This paper examines the spatio-temporal evolution of individuals aged 80 and over across Italian provinces from 2010 to 2022. From a methodological point of view, we employ a well-established Bayesian model for spatio-temporal disease mapping, with particular attention to model parameterization, the application of appropriate constraints, and the specification of priors. For the latter, we use design- and structure-dependent priors that account for both the design and structure matrices involved in defining the prior distributions of the random effects.