Stroke causes substantial morbidity and mortality, and physical activity can reduce the risk of stroke occurrence. The purpose of this study was to test the association between biopsychosocial factors and levels of physical activity and to develop a model to predict inactivity for US stroke survivors. A quantitative, cross-sectional analysis was performed of the 2013 National Health Interview Survey (NHIS), which is a representative sample of US households. Association for 1,077 stroke survivors was tested with chi-square between physical activity and independent variables: biological factors (age, sex, race, body mass index, musculoskeletal conditions, and cardiovascular diseases), psychological factors (mental distress, perception of health), and sociological factors (income, health provider contact, family structure, neighborhood, region, marriage, and education). Multiple variable logistic regression was weighted and adjusted for a complex sampling design. Independent associations were found among biopsychosocial variables. A multiple logistic regression model demonstrated statistically significant variables of older age (OR 6.1, 95% CI 2.1 to 17.6), poor perceived health (OR 4.6, 95% CI 3.0 to 6.8), lower levels of education (OR 2.8, 95% CI 1.5 to 5.0) and living in the Northwest (OR 2.2, 95% CI 1.2 to 4.1) or Midwest region (OR 1.6, 95% CI 1.0 to 2.7), predicting the likelihood of inactivity for stroke survivors. This biopsychosocial model may contribute to positive social change by identifying stroke survivors at risk for inactivity and directing interventions and supportive care. Targeting those most at risk and increasing activity could help to reduce morbidity and mortality among stroke survivors, which could improve their lives and the lives of their families and communities.
| Identifer | oai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-3001 |
| Date | 01 January 2016 |
| Creators | Johnson, Claire |
| Publisher | ScholarWorks |
| Source Sets | Walden University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Walden Dissertations and Doctoral Studies |
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