How to interpret the intercept in a regression model which has a categorical covariate?

I have a regression model with some response Y and covariates height, weight, age, sex.
Sex is the only categorical covariate and it takes on the value
Sex = 0, for female
Sex = 1, for male

I want to interpret the intercept of this model, that is the estimated mean value of Y when all the covariate coefficients are zero.
But I don’t understand how to view a zero coefficient in front of a categorical variable such as sex. If all coefficients are zero, am I looking at 0 height, 0 weight, 0 age, no sex. Or am I looking at 0 height, 0 weight, 0 age, female, since sex = 0 represents female?

In other words, does sex having a zero coefficient represent no sex or does it represent female?


Less is more. Stay pure. Stay poor.
Represents female, the reference group. You also have to rationalize in your mind such a person does not exist, since it is impossible to have a wt, age, ht of '0'. Many people will standardized the continuous variables before entering them into the model, which would represent the mean of the continuous variables for a females.

Good luck.