Correlates of Physical Activity among Blacks and Whites with Arthritis Cheryl A. Der Ananian, PhD; Christopher Churan, MS; Marc A. Adams, PhD, MPH Objective: To evaluate the correlates of physical activity (PA) participation among white and black individuals with diagnosed arthritis. Methods: This study used a cross-sectional design, grounded in the Social Ecological Model. Participants (N = 205) completed a survey regarding PA participation and potential correlates of PA. Bivariate and multivariate analyses were used to examine the correlates of PA. Results: Nearly 30% of the population met the current guidelines for aerobic PA. A greater proportion of Whites (35.3%) than Blacks (20.9%) met current guidelines (χ2 = 4.98, p = .03). In bivariate analyses, ethnicity, income, body mass index, selfefficacy for exercise, exercise outcome expectations, physical function, physician

D

ue to its high prevalence, its effects on disability and its associated healthcare costs, arthritis substantially impacts public health. Currently, 52.5 million adults in the United States (US) report diagnosed arthritis, and of those, 22.7 million report arthritis-related activity limitations, making it the leading cause of disability in US adults.1 By 2030, arthritis is projected to impact 67 million US adults and the prevalence of arthritisrelated activity limitations is expected to increase to 25 million.2 As a result of the high prevalence of arthritis and its impact on function and disability, there is a considerable economic burden associated with arthritis. Total costs associated with arthritis in 2003 were $128 billion.3 As of 2011, arthritis ranked second for costs associated with hospital visits and costs billed to Medicare.4 Increasing physical activity (PA) participation among people with arthritis may help reduce the public health burden of arthritis. PA is considered a primary treatment and prevention strategy for arthritis.5-7 Regular participation in PA has been Cheryl A. Der Ananian, Assistant Professor, Christopher Churan, Graduate Student, and Marc A. Adams, Assistant Professor, School of Nutrition and Health Promotion, Arizona State University, Phoenix, AZ. Correspondence Dr Der Ananian; [email protected]

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advice to exercise, and perceived safety from neighborhood crime and traffic were associated with meeting PA guidelines (p < .05). In regression analyses adjusted for socio-demographic characteristics, exercise self-efficacy and physician’s advice to exercise were the only significant predictors of PA (p < .05). This finding was confirmed with stepwise forward regression. Conclusions: PA interventions for people with arthritis should focus on enhancing self-efficacy for exercise and include strategies to optimize communication about PA by healthcare providers. Key words: physical activity; arthritis; aging; correlates Am J Health Behav. 2015;39(4):562-572 DOI: http://dx.doi.org/10.5993/AJHB.39.4.13

shown to improve pain, stiffness, and physical function, and may delay disability among people with arthritis.8-11 These benefits are in addition to the general health benefits of PA.12 Despite the abundance of evidence demonstrating the benefits of PA for arthritis, participation rates are low in people with arthritis. Individuals with arthritis are less likely to meet the current PA recommendations and more likely to report no leisure time PA than those without diagnosed arthritis.13 This reduced participation in PA participation may be more pronounced in ethnic minority populations with arthritis although this has not been well-studied. Some cross-sectional studies suggest the prevalence of inactivity is significantly higher among black individuals than among white individuals.13 However, an important limitation of these studies is that confounding factors such as socio-economic status, health, or physical environment are not taken into consideration. Song et al14 examined the percentage of black and white adults with radiographic evidence of osteoarthritis of the knee who met the current PA recommendations using accelerometer-derived measures of PA. Only 1.9% of black adults and 12.7% of white adults met the PA guidelines. These differences remained statistically significant after adjusting for socio-demographic and health characteristics, suggesting

