Journal articles: 'Glycaemic load'

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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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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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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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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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YAMANOUCHI, Toshikazu, Tae INOUE, Eri OGATA, Akiko KASHIWABARA, Nobuyuki OGATA, Nori SEKINO, Tomoe YOSHIMURA, Kaoru ICHIYANAGI, and Takahiro KAWASAKI. "Post-load glucose measurements in oral glucose tolerance tests correlate well with 1,5-anhydroglucitol, an indicator of overall glycaemic state, in subjects with impaired glucose tolerance." Clinical Science 101, no. 3 (August 3, 2001): 227–33. http://dx.doi.org/10.1042/cs1010227.

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Using both cross-sectional and longitudinal methods, we investigated the relationship between post-load serum glucose concentration in a 75 g oral glucose tolerance test (OGTT) and overall glycaemic state in subjects with impaired glucose tolerance (IGT). Glycaemic state was assessed by measuring glycated haemoglobin (HbA1c) and the serum concentration of 1,5-anhydroglucitol (1,5-AG). In the cross-sectional study, the concentration of 1,5-AG, while remaining within a normal range, was reduced to a degree proportional to the post-load glycaemic level. Although the correlation between HbA1c and post-load plasma glucose was relatively weak (r = 0.281, P < 0.001), a significant inverse correlation (r =-0.824, P < 0.0001) was found between 1,5-AG and mean post-load plasma glucose concentration in 211 subjects with IGT. Fasting plasma glucose (r =-0.539, P < 0.0001) and 2 h plasma glucose (r =-0.621, P < 0.0001) were correlated with 1,5-AG less strongly than was post-load glycaemia. Both 1,5-AG and HbA1c were correlated weakly but significantly with the fasting insulin concentration. In the longitudinal study we measured 1,5-AG and mean post-load plasma glucose with an OGTT once yearly for 10 years in 15 subjects with IGT. Strong inverse correlations were seen between 1,5-AG and mean post-load plasma glucose in each subject (range of r values among subjects of -0.584 to -0.978). These findings suggest a close relationship between post-load plasma glucose concentration measured by OGTT and overall glycaemic state in subjects with IGT.

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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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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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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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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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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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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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Silvera, Stephanie AN, Meera Jain, Geoffrey R. Howe, Anthony B. Miller, and Thomas E. Rohan. "Glycaemic index, glycaemic load and ovarian cancer risk: a prospective cohort study." Public Health Nutrition 10, no. 10 (October 2007): 1076–81. http://dx.doi.org/10.1017/s1368980007696360.

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AbstractBackgroundThere is some evidence that plasma insulin levels might influence ovarian cancer risk. Glyacemic index (GI) and glycaemic load (GL) are measures that allow the carbohydrate content of individual foods to be classified according to their postprandial glycaemic effects and hence their effects on circulating insulin levels. Therefore, we examined ovarian cancer risk in association with GI and GL, and intake of dietary carbohydrate and sugar.MethodsThe study was conducted in a prospective cohort of 49 613 Canadian women enrolled in the National Breast Screening Study (NBSS) who completed a self-administered food-frequency questionnaire (FFQ) between 1980 and 1985. Linkages to national mortality and cancer databases yielded data on deaths and cancer incidence, with follow-up ending between 1998 and 2000. Data from the FFQ were used to estimate overall GI and GL, and Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between energy-adjusted quartile levels of GL, overall GI, total carbohydrates, total sugar and ovarian cancer risk.ResultsDuring a mean 16.4 years of follow-up, we observed 264 incident ovarian cancer cases. GI and total carbohydrate and sugar intakes were not associated with ovarian cancer risk in the total cohort. GL was positively associated with a 72% increase in risk of ovarian cancer (HR = 1.72, 95% CI = 1.13–2.62, Ptrend = 0.01) and the magnitude of the association was slightly greater among postmenopausal (HR = 1.89, 95% CI = 0.98–3.65, Ptrend = 0.03) than among premenopausal women (HR = 1.64, 95% CI = 0.95–2.88, Ptrend = 0.07).ConclusionsOur data suggest that consumption of diets with high GL values may be associated with increased risk of ovarian cancer.

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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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Al-Mssalle, M. Q. "Consumption of Traditional Saudi Foods and Their Estimated Glycaemic Index and Glycaemic Load." Pakistan Journal of Nutrition 17, no. 11 (October 15, 2018): 518–23. http://dx.doi.org/10.3923/pjn.2018.518.523.

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Tavani, A. "Carbohydrates, dietary glycaemic load and glycaemic index, and risk of acute myocardial infarction." Heart 89, no. 7 (July 1, 2003): 722–26. http://dx.doi.org/10.1136/heart.89.7.722.

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Henry, C. Jeya K., Helen J. Lightowler, Caroline M. Strik, Hamish Renton, and Simon Hails. "Glycaemic index and glycaemic load values of commercially available products in the UK." British Journal of Nutrition 94, no. 6 (December 2005): 922–30. http://dx.doi.org/10.1079/bjn20051594.

