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An investigation of beliefs about smoking among diabetes patients: Information for improving cessation efforts
181
Patient Education and Counseling, 15(1990) 181-189 Elsevier Scientific
Publishers
Ireland
Ltd.
An Investigation of Beliefs About Smoking Among Diabetes Patients: Information for Improving Cessation Efforts Richard D. Stacy and Brenda H. Loyd” School of HPER, University of Nebraska at Omaha, Omaha, NE 68182-0216 and “Department of Educational Research, Curry School of Education, University of Virginia, Charlottesville, VA 22903 (U.S.A.) (Received March 3rd, 1989) (Accepted October 27th, 1989)
Abstract
The purpose of this study was to identify differences between current smokers and exsmokers in beliefs about the health effects of smoking. This information will enable educators to design better smoking cessation interventions for diabetes patients. A smoking behavior questionnaire was developed to collect information about demographics, personal lifestyle, and beliefs about smoking and diabetes. Participants were 40 current smokers and 30 ex-smokers located from a patient registry at the University of Virginia Diabetes Research and Training Center. Less than half of the diabetic smokers in the study reported receiving advice to quit from their physician and none of them reported having attended a formal smoking cessation program. Results indicate that demographic and lifestyle variables predict 21 oloof the variance between smokers and non-smokers in this sample. The group of health belief variables collectively raised the amount of variance that could be accounted for from 21% to 42 9’0.It is recommended that health professionals who provide services to diabetes patients determine present smoking behavior of each diabetes patient, provide firm advice to stop smoking, R.D. Stacy, EdD, Assistant Health Education.
Professor
and
Coordinator
of
B.H.Loyd,PhD,AssistantProfessorofEducationalResearch.
0738-3991/90/%03.50 Published and Printed
0 1990 Elsevier Scientific in Ireland
Publishers
lreland
assess the special circumstances of the smokers, and offer specific smoking cessation programs to meet the unique needs o-f diabetes patients. Keywords: Smoking cessation; Diabetes.
Introduction
Cigarette smoking is a factor in the development of a variety of chronic diseases including heart disease, emphysema, chronic bronchitis, and many types of cancer [l]. Cigarette smoking is not a factor in the development of diabetes, but many of the problems associated with diabetes are complicated by cigarette smoking. The most serious health risks for persons with diabetes are: increased risks of blindness due to diabetic retinopathy, increased risks of kidney failure due to nephropathy, a two-fold increase in risk for heart disease, and increased risks of losing lower extremities due to problems with peripheral circulation. There is conflicting evidence regarding cigarette smoking and increased risk of retinopathy in diabetes patients. Some studies suggest an association [2--31 while others do not [46]. At this time, it cannot be concluded that cigarette smoking constitutes an independent risk for retinopathy in diabetes patients. Smoking has been found to be a factor in the Ltd.
182
development of nephropathy [4-71 and for the progression from incipient to overt nephropathy [6]. Smoking also causes vasoconstriction which contributes to the health problems associated with arteriosclerosis [8-lo]. Diabetes patients who smoke are also more likely to experience peripheral circulatory problems than diabetes patients who do not smoke [11,12]. Diabetes patients have a greater need than the general public not to smoke. Health professionals have a responsibility to help all persons reduce or stop cigarette smoking and for some patients, those with heart and respiratory disease and diabetes, the need to help the patients is even greater. The long term success rate for smoking cessation programs for the general public tend to fall between 25 and 40% [ 131. Those for people with chronic diseases related to smoking have a greater opportunity for success and the success rate may be increased when interventions are intensified and when physician advice and follow-up are provided. The MRFIT experience found that 40% of smokers in a group of men in the upper 10-l 5% of heart attack risk were abstinent 4 years after intervention that consisted of group programs employing behavioral assessment, self-monitoring, behavioral contracts, and relaxation techniques [14]. The impact of physician advice and follow-up has proven to be substantial. The cessation results of physician intervention ranges from 3 to 5% for advice to quit accompanied by an informational leaflet to 23% for firm advice, three to five minute counseling and one, three, and six month follow-up [15]. However, patients are more likely to receive advice and assistance to stop smoking if a smoking related disease is present [14], and physicians are more likely to advise cessation for patients with active disease than for well patients [ 161. Diabetes patients present an unusual situation. Although smoking is not a factor in the development of the disease, some of the complications are exacerbated by smoking. Physicians may be less likely to advise diabetes
patients to stop smoking because the disease is not caused by smoking and likewise beliefs about the effect of smoking on diabetes may be less of a factor in the decision by diabetes patients to stop smoking. A comparison of smokers and ex-smokers in the diabetes population may be useful when the comparison is made on the basis of beliefs about smoking and diabetes and on the basis of advice from their physician to stop smoking. The comparison will enable educators to design better smoking cessation interventions. Beliefs about the relationship between smoking and diabetes complications may be important determinants in the process by which decisions to attempt to stop smoking are made and are likely to be formed as a result of advice from the patients’ physicians. In the general population, there are many variables associated with whether or not a smoker will become an ex-smoker. Among these are demographic variables: age, race, marital status, gender, level of education, number of pounds over/under-weight, and the number of smokers in the household. Smokers who are older, better educated, and have fewer smokers in their environment are more likely to be able to stop than younger, less educated smokers. Male, blue collar and unemployed black males are the least likely to have tried to stop smoking. Women may have more difficulty abstaining from smoking than men. [17]. And Stevens et al. reported that smoking behavior is related to exercise in that those who exercise more are likely to smoke less [18]. Pederson, Baskerville, and Wanklin reported that in a study of pulmonary patients, being married was positively associated with quitting [19]. There are also variables associated with one’s lifestyle and smoking history that may also be associated with the likelihood of stopping smoking. These include: duration of the smoking habit, number of cigarettes smoked, and the number of attempts to stop smoking. For both males and females and across birth cohorts, the younger one begins to smoke, the more likely one is to be a current smoker. Those who
183
smoke a greater number of cigarettes per day are less likely to stop; and the likelihood of stopping increases with the number of attempts to stop [ 171. The Health Belief Model (HBM) has been widely used as a framework to study the relationship between various beliefs about disease and related causal behavior and decisions to change the behavior in question. It has been used to study smoking behavior and to study compliance behavior of diabetes patients, but never to study smoking behavior of diabetes patients. The basic components of the HBM framework are: perceived susceptibility to a disease or condition; perceived severity of the disease or condition; the perceived benefits of making the behavior change in question; the perceived barrier or costs (in terms of pain, inconvenience, discomfort, time) of making the change in relation to the benefits; a cue to action; and various modifying factors including social support [20]. Compliance with recommended regimen by diabetes patients has been examined using the HBM as a framework. A study by Alogna found compliance with a diet regimen more likely by patients who perceived their illness as more severe [21]. Cerkoney and Hart reported that a total compliance score for insulin administration, urine testing, diet, hypoglycemia management, and foot care was positively associated with each of the HBM components [22]. Harris et al. found significant correlations between beliefs about susceptibility to complications and dietary compliance, between perceptions of benefits and exercise, and between barriers to change and use of medication [23]. The HBM has also been used as a framework to study cigarette smoking. Aho reported a significant relationship between seriousness and smoking [24] and Weinberger et al. were able to correctly classify 66% of 120 patients as current smokers, as moderate smokers (10 or fewer cigarettes per day), or as ex-smokers based on beliefs of susceptibility and severity [25]. The Health Belief Model was used as a framework for examining the relationship
