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Health Perceptions As Predictorsof Exercise Adherence in Older Women

Alison Kleppinger, Mark Litt, Martin Kulldorff,Christine Unson, and James Oat Judge

Purpose: To determine if health perceptions, measured by SF-36 subscales,could identify women more likely to adhere to exercise, particularly duringexercise adoption and maintenance phases. Design and Methods: Subjects(Age = 67 5 yr, BMI = 24.4 3 kg/m2) were 189 estrogen-taking, postmeno-pausal women in a 2-year home-based resistance-training program. Results:Vitality, role-emotional, bodily pain, social functioning, and mental healthsubscales of the SF-36 were significantly (p < .05) predictive of exercise adop-tion. Vitality, role-emotional, general health, and bodily pain subscales weresignificantly (p < .05) predictive of exercise maintenance. Implications: Womenwho perceived themselves as having more energy, fewer emotional problems,less pain, fewer social problems, less feelings of nervousness and depressionwere more likely to start exercising. Women who perceived themselves ashaving more energy, fewer emotional problems, excellent health, less painwere more likely to continue exercising. Additionally, the present study indi-cated that different components of the SF-36 affected different behavior phasesof adherence during the exercise program.Key Words: health perceptions, exercise, self-rated health, SF036Key Points:1. Women who perceived themselves as having more energy, fewer emotional prob-

lems, less pain, fewer social problems, less feelings of nervousness and depressionwere more likely to start exercising.

2. Women who perceived themselves as having more energy, fewer emotional prob-lems, excellent health, less pain were more likely to continue exercising.

3. Different components of the SF-36 affected different behavior phases of adherenceduring the exercise program.

In an attempt to keep older adults active longer, health care providers encouragehealthy behaviors. Health behaviors can be defined as exercise, treatment therapies,

European Journal of Sport Science, vol. 3, issue 42003 by Human Kinetics Publishers and the European College of Sport Science

A. Kleppinger and C. Unson are with the Claude Pepper Older Americans Indepen-dence Center at the University of Connecticut Health Center, Farmington, CT 06030. M. Littis with the Department of Behavioral Sciences at the University of Connecticut HealthCenter. M. Kulldorff is with the Division of Biostatistics in the Department of CommunityMedicine and Health Care at the University of Connecticut School of Medicine. J.O. Judgeis with the Center on Aging at the University of Connecticut School of Medicine.

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medications, or several other actions that improve wellness and quality of life. Anabundance of research has supported exercise as a means of health maintenance.Many aspects of exercise adherence have been monitored to determine how to keepolder adults active and maintain healthy activities or behaviors. However, attritionrates as high as 50% in the first 6 months have been documented in some exerciseprograms (4, 16). It has become important to determine what factors are mostpredictive of adherence to exercise, particularly in the long-term, if exercise regi-mens are to have their optimal effects. Motivating or inspiring older adults to adhereto exercise behaviors is thus an important goal.

According to Janis and Rodin (7), A persons health-seeking behavior is, to agreat extent, based on his or her perception of a bodily state, rather than on the bodystrue, physical condition (7: p. 488). Learning more about an individuals healthperceptions could improve strategies to maximize exercise adherence, particularlyat home.

Several studies have linked perceived health status or self-health percep-tions with exercise behaviors (8, 10, 12, 13, 20). Marks and Lutgendorf (13)confirmed the notion that older adults who perceived themselves as healthier en-gaged in more health behaviors, specifically exercise. Laforge et al. (10) found thatself-perceived health status improved as stages of exercise behaviors progressedfrom adoption to maintenance.

There are, however, several dimensions to health perceptions, including per-ceptions of vitality, physical functioning, mental health, emotional health, and soon. It is not clear what kinds of health perceptions are most predictive of exercisebehavior, particularly in the elderly. Those who perceive themselves as more ill ormore at risk for conditions, such as osteoporosis, could be more motivated to seek aremedy. On the other hand, those who perceive themselves as too impaired may feelfearful or hopeless about the prospects of exercise (15). Perceptions of good healthmay predict high levels of exercise behavior, but may also predict low levels, in thatthose who feel generally well may not perceive a need to exercise. Likewise, onecould perceive oneself as physically healthy but emotionally overburdened, andthus not be prepared to embark on an extended exercise program. Knowing whichtype of health perceptions predict exercise behavior may help researchers tailorcommunications that could improve exercise adherence.