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The objective of this paper is to provide glycaemic index (GI) and glycaemic load (GL) values for a variety of foods that are commercially available in the UK and to compare these with previously published values. Fasted subjects were given isoglucidic (50 or 25 g carbohydrate) servings of a glucose reference at least two to three times, and test foods once, on separate occasions. For each test food, tests were repeated in at least eight subjects. Capillary blood glucose was measured via finger-prick samples in fasting subjects (0 min) and at 15, 30, 45, 60, 90 and 120 min after the consumption of each test food. The GI of each test food was calculated geometrically by expressing the incremental area under the blood glucose response curve (IAUC) of each test food as a percentage of each subject's average IAUC for the reference food. GL was calculated as the product of the test food's GI and the amount of available carbohydrate in a reference serving size. The majority of GI values of foods tested in the current study compare well with previously published values. More importantly, our data set provides GI values of several foods previously untested and presents values for foods produced commercially in the UK.

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Levitan, Emily B., Murray A. Mittleman, and Alicja Wolk. "Dietary glycaemic index, dietary glycaemic load and incidence of myocardial infarction in women." British Journal of Nutrition 103, no. 7 (December 14, 2009): 1049–55. http://dx.doi.org/10.1017/s0007114509992674.

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The association of dietary glycaemic index (GI) and glycaemic load (GL) with CVD has been examined in several populations with varying results. We tested the hypothesis that women with diets high in GI or GL would have higher rates of myocardial infarction (MI), and the associations would be stronger in overweight women. We measured dietary GI and GL in 36 234 Swedish Mammography Cohort participants aged 48–83 years using FFQ. Cox models were used to calculate incidence rate ratios (RR) and 95 % CI for hospitalisation or death due to MI assessed using the Swedish inpatient and cause-of-death registers from 1 January 1998 until 31 December 2006. Over 9 years of follow-up, 1138 women were hospitalised or died due to a first MI. In multivariable-adjusted models, the RR comparing top to bottom quartile of dietary GI were 1·12 (95 % CI 0·92, 1·35, P-trend = 0·24), and the RR comparing top to bottom quartile of dietary GL were 1·22 (95 % CI 0·90, 1·65, P-trend = 0·23). Among overweight women, the RR comparing top to bottom quartile of dietary GI were 1·20 (95 % CI 0·91, 1·58, P-trend = 0·22), and the RR comparing top to bottom quartile of dietary GL were 1·45 (95 % CI 0·93, 2·25, P-trend = 0·16). There were no statistically significant associations of dietary GI or GL with MI in this population.

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Sun, Lijuan, Davina Elizabeth Mei Lee, Wei Jie Kevin Tan, Dinesh Viren Ranawana, Yu Chin Rina Quek, Hui Jen Goh, and Christiani Jeyakumar Henry. "Glycaemic index and glycaemic load of selected popular foods consumed in Southeast Asia." British Journal of Nutrition 113, no. 5 (February 26, 2015): 843–48. http://dx.doi.org/10.1017/s0007114514004425.

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The objective of the present study was to determine the glycaemic index (GI) and glycaemic load (GL) values of standard portion sizes of Southeast Asian traditional foods. A total of fifteen popular Southeast Asian foods were evaluated. Of these foods, three were soft drinks, while the other twelve were solid foods commonly consumed in this region. In total, forty-seven healthy participants (eighteen males and twenty-nine females) volunteered to consume either glucose at least twice or one of the fifteen test foods after a 10–12 h overnight fast. Blood glucose concentrations were analysed before consumption of the test food, and 15, 30, 45, 60, 90 and 120 min after food consumption, using capillary blood samples. The GI value of each test food was calculated by expressing the incremental area under the blood glucose response curve (IAUC) value of the test food as a percentage of each participant's average IAUC value, with glucose as the reference food. Among the fifteen foods tested, six belonged to low-GI foods (Ice Green Tea, Beehoon, Pandan Waffle, Curry Puff, Youtiao and Kaya Butter Toast), three belonged to medium-GI foods (Barley Drink, Char Siew Pau and Nasi Lemak), and the other six belonged to high-GI foods (Ice Lemon Tea, Chinese Carrot Cake, Chinese Yam Cake, Chee Cheong Fun, Lo Mai Gai and Pink Rice Cake). The GI and GL values of these traditional foods provide valuable information to consumers, researchers and dietitians on the optimal food choice for glycaemic control. Moreover, our dataset provides GI values of fifteen foods that were not previously tested extensively, and it presents values of foods commonly consumed in Southeast Asia.

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Di Rosa, Claudia, Elisa De Arcangelis, Virginia Vitelli, Salvatore Crucillà, Martina Angelicola, Maria Carmela Trivisonno, Francesco Sestili, et al. "Effect of Three Bakery Products Formulated with High-Amylose Wheat Flour on Post-Prandial Glycaemia in Healthy Volunteers." Foods 12, no. 2 (January 9, 2023): 319. http://dx.doi.org/10.3390/foods12020319.

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Both Glycaemic index (GI) and Glycaemic Load (GL) were introduced to measure the impact of a carbohydrate-containing food on blood glucose. From this perspective, high-amylose (HA) flours, with a higher percentage of resistant starch (RS), may represent a suitable raw material to improve the glycaemic response. The present work aims to investigate the GI of HA bakery products (biscuits, taralli and bread) compared to products obtained from conventional flour. Ten healthy volunteers were enrolled and their capillary blood glucose was measured every 15 min for 2 h after the consumption of HA and control products containing 50 g of available carbohydrates. On average, in the three bakery products, the amount of total starch replaced by RS was equal to 12%. HA biscuits and HA bread showed significantly lower GI than their control counterparts (p = 0.0116 and p = 0.011, respectively) and better glycaemic control. From the survey to assess liking and willingness to pay on HA snacks, HA packages received an average premium of €0.66 compared to control products. Although HA flour results in lower GI in both biscuits and bread, further studies are needed to evaluate the correct composition of HA products to have beneficial effects on post-prandial glycaemia.

