Tobacco Use and Recovery of Gait and Balance Function in Older Adults

Article Outline

• Abstract
• Methods
  • Participants
  • Primary Outcome Measures
    • Berg Balance Scale
    • Dynamic Gait Index
    • Health-related quality of life (SF-36 PF)
  • Impairment Measure
    • Strength
  • Analysis
• Results
  • Preintervention Comparisons
  • Postintervention
• Discussion
  • Study Limitations
• Conclusions
• References
• Copyright

Abstract 

Bishop MD, Robinson ME, Light KE. Tobacco use and recovery of gait and balance function in older adults.

Objective

To examine the influence of tobacco use status on outcome after an exercise program designed to improve gait and balance.

Design

Review of clinical database.

Setting

Standardized assessment clinic in a tertiary care setting.

Participants

Patients (N=136, 77.2±5.8y, 3 women) who were attending a Gait and Balance Disorders clinic.

Interventions

Individualized home exercise programs based on findings of an extensive gait and mobility examination. Patients were evaluated every 4 weeks for 12 weeks.

Main Outcome Measures

Berg Balance Scale (BBS), Dynamic Gait Index (DGI), and Medical Outcomes Study 36-item Short Form Health Survey Physical Functioning subscale (SF-36 PF). Differences were assessed preintervention, and separate hierarchical linear regression models were used to examine the unique contribution of tobacco use to changes in each of primary outcome measures.

Results

Current tobacco users had higher frequencies of chronic obstructive pulmonary disease (P=.009) and depression (0.037). No differences were noted on preintervention measures of the primary outcomes based on tobacco use. Tobacco use explained a significant amount of additional variance in the postintervention score on each of the primary outcomes (BBS, 25.4%; DGI, 8.7%; SF-36 PF, 30.3%) after controlling for preintervention score, depression, and limb strength. Inspection of the adjusted means indicated that the group that had never used tobacco showed greater improvement than the current users for all variables after adjusting for factors used in the regression models.

Conclusions

Older adults who never used tobacco showed greater improvement than the current users for all variables after adjusting for factors used in the regression models. Current tobacco users perceived themselves to be more limited by their health after participation in the rehabilitation exercise program.

Key Words: Aging, Falling, Gait, Rehabilitation

List of Abbreviations: BBS, Berg Balance Scale, COPD, chronic obstructive pulmonary disease, DGI, Dynamic Gait Index, SF-36, Medical Outcomes Study 36-item Short Form Health Survey, SF-36 PF, Medical Outcomes Study 36-item Short Form Health Survey Physical Functioning subscale

ONE IN 3 ADULTS over age 65 in the United States will fall at least once a year.¹, ², ³ This proportion and the severity of fall-related complications increases with age.², ³ The risk of falling that accompanies advancing age may be ameliorated through rehabilitation programs. Such exercise programs have been identified as beneficial in falls prevention.⁴, ⁵ The majority of these rehabilitation exercise programs involve a combination of aerobic exercise, strengthening, and targeted balance activities to improve these impairments and skills in older adults exhibiting functional decline.⁶, ⁷, ⁸ A recent systematic review of 20 studies of exercise training in older adults concluded that regular exercise training can improve functional performance including gait and balance.⁹ Additionally, a recent meta-analysis¹⁰ of home-based programs of muscle, strength, and endurance training for high-risk participants reduced falls risk by 35%.

Observable functional decline of elders is associated with tobacco use status.¹¹, ¹², ¹³, ¹⁴ The association between tobacco use and loss of function strengthens if the 5% of elders who declined in 5 or more functional activities are considered.¹⁴ Elders may be the persons most affected by the tobacco experience because of increased duration of exposure to tobacco and the resultant tobacco-related comorbidities. Many are suffering from multiple chronic illnesses caused by tobacco use or related to the tobacco culture that surrounded them during their youth.

