Abstract

Educational attainment and maximal metabolic equivalencies (METs) are strong predictors of health-related behaviors. Studies suggest educational accomplishment is an important predictor in CR participation rates. PURPOSE: The study aimed to compare age, gender, attended sessions, and METs of college graduate (CG) and non-college graduate (NCG) Phase II CR participants. METHODS: A retrospective comparative design compared 182 participants completing ≥ 12 sessions between November 2012 and September 2015. A Patient Education Assessment Tool, a 9-item educational level questionnaire, was administered at initial CR session. Medical record review collected gender, age, METs, and education. Education was compared to program end METs by age, gender and number of sessions. T-tests and Ordinary Least Squares regression determined statistical significance. RESULTS: 143 males (mean = 64.7 years) and 39 females (mean = 70.7 years) completed an average of 26 sessions. 114 participants were CG (mean = 65.8 years) and 68 NCG (mean = 66.2 years). CGs achieved significantly higher mean METs than NCGs (6.9 vs 6.1 mean METs; t=-2.472; p=0.0145). There is a significant interaction between age and education adjusting for gender. In the adjusted analysis, METs significantly varied with education and age (F = 13.88, p < 0.001). MET levels were significantly lower in NCGs aged ≥ 65 years (t = −2.41, p = 0.017). This finding is significant for men only (t = 3.03, p = 0.003). There was no significant difference between CGs and NCGs in session attendance (t=-0.1209; p=0.903). Significant associations existed between mean METs and age. For every one year increase in age, percent of average METs completed declines 11%, holding education and gender constant (p < 0.001 t = -8.43). CONCLUSION: CGs achieve higher METs than NCGs. Education achievement did not affect sessions attended. Knowledge of education differences can help CR staff develop strategies to meet needs of participants during rehabilitation. Further research is needed to determine effects of other social and economic variables.

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