Der Ananian et al PA participation may vary by ethnicity.14 Understanding the correlates of PA is necessary for promoting PA and improving the design of PA interventions for people with arthritis. Whereas numerous studies have examined the correlates and determinants of PA in people with arthritis, the majority have included samples that were predominantly white, female, and highly educated.15 As the population of the US ages, it will become more ethnically diverse necessitating the need to understand correlates of PA in diverse populations with arthritis. Enhanced participation in PA may be particularly important for improving arthritisrelated outcomes among black individuals who may be more adversely affected by it. Arthritisrelated pain is reported to be more pronounced in black individuals16 and there is some evidence that black individuals experience greater impairments in physical function compared to the white individuals.17,18 Decreased participation in PA may contribute to the adverse outcomes experienced by black individuals, and enhanced participation may help alleviate the disparities in arthritis-related outcomes. Additionally, to date, most studies examining PA participation among individuals with arthritis have only examined intra- and inter-personal factors or correlates.15 Because people with arthritis often report mobility limitations, the built environment may be a key influence on PA participation. To date, there is a dearth of studies examining the influence of the built environment on PA in this population. The Social Ecological Model (SEM) provides a framework to look at the intra-personal, inter-personal, organizational, community, environmental, and policy factors that influence engagement in health behaviors.19,20 Therefore, this exploratory study examined PA participation and the correlates of PA participation in a convenience sample of older non—Hispanic white (NHW) and non-Hispanic black (NHB) individuals with arthritis using the Social Ecological Model19 as the theoretical framework. METHODS Study Design A mailed survey was used to examine PA level and potential correlates of PA in a cross-section of NHB and NHW individuals, aged 50 and older (mean age = 67.4 + 10.1 years), with a diagnosis of arthritis. Participants and Recruitment Participants were from a convenience sample of community-dwelling individuals with a diagnosis of arthritis and who were willing to complete a survey about their PA behaviors and health, psychosocial, and environmental factors that may influence PA participation. Inclusion criteria were: being at least 50 years of age, being able to provide a self-report of a healthcare provider’s diagnosis of arthritis, self-identifying as NHB or NHW, and being able to

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read, write, and speak English. Recruitment for the study took place in the Greater Chicago area (Chicago and surrounding suburbs). Flyers advertising the study were placed in community-based organizations serving seniors (eg, senior centers, cafes and restaurants, community health centers, fitness facilities, churches and parks and recreation facilities) and research staff recruited faceto-face during events. Participants were recruited through letters sent to members of the local Arthritis Foundation and via advertisements placed on their website and in their newsletters. Study flyers also were placed in 1500 “goody bags” provided to participants in a fitness walk specifically for older adults. To enhance recruitment of NHB individuals, flyers were distributed to every resident of 2 large, predominantly NHB senior housing complexes and an advertisement was placed in a newspaper whose target audience is primarily the black community. Eligible participants indicated they heard about the study primarily through the Arthritis Foundation (56.3% of NHWs and 26.7% of NHBs), senior centers (38.4% of NHBs and 10.8% of NHWs), other locations including unknown (14% of NHBs and 22.7% of NHWs), senior housing (14% of NHBs only), and the fitness walk (7% of NHBs and 8% of NHWs). Individuals were screened over the phone for eligibility. Eligible individuals were mailed the consent form and questionnaire. Subsequently, research staff called the study participants to review the consent form. Participants returned the signed consent form with their survey. Theoretical Framework The SEM provided the theoretical framework for this study. The model was designed to address complex multilevel factors that facilitate or constrain healthy and unhealthy behaviors.19 The primary assumption of the SEM is that change in an individual’s behavior comes from appropriate changes in the social and physical environments. The model also assumes individuals are essential for creating environmental changes. In the present study, the framework was operationalized to PA as follows: intrapersonal factors (age, sex, education, ethnicity/ethnicity, income, disease severity, pain, and mobility limitations); interpersonal factors (social support for exercise and physician’s advice to exercise); community and organizational factors (availability of exercise programs), and the physical and built environment. Measures Socio-demographics. Participants self-reported their age, sex, ethnicity (NHB OR NHW), education level, marital status, and income (< $29,999, $30,000- $60,000 or >$ 60,000). Physical Activity Level: PA level was obtained using a modified version of the 2001 Behavioral Risk Factor Surveillance System (BRFSS) PA module (http://www.cdc.gov/brfss/annual_data/pdf-

