A randomized trial to increase physical activity among native elders

A randomized trial to increase physical activity among native elders

Preventive Medicine 47 (2008) 89–94 Contents lists available at ScienceDirect Preventive Medicine j o u r n a l h o m e p a g e : w w w. e l s ev i ...

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Preventive Medicine 47 (2008) 89–94

Contents lists available at ScienceDirect

Preventive Medicine j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / y p m e d

A randomized trial to increase physical activity among native elders☆ Craig N. Sawchuk a,⁎, Steve Charles b, Yang Wen b, Jack Goldberg c,d, Ralph Forquera e, Peter Roy-Byrne a, Dedra Buchwald a,b,d a

Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA Medicine, University of Washington, Seattle, WA, USA Department of Epidemiology, University of Washington, Seattle, WA, USA d American Indian and Alaska Native Programs, University of Colorado Health Sciences Center, Denver, CO, USA e Seattle Indian Health Board, Seattle, WA, USA b c

a r t i c l e

i n f o

Article history: Available online 26 March 2008 Keywords: American Indian Physical activity Exercise Walking Pedometers

a b s t r a c t Objective. Physical inactivity is common among older populations and American Indians. Our objective was to compare two methods for increasing physical activity and walking among American Indian elders. Methods. We conducted a two arm randomized trial to increase physical activity in 125 American Indians aged 50–74 years at the Seattle Indian Health Board in 2005. Participants were randomized into either an activity monitoring (N = 63) or activity monitoring with a pedometer (N = 62) arm over a six-week period. Outcomes included self-reported physical activity and well-being, and the 6-min walk test. Results. There were no group differences in self-reported physical activities and well-being. The 6-min walk test yielded no between-group differences. All participants increased the frequency of leisure walking (p b 0.01), frequency of all exercise-related activities (p b 0.01), frequency of moderate-intensity exercise activities (p b 0.01), and improved weekly caloric expenditure for all exercise activities (p b 0.05) by the end of the trial. Conclusions. Pedometers did not confer enhanced performance on the physical activity outcomes beyond those achieved through self-monitoring. Physical activity can be promoted among at-risk groups in a brief, inexpensive manner in primary care. Exercise prescription and culturally relevant enhancement strategies may optimize physical activity outcomes for elder American Indians. © 2008 Elsevier Inc. All rights reserved.

Introduction Physical inactivity and sedentary lifestyles are becoming increasingly common in the general U.S. population (National Center for Health Statistics, 2003; US Department of Health and Human Services, 1996), and elevate the risk for obesity, hypertension, diabetes, and cardiovascular disease (Paffenbarger et al., 1986; US Department of Health and Human Services, 2000). Rates of physical inactivity are disproportionately higher in certain groups, especially among older, lower income, and unemployed populations (Clarke et al., 2007; Taylor et al., 1998; Trost et al., 2002). Physical inactivity is also prevalent among ethnic/racial minority groups (Belza et al., 2004; Centers for Disease Control, 2004; Crespo et al., 2000), especially American Indians (Coble and Rhodes, 2006; US Department of Health and Human Services, 1996). Studies with geographically diverse tribes consistently show low levels of leisure-time physical activity (Welty et al., 1995; Young, 1991), less frequent exercise (Cheadle et al., 1994;

☆ Financial support: This study was supported by grant 5 P01 HS 10854-02 from the Agency for Healthcare Research and Quality. ⁎ Corresponding author. University of Washington, Harborview Medical Center, Box 359911, 325 9th Avenue, Seattle, WA 98104, USA. Fax: +1 206 731 3236. E-mail address: [email protected] (C.N. Sawchuk). 0091-7435/$ – see front matter © 2008 Elsevier Inc. All rights reserved. doi:10.1016/j.ypmed.2008.03.011

