Journal of Physical Activity and Health, 2016, 13, 1 -5 http://dx.doi.org/10.1123/jpah.2014-0605 © 2016 Human Kinetics, Inc.
ORIGINAL RESEARCH
Association of Longitudinal Changes of Physical Activity on Smoking Cessation Among Young Daily Smokers Paul D. Loprinzi and Jerome F. Walker Objective: To our knowledge, no longitudinal epidemiological study among daily smokers has examined the effects of physical activity change/ trajectory on smoking cessation. The purpose of this study was to examine the longitudinal effects of changes in physical activity on smoking cessation among a national sample of young (16–24 y) daily smokers. Methods: Data from the 2003–2005 National Youth Smoking Cessation Survey were used (N = 1178). Using hierarchical agglomerative cluster analysis, 5 distinct self-reported physical activity trajectories over 3 time periods (baseline, 12-month, and 24-month follow-up) were observed, including stable low physical activity, decreasing physical activity, curvilinear physical activity, stable high physical activity, and increasing physical activity. Nicotine dependence (Heaviness of Smoking Index) and demographic parameters were assessed via survey. Results: With stable low physical activity (16.2% quit smoking) serving as the referent group, those in the stable high physical activity (24.8% quit smoking) group had 1.8 greater odds of not smoking at the 24-month follow-up period (odds ratio = 1.81; 95% confidence interval, 1.12–2.91) after adjusting for nicotine dependence, age, gender, race-ethnicity, and education. Conclusions: Maintenance of regular physical activity among young daily smokers may help to facilitate smoking cessation. Keywords: epidemiology, exercise, nicotine dependence
The relationship between smoking and physical activity is widely established, with smokers engaging in less physical activity than their nonsmoking counterparts.1,2 This relationship is possibly bidirectional, in that regular physical activity may help to prevent smoking initiation.2 Nonsmokers are reported as more physically active, particularly during the critical period between adolescence and young adulthood.3 And among smokers, physical activity may facilitate smoking cessation4,5 via reducing nicotine cravings,6 favoring quit attempts,7 and improving mood and self-efficacy.8 Recent cross-sectional work found 16- to 24-year-old youth meeting physical activity guidelines were less nicotine dependent.9 Encouraging intervention-based work suggests physical activity may help to mitigate cigarette cravings and facilitate smoking cessation.10–13 Not all studies, however, point to a smoking and physical activity relationship. A 2008 systematic review of smoking and physical activity found over half the studies were null, and, where effects were found, they were less pronounced among adolescents and youth.14 A more recent (2014) Cochrane review reported only 2 of 20 interventional trials offered evidence of exercise aiding in smoking cessation. Marked variations in the length, type, and timing of exercise among studies were noted.10 Yet if and how physical activity and smoking interact is of significant importance, particularly among the young, as smoking is a youth-onset disorder with mean age of onset at approximately 12 years. Nearly 20% of youth are fully nicotine dependent by the age of 14 to 15 years.15 A gap in the current literature on this topic includes the limited number of longitudinal epidemiological studies among daily smokers that have examined the possibility of physical activity facilitating smoking cessation. Notably, other related longitudinal epidemiological studies2,16 have been conducted, but they did not specifically focus on daily smokers and were drawn from nonnationally
representative samples. To our knowledge, no nationally representative longitudinal epidemiological study among daily smokers has examined the effects of physical activity change/trajectory on smoking cessation, which was the purpose of this brief report.
Methods Design Data from the 2003–2005 National Youth Smoking Cessation Survey (NYSCS) were used. This epidemiological prospective study of 16- to 24-year-old smokers examined factors associated with smoking cessation. The NYSCS employs a nationally representative sample of young smokers using a single-stage, unclustered design. Using random digit dialing methodology, persons residing in households in the 50 US states and the District of Columbia who smoked 20 or more lifetime cigarettes and had smoked in the previous 30 days were initially interviewed during June to November 2003. Follow-up assessment at 12 months and 24 months also occurred. All participants provided informed consent before participation in the study; the authors’ institution granted exemption of Institutional Review Board review.
Demographic Variables Sample demographic variables included an a priori age category (16–17, 18–20, 21–24 y; continuous measure of age not available in dataset), gender, race-ethnicity (non-Hispanic white, non-Hispanic black, Hispanic, and other race-ethnicity), and education (< 12th grade, high school graduate, and some college/college graduate).
Nicotine Dependence Loprinzi ([email protected]) is with the Dept of Health, Exercise Science, and Recreation Management, University of Mississippi, University, MS. Walker is with the Dept of Respiratory Therapy, Bellarmine University, Louisville, KY.
At baseline, nicotine dependence was established using a modified Heaviness of Smoking Index (HSI), calculated as the numeric sum of two coded questions: (1) “In the past 30 days, how many cigarettes did you smoke per day?” (responses of 10 or less, 11 to 20, and 1
2 Loprinzi and Walker
21+, respectively, were coded as 0, 1, and 2), and (2) “How soon after you wake up do you smoke?” (responses: within 5 minutes, from 6 to 30 minutes, from more than 30 minutes to 1 hour, and more than 1 hour, respectively, were coded as 3, 2, 1, and 0).17,18 HSI has been reported as a valid indicator of dependence, having utility as a predictor of quit attempt maintenance.19
Smoking Status at 24-Month Follow-up At the 24-month follow-up, current smoking was defined as selfreported smoking within the last 30 days, with no longer smoking defined as not smoking within the last 30 days.
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Physical Activity At baseline, 12-month follow-up, and 24-month follow-up, participants were asked, “How many hours per week on average do you exercise? This includes playing sports, working out, aerobics, running, swimming, brisk walking, and other exercise activities.”
