Received 15 March 1999; in revised form 26 July 1999; accepted 10 August 1999
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ABSTRACT |
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INTRODUCTION |
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Although few clinicians or researchers question the importance of the relationship between cigarette use and alcohol dependence, most studies have been of relatively modest size and, thus, were unable to control for potentially important additional variables. For example, there are gender differences in the clinical course of alcohol and nicotine dependence (Carmody et al., 1985; Breslau et al., 1994
; Patton et al., 1998b
; Schuckit et al., 1998a
), raising the question of whether the correlates of conjoint alcoholism and heavy smoking apply equally to men and women. A second potentially confounding factor is the possibility that the more severe clinical course of conjoint alcohol and nicotine dependence might reflect the impact of a third disorder. Thus, for example, the concurrence of alcohol and nicotine dependence carries with it a 5-fold increased risk for bipolar disorder, a 6-fold increased risk for use of illegal drugs, and an almost 20-fold increased rate of the antisocial personality disorder (ASPD) (Helzer et al., 1991
).
This study reports data from a large heterogeneous sample of alcoholics where extensive clinical interviews were used to gather detailed data on these potentially important issues. The major purpose was to evaluate whether the characteristics of alcohol use history are associated with smoking status even after controlling for the potential impact of ASPD, additional drug dependence diagnoses, and gender.
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METHOD |
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All subjects and their available first and second degree relatives gave informed consent and participated in a structured face-to-face interview, using the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) instrument given by well-trained interviewers (Bucholz et al., 1994). The SSAGA screens for 17 Axis I DSM-III-R diagnoses (American Psychiatric Association, 1987
), including misuse and dependence on substances. Subjects were questioned regarding recent drinking histories, patterns of alcohol use, periods of abstinence, a series of 44 life experiences related to alcohol, and the nine criteria relevant to establishing the DSM-III-R diagnoses of alcohol and nicotine dependence (Schuckit et al., 1998a
,b
). Similar data were gathered regarding dependence on most drugs of misuse, and information was obtained regarding most major psychiatric disorders. Regarding major depressive disorder (MDD) among alcohol-dependent subjects, a distinction was made between major depressive episodes that only occurred during periods of alcohol or drug use (substance-induced MDD), versus those observed before the onset of alcohol dependence or during periods of at least 3 months of abstinence (independent MDD) (Schuckit et al., 1997a
).
Consistent with several other studies, cigarette smoking was defined as daily cigarette use for at least 1 month at any time in a person's life (Robins et al., 1989; Breslau et al., 1994
). The smoking history section of the SSAGA was expanded to include the Fagerström Test for Nicotine Dependence (FTND) (Payne et al., 1994
). The FTND was used to generate a modified score based on five instead of six questions, as the item asking which cigarette is the most difficult to give up (explaining 6.7% of the variance of the total score) was not included in the interview. Indeed, it is hard to believe that subjects who smoked cigarettes daily for several years were not considered nicotine dependent. For these analyses, nicotine dependence was defined according to DSM-III-R criteria, which apply only to smokers experiencing severe repercussions of their tobacco use, i.e. on their social functioning, physical or psychological health. Therefore, the distinction between smokers with and without DSM-III-R nicotine dependence might reflect stages in the severity of nicotine dependence, rather than a categorical distinction between those with and without nicotine dependence.
Statistical analyses compared data between groups defined according to smoking status or nicotine dependence. 2-Tests were applied for categorical data across groups, whereas F-values were used to determine the two-tailed significance of differences in group means for continuous variables. If more than two groups were compared, for items that were significant overall, post-hoc tests of pairwise comparisons were applied using Tukey's Honestly Significant Difference Test for continuous variables and the
2 for proportions for dichotomous variables. Consistent with the COGA approach to data analyses, demographic, alcohol- and drug-related items were compared across groups without correction for multiple comparisons in order to avoid a conservative approach where meaningful differences across groups are missed. Finally, logistic regression was used to determine the potential importance of the variables which were significant at the univariate level in predicting current smoking status or nicotine dependence. The approach used to evaluate the proportion of the variance explained by the logistic regression analyses followed the recommendations of Hosmer and Lemeshow (1989) through which an R2 = 100 (1 Lp/L0).
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RESULTS |
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Table 1 compares demographic background, alcohol and tobacco use histories, and associated diagnoses across five groups of subjects. These include 180 alcoholics who were non-smokers (Group 1), 167 former smokers (divided into those in Group 2 who were never nicotine dependent versus those in Group 3 who fulfilled such criteria), and similar non-dependent and dependent subdivisions of 658 current smokers (Groups 4 and 5). Looking across Groups 1 through 5, it is apparent that almost 18% of these alcohol-dependent men and women had never regularly smoked cigarettes, and that a lower proportion of former smokers had ever been nicotine dependent (84 of 167 or 50.3%), compared to current smokers (479 of 658 or 72.8%) (
2 = 31.10; P < 0.001). Regarding demographics, former smokers were older than the remaining subjects (indicating that one might expect higher rates of former smoking in Groups 4 and 5 over time), and, within both former and current smokers, women were more likely to have ever been nicotine dependent. The remaining two demographic items demonstrate that, among Groups 2 to 5, current smokers and nicotine-dependent subjects had lower proportions of individuals who were employed or who had received a high school diploma.
