Predictors of quitting in hospitalized smokers

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1 Nicotine & Tobacco Research (2003) 5, Predictors of quitting in hospitalized smokers Harry Lando, Deborah Hennrikus, Maribet McCarty, John Vessey [Received 12 October 2001; accepted 8 August 2002] Hospitalization represents a teachable moment for quitting. The current study examined predictors of quitting among hospitalized smokers. Patients reported smoking history and demographic characteristics during in-hospital baseline interviews. Discharge diagnosis also was collected. Smoking status was ascertained in interviews at 7 days and at 12 months after discharge. A total of 2,350 patients in four Minneapolis and St. Paul (Twin Cities), Minnesota, area hospitals participated in the study; 1,477 patients who provided data at both follow-ups and whose 12-month selfreport of quitting was corroborated by cotinine analysis of saliva samples were included in the current analyses. Predictors of both short- and long-term abstinence in the multivariate analysis included smoking-related illness, age (those who were older were more likely to be abstinent), stage of change (precontemplators were least likely to quit, and those initially in action were most likely to quit), and time to first cigarette (those who reported smoking within 5 min of awakening were least likely to quit). The predictors presented few surprises; the most important finding may have been that the experience of hospitalization itself led to substantial long-term quitting for virtually all categories of hospitalized smokers. Introduction Hospitalization represents a teachable moment for quitting smoking (Emmons & Goldstein, 1992; Goldstein, 1999; Rigotti, 2000a; Stevens, Glasgow, Hollis, & Mount, 2000). The recent clinical practice guideline for treating tobacco use and dependence recommends that hospitalized patients be provided smoking cessation treatments that have been shown to be effective (Fiore et al., 2000). However, an important issue may be the potential return on investment in delivering cessation services routinely to all hospitalized smokers. If resources are limited, concentrating resources on patients who are more likely to act on cessation advice might be warranted. This idea is reflected in the studies that have been published in this area. Although a few studies have attempted to intervene with all hospitalized smokers (Stevens et al., 2000; Rigotti, Arnsten, McKool, Wood-Reid, Pasternak, & Singer, 1997; Stevens, Glasgow, Hollis, Lichtenstein, & Vogt, 1993), most have focused on smokers who expressed interest in Harry Lando, Ph.D., Deborah Hennrikus, Ph.D. and Maribet McCarty, Ph.D., University of Minnesota, Minneapolis, MN; John Vessey, Ph.D., Wheaton College, Wheaton, IL. Correspondence: Harry Lando, University of Minnesota, Division of Epidemiology, 1300 South Second Street, Suite 300, Minneapolis, MN USA. Tel.: z1 (612) ; Fax: z1 (612) ; lando@epi.umn.edu quitting or had smoking-related disease (Johnson, Budz, Mackay, & Miller, 1999; Orleans & Slade, 1993; Taylor, Houston-Miller, Killen, & DeBusk, 1990). Results of studies that have included patients with a range of diagnoses indicate that quit rates among hospitalized smokers vary as a function of diagnosis (Gritz, Kristeller, & Burns, 1993; Ockene et al., 1992). Cardiovascular patients, for instance, quit at higher rates than do patients with other medical conditions (Goodman, Nadkarni, & Schorling, 1998; Rice, 1999; Rigotti, 2000b; Taylor et al., 1990; 1996). The current study examined predictors of quitting as part of the Teachable Moment (TEAM) project, a study that was implemented in four hospitals in the Minneapolis-St. Paul, Minnesota, Twin Cities area. TEAM assessed the effectiveness of a systems-based approach in which experimental subjects were identified in the medical records or by self-report as smokers. Smokers were eligible for participation in TEAM regardless of their diagnosis, with some exceptions (see Subjects, below) and regardless of their expressed interest in quitting. Analysis focused on predictors of both short- and long-term quitting. The study included a large heterogeneous population from the four hospitals. It was possible to examine a number of potential predictors, including patient smoking history and demographic ISSN print/issn X online/03/ #2003 Society for Research on Nicotine and Tobacco DOI: /