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Gilsenan, Mary B., Eveline A. de Bruin, and Louise Dye. "The influence of carbohydrate on cognitive performance: a critical evaluation from the perspective of glycaemic load." British Journal of Nutrition 101, no. 7 (March 12, 2009): 941–49. http://dx.doi.org/10.1017/s0007114508199019.

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Links between nutrition and cognition are widely acknowledged. Within the context of short-term cognitive performance, carbohydrate has been the dietary component most commonly investigated. The majority of studies investigating the influence of carbohydrate on cognitive performance have employed oral glucose drink interventions followed by measures of performance on cognitive tests. More recently, studies have investigated the effect of different carbohydrates on cognitive performance rather than just pure glucose drinks. To date, studies have not been evaluated based on a standardised measure of glycaemic response, such as glycaemic load. The present review provides a critical evaluation of eight studies that have explored the relationships between food carbohydrate and cognitive performance and allow glycaemic load to be used as a basis for comparison. The key finding is that these provide insufficient evidence to support a consistent effect of glycaemic load on short-term cognitive performance. Future studies should employ consistent test methodologies and describe food interventions in more detail to facilitate meaningful comparisons and interpretations of results.

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Mohan, Viswanathan, Ganesan Radhika, Rangaswamy Mohan Sathya, Selvi Ramjothi Tamil, Anbazhagan Ganesan, and Vasudevan Sudha. "Dietary carbohydrates, glycaemic load, food groups and newly detected type 2 diabetes among urban Asian Indian population in Chennai, India (Chennai Urban Rural Epidemiology Study 59)." British Journal of Nutrition 102, no. 10 (July 9, 2009): 1498–506. http://dx.doi.org/10.1017/s0007114509990468.

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The aim of the study was to examine the association of dietary carbohydrates and glycaemic load with the risk of type 2 diabetes among an urban adult Asian Indian population. Adult subjects aged >20 years (n 1843) were randomly selected from the Chennai Urban Rural Epidemiology Study, in Chennai city in southern India. Dietary carbohydrates, glycaemic load and food groups were assessed using FFQ. Oral glucose tolerance tests were performed using 75 g glucose in all subjects. Diagnosis of diabetes was based on WHO Consulting Group criteria. OR for newly detected diabetes were calculated for carbohydrates, glycaemic load and specific food groups comparing subjects in the highest with those in the lowest quartiles, after adjustment for potential confounders such as age, sex, BMI, family history of diabetes, physical activity, current smoking, alcohol consumption and relevant dietary factors. We identified 156 (8·5 %) newly diagnosed cases of type 2 diabetes. Refined grain intake was positively associated with the risk of type 2 diabetes (OR 5·31 (95 % CI 2·98, 9·45); P < 0·001). In the multivariate model, after adjustment for potential confounders, total carbohydrate (OR 4·98 (95 % CI 2·69, 9·19), P < 0·001), glycaemic load (OR 4·25 (95 % CI 2·33, 7·77); P < 0·001) and glycaemic index (OR 2·51 (95 % CI 1·42, 4·43); P = 0·006) were associated with type 2 diabetes. Dietary fibre intake was inversely associated with diabetes (OR 0·31 (95 % CI 0·15, 0·62); P < 0·001). In urban south Indians, total dietary carbohydrate and glycaemic load are associated with increased, and dietary fibre with decreased, risk of type 2 diabetes.

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Miller, Carla K., Melissa Davis Gutschall, and Frank Lawrence. "The development of self-efficacy and outcome expectation measures regarding glycaemic load and the nutritional management of type 2 diabetes." Public Health Nutrition 10, no. 6 (June 2007): 628–34. http://dx.doi.org/10.1017/s1368980007249778.

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AbstractObjectiveTraditionally, carbohydrate has been the largest contributor to energy intake among people with diabetes, yet different carbohydrate foods produce different glycaemic responses. Glycaemic load represents the total glycaemic effect of the diet and influences glycaemic control. Adequate self-efficacy and outcome expectations are needed to change carbohydrate intake and to evaluate relevant interventions. The purpose of this research was to develop and test instruments regarding self-efficacy and outcome expectations for the adoption of a lower glycaemic load diet.DesignParticipants completed each instrument at their convenience and mailed the instruments to the investigators.Setting/subjectsA community sample of individuals 21–75 years of age with type 2 diabetes for ≥ 1 year (n = 108) was recruited.ResultsPrincipal components analysis revealed three factors on the self-efficacy questionnaire: glycaemic index, negative food selection and self-regulation efficacy which accounted for 62% of the variance in these items. The outcome expectations instrument yielded three factors: barriers to dietary change and glycaemic control, and family support expectations which accounted for 48% of the variance. Coefficient α for each construct was >0.70 and coefficientHfor each construct was ≥ 0.80.ConclusionsThe two instruments developed for this study can provide important insights about the self-efficacy and outcome expectations regarding the quantity and quality of carbohydrate consumed and self-monitoring performed for diabetes management. Future research is needed to evaluate the relationship among these constructs, dietary intake and glycaemic control.

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Osman, Nur Maziah Hanum, Barakatun Nisak Mohd Yusof, and Amin Ismail. "Glycaemic index and glycaemic load of foods and food products in Malaysia: a review." International Food Research Journal 28, no. 2 (April 1, 2021): 217–29. http://dx.doi.org/10.47836/ifrj.28.2.01.

