ArticleNutrients2016
Algorithms to Improve the Prediction of Postprandial Insulinaemia in Response to Common Foods.
Article in Nutrients, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed, 36 citations in OpenAlex.
- Trial
- Do the Types of Dietary Carbohydrate and Protein Affect Postprandial Glycemia in Type 1 Diabetes?Nutrients · 2025Trial
- The Link Between Dietary Indices, Sarcopenia, and Clinical Parameters in Diabetic and Non-Diabetic Hemodialysis Patients.Journal of clinical medicine · 2026Article
- The Influence of the Interaction between the rs1042713 ADRΒ2 Polymorphism and Dietary Insulin Indices on Cardiometabolic Risk Factors in Iranian Adults: Results from Fasa Adult Cohort Study (FACS).Current developments in nutrition · 2026Article
- Dietary glycemic and insulin indices in association with sleep quality and duration in patients undergoing angiography.BMC nutrition · 2025Article
- Dietary insulin index and load in relation to the risk of diminished ovarian reserve: a case-control study.Frontiers in nutrition · 2025Article
- Dietary insulin index and dietary insulin load in relation to non-alcoholic fatty liver disease: a cross-sectional study.Public health nutrition · 2024Article
- Association between dietary insulin index and postmenopausal osteoporosis in Iranian women: a case-control study.BMC women's health · 2024Article
- The Application of the Food Insulin Index in the Prevention and Management of Insulin Resistance and Diabetes: A Scoping Review.Nutrients · 2024Article
- Dietary Insulin Index (DII) and Dietary Insulin load (DIL) and Caveolin gene variant interaction on cardiometabolic risk factors among overweight and obese women: a cross-sectional study.European journal of medical research · 2024Article
- Dietary insulin index, dietary insulin load and dietary patterns and the risk of metabolic syndrome in Hoveyzeh Cohort Study.Scientific reports · 2024Article
- Article
- The High-Dietary Insulin Load Score Is Associated With Elevated Level of Fasting Blood Sugar in Iranian Adult Men: Results From Fasa PERSIAN Cohort Study.BioMed research international · 2024Article
- Article
- Association between dietary insulin index and load with brain derived neurotrophic factor, adropin and metabolic health status in Iranian adults.Scientific reports · 2023Article
- Dietary insulin index and load and cardiometabolic risk factors among people with obesity: a cross-sectional study.BMC endocrine disorders · 2023Article
- Article
- Article
- The association of dietary insulin load and dietary insulin index with body composition among professional soccer players and referees.BMC sports science, medicine & rehabilitation · 2023Article
- How do carbohydrate quality indices influence on bone mass density in postmenopausal women? A case-control study.BMC women's health · 2023Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Dietary patterns that induce excessive insulin secretion may contribute to worsening insulin resistance and beta-cell dysfunction. Our aim was to generate mathematical algorithms to improve the prediction of postprandial glycaemia and insulinaemia for foods of known nutrient composition, glycemic index (GI) and glycemic load (GL). We used an expanded database of food insulin index (FII) values generated by testing 1000 kJ portions of 147 common foods relative to a reference food in lean, young, healthy volunteers. Simple and multiple linear regression analyses were applied to validate previously generated equations for predicting insulinaemia, and develop improved predictive models. Large differences in insulinaemic responses within and between food groups were evident. GL, GI and available carbohydrate content were the strongest predictors of the FII, explaining 55%, 51% and 47% of variation respectively. Fat, protein and sugar were significant but relatively weak predictors, accounting for only 31%, 7% and 13% of the variation respectively. Nutritional composition alone explained only 50% of variability. The best algorithm included a measure of glycemic response, sugar and protein content and explained 78% of variation. Knowledge of the GI or glycaemic response to 1000 kJ portions together with nutrient composition therefore provides a good approximation for ranking of foods according to their "insulin demand".
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.