Data have demonstrated county- and state-wide variability in mortality rates from liver disease, but data are lacking at the 'local' (e.g., county) level to identify factors associated with variability in liver disease-related mortality and hotspots of liver disease mortality.We used CDC Wonder data from 2009-2018 to calculate county-level age-adjusted liver disease-related death rates. We fit multivariable linear regression models to adjust for county-level covariates related to demographics (i.e., race and ethnicity), medical co-morbidities (e.g., obesity), access-to-care (e.g., uninsured rate), and geographic (e.g., distance to closest liver transplant center) variables. We used optimized hotspot analysis to identify clusters of liver disease mortality hotspots based on the final multivariable models.In multivariable models, 61% of the variability in among-county mortality was explained by county-level race/ethnicity, poverty, uninsured rates, distance to the closest transplant center, and local rates of obesity, diabetes, and alcohol use. Despite adjustment, there was significant within-state variability in county-level mortality rates. Of counties with the 'top' 5th percentile (i.e., highest mortality) of fully adjusted mortality, 60% were located in three states: Oklahoma, Texas, and New Mexico. Adjusted mortality rates were highly spatially correlated, representing five clusters: 1) South Florida; 2) Appalachia and the eastern part of the Midwest; 3) Texas and Oklahoma; 4) New Mexico, Arizona, California, and southern Oregon; and 5) parts of Washington and Montana.Our data demonstrate significant intra-state differences in liver disease-related mortality, with more than 60% of the variability being explained by patient demographics, clinical risk factors for liver disease, and access to specialty liver care.