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The relation between alcohol consumption and smoking abstinence
Addictive Behaviors 27 (2002) 367 – 379
The relation between alcohol consumption and smoking abstinence: Results from the Working Well Trial$ Jennifer B. McClurea,*, David W. Wetterb, Carl de Moorb, Paul M. Cinciripinib, Ellen R. Gritzb a
Group Health Cooperative, Center for Health Studies, Suite 1600, 1730 Minor Avenue, Seattle, WA 98101, USA b M.D. Anderson Cancer Center, University of Texas, Houston, TX, USA
Abstract The current study examined the relation between drinking and smoking abstinence in a community-based sample from the Working Well Trial (WWT). At baseline, drinking level was related to smoking history (never, former, or current smoker; P < .0001) and abstinence history. Mean monthly alcohol consumption increased linearly with decreases in duration of recent abstinence (i.e., longest period quit in the past year among current smokers; P < .05) and current abstinence (i.e., time since quitting among former smokers; P < .0001), even controlling for relevant demographic factors. Among baseline smokers, lower beer consumption predicted smoking abstinence at 4-year follow-up ( P < .01). A trend towards significance was found for total alcohol consumption ( P = .06). The results suggest (a) a dose – response relation between baseline drinking and duration of smoking abstinence, and (b) that heavier drinkers are less likely to quit smoking over a 4-year period. D 2002 Elsevier Science Ltd. All rights reserved. Keywords: Smoking; Alcohol; Smoking abstinence; Smoking cessation
$ This work was conducted in the Department of Behavioral Science at the University of Texas, M.D. Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX, 77030-4095, USA. * Corresponding author. Tel.: +1-206-287-2737; fax: +1-206-287-2871. E-mail address: [email protected] (J.B. McClure).
0306-4603/02/$ – see front matter D 2002 Elsevier Science Ltd. All rights reserved. PII: S 0 3 0 6 - 4 6 0 3 ( 0 1 ) 0 0 1 7 7 - 0
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1. Introduction It is well documented that smoking and alcohol use are related (Miller & Gold, 1998; Shiffman & Balabanis, 1995). Smokers are significantly more likely to drink than nonsmokers (Shiffman & Balabanis, 1995) and 30% of smokers are alcoholics, compared to 10% of the general population (Miller & Gold, 1998). Among alcoholics, smoking prevalence is three times greater than in the general population (80–90%; Patten, Martin, & Owen, 1996). There is also a dose–response relation between drinking and smoking. Heavy drinking is associated with heavy smoking and vice versa (Batel, Pessione, Maitre, & Rueff, 1995; Burling & Tiff, 1988; Friedman, Tekawa, Klatsky, Sidney, & Armstrong, 1991). The determinants of this relation are not completely clear, but are likely to be due to a combination of environmental, cultural, psychological, and biological factors (e.g., Flay, Phil, Petraitis, & Hu, 1995; Swan, Carmelli, Rosenman, Fabsitz, & Christian, 1990; True et al., 1999). Not only is there a high comorbidity between smoking and alcohol use, but there is evidence that drinking can alter smoking behavior. In laboratory studies, drinking increases the rate and amount of smoking among smokers (Mintz, Boyd, Rose, Charuvastra, & Jarvik, 1985) and exposure to drinking cues increases urges to smoke among smoking-deprived alcoholics (Monti, Rohsenow, Colby, & Abrams, 1995). Alcoholics may also experience higher levels of nicotine withdrawal after quitting smoking (Marks, Hill, Pomerleau, Mudd, & Blow, 1997), which could subsequently increase their likelihood of relapse. Studies such as these suggest that alcohol consumption, particularly among heavier drinkers, may interfere with smoking abstinence. In fact, heavy drinkers are less likely to attempt to quit smoking and are less successful when they do try to quit (Breslau, Peterson, Schultz, Andreski, & Chilcoat, 1996; Zimmerman, Warheit, Ulbrich, & Auth, 1990), even when receiving nicotine patch therapy (Hays et al., 1999). However, most of the research in this area has been conducted with alcoholics or persons receiving treatment for alcohol or nicotine dependence. The relation between drinking and smoking abstinence has not been well evaluated in community samples. One population-based study (Nothwehr, Lando, & Bobo, 1995) failed to find an association between baseline drinking status and smoking abstinence at follow-up, but drinking was evaluated as a dichotomous variable (drinker/nondrinker). Dichotomizing alcohol consumption into drinkers and nondrinkers may obscure a dose–response relation between drinking and smoking cessation, and the amount of alcohol consumed may be a more sensitive prospective predictor of smoking cessation than whether or not one drinks any alcohol. To address these issues in a population-based sample, we conducted post hoc analyses of data from the Working Well Trial (WWT). Specifically, the present investigation examined the relation between baseline alcohol consumption and smoking abstinence. Based on evidence that there is a dose–response relation between drinking and smoking (Batel et al., 1995; Burling & Tiff, 1988; Friedman et al., 1991) and evidence that heavier drinkers are less likely to quit smoking (Breslau et al., 1996; Hays et al., 1999; Zimmerman et al., 1990), we hypothesized that higher drinking levels at baseline would be associated with shorter periods of abstinence history among current and former smokers at baseline. In addition, we hypothesized that baseline smokers’ drinking level would prospectively predict smoking abstinence at 4-year follow-up.
