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(Chest. 2005;128:2528-2537.)
© 2005 American College of Chest Physicians

Effects of Cigarette Reduction on Cardiovascular Risk Factors and Subjective Measures*

Dorothy K. Hatsukami, PhD; Michael Kotlyar, PharmD; Sharon Allen, PhD, MD; Joni Jensen, MS; Shelby Li, PhD; Chap Le, PhD and Sharon Murphy, PhD

* From the Transdisciplinary Tobacco Use Research Center (Drs. Hatsukami, Li, Le, and Murphy, and Ms. Jensen), University of Minnesota; Department of Experimental and Clinical Pharmacology (Dr. Kotlyar), College of Pharmacy, University of Minnesota; and Department of Family Practice (Dr. Allen), University of Minnesota, Minneapolis, MN.

Correspondence to: Dorothy K. Hatsukami, PhD, University of Minnesota, Tobacco Use Research Center, 2701 University Ave SE, Minneapolis, MN 55414; e-mail: hatsu001{at}umn.edu


   Abstract
TOP
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Study objectives: To assess the effect of continued smoking and smoking reduction on cardiovascular biomarkers (eg, WBC count, cholesterol concentrations, BP, heart rate).

Design, setting, and participants: This study, conducted at the University of Minnesota, randomized smokers interested in significantly reducing cigarette use but not quitting to either start 12 weeks of smoking reduction immediately (n = 102), assisted by nicotine replacement therapy, or to a 6-week wait list (n = 49). Those starting smoking reduction were required to reduce smoking by 25% for 2 weeks, 50% for 2 weeks, and 75% during the final 2 weeks. After 6 weeks, the subjects were asked to maintain a 50% reduction or quit. Nicotine gum and, if necessary, nicotine patch were used to achieve reduction goals. The wait list group (n = 49) smoked ad libitum for 6 weeks and then reduced smoking as previously described.

Measurements and results: Cardiovascular biomarkers (eg, WBC count, cholesterol concentrations, BP, heart rate) were assessed at several time points after enrollment. During ad libitum smoking, cardiovascular biomarkers remained relatively stable with correlation coefficients across the various time measurements, ranging from 0.44 to 1.00 (p < 0.01 for all measures). Among successful nonabstinent reducers (64 of 151 subjects), significant improvements were found in many biomarkers (eg, hemoglobin, hematocrit, RBC and WBC counts, lipids, BP, heart rate, respiratory symptoms, all p < 0.0167).

Conclusions: These results show the availability of reliable and dose-sensitive biomarkers and that reduction in smoking can lead to significant but only modest changes in cardiovascular risk factors in healthy smokers. It is not known whether the reductions in cardiovascular risk factors observed after smoking reduction are also associated with reduced disease risk. Additional research is necessary to address this issue.

Key Words: biomarkers • cardiovascular risk factors • cigarette reduction • harm reduction


   Introduction
TOP
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Although the idea of reducing tobacco toxin exposure among continuing smokers is not a new concept, recent efforts by the tobacco industry to develop and market potential reduced-exposure products have resulted in an increased interest in examining this approach. The escalating introduction of potential reduced-exposure products has prompted the US Food and Drug Administration to sponsor a report from the Institute of Medicine and for the National Cancer Institute to convene an expert panel to consider the feasibility of this approach, the necessary science and systems that need to be in place in order to ensure public health, and the specific research areas that will need to be pursued.12 The identification of reliable and valid biomarkers for tobacco toxin exposure was determined to be a particularly important area of research.

Biomarkers can be considered as measures of the following: (1) toxins specifically related to exposure of tobacco constituents, such as nicotine or tobacco-specific nitrosamines; (2) risk contributors to disease, such as lipoproteins, C-reactive protein, WBC count; (3) disease markers such as pulmonary function; or (4) clinical outcome measures, such as hospitalizations, occurrence of disease, or death. Smokers compared to nonsmokers have significantly elevated risk factors for cardiovascular disease (CVD),3 and these risk factors improve among smokers after cessation of cigarettes.14 To date, few studies have examined the effects of changes in cigarette dose on cardiovascular risk factors. Of the studies that currently exist, the results show significant improvement on these measures; however, the sample sizes have tended to be small,5 and no control groups have been used.56

In this study, the reliability and validity of measures of risk contributors to CVD were examined. The reliability of these measures was determined by examining the consistency of these measures over time during ad libitum tobacco use. The potential validity and sensitivity of these measures were determined by examining the dose-response relationship of these measures as the number of cigarettes smoked is reduced. We hypothesized that smoking reduction leads to a dose-related improvement on cardiovascular risk factors.

