ArticleCirculation. Heart failure2021
Association Between Coffee Intake and Incident Heart Failure Risk: A Machine Learning Analysis of the FHS, the ARIC Study, and the CHS.
Article in Circulation. Heart failure, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 47 citations in OpenAlex.
- Habitual coffee consumption and risk of incident heart failure: an updated systematic review and dose-response meta-analysis of prospective cohort studies.Journal of health, population, and nutrition · 2026Pooled it
- Well-Known and Novel Behavioural Risk Factors for Heart Failure.Journal of cardiovascular development and disease · 2026Review
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- Article
- Unsupervised machine learning for cardiovascular disease: A framework for future studies.European journal of heart failure · 2025Review
- Evaluating the effects of coffee consumption on the structure and function of the heart from multiple perspectives.Frontiers in cardiovascular medicine · 2025Article
- A cross-sectional analysis of coffee intake and hypertension prevalence: results from the NHANES 2005-2020.Frontiers in nutrition · 2025Article
- Coffee consumption and cardiometabolic health: a comprehensive review of the evidence.GeroScience · 2024Review
- Evaluation of the responsiveness pattern to caffeine through a smart data-driven ECG non-linear multi-band analysis.Heliyon · 2024Article
- Data-Driven Identification of Factors That Influence the Quality of Adverse Event Reports: 15-Year Interpretable Machine Learning and Time-Series Analyses of VigiBase and QUEST.JMIR medical informatics · 2024Article
- Characterization of caffeine response regulatory variants in vascular endothelial cells.eLife · 2024Article
- Role of nutrition and healthy lifestyle, for individuals in primary prevention: recent data, gaps in evidence and future directions.Archives of medical science : AMS · 2024Article
- Machine Learning in Cardio-Oncology: New Insights from an Emerging Discipline.Reviews in cardiovascular medicine · 2023Review
- Long-term outcomes from the UK Biobank on the impact of coffee on cardiovascular disease, arrhythmias, and mortality: Does the future hold coffee prescriptions?Global cardiology science & practice · 2023Article
- Association of beverage consumption with subclinical atherosclerosis in a Spanish working population.Scientific reports · 2023Article
- Coffee and cardiac arrhythmias: Up-date review of the literature and clinical studies.Cardiology journal · 2023Review
- Coffee consumption and all-cause and cardiovascular mortality in older adults: should we consider cognitive function?Frontiers in nutrition · 2023Article
- Impact of Coffee Consumption on Cardiovascular Health.Ochsner journal · 2023Review
- Genetic Variations on Redox Control in Cardiometabolic Diseases: The Role of Nrf2.Antioxidants (Basel, Switzerland) · 2022Review
- Protective Effects of Curcumin in Cardiovascular Diseases-Impact on Oxidative Stress and Mitochondria.Cells · 2022Review
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundCoronary heart disease, heart failure (HF), and stroke are complex diseases with multiple phenotypes. While many risk factors for these diseases are well known, investigation of as-yet unidentified risk factors may improve risk assessment and patient adherence to prevention guidelines. We investigated the diet domain in FHS (Framingham Heart Study), CHS (Cardiovascular Heart Study), and the ARIC study (Atherosclerosis Risk in Communities) to identify potential lifestyle and behavioral factors associated with coronary heart disease, HF, and stroke.
methodsWe used machine learning feature selection based on random forest analysis to identify potential risk factors associated with coronary heart disease, stroke, and HF in FHS. We evaluated the significance of selected variables using univariable and multivariable Cox proportional hazards analysis adjusted for known cardiovascular risks. Findings from FHS were then validated using CHS and ARIC.
resultsWe identified multiple dietary and behavioral risk factors for cardiovascular disease outcomes including marital status, red meat consumption, whole milk consumption, and coffee consumption. Among these dietary variables, increasing coffee consumption was associated with decreasing long-term risk of HF congruently in FHS, ARIC, and CHS.
conclusionsHigher coffee intake was found to be associated with reduced risk of HF in all three studies. Further study is warranted to better define the role, possible causality, and potential mechanism of coffee consumption as a potential modifiable risk factor for HF.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.