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. Author manuscript; available in PMC: 2017 May 1.
Published in final edited form as: AIDS Care. 2015 Dec 15;28(5):603–607. doi: 10.1080/09540121.2015.1120854

The Role of BMI Change on Smoking Abstinence in a Sample of HIV-Infected Smokers

Meredith K Buchberg 1,1,✉, Ellen R Gritz 2, George Kypriotakis 3, Roberto C Arduino 4, Damon J Vidrine 5
PMCID: PMC4970860  NIHMSID: NIHMS802192  PMID: 26666313

Abstract

The prevalence of cigarette smoking among persons living with HIV/AIDS (PLWHA) is approximately 40%, significantly higher than that of the general population. Identifying predictors of successful smoking cessation for PLWHA is necessary to alleviate the morbidity and mortality associated with smoking in this population. Weight gain has been associated with smoking relapse in the general population, but has not been studied among PLWHA. Data from 474 PLWHA enrolled in a smoking cessation randomized clinical trial were analyzed to examine the effect of BMI change, from baseline to 3-month follow-up, on smoking outcomes using multiple logistic regression. The odds of 7-day smoking abstinence at 3-month follow-up were 4.22 (95% CI=1.65, 10.82) times higher for participants classified as BMI decrease and 4.22 (95% CI=1.62, 11.01) times higher for participants classified as BMI increase as compared to participants with a minimal increase or decrease in BMI. In this sample, both weight gain and loss following smoking cessation were significantly associated with abstinence at 3-month follow-up among HIV-infected smokers. Further research and a better understanding of predictors of abstinence will encourage more tailored interventions, with the potential to reduce morbidity and mortality.

Keywords: HIV, smoking cessation, BMI, body image, obesity

Introduction

The estimated prevalence of smoking among people living with HIV/AIDS (PLWHA) is approximately 40% (Mdodo et al., 2015)as compared to 15% (Centers for Disease Control and Prevention, 2015)in the general population. Helleberg et al. (Helleberg et al., 2013) reported that the excess number of years of life lost due to HIV and smoking was 12.3 years for HIV-infected smokers as compared to HIV-infected non-smokers. Few randomized controlled trials have examined the effectiveness of smoking cessation programs tailored for PLWHA. Results from existing trials indicate that cessation rates, particularly long-term, are low and adherence is suboptimal (Gritz et al., 2013; Lloyd-Richardson et al., 2009; Matthews, Conrad, Kuhns, Vargas, & King, 2013; Moadel et al., 2012). A better understanding of the factors associated with cessation treatment efficacy could help improve low cessation rates and increase adherence to the prescribed intervention.

In the general population, weight gain following smoking cessation has been associated with decreased motivation and a lower number of quit attempts (Klesges, Meyers, Klesges, & La Vasque, 1989; Meyers et al., 1997; Ward, Klesges, Zbikowski, Bliss, & Garvey, 1997). Greater weight gain post-cessation has also been associated with African-American race and low socioeconomic status (Swan & Carmelli, 1995; Williamson et al., 1991), both of which are overrepresented characteristics of PLWHA in the United States.

Existing literature has shown that PLWHA are receptive to smoking cessation interventions (Vidrine, 2009; Vidrine, Marks, Arduino, & Gritz, 2012), but these studies have not focused on weight gain as a predictor of relapse. The current study attempts to assess this relationship.

Methods

Recruitment and Follow-Up

The parent study, which was a two-group randomized controlled trial, compared a Cell Phone Intervention (CPI) for smoking cessation to Usual Care (UC) (Gritz et al., 2013; Vidrine et al., 2012). Current smokers were recruited from a county clinic in Houston, TX that provides comprehensive care to underserved PLWHA. Weight change was not specifically addressed in either study group. Structured follow-up assessments and expired CO levels were conducted at 3, 6 and 12 months post-enrollment. In the current study, only baseline and 3-month follow-up data were used.

BMI Change

BMI change was calculated using height and weight information taken from the clinic’s electronic medical record system (EMR). Data were recorded from participant appointments closest to the dates, either preceding or following, that participants completed the baseline and 3-month assessments. Carry forward methodology was used for participants who did not have BMI data in the EMR at 3-months. For these participants, the 3-month BMI was coded the same as the baseline BMI and the overall BMI change was coded as “0” This methodology has been used in other randomized controlled trials, including those focusing on HIV and weight loss (Fairclough, Thijs, Huang, Finnern, & Wu, 2008; Lane, 2008; Ware, 2003).

