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Weight control smoking among sedentary women
Addictive Behaviors, Vol. 24, No. 1, pp. 75–86, 1999 Copyright © 1998 Elsevier Science Ltd Printed in the USA. All rights reserved 0306-4603/99/$–see front matter
Pergamon
PII S0306-4603(98)00034-3
WEIGHT CONTROL SMOKING AMONG SEDENTARY WOMEN BERNARDINE M. PINTO, BELINDA BORRELLI, TERESA K. KING, BETH C. BOCK, MATTHEW M. CLARK, MARY ROBERTS, and BESS H. MARCUS The Miriam Hospital and Brown University School of Medicine
Abstract — This study examined characteristics associated with weight control smoking among 281 sedentary women enrolled in a smoking cessation trial. A series of regression models were developed to identify predictors of weight control smoking as measured by the Smoking Situations Questionnaire. Predictor variables included demographic variables, dietary intake, weight gain following previous quit attempts, dietary restraint, self-efficacy for weight management, smoking behavior, exercise behavior, negative affect and psychological constructs relevant to smoking cessation, and exercise adoption. In the final predictor model, anticipation of weight gain in the current quit attempt, higher dietary restraint, younger age, greater Fagerstrom scores, greater number of pounds gained in previous quit attempts, and lower levels of self-efficacy to manage weight in negative affect situations were associated with smoking for weight control. Treatment implications for women who smoke for weight control reasons are discussed. © 1998 Elsevier Science Ltd
Women who smoke cigarettes are at increased risk for cardiovascular disease, stroke, cancer, and osteoporosis, which are the major causes of death and disability among American women (Ockene, 1993; USDHHS, 1989). Although smoking prevalence among women has been declining over the past 25 years, cessation rates among women lag behind those among men (Fiore et al., 1989; USDHHS, 1994). One important reason why women smokers do not attempt and/or succeed at quitting smoking is the concern about postcessation weight gain (Pirie, Murray, & Luepker, 1991; Camp, Klesges, & Relyea, 1993). The relationship of weight concern to smoking status has been assessed with both cross-sectional and prospective designs, with cross-sectional designs yielding predominantly positive associations between smoking-specific weight concern and smoking (Camp et al., 1993; Klesges et al., 1988b; Weekley, Klesges, & Reylea, 1992), and prospective designs showing little or no association between smoking-specific weight concerns and smoking (Borrelli, Mermelstein, & Shadel, 1995; French, Jeffery, Pirie, & McBride, 1992). These mixed findings may be due to the fact that, in the cross-sectional studies, smokers are not trying to quit smoking. Additionally, these inconsistencies may be the result of varying conceptualizations and measures of weight concerns such as dietary restraint (French et al., 1992), smoking-specific weight concern This project was supported in part through grants from the National Cancer Institute (KO7CA01757 and R29CA59660) and a supplement to R29CA59660 from the Office of Research on Women’s Health, to Dr. Marcus. We acknowledge and thank David Abrams, PhD, Anna Albrecht, RN, MS, and Alfred Parisi, MD, for their contributions to this trial. We thank Regina Traficante, MA, and Janice Tripolone, BS, for their numerous contributions to the implementation of this study. We also thank Barbara Doll for her help in manuscript preparation. The work was carried out at The Miriam Hospital, 164 Summit Ave., Providence, RI 02906. Requests for reprints should be sent to Bernardine M. Pinto, PhD, Assistant Professor of Psychiatry and Human Behavior, The Miriam Hospital, and Brown University School of Medicine, 164 Summit Ave., Providence, RI 02906. 75
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(French et al., 1992), general weight concern (Klesges et al., 1988b), smoking for weight control (Camp et al., 1993; Pomerleau et al., 1993, Weekley et al., 1992), perceived risk and seriousness of weight gain following smoking cessation (Borrelli et al., 1995; Pirie et al., 1991; Klesges et al., 1988a; Streater, Sargent, & Ward, 1989), current dieting, dieting history, and personal weight preferences (French, Jeffery, Klesges, & Forster, 1995), fear of, and preoccupation with, body weight and weight gain (French, Perry, Leon, & Fulkerson, 1994; Gritz, Berman, Read, Marcus, & Siau, 1990), and finally, some studies do not specify how weight concern was measured (Pirie et al., 1992). Therefore, it has become increasingly difficult to draw conclusions from the literature regarding the association between smoking-related weight concern and smoking cessation (French & Jeffery, 1995). In the present paper, we defined smoking-related weight concern as smoking for weight control (Weekley et al., 1992), and we assessed demographic factors, dietary intake, smoking, and exercise variables that may be associated with smoking for weight control in women enrolled in a smoking cessation trial (Marcus, King, Albrecht, Parisi, & Abrams, 1997). While a few studies have found that smoking for weight control was associated with greater weight gain during previous quit attempts, lower education, and higher dietary restraint (Pomerleau et al., 1993; Weekley et al., 1992), these characteristics have not been examined among women enrolled in a smoking cessation program. Identifying the predictors of women who smoke for weight control is important for two reasons. First, there probably is a constellation of characteristics that is related to smoking for weight control which inhibit smoking cessation such as higher levels of dietary restraint and higher levels of nicotine dependence. Second, smoking for weight control itself may be an important barrier to quitting, suggesting the need for tailored treatments for this subgroup of smokers to enhance quit rates. This paper extends the literature by examining variables relevant to weight control smoking such as dietary intake and exercise behavior in women who have volunteered to participate in a smoking cessation trial. We examined the dietary habits of this subsample of women smokers because these data may help design appropriate weight-management interventions for women smokers concerned about postcessation weight gain. Our hypothesis was that lower caloric consumption would be associated with higher levels of weight control smoking since dietary restraint has been associated with weight control smoking (Camp et al., 1993) and, dietary restraint has been shown to be higher in women smokers (Weekley et al., 1992). Additionally, lack of control over eating or disinhibition has been found to predict weight gain after smoking cessation (Duffy & Hall, 1988). To identify the situations in which weight control smokers report difficulty in managing food intake, we included a measure of self-efficacy for weight management (Clark, Abrams, Niaura, Eaton, & Rossi, 1991). We expected that low efficacy for controlling eating would be associated with weight control smoking. This study also explored the relationship of weight control smoking to psychological mediators of smoking cessation (e.g., pros and cons for smoking, and self-efficacy for smoking cessation) and exercise adoption (e.g., pros and cons, and self-efficacy). We hypothesized that weight control smokers would endorse more advantages (pros) than disadvantages of smoking (cons) and have less confidence in their ability to quit smoking. Exercise is an effective method of weight management when combined with dietary changes, and women smokers who are concerned about postcessation weight gain may be more favorably disposed toward exercise. The smoking cessation trial of-
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fered an exercise program to those in the intervention group; hence, we expected that enrollees would favor exercise participation. This bias notwithstanding, we expected that higher levels of smoking for weight control would be associated with greater endorsement of the pros of exercise. We also hypothesized that negative affect would be associated with greater smoking for weight control. Dysphoric mood and/or depressive states have been associated with eating-disordered behaviors and high levels of dietary restraint (Kuehnel & Wadden, 1994; Ruderman, 1986). Furthermore, negative affect has been linked to smoking among women (Abrams et al., 1987; Sorenson & Pechacek, 1987). Women who report higher levels of negative affect may eat more to assuage negative affect (Wurtman, 1993) and either smoke to offset this greater eating, or smoke as a food substitute. In sum, in studying the characteristics of women who smoke to control weight, we hypothesized that lower caloric consumption, higher dietary restraint, and lower efficacy for weight management would be associated with smoking for weight control. Additional hypotheses were that higher pros for smoking, lower self-efficacy for smoking cessation, and higher pros for exercise adoption would be associated with smoking for weight control. Finally, we hypothesized that greater negative affect would be associated with smoking for weight control. M E T H O D
Data for the present investigation comprise part of the baseline data from a larger study designed to compare the efficacy of a 12-session cognitive-behavioral smoking cessation treatment plus supervised vigorous exercise with the same cessation treatment plus contact control (Marcus et al., 1997). Participants Participants were 281 women who completed pretreatment measures as described elsewhere (Marcus et al., 1997). The study population consisted predominantly of White (92.1%) middle-aged (M 5 40.2) women (see Table 1). Seventy-six percent of the subjects were employed and 55.2% were married. The median household income level was in the $30,000 to $39,999 range. Subjects weighed an average of 147.7 lb (SD 5 30.3). The average Body Mass Index (BMI) was 25.4 (SD 5 5.0), and the average percent body fat was 29.9 (SD 5 7.2). Subjects reported smoking on average 22.2 (SD 5 9.3) cigarettes per day. Procedure Healthy sedentary women (18–65 years) smokers ($10 cigarettes per day for a minimum of 3 years) were recruited through newspaper advertisements. Exclusionary criteria included medical problems and/or medications that would make compliance with the study protocol difficult or dangerous. Women with a current psychiatric illness, alcoholism, alcohol abuse, or other substance abuse were also excluded. Subjects agreed to be assigned randomly to either of the two investigational conditions and provided written informed consent to participate in the research procedures. Measures The following measures were used to assess weight control smoking, dietary restraint, smoking, and exercise variables. Psychometrics are reported as available for each instrument.
