Investigation of mechanisms linking depressed mood to nicotine dependence

Pergamon

Addictive Behaviors. Vol. 21, No. 1, pp. 9-19, 1996 Copyright ~:: 1996 Elsevier Science Ltd Printed in the USA. All rights reserved 0306-4603/96 S15.00 + .00

SSDI 0306-4603(95)00032-1

INVESTIGATION OF MECHANISMS LINKING D E P R E S S E D M O O D TO NICOTINE D E P E N D E N C E CARYN LERMAN,* JANET AUDRAIN,* C. TRACY ORLEANS,t-: RICHARD BOYD,+ KAREN GOLD,* DAV1D MAIN,* and NEIL CAPORASO§ *Lombardi Cancer Center. Georgetown University Medical Center +Fox Chase Cancer Center SJohnson & Johnson Behavioral Technologies ~Genetic Epidemiology Branch. National Cancer Institute A b s t r a c t - The present study examined the cognitive-behavioral linkages between depressed mood and level of nicotine dependence in smokers seeking smoking cessation treatment. Prior to treatment, 202 subjects completed validated self-report measures of smoking history, depressive symptomatology, -self medication'" processes, "learned helplessness" processes, and nicotine dependence. Results revealed that 48% of the stud~ population scored in the "depressed'* range on the Center for Epidemiologic Studies (CESD) depression scale. Further. these smokers reported significantly higher levels of nicotine dependence than other nondepressed smokers. Depressed and mmdepressed smokers did not differ with respect to several cognitions related to learned helplessness theory. However, depressed smokers were more likely to report "self medication" processes (i.e.. negative affect reduction smoking and stimulation smoking). In addition, multivariable regression and path analyses suggested that negative affect reduction smoking and stimulation smoking are sequential mediators of the depression-nicotine dependence relationship. These results underscore the need to screen for depressive symptomatology among smokers seeking treatment, and to develop cessation treatments that are tailored to the needs of depressed smokers.

1 N T R O D U C T 10

N

Although significant health benefits from smoking cessation have been well-documented (Fries, Green, & Levine, 1989), efforts to promote smoking cessation on a large-scale population basis have been disappointing (Shiffman, 1993). Patientmatched cessation treatment, which involves tailoring treatment based on one or more individual difference variables, is one promising strategy for improving the success of formal smoking treatment programs (Abrams, 1993: Orleans, Glynn. Manley, & Slade, 1993). However, before tailored cessation treatments can be designed and tested, two prerequisites must be met: (a) we must identify psychological or other dimensions on which smokers can be reliably discriminated, and (b) we must elucidate the cognitive and motivational processes that maintain smoking among subgroups of smokers.

This research was supported by National Institutes of Health Grant ROI CA63562. The authors appreciate greatly the efforts of the following individuals who contributed to the data collection and management for this research: Anna Ryan MA. Irene Angel BA, Rebecca Steffens MPH, Susan Marx BS, and Ann Jones. We also would like to thank John Hughes MD and Seth Emont PhD for their very helpful comments on an earlier version of this manuscript. Requests for reprints should be sent to Caryn Lerman PhD, Associate Professor of Medicine and Psychiatry, Georgetown University Medical Center. 2233 Wisconsin Aventle, N.W., Suite 535. Washington, DC 20007.

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C. LERMAN el al.