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Correlates of Physical Activity among Blacks and Whites with Arthritis ques/2001brfss.pdf). The wording of the module was modified to include only structured or purposeful moderate and vigorous aerobic exercise. Specifically, the terms gardening, vacuuming, and yard work were omitted from the wording of the questions. The strength-training question was used verbatim. Based on responses, participants were classified as either meeting or not meeting the American College of Sports Medicine and American Heart Association (ACSM – AHA) guidelines for moderate-to-vigorous aerobic PA.21 Explicitly, if participants engaged in moderate intensity PA for at least 30 minutes on 5 or more days per week or vigorous PA for at least 20 minutes on at least 3 days per week, they were classified as meeting the guidelines. Individuals who engaged in strengthtraining exercises at least 2 days per week were classified as meeting the strength-training guidelines. Healthcare provider (HCP) advice to exercise. Participants were asked a series of questions to assess HCP advice to exercise. Participants were asked first if they had seen a HCP or physician in the past 12 months (yes or no). Participants who responded yes to this question were asked if the HCP recommended or advised exercise. This series of questions was repeated for rheumatologists or specialists in arthritis. Participants who reported they had not seen a HCP or a rheumatologist within the past year were classified as not seeing a HCP. Participants who saw a rheumatologist and/ or a general HCP and indicated that they did not receive advice to exercise were classified as not receiving HCP advice to exercise. Participants who saw a rheumatologist and/or a general HCP and indicated that they received advice to exercise were classified as receiving HCP advice to exercise. Body mass index (BMI). BMI (m/kg2) was calculated using self-reported height and weight. Participants were classified as underweight if they had a BMI < 18.5 kg/m2, normal weight if they had a BMI between 18.5 and 24.9 kg/m2 , overweight if they had a BMI between 25.0 and 29.9 kg/m2, and obese if they had a BMI ≥ 30.0 kg/m2. Arthritis impact measurement survey version 2 (AIMS2). The AIMS2 is an arthritis-specific survey that assesses physical functioning, pain, psychological status, social interactions, social support, perceptions of health, and demographic information.22 We used a 3-component model (physical function impairment, affect, and symptoms) to assess arthritis impact. The summary score for physical functioning included 6 subscales: level of mobility, walking and bending, hand and finger function, arm function, personal care, and household tasks. Affect included 2 subscales: tension level and mood. Symptoms used one scale, which assessed the overall pain associated with arthritis. Scores for each subscale were normalized to a 0-10 scale; a higher score was indicative of poorer outcomes. The AIMS2 is a reliable and valid scale for assessing the overall impact of arthritis-specif-

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ic symptoms. In the original validation study, the Cronbach’s alpha coefficients for each scale ranged from 0.72 to 0.91 and 0.74 to 0.96 in individuals with rheumatoid arthritis and osteoarthritis, respectively.22 Self-efficacy for exercise. A 5-item scale, examining one’s confidence in performing exercise in the presence of barriers was used to measure barriers self-efficacy for exercise.23 For each question, participants ranked their confidence using a 7-point Likert Scale (not confident = 1 to very confident = 7). The average score for the 5 questions was calculated. This scale has demonstrated good test-retest reliability (0.90) and internal consistency ranging from 0.7623 to 0.8424 in previous studies. Participants’ confidence in their ability to engage in regular exercise was assessed using the 3-item Lorig self-efficacy for exercise scale.25 Specifically, the Lorig scale assesses participants’ confidence to engage in strength and flexibility exercise, aerobic exercises, and to exercise without making their arthritis symptoms worse. Participants indicated their level of certainty using a 10-point Likert scale (not confident at all = 1 to totally confident =10). The average score for the 3 questions was calculated. In a study with 478 individuals, the Lorig self-efficacy for exercise scale had good test-retest reliability (0.86) and the Cronbach’s alpha for internal consistency was 0.83.25 Social support for exercise. A 5-item scale was used to measure the role of social support from family or friends in relation to exercise behaviors.26 Participants rated their level of agreement regarding the support they receive from their family and friends for PA using a 4-point Likert scale (Strongly Disagree = 1 to Strongly Agree = 4). The average score for the 5 questions was calculated. In a previous validation study with women, the scale had an internal consistency of 0.70 and a test-retest reliability of 0.40 using Cohen’s Kappa.26 Outcome expectations for exercise. Outcome expectations regarding people’s beliefs about the benefits they will obtain from exercising were measured using a 9-item scale.27 Participants were asked to rate the level to which they agree exercise affects their health using a 5-point Likert scale (strongly disagree =1 to strongly agree =5). The average score for the 9 questions was calculated. In a large sample of 175 older adults, the Cronbach’s alpha for this scale was 0.89.27 Neighborhood walkability. The Neighborhood Environment Walkability Scale-Abbreviated (NEWS-A) was used to assess individuals’ perceptions about his or her neighborhood environment.28 Derived from the longer Neighborhood Environment Walkability Scale (NEWS), the NEWS-A includes 54 questions measuring residential density (which was not assessed in the present study), land-use mix diversity, land-use mix access, street connectivity, infrastructure and safety for walking, aesthetics, traffic hazards and crime. The NEWS-