between beliefs about diabetes and smoking and the role of these beliefs in smoking cessation by diabetes patients [ 181. Variables were investigated in correspondence with the dimensions of the model (Table I). The purpose of this study was to determine whether one or a combination of these variables could be used to differentiate smokers and exsmokers in the diabetes population. Method
Instrumentation The instrument was divided into four sections containing questions that were phrased differently depending upon smoking status. The items were divided into three categories that included demographics, lifestyle items, and items related to components of the health belief model (see Table II). The personal and demographic items were selected because of their demonstrated influence on smoking cessation. The items relating to the influence of physicians and beliefs about smoking and diabetes were adapted from instruments used by Pederson et al. [19] with research involving respiratory disease patients. Table I.
Dimension
Variable(s)
Percived susceptibility
Beliefs that smoking makes diabetes worse Beliefs about the extent to which smoking makes diabetes worse Beliefs that stopping smoking makes diabetes improve Beliefs about the extent to which stopping smoking makes diabetes improve Physician advice to stop smoking Perceptions of the strength of the advice Physician assistance to stop smoking Demographic and personal variables listed above Social support to stop smoking
Perceived severity
Perceived benefits
Cue to action
Modifying factors
184 Table
II.
Smoking
behavior
questionnaire:
summary
of
items. Education Marital status No. smokers in household
Demographic items
Age Race Gender
Lifestyle items
Exercise Pounds over/under weight No. cigarettes smoked per day No attempts to stop smoking Duration of the smoking habit
Health belief items
Advised by your physician to stop smoking if yes, perception of the strength of the advice 12345 Assistance to quit smoking provided by your physician Belief that smoking makes diabetes worse if yes, to what extent 12345 Belief that stopping smoking improves diabetes if yes, to what extent 12345 Help to stop smoking by some one close
Section 1: Demographics only. Completed by all respondents (including non-smokers) Section 2: Completed by all respondents who had ever been a smoker Section 3: Completed by ex-smokers only Section 4: Completed by current smokers only
Sample The study population consisted of patients on the patient registry at the University of Virginia Diabetes Research and Training Center (DRTC). The final mailing list consisted of 435 patients. The survey was returned by 183 (45%) of the patients. The response rate was a concern to the researchers. A comparison was made of demographics of the sample and of the DRTC population as a whole, and based on the comparison the sample was considered representative. The DRTC registry did not include smoking status. Of the 183 respondents, 70 diabetic patients composed
the target sample of interest for this study. These 70 were or had been smokers. Of this sample of 70, 40 were current smokers, and 30 were ex-smokers. The mean age of the sample was 58 years (SD. = 11.5). Most were male (56%), 50% were married, 67% were black, and 54% were educated beyond elementary school. The majority (76%) were non-insulin dependent. The mean duration of diabetes was 10 years and the mean duration of smoking was 26 years. Patients in this sample were an average 27 pounds overweight using the mid-range of the Metropolitan Life Insurance scale. None (0%) reported participating in a smoking cessation program. Analyses Two questions were addressed. The first question was whether current smokers and exsmokers can be differentiated on the basis of demographic characteristics and lifestyle characteristics. Eight variables based on the Health Belief Model were also investigated. They include: advice from a physician to stop smoking perceived strength of the advice assistance (to stop smoking) from the physician beliefs about the effect of smoking on diabetes beliefs about the extent of the effect beliefs about the benefits of stopping smoking on diabetes beliefs about the extent of the benefits social support to stop smoking (the item that measured social support to stop smoking specifically asked “When you stopped smoking (attempted to stop) would you say that someone close to you helped you to stop?“) The set of variables above became the set of independent variables which were considered in the effort to differentiate smokers from ex-smokers. Therefore the dependent variable in this study was smoking status, indicating whether or not individuals had been successful at smoking cessation. Patients
185
who had smoked in their lifetime were classified as either smokers or ex-smokers. Smokers were defined as those who had smoked three or more cigarettes per day on a regular basis any time within the past year. Ex-smokers were defined as those who had once smoked three or more cigarettes per day on a regular basis sometime in their life but not within the past year. The variables listed above were entered into the discriminant function using the stepwise procedure. The stepwise procedure was chosen so that the order of entry of the variables into the discriminant function could be controlled by their ability to add to the prediction. Those variables that have limited value as predictors are not entered into the discriminant analysis equation, The stepwise procedure was followed until no additional variable provided improvement in predicting group membership (smoking status as either smoker or ex-smoker). Statistical significance of the function was evaluated by means of Wilk’s lambda. The second question of interest was: What was the ability of health belief variables to differentiate current smokers from ex-smokers, after accounting for the predictive power of demographic and lifestyle characteristics. These variables were: physicians’ advice to stop smoking; physicians’ assistance to stop smoking; perceptions of the strength of advice to stop smoking; belief that smoking makes diabetes worse; beliefs about the extent to which smoking makes diabetes worse; belief that stopping smoking will improve diabetes related health problems; beliefs about the extent to which stopping smoking improves diabetes related health problems; and support of family or friends during attempts to stop smoking. The second question was again addressed by using a discriminant analysis procedure, the set of variables measuring demographic and lifestyle characteristics which were shown to be effective in differentiating the two groups were entered into the discriminant equation and then the eight health belief
variables were entered. The result was evaluated with a Wilk’s lambda statistic and a significance level of 0.05 or less was considered statistically significant. Results
The first question was whether smokers and ex-smokers can be differentiated on the basis of demographic or lifestyle variables. The 16 variables were entered into the discriminant analysis equation in step-wise manner. Six remained in the equation based on their power to predict (P < 0.05) and were able to account for 21% of the variance (Table V). Being older, married, more overweight, exercising more frequently, smoking fewer cigarettes per day and having made a greater number of attempts to stop were predictive of ex-smokers. The results of this discriminant analysis procedure are presented in Tables III and IV. The second question concerned whether smokers and ex-smokers in the diabetes population could be differentiated on the basis of the predictor variables as a group after consideration of the significant set of demographic and lifestyle variables. The six variables that were found to be predictive were first entered into the equation, then the eight health belief variables were entered as a group. The group of health belief variables as a group raised the amount of variance that could be accounted for from 21 %I to 42%. The canonical correlation was 0.65 and the Wilk’s lambda value was statistically significant. Results of the second discriminant analysis are presented in Table VI. Predictor variables that were able to make significant individual contributions to the discriminant analysis were: - physicians’ advice to stop; - physicians’ assistance to stop, and - social support to stop smoking. Patients who had been given advice and assistance to stop smoking from their physician and who received social support were