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2. Method 2.1. Study design The design of the WWT has been presented in detail elsewhere (Abrams et al., 1994; Sorensen et al., 1996). Briefly, the WWT was a large multisite cancer control trial conducted in 114 worksites by four study centers, a coordinating center and the National Cancer Institute. The study included a 2-year multirisk factor intervention targeting smoking, nutrition, and either occupational carcinogen exposure, smokeless tobacco (ST), or exercise, depending on the study center. Data in the present investigation were collected by The University of Texas M.D. Anderson Cancer Center from 40 worksites in the southeastern United States. Baseline information was collected during mandatory worksite meetings between September and December 1990. Follow-up surveys were conducted in the fall of 1994. Data at both time points were collected via confidential health behavior surveys completed by the employees at each of the 40 participating worksites. Each worksite had an average of 193 eligible employees (Abrams et al., 1994). 2.2. Participants 2.2.1. Baseline sample A total of 6867 participants were sampled at baseline. Of these, 5157 met the inclusion criteria for the baseline analyses in this investigation (i.e., never, current, or former smoker). Persons who did not provide information on their tobacco use (n = 479) and those reporting exclusive use of pipes (n = 38), cigars (n = 70), ST (dip, chew, or snuff; n = 891), or dual tobacco use (cigarettes and ST; n = 232) were excluded because there was insufficient information to categorize their abstinence history. Overall, participants in the baseline sample tended to be male (74%), Caucasian (87.8%), married (79.8%), and have some post-high school education (59.4%). Mean age was 39.5 years. Demographic composition by tobacco use status is presented in Table 1. 2.2.2. Longitudinal cohort More than half of the baseline sample in this study (n = 3303) also provided information on their tobacco use at follow-up. To prospectively predict smoking cessation, however, the longitudinal cohort was limited to baseline smokers (n = 728). Demographic characteristics of the cohort are presented in Table 1. 2.3. Measures 2.3.1. Tobacco use and abstinence history classification To examine alcohol consumption across groups with varying smoking histories, participants were categorized as current smokers, former smokers, or never smokers at baseline and then further subdivided based on their abstinence history. Smoking status was strictly defined to ensure proper group identification. Persons were considered to be never smokers if they
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Table 1 Demographic characteristics of baseline sample and longitudinal cohort Baseline sample
Race Caucasian African American Asian Other Males Education High school > High school Married Drink 1/month Mean age
Longitudinal cohort
Never smokers (n = 2425)
Former smokers (n = 1505)
Current smokers (n = 1227)
Current smokers (n = 728)
89.3% 8.1% 0.3% 2.4% 68.6%
93.8% 4.2% 0.1% 1.8% 84.8%
88.9% 8.8% 0.2% 2.2% 78.4%
91.6% 6.6% 0.3% 1.5% 78.8%
36.4% 63.6% 79.2% 49.0% 37.31
40.7% 59.3% 88.1% 55.1% 43.18
44.7% 55.3% 78.5% 67.7% 39.38
46.6% 53.4% 80.5% 66.2% 39.29
Based on data reported at baseline.
had not smoked more than 100 cigarettes in their life and did not currently use ST. Individuals were classified as former smokers if they had smoked at least 100 cigarettes in their life, had not smoked even a puff in the past 7 days, did not categorize themselves as a smoker, and did not currently use ST. Current smokers included individuals who had smoked at least 100 cigarettes in their life, had smoked in the past 7 days, reported that they were a current smoker, and reported no current use of ST. Based on the smoking continuum in the 1990 Surgeon General’s Report (U.S. Department of Health and Human Services (USDHHS), 1990), former and current smokers were further subdivided by quit attempt history. Minor modifications were made to the abstinence categories to adapt them to the Working Well data (e.g., ‘‘quit 3–12 months in the last year’’ was changed to ‘‘quit 4–12 months in the last year’’). Former smokers were classified based on the length of time since quitting smoking (i.e., former smoker quit >5 years, former smoker quit 1–5 years, former smoker quit 4–12 months, former smoker quit 3 months). Current smokers were classified based on the longest period of abstinence in the preceding year (i.e., quit 4–12 months in the last year, quit 1–3 months in the last year; quit 1–4 weeks in the last year; quit 2–6 days in the last year; no quit attempts in the last year). 2.3.2. Alcohol consumption Monthly alcohol consumption was calculated from quantity and frequency data for beer, wine, and liquor. Participants indicated their standard drink size for each type of alcohol (small, medium, large). A ‘‘medium’’ drink was quantified as a 12-oz beer, medium glass of wine, or 1 1/2 oz of liquor. A ‘‘small’’ beverage was calculated as 1/2 of a medium drink and a ‘‘large’’ beverage as 1 1/2 medium drinks. Participants also indicated the average number of alcoholic beverages consumed over the previous 6-month period using the following response options: never or less than one per month, 1–3 per month, 1 per week, 2–4 per
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week, 5–6 per week, 1 per day, 2–3 per day, 4–5 per day, 6+ per day. These values were converted to monthly equivalents. Because responses were based on ranges, median values for each range were used to estimate average monthly consumption for beer, wine, liquor, and combined alcohol intake (e.g., if the range were 8 to 16 drinks per month, the monthly estimate would be 12 drinks). Drink frequency was multiplied by drink size to estimate average monthly alcohol consumption. Consumption values were calculated for beer, wine, liquor, and total alcohol intake. 2.3.3. Smoking abstinence Smoking abstinence at a 4-year follow-up was defined as having not smoked even a puff in the past 7 days. 2.4. Statistical analyses Characteristics of the baseline sample and longitudinal cohort were evaluated using standard descriptive statistics. Comparisons between the tobacco use groups’ alcohol intake at baseline were conducted using chi-square and t test analyses. To test the first hypothesis that there would be a dose–response relation between baseline alcohol consumption and history of smoking abstinence, we calculated and graphed the mean level of monthly alcohol consumption for never smokers and for each abstinence history group within current and former smokers. To examine whether alcohol level increased across these groups as abstinence duration decreased, we used general linear modeling (GLM) to run regression models testing for linear and quadratic trends and adjusted for the influence of relevant demographic factors (i.e., race, gender, education, and age). To control for the randomization of the worksites in the longitudinal analyses, we conducted logistic regression analyses using generalized estimating equations (GEE; PROC GENMOD; SAS Institute, 1996) adjusting for treatment group. GEE reduces the chance of making a Type I error by adjusting the standard errors of the regression coefficient for the observed within cluster (i.e., treatment group) correlations (Liang & Zeger, 1986; Norton, Bieler, Ennett, & Zarkin, 1996). By doing this, we were able to control for the fact that the participants’ abstinence rates may have differed by treatment group.