Mendlein et al., 1997), and a higher proportion of being classified as sedentary (Goldberg et al., 1991; Molina and Campos-Outcalt, 1991) relative to majority populations. These findings are particularly alarming given that obesity, hypertension, diabetes, and cardiovascular disease are on the rise in many American Indian communities (Galloway, 2005). Physical activity interventions designed for older populations have shown promising health and fitness outcomes in both majority (Hui and Rubenstein, 2006; Vaitkevicius et al., 2002) and ethnic/racial minority (Sin et al., 2005) samples. Walking is an ideal physical activity for sedentary individuals given its accessibility, affordability, and low risk for injury (Eyler et al., 2003; Hootman et al., 2001). Furthermore, walking is one of the most common and preferred physical activities among adults (Centers for Disease Control, 2004; Rafferty et al., 2002). Despite the health benefits and logistical advantages of walking, epidemiological studies note that older age groups contain the lowest percentage of regular walkers and the highest percentage of never walkers (Eyler et al., 2003). Of interest, several community-based studies have explored the use of electronic pedometers in promoting walking behavior among adults across the age spectrum (Bravata et al., 2007; Iwane et al., 2000; Merom et al., 2007; Sequeira et al., 1995; Stovitz et al., 2005). The step-counting function of these portable, inexpensive, easy to operate, waist-affixed devices provides a relatively objective measure of

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accumulated steps, and can be used for goal setting and motivational engagement for older individuals (Farmer et al., 2006). Although qualitative data highlight the perceived health benefits of exercise and interest in physical activity programs such as walking among older American Indians (Belza et al., 2004; Henderson and Ainsworth, 2003), pedometers have not been used in any American Indian health studies. We conducted a randomized trial of the use of pedometers to increase physical activity and fitness levels in a primary care sample of American Indian elders. Elders were randomized to receive either basic instruction in daily physical activity monitoring or daily physical activity monitoring augmented with a pedometer to track and record their total daily step counts. We hypothesized that those elders who augment their physical activity monitoring with the use of a pedometer would report significantly greater increases in self-reported physical activities and well-being, and enhanced performance on the 6-min walk test of fitness relative to their counterparts who only monitored their daily physical activities. Methods Subjects All study procedures were conducted between April and November 2005 at the Seattle Indian Health Board, a large urban primary care medical facility for American Indians and Alaska Natives in the greater metropolitan Seattle area. American Indian elders were recruited through advertisements at the Board, Native health fairs, and by word of mouth. Potential participants were screened for age and American Indian ethnicity prior to completing a brief telephone interview to determine final study eligibility. Inclusion criteria included 1) being 50–74 years of age, 2) having a sedentary lifestyle, assessed by responding “no” to the question “Have you been physically active for the past 6 months?”, 3) being able to walk without assistance, 4) denying medical contraindications to walking, and 5) living within a 2-h drive from the study site. Of note, the term “elder” is acceptable in many American Indian cultures, communities, and families for individuals aged 50 years and older as it denotes a certain status within the community beyond that of chronological age. Approval for this study was obtained from both the Human Subjects Division at the University of Washington and the Privacy Board at the Seattle Indian Health Board. Measures Self-reported physical activities and health The Community Healthy Activities Model Program for Seniors (CHAMPS) Questionnaire is a 41-item measure assessing a range of light, moderate, and vigorous physical activities in leisure, work, exercise, and chore-related domains (Stewart et al., 1997). Respondents report their weekly frequency and duration of participation in activities over the previous 4 weeks, yielding four primary summary scores: total weekly caloric expenditure for all exercise activities; total weekly caloric expenditure for moderate-intensity exercise-related activities; weekly frequency of all exerciserelated activities; and weekly frequency of moderate-intensity exercise-related activities. The CHAMPS has excellent psychometric characteristics and has been used extensively with older adults as an outcome measure for physical activity interventions (Harada et al., 2001; Stewart et al., 2001). The Short Form 36 of the Medical Outcomes Survey (SF-36) is a 36-item measure of health-related quality of life across eight domains: physical functioning, role-physical, bodily pain, general health, vitality, social functioning, role-emotional, and mental health (Ware and Sherbourne, 1992). Two higher-order component summary scores (mental and physical component scores) are derived from the eight scales of the SF-36. Respondents rate their health-related functioning over the last 4 weeks. The SF-36 has well-established reliability and validity (Ware and Sherbourne, 1992), and has been used with diverse patient populations (Schlenk et al., 1998; Yost et al., 2005), elderly (Chapman et al., 2007; Hu, 2007; Wolinsky et al., 1998), and American Indian samples (Beals et al., 2006; Johnson et al., 1996). Test of physical fitness The 6-min walk test was used as our primary behavioral outcome of fitness. The 6min walk has been widely used as a reliable and valid measure of fitness in healthy (Harada et al., 1999, 2001; Simonsick et al., 2001) and medically compromised (Bittner et al., 1994; Peeters and Mets, 1996; Montgomery and Gardner, 1998) older adults. Participants are instructed to walk around two traffic cones on opposite ends of a 50-ft corridor, unassisted, while covering as much distance as possible within the 6-min time frame. Following a standardized administration protocol (Peeters and Mets, 1996), the research assistant provided encouragement at fixed intervals during the walk, and recorded the total number of laps completed. At the end of 6 min, a marker was placed on the ground next to the subject, and total distance was calculated in feet with a rolling tape measure.

