The Effect of a Vegan Diet on the Cardiovascular System

Koutentakis, Michail; Surma, Stanisław; Rogula, Sylwester; Filipiak‬, Krzysztof J.

doi:10.3390/jcdd10030094

Cited by 6 publications

(1 citation statement)

References 115 publications

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“…The aging process is often accompanied by inflammaging, a chronic low-grade state of inflammation, as well as an impaired glucose and lipid metabolism, which increases the risk of cardio-metabolic disease. [1,2] A vegan diet which omits all animal-based foods has been linked to many health benefits such as improved gut microbiome, [3][4][5] lowered blood glucose, and triglyceride concentrations, [6,7] lower risk of cardiovascular disease [8] as well as lower incidence of malignant tumors [9] and lower inflammation. [10,11] In recent years, popularity for vegan diets has surged with a growing interest even among adults aged over 65 years.…”

Section: Introductionmentioning

confidence: 99%

Effects of a Short‐Term Vegan Challenge in Older Adults on Metabolic and Inflammatory Parameters—A Randomized Controlled Crossover Study

Döschner,

Schulze,

Göger

et al. 2024

Molecular Nutrition Food Res

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ScopeA long‐term vegan diet carries the risk of insufficient protein and micronutrient intake for older adults. However, even a short‐term (48 h) vegan diet exerts positive metabolic effects in younger adults. In this study, we investigate the feasibility and effects of a short‐term vegan challenge on metabolic and inflammatory markers in older adults.Method and resultsIn this randomized controlled crossover‐study, 30 healthy older adults (≥65 years) are assigned to either a 48 h ad libitum vegan or omnivorous diet. During the vegan diet, participants exhibit lower protein (p = 0.001) and fat intake as well as higher carbohydrate and dietary fiber intake, resulting in a lower caloric intake (all p < 0.001). Insulin concentrations (p = 0.042) and insulin resistance (p = 0.036) decline only after the vegan diet. The study observes reductions in serum glucose (p < 0.001), triglyceride (p = 0.005), and hsCRP (p = 0.044) concentrations and weight (p < 0.001), independent of the diet. Participants with low‐grade inflammation exhibit notable metabolic improvements after the vegan diet.ConclusionImprovements in insulin homeostasis are observed after the vegan diet, but meeting protein requirements are not feasible during the short‐term vegan challenge despite dietary counseling, which warrants concern.

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Section: Introductionmentioning

confidence: 99%

Effects of a Short‐Term Vegan Challenge in Older Adults on Metabolic and Inflammatory Parameters—A Randomized Controlled Crossover Study

Döschner,

Schulze,

Göger

et al. 2024

Molecular Nutrition Food Res

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Attitudinal factors associated with protein sufficiency in Chilean vegan university students — A pilot study

Leonario-Rodríguez,

Kovacic,

Sanhueza

et al. 2024

Nutr Hosp

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Integrating Phenotypic Information of Obstructive Sleep Apnea and Deep Representation of Sleep-Event Sequences for Cardiovascular Risk Prediction

Zheng,

Song,

Cheng

et al. 2024

Preprint

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Background: Advances in mobile, wearable and machine learning (ML) technologies for gathering and analyzing long-term health data have opened up new possibilities for predicting and preventing cardiovascular diseases (CVDs). Meanwhile, the association between obstructive sleep apnea (OSA) and CV risk has been well-recognized. This study seeks to explore effective strategies of incorporating OSA phenotypic information and overnight physiological information for precise CV risk prediction in the general population. Methods: 1,874 participants without a history of CVDs from the MESA dataset were included for the 5-year CV risk prediction. Four OSA phenotypes were first identified by the K-mean clustering based on static polysomnographic (PSG) features. Then several phenotype-agnostic and phenotype-specific ML models, along with deep learning (DL) models that integrate deep representations of overnight sleep-event feature sequences, were built for CV risk prediction. Finally, feature importance analysis was conducted by calculating SHapley Additive exPlanations (SHAP) values for all features across the four phenotypes to provide model interpretability. Results: All ML models showed improved performance after incorporating the OSA phenotypic information. The DL model trained with the proposed phenotype-contrastive training strategy performed the best, achieving an area under the Receiver Operating Characteristic (ROC) curve of 0.877. Moreover, PSG and FOOD FREQUENCY features were recognized as significant CV risk factors across all phenotypes, with each phenotype emphasizing unique features. Conclusion: Models that are aware of OSA phenotypes are preferred, and lifestyle factors should be a greater focus for precise CV prevention and risk management in the general population.

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The Effect of a Vegan Diet on the Cardiovascular System

Cited by 6 publications

References 115 publications

Effects of a Short‐Term Vegan Challenge in Older Adults on Metabolic and Inflammatory Parameters—A Randomized Controlled Crossover Study

Effects of a Short‐Term Vegan Challenge in Older Adults on Metabolic and Inflammatory Parameters—A Randomized Controlled Crossover Study

Attitudinal factors associated with protein sufficiency in Chilean vegan university students — A pilot study

Integrating Phenotypic Information of Obstructive Sleep Apnea and Deep Representation of Sleep-Event Sequences for Cardiovascular Risk Prediction

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