Data Analysis All statistical analyses were performed using procedures from sample survey data using Stata (version 12.0; StataCorp LP, College State, TX) to account for the complex survey design used in the NYSCS. Survey sample weights were used to adjust for the complex survey design and to represent a national sample of US adolescent and young adult smokers. Specifically, sample weights were derived to compensate for differential probabilities of selection, reduce biases due to nonresponse, and adjust for under-coverage due to households without telephones. The final weights for the completed baseline interview were generated from a series of sequential adjustments, including the development of a household base weight that is the inverse of the probability of selecting the telephone number from the sampling frame, which is then adjusted for unknown residential status, screener nonresponse, and post stratification of the number of households from Current Population Survey data. Subsequently, follow-up final weights for those that completed the 24-month interviews were derived from additional adjustments, including, for example, adjusting the base weights for the 24-month nonresponse and then raking (ratio adjustment) these nonresponse adjusted base weights. Hierarchical agglomerative cluster (HAC) analysis, using Ward’s method on the principal component score, defined the number of physical activity clusters across the 3 time periods; k-means procedure was then used to form the clusters. A multivariable logistic regression was used to examine the association between physical activity trajectories and smoking status at the 24-month follow-up period (outcome variable); smoking at 2-year follow-up served as the referent group for the outcome variable. Covariates included baseline nicotine dependence, age group, gender, raceethnicity, and education. Statistical significance was established as P < .05.
Results In the 2003–2005 NYSCS, 2582 young smokers consented and provided data at baseline. The overall screener response rate at baseline was 60%, with an extended response rate of 70%; the extended response rate assumed that persons on military duty were ineligible for the study. The interview response rate for the 16- to 17-year-old youth was 70.4%, with the response rate among 18- to 24-year-olds
being 69.4%. Lastly, the overall response rate for both smokers and nonsmokers was identical across the age groups: 70.4% for younger youth and 69.4% for older participants. After excluding those with missing nicotine dependence and demographic data at baseline (n = 74), missing smoking status at the 24-month follow-up (n = 1122), and missing physical activity data at any of the three time periods (n = 208), 1178 participants remained and constituted the analytic sample (45% retention rate). Details on differences between those lost to follow-up and those retained have been reported in our previous work using this dataset that examined demographic and psychosocial determinants of smoking cessation17; those lost to follow-up were less educated and less likely to be non-Hispanic white. Notably, there were no differences in baseline physical activity (5.5 h/wk vs 5.2 h/wk, P = .40) or baseline nicotine dependence (1.20 vs 1.41, P = .09) among those included in the final sample compared with those excluded. Characteristics of the study variables are shown in Table 1. Based on the HAC analysis, 5 distinct physical activity clusters/ trajectories across the 3 time periods were identified (Figure 1). Based on the mean physical activity changes observed across the 3 time periods, we labeled these trajectories as: stable low physical activity, decreasing, curvilinear, stable high, and increasing. Across the 3 time periods, and for the stable low group (n = 466), mean (SE) physical activity (h/wk) changed from 2.4 (0.1) to 2.4 (0.1) to 2.2 (0.1). For the decreasing group (n = 159), physical activity changed from 10.1 (0.1) to 3.7 (0.2) to 3.5 (0.2). For the curvilinear group (n = 191), physical activity changed from 4.5 (0.2) to 9.9 (0.2) to 3.7 (0.1). For the stable high group (n = 200), physical activity changed from 11.6 (0.1) to 10.3 (0.2) to 10.0 (0.1). Lastly, for the increasing group (n = 162), physical activity changed from 3.8 (0.2) to 6.1 (0.3) to 10.9 (0.1). Across the 5 physical activity groups (stable low physical activity, decreasing, curvilinear, stable high, and increasing), respectively, the weighted proportion of those not smoking at the 24-month follow-up period was 16.2%, 15.7%, 18.9%, 24.8%, and 18.2%. Table 2 displays the weighted multivariable logistic regression analysis examining the association between physical activity trajectories and 24-month smoking status. With stable low physical activity serving as the referent group, the only physical activity trajectory associated with 24-month smoking status was stable high physical activity. Those in the stable high physical activity group had 1.8 greater odds of not smoking at the 24-month follow-up period (odds ratio = 1.81; 95% confidence interval, 1.12–91; P = .01). Analyses were recomputed with the inclusion of other covariates, including number of years smoking, and the results were unchanged (data not shown).
Discussion The purpose of this brief report was to examine, in a nationally representative sample of young US daily smokers, the association of physical activity changes on smoking cessation. Despite this novelty and notable strength, the main limitation of this study includes the subjective assessment of physical activity and smoking. Further, the assessment in physical activity in this study was not domain- or intensity-specific; therefore, the findings presented herein should be interpreted with this in mind. To our knowledge, no nationallyrepresentative epidemiological longitudinal study among daily smokers has examined the association between changes in physical activity on smoking cessation. This study adds to the literature by demonstrating that regular exercise over time among daily smokers may help to facilitate smoking cessation.