Materials Pedometer A Yamax Digiwalker model SW-701 pedometer was used to monitor total daily step counts. The Yamax SW-701 has been found to be sensitive and reliable in recording step counts (Crouter et al., 2003; Schneider et al., 2003, 2004), even among overweight and moderately obese individuals (Swartz et al., 2003). Weight and height A portable digital scale was used to assess weight, and a tape measure against a wall was used to measure height. Body mass index was calculated using the following formula: weight in kg/height in meters2. Activity monitoring Participants were given a booklet of daily self-monitoring physical activity forms. Additional space was available for personal comments regarding their activities. Participants randomized to the pedometer group also had a space to write in their total daily step counts. Procedure During the 6-week trial, all participants completed two face-to-face clinic visits at the Seattle Indian Health Board, spaced 6 weeks apart with the research assistant. Each clinic visit lasted between 60 to 90 min in length. Participants also received two, 10-min phone calls from the research assistant at weeks two and four of the trial. The purpose of these calls was to bolster continued participation in the study, address any studyrelated concerns, encourage engagement with physical activity and exercise, and reaffirm the date and time of their final study visit. During the first clinic visit, study purpose and procedures were verbally described to the participant, and written informed consent was obtained. A structured interview was conducted to collect additional demographic and medical information, followed by completion of the CHAMPS and SF-36. A research assistant measured each participant's height and weight, and then randomly assigned participants to either the activity monitoring only group or the pedometer group. Allocation to the study groups was determined by an independent statistician using a random number table. The group assignment for each participant was placed in a sealed envelope by the statistician and given to the research assistant prior to the first study visit. Participants randomized into the activity monitoring only group were given a series of weekly activity-monitoring sheets, and the interviewer demonstrated how to complete each daily activity entry. The research assistant reviewed different types of physical activities and exercises the participant might try over the six-week study period. An educational handout on the health benefits of increased physical activity was also reviewed with each participant. Finally, the research assistant verified contact information and scheduled the telephone appointments at weeks two and four of the protocol, as well as their final study visit at the study site at week six. Participants randomized into the pedometer group were given the same instruction, materials, and scheduling procedures described above. Participants were also trained in the use of a pedometer, shown how to read the step counter, and how to record their total daily step count on the activity-monitoring forms. Weight and stride length were used to calibrate the pedometer for each individual participant. At the end of the first clinic visit, all participants were compensated with a $40.00 grocery gift card. During the week two and four telephone calls, the research assistant briefly reviewed progress with the activity-monitoring logs, but did not provide any specific motivational feedback or goal setting for physical activity and exercise progress. Participants were mailed another $40.00 grocery gift card for compensation after completing the week four telephone appointment. At the second clinic visit, the research assistant reviewed the daily activitymonitoring forms, re-administered the CHAMPS and SF-36, and reassessed height and weight. Changes in health status and ambulatory functioning since starting the study, resting oxygen saturation, heart rate, blood pressure, and the Borg–Dyspnea scale were measured prior to completing the 6-min walk. Following completion of the walk, participants were debriefed and compensated with a $60.00 grocery gift card. Statistical analyses Initial descriptive analysis compared demographics, body mass index, medical conditions, baseline physical activities, and health-related quality of life in both treatment groups. Means and standard deviations were used for continuous variables and percent distributions were used for categorical variables. We calculated the change in CHAMPS and SF-36 measurements for each subject from baseline to week 6. We used linear regression to compare these mean change scores between the two treatment groups. The regression model also included baseline body mass index to control for this factor. For the 6-min walk test we did not take a baseline measurement. We compared the groups on mean distance traveled during the 6-min walk test at the final study visit. To examine time trends in the CHAMPS and SF-36 scores we used a paired t-test comparing baseline and week 6 measurements. Information obtained from the activitymonitoring forms were not coded for analysis in the present study. All analyses used an intention-to-treat approach. The level of statistical significance was set at 0.05. We analyzed the data using SAS (Version 9.1) statistical software.

