Here is a really quick tip for making the statistics and outputs of SPSS much easier to interpret when using dichotomous predictor and outcome variables. Whatever "level" of the dichotomy that you are most interested in should be codified as a "1." If a participant has the characteristic or outcome of interest, codify those observations as "1" and the absence of the characteristic or outcome of interest as "0."  

SPSS has a default that always makes the highest numerical category be the reference group. However, most times, researchers want to know the odds of something occurring versus not occurring, NOT the odds of something not occurring versus the odds of it occurring. Therefore, it is important when running bivariate associations between dichotomous categorical variables to always use the codification scheme above so that the statistical outputs can be interpreted properly.

When conducting multivariate analyses, SPSS still uses the same reference default for the highest number category. The "point and click" interface for multivariate statistics in SPSS gives you the option to click on a "Categorical" button. Always do this and make sure that you set the category to "first" when running these types of statistics.