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Journal articles on the topic 'Glycaemic index'

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Author: Grafiati

Published: 4 June 2021

Last updated: 10 March 2023

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1

Brouns, F., I. Bjorck, K. N. Frayn, A. L. Gibbs, V. Lang, G. Slama, and T. M. S. Wolever. "Glycaemic index methodology." Nutrition Research Reviews 18, no. 1 (June 2005): 145–71. http://dx.doi.org/10.1079/nrr2005100.

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AbstractThe glycaemic index (GI) concept was originally introduced to classify different sources of carbohydrate (CHO)-rich foods, usually having an energy content of >80 % from CHO, to their effect on post-meal glycaemia. It was assumed to apply to foods that primarily deliver available CHO, causing hyperglycaemia. Low-GI foods were classified as being digested and absorbed slowly and high-GI foods as being rapidly digested and absorbed, resulting in different glycaemic responses. Low-GI foods were found to induce benefits on certain risk factors for CVD and diabetes. Accordingly it has been proposed that GI classification of foods and drinks could be useful to help consumers make ‘healthy food choices’ within specific food groups. Classification of foods according to their impact on blood glucose responses requires a standardised way of measuring such responses. The present review discusses the most relevant methodological considerations and highlights specific recommendations regarding number of subjects, sex, subject status, inclusion and exclusion criteria, pre-test conditions, CHO test dose, blood sampling procedures, sampling times, test randomisation and calculation of glycaemic response area under the curve. All together, these technical recommendations will help to implement or reinforce measurement of GI in laboratories and help to ensure quality of results. Since there is current international interest in alternative ways of expressing glycaemic responses to foods, some of these methods are discussed.

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2

Rizkalla, S. W., F. Bellisle, and G. Slama. "Health benefits of low glycaemic index foods, such as pulses, in diabetic patients and healthy individuals." British Journal of Nutrition 88, S3 (December 2002): 255–62. http://dx.doi.org/10.1079/bjn2002715.

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The present paper covers the health benefits of low glycaemic index foods, such as pulses. Nutritional factors potentially play a crucial role in health and disease. A low-fat, high-carbohydrate diet is often recommended as a part of a healthy life-style. Historical works have shown that carbohydrate foods differ in their ability to affect post-ingestive glycaemia. The glycaemic index concept allows a ranking of carbohydrate-rich foods in terms of their blood glucose raising potential. Pulses are foods with very low glycaemic index values. Numerous studies have documented the health benefits that can be obtained by selecting foods of low glycaemic index. These benefits are of crucial importance in the dietary treatment of diabetes mellitus: glycaemic control is improved as well as several metabolic parameters, such as blood lipids. The results of human studies have been confirmed by animal experiments in the field of diabetes. Diets with low glycaemic index value improve the prevention of coronary heart disease in diabetic and healthy subjects. In obese or overweight individuals, low-glycaemic index meals increase satiety and facilitate the control of food intake. Selecting low glycaemic index foods has also demonstrated benefits for healthy persons in terms of post-prandial glucose and lipid metabolism. Several public health organizations have recently integrated consideration of the glycaemic index in their nutritional recommendations for patients with metabolic diseases and for the general population.

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3

Arvidsson-Lenner, Ragnhild, Nils-Georg Asp, Mette Axelsen, Susanne Bryngelsson, Eliina Haapa, Anette Järvi, Brita Karlström, et al. "Glycaemic Index." Scandinavian Journal of Nutrition 48, no. 2 (January 2004): 84–94. http://dx.doi.org/10.1080/11026480410033999.

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4

Emerson, Sam R., Mark D. Haub, Colby S. Teeman, Stephanie P. Kurti, and Sara K. Rosenkranz. "Summation of blood glucose and TAG to characterise the ‘metabolic load index’." British Journal of Nutrition 116, no. 9 (October 24, 2016): 1553–63. http://dx.doi.org/10.1017/s0007114516003585.

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AbstractResearch points to postprandial glucose and TAG measures as preferable assessments of cardiovascular risk as compared with fasting values. Although elevated postprandial glycaemic and lipaemic responses are thought to substantially increase chronic disease risk, postprandial glycaemia and lipaemia have historically only been considered separately. However, carbohydrates and fats can generally ‘compete’ for clearance from the stomach, small intestine, bloodstream and within the peripheral cell. Further, there are previous data demonstrating that the addition of carbohydrate to a high-fat meal blunts the postprandial lipaemic response, and the addition of fat to a high-carbohydrate meal blunts the postprandial glycaemic response. Thus, postprandial glycaemia and lipaemia are interrelated. The purpose of this brief review is 2-fold: first, to review the current evidence implicating postprandial glycaemia and lipaemia in chronic disease risk, and, second, to examine the possible utility of a single postprandial glycaemic and lipaemic summative value, which will be referred to as the metabolic load index. The potential benefits of the metabolic load index extend to the clinician, patient and researcher.

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5

DU, Huaidong, Daphne L. VAN DER A, and Edith J. M. FESKENS. "Dietary Glycaemic Index." Acta Cardiologica 61, no. 4 (August 1, 2006): 383–97. http://dx.doi.org/10.2143/ac.61.4.2017298.

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6

OʼReilly, John, Stephen H. S. Wong, and Yajun Chen. "Glycaemic Index, Glycaemic Load and Exercise Performance." Sports Medicine 40, no. 1 (January 2010): 27–39. http://dx.doi.org/10.2165/11319660-000000000-00000.