3. Results 3.1. Baseline alcohol consumption and tobacco use A clear pattern was found between drinking and smoking status at baseline. Never smokers were less likely to drink (49.0%) than former smokers (55.1%) or current smokers (67.7%; c2 = 108.77, df = 2, P .0001). Never smokers reported the lowest level of alcohol consumption per month (M = 11.22, S.D. = 34.31), followed by former smokers (M = 14.88, S.D. = 32.82; P .001), and current smokers (M = 29.52, S.D. = 58.50; P < .0001). Among current smokers, number of cigarettes smoked per day was correlated with total alcohol
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consumption (r = .12, P < .01) and beer consumption (r = .13, P < .01), but not with amount of liquor or wine consumed. 3.2. Relation between drinking and smoking abstinence at baseline 3.2.1. Current smokers Drinking level was calculated for each subgroup of current smokers on the smoking continuum. Drinking increased linearly as the duration of recent abstinence (i.e., in the past year) decreased (see Fig. 1). This trend was significant for total alcohol intake ( F = 4.11, P < .05). A trend towards significance was also observed when testing for a linear trend across beer consumption ( F = 3.44, P = .06). No significant linear trends were found for liquor or wine and no significant quadratic trends were observed across any of the alcohol categories. All analyses adjusted for the influence of participants’ age, race, gender, and education. 3.2.2. Never and former smokers Similarly, drinking was lowest among never smokers and increased linearly across former smokers as the duration of their current abstinence decreased (see Fig. 2). Across former smokers, significant linear trends were found when analyzing total alcohol intake ( F = 18.863, P < .0001), beer ( F = 8.93, P < .01), wine ( F = 10.98, P < .001), and liquor
Fig. 1. Baseline current smokers’ mean alcohol intake by longest period of smoking abstinence in the past year.
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Fig. 2. Baseline never and former smokers’ mean alcohol intake by current abstinence history.
( F = 3.71, P .05) and relevant demographic factors were controlled. There were no significant quadratic trends across any of the analyses. 3.3. Prospective relation between drinking and smoking abstinence We hypothesized that baseline drinking would predict tobacco abstinence at follow-up in the longitudinal cohort of baseline smokers. Eighteen percent of smokers in the cohort were abstinent at follow-up. Participants who continued to smoke at follow-up drank significantly more at study intake than those who were abstinent at follow up (M = 31.78, S.D. = 62.53 vs. M = 20.94, S.D. = 36.94; P = .01). Using GEE logistic regression analyses, total alcohol consumption significantly predicted smoking abstinence after controlling for treatment group ( P < .05) and treatment group plus relevant demographic characteristics (i.e., age, race, gender, and education) ( P < .05; see Table 2). However, the relation between total alcohol consumption and abstinence only approached significance when controlling for treatment group, smoking rate (cigarettes per day), and number of quit attempts in the previous year ( P = .06), and when controlling for the combination of the demographic variables and smoking history variables ( P = .06). Beer consumption was a better predictor of prospective smoking abstinence than total alcohol consumption. It predicted smoking abstinence after controlling for treatment group ( P < .001); treatment group and relevant demographic variables ( P < .001); treatment
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Table 2 Prospective logistic regression analyses predicting smoking abstinence from baseline drinking Total alcohol consumptiona
Beera
Control variables
Parameter estimate
ORb
S.E.c
Parameter estimate
ORb
S.E.c
Treatment group Treatment group and demographicsd Treatment group and smoking variablese Treatment group, smoking variablese and demographicsd
0.005 0.004
0.99* 1.00*
0.002 0.002
0.007 0.006
0.99** 0.99**
0.003 0.002
0.004
1.00y
0.002
0.007
0.99**
0.003
0.004
1.00y
0.002
0.006
0.99**
0.002
a
Alcohol type used in each model (total alcohol intake or beer only). OR = odds ratio. c SE = standard error. d Demographics = age, race, gender, and education. e Smoking variables — cigarettes per day and number of quit attempts in the past year. * P < .05. ** P .01. y P = .06. b
group, smoking rate, and quit attempts ( P < .01), as well as the combined model ( P < .01; see Table 2). Neither wine nor liquor consumption was significantly related to follow-up smoking abstinence.
Fig. 3. Probability of quitting smoking at follow-up.
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Finally, we looked at the probability of quitting smoking at follow-up based on monthly beer consumption (see Fig. 3). Because the parameter estimates and odds ratios were relatively unchanged across each of the logistic regression models (see Table 2), the probabilities were calculated controlling for treatment group alone. The probability of quitting smoking after 4 years steadily declined as beer consumption at baseline increased. For example, compared to a person who did not drink beer, drinking one beer a day, or an average of 30 per month, decreased the probability of being abstinent by 15% (i.e., the probability of being quit declines from nearly 20% to 17%). Drinking an average of two beers a day decreased the odds of quitting by 29%, etc. Thirty-seven percent of beer drinkers in the longitudinal cohort reportedly drank 30 or more beers a month.