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Figure 1 Participant Recruitment and Flow

Interested Participants (N = 300) Unable to contact (N = 9)

• Participants Screened for Eligibility (N = 291)

• •

No diagnosis of arthritis (N = 26) Not interested (N = 14) Unable to contact (N = 7)

•

 

•

Eligible Participants Mailed Survey (N = 244)

Returned Surveys (N = 215)

• • •

Surveys not returned (N = 29)

•

Excluded from analyses due to incomplete survey (N = 10)

Participants included in analyses (N = 205)

A was scored using the individual-level subscale scoring recommended by Cerin et al.28 Land use mix-diversity was scored from 1 to 5 (1 to 5 minutes = 1 to 31 or more minutes = 5). Participants also could check “don’t know” for the walking distance and this was coded as a 5. Responses were then reverse coded. All other subscales on the survey were scored from strongly disagree (1) to strongly agree (4). A higher score indicated more favorable environmental conditions and higher walkability for all subscales except safety from traffic and crime. For these subscales, a higher score indicated less safety from traffic and crime, respectively. The NEWS survey has been validated in previous research.29-31 In a validation study comparing the NEWS and the

NEWS-A surveys, Cerin et al28 found the inter-factor correlation between the surveys ranged from 0.82 and 0.98 for the block group level and 0.83 and 0.97 for the individual level group. Availability of exercise programs. Participants were asked 2 questions to assess the availability of exercise programs for individuals with arthritis. Participants were asked if there were “fitness centers or senior centers that offer PA programs for people with arthritis within a mile of my home.” Similarly, they were asked if there were “water aerobics programs for people with arthritis (2 separate questions) within a mile of my home.” Participants responded using a 5-point Likert scale (1=Strongly Agree to 5 = Strongly Disagree).

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Correlates of Physical Activity among Blacks and Whites with Arthritis

Table 1 Sample Socio-demographic Characteristics by Physical Activity (PA) Status (N = 205)

Variable Age (years)

Full Sample N (%) or Mean (SD)

Meets Aerobic PA Recommendations N (%) or Mean (SD)

Does not meet Aerobic PA Recommendations N (%) or Mean (SD)

χ2 or value of t

p-value

67.4 (10.1)

65.4 (10.0)

68.3 (10.0)

1.45

.07

0.21

.64

4.98

.03

6.84

.03

1.47

.69

5.5

.06

4.28

.23

9.56

.03

Sex Female

176 (86.7)

51 (29.0)

125 (71.0)

Male

27 (13.3)

9 (33.3)

18 (66.7)

Ethnicity Non-Hispanic White

119 (58.1)

42 (35.3)

77 (64.7)

Non-Hispanic Black

86 (41.9)

18 (20.9)

68 (79.1)

$0-29,999

72 (41.9)

13 (18.1)

59 (81.9)

$30,000-59,999

58 (33.7)

16 (27.6)

42 (72.4)

>$60,000

42 (24.4)

17 (40.5)

25 (59.5)

Income per year

Education Less than HS

22 (11.3)

7 (31.8)

15 (68.2)

HS graduate or GED

21 (10.8)

5 (23.8)

16 (76.2)

Attended some college

69 (35.4)

18 (26.1)

51 (73.9)

College graduate or higher

83 (42.6)

28 (33.7)

55 (66.3)

57 (28.9)

21 (36.8)

36 (63.2)

Employment Status Full or part-time Unemployed or homemaker

21 (10.7)

8 (38.1)

13 (61.9)

Retired

119 (60.4)

26 (21.9)

93 (78.1)

Marital Status Married/living with a partner

87 (43.1)

32 (36.8)

55 (63.2)

