- Email: [email protected]
Smoking Status and Quality of Life
Smoking Status and Quality of Life A Longitudinal Study Among Adults with Disabilities Monika Mitra, PhD, Mei-Chun Chung, MPH, Nancy Wilber, EdD, Deborah Klein Walker, EdD Background: Current research suggests that people with disabilities are more likely to use tobacco, less likely to quit, and less likely to be screened for tobacco use. However, little is known about the impact of changes in smoking status on the health-related quality of life (HRQL) of people with disabilities. Objective:
The primary objective of this paper is to examine the association between changes in HRQL and smoking status over time among people with disabilities.
Methods:
The study data were derived from the Massachusetts Survey of Secondary Conditions, a longitudinal survey of adults with disabilities; Phase I was conducted in 1996 –1998, Phase II in 1998 –1999, and Phase III in 1999 –2000. The main outcome measure was HRQL as measured by the Medical Outcomes Study Short Form-36 (SF-36). Analysis was primarily done in 2003.
Results:
Current smokers and those who began smoking during follow-up had significantly poorer HRQL compared with nonsmokers with disabilities. Longitudinal analysis suggests that controlling for age, gender, race/ethnicity, education, and activities of daily living, changes in HRQL scores over time were associated with changes in smoking status. Compared to smokers, those who quit smoking during follow-up experienced a significant improvement in mean SF-36 scores over time for the dimensions of mental health, energy and vitality, and general health.
Conclusions: Findings from this study highlight a strong need to inform public health programs, people with disabilities and healthcare providers about the association between tobacco cessation and improved health-related quality of life among people with disabilities. (Am J Prev Med 2004;27(3):258 –260) © 2004 American Journal of Preventive Medicine
Introduction
T
he adverse effects of smoking are well established.1 Numerous studies have examined the association between tobacco use and the development of specific diseases, disabilities,2 morbidity,3,4 and poor health-related quality of life (HRQL)5,6 in the general population. Research indicates that people with disabilities are more likely to smoke,7–10 less likely to quit,7 and less likely to be screened for tobacco use than their nondisabled counterparts.11 Yet few studies focus on this population. An earlier study examining the relationship between smoking status and HRQL among a sample of Medicare managed care enrollees found that people with disabilities aged ⬍65 years who smoked reported worse physical and mental functional status than those who never smoked.12 The current study examined (1) the cross-sectional association be-
From the Massachusetts Department of Public Health (Mitra, Wilber, Klein Walker), and Tufts-New England Medical Center (Chung), Boston, Massachusetts Address correspondence and reprint requests to: Monika Mitra, PhD, Massachusetts Department of Public Health, Bureau of Family and Community Health, 250 Washington St, 5th Floor, Boston MA 02108. E-mail: [email protected].
258
Am J Prev Med 2004;27(3) .
tween smoking status and HRQL, and (2) the longitudinal association between changes in smoking status and HRQL among a sample of people with disabilities.