Finally, it is possible that the factors influencing exercise adoption may bedifferent from those that assist in maintaining exercise (2, 11, 17, 18). Investigatingbehavior influenced by health perceptions during the adoption stage, as well as themaintenance stage, may provide insight into boosting initiation of exercise as wellas optimizing long-term adherence to exercise programs.

The present paper is based on a study of 189 older women taking estrogen andenrolled in a 2-year study of the effects of exercise on bone density. Various social,psychological, and physical measures were obtained prior to the exercise trial. TheMedical Outcomes Study 36-item short form health survey, or SF-36, was one of themeasures attained from each volunteer at baseline. The SF-36 has been used toassess the health status and quality of life in the general population, and is consid-ered a valid and reliable measure (25). The specific scoring of eight different healthperceptions, including bodily pain, role-emotional, physical functioning, role-physi-cal, vitality, general health, and mental health, allow a more detailed exploration ofperceptions of health. Although the SF-36 is usually viewed as an outcome measureto rate health status, the current study treated the subscales, obtained prior to an

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exercise study, as different perceptions of health that might later influence behavior,such as exercise adherence.

The primary purpose of this study was to determine if health perceptions,measured by the SF-36 subscales, could identify women more likely to adhere tohealthy behaviors such as at-home exercise. The secondary purpose was to investi-gate the influence health perceptions might have on exercise adherence over theadoption and maintenance stages of exercise behavior. If health perceptions canhelp determine exercise adherence, then new strategies to improve adherence ratesmight be developed. We expected that women with positive perceptions of theirhealth to have higher adherence than those women with negative perceptions oftheir health.

Method

Participants

Participants were 189 women taking estrogen replacement therapy recruited for anintervention study measuring the effect of exercise on osteoporosis (low bone min-eral density). Women were included in the study if they had been receiving hormonereplacement for at least 2 years. Exclusion criteria were developed to exclude anyvariables that may effect bone mineral density: current smoker, use of medicationsknown to affect bone mineral density (calcitonin, bisphosphonates, prednisone \gte\5 mg/day, testosterone, phenytoin), prior hip fracture, body mass index > 30 kg/m2(based on self-report of height and weight), history of cancer in the last 5 years(excluding skin cancer), regular heavy resistance exercises, or physically activemore than 210 min per week.

Measures and Instruments

SF-36. Research staff administered the SF-36 at baseline, prior to randomizationand exercise. The SF-36 was developed to attain a quantitative measure of healthperceptions. It is a paper and pencil survey with 36 items and eight different subscales.Most items on the survey questioned the subjects views about his or her health,assessing the persons estimate of his or her health in a variety of domains. Itemswere scored using several different Likert scales to rank responses appropriately.Each subscale was transformed to a scale ranging from 0100. Eight subscales canbe obtained from the SF-36 including role-emotional, role-physical, vitality, physi-cal function, social function, general health, mental health, and bodily pain. Refer toTable 1 for a list of the SF-36 subscales and the meaning of their scores. Scoring wasobtained using the program supplied by Medical Outcomes Trust Manual, the scoredeveloper (26). Despite the conceptual uniqueness of each of the subscales, subscalescores were highly intercorrelated in this sample (minimum r = .40, p < .001).Adherence Measurements. Adherence to exercise was measured using exerciselogs. Self-report logs of behavior have been generally reliable and valid (1). Sub-jects were instructed to record at the end of each day whether they had exercised theprescribed 3045 min (one exercise session). Logs were kept for the duration of thestudy.

Adherence was calculated by the total number of at-home exercise sessionsreported on the exercise logs divided by the expected sum of sessions as determined

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by the assigned protocol (3 times each week). To investigate the adoption andmaintenance stages of behavior over time, adherence was calculated into 6-monthtime intervals of weekly compliance. Exercise adherence in the adoption phase wasthe average weekly number of home exercise sessions reported in the exercise logscalculated from months 7 through 12. The maximum number of sessions prescribedfor these women was 3 sessions per week. Adherence in months 0 through 6 was notconsidered valid for judging adoption because most sessions during these months ofthe study were performed in hospital-based classes, not at home. Thus, months 712represent a period during which participants either did or did not independentlyadopt the at-home exercise program. Exercise adherence in the maintenance phasewas calculated as the average number of weekly sessions reported in months 19through 24.

