We Run a Regression Model Using GSS2006 Data and Find

We run a regression model using GSS2006 data and find out that the older one is, the higher he/she scores on an index of religiosity (where 0=not religious up to 9=very religious) . Then, we hypothesize that, because women outlive men, and because women are typically more religious than men are, part of this age effect is actually due to sex. We run a second model in which we add a variable for sex:
$\begin{array}{lcc}\text { Independent Variable } & \text { Model 1 } & \text { Model 2 } \\\text { Age (in years) } & .03 * * * & .03 * * * \\\text { Sex }(\mathrm{F}=0, \mathrm{M}=1) & --- & -.93 * * * \\\text { Constant } & 4.23 & 4.65 \\\text { R-Squared } & .04 & .07 \\\mathrm{n} & 2912 & 2912\end{array}$ Which of the following is the most appropriate interpretation of what is going on here?

A) Sex clearly has a larger effect than age, so our hypothesis is supported.
B) The value of R-Squared rises, so our hypothesis is supported.
C) The effect of age does not change, so our hypothesis is not supported.
D) The constant increases, so our hypothesis is not supported.