Abstract
We compared characteristics of homeless smokers and economically disadvantaged domiciled smokers (Dallas, TX; August 2011–November 2012). Although findings indicated similar smoking characteristics across samples, homeless smokers (n = 57) were exposed to more smokers and reported lower motivation to quit, lower self-efficacy for quitting, more days with mental health problems, and greater exposure to numerous stressors than domiciled smokers (n = 110). The sample groups reported similar scores on measures of affect, perceived stress, and interpersonal resources. Results may inform novel cessation interventions for homeless smokers.
Homeless individuals in the United States1 have higher rates of disease, shorter life expectancy, and disproportionately higher health care costs than domiciled, socioeconomically disadvantaged individuals.2–5 A primary cause of these disparities is that smoking prevalence among homeless individuals (70% of whom smoke)6–8 is twice as high as that among those living in poverty (34.7% of whom smoke9). Numerous studies have indicated that many variables typical of low socioeconomic status (SES) and homelessness (e.g., low education, low income, high financial strain, unemployment) are associated with a reduced likelihood of smoking cessation.10–13 However, few studies have specifically examined psychosocial and smoking characteristics of homeless smokers. The purpose of the current study was to compare homeless smokers with domiciled, socioeconomically disadvantaged smokers to highlight additional obstacles specific to homeless smokers that may need to be addressed during smoking cessation interventions.
METHODS
Participants included in the current analyses were recruited into 1 of 2 studies at tobacco cessation clinics in the Dallas, Texas, metropolitan area between August 2011 and November 2012. Inclusion criteria were being aged 18 years or older, a reading level higher than 6th grade (assessed via the Rapid Estimate of Adult Literacy in Medicine),14 smoking 5 cigarettes or more per day, carbon monoxide level of 8 parts per million or more at baseline, willing to quit smoking within 7 days, and ability to attend 6 weekly assessment sessions. The domiciled sample was recruited from a Dallas safety-net hospital smoking cessation clinic and the homeless sample was recruited from the smoking cessation clinic at a Dallas homeless shelter. In the homeless sample, only those who resided in the transitional shelter were eligible.
All participants completed measures of sociodemographic and smoking characteristics (Table 1). In addition, participants completed measures of subjective social status,15 nicotine dependence,16 affect and perceived stress,17,18 mental health,19–21 negative experiences or exposure to threat or harm,22–25 interpersonal resources,26–30 and self-efficacy or motivation for smoking cessation (Table 2; Castro et al., unpublished data, 2012).31 We conducted analyses of group differences (i.e., homeless vs domiciled samples) using χ2 or analysis of variance.
TABLE 1—
Characteristic | Homeless Smokers (n = 57), Mean (SD) or % | Domiciled Smokers (n = 110), Mean (SD) or % | P |
Demographic | |||
Age, y | 50.0 (7.7) | 52.6 (7.2) | .03 |
Gender, male | 66.7 | 43.6 | .005 |
Race, Black | 55.4 | 65.5 | .205 |
Married or partnered | 35.1 | 55.5 | .013 |
Education, y | 12.4 (2.0) | 12.1 (1.9) | .258 |
Reading level14 | 61.9 (4.9) | 60.8 (5.8) | .229 |
Employed at least part time | 5.3 | 17.3 | .03 |
Family income < $12 000/y | 96.3 | 58.3 | < .001 |
Not insured, % yes | 87.7 | 55.5 | < .001 |
Community social status ladder15 | 4.3 (2.5) | 5.6 (2.2) | .001 |
US social status ladder15 | 3.3 (2.3) | 4.3 (2.0) | .005 |
Smoking | |||
Cigarettes/d | 18.3 (10.5) | 17.0 (8.5) | .375 |
Years smoking | 29.3 (10.7) | 31.6 (9.5) | .161 |
Lifetime quit attempts lasting at least 24 h | 4.2 (3.3) | 4.1 (3.3) | .772 |
No. of smokers exposed to each d | 42.9 (29.1) | 3.5 (4.1) | < .001 |
Heaviness of Smoking Index16 | 2.9 (1.5) | 3.1 (1.2) | .401 |
TABLE 2—
Variable | Homeless Smokers (n = 57), Mean (SD) or % | Domiciled Smokers (n = 110), Mean (SD) or % | P |
Affect and perceived stress | |||
PANAS—Negative Affect17 | 18.0 (6.6) | 19.5 (8.0) | .233 |
PANAS—Positive Affect17 | 31.2 (10.5) | 29.2 (9.4) | .22 |
Perceived Stress Scale18 | 6.1 (3.4) | 6.3 (3.3) | .618 |
Mental health | |||
PHQ Alcohol Dependence20 | 17.5 | 17.3 | .965 |
Depression diagnosis history | 80.7 | 50.9 | <.001 |
BRFSS no. of days with mental health problems21 | 11.5 (10.5) | 8.0 (9.8) | .035 |
CES–D,9 | 15.7 (10.3) | 16.0 (11.1) | .879 |
Negative experiences and exposure to threat or harm | |||
Detroit Discrimination Scale25 | 31.5 (13.4) | 19.5 (10.0) | <.001 |
Urban Life Stress Scale24 | 48.4 (11.1) | 43.2 (11.8) | .006 |
