ENVIRONMENTAL CORRELATES OF PHYSICAL ACTIVITY IN PERSONS WITH - - PDF document

ENVIRONMENTAL CORRELATES OF PHYSICAL ACTIVITY IN PERSONS WITH MULTIPLE SCLEROSIS

Stephanie L. Silveira & Robert W. Motl Exercise Neuroscience Research Lab Department of Physical Therapy

BACKGROUND Benefits of physical activity in MS

(Motl & Pilutti 2012)

GUIDELINES FOR PHYSICAL ACTIVITY

(Latimer-Chung et al., 2013)

BACKGROUND Rates of physical activity (MVPA)

80%

(Klaren et al., 2013)

SOCIAL COGNITIVE THEORY

(Bandura, 2004)

SOCIAL ECOLOGICAL MODEL

Individual Policy Social Environment Built Environment

Sallis, Owen, & Fisher, 2015

BACKGROUND

CURRENT STUDY

Are there hierarchical associations among the built environment, social environment, and individual determinants of physical activity in persons with MS?

HYPOTHESIS

Self-Efficacy Strong Social Support Medium Perceived Built Environment Small

METHOD: PARTCIPANTS & MEASURES

• Persons with MS across the U.S.
• Inclusion: 18 years or older, diagnosis of MS
• Advertised via e-mail from National Multiple

Sclerosis Society list serve

• Online Questionnaire:
• Demographics & Clinical Characteristics
• Built Environment: The Abbreviated

Neighborhood Walkability Scale (NEWS-A)

• Social Environment: Social Provisions Scale

(SPS)

• Self-Efficacy: Exercise Self-Efficacy Scale

(EXSE)

• Physical Activity: Godin Leisure-Time

Exercise Questionnaire (GLTEQ)

(Learmonth et al., 2013; Cerin et al., 2006; Konopack & McAuley , 2012; Motl et al. 2017; Godin & Shepard, 1985)

METHOD: NEWS-A

• Neighborhood Walkability Scale

(NEWS-A)

• Residential density
• Land-use mix diversity
• Land-use mix access
• Street connectivity
• Infrastructure and safety for

walking

• Aesthetics
• Traffic hazards
• Crime

(Cerin et al., 2006)

METHOD: GLTEQ

Godin & Shepard, 1985

METHOD: DATA ANALYSIS

• Spearman’s Rank-Order Correlations for

examining associations among NEWS-A subscales, SPS, EXSE, and GLTEQ

• Hierarchical Linear Regression
• Step 1: regressed GLTEQ with NEWS-A

subscales (built environment)

• Step 2: addition of SPS (social environment)
• Step 3: addition of EXSE (individual

determinant)

PARTICIPANTS

Variable, units (n) Age, years (596) Mean±SD 51.7±12.0 MS Duration, years (610) 13.9±10.0 PDDS, (612) Median(IQR) 2.0(4.0) MS Clinical Course, (612) RRMS Primary Progressive Secondary Progressive n(%) 485(79.3) 42(6.9) 85(13.9) Gender, (611) Female Male 512(83.8) 99(16.2) Marital Status, (610) Married Single Divorced/Separated Widow/Widower 398(65.2) 102(16.7) 90(14.8) 20(3.3) Employed, (611) Y es No 309(49.4) 309(50.6) Race, (611) Caucasian African American Latino/a Other 554(90.7) 25(4.1) 12(2.0) 20(3.2) Note: PDDS= Patient Determined Disease Steps RRMS= Relapsing Remitting Multiple Sclerosis

SPEARMAN’S RANK-ORDER CORRELATIONS HIERARCHIAL REGRESSION: STEP 1

Hierarchical Linear Regression SEM Model Predicting Physical Activity N=594

GLTEQ B SE B β R2 ΔR2 Step 1 NEWS-A Residential Density NEWS-A Land-use Mix Diversity NEWS-A Land-use Mix Access NEWS-A Infrastructure and Safety for Walking NEWS-A Aesthetics

• .01

3.03 5.00

• 2.37

4.17 .01 1.28 1.29 1.25 1.43

• .03

.12* .22***

• .09

.12** .10 .10***

Note: GLTEQ= Godin Leisure-Time Exercise Questionnaire; NEWS-A= The Abbreviated Neighborhood Walkability Scale; SPS= Social Provisions Scale; EXSE= Exercise Self-Efficacy Scale *P <.05, **P <.01, ***P <.001

HIERARCHIAL REGRESSION: STEP 2

Hierarchical Linear Regression SEM Model Predicting Physical Activity N=594

GLTEQ B SE B β R2 ΔR2 Step 2 NEWS-A Residential Density NEWS-A Land-use Mix Diversity NEWS-A Land-use Mix Access NEWS-A Infrastructure and Safety for Walking NEWS-A Aesthetics SPS