Tobacco use is recognized as a major contributing factor to musculoskeletal pain conditions because of the effects of tobacco on microvasculature, healing, and tissue nutrition.¹⁵ Tobacco usage is also significantly related to depressive and other psychiatric disorders¹⁶ and associated with poor adherence to medication protocols¹⁷ and dropout of patients from medical follow-up in health-screening programs.¹⁸

Based on these findings, we speculated that older adults participating in a rehabilitation exercise program who were currently using tobacco might not experience the same benefits as those nontobacco users. First, we hypothesized that adults who did not use tobacco would perform better at preintervention testing on measures of activity and participation limitation than current users of tobacco. We used tests of mobility and balance to examine activity limitations and a health-related quality of life measure to examine differences in participation.

Our second purpose was to determine whether adults who did not use tobacco would show greater improvements after 12 weeks of exercise training than those who were current users. Our primary outcomes were the same activity and participation measures. Our hypothesis was that tobacco use would contribute unique amounts of variance in outcome after controlling for any coexisting conditions. We also hypothesized that tobacco use would negatively influence outcome.

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Methods 

A clinical database of patients who attended a Gait and Balance Disorders clinic between 1997 and 2002 was searched for patients who had a history of falling at least twice in the 12 months previous to referral, the ability to walk 20 feet with or without an assistive device, and a score of 20 or higher on the Mini-Mental State Examination. The University Institutional Review Board and the Veteran's Affairs Subcommittee for Clinical Investigation approved a waiver of informed consent for this project. Patient records were not included for review if the primary cause of falling was determined to be related to polypharmacy, orthostatic hypertension, dementia, or vestibulopathy because these conditions were not treated by using the rehabilitation exercise program.

Participants 

All patients participated in a multidisciplinary evaluation that included a geriatrician, physical therapist, and pharmacist. Patients were examined by a physical therapist using a standardized battery of tests and measures that included the primary outcomes described later. In addition, impairment measures of strength and mobility (timed gait and stair climbing) were evaluated and assisted in developing the home exercise intervention.

Patients received instruction in a home exercise program tailored to the individual. Home exercises were developed based on the examination findings by using a decision tree model that is described in detail elsewhere.¹⁹ If the patient had problems with stabilization and significant weakness in the hip abductors, quadriceps, plantarflexors, or dorsiflexors, specific strengthening exercises were developed for those muscle groups based on the evaluation. If the patient was unable to walk farther than 500ft in 2 minutes, he/she was placed on both an endurance training program for walking and an interval training program focused on the goal of achieving the ability to walk for at least 20 minutes continuously without stopping. The programs were also progressed by requiring walking on a variety of uneven surfaces, inclines, and stairs. The exact exercises taught to the patient varied; however, each home exercise program was progressed such that the amount of time required to perform the exercises was approximately the same for all patients. Patients returned to the clinic for monthly follow-up evaluations. The final evaluation occurred after 12 weeks. The same physical therapist performed all evaluations.

Primary Outcome Measures 

The BBS was developed to assess balance in elderly patients.²⁰ The scale has 14 items that are rated by using a 5-point ordinal scale, ranging from 0 to 4, on which “0” indicates the lowest level of function and “4” the highest level of function. Total scores range from 0 to 56 points. The higher the score, the more independent the patient is in tasks of balance. The BBS has been found to be internally consistent and to have a high degree of inter- and intrarater reliability.²⁰

This is an 8-item index created by rating the subject's performance on walking tasks. The total score ranges from 0 to 24, with higher scores indicating greater independence in dynamic gait-related activities.²¹ Additionally, Whitney et al²¹ indicate that subjects are 2.58 times more likely to have reported a fall in the previous 6 months if they score less than 19 out of 24 points on this instrument.

Question 3 of the SF-36 represents the impact of a person's health on his/her ability to perform physical tasks. The question includes 10 items (vigorous activities; moderate activities; lifting or carrying groceries; climbing 1 flight of stairs; bending, kneeling, or stooping; walking several blocks; walking 1 block; and bathing or dressing),²², ²³, ²⁴ and the person rates how limited they are in each activity because of their health. SF-36 PF has good responsiveness and item separation in older adults.²⁵

