# Odds ratio for poisson regression

Can I compute Odds ratio coefficients and their 95% CI from a Poisson regression (GLM) using the exp function?

I have an ordinal dependent variable (i.e., a GS of a scale) and some independent variables which are either categorial or continuous (e.g., Age, Presence/absence of hypertension ...).

For each variable, in R, I did this:

#Poisson regression
model_name1 <-glm(dependentvariable ~ indepvariable1,
family = poisson(), data=data_name)

#OR and 95% CI
exp(coef(model_name1))
exp(confint(model_name1))


My question is: can estimate the ORs of a poisson regression (as for a logistic binomial regression)? Can I compute it with the function "exp" as I did? Thank you

• Possible duplicate of Log-linear regression vs. logistic regression Dec 15, 2017 at 14:46
• You seem rather confused about what you are trying to do. If the link which @AdamO provides does not sort out your problem can you edit your question to give us more details about what precisely your scientific problem is? Dec 15, 2017 at 14:49

If you have a Poisson regression then exponentiating the coefficients gives you the multiplier corresponding to a unit change in the predictor variable. So if you measure age in years and the coefficient was 0.1 then a difference of one year would correspond to being $e^{0.1} = 1.10$ times higher scoring or about 10% more. It is not an odds ratio. Some software calls it an incidence rate ratio but you do not seem to have an outcome variable for which that interpretation makes much sense.