2 216 PREDICTORS OF QUITTING IN HOSPITALIZED SMOKERS characteristics, and whether hospitalization was related to smoking. Patient characteristics associated with longterm quitting were of particular interest. A key question was whether patient characteristics were associated with low (or, conversely, high) rates of quitting that might suggest potential priority targets for intervention, or whether intervention might routinely be delivered to all hospitalized smokers. Method Hospitals The four hospitals participating in this study differed substantially in their patient populations. Two of the hospitals were county facilities located in downtown settings. The other two hospitals were private and were located in suburbs. Subjects Patients were drawn from admissions to the four study hospitals. Patients were potentially eligible if they had smoked a cigarette in the 3 months prior to admission and if they considered themselves regular smokers for at least 1 month during the year prior to admission. Patients who were pregnant and those with chemical dependency or psychiatric disturbance as the primary reason for admission were excluded from the study. Other eligibility requirements included age between 18 and 75, length of hospital stay of 24 hr or greater, ability to be contacted by telephone, and being well enough to participate and to give informed consent. Patient recruitment In each hospital, a research assistant obtained a list of all admissions from the previous day. Patients meeting age and admission diagnosis requirements were screened for smoking status and other eligibility criteria listed above. Eligible patients were approached for informed consent. Consenting patients completed a baseline interview and were then randomized to one of three treatment conditions. Research assistants screened 55,120 patients during the period from January 1997 through June Approximately 25% were smokers, and, of those, 5,421 patients were eligible for study participation and 4,243 were approached for consent. Major reasons for ineligibility of identified smokers were length of stay less than 24 hr (8.2%), admission for a psychiatric problem or chemical dependence (18.7%), being too ill to participate (10.1%), and lack of a telephone (6.4%). The research team s inability to approach 22% of those eligible for the study was related to the brevity of many hospital stays. In addition, it often was necessary to contact multiple patients on different units within a limited time, and patients were involved in tests and medical procedures, were asleep, or had visitors on occasions when a research assistant was available to meet with them. The researchers enrolled 2,350 patients (55% of patients who were approached for consent). The fact that this was a research project rather than simply a clinical intervention may have reduced participation. Although study participation requirements were relatively minimal (completion of baseline and follow-up surveys, agreement to random assignment to treatment condition), a lengthy consent form was required. In addition, the consent rate reflected the fact that researchers attempted to enroll all admitted smokers rather than just those who were interested in cessation. For current analyses, the investigators began with data from subjects who completed both the 7-day and 12-month follow-up interviews (n~1,635). However, to be conservative in our analyses of predictors, we excluded those who claimed abstinence at 12 months, but who either refused or failed to return a saliva sample (n~105) or those whose saliva sample disconfirmed their self-report of not using tobacco (n~53). This yielded a final sample size of 1,477. Intervention The primary purpose of the study was to examine predictors of successful outcome, independent of study condition. Study outcomes by treatment condition will be reported in a separate manuscript. Patients were randomized to one of three study conditions: (a) modified usual care [patients received two smoking cessation manuals tailored for hospital inpatients (Stillman, Warshow, Stern, & Jones, 1990a, b), and a directory of resources for smoking cessation]; (b) provider advice (nurses and physicians were cued in patient charts to give and document brief smoking cessation advice, and patients were given the smoking cessation manuals; or (c) provider advice plus counseling (patients received the interventions delivered to those in the two other conditions plus a 20- to 30-min bedside counseling session, and three to six telephone calls from a smoking cessation counselor after discharge). Data collection A baseline interview was conducted in the hospital before randomization to treatment. Follow-up interviews were conducted by the Division of Epidemiology s Telephone Survey Center at 7 18 days (median~9 days, mean~9.4 days) and at approximately 12 months (median~369 days, mean~373.1 days) after hospital discharge. Measures Demographic characteristics assessed at baseline included age, gender, ethnicity, marital status, and education.