JPAH Vol. 13, No. 1, 2016
Table 1 Weighted Characteristics, 2003–2005 National Youth Smoking Cessation Survey (N = 1178) Mean/Proportion (SE) Baseline characteristics
Stable low (n = 466)
Decreasing (n = 159)
Curvilinear (n = 191)
Stable high (n = 200)
Increasing (n = 162)
Age group, % 16–17 y
12.7 (1.5)
10.7 (2.3)
11.7 (2.2)
14.9 (2.4)
14.0 (2.6)
18–20 y
29.6 (2.1)
31.4 (3.6)
35.8 (3.6)
42.1 (3.7)
37.6 (4.0)
21–24 y
57.7 (2.4)
57.9 (4.0)
52.4 (3.8)
42.9 (3.8)
48.4 (4.4)
Male
44.1 (2.5)
60.5 (4.0)
59.0 (3.7)
71.9 (3.2)
55.2 (4.3)
Female
55.8 (2.5)
39.4 (4.0)
40.9 (3.7)
28.0 (3.2)
44.8 (4.3)
Gender, %
Education, % Less than 12th grade
23.6 (2.0)
26.1 (3.5)
29.0 (3.5)
31.7 (3.4)
32.9 (4.0)
High school graduate
31.4 (2.2)
31.2 (3.9)
32.9 (3.7)
34.4 (3.7)
30.2 (4.0)
Some college/college degree
45.0 (2.5)
42.6 (4.2)
38.1 (3.8)
33.9 (3.6)
36.9 (4.2)
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Race/ethnicity, % Non-Hispanic white
70.7 (2.3)
80.2 (3.4)
72.8 (3.6)
70.6 (3.6)
71.5 (4.0)
Non-Hispanic black
11.1 (1.5)
10.3 (2.5)
8.8 (2.3)
7.4 (2.1)
5.4 (1.7)
Hispanic
12.7 (1.9)
8.1 (2.4)
12.8 (2.9)
14.4 (3.0)
17.7 (3.6)
Non-Hispanic other
5.3 (1.1)
1.3 (0.8)
5.6 (1.6)
7.4 (1.8)
5.2 (1.8)
Nicotine dependence, baseline mean
1.25 (0.1)
1.23 (0.1)
1.07 (0.1)
1.29 (0.1)
1.10 (0.1)
Nicotine dependence, baseline range, 95% confidence interval
0–5, 1.10–1.39
0–5, 0.98–1.48
0–5, 0.85–1.29
0–5, 1.05–1.52
0–5, 0.84–1.34
Current smoker
83.8 (1.8)
84.3 (3.0)
81.0 (3.1)
75.2 (3.3)
81.8 (3.4)
Nonsmoker
16.2 (1.8)
15.7 (3.0)
18.9 (3.1)
24.8 (3.3)
18.2 (3.4)
Smoking status at 2-y follow-up, %
Figure 1 — Observed physical activity patterns across the 2-year period. Sample size (n) and weighted proportions for each physical activity group are as follows: stable low physical activity (n = 466; 40.1%), decreasing (n = 159; 13.5%), curvilinear (n = 191; 16.4%), stable high (n = 200; 17.0%), and increasing (n = 162; 13.0%). JPAH Vol. 13, No. 1, 2016
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4 Loprinzi and Walker
Table 2 Weighted Multivariable Logistic Regression Analysis Examining the Association Between Physical Activity Trajectories and Smoking Status (Outcome), 2003–2005 National Youth Smoking Cessation Survey (N = 1178) Odds ratio not smoking at 2-year follow-upa
Variable
95% CI
P-value
Physical activity trajectories Decreasing vs stable low
1.05
0.61–1.80
.84
Curvilinear vs stable low
1.16
0.69–1.95
.56
Stable High vs stable low
1.81
1.12–2.91
.01
Increasing vs stable low
1.06
0.61–1.84
.81
High school graduate vs less than 12th grade
1.29
0.72–2.32
.38
At least some college vs less than 12th grade
1.24
0.69–2.24
.45
Covariates
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Education
Race/ethnicity Non-Hispanic black vs non-Hispanic white
1.37
0.77–2.43
.27
Hispanic vs non-Hispanic white
2.53
1.56–4.11
< .01
Non-Hispanic other vs non-Hispanic white
1.29
0.64–2.58
.46
1.13
0.79–1.59
.48
1.11
0.57–2.17
.74
Gender Female vs male Age-category 18–20 vs 16–17 y 21–24 vs 16–17 y
0.91
0.44–1.88
.80
Nicotine dependence, 1 HSI increase
0.64
0.54–0.75
< .01
Abbreviations: CI, confidence interval; HSI, Heaviness of Smoking Index. a Smoking at 2-y follow-up served as the referent group for the outcome variable.
Specifically, we found 16- to 24-year-old smokers steadily engaging (over 2 years) in roughly 10 to 11 hours per week of physical activity were more likely to quit smoking than those that remained less active over time. This comports with a recent review of randomized control trials examining physical activity as therapy for substance use disorders, which found training frequency and intensity ≥ 3 sessions per week associates with fitness gains and, in turn, with favorable smoking outcomes.20 This is also in general agreement with work done by Audrain-McGovern and colleagues2 who examined 978 14- to 18-year-old Northern Virginia high school students, finding a relationship between maintaining roughly 12 hours per week of moderate intensity physical activity and the likelihood of initiating smoking, or of smoking progression among those that already smoked. Her group also examined 1384 Philadelphia high school students self-reporting their physical activity every 6 months from the ninth to the 12th grade.16 Latent growth curve modeling across the 8 waves (2 yearly physical activity assessments × 4 years) yielded 5 physical activity patterns (stable higher, decreasing, stable regular, curvilinear, and stable low) that were similar to our cluster analysis results. Smoking likelihood was twice as great among adolescents in the stable low, stable regular, and decreasing physical activity groups as in the stable high physical activity group. There were some differences between these studies and ours. Rather than longitudinal smoking initiation or smoking progression patterns among smoking and nonsmoking high-school students, 14- to 18-year-olds and from the eastern United States, we examined longitudinal self-reported smoking status among 16- to
24-year-olds, all smokers at baseline, drawn from a nationally representative sample. In conclusion, only the stable high physical activity group when compared with the low stable physical activity group had increased odds of not smoking at the 2-year follow-up period. If confirmed by future experimental and prospective work, understanding why higher levels of physical activity is most favorably associated with smoking cessation is warranted. Again, however, the current study was limited by the assessment of physical activity; therefore, future replicative work utilizing a better measure of physical activity is needed to improve our understanding of a potential dose- and intensity-dependent effect of physical activity on smoking cessation. Although speculative, higher doses of physical activity for vulnerable populations (eg, smokers, overweight/obese adults) may be needed to prevent behavioral relapses or for distraction purposes. Future mechanistic work on this topic is clearly needed. Another potential area in need of future inquiry is the possibility that physical activity may help to facilitate smoking cessation via physical activity–induced changes in executive function,21 as individuals with higher executive function (component of cognitive functioning) have an increased ability to maintain a goal-directed purposeful behavior,22 possibly as a result of a complex integration of planning, filtering competing information, maintaining a goal despite distraction, and inhibiting goal-inconsistent responses.23 Clearly, promotion of physical activity among daily smokers is needed, but such an effort will require careful planning and evaluation, as smokers are more likely to have various attributes (eg, psychiatric
JPAH Vol. 13, No. 1, 2016
Physical Activity and Smoking Cessation 5
disease, lower fitness level, little experience with physical activity, and fear that physical activity may induce dyspnea, tachycardia, or dizziness24) that may negatively influence physical activity.