Table 1 SF-36 Health Status Scales

Concepts/ Items Meaning of Meaning ofsubscales (no.) low scores high scores

Physical 10 Limited a lot of performing Performs all types of physicalfunctioning all physical activities including activities including the most

bathing or dressing due to health vigorous without limitationsdue to health

Role- 4 Problems with work or other No problems with work orphysical daily activities as a result of other daily activities as a

physical health result of physical health

Bodily 2 Very severe and extremely No pain or limitations due topain limiting pain pain

General 5 Evaluates personal health as Evaluates personal health ashealth poor and believes it is likely excellent

to get worse

Vitality 4 Feels tired and worn out all Feels full of pep and energyof the time all of the time

Social 2 Extreme and frequent inter- Performs normal socialfunctioning ference with normal social activities without interference

activities due to physical or due to physical or emotionalemotional problems problems

Role- 3 Problems with work or other No problems with work oremotional daily activities as a result of other daily activities as a

emotional problems result of emotional problems

Mental 5 Feelings of nervousness and Feels peaceful, happy, andhealth depression all of the time calm all of the time

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Each month, subjects were asked to return their completed exercise logs.Exercise logs that were never returned to instructors were considered missing data.If a participant failed to turn in a set of logs, the volunteer filled in those daily data atthe next follow-up visit. If the missing data were never recalled by the volunteer,then it was resolved by imputing predicted values based on a linear trend modelusing SPSS software (23). Missing values were replaced with the mean of the valuesof the points on the preceding and succeeding days. Data points were imputed onlyfor those values missing, not for the values following exercise drop out. Participantswere considered exercise dropouts when they explicitly informed the research staffthat they no longer had any intention to continue prescribed exercise. For partici-pants who did drop out, zeroes were recorded for all log data after the drop date.Drop dates were defined as the date on which the participant submitted her lastexercise log.

Procedures

Recruitment. Recruitment targeted a diverse group of older women from centralConnecticut. Participants were recruited via targeted direct mailing, print, and broad-cast media, and through a community outreach program. Letters of invitation weresent to patients of a large obstetric and gynecological group practice (6,350), pa-tients of the University of Connecticut Health System internal medicine practices(1,914), Department of Motor Vehicle licensees (approx. 5,800), university alumni(1,366), and community organizations (170). Flyers were also inserted in newslet-ters of retiree associations (approx. 4,800). Four advertisements in the food sectionof a metropolitan newspaper were run. Multiple feature articles in area newspapers,television news, and radio programs with a predominantly older audience were alsoused. Several community talks were also given at senior centers, retirement commu-nities and retiree associations. A total of one hundred and eighty-nine women wererandomized to an exercise intervention group; either the upper body or the lowerbody. The current study was a sub-study of the exercise intervention study.Exercise Interventions. Both exercise groups were required to attend two classeseach week for the first 2 months. In the next 2 months participants attended one classeach week. In months 5 and 6, participants were attending class every other week.Following the 6-month point, participants were told to attend either one or twoclasses each month. Participants were expected to perform the prescribed exercisesthree times each week, including both their at-home exercise and monthly classsessions. Exercise sessions lasted 1 hour in class; however, most at-home sessionswere reported as lasting only 3045 min. Variation in the order of exercises per-formed was encouraged. A videotape and paper handouts of the exercises weredistributed to ensure good form and technique. In addition to upper- or lower-bodyexercises, participants of both groups were encouraged to walk at least 45 min eachweek (15 min, three times per week).Lower-Body Intervention. Each class began with a 5-min warmup, weight-resis-tance exercises, 15-min abdomen and lower-back exercises, and a 5-min cool-down. The weight-resistance exercises consisted of 4 different loaded exercises;chair-rise, stair climb, calf raises, and hip flexion. Each exercise consisted of 34sets of 10 repetitions. Participants were loaded with weighted belts around the waist.

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Each exerciser was assigned to lift 6% of their body weight at the start. Based ontheir form, participants progressed in 2-lb. increments. Muscle groups emphasizedwere quadriceps, calves, gluteus maximus, hip flexors, hamstrings, lower back, andabdomen.Upper-Body Intervention. Each class began with a 5-min warmup, weight-resis-tance exercises, 15-min abdomen and lower-back exercises, and a 5-min cool-down. The weight-resistance exercises consisted of 4 Theraband stretches and 67dumbbell exercises. Each exercise consisted of 2 sets of 10 repetitions. Musclegroups emphasized were upper back, chest, shoulders, triceps, biceps, forearms,lower back, and abdomen.