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Table 1 also offers information about tobacco use histories among current and former smokers. Reflecting the way the groups were defined, nicotine-dependent subjects had a more severe course of nicotine use with, for most items, a greater maximum intake and more lifetime tobacco-related problems illustrated by more DSM-III-R criteria of nicotine dependence for current versus former smokers. However, problems were still apparent for non-nicotine-dependent smokers.
Of central interest is whether the group differences on alcohol use and problems might actually reflect additional associated diagnoses. Antisocial personality disorders (ASPD) and substance dependence diagnoses were more likely in smokers, especially those whose use was current, and, among smokers, in nicotine-dependent individuals. For Groups 2 to 5, dependent subjects were also more likely to have independent and substance-induced mood disorders, with the latter diagnoses more likely among current, versus former, smokers. Thus, it is possible that the association of some aspects of more evidence of social impairment (unemployment, low level of education), higher levels of alcohol use, and more intense tobacco use with a history of current (versus former) smoking and with nicotine dependence might reflect differences between groups regarding gender, ASPD, and dependence on drugs other than alcohol and nicotine.
To test this, the top portion of Table 2 evaluates the characteristics associated with being a former smoker, and the bottom relates to the pattern of those characteristics associated with a history of nicotine dependence using logistic regression analyses. In predicting former (versus current) smokers among individuals who had ever regularly consumed cigarettes, and in predicting nicotine dependence among smokers, each of the items from Table 1
that were significantly associated with the relevant dependent variable (e.g. nicotine dependence) were entered into the logistic regression analyses, with Table 2
presenting only those items that significantly contributed to the final equation. Regarding the ability to become a former smoker after regularly consuming cigarettes, the regression analysis explained 17.8% of the variance. Items that significantly added to the equation indicated a greater probability of smoking cessation in older alcoholics, those who were employed, and were also associated with a lower maximum of drinks per day, fewer alcohol-related problems, fewer of the nine DSM-III-R nicotine dependence criteria, and a lower modified Fagerström score. The age of onset of alcohol dependence acted as a suppressor variable in the context of current age, and, thus, the direction of the odds ratio was reversed. It is interesting to note that these predictors were unaffected by the presence or absence of ASPD, dependencies on drugs other than alcohol, prior treatment for alcohol, or gender, as none of these latter items entered the final regression analysis.
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DISCUSSION |
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Reflecting the limited number of subjects in most investigations as well as the research methodologies invoked, prior studies were usually unable to determine whether the greater intensity of alcoholism associated with current smoking and nicotine dependence might be an indirect reflection of additional characteristics, such as ASPD, other drug dependencies, and gender. The results in Table 1 support the relationship between nicotine and alcohol use disorders. Table 2
reveals that, even after considering the impact of gender, ASPD, and additional drug dependencies, both current smokers and nicotine-dependent smokers continued to show evidence of a greater number of alcohol-related life problems.
Another interesting result concerns the relationship of gender to nicotine dependence in the logistic regressions. Similar results have also been reported in the literature (Swan et al., 1997). It is postulated that women smokers might respond to a wider range of environmental cues, which increased their desire for cigarettes, and are thus more likely to develop dependence and, perhaps, even less likely to respond to nicotine replacement treatment. In any event, the current results support the need to consider gender when evaluating issues related to smoking behaviours in general, including those among alcohol-dependent individuals.
Several studies have also discussed the relationship between mood disorders and smoking (e.g. Glassman, 1993), as well as mood disorders and heavy drinking (Schuckit et al., 1997a). Using methods established for alcohol, the current study distinguished between independent major depressive episodes as described in the DSMs and temporary, substance-induced mood disorders that are observed in
30% of alcoholics (Schuckit et al., 1997a
). The univariate analyses in Table 1
show fairly strong group differences in substance-induced mood disorders among smokers, and some, perhaps less intense, differences for independent major depression. Table 2
indicates that, after considering additional group differences, only the differential in induced depressions remains robust. The first implication of these results is the need for future researchers to distinguish between substance-induced and independent depressive episodes in looking at nicotine-dependent individuals, at least among those with alcohol or drug dependence.
Although the current sample was large and the subjects diverse regarding demography and associated diagnoses, several caveats should be considered. First, the data were generated from families with a high density of alcoholism selected through an alcoholic proband. Second, more detail was available regarding alcohol, drugs, and mental health problems than was true for the nicotine history. Third, most of the subjects had modest levels of education. Thus, the generalizability of the current results to other populations will need to be tested. Moreover, other variables related to subjects' personality, social, and cultural characteristics with potentially important influences on the smoking status were not considered in these analyses. Nonetheless, the data presented here document that, within this sample, the reported heightened intensity of alcohol-related problems among smoking alcoholics appears to be independent of ASPD, additional drug dependencies, prior alcohol treatment, and that some similar generalizations apply to both genders.
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ACKNOWLEDGEMENTS |
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FOOTNOTES |
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The Collaborative Study on the Genetics of Alcoholism (COGA) (H. Begleiter, SUNY HSCB Principal Investigator; T. Reich, Washington University, Co-Principal Investigator) includes six different centres where data collection takes place. The six sites and Principal Investigator and Co-Investigators are: Indiana University (J. Nurnberger Jr, T.-K. Li, P. M. Conneally, H. Edenberg); University of Iowa (R. Crowe, S. Kuperman); University of California at San Diego and Scripps Institute (M. Schuckit, F. Bloom); University of Connecticut (V. Hesselbrock); State University of New York, Health Sciences Center at Brooklyn (H. Begleiter, B. Porjesz); Washington University in St Louis (T. Reich, C. R. Cloninger, J. Rice).
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