186 Table IIL4.
Comparison of smokers and ex-smokers by demographic and lifestyle statistics with means and standard deviations. Ex-smokers (A’= 30) Mean
Age (y=rs)
SD
60.4 0.63 + 33.0 19.5 18.1 3.1 1.8
No. smokers in household Pounds over/under weight Duration of habit (years) No. cigarettes smoked/day No attempts to stop Frequency of exercise/week
11.5 0.9 33.1 14.5 10.1 3.1 0.4
Table IIIB. Comparison of smokers and ex-smokers demographic and lifestyle with descriptive statistics. Ex-smokers (@Jo)
Smokers (Qa)
Race Black White
73 21
65 35
Marital status Married Not maried
60 40
31 63
47 53 54
45 55 53
Gender Male Female Education beyond elementary
by
Table IV. Comparison of smokers and ex-smokers by predictor variables with descriptive variables.
MD Advice to stop (Voyes) Strength of advice (5-point scale) MD assistance to stop (@IO yes) Believe smoking makes diabetes worse (Voyes) Extent of belief @-point scale) Believe stopping improves diabetes (To yes) Extent of belief &point scale) Social support to stop (To yes)
Smokers (N = 40)
Ex-smokers (N = 30)
Smokers (N = 40)
55 3.75 22 38
38 3.71 16 13
3.0 43
2.9 30
3.7 37
2.6 13
Mean 56.4 0.78 + 23.0 31.5 19.9 2.1 1.7
SD 11.4 0.8 28.0 5.1 10.2 0.4 2.9
more likely to be ex-smokers. In discriminant analysis individual variables may remain in an analysis even when the individual significance level is greater than 0.05. Discussion The differentiation between the smokers and the ex-smokers in a diabetes population analyzing the accomplished by was contribution of various combinations of independent variables in predicting membership in either the group of smokers or the group of ex-smokers. The first procedure involved a stepwise discriminant analysis and revealed that six of the demographic and lifestyle variables were significant predictors of smoking status of diabetes patients. The predictors of smokers/ex-smokers are similar to those for the general population. Two demographic variables that are predictors for the general population (race and gender) were not significant in this study. Frequency of exercise remained in the stepwise discriminant function even though the frequency for smokers and for ex-smokers was low and the variance among the two groups was slight. Advice from a physician is a predictor of cessation in the general population but much less so for non-smoking related disease patients. It should be noted that differences observed between smokers and ex-smokers in a retrospective study like this may represent health beliefs that existed concurrently with the decision to quit and are not necessarily an
187
Table V.
Summary table for stepwise discriminant analysis of control variables.
Order
Variables entered
Wilk’s lambda
Significance level
1 2 3 4 5 6
Marital status Age Pounds over/under weight Exercise No cigarettes smoked/day No attempts to stop
0.95 0.91 0.86 0.83 0.81 0.79
0.054 0.036 0.016 0.015 0.017 0.020
Canonical correlation
=
R'
=
Significance
=
Table VI. variables.
