# Omited variable bias clarification

Let’s say we have a true model for health that goes $$h=c+bw+di+u$$ where w is weight and i is income. Now this means that holding weight constant a one unit change in income on average causes a d unit change in health. Now let’s assume income and weight are correlated. We we regress health on only income we will get a larger coefficient estimate. Now this is generally referred to as omitted variable bias. But I don’t see where the bias is. Isn’t the coefficient just larger because we are not holding weight constant? Isn’t this model just as valid?

Edit: let me try to clarify my question. Let’s say due to leaving out weight in our regression our estimate for the income coefficient is too large due to OVB. Too large compared to what? The coefficient is correctly telling me what the difference in expected health is between two people if all I know is that they have a one unit difference in income? What is the correct coefficient supposed to tell me?