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Table 1. Demographics and smoking history of participants in the Commit to Quit trial Variable Age (years) Baseline weight (pounds) Body Mass Index (BMI) Base VO2 estimate (ml/kg*min) Baseline total daily METS Number of cigarettes/day Carbon monoxide (ppm) Fagerstrom score Baseline CES-D score Baseline T–MAS score Smoking situations questionnaire
N
Mean
SD
281 277 275 277 235 269 263 281 277 280 277
40.16 147.67 25.41 24.97 44.87 22.19 17.44 6.27 12.33 6.47 17.30
8.92 30.30 4.99 5.09 9.35 9.34 10.16 1.91 9.14 4.27 7.17
Variable Race Occupation Employment status Marital status Education level Income level
Percent Caucasian White collar Employed Married/Living together HS Graduate or higher $$20,000/year
91.8 55.7 76.0 55.2 95.7 80.1
Weight-control smoking. The Smoking Situations Questionnaire (SSQ; Weekley et al., 1992) is a 6-item instrument used to measure the extent to which subjects smoke for weight control reasons. The SSQ appears to be a unidimensional measure with adequate internal consistency (alpha 5 .76) and stability (test-retest r 5 .95; Weekley et al., 1992). The scores range from 6 to 36. Higher scores indicate a greater degree of smoking for weight control. Dietary variables. The Revised Restraint Scale (RRS; Herman & Polivy, 1980) was used to measure dietary restraint. This 10-item questionnaire was designed to identify chronic dieters who restrain their eating and inhibit caloric intake. Psychometric evaluations of the RRS have yielded adequate measures of internal consistency for nonobese individuals (alpha 5 .83). Test-retest reliability over a 1-week period is .93 (Kickham & Gayton, 1977). The Weight Efficacy Life-Style Questionnaire (WEL; Clark et al., 1991) consists of 20 Likert-type items that ask subjects to rate their self-efficacy for controlling their eating in various situations. The WEL has five subscales (four items each): Negative emotions, Availability, Social pressure, Physical discomfort, and Positive activities. Cronbach’s alphas for the subscales among obese populations range from .79 to .88, demonstrating adequate internal consistency. Higher scores indicate greater levels of self-efficacy for weight management. The Food Frequency Questionnaire (FFQ; Block et al., 1986), a valid and reliable measure (Zulkifli & Yu, 1992) was used to assess dietary intake and total caloric consumption. The FFQ consists of a list of food items for which average frequency of consumption is determined in reference to a specified time period, defined in this study as 1 month. Subjects were also asked questions about their maximum body weight as an adult, the amount of weight gain after their last quit attempt, and the amount of anticipated weight gain with the present cessation effort. Body weight and height were measured on a calibrated scale (Detecto medical scale) to the nearest quarter pound and the
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nearest quarter inch, respectively. Body fat was estimated from skinfold thickness measured on the right side at the triceps, suprailiac crest, and thigh (Jackson, Pollock, & Ward, 1980). Smoking measures. These included daily smoking rate and number and duration of previous quit attempts. Nicotine dependence was assessed through the Fagerstrom Tolerance Questionnaire (FTQ; Fagerstrom, 1978). Carbon monoxide levels were measured using a carbon monoxide analyzer. The number of withdrawal symptoms during previous quit attempts (from among 16 symptoms) were assessed using DSMIII-R criteria (American Psychiatric Association, 1987). A short version of the previously developed Smoking Abstinence Self-Efficacy scale (SASE; DiClemente, Prochaska, & Gibertini, 1985) assessed the smoker’s level of confidence to refrain from smoking in nine challenging situations. The various forms of this self-efficacy measure have demonstrated good internal consistency (Cronbach alpha 5 .88–.92) and both construct and predictive validity (DiClemente et al., 1991). High scores indicate high levels of efficacy for abstinence. A short 6-item version of the smoking decisional balance scale (Velicer, DiClemente, Prochaska, & Brandenburg, 1985) measured positive and negative attitudes relating to smoking. The pros and cons scales have demonstrated good concurrent and predictive validity (DiClemente et al., 1991). In our sample, Cronbach alphas for the pros and cons scales were .69 and .57, respectively. High scores on the pros scale indicate perception of high benefits from smoking (this scale does not include an item on smoking-related weight control benefits), and high scores on the cons scale indicate perception of high costs of smoking. A decisional balance score (ratio of pros to cons) was not computed to avoid assuming equal beta weight for the pros and cons in the regression analyses. Exercise measures. A 5-item measure of self-efficacy for exercise participation was administered (Marcus, Selby, Niaura, & Rossi, 1992b). A 5-point scale was used to rate each item ranging from not at all confident (1) to extremely confident (5). This scale has good internal consistency (Marcus et al., 1992b), and in this sample the Cronbach alpha was .80. High scores indicate a high level of self-efficacy for exercise. A 16-item decisional balance measure for exercise was administered (Marcus, Rakowski, & Rossi, 1992a). Higher scores on the “pro” scale indicate perceptions of high benefits from exercise (the scale does not include any items on weight control benefits of exercise); high scores on the “con” scale indicate perceptions of high costs of exercise. Internal consistency for the pros and cons of exercise for this sample were .92 and .73, respectively. A decisional balance score (ratio of pros to cons) was not computed. We assessed exercise behavior via a self-administered version of the Seven-Day Physical Activity Recall (7-Day PAR; Blair et al., 1985) to determine if smoking to control weight was associated with greater levels of exercise participation. The 7-Day PAR yields metabolic equivalents (MET values) for varying intensities of exercise. It is a valid (Blair et al., 1985) and a reliable measure of habitual physical activity (Sallis et al., 1985). Mood measures. The Center for Epidemiologic Studies Depression Scale (CES-D) was used to measure depressive symptoms. This 20-item scale has been widely used and extensively validated (Weissman, Sholomskas, Pottenger, Prusoff, & Locke, 1977). Coefficient alphas ranging from 0.84 to 0.90 have been reported for the CES-D
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in clinical trials (Radloff, 1977). The 20-item version of the Taylor Manifest Anxiety Scale (TMAS) was used to assess trait anxiety (Bendig, 1956; Taylor, 1953). Data analyses We computed a series of stepwise multiple regression models with smoking for weight control as assessed by the SSQ as the dependent variable (Weekley et al., 1992). The goal was to assess which variables predict smoking for weight control based on a priori hypotheses, and to determine the best predictor(s) for smoking for weight control. In each model, age and BMI were forced, respectively, into the equation prior to other independent variables because these variables have been shown to be related to higher levels of smoking-specific weight concern (Klesges et al., 1989). We divided the independent variables into conceptually distinct groups (e.g., dietary intake, dietary restraint, smoking variables, exercise variables), conducted tests of multicollinearity within each group, and then computed separate stepwise multiple regression models. Finally, a regression equation using the backward elimination procedure (Myers, 1990) was conducted utilizing significant predictors from the previous models.
R E S U L T S
Demographic factors In the stepwise multiple regression model, demographic variables such as race, occupation, marital status, and education did not significantly enter the model over and above age and baseline BMI, which were forced into the equation first and second, respectively. Both age and BMI significantly entered the model (F 5 10.2, df 5 2,268, p , .0001), such that older age was associated with lower levels of smoking for weight control (b 5 .14) and greater BMI was associated with higher levels of smoking for weight control (b 5 .30). Age and BMI accounted for 7% of the variance in smoking for weight control. Dietary intake In the stepwise multiple regression model, total caloric consumption did not enter significantly into the model after baseline age and BMI were forced into the model. Dietary restraint Dietary restraint (Revised Restraint Scale) significantly entered into the stepwise multiple regression model (over and above age and BMI) and contributed to 14% of the variance. As hypothesized, higher levels of dietary restraint (b 5 .51) were associated with a greater degree of smoking for weight control (F 5 23.34, df 5 3,263, p , .0001). The model accounted for 21% of the variance in smoking for weight control. Self-efficacy for weight management We entered the WEL subscales into a stepwise multiple regression model, after controlling for baseline age and BMI. The negative emotion subscale significantly entered the model after age and BMI, accounting for 10.3% of the variance. These three variables accounted for 16% of the variance in smoking for weight control (F 5 15.6, df 5 3,239, p , .0001). Lower levels of self-efficacy to control eating during negative affect situations were associated with higher levels of smoking for weight control (b 5 2.30).