Recent epidemiologic studies suggest that the presence of depression can be used to characterize smokers and to tailor cessation treatment (Glassman, 1993). Smokers often have a history of major depression (Glassman et al., 1990) and are more likely to commit suicide than nonsmokers (Hemenway, Solnick, & Colditz, t993). P6rezStable and colleagues (1990) found that 39% of female smokers and 22c~ of male smokers in the population scored in the depressed range on the Center for Epidemiologic Studies Depression Scale (CES-D), compared to 15% of nonsmokers. The presence of depression also is an important predictor of an individual's success with quitting smoking (Hall, Munoz, Reus, & Sees, 1993). In a national survey of about 3,000 individuals, depressed smokers had an odds of quitting that was about 40% less than nondepressed smokers (Anda et al., 1990). This may be due. in part, to greater nicotine dependence in depressed smokers. Nicotine dependence, as determined by the DSM-III-R, has been shown to be more prevalent in individuals with a history of major depression (Breslau, Andreski, & Kilbey, 1991: 1993). Despite this suggestion of a link between depressed mood and nicotine dependence, there has been little attention to the possible cognitive-behavioral mechanisms. In the absence of empirical studies, a few plausible theories have been advanced. A biologically-based hypothesis proposes that depressed persons use the nicotine in tobacco to increase their arousal and/or minimize negative affect (Carmody, 1989; Hughes, 1988; Pomerleau & Pomerleau, 1984). This ++self-medication" hypothesis is supported by evidence for effects of nicotine on neurotransmitter systems (Pomerleau & Pomerleau, 1984). Enhanced dopamine and norepine phrine release are associated with smoking-related stimulation, while release of beta-endorphin is associated with a reduction of negative affect (USDHHS, 1988). A more cognitively oriented hypothesis is derived in part from the learned helplessness theory of depression (Abramson, Seligman, & Teasdale, 1978). This theory suggests that depressed persons continue to smoke because they have less selfefficacy related to quitting (Hughes, 1988). That is, following a relapse, depressed smokers may be more likely than nondepressed smokers to conclude that they will fail at future quit attempts. However, a recent study failed to find an association between quitting self-efficacy and a history of a major depressive disorder (Hall, Munoz, & Reus, 1991). Thus, at present, support for cognitive mechanisms linking depressed mood and nicotine dependence is limited. The present paper reports on a preliminary test of the ~'self-medication" and "learned helplessness" hypotheses in a sample of smokers volunteering for a minimal contact smoking cessation research program. Using the Center for Epidemiologic Studies Depression (CES-D) Scale, subjects were characterized as having either depressed or nondepressed moods. First, we sought to determine whether there was an association between presence of depressed mood and level of nicotine dependence. We expected that persons with depressed mood would have higher levels of nicotine dependence than persons who are not depressed. In addition, we hypothesized that higher levels of nicotine dependence in depressed smokers would be mediated by self-medication behavior (i.e., negative affect reducation and stimulation smoking), rather than by cognitive factors (i.e., self-efficacy and motivation). A multivariate path analysis was conducted to explore these mechanisms linking depressed mood and nicotine dependence.

Depression and nicotine dependence

I1

METHOD

Subjects The subjects were 92 male and 1I0 female smokers ages 18-75, who responded to advertisements for a free smoking cessation trial involving a minimal contact intervention. Eligible smokers were those currently smoking at least 5 cigarettes a day. Smokers who were pregnant or who had a personal history of cancer were excluded.

Measures Background and smoking history assessment. A detailed smoking history questionnaire was administered at baseline to collect the following data: demographic characteristics (age, gender, ethnicity, marital status, and education), age at smoking initiation, prior abstinence periods, and current smoking rate.

"Learned helplessness" processes. Three Likert-style items measuring quitting self-efficacy (confidence) and quitting outcome efficacy (perceived benefits of quitling) were adapted from items used in smoking intervention outcomes research (NCI, 1986). One self-efficacy item asked " H o w confident are you that you could quit smoking for good'?" (0 = not at all to 3 = very much). This item has predicted smoking cessation in several prospective studies of self-help treatments (Orleans et al., 1991; Rimer & Orleans, 1994). The two related outcome efficacy items asked ~'In your opinion, how much would quitting smoking reduce your chances of getting lung cancer [ . . . of getting other smoking-related diseases such as emphysema, stroke and heart disease]?" (0 = not at all to 3 = very much). Readiness to quit smoking, or stage of change, was determined by responses to a single forced-choice item used successfully by DiClemente et al. (1991). Subjects were classified into one of three pre-quitting stages: (a) precontemplation--those not seriously considering quitting in the next 6 months: (b) contemplation--those seriously considering quitting in the next 6 months: (c) preparation--those planning to quit within the next 30 days and who also reported a quit attempt in the past 12 months. The stage of change construct has been validated extensively in studies of smokers and found to relate to subsequent quitting success (Lichtenstein, Lando, & Nothwehr, 1994; Prochaska, Velicer, Guadagnoli, Rossi, & DiClemente, 199t).

