The science behind IQFood

How the estimates are made

• Glucose. Each meal's glycemic load (its carbohydrates, adjusted for the type of food) sets the size of an estimated rise. Fiber, fat and protein slow digestion and change the shape of the curve, and a larger, faster rise can be followed by a dip a few hours later.
• Insulin. Estimated as a response to that rise, in two phases, the way human studies describe it.
• Ketones and fasting. As time since the last meal grows and insulin settles, the estimated fuel mix shifts gradually toward fat, and ketones rise slowly. Adapting to a low-carbohydrate diet is modeled as a gradual change over days to weeks.
• Energy, cravings and the day ahead. Sleep, stress, workouts and activity from your check-ins and from Apple Health or Health Connect shift the estimates, and the next hours are drawn in advance.
• Weight. The trend separates longer-term change from daily swings such as water, and the forecast is estimated from your recent weight trend and what you log, adjusting as your weight changes, rather than from a fixed calorie rule.
• Personalization. A personal profile built from your answers, your weight trend and your logs adjusts the model over time (and on Android, lab values you choose to add).

What the estimates cannot do

• They are not readings. IQFood does not connect to glucose meters or sensors, and its curves can differ from your real physiology.
• People respond differently to the same food. Large studies found that identical meals produce very different glucose responses between individuals (Zeevi et al., 2015; Berry et al., 2020), so treat the curves as a guide to patterns, not exact values.
• They are only as good as what you log. Missed snacks, guessed portions and incomplete product data all move the estimates.
• They are not for medical decisions. IQFood does not diagnose, treat or prescribe, and it is not a medical device. For anything medical, including medication, talk to a qualified professional.

What IQFood does not claim

Popular nutrition claims often run ahead of the evidence. Where they do, the engine models the cautious, evidence-backed version, and the app does not say:

• that a normal rise in glucose after a meal is harmful, or that every dip after a meal is a medical problem;
• that high insulin automatically means fat gain;
• that a set number of fasting hours guarantees ketosis or autophagy, or that a ketone level measures autophagy;
• that one day of eating less puts the body in "starvation mode", or that fasted cardio melts fat;
• that IQFood prevents, treats or reverses any disease, or slows aging.

Autophagy in particular has no validated non-invasive measure in people, so IQFood shows only a direction estimated from your fasting and meal pattern, never a benefit.

Sources

The 45 peer-reviewed references behind the app's estimates, each checked against PubMed and Crossref in August 2026. The note under each reference says what it supports and, where it matters, how large the study was and whom it enrolled.

Blood glucose

1. Zurbau A, Noronha JC, Khan TA, et al. (2021). The effect of oat beta-glucan on postprandial blood glucose and insulin responses: a systematic review and meta-analysis. European Journal of Clinical Nutrition.
   Supports: Viscous oat beta-glucan blunts postprandial glucose rise
2. Wyatt P, Berry SE, Finlayson G, et al. (2021). Postprandial glycaemic dips predict appetite and energy intake in healthy individuals. Nature Metabolism.
   Supports: Larger glucose dips after meals modestly predicted hunger and later energy intake (1,070 adults)
3. Berry SE, Valdes AM, Drew DA, et al. (2020). Human postprandial responses to food and potential for precision nutrition. Nature Medicine.
   Supports: Postprandial glucose and insulin responses differ markedly between people
4. Morris CJ, Yang JN, Garcia JI, et al. (2015). Endogenous circadian system and circadian misalignment impact glucose tolerance via separate mechanisms in humans. Proceedings of the National Academy of Sciences of the United States of America.
   Supports: Evening meals meet lower circadian glucose tolerance
5. Zeevi D, Korem T, Zmora N, et al. (2015). Personalized nutrition by prediction of glycemic responses. Cell.
   Supports: Glucose response varies widely between people eating identical food
6. Shukla AP, Iliescu RG, Thomas CE, et al. (2015). Food order has a significant impact on postprandial glucose and insulin levels. Diabetes Care.
   Supports: Eating protein and vegetables before carbohydrates lowered the post-meal glucose rise (small study)
7. Richter EA, Hargreaves M (2013). Exercise, GLUT4, and skeletal muscle glucose uptake. Physiological Reviews.
   Supports: Contraction drives insulin-independent muscle glucose uptake
8. Fromentin C, Tome D, Nau F, et al. (2013). Dietary proteins contribute little to glucose production, even under optimal gluconeogenic conditions in healthy humans. Diabetes.
   Supports: Dietary protein contributes little to glucose production
9. Monnier L, Colette C, Dejager S, et al. (2013). Magnitude of the dawn phenomenon and its impact on the overall glucose exposure in type 2 diabetes. Diabetes Care.
   Supports: Glucose rises in the early morning hours, the dawn phenomenon (248 people with type 2 diabetes)
10. Gentilcore D, Chaikomin R, Jones KL, et al. (2006). Effects of fat on gastric emptying of and the glycemic, insulin, and incretin responses to a carbohydrate meal in type 2 diabetes. The Journal of Clinical Endocrinology and Metabolism.
    Supports: Fat slowed stomach emptying and flattened the glucose peak (6 men with type 2 diabetes)
11. Marliss EB, Vranic M (2002). Intense exercise has unique effects on both insulin release and its roles in glucoregulation: implications for diabetes. Diabetes.
    Supports: Very intense exercise can raise blood glucose rather than lower it (review)
12. Landau BR, Wahren J, Chandramouli V, et al. (1996). Contributions of gluconeogenesis to glucose production in the fasted state. The Journal of Clinical Investigation.
    Supports: Gluconeogenesis ramps up as fasting hours accumulate
13. Service FJ (1995). Hypoglycemic disorders. The New England Journal of Medicine.
    Supports: Clinical review: true low blood glucose after meals is over-diagnosed unless confirmed by strict criteria (Whipple's triad)
14. Rothman DL, Magnusson I, Katz LD, et al. (1991). Quantitation of hepatic glycogenolysis and gluconeogenesis in fasting humans with 13C NMR. Science.
    Supports: Measured how liver glycogen and new glucose production change during a fast
15. Matthews DR, Hosker JP, Rudenski AS, et al. (1985). Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia.
    Supports: HOMA, a research index estimated from fasting glucose and insulin
16. Brener W, Hendrix TR, McHugh PR (1983). Regulation of the gastric emptying of glucose. Gastroenterology.
    Supports: Stomach empties calories at a near-constant rate