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7

Venn, B. J., S. M. Williams, T. Perry, S. Richardson, A. Cannon, and J. I. Mann. "Age-related differences in postprandial glycaemia and glycaemic index." Age and Ageing 40, no. 6 (July 27, 2011): 755–58. http://dx.doi.org/10.1093/ageing/afr096.

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8

Jones, M. E., J. Louie, A. Barclay, and J. Brand-Miller. "Dietary glycaemic index and glycaemic load among Australians." Journal of Nutrition & Intermediary Metabolism 4 (June 2016): 9. http://dx.doi.org/10.1016/j.jnim.2015.12.180.

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9

Prasad, Madhrapakkam Pagadala Rajendra, Benhur Dayakar Rao, Kommi Kalpana, Mendu Vishuvardhana Rao, and Jagannath Vishnu Patil. "Glycaemic index and glycaemic load of sorghum products." Journal of the Science of Food and Agriculture 95, no. 8 (September 1, 2014): 1626–30. http://dx.doi.org/10.1002/jsfa.6861.

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10

Stevenson, Emma J., and Dean M. Allerton. "The role of whey protein in postprandial glycaemic control." Proceedings of the Nutrition Society 77, no. 1 (September 25, 2017): 42–51. http://dx.doi.org/10.1017/s0029665117002002.

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Epidemiological studies demonstrate that poor glycaemic control is an independent risk factor for CVD. Postprandial glycaemia has been demonstrated as a better predictor of glycated Hb, the gold standard of glycaemic control, when compared with fasting blood glucose. There is a need for more refined strategies to tightly control postprandial glycaemia, particularly in those with type 2 diabetes, and nutritional strategies around meal consumption may be effective in enhancing subsequent glycaemic control. Whey protein administration around meal times has been demonstrated to reduce postprandial glycaemia, mediated through various mechanisms including an enhancement of insulin secretion. Whey protein ingestion has also been shown to elicit an incretin effect, enhancing the secretion of glucose-dependent insulinotropic peptide and glucagon-like peptide-1, which may also influence appetite regulation. Acute intervention studies have shown some promising results however many have used large dosages (50–55 g) of whey protein alongside high-glycaemic index test meals, such as instant powdered potato mixed with glucose, which does not reflect realistic dietary strategies. Long-term intervention studies using realistic strategies around timing, format and amount of whey protein in relevant population groups are required.

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11

Björck, Inger, Helena Liljeberg, and Elin Östman. "Low glycaemic-index foods." British Journal of Nutrition 83, S1 (June 2000): S149—S155. http://dx.doi.org/10.1017/s0007114500001094.

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Accumulating data indicate that a diet characterized by low glycaemic-index (GI) foods not only improves certain metabolic ramifications of insulin resistance, but also reduces insulin resistance per se. Epidemiological data also suggest a protective role against development of non-insulin-dependent diabetes mellitus and cardiovascular disease. A major disadvantage in this connection is the shortage of low-GI foods, and many common starchy staple foods, such as bread products, breakfast cereals and potato products, have a high GI. Studies in our laboratory show that it is possible to significantly lower the GI of starchy foods, for example by choice of raw material and/or by optimizing the processing conditions. Such low-GI foods may or may not influence glucose tolerance at a subsequent meal. Consequently, certain low-GI breakfasts capable of maintaining a net increment in blood glucose and insulin at the time of the next meal significantly reduced post-prandial glycaemia and insulinaemia following a standardized lunch meal, whereas others had no ‘second-meal’ impact. These results imply that certain low-GI foods may be more efficient in modulating metabolism in the long term. Although the literature supports a linear correlation between the GI and insulinaemic index (II) of foods, this is not always the case. Consequently, milk products elicited elevated IIs, indistinguishable from a white bread reference meal, despite GIs in the lower range. This inconsistent behaviour of milk products has not been acknowledged, and potential metabolic consequences remain to be elucidated.

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12

Monro, John. "Expressing the glycaemic potency of foods." Proceedings of the Nutrition Society 64, no. 1 (February 2005): 115–22. http://dx.doi.org/10.1079/pns2004401.

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The glycaemic index (GI) was introduced to guide food exchanges within equicarbohydrate food categories, and it expresses the glycaemic potency of the available carbohydrate component in a food relative to that of glucose. As GI is a relative value based on ‘available carbohydrate’ it cannot guide food choice for glycaemic control unless the foods are equal in available carbohydrate. Furthermore, GI cannot respond to food intake or to effects on food glycaemic potency of replacing glycaemic ingredients with non-glycaemic ingredients. The glycaemic glucose equivalent (GGE) overcomes these limitations of GI. The GGE content of an amount of food is the weight of glucose (g) that would induce a glycaemic response equal to that induced by the food. Few studies have compared GI and GGE as guides to food choice for glycaemic control, but in a direct test of the predictive validity of GGE in a group of foods of differing carbohydrate and GI, GGE predicted glycaemic potency well, whereas GI was unrelated to glycaemic effect. Furthermore, an information-processing model of the use of food information in food choice shows that GI has fundamental flaws when used outside the restriction of equicarbohydrate food exchange categories. As a general guide to food choices for the control of glycaemia GI does not satisfy the criteria predictive validity, accuracy, safety, ease of use, flexibility, sufficiency and compatability, whereas GGE does. GGE is also a scientifically precise and meaningful term with which to express glycaemic potency than is ‘glycaemic load’.

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13

Monro, John A. "Glycaemic glucose equivalent: combining carbohydrate content, quantity and glycaemic index of foods for precision in glycaemia management." Asia Pacific Journal of Clinical Nutrition 11, no. 3 (September 2002): 217–25. http://dx.doi.org/10.1046/j.1440-6047.2002.00295.x.