Methods Study data were derived from Phases I and III of the Massachusetts Survey of Secondary Conditions (MSSC), a threephased longitudinal survey of independently living adults with major disabilities in Massachusetts. Phase I was conducted between 1996 and 1998, Phase II in 1998 –1999, and Phase III in 1999 –2000. Analysis was primarily done in 2003. Survey participants were recruited from six independent living centers (ILCs) and two health maintenance organizations (HMOs) in Massachusetts. Although the samples were not population based or random, the organizations were asked to select respondents systematically; for example, every third name from the alphabetical membership lists. Of the 932 eligible respondents contacted, 656 (70%) completed the baseline survey. Between Phases I and II, 30.8% (202/656) of baseline respondents dropped out of the survey, and between Phases II and III 21.8% (99/454) dropped out, leaving 355 respondents for Phase III. A detailed description of the methodology and sample selection can be found in earlier papers.13–15
0749-3797/04/$–see front matter doi:10.1016/j.amepre.2004.06.002
Table 1. Changes in smoking status and crude mean SF-36 scores, Massachusetts Survey of Secondary Conditions Phase III data
Dimension
Nonsmokers (nⴝ232) Mean (SD)
Smokers (nⴝ82) Mean (SD)
Quitters (nⴝ28) Mean (SD)
Starters (nⴝ11) Mean (SD)
Physical functioning Role limitation, physical Role limitation, emotional Mental health Energy and vitality Bodily pain General health
27.7 (29.9) 34.7 (36.3) 65.2 (41.0) 67.3 (20.1) 49.1 (22.8) 54.2 (29.2) 53.3 (24.9)
29.9 (28.2) 29.3 (33.5)a 51.6 (41.3)* 57.9 (24.6)* 39.3 (22.5)* 42.5 (28.3)* 39.5 (24.0)*
29.1 (31.3) 42.0 (36.7) 65.5 (42.0) 65.3 (22.8) 45.2 (26.1) 56.2 (27.9) 51.1 (22.7)
32.1 (34.1) 9.1 (20.2)* 30.3 (37.9)* 52.4 (26.9)* 30.0 (26.0)* 30.1 (30.2)* 33.4 (29.8)*
a
Mean score clinically significantly lower than nonsmokers. *Statistically significantly lower (pⱕ0.05) than nonsmokers (bolded). SD, standard deviation; SF-36, Medical Outcomes Study Short Form-36.
Measures Based on their smoking status, respondents were grouped as nonsmokers, current smokers, quitters, or starters. Nonsmokers included those who reported not having smoked in the past month in Phases I and III of the study; current smokers were respondents who reported smoking in the past month in both phases; quitters were those who reported being a current smoker in Phase I but not in Phase III, and starters were those who reported being a current smoker in Phase III but not in Phase I. Health related quality of life was measured using the Medical Outcomes Study SF-36, a validated, standard measure of health status in the general population.16 During administration of Phase I of the survey, people with mobility impairments found certain items of the SF-36 offensive.17,18 Therefore, the study used an “enabled” SF-36, substituting “go” for “walk” and “climb” in three of the ten questions comprising the physical functioning domain. One of the two items that comprise the social functioning (SF) domain was not included in the MSSC. As a result, the SF domain was dropped from the analyses. Other missing data were imputed by averaging the available data for the particular dimension, as suggested by the SF-36 manual.16
Analysis First, crude Phase III means for quitters, current smokers, and starters were each compared to means for nonsmokers for the
seven SF-36 dimensions. Next, we estimated multiple mixedlinear regressions to (1) examine the longitudinal change in HRQL for the four groups, and (2) compare the longitudinal change in HRQL between quitters and smokers. The dependent variable in the model was the SF-36 dimension score. Separate models were fit for each of the seven SF-36 dimensions. A separate dichotomous variable, “time,” was included to indicate whether the SF-36 score was measured at Phase I or at Phase III. In order to assess whether changes in HRQL differed by group, interactions were created between time and smoking status. The interaction term between quitters and time was used to assess whether the change in HRQL for quitters differed from the change among smokers (reference group). Fixed covariates in the model included gender, race/ethnicity, years of education, age at baseline interview, and number of domains in which respondents were dependent in activities of daily living (ADLs).