Standardized weights 0.579 0.746 0.525 0.383 0.356 - 0.323
0.454 0.206 0.020
Summary table for direct discriminant analysis for all predictor variables as a group after consideration of control
Order
Variables entered
Wilk’s lambda
Significance level
Standardized weights
1 2 3 4 5 6 7 8 9 10
Age
0.96 0.89 0.86 0.85 0.78 0.74 0.73 0.73 0.73 0.73
0.170 0.049 0.058 0.077 0.031 0.020 0.031 0.054 0.087 0.131
0.348 - 0.438 0.041 0.161 0.407 - 0.660 0.073 - 0.067 0.135 - 0.914
0.72
0.157
0.790
0.71
0.205
- 0.079
0.71
0.273
0.085
0.037
0.871
11
12
13
14
Married Exercise Pounds over/under weight No. cigarettes smoked/day No. attempts to stop MD advice to stop MD assist to stop Strength of MD advice Beliefs that smoking makes diabetes worse Beliefs about extent to which smoking makes diabetes worse Believes that stopping smoking makes diabetes improve Beliefs about extent to which stopping smoking makes diabetes improve Support to stop Canonical correlation
R= Significance
0.58 = = =
0.647 0.419 0.037
188
indication that the beliefs caused the smokers to quit. A prospective study that could document when changes in beliefs occur and determine if those changes were followed by a decision to quit would provide helpful insight. Patients who were more pounds overweight were more likely to be ex-smokers. One of the fears often expressed by smokers who are trying to quit is that of gaining weight after quitting. This concern may be of greater magnitude for diabetes patients and clinicians who treat them. It should be pointed out that weight gain does not always accompany cessation, but since the concern is great, dietary counseling should be intensified when assisting diabetes patients to stop. Smoking cessation and weight reduction are both complex behavior changes and should not be attempted simultaneously. It may be best to delay smoking cessation until after ideal body weight has been achieved and maintained for an ample period of time to indicate stability. Elements of the health belief model (i.e. perceptions of severity, perceptions of susceptibility, cues to action, and the modifying factor social support) were significant predictors of smoking cessation by diabetes patients beyond the demographic and lifestyle variables. Social support to stop smoking has been identified as a correlate with successful smoking cessation. There is some variation in the manner in which social support has been documented and reported. Ockene et al. compared success rates of participants in a smoking cessation program whose significant other also took part with those who attended alone. Those who were accompanied were more likely to be successful [26]. Mermelstein et al. studied the relationship between the frequency and perceived helpfulness of spouse interactions related to smoking cessation and successful abstinence at l-, 3-, and 6intervention. followups after month Successful abstainers had significantly higher “experienced helpfulness” scores than those who did not quit or who quit and relapsed [27]. Mallott et al. found that participants in
a worksite smoking cessation program who were matched with other participants as partners were no more likely to reduce the number of cigarettes smoked daily, nor to reduce the percentage of each cigarette smoked [28]. Future studies that assess the amount and specific nature of social support and the intensity of the relationship between the smoker and the support person would be helpful. Sallis et al. have developed scales to measure social support for diet and exercise that may be adaptable for smoking cessation
PI In this study less than half of the patients receiving care in this treatment center reported that their doctor advised them to stop smoking and 83% did not report that they received assistance or suggestions on how to stop smoking. This indicates that they either were not advised to stop smoking or they were advised but do not recall being given advice. It is possible that when advice to stop smoking is given to diabetes patients it is not given the same emphasis as other advice included in the treatment regimen for diabetes and thus makes less of an impact. Table VII.
(1) (2)
(3)
(4)
(9
Implications for practice.
Determine the present and past smoking behavior of each diabetes patient during patient counseling Firm advice to stop smoking should be given by all persons treating patients for diabetes and should be originated and continually reinforced by the physician, the advice should be accompanied by a thorough explanation of the effects of smoking on diabetes and by specific suggestions for cessation strategies An in-depth assessment should be done of the special circumstances of smokers in the diabetes population in terms of cessation strategies, history of smoking behavior, and beliefs about smoking and diabetes Diabetes patients should be given clear and concise information about the relationship between smoking and the complications of diabetes. This relationship is not as widely known as that of smoking and heart disease or lung cancer and it should not be assumed that diabetes patients have this information Diabetes patients who smoke should be urged to employ available support persons to assist them in the cessation process; when appropriate, support persons should be invited to any smoking related counseling; when feasible patients should be referred to an established smoking cession program with timely follow-up for compliance
189
Further investigation of this topic might investigate what specific information diabetes patients have with respect to just how smoking may complicate their health problems and from what source did they receive their information. These findings lead to recommendations that are implications for practice for those who provide clinical and educational services to diabetes patients (Table VII).
16
methods: United States and Canada. 1978-1985. U.S. Department of Health and Human Service, National Institutes of Health. NlH Publication No. 87-2940, April 1987. Washington, DC: U.S. Government Printing Office. Ockene JK, Hymowitz N, Sexton M, Broste SK: Comparison of patterns of smoking behavior change among smokers in the Multiple Risk Factor Intervention Trial (MRFIT). Prev Med 1982; 11: 621-638. Ockene JK: Physician-delivered interventions for smoking cessation: strategies for increasing effectiveness. Prev Med 1987; 16: 723-737. Ockene, JK, Hosmer DW, Williams JW, Goldber RJ,
17
Ockene IS, Dalen JE: The relationship of patient characteristics to physician delivered smoking cessation advice. J Gen Intern Med 1987; 2: 337-340. U.S. Department of Health and Human Service: Smoking
14