Impairment Measure 

Isometric testing was performed by using a Microfet 2 handheld dynamometer.^a Measurements were taken of the strength of hip abductor muscle, ankle plantar flexor, knee extensor, and ankle dorsiflexor muscles. These muscles were chosen given the association of these muscles to functional tasks such as gait termination and turning.²⁶, ²⁷ Three repetitions of each test were performed, and the average of the peak isometric test was recorded. Patient positioning and dynamometer placement are summarized in table 1. The reliability of handheld dynamometry has been previously reported as greater than 0.9 at the hip²⁸ and for knee extension.²⁹

Table 1. Patient and Dynamometer Positions for Strength Assessment

Analysis 

Demographic characteristics of patients currently using tobacco and those who had never used tobacco products were compared by using t tests or chi-square analysis. Comorbid conditions reported in the medical record were coded by using the list in table 2. Groups were compared by using chi-square analysis on the frequency of coexisting conditions present per patient and the numbers of patients with each condition. The number of limb strength variables was reduced by performing a factor analysis by using a principal component analysis with varimax rotation. Eigen values greater than 1 were considered the threshold to retain the factor for further analyses. For any variables that differed between groups based on tobacco use status, additional comparisons were made to test association with the following primary outcome measures: BBS, DGI, and SF-36 PF.

Table 2. Conditions Present Resulting in Classification of the Category of Disorder

Next, we built separate hierarchical linear regression models for each of the primary outcome measures. We chose this method to examine the contributions that predictor variables made to the total variance in the model. Of specific interest in this current study was the amount of unique variance that could be explained by tobacco use behavior. Consequently, the first block of each analysis included the preintervention score of the outcome measure of interest and any of the variables that (1) differed between groups and (2) were correlated to the outcomes of interest. The grouping variable for tobacco use was added as the second block.

Missing data were modeled by using multiple imputation. Imputed values were generated based on the collected data. For each imputed dataset, missing data points were filled with values drawn randomly from the overall fitted multivariate distribution. Five iterative analyses were performed as though the data were complete, and the results of these analyses were then pooled to provide point and variance estimates for the effects of interest. Type 1 error was set at 5% throughout and control for multiple comparisons on dependent response variables.

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Results 

Preintervention Comparisons 

Of the 256 patients who attended the clinic, 37 were currently using tobacco products, and 79 indicated that they had never used tobacco products, resulting in 136 patients being included in the analysis (aged 77.2±5.8y, 3 women). The low number of female patients was expected because the clinic is situated within the Veteran's Affairs Medical System.

Groups, based on tobacco use status, were not statistically different based on age or sex. When directly comparing the frequency of comorbid condition categories per patient, there was no statistical difference between groups. Current users of tobacco had a condition from 2.9 different disease categories, and those who had never used tobacco had a condition from 2.8 (χ²=1.96, P=.780). However, when the frequency of specific conditions was considered, more subjects currently using tobacco products had pulmonary conditions, specifically COPD, and more patients had depression. These data are summarized in table 3.

Table 3. Proportions of Subjects Who Have Diagnoses With the Categories of Conditions

	Never Smoked	Current Smoker	P
Age (mean years ± SD)	77.3±5.1	77.1±6.3	0.909
Sex (women), n	2	1	1.000
Condition category (%)
Vestibular	21.2	17.9	0.799
Cognitive	12.1	7.7	0.734
Pulmonary	16.7	45.9	0.001
Cardiovascular	57.6	69.2	0.300
Neurologic	39.4	46.2	0.543
Musculoskeletal	53.0	51.3	1.000
Renal	0.0	5.1	0.063
Specific conditions (%)
Neuropathy	13.6	12.8	1.000
Endocrine	24.2	35.9	0.264
Cardiovascular surgery	16.7	42.0	0.092
Cerebrovascular accident	18.0	30.8	0.093
Depression	24.1	50.0	0.037

The 8 limb strength variables were reduced to 2 factors that accounted for 65% of the cumulative variance in strength measures. In factor 1, quadriceps and ankle plantar flexors had weights greater than 0.55, and ankle dorsiflexors had weights of less than 0.1. In factor 2, hip abductors and ankle dorsiflexors were weighted greater than 0.57 and ankle plantarflexors less than 0.1. These strength factors were significantly correlated with preintervention scores on BBS and DGI.