Results Among Phase III respondents, 23.2% (n ⫽82) were current smokers; 65.5% (n ⫽232) were nonsmokers; 7.9% (n ⫽28) were quitters, and 3.1% (n ⫽11) were starters. Current smokers scored significantly lower than nonsmokers in five of the seven dimensions reported: role limitations due to emotional problems mental health,
Table 2. Changes in SF-36 scores from Phase I to Phase III for smokers, nonsmokers, quitters, and starters, controlling for age, gender, race/ethnicity, and activities of daily livinga
Dimension
Nonsmokers (nⴝ232) Mean (SD)
Smokers (nⴝ82) Mean (SD)
Quitters (nⴝ28) Mean (SD)
Starters (nⴝ11) Mean (SD)
Physical functioning Role limitation, physical Role limitation, emotional Mental health Energy and vitality Bodily pain General health
⫺1.2 (⫺4.4, 2.1) 0.2 (⫺4.7, 5.0) ⫺0.4 (⫺5.9, 5.1) ⫺0.3 (⫺2.8, 2.3) ⫺0.4 (⫺2.8, 2.1) 0.8 (⫺2.4, 4.0) 0.3 (⫺2.4, 2.9)
⫺2.5 (⫺8.1, 3.0) 2.9 (⫺5.2, 11.0) 2.5 (⫺6.7, 11.7) ⫺0.4 (⫺4.6, 3.9) ⫺1.8 (⫺5.9, 2.3) 1.4 (⫺4.0, 6.8) ⫺2.6 (⫺7.1, 1.8)
⫺3.5 (⫺13.0, 5.9) 17.9 (4.1, 31.7)* 18.5 (2.8, 34.1)* 11.1 (3.9, 18.4)** 7.0 (ⴚ0.1, 14.0)1* 6.8 (⫺2.4, 15.9)1 11.1 (3.5, 18.6)**
⫺13.0 (⫺28.7, 2.7)2b ⫺5.0 (⫺28.1, 18.1)2 ⫺16.7 (⫺42.8, 9.5)2 ⫺6.8 (⫺18.9, 5.3)2 ⫺6.0 (⫺17.8, 5.8)2 ⫺2.6 (⫺17.9, 12.7) ⫺2.8 (⫺16.0, 10.4)
a
Separate models run for each SF-36 dimension, with estimates derived from mixed models. 1 or 2 indicates direction of clinically significant change in HRQL score from Phase I to Phase III; double-shaft arrows indicate change statistically significant at alpha⫽0.05 (bolded). *Change in HRQL score is statistically different from change among smokers (reference group⫽smokers) alpha⫽0.05 (bolded). HRQL, health-related quality of life; SD, standard deviation; SF-36, Medical Outcomes Study Short Form-36
b
Am J Prev Med 2004;27(3)
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energy and vitality, bodily pain, and general health (Table 1). Starters scored significantly lower than nonsmokers in the dimensions of role limitations due to physical health, role limitations due to emotional problems, mental health, energy and vitality, bodily pain, and general health. Controlling for demographics and ADLs, quitters experienced a significant improvement in the mean score for four dimensions (role limitations due to emotional problems, role limitations due to physical health, mental health, and general health) over time (Table 2). The improvement in mean score during follow-up for the bodily pain and energy and vitality dimensions among quitters was clinically and socially relevant (difference of more than five points).16 Among starters, there was a clinically and socially relevant reduction in the dimensions of physical functioning; role limitations due to physical health; role limitations due to emotional problems; mental health; and energy and vitality. In addition, results suggest that—after controlling for demographics and ADLs— quitters were more likely to have an improved HRQL over time compared to smokers in the following domains: mental health, energy and vitality, and general health perception (Table 2).
Discussion The results of this study suggest that, as in the general population, smoking is associated with poorer HRQL. Current smokers and those who began smoking during follow-up were more likely to report poorer HRQL than those who had not smoked during the survey period. Longitudinal changes in smoking status were also associated with changes in HRQL. Compared to smokers, quitters were more likely to have improved HRQL over time. It is important to note the limitations of this study. First, the use of a more “enabled” SF-36 limited the comparability of the study, particularly for the physical functioning domain. Second, the small sample size of the starters raised questions about the reliability of the findings. In addition, the MSSC sample consisted of adults identified by ILCs and HMOs, whose experiences may or may not be representative of people with disabilities in Massachusetts.13 These data were based on self-report and subject to the limitations of self-reported data. The sample attrition between phases may also have biased the results of the study. Finally, ceiling and floor effects were found in the emotional and physical role domains for nonsmokers, current smokers, and quitters, which may have compromised the responsiveness of the data. Results here suggest that people with disabilities, public health agencies, and healthcare providers should be educated about the association between smoking status and quality of life among people with disabilities. Clinicians should inform smokers with disabilities of the detrimental 260
What This Study Adds . . . This study suggests that tobacco use among persons with disabilities is associated with healthrelated quality of life (HRQL). In particular, change in smoking status was associated with a change in HRQL. Respondents who quit smoking over time were also more likely to have better HRQL.
health-related consequences of smoking and refer them to accessible smoking-cessation programs. For public health departments, the inclusion and targeting of people with disabilities in smoking-prevention and -cessation programs is vital to reducing smoking among people with disabilities and promoting a high quality of life. Preventive health services are a priority for people with disabilities, just as in the general population.
