In the green table you're comparing the average of men and of women to the average of the third category in the Gender variable ("U"). Maybe there's a difference between men and women but not between either men or women and the U category (esp. if the sample size of the "U" is small). The test for gender in the blue table is a 2-degree-of-freedom test, whereas each test in the green table is a 1-degree-of-freedom test.
In other words, they're not the same tests at all. The green table tests the average difference between Men and U, and between Women and U; the blue table tests the increase in model fit when adding the gender variable to your model (i.e. whether adding gender to your model increases the accuracy of your predictions).