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Results Participant characteristics A total of 205 elders were screened for eligibility, 164 met study criteria, 125 (76%) were enrolled into the study; 63 were randomized to the activity monitoring only group and 62 were randomized to the pedometer group (Fig. 1). The average age of the full sample was 58 years and 74% of were female (Table 1). Most participants reported at least one chronic medical condition, with 83% reporting two or more co-occurring medical problems. Participants in the pedometer group had a higher body mass index at baseline (p = 0.03). No other between-group differences on the CHAMPS or SF-36 at baseline were noted. Over the course of the study, six participants in the pedometer group and two participants in the activity monitoring only group dropped out. Study completers and dropouts did not differ on any baseline demographic, CHAMPS, or SF-36 variable. Self-reported physical activities and health Table 2 presents mean change scores and standard errors for the CHAMPS and SF-36 measures during the six-week intervention. No between-group differences were found in mean SF-36 difference scores. Nor were there any significant mean difference scores in weekly caloric expenditure or exercise frequency on the CHAMPS. The most frequently endorsed physical activities for both groups at baseline included light housework, walking for errands, walking for leisure/pleasure, and walking/hiking uphill. At the end of the 6-week study period, the most frequently endorsed physical activities included light housework, walking for leisure/pleasure, walking for errands, and stretching/flexibility exercises. In both groups the frequency of walking for leisure/pleasure increased from baseline to week six (p b 0.01).

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Table 1 Demographic and clinical characteristics according to Activity Monitoring and Pedometer groups, Seattle 2005 Demographics and clinical characteristics Demographics Age, mean years Female, % Attended 12 or more years of school, % Married, % Employed full/part time, % Body Mass Index, mean kg/m2 (SD)⁎ Self-reported medical conditions, % Arthritis or osteoporosis Asthma Cancer Diabetes Heart disease or stroke Hypertension At least one medical condition Two or more medical conditions

Activity monitoring only (N = 63)

Pedometer (N = 62)

58 78 84 23a 27 29.8 (5.1)a

58 71 82b 16 16 32.3 (7.4)

52 23a 13 22 17 38 94 79

60 20a 10 29 15 43a 98 87

a

Missing one observation. Missing two observations. ⁎ p = 0.03. b

Test of physical fitness At week 6, the BMI-adjusted mean distance traveled during the 6min walk was very similar in both treatment groups (1334 in the activity only group and 1287 in the pedometer group). This difference was not significant (p = 0.58). Differences over time The two treatment groups were then collapsed into a single sample and paired sample t-tests examined changes in CHAMPS and SF-36 Table 2 The effects of the pedometer intervention on physical activity and health-related quality of life, Seattle 2005 Outcomes

CHAMPS Caloric expenditure/ week in all exerciserelated activities Caloric expenditure/ week in moderateintensity exerciserelated activities Frequency/week of all exercise-related activities Frequency/week of moderate-intensity exercise-related activities Short form-36 Physical functioning Role-physical Role-emotional Social functioning Bodily pain Mental health Vitality General health Physical component score Mental component score Fig. 1. Trial profile and participant flow.