References 1. Centers for Disease Control and Prevention. Tobacco use—United States, 1900 –1999. MMWR Morb Mortal Wkly Rep 1999;48:986 –93. 2. Giovino GA, Henningfield JE, Tomar SC, Escobedo LG, Slade J. Epidemiology of tobacco use and dependence. Epidemiol Rev 1995;17:48 – 65. 3. Nusselder WJ, Looman CW, Marang-van de Mheen PJ, van de Mheen H, Mackenbach JP. Smoking and the compression of morbidity. J Epidemiol Community Health 2000;54:566 –74. 4. Ostbye T, Taylor DH, Jung SH. A longitudinal study of the effects of tobacco smoking and other modifiable risk factors on ill health in middle-aged and old Americans: results from the Health and Retirement Study and Asset and Health Dynamics among the Oldest Old survey. Prev Med 2002;34:334 – 45. 5. Mulder I, Tijhuis M, Smit HA, Kromhout D. Smoking cessation and quality of life: the effect of amount of smoking and time since quitting. Prev Med 2001;33:653– 60. 6. Wilson D, Parsons J, Wakefield M. The health-related quality-of-life of never smokers, quitters, and light, moderate, and heavy smokers. Prev Med 1999;29:139 – 44. 7. Brawarsky P, Brooks DR, Wilber N, Gertz RE Jr, Walker DK. Tobacco use among adults with disabilities in Massachusetts. Tob Control 2002;11(suppl 2):29 –33. 8. Glassman AH. Cigarette smoking: implications for psychiatric illness. Am J Psychiatry 1993;150:546 –53. 9. Hughes JR, Hatsukami DK, Mitchell JE, Dahlgren LA. Prevalence of smoking among psychiatric outpatients. Am J Psychiatry 1986;143:993–7. 10. Lasser K, Boyd JW, Woolhandler S, Himmelstein DU, McCormick D, Bor DH. Smoking and mental illness: a population-based prevalence study. JAMA 2000;284:2606 –10. 11. Iezzoni LI, McCarthy EP, Davis RB, Siebens H. Mobility impairments and use of screening and preventive services. Am J Public Health 2000;90:955– 61. 12. Arday DR, Milton MH, Husten CG, et al. Smoking and functional status among medicare managed care enrollees. Am J Prev Med 2003;24:234 – 41. 13. Wilber N, Mitra M, Walker DK, Allen D, Meyers AR, Tupper P. Disability as a public health issue: findings and reflections from the Massachusetts Survey of Secondary Conditions. Milbank Q 2002; 80:393– 421. 14. Meyers AR, Mitra M, Walker DK, Wilber N, Allen D. Predictors of secondary conditions in a sample of independently living adults with high-level spinal cord injury. Top Spinal Cord Inj Rehabil 2000;6:1– 8. 15. Mitra M, Wilber N, Allen D, Walker DK. Prevalence and correlates of depression as a secondary condition among people with disabilities. Am J Orthopsychiatry. 2004. In press. 16. Ware JE, Snow KK, Kosinski M, Gandek B. SF-36 Health survey manual and interpretation guide. Boston: Health Institute, 1993. 17. Andresen EM, Meyers AR. Health-related quality of life outcomes measures. Arch Phys Med Rehabil 2000;81(suppl 2):30 – 45. 18. Meyers AR, Andresen EM. Enabling our instruments: Accommodation, universal design and access to participation in research. Arch Phys Med Rehabil 2000;81(suppl 2):5–9.
American Journal of Preventive Medicine, Volume 27, Number 3
The primary objective of this paper is to examine the association between changes in HRQL and smoking status over time among people with disabilities.