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Smoking cessation attempts and weight gain The stepwise multiple regression model included the following variables in addition to age and BMI: previous quit attempts (yes/no), weight gain during previous quit attempts (yes/no), number of pounds gained during previous quit attempts, anticipation of weight gain during the current quit attempt (yes/no) and the number of pounds of anticipated weight gain during the current quit attempt. The number of pounds gained during previous quit attempts (b 5 .21), and anticipation of weight gain (yes/no) in the current quit attempt (b 5 3.68) (F 5 16.2, df 5 4,266, p , .0001) significantly predicted smoking for weight control (above and beyond age and BMI). The number of pounds gained at previous quit attempts contributed to 8.5% of the variance, and anticipation of weight gain contributed to 3.9% of the variance. Higher levels of smoking for weight control were related to a greater amount of weight gained during previous quits and anticipation of weight gain in the current quit attempt. This model accounted for 20% of the variance in smoking for weight control. Smoking variables In the stepwise regression model with smoking variables as predictors, the following variables were included: the Fagerstrom score, number of withdrawal symptoms during previous quit attempts, carbon monoxide level, average daily smoking rate, duration of the longest prior quit attempt, duration of the most recent quit attempt, number of 12-hour quit attempts, and number of 24-hour quit attempts. The Fagerstrom, the number of withdrawal symptoms during past quit attempts, and the number of days in the most recent quit attempt significantly predicted smoking for weight control over and above age and BMI (F 5 8.4, df 5 5,225, p , .0001). Higher scores on the Fagerstrom (b 5 .65), greater number of self-reported withdrawal symptoms during past quit attempts (b 5 .37), and greater number of days in the most recent quit attempt (b 5 .003) were associated with greater levels of smoking for weight control. Fagerstrom scores contributed to 3.7% of the variance, number of withdrawal symptoms during past quit attempts accounted for 2.4% of the variance, and the number of days in the most recent quit attempt contributed to 1.7% of the variance. The total model accounted for 16% of the variance. Self-efficacy for smoking, and pros and cons for smoking In a stepwise multiple regression model that included the pros of smoking, the cons of smoking, and self-efficacy for quitting smoking, only the pros of smoking significantly predicted smoking for weight control over and above age and BMI (F 5 10.3, df 5 3,254, p , .0001), such that higher scores on the pros of smoking were related to a higher level of smoking for weight control (b 5 1.53) and contributed to 4.5% of the variance. Age, BMI, and pros of smoking accounted for 10% of the variance. Exercise variables We computed a stepwise multiple regression model with the following baseline variables: self-efficacy for exercise adoption, pros and cons for exercise adoption, and METS from the 7-Day PAR. The pros of exercise adoption (b 5 1.43) was the only variable to enter the model over and above age and BMI (F 5 10.3, df 5 3,220, p , .0001) with higher pros for exercise associated with greater smoking for weight control, and accounting for 2.3% of the variance. Age, BMI, and pros for exercise contributed to 12% of the variance.
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Mood measures We computed a stepwise multiple regression model with the following measures of negative affect as independent variables: CES-D (depression), and TMAS (anxiety). Scores on the TMAS significantly predicted smoking for weight control over and above age and BMI (F 5 11.1, df 5 3,263, p , .0001), such that higher scores on the TMAS were associated with greater likelihood of smoking for weight control (b 5 .33) accounting for 3.8% of the variance. Age, BMI, and TMAS scores contributed to 11% of the variance. CES-D scores did not significantly enter the equation. Final prediction model To determine the strongest predictors of smoking for weight control, we computed a final stepwise regression model that included all of the significant predictors from the previous models (Table 2). We used a backward elimination procedure to enter the following procedures: age, BMI, dietary restraint, scores on the negative emotion subscale of the WEL, anticipation of weight gain (yes/no), number of pounds gained during previous quit attempts, Fagerstrom scores, number of withdrawal symptoms during previous quit attempts, number of days in the most recent quit attempt, pros of smoking, pros of exercise adoption, and the TMAS scores. The only variables to significantly enter the stepwise model were anticipation of weight gain in the current quit Table 2. Smoking for weight control: Results of stepwise regression analysisa Modelb Demographics Dietary restraint Managing food Consumption Smoking Constructs Exercise Constructs Smoking Cessation Attempts
Weight concerns
Mood
aTable
Variables
B
R2D
FD
df
p,
BMI Age BMI Age Dietary restraint BMI Age WEL Negative Emotions BMI Age Smoking pros BMI Age Exercise pros BMI Age Fagerstrom score No. of withdrawal symptoms No. of days recent quit BMI Age No. lb gained at prior quit Anticipation of weight gain BMI Age TMAS
0.295 20.139 20.023 20.128 0.511 0.124 20.141 20.296
0.0417 0.0294
11.713 1.464
1,269 1,268
.001 .001
0.0718 0.1384
10.215 13.123
2,264 1,263
.001 .001
0.0604 0.1037
7.717 7.925
2,240 1,239
.001 .001
0.0684 0.0455
9.732 1.577
2,265 1,264
.001 .001
0.0997 0.0236
12.238 1.922
2,221 1,220
.001 .001
0.0782 0.0375 0.0241
9.667 0.23 0.716
2,228 1,227 1,226
.001 .001 .001
0.003
0.0175
0.782
1,225
.001
0.259 20.181 0.211
0.0711 0.0854
10.249 6.262
2,268 1,267
.001 .001
3.676
0.0397
0.277
1,266
.001
0.293 20.122 0.332
0.0737 0.0385
10.507 0.57
2,264 1,263
.001 .001
0.307 20.155 1.535 0.356 20.139 1.433 0.292 20.154 0.655 0.377
only includes variables that were statistically significant at each step. intake model was excluded from the summary since only age and BMI were significant.
bDietary
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Table 3. Results of final backward elimination regression analysis Variables remaining Age WEL Negative emotions Fagerstrom score Anticipation of weight gain No. of lb gained at prior quit Dietary restraint
B
se(B)
p-Value
20.162 20.117 0.423 3.689 0.129 0.395
0.0464 0.0578 0.2176 1.0556 0.0447 0.0802
.00 .04 .05 .00 .00 .00
Exercise pros Smoking pros
TMAS BMI
Model Statistics R2 5 .3279, F (6,218 5 17.72, p , .001 Variables Removed No. of withdrawal symptoms No. of days recent quit Overall Statistics for Variables Removed R2D 5 .0140, FD(6,218) 5 8.549, p , .001.
attempt (b 5 3.68), Fagerstrom scores (b 5 0.42), dietary restraint (b 5 .39), the number of pounds gained in the previous quit attempts (b 5 .13), age (b 5 20.16), and scores on the WEL Negative Emotion (b 5 20.12) (Table 3). These variables contributed to 33% of the variance. Therefore, anticipation of weight gain in the current quit attempt, higher levels of nicotine dependence, higher levels of dietary restraint, amount of weight gained in previous quit attempts, younger age, and lower self-efficacy for controlling eating in negative affect situations were associated with greater levels of smoking for weight control. D I S C U S S I O N
Our primary purpose in this study was to examine the characteristics associated with smoking for weight control among women enrolled in a smoking cessation program. In our final model we found that several variables were independently associated with greater levels of smoking for weight control: anticipation of postcessation weight gain, higher levels of dietary restraint, younger age, greater number of pounds gained during previous quit attempts, higher Fagerstrom scores, and lower self-efficacy for weight management in negative affect situations. These six variables accounted for 33% of the variance in smoking for weight control. This model presents a theoretically interesting and clinically useful picture of the weight control smoker. Weight control smokers scored higher on dietary restraint, indicating greater levels of preoccupation with food and dieting. This finding is consistent with previous studies (Camp et al., 1993; Pomerleau et al., 1993; Weekley et al., 1992). Research has shown that restrained eaters are vulnerable to disinhibition effects when restraint is broken, and they are likely to overeat (Herman & Polivy, 1984). Among smokers trying to quit, high levels of dietary restraint are related to greater postcessation weight gain (Hall, Ginsberg, & Jones, 1986). Greater postcessation weight gain among restrainers may be due to the disinhibitory effect of negative affect following cessation (Duffy & Hall, 1988; Herman & Polivy, 1984). A prospective design is needed to determine whether weight control smokers were chronic dieters before a cessation attempt that led to weight gain or became restrained eaters as a result of cessation-related weight gain. In our sample, women reporting a higher level of smoking for weight control also