Social Cohesion and Trust Scale23 | 14.2 (2.3) | 15.6 (2.7) | .001 |
Fear Scale22 | 1.7 (0.8) | 1.5 (0.6) | .027 |
Mistrust Scale22 | 1.9 (0.7) | 1.6 (0.6) | .002 |
Reserve capacity | |||
Loneliness28 | 5.3 (2.0) | 5.2 (1.9) | .713 |
General Self-Efficacy Scale26 | 34.1 (6.1) | 33.8 (5.8) | .738 |
Revised Life Orientation Test30 | 13.8 (4.4) | 14.5 (4.1) | .362 |
ISEL27 | |||
Appraisal scale | 12.4 (3.1) | 12.5 (2.9) | .87 |
Belonging scale | 12.5 (2.9) | 12.2 (3.1) | .523 |
Tangible support scale | 12.3 (3.0) | 12.3 (3.0) | .077 |
Lubben Social Network Scale29 | 12.1 (7.3) | 13.7 (6.3) | .122 |
Self-efficacy/motivation for quitting | |||
Self-efficacy and motivation for quitting: TSAMS Motivation for Quittinga | 20.9 (4.4) | 22.2 (3.9) | .047 |
Self-efficacy for quitting31 | |||
Positive affect and social situations | 2.2 (0.9) | 2.7 (0.8) | <.001 |
Negative affect situations | 2.1 (0.9) | 2.3 (0.9) | .069 |
Habit and craving situations | 2.3 (0.9) | 2.8 (0.8) | .001 |
Note. BRFSS = Behavioral Risk Factor Surveillance System; CES-D = Center for Epidemiological Studies—Depression scale; ISEL = Interpersonal Support Evaluation List; PANAS = Positive and Negative Affect Schedule; PHQ = Patient Health Questionnaire; TSAMS = Texas Smoking Abstinence Motivation Scale.
Castro et al., unpublished data, 2012.
RESULTS
Homeless participants (n = 57) were more likely to be male, younger, single, uninsured, and unemployed than domiciled participants (n = 110; Table 1). In addition, domiciled smokers placed themselves on higher rungs of the community and US subjective social status ladders.15 Although smoking characteristics were similar across samples, homeless smokers reported daily exposure to substantially more smokers than did domiciled smokers (Table 1).
The homeless and domiciled samples were similar on measures of recent affect, current symptoms of depression, perceived stress, and alcohol abuse (Table 2). However, the homeless sample reported more recent days with mental health problems, greater depression diagnosis prevalence, higher levels of discrimination, higher scores on the Urban Life Stress Scale, more fear, more mistrust of others, and lower social cohesion and trust than did the domiciled sample (Table 2). The sample groups scored similarly on measures of loneliness, general self-efficacy, dispositional optimism, social support, and social isolation (Table 2). Finally, the homeless sample was less motivated to quit smoking and reported lower confidence in maintaining abstinence than did the domiciled sample (Table 2).
DISCUSSION
Study results indicate that, compared with low-SES domiciled smokers, homeless smokers may have more mental health problems, be surrounded by more smokers, be exposed to substantially more stressors and discrimination, and have lower motivation and self-efficacy for quitting. Each of these variables may play a role in the extremely high prevalence of smoking among homeless individuals and the low smoking cessation rate in this population. These differences may suggest that homeless smokers seeking treatment may not respond to cessation interventions specifically developed for domiciled low-SES smokers. Study findings also demonstrate that homeless smokers possess psychosocial resources comparable to those of socioeconomically disadvantaged domiciled smokers. Thus, homeless individuals may have effective coping mechanisms that may be used to increase successful smoking cessation if tapped in novel smoking cessation interventions.
Findings highlight many variables that may be targeted in future cessation programs specifically tailored to the needs of homeless smokers, and results may be used to support changes in tobacco use policies at shelters. For example, creating smoke-free zones or disallowing smoking altogether on shelter grounds may reduce continued exposure to other smokers, thus addressing a known barrier to successful smoking cessation.32,33 This policy is consistent with recommendations from the Break Free Alliance Expert Panel.34
Study limitations include the use of small regional samples seeking cessation treatment, which may limit generalizability and analysis power, reliance on self-report, and our comparison of 2 different populations of smokers. Although these limitations are significant, we believe that this type of comparison is warranted because of the dearth of knowledge regarding the potential causes for the high smoking prevalence and the low smoking cessation rate among homeless individuals. Novel smoking cessation interventions that address specific barriers experienced by homeless smokers should be developed. These tailored interventions may have an enormous impact on the health and life expectancy of this underserved and vulnerable population.