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14

Brand-Miller, Jennie C., and Thomas M. S. Wolever. "The use of glycaemic index tables to predict glycaemic index of breakfast meals." British Journal of Nutrition 94, no. 1 (July 2005): 133–34. http://dx.doi.org/10.1079/bjn20041423.

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15

Flint, Anne, Bente K. Møller, Anne Raben, Inge Tetens, Jens J. Holst, and Arne Astrup. "The use of glycaemic index tables to predict glycaemic index of breakfast meals." British Journal of Nutrition 94, no. 1 (July 2005): 135–36. http://dx.doi.org/10.1079/bjn20041424.

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16

Sankari, P., N. Prabavathi, and N. R. Shanker. "Determination of Glycaemic Index (GI) through Detecting Insulin Secretion in Pancreas Using GMR Sensor." Journal of Sensors 2020 (September 18, 2020): 1–13. http://dx.doi.org/10.1155/2020/8847114.

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Diabetes is a metabolic disease that affects the ability of the body to process blood glucose, otherwise known as blood sugar. Diabetes occurs when the body produces minimal or no insulin. The diabetes patients check their glycaemic index after each meal and intake medicine to control glycaemic index. Traditionally, glycaemic index estimates the glucometer by acquiring blood sample. In this paper, we propose a noninvasive method to estimate glycaemic index from the pancreas. The magnetic signal from the pancreas acquires with Giant Magneto Resistance (GMR) sensor for glycaemic index estimation. The GMR acquired pancreatic magnetic signal process with Multi Synchro Squeezing Transform (MSST) for feature extraction. The MSST analysis shows significant changes in instantaneous frequency of the pancreas biomagnetic signal before and after meal consumption. The signal statistical parameters help to predict glycaemic index via regression modelling. The proposed method estimates glycaemic index with 88% accuracy.

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17

Myke-Mbata, Blessing, Simeon Adelani Adebisi, Terry Terfa Gbaa, and Basil Bruno. "Effect of cassava on proximate composition, insulin index, glycemic profile, load, and index in healthy individuals: a cross-sectional study." Functional Foods in Health and Disease 11, no. 1 (January 26, 2021): 1. http://dx.doi.org/10.31989/ffhd.v11i1.772.

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Background: The major challenge in Africa is the growing prevalence of metabolic syndrome which has been attributed to changing lifestyles in developing countries. The impact of the commonly available staple starchy food; eaten in this environment may also be a factor contributing to growing concerns of metabolic syndrome. Hence, the need to assess the affordable staple starchy foods. Cassava is the most consumed staple starchy food in our environment; therefore, our study evaluated its impact on glycaemic and insulin response in consumers.Aim: To determine Insulin Index (II), glycaemic profile (GP), glycaemic load (GL) and Glycaemic Index (GI), incremental glucose peak value (IGPV), and glycaemic profile index (GPI) of cassava food meals.Methods: Participants ingested three cassava processed products (cassava dough [fufu], chips [Abacha], and flakes [garri] (the equivalent of 50g glucose) and 50 g of reference meal (glucose solution). Fasting and post-prandial samples were taken for blood glucose and insulin however sample for glucose was taken at intervals of 30 mins to a maximum of 180mins and 120 mins for insulin, respectively.Result: The GI for cassava dough, flakes and chips were 93.26; 95.92 and 91.94, respectively. Their glycaemic load was 46.62; 47.96 and 45.97, respectively. The glycaemic profile index was 37.34; 41.41 and 46.19, respectively. In addition, the insulin index was 55.83; 69.36 and 97.02. The proximate analysis showed protein, moisture, fibre, fat, ash, and carbohydrate content as follows the cassava (%) (crude form) 1.075%; 72.00%; 0.80%; 0.58%; 0.35%; 25.07%, Chips 1.44%; 59.13%; 0.73%; 1.71%; 36.83%, flakes 1.82%; 67.36%; 0.15%; 0.91%; 0.25%; 39.64% and dough 1.56%; 67.51%; 0.21%; 0.52%; 0.20%; 30.22% respectively.Conclusion: II, GP, GL, and GI of cassava dough (fufu), cassava flakes(garri)and cassava chips (Abacha) were found to be high. Unregulated dietary intake in adults may lead to metabolic diseases.Keywords: Glycaemic index, Glycaemic load, Glycaemic profile, Cassava, Makurdi

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18

Mayer-Davis, Elizabeth J., Ashish Dhawan, Angela D. Liese, Karen Teff, and Mandy Schulz. "Towards understanding of glycaemic index and glycaemic load in habitual diet: associations with measures of glycaemia in the Insulin Resistance Atherosclerosis Study." British Journal of Nutrition 95, no. 2 (February 2006): 397–405. http://dx.doi.org/10.1079/bjn20051636.

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Epidemiologic studies have applied the glycaemic index (GI) and glycaemic load (GL) to assessments of usual dietary intake. Results have been inconsistent particularly for the association of GI or GL with diabetes incidence. We aimed to advance understanding of the GI and GL as applied to food frequency questionnaires (FFQ) by evaluating GI and GL in relation to plasma measures of glycaemia. Included were 1255 adults at a baseline examination (1994–6) and 813 who returned for the 5-year follow-up examination. Usual diet, at both examinations, was assessed by a validated FFQ. GI and GL were evaluated in relation to average fasting glucose (two measures at each examination) and 2h post-75g glucose load plasma glucose (baseline and follow-up), and glycated haemoglobin (A1c; follow-up only); using generalized linear models. Correlation coefficients (r) for GI and GL related to measures of glycaemia, adjusted for total energy intake, ranged from −0·004 to 0·04 (all NS) for both examinations. Adjustment for potential confounders, for fasting glucose in models for 2h glucose (to model incremental glucose) and for average fasting glucose in models for A1c (to account, in part, for overnight endogenous glucose production) also did not materially alter findings, nor did inclusion of data from both examinations together in linear mixed models. The present results call into question the utility of GI and GL to reflect glycaemic response to food adequately, when used in the context of usual diet. Further work is needed to quantify usual dietary exposures relative to glucose excursion and associated chronic glycaemia and other metabolic parameters.