Activity monitoring only

Pedometer

N

Mean difference (SE)⁎

N

58 1309.5 (631.2)

56

58

t- score p-value

Mean difference (SE) 380 (551.4)

717.9 (469.6) 56 −119.4 (357)

−1.11

0.27

−1.32

0.19

61

6.1 (1.9)

56

5.5 (1.6)

−0.46

0.65

61

2.2 (1.0)

56

1.9 (1.0)

−0.23

0.82

61 58 58 61 61 61 61 61 58

1.6 (2.4) 9.9 (4.9) 4.6 (5.1) − 2.5 (2.9) 5.6 (2.6) 1.0 (1.7) 3.4 (2.1) −1.0 (1.9) 1.7 (1.0)

56 54 54 56 56 56 56 55 53

−0.21 −1.45 0.72 1.19 −1.0 0.65 0.15 1.01 −1.51

0.83 0.15 0.47 0.24 0.32 0.51 0.88 0.32 0.13

58

0.3 (1.2)

53

1.5

0.14

0.8 1.4 9.3 4.3 2.2 3.0 4.5 1.6 −0.4

(2.8) (5.3) (5.8) (3.1) (3.3) (2.0) (2.4) (1.9) (1.2)

3.2 (1.4)

⁎Mean differences were between baseline and at 6 weeks.

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Table 3 Paired comparison of changes on body mass index, physical activity, and health-related quality of life at baseline and week six for entire sample, Seattle, 2005 Outcomes

N

Baseline

Week 6

t- score

p-value

Mean (SE)

Mean (SE)

Body Mass Index, mean kg/m2 (SD) CHAMPS Caloric expenditure/week in all exercise-related activities Caloric expenditure/week in moderate-intensity exercise-related activities Frequency/week of all exercise-related activities Frequency/week of moderate-intensity exercise-related activities Short form-36 Physical functioning Role-physical Role-emotional Social functioning Bodily pain Mental health Vitality General health Physical component score

114

31 (1)

31 (1)

0.03

0.97

114

3,819 (354)

4,672 (448)

2.03

0.04

114

2,130 (268)

2,437 (327)

1.03

0.31

117

21 (1)

27 (1)

4.59

b 0.01

117

7 (1)

9 (1)

2.9

b 0.01

117 112 112 117 117 117 117 116 111

67 (2) 62 (3) 62 (4) 73 (2) 54 (2) 67 (2) 54 (2) 62 (2) 43 (1)

69 (2) 68 (3) 69 (4) 73 (2) 58 (2) 69 (2) 58 (2) 63 (2) 43 (1)

0.68 1.61 1.78 0.35 1.91 1.5 2.47 0.19 0.9

0.5 0.11 0.08 0.73 0.06 0.14 0.02 0.85 0.37

scores from baseline to week six. The results of these analyses are presented in Table 3. On the CHAMPS, participants reported improved weekly caloric expenditure for all exercise-related activities (p = 0.04), frequency of all exercise-related activities (p b 0.01), and frequency of moderate-intensity exercise-related activities (p b 0.01). On the SF-36, participants reported an overall increase in vitality (p = 0.02). Discussion Our study compared two simple, inexpensive methods for increasing physical activity levels in a primary care sample of American Indian elders. As in previous investigations with majority and minority populations (Tudor-Locke and Myers, 2001; Rafferty et al., 2002; Whitt et al., 2004), walking for instrumental and leisure purposes was a common activity endorsed by elders at the start of the study. Walking frequency, especially for leisure/pleasure, increased significantly across the six-week study period, irrespective of group assignment. These findings support previous qualitative research that found walking is a physical activity preferred by American Indian elders (Belza et al., 2004; Coble and Rhodes, 2006; Henderson and Ainsworth, 2003) and an ideal physical activity for older-aged individuals (Eyler et al., 2003; Hootman et al., 2001). Our findings are encouraging because routine exercise can reduce the risk for many medical conditions (Coble and Rhodes, 2006), including obesity, diabetes, hypertension, and cardiovascular disease, all of which are on the rise in Native communities (Broussard et al., 1995; Burrows et al., 2000; Galloway, 2005). Indeed, 96% of our primary care sample endorsed at least one chronic medical condition at baseline, with most reporting two or more. Contrary to our hypothesis, adding a pedometer to daily physical activity monitoring did not produce appreciable differences in selfreported physical activity levels as assessed by the CHAMPS. However, we did observe improvements in the frequencies of engaging in leisure walking, all exercise activities, and exercises of moderateintensity for all study participants during the trial. Furthermore, all participants also increased their weekly caloric expenditure for all exercise-related activities over the course of the study. As found in prior studies (Gleeson-Kreig, 2006; Speck and Looney, 2001), basic monitoring of daily physical activities can produce desired changes in