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References 1. Verkooijen KT, Nielsen GA, Kremers SP. The association between leisure time physical activity and smoking in adolescence: an examination of potential mediating and moderating factors. Int J Behav Med. 2008;15(2):157–163. PubMed doi:10.1080/10705500801929833 2. Audrain-McGovern J, Rodriguez D, Moss HB. Smoking progression and physical activity. Cancer Epidemiol Biomarkers Prev. 2003;12(11 pt 1):1121–1129. PubMed 3. Yang X, Telama R, Leino M, Viikari J. Factors explaining the physical activity of young adults: the importance of early socialization. Scand J Med Sci Sports. 1999;9(2):120–127. PubMed doi:10.1111/j.1600-0838.1999.tb00220.x 4. Paavola M, Vartiainen E, Puska P. Smoking cessation between teenage years and adulthood. Health Educ Res. 2001;16(1):49–57. PubMed doi:10.1093/her/16.1.49 5. Bernard P, Ninot G, Moullec G, Guillaume S, Courtet P, Quantin X. Smoking cessation, depression, and exercise: empirical evidence, clinical needs, and mechanisms. Nicotine Tob Res. 2013;15(10):1635– 1650. PubMed doi:10.1093/ntr/ntt042 6. Scerbo F, Faulkner G, Taylor A, Thomas S. Effects of exercise on cravings to smoke: the role of exercise intensity and cortisol. J Sports Sci. 2010;28(1):11–19. PubMed doi:10.1080/02640410903390089 7. King TK, Marcus BH, Pinto BM, Emmons KM, Abrams DB. Cognitive-behavioral mediators of changing multiple behaviors: smoking and a sedentary lifestyle. Prev Med. 1996;25(6):684–691. PubMed doi:10.1006/pmed.1996.0107 8. Prochaska JJ, Hall SM, Humfleet G, et al. Physical activity as a strategy for maintaining tobacco abstinence: a randomized trial. Prev Med. 2008;47(2):215–220. PubMed doi:10.1016/j.ypmed.2008.05.006 9. Loprinzi PD, Kane CJ, Mahoney S, Walker JF. Physical activity and nicotine dependence among a national sample of young U.S. adults who smoke daily: evaluation of cross-sectional and longitudinal associations to determine which behavior drives this relationship. Physiol Behav. 2015;139:1–6. PubMed 10. Ussher MH, Taylor AH, Faulkner GE. Exercise interventions for smoking cessation. Cochrane Database Syst Rev. 2014;8:CD002295. PubMed 11. Haasova M, Warren FC, Ussher M, et al. The acute effects of physical activity on cigarette cravings: systematic review and meta-analysis with individual participant data. Addiction. 2013;108(1):26–37. PubMed doi:10.1111/j.1360-0443.2012.04034.x 12. Haasova M, Warren FC, Ussher M, et al. The acute effects of physical activity on cigarette cravings: exploration of potential moderators,
mediators and physical activity attributes using individual participant data (IPD) meta-analyses. Psychopharmacology (Berl). 2014;231(7):1267–1275. PubMed doi:10.1007/s00213-014-3450-4 13. Horn K, Dino G, Branstetter SA, et al. Effects of physical activity on teen smoking cessation. Pediatrics. 2011;128(4):e801–e811. PubMed doi:10.1542/peds.2010-2599 14. Kaczynski AT, Manske SR, Mannell RC, Grewal K. Smoking and physical activity: a systematic review. Am J Health Behav. 2008;32(1):93–110. PubMed doi:10.5993/AJHB.32.1.9 15. Dierker L, Swendsen J, Rose J, He J, Merikangas K; Tobacco Etiology Research Network. Transitions to regular smoking and nicotine dependence in the Adolescent National Comorbidity Survey (NCS-A). Ann Behav Med. 2012;43(3):394–401. PubMed doi:10.1007/s12160011-9330-9 16. Audrain-McGovern J, Rodriguez D, Rodgers K, Cuevas J, Sass J. Longitudinal variation in adolescent physical activity patterns and the emergence of tobacco use. J Pediatr Psychol. 2012;37(6):622–633. PubMed doi:10.1093/jpepsy/jss043 17. Walker JF, Loprinzi PD. Longitudinal examination of predictors of smoking cessation in a national sample of U.S. adolescent and young adult smokers. Nicotine Tob Res. 2014;16(6):820–827. PubMed doi:10.1093/ntr/ntu005 18. Kozlowski LT, Porter CQ, Orleans CT, Pope MA, Heatherton T. Predicting smoking cessation with self-reported measures of nicotine dependence: FTQ, FTND, and HSI. Drug Alcohol Depend. 1994;34(3):211–216. PubMed doi:10.1016/0376-8716(94)90158-9 19. Borland R, Yong HH, O’Connor RJ, Hyland A, Thompson ME. The reliability and predictive validity of the Heaviness of Smoking Index and its two components: findings from the International Tobacco Control Four Country study. Nicotine Tob Res. 2010;12(Suppl):S45–S50. PubMed doi:10.1093/ntr/ntq038 20. Zschucke E, Gaudlitz K, Ströhle A. Exercise and physical activity in mental disorders: clinical and experimental evidence. J Prev Medicine Public Health. 2013;46(Suppl 1):S12–S21. 21. Loprinzi PD, Herod SM, Walker JF, Cardinal BJ, Mahoney SM, Kane CJ. Development of a conceptual model for smoking cessation: physical activity, neurocognition and executive functioning. Res Q Exerc Sport. 2015;86(4):338–46. PubMed 22. Posner MI, DiGirolamo GJ. Executive attention: conflict, target detection, and cognitive control. In: Parasuraman R, ed. The Attentive Brain. Cambridge, MA: MIT Press; 1998:401–423. 23. Glass JM, Buu A, Adams KM, et al. Effects of alcoholism severity and smoking on executive neurocognitive function. Addiction. 2009;104(1):38–48. PubMed doi:10.1111/j.1360-0443.2008.02415.x 24. Meyer T, Broocks A. Therapeutic impact of exercise on psychiatric diseases: guidelines for exercise testing and prescription. Sports Med. 2000;30(4):269–279. PubMed doi:10.2165/00007256-20003004000003
JPAH Vol. 13, No. 1, 2016
ORIGINAL RESEARCH