"Self-medication" processes. Subjects completed a modified version of the HornWaingrow Reasons for Smoking (RFS) Scale (Horn & Waingrow. 1966). For the present study, we selected two specific factors that corresponded to the self-medication hypothesis: smoking for stimulation (4 items: e.g., "'l get a definite lift and feel more alert when smoking"), and smoking for negative affect regulation (3 items: e.g., "When I feel blue or want to take my mind off cares and worries, I smoke cigarettes"). Subjects were asked to rate the statements on a Likert scale "'How much is each of the following characteristic of you" (0 = not at all to 3 - very much so). Both of these subscale factors have been shown to correlate significantly with self-monitored smoking data (Joffe, Lowe, & Fisher, 1981: Shiffman & Prange, 1988; Tate & Stanton, 1990) and have stable factor structures and satisfactory test-retest reliability (Costa, McCrae, & Bosse, 1980). In our sample, the Cronbach coefficient alpha estimates for the stimulation smoking and negative affect reduction smoking were .75 and .74, respectively.

12

c. LERMANet al.

Fagerstrom test for nicotine dependence (FTND). The FTND is a 6-item, selfreport measure of nicotine dependence derived from the Fagerstrom Tolerance Questionnaire (FTQ) (Heatherton, Kozlowski, Frecker, & Fagerstrom, 1991). Sample items include the number of cigarettes smoked in the past seven days and the average length of time from waking to smoking. The FTND scale has satisfactory internal consistency (Cronbach's alpha = .64) and high test-retest reliability (r = .88) (Pomerleau et al., 1994). The item "time until first cigarette of the day" has been shown to be a highly reliable single item index of nicotine dependency (Pomerleau, Pomerleau, Majchrzak, Kloska, & Malakuti, 1990). Center for epidemiologic studies depression (CES-D) scale. The CES-D is a 20item Likert-style scale used to assess depressive symptomatology. This scale has high internal consistency (r = .85-.90), test-retest reliability (r = .57 for 2-8 weeks), and has been shown to correlate with clinical ratings of the severity of depression (Radloff, 1977). The Cronbach coefficient alpha in our sample was .90. Procedures Subjects responding to newspaper advertisements received a short telephone screening interview to determine eligibility and received a brief description of the study and participation requirements. During an initial visit to the Smoking Clinic, all subjects completed a written consent form and the set of self-report questionnaires described above. All subjects received the minimal contact quit smoking intervention during a subsequent visit about two weeks later. The analyses described below are based on self-report data collected at the pre-treatment visit. RESULTS

Demographic and smoking behavior characteristics of study population Of the 202 subjects in the study population, 45% were male and 55% were female. The average age of subjects was 42 years (SD = 12.4). Seventy-eight percent of subjects were White, 16% were African American, and 6% were Hispanic. Forty percent were married and 79% had education beyond high school. The average FTND score in the sample was 5.3 (SD = 2.1) and 83% of subjects reported having a cigarette within 30 minutes after waking, indicating a moderate level of nicotine dependence. On average, subjects initiated smoking at age 16 years (SD = 4) and smoked 22 cigarettes per day (SD = 11).

Comparison of depressed and non-depressed smokers on demographic' and smoking variables The average CES-D score in the study sample was 16 _+ 10. Overall, 48% (n = 97) scored above the depression cutoff (16 or greater) on the CES-D scale, compared to 21% in the general population (Radloff, 1977). Twenty-three subjects (11%) were on antidepressant medication (14% of depressed subjects and 9% of nondepressed subjects). As shown in Table 1, subjects who had education beyond high school were significantly less likely to have depressed mood than those with less education (Chi Sq = 5.2, p = .02). White subjects were less likely to have depressed mood than nonwhites (Chi Sq = 3.9, p = .05). Depression was not associated with age, gender, or marital status. Depressed smokers had significantly higher scores on the continuous FTND scale than nondepressed smokers (5.6 vs. 4.9, T = -2.1, p = .04). In addition, depressed

Depression and nicotine dependence

13

Table 1. C o m p a r i s o n of d e p r e s s e d vs. n o n d e p r e s s e d s m o k e r s on demographic variables Measure Age 18-39 40-59 60 + Ethnicity White Non-white Education -< High school > High school Gender Female Male Marital Status Married Unmarried

% depressed

Chi square

P Value

43% 48c/c 9c/c

1.7

ns

45% 61c~

3.9

.05

64% 43c~

5.2

.02

49% 46cA

.17

ns

4557c 51%

.77

ns

and nondepressed smokers differed significantly in the length of time to their first cigarette in the morning; 45% of depressed smokers had a cigarette within 5 minutes of waking, compared to 31% of nondepressed smokers (Chi square = 5.1, p = .05). Depressed and nondepressed smokers did not differ significantly in the age at smoking initiation, current smoking rate or longest abstinence period.