As a secondary aim, this study examined the feasibility of reducing the number of cigarettes smoked among smokers unwilling or unable to quit smoking. Prior studies17 have shown that smokers are able to reduce the number of cigarettes smoked with or without the use of pharmacologic agents; however, whether a significant proportion of the population is able to sustain this reduction478 or whether this reduction leads to significant reduction in biomarkers for disease9 has been called to question. Data were analyzed to determine the extent to which subjects were able to reduce smoking and the proportion of subjects able to sustain this reduction. We hypothesized that the majority of subjects can reduce smoking; however, sustaining significant reductions in smoking that leads to beneficial effects from smoking may be difficult to achieve.


   Materials and Methods
TOP
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Study Design
Details of the study design have been described previously.10 In brief, cigarette smokers from 18 to 70 years of age and interested in significantly reducing cigarette use were recruited. Inclusion criteria included the following: (1) smoking from 15 to 45 cigarettes per day (CPD) for the past year (in order to reduce heterogeneity); (2) uninterested in and no plans for quitting in the next 30 days; (3) good physical health (no unstable medical condition); (4) no contraindications for nicotine replacement use; (5) good mental health (eg, not meeting Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition,11 criteria for any psychiatric diagnosis, including substance abuse, within the past 6 months); (6) not using other tobacco or nicotine products or medications that might affect tobacco use or be affected by reduction of tobacco use; and (7) for female subjects, not pregnant or nursing. The University of Minnesota Institutional Review Board approved this study and the informed consent procedures.

Subjects who met inclusion criteria monitored their use of cigarettes (and other tobacco products) on a daily basis for a period of 2 weeks to assess baseline tobacco use. The following week, subjects returned for the baseline visit (visit – 1), when they were randomly assigned to the experimental cigarette reduction group or to the wait list control group for 6 weeks. Subjects monitored their smoking for another week, after which baseline measures were repeated at a second baseline visit (visit 0). Subjects assigned to the wait list control were the basis for the analysis that examined the consistency or intrasubject reliability across the various biomarkers for health risks or tobacco toxin exposure. This group was required to maintain and monitor smoking for a total period of 8 weeks. Subjects were assessed on all dependent measures during the first two baseline visits and then at weeks 4 and 6 after the second baseline visit. After the 8 weeks of ad libitum smoking, subjects entered the treatment reduction phase as described below.

Subjects assigned to the cigarette reduction group were expected to reduce their cigarette intake by 25% in the first 2 weeks, 50% in the subsequent 2 weeks, and 75% in the final 2 weeks. Subjects were given 4-mg nicotine gum to assist in their reduction of cigarette smoking and were instructed on several possible methods to use nicotine gum to achieve reduction goals, including substitution of nicotine gum for cigarettes, timed interval for nicotine gum use, and situational use of nicotine gum. The amount of gum recommended was based on the number of cigarettes smoked (eg, 10 pieces of nicotine gum for a 20-CPD smoker for a 50% reduction in cigarettes; 15 pieces of nicotine gum for a 20-CPD smoker for a 75% reduction in cigarettes). If a subject was unable to approach the 50% goal (more than two cigarettes from 50% reduction goal), he or she was offered the option of using a 14-mg patch (Nicoderm CQ; SmithKlineBeecham; Research Triangle Park, NC) in conjunction with the nicotine gum for a 2-week period until the 75% reduction period. Similarly, if a subject was unable to approach the 75% reduction goal or expressed concern about that level of reduction, an option of using a 21-mg Nicoderm CQ patch in conjunction with the nicotine gum was offered. After the 6-week treatment period, subjects who demonstrated some reduction in smoking were given nicotine replacements (nicotine gum or patch) for another 6 weeks, with the goal of gradually reducing their use of nicotine gum over this latter 6-week period.