Association of Longitudinal Changes of Physical Activity on Smoking Cessation Among Young Daily Smokers Paul D. Loprinzi and Jerome F. Walker Objective: To our knowledge, no longitudinal epidemiological study among daily smokers has examined the effects of physical activity change/ trajectory on smoking cessation. The purpose of this study was to examine the longitudinal effects of changes in physical activity on smoking cessation among a national sample of young (16–24 y) daily smokers. Methods: Data from the 2003–2005 National Youth Smoking Cessation Survey were used (N = 1178). Using hierarchical agglomerative cluster analysis, 5 distinct self-reported physical activity trajectories over 3 time periods (baseline, 12-month, and 24-month follow-up) were observed, including stable low physical activity, decreasing physical activity, curvilinear physical activity, stable high physical activity, and increasing physical activity. Nicotine dependence (Heaviness of Smoking Index) and demographic parameters were assessed via survey. Results: With stable low physical activity (16.2% quit smoking) serving as the referent group, those in the stable high physical activity (24.8% quit smoking) group had 1.8 greater odds of not smoking at the 24-month follow-up period (odds ratio = 1.81; 95% confidence interval, 1.12–2.91) after adjusting for nicotine dependence, age, gender, race-ethnicity, and education. Conclusions: Maintenance of regular physical activity among young daily smokers may help to facilitate smoking cessation. Keywords: epidemiology, exercise, nicotine dependence
The relationship between smoking and physical activity is widely established, with smokers engaging in less physical activity than their nonsmoking counterparts.1,2 This relationship is possibly bidirectional, in that regular physical activity may help to prevent smoking initiation.2 Nonsmokers are reported as more physically active, particularly during the critical period between adolescence and young adulthood.3 And among smokers, physical activity may facilitate smoking cessation4,5 via reducing nicotine cravings,6 favoring quit attempts,7 and improving mood and self-efficacy.8 Recent cross-sectional work found 16- to 24-year-old youth meeting physical activity guidelines were less nicotine dependent.9 Encouraging intervention-based work suggests physical activity may help to mitigate cigarette cravings and facilitate smoking cessation.10–13 Not all studies, however, point to a smoking and physical activity relationship. A 2008 systematic review of smoking and physical activity found over half the studies were null, and, where effects were found, they were less pronounced among adolescents and youth.14 A more recent (2014) Cochrane review reported only 2 of 20 interventional trials offered evidence of exercise aiding in smoking cessation. Marked variations in the length, type, and timing of exercise among studies were noted.10 Yet if and how physical activity and smoking interact is of significant importance, particularly among the young, as smoking is a youth-onset disorder with mean age of onset at approximately 12 years. Nearly 20% of youth are fully nicotine dependent by the age of 14 to 15 years.15 A gap in the current literature on this topic includes the limited number of longitudinal epidemiological studies among daily smokers that have examined the possibility of physical activity facilitating smoking cessation. Notably, other related longitudinal epidemiological studies2,16 have been conducted, but they did not specifically focus on daily smokers and were drawn from nonnationally
representative samples. To our knowledge, no nationally representative longitudinal epidemiological study among daily smokers has examined the effects of physical activity change/trajectory on smoking cessation, which was the purpose of this brief report.
Methods Design Data from the 2003–2005 National Youth Smoking Cessation Survey (NYSCS) were used. This epidemiological prospective study of 16- to 24-year-old smokers examined factors associated with smoking cessation. The NYSCS employs a nationally representative sample of young smokers using a single-stage, unclustered design. Using random digit dialing methodology, persons residing in households in the 50 US states and the District of Columbia who smoked 20 or more lifetime cigarettes and had smoked in the previous 30 days were initially interviewed during June to November 2003. Follow-up assessment at 12 months and 24 months also occurred. All participants provided informed consent before participation in the study; the authors’ institution granted exemption of Institutional Review Board review.
Demographic Variables Sample demographic variables included an a priori age category (16–17, 18–20, 21–24 y; continuous measure of age not available in dataset), gender, race-ethnicity (non-Hispanic white, non-Hispanic black, Hispanic, and other race-ethnicity), and education (< 12th grade, high school graduate, and some college/college graduate).
Nicotine Dependence Loprinzi ([email protected]) is with the Dept of Health, Exercise Science, and Recreation Management, University of Mississippi, University, MS. Walker is with the Dept of Respiratory Therapy, Bellarmine University, Louisville, KY.
At baseline, nicotine dependence was established using a modified Heaviness of Smoking Index (HSI), calculated as the numeric sum of two coded questions: (1) “In the past 30 days, how many cigarettes did you smoke per day?” (responses of 10 or less, 11 to 20, and 1
2 Loprinzi and Walker
21+, respectively, were coded as 0, 1, and 2), and (2) “How soon after you wake up do you smoke?” (responses: within 5 minutes, from 6 to 30 minutes, from more than 30 minutes to 1 hour, and more than 1 hour, respectively, were coded as 3, 2, 1, and 0).17,18 HSI has been reported as a valid indicator of dependence, having utility as a predictor of quit attempt maintenance.19
Smoking Status at 24-Month Follow-up At the 24-month follow-up, current smoking was defined as selfreported smoking within the last 30 days, with no longer smoking defined as not smoking within the last 30 days.
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Physical Activity At baseline, 12-month follow-up, and 24-month follow-up, participants were asked, “How many hours per week on average do you exercise? This includes playing sports, working out, aerobics, running, swimming, brisk walking, and other exercise activities.”