Divorced/ separated

49 (24.3)

12 (24.5)

37 (75.5)

Widowed

39 (19.3)

9 (23.08)

30 (76.9)

Never married

27 (13.4)

6 (22.2)

21 (77.8)

Underweight

17 (8.4)

5 (29.4)

12 (70.6)

Normal

51 (25.1)

22 (44.0)

28 (56.0)

Overweight

51 (25.1)

15 (29.4)

36 (70.6)

Obese

84 (41.4)

16 (19.1)

68 (80.9)

BMI

Data Analysis Statistical analyses were performed using SPSS statistical software (version 21.0, IBM Corporation, Armonk, NY). Descriptive statistics were performed for the entire sample and by PA level. Bivariate analyses were used to examine differences in potential correlates of PA by PA level. Specifically, chi-square tests were used to examine differences by PA level for categorical variables and t-tests were used to assess differences by PA level

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for continuous variables. All data were tested for normality prior to any analyses. Multiple logistic regression analyses, adjusted for socio-demographic variables, were performed to examine correlates of PA. Variables that were significantly associated with meeting the PA recommendation in bivariate analyses were entered into the multiple logistic regression analyses. To avoid multicollinearity, variables that were strongly associated with one another were excluded. In-

Der Ananian et al come was omitted because it was strongly associated with education. Likewise, marital status was excluded due to its association with age and ethnicity. Finally, due to strong correlations (r >.60) among the Lorig self-efficacy for exercise, barriers exercise self-efficacy, and exercise outcome expectations, only the Lorig self-efficacy for exercise scale was included. A stepwise, forward logistic regression analysis was performed to examine which variables were the best predictors of PA in this population. For all analyses, a significance level of p < .05 was considered significant. RESULTS Figure 1 shows participant flow through the study. We screened 291 individuals for eligibility and initially excluded 47 participants for not having a diagnosis of arthritis (N = 26), a lack of interest in participation (N =14), and unable to contact (N = 7). Of the 244 eligible participants who were mailed surveys, 215 participants returned the survey (88.1% return rate). An additional 10 surveys were excluded from data analyses due to incomplete surveys (>25% missing data) resulting in a final sample size of 205 participants (84.0 % completion rate). Table 1 provides a description of the baseline characteristics of the entire sample and by PA level. The majority of the sample was at least 65 years old (58.3%), female (86.8%), NHW (58.1%) and had a fairly high education level with 78.0% reporting either attending some college or attaining at least a baccalaureate degree. Nearly 42% of the sample reported earning an annual income of less than $30,000 per year. Nearly 30% of the sample met the ACSM-AHA guidelines for moderate-to-vigorous aerobic PA (at least 5 days per week for at least 30 minutes per day of moderate intensity PA or 3 or more days per week of vigorous intensity PA for at least 20 minutes per day). The proportion that met these guidelines differed by ethnicity. Only 20.9% of NHB individuals met the ACSM-AHA guidelines compared to 35.3% of NHW individuals (χ2 1 = 4.98, p = .03). Nearly 28% of the sample engaged in strength training on at least 2 days per week and there were no differences in the proportion who met the strength-training recommendations by ethnicity (NHW 32.9% versus NHB: 20.8%, p = .09). A larger proportion of individuals that reported an income of greater than $60,000 (p < .05) met the PA recommendations. Likewise, a larger proportion of individuals that reported a normal weight BMI met the PA recommendations than overweight or obese individuals (p = .03). In bivariate analyses (Table 2), several psychosocial variables were associated with meeting the recommendations. Persons who met the recommendations for PA reported higher self-efficacy for exercise (t202 = 2.86, p < .0001) and self-efficacy for overcoming barriers to exercise (t207 = 2.91, p < .01), and lower outcome expectations for exercise (t200 = 2.33, p = .02) . A smaller proportion of indi-