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U.S. Surgeon General: The health consequences of smoking: Nicotine addiction. A report of the Surgeon General. Washington, DC: U.S. Government Printing office, 1988. Eadington DW, Patrick AW, Collier A, Frier BM: Limited joint mobility, Dupuytren’s contracture and retinopathy in type 1 diabetes: association with cigarette smoking. Diabetic Med 1989; 6: 152-157. Walker JM, Cove DH, Beeverg DC, Dodson PM, Leatherdale BA, Fletcher RF, Wright AD: Cigarette smoking, blood pressure and the control of blood glucose in the development of diabetic retionpathy. Diabetes Res 1985; 2: 183-186. Telmer S, Christiansen JS, Andersen AR, Nerup .I, Deckert T: Smoking habits and prevalence of clinical diabetic microangiopathy in insulin dependent diabetics. Acta Med Stand 1984; 215 : 63-68; Paetkau KE, Bod TA, Winship B, Grace M: Cigarette smoking and diabetic retinopathy. Diabetes 1977; 26: 46-49. Klein R, Klein BE, Davis MD: Is cigarette smoking associated with diabetic retinopathy? Am J Epidemiol 1983; 118: 228-238. Muhlhauser 1, Sawicki P, Berger M: Cigarette smoking as a risk factor for macroproteinuria and proliferative retinopathy in type 1 (insulin dependent) diabetes. Diabetologia 1986; 29: 500-502. Norden G, Nyberg G: Smoking and diabetic nephropathy. Acta Med Stand 1984; 215: 257-261. Brothers MJ: Diabetes, the New Approach. New York: Gosset and Dunlap, 1976, p. 229. Vague J, Vague P, Ebling J: Diabetes and Obesity. Amsterdam: Excerpta Medica, 1978, p. 399. Suarez L, Barrett-Conner E: Interaction between cigarette smoking and diabetes mellitus in the prediction oi death attributed to cardiovascular disease. Am J Epidemiol 1984; 120: 670-675. Beach KW, Standness DE: Arteriosclerosis obliterans and associated risk factors in insulin-dependent and noninsulin dependent diabetes. Diabetes 1980; 29: 882-888. Liedberg E, Persson BM: Age, diabetes and smoking in lower limb amputation for arterial occlusive disease. Acta Orthoped Stand 1983; 54: 383-384. Schwartz JL: Review and evaluation of smoking cessation
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and Health: A National Status Report. Washington, DC: U.S. Government Printing Office, 1986. Stevens PA, Greene JT, Primavera LH: Predicting successful smoking cessation. J Sot Psycho1 1982; 118: 235241. Pederson LL, Baskerville JC, Wanklin JM: Multivariate statistical models for predicting change in smoking behavior following physician advice to quit smoking. Prev Med 1982; 11: 536-549. Jam NK, Becker MH: The Health Belief Model: a decade later. Health Educ Q 1984; 11: l-47. Alogna M: Perception of severity of disease and health locus of control in compliant and noncompliant diabetic patients. Diabetes Care 1980; 3: 533-534. Cerkoney KA, Hart LK: The relationship between the health belief model and compliance of persons with diabetes mellitus. Diabetes Care 1980; 3: 594.-598. Harris R, Skyler JS, Linn MW, et al: Relationship between the health belief model and compliance as a basis for intervention in diabetes mellitus. In: Psychological Aspects of Diabetes in Children and Adolescents. Pediatric Adolescent Endocrinology 1982; 10: 123-132. Aho WR: Smoking, dieting, and exercise: age differences in attitudes and behavior relevant to selected health belief model variables. Rhode Island Med J 1979; 62: 85-92. Weinberger M, Greene JY, Mamlin JJ et al: Health beliefs and smoking behavior. Am .I Public Health 1981; 71: 1253-1255. Ockene JK, Benfari RC, Nuttal RL, Hurwjitz I: Relationship of psychosocial factors to smoking behavior change in an intervention program. Prev Med 1982; I I : 13-28. Mermelstein R, Lichtenstein E, McIntyre K: Partner support and relapse in smoking cessation programs. J Consult Clin Psycho1 1983; 5 I : 465-466. Malott JM, Glasgow RE, O’Neii HK, Klesges RC: Coworker social support in a worksite smoking control program. J Appl Behav Anal 1984; 17: 485--495. Sallis JF, Grossman MS, Pinski MS, Patterson TL, Nader PR: The development of scales to measure social support for diet and exercise behaviors Prev Med 1987; 16: 825-836.
Patient Education and Counseling, 15(1990) 181-189 Elsevier Scientific
Publishers
Ireland
Ltd.
An Investigation of Beliefs About Smoking Among Diabetes Patients: Information for Improving Cessation Efforts Richard D. Stacy and Brenda H. Loyd” School of HPER, University of Nebraska at Omaha, Omaha, NE 68182-0216 and “Department of Educational Research, Curry School of Education, University of Virginia, Charlottesville, VA 22903 (U.S.A.) (Received March 3rd, 1989) (Accepted October 27th, 1989)
Abstract
The purpose of this study was to identify differences between current smokers and exsmokers in beliefs about the health effects of smoking. This information will enable educators to design better smoking cessation interventions for diabetes patients. A smoking behavior questionnaire was developed to collect information about demographics, personal lifestyle, and beliefs about smoking and diabetes. Participants were 40 current smokers and 30 ex-smokers located from a patient registry at the University of Virginia Diabetes Research and Training Center. Less than half of the diabetic smokers in the study reported receiving advice to quit from their physician and none of them reported having attended a formal smoking cessation program. Results indicate that demographic and lifestyle variables predict 21 oloof the variance between smokers and non-smokers in this sample. The group of health belief variables collectively raised the amount of variance that could be accounted for from 21% to 42 9’0.It is recommended that health professionals who provide services to diabetes patients determine present smoking behavior of each diabetes patient, provide firm advice to stop smoking, R.D. Stacy, EdD, Assistant Health Education.
Professor
and
Coordinator
of
B.H.Loyd,PhD,AssistantProfessorofEducationalResearch.
0738-3991/90/%03.50 Published and Printed
0 1990 Elsevier Scientific in Ireland
Publishers
lreland
assess the special circumstances of the smokers, and offer specific smoking cessation programs to meet the unique needs o-f diabetes patients. Keywords: Smoking cessation; Diabetes.
Introduction
Cigarette smoking is a factor in the development of a variety of chronic diseases including heart disease, emphysema, chronic bronchitis, and many types of cancer [l]. Cigarette smoking is not a factor in the development of diabetes, but many of the problems associated with diabetes are complicated by cigarette smoking. The most serious health risks for persons with diabetes are: increased risks of blindness due to diabetic retinopathy, increased risks of kidney failure due to nephropathy, a two-fold increase in risk for heart disease, and increased risks of losing lower extremities due to problems with peripheral circulation. There is conflicting evidence regarding cigarette smoking and increased risk of retinopathy in diabetes patients. Some studies suggest an association [2--31 while others do not [46]. At this time, it cannot be concluded that cigarette smoking constitutes an independent risk for retinopathy in diabetes patients. Smoking has been found to be a factor in the Ltd.
