Expanded Fermi Solution to estimate health risks or benefits from interacting factors

Area of Science:

• Food Safety and Risk Assessment
• Quantitative Toxicology
• Computational Biology

Background:

• Health risks and benefits from food factors can interact in complex ways, not just additively or multiplicatively.
• Uncertainty in risk/benefit factor magnitudes necessitates probabilistic approaches over single-value estimates.
• Existing methods may not adequately capture the interactive nature of multiple food-related health factors.

Purpose of the Study:

• To present the Expanded Fermi Solution method for assessing combined food-related health risks and benefits.
• To demonstrate a computational approach for handling uncertainty and interactions among risk/benefit factors.
• To provide accessible software tools for analyzing complex food safety scenarios.

Main Methods:

• Utilizing the Expanded Fermi Solution method with random value generation within defined ranges for risk/benefit factors.
• Applying chosen mathematical models (additive, multiplicative, interactive) to calculate combined risks/benefits.
• Automating calculations and developing interactive Wolfram Demonstrations for complex risk/benefit models.

Main Results:

• For additive and multiplicative factors, calculated risks/benefits showed normal and lognormal distributions, respectively.
• The mode of the distribution was identified as the best estimate for combined risks/benefits.
• Interactive models, though not guaranteeing specific distributions, allowed for best estimate identification via histograms.

Conclusions:

• The Expanded Fermi Solution method effectively estimates combined risks/benefits from food factors, even with interactive and uncertain parameters.
• Automated software and Wolfram Demonstrations facilitate rapid analysis of numerous factor combinations for food and supplement safety.
• This approach enhances the evaluation of potential health effects, contributing to more robust risk assessments.