Glycemic index and load

1. Atkinson FS, Brand-Miller JC, Foster-Powell K, et al. (2021). International tables of glycemic index and glycemic load values 2021: a systematic review. The American Journal of Clinical Nutrition.
   Supports: Source of glycemic index and glycemic load values
2. Salmeron J, Manson JE, Stampfer MJ, et al. (1997). Dietary fiber, glycemic load, and risk of non-insulin-dependent diabetes mellitus in women. JAMA.
   Supports: Long-term association of glycemic load and fiber with later risk (observational cohort of 65,173 US women)
3. Jenkins DJ, Wolever TM, Taylor RH, et al. (1981). Glycemic index of foods: a physiological basis for carbohydrate exchange. The American Journal of Clinical Nutrition.
   Supports: Glycemic index definition used for glucose curve shape

Fiber

1. Reynolds AN, Akerman AP, Mann J (2020). Dietary fibre and whole grains in diabetes management: Systematic review and meta-analyses. PLOS Medicine.
   Supports: More fiber went with lower HbA1c and fasting glucose (meta-analysis in people with diabetes)
2. Nilsson AC, Ostman EM, Holst JJ, et al. (2008). Including indigestible carbohydrates in the evening meal of healthy subjects improves glucose tolerance, lowers inflammatory markers, and increases satiety after a subsequent standardized breakfast. The Journal of Nutrition.
   Supports: Fermentable fibre improves glucose tolerance at the next meal

Fat, protein and digestion speed

1. Wolpert HA, Atakov-Castillo A, Smith SA, et al. (2013). Dietary fat acutely increases glucose concentrations and insulin requirements in patients with type 1 diabetes: implications for carbohydrate-based bolus dose calculation and intensive diabetes management. Diabetes Care.
   Supports: Dietary fat moved part of the glucose rise later (7 adults with type 1 diabetes)
2. Ma J, Stevens JE, Cukier K, et al. (2009). Effects of a protein preload on gastric emptying, glycemia, and gut hormones after a carbohydrate meal in diet-controlled type 2 diabetes. Diabetes Care.
   Supports: A protein preload slowed stomach emptying and lowered post-meal glucose (8 people with type 2 diabetes)
3. Moore DR, Robinson MJ, Fry JL, et al. (2009). Ingested protein dose response of muscle and albumin protein synthesis after resistance exercise in young men. The American Journal of Clinical Nutrition.
   Supports: Around 20 g of egg protein gave a near-maximal short-term muscle response after resistance exercise (6 young men)

Insulin

1. Sutton EF, Beyl R, Early KS, et al. (2018). Early time-restricted feeding improves insulin sensitivity, blood pressure, and oxidative stress even without weight loss in men with prediabetes. Cell Metabolism.
   Supports: In a small 5-week study of men with prediabetes, eating within an early 6-hour window improved insulin sensitivity without weight loss
2. Hall KD, Bemis T, Brychta R, et al. (2015). Calorie for calorie, dietary fat restriction results in more body fat loss than carbohydrate restriction in people with obesity. Cell Metabolism.
   Supports: In a 6-day calorie-matched inpatient study (19 adults), cutting carbohydrate did not produce more body-fat loss than cutting fat
3. Gerich JE (2002). Is reduced first-phase insulin release the earliest detectable abnormality in individuals destined to develop type 2 diabetes?. Diabetes.
   Supports: Review of early changes in first-phase insulin release
4. Spiegel K, Leproult R, Van Cauter E (1999). Impact of sleep debt on metabolic and endocrine function. The Lancet.
   Supports: Sleep debt impairs glucose tolerance and raises cortisol
5. Plat L, Leproult R, L'Hermite-Baleriaux M, et al. (1999). Metabolic effects of short-term elevations of plasma cortisol are more pronounced in the evening than in the morning. The Journal of Clinical Endocrinology and Metabolism.
   Supports: Cortisol impairs glucose tolerance with a delayed evening-weighted effect
6. Mikines KJ, Sonne B, Farrell PA, et al. (1988). Effect of physical exercise on sensitivity and responsiveness to insulin in humans. American Journal of Physiology.
   Supports: One session raises insulin sensitivity for many hours
7. Nauck M, Stockmann F, Ebert R, et al. (1986). Reduced incretin effect in type 2 (non-insulin-dependent) diabetes. Diabetologia.
   Supports: Oral glucose drives larger insulin release than intravenous glucose

