Multinomial logistic regression Interpretation

I'm trying to understand the result of the Odds Ratio
model <- multinom(labs~GENDER+Education+Imp,data=mydata)
GENDER = (Man, Woman)
Education = (Primary, Secondary, University)
Imp = (YES, NO)

I have 300 participants in my study, I clustered them in 3 Clusters
So in labs I have for each individual to which Cluster he belongs

In order to calculate Odds Ratios I run
And I get this results

          (Intercept) GENDERWoman EducationSecondary EducationUniversity ImpYES
Cluster 2       2.313       1.847              0.561               0.381          1.094
Cluster 3       1.029       0.824              0.382               0.366          1.136
But I can't figure out how to interpret this results, for example for GENDER = Woman in Cluster 2 I get 1.847, it is higher than 1 so it means that Women are 84,7% more likely to belong to Cluster 2, is this correct?
And when they are lower than zero, for example for Gender = Woman in Cluster 3 I get 0.824 it means that the odds of belong to Cluster 3 are 1/0.824 but what does this mean?