Methods:
The study data were derived from the Massachusetts Survey of Secondary Conditions, a longitudinal survey of adults with disabilities; Phase I was conducted in 1996 –1998, Phase II in 1998 –1999, and Phase III in 1999 –2000. The main outcome measure was HRQL as measured by the Medical Outcomes Study Short Form-36 (SF-36). Analysis was primarily done in 2003.
Results:
Current smokers and those who began smoking during follow-up had significantly poorer HRQL compared with nonsmokers with disabilities. Longitudinal analysis suggests that controlling for age, gender, race/ethnicity, education, and activities of daily living, changes in HRQL scores over time were associated with changes in smoking status. Compared to smokers, those who quit smoking during follow-up experienced a significant improvement in mean SF-36 scores over time for the dimensions of mental health, energy and vitality, and general health.
Conclusions: Findings from this study highlight a strong need to inform public health programs, people with disabilities and healthcare providers about the association between tobacco cessation and improved health-related quality of life among people with disabilities. (Am J Prev Med 2004;27(3):258 –260) © 2004 American Journal of Preventive Medicine
Introduction
T
he adverse effects of smoking are well established.1 Numerous studies have examined the association between tobacco use and the development of specific diseases, disabilities,2 morbidity,3,4 and poor health-related quality of life (HRQL)5,6 in the general population. Research indicates that people with disabilities are more likely to smoke,7–10 less likely to quit,7 and less likely to be screened for tobacco use than their nondisabled counterparts.11 Yet few studies focus on this population. An earlier study examining the relationship between smoking status and HRQL among a sample of Medicare managed care enrollees found that people with disabilities aged ⬍65 years who smoked reported worse physical and mental functional status than those who never smoked.12 The current study examined (1) the cross-sectional association be-
From the Massachusetts Department of Public Health (Mitra, Wilber, Klein Walker), and Tufts-New England Medical Center (Chung), Boston, Massachusetts Address correspondence and reprint requests to: Monika Mitra, PhD, Massachusetts Department of Public Health, Bureau of Family and Community Health, 250 Washington St, 5th Floor, Boston MA 02108. E-mail: [email protected].
258
Am J Prev Med 2004;27(3) .
tween smoking status and HRQL, and (2) the longitudinal association between changes in smoking status and HRQL among a sample of people with disabilities.
Methods Study data were derived from Phases I and III of the Massachusetts Survey of Secondary Conditions (MSSC), a threephased longitudinal survey of independently living adults with major disabilities in Massachusetts. Phase I was conducted between 1996 and 1998, Phase II in 1998 –1999, and Phase III in 1999 –2000. Analysis was primarily done in 2003. Survey participants were recruited from six independent living centers (ILCs) and two health maintenance organizations (HMOs) in Massachusetts. Although the samples were not population based or random, the organizations were asked to select respondents systematically; for example, every third name from the alphabetical membership lists. Of the 932 eligible respondents contacted, 656 (70%) completed the baseline survey. Between Phases I and II, 30.8% (202/656) of baseline respondents dropped out of the survey, and between Phases II and III 21.8% (99/454) dropped out, leaving 355 respondents for Phase III. A detailed description of the methodology and sample selection can be found in earlier papers.13–15
0749-3797/04/$–see front matter doi:10.1016/j.amepre.2004.06.002
Table 1. Changes in smoking status and crude mean SF-36 scores, Massachusetts Survey of Secondary Conditions Phase III data
Dimension
Nonsmokers (nⴝ232) Mean (SD)
Smokers (nⴝ82) Mean (SD)
Quitters (nⴝ28) Mean (SD)
Starters (nⴝ11) Mean (SD)
Physical functioning Role limitation, physical Role limitation, emotional Mental health Energy and vitality Bodily pain General health
27.7 (29.9) 34.7 (36.3) 65.2 (41.0) 67.3 (20.1) 49.1 (22.8) 54.2 (29.2) 53.3 (24.9)
29.9 (28.2) 29.3 (33.5)a 51.6 (41.3)* 57.9 (24.6)* 39.3 (22.5)* 42.5 (28.3)* 39.5 (24.0)*
29.1 (31.3) 42.0 (36.7) 65.5 (42.0) 65.3 (22.8) 45.2 (26.1) 56.2 (27.9) 51.1 (22.7)
32.1 (34.1) 9.1 (20.2)* 30.3 (37.9)* 52.4 (26.9)* 30.0 (26.0)* 30.1 (30.2)* 33.4 (29.8)*
a
Mean score clinically significantly lower than nonsmokers. *Statistically significantly lower (pⱕ0.05) than nonsmokers (bolded). SD, standard deviation; SF-36, Medical Outcomes Study Short Form-36.