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19

Pardo-Buitimea, Naysin Yaheko, Montserrat Bacardí-Gascón, Lidia Castañeda-González, and Arturo Jiménez-Cruz. "Glycaemic index and glycaemic load of three traditional Mexican dishes." International Journal of Food Sciences and Nutrition 63, no. 1 (July 29, 2011): 114–16. http://dx.doi.org/10.3109/09637486.2011.604306.

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20

Kamchansuppasin, Achiraya, Prapaisri P. Sirichakwal, Luksana Bunprakong, Uruwan Yamborisut, Ratchanee Kongkachuichai, Wantanee Kriengsinyos, and Jureeporn Nounmusig. "Glycaemic index and glycaemic load of commonly consumed Thai fruits." International Food Research Journal 28, no. 4 (August 1, 2021): 788–94. http://dx.doi.org/10.47836/ifrj.28.4.15.

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The present work was aimed to determine the glycaemic index (GI) and glycaemic load (GL) of commonly consumed Thai fruits for the potential risk of chronic diseases. Healthy subjects consumed 25 g available carbohydrate (fruits and glucose) in random order. Eighteen fruits were classified as low GI (26.5 - 54.8%) including jujube, unripe mango, banana (Kluai-Namwa, Kluai-Khai, and Kluai-Leb-Mu-Nang varieties), guava, tamarind, jackfruit, durian (Monthong and Chanee varieties), tangerine, longan, starfruit, pomelo (Thong Dee variety), sapodilla, white dragon fruit, sala, and rambutan. Fruits with medium GI (55.4 - 69.6%) includes pomelo (Kao Nampheung variety), banana (Kluai Hom variety), red dragon fruit, watermelon, coconut, mangosteen, longkong, ripe mango, papaya, rose apple, and lychee. Pineapple has a high GI value. Most of the studied fruits were classified as low GL except for tamarind, red dragon fruit, mangosteen, lychee, and pineapple which were classified as medium GL. Various kinds of Thai fruits provided different GI and GL values. Therefore, low GI fruit with low GL regimen can be considered as alternative food sources to be used for diet manipulation in diabetic patients as well as in healthy population.

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21

Walton, Peter, and Edward C. Rhodes. "Glycaemic Index and Optimal Performance." Sports Medicine 23, no. 3 (March 1997): 164–72. http://dx.doi.org/10.2165/00007256-199723030-00003.

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22

Thorburn, Anne W., Jennie C. Brand, and A. Stewart Truswell. "The glycaemic index of foods." Medical Journal of Australia 144, no. 11 (May 1986): 580–82. http://dx.doi.org/10.5694/j.1326-5377.1986.tb112314.x.

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23

Arens, Ursula. "1 Glycaemic index goes international." Nutrition Bulletin 21, no. 3 (September 1996): 163–65. http://dx.doi.org/10.1111/j.1467-3010.1996.tb00846.x.

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24

Theobald, H. E. "Glycaemic index: what's the story?" Nutrition Bulletin 29, no. 4 (December 2004): 291–94. http://dx.doi.org/10.1111/j.1467-3010.2004.00452.x.

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25

Buttriss, Judy. "Glycaemic index: a meaningful measure?" Nutrition Bulletin 27, no. 1 (March 2002): 61–64. http://dx.doi.org/10.1046/j.1467-3010.2002.00214.x.

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26

Poli, Andrea. "On the glycaemic index again." Nutrafoods 12, no. 4 (December 2013): 115. http://dx.doi.org/10.1007/s13749-013-0060-4.

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27

Augustin, Livia S. A. "Glycaemic index in chronic disease." Nutrafoods 12, no. 4 (December 2013): 117–25. http://dx.doi.org/10.1007/s13749-013-0061-3.

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28

Borczak, Barbara, Marek Sikora, Elżbieta Sikora, Anna Dobosz, and Joanna Kapusta-Duch. "Glycaemic index of wheat bread." Starch - Stärke 70, no. 1-2 (October 4, 2017): 1700022. http://dx.doi.org/10.1002/star.201700022.

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29

Flint, Anne, Bente K. Møller, Anne Raben, Dorthe Pedersen, Inge Tetens, Jens J. Holst, and Arne Astrup. "The use of glycaemic index tables to predict glycaemic index of composite breakfast meals." British Journal of Nutrition 91, no. 6 (June 2004): 979–89. http://dx.doi.org/10.1079/bjn20041124.