• .003

2.69 4.28

• 2.74

3.11 1.56 .01 1.24 1.26 1.22 1.40 .27

• .01

.11* .19**

• .10*

.09* .23*** .15 .05***

Note: GLTEQ= Godin Leisure-Time Exercise Questionnaire; NEWS-A= The Abbreviated Neighborhood Walkability Scale; SPS= Social Provisions Scale; EXSE= Exercise Self-Efficacy Scale *P <.05, **P <.01, ***P <.001

HIERARCHIAL REGRESSION: STEP 3

Hierarchical Linear Regression SEM Model Predicting Physical Activity N=594

GLTEQ B SE B β R2 ΔR2 Step 3 NEWS-A Residential Density NEWS-A Land-use Mix Diversity NEWS-A Land-use Mix Access NEWS-A Infrastructure and Safety for Walking NEWS-A Aesthetics SPS EXSE .004 1.65 1.95

• 1.95

2.73 .28 .36 .01 1.03 1.05 1.00 1.15 .23 .02 .01 .07 .09

• .07

.08* .04 .58*** .43 .28***

Note: GLTEQ= Godin Leisure-Time Exercise Questionnaire; NEWS-A= The Abbreviated Neighborhood Walkability Scale; SPS= Social Provisions Scale; EXSE= Exercise Self-Efficacy Scale *P <.05, **P <.01, ***P <.001

R2 CHANGE

Self-Efficacy .28*** Social Support .05*** Perceived Built Environment .10***

DISCUSSION

• Built environment, social environment, and individual

factors are correlated with physical activity in MS

• Exercise self-efficacy accounts for the majority of

variance in physical activity in this sample

• Aesthetics are also important to consider
• General population literature versus our findings
• Self-efficacy is key in MS
• Correlates of physical activity differ in magnitude self-

efficacy (micro-level) out toward the social and built environment (macro-level)

(Rhodes, Saelens, & Sauvage-Mar, 2018)

LIMITATIONS AND FUTURE DIRECTIONS

• Limitations: Sample from NMSS
• Multi-level physical activity interventions for persons

with MS are needed that incorporate evidence-based behavior change methods to improve exercise self- efficacy

• Social and built environment variables may further

influence exercise behavior and should be addressed in the design of these multi-level interventions

ACKNOWLEDGEMENTS

• Funding was provided from the National Multiple Sclerosis

Society (MB0029)

• Research Participants

REFERENCES

1. Bandura A. Health promotion by social cognitive means. Health Educ Behav. 2004;31:143-64. 2. Cerin E, Saelens BE, Sallis JF, Frank LD. Neighborhood Environment Walkability Scale: validity and development of a short form. Med Sci Sports Exerc. 2006;38:1682-91. 3. Doerksen SE, Motl RW, McAuley E. Environmental correlates of physical activity in multiple sclerosis: a cross-sectional study. Int J Behav Nutr Phys Act. 2007;4:49. 4. Godin G, Shephard R. A simple method to assess exercise behavior in the community. Can J Appl Sport Sci. 1985;10:141-6. 5. Klaren RE, Motl RW, Dlugonski D, Sandroff BM, Pilutti LA. Objectively quantified physical activity in persons w ith multiple sclerosis. Arch Phys Med Rehabil. 2013;94:2342-8. 6. Konopack JF, McAuley E. Efficacy-mediated effects of spirituality and physical activity on quality of life: a path analysis. Health Qual Life Outcomes. 2012;10:57. 7. Latimer-Cheung AE, Ginis KA, Hicks AL, Motl RW, Pilutti LA, Duggan M, Wheeler G, Persad R, Smith KM. Development of evidence- informed physical activity guidelines for adults w ith multiple sclerosis. Archives of physical medicine and rehabilitation. 2013 Sep 1;94(9):1829-36. 8. Learmonth YC, Motl RW, Sandroff BM, Pula JH, Cadavid D. Validation of patient determined disease steps (PDDS) scale scores in persons w ith multiple sclerosis. BMC Neurol. 2013;13:37. 9. Morris KS, McAuley E, Motl RW. Self-efficacy and environmental correlates of physical activity among older w omen and w omen w ith multiple sclerosis. Health education research. 2007 Oct 24;23(4):744-52.

• 10. Motl RW, Balto JM, Ensari I, Hubbard EA. Self-efficacy and w alking performance in persons w ith multiple sclerosis. J Neurol Phys
• Ther. 2017;41:114-8.
• 11. Motl RW, Pilutti LA. The benefits of exercise training in multiple sclerosis. Nature Review s Neurology. 2012 Sep;8(9):487.
• 12. Rhodes RE, Saelens BE, Sauvage-Mar C. Understanding Physical Activity through Interactions Betw een the Built Environment and

Social Cognition: A Systematic Review . Sports Med. 2018;48:1893-1912.

• 13. Sallis JF, Ow en N, Fisher E. Ecological models of health behavior. Health behavior: Theory, research, and practice. 2015 Jul 1;5:43-

64.

THANK YOU!

ssilveira@uab.edu