Geographic Clustering of Systemic Sclerosis in Areas of Environmental Pollution.

Objective: Systemic sclerosis (SSc) is a rare autoimmune disease characterized by fibrosis of the skin and other organs. SSc is thought to arise in genetically predisposed individuals with occupational triggers, although further environmental etiologies still need to be identified. Limited research exists detailing which environmental factors lead to the downstream inflammatory and fibrotic symptoms experienced by patients with SSc across the United States. This study describes a retrospective cohort of 179,188 individuals with an SSc or SSc-related diagnosis code enrolled in the Medicare beneficiary program between the years 2014 and 2018.

Methods: The incidence of SSc and SSc-related diagnosis codes in all US zip codes with beneficiary counts greater than 11 was calculated. We conducted global and local Moran's Index (Moran's I) as well as a hot spot analysis with the Getis Ord Gi statistic to determine whether SSc and SSc-related diagnosis codes exhibited clustered or dispersed patterns across the United States. We identified clusters of SSc and SSc-related diagnosis code with high incidences in or around Superfund sites, which are federally identified areas of environmental contamination.

Results: SSc exhibited clustered patterns in two analyzed cohorts based on global Moran's I statistics of 0.588 and 0.521. Results of local Moran's I indicated clusters of disease in Mississippi, New York, Wisconsin, and Michigan, among others. Some zip codes with high disease incidences were home to at least one Superfund site.

Conclusion: SSc exhibits nonrandom, clustered distributions in a US Medicare beneficiary cohort composed of 179,188 individuals from 2014 to 2018.