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The applicability of the glycaemic index (GI) in the context of mixed meals and diets is still debatable. The objective of the present study was to investigate the predictability of measured GI in composite breakfast meals when calculated from table values, and to develop prediction equations using meal components. Furthermore, we aimed to study the relationship between GI and insulinaemic index (II). The study was a randomised cross-over meal test including twenty-eight healthy young men. Thirteen breakfast meals and a reference meal were tested. All meals contained 50 g available carbohydrate, but differed considerably in energy and macronutrient composition. Venous blood was sampled for 2 h and analysed for glucose and insulin. Prediction equations were made by regression analysis. No association was found between predicted and measured GI. The meal content of energy and fat was inversely associated with GI (R20·93 and 0·88, respectively;P<0·001). Carbohydrate content (expressed as percentage of energy) was positively related to GI (R20·80;P<0·001). Using multivariate analysis the GI of meals was best predicted by fat and protein contents (R20·93;P<0·001). There was no association between GI and II. In conclusion, the present results show that the GI of mixed meals calculated by table values does not predict the measured GI and furthermore that carbohydrates do not play the most important role for GI in mixed breakfast meals. Our prediction models show that the GI of mixed meals is more strongly correlated either with fat and protein content, or with energy content, than with carbohydrate content alone. Furthermore, GI was not correlated with II.

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30

Tan, Wei Shuan Kimberly, Wei Jie Kevin Tan, Shalini D/O Ponnalagu, Katie Koecher, Ravi Menon, Sze-Yen Tan, and Christiani J. Henry. "The glycaemic index and insulinaemic index of commercially available breakfast and snack foods in an Asian population." British Journal of Nutrition 119, no. 10 (May 15, 2018): 1151–56. http://dx.doi.org/10.1017/s0007114518000703.

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AbstractA low-glycaemic-index (GI) breakfast has been shown to lower blood glucose levels throughout the day. A wide variety of breakfast foods are consumed, but their GI values are largely unknown, hence limiting consumers’ ability to select healthier options. This study investigated the GI values of ten common breakfast (five Asian and five Western) foods in this region using a randomised, cross-over study design. Participants arrived after an overnight fast, and fasting blood sample was taken before participants consumed test foods. Next, blood samples were taken at fixed intervals for 180 min. Glycaemic and insulinaemic responses to test foods were calculated as incremental AUC over 120 min, which were subsequently reported as glycaemic and insulinaemic indices. In all, nineteen healthy men (nine Chinese and ten Indians) aged 24·7 (sem 0·4) years with a BMI of 21·7 (sem 0·4) kg/m2 completed the study. Asian breakfast foods were of medium (white bun filled with red bean paste=58 (sem 4); Chinese steamed white bun=58 (sem 3)) to high GI (rice idli=85 (sem 4); rice dosa=76 (sem 5); upma=71 (sem 6)), whereas Western breakfast foods were all of low GI (whole-grain biscuit=54 (sem 5); whole-grain biscuit filled with peanut butter=44 (sem 3); whole-grain oat muesli=55 (sem 4); whole-grain oat protein granola=51 (sem 4); whole-grain protein cereal=49 (sem 3)). The GI of test foods negatively correlated with protein (rs−0·366), fat (rs−0·268) and dietary fibre (rs−0·422) (all P<0·001). GI values from this study contribute to the worldwide GI database, and may assist healthcare professionals in recommending low-GI breakfast to assist in lower daily glycaemia among Asians who are susceptible to type 2 diabetes mellitus.

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31

Monro, John, Kerry Bentley-Hewitt, and Suman Mishra. "Kiwifruit Exchanges for Increased Nutrient Richness with Little Effect on Carbohydrate Intake, Glycaemic Impact, or Insulin Response." Nutrients 10, no. 11 (November 8, 2018): 1710. http://dx.doi.org/10.3390/nu10111710.

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Background: Kiwifruit are nutrient-rich and have properties which indicate a low glycaemic impact compared with many cooked cereal foods, suggesting that they may be used for dietary enrichment of vitamin C without glycaemic cost. Aim: To develop tables for equi-carbohydrate and equi-glycaemic partial exchange of kiwifruit for glycaemic carbohydrate foods. Method: The available carbohydrate content of Zespri® Green and Zespri® SunGold kiwifruit was determined as sugars released during in vitro digestive analysis. Glycaemic potency was determined as grams of glucose equivalents (GGEs) in a clinical trial using 200 g (a two-kiwifruit edible portion) of each cultivar, non-diabetic subjects (n = 20), and a glucose reference. GGE values were also estimated for a range of carbohydrate foods in the New Zealand Food Composition Database for which available carbohydrate and glycaemic index values were available. The values allowed exchange tables to be constructed for either equi-carbohydrate or equi-glycaemic partial exchange of kiwifruit for the foods. Results: GGE values of both kiwifruit cultivars were low (“Hayward”, 6.6 glucose equivalents/100 g; “Zesy002”, 6.7 glucose equivalents/100 g). Partial equi-carbohydrate substitution of foods in most carbohydrate food categories substantially increased vitamin C with little change in glycaemic impact, while equi-glycaemic partial substitution by kiwifruit could be achieved with little change in carbohydrate intake. Conclusion: Equi-carbohydrate partial exchange of kiwifruit for starchy staple foods is a means of greatly increasing nutrient richness in a diet without the physiological costs of increased glycaemia and insulin responses or carbohydrate intake.

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32

Ford, Heather, and Gary Frost. "Glycaemic index, appetite and body weight." Proceedings of the Nutrition Society 69, no. 2 (April 28, 2010): 199–203. http://dx.doi.org/10.1017/s0029665110000091.