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viduals that saw a physician in the past year and did not receive advice to exercise reported meeting the recommendations for PA (10.3%) than did those who saw a physician and received advice for PA (30.9%) or did not see a doctor in the past 12 months (37.5%; χ2 = 9.48, p < .01). Individuals who reported lower perceived safety from crime (t203 = 2.15, p < .03) or lower perceived safety from traffic concerns (t201 = 2.65, p < .01) were less likely to report meeting the PA recommendations. In multiple logistic regression analyses adjusting for socio-demographic characteristics (Table 3), the only significant predictors of meeting the recommendations were self-efficacy for exercise and receiving advice from a physician to exercise (p < .05). The full model had a Cox and Snell R squared of 0.22 and a Nagelkerke R Square of 0.31. These findings were confirmed in a stepwise forward regression analysis. In the stepwise regression model, visiting a doctor and not receiving advice to exercise was associated with an 88% reduction (OR= 0.12, 95% CI: 0.03 – 0.56) in the odds of meeting the recommendations compared to individuals who had not seen their healthcare provider in the past year, and a one point increase in self-efficacy for exercise was associated with a 64% increase in the odds of meeting the recommendations (OR = 1.64, 95% CI: 1.28 – 2.10). DISCUSSION Consistent with the literature for individuals with arthritis 13,14,32 the present data suggest the majority of individuals with arthritis, regardless of ethnicity, are not meeting the ACSM-AHA recommendations for PA. In the present study, a significantly larger proportion of NHB individuals did not meet the aerobic PA guidelines compared with NHW individuals. However ethnicity was not an independent predictor of meeting the aerobic PA guidelines once other socio-demographic, health-related, psychosocial, and environmental factors were considered. Additionally there were no differences by ethnicity in meeting the recommendations for strength training. Enhancing participation in PA by people with arthritis has the potential to reduce the health burden associated with it. Identifying effective intervention strategies and messages promoting PA is necessary to improve exercise adoption and maintenance in this population. Our findings suggest that ethnicity in and of itself is not the critical determinant of PA participation. Instead, our findings suggest that other factors associated with ethnicity such as education, income level, or physical environment may confound this relationship. In our study, NHB individuals had significantly lower levels of education and income than did NHW individuals (data available upon request). This disparity in education and income levels may contribute to the gap in PA levels between Whites and persons of other ethnicities. Shih et al13 demonstrated that lower levels of education are associated with a reduction in PA. Likewise, in a

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Table 2 Comparison of Psychosocial and Health-related Characteristics between Those Who Meet the Recommendations and Those Who Do Not (N = 205) Meets the Recommendations for Aerobic PA M (SD)

Does Not Meet the Recommendations for Aerobic PA M (SD)

t-test

p-value

Self-efficacy

4.98 (1.50)

4.28 (1.60)

2.91

< .01

Social support

2.35 (0.56)

2.33 (0.66)

0.19

.85

Outcome expectations

1.69 (0.54)

1.90 (0.59)

2.33

.02

Lorig SE for exercise

8.46 (2.03)

6.97 (2.51)

2.86

< .0001

9.48

< .01

Variables Psychosocial Characteristics

MD Advice for Exercise Saw MD, received no advice

4 (10.3)

35 (89.7)

Saw MD, received advice

26 (30.9)

58 (69.1)

Did not see MD in year prior

30 (37.5)

50 (62.5)

Physical function

1.46 (1.33)

2.05 (1.67)

2.44

.02

Affect

3.21 (1.58)

3.09 (1.73)

0.49

.62

Symptom

4.80 (2.40)

5.37 (2.58)

1.47

.14

Social interaction

4.00 (1.80)

4.39 (1.87)

1.38

.17

Land-use mix-diversity

2.40 (0.88)

2.29 (0.88)

0.71

.48

Land-use mix-access

3.05 (0.97)

2.78 (0.93)

1.80

.07

Street connectivity

3.02 (0.86)

3.03 (0.85)

0.09

.93

Pedestrian and cycling infrastructure

3.09 (0.57)

3.17 (0.60)

0.83

.41

Aesthetics

AIMS2a

Environmental Characteristics

3.31 (0.71)

3.21 (0.62)

1.04

.29

b

2.16 (0.71)

2.44 (0.66)

2.65

< .01

Crime safety b

1.80 (0.89)

2.11 (0.92)

2.15

.03

Fitness program availability

1.76 (1.08)

1.93 (1.14)

