Table 3.
Linear Regression Model Estimating the Adjusted Effect of Time Sitting /Day on CESD Depression (n = 315).
| Predictor | CESD ba (95% CI)b |
|---|---|
| Years Age | .03 (−.07; .14) |
| Gender | −05 (−.25; .16) |
| Ethnicity (Caucasian) | −16 (−.44; .12) |
| Educational Attainment | −18** (−.28; −07) |
| Employed (Yes) | −18 (−.43; .07) |
| SF-12 Physical Function | −23** (−.35; −12) |
| Moderate+ Activity (Yes) | .13 (−.08; .34) |
| Minutes Sitting / Day | .16** (.05; .27) |
| Intercept | .14 |
| Model Fit | R2 = .168 F8,305 = 9.91, p < .001 |
*
p < .05;
**
p < .01
a
Coefficients for continuous predictors are fully standardized, coefficients for categorical predictors are y-standardized.
b
Confidence interval estimates and tests of significance are based on robust (Huber-White) variance estimators