Data Analysis All statistical analyses were performed using procedures from sample survey data using Stata (version 12.0; StataCorp LP, College State, TX) to account for the complex survey design used in the NYSCS. Survey sample weights were used to adjust for the complex survey design and to represent a national sample of US adolescent and young adult smokers. Specifically, sample weights were derived to compensate for differential probabilities of selection, reduce biases due to nonresponse, and adjust for under-coverage due to households without telephones. The final weights for the completed baseline interview were generated from a series of sequential adjustments, including the development of a household base weight that is the inverse of the probability of selecting the telephone number from the sampling frame, which is then adjusted for unknown residential status, screener nonresponse, and post stratification of the number of households from Current Population Survey data. Subsequently, follow-up final weights for those that completed the 24-month interviews were derived from additional adjustments, including, for example, adjusting the base weights for the 24-month nonresponse and then raking (ratio adjustment) these nonresponse adjusted base weights. Hierarchical agglomerative cluster (HAC) analysis, using Ward’s method on the principal component score, defined the number of physical activity clusters across the 3 time periods; k-means procedure was then used to form the clusters. A multivariable logistic regression was used to examine the association between physical activity trajectories and smoking status at the 24-month follow-up period (outcome variable); smoking at 2-year follow-up served as the referent group for the outcome variable. Covariates included baseline nicotine dependence, age group, gender, raceethnicity, and education. Statistical significance was established as P < .05.
Results In the 2003–2005 NYSCS, 2582 young smokers consented and provided data at baseline. The overall screener response rate at baseline was 60%, with an extended response rate of 70%; the extended response rate assumed that persons on military duty were ineligible for the study. The interview response rate for the 16- to 17-year-old youth was 70.4%, with the response rate among 18- to 24-year-olds
being 69.4%. Lastly, the overall response rate for both smokers and nonsmokers was identical across the age groups: 70.4% for younger youth and 69.4% for older participants. After excluding those with missing nicotine dependence and demographic data at baseline (n = 74), missing smoking status at the 24-month follow-up (n = 1122), and missing physical activity data at any of the three time periods (n = 208), 1178 participants remained and constituted the analytic sample (45% retention rate). Details on differences between those lost to follow-up and those retained have been reported in our previous work using this dataset that examined demographic and psychosocial determinants of smoking cessation17; those lost to follow-up were less educated and less likely to be non-Hispanic white. Notably, there were no differences in baseline physical activity (5.5 h/wk vs 5.2 h/wk, P = .40) or baseline nicotine dependence (1.20 vs 1.41, P = .09) among those included in the final sample compared with those excluded. Characteristics of the study variables are shown in Table 1. Based on the HAC analysis, 5 distinct physical activity clusters/ trajectories across the 3 time periods were identified (Figure 1). Based on the mean physical activity changes observed across the 3 time periods, we labeled these trajectories as: stable low physical activity, decreasing, curvilinear, stable high, and increasing. Across the 3 time periods, and for the stable low group (n = 466), mean (SE) physical activity (h/wk) changed from 2.4 (0.1) to 2.4 (0.1) to 2.2 (0.1). For the decreasing group (n = 159), physical activity changed from 10.1 (0.1) to 3.7 (0.2) to 3.5 (0.2). For the curvilinear group (n = 191), physical activity changed from 4.5 (0.2) to 9.9 (0.2) to 3.7 (0.1). For the stable high group (n = 200), physical activity changed from 11.6 (0.1) to 10.3 (0.2) to 10.0 (0.1). Lastly, for the increasing group (n = 162), physical activity changed from 3.8 (0.2) to 6.1 (0.3) to 10.9 (0.1). Across the 5 physical activity groups (stable low physical activity, decreasing, curvilinear, stable high, and increasing), respectively, the weighted proportion of those not smoking at the 24-month follow-up period was 16.2%, 15.7%, 18.9%, 24.8%, and 18.2%. Table 2 displays the weighted multivariable logistic regression analysis examining the association between physical activity trajectories and 24-month smoking status. With stable low physical activity serving as the referent group, the only physical activity trajectory associated with 24-month smoking status was stable high physical activity. Those in the stable high physical activity group had 1.8 greater odds of not smoking at the 24-month follow-up period (odds ratio = 1.81; 95% confidence interval, 1.12–91; P = .01). Analyses were recomputed with the inclusion of other covariates, including number of years smoking, and the results were unchanged (data not shown).
Discussion The purpose of this brief report was to examine, in a nationally representative sample of young US daily smokers, the association of physical activity changes on smoking cessation. Despite this novelty and notable strength, the main limitation of this study includes the subjective assessment of physical activity and smoking. Further, the assessment in physical activity in this study was not domain- or intensity-specific; therefore, the findings presented herein should be interpreted with this in mind. To our knowledge, no nationallyrepresentative epidemiological longitudinal study among daily smokers has examined the association between changes in physical activity on smoking cessation. This study adds to the literature by demonstrating that regular exercise over time among daily smokers may help to facilitate smoking cessation.