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Much interest has been focused on the relationship between glycaemic index and body-weight loss, some of which is fuelled by popular media. However, there is a number of potential mechanisms that could be triggered by reducing the glycaemic index of the carbohydrate consumed in the diet. For example, the effect of foods on the gastrointestinal tract and the effect on blood glucose both could lead to potential appetite effects. Acute meal studies seem to point to an effect of glycaemic index on appetite regulation. However, the results of longer-term studies of weight loss are not as clear. In the present review a possible reason for this variation in outcome from the weight-loss studies will be discussed. The present review focuses on the possibility that the fermentable fibre content of the low-glycaemic-index diet may be important in weight-loss efficacy. A novel receptor that binds SCFA, the products of carbohydrate fermentation, has recently been described on the enteroendocrine L-cell in the colon. This cell releases a number of anorectic hormones and could offer an explanation of the appetite suppressant effects of fermentable carbohydrates. It could also explain the variability in the results of glycaemic-index weight-loss studies.

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Li, Dongmei. "The Research on the Effect of the Food with Different Glycaemic Index and Glycaemic Load on the Immunity of Endurance Athletes." Open Biomedical Engineering Journal 9, no. 1 (October 19, 2015): 305–9. http://dx.doi.org/10.2174/1874120701509010305.

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For studying the effect of eating the food containing carbohydrates with different glycaemic index and glycaemic load 2 hours before athletics on the exercise tolerance and immune function, select 10 men long-distance endurance athletes, use not completely random balance repeated testing methods, randomized complete the three endurance tests. And each test interval is not less than seven days. The results suggest that there is no apparent effect of eating the food containing carbohydrates with different glycaemic index and glycaemic load 2 hours before athletics on the exercise tolerance and immune function. Compared with the glycaemic index and glycaemic load of food, the carbohydrate content of the diet before athletics may be the more important factor affecting the immune response in endurance sports.

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O'SULLIVAN, Therese A., Alexandra P. BREMNER, Pieta C. CEDARO, Sheila O'NEILL, and Philippa LYONS-WALL. "Glycaemic index and glycaemic load intake patterns in older Australian women." Nutrition & Dietetics 66, no. 3 (September 2009): 138–44. http://dx.doi.org/10.1111/j.1747-0080.2009.01357.x.

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Chun Yu Louie, Jimmy, Anette E. Buyken, Kristina Heyer, and Victoria M. Flood. "Dietary glycaemic index and glycaemic load among Australian children and adolescents." British Journal of Nutrition 106, no. 8 (May 18, 2011): 1273–82. http://dx.doi.org/10.1017/s0007114511001577.

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There are no published data regarding the overall dietary glycaemic index (GI) and glycaemic load (GL) of Australian children and adolescents. We therefore aim to describe the dietary GI and GL of participants of the 2007 Australian National Children's Nutrition and Physical Activity Survey (2007ANCNPAS), and to identify the main foods contributing to their GL. Children, aged 2–16 years, who provided two 24 h recalls in the 2007ANCNPAS were included. A final dataset of 4184 participants was analysed. GI of each food item was assigned using a previously published method. GL was calculated, and food groups contributing to the GL were described by age group and sex. The weighted mean dietary GI and GL of the participants were 54 (sd 5) and 136 (sd 44), respectively. Among the nutrients examined, Ca had the highest inverse relationship with GI (P < 0·001), while percentage energy from starch was most positively associated with GI. The association between fibre density and GI was modest, and percentage energy from sugar had an inverse relationship with GI. Daily dietary GL contributed by energy-dense and/or nutrient-poor (EDNP) items in subjects aged 14–16 years was more than doubled that of subjects aged 2–3 years. To conclude, Australian children and adolescents were having a high-GI dietary pattern characterised by high-starchy food intake and low Ca intake. A significant proportion of their dietary GL was from EDNP foods. Efforts to reduce dietary GI and GL in children and adolescents should focus on energy-dense starchy foods.

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Grout, Matthew, Daniel Lamport, and Julie Lovegrove. "Utilising the glycaemic index: An investigation of glycaemic response and cognition." Appetite 130 (November 2018): 305–6. http://dx.doi.org/10.1016/j.appet.2018.05.192.

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Silvera, Stephanie AN, Thomas E. Rohan, Meera Jain, Paul D. Terry, Geoffrey R. Howe, and Anthony B. Miller. "Glycaemic index, glycaemic load and risk of endometrial cancer: a prospective cohort study." Public Health Nutrition 8, no. 7 (October 2005): 912–19. http://dx.doi.org/10.1079/phn2005741.

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AbstractObjectiveHigh-glycaemic-load diets may increase endometrial cancer risk by increasing circulating insulin levels and, as a consequence, circulating oestrogen levels. Given the paucity of epidemiological data regarding the relationship between dietary glycaemic index and glycaemic load and endometrial cancer risk, we sought to examine these associations using data from a prospective cohort study.Design, setting and subjectsWe examined the association between dietary glycaemic load and endometrial cancer risk in a cohort of 49 613 Canadian women aged between 40 and 59 years at baseline who completed self-administered food-frequency questionnaires between 1982 and 1985. Linkages to national mortality and cancer databases yielded data on deaths and cancer incidence, with follow-up ending between 1998 and 2000.ResultsDuring a mean of 16.4 years of follow-up, we observed 426 incident cases of endometrial cancer. Hazard ratios for the highest versus the lowest quartile level of overall glycaemic index and glycaemic load were 1.47 (95% confidence interval (CI) = 0.90–2.41; P for trend = 0.14) and 1.36 (95% CI = 1.01–1.84; P for trend = 0.21), respectively. No association was observed between total carbohydrate or total sugar consumption and endometrial cancer risk. Among obese women (body mass index > 30 kg m−2) the hazard ratio for the highest versus the lowest quartile level of glycaemic load was 1.88 (95% CI = 1.08–3.29; P for trend = 0.54) and there was a 55% increased risk for the highest versus the lowest quartile level of glycaemic load among premenopausal women. There was also evidence to support a positive association between glycaemic load and endometrial cancer risk among postmenopausal women who had used hormone replacement therapy.ConclusionsOur data suggest that diets with high glycaemic index or high glycaemic load may be associated with endometrial cancer risk overall, and particularly among obese women, premenopausal women and postmenopausal women who use hormone replacement therapy.