No statistical differences were noted in the tests of balance and mobility or in the self-reports of function used at the clinic (table 4). Comparisons were made between patients with and without depression by using the primary outcome measures as the dependent variables. Patients with depression scored lower than patients without depression on BBS (mean difference, 4.99; P=.032), DGI (mean difference, 3.95; P=.003), and SF-36 PF scores (mean difference, 4.86; P<.001). These results indicated that the presence of depression might have an effect on the outcome variables. Consequently, depression was included in those regression analyses. This process was repeated for subjects with and without COPD; however, no statistical differences were noted in the outcome measures based on whether a subject had COPD.

Table 4. Comparison of Measures at the First Examination

Measure	Never Smoked	Current Smoker	P	95% CI of Mean Difference
BBS	41.2±9.2	39.7±8.4	.403	−4.9to2.02
DGI	13.5±5.0	12.4±4.9	.347	−3.23to1.16
SF-36 PF	17.8±6.2	15.6±5.9	.134	−5.15to0.71

NOTE. Data are presented as mean ± SD.

Abbreviation: CI, confidence interval.

Postintervention 

For BBS and DGI, after controlling for the preintervention score, depression, and limb strength, tobacco use status explained a significant amount of additional variance (25.4% and 8.7%, respectively). The total models explained 29.2% for BBS and 18.1% for DGI. No other variables contributed significantly to the model for either outcome measure. The model for SF-36 PF postintervention scores included preintervention scores and depression as the first block and tobacco use as the second block. Tobacco use explained 30.3% of the total 32.5% variance. The total models are presented in table 5.

Table 5. Regression Models for Each of the Primary Outcome Variables

Outcome	Standardized Beta	P	R2 Change
BBS
Block 1
Preintervention score	0.196	.074	.082
Depression	−1.255	.213
Strength factor 1	0.018	.949
Strength factor 2	0.007	.653
Block 2
Tobacco use	−0.519	<.001	.254
DGI
Block 1
Preintervention score	−0.103	.460	.089
Depression	−0.197	.119
Strength factor 1	−0.048	.702
Strength factor 2	0.240	.092
Block 2
Tobacco use	−0.300	.012	.087
SF-36 PF
Block 1
Preintervention score	0.147	.193	.057
Depression	−0.202	.077
Block 2
Tobacco use	−0.555	<.001	.303

Inspection of the adjusted means indicated that the group that had never used tobacco showed a greater improvement than the current users for all variables after adjusting for factors used in the regression models (fig 1A, B). Additionally, current users of tobacco reported that they were more limited because of their health condition after the intervention (fig 1C).

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• Fig 1. 

  Comparison of the pre- and postintervention adjusted means (±SE for each of the primary variables split by group [based on tobacco use status]). Those patients who were using tobacco had less improvement in balance and mobility (A and B). C shows that current tobacco users actually perceived their health condition to limit their physical function to greater extent after the intervention, despite modest improvements in balance.

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Discussion 

The first finding of this study was that patients of this tertiary care facility did not differ on tests of mobility and balance and perceived limits to physical function at the preintervention evaluations based on tobacco use. Our second finding was that patients who never used tobacco improved to a greater extent than current users of tobacco on all the measures used in this study. That remained true after controlling for depression and limb strength.

Originally, we had speculated that adults currently using tobacco products would have more coexisting medical conditions, and this might influence a patient's performance on measures of balance and mobility or how he/she perceived his/her health to be affected. However, we found no statistical differences between patients when using the categories we chose for this study. The lack of difference could reflect the tertiary care setting of this clinic (ie, patients seeking care at a tertiary institution may have more comorbid conditions in general, resulting in a ceiling effect in this type of measure). Consequently, our measure may not have been sensitive enough to capture the expected differences when using broad categories based on the type of body system affected by the underlying conditions.