0.97

.33

Traffic safety

Note. a = All subscale scores from the AIMS2 are normalized to a 0-10 scale; a higher score indicates a poorer outcome. b = A higher score indicates a lower level of perceived safety

study by Abell et al,33 individuals who earned an income less than $25,000 were less active than those who earned incomes greater than $25,000. Whereas several individuals in the present study were retired, many still were working full- or part-time and earning less than $30,000 annually and having a lower income is associated with lower levels of PA. Income may influence participation in PA through access to programs and lower income individuals may also reside in neighborhoods that are less safe for PA. These factors must be taken into consideration when designing interventions to increase PA in people with arthritis to enhance success. Recent data suggest that arthritis is a barrier to PA among obese individuals.34 Obesity is also a well-established risk factor for the development

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and progression of osteoarthritis.35-37 In the present study, obesity was associated decreased participation in PA in bivariate analyses. The relationship between PA and obesity in arthritis may be cyclical; higher levels of obesity may place obese individuals at increased risk for developing arthritis-related mobility limitations, which may contribute to decreased PA levels, and which may promote additional mobility limitations. PA is beneficial for maintaining a healthy body mass and improving physical function in people with arthritis,8,10,11 yet access to arthritis specific PA programs may be a limitation. Expanding the availability of evidencebased PA programs for arthritis may be necessary for improving health outcomes in this population.6 Results of this study showed that self-efficacy

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Table 3 Odds Ratio Estimates from Results of Multiple Logistic Regression Analyses for Meeting the Physical Activity Recommendations (N = 160) Variable

OR (95% CI)

p-value

0.97 (0.92 – 1.02)

.22

Socio-demographic Characteristics Age Sex Male

REF

Female

1.09 (0.33 – 3.55)

.89

Ethnicity Non-Hispanic Black

REF

Non-Hispanic White

1.61 (0.48 – 5.28)

Education

.44 .32

College grad

REF

Less than high school

3.54 (0.75 – 16.8)

.11

High school grad or equivalent

0.57 (0.09 – 3.50)

.54

Some college

0.80 (0.34 – 2.28)

.80

Employment Status

.75

Retired

REF

Full or part-time Unemployed or homemaker BMI (kg/m2)

1.09 (0.26 – 4.65)

.90

1.52 (0.50 -4.65)

.47

0.96 (0.90 – 1.03)

.25

1.39 (1.05 -1.83)

.02

Psychosocial Characteristics Lorig SE for exercise MD Advice for Exercise

.06

Did not see MD in year prior

REF

Saw MD, rec’d no advice

0.16 (0.03 – 0.83)

.03

Saw MD, rec’d advice

0.56 (0.23 -1.40)

.22

Physical function (AIMS2a)

0.91 (0.62 – 1.33)

.61

Traffic safetyb

0.86 (0.45 – 1.65)

.65

Crime safety

1.14 (0.57 – 2.28)

.71

Environmental Characteristics b

Note. ???Where is the note for a and b below??? a= b=

was a significant predictor of exercise in both bivariate and multiple logistic regression analyses. In the present study, persons who did not meet the recommendations for PA reported significantly lower levels of self-efficacy for exercise and selfefficacy for overcoming exercise barriers than did individuals who met the recommendations. NHB individuals in the present study also had significantly lower levels of self-efficacy than NHW individuals, which may potentially contribute to disparities in PA participation. Our findings are consistent with other research studies. In a study

among African Americans with arthritis, self-efficacy was the most consistent explanatory factor for PA participation.38 Similarly, in a review of the correlates of exercise participation in people with arthritis, self-efficacy was consistently associated with increased PA.15 PA interventions targeting self-efficacy have been successful at improving PA levels among individuals with arthritis.9,39,40 Collectively, these findings suggest a need to target self-efficacy for exercise and overcoming barriers to exercise to increase PA among people with arthritis, particularly in the NHB population.

