Physical activity behavior after total hip arthroplasty (THA): a prediction based on patient characteristics

Patient Educ Couns. 2007 Dec;69(1-3):196-9. doi: 10.1016/j.pec.2007.08.012. Epub 2007 Oct 29.

Abstract

Objective: To determine to what extent aspects of patient characteristics (age, gender, family status, education and comorbidity) are predictive for the level of physical activity of persons with a total hip arthroplasty (THA).

Methods: A cross-sectional study including 372 patients. Demographics, comorbidity and physical activity behavior were assessed by means of a questionnaire and from medical records. Linear regression analysis was used to determine to what extent patient characteristics are predictive of level of physical activity. Binary logistic regression modeling was used to determine the extent to which patient characteristics are predictive in meeting international guidelines on health-enhancing physical activity.

Results: Age, education and family status significantly predict level of physical activity (R(2)=0.19). Only gender significantly predicts meeting international guidelines on health-enhancing physical activity (OR=2.06, 95% CI 1.20-3.54).

Conclusion: Patients at risk can be identified by means of patient characteristics. Increasing age, lower education and living alone are associated with a physically inactive lifestyle.

Practice implications: Health care workers involved in the treatment of THA patients should lay an emphasis on the beneficial aspects of physical activity.

MeSH terms

  • Aged
  • Analysis of Variance
  • Arthroplasty, Replacement, Hip* / psychology
  • Arthroplasty, Replacement, Hip* / rehabilitation
  • Comorbidity
  • Cross-Sectional Studies
  • Educational Status
  • Exercise Therapy*
  • Female
  • Geriatric Assessment / methods*
  • Guideline Adherence
  • Health Behavior
  • Humans
  • Linear Models
  • Logistic Models
  • Male
  • Middle Aged
  • Models, Psychological
  • Netherlands
  • Patient Compliance / psychology*
  • Patient Compliance / statistics & numerical data
  • Patient Education as Topic
  • Predictive Value of Tests
  • Residence Characteristics
  • Risk Assessment / methods
  • Self Care / psychology*
  • Surveys and Questionnaires