Current tobacco users did have a greater incidence of COPD and depression than nontobacco users. The greater number of patients with a diagnosis of COPD is not unexpected given the strong associations between smoking and COPD. COPD is influenced by age, with the prevalence of COPD highest in men and women 65 years of age and older (16.7% among men and 12.6% among women).³⁰ Our dataset was predominantly men and matched this reported proportion very closely. The Gait and Balance Clinic is located in a Veteran's Affairs Hospital, and the majority of the patients were men. Also, the predominant risk factor for COPD is cigarette smoking.³⁰ Data from the Plan and Operation of the Third National Health and Nutrition Examination Survey³¹ indicate that approximately 60% of current smokers had COPD at the time of that survey, again matching the group of patients assessed in our study. Likewise, our data are consistent regarding depression in older adults who use tobacco.¹⁶ Combined, the similarity of previously reported findings to our own supports the validity of applying our results to older adults outside this very specific group of patients with balance and mobility disorders.

The second hypothesis of this study was that nonusers of tobacco would show more improvement during an intervention plan, and, in fact, nonusers showed improvements in all the measures used in this study. Being a current tobacco user had a negative association with all the outcomes chosen for this study. This association was observed after controlling for other factors such as limb strength and depression. Patients who never used tobacco made a mean change on the BBS of 8.7 points, which exceeds the minimally detectable change reported for patients with parkinsonism (5 points)³² and adults living in residential facilities (8 points).³³ Also, the mean score on the DGI for patients who had never used tobacco improved to be greater than 19 points. Previous work²¹ has indicated that subjects are 2.58 times more likely to have reported a fall in the previous 6 months if they score less than 19 on the DGI. These data suggest that patients who have never used tobacco can make meaningful and measurable change in these measures.

Interestingly, the SF-36 PF scores decreased after intervention for those who were current users. The implication is that those patients perceived themselves to be more limited by their health despite participating in a program that (in general) improved performance in the other group of patients. Intrinsic factors associated with tobacco use that we did not measure may account for this lack of improvement. Factors such as pain or anxiety could mediate this relationship as could other behaviors in the groups of patients related to alcohol or drug use. Perhaps older adults who were currently using tobacco did not think they could make changes or improve. This may also contribute to continued tobacco use despite tobacco-cessation advice in patients with COPD.

Study Limitations 

Interpretation of our results should consider the limitations of the study design. Underlying assumptions are that the patient records were accurately recorded and entered, but we are unable to verify the accuracy of the tobacco-use screen used in the geriatric medicine clinical intake. Additionally, we assessed adherence to the exercise program generally by asking patients to return their home exercise sheets and show their exercise program when they returned for follow-up. We were unable to control for the level or amount of adherence of each patient. Tobacco users have been shown to be less adherent to medical advice or guidance,¹⁷, ¹⁸ so this may have influenced changes in performance on the gait and balance outcome measures.

Other factors are that patients were attending a tertiary health care setting and were overwhelmingly men. Nonetheless, the fact that older adults who were current tobacco users at the time of their participation in a gait and balance intervention did not perceive themselves to have made improvements despite changes in balance and mobility remains meaningful. We suggest that those patients who are currently using tobacco may benefit from additional interventions to improve efficacy and perceived restriction to activities of daily living.

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Conclusions 

One goal of this study was to validate empiric observations that patients who were using tobacco did not make changes in the program. Our findings provide some preliminary evidence to support this. We suggest that patients currently using tobacco may benefit from targeted behavioral programs designed to increase participation in conjunction with tobacco-cessation programs. Self-management programs based on cognitive-behavioral approaches, for example, allow people with a wide variety of chronic conditions to actively participate in the management of their own condition.³⁴ These types of programs involve group treatment plans and are best led by peers rather than health professionals. Although the evidence suggests that these programs in and of themselves do not affect health-related quality of life, they can improve self-efficacy and increase participation of the patient with a chronic health condition.³⁴ Interventions for depression are effective for older adults,³⁵ and a recent trial³⁶ indicated that health-related quality of life in patients who had COPD and depression remained improved over 12 months after only 8 group treatment sessions that included education about COPD and tobacco-cessation or cognitive-behavioral interventions to decrease anxiety and depression. Participation in these types of programs might improve the outcomes of those older adults who are current tobacco users.

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• a Microfet 2; Hoggan Health Industries Inc, 8020 So 1300 W, West Jordan, UT 84088.