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Glycaemic index (GI) is a method used to classify the type of carbohydrate-rich foods according to their effect on postprandial glycaemic responses. While the GI concept provides a measure of carbohydrate quality, glycaemic load (GL) quantifies the overall glycaemic effects by considering both the quality and quantity of carbohydrate-rich foods. The higher the GI and GL of the foods, the greater the elevation of blood glucose and insulin demand. Reduction in dietary GI and GL are associated with the prevention and control of chronic diseases, including type 2 diabetes. Although the GI concept has been applied in various nutrition-related interventions in Malaysia, a reliable database on Malaysian foods and food products are scarce. This review attempts to determine and compile reliable data of GI and GL values of Malaysian foods and food products. A literature search was performed using predefined terms and criteria not only limited to web-based databases (n = 20), but included abstracts (n = 6) and manufacturer (n = 1). The GL value for each food was calculated. A total of 83 foods was identified with the most common being rice (25.3%) and bread (16.9%), either eaten alone or in mixed meals. Food with the highest GI value was sago (GI = 156; GL = 59), while food with the lowest GI value was spaghetti with chicken soup (GI = 35; GL = 4). This review shows that the number of foods and food products with the assigned GI and GL values in Malaysia is still limited, which warrants for more studies in this area.

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Nielsen, Birgit M., Kirsten S. Bjørnsbo, Inge Tetens, and Berit L. Heitmann. "Dietary glycaemic index and glycaemic load in Danish children in relation to body fatness." British Journal of Nutrition 94, no. 6 (December 2005): 992–97. http://dx.doi.org/10.1079/bjn20051465.

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The aim of this study was to describe dietary glycaemic index (GI) and glycaemic load (GL) values in the diets of Danish children, and to examine the associations between dietary GI, GL and body fatness. Data were collected during 1997–8 as part of the European Youth Heart Study. The study population comprised 485 children aged 10 years and 364 children aged 16 years from Odense County, Denmark. Dietary GI and GL were estimated using international food tables, and the associations between energy-adjusted dietary GI, GL and body fatness were analysed by multiple linear regression. The mean daily dietary GI value was 85 (SD 6·9) with a range of 62–111. No significant differences were found between age groups and gender. The daily dietary GL was higher among boys aged 16, with a GL of 330 (sd 95) (P<0·05), compared with girls or younger boys. Dietary GL was higher among 10-year-old boys than girls (250 (sd 81) v. 230 (sd 66) P<0·05), whereas dietary GL among 16-year-old girls was 230 (sd 56). Neither dietary GI nor GL was associated with the sum of four skinfolds (ΣSF) among girls or among 10-year-old boys. Among 16-year-old boys, significant associations were observed between dietary GI and ΣSF (β+0·60, SE+0·21, P=0·006), and between dietary GL and ΣSF (β+0·15, SE+0.06, P=0·009). In conclusion, dietary GI and GL were positively associated with body fatness among Danish boys aged 16 years, whereas no associations were found among girls or younger boys.

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Grau, Katrine, Inge Tetens, Kirsten S. Bjørnsbo, and Berit L. Heitman. "Overall glycaemic index and glycaemic load of habitual diet and risk of heart disease." Public Health Nutrition 14, no. 1 (June 25, 2010): 109–18. http://dx.doi.org/10.1017/s136898001000176x.

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AbstractObjectiveTo test the hypothesis that diets with high glycaemic index (GI) and glycaemic load (GL) increase the risk of heart disease.DesignOverall GI and GL were assessed from 7 d diet records or diet history interviews.SettingInformation on hospitalization and death due to CVD and CHD was obtained from the National Register of Cause of Death and the National Register of Patients.SubjectsIn total 3959 adult Danes were – depending on time of entry – followed for 6–25 years until 31 December 1999.ResultsOverall GI was inversely associated with heart disease in men. The hazard ratios (95 % CI) for the 10th and 90th GI percentiles compared with the median were 1·38 (1·13, 1·68) and 0·90 (0·76, 1·07) for CVD morbidity, 1·45 (1·05, 1·99) and 0·81 (0·62, 1·06) for CVD mortality, and 1·31 (0·97, 1·76) and 0·65 (0·51, 0·84) for CHD morbidity. In male subjects GL was not associated with either outcome. In women no clear association between overall GI and heart disease was found, whereas positive non-linear associations were found for GL: at very high levels of GL, increase in GL was associated with increasing CVD and CHD morbidity.ConclusionsIn men low-GI diets were associated increased risk of heart disease and GL was not associated with heart disease. In women there was no clear association between GI and heart disease, but to some extent a positive association between GL and heart disease was observed as hypothesized.

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Saltaouras, Georgios, Patricia K. Shaw, Ann C. Fraser, Chris Hawes, Harry Smith, Louisa Handley, Helen Whitby, Sangeetha P. Thondre, and Helen J. Lightowler. "Glycaemic index, glycaemic load and dietary fibre characteristics of two commercially available fruit smoothies." International Journal of Food Sciences and Nutrition 70, no. 1 (June 11, 2018): 116–23. http://dx.doi.org/10.1080/09637486.2018.1481201.

