Why the study?
Amid recently rising heart failure death rates in the United States, county-level trends in heart failure mortality across demographic groups had not been described.
There has been a pervasive increase in county-level heart failure mortality rates across the US from 2011 to 2018, particularly among adults aged 35 to 64 years.
County-level HF mortality disparities persist by race, sex, and age; extends national trends but leaves open targeted causal research.
Background Amid recently rising heart failure (HF) death rates in the United States, we describe county-level trends in HF mortality from 1999 to 2018 by racial/ethnic group and sex for ages 35 to 64 years and 65 years and older. Methods and Results Applying a hierarchical Bayesian model to National Vital Statistics data representing all US deaths, ages 35 years and older, we estimated annual age-standardized county-level HF death rates and percent change by age group, racial/ethnic group, and sex from 1999 through 2018. During 1999 to 2011, ~30% of counties experienced increasing HF death rates among adults ages 35 to 64 years. However, during 2011 to 2018, 86.9% (95% CI, 85.2-88.2) of counties experienced increasing mortality. Likewise, for ages 65 years and older, during 1999 to 2005 and 2005 to 2011, 27.8% (95% CI, 25.8-29.8) and 12.6% (95% CI, 11.2-13.9) of counties, respectively, experienced increasing mortality. However, during 2011 to 2018, most counties (67.4% [95% CI, 65.4-69.5]) experienced increasing mortality. These temporal patterns by age group held across racial/ethnic group and sex. Conclusions These results provide local context to previously documented recent national increases in HF death rates. Although county-level declines were most common before 2011, some counties and demographic groups experienced increasing HF death rates during this period of national declines. However, recent county-level increases were pervasive, occurring across counties, racial/ethnic group, and sex, particularly among ages 35 to 64 years. These spatiotemporal patterns highlight the need to identify and address underlying clinical risk factors and social determinants of health contributing to these increasing trends.
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Vaughan et al. (2021) studied this question.
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