health-related behavior. The act of self-monitoring can raise awareness of modifiable health habits, create an external environmental reminder to increase personal accountability, improve self-efficacy, and provide on-going feedback on progress (Bravata et al., 2007). Such interventions are ideally suited for the primary care setting given their simplicity, low cost, and ability to be tailored to individuals (Aittasalo et al., 2006; Bravata et al., 2007; Sherman et al., 2007). Furthermore, a review of monitoring records during clinic visits requires minimal time, and allows the provider to positively reinforce specific health change efforts in the moment and engage the patient in solutionbased problem solving (Aittasalo et al., 2006; Gleeson-Kreig, 2006; Nied and Franklin, 2002). Engagement in physical activity is positively associated with measures of social support (Eyler et al., 1999; Umstattd et al., 2006; Wilcox et al., 2000) and emotional functioning (Blumenthal et al., 1999; Mather et al., 2002) among older adults. The novelty of using a pedometer and/or increasing awareness through self-monitoring may have encouraged elders to increase their activity outside their homes and walk in more public areas. This change may increase the likelihood of having more interactive and pleasurable social encounters. Social isolation is a common barrier to physical activity among the aged (Eyler et al., 2003), including American Indians (Belza et al., 2004; Harnack et al., 1999; Heesch et al., 2000). Previous studies with American Indians have shown a five-fold increase in physical activity engagement among those who know someone in their community who also exercises (Thompson et al., 2003). Designing activity plans that bolster social support through establishing walking partners or organizing walking groups may be particularly important for activity promotion and maintenance in this population. We failed to find any group differences on the 6-min walk test of fitness. Both groups traveled an average distance comparable to similar-aged, healthy adults (Enright et al., 2003; Sanderson and Bittner, 2006). Like previous studies (Enright and Sherrill, 1998), our participants varied widely in the total distance covered during the walk. Factors such as height, weight, body mass index, smoking history, health status, and education have been associated with physical activity levels in general (Eyler et al., 2003; Trost et al., 2002; Umstattd et al., 2006), and 6-min walk test performance in particular (Enright et al., 2003; Sanderson and Bittner, 2006). To our knowledge, this represents the first study to use the 6-min walk test with American Indians elders. Additional analyses are warranted to determine if similar demographic, health, and social variables predict 6-min walk performance among older American Indians. The 6-min walk is regarded as a brief, safe, economical, and sensitive measure of physical functioning that can be easily integrated into health care settings (Enright et al., 2003), and may be particularly well suited for use in under funded community clinics. The finding that a pedometer did not confer an advantage over basic self-monitoring suggests that self-monitoring alone may be sufficient, a finding similar to that reported by Stovitz and colleagues (2005). This conclusion may be premature, however, given that participants using pedometers in our study were not offered any instruction in daily stepcount goal setting. Previous studies have found that pedometer goal setting (Hultquist et al., 2005; Moreau et al., 2001) and directive prescriptions of exercise intensity and frequency levels (Duncan et al., 2005) can enhance physical activity outcomes relative to no-instruction conditions (Bravata et al., 2007). Activity prescriptions that incorporate cultural values and an improved sense of community may be key motivators for American Indians (Belza et al., 2004). Future research with older American Indians in primary care should examine culturally relevant prescription strategies as a means of optimizing physical activity and fitness outcomes. Furthermore, tailoring exercise prescriptions to benchmarks established by the American Heart Association, Centers for Disease Control and Prevention, and the Surgeon General may be particularly important so that physical activity levels do produce measurable health benefits (Duncan et al., 2005).