182
development of nephropathy [4-71 and for the progression from incipient to overt nephropathy [6]. Smoking also causes vasoconstriction which contributes to the health problems associated with arteriosclerosis [8-lo]. Diabetes patients who smoke are also more likely to experience peripheral circulatory problems than diabetes patients who do not smoke [11,12]. Diabetes patients have a greater need than the general public not to smoke. Health professionals have a responsibility to help all persons reduce or stop cigarette smoking and for some patients, those with heart and respiratory disease and diabetes, the need to help the patients is even greater. The long term success rate for smoking cessation programs for the general public tend to fall between 25 and 40% [ 131. Those for people with chronic diseases related to smoking have a greater opportunity for success and the success rate may be increased when interventions are intensified and when physician advice and follow-up are provided. The MRFIT experience found that 40% of smokers in a group of men in the upper 10-l 5% of heart attack risk were abstinent 4 years after intervention that consisted of group programs employing behavioral assessment, self-monitoring, behavioral contracts, and relaxation techniques [14]. The impact of physician advice and follow-up has proven to be substantial. The cessation results of physician intervention ranges from 3 to 5% for advice to quit accompanied by an informational leaflet to 23% for firm advice, three to five minute counseling and one, three, and six month follow-up [15]. However, patients are more likely to receive advice and assistance to stop smoking if a smoking related disease is present [14], and physicians are more likely to advise cessation for patients with active disease than for well patients [ 161. Diabetes patients present an unusual situation. Although smoking is not a factor in the development of the disease, some of the complications are exacerbated by smoking. Physicians may be less likely to advise diabetes
patients to stop smoking because the disease is not caused by smoking and likewise beliefs about the effect of smoking on diabetes may be less of a factor in the decision by diabetes patients to stop smoking. A comparison of smokers and ex-smokers in the diabetes population may be useful when the comparison is made on the basis of beliefs about smoking and diabetes and on the basis of advice from their physician to stop smoking. The comparison will enable educators to design better smoking cessation interventions. Beliefs about the relationship between smoking and diabetes complications may be important determinants in the process by which decisions to attempt to stop smoking are made and are likely to be formed as a result of advice from the patients’ physicians. In the general population, there are many variables associated with whether or not a smoker will become an ex-smoker. Among these are demographic variables: age, race, marital status, gender, level of education, number of pounds over/under-weight, and the number of smokers in the household. Smokers who are older, better educated, and have fewer smokers in their environment are more likely to be able to stop than younger, less educated smokers. Male, blue collar and unemployed black males are the least likely to have tried to stop smoking. Women may have more difficulty abstaining from smoking than men. [17]. And Stevens et al. reported that smoking behavior is related to exercise in that those who exercise more are likely to smoke less [18]. Pederson, Baskerville, and Wanklin reported that in a study of pulmonary patients, being married was positively associated with quitting [19]. There are also variables associated with one’s lifestyle and smoking history that may also be associated with the likelihood of stopping smoking. These include: duration of the smoking habit, number of cigarettes smoked, and the number of attempts to stop smoking. For both males and females and across birth cohorts, the younger one begins to smoke, the more likely one is to be a current smoker. Those who
183
smoke a greater number of cigarettes per day are less likely to stop; and the likelihood of stopping increases with the number of attempts to stop [ 171. The Health Belief Model (HBM) has been widely used as a framework to study the relationship between various beliefs about disease and related causal behavior and decisions to change the behavior in question. It has been used to study smoking behavior and to study compliance behavior of diabetes patients, but never to study smoking behavior of diabetes patients. The basic components of the HBM framework are: perceived susceptibility to a disease or condition; perceived severity of the disease or condition; the perceived benefits of making the behavior change in question; the perceived barrier or costs (in terms of pain, inconvenience, discomfort, time) of making the change in relation to the benefits; a cue to action; and various modifying factors including social support [20]. Compliance with recommended regimen by diabetes patients has been examined using the HBM as a framework. A study by Alogna found compliance with a diet regimen more likely by patients who perceived their illness as more severe [21]. Cerkoney and Hart reported that a total compliance score for insulin administration, urine testing, diet, hypoglycemia management, and foot care was positively associated with each of the HBM components [22]. Harris et al. found significant correlations between beliefs about susceptibility to complications and dietary compliance, between perceptions of benefits and exercise, and between barriers to change and use of medication [23]. The HBM has also been used as a framework to study cigarette smoking. Aho reported a significant relationship between seriousness and smoking [24] and Weinberger et al. were able to correctly classify 66% of 120 patients as current smokers, as moderate smokers (10 or fewer cigarettes per day), or as ex-smokers based on beliefs of susceptibility and severity [25]. The Health Belief Model was used as a framework for examining the relationship
between beliefs about diabetes and smoking and the role of these beliefs in smoking cessation by diabetes patients [ 181. Variables were investigated in correspondence with the dimensions of the model (Table I). The purpose of this study was to determine whether one or a combination of these variables could be used to differentiate smokers and exsmokers in the diabetes population. Method
Instrumentation The instrument was divided into four sections containing questions that were phrased differently depending upon smoking status. The items were divided into three categories that included demographics, lifestyle items, and items related to components of the health belief model (see Table II). The personal and demographic items were selected because of their demonstrated influence on smoking cessation. The items relating to the influence of physicians and beliefs about smoking and diabetes were adapted from instruments used by Pederson et al. [19] with research involving respiratory disease patients. Table I.
Dimension
Variable(s)
Percived susceptibility
Beliefs that smoking makes diabetes worse Beliefs about the extent to which smoking makes diabetes worse Beliefs that stopping smoking makes diabetes improve Beliefs about the extent to which stopping smoking makes diabetes improve Physician advice to stop smoking Perceptions of the strength of the advice Physician assistance to stop smoking Demographic and personal variables listed above Social support to stop smoking
Perceived severity
Perceived benefits
Cue to action
Modifying factors
184 Table
II.