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Table 1 Weighted Characteristics, 2003–2005 National Youth Smoking Cessation Survey (N = 1178) Mean/Proportion (SE) Baseline characteristics
Stable low (n = 466)
Decreasing (n = 159)
Curvilinear (n = 191)
Stable high (n = 200)
Increasing (n = 162)
Age group, % 16–17 y
12.7 (1.5)
10.7 (2.3)
11.7 (2.2)
14.9 (2.4)
14.0 (2.6)
18–20 y
29.6 (2.1)
31.4 (3.6)
35.8 (3.6)
42.1 (3.7)
37.6 (4.0)
21–24 y
57.7 (2.4)
57.9 (4.0)
52.4 (3.8)
42.9 (3.8)
48.4 (4.4)
Male
44.1 (2.5)
60.5 (4.0)
59.0 (3.7)
71.9 (3.2)
55.2 (4.3)
Female
55.8 (2.5)
39.4 (4.0)
40.9 (3.7)
28.0 (3.2)
44.8 (4.3)
Gender, %
Education, % Less than 12th grade
23.6 (2.0)
26.1 (3.5)
29.0 (3.5)
31.7 (3.4)
32.9 (4.0)
High school graduate
31.4 (2.2)
31.2 (3.9)
32.9 (3.7)
34.4 (3.7)
30.2 (4.0)
Some college/college degree
45.0 (2.5)
42.6 (4.2)
38.1 (3.8)
33.9 (3.6)
36.9 (4.2)
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Race/ethnicity, % Non-Hispanic white
70.7 (2.3)
80.2 (3.4)
72.8 (3.6)
70.6 (3.6)
71.5 (4.0)
Non-Hispanic black
11.1 (1.5)
10.3 (2.5)
8.8 (2.3)
7.4 (2.1)
5.4 (1.7)
Hispanic
12.7 (1.9)
8.1 (2.4)
12.8 (2.9)
14.4 (3.0)
17.7 (3.6)
Non-Hispanic other
5.3 (1.1)
1.3 (0.8)
5.6 (1.6)
7.4 (1.8)
5.2 (1.8)
Nicotine dependence, baseline mean
1.25 (0.1)
1.23 (0.1)
1.07 (0.1)
1.29 (0.1)
1.10 (0.1)
Nicotine dependence, baseline range, 95% confidence interval
0–5, 1.10–1.39
0–5, 0.98–1.48
0–5, 0.85–1.29
0–5, 1.05–1.52
0–5, 0.84–1.34
Current smoker
83.8 (1.8)
84.3 (3.0)
81.0 (3.1)
75.2 (3.3)
81.8 (3.4)
Nonsmoker
16.2 (1.8)
15.7 (3.0)
18.9 (3.1)
24.8 (3.3)
18.2 (3.4)
Smoking status at 2-y follow-up, %
Figure 1 — Observed physical activity patterns across the 2-year period. Sample size (n) and weighted proportions for each physical activity group are as follows: stable low physical activity (n = 466; 40.1%), decreasing (n = 159; 13.5%), curvilinear (n = 191; 16.4%), stable high (n = 200; 17.0%), and increasing (n = 162; 13.0%). JPAH Vol. 13, No. 1, 2016
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4 Loprinzi and Walker
Table 2 Weighted Multivariable Logistic Regression Analysis Examining the Association Between Physical Activity Trajectories and Smoking Status (Outcome), 2003–2005 National Youth Smoking Cessation Survey (N = 1178) Odds ratio not smoking at 2-year follow-upa
Variable
95% CI
P-value
Physical activity trajectories Decreasing vs stable low
1.05
0.61–1.80
.84
Curvilinear vs stable low
1.16
0.69–1.95
.56
Stable High vs stable low
1.81
1.12–2.91
.01
Increasing vs stable low
1.06
0.61–1.84
.81
High school graduate vs less than 12th grade
1.29
0.72–2.32
.38
At least some college vs less than 12th grade
1.24
0.69–2.24
.45
Covariates
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Education
Race/ethnicity Non-Hispanic black vs non-Hispanic white
1.37
0.77–2.43
.27
Hispanic vs non-Hispanic white
2.53
1.56–4.11
< .01
Non-Hispanic other vs non-Hispanic white
1.29
0.64–2.58
.46
1.13
0.79–1.59
.48
1.11
0.57–2.17
.74
Gender Female vs male Age-category 18–20 vs 16–17 y 21–24 vs 16–17 y
0.91
0.44–1.88
.80
Nicotine dependence, 1 HSI increase
0.64
0.54–0.75
< .01
Abbreviations: CI, confidence interval; HSI, Heaviness of Smoking Index. a Smoking at 2-y follow-up served as the referent group for the outcome variable.
Specifically, we found 16- to 24-year-old smokers steadily engaging (over 2 years) in roughly 10 to 11 hours per week of physical activity were more likely to quit smoking than those that remained less active over time. This comports with a recent review of randomized control trials examining physical activity as therapy for substance use disorders, which found training frequency and intensity ≥ 3 sessions per week associates with fitness gains and, in turn, with favorable smoking outcomes.20 This is also in general agreement with work done by Audrain-McGovern and colleagues2 who examined 978 14- to 18-year-old Northern Virginia high school students, finding a relationship between maintaining roughly 12 hours per week of moderate intensity physical activity and the likelihood of initiating smoking, or of smoking progression among those that already smoked. Her group also examined 1384 Philadelphia high school students self-reporting their physical activity every 6 months from the ninth to the 12th grade.16 Latent growth curve modeling across the 8 waves (2 yearly physical activity assessments × 4 years) yielded 5 physical activity patterns (stable higher, decreasing, stable regular, curvilinear, and stable low) that were similar to our cluster analysis results. Smoking likelihood was twice as great among adolescents in the stable low, stable regular, and decreasing physical activity groups as in the stable high physical activity group. There were some differences between these studies and ours. Rather than longitudinal smoking initiation or smoking progression patterns among smoking and nonsmoking high-school students, 14- to 18-year-olds and from the eastern United States, we examined longitudinal self-reported smoking status among 16- to
24-year-olds, all smokers at baseline, drawn from a nationally representative sample. In conclusion, only the stable high physical activity group when compared with the low stable physical activity group had increased odds of not smoking at the 2-year follow-up period. If confirmed by future experimental and prospective work, understanding why higher levels of physical activity is most favorably associated with smoking cessation is warranted. Again, however, the current study was limited by the assessment of physical activity; therefore, future replicative work utilizing a better measure of physical activity is needed to improve our understanding of a potential dose- and intensity-dependent effect of physical activity on smoking cessation. Although speculative, higher doses of physical activity for vulnerable populations (eg, smokers, overweight/obese adults) may be needed to prevent behavioral relapses or for distraction purposes. Future mechanistic work on this topic is clearly needed. Another potential area in need of future inquiry is the possibility that physical activity may help to facilitate smoking cessation via physical activity–induced changes in executive function,21 as individuals with higher executive function (component of cognitive functioning) have an increased ability to maintain a goal-directed purposeful behavior,22 possibly as a result of a complex integration of planning, filtering competing information, maintaining a goal despite distraction, and inhibiting goal-inconsistent responses.23 Clearly, promotion of physical activity among daily smokers is needed, but such an effort will require careful planning and evaluation, as smokers are more likely to have various attributes (eg, psychiatric
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Physical Activity and Smoking Cessation 5
disease, lower fitness level, little experience with physical activity, and fear that physical activity may induce dyspnea, tachycardia, or dizziness24) that may negatively influence physical activity.