Smoking Abstinence

The primary outcome was 7-day smoking abstinence which was biochemically verified with expired CO level. An intent-to-treat approach was used, with participants who did not complete the 3-month follow-up coded as smoking (Matthews et al., 2013; Moadel et al., 2012).

Co-variables

Demographic co-variables of interest included age, self-reported sex and racial/ethnic affiliation. The Fagerstrom Test of Nicotine Dependence (Heatherton, Kozlowski, Frecker, & Fagerstrom, 1991) and Center for Epidemiologic Studies Depression Scale scores (Lewinsohn, Seeley, Roberts, & Allen, 1997; Radloff, 1977) were also considered. A variable quantifying the number of days elapsed between the baseline and 3-month BMI measurements was included as a log exposure variable in all models.

Statistical Analyses

Descriptive statistics were calculated for the socio-demographic and smoking variables. Multiple logistic regression models were used to compare the association between BMI change and smoking abstinence at 3-months. BMI change was analyzed by quartiles in order to identify if larger magnitudes of BMI change, either increased or decreased, were associated with smoking abstinence. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to measure the strength and precision of the associations. Finally, chi-square and t-tests were used to test for differences at baseline in important covariates between the full sample and a complete case sample excluding participants with missing data at 3-months.

Results

A total of 474 participants were enrolled in the parent treatment trial (Gritz et al., 2013; Vidrine et al., 2012). See Table 1 for baseline socio-demographic and smoking characteristics of participants. No statistically significant differences in socio-demographic variables were observed between participants in the full sample and complete case sample.

Table 1.

Baseline Characteristics of Study Participants (n=474)

Characteristic, n (%)
Age, mean (SD) 44.8 (8.1)
Male 332 (70.0)
Race/ethnicity
 White 59 (12.4)
 Black/African American 361 (76.2)
 Latino/Hispanic 43 (9.1)
 Other 11 (2.3)
HIV Transmission
 Male homosexual contact 119 (25.1)
 Heterosexual contact 215 (45.4)
 Injection drug use 81 (17.1)
 Other 57 (12.0)
Years of formal education, mean (SD) 10.9 (2.6)
Depression (CES-D1 score) ≥ 16 319 (67.3)
Cigarettes smoked per day, mean (SD) 19.2 (11.6)
Nicotine dependence (FTND2), mean (SD) 5.78 (2.3)
Body mass index, mean (SD) 26.2 (6.0)
Current diagnosis of a co-morbid condition 291 (61.4)
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1

Centers for Epidemiologic Studies Depression scale; scores ≥16 indicate clinical depression

2

Fagerstrom Test for Nicotine Dependence

At baseline, the mean (SD) BMI in the sample was 26.22 (5.97) units. The percentage of patients classified as wasting (BMI <18.5) and overweight or obese (BMI >25) were 3.5% and 50.0%, respectively. The mean (SD) time elapsed between collection of baseline and 3-month BMI data was 94.43 (26.63) days. Table 2 presents the results from multiple regression models of smoking outcomes at the 3-month follow-up. To facilitate comparisons, BMI change was categorized in quartiles: BMI decrease, minimal BMI decrease, minimal BMI increase and BMI increase. Because the intent of this analysis was to investigate the association of a larger magnitude of BMI change and smoking abstinence, the minimal BMI decrease and minimal BMI increase quartiles were combined into a single minimal change referent group. Participants in both the BMI increase and decrease groups (vs. the minimal change group) were significantly more likely to report 7-day abstinence.

Table 2.

BMI Change as a Predictor of Smoking Abstinence at 3-month Follow-up1,2

Quartile OR (95% CI) P-Value
BMI Decrease3
7-day 4.22 (1.65, 10.82) 0.003
BMI Increase4
7-day 4.22 (1.62, 11.01) 0.003
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1

Models adjusted for treatment group, age, sex, race, nicotine dependence, depression

2

Models compared to minimal BMI decrease and minimal BMI increase as referent (Range: −0.41≤ BMI change<0.81 units).

3

BMI change <−0.41 units

4

BMI change >0.81 units

The odds of 7-day smoking abstinence at 3-month follow-up were 4.22 (95% CI=1.65, 10.82) times higher for participants classified as BMI decrease (Range: −4.91≤BMI change<−0.41) as compared to participants with a minimal increase or decrease in BMI The odds of 7-day smoking abstinence for participants classified as BMI increase (Range: 0.81≤BMI change<7.82 units) were 4.22 (95% CI=1.62, 11.01) times higher as compared to participants with a minimal increase or decrease in BMI.