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Study limitations and strengths Our study has several limitations and notable strengths. Unfortunately, we observed a baseline difference in body mass index with participants assigned in the pedometer group having significantly higher values than those in the activity monitoring only group. Higher body mass index is inversely associated with overall physical activity levels (Martinez-Gonzalez et al., 1999), pedometer walking distance (Bennett et al., 2006; Merom et al., 2007; Sherman et al., 2007), and performance on the 6-min walk test of fitness (Enright et al., 2003; Hulens et al., 2003). Although we statistically corrected for this difference, block randomization based on body mass index would be one way to ensure the groups are equal on this dimension at baseline. Furthermore, we failed to conduct a-priori power analyses on our study measures. Second, we relied largely on self-reported measures of outcome. Future studies could monitor changes in objective assessments of health status such as lipid protein levels during the intervention. Systematic reviews have noted significant reductions in BMI and systolic blood pressure (Bravata et al., 2007). Third, we did not examine baseline personal or environmental barriers to physical activity. Older adults experience challenges in establishing and maintaining physically active lifestyles, such as managing chronic health conditions, restricted access to transportation and recreational facilities, financial difficulties, limited social support, and isolation (Belza et al., 2004). Although not an aim of this study, assessing these factors would highlight those barriers that are most relevant to American Indian elders, those that are most predictive of physical activity outcome, and those that are modifiable through basic problem solving. Fourth, previous studies suggest that many individuals fail to maintain an exercise regimen over the long-term (Sallis et al., 1986). More effective motivational techniques and culturally meaningful reinforcers could help participants maintain positive physical activity changes (Scales and Miller, 2003). Finally, our design did not include a no-treatment or attentioncontrol condition. Demand characteristics, social desirability, measurement reactivity, and monetary incentives may have influenced our findings. Both groups received significant attention, education, and feedback during the trial in the form of in-person clinic visits, brief telephone calls, and personal monitoring, a design similar to that employed by Stovitz et al. (2005). Other studies have directly controlled the effect of feedback by comparing open with sealed pedometers (Speck and Looney, 2001) and eliminating contact with research personnel (Merom et al., 2007). Observed changes in the present study may be due to the reinforcing and motivational value of receiving consistent, daily personal feedback regarding physical activity levels rather than simply the behavioral act of activity recording per se. Future designs will need to control the effects of pedometer and interpersonal feedback to isolate the effects of the intervention. Additionally, studies may compare the relative strength of different forms of feedback (e.g., total amount of time spent in physical activity compared to changes in blood pressure) on activity performance. Despite these limitations, this study represents the first randomized trial on physical activity with a primary care sample of American Indian elders. Given that the majority of primary care service centers for American Indians are profoundly under funded, the simple and low-cost nature of this intervention is readily generalizable to this practice setting. Our findings contribute to the scant literature on physical activity promotion efforts with disadvantaged, ethnically/ racially diverse populations. Conclusions Few efforts have been made to study the promotion of physical activity among American Indian elders. Although disease risk factors are disproportionately high among American Indian populations, adverse health outcomes and management of disease risk factors are potentially

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modifiable through routine physical activity (e.g., Ballor and Keesey, 1991; Blumenthal et al., 1999; Dunn et al., 1999; Lee and Paffenbarger, 2000; US Department of Health and Human Services, 1996). Physical activity interventions can be tailored for delivery in the primary care treatment setting. Increased attention to the study of simple, low-cost, and effective methods for physical activity that address relevant exercise barriers is needed to reduce health disparities among older American Indians. Future research also should objectively assess changes in biological markers for disease, such as body/fat mass, lipoprotein and fasting insulin levels, and blood pressure, as a function of adherence to a prescribed physical activity intervention. References Aittasalo, M., Miilunpalo, S., Kukkonen-Harjula, K., Pasanen, M., 2006. A randomized intervention of physical activity promotion and patient self-monitoring in primary health care. Prev. Med. 42, 40–46. 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