Demographic trends of cardiorenal and heart failure deaths in the United States, 2011-2020

Area of Science:

• Cardiovascular Medicine
• Nephrology
• Public Health Epidemiology

Background:

• Heart failure (HF) and kidney disease frequently coexist, creating cardiorenal syndrome with elevated mortality risk.
• The epidemiology and demographic disparities in cardiorenal syndrome mortality are not well understood.
• Shared risk factors exist between HF and cardiorenal syndrome, but mortality differences across demographics require investigation.

Purpose of the Study:

• To analyze annual trends in cardiorenal-related mortality in the US from 2011-2020.
• To evaluate demographic differences (age, sex, race/ethnicity) in these mortality trends.
• To compare cardiorenal syndrome mortality trends with those of heart failure mortality.

Main Methods:

• Utilized the CDC Wide-ranging ONline Data for Epidemiologic Research (WONDER) database for US mortality data (2011-2020).
• Classified cardiorenal (ICD-10: I13.x) and HF (ICD-10: I11.0, I13.0, I13.2, I50.x) deaths for individuals aged 15 and older.
• Calculated crude and age-adjusted mortality rates (AAMR) and annual percent changes (APC), stratifying by age, sex, and race/ethnicity.

Main Results:

• Total deaths: 97,135 cardiorenal-related and 3,453,655 HF-related.
• Cardiorenal mortality (AAMR 3.26) was lower than HF mortality (AAMR 115.7).
• Cardiorenal mortality showed a significant increasing trend (APC 19.7% in 2015-2020), far exceeding the HF mortality increase (APC 2.4%).
• Mortality was highest in older adults and males; non-Hispanic/Latino Blacks had higher cardiorenal mortality compared to Whites.
• Cardiorenal syndrome was the underlying cause in 67.0% of cardiorenal deaths, versus 1.2% for HF deaths.

Conclusions:

• Cardiorenal deaths are increasing at an alarming rate, with a disproportionate burden on non-Hispanic/Latino Black individuals.
• Continued surveillance of cardiorenal mortality trends is crucial.
• Future research should incorporate biomarker and social determinants of health data to understand mortality disparities.