Ketones and fat-adaptation

1. de Cabo R, Mattson MP (2019). Effects of intermittent fasting on health, aging, and disease. The New England Journal of Medicine.
   Supports: Review of intermittent fasting: ketone production rises with longer fasts, and how long it takes varies between people
2. Anton SD, Moehl K, Donahoo WT, et al. (2018). Flipping the metabolic switch: understanding and applying the health benefits of fasting. Obesity.
   Supports: Review: as a fast continues, the body shifts toward fat and ketones; the timing varies a lot between people
3. Volek JS, Freidenreich DJ, Saenz C, et al. (2016). Metabolic characteristics of keto-adapted ultra-endurance runners. Metabolism: Clinical and Experimental.
   Supports: Athletes adapted to a ketogenic diet for months reached about 2.3 times higher peak fat burning than athletes eating a high-carbohydrate diet (cross-sectional, 20 athletes)
4. Cahill GF Jr (2006). Fuel metabolism in starvation. Annual Review of Nutrition.
   Supports: Fasting stage fuel sequence from glucose to ketones
5. McGarry JD, Foster DW (1980). Regulation of hepatic fatty acid oxidation and ketone body production. Annual Review of Biochemistry.
   Supports: Insulin gates hepatic ketone production
6. Owen OE, Morgan AP, Kemp HG, et al. (1967). Brain metabolism during fasting. The Journal of Clinical Investigation.
   Supports: Brain shifts toward ketones during prolonged fasting

Fasting

1. Vendelbo MH, Moller AB, Christensen B, et al. (2014). Fasting increases human skeletal muscle net phenylalanine release and this is associated with decreased mTOR signaling. PLoS One.
   Supports: Fasting lowered mTOR signalling in human skeletal muscle (small study)

Autophagy

1. Moller AB, Vendelbo MH, Christensen B, et al. (2015). Physical exercise increases autophagic signaling through ULK1 in human skeletal muscle. Journal of Applied Physiology.
   Supports: Exercise raised an autophagy signalling marker (ULK1) in human muscle (small study)
2. Jamart C, Benoit N, Raymackers JM, et al. (2012). Autophagy-related and autophagy-regulatory genes are induced in human muscle after ultraendurance exercise. European Journal of Applied Physiology.
   Supports: Autophagy-related genes were more active in muscle after a 200 km race (8 men; a gene marker, not a direct measure of autophagy)

Exercise and fuel use

1. Hill EE, Zack E, Battaglini C, et al. (2008). Exercise and circulating cortisol levels: the intensity threshold effect. Journal of Endocrinological Investigation.
   Supports: Cortisol rises only above an exercise intensity threshold
2. Romijn JA, Coyle EF, Sidossis LS, et al. (1993). Regulation of endogenous fat and carbohydrate metabolism in relation to exercise intensity and duration. American Journal of Physiology.
   Supports: Fat versus carb fuel crossover by exercise intensity

Stress, cortisol and sleep

1. Spiegel K, Tasali E, Penev P, et al. (2004). Brief communication: sleep curtailment in healthy young men is associated with decreased leptin levels, elevated ghrelin levels, and increased hunger and appetite. Annals of Internal Medicine.
   Supports: Sleep loss lowers leptin, raises ghrelin, increases hunger
2. Epel E, Lapidus R, McEwen B, et al. (2001). Stress may add bite to appetite in women: a laboratory study of stress-induced cortisol and eating behavior. Psychoneuroendocrinology.
   Supports: Women with a larger cortisol response to stress ate more after a laboratory stressor (59 women)
3. Leproult R, Copinschi G, Buxton O, et al. (1997). Sleep loss results in an elevation of cortisol levels the next evening. Sleep.
   Supports: Sleep loss raises next-evening cortisol

Food data and AI

Packaged-food lookups use Open Food Facts (Open Database License), generic foods use USDA FoodData Central, and AI meal logging is processed on Google Cloud. More on the About page.

Corrections

If you think an estimate, an explanation or a source is wrong, write to support@iqfood.app. We check every report against the research and correct the app and this page when we are wrong.

Get IQFood

Free to download on Android and iPhone.