Measures Based on their smoking status, respondents were grouped as nonsmokers, current smokers, quitters, or starters. Nonsmokers included those who reported not having smoked in the past month in Phases I and III of the study; current smokers were respondents who reported smoking in the past month in both phases; quitters were those who reported being a current smoker in Phase I but not in Phase III, and starters were those who reported being a current smoker in Phase III but not in Phase I. Health related quality of life was measured using the Medical Outcomes Study SF-36, a validated, standard measure of health status in the general population.16 During administration of Phase I of the survey, people with mobility impairments found certain items of the SF-36 offensive.17,18 Therefore, the study used an “enabled” SF-36, substituting “go” for “walk” and “climb” in three of the ten questions comprising the physical functioning domain. One of the two items that comprise the social functioning (SF) domain was not included in the MSSC. As a result, the SF domain was dropped from the analyses. Other missing data were imputed by averaging the available data for the particular dimension, as suggested by the SF-36 manual.16
Analysis First, crude Phase III means for quitters, current smokers, and starters were each compared to means for nonsmokers for the
seven SF-36 dimensions. Next, we estimated multiple mixedlinear regressions to (1) examine the longitudinal change in HRQL for the four groups, and (2) compare the longitudinal change in HRQL between quitters and smokers. The dependent variable in the model was the SF-36 dimension score. Separate models were fit for each of the seven SF-36 dimensions. A separate dichotomous variable, “time,” was included to indicate whether the SF-36 score was measured at Phase I or at Phase III. In order to assess whether changes in HRQL differed by group, interactions were created between time and smoking status. The interaction term between quitters and time was used to assess whether the change in HRQL for quitters differed from the change among smokers (reference group). Fixed covariates in the model included gender, race/ethnicity, years of education, age at baseline interview, and number of domains in which respondents were dependent in activities of daily living (ADLs).
Results Among Phase III respondents, 23.2% (n ⫽82) were current smokers; 65.5% (n ⫽232) were nonsmokers; 7.9% (n ⫽28) were quitters, and 3.1% (n ⫽11) were starters. Current smokers scored significantly lower than nonsmokers in five of the seven dimensions reported: role limitations due to emotional problems mental health,
Table 2. Changes in SF-36 scores from Phase I to Phase III for smokers, nonsmokers, quitters, and starters, controlling for age, gender, race/ethnicity, and activities of daily livinga
Dimension
Nonsmokers (nⴝ232) Mean (SD)
Smokers (nⴝ82) Mean (SD)
Quitters (nⴝ28) Mean (SD)
Starters (nⴝ11) Mean (SD)
Physical functioning Role limitation, physical Role limitation, emotional Mental health Energy and vitality Bodily pain General health
⫺1.2 (⫺4.4, 2.1) 0.2 (⫺4.7, 5.0) ⫺0.4 (⫺5.9, 5.1) ⫺0.3 (⫺2.8, 2.3) ⫺0.4 (⫺2.8, 2.1) 0.8 (⫺2.4, 4.0) 0.3 (⫺2.4, 2.9)
⫺2.5 (⫺8.1, 3.0) 2.9 (⫺5.2, 11.0) 2.5 (⫺6.7, 11.7) ⫺0.4 (⫺4.6, 3.9) ⫺1.8 (⫺5.9, 2.3) 1.4 (⫺4.0, 6.8) ⫺2.6 (⫺7.1, 1.8)
⫺3.5 (⫺13.0, 5.9) 17.9 (4.1, 31.7)* 18.5 (2.8, 34.1)* 11.1 (3.9, 18.4)** 7.0 (ⴚ0.1, 14.0)1* 6.8 (⫺2.4, 15.9)1 11.1 (3.5, 18.6)**
⫺13.0 (⫺28.7, 2.7)2b ⫺5.0 (⫺28.1, 18.1)2 ⫺16.7 (⫺42.8, 9.5)2 ⫺6.8 (⫺18.9, 5.3)2 ⫺6.0 (⫺17.8, 5.8)2 ⫺2.6 (⫺17.9, 12.7) ⫺2.8 (⫺16.0, 10.4)
a
Separate models run for each SF-36 dimension, with estimates derived from mixed models. 1 or 2 indicates direction of clinically significant change in HRQL score from Phase I to Phase III; double-shaft arrows indicate change statistically significant at alpha⫽0.05 (bolded). *Change in HRQL score is statistically different from change among smokers (reference group⫽smokers) alpha⫽0.05 (bolded). HRQL, health-related quality of life; SD, standard deviation; SF-36, Medical Outcomes Study Short Form-36
