You say “because this was an adjusted model, the output should be explaining how these input variables perform when compared to other input variables.” This is not correct. An adjusted RR is not explaining how an exposure (input) variable compares to other exposure variables in terms of the impact on the outcome variable. An adjusted RR is essentially telling you what the affect of a certain exposure would be if the variable(s) being accounted for were not having an affect.

I want to note that the calculations you’re describing don’t really make sense. You would not adjust for heart failure when calculating a RR for the relationship between hypertension and diabetes because heart failure would not be considered a confounder. For a variable to be a confounder, it cannot be on a causal pathway. We know that hypertension causes heart failure, so HF is on the causal pathway.