For instance, if one wants to control for age, sex and education (common confounders) in a linear regression, we don’t have to worry about e.g. age being linearly related to the outcome variable or that the assumption of homoscedasticity is met. I am told that this is supposed to be so because when we control/adjust for confounders we are not necissarily interested in the estimates (beta coefficients) of these variables. Supposedly, violating these assumptions does not affect the estimates of the beta coefficients we are interested in, i.e. other than age,sex,education.

Is it true that we don't have to worry about violating any assumptions when we ust want to control/adjust for? Anybody knows? If true, are there other things we have to have in mind when just controling/adjusting for variables?Thanks a lot!