Chronic liver diseases (CLD) and diabetes mellitus (DM) are major public health concerns worldwide. The co-occurrence of cirrhosis and DM represents a growing global health challenge, driven by both shared and disease-specific modifiable risk factors. Most previous research has focused on these two diseases in isolation; however, their co-occurrence has rarely been examined, limiting understanding of shared mechanisms and hindering integrated prevention and resource planning. We aimed to characterize the global co-occurrence pattern of CLD and DM from a spatial perspective and to identify the corresponding risk factors of the comorbidity.

From the Global Burden of Diseases (GBD), injuries, and risk factors 2023 study, we retrieved age-standardized incidence rates (ASIRs, per 100,000) for CLD and DM and exposure value for 64 granular risk factors among populations in 204 countries and territories. According to the quartiles of global incidence rates for both diseases, countries were categorized into three co-occurrence regions: consistent, CLD-dominant, and DM-dominant areas. Employing machine learning algorithms alongside negative binomial regression models, we identified and quantified the impact of relevant risk factors. The population-attributable fraction and a composite risk index were subsequently calculated to assess the disease burden associated with CLD and DM.

From the Global Burden of Diseases (GBD), injuries, and risk factors 2023 study, we retrieved age-standardized incidence rates (ASIRs, per 100,000) for CLD and DM and exposure value for 64 granular risk factors among populations in 204 countries and territories. According to the quartiles of global incidence rates for both diseases, countries were categorized into three co-occurrence regions: consistent, CLD-dominant, and DM-dominant areas. Employing machine learning algorithms alongside negative binomial regression models, we identified and quantified the impact of relevant risk factors. The population-attributable fraction and a composite risk index were subsequently calculated to assess the disease burden associated with CLD and DM.

Kidney dysfunction and high temperature emerged as the most influential common determinants, while nutritional deficiencies, metabolic factors, and environmental exposures contributed distinct risks to each condition. The spatial alignment of co-occurrence patterns with composite risk exposure underscores the synergistic effects of multiple risk factors. Targeted, integrated interventions, including kidney health protection, nutritional support, metabolic control, and climate adaptation, tailored to regional co-occurrence profiles can substantially reduce the global burden of both diseases.