4. Discussion The present study looked at whether alcohol consumption is associated with smoking abstinence in a population-based sample. Unlike most of the research linking smoking and drinking, we looked at never, former, and current smokers, and included all participants, not just those seeking treatment for nicotine or alcohol dependence or those labeled as pathological drinkers. Some participants in the longitudinal investigation were exposed to a worksite intervention for smoking cessation, but the treatment did not increase abstinence rates (Sorensen et al., 1996). Nevertheless, we adjusted for this factor in the prospective analyses. Furthermore, we evaluated drinking level, as opposed to absolute drinking status. Consequently, the results of this study enhance our understanding of the association between alcohol use and smoking abstinence in the general population. We found a strong linear relation between drinking (i.e., average monthly consumption over the past 6 months) and smoking abstinence history. The amount of total alcohol consumed increased linearly as the duration of current abstinence (among former smokers) and duration of abstinence in the past year (among current smokers) decreased (see Figs. 1 and 2). Previous studies have found that drinking level does not decrease after quitting smoking (Keenan, Hatsukami, Pickens, Gust, & Strelow, 1990; Maletzky & Klotter, 1974; Nothwehr et al., 1995). If this is the case, our results suggest that persons who drink less alcohol are able to remain abstinent from smoking longer. Since these data were collected cross-sectionally, it is possible that participants reduced their drinking subsequent to quitting smoking, but we believe this is unlikely. The most plausible explanation for the linear relation between drinking and abstinence history is that drinking level itself influenced participants’ ability to remain cigarette-free. The prospective analyses appear to confirm this explanation. As hypothesized, baseline beer drinking predicted smoking abstinence after 4 years, even after controlling for treatment group, demographic characteristics (age, race, gender, education), baseline smoking rate, and number of quit attempts in the preceding year at
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intake — a gross indicator of motivation for quitting ( P < .01). Furthermore, the probability of being abstinent from cigarettes after 4 years declined steadily as baseline beer consumption increased. Controlling for treatment group alone, total alcohol consumption also predicted abstinence in our logistic regression analyses ( P < .05), but was not quite significant after controlling for the full model of treatment group, demographic characteristics, and smokingrelated variables ( P = .06). Taken together, however, the prospective analyses revealed that participants who quit smoking at follow-up drank significantly less alcohol at study initiation than those who continued smoking ( P = .01), and baseline drinking level predicted future smoking abstinence. 4.1. Study limitations There are several limitations worth noting. First, the data in this study are based on selfreport information collected in the WWT, so we do not have biochemical confirmation of smoking status or alcohol consumption. However, it is standard practice to forego biochemical smoking confirmation in community-based studies and there is evidence that this is a valid practice (Velicer, Prochaska, Rossi, & Snow, 1992). Furthermore, there is no reason to believe that deception was a significant factor in this sample. Participants were sampled in conjunction with general health behavior surveys. No special emphasis was placed on smoking or smoking cessation. The tobacco intervention was of low intensity and targeted the entire worksite. Smokers were not singled out. As a result, the social pressures to quit, or to report false abstinence, should have been low. However, if exposure to the treatment did result in a response bias towards deception, this effect would have been controlled for in the prospective analyses. Because these are secondary analyses of the WWT data, we were limited by the scope and wording of the questions on the WWT health behavior surveys. For example, we could not look at the relation between drinking and tobacco abstinence among ST users, pipe smokers, or cigar users because we did not have sufficient information on these groups’ abstinence history. Furthermore, information on alcohol consumption was assessed in ranges of drinks per day, per week, or per month. That is, some participants provided monthly estimations, some weekly, and some daily, depending on the magnitude of their intake (e.g., less than one drink per month, two to three drinks per day). To generate an equivalent scale across participants, we transformed everyone’s drinking estimates to drinks per month and used the median value of their average monthly drinking range in our analyses (e.g., if the range were 20 to 24 drinks per month, we used 22 drinks). This provides an appropriate general index of monthly consumption, but does increase the error in our alcohol measures, which could obscure the relation between drinking and abstinence. We were also constrained to point prevalence abstinence at 4-year follow-up. It is significant to demonstrate that alcohol consumption predicts abstinence after such a period, but the results would be more telling if more frequent assessments including information on continuous abstinence were available.
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Finally, the results of this study were based on a sample of predominantly white males in the southeastern United States. These findings may not generalize to groups with a more diverse sociocultural background. 4.2. Summary and conclusions In sum, the results of this study confirm and extend previous research on nicotine and alcohol. Consistent with prior work (Breslau et al., 1996; Zimmerman et al., 1990), we found that heavier drinkers were less likely to quit smoking, but we demonstrated this after a period of 4 years and among persons who were not recruited on the basis of pathological or ‘‘problem’’ drinking. Furthermore, we found a dose–response relation between current drinking and one’s historical cigarette use. To our knowledge, this is the first study to examine the relation between alcohol consumption and smoking abstinence in a sample with varying histories of cigarette use (never, former, and current smokers) and to so finely delineate the relation between drinking and abstinence duration. Together, these findings underscore our need to better understand the etiology of comorbid nicotine and alcohol use. If the causal nature of the link between these drugs is better understood, our ability to modify smoking behavior may be increased. Furthermore, these data illustrate the need for interventions which target both drinking and smoking. If consuming less alcohol increases one’s chances of quitting smoking, then smoking cessation interventions may be well served to focus more specifically on alcohol reduction, even among nondiagnostic drinkers.
Acknowledgments The Working Well Trial was funded by the National Cancer Institute (P01 CA51671). Additional support for this study was provided to the first author by the National Cancer Institute (K07 CA85603-01). A portion of the baseline results was presented at the Twentieth Annual meeting of the Society for Behavioral Medicine in San Diego, CA, March 1999. The authors would like to thank Diana Miglioretti, PhD and Lou Grothaus, M.A. for their statistical consultation on this project.