Acknowledgments
Funding for this research was provided by the University of Texas School of Public Health. Data analysis and article preparation were additionally supported by grants from the American Cancer Society to M. S. Businelle (MRSGT-12-114-01-CPPB) and D. E. Kendzor (MRSGT-10-104-01-CPHPS).
We thank the staffs at the Bridge Homeless Assistance Center and Parkland Health and Hospital System, Dallas, TX, for their work and support throughout the data collection portion of this project. In addition, we thank Jay Dunn (Bridge CEO) and Neil Phillips (Bridge smoking cessation program coordinator and counselor) for their efforts that enabled this research.
Human Participant Protection
This study was approved by the institutional review boards at the University of Texas School of Public Health and the University of Texas Southwestern Medical Center.
References
- 1.US Department of Housing and Urban Development. Homeless emergency assistance and rapid transition to housing: defining “homeless.”. Fed Regist. 2011;76(233):75994–76019. [Google Scholar]
- 2.Barrow SM, Herman DB, Cordova P, Struening EL. Mortality among homeless shelter residents in New York City. Am J Public Health. 1999;89(4):529–534. doi: 10.2105/ajph.89.4.529. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Hwang SW, Wilkins R, Tjepkema M, O’Campo PJ, Dunn JR. Mortality among residents of shelters, rooming houses, and hotels in Canada: 11 year follow-up study. BMJ. 2009;339 doi: 10.1136/bmj.b4036. b4036. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Weinreb L, Goldberg R, Perloff J. Health characteristics and medical service use patterns of sheltered homeless and low-income housed mothers. J Gen Intern Med. 1998;13(6):389–397. doi: 10.1046/j.1525-1497.1998.00119.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Buck DS, Brown CA, Mortensen K, Riggs JW, Franzini L. Comparing homeless and domiciled patients’ utilization of the Harris County Texas public hospital system. J Health Care Poor Underserved. 2012;23(4):1660–1670. doi: 10.1353/hpu.2012.0171. [DOI] [PubMed] [Google Scholar]
- 6.Arnsten JH, Reid K, Bierer M, Rigotti N. Smoking behavior and interest in quitting among homeless smokers. Addict Behav. 2004;29(6):1155–1161. doi: 10.1016/j.addbeh.2004.03.010. [DOI] [PubMed] [Google Scholar]
- 7.Butler J, Okuyemi KS, Jean S, Nazir N, Ahluwalia JS, Resnicow K. Smoking characteristics of a homeless population. Subst Abus. 2002;23(4):223–231. doi: 10.1080/08897070209511495. [DOI] [PubMed] [Google Scholar]
- 8.Hwang SW, Henderson MJ. Health Care Utilization in Homeless People: Translating Research into Policy and Practice. Rockville, MD: Agency for Healthcare Research and Quality; 2010. Working Paper No. 10002. [Google Scholar]
- 9.Barbeau EM, Krieger N, Soobader M. Working class matters: Socioeconomic disadvantage, race/ethnicity, gender, and smoking in NHIS 2000. Am J Public Health. 2004;94(2):269–278. doi: 10.2105/ajph.94.2.269. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Businelle MS, Kendzor DE, Costello TJ et al. Mechanisms linking socioeconomic status to smoking cessation: a structural equation modeling approach. Health Psychol. 2010;29(3):262–273. doi: 10.1037/a0019285. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Kendzor DE, Businelle MS, Costello TJ et al. Financial strain and smoking cessation among racially/ethnically diverse smokers. Am J Public Health. 2010;100(4):702–706. doi: 10.2105/AJPH.2009.172676. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Siahpush M, Carlin JB. Financial stress, smoking cessation and relapse: results from a prospective study of an Australian national sample. Addiction. 2006;101(1):121–127. doi: 10.1111/j.1360-0443.2005.01292.x. [DOI] [PubMed] [Google Scholar]
- 13.Fernández E, Schiaffino A, Borrell C et al. Social class, education, and smoking cessation: long-term follow-up of patients treated at a smoking cessation unit. Nicotine Tob Res. 2006;8(1):29–36. doi: 10.1080/14622200500264432. [DOI] [PubMed] [Google Scholar]
- 14.Davis TC, Crouch MA, Long SW et al. Rapid assessment of literacy levels of adult primary care patients. Fam Med. 1991;23(6):433–435. [PubMed] [Google Scholar]
- 15.Adler NE, Stewart J. The MacArthur scale of subjective social status. Available at: http://www.macses.ucsf.edu/Research/Psychosocial/subjective.php. Accessed December 20, 2012.
