# How does one interpret predictor variables that all show insignificant betas in multiple regression from SPSS output?

I wanted assistance on interpreting SPSS output that I made for my Group Project regarding Eating Habits. We basically made a survey related to eating habits and wrote down the score of each participant in SPSS. We also compared these scores to another group's survey that was related to stress and their scores. We have to analyze betas and p values, basically multiple regression.

Here's what I have written:

From our multiple regression analysis, we derived a beta of -0.260 for the predictor variable called stress scores. This beta of -0.260 implies that stress scores is negatively associated with eating habits scores, such that higher stress scores predicts lower eating habits scores, when controlling for other predictor variables like age and gender. A more meaningful interpretation would be eating habits scores decreased by 0.260 standard deviations for each 1 standard deviation change in stress scores... In conjunction to beta and b, we observed a p value of 0.277 which determines no statistical significance because its value exceeds the significance threshold of 0.05.

I have attached my SPSS output at the very bottom.

My question was: Can I say that...

The relationship between stress scores and eating habits is not significant when controlling for age or gender. OR... The relationship between stress scores and eating habits scores goes away when age and gender are held constant.

                  Standardized Coefficients Beta             Significance
(Constant)
Stress Scores     -0.260                                       0.277
Age                0.055                                       0.811
Gender             0.325                                       0.182


Dependent variable = Eating Habits Scores

What would be a better way to explain the relationship between stress scores and eating habits scores with respect to other predictor variables such as age and gender?