The Science Behind RealFoods

Why calories are the wrong unit

Calories measure energy. They establish nothing about what the body intends to do with that energy. A calorie is a physics unit: the heat required to raise one gram of water by one degree Celsius. Human biology is not a bomb calorimeter.

Consider two 400-calorie meals. Meal A: a bowl of sugary cereal with skim milk. Meal B: salmon, avocado, and mixed greens. Both deliver roughly equal energy. Meal A drives blood sugar to 160-180 mg/dL within 30 minutes. Meal B barely moves the needle. The body's response is completely different, and that response, not the calorie arithmetic, is what determines whether fat is stored or released.

Ludwig and colleagues, publishing in JAMA Internal Medicine in 2021, established the carbohydrate-insulin model as a physiological framework for the obesity epidemic: dietary carbohydrate composition drives insulin secretion, which in turn drives fat storage and hunger, and the calorie-surplus model cannot explain the observed pattern of obesity without invoking hormonal mechanisms.

How insulin drives fat storage

When blood sugar rises rapidly after a high-carbohydrate meal, the pancreas releases a surge of insulin. Insulin performs three jobs simultaneously:

1. Clears blood glucose by routing it into muscle and liver cells for storage as glycogen.
2. Activates fat synthesis (lipogenesis) once glycogen stores are full, routing excess glucose to adipose tissue as triglycerides.
3. Suppresses fat burning (lipolysis) directly: elevated insulin inhibits hormone-sensitive lipase, the enzyme that releases stored fat for fuel. While insulin is elevated, the fat-burning switch is off. Full stop.

Dr. Benjamin Bikman, professor of cell biology and physiology at BYU, sources this mechanism in his research: chronically elevated insulin, not excess calorie intake, is the proximate cause of fat accumulation in most cases of obesity. A person who eats 1,600 calories per day from whole-wheat toast, fruit juice, flavoured yogurt, and granola will have a very different insulin environment from someone eating 1,600 calories from eggs, salmon, vegetables, and olive oil. The scale will confirm it.

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The same food produces different responses in different people

Zeevi and colleagues at the Weizmann Institute (Cell 2015) recruited 800 participants, fitted them with continuous glucose monitors, and fed them standardised meals. Their finding: the same food produced glucose curves that varied by up to 2-3x between individuals. Standard nutritional guidelines, which assign a single glycaemic value to a food regardless of who is eating it, cannot capture this variation.

We argue this research is important not as a counsel of despair but as a call for meal-level rather than food-level scoring. The variables that drive the insulin response of a complete meal, the ratio of refined carbohydrate to fibre, protein, and fat, are consistent enough across individuals that a meal-level score is meaningfully predictive even where a single-food GI value is not.

How the Weight Impact Score works

The WI Score estimates the insulin response a meal will produce based on:

• Carbohydrate quality. Refined starches and added sugars spike blood sugar steeply. Intact whole grains and fibre-dense carbohydrates do so slowly. The difference between white bread and lentils at the same carbohydrate gram count is physiologically enormous.
• Protein and fat content. Both slow gastric emptying and blunt the post-meal glucose curve. A meal rich in protein and fat produces a far lower insulin response than the same carbohydrate load eaten alone.
• Fibre content. Dietary fibre physically slows glucose absorption. The fibrous matrix of whole vegetables, legumes, and intact grains is the main reason they score low despite containing carbohydrates.
• Portion adjustment. The score scales with the logged portion. 300g of white rice has a higher hormonal impact than 100g of the same food.

The output: a 1-10 score per meal. A daily average below 5 corresponds to a dietary pattern that keeps insulin low enough for fat oxidation to proceed. Jessie Inchauspé's glucose-curve research sources the food-sequencing and fibre-buffering logic that makes the scoring consistent at the meal level even when individual glycaemic responses vary.

Continue reading: how the Weight Impact Score is calculated in detail, how blood sugar drives weight gain, or the peer-reviewed studies behind RealFoods.