In this paper we investigate the dynamics of obesity rates across Italian regions from 2010 to 2022, aiming to assess potential spatial and gender heterogeneities. We implement three Bayesian hierarchical Beta models to analyze regional obesity rates, integrating spatial and gender random effects. The analysis reveals both heterogeneity and dependence in obesity rates over the study period, emphasizing the importance of considering gender and spatial correlation in explaining its dynamics over time. While socioeconomic and lifestyle factors remain fundamental at a micro-level, the findings demonstrate that the integration of random effect structures is critical for capturing macro-level obesity variations.