#507: Does a Higher Portfolio Diet Score Reduce Heart Disease? – Andrea Glenn, PhD

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Table of Contents

  1. Introduction
  2. Guest Information
  3. Related Resources
  4. Premium Content
    • Detailed Study Notes
    • Transcript


The Portfolio diet is a nutritional approach that has garnered attention for its ability to reduce blood lipids and thus improve cardiovascular health.

While past intervention trials have demonstrated significant reductions in blood lipids, a critical aspect often overlooked is the long-term impact, both in terms of adherence and disease outcomes.

A recent study aimed to address this by looking at disease risk across three cohorts: the Nurses’ Health Study I, Nurses’ Health Study II, and the Health Professionals Follow-up Study.

The study made use of a Portfolio Diet Score (PDS), a comprehensive metric that evaluates the diet’s efficacy based on specific components.

These components include positive rankings for plant proteins (especially from legumes), nuts and seeds, viscous fiber sources, phytosterols (mg/day), and plant monounsaturated fat sources. Conversely, the PDS negatively ranks foods high in saturated fat and cholesterol.

In this episode, Dr. Andrea Glenn, the lead author of this study, discusses the intricacies of the research, providing insights into its findings and shedding light on how these findings resonate within the broader landscape of literature.

Guest Information

Andrea Glenn, PhD, RD

Dr. Andrea Glenn is a Postdoctoral Research Fellow at the Department of Nutrition at the Harvard T.H. Chan School of Public Health and the Department of Nutritional Sciences at the University of Toronto. Registered Dietitian (RD).

Her main research interests include addressing questions of public health and clinical importance in relation to dietary patterns and cardiometabolic disease risk, particularly cardiovascular disease and type 2 diabetes, and healthy aging.

She is currently working on the role of the cholesterol-lowering portfolio diet in preventing cardiovascular disease, incorporating traditional epidemiological analyses, clinical trial data, and metabolomics.

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