Comparison of depressed and non-depressed smokers on "learned helplessness" and "self-medication"variables As shown in Table 2, none of the "learned helplessness ~' variables differed significantly between depressed and nondepressed smokers. Depressed and nondepressed

Table 2. C o m p a r i s o n of d e p r e s s e d and n o n d e p r e s s e d s m o k e r s on ' l e a r n e d h e l p l e s s n e s s " and "self-medication w~riables'"

Measure " L e a r n e d h e l p l e s s n e s s " variables Quitting self-efficacy c/c quite a bit/very confident Quitting o u t c o m e efficacy % believe quitting reduces cancer risk very m u c h C~- believe quitting reduces other disease risks very much Quitting motivation % preparation stage of change

Depressed 01 = 97)

Nondepressed (n = 105)

Chi square

p value

36C;

48C;2

.II

ns

630;

59¢5

.57

n,

77'/c

79(;;

.86

ns

50(,4

5()5~

.4g

ns

M

SD

M

SD

Z* I

"'Self-medication" variables Stimulating s m o k i n g Negative affect reduction smoking

10.5 9.7

3.2 2.0

9.6 8.9

3.3 2.3

1.9

2.3

.06 .02

*Wilcoxon Rank S u m T e s t s were performed due to ordinal scaling. Identical results were obtained with, /-tests.

14

C. L E R M A N et al.

smokers reported similar levels of self-efficacy, outcome efficacy, and quitting motivation. Overall, fewer than one-half of smokers felt at least "quite a bit" confident that they could quit smoking. Most, but not all, smokers believed that quitting smoking would reduce their risk of cancer and other diseases. Exactly one-half of depressed and nondepressed smokers were in the preparation stage of quitting motivation (i.e., planning to quit in the next 30 days). By contrast, both "self-medication" variables exhibited the expected associations with depression. As shown in Table 2, smokers with depressed mood tended to have higher scores on the stimulation smoking subscale (Z = 1.9, p = .06) and scored significantly higher than nondepressed smokers on the negative affect reduction smoking subscale (Z = 2.3, p -- .02). Factors associated with nicotine dependence: Bivariate associations

In order to identify variables to consider in the multivariable models of nicotine dependence, we examined the bivariate associations of demographic, learned helplessness, and self-medication variables with FTND scores. Only race and education were even marginally associated with nicotine dependence. Specifically, FTND scores were higher for smokers with a high school education or less compared to those with education beyond high school (5.8 vs. 5.0, respectively, p = .04), and for smokers who were White compared to non-White (5.4 vs. 4.5, respectively, p = .08). Thus, both education and ethnicity were controlled in the multivariate analysis described below. Stimulation smoking ( r - .30, p < .001) and negative affect reduction smoking (r = . 18, p = .07) both correlated positively with FTND scores. Models to test f o r mediation

Linear regression models were used to examine the independent effects of depression and self-medication variables on nicotine dependence. As shown in Table 3, after controlling for education and race, depression contributed significant incremental variance to the model; however, depression accounted for only 3% of the variance. In a second model, the self-medication variables (negative affect reduction and stimulation smoking) were entered following education and race. Together, these variables contributed an additional 7% of the variance in nicotine dependence. Depression scores contributed another 2% of variance above the demographic and selfmedication variables (R 2 for complete model = . 14, p = .0001).