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Meynier, Alexandra, Aurélie Goux, Fiona Atkinson, Olivier Brack, and Sophie Vinoy. "Postprandial glycaemic response: how is it influenced by characteristics of cereal products?" British Journal of Nutrition 113, no. 12 (May 22, 2015): 1931–39. http://dx.doi.org/10.1017/s0007114515001270.

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Cereal products exhibit a wide range of glycaemic indexes (GI), but the interaction of their different nutrients and starch digestibility on blood glucose response is not well known. The objective of this analysis was to evaluate how cereal product characteristics can contribute to GI and insulinaemic index and to the parameters describing glycaemic or insulinaemic responses (incremental AUC, maximum concentration and Δpeak). Moreover, interactions between the different cereal products characteristics and glycaemic response parameters were assessed for the first time. Relationships between the cereal products characteristics and the glycaemic response were analysed by partial least square regressions, followed by modelling. A database including 190 cereal products tested by the usual GI methodology was used. The model on glycaemic responses showed that slowly digestible starch (SDS), rapidly digestible starch (RDS) and fat and fibres, and several interactions involving them, significantly explain GI by 53 % and Δpeakof glycaemia by 60 %. Fat and fibres had important contributions to glycaemic response at low and medium SDS contents in cereal products, but this effect disappears at high SDS levels. We showed also for the first time that glycaemic response parameters are dependent on interactions between starch digestibility (interaction between SDS and RDS) and nutritional composition (interaction between fat and fibres) of the cereal products. We also demonstrated the non-linear effect of fat and fibres (significant effect of their quadratic terms). Hence, optimising both the formula and the manufacturing process of cereal products can improve glucose metabolism, which is recognised as strongly influential on human health.

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Teixeira, Fabio A., Daniela P. Machado, Juliana T. Jeremias, Mariana R. Queiroz, Cristiana F. F. Pontieri, and Marcio A. Brunetto. "Effects of pea with barley and less-processed maize on glycaemic control in diabetic dogs." British Journal of Nutrition 120, no. 7 (August 22, 2018): 777–86. http://dx.doi.org/10.1017/s000711451800171x.

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AbstractThe source of starch may interfere with glycaemic control in dogs, but few studies have evaluated these aspects in diabetic dogs. This study compared the effects of two isonutrient diets with different starch sources, peas and barley (PB) v. maize (Mi), on diabetic dogs. The Mi diet was processed in order to generate a lower starch gelatinisation index. In all, fifteen adult diabetic dogs without other conditions were included. The animals were fed two dry extruded rations with moderate levels of fat and starch and high levels of protein and fibre using a random, double-blind cross-over design. Glycaemic curves over 48 h were developed via continuous glucose monitoring after 60 d on each diet and with the same neutral protamine Hagedorn (NPH) insulin dosage. The following were compared: fasting, mean, maximum and minimum blood glucose, maximum and minimum glycaemia difference, glycaemic increment, area under the glycaemic curve, area under the glycaemic increment curve and serum fructosamine concentration. Paired t tests or Wilcoxon signed-rank tests were used to compare the amount of food and nutrients ingested and the dietary effects on glycaemic variables between the diets. Dogs fed the PB diet presented a lower average mean interstitial glucose (P=0·01), longer mean hypoglycaemic time (P<0·01), shorter mean hyperglycaemic time (P<0·01) and smaller difference between maximum and minimum blood glucose levels (P=0·03). Thus, the processing applied to the Mi diet was not sufficient to achieve the same effects of PB on glycaemic control in diabetic dogs.

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Nugraheni, Mutiara, Sutriyati Purwanti, and Prihastuti Ekawatiningsih. "Chemical composition, glycaemic index, and antidiabetic property of analogue rice made from composite tubers, germinated legumes, and cereal flours." International Food Research Journal 29, no. 6 (December 6, 2022): 1304–13. http://dx.doi.org/10.47836/ifrj.29.6.07.

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The dependence on rice as a source of carbohydrates in Indonesia is among the highest in Asia. Innovations to develop products that can be used as a carbohydrate source, and have functional values beneficial to health are currently needed. The present work thus aimed to determine the chemical composition, glycaemic index, and antidiabetic property of three analogue rice types. The formulation of three types of analogue rice was done by combining natural tuber flour, modified tuber flour, germinated cereals, and germinated legumes. The glycaemic index was assessed using experimental animal. The antidiabetic properties of three types of analogue rice were assessed by food efficiency ratio, glucose profile, lipid profile, and atherogenic index. Results showed that analogue rice had high dietary fibre, resistant starch, and protein, and low fat and carbohydrate. The three types of analogue rice were classified as low glycaemic index based on glycaemic response tests. The glycaemic index of analogue rice I, II, and III were 41.23 ± 3.39, 42.55 ± 3.21, and 40.19 ± 3.34, respectively. The ability of analogue rice to decrease glucose, triglycerides, total cholesterol, low-density lipoprotein, atherogenic index; and increase high-density lipoprotein in diabetic mice was affected by its low glycaemic index and chemical composition benefits. The ability to improve the characteristics of glucose and lipids should support the development of analogue rice as a functional food.