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Giles, Graham G., Julie A. Simpson, Dallas R. English, Allison M. Hodge, Dorota M. Gertig, Robert J. MacInnis, and John L. Hopper. "Dietary carbohydrate, fibre, glycaemic index, glycaemic load and the risk of postmenopausal breast cancer." International Journal of Cancer 118, no. 7 (April 1, 2006): 1843–47. http://dx.doi.org/10.1002/ijc.21548.

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Puspareni, Luh Desi, A'immatul Fauziyah, and Sofia Wardhani. "Are Glycaemic Response, Glycaemic Index, and Glycaemic Load of Traditional Palm Sugar (Arenga pinnata) Different from Cane Sugar?: An Oral Glucose Tolerance Test." Amerta Nutrition 6, no. 2 (June 6, 2022): 206–11. http://dx.doi.org/10.20473/amnt.v6i2.2022.206-211.

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Background: Palm sugar (Arenga pinnata) is believed to benefit people with diabetes mellitus since they believe it has a low glycemic index. However, the total carbohydrates in palm sugar, particularly sucrose, are high. Thus, offering palm sugar to diabetic people still needs further studies.Objectives: The purpose of this study was to examine differences in the glycemic response, glycemic index, and glycemic load of palm sugar compared to cane sugar.Methods: This study used an experimental design. Measurement of the oral glucose tolerance test (OGTT) through the finger-prick capillary blood test method. The main materials in this study were commercial white cane sugar as reference food and traditional palm sugar product of Lebak District, Banten Province, as a test food. Reference food and test food were provided equivalent to 50 g available carbohydrate dissolved in 250 ml mineral water subjected to 5 men and 5 women. The glycemic response was determined by the area under the curve (AUC) of the trapezoid method. The difference in glycemic response between the reference food and the test food was assessed using the independent sample t-test.Results: The peak of the increase in blood glucose occurred at 30 minutes. There was no difference in glycemic response between the reference food and the test food (p-value 0.685). The palm sugar glycemic index was 98.71 and was categorized into the high GI category. Meanwhile, the glycemic load of palm sugar and cane sugar was 11.80 and 12.22, those categorized into the medium GL category.Conclusions: No differences in glycemic response between palm sugar and cane sugar. The glycemic index of palm sugar was considered high and was not significantly different from cane sugar. The glycemic load of palm sugar and cane sugar was classified as moderate due to the small serving size. Using palm sugar less than cane sugar was expected to provide a lower glycemic response, glycemic index, and glycemic load.

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Moreland, N. "Liraglutide lightens glycaemic load in type 2 diabetes." Inpharma Weekly &NA;, no. 1596 (July 2007): 11–12. http://dx.doi.org/10.2165/00128413-200715960-00020.

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Keshteli, A. H., F. Haghighatdoost, L. Azadbakht, H. Daghaghzadeh, C. Feinle-Bisset, H. Afshar, A. Feizi, A. Esmaillzadeh, and P. Adibi. "Dietary glycaemic index and glycaemic load and upper gastrointestinal disorders: results from the SEPAHAN study." Journal of Human Nutrition and Dietetics 30, no. 6 (June 20, 2017): 714–23. http://dx.doi.org/10.1111/jhn.12480.

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van Bakel, M. M. E., R. Kaaks, E. J. M. Feskens, S. Rohrmann, A. A. Welch, V. Pala, K. Avloniti, et al. "Dietary glycaemic index and glycaemic load in the European Prospective Investigation into Cancer and Nutrition." European Journal of Clinical Nutrition 63, S4 (November 2009): S188—S205. http://dx.doi.org/10.1038/ejcn.2009.81.

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Melekoglu, Ebru, Dincer Goksuluk, and Emine Akal Yildiz. "Association between Dietary Glycaemic Index and Glycaemic Load and Adiposity Indices in Polycystic Ovary Syndrome." Journal of the American College of Nutrition 39, no. 6 (December 30, 2019): 537–46. http://dx.doi.org/10.1080/07315724.2019.1705200.

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Herrera, Christopher P., Keir Smith, Fiona Atkinson, Patricia Ruell, Chin Moi Chow, Helen O'Connor, and Jennie Brand-Miller. "High-glycaemic index and -glycaemic load meals increase the availability of tryptophan in healthy volunteers." British Journal of Nutrition 105, no. 11 (February 24, 2011): 1601–6. http://dx.doi.org/10.1017/s0007114510005192.

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The purpose of the present study was to determine the influence of the glycaemic index (GI) and glycaemic load (GL) on the ratio of tryptophan (TRP) relative to other large neutral amino acids (LNAA). Ten healthy men (age 22·9 (sd3·4) years; BMI 23·5 (sd1·6) kg/m2) underwent standard GI testing, and later consumed each of a mixed-macronutrient (1915 kJ; 66·5 % carbohydrate (CHO), 17 % protein and 16·5 % fat) high-GI (MHGI), an isoenergetic, mixed-macronutrient low-GI (MLGI) and a CHO-only (3212 kJ; 90 % CHO, 8 % protein, 2 % fat) high-GI (CHGI) meal on separate days. The GI, GL and insulin index values (e.g. area under the curve) were largest after the CHGI meal (117, 200, 158), followed by the MHGI (79, 59, 82) and MLGI (51, 38, 56) meals, respectively (all values were significantly different,P < 0·05). After the MHGI and MLGI meals but not after the CHGI meal, TRP was elevated at 120 and 180 min (P < 0·05). After the CHGI, LNAA was lower compared with the MLGI (P < 0·05); also the rate of decline in LNAA was higher after CHGI compared with MHGI and MLGI (both comparisonsP < 0·05). The percentage increase from baseline in TRP:LNAA after CHGI (23 %) was only marginally higher than after the MHGI meal (17 %;P = 0·38), but it was threefold and nearly significantly greater than MLGI (8 %;P = 0·05). The present study demonstrates that the postprandial rise in TRP:LNAA was increased by additional CHO ingestion and higher GI. Therefore, the meal GL appears to be an important factor influencing the postprandial TRP:LNAA concentration.