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reported higher anxiety and lower efficacy in managing food intake when experiencing negative affect, which may indicate a greater risk for disinhibition and thus postcessation weight gain. However, the relationship among weight control smoking, negative affect, smoking abstinence, and eating behaviors will need further examination in prospective studies. In our sample, weight control smoking was negatively associated with age. Although the relationship between age and weight control smoking has not been previously reported in the literature, one can expect that younger women may be more likely to adhere to culturally prescribed norms of “thinness” and, therefore, be more likely to endorse smoking as a weight control strategy. Both the extent of weight gain during previous quit attempts and the anticipation of weight gain during the current quit attempt were also characteristic of weight control smokers enrolled in this smoking cessation trial, and these are consistent with data on weight-control smokers not attempting to quit smoking (Weekley et al., 1992). Our findings suggest that weight control smoking is associated with a number of characteristics that have been previously shown to be related to difficulty in quitting smoking. These results may facilitate the identification of women who smoke to control weight (e.g., younger women, higher nicotine dependency), and the development of tailored interventions for these women. It may not be necessary to offer weight management to all women smokers as extra treatment components may prove overwhelming for those who do not smoke for weight control reasons. For example, our data show that weight control smokers report low efficacy in managing food intake when they experience negative emotions. Ability to cope with negative affect without resorting to greater food intake during smoking abstinence may be critical to staying off cigarettes, particularly among women with higher nicotine dependency. Managing negative affect through exercise or relaxation may help these women to attenuate anxiety and thereby prevent relapse. Exercise may also be more attractive to our sample of weight control smokers, since exercise plus dieting appears to hold greater promise as a long-term weight control strategy than dieting alone (e.g., Sale, McCargar, Crawford, & Taunton, 1995; Stefanick, 1993). The lack of success with including weight management components to facilitate smoking cessation (Hall, Tunstall, Vila, & Duffy, 1992; Pirie et al., 1992) has led some researchers to suggest that treatments should help ex-smokers to accept (“normalize”) postcessation weight gain (Perkins, 1994). In sum, consistent with our hypotheses, higher dietary restraint, endorsement of the benefits of smoking and the benefits of exercise adoption, and negative affect (anxiety) were associated with higher levels of smoking for weight control. Our hypothesis that weight control smoking would be associated with lower self-efficacy for weight management received partial support in that we did find that greater weight control smoking was associated with lower self-efficacy for managing food intake specifically during negative emotions. Contrary to our hypothesis, lower caloric consumption was not associated with weight control smoking. Limitations of this study include the cross-sectional nature of the analyses, which limit our ability to make conclusions about causal relationships between weight control smoking and other characteristics of women smokers. For this study, we used backward regression in the final model, which is appropriate for exploratory purposes, but owing to the effects of chance factors, it is possible that the results may not generalize to other groups of women smokers. Although our findings reveal important information about the characteristics associated with weight control smoking, they ac-
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counted for only 33% of the variance. Hence, the variables that account for the remaining two-thirds of the variance have yet to be identified. Finally, our data are not generalizable to women smokers who are not trying to quit, nor to men smokers. Despite these limitations, no previous studies of weight control smokers have examined such a comprehensive compendium of variables related to weight and smoking, nor have they determined the relative strength of each of their predictors in a final prediction model as does the present study. This final constellation of characteristics can inform smoking cessation treatments, and target individuals with these characteristics for either adjunctive weight control treatment or cognitive restructuring regarding beliefs about weight control. Finally, future studies can test this model in a prospective manner to predict smoking outcomes among smokers trying to quit. R E F E R E N C E S Abrams, D. B., Monti, P. M., Pinto, R., Elder, J. P., Brown, R. A., & Jacobus, S. I. (1987). Psychosocial stress and coping in smokers who relapse or quit. Health Psychology, 6, 289–303. American Psychiatric Association. (1987). Diagnostic and statistical manual of mental disorders (3d ed. rev.). Washington, DC: Author. Bendig, A. W. (1956). The development of a short form of the manifest anxiety scale. Journal of Consulting & Clinical Psychology, 20, 384. Blair, S. N., Haskell, W. L., Ho, P., Paffenbarger, R. S., Vranizan, K. M., Farquhar, J. W., & Wood, P. D. (1985). Assessment of habitual physical activity by seven-day recall in a community survey and controlled experiments. American Journal of Epidemiology, 122, 794–804. Block, G., Hartman, A. M., Dresser, C. M., Carroll, M. D., Gannon, J., & Gardner, L. (1986). A data-based approach to diet questionnaire design and testing. American Journal of Epidemiology, 124, 453–469. Borrelli, B., Mermelstein, R., & Shadel, W. G. (1995). The role of weight concern and self-efficacy in smoking cessation and weight gain. Paper presented at the Annual Meeting of the Society of Behavioral Medicine, San Diego, CA. Camp, D. E., Klesges, R. C., & Relyea, G. (1993). The relationship between body weight concerns and adolescent smoking. Health Psychology, 12, 24–32. Clark, M. M., Abrams, D. B., Niaura, R. S., Eaton, C. A., & Rossi, J. S. (1991). Self-efficacy in weight management. Journal of Consulting & Clinical Psychology, 59, 739–744. DiClemente, C. C., Prochaska, J. O., Fairhurst, S., Velicer, W. F., Velasquez, M., & Rossi, J. S. (1991). The process of smoking cessation: An analysis of precontemplation, contemplation and preparation stages of change. Journal of Consulting & Clinical Psychology, 59, 295–304. DiClemente, C. C., Prochaska, J. O., & Gibertini, M. (1985). Self-efficacy and the stages of self-change of smoking. Cognitive Therapy & Research, 9(2), 181–200. Duffy, J., & Hall, S. M. (1988). Smoking abstinence, eating style, and food intake. Journal of Consulting & Clinical Psychology, 56, 417–421. Fagerstrom, K. O. (1978). Measuring degree of physical dependence to tobacco smoking with reference to individualization of treatment. Addictive Behaviors, 3, 235–241. Fiore, M. C., Novotny, T. E., Pierce, J. P., Hatziandreu, E. J., Patel, K. M., & Davis, R. M. (1989). Trends in cigarette smoking in the United States: The changing influence of gender and race. Journal of the American Medical Association, 262, 49–55. French, S. A., & Jeffery, R. W. (1995). Weight concerns and smoking: A literature review. Annals of Behavioral Medicine, 17(3), 234–244. French, S. A., Jeffery, R. W., Klesges, L. M., & Forster, J. L. (1995). Weight concerns and change in smoking behavior over two years in a working population. American Journal of Public Health, 85(5), 720–722. French, S. A., Jeffery, R. W., Pirie, P. L., & McBride, C. M. (1992). Do weight concerns hinder smoking cessation efforts? Addictive behaviors, 17, 219–226. French, S. A., Perry, C. L., Leon, G. R., & Fulkerson, J. A. (1994). Weight concerns, dieting behavior, and smoking initiation among adolescents: A prospective study. American Journal of Public Health, 84(11), 1818–1820. Gritz, E. R., Berman, B. A., Read, L. L., Marcus, A. C., & Siau, J. (1990). Weight change among registered nurses in a self-help smoking cessation program. American Journal of Health Promotion, 5, 155–171. Hall, S. M., Ginsberg, D., & Jones, J. T. (1986). Smoking cessation and weight gain. Journal of Consulting and Clinical Psychology, 54, 342–346. Hall, S. M., Tunstall, C. D., Vila, K. L., & Duffy J. (1992). Weight gain prevention and smoking cessation: Cautionary findings. American Journal of Public Health, 82(6), 799–803. Herman, C. P., & Polivy, J. (1980). Restrained eating. In A. J. Stunkard (Ed.), Obesity (pp. 208–225). Philadelphia: Saunders.