Table 3. Linear regression models of nicotine dependence Incremental R2

Cumulative R-"

P value

Model 1 Education Race Depression

.017 .026 .029

.017 .043 .072

.07 I .026 .003

Model 2 Education Race Negative affect Stimulation Depression

.017 .026 .033 .040 .020

.017 .043 .076 .116 .136

.07 I .026 .002 .0001 .0001

Depression and nicotine dependence

15

A series of path analyses (Pedhazur, 1982) were considered to explore further the mechanisms linking depression (CES-D) and nicotine dependence (FTND). Before examining the models, it is useful to recall that a mediating variable is defined by the following relationships: (1) the predictor (e.g., CES-D) is related significantly to the mediating variable (e.g., negative affect, stimulation) and the criterion (e.g., FTND), (2) the mediator is significantly related to the criterion; and (3) when controlling for the mediating variable, the previous relationship between the predictor and the criterion is greatly reduced or nonsignificant. The complete path model is shown in Figure 1. Controlling for education and race throughout, the complete model is characterized both by a direct effect of depression on nicotine dependence and by several indirect effects via intermediate variables. This complete path model accounts for twice as much variation in the nicotine dependence variable as a regression that only included depression as a predictor variable (see Table 3; R: = .14, compared to R e - .07). While neither negative affect smoking nor stimulation smoking individually mediate the relationship between depression and nicotine dependence, there is a more complex process of mediation. Using the criteria described above, we found that negative affect smoking mediates the relationship between depression and stimulation smoking. Further, stimulation smoking mediates the relationship between negative affect smoking and nicotine dependence. Through the introduction of this mediating sequence, we found that the direct effect of depression on nicotine dependence was reduced (beta = . 15, p = .04), as compared to the direct effect of depression on nicotine dependence in the regression model (beta = . 18, p = .01). In the complete path model, depression maintains a direct effect on nicotine dependence (beta = .15, p = .04). Also, depression influences nicotine dependence indirectly via the sequence of self-medication variables. Using the path coefficients, we can partition the relationship between depression and nicotine dependence (as reflected by their correlation) into direct, indirect and spurious effects, Accordingly, 82% of the correlation between depression and nicotine dependence is accounted for by the direct effect of depression on dependence (as well as the effects of unmea-

CES-D = Center for Epidemiologic Studies Depression Scale NEGAFF = Negative Affect Reduction Smoking STIM = Stimulation Smoking FTND = Fagerstrom Test for Nicotine Dependence

NEGAFF

+/

~

150 + STIM

,

CES-D .15

FTND

*

Fig. 1. Path model of depression, self-medication smoking, and nicotine dependence. • Represents a statisticallysignificantpalh (beta) coefficient.

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C. LERMAN et al.

sured variables). The remaining 18% is accounted for by the indirect effect of depression on nicotine dependence, as mediated by negative affect and stimulation smoking. It should be noted that other explanations for the proposed mediation between depression and nicotine dependence were considered. Occasionally, phenomena such as disparate reliabilities between a predictor and mediator variable can indicate a statistical artifact such as multicolinearity, rather than a substantive phenomenon. Since both stimulation smoking and negative affect smoking have Cronbach's alpha reliabilities of .75 and .74, respectively, and their correlation is less than .5, this possibility was ruled out. Nonetheless, a longitudinal study is necessary to determine whether these processes are causal. DISCUSSION

The present study was undertaken to examine the linkages between depressed mood and level of nicotine dependence in smokers volunteering for smoking cessation treatment. Confirming past findings, the results show a relatively high prevalence of depressive symptomatology in this population (Glass, 1990; Glassman et al., 1988). Almost one-half of the present sample scored in the depressed range of the CES-D scale. However, since the current sample was self-selected for an individual smoking treatment program, the rate of depressive symptoms might be inflated relative to that of smokers in the general population. This investigation furthers our understanding of the relationship between depression and smoking behavior by revealing a positive relationship between the presence of depressive symptoms and degree of nicotine dependence. In fact, almost one-half of the depressed smokers reported smoking within five minutes of awakening, compared to only a third of nondepressed smokers. This is consistent with a greater level of dependency in depressed smokers (Pomerleau et al., 1990). While a previous study showed a positive association between major depression and nicotine dependence (Breslau et al., 1991), the present study extends this finding to mild depressive symptoms that are more prevalent in the general population. The present investigation also furnishes suggestive new evidence concerning the importance of specific factors linking depression and nicotine dependence. Depressed and nondepressed smokers did n o t differ with respect to several cognitions, including quitting self-efficacy, outcome efficacy (the perceived health benefits of quitting) and stage of change (quitting motivation). Thus, we did not find support for the hypothesis that learned helplessness processes underlie the relationship between depression and nicotine dependence. While such a relationship may exist, a more comprehensive assessment may be required to evaluate this systematically. For example, cognitions more proximal to the quit attempt (e.g., during withdrawal) may differentiate depressed and nondepressed smokers. In contrast, present results appear to provide tentative support for the '~self medication" hypothesis (Hughes, 1988; Khantzian, 1985). Common measures of negative affect reduction and stimulation smoking (Horn & Waingrow, 1966) differentiated depressed and nondepressed smokers. Moreover, regression and path analyses suggested that these variables may be sequential mediators of the relationship between depression and nicotine dependence; however the effect sizes, although significant, were rather small. Nonetheless, the results suggest that higher levels of depression correspond to higher levels of negative affect smoking. Negative affect smoking, in