Statistical Analysis

The present trial is a substudy of an exercise intervention; therefore, it was possiblethat the different types of exercises being performed may have affected adherencerates. In order to rule out exercise type as affecting adherence rates, repeated mea-sures analyses of covariance on the two sets of dependent variables (adoption phaseadherence scores and maintenance phase adherence scores) were conducted. Exer-cise condition was used as the independent variable and baseline SF-36 scores as thecovariates.

Logistic regression analysis was used to identify whether women who droppedout of at-home exercise had different health perceptions than those women stillexercising after 24 months. Dropout at any point was the binary dependent variable,and SF-36 subscale scores served as predictors. Each SF-36 subscale score wasanalyzed independently in a logistic regression model adjusted for age, body massindex, and exercise intervention. Odds ratios were presented, along with 95% confi-dence intervals and a p value for a test of no effect.

Linear regression analyses were performed using the intention-to-treat sampleof 189 subjects. Although considered conservative, this type of analysis producesmore accurate estimates of effects (5). Each SF-36 subscale score was analyzedindependently in a regression model adjusted for age, body mass index, and exerciseintervention. These independent analyses were conducted because SF-36 subscalesare highly correlated, making it difficult to analyze the effect each has on adherencewhen they are combined in a single model. Eight multiple linear regressions, witheach SF-36 subscale as an independent variable, were therefore used to predictadoption of at-home exercise (months 712). An additional eight multiple linearregressions, with each SF-36 subscale as an independent variable, were used topredict maintenance of at-home exercise (months 1924). The effect sizes werecalculated together with 95% confidence intervals and a p value for a test of noeffect. Tests of normality were conducted on the regression residuals and found tobe approximately normal.

Results

The age of the resulting sample ranged from 59 to 78 years, with the average agebeing 67.4 years (SD = 4.8). Almost all the participants (99%) were white. The meanbody mass index (BMI) was 24.4 3 kg/m2.

SF-36 Predicts Exercise Adherence / 7

Health Perception Variables

Table 2 presents summary statistics of the SF-36 subscales in this sample. Inspec-tion of the table suggests that this sample of older women viewed all aspects of theirhealth perceptions more positively than the norms (26).

Overall adherence at 24 months of exercising was good: 137 subjects (72.5%)continued exercising. At month 12, 16% of the women had discontinued exercise.By month 18, 23% of the participants had stopped exercising. Only 52 women(27.5%) had discontinued exercise by 24 months.

Women were exercising an average of 1.4 times each week at month 24,regardless of the exercise group to which they had been assigned. Figure 1 presentsthe trend of adherence in the sample. Inspection of the graph suggests that overalladherence decreased over time.

Influence of Exercise Intervention on Adherence

In analyses of covariance with exercise behavior at adoption (months 712) and atmaintenance (months 1924) as the dependent variables, no main effect was seenfor exercise condition, no time effect emerged, and there was no interaction ofexercise intervention and time. Additionally, both upper body and lower bodyexercise groups had a similar number of dropouts.

Table 2 Characteristics of Respondents

Norms forVariables N SF-36* Mean Minimum Maximum SD

Age 189 65+ 67 60 78 4.7Body Mass Index

(kg/cm2) 189 N/A 24.4 18 34 3.0Weight (kg) 189 N/A 63 45 88 8.2Height (cm) 189 N/A 160.8 144 177 6.3Vitality 173 55.5 70.2 20 100 15.6Physical function 177 61.9 87.1 40 100 13.2Role emotional 175 73.4 88.5 0 100 26.8Role physical 174 56.1 86.3 0 100 25.9General health 172 61.6 83.6 42 100 12.6Bodily pain 175 63.4 79.6 22 100 19.3Social functioning 176 77.0 94.3 12.5 100 14.4Mental health 175 74.7 81.9 40 100 12.3

Note. SD = standard deviation. *SF-36 Manual of norms based on healthy women, ages 6070.

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Predictors of Exercisers Versus Drop-Outs

After 24 months, dropouts totaled 52, leaving 137 women still exercising. Role-emotional and social function subscales were significant predictors of dropout (p