Smoking
behavior
questionnaire:
summary
of
items. Education Marital status No. smokers in household
Demographic items
Age Race Gender
Lifestyle items
Exercise Pounds over/under weight No. cigarettes smoked per day No attempts to stop smoking Duration of the smoking habit
Health belief items
Advised by your physician to stop smoking if yes, perception of the strength of the advice 12345 Assistance to quit smoking provided by your physician Belief that smoking makes diabetes worse if yes, to what extent 12345 Belief that stopping smoking improves diabetes if yes, to what extent 12345 Help to stop smoking by some one close
Section 1: Demographics only. Completed by all respondents (including non-smokers) Section 2: Completed by all respondents who had ever been a smoker Section 3: Completed by ex-smokers only Section 4: Completed by current smokers only
Sample The study population consisted of patients on the patient registry at the University of Virginia Diabetes Research and Training Center (DRTC). The final mailing list consisted of 435 patients. The survey was returned by 183 (45%) of the patients. The response rate was a concern to the researchers. A comparison was made of demographics of the sample and of the DRTC population as a whole, and based on the comparison the sample was considered representative. The DRTC registry did not include smoking status. Of the 183 respondents, 70 diabetic patients composed
the target sample of interest for this study. These 70 were or had been smokers. Of this sample of 70, 40 were current smokers, and 30 were ex-smokers. The mean age of the sample was 58 years (SD. = 11.5). Most were male (56%), 50% were married, 67% were black, and 54% were educated beyond elementary school. The majority (76%) were non-insulin dependent. The mean duration of diabetes was 10 years and the mean duration of smoking was 26 years. Patients in this sample were an average 27 pounds overweight using the mid-range of the Metropolitan Life Insurance scale. None (0%) reported participating in a smoking cessation program. Analyses Two questions were addressed. The first question was whether current smokers and exsmokers can be differentiated on the basis of demographic characteristics and lifestyle characteristics. Eight variables based on the Health Belief Model were also investigated. They include: advice from a physician to stop smoking perceived strength of the advice assistance (to stop smoking) from the physician beliefs about the effect of smoking on diabetes beliefs about the extent of the effect beliefs about the benefits of stopping smoking on diabetes beliefs about the extent of the benefits social support to stop smoking (the item that measured social support to stop smoking specifically asked “When you stopped smoking (attempted to stop) would you say that someone close to you helped you to stop?“) The set of variables above became the set of independent variables which were considered in the effort to differentiate smokers from ex-smokers. Therefore the dependent variable in this study was smoking status, indicating whether or not individuals had been successful at smoking cessation. Patients
185
who had smoked in their lifetime were classified as either smokers or ex-smokers. Smokers were defined as those who had smoked three or more cigarettes per day on a regular basis any time within the past year. Ex-smokers were defined as those who had once smoked three or more cigarettes per day on a regular basis sometime in their life but not within the past year. The variables listed above were entered into the discriminant function using the stepwise procedure. The stepwise procedure was chosen so that the order of entry of the variables into the discriminant function could be controlled by their ability to add to the prediction. Those variables that have limited value as predictors are not entered into the discriminant analysis equation, The stepwise procedure was followed until no additional variable provided improvement in predicting group membership (smoking status as either smoker or ex-smoker). Statistical significance of the function was evaluated by means of Wilk’s lambda. The second question of interest was: What was the ability of health belief variables to differentiate current smokers from ex-smokers, after accounting for the predictive power of demographic and lifestyle characteristics. These variables were: physicians’ advice to stop smoking; physicians’ assistance to stop smoking; perceptions of the strength of advice to stop smoking; belief that smoking makes diabetes worse; beliefs about the extent to which smoking makes diabetes worse; belief that stopping smoking will improve diabetes related health problems; beliefs about the extent to which stopping smoking improves diabetes related health problems; and support of family or friends during attempts to stop smoking. The second question was again addressed by using a discriminant analysis procedure, the set of variables measuring demographic and lifestyle characteristics which were shown to be effective in differentiating the two groups were entered into the discriminant equation and then the eight health belief
variables were entered. The result was evaluated with a Wilk’s lambda statistic and a significance level of 0.05 or less was considered statistically significant. Results
The first question was whether smokers and ex-smokers can be differentiated on the basis of demographic or lifestyle variables. The 16 variables were entered into the discriminant analysis equation in step-wise manner. Six remained in the equation based on their power to predict (P < 0.05) and were able to account for 21% of the variance (Table V). Being older, married, more overweight, exercising more frequently, smoking fewer cigarettes per day and having made a greater number of attempts to stop were predictive of ex-smokers. The results of this discriminant analysis procedure are presented in Tables III and IV. The second question concerned whether smokers and ex-smokers in the diabetes population could be differentiated on the basis of the predictor variables as a group after consideration of the significant set of demographic and lifestyle variables. The six variables that were found to be predictive were first entered into the equation, then the eight health belief variables were entered as a group. The group of health belief variables as a group raised the amount of variance that could be accounted for from 21 %I to 42%. The canonical correlation was 0.65 and the Wilk’s lambda value was statistically significant. Results of the second discriminant analysis are presented in Table VI. Predictor variables that were able to make significant individual contributions to the discriminant analysis were: - physicians’ advice to stop; - physicians’ assistance to stop, and - social support to stop smoking. Patients who had been given advice and assistance to stop smoking from their physician and who received social support were
186 Table IIL4.
Comparison of smokers and ex-smokers by demographic and lifestyle statistics with means and standard deviations. Ex-smokers (A’= 30) Mean
Age (y=rs)
SD
60.4 0.63 + 33.0 19.5 18.1 3.1 1.8
No. smokers in household Pounds over/under weight Duration of habit (years) No. cigarettes smoked/day No attempts to stop Frequency of exercise/week
11.5 0.9 33.1 14.5 10.1 3.1 0.4
Table IIIB. Comparison of smokers and ex-smokers demographic and lifestyle with descriptive statistics. Ex-smokers (@Jo)
Smokers (Qa)
Race Black White
73 21
65 35
Marital status Married Not maried
60 40
31 63
47 53 54
45 55 53
Gender Male Female Education beyond elementary
by
Table IV. Comparison of smokers and ex-smokers by predictor variables with descriptive variables.
MD Advice to stop (Voyes) Strength of advice (5-point scale) MD assistance to stop (@IO yes) Believe smoking makes diabetes worse (Voyes) Extent of belief @-point scale) Believe stopping improves diabetes (To yes) Extent of belief &point scale) Social support to stop (To yes)
Smokers (N = 40)
Ex-smokers (N = 30)
Smokers (N = 40)
55 3.75 22 38
38 3.71 16 13
3.0 43
2.9 30
3.7 37
2.6 13
Mean 56.4 0.78 + 23.0 31.5 19.9 2.1 1.7
SD 11.4 0.8 28.0 5.1 10.2 0.4 2.9
more likely to be ex-smokers. In discriminant analysis individual variables may remain in an analysis even when the individual significance level is greater than 0.05. Discussion The differentiation between the smokers and the ex-smokers in a diabetes population analyzing the accomplished by was contribution of various combinations of independent variables in predicting membership in either the group of smokers or the group of ex-smokers. The first procedure involved a stepwise discriminant analysis and revealed that six of the demographic and lifestyle variables were significant predictors of smoking status of diabetes patients. The predictors of smokers/ex-smokers are similar to those for the general population. Two demographic variables that are predictors for the general population (race and gender) were not significant in this study. Frequency of exercise remained in the stepwise discriminant function even though the frequency for smokers and for ex-smokers was low and the variance among the two groups was slight. Advice from a physician is a predictor of cessation in the general population but much less so for non-smoking related disease patients. It should be noted that differences observed between smokers and ex-smokers in a retrospective study like this may represent health beliefs that existed concurrently with the decision to quit and are not necessarily an
187
Table V.