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Herman, C. P., & Polivy, J. (1984). A boundary model for the regulation of eating. In A. B. Stunkard & E. Stellar (Eds.), Eating and its disorders (pp. 141–156). New York: Raven Press. Jackson, A., Pollock, M. L., & Ward A. (1980). Generalized equations for predicting body density of women. Medicine & Science in Sports & Exercise, 12, 175–182. Kickham, K., & Gayton, W. S. (1977). Social desirability and the Restraint Scale. Psychological Reports, 40, 550. Klesges, R. C., Brown, K., Pascale, R. W., Murphy, M., Williams, E., & Cigrang, J. (1988a). Factors associated with participation, attrition, and outcome in a smoking cessation program at the workplace. Health Psychology, 7, 575–590. Klesges, R. C., Meyers, A. W., Klesges, L. M., & La Vasque, M. E. (1989). Smoking, body weight and their effects on smoking behavior: A comprehensive review of the literature. Psychological Bulletin, 106, 204–230. Klesges, R. C., Somes, G. W., Pascale, R., Klesges, L. M., Murphy, M., Brown, K., & Williams, E. (1988b). Knowledge and beliefs regarding the consequences of cigarette smoking and their relationships to smoking status in a biracial sample. Health Psychology, 7, 387–401. Kuehnel, R. H., & Wadden, T. A. (1994). Binge eating disorder, weight cycling and psychopathology. International Journal of Eating Disorders, 15, 321–329. Marcus, B. H., King, T. K., Albrecht, A. E., Parisi, A. F., & Abrams, D. B. (1997). Rationale, design, and baseline data for Commit to Quit: An exercise efficacy trial for smoking cessation in women. Preventive Medicine, 26, 586–597. Marcus, B. H., Rakowski, W., & Rossi, J. S. (1992a). Assessing motivational readiness and decision making for exercise. Health Psychology, 11, 257–261. Marcus, B. H., Selby, V. C., Niaura, R. S., & Rossi, J. S. (1992b). Self-efficacy and the stages of exercise behavior change. Research Quarterly of Exercise & Sport, 63, 60–66. Myers, R. H. (1990). Classical and modern regression with applications (2d ed.). Belmont, CA: PWS–Kent Publishing. Ockene, J. K. (1993). Smoking among women across the life span: Prevalence, interventions, and implications for cessation research. Annals of Behavioral Medicine, 15, 135–148. Perkins, K. (1994). Issues in the prevention of weight gain following smoking cessation. Annals of Behavioral Medicine, 16, 46–52. Pirie, P. L., McBride, C., Hellerstedt, W., Jeffery, R. W., Hatsukami, D., Allen, S., & Lando, H. (1992). Smoking cessation in women concerned about weight. American Journal of Public Health, 82(9), 1238–1243. Pirie, P. L., Murray, D. M., & Luepker, R. V. (1991). Gender differences in cigarette smoking and quitting in a cohort of young adults. American Journal of Public Health, 81, 324–327. Pomerleau, C. S., Ehrilich, E., Tate, J. C., Marks, J. L., Flessland, K. A., & Pomerleau, O. (1993). The female weight-control smoker: A profile. Journal of Substance Abuse, 5, 391–400. Radloff, L. S. (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385–401. Ruderman, A. J. (1986). Dietary restraint: A theoretical and empirical review. Psychological Bulletin, 99, 247–262. Sale, J. E., McCargar, L. J., Crawford, S. M., & Taunton, J. E. (1995). Effects of exercise modality on metabolic rate and body composition. Clinical Journal of Sports Medicine, 5, 100–107. Sallis, J. F., Haskell, W. L., Wood, P. D., Fortmann, S. P., Rogers, T., Blair, S. N., & Paffenbarger, R. S. (1985). Physical activity assessments methodology in the Five-City Project. American Journal of Epidemiology, 121, 91–106. Sorenson, G., & Pechacek, T. F. (1987). Attitudes towards smoking cessation among men and women. Journal of Behavioral Medicine, 10, 129–137. Stefanick, M. L. (1993). Exercise and weight control. Exercise and Sports Science Reviews, 21, 363–396. Streater, J. A., Sargent, R. G., & Ward, D. S. (1989). A study of factors associated with weight change in women who attempt smoking cessation. Addictive Behaviors, 14, 523–530. Taylor, J. A. (1953). A personality scale of manifest anxiety. Journal of Abnormal Social Psychology, 48, 285–290. U.S. Department of Health and Human Services (USDHHS). (1989). Reducing the health consequences of smoking: 25 Years of progress. A report of the Surgeon-General. Rockville, MD: Public Health Service, Office on Smoking and Health. U.S. Department of Health and Human Services (USDHHS). (1994). Surveillance for selected tobacco use behaviors-United States, 1900–1994. Morbidity and Mortality Weekly Report, 43, 1–43. Velicer, W. F., DiClemente, C. C., Prochaska, J. O., & Brandenburg, N. (1985). A decisional balance measure for assessing and predicting smoking status. Journal of Personality & Social Psychology, 48, 1279–1289. Weekley, C. K., Klesges, R. C., & Reylea, G. (1992). Smoking as a weight control strategy and its relationship to smoking status. Addictive Behaviors, 17, 259–271. Weissman, M. M., Sholomskas, D., Pottenger, M., Prusoff, B. A., & Locke, B. Z. (1977). Assessing depressive symptoms in five psychiatric populations. American Journal of Epidemiology, 106, 203–214. Wurtman, J. J. (1993). Depression and weight gain: The serotonin connection. Journal of Affective Disorders, 29, 183–192. Zulkifli, S. N., & Yu, S. M. (1992). The food frequency method for dietary assessment. Journal of the American Dietetic Association, 92, 681–685.
Pergamon
PII S0306-4603(98)00034-3
WEIGHT CONTROL SMOKING AMONG SEDENTARY WOMEN BERNARDINE M. PINTO, BELINDA BORRELLI, TERESA K. KING, BETH C. BOCK, MATTHEW M. CLARK, MARY ROBERTS, and BESS H. MARCUS The Miriam Hospital and Brown University School of Medicine
Abstract — This study examined characteristics associated with weight control smoking among 281 sedentary women enrolled in a smoking cessation trial. A series of regression models were developed to identify predictors of weight control smoking as measured by the Smoking Situations Questionnaire. Predictor variables included demographic variables, dietary intake, weight gain following previous quit attempts, dietary restraint, self-efficacy for weight management, smoking behavior, exercise behavior, negative affect and psychological constructs relevant to smoking cessation, and exercise adoption. In the final predictor model, anticipation of weight gain in the current quit attempt, higher dietary restraint, younger age, greater Fagerstrom scores, greater number of pounds gained in previous quit attempts, and lower levels of self-efficacy to manage weight in negative affect situations were associated with smoking for weight control. Treatment implications for women who smoke for weight control reasons are discussed. © 1998 Elsevier Science Ltd
Women who smoke cigarettes are at increased risk for cardiovascular disease, stroke, cancer, and osteoporosis, which are the major causes of death and disability among American women (Ockene, 1993; USDHHS, 1989). Although smoking prevalence among women has been declining over the past 25 years, cessation rates among women lag behind those among men (Fiore et al., 1989; USDHHS, 1994). One important reason why women smokers do not attempt and/or succeed at quitting smoking is the concern about postcessation weight gain (Pirie, Murray, & Luepker, 1991; Camp, Klesges, & Relyea, 1993). The relationship of weight concern to smoking status has been assessed with both cross-sectional and prospective designs, with cross-sectional designs yielding predominantly positive associations between smoking-specific weight concern and smoking (Camp et al., 1993; Klesges et al., 1988b; Weekley, Klesges, & Reylea, 1992), and prospective designs showing little or no association between smoking-specific weight concerns and smoking (Borrelli, Mermelstein, & Shadel, 1995; French, Jeffery, Pirie, & McBride, 1992). These mixed findings may be due to the fact that, in the cross-sectional studies, smokers are not trying to quit smoking. Additionally, these inconsistencies may be the result of varying conceptualizations and measures of weight concerns such as dietary restraint (French et al., 1992), smoking-specific weight concern This project was supported in part through grants from the National Cancer Institute (KO7CA01757 and R29CA59660) and a supplement to R29CA59660 from the Office of Research on Women’s Health, to Dr. Marcus. We acknowledge and thank David Abrams, PhD, Anna Albrecht, RN, MS, and Alfred Parisi, MD, for their contributions to this trial. We thank Regina Traficante, MA, and Janice Tripolone, BS, for their numerous contributions to the implementation of this study. We also thank Barbara Doll for her help in manuscript preparation. The work was carried out at The Miriam Hospital, 164 Summit Ave., Providence, RI 02906. Requests for reprints should be sent to Bernardine M. Pinto, PhD, Assistant Professor of Psychiatry and Human Behavior, The Miriam Hospital, and Brown University School of Medicine, 164 Summit Ave., Providence, RI 02906. 75
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(French et al., 1992), general weight concern (Klesges et al., 1988b), smoking for weight control (Camp et al., 1993; Pomerleau et al., 1993, Weekley et al., 1992), perceived risk and seriousness of weight gain following smoking cessation (Borrelli et al., 1995; Pirie et al., 1991; Klesges et al., 1988a; Streater, Sargent, & Ward, 1989), current dieting, dieting history, and personal weight preferences (French, Jeffery, Klesges, & Forster, 1995), fear of, and preoccupation with, body weight and weight gain (French, Perry, Leon, & Fulkerson, 1994; Gritz, Berman, Read, Marcus, & Siau, 1990), and finally, some studies do not specify how weight concern was measured (Pirie et al., 1992). Therefore, it has become increasingly difficult to draw conclusions from the literature regarding the association between smoking-related weight concern and smoking cessation (French & Jeffery, 1995). In the present paper, we defined smoking-related weight concern as smoking for weight control (Weekley et al., 1992), and we assessed demographic factors, dietary intake, smoking, and exercise variables that may be associated with smoking for weight control in women enrolled in a smoking cessation trial (Marcus, King, Albrecht, Parisi, & Abrams, 1997). While a few studies have found that smoking for weight control was associated with greater weight gain during previous quit attempts, lower education, and higher dietary restraint (Pomerleau et al., 1993; Weekley et al., 1992), these characteristics have not been examined among women enrolled in a smoking cessation program. Identifying the predictors of women who smoke for weight control is important for two reasons. First, there probably is a constellation of characteristics that is related to smoking for weight control which inhibit smoking cessation such as higher levels of dietary restraint and higher levels of nicotine dependence. Second, smoking for weight control itself may be an important barrier to quitting, suggesting the need for tailored treatments for this subgroup of smokers to enhance quit rates. This paper extends the literature by examining variables relevant to weight control smoking such as dietary intake and exercise behavior in women who have volunteered to participate in a smoking cessation trial. We examined the dietary habits of this subsample of women smokers because these data may help design appropriate weight-management interventions for women smokers concerned about postcessation weight gain. Our hypothesis was that lower caloric consumption would be associated with higher levels of weight control smoking since dietary restraint has been associated with weight control smoking (Camp et al., 1993) and, dietary restraint has been shown to be higher in women smokers (Weekley et al., 1992). Additionally, lack of control over eating or disinhibition has been found to predict weight gain after smoking cessation (Duffy & Hall, 1988). To identify the situations in which weight control smokers report difficulty in managing food intake, we included a measure of self-efficacy for weight management (Clark, Abrams, Niaura, Eaton, & Rossi, 1991). We expected that low efficacy for controlling eating would be associated with weight control smoking. This study also explored the relationship of weight control smoking to psychological mediators of smoking cessation (e.g., pros and cons for smoking, and self-efficacy for smoking cessation) and exercise adoption (e.g., pros and cons, and self-efficacy). We hypothesized that weight control smokers would endorse more advantages (pros) than disadvantages of smoking (cons) and have less confidence in their ability to quit smoking. Exercise is an effective method of weight management when combined with dietary changes, and women smokers who are concerned about postcessation weight gain may be more favorably disposed toward exercise. The smoking cessation trial of-