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The relation between alcohol consumption and smoking abstinence: Results from the Working Well Trial$ Jennifer B. McClurea,*, David W. Wetterb, Carl de Moorb, Paul M. Cinciripinib, Ellen R. Gritzb a
Group Health Cooperative, Center for Health Studies, Suite 1600, 1730 Minor Avenue, Seattle, WA 98101, USA b M.D. Anderson Cancer Center, University of Texas, Houston, TX, USA
Abstract The current study examined the relation between drinking and smoking abstinence in a community-based sample from the Working Well Trial (WWT). At baseline, drinking level was related to smoking history (never, former, or current smoker; P < .0001) and abstinence history. Mean monthly alcohol consumption increased linearly with decreases in duration of recent abstinence (i.e., longest period quit in the past year among current smokers; P < .05) and current abstinence (i.e., time since quitting among former smokers; P < .0001), even controlling for relevant demographic factors. Among baseline smokers, lower beer consumption predicted smoking abstinence at 4-year follow-up ( P < .01). A trend towards significance was found for total alcohol consumption ( P = .06). The results suggest (a) a dose – response relation between baseline drinking and duration of smoking abstinence, and (b) that heavier drinkers are less likely to quit smoking over a 4-year period. D 2002 Elsevier Science Ltd. All rights reserved. Keywords: Smoking; Alcohol; Smoking abstinence; Smoking cessation
$ This work was conducted in the Department of Behavioral Science at the University of Texas, M.D. Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX, 77030-4095, USA. * Corresponding author. Tel.: +1-206-287-2737; fax: +1-206-287-2871. E-mail address: [email protected] (J.B. McClure).
0306-4603/02/$ – see front matter D 2002 Elsevier Science Ltd. All rights reserved. PII: S 0 3 0 6 - 4 6 0 3 ( 0 1 ) 0 0 1 7 7 - 0
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1. Introduction It is well documented that smoking and alcohol use are related (Miller & Gold, 1998; Shiffman & Balabanis, 1995). Smokers are significantly more likely to drink than nonsmokers (Shiffman & Balabanis, 1995) and 30% of smokers are alcoholics, compared to 10% of the general population (Miller & Gold, 1998). Among alcoholics, smoking prevalence is three times greater than in the general population (80–90%; Patten, Martin, & Owen, 1996). There is also a dose–response relation between drinking and smoking. Heavy drinking is associated with heavy smoking and vice versa (Batel, Pessione, Maitre, & Rueff, 1995; Burling & Tiff, 1988; Friedman, Tekawa, Klatsky, Sidney, & Armstrong, 1991). The determinants of this relation are not completely clear, but are likely to be due to a combination of environmental, cultural, psychological, and biological factors (e.g., Flay, Phil, Petraitis, & Hu, 1995; Swan, Carmelli, Rosenman, Fabsitz, & Christian, 1990; True et al., 1999). Not only is there a high comorbidity between smoking and alcohol use, but there is evidence that drinking can alter smoking behavior. In laboratory studies, drinking increases the rate and amount of smoking among smokers (Mintz, Boyd, Rose, Charuvastra, & Jarvik, 1985) and exposure to drinking cues increases urges to smoke among smoking-deprived alcoholics (Monti, Rohsenow, Colby, & Abrams, 1995). Alcoholics may also experience higher levels of nicotine withdrawal after quitting smoking (Marks, Hill, Pomerleau, Mudd, & Blow, 1997), which could subsequently increase their likelihood of relapse. Studies such as these suggest that alcohol consumption, particularly among heavier drinkers, may interfere with smoking abstinence. In fact, heavy drinkers are less likely to attempt to quit smoking and are less successful when they do try to quit (Breslau, Peterson, Schultz, Andreski, & Chilcoat, 1996; Zimmerman, Warheit, Ulbrich, & Auth, 1990), even when receiving nicotine patch therapy (Hays et al., 1999). However, most of the research in this area has been conducted with alcoholics or persons receiving treatment for alcohol or nicotine dependence. The relation between drinking and smoking abstinence has not been well evaluated in community samples. One population-based study (Nothwehr, Lando, & Bobo, 1995) failed to find an association between baseline drinking status and smoking abstinence at follow-up, but drinking was evaluated as a dichotomous variable (drinker/nondrinker). Dichotomizing alcohol consumption into drinkers and nondrinkers may obscure a dose–response relation between drinking and smoking cessation, and the amount of alcohol consumed may be a more sensitive prospective predictor of smoking cessation than whether or not one drinks any alcohol. To address these issues in a population-based sample, we conducted post hoc analyses of data from the Working Well Trial (WWT). Specifically, the present investigation examined the relation between baseline alcohol consumption and smoking abstinence. Based on evidence that there is a dose–response relation between drinking and smoking (Batel et al., 1995; Burling & Tiff, 1988; Friedman et al., 1991) and evidence that heavier drinkers are less likely to quit smoking (Breslau et al., 1996; Hays et al., 1999; Zimmerman et al., 1990), we hypothesized that higher drinking levels at baseline would be associated with shorter periods of abstinence history among current and former smokers at baseline. In addition, we hypothesized that baseline smokers’ drinking level would prospectively predict smoking abstinence at 4-year follow-up.