Summary table for stepwise discriminant analysis of control variables.
Order
Variables entered
Wilk’s lambda
Significance level
1 2 3 4 5 6
Marital status Age Pounds over/under weight Exercise No cigarettes smoked/day No attempts to stop
0.95 0.91 0.86 0.83 0.81 0.79
0.054 0.036 0.016 0.015 0.017 0.020
Canonical correlation
=
R'
=
Significance
=
Table VI. variables.
Standardized weights 0.579 0.746 0.525 0.383 0.356 - 0.323
0.454 0.206 0.020
Summary table for direct discriminant analysis for all predictor variables as a group after consideration of control
Order
Variables entered
Wilk’s lambda
Significance level
Standardized weights
1 2 3 4 5 6 7 8 9 10
Age
0.96 0.89 0.86 0.85 0.78 0.74 0.73 0.73 0.73 0.73
0.170 0.049 0.058 0.077 0.031 0.020 0.031 0.054 0.087 0.131
0.348 - 0.438 0.041 0.161 0.407 - 0.660 0.073 - 0.067 0.135 - 0.914
0.72
0.157
0.790
0.71
0.205
- 0.079
0.71
0.273
0.085
0.037
0.871
11
12
13
14
Married Exercise Pounds over/under weight No. cigarettes smoked/day No. attempts to stop MD advice to stop MD assist to stop Strength of MD advice Beliefs that smoking makes diabetes worse Beliefs about extent to which smoking makes diabetes worse Believes that stopping smoking makes diabetes improve Beliefs about extent to which stopping smoking makes diabetes improve Support to stop Canonical correlation
R= Significance
0.58 = = =
0.647 0.419 0.037
188
indication that the beliefs caused the smokers to quit. A prospective study that could document when changes in beliefs occur and determine if those changes were followed by a decision to quit would provide helpful insight. Patients who were more pounds overweight were more likely to be ex-smokers. One of the fears often expressed by smokers who are trying to quit is that of gaining weight after quitting. This concern may be of greater magnitude for diabetes patients and clinicians who treat them. It should be pointed out that weight gain does not always accompany cessation, but since the concern is great, dietary counseling should be intensified when assisting diabetes patients to stop. Smoking cessation and weight reduction are both complex behavior changes and should not be attempted simultaneously. It may be best to delay smoking cessation until after ideal body weight has been achieved and maintained for an ample period of time to indicate stability. Elements of the health belief model (i.e. perceptions of severity, perceptions of susceptibility, cues to action, and the modifying factor social support) were significant predictors of smoking cessation by diabetes patients beyond the demographic and lifestyle variables. Social support to stop smoking has been identified as a correlate with successful smoking cessation. There is some variation in the manner in which social support has been documented and reported. Ockene et al. compared success rates of participants in a smoking cessation program whose significant other also took part with those who attended alone. Those who were accompanied were more likely to be successful [26]. Mermelstein et al. studied the relationship between the frequency and perceived helpfulness of spouse interactions related to smoking cessation and successful abstinence at l-, 3-, and 6intervention. followups after month Successful abstainers had significantly higher “experienced helpfulness” scores than those who did not quit or who quit and relapsed [27]. Mallott et al. found that participants in
a worksite smoking cessation program who were matched with other participants as partners were no more likely to reduce the number of cigarettes smoked daily, nor to reduce the percentage of each cigarette smoked [28]. Future studies that assess the amount and specific nature of social support and the intensity of the relationship between the smoker and the support person would be helpful. Sallis et al. have developed scales to measure social support for diet and exercise that may be adaptable for smoking cessation
PI In this study less than half of the patients receiving care in this treatment center reported that their doctor advised them to stop smoking and 83% did not report that they received assistance or suggestions on how to stop smoking. This indicates that they either were not advised to stop smoking or they were advised but do not recall being given advice. It is possible that when advice to stop smoking is given to diabetes patients it is not given the same emphasis as other advice included in the treatment regimen for diabetes and thus makes less of an impact. Table VII.
(1) (2)
(3)
(4)
(9
Implications for practice.
Determine the present and past smoking behavior of each diabetes patient during patient counseling Firm advice to stop smoking should be given by all persons treating patients for diabetes and should be originated and continually reinforced by the physician, the advice should be accompanied by a thorough explanation of the effects of smoking on diabetes and by specific suggestions for cessation strategies An in-depth assessment should be done of the special circumstances of smokers in the diabetes population in terms of cessation strategies, history of smoking behavior, and beliefs about smoking and diabetes Diabetes patients should be given clear and concise information about the relationship between smoking and the complications of diabetes. This relationship is not as widely known as that of smoking and heart disease or lung cancer and it should not be assumed that diabetes patients have this information Diabetes patients who smoke should be urged to employ available support persons to assist them in the cessation process; when appropriate, support persons should be invited to any smoking related counseling; when feasible patients should be referred to an established smoking cession program with timely follow-up for compliance
189
Further investigation of this topic might investigate what specific information diabetes patients have with respect to just how smoking may complicate their health problems and from what source did they receive their information. These findings lead to recommendations that are implications for practice for those who provide clinical and educational services to diabetes patients (Table VII).
16
methods: United States and Canada. 1978-1985. U.S. Department of Health and Human Service, National Institutes of Health. NlH Publication No. 87-2940, April 1987. Washington, DC: U.S. Government Printing Office. Ockene JK, Hymowitz N, Sexton M, Broste SK: Comparison of patterns of smoking behavior change among smokers in the Multiple Risk Factor Intervention Trial (MRFIT). Prev Med 1982; 11: 621-638. Ockene JK: Physician-delivered interventions for smoking cessation: strategies for increasing effectiveness. Prev Med 1987; 16: 723-737. Ockene, JK, Hosmer DW, Williams JW, Goldber RJ,
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Ockene IS, Dalen JE: The relationship of patient characteristics to physician delivered smoking cessation advice. J Gen Intern Med 1987; 2: 337-340. U.S. Department of Health and Human Service: Smoking
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