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fered an exercise program to those in the intervention group; hence, we expected that enrollees would favor exercise participation. This bias notwithstanding, we expected that higher levels of smoking for weight control would be associated with greater endorsement of the pros of exercise. We also hypothesized that negative affect would be associated with greater smoking for weight control. Dysphoric mood and/or depressive states have been associated with eating-disordered behaviors and high levels of dietary restraint (Kuehnel & Wadden, 1994; Ruderman, 1986). Furthermore, negative affect has been linked to smoking among women (Abrams et al., 1987; Sorenson & Pechacek, 1987). Women who report higher levels of negative affect may eat more to assuage negative affect (Wurtman, 1993) and either smoke to offset this greater eating, or smoke as a food substitute. In sum, in studying the characteristics of women who smoke to control weight, we hypothesized that lower caloric consumption, higher dietary restraint, and lower efficacy for weight management would be associated with smoking for weight control. Additional hypotheses were that higher pros for smoking, lower self-efficacy for smoking cessation, and higher pros for exercise adoption would be associated with smoking for weight control. Finally, we hypothesized that greater negative affect would be associated with smoking for weight control. M E T H O D
Data for the present investigation comprise part of the baseline data from a larger study designed to compare the efficacy of a 12-session cognitive-behavioral smoking cessation treatment plus supervised vigorous exercise with the same cessation treatment plus contact control (Marcus et al., 1997). Participants Participants were 281 women who completed pretreatment measures as described elsewhere (Marcus et al., 1997). The study population consisted predominantly of White (92.1%) middle-aged (M 5 40.2) women (see Table 1). Seventy-six percent of the subjects were employed and 55.2% were married. The median household income level was in the $30,000 to $39,999 range. Subjects weighed an average of 147.7 lb (SD 5 30.3). The average Body Mass Index (BMI) was 25.4 (SD 5 5.0), and the average percent body fat was 29.9 (SD 5 7.2). Subjects reported smoking on average 22.2 (SD 5 9.3) cigarettes per day. Procedure Healthy sedentary women (18–65 years) smokers ($10 cigarettes per day for a minimum of 3 years) were recruited through newspaper advertisements. Exclusionary criteria included medical problems and/or medications that would make compliance with the study protocol difficult or dangerous. Women with a current psychiatric illness, alcoholism, alcohol abuse, or other substance abuse were also excluded. Subjects agreed to be assigned randomly to either of the two investigational conditions and provided written informed consent to participate in the research procedures. Measures The following measures were used to assess weight control smoking, dietary restraint, smoking, and exercise variables. Psychometrics are reported as available for each instrument.
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Table 1. Demographics and smoking history of participants in the Commit to Quit trial Variable Age (years) Baseline weight (pounds) Body Mass Index (BMI) Base VO2 estimate (ml/kg*min) Baseline total daily METS Number of cigarettes/day Carbon monoxide (ppm) Fagerstrom score Baseline CES-D score Baseline T–MAS score Smoking situations questionnaire
N
Mean
SD
281 277 275 277 235 269 263 281 277 280 277
40.16 147.67 25.41 24.97 44.87 22.19 17.44 6.27 12.33 6.47 17.30
8.92 30.30 4.99 5.09 9.35 9.34 10.16 1.91 9.14 4.27 7.17
Variable Race Occupation Employment status Marital status Education level Income level
Percent Caucasian White collar Employed Married/Living together HS Graduate or higher $$20,000/year
91.8 55.7 76.0 55.2 95.7 80.1
Weight-control smoking. The Smoking Situations Questionnaire (SSQ; Weekley et al., 1992) is a 6-item instrument used to measure the extent to which subjects smoke for weight control reasons. The SSQ appears to be a unidimensional measure with adequate internal consistency (alpha 5 .76) and stability (test-retest r 5 .95; Weekley et al., 1992). The scores range from 6 to 36. Higher scores indicate a greater degree of smoking for weight control. Dietary variables. The Revised Restraint Scale (RRS; Herman & Polivy, 1980) was used to measure dietary restraint. This 10-item questionnaire was designed to identify chronic dieters who restrain their eating and inhibit caloric intake. Psychometric evaluations of the RRS have yielded adequate measures of internal consistency for nonobese individuals (alpha 5 .83). Test-retest reliability over a 1-week period is .93 (Kickham & Gayton, 1977). The Weight Efficacy Life-Style Questionnaire (WEL; Clark et al., 1991) consists of 20 Likert-type items that ask subjects to rate their self-efficacy for controlling their eating in various situations. The WEL has five subscales (four items each): Negative emotions, Availability, Social pressure, Physical discomfort, and Positive activities. Cronbach’s alphas for the subscales among obese populations range from .79 to .88, demonstrating adequate internal consistency. Higher scores indicate greater levels of self-efficacy for weight management. The Food Frequency Questionnaire (FFQ; Block et al., 1986), a valid and reliable measure (Zulkifli & Yu, 1992) was used to assess dietary intake and total caloric consumption. The FFQ consists of a list of food items for which average frequency of consumption is determined in reference to a specified time period, defined in this study as 1 month. Subjects were also asked questions about their maximum body weight as an adult, the amount of weight gain after their last quit attempt, and the amount of anticipated weight gain with the present cessation effort. Body weight and height were measured on a calibrated scale (Detecto medical scale) to the nearest quarter pound and the
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nearest quarter inch, respectively. Body fat was estimated from skinfold thickness measured on the right side at the triceps, suprailiac crest, and thigh (Jackson, Pollock, & Ward, 1980). Smoking measures. These included daily smoking rate and number and duration of previous quit attempts. Nicotine dependence was assessed through the Fagerstrom Tolerance Questionnaire (FTQ; Fagerstrom, 1978). Carbon monoxide levels were measured using a carbon monoxide analyzer. The number of withdrawal symptoms during previous quit attempts (from among 16 symptoms) were assessed using DSMIII-R criteria (American Psychiatric Association, 1987). A short version of the previously developed Smoking Abstinence Self-Efficacy scale (SASE; DiClemente, Prochaska, & Gibertini, 1985) assessed the smoker’s level of confidence to refrain from smoking in nine challenging situations. The various forms of this self-efficacy measure have demonstrated good internal consistency (Cronbach alpha 5 .88–.92) and both construct and predictive validity (DiClemente et al., 1991). High scores indicate high levels of efficacy for abstinence. A short 6-item version of the smoking decisional balance scale (Velicer, DiClemente, Prochaska, & Brandenburg, 1985) measured positive and negative attitudes relating to smoking. The pros and cons scales have demonstrated good concurrent and predictive validity (DiClemente et al., 1991). In our sample, Cronbach alphas for the pros and cons scales were .69 and .57, respectively. High scores on the pros scale indicate perception of high benefits from smoking (this scale does not include an item on smoking-related weight control benefits), and high scores on the cons scale indicate perception of high costs of smoking. A decisional balance score (ratio of pros to cons) was not computed to avoid assuming equal beta weight for the pros and cons in the regression analyses. Exercise measures. A 5-item measure of self-efficacy for exercise participation was administered (Marcus, Selby, Niaura, & Rossi, 1992b). A 5-point scale was used to rate each item ranging from not at all confident (1) to extremely confident (5). This scale has good internal consistency (Marcus et al., 1992b), and in this sample the Cronbach alpha was .80. High scores indicate a high level of self-efficacy for exercise. A 16-item decisional balance measure for exercise was administered (Marcus, Rakowski, & Rossi, 1992a). Higher scores on the “pro” scale indicate perceptions of high benefits from exercise (the scale does not include any items on weight control benefits of exercise); high scores on the “con” scale indicate perceptions of high costs of exercise. Internal consistency for the pros and cons of exercise for this sample were .92 and .73, respectively. A decisional balance score (ratio of pros to cons) was not computed. We assessed exercise behavior via a self-administered version of the Seven-Day Physical Activity Recall (7-Day PAR; Blair et al., 1985) to determine if smoking to control weight was associated with greater levels of exercise participation. The 7-Day PAR yields metabolic equivalents (MET values) for varying intensities of exercise. It is a valid (Blair et al., 1985) and a reliable measure of habitual physical activity (Sallis et al., 1985). Mood measures. The Center for Epidemiologic Studies Depression Scale (CES-D) was used to measure depressive symptoms. This 20-item scale has been widely used and extensively validated (Weissman, Sholomskas, Pottenger, Prusoff, & Locke, 1977). Coefficient alphas ranging from 0.84 to 0.90 have been reported for the CES-D
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in clinical trials (Radloff, 1977). The 20-item version of the Taylor Manifest Anxiety Scale (TMAS) was used to assess trait anxiety (Bendig, 1956; Taylor, 1953). Data analyses We computed a series of stepwise multiple regression models with smoking for weight control as assessed by the SSQ as the dependent variable (Weekley et al., 1992). The goal was to assess which variables predict smoking for weight control based on a priori hypotheses, and to determine the best predictor(s) for smoking for weight control. In each model, age and BMI were forced, respectively, into the equation prior to other independent variables because these variables have been shown to be related to higher levels of smoking-specific weight concern (Klesges et al., 1989). We divided the independent variables into conceptually distinct groups (e.g., dietary intake, dietary restraint, smoking variables, exercise variables), conducted tests of multicollinearity within each group, and then computed separate stepwise multiple regression models. Finally, a regression equation using the backward elimination procedure (Myers, 1990) was conducted utilizing significant predictors from the previous models.
