risk youth population in the United States.
First symptom prevalence rates and lifetime prevalence rates of DSM-IV alcohol abuse (AA) and alcohol dependence (AD) symptoms.
In addition to the issue of temporal progression of appearance, individual AUD symptoms may also have potential as early harbingers to predict the likelihood of progression to alcohol dependence. Such information can improve screening of high risk cases at an early stage.Nelson et al. (1996)
found that people who reported AD2 (withdrawal) or AD6 (activity given up) as their first symptom were most likely to progress subsequently to alcohol dependence than those who reported other symptoms. This finding was based on retrospective data from a representative sample of the adult population in the U.S. However, prospective data from the EDSP study (Behrendt et al., 2008
) showed that the risk for alcohol dependence was elevated for those with a completely different set of first symptoms: AD1 (tolerance), AD4 (quit/control), AD5 (time spent), or AD7 (physical/psychological problems). These inconsistent findings could be the result of the differences between the two studies in terms of sample characteristics, study designs, or analytic methods. One shared limitation of these two studies is that they did not control for some well-known risk factors such as early onset of drinking as they evaluated the association between first AUD symptoms and the risk for progression to alcohol dependence. Without taking into account important preexisting risk profiles, it is impossible to know if these first symptoms add any new information about risk.
Extant literature has identified risk factors for progression from alcohol use to alcohol dependence (or AUD). National epidemiologic surveys consistently found that men were at higher risk for progression to an alcohol dependence diagnosis than women (Keyes, Martins, Blanco, & Hasin, 2010
; Wagner & Anthony, 2007
). Such gender differences were also supported by prospective longitudinal data from a community sample (Hussong, Bauer, & Chassin, 2008
). In addition to gender, national survey data showed that a higher density of family history of alcoholism was associated with higher risk of progression to alcohol dependence diagnosis (Dawson, 2000
). Specifically, parental history of alcohol problems or AUD diagnosis was linked to a higher risk of progression to alcohol dependence symptoms or AUD diagnosis in adolescents (Bucholz, Heath, & Madden, 2000
; Hussong et al., 2008
). Another risk factor shown to be associated with progression to an alcohol dependence diagnosis in cross-sectional health surveys was early onset of drinking (Dawson, 2000
; DeWit, Adlaf, Offord, & Ogborne, 2000
). Prospective longitudinal data also supported this association (Behrendt, Wittchen, Hofler, Lieb, & Beesdo, 2009
). Moreover, twin studies consistently found a common genetic factor, labeled as externalizing, underlying conduct disorder, antisocial personality disorder, and alcohol dependence (Kendler, Prescott, Myers, & Neale, 2003
; Krueger, Hicks, Patrick, Carlson, Iacono, & McGue, 2002
). In a prospective longitudinal study, adolescent externalizing behavior reported at the age of drinking onset was shown to be a significant risk factor for progression to AUD diagnosis (Hussong et al., 2008
). The externalizing measure used in that study was a composite of delinquency and aggression subscales of the Child Behavior Checklist (Achenbach, 1991a
). Recent work by our group (Mayzer, Fitzgerald, & Zucker, 2009
) using the same instrument found that delinquent behavior predicted problem drinking better than aggression in a longitudinal design. Thus, delinquency may be a more fine grained risk factor than the broad band externalizing factor.
The current study examines the patterning of emergence of AUD symptoms, and evaluates their potential as early indicators for the progression to alcohol dependence. We analyze prospective data on alcohol use, symptoms, and diagnoses collected from a community sample of high risk youth followed from early childhood to early adulthood. The longitudinal study design covers the age range of highest probability for AUD symptom onset, 10–24 (Nelson et al., 1998
). The following are the objectives of this study. First, we aim to characterize the longitudinal patterns of risk for developing individual AUD symptoms during the ten years after onset of regular drinking. Based on existing retrospective data on symptom onset from adolescent drinkers (Martin et al., 1996
), we expect that young people will be at the highest risk for developing AD3 (larger/longer) and AA4 (social/interpersonal problems) at the onset of regular drinking; the risk for developing AD1 (tolerance) will not start high at the onset of regular drinking but will drastically increase for some years and then decrease. We also expect that young people will be at high risk for developing AD6 (activities given up) and AD7 (physical/psychological problems) in later years. The second objective is to investigate if there is a synergy (i.e. statistical interactions) between any pairs of precursive risk factors including being male, COA, an early onset drinker, and higher in delinquent behavior at drinking onset. We expect that the people who carry both risk factors in a pair will be more likely to develop into alcohol dependence than those who only qualify for one of the risk factors. The third objective is to evaluate the potential of individual AUD symptoms as first symptoms to predict future progression to alcohol dependence diagnosis, incrementally beyond the precursive risk structure already in place. Based on existing prospective data from young people (Behrendt et al., 2008
), we expect AD1 (tolerance), AD4 (quit/control), AD5 (time spent), and AD7 (physical/psychological problems) to be important first symptom predictors. The fourth objective is to examine if the first symptoms identified as significant predictors for progression to alcohol dependence are particularly important warning signs for drinkers with certain precursive risk profiles (i.e. there are statistical interactions between precursive risk factors and first symptom predictors). Due to the exploratory nature of this set of analysis, we do not have any particular expectation for this objective.