Discussion

In the general population, concerns about weight gain have been associated with decreased motivation to quit (Meyers et al., 1997; Pomerleau & Kurth, 1996), and post-cessation weight gain has been observed among successful quitters (Swan & Carmelli, 1995; Williamson et al., 1991). In this sample of HIV-infected smokers, larger magnitude of BMI change, either positive or negative, versus minimal BMI change was significantly associated with 7-day smoking abstinence at 3-months. The partially contrary nature of the results in this sample to smoking behaviors observed in the general population may be related to different perceptions of weight gain among minorities and PLWHA (Clark, Niccolai, Kissinger, Peterson, & Bouvier, 1999; Fingeret, Vidrine, Arduino, & Gritz, 2007).

Clark et al. (Clark et al., 1999) found that HIV-infected African-American women were more likely than non-infected African-American women to be satisfied with their weight, have the desire to be bigger, believe that weight gain would protect against sickness and that they would not be perceived as sick if they gained weight. Sharma et al.(Sharma, Howard, Schoenbaum, Buono, & Webber, 2006; Sharma et al., 2007) found that among overweight, HIV-infected men, only 26.0% perceived themselves as too heavy; among overweight, HIV-infected women, 52.4% women believed their weight was “just right.” It is possible that in our sample, weight gain was not associated with poorer abstinence outcomes because participants perceived themselves as being at a healthy weight even if their BMI classified them as overweight or obese.

Missing data is a limitation of this study. However, we believe the data were missing at random because no significant differences were seen between participants that had complete BMI and smoking data as compared to those that were analyzed with carry forward and intent to treat methodology. Although the average time elapsed between baseline and 3-month BMI collection was approximately 3-months (Mean=94.43 days), the time elapsed ranged from 20–308 days giving participants differing amounts of follow-up time. In addition, although the CPI intervention did not specifically cover weight change, it is possible that some participants brought it up on their own with their counselor. Results from the parent study indicated that the treatment group had a significant effect on smoking abstinence (Gritz et al., 2013; Vidrine et al., 2012), but from this analysis we cannot identify the effect of BMI change on smoking outcomes without the compounded effect of treatment group.

To our knowledge, this is the first analysis of the association between BMI change and smoking outcomes in a sample of HIV-infected smokers. Smoking is a major contributor to morbidity and mortality in this population (Crothers et al., 2005; Helleberg et al., 2013; Lifson et al., 2010). As people live longer with HIV/AIDS, obesity is becoming another factor contributing to the burden of chronic disease (Amorosa et al., 2005; Shor-Posner et al., 2000). In this sample, both large increases and decreases in BMI were associated with smoking abstinence. Weight gain and loss may serve as potential teachable moments for smoking cessation. A better understanding of how weight gain/loss following smoking cessation affects prolonged abstinence may inform the development of more effective treatment approaches in the future, which may ultimately minimize the adverse health outcomes associated with both smoking and obesity.

Acknowledgments

This trial has been registered at clinicaltrails.gov [NCT00502827]

This work was supported by the National Cancer Institute at the National Institutes of Health under grants [R01CA097893] awarded to Ellen Gritz, and [P30CA16672] awarded to Ronald DePinho.

Footnotes

Author Disclosure Statement

No competing financial interests exist.

Contributor Information

Meredith K. Buchberg, Email: buchberg@uthscsa.edu, Department of Behavioral Science, MD Anderson Cancer Center, 1155 Pressler, Unit 1330, Houston, TX 77030, United States.

Ellen R. Gritz, Email: egritz@mdanderson.org, Department of Behavioral Science, MD Anderson Cancer Center, 1155 Pressler, Unit 1330, Houston, TX 77030, United States; Telephone (713) 745-3187.

George Kypriotakis, Email: GKypriotakis@mdanderson.org, Department of Behavioral Science, MD Anderson Cancer Center, 1155 Pressler, Unit 1330, Houston, TX 77030, United States; Telephone (713) 792-8270.

Roberto C. Arduino, Email: Roberto.c.arduino@uth.tmc.edu, Department of Internal Medicine, University of Texas Health Science Center at Houston, 6431 Fannin Street, MSB 2.112, Houston, TX 77030, United States; Telephone (713) 500-6767.

Damon J. Vidrine, Email: Damon-Vidrine@ouhsc.edu, Department of Family and Preventative Medicine, The University of Oklahoma Health Sciences Center, 655 Research Parkway, Suite 400, Oklahoma City, OK, 73104; United States; Telephone (405) 271-4005.