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Qin, Bo, Patricia G. Moorman, Anthony J. Alberg, Jill S. Barnholtz-Sloan, Melissa Bondy, Michele L. Cote, Ellen Funkhouser, et al. "Dietary carbohydrate intake, glycaemic load, glycaemic index and ovarian cancer risk in African-American women." British Journal of Nutrition 115, no. 4 (December 16, 2015): 694–702. http://dx.doi.org/10.1017/s0007114515004882.

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AbstractEpidemiological evidence regarding the association between carbohydrate intake, glycaemic load (GL) and glycaemic index (GI) and risk of ovarian cancer has been mixed. Little is known about their impact on ovarian cancer risk in African-American women. Associations between carbohydrate quantity and quality and ovarian cancer risk were investigated among 406 cases and 609 controls using data from the African American Cancer Epidemiology Study (AACES). AACES is an ongoing population-based case–control study of ovarian cancer in African-Americans in the USA. Cases were identified through rapid case ascertainment and age- and site-matched controls were identified by random-digit dialling. Dietary information over the year preceding diagnosis or the reference date was obtained using a FFQ. Multivariable logistic regression models were used to estimate odds ratios and 95 % CI adjusted for covariates. The OR comparing the highest quartile of total carbohydrate intake and total sugar intake v. the lowest quartile were 1·57 (95 % CI 1·08, 2·28; Ptrend=0·03) and 1·61 (95 % CI 1·12, 2·30; Ptrend<0·01), respectively. A suggestion of an inverse association was found for fibre intake. Higher GL was positively associated with the risk of ovarian cancer (OR 1·18 for each 10 units/4184 kJ (1000 kcal); 95 % CI 1·04, 1·33). No associations were observed for starch or GI. Our findings suggest that high intake of total sugars and GL are associated with greater risk of ovarian cancer in African-American women.

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Sluik, Diewertje, Fiona S. Atkinson, Jennie C. Brand-Miller, Mikael Fogelholm, Anne Raben, and Edith J. M. Feskens. "Contributors to dietary glycaemic index and glycaemic load in the Netherlands: the role of beer." British Journal of Nutrition 115, no. 7 (February 9, 2016): 1218–25. http://dx.doi.org/10.1017/s0007114516000052.

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AbstractDiets high in glycaemic index (GI) and glycaemic load (GL) have been associated with a higher diabetes risk. Beer explained a large proportion of variation in GI in a Finnish and an American study. However, few beers have been tested according to International Organization for Standardization (ISO) methodology. We tested the GI of beer and estimated its contribution to dietary GI and GL in the Netherlands. GI testing of pilsner beer (Pilsner Urquell) was conducted at The University of Sydney according to ISO international standards with glucose as the reference food. Subsequently, GI and GL values were assigned to 2556 food items in the 2011 Dutch food composition table using a six-step methodology and consulting four databases. This table was linked to dietary data from 2106 adults in the Dutch National Food Consumption Survey 2007–2010. Stepwise linear regression identified contribution to inter-individual variation in dietary GI and GL. The GI of pilsner beer was 89 (sd 5). Beer consumption contributed to 9·6 and 5·3 % inter-individual variation in GI and GL, respectively. Other foods that contributed to the inter-individual variation in GI and GL included potatoes, bread, soft drinks, sugar, candy, wine, coffee and tea. The results were more pronounced in men than in women. In conclusion, beer is a high-GI food. Despite its relatively low carbohydrate content (approximately 4–5 g/100 ml), it still made a contribution to dietary GL, especially in men. Next to potatoes, bread, sugar and sugar-sweetened beverages, beer captured a considerable proportion of between-person variability in GI and GL in the Dutch diet.

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Al Dhaheri, Ayesha S., C. Jeyakumar K. Henry, Maysm N. Mohamad, Eric O. Ohuma, Leila Cheikh Ismail, Fatima T. Al Meqbaali, and Amjad H. Jarrar. "Glycaemic index and glycaemic load values of commonly consumed foods in the United Arab Emirates." British Journal of Nutrition 117, no. 8 (April 28, 2017): 1110–17. http://dx.doi.org/10.1017/s0007114517001027.

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AbstractGlycaemic index (GI) and glycaemic load (GL) values of some commonly consumed foods in the United Arab Emirates were determined with an aim of adding these values to the existing international table of GI and GL values. In all, eighteen test foods categorised into breads (n5), entrée dishes (n3), main dishes (n5) and sweet dishes (n5) were tested. For each test food, at least fifteen healthy participants consumed 25 or 50 g available carbohydrate portions of a reference food (glucose), which was tested three times, and a test food after an overnight fast, was tested once, on separate occasions. Capillary blood samples were obtained by finger-prick and blood glucose was measured using clinical chemistry analyser. A fasting blood sample was obtained at baseline and before consumption of test foods. Additional blood samples were obtained at 15, 30, 45, 60, 90 and 120 min after the consumption of each test food. The GI value of each test food was calculated as the percentage of the incremental area under the blood glucose curve (IAUC) for the test food of each participant divided by the average IAUC for the reference food of the same participant. The GI values of tested foods ranged from low (55 or less) to high (70 or more). The GI values of various breads and rice-containing dishes were comparable with previously published values. This study provides GI and GL values of previously untested traditional Emirati foods which could provide a useful guide on dietary recommendations for the Emirati population.

