DataFood Engine.Monexa Data Node
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High Efficiency

Fava.

Metabolic profile analysis. Technical breakdown of Fava and its impact on skeletal muscle retention and daily energy expenditure.

Total Energy40kcal
Bio-Protein29g
Carbohydrates46g
Total Lipids2g

Nutritional Efficiency Report

Fava is a very low-calorie food with high-protein content. At 40 kcal per 100g, it delivers 29g of protein — representing 290% of its total caloric load. Carbohydrates account for 460% and fats for 45% of calories.

"Efficiency Score 1.00 — this asset ranks in the top tier of the DataFood database for protein delivery per calorie. Optimal for fat loss, lean bulking, and body recomposition phases."

At 46g carbs per 100g, it is better suited to carb-cycling or maintenance phases.

With only 40 kcal per 100g, Fava is a high-volume food — you can consume a large serving while keeping total caloric intake controlled. This makes it particularly effective for hunger management in deficit phases.

Protocol Compatibility

Ketosis Impact

At 46g carbs per 100g, it is better suited to carb-cycling or maintenance phases.

Thermic Effect (TEF)

Protein content of 29g per 100g triggers a significant Thermic Effect of Food. The body expends approximately 20–30% of protein calories during digestion, yielding a net caloric benefit compared to equivalent fat or carbohydrate sources.

Expand Your Protocol.

Based on the metabolic profile of Fava, these related data nodes are most relevant to your nutrition architecture:

High Protein Foods Fat Loss Foods Database

Integrate Asset.

Use the clinical weekly planner to distribute Fava across your metabolic windows.

Generate Weekly Protocol

Input physical metrics to generate a synchronized 7-day protocol.

1. Biological Metrics

2. Dietary Logic

Institutional Disclaimer: The nutritional data provided for Fava is derived from clinical databases and algorithmic estimation. This report is for metabolic infrastructure planning only and does not constitute medical advice. Consult a clinical nutritionist before implementing aggressive deficit protocols.