3 NICOTINE & TOBACCO RESEARCH 217 To determine smoking status at baseline, respondents were first asked if they had ever smoked cigarettes on a regular basis, i.e., more than 100 cigarettes in their lifetime. Those who had smoked to that extent then were asked whether they smoked cigarettes at the time of the assessment. If they were not current smokers, they were asked if they had smoked in the 3 months prior to hospitalization and, if so, if there had been a period of at least 1 month in the previous year when they generally smoked every day. Respondents who reported that they had smoked 100 cigarettes in their lifetime, had smoked in the previous 3 months, and had been a daily smoker for at least 1 month in the previous year were considered smokers and, therefore, were eligible for the study. Other smoking variables measured at baseline included number of cigarettes smoked per day (daily smokers only) or per week (occasional smokers); age of initiation of smoking; number of years as a smoker; stage of change (DiClemente, Prochaska, Fairhurst, Velicer, Velasquez, & Rossi, 1991); level of addiction to nicotine, as indicated by whether the first cigarette of the day was smoked within 30 min of waking; and level of selfefficacy for cessation, measured by a single item that asked participants to rate on a 0 10 scale their confidence that they could quit permanently if they decided to do so. During both follow-up interviews, the main cessation outcome assessed was 7-day point prevalence of smoking, i.e., subjects were asked whether they had smoked in the previous 7 days. As a test of the validity of self-reported abstinence from smoking, all subjects who reported during the 12-month interview that they had not smoked or used nicotine-containing products in the previous 7 days were asked to provide a saliva sample that would be tested for cotinine. Saliva cotinine samples were analyzed by gas chromatography. If respondents consented, they were mailed a kit with materials for saliva collection. Those who returned a sample by mail were sent an incentive payment of $25. Some 412 subjects reported at 12 months that they had not smoked at all in the past 7 days and were not currently using tobacco products. Those who indicated that they were currently using nicotine replacement therapy (n~14) were not asked to submit saliva samples. Of 398 self-reported quitters who indicated that they were not using nicotine replacement therapy, 13 (3.3%) refused to send a sample, and 92 (23.1%) failed to return a sample despite indicating that they would do so. Of the 293 samples that were returned, 240 (81.9%) were negative (v15 ng/ml cotinine) and 53 (18.1%) were positive. Self-reported abstinence was biochemically validated only at 12 months. Those subjects who refused or failed to provide saliva samples and those with positive cotinine results were excluded from all data analyses. This allowed a clear differentiation between smokers and biochemically confirmed nonsmokers. Discharge diagnosis was based on information abstracted from the patient s medical record by hospital personnel trained in nosological coding. Patients were assigned a primary diagnosis code corresponding to the primary reason for hospitalization, and as many as 15 secondary codes corresponding to concurrent illnesses. Each hospital was given a list of names, admission dates, and medical record numbers for all patients enrolled in the study. Information on primary and secondary discharge diagnoses in the form of codes based on the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM; Centers for Disease Control and Prevention [CDC], 2000) were returned to the university. Patients then were classified by the presence or absence of a smoking-related illness, based on their primary discharge diagnosis. Table 1 contains the list of ICD-9-CM codes considered to be smoking related. This classification of smoking-related illness was based on a U.S. Surgeon General s report on the health consequences of smoking (CDC, 1993; U.S. Department of Health and Human Services, 1989). Analyses Analyses were conducted using the SAS statistical package, version 8.1 (SAS Institute, 1999). Pearson s x 2 was used to test associations between smoking cessation and categorical variables, and t tests were used to test the associations between smoking cessation and continuous variables. The outcome variable, smoking cessation, is dichotomous; therefore, multivariate analyses were conducted using logistic regression techniques. Predictor variables with a p value less than.10 were entered into the multivariate model simultaneously. Variables were removed if the p value was greater than.10. Table 1. ICD-9-CM code Illnesses classified as smoking related Disease name Neoplasms of the oral cavity and pharynx 150 Neoplasm of the esophagus 157 Neoplasm of the pancreas 161 Neoplasm of the larynx 162 Neoplasm of the trachea, bronchus, and lung 180 Neoplasm of the cervix uteri 188 Neoplasm of the bladder 189 Neoplasm of the kidney, other urinary organs 205 Myeloid leukemia Ischemic heart disease Other heart disease Cerebrovascular diseases 440 Atherosclerosis 441 Aortic aneurysm Other arterial disease Pneumonia Bronchitis, emphysema 496 Chronic airway obstruction Other airway disease CDC (1993); Shopland (1995).