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Mullie, Patrick, Benedicte Deforche, Evelien Mertens, Ruben Charlier, Sara Knaeps, Johan Lefevre, and Peter Clarys. "Low 10-year reproducibility of glycaemic index and glycaemic load in a prospective cohort study." British Journal of Nutrition 120, no. 2 (June 27, 2018): 227–30. http://dx.doi.org/10.1017/s0007114518001459.

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AbstractWhen relating glycaemic index (GI) and glycaemic load (GL) to health outcomes, many prospective cohort studies assess the nutritional exposure only once in time, that is, at the start of the study, presuming a stability in nutritional consumption during the course of the study. The aim of this study is to investigate the reproducibility of GI and GL. This is a prospective cohort study in which 562 middle-aged Belgian adults noted all foods and drinks consumed during 3 d in 2002 and 2012. GI and GL were calculated after reference tables. The Pearson correlation coefficients between 2002 and 2012 were 0·27 for GI and 0·41 for GL. For GI, 33 % of the participants remained in the same quintile between 2002 and 2012, whereas 31 % moved to a non-adjacent quintile. For GL, this was 34 and 28 %, respectively. The lowest and the highest quintiles of GI were the most stable, with 40 and 44 % of the participants staying in the same quintile. This was only 22 % for the fourth quintile. The same tendency was present for GL – that is, the most extreme quintiles were the most stable. This study shows 10-year correlation coefficients for GI and GL below 0·50. Multiple nutritional assessments and limiting the analysis to the extreme quintiles of GI and GL will limit a possible misclassification in the prospective cohort studies owing to the low reproducibility.

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Mulholland, H. G., L. J. Murray, C. R. Cardwell, and M. M. Cantwell. "Dietary glycaemic index, glycaemic load and breast cancer risk: a systematic review and meta-analysis." British Journal of Cancer 99, no. 7 (August 26, 2008): 1170–75. http://dx.doi.org/10.1038/sj.bjc.6604618.

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Wilson, Claire A., Paul Seed, Angela C. Flynn, Louise M. Howard, Emma Molyneaux, Julie Sigurdardottir, and Lucilla Poston. "Is There an Association Between Diet, Physical Activity and Depressive Symptoms in the Perinatal Period? An Analysis of the UPBEAT Cohort of Obese Pregnant Women." Maternal and Child Health Journal 24, no. 12 (April 30, 2020): 1482–93. http://dx.doi.org/10.1007/s10995-020-02933-3.

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Abstract Introduction Depression is a common morbidity of the perinatal period (during pregnancy and up to one year postpartum). There is evidence for an association between diet and physical activity, and depression in the non-pregnant population but this association has been relatively less explored during the perinatal period; particularly poorly understood is the relationship between specific dietary components and depression. The aim of this study was to explore the association between glycaemic load, saturated fat intake and physical activity and depressive symptoms in a high-risk population of obese pregnant women. Methods In a cohort of 1522 women participating in the UPBEAT trial, physical activity, glycaemic load and saturated fat intake were used as predictors of depressive symptoms measured using the Edinburgh Postnatal Depression Scale (EPDS). Measures taken in early pregnancy were used in linear and logistic regression models. Repeated measures at three points during pregnancy and at six months postpartum were utilised in multilevel mixed effects models. Multiple imputation was used to account for missing data. Results Increased glycaemic load was associated with small increases in levels of depressive symptoms across the perinatal period (adjusted beta coefficient 0.01; 95% CI 0.01,0.02). There was no evidence for an association between reduced physical activity and increased saturated fat intake and increased levels of depressive symptoms. Conclusions Glycaemic load may be a useful focus for interventions aiming to optimise the mental health of obese women in the perinatal period.

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Górecka, Danuta, Patrycja Komolka, Krzysztof Dziedzic, and Jarosław Walkowiak. "The Influence of Thermal Processing of Fruit and Vegetables on Their Glycaemic Index and Glycaemic Load*." Postępy Higieny i Medycyny Doświadczalnej 74 (June 26, 2020): 205–12. http://dx.doi.org/10.5604/01.3001.0014.2493.

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Aim: Diabetes is a metabolic disease caused, among others, by malnutrition. Therefore, more attention is paid to products containing carbohydrates, as they increase the blood glucose concentration. In order to prevent type 2 diabetes and obesity, it is recommended to consume food with a low glycaemic index (GI) and glycaemic load (GL). The GI value of foodstuffs is influenced by their composition, as well as physicochemical and biochemical changes occurring in raw materials during technological processes. The aim of the study was to determine the influence of technological processing on the glycaemic index and glycaemic load values of selected vegetables and fruit. Material/Methods: The research was conducted on cruciferous vegetables, carrots, potatoes and apples. The raw materials underwent pretreatment, which included washing, peeling, shredding and thermal processing. In order to determine the glycaemic index, clinical trials were conducted on 20 healthy people of both sexes, aged 20–60 years, normal weight (BMI 18–24.5). The content of dietary fibre and its fractions was also measured in the products. Results: The thermal treatment influenced the GI and GL values of the food products and content of dietary fibre. The highest GI and GL values were measured in the boiled and baked products, whereas the GI and GL values of the steamed foodstuffs were slightly lower. Conclusions: The results let us conclude that adequate handling of raw materials, i.e. appropriate thermal processing, may limit the development of type 2 diabetes. Diabetic patients are advised to use steaming as the preferable method of thermal processing of foodstuffs.

