I’ve never seen a paper that does an age and sex adjustment when attempting to show descriptive statistics for baseline distributions. That’s not to say that it doesn’t have meaning; it’s just unconventional. It also depends on whether you are wanting to adjust to an external population distribution (which would require a lot more information) or to adjust to a single value of age and sex.
Showing baseline characteristics stratified by Y (in your case diabetes status) is a common way to present data and it is highly problematic. That is because you are switching the roles of independent and dependent variables, make diabetes the sole independent variable. Always treat dependent variables as dependent variables. Provide real information that is not misleading by replacing Table 1 with https://discourse.datamethods.org/t/should-we-ignore-covariate-imbalance-and-stop-presenting-a-stratified-table-one-for-randomized-trials.