In causal inference terminology, if the study was randomized then age and weight (covariates not affected by your treatment) are not expected to be confounders by design.
When you successfully randomize, your treatment assignment is unconfounded, and you can measure the average treatment effect without adjusting for any other covariates. In experiments, you usually adjust for other covariates to (i) improve precision and/or (ii) estimate conditional effects or direct effects --- but not for control of confounding. As a matter of fact, regression adjustment in experiments might have unintended consequences if you are not careful, see for instance here.
In your case I just noticed that you also mention "duration of smoking", which seems to be something affected by your treatment. This is definitely not a confounder, it is either another outcome of interest or a mediator, so you should not mindlessly adjust for it in your regression before defining what your target effect of interest is and writing down your causal model.
To sum up, when you say certain variables are confounders this has a very specific meaning in causal inference: you are claiming that your randomization procedure was not successful and these variables not only affect your outcome, but somehow also influenced treatment uptake (also, you are claiming that these variables are not mediators). That is, you would be claiming that one needs to adjust for these covariates to get consistent estimates of your treatment.
Finally, if this is just a homework question and you do not fully understand causal inference yet, here is a simplified version --- for your case "duration of smoking" and the "number of cigarettes smoked" are either "dependent" variables or "outcomes" or "mediators", since they are affected by your treatment; whereas "age" and "weight" are independent variables (not confounders), they are not affected by your treatment nor they have affected your treatment (assuming randomization) but they may affect your "dependent variables" (your outcomes/mediators) of interest. None of the covariates are confounders under randomization.