- 16.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. doi: 10.1016/0376-8716(94)90158-9. [DOI] [PubMed] [Google Scholar]
- 17.Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative affect: The PANAS scales. J Pers Soc Psychol. 1988;54(6):1063–1070. doi: 10.1037//0022-3514.54.6.1063. [DOI] [PubMed] [Google Scholar]
- 18.Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24(4):385–396. [PubMed] [Google Scholar]
- 19.Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1(3):385–401. [Google Scholar]
- 20.Spitzer RL, Kroenke K, Williams JB. Validation and utility of a self-report version of PRIME-MD: the PHQ Primary Care Study. Primary care evaluation of mental disorders. Patient Health Questionnaire. JAMA. 1999;282(18):1737–1744. doi: 10.1001/jama.282.18.1737. [DOI] [PubMed] [Google Scholar]
- 21.Centers for Disease Control and Prevention. Behavioral Risk Factor Surveillance System Survey Data. Atlanta, GA: US Department of Health and Human Services; 2009. [Google Scholar]
- 22.Ross CE, Jang SJ. Neighborhood disorder, fear, and mistrust: the buffering role of social ties with neighbors. Am J Community Psychol. 2000;28(4):401–420. doi: 10.1023/a:1005137713332. [DOI] [PubMed] [Google Scholar]
- 23.Sampson RJ, Raudenbush SW, Felton E. Neighborhoods and violent crime: a multilevel study of collective efficacy. Science. 1997;277(5328):918–924. doi: 10.1126/science.277.5328.918. [DOI] [PubMed] [Google Scholar]
- 24.Jaffee KD, Liu GC, Canty-Mitchell J, Qi RA, Austin J, Swigonski N. Race, urban community stressors, and behavioral and emotional problems of children with special health care needs. Psychiatr Serv. 2005;56(1):63–69. doi: 10.1176/appi.ps.56.1.63. [DOI] [PubMed] [Google Scholar]
- 25.Taylor TR, Kamarck TW, Shiffman S. Validation of the Detroit Area Study Discrimination Scale in a community sample of older African American adults: the Pittsburgh healthy heart project. Int J Behav Med. 2004;11(2):88–94. doi: 10.1207/s15327558ijbm1102_4. [DOI] [PubMed] [Google Scholar]
- 26.Chen G, Gully SM, Eden D. Validation of a new general self-efficacy scale. Organizational Res Methods. 2001;4(1):62–83. [Google Scholar]
- 27.Cohen S, Hoberman HM. Positive events and social supports as buffers of life change stress. J Appl Soc Psychol. 1983;13(2):99–125. [Google Scholar]
- 28.Hughes ME, Waite LJ, Hawkley LC, Cacioppo JT. A short scale for measuring loneliness in large surveys: results from two population-based studies. Res Aging. 2004;26(6):655–672. doi: 10.1177/0164027504268574. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Lubben J, Blozik E, Gillmann G et al. Performance of an abbreviated version of the Lubben Social Network Scale among three European community-dwelling older adult populations. Gerontologist. 2006;46(4):503–513. doi: 10.1093/geront/46.4.503. [DOI] [PubMed] [Google Scholar]
- 30.Scheier MF, Carver CS, Bridges MW. Distinguishing optimism from neuroticism (and trait anxiety, self-mastery, and self-esteem): a reevaluation of the Life Orientation Test. J Pers Soc Psychol. 1994;67(6):1063–1078. doi: 10.1037//0022-3514.67.6.1063. [DOI] [PubMed] [Google Scholar]
- 31.Velicer WF, Diclemente CC, Rossi JS, Prochaska JO. Relapse situations and self-efficacy: an integrative model. Addict Behav. 1990;15(3):271–283. doi: 10.1016/0306-4603(90)90070-e. [DOI] [PubMed] [Google Scholar]
- 32.Zhou X, Nonnemaker J, Sherrill B, Gilsenan AW, Coste F, West R. Attempts to quit smoking and relapse: factors associated with success or failure from the ATTEMPT cohort study. Addict Behav. 2009;34(4):365–373. doi: 10.1016/j.addbeh.2008.11.013. [DOI] [PubMed] [Google Scholar]
- 33.Shiffman S, Paty JA, Gnys M, Kassel JA, Hickcox M. First lapses to smoking: Within-subjects analysis of real-time reports. J Consult Clin Psychol. 1996;64(2):366–379. doi: 10.1037//0022-006x.64.2.366. [DOI] [PubMed] [Google Scholar]
- 34.Porter J, Houston L, Anderson RH, Maryman K. Addressing tobacco use in homeless populations: recommendations of an expert panel. Health Promot Pract. 2011;12(6 suppl 2):144S–151S. doi: 10.1177/1524839911414412. [DOI] [PubMed] [Google Scholar]