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2. Method 2.1. Study design The design of the WWT has been presented in detail elsewhere (Abrams et al., 1994; Sorensen et al., 1996). Briefly, the WWT was a large multisite cancer control trial conducted in 114 worksites by four study centers, a coordinating center and the National Cancer Institute. The study included a 2-year multirisk factor intervention targeting smoking, nutrition, and either occupational carcinogen exposure, smokeless tobacco (ST), or exercise, depending on the study center. Data in the present investigation were collected by The University of Texas M.D. Anderson Cancer Center from 40 worksites in the southeastern United States. Baseline information was collected during mandatory worksite meetings between September and December 1990. Follow-up surveys were conducted in the fall of 1994. Data at both time points were collected via confidential health behavior surveys completed by the employees at each of the 40 participating worksites. Each worksite had an average of 193 eligible employees (Abrams et al., 1994). 2.2. Participants 2.2.1. Baseline sample A total of 6867 participants were sampled at baseline. Of these, 5157 met the inclusion criteria for the baseline analyses in this investigation (i.e., never, current, or former smoker). Persons who did not provide information on their tobacco use (n = 479) and those reporting exclusive use of pipes (n = 38), cigars (n = 70), ST (dip, chew, or snuff; n = 891), or dual tobacco use (cigarettes and ST; n = 232) were excluded because there was insufficient information to categorize their abstinence history. Overall, participants in the baseline sample tended to be male (74%), Caucasian (87.8%), married (79.8%), and have some post-high school education (59.4%). Mean age was 39.5 years. Demographic composition by tobacco use status is presented in Table 1. 2.2.2. Longitudinal cohort More than half of the baseline sample in this study (n = 3303) also provided information on their tobacco use at follow-up. To prospectively predict smoking cessation, however, the longitudinal cohort was limited to baseline smokers (n = 728). Demographic characteristics of the cohort are presented in Table 1. 2.3. Measures 2.3.1. Tobacco use and abstinence history classification To examine alcohol consumption across groups with varying smoking histories, participants were categorized as current smokers, former smokers, or never smokers at baseline and then further subdivided based on their abstinence history. Smoking status was strictly defined to ensure proper group identification. Persons were considered to be never smokers if they
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Table 1 Demographic characteristics of baseline sample and longitudinal cohort Baseline sample
Race Caucasian African American Asian Other Males Education High school > High school Married Drink 1/month Mean age
Longitudinal cohort
Never smokers (n = 2425)
Former smokers (n = 1505)
Current smokers (n = 1227)
Current smokers (n = 728)
89.3% 8.1% 0.3% 2.4% 68.6%
93.8% 4.2% 0.1% 1.8% 84.8%
88.9% 8.8% 0.2% 2.2% 78.4%
91.6% 6.6% 0.3% 1.5% 78.8%
36.4% 63.6% 79.2% 49.0% 37.31
40.7% 59.3% 88.1% 55.1% 43.18
44.7% 55.3% 78.5% 67.7% 39.38
46.6% 53.4% 80.5% 66.2% 39.29
Based on data reported at baseline.
had not smoked more than 100 cigarettes in their life and did not currently use ST. Individuals were classified as former smokers if they had smoked at least 100 cigarettes in their life, had not smoked even a puff in the past 7 days, did not categorize themselves as a smoker, and did not currently use ST. Current smokers included individuals who had smoked at least 100 cigarettes in their life, had smoked in the past 7 days, reported that they were a current smoker, and reported no current use of ST. Based on the smoking continuum in the 1990 Surgeon General’s Report (U.S. Department of Health and Human Services (USDHHS), 1990), former and current smokers were further subdivided by quit attempt history. Minor modifications were made to the abstinence categories to adapt them to the Working Well data (e.g., ‘‘quit 3–12 months in the last year’’ was changed to ‘‘quit 4–12 months in the last year’’). Former smokers were classified based on the length of time since quitting smoking (i.e., former smoker quit >5 years, former smoker quit 1–5 years, former smoker quit 4–12 months, former smoker quit 3 months). Current smokers were classified based on the longest period of abstinence in the preceding year (i.e., quit 4–12 months in the last year, quit 1–3 months in the last year; quit 1–4 weeks in the last year; quit 2–6 days in the last year; no quit attempts in the last year). 2.3.2. Alcohol consumption Monthly alcohol consumption was calculated from quantity and frequency data for beer, wine, and liquor. Participants indicated their standard drink size for each type of alcohol (small, medium, large). A ‘‘medium’’ drink was quantified as a 12-oz beer, medium glass of wine, or 1 1/2 oz of liquor. A ‘‘small’’ beverage was calculated as 1/2 of a medium drink and a ‘‘large’’ beverage as 1 1/2 medium drinks. Participants also indicated the average number of alcoholic beverages consumed over the previous 6-month period using the following response options: never or less than one per month, 1–3 per month, 1 per week, 2–4 per
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week, 5–6 per week, 1 per day, 2–3 per day, 4–5 per day, 6+ per day. These values were converted to monthly equivalents. Because responses were based on ranges, median values for each range were used to estimate average monthly consumption for beer, wine, liquor, and combined alcohol intake (e.g., if the range were 8 to 16 drinks per month, the monthly estimate would be 12 drinks). Drink frequency was multiplied by drink size to estimate average monthly alcohol consumption. Consumption values were calculated for beer, wine, liquor, and total alcohol intake. 2.3.3. Smoking abstinence Smoking abstinence at a 4-year follow-up was defined as having not smoked even a puff in the past 7 days. 2.4. Statistical analyses Characteristics of the baseline sample and longitudinal cohort were evaluated using standard descriptive statistics. Comparisons between the tobacco use groups’ alcohol intake at baseline were conducted using chi-square and t test analyses. To test the first hypothesis that there would be a dose–response relation between baseline alcohol consumption and history of smoking abstinence, we calculated and graphed the mean level of monthly alcohol consumption for never smokers and for each abstinence history group within current and former smokers. To examine whether alcohol level increased across these groups as abstinence duration decreased, we used general linear modeling (GLM) to run regression models testing for linear and quadratic trends and adjusted for the influence of relevant demographic factors (i.e., race, gender, education, and age). To control for the randomization of the worksites in the longitudinal analyses, we conducted logistic regression analyses using generalized estimating equations (GEE; PROC GENMOD; SAS Institute, 1996) adjusting for treatment group. GEE reduces the chance of making a Type I error by adjusting the standard errors of the regression coefficient for the observed within cluster (i.e., treatment group) correlations (Liang & Zeger, 1986; Norton, Bieler, Ennett, & Zarkin, 1996). By doing this, we were able to control for the fact that the participants’ abstinence rates may have differed by treatment group.