References

  1. Amorosa V, Synnestvedt M, Gross R, Friedman H, MacGregor RR, Gudonis D, Tebas P. A tale of 2 epidemics: The intersection between obesity and HIV infection in philadelphia. Journal of Acquired Immune Deficiency Syndromes (1999) 2005;39(5):557–561. [PubMed] [Google Scholar]
  2. Centers for Disease Control and Prevention. Early release of selected estimates based on data from the national health interview survey, January–March 2015. 2015. [Google Scholar]
  3. Clark RA, Niccolai L, Kissinger PJ, Peterson Y, Bouvier V. Ethnic differences in body image attitudes and perceptions among women infected with human immunodeficiency virus. Journal of the American Dietetic Association. 1999;99(6):735–737. doi: 10.1016/S0002-8223(99)00398-3. doi:S0002-8223(99)00398-3 [pii] [DOI] [PubMed] [Google Scholar]
  4. Crothers K, Griffith TA, McGinnis KA, Rodriguez-Barradas MC, Leaf DA, Weissman S, Justice AC. The impact of cigarette smoking on mortality, quality of life, and comorbid illness among HIV-positive veterans. Journal of General Internal Medicine. 2005;20(12):1142–1145. doi: 10.1111/j.1525-1497.2005.0255.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Fairclough DL, Thijs H, Huang IC, Finnern HW, Wu AW. Handling missing quality of life data in HIV clinical trials: What is practical? Quality of Life Research: An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation. 2008;17(1):61–73. doi: 10.1007/s11136-007-9284-3. [DOI] [PubMed] [Google Scholar]
  6. Fingeret MC, Vidrine DJ, Arduino RC, Gritz ER. The association between body image and smoking cessation among individuals living with HIV/AIDS. Body Image. 2007;4(2):201–206. doi: 10.1016/j.bodyim.2007.01.005. doi:S1740-1445(07)00004-6 [pii] [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Gritz ER, Danysh HE, Fletcher FE, Tami-Maury I, Fingeret MC, King RM, Vidrine DJ. Long-term outcomes of a cell phone-delivered intervention for smokers living with HIV/AIDS. Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America. 2013;57(4):608–615. doi: 10.1093/cid/cit349. doi:10.1093/cid/cit349 [doi] [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Heatherton TF, Kozlowski LT, Frecker RC, Fagerstrom KO. The fagerstrom test for nicotine dependence: A revision of the fagerstrom tolerance questionnaire. British Journal of Addiction. 1991;86(9):1119–1127. doi: 10.1111/j.1360-0443.1991.tb01879.x. [DOI] [PubMed] [Google Scholar]
  9. Helleberg M, Afzal S, Kronborg G, Larsen CS, Pedersen G, Pedersen C, Obel N. Mortality attributable to smoking among HIV-1-infected individuals: A nationwide, population-based cohort study. Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America. 2013;56(5):727–734. doi: 10.1093/cid/cis933. [DOI] [PubMed] [Google Scholar]
  10. Klesges RC, Meyers AW, Klesges LM, La Vasque ME. Smoking, body weight, and their effects on smoking behavior: A comprehensive review of the literature. Psychological Bulletin. 1989;106(2):204–230. doi: 10.1037/0033-2909.106.2.204. [DOI] [PubMed] [Google Scholar]
  11. Lane P. Handling drop-out in longitudinal clinical trials: A comparison of the LOCF and MMRM approaches. Pharmaceutical Statistics. 2008;7(2):93–106. doi: 10.1002/pst.267. [DOI] [PubMed] [Google Scholar]
  12. Lewinsohn PM, Seeley JR, Roberts RE, Allen NB. Center for epidemiologic studies depression scale (CES-D) as a screening instrument for depression among community-residing older adults. Psychology and Aging. 1997;12(2):277–287. doi: 10.1037//0882-7974.12.2.277. [DOI] [PubMed] [Google Scholar]
  13. Lifson AR, Neuhaus J, Arribas JR, van den Berg-Wolf M, Labriola AM, Read TR, INSIGHT SMART Study Group Smoking-related health risks among persons with HIV in the strategies for management of antiretroviral therapy clinical trial. American Journal of Public Health. 2010;100(10):1896–1903. doi: 10.2105/AJPH.2009.188664. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Lloyd-Richardson EE, Stanton CA, Papandonatos GD, Shadel WG, Stein M, Tashima K, Niaura R. Motivation and patch treatment for HIV+ smokers: A randomized controlled trial. Addiction (Abingdon, England) 2009;104(11):1891–1900. doi: 10.1111/j.1360-0443.2009.02623.x. [doi] [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Matthews AK, Conrad M, Kuhns L, Vargas M, King AC. Project exhale: Preliminary evaluation of a tailored smoking cessation treatment for HIV-positive african american smokers. AIDS Patient Care and STDs. 2013;27(1):22–32. doi: 10.1089/apc.2012.0253. [DOI] [PubMed] [Google Scholar]
