Agora o Matt Bogard do Econometric Sense dá a dica de como interpretar esse número:
From the basic probabilities above, we know that the probability of event Y is greater for males than females. The odds of event Y are also greater for males than females. These relationships are also reflected in the odds ratios. The odds of event Y for males is 3 times the odds of females. The odds of event Y for females are only .33 times the odds of males. In other words, the odds of event Y for males are greater and the odds of event Y for females is less.
This can also be seen from the formula for odds ratios. If the OR M vs F = odds(M)/odds(F), we can see that if the odds (M) > odds(F), the odds ratio will be greater than 1. Alternatively, for OR F vs M = odds(F)/odds(M), we can see that if the odds(F) < odds(M) then the ratio will be less than 1. If the odds for both groups are equal, the odds ratio will be 1 exactly.
RELATION TO LOGISTIC REGRESSION
Odds ratios can be obtained from logistic regression by exponentiating the coefficient or beta for a given explanatory variable. For categorical variables, the odds ratios are interpreted as above. For continuous variables, odds ratios are in terms of changes in odds as a result of a one-unit change in the variable.