3. Results 3.1. Baseline alcohol consumption and tobacco use A clear pattern was found between drinking and smoking status at baseline. Never smokers were less likely to drink (49.0%) than former smokers (55.1%) or current smokers (67.7%; c2 = 108.77, df = 2, P .0001). Never smokers reported the lowest level of alcohol consumption per month (M = 11.22, S.D. = 34.31), followed by former smokers (M = 14.88, S.D. = 32.82; P .001), and current smokers (M = 29.52, S.D. = 58.50; P < .0001). Among current smokers, number of cigarettes smoked per day was correlated with total alcohol
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consumption (r = .12, P < .01) and beer consumption (r = .13, P < .01), but not with amount of liquor or wine consumed. 3.2. Relation between drinking and smoking abstinence at baseline 3.2.1. Current smokers Drinking level was calculated for each subgroup of current smokers on the smoking continuum. Drinking increased linearly as the duration of recent abstinence (i.e., in the past year) decreased (see Fig. 1). This trend was significant for total alcohol intake ( F = 4.11, P < .05). A trend towards significance was also observed when testing for a linear trend across beer consumption ( F = 3.44, P = .06). No significant linear trends were found for liquor or wine and no significant quadratic trends were observed across any of the alcohol categories. All analyses adjusted for the influence of participants’ age, race, gender, and education. 3.2.2. Never and former smokers Similarly, drinking was lowest among never smokers and increased linearly across former smokers as the duration of their current abstinence decreased (see Fig. 2). Across former smokers, significant linear trends were found when analyzing total alcohol intake ( F = 18.863, P < .0001), beer ( F = 8.93, P < .01), wine ( F = 10.98, P < .001), and liquor
Fig. 1. Baseline current smokers’ mean alcohol intake by longest period of smoking abstinence in the past year.
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Fig. 2. Baseline never and former smokers’ mean alcohol intake by current abstinence history.
( F = 3.71, P .05) and relevant demographic factors were controlled. There were no significant quadratic trends across any of the analyses. 3.3. Prospective relation between drinking and smoking abstinence We hypothesized that baseline drinking would predict tobacco abstinence at follow-up in the longitudinal cohort of baseline smokers. Eighteen percent of smokers in the cohort were abstinent at follow-up. Participants who continued to smoke at follow-up drank significantly more at study intake than those who were abstinent at follow up (M = 31.78, S.D. = 62.53 vs. M = 20.94, S.D. = 36.94; P = .01). Using GEE logistic regression analyses, total alcohol consumption significantly predicted smoking abstinence after controlling for treatment group ( P < .05) and treatment group plus relevant demographic characteristics (i.e., age, race, gender, and education) ( P < .05; see Table 2). However, the relation between total alcohol consumption and abstinence only approached significance when controlling for treatment group, smoking rate (cigarettes per day), and number of quit attempts in the previous year ( P = .06), and when controlling for the combination of the demographic variables and smoking history variables ( P = .06). Beer consumption was a better predictor of prospective smoking abstinence than total alcohol consumption. It predicted smoking abstinence after controlling for treatment group ( P < .001); treatment group and relevant demographic variables ( P < .001); treatment
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Table 2 Prospective logistic regression analyses predicting smoking abstinence from baseline drinking Total alcohol consumptiona
Beera
Control variables
Parameter estimate
ORb
S.E.c
Parameter estimate
ORb
S.E.c
Treatment group Treatment group and demographicsd Treatment group and smoking variablese Treatment group, smoking variablese and demographicsd
0.005 0.004
0.99* 1.00*
0.002 0.002
0.007 0.006
0.99** 0.99**
0.003 0.002
0.004
1.00y
0.002
0.007
0.99**
0.003
0.004
1.00y
0.002
0.006
0.99**
0.002
a
Alcohol type used in each model (total alcohol intake or beer only). OR = odds ratio. c SE = standard error. d Demographics = age, race, gender, and education. e Smoking variables — cigarettes per day and number of quit attempts in the past year. * P < .05. ** P .01. y P = .06. b
group, smoking rate, and quit attempts ( P < .01), as well as the combined model ( P < .01; see Table 2). Neither wine nor liquor consumption was significantly related to follow-up smoking abstinence.
Fig. 3. Probability of quitting smoking at follow-up.
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Finally, we looked at the probability of quitting smoking at follow-up based on monthly beer consumption (see Fig. 3). Because the parameter estimates and odds ratios were relatively unchanged across each of the logistic regression models (see Table 2), the probabilities were calculated controlling for treatment group alone. The probability of quitting smoking after 4 years steadily declined as beer consumption at baseline increased. For example, compared to a person who did not drink beer, drinking one beer a day, or an average of 30 per month, decreased the probability of being abstinent by 15% (i.e., the probability of being quit declines from nearly 20% to 17%). Drinking an average of two beers a day decreased the odds of quitting by 29%, etc. Thirty-seven percent of beer drinkers in the longitudinal cohort reportedly drank 30 or more beers a month.