R E S U L T S
Demographic factors In the stepwise multiple regression model, demographic variables such as race, occupation, marital status, and education did not significantly enter the model over and above age and baseline BMI, which were forced into the equation first and second, respectively. Both age and BMI significantly entered the model (F 5 10.2, df 5 2,268, p , .0001), such that older age was associated with lower levels of smoking for weight control (b 5 .14) and greater BMI was associated with higher levels of smoking for weight control (b 5 .30). Age and BMI accounted for 7% of the variance in smoking for weight control. Dietary intake In the stepwise multiple regression model, total caloric consumption did not enter significantly into the model after baseline age and BMI were forced into the model. Dietary restraint Dietary restraint (Revised Restraint Scale) significantly entered into the stepwise multiple regression model (over and above age and BMI) and contributed to 14% of the variance. As hypothesized, higher levels of dietary restraint (b 5 .51) were associated with a greater degree of smoking for weight control (F 5 23.34, df 5 3,263, p , .0001). The model accounted for 21% of the variance in smoking for weight control. Self-efficacy for weight management We entered the WEL subscales into a stepwise multiple regression model, after controlling for baseline age and BMI. The negative emotion subscale significantly entered the model after age and BMI, accounting for 10.3% of the variance. These three variables accounted for 16% of the variance in smoking for weight control (F 5 15.6, df 5 3,239, p , .0001). Lower levels of self-efficacy to control eating during negative affect situations were associated with higher levels of smoking for weight control (b 5 2.30).
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Smoking cessation attempts and weight gain The stepwise multiple regression model included the following variables in addition to age and BMI: previous quit attempts (yes/no), weight gain during previous quit attempts (yes/no), number of pounds gained during previous quit attempts, anticipation of weight gain during the current quit attempt (yes/no) and the number of pounds of anticipated weight gain during the current quit attempt. The number of pounds gained during previous quit attempts (b 5 .21), and anticipation of weight gain (yes/no) in the current quit attempt (b 5 3.68) (F 5 16.2, df 5 4,266, p , .0001) significantly predicted smoking for weight control (above and beyond age and BMI). The number of pounds gained at previous quit attempts contributed to 8.5% of the variance, and anticipation of weight gain contributed to 3.9% of the variance. Higher levels of smoking for weight control were related to a greater amount of weight gained during previous quits and anticipation of weight gain in the current quit attempt. This model accounted for 20% of the variance in smoking for weight control. Smoking variables In the stepwise regression model with smoking variables as predictors, the following variables were included: the Fagerstrom score, number of withdrawal symptoms during previous quit attempts, carbon monoxide level, average daily smoking rate, duration of the longest prior quit attempt, duration of the most recent quit attempt, number of 12-hour quit attempts, and number of 24-hour quit attempts. The Fagerstrom, the number of withdrawal symptoms during past quit attempts, and the number of days in the most recent quit attempt significantly predicted smoking for weight control over and above age and BMI (F 5 8.4, df 5 5,225, p , .0001). Higher scores on the Fagerstrom (b 5 .65), greater number of self-reported withdrawal symptoms during past quit attempts (b 5 .37), and greater number of days in the most recent quit attempt (b 5 .003) were associated with greater levels of smoking for weight control. Fagerstrom scores contributed to 3.7% of the variance, number of withdrawal symptoms during past quit attempts accounted for 2.4% of the variance, and the number of days in the most recent quit attempt contributed to 1.7% of the variance. The total model accounted for 16% of the variance. Self-efficacy for smoking, and pros and cons for smoking In a stepwise multiple regression model that included the pros of smoking, the cons of smoking, and self-efficacy for quitting smoking, only the pros of smoking significantly predicted smoking for weight control over and above age and BMI (F 5 10.3, df 5 3,254, p , .0001), such that higher scores on the pros of smoking were related to a higher level of smoking for weight control (b 5 1.53) and contributed to 4.5% of the variance. Age, BMI, and pros of smoking accounted for 10% of the variance. Exercise variables We computed a stepwise multiple regression model with the following baseline variables: self-efficacy for exercise adoption, pros and cons for exercise adoption, and METS from the 7-Day PAR. The pros of exercise adoption (b 5 1.43) was the only variable to enter the model over and above age and BMI (F 5 10.3, df 5 3,220, p , .0001) with higher pros for exercise associated with greater smoking for weight control, and accounting for 2.3% of the variance. Age, BMI, and pros for exercise contributed to 12% of the variance.
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Mood measures We computed a stepwise multiple regression model with the following measures of negative affect as independent variables: CES-D (depression), and TMAS (anxiety). Scores on the TMAS significantly predicted smoking for weight control over and above age and BMI (F 5 11.1, df 5 3,263, p , .0001), such that higher scores on the TMAS were associated with greater likelihood of smoking for weight control (b 5 .33) accounting for 3.8% of the variance. Age, BMI, and TMAS scores contributed to 11% of the variance. CES-D scores did not significantly enter the equation. Final prediction model To determine the strongest predictors of smoking for weight control, we computed a final stepwise regression model that included all of the significant predictors from the previous models (Table 2). We used a backward elimination procedure to enter the following procedures: age, BMI, dietary restraint, scores on the negative emotion subscale of the WEL, anticipation of weight gain (yes/no), number of pounds gained during previous quit attempts, Fagerstrom scores, number of withdrawal symptoms during previous quit attempts, number of days in the most recent quit attempt, pros of smoking, pros of exercise adoption, and the TMAS scores. The only variables to significantly enter the stepwise model were anticipation of weight gain in the current quit Table 2. Smoking for weight control: Results of stepwise regression analysisa Modelb Demographics Dietary restraint Managing food Consumption Smoking Constructs Exercise Constructs Smoking Cessation Attempts
Weight concerns
Mood
aTable
Variables
B
R2D
FD
df
p,
BMI Age BMI Age Dietary restraint BMI Age WEL Negative Emotions BMI Age Smoking pros BMI Age Exercise pros BMI Age Fagerstrom score No. of withdrawal symptoms No. of days recent quit BMI Age No. lb gained at prior quit Anticipation of weight gain BMI Age TMAS
0.295 20.139 20.023 20.128 0.511 0.124 20.141 20.296
0.0417 0.0294
11.713 1.464
1,269 1,268
.001 .001
0.0718 0.1384
10.215 13.123
2,264 1,263
.001 .001
0.0604 0.1037
7.717 7.925
2,240 1,239
.001 .001
0.0684 0.0455
9.732 1.577
2,265 1,264
.001 .001
0.0997 0.0236
12.238 1.922
2,221 1,220
.001 .001
0.0782 0.0375 0.0241
9.667 0.23 0.716
2,228 1,227 1,226
.001 .001 .001
0.003
0.0175
0.782
1,225
.001
0.259 20.181 0.211
0.0711 0.0854
10.249 6.262
2,268 1,267
.001 .001
3.676
0.0397
0.277
1,266
.001
0.293 20.122 0.332
0.0737 0.0385
10.507 0.57
2,264 1,263
.001 .001
0.307 20.155 1.535 0.356 20.139 1.433 0.292 20.154 0.655 0.377
only includes variables that were statistically significant at each step. intake model was excluded from the summary since only age and BMI were significant.
bDietary
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Table 3. Results of final backward elimination regression analysis Variables remaining Age WEL Negative emotions Fagerstrom score Anticipation of weight gain No. of lb gained at prior quit Dietary restraint
B
se(B)
p-Value
20.162 20.117 0.423 3.689 0.129 0.395
0.0464 0.0578 0.2176 1.0556 0.0447 0.0802
.00 .04 .05 .00 .00 .00
Exercise pros Smoking pros
TMAS BMI
Model Statistics R2 5 .3279, F (6,218 5 17.72, p , .001 Variables Removed No. of withdrawal symptoms No. of days recent quit Overall Statistics for Variables Removed R2D 5 .0140, FD(6,218) 5 8.549, p , .001.
