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 80% Rates of physical activity (MVPA) (Klaren et al., 2013)

SOCIAL COGNITIVE THEORY (Bandura, 2004) SOCIAL ECOLOGICAL MODEL Policy Built Environment Social Environment Individual 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 Perceived Built Environment Small Social Support Medium Self-Efficacy Strong 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) Mean±SD Age, years (596) 51.7±12.0 MS Duration, years (610) 13.9±10.0 Median(IQR) PDDS, (612) 2.0(4.0) MS Clinical Course, (612) n(%) RRMS 485(79.3) Primary Progressive 42(6.9) Secondary Progressive 85(13.9) Gender, (611) Female 512(83.8) Male 99(16.2) Marital Status, (610) Married 398(65.2) Single 102(16.7) Divorced/Separated 90(14.8) Widow/Widower 20(3.3) Employed, (611) Y es 309(49.4) No 309(50.6) Race, (611) Caucasian 554(90.7) African American 25(4.1) Latino/a 12(2.0) Other 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 R 2 ΔR 2 Step 1 .10 . 10*** NEWS-A Residential Density -.01 .01 -.03 NEWS-A Land-use Mix Diversity 3.03 1.28 .12* NEWS-A Land-use Mix Access 5.00 1.29 .22*** NEWS-A Infrastructure and Safety for Walking -2.37 1.25 -.09 NEWS-A Aesthetics 4.17 1.43 .12** 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 R 2 ΔR 2 Step 2 .15 .05*** NEWS-A Residential Density -.003 .01 -.01 NEWS-A Land-use Mix Diversity 2.69 1.24 .11* NEWS-A Land-use Mix Access 4.28 1.26 .19** NEWS-A Infrastructure and Safety for Walking -2.74 1.22 -.10* NEWS-A Aesthetics 3.11 1.40 .09* SPS 1.56 .27 .23*** 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 R 2 ΔR 2 Step 3 .43 .28*** NEWS-A Residential Density .004 .01 .01 NEWS-A Land-use Mix Diversity 1.65 1.03 .07 NEWS-A Land-use Mix Access 1.95 1.05 .09 NEWS-A Infrastructure and Safety for Walking -1.95 1.00 -.07 NEWS-A Aesthetics 2.73 1.15 .08* SPS .28 .23 .04 EXSE .36 .02 .58*** 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

R 2 CHANGE Perceived Built Environment .10*** Social Support .05*** Self-Efficacy .28*** 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