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Diet and Exercise: Cardiovascular Responses in Health and Disease

A special issue of Nutrients (ISSN 2072-6643). This special issue belongs to the section "Sports Nutrition".

Deadline for manuscript submissions: 20 June 2026 | Viewed by 18

Special Issue Editor


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Guest Editor
Department of Pharmacoepidemiology, Graduate School of Medicine and Public Health, Kyoto University, Yoshidakonoe-cho, Sakyo-ku, Kyoto 606-8501, Japan
Interests: cardiovascular epidemiology; deep medicine; prevention; prediction; machine learning; population study; sex differences; nutrition

Special Issue Information

Dear Colleagues,

This Special Issue of Nutrients (Sports Nutrition) examines how diet and physical activity (exercise) independently and synergistically modulate cardiovascular function across the spectrum of health and disease. We welcome studies in the general public and in populations at elevated risk—such as obesity, hypertension, type 2 diabetes, atrial fibrillation, and heart failure—including cardiac rehabilitation settings.

We invite work on dietary patterns (e.g., Mediterranean, DASH, plant-based, lower-carbohydrate/ketogenic), macro- and micronutrients and bioactives (nitrate, iron, omega-3 fatty acids, polyphenols), hydration and electrolytes, and ergogenic aids (caffeine, creatine, bicarbonate). Outcomes may include blood pressure and haemodynamics, vascular endothelial function, autonomic balance, arrhythmia, cardiac structure and performance, recovery, and biomarkers of stress/injury and inflammation (e.g., BNP/NT-proBNP, troponin). We welcome genomic and multi-omics studies—including nutrigenomics, transcriptomics, proteomics, metabolomics, lipidomics, and microbiome analyses—to clarify mechanisms, heterogeneity of response, and potential gene–diet and diet–exercise interactions. Submissions leveraging multimodal data (e.g., wearables, ECG/PPG, imaging-derived phenotypes) and robust analytics (causal inference, machine learning) are also encouraged.

We seek a diverse methodological portfolio: randomised trials, mechanistic and cohort studies, real-world database studies, systematic reviews/meta-analyses, and implementation research. Our aim is to translate complex evidence into actionable, practice-ready guidance for clinicians, practitioners, and policy.

Dr. Yoko M. Nakao
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Nutrients is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cardiovascular diseases
  • diet–exercise interactions
  • gene–diet interactions
  • haemodynamics
  • endothelial function
  • obesity
  • arrhythmia
  • heart failure
  • micronutrients
  • nutrigenomics
  • multi-omics
  • hydration and electrolytes
  • cardiac rehabilitation
  • machine learning
  • causal inference

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Published Papers

This special issue is now open for submission.
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