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References 1. Verkooijen KT, Nielsen GA, Kremers SP. The association between leisure time physical activity and smoking in adolescence: an examination of potential mediating and moderating factors. Int J Behav Med. 2008;15(2):157–163. PubMed doi:10.1080/10705500801929833 2. Audrain-McGovern J, Rodriguez D, Moss HB. Smoking progression and physical activity. Cancer Epidemiol Biomarkers Prev. 2003;12(11 pt 1):1121–1129. PubMed 3. Yang X, Telama R, Leino M, Viikari J. Factors explaining the physical activity of young adults: the importance of early socialization. Scand J Med Sci Sports. 1999;9(2):120–127. PubMed doi:10.1111/j.1600-0838.1999.tb00220.x 4. Paavola M, Vartiainen E, Puska P. Smoking cessation between teenage years and adulthood. Health Educ Res. 2001;16(1):49–57. PubMed doi:10.1093/her/16.1.49 5. Bernard P, Ninot G, Moullec G, Guillaume S, Courtet P, Quantin X. Smoking cessation, depression, and exercise: empirical evidence, clinical needs, and mechanisms. Nicotine Tob Res. 2013;15(10):1635– 1650. PubMed doi:10.1093/ntr/ntt042 6. Scerbo F, Faulkner G, Taylor A, Thomas S. Effects of exercise on cravings to smoke: the role of exercise intensity and cortisol. J Sports Sci. 2010;28(1):11–19. PubMed doi:10.1080/02640410903390089 7. King TK, Marcus BH, Pinto BM, Emmons KM, Abrams DB. Cognitive-behavioral mediators of changing multiple behaviors: smoking and a sedentary lifestyle. Prev Med. 1996;25(6):684–691. PubMed doi:10.1006/pmed.1996.0107 8. Prochaska JJ, Hall SM, Humfleet G, et al. Physical activity as a strategy for maintaining tobacco abstinence: a randomized trial. Prev Med. 2008;47(2):215–220. PubMed doi:10.1016/j.ypmed.2008.05.006 9. Loprinzi PD, Kane CJ, Mahoney S, Walker JF. Physical activity and nicotine dependence among a national sample of young U.S. adults who smoke daily: evaluation of cross-sectional and longitudinal associations to determine which behavior drives this relationship. Physiol Behav. 2015;139:1–6. PubMed 10. Ussher MH, Taylor AH, Faulkner GE. Exercise interventions for smoking cessation. Cochrane Database Syst Rev. 2014;8:CD002295. PubMed 11. Haasova M, Warren FC, Ussher M, et al. The acute effects of physical activity on cigarette cravings: systematic review and meta-analysis with individual participant data. Addiction. 2013;108(1):26–37. PubMed doi:10.1111/j.1360-0443.2012.04034.x 12. Haasova M, Warren FC, Ussher M, et al. The acute effects of physical activity on cigarette cravings: exploration of potential moderators,
mediators and physical activity attributes using individual participant data (IPD) meta-analyses. Psychopharmacology (Berl). 2014;231(7):1267–1275. PubMed doi:10.1007/s00213-014-3450-4 13. Horn K, Dino G, Branstetter SA, et al. Effects of physical activity on teen smoking cessation. Pediatrics. 2011;128(4):e801–e811. PubMed doi:10.1542/peds.2010-2599 14. Kaczynski AT, Manske SR, Mannell RC, Grewal K. Smoking and physical activity: a systematic review. Am J Health Behav. 2008;32(1):93–110. PubMed doi:10.5993/AJHB.32.1.9 15. Dierker L, Swendsen J, Rose J, He J, Merikangas K; Tobacco Etiology Research Network. Transitions to regular smoking and nicotine dependence in the Adolescent National Comorbidity Survey (NCS-A). Ann Behav Med. 2012;43(3):394–401. PubMed doi:10.1007/s12160011-9330-9 16. Audrain-McGovern J, Rodriguez D, Rodgers K, Cuevas J, Sass J. Longitudinal variation in adolescent physical activity patterns and the emergence of tobacco use. J Pediatr Psychol. 2012;37(6):622–633. PubMed doi:10.1093/jpepsy/jss043 17. Walker JF, Loprinzi PD. Longitudinal examination of predictors of smoking cessation in a national sample of U.S. adolescent and young adult smokers. Nicotine Tob Res. 2014;16(6):820–827. PubMed doi:10.1093/ntr/ntu005 18. Kozlowski LT, Porter CQ, Orleans CT, Pope MA, Heatherton T. Predicting smoking cessation with self-reported measures of nicotine dependence: FTQ, FTND, and HSI. Drug Alcohol Depend. 1994;34(3):211–216. PubMed doi:10.1016/0376-8716(94)90158-9 19. Borland R, Yong HH, O’Connor RJ, Hyland A, Thompson ME. The reliability and predictive validity of the Heaviness of Smoking Index and its two components: findings from the International Tobacco Control Four Country study. Nicotine Tob Res. 2010;12(Suppl):S45–S50. PubMed doi:10.1093/ntr/ntq038 20. Zschucke E, Gaudlitz K, Ströhle A. Exercise and physical activity in mental disorders: clinical and experimental evidence. J Prev Medicine Public Health. 2013;46(Suppl 1):S12–S21. 21. Loprinzi PD, Herod SM, Walker JF, Cardinal BJ, Mahoney SM, Kane CJ. Development of a conceptual model for smoking cessation: physical activity, neurocognition and executive functioning. Res Q Exerc Sport. 2015;86(4):338–46. PubMed 22. Posner MI, DiGirolamo GJ. Executive attention: conflict, target detection, and cognitive control. In: Parasuraman R, ed. The Attentive Brain. Cambridge, MA: MIT Press; 1998:401–423. 23. Glass JM, Buu A, Adams KM, et al. Effects of alcoholism severity and smoking on executive neurocognitive function. Addiction. 2009;104(1):38–48. PubMed doi:10.1111/j.1360-0443.2008.02415.x 24. Meyer T, Broocks A. Therapeutic impact of exercise on psychiatric diseases: guidelines for exercise testing and prescription. Sports Med. 2000;30(4):269–279. PubMed doi:10.2165/00007256-20003004000003
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