4 218 PREDICTORS OF QUITTING IN HOSPITALIZED SMOKERS Results Baseline subject characteristics Baseline characteristics of subjects are presented in Table 2. As would be expected, this was an older population with a long smoking history (mean~29.4 years). The sample was primarily White (82.8%), with 12.4% African American and 4.8% other. Subjects were distributed across stage of change, with fewer than 15% of these hospitalized smokers identifying themselves as precontemplators. Subjects reported substantial nicotine Table 2. Demographic and smoking history characteristics and distribution across hospitals Variable n % Sex Male Female Age Ethnicity White 1, African American Other Marital status Married Other Education High school graduate or less Vocational/some college College graduate or advanced degree Age of initiation of smoking 14 years or younger years years or older Time to first cigarette Within 5 min min min After 60 min Stage of change Precontemplation Contemplation Preparation Action Cigarettes per day 9 or fewer or more Smoking-related diagnosis Yes No 1, Patient perception: smoking related to hospitalization Not at all related Somewhat related Very much related Don t know Hospital dependence, with overall mean daily consumption of 19.4 cigarettes and self-report of almost 70% reporting smoking within 30 min after waking. Predictors of 7-day and 12-month abstinence Bivariate analyses revealed multiple significant predictors of both 7-day and 12-month abstinence. Strong predictors were found for both demographic and smoking history characteristics (Table 3). Significant demographic predictors at both time points included age (higher success rates in older patients), gender (higher quit rates among males), and ethnicity (lower quit rates among African Americans). Marital status (higher quit rates among those who were married) predicted shortterm, but not long-term, abstinence. Differences among hospitals were significant at 7 days and at 12 months. Predictive smoking history characteristics at both time points included time to first cigarette and stage of change. Those smoking within the first 5 min after awakening were least likely to be abstinent, as were those in precontemplation. The pattern for number of cigarettes was nonlinear and was only predictive at 12 months. Earlier age of initiation also was predictive at 12 months but not at 7 days (Table 3). Both the patients perception that smoking was related to hospitalization, and presence of a smokingrelated disease (based on ICD-9-CM classification code of final discharge diagnosis), predicted substantially increased likelihood of quitting at 7 days and at 12 months. Both 24-hr quit attempts prior to the 7-day interview and smoking status at 7-day follow-up were predictive of 12-month outcome. Absolute abstinence rates were low for those who failed to make a 24-hr quit attempt prior to the 7-day interview, as well as for those who were smoking at 7-day follow-up, regardless of quit attempt. Multiple logistic regression models Tables 4 and 5 present the results of multivariate logistic regression analyses that tested the relationships between predictor variables and smoking status at 7-day and 12-month follow-up. A number of predictive variables dropped out of the final models. Predictive variables that were significant at both 7-day and 12-month follow-ups included age (those who were older were more likely to be abstinent), smoking-related illness (those with smokingrelated illness were more likely to quit), stage of change (precontemplators were least likely to quit, and those initially in action were most likely to quit), and time to first cigarette (those who smoked in the first 5 min after waking were least likely to be abstinent). Predictors significant at 7 days, but not at 12 months, included ethnicity (Whites experienced higher quit rates) and hospital. Patient perception that their hospitalization was very much related to their smoking predicted 12-month, but not 7-day, abstinence.

