Latent Class Analysis of COVID-19 Deaths by Comorbidities— United States, February-May 2020
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Purpose
Risk factors for coronavirus disease 2019 (COVID-19) mortality include older age, cardiovascular disease, diabetes, and other comorbidities. Latent class analysis (LCA) can identify unrecognized morbidity patterns for decedents with COVID-19.
Methods
Data were collected from 23 U.S. jurisdictions about decedents with COVID-19 early in the COVID-19 pandemic (February 12–May 12, 2020). LCA identified groups of individuals based upon pre-existing comorbidities: cardiovascular, renal, lung, neurologic, and liver disease; obesity; diabetes; and immunocompromised state. Results were stratified by sex, age, race/ethnicity, and location of death.
Results
Of 12,340 decedents, LCA identified three classes, which included classes with prominent cardiovascular disease and diabetes (32%), prominent cardiovascular disease without diabetes (19%), and a “minimal prevalence” class (49%) with a low frequency of comorbidities. Individuals in the “minimal prevalence” class had risk factors in <2 comorbidity groups, where cardiovascular disease was the most common for individuals with a single comorbidity.
Conclusions
LCA analysis reaffirms the importance of diabetes and cardiovascular disease as risk factors for COVID-19 mortality and indicates that about half of decedents were in the “minimal prevalence” group. Results could guide vaccination and treatment messaging to groups with no or few underlying conditions.
Disclaimer
The conclusions, findings, and opinions expressed by the authors do not necessarily reflect the offical position of the Centers for Disease Control and Prevention or the authors’ affililated institutions.
