How to Interpret different odds ratio results into words- output from Proc logistic and glimmix

[fastandcurious]

Hello,

I created different statistical models using demo data and need help interpreting/wording the odds ratio/output from Proc logistic simple terms. I have models with and without interactions. I appreciate any input as I am still learning to read output correctly. There are so many different ways to get Odds ratios that I worry about reading it incorrectly or am missing a step when it comes to inverted values.

Proc Logistic: Interaction Model Questions:

I used the exponentiated values from the Estimate value  from the Analysis of Maximum Likelihood Estimates table, to calculate the Odds ratio (OR)

1.  If I exponentiate , 0.2888 (for the interaction Race*SomeCollege Hispanic Yes and get 1.33,can I say that Hispanic women who attended some college were 33% more likely to have infants with low birthweight, compared to White women who did not attend college?
2. If I  exponentiate an inverse value such as -0.2205, and get 0.802, do I substract from 1 and say: Hispanic women  were ~20% less likely to have infants with low birthweight, compared to White women.
3. For the estimate table (Exp=1.9422), can I say, Black women who did not attend college were 94% more likely to have infants with low birthweight, compared to White women who did not attend college?

proc logistic data=Sashelp.Birthwgt plots(only)=(effect oddsratio) ;
class race (ref="White")somecollege(ref="No")/param=ref;
model LowBirthWgt (event="Yes")=somecollege|race/ clodds=pl selection=backward;
estimate 'Black, no college' race 0 1 somecollege 0/exp;
run;

Questions from a simple Logistic Model with No Interactions :

1. Using the Odds Ratio Estimates table- Can I say women who went to college, were 82% less likely to have low birth weight infants, than women who did not attend college? Or would it be, 18% because I have to subtract from 1?

proc logistic data=Sashelp.Birthwgt plots(only)=(effect oddsratio) ;
class race (ref="White")somecollege(ref="No")/param=ref;
model LowBirthWgt (event="Yes")=somecollege race/ clodds=pl selection=backward;
run;

Lastly, I am using Proc glimmix for the first time.

1.  Are the groups being compared with eachother both groups who attended some college? 
2. For the odds ratio here, do I need to substract from 1 for inverted values? For example, if the OR is .802 is that comparison 80% less likely or or 20% less?

proc glimmix data=Sashelp.Birthwgt;
class race (ref="White") somecollege(ref="No");
model LowBirthWgt (event="Yes") = somecollege*race/ dist=binary;
lsmeans somecollege*race / slicediff=somecollege oddsratio ilink;
run;

I apologize in advance for the long post, if it's better to break up the questions in the future, please advise. I  learn best by seeing examples and annotated output, which I've had difficulty finding for this. Any recommendations on resources like this are welcome. Thank you for helping out a rookie!

[StatDave]

See this note on computing and interpreting odds ratio estimates in a model with interaction. It discusses both LOGISTIC and GLIMMIX. It shows multiple ways to compute odds ratios in PROC LOGISTIC. In short, you do not exponentiate interaction parameters - an interaction means that the effect of one variable depends on the level of the other regardless of the type of model. So, in a logistic model, you need to compute odds ratios for one variable at given levels of the other. An odds ratio estimate of, say, 2 means that the odds of the event for the group in the numerator is twice the event odds for the group in the denominator. If you want to interpret it as a percent change from the denominator group, use the odds ratio minus 1 and then multiply by 100.

[fastandcurious]

Thank you for the link- do you know if there  there are any other resources with more examples by any chance?