In addition to the pharmacologic therapies, subjects met with a trained counselor during the clinic visits for brief individual sessions lasting approximately 10 min. During these sessions, a specific, structured format was followed. Topics included the following: (1) current tobacco use status; (2) motivations for tobacco reduction; (3) problems encountered; (4) problem solving in these difficult situations; and (5) providing support. If at any time after (or during) the 6-week treatment sessions the subject reported wanting to quit, a target quit date was established and self-help treatment manuals were dispensed. Brief standardized behavioral cessation was offered. Follow-up sessions occurred at 8, 12, and 26 weeks after the initiation of the study, although 8 weeks and 12 weeks were the primary assessment period for data analysis.

Outcome Measures
The primary outcomes of interest were the stability of cardiovascular biomarkers during ad libitum smoking and the extent to which cardiovascular biomarkers change in response to smoking reduction. Table 1 shows the measurements and times when these measurements were collected. Blood samples were analyzed for routine hemograms by Health East Medical Laboratories, St. Paul, MN. Fasting lipoprotein profiles were analyzed by Fairview University Diagnostic Laboratories, Minneapolis, MN. First morning urine voids were used to determine concentrations of total cotinine12 and anatabine, a tobacco alkaloid that is present in tobacco products but not in medicinal nicotine.1314 Results on uptake of tobacco-specific nitrosamines have been published elsewhere.10


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  		Table 1.. Schedule of Visits and Measures

 
Subjective measures included a tobacco daily diary in which subjects were asked to record the date, time, and situation of each cigarette smoked, each piece of nicotine gum used, and the use of any other tobacco product. In addition, a tobacco use questionnaire that asked about current tobacco use status (cigarettes and other tobacco use products), number of ≥ 24-h quit attempts, and duration of abstinence during these quit attempts was also administered at the clinic visits. Other subjective measures included a respiratory symptoms questionnaire using a scale that rated cough, phlegm production, shortness of breath, and other respiratory symptoms on a scale ranging from 0 (none) to 10 (severe), with a total respiratory score determined by adding the scores of each of these items. Secondary outcomes included the extent to which subjects were able to reduce smoking and the proportion of subjects able to sustain this reduction.

Visit Compliance
Compliance with attending sessions was maximized by paying subjects cash for each visit. The amount paid per visit was dependent on the procedures for that visit. Subjects were paid $40 for visits that involved a fasting blood draw and $10 or $25 for other visits plus a $50 bonus. The maximum earned in the reduction and follow-up period was $325. If assigned to the wait list, an additional $120 was earned.

Sample Size Determination and Statistical Analysis
Our overall goal was to enroll 150 subjects, with 100 subjects completing the study. The primary analysis included only those individuals who were able to reduce by at least 40% but did not achieve abstinence. Forty percent was chosen to increase the sample size. This requirement led to a sample size of 64 nonabstinent subjects who achieved at least 40% reduction from weeks 4 to 12, with 7 of these subjects meeting at least 40% but not 50% reduction. This sample size should be sufficient since significant reduction in biomarkers for disease have been observed in sample sizes as small as 16 to 33.69 In order to draw inference about the reliability of all measurements, Pearson correlation coefficients were calculated between every pair of the baseline data for each variable, using the data collected from wait list control group. Analyses were also conducted to determine if the cigarette reduction would lead to a change in CVD risk factors and a subjective measure of respiratory symptoms. Because the study was designed with each subject decreasing his/her CPD over time, time effects were examined among those who achieved at least a 40% reduction at week 4, from weeks 4 to 6, and from weeks 4 to 12. Summary statistics were obtained for each CVD risk factor and the self-reported respiratory symptoms. A change score (each measurement time minus baseline) for each variable was calculated for every subject. The score was then averaged at each time point to yield the overall mean change. Random effects modeling technique and paired t tests were used to investigate these time effects. Effect size was calculated by dividing the mean of the paired difference by its SD. Effect size (d) was defined as small, d = 0.2, medium, d = 0.5, and large, d = 0.8.15 Finally, correlation coefficients between the percentage change in CPD and percentage change in biomarkers for each randomized subject who completed week 12 visit were obtained. The point estimate of the overall correlation is the back-transformed average.