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Correlates of Physical Activity among Blacks and Whites with Arthritis Physician advice for exercise has the potential to be a powerful tool for PA promotion among individuals with arthritis. Nearly one in 5 participants in this study indicated that they did not receive any advice to exercise from their physician and this lack of advice was associated with a decreased likelihood of meeting the PA recommendations in comparison to individuals who did not see their physician in the past year. A possible explanation for this finding is that individuals who had not seen their physician in the past year were healthier and more likely to exercise, whereas those visiting their physicians were experiencing more health concerns. The literature is conflicting on the effectiveness of exercise advice by healthcare professionals for people with arthritis.41-43 Individuals may fear exercising due to exacerbating the symptoms of arthritis.44,45 Hence, patients may look to HCPs to provide them with education about the benefits of exercise for arthritis and which exercises are safe and appropriate for their condition prior to engaging in an exercise program. Physical function is important for maintaining independence as one ages and arthritis is known to cause physical function impairment. Physical activity participation in people with arthritis is associated with higher levels of physical functioning.46 In the present study, physical functioning was only associated with PA in bivariate analysis and this may be because NHB individuals and those with lower income and education levels also reported lower levels of physical function. Helping people with arthritis understand the relationship between PA and mobility limitations might be a salient message for those experiencing arthritisrelated mobility limitations. Likewise, it has practical implications for the design of interventions because they may need to be tailored to physical capabilities and use modifiable exercises. In regards to perceptions about neighborhood walkability, a lack of perceived safety from neighborhood crime and traffic were negatively associated with meeting the recommendations for PA in bivariate analyses, but not in multiple regression analyses. Income and ethnicity were both strongly associated with perceived safety from crime and traffic in the present study with NHB individuals and lower income individuals perceiving their neighborhoods as less safe. This may explain why we only observed the association between PA and neighborhood characteristics in bivariate analyses. Other research has shown that residents of low-income neighborhoods perceive their neighborhood environments as less favorable for PA and this disparity applies to neighborhoods with high and low walkability.47 Strategies to improve equity and access to health promoting environments are warranted. Some practical strategies for enhancing safety concerns and improving PA include walking clubs with police escorts or patrols or enhanced availability of indoor exercise programs within higher crime neighborhoods. Related to this, there

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is a growing recognition of the need to increase evidence-based arthritis-specific exercise programs in community settings to enhance exercise participation in people with arthritis,6 and this may be particularly relevant for people who perceive their environment as unsafe. Increasing availability and access to these programs would provide a safe place to exercise. Limitations This study had a number of limitations. A convenience sample of older, community-dwelling older adults was used and this may limit the generalizability of our findings. The study used a cross-sectional design, which limits our ability to determine causality and reduces the likelihood that all confounders were controlled. Consistent with survey research, self-reported measures were used for all the independent and dependent variables. As such, participants may have over-reported their PA level and responses could have been biased by social desirability. Lastly, the sample that was recruited was relatively small and did not sample neighborhoods with diverse walkability and recreation environments in the region. Participants responded to advertisements in a community setting and volunteered to participate in this study. As a result, the study population may not be a realistic representation of the general population. It was, however, a sample that was fairly diverse in terms of socio-demographic characteristics and had a relatively large percentage of NHB participants. Conclusions Despite their limitations, our findings indicate self-efficacy for exercise is an important correlate of PA in people with arthritis and enhancing selfefficacy may be vital for increasing PA participation among individuals with arthritis. Importantly, after controlling for other socio-demographic, psychosocial, arthritis-related, health-related, and environmental correlates of PA, ethnicity was not associated with meeting PA recommendations, suggesting that other variables contribute more substantially to differences in participation in PA than ethnicity. NHB individuals in this study reported higher BMI levels, lower education and income, lower selfefficacy for exercise and self-efficacy for overcoming barriers, greater physical impairments, and lower walkability ratings for some aspects of the environment, all of which were associated with PA participation in bivariate analyses. Local gyms and fitness facilities could play a pivotal role in reducing some of the burden from arthritis by offering arthritis-specific programs throughout the day. Finally, physicians may play a pivotal role in influencing PA participation by engaging patients in discussions about PA and assisting them to become more active. Human Subjects Statement The Institutional Review Board at the University

Der Ananian et al of Illinois at Chicago approved the study and the Institutional Review Board at Arizona State University approved secondary data analysis. All participants provided informed consent for participation in the study.

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Conflict of Interest Statement The authors have no conflicts of interest to report. Acknowledgments This study was funded through a sub-award from Midwest Roybal Center for Health Promotion, 5P30AG022849-05. We thank all of the participants for their time and effort in this study. We also thank Dan Diaz for his assistance with data collection and Dr Thomas Prohaska and Dr Susan Hughes for their mentorship on this project. References

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