b
Am J Prev Med 2004;27(3)
259
energy and vitality, bodily pain, and general health (Table 1). Starters scored significantly lower than nonsmokers in the dimensions of role limitations due to physical health, role limitations due to emotional problems, mental health, energy and vitality, bodily pain, and general health. Controlling for demographics and ADLs, quitters experienced a significant improvement in the mean score for four dimensions (role limitations due to emotional problems, role limitations due to physical health, mental health, and general health) over time (Table 2). The improvement in mean score during follow-up for the bodily pain and energy and vitality dimensions among quitters was clinically and socially relevant (difference of more than five points).16 Among starters, there was a clinically and socially relevant reduction in the dimensions of physical functioning; role limitations due to physical health; role limitations due to emotional problems; mental health; and energy and vitality. In addition, results suggest that—after controlling for demographics and ADLs— quitters were more likely to have an improved HRQL over time compared to smokers in the following domains: mental health, energy and vitality, and general health perception (Table 2).
Discussion The results of this study suggest that, as in the general population, smoking is associated with poorer HRQL. Current smokers and those who began smoking during follow-up were more likely to report poorer HRQL than those who had not smoked during the survey period. Longitudinal changes in smoking status were also associated with changes in HRQL. Compared to smokers, quitters were more likely to have improved HRQL over time. It is important to note the limitations of this study. First, the use of a more “enabled” SF-36 limited the comparability of the study, particularly for the physical functioning domain. Second, the small sample size of the starters raised questions about the reliability of the findings. In addition, the MSSC sample consisted of adults identified by ILCs and HMOs, whose experiences may or may not be representative of people with disabilities in Massachusetts.13 These data were based on self-report and subject to the limitations of self-reported data. The sample attrition between phases may also have biased the results of the study. Finally, ceiling and floor effects were found in the emotional and physical role domains for nonsmokers, current smokers, and quitters, which may have compromised the responsiveness of the data. Results here suggest that people with disabilities, public health agencies, and healthcare providers should be educated about the association between smoking status and quality of life among people with disabilities. Clinicians should inform smokers with disabilities of the detrimental 260
What This Study Adds . . . This study suggests that tobacco use among persons with disabilities is associated with healthrelated quality of life (HRQL). In particular, change in smoking status was associated with a change in HRQL. Respondents who quit smoking over time were also more likely to have better HRQL.
health-related consequences of smoking and refer them to accessible smoking-cessation programs. For public health departments, the inclusion and targeting of people with disabilities in smoking-prevention and -cessation programs is vital to reducing smoking among people with disabilities and promoting a high quality of life. Preventive health services are a priority for people with disabilities, just as in the general population.
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American Journal of Preventive Medicine, Volume 27, Number 3