The spatial distribution of diagnosed Type 2 diabetes mellitus and cardiovascular disease incidence in Valencia, 2015–2022: a retrospective, registry-based study

Cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM) are major contributors to global morbidity and mortality, shaped by social, environmental and behavioural determinants. Assessing the spatial distribution and socio-economic stratification of these conditions at fine geographic scales can inform place-based public health strategies. This study characterises the spatial patterns, socioeconomic gradients and temporal evolution of diagnosed CVD and T2DM incidence in the urban context of Valencia, Spain, for adults aged ≥ 40 years from 2015 to 2022. We conducted a retrospective, registry-based, open cohort study using routinely collected clinical data linked to population registries across 26 postcodes in Valencia. Incident CVD and T2DM cases were identified using prespecified ICD-9/10-CM codes. Person-years at risk were aggregated annually by census tract, sex and age. Age- and sex-adjusted incidence rates were derived by direct standardisation. Spatial clustering was evaluated using global Moran’s I with first-order queen contiguity weights. Socioeconomic gradients were assessed via tract-level mean income per unit of consumption, both categorically (quartiles) and continuously using generalised additive models to analyse non-linear associations. Over 3.4 million person-years, we identified 19,902 first CVD events and 27,245 T2DM diagnoses, corresponding to crude incidence rates of 5.85 and 8.55 per 1,000 person-years, respectively. Age- and sex-adjusted incidence exhibited inverse gradients across income quartiles for both outcomes, steeper for T2DM. Spatial autocorrelation was significant for all incidence surfaces (p < 0.001), markedly stronger for T2DM (I = 0.462) than for CVD (I = 0.174). Non-linear modelling revealed pronounced socioeconomic gradients at lower income levels, particularly for T2DM. In Valencia, diagnosed CVD and T2DM incidence show clear socioeconomic and spatial inequalities, with pronounced clustering and steep income-related gradients for T2DM. These results underscore the importance of geographically targeted interventions to mitigate cardiometabolic health disparities.