Document Type
Article
Publication Date
11-5-2024
Abstract
BACKGROUND: As future cardiovascular disease mortality trends have public health implications, we aimed to project ischemic heart disease (IHD), cerebrovascular disease (CeVD), and heart failure (HF) mortality rates for adults (40–79 years). METHODS AND RESULTS: In this population-level study, we linked the yearly mortality rates (per 100 000 US residents) (2000– 2019) with IHD, CeVD, or HF as the primary cause of death from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research with the midyear US population estimates (2000–2035) for adults (40–79 years). We calculated the observed age-standardized mortality rates (2000–2019) (per 100 000 residents) (aSMR) and fitted Bayesian age-period-cohort models to project aSMR for IHD, CeVD, and HF up to 2035 in the United States. Between 2019 (last year of observed data) and 2035 (last year of projected results), the US population (40–79 years) will increase by 16% and age. The IHD aSMR will reduce from 111.9 (in 2019) to 81.8 (66.7–96.9) in 2035, an effect observed for all age groups. The CeVD aSMR will remain comparable between 2019 (37.4) and 2035 (38.6 [30.7–46.5]). The HF aSMR will increase from 16.5 in 2019 to reach 30.9 (13–48.8) in 2035; such increases were observed in all age groups. CONCLUSIONS: In the United States, between 2020 and 2035, the aSMR for IHD is expected to decrease, for CeVD will remain stable, and for HF will increase substantially. These data can inform resource allocation for future public health initiatives.
Keywords
age period cohort models, atherosclerotic cardiovascular disease, bayesian modeling, cardiovascular health, cerebrovascular disease, heart failure, myocardial infarction
Language
English
Publication Title
Journal of the American Heart Association
Rights
© 2024 The Author(s). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/), which permits non-commercial copying and redistribution of the material in any medium or format, provided the original work is not changed in any way and is properly cited.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Deo, Salil V.; Al-Kindi, Sadeer; Salerno, Pedro R.V.O.; Cotton, Antoinette; Elgudin, Yakov; and Rajagopalan, Sanjay, "Bayesian Model Projecting Cardiovascular Disease Related Mortality Trends in the United States" (2024). Faculty Scholarship. 1254.
https://commons.case.edu/facultyworks/1254
Manuscript Version
Final Publisher Version