   Results
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Recruitment and Characteristics of Subjects
A total of 151 subjects were enrolled in this study. Of these, 102 subjects were randomized to the experimental group and 49 subjects were randomized to the wait list control (Fig 1 ). Among those in the wait list control, 3 patients dropped out during the wait list portion of the study and 13 patients dropped out during the reduction phase of the study. Of the participants randomized to the experimental group, no subjects dropped out prior to or during baseline measurements; a total of 25 subjects dropped out by week 6, 34 subjects by week 8, and 37 subjects by week 12 of treatment. In total, 98 of 151 subjects completed treatment through week 12, and 53 subjects dropped out. Table 2 describes the characteristics of all randomized subjects, subjects who reduced by at least 40% at week 4, from weeks 4 to 6, and from weeks 4 to 12. Logistic regression was used to compare the groups on differences in demographics and smoking history. The only significant differences among these groups were for age between all randomized subjects compared to those subjects who constituted the sample for visit 4 (p = 0.0031), visit 6 (p = 0.001), and visit 12 (p = 0.02); for years smoked between all randomized subjects and subjects who comprised the sample for visit 4 (p = 0.04) and visit 6 (p = 0.01); and for motivation to quit between all randomized subjects, compared to subjects who comprised the sample for visit 12 (p = 0.03) and between subjects who comprised the sample for visit 4 compared to visit 12 (p = 0.05). The results show that subjects who were older (odds ratio, 1.04, p = 0.02) and reported more motivation to quit (odds ratio, 1.13; p = 0.04) were more successful in sustaining reduction through week 12.



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  		Figure 1.. Flow chart of subjects randomized to a wait list group and cigarette reduction groups.

 

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  		Table 2.. Demographics and Smoking History*

 
Reliability of Biomarkers for Disease
Data were analyzed from the subjects who were assigned to the wait list control to determine intrasubject reliability, that is the correlation coefficients across each time period (baseline visit – 1 by visit 0, visit – 1 and visit 0 by visit 4 and visit 6, visit 4 by visit 6) for all measures. Table 3 shows the correlation coefficients over time for the cardiovascular biomarkers. Correlation coefficients across the various time measurements were significant for all the measures ranging from 0.44 to 1.00.


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  		Table 3.. Correlation Coefficients Over Time for Biomarkers (n = 34 to 47)

 
Reduction in Biomarkers for CVD Risk Associated With Reduction in Cigarette Smoking
Table 4 shows that significant changes were observed in a number of cardiovascular biomarkers, excluding all abstinent subjects. Within the wait list group, comparing mean values obtained during the baseline visits with values obtained during the reduction phase visit found significant differences (p < 0.05) in many of the biomarkers measured (hemoglobin, hematocrit, RBC count, WBC count, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), triglycerides, total cholesterol, total cholesterol/high-density lipoprotein [HDL] ratio, apolipoprotein B (ApoB), heart rate, and respiratory symptoms), suggesting that these changes were due to the effect of smoking reduction and not random fluctuations in the value of these measures. Correlation coefficients for percentage reduction in cigarettes with percentage reduction in disease risk biomarkers were calculated for all variables that showed significant decreases during the reduction phase observed in Table 4Go. Among all randomized subjects who completed 12 weeks of treatment, positive correlations were observed for WBC count (r = 0.26, p = 0.01), total cholesterol/HDL ratio (r = 0.25, p = 0.02), and heart rate (r = 0.21, p = 0.05).


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  		Table 4.. Effects of Reduction in CPD on Biomarkers for Disease Risk in Smokers Who Reduced Their Self-Reported CPD by ≥ 40% Compared to Baseline and Excluding Abstainers, at Week 4, Weeks 4 to 6, and Weeks 4 to 12

 

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  		Table 4A.. Continued

 
Achievement of Reduction in Smoking and Abstinence
The mean reduction in cigarettes (baseline – week/baseline) across the total sample who completed the study was 51.7% at week 4, 71.1% at week 6, and 62.1% at week 12. The number of individuals who were able to achieve at least 40% reduction (including abstainers) by self-report from week 4 through 12 was 64 of 151 subjects. The number of individuals who were abstinent for the past 1 month with biochemical verification (carbon monoxide ≤ 8 ppm) was 1 of 151 subjects at 6 weeks and 9 of 151 subjects at 12 weeks. When the 26-week data were examined, 27% (41 of 151 subjects) achieved at least a 40% reduction in cigarette smoking and 7% (11 of 151 subjects) achieved biochemically verified abstinence for the past month.