attempt (b 5 3.68), Fagerstrom scores (b 5 0.42), dietary restraint (b 5 .39), the number of pounds gained in the previous quit attempts (b 5 .13), age (b 5 20.16), and scores on the WEL Negative Emotion (b 5 20.12) (Table 3). These variables contributed to 33% of the variance. Therefore, anticipation of weight gain in the current quit attempt, higher levels of nicotine dependence, higher levels of dietary restraint, amount of weight gained in previous quit attempts, younger age, and lower self-efficacy for controlling eating in negative affect situations were associated with greater levels of smoking for weight control. D I S C U S S I O N
Our primary purpose in this study was to examine the characteristics associated with smoking for weight control among women enrolled in a smoking cessation program. In our final model we found that several variables were independently associated with greater levels of smoking for weight control: anticipation of postcessation weight gain, higher levels of dietary restraint, younger age, greater number of pounds gained during previous quit attempts, higher Fagerstrom scores, and lower self-efficacy for weight management in negative affect situations. These six variables accounted for 33% of the variance in smoking for weight control. This model presents a theoretically interesting and clinically useful picture of the weight control smoker. Weight control smokers scored higher on dietary restraint, indicating greater levels of preoccupation with food and dieting. This finding is consistent with previous studies (Camp et al., 1993; Pomerleau et al., 1993; Weekley et al., 1992). Research has shown that restrained eaters are vulnerable to disinhibition effects when restraint is broken, and they are likely to overeat (Herman & Polivy, 1984). Among smokers trying to quit, high levels of dietary restraint are related to greater postcessation weight gain (Hall, Ginsberg, & Jones, 1986). Greater postcessation weight gain among restrainers may be due to the disinhibitory effect of negative affect following cessation (Duffy & Hall, 1988; Herman & Polivy, 1984). A prospective design is needed to determine whether weight control smokers were chronic dieters before a cessation attempt that led to weight gain or became restrained eaters as a result of cessation-related weight gain. In our sample, women reporting a higher level of smoking for weight control also
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reported higher anxiety and lower efficacy in managing food intake when experiencing negative affect, which may indicate a greater risk for disinhibition and thus postcessation weight gain. However, the relationship among weight control smoking, negative affect, smoking abstinence, and eating behaviors will need further examination in prospective studies. In our sample, weight control smoking was negatively associated with age. Although the relationship between age and weight control smoking has not been previously reported in the literature, one can expect that younger women may be more likely to adhere to culturally prescribed norms of “thinness” and, therefore, be more likely to endorse smoking as a weight control strategy. Both the extent of weight gain during previous quit attempts and the anticipation of weight gain during the current quit attempt were also characteristic of weight control smokers enrolled in this smoking cessation trial, and these are consistent with data on weight-control smokers not attempting to quit smoking (Weekley et al., 1992). Our findings suggest that weight control smoking is associated with a number of characteristics that have been previously shown to be related to difficulty in quitting smoking. These results may facilitate the identification of women who smoke to control weight (e.g., younger women, higher nicotine dependency), and the development of tailored interventions for these women. It may not be necessary to offer weight management to all women smokers as extra treatment components may prove overwhelming for those who do not smoke for weight control reasons. For example, our data show that weight control smokers report low efficacy in managing food intake when they experience negative emotions. Ability to cope with negative affect without resorting to greater food intake during smoking abstinence may be critical to staying off cigarettes, particularly among women with higher nicotine dependency. Managing negative affect through exercise or relaxation may help these women to attenuate anxiety and thereby prevent relapse. Exercise may also be more attractive to our sample of weight control smokers, since exercise plus dieting appears to hold greater promise as a long-term weight control strategy than dieting alone (e.g., Sale, McCargar, Crawford, & Taunton, 1995; Stefanick, 1993). The lack of success with including weight management components to facilitate smoking cessation (Hall, Tunstall, Vila, & Duffy, 1992; Pirie et al., 1992) has led some researchers to suggest that treatments should help ex-smokers to accept (“normalize”) postcessation weight gain (Perkins, 1994). In sum, consistent with our hypotheses, higher dietary restraint, endorsement of the benefits of smoking and the benefits of exercise adoption, and negative affect (anxiety) were associated with higher levels of smoking for weight control. Our hypothesis that weight control smoking would be associated with lower self-efficacy for weight management received partial support in that we did find that greater weight control smoking was associated with lower self-efficacy for managing food intake specifically during negative emotions. Contrary to our hypothesis, lower caloric consumption was not associated with weight control smoking. Limitations of this study include the cross-sectional nature of the analyses, which limit our ability to make conclusions about causal relationships between weight control smoking and other characteristics of women smokers. For this study, we used backward regression in the final model, which is appropriate for exploratory purposes, but owing to the effects of chance factors, it is possible that the results may not generalize to other groups of women smokers. Although our findings reveal important information about the characteristics associated with weight control smoking, they ac-
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counted for only 33% of the variance. Hence, the variables that account for the remaining two-thirds of the variance have yet to be identified. Finally, our data are not generalizable to women smokers who are not trying to quit, nor to men smokers. Despite these limitations, no previous studies of weight control smokers have examined such a comprehensive compendium of variables related to weight and smoking, nor have they determined the relative strength of each of their predictors in a final prediction model as does the present study. This final constellation of characteristics can inform smoking cessation treatments, and target individuals with these characteristics for either adjunctive weight control treatment or cognitive restructuring regarding beliefs about weight control. Finally, future studies can test this model in a prospective manner to predict smoking outcomes among smokers trying to quit. R E F E R E N C E S Abrams, D. B., Monti, P. M., Pinto, R., Elder, J. P., Brown, R. A., & Jacobus, S. I. (1987). Psychosocial stress and coping in smokers who relapse or quit. Health Psychology, 6, 289–303. American Psychiatric Association. (1987). Diagnostic and statistical manual of mental disorders (3d ed. rev.). Washington, DC: Author. Bendig, A. W. (1956). The development of a short form of the manifest anxiety scale. Journal of Consulting & Clinical Psychology, 20, 384. Blair, S. N., Haskell, W. L., Ho, P., Paffenbarger, R. S., Vranizan, K. M., Farquhar, J. W., & Wood, P. D. (1985). Assessment of habitual physical activity by seven-day recall in a community survey and controlled experiments. American Journal of Epidemiology, 122, 794–804. Block, G., Hartman, A. M., Dresser, C. M., Carroll, M. D., Gannon, J., & Gardner, L. (1986). A data-based approach to diet questionnaire design and testing. American Journal of Epidemiology, 124, 453–469. Borrelli, B., Mermelstein, R., & Shadel, W. G. (1995). The role of weight concern and self-efficacy in smoking cessation and weight gain. Paper presented at the Annual Meeting of the Society of Behavioral Medicine, San Diego, CA. Camp, D. E., Klesges, R. C., & Relyea, G. (1993). The relationship between body weight concerns and adolescent smoking. Health Psychology, 12, 24–32. Clark, M. M., Abrams, D. B., Niaura, R. S., Eaton, C. A., & Rossi, J. S. (1991). Self-efficacy in weight management. Journal of Consulting & Clinical Psychology, 59, 739–744. DiClemente, C. C., Prochaska, J. O., Fairhurst, S., Velicer, W. F., Velasquez, M., & Rossi, J. S. (1991). The process of smoking cessation: An analysis of precontemplation, contemplation and preparation stages of change. Journal of Consulting & Clinical Psychology, 59, 295–304. DiClemente, C. C., Prochaska, J. O., & Gibertini, M. (1985). Self-efficacy and the stages of self-change of smoking. Cognitive Therapy & Research, 9(2), 181–200. Duffy, J., & Hall, S. M. (1988). Smoking abstinence, eating style, and food intake. Journal of Consulting & Clinical Psychology, 56, 417–421. Fagerstrom, K. O. (1978). Measuring degree of physical dependence to tobacco smoking with reference to individualization of treatment. Addictive Behaviors, 3, 235–241. Fiore, M. C., Novotny, T. E., Pierce, J. P., Hatziandreu, E. J., Patel, K. M., & Davis, R. M. (1989). Trends in cigarette smoking in the United States: The changing influence of gender and race. Journal of the American Medical Association, 262, 49–55. French, S. A., & Jeffery, R. W. (1995). Weight concerns and smoking: A literature review. Annals of Behavioral Medicine, 17(3), 234–244. French, S. A., Jeffery, R. W., Klesges, L. M., & Forster, J. L. (1995). Weight concerns and change in smoking behavior over two years in a working population. American Journal of Public Health, 85(5), 720–722. French, S. A., Jeffery, R. W., Pirie, P. L., & McBride, C. M. (1992). Do weight concerns hinder smoking cessation efforts? Addictive behaviors, 17, 219–226. French, S. A., Perry, C. L., Leon, G. R., & Fulkerson, J. A. (1994). Weight concerns, dieting behavior, and smoking initiation among adolescents: A prospective study. American Journal of Public Health, 84(11), 1818–1820. Gritz, E. R., Berman, B. A., Read, L. L., Marcus, A. C., & Siau, J. (1990). Weight change among registered nurses in a self-help smoking cessation program. American Journal of Health Promotion, 5, 155–171. Hall, S. M., Ginsberg, D., & Jones, J. T. (1986). Smoking cessation and weight gain. Journal of Consulting and Clinical Psychology, 54, 342–346. Hall, S. M., Tunstall, C. D., Vila, K. L., & Duffy J. (1992). Weight gain prevention and smoking cessation: Cautionary findings. American Journal of Public Health, 82(6), 799–803. Herman, C. P., & Polivy, J. (1980). Restrained eating. In A. J. Stunkard (Ed.), Obesity (pp. 208–225). Philadelphia: Saunders.
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