5 NICOTINE & TOBACCO RESEARCH 219 Table 3. Bivariate analyses: Predictors of cessation at 7-day and 12-month post hospital discharge Variable Percent Quit at 7 days Percent Quit at 12 months Sex p~.0007 p~.0540 Male Female Age pv.0001 pv Ethnicity pv.0001 p~.0355 White African American Other Marital status p~.0055 p~.1474 Married Other Education p~.1104 p~.4965 High school graduate or less Vocational/some college College graduate or advanced degree Hospital pv.0001 p~ Time to first cigarette p~.0055 p~.0293 Within 5 min min min After 60 min Stage of change pv.0001 pv.0001 Precontemplation Contemplation Preparation Action Cigarettes per day p~.1827 p~ or fewer or more Age of initiation of smoking p~.1275 p~ years or younger years years or older Patient perception: smoking related to hospitalization pv.0001 pv.0001 Not at all related Somewhat related Very much related Don t know Smoking-related diagnosis Yes No hr quit attempt from discharge to 7-day interview pv.0001 pv.0001 Yes No.0 a 6.3 Quit at 7-day interview pv.0001 Yes 38.1 No 7.4 a By definition, a subject could not be abstinent at 7-day follow-up without having made at least a 24-hr quit attempt. Discussion The present study extends previous findings by including a large multiethnic population from four diverse hospitals. The study sample included a reasonably broad distribution of smokers across initial stages of change. A number of significant predictors were found for both short- and long-term outcomes, most of which were as might be expected (Freund, D Agostino, Belanger, Kannel, & Stokes, 1992; Glasgow, Stevens, Vogt, Mullooly, & Lichtenstein, 1991; Ockene et al., 1992; Smith, Kraemer, Miller, DeBusk, & Taylor, 1999). Prominent among these were age, smoking-related illness, stage of change, and time to first cigarette. The magnitude of the effect for stage of change was

6 220 PREDICTORS OF QUITTING IN HOSPITALIZED SMOKERS Table 4. Final logistic regression model for smoking cessation at 7-day follow-up (n~1366) Variable Estimate SE Wald x 2 p Value Odds ratio (CI ) Sex Female Male (.989, 1.655) Age a (1.008, 1.030) Ethnicity White African American (.315,.804) Other (.440, 1.567) Smoking-related illness No Yes v (1.765, 3.125) Stage of change Precontemplation Contemplation v (2.372, 7.224) Preparation v (2.964, 9.234) Action v (12.460, ) Confidence in ability to quit b v (1.053, 1.167) Time to first cigarette Within 5 min 6 30 min (1.234, 2.304) min (1.091, 2.555) After 60 min (1.184, 2.519) Hospital (1.374, 3.502) (.983, 2.727) (.913, 2.743) The n is less than 1,477 because of missing data for the predictor variables. a Per one year of age. b Per one unit change on scale from 1 to 10. especially striking at the 7-day follow-up. The effect for stage persisted following adjustment for numerous other variables, including dependence. Relatively strong effects also were found at both time points for smokingrelated illness. Those with diagnosed smoking-related illness were considerably more likely to report abstinence Table 5. at both follow-up points. Interestingly, however, patients perception that their hospitalization was related to their hospitalization predicted 12-month, but not 7-day, abstinence. Smoking within 5 minutes after waking also was a strong predictor at both time points. Ethnicity was a significant predictor only of short-term abstinence. Final logistic regression model for smoking cessation at 12-month follow-up (n~1,401) Variable Estimate SE Wald x 2 p Value Odds ratio (CI ) Sex Female Male (.927, 1.656) Age a v (1.016, 1.042) Smoking-related illness No Yes (1.555, 2.430) Patient perception: smoking related to hospitalization Not at all related (.448, 1.067) Somewhat related (.351,.838) Very much related Don t know (.244, 1.014) Stage of change Precontemplation Contemplation (1.572, 5.350) Preparation (1.371, 4.849) Action v (3.080, ) Time to first cigarette Within 5 min min (.992, 2.040) min (1.042, 2.726) After 60 min v (1.572, 3.603) The n is less than 1,477 because of missing data for the predictor variables. a Per one year of age.