  16. Mdodo R, Frazier EL, Dube SR, Mattson CL, Sutton MY, Brooks JT, Skarbinski J. Cigarette smoking prevalence among adults with HIV compared with the general adult population in the united states: Cross-sectional surveys. Annals of Internal Medicine. 2015;162(5):335–344. doi: 10.7326/M14-0954. [doi] [DOI] [PubMed] [Google Scholar]
  17. Meyers AW, Klesges RC, Winders SE, Ward KD, Peterson BA, Eck LH. Are weight concerns predictive of smoking cessation? A prospective analysis. Journal of Consulting and Clinical Psychology. 1997;65(3):448–452. doi: 10.1037//0022-006x.65.3.448. [DOI] [PubMed] [Google Scholar]
  18. Moadel AB, Bernstein SL, Mermelstein RJ, Arnsten JH, Dolce EH, Shuter J. A randomized controlled trial of a tailored group smoking cessation intervention for HIV-infected smokers. Journal of Acquired Immune Deficiency Syndromes (1999) 2012;61(2):208–215. doi: 10.1097/QAI.0b013e3182645679. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Pomerleau CS, Kurth CL. Willingness of female smokers to tolerate postcessation weight gain. Journal of Substance Abuse. 1996;8(3):371–378. doi: 10.1016/s0899-3289(96)90215-1. [DOI] [PubMed] [Google Scholar]
  20. Radloff L. The CES-D scale a self-report depression scale for research in the general population. Applied Psychological Measurement. 1977;1:385–401. [Google Scholar]
  21. Sharma A, Howard AA, Klein RS, Schoenbaum EE, Buono D, Webber MP. Body image in older men with or at-risk for HIV infection. AIDS Care. 2007;19(2):235–241. doi: 10.1080/09540120600774354. doi:769863076 [pii] [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Sharma A, Howard AA, Schoenbaum EE, Buono D, Webber MP. Body image in middle-aged HIV-infected and uninfected women. AIDS Care. 2006;18(8):998–1003. doi: 10.1080/09540120500521517. doi:PW8433691621VX5K [pii] [DOI] [PubMed] [Google Scholar]
  23. Shor-Posner G, Campa A, Zhang G, Persaud N, Miguez-Burbano MJ, Quesada J, Baum MK. When obesity is desirable: A longitudinal study of the miami HIV-1-infected drug abusers (MIDAS) cohort. Journal of Acquired Immune Deficiency Syndromes (1999) 2000;23(1):81–88. doi: 10.1097/00126334-200001010-00011. [DOI] [PubMed] [Google Scholar]
  24. Swan GE, Carmelli D. Characteristics associated with excessive weight gain after smoking cessation in men. American Journal of Public Health. 1995;85(1):73–77. doi: 10.2105/ajph.85.1.73. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Vidrine DJ. Cigarette smoking and HIV/AIDS: Health implications, smoker characteristics and cessation strategies. AIDS Education and Prevention: Official Publication of the International Society for AIDS Education. 2009;21(3 Suppl):3–13. doi: 10.1521/aeap.2009.21.3_supp.3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Vidrine DJ, Marks RM, Arduino RC, Gritz ER. Efficacy of cell phone-delivered smoking cessation counseling for persons living with HIV/AIDS: 3-month outcomes. Nicotine & Tobacco Research: Official Journal of the Society for Research on Nicotine and Tobacco. 2012;14(1):106–110. doi: 10.1093/ntr/ntr121. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Ward KD, Klesges RC, Zbikowski SM, Bliss RE, Garvey AJ. Gender differences in the outcome of an unaided smoking cessation attempt. Addictive Behaviors. 1997;22(4):521–533. doi: 10.1016/s0306-4603(96)00063-9. [DOI] [PubMed] [Google Scholar]
  28. Ware JH. Interpreting incomplete data in studies of diet and weight loss. The New England Journal of Medicine. 2003;348(21):2136–2137. doi: 10.1056/NEJMe030054. [DOI] [PubMed] [Google Scholar]
  29. Williamson DF, Madans J, Anda RF, Kleinman JC, Giovino GA, Byers T. Smoking cessation and severity of weight gain in a national cohort. The New England Journal of Medicine. 1991;324(11):739–745. doi: 10.1056/NEJM199103143241106. [DOI] [PubMed] [Google Scholar]

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