   Discussion
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
Although smoking cessation has been clearly demonstrated to reduce subsequent cardiovascular mortality,16 whether smoking reduction or "reduced exposure" products confer any health benefits is still unknown. Due to the difficulty in carrying out prospective, randomized studies assessing long-term outcomes data, use of other measures (ie, biomarkers) that are known to be altered during smoking and normalize during smoking cessation is an attractive alternative in researching risk reduction approaches. Partial normalization of reliable biomarkers during smoking reduction may indicate that this approach confers some health benefits especially if changes in the selected biomarkers are the underlying cause for smoking-related disease. To date, few studies have systematically examined the reliability and dose-responsiveness of biomarkers for CVD.

This study demonstrated that certain biomarkers of CVD risk factors (eg, hemoglobin, hematocrit, RBC count, WBC count, lipoproteins concentrations, heart rate, respiratory symptoms) known to be affected by smoking are relatively stable over time when amount smoking is maintained at a constant rate but are altered in response to changes in smoking behavior. This suggests that some of these measures are likely to be sensitive to changes in tobacco toxin exposure. The results seen in this study are consistent with two previous studies5,6 that assessed the effect of smoking reduction on various biomarkers. An open-label study6 in which subjects were encouraged to reduce smoking by at least 50% for 8 weeks and then quit smoking entirely for 8 weeks while using ad libitum nicotine nasal spray found significant decreases in WBC blood count, RBC count, hemoglobin, hematocrit, and fibrinogen with significantly increased HDL/low-density lipoprotein (LDL) ratio after both reduction and cessation. For WBC and RBC counts, greater improvements were observed after cessation than after reduction. Changes to LDL and HDL (decrease and increase, respectively) were statistically significant only after cessation, although nonsignificant changes were seen with reduction as well.6 A study of 25 subjects able to reduce smoking by ≥ 50% found that these subjects had significantly higher HDL levels and significantly lower total cholesterol/HDL ratio, LDL, hemoglobin, hematocrit, FEV1, and systolic BP than observed prior to reduction.5

Despite finding significant changes after reduction, our study found only weak correlations between the extent of reduction in amount smoked and percentage of improvement in biomarker measurements and for only a few of the biomarkers assessed. Significant correlations were observed between reductions in amount smoked and WBC count, total cholesterol/HDL, and heart rate, suggesting that these measures may be particularly sensitive to measuring a range of changes in tobacco exposure. There are a number of potential explanations for the poor relationship between reduction in amount smoked and reduction in biomarkers. (1) CPD may not be a good measure of tobacco exposure, since smokers can compensate for fewer cigarettes smoked by smoking each cigarette more completely or inhaling more deeply. (2) If changes in certain biomarker measures require prolonged smoking reduction, 12 weeks may be insufficient time for biomarkers to equilibrate to the reduced level of smoking. (3) The possibility that a dose-response curve is observed only at lower levels of smoking, so reduction to levels above a certain plateau do not significantly affect biomarker measurements. Data examining the relationship between amount smoked and CVD indicate that smoking even small amounts (< 5 CPD) increases cardiovascular risk, but there is a dose-response relationship present.17 There are, however, conflicting data regarding whether a plateau for risk is reached and at what level of smoking such a plateau occurs.17 (4) A confounding factor (eg, nutrition or lifestyle modifications) was present that was responsible for some of the observed change in biomarker values. Although subjects were not specifically asked about changes in nutrition or exercise, it is unlikely that significant lifestyle modification occurred given the observation that no significant weight change occurred during the smoking reduction period.