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Wright, Hattie. "The glycaemic index and sports nutrition." South African Journal of Clinical Nutrition 18, no. 3 (December 2005): 222–28. http://dx.doi.org/10.1080/16070658.2005.11734071.

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Levi, F., C. Pasche, F. Lucchini, C. Bosetti, and C. La Vecchia. "Glycaemic index, breast and colorectal cancer." Annals of Oncology 13, no. 10 (October 2002): 1688–89. http://dx.doi.org/10.1093/annonc/mdf261.

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Beckwith, Sue. "The glycaemic index and its use." Practice Nursing 15, no. 8 (August 2004): 401–4. http://dx.doi.org/10.12968/pnur.2004.15.8.15382.

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Aston, Louise M. "Glycaemic index and metabolic disease risk." Proceedings of the Nutrition Society 65, no. 1 (February 2006): 125–34. http://dx.doi.org/10.1079/pns2005485.

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There is growing evidence that the type of carbohydrate consumed is important in relation to metabolic disease risk, and there is currently particular interest in the role of low-glycaemic-index (GI) foods. Observational studies have associated low-GI diets with decreased risk of type 2 diabetes and CHD, and improvements in various metabolic risk factors have been seen in some intervention studies. However, findings have been mixed and inconsistent. There are a number of plausible mechanisms for the effects of these foods on disease risk, which arise from the differing metabolic responses to low- and high-GI foods, with low-GI foods resulting in reductions in hyperglycaemia, hyperinsulinaemia and late postprandial circulating NEFA levels. Low-GI foods may also increase satiety and delay the return of hunger compared with high-GI foods, which could translate into reduced energy intake at later time points. However, the impact of a low-GI diet on body weight is controversial, with many studies confounded by dietary manipulations that differ in aspects other than GI. There is currently much interest in GI from scientists, health professionals and the public, but more research is needed before clear conclusions can be drawn about relationships with metabolic disease risk.

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Bornet, F. R. J., M. S. Billaux, and B. Messing. "Glycaemic index concept and metabolic diseases." International Journal of Biological Macromolecules 21, no. 1-2 (August 1997): 207–19. http://dx.doi.org/10.1016/s0141-8130(97)00066-4.

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Vervuert, I., and M. Coenen. "Glycaemic index of feeds for horses." Pferdeheilkunde Equine Medicine 21, no. 7 (2005): 79–82. http://dx.doi.org/10.21836/pem20050734.

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Mani, U. V., S. N. Pradhan, N. C. Mehta, D. M. Thakur, U. Iyer, and I. Mani. "Glycaemic index of conventional carbohydrate meals." British Journal of Nutrition 68, no. 2 (September 1992): 445–50. http://dx.doi.org/10.1079/bjn19920102.

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The glycaemic index (GI) and the triacylglycerol response were measured in thirty non-insulin-dependent diabetes mellitus patients given 50 g portions of five different conventional Indian meals containing semolina (Triticum aestivum) cooked by two different methods, or combinations of semolina and pulse (black gram dhal (Phaseolus mungo), green gram dhal (Phaseolus aureus) or Bengal gram dhal (Cicer arietum)). There were no significant differences among meals in mean GI except for meals based on roasted semolina or semolina-black gram dhal. Compared with the blood glucose response for a 50 g glucose load, only meals based on steam-cooked semolina and semolina-Bengal gram dhal elicited a significantly lower response at 1 h postprandially, and only meals based on semolina-black gram dhal at 2 h postprandially. No significant differences were found among the meals in the triacylglycerol response

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Chepulis, Lynne, and Evelyn Francis. "The glycaemic index of Manuka honey." e-SPEN Journal 8, no. 1 (February 2013): e21-e24. http://dx.doi.org/10.1016/j.clnme.2012.11.002.

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Lingegowda, V. "Review: low glycaemic-index diets reduce HbA1c more than high glycaemic-index diets in diabetes mellitus." Evidence-Based Medicine 14, no. 4 (July 31, 2009): 106. http://dx.doi.org/10.1136/ebm.14.4.106.

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McGowan, Ciara A., and Fionnuala M. McAuliffe. "The influence of maternal glycaemia and dietary glycaemic index on pregnancy outcome in healthy mothers." British Journal of Nutrition 104, no. 2 (March 23, 2010): 153–59. http://dx.doi.org/10.1017/s0007114510000425.

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Infant birth weight has increased in Ireland in recent years along with levels of childhood overweight and obesity. The present article reviews the current literature on maternal glycaemia and the role of the dietary glycaemic index (GI) and its impact on pregnancy outcomes. It is known that maternal weight and weight gain significantly influence infant birth weight. Fetal macrosomia (birth weight >4000 g) is associated with an increased risk of perinatal trauma to both mother and infant. Furthermore, macrosomic infants have greater risk of being obese in childhood, adolescence and adulthood compared to normal-sized infants. There is evidence that there is a direct relationship between maternal blood glucose levels during pregnancy and fetal growth and size at birth, even when maternal blood glucose levels are within their normal range. Thus, maintaining blood glucose concentrations within normal parameters during pregnancy may reduce the incidence of fetal macrosomia. Maternal diet, and particularly its carbohydrate (CHO) type and content, influences maternal blood glucose concentrations. However, different CHO foods produce different glycaemic responses. The GI was conceived by Jenkins in 1981 as a method for assessing the glycaemic responses of different CHO. Data from clinical studies in healthy pregnant women have documented that consuming a low-GI diet during pregnancy reduces peaks in postprandial glucose levels and normalises infant birth weight. Pregnancy is a physiological condition where the GI may be of particular relevance as glucose is the primary fuel for fetal growth.

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