4. Discussion The present study looked at whether alcohol consumption is associated with smoking abstinence in a population-based sample. Unlike most of the research linking smoking and drinking, we looked at never, former, and current smokers, and included all participants, not just those seeking treatment for nicotine or alcohol dependence or those labeled as pathological drinkers. Some participants in the longitudinal investigation were exposed to a worksite intervention for smoking cessation, but the treatment did not increase abstinence rates (Sorensen et al., 1996). Nevertheless, we adjusted for this factor in the prospective analyses. Furthermore, we evaluated drinking level, as opposed to absolute drinking status. Consequently, the results of this study enhance our understanding of the association between alcohol use and smoking abstinence in the general population. We found a strong linear relation between drinking (i.e., average monthly consumption over the past 6 months) and smoking abstinence history. The amount of total alcohol consumed increased linearly as the duration of current abstinence (among former smokers) and duration of abstinence in the past year (among current smokers) decreased (see Figs. 1 and 2). Previous studies have found that drinking level does not decrease after quitting smoking (Keenan, Hatsukami, Pickens, Gust, & Strelow, 1990; Maletzky & Klotter, 1974; Nothwehr et al., 1995). If this is the case, our results suggest that persons who drink less alcohol are able to remain abstinent from smoking longer. Since these data were collected cross-sectionally, it is possible that participants reduced their drinking subsequent to quitting smoking, but we believe this is unlikely. The most plausible explanation for the linear relation between drinking and abstinence history is that drinking level itself influenced participants’ ability to remain cigarette-free. The prospective analyses appear to confirm this explanation. As hypothesized, baseline beer drinking predicted smoking abstinence after 4 years, even after controlling for treatment group, demographic characteristics (age, race, gender, education), baseline smoking rate, and number of quit attempts in the preceding year at
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intake — a gross indicator of motivation for quitting ( P < .01). Furthermore, the probability of being abstinent from cigarettes after 4 years declined steadily as baseline beer consumption increased. Controlling for treatment group alone, total alcohol consumption also predicted abstinence in our logistic regression analyses ( P < .05), but was not quite significant after controlling for the full model of treatment group, demographic characteristics, and smokingrelated variables ( P = .06). Taken together, however, the prospective analyses revealed that participants who quit smoking at follow-up drank significantly less alcohol at study initiation than those who continued smoking ( P = .01), and baseline drinking level predicted future smoking abstinence. 4.1. Study limitations There are several limitations worth noting. First, the data in this study are based on selfreport information collected in the WWT, so we do not have biochemical confirmation of smoking status or alcohol consumption. However, it is standard practice to forego biochemical smoking confirmation in community-based studies and there is evidence that this is a valid practice (Velicer, Prochaska, Rossi, & Snow, 1992). Furthermore, there is no reason to believe that deception was a significant factor in this sample. Participants were sampled in conjunction with general health behavior surveys. No special emphasis was placed on smoking or smoking cessation. The tobacco intervention was of low intensity and targeted the entire worksite. Smokers were not singled out. As a result, the social pressures to quit, or to report false abstinence, should have been low. However, if exposure to the treatment did result in a response bias towards deception, this effect would have been controlled for in the prospective analyses. Because these are secondary analyses of the WWT data, we were limited by the scope and wording of the questions on the WWT health behavior surveys. For example, we could not look at the relation between drinking and tobacco abstinence among ST users, pipe smokers, or cigar users because we did not have sufficient information on these groups’ abstinence history. Furthermore, information on alcohol consumption was assessed in ranges of drinks per day, per week, or per month. That is, some participants provided monthly estimations, some weekly, and some daily, depending on the magnitude of their intake (e.g., less than one drink per month, two to three drinks per day). To generate an equivalent scale across participants, we transformed everyone’s drinking estimates to drinks per month and used the median value of their average monthly drinking range in our analyses (e.g., if the range were 20 to 24 drinks per month, we used 22 drinks). This provides an appropriate general index of monthly consumption, but does increase the error in our alcohol measures, which could obscure the relation between drinking and abstinence. We were also constrained to point prevalence abstinence at 4-year follow-up. It is significant to demonstrate that alcohol consumption predicts abstinence after such a period, but the results would be more telling if more frequent assessments including information on continuous abstinence were available.
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Finally, the results of this study were based on a sample of predominantly white males in the southeastern United States. These findings may not generalize to groups with a more diverse sociocultural background. 4.2. Summary and conclusions In sum, the results of this study confirm and extend previous research on nicotine and alcohol. Consistent with prior work (Breslau et al., 1996; Zimmerman et al., 1990), we found that heavier drinkers were less likely to quit smoking, but we demonstrated this after a period of 4 years and among persons who were not recruited on the basis of pathological or ‘‘problem’’ drinking. Furthermore, we found a dose–response relation between current drinking and one’s historical cigarette use. To our knowledge, this is the first study to examine the relation between alcohol consumption and smoking abstinence in a sample with varying histories of cigarette use (never, former, and current smokers) and to so finely delineate the relation between drinking and abstinence duration. Together, these findings underscore our need to better understand the etiology of comorbid nicotine and alcohol use. If the causal nature of the link between these drugs is better understood, our ability to modify smoking behavior may be increased. Furthermore, these data illustrate the need for interventions which target both drinking and smoking. If consuming less alcohol increases one’s chances of quitting smoking, then smoking cessation interventions may be well served to focus more specifically on alcohol reduction, even among nondiagnostic drinkers.
Acknowledgments The Working Well Trial was funded by the National Cancer Institute (P01 CA51671). Additional support for this study was provided to the first author by the National Cancer Institute (K07 CA85603-01). A portion of the baseline results was presented at the Twentieth Annual meeting of the Society for Behavioral Medicine in San Diego, CA, March 1999. The authors would like to thank Diana Miglioretti, PhD and Lou Grothaus, M.A. for their statistical consultation on this project.
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