The extent of improvement of cardiovascular risk factors that is necessary to improve health risk is unknown. Smokers have a higher risk for heart disease than nonsmokers, and differences in a number of blood chemistry measures have been consistently reported in smokers (relative to nonsmokers). For example, WBC counts have been found to be higher in smokers than nonsmokers, and some studies181920 suggest that this effect is dose dependent. Craig et al,3 in reviewing 54 published studies assessing the effect of smoking on serum lipids and lipoproteins, found that smokers compared to nonsmokers had significantly higher serum concentrations of cholesterol (3.0% higher), triglycerides (9.1% higher), very LDL (10.4% higher), and LDL (1.7% higher), but significantly lower levels of HDL (5.7% lower) and apolipoprotein A1(ApoA1) [4.2% lower], with these changes being dose dependent. Studies suggest21 that newer risk factors, such as C-reactive protein, fibrinogen, and homocysteine levels, are also altered in smokers, as are other physiologic parameters, such as RBC mass, BP, and heart rate.2223 On smoking cessation, levels of many of these measures begin to normalize (although in some cases it may take several years for complete normalization to occur).420242526 The improvements we observed for many of the biomarkers after reduction were smaller than the previously described differences between smokers and nonsmokers, suggesting that greater differences would have likely been seen after cessation. This is consistent with the finding by Eliasson et al6 that smoking cessation resulted in greater changes in cardiovascular risk factors than smoking reduction. Therefore, the modest changes observed with reduction may not confer any health benefits, and a large epidemiologic study27 suggests that cigarette reduction does not lead to reduction in smoking-related disease. Furthermore, it is yet to be determined the degree to which smoking must be reduced to observe a beneficial health benefit.

Smoking reduction, nonetheless, has been suggested as a first step to achieving cessation in smokers unwilling or perceiving themselves unable to quit. We found that at 26 weeks, 27% of subjects maintained at least a 40% reduction in the number of cigarettes smoked and 7% had achieved abstinence. Subjects in this study were paid for continued participation in this study; therefore, these rates of reduction may not reflect what would happen in a more natural setting. However, these data are consistent with other studies in which pharmacotherapy was used to assist smokers unwilling to quit smoking to reduce the amount they smoke. One study28 found that 16% of those receiving bupropion had reduced smoking by at least 50% at 6 months, and 7% subsequently were abstinent continuously for 22 weeks. Another study8 found that 26% of those using the nicotine inhaler had reduced smoking by at least 50% at 4 months, and 8% were abstinent at 1 year. A third study7 found that 35% of those receiving nicotine replacement therapy achieved a > 50% reduction in smoking at 6 months, and > 5% had quit. A study29 in which smokers not interested in quitting were randomized to either reduction for 4 weeks followed by advice to quit or to a usual-care group that included only advice to quit found similar quit rates between groups at 6 months. The data as a whole therefore suggest that reduction does not appear to impede future smoking cessation attempts.

In summary, this study demonstrates that a number of biomarkers associated with CVD risk are relatively stable over time and change as the amount smoked changes. Reduction in smoking does improve measures of some of these biomarkers, demonstrating that these biomarkers are sensitive to change in smoking intake. It is not clear, however, whether these changes translate into significant health improvements. Unlike the data with smoking cessation, which demonstrate that health improves after quitting smoking, there are currently no data suggesting that this is also the case for reduction. Additional research is clearly necessary to determine if reduction is beneficial, if so to what extent smoking needs to be reduced for health benefits to occur, and which biomarkers are most sensitive to measuring improved health. There is therefore currently not enough data to recommend smoking reduction as a method by which to improve health; however, reduction in smoking may be a good method to engage subjects in treatment and may serve as a good stepping stone for individuals who are resistant to quitting.


   Footnotes
 
Abbreviations: ApoA1 = apolipoproteins A1; ApoB = apolipoproteins B; CPD = cigarettes per day; CVD = cardiovascular disease; HDL = high-density lipoprotein; LDL = low-density lipoprotein; MCH = mean corpuscular hemoglobin; MCV = mean corpuscular volume

This study was performed at the University of Minnesota, Minneapolis, MN.

This study was supported by National Institutes of Health grant P50DA 13333.

Received for publication January 27, 2005. Accepted for publication April 4, 2005.


   References
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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