# Logistic Regression Coefficient Interpretation for more than 2 dummy variables

I'm not too sure how to interpret the coefficients of a variable that has more than 2 levels. Please note that my model contains explanatory variables that are numeric, binary, and with multiple category

Given that my response variable $$0 = \text{no late debt payment} , 1 = \text{has late debt payment}$$ and one of my x variables in the model is education level given by: $$1 = \text{no high school diploma/GED} \\ 2 = \text{has high school diploma/GED}\\ 3 = \text{some college education}\\ 4 = \text{College education.}$$

So, in the R glm output (family = "binomial), the coefficients for the dummy variables are: $$\text{EDCL2}= 0.48430 \\ \text{EDCL3}= 0.89571 \\ \text{EDCL4}= 0.45851 \\ ...$$

After exponentiating them, they are : $$\text{EDCL2}= 1.56 \\ \text{EDCL3}= 2.36 \\ \text{EDCL4}= 1.38 \\ ...$$

So my interpretation is as follows:

EDCL2: Implies that a respondent that has completed high school education is about 1.56 times as likely to have a late debt payment as a respondent that has NOT completed high school.

EDCL3: Implies that a respondent that has some college education is about 2.69 times as likely to have a late debt payment as a respondent that has NOT completed high school.

EDCL3: Implies that a respondent that has some college education is about 1.38 times as likely to have a late debt payment as a respondent that has NOT completed high school.

Is this interpretation correct? I know that it may be more complex than that and what would be the right way to interpret this data? Any help is appreciated. THANK YOU!