Depression and nicotine dependence

17

turn, relates to higher levels of stimulation smoking which, in turn, corresponds to higher levels of nicotine dependence. Thus, the path analysis suggests a two-step mediation process in which two selfmedication variables (negative affect regulation and stimulation smoking) explain, in part, the link between depression and nicotine dependence. One interpretation of this finding is that depressed smokers may find that smoking reduces negative affect (negative reinforcement), including the negative affect associated with nicotine withdrawal (Hall et al., 1991). Experiencing this benefit, they then engage in stimulation smoking to gain more frequent positive reinforcement. This is consistent with Schuster's (1993) recent analysis of tobacco addiction which highlights the vulnerability of depressed smokers to negative reinforcement (e.g., negative affect reduction) and positive reinforcement (e.g., stimulation smoking). Regardless of how negative affect reduction and stimulation smoking may be linked in the relationship between depression and nicotine dependence, the present results would suggest that greater attention be given to both factors in treatments aimed at smokers who suffer from depressed mood. Results from a randomized trial of a ~'mood management" intervention provide support for the benefits of interventions designed to reduce negative affect. Among smokers who reported a history of major depressive disorder, mood management produced significantly higher @month quit rates than a health motivation control condition (50% vs. 12%, respectively) (Hall et al., 1993). The results of the present investigation suggest that cognitivebehavioral interventions that incorporate strategies to elevate arousal, in addition to mood, might yield additional benefits. For example, physical activity might be used to create the pleasurable stimulation produced by nicotine and, thereby, may improve quit rates (Marcus, Albrecht. Niaura, Abrams, & Thompson. 1991). Physical activity increases the circulation of blood and oxygen throughout the body which has a stimulating effect. In addition, physical activity appears to affect mood through its impact on endorphins and catecholamines ~Siever & Davis, 1985: Thor~n et al., 1990). It should be noted that the results of the present study also provide support for the existence of other pathways linking depressed mood to nicotine dependence. In fact, the larger proportion of the variance in nicotine dependence (82%) was accounted for by a ~'direct effect" of depression on nicotine dependence. This ~"effect" includes all of the other unmeasured mechanisms, as well as the ~'true" direct effect of depression. Deficiencies in social support are one example of an unmeasured factor which may mediate the relationship between depression and nicotine dependence (Hughes, 1988). For example, due to limitations in interpersonal functioning, depressed smokers may not have the benefit of social support to enhance their quitting efforts (Coppotelli & Orleans, 1985; Mermelstein, Cohen, Lichtenstein, Baer, & Kamarck, 1986). Alternatively, both depression and nicotine dependence might be influenced by a third variable, such as socioeconomic status (Schuster. 1993). Another plausible hypothesis is that depression and nicotine dependence may result from the same genetic predisposition (Hughes, 1988). A recent study of female twins suggests that a common inherited susceptibility may predispose some individuals to both smoking and to major depression (Kendler et al., 1993). In sum, there is much fertile ground for future study of the linkages between depression and nicotine dependence and for the exploration of the underlying cognitive-behavioral processes. Present results add to past research underscoring the need to screen for depressive symptomatology among smokers seeking treatment.

18

C. LERMAN et al.

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Depression and nicotine dependence

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