7 NICOTINE & TOBACCO RESEARCH 221 The lower initial rates of quitting for African Americans, even when adjusted for sociodemographic factors, suggested the need for more aggressive promotion of cessation in this population. Approaches that are culturally sensitive may be beneficial (US Department of Health and Human Services, 1998). However, ethnicity was not a predictor of 12-month cessation in the multivariate analysis. Furthermore, 12-month abstinence rates for African Americans (10.4%) were at least moderately encouraging. Quit rates lower than the average for all hospitalized patients also may suggest the need for different types of intervention (Gritz et al., 1993). Thus, for those whose disease was not directly related to smoking, more emphasis on the personal relevance and benefit of quitting, as well as hospitalization being an opportune time for doing so, may be appropriate (Rigotti et al., 1997; Stevens et al., 1993). However, 12-month abstinence was 13.7% even for those who did not perceive that smoking was related to their hospitalization. The dramatic increase in both short- and long-term quitting for those in later stages of change supports the importance of intervention designed to encourage stage progression in patients who are not currently thinking of quitting. Motivational interviewing techniques may be particularly appropriate for these smokers (Miller & Rollnick, 1991). Previous studies sometimes have been restricted to patients with smoking-related disease (e.g., cardiac patients; Taylor et al., 1990) or those who express at least minimal readiness to change (e.g., excluding precontemplators; Johnson et al., 1999). One limitation in evaluating the results was the failure in a substantial number of cases to biochemically validate self-reported abstinence at 12-month followup. Those who claimed to be abstinent were asked to provide saliva samples by mail and were provided an incentive for doing so. Although overall completion rates of 86.9% for the 7-day interview, 76.3% for the 12-month interview, and 69.5% for both are comparable to those we have obtained in other studies (McBride, Curry, Lando, Pirie, Grothaus, & Nelson, 1999), the level of discomfirmation was higher. More than half of those who were disconfirmed reported either tobacco or nicotine replacement therapy use at the time they returned their saliva samples. Inaccuracies in characterizing respondents smoking status obviously could affect predictive relationships. We therefore decided to include only data from self-reported nonsmokers whose selfreports were biochemically validated. Saliva samples were not solicited at 7 days partly not to overburden participants and also because 12-month abstinence was the primary measure of intervention effectiveness for the main outcome study. Most findings were consistent with expectations, although we noted exceptions. Those in the preparation stage of change, for example, achieved no better long-term outcome than those in contemplation, and heavy smokers who consumed 30 or more cigarettes per day were as successful as more moderate and lighter smokers. Perhaps more important than the predictive relationships was the finding that intervention may be worthwhile for all smokers. Hospitalized smokers achieved at least reasonable long-term outcomes regardless of smoking-related disease, gender, ethnicity, or smoking history. We emphasize that this study was correlational and focused on predictors of quitting in a population of hospitalized smokers, not on effects of intervention. Even so, the findings were reassuring, with the exception of findings about precontemplators. Quit rates of 6.1% among precontemplators at 12-month follow-up were substantially lower than those achieved by subjects in later stages of readiness. Even these quit rates compared favorably with overall outcomes that might be expected in a general population of smokers, however. Furthermore, hospitalization may represent a teachable moment to motivate quitting in those who have not intended to quit. Although correlational, the results supported following clinical practice guidelines for all hospitalized smokers and, consistent with these guidelines, delivering cessation intervention to those interested in quitting and motivational intervention to those not currently interested. The findings also strongly suggested that hospitalization presents an excellent teachable moment for virtually all smokers. Acknowledgment This research was supported by grant HL54132 from the National Institutes of Health. References Centers for Disease Control and Prevention. (1993). Cigarette smoking-attributable mortality and years of potential life lost United States, Morbidity and Mortality Weekly, 42, Centers for Disease Control and Prevention. 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