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Kim, Do-Yeon, Yeajee Kim, and Hyunjung Lim. "Glycaemic indices and glycaemic loads of common Korean carbohydrate-rich foods." British Journal of Nutrition 121, no. 4 (December 27, 2018): 416–25. http://dx.doi.org/10.1017/s0007114518003446.

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AbstractGlycaemic index (GI) and glycaemic load (GL) values of foods consumed in Asia remain poorly characterised despite the fact that Asian diets are high in carbohydrates. We evaluated the GI and GL of the most commonly consumed carbohydrate-rich foods, according to food type and cooking methods. GI and GL values were determined using protocols from the FAO/WHO and International Standards Organization recommendations. A total of 152 healthy subjects were enrolled in the study. In all, forty-nine carbohydrate-rich foods were categorised as cereal grains, noodles and pasta, breads and other processed grains and starchy vegetables, prepared using standard cooking methods and evaluated. Cereal grains had the widest range of GI values that the food made with white rice and barley had GI values of 51–93 and 35–70, respectively, according to cooking methods, and most cereal grains had high GL values. Noodles and pasta had low to medium GI values, but most foods had high GL values. Breads had medium to high GI and GL values, while other processed grains had low to medium GI and GL values. The GI values for food made with starchy vegetables (e.g. potatoes and sweet potatoes) varied widely for different cooking methods but tended to have low GL values. In conclusion, GI values for a single food type varied widely with the cooking method used. This study of GI and GL values for common carbohydrate-rich foods provides a valuable reference for consumers and health professionals to make informed food choices for glycaemic control.

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Young, Hayley A., and David Benton. "Glycaemic load and cognition: comments concerning Marchand et al." British Journal of Nutrition 125, no. 1 (June 8, 2020): 101–2. http://dx.doi.org/10.1017/s0007114520001919.

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Lok, Kris Y., Ruth Chan, Dicken Chan, Liz Li, Grace Leung, Jean Woo, Helen J. Lightowler, and C. Jeya K. Henry. "Glycaemic index and glycaemic load values of a selection of popular foods consumed in Hong Kong." British Journal of Nutrition 103, no. 4 (September 28, 2009): 556–60. http://dx.doi.org/10.1017/s0007114509992042.

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The objective of the present paper is to provide glycaemic index (GI) and glycaemic load (GL) values for a variety of foods that are commonly consumed in Hong Kong and expand on the international GI table of Chinese foods. Fasted healthy subjects were given 50 g of available carbohydrate servings of a glucose reference, which was tested twice, and test foods of various brands of noodles (n5), instant cereals (n3) and breads (n2), which were tested once, on separate occasions. For each test food, tests were repeated in ten healthy subjects. Capillary blood glucose was measured via finger-prick samples in fasting subjects ( − 5, 0 min) and at 15, 30, 45, 60, 90 and 120 min after the consumption of each test food. The GI of each test food was calculated geometrically by expressing the incremental area under the blood glucose response curve (IAUC) of each test food as a percentage of each subject's average IAUC for the reference food. GL was calculated as the product of the test food's GI and the amount of available carbohydrate in a reference serving size. The majority of GI values of foods tested were medium (a GI value of 56–69) to high (a GI value of 70 or more) and compared well with previously published values. More importantly, our dataset provides GI values of ten foods previously untested and presents values for foods commonly consumed in Hong Kong.

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Choi, Yuni, Edward Giovannucci, and Jung Eun Lee. "Glycaemic index and glycaemic load in relation to risk of diabetes-related cancers: a meta-analysis." British Journal of Nutrition 108, no. 11 (October 18, 2012): 1934–47. http://dx.doi.org/10.1017/s0007114512003984.

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Diets high in glycaemic index (GI) or glycaemic load (GL) have been hypothesised to increase the risks of certain cancers by increasing blood glucose or insulin concentrations. We aimed to conduct a meta-analysis of prospective cohort studies to evaluate the association between GI or GL and diabetes-related cancers (DRC), including bladder, breast, colon–rectum, endometrium, liver and pancreas, which are associated with an increased risk for diabetes, and prostate cancer, which is associated with a reduced risk for diabetes. We searched Pubmed, EMBASE and MEDLINE databases up to September 2011 and reference lists of relevant articles. Relative risks (RR) and 95 % CI for the highest v. the lowest categories were extracted and pooled using a random-effects model. Thirty-six prospective cohort studies with a total of 60 811 DRC cases were included in the present meta-analysis. In a comparison of the highest and lowest categories, the pooled RR of DRC were 1·07 (95 % CI 1·04, 1·11; n 30) for GI and 1·02 (95 % CI 0·96, 1·08; n 33) for GL. In an analysis of site-specific cancer risks, we found significant associations for GI in relation to breast cancer (RR 1·06; 95 % CI 1·02, 1·11; n 11) and colorectal cancer (RR 1·08; 95 % CI 1·00, 1·17; n 9 studies). GL was significantly associated with the risk of endometrial cancer (RR 1·21; 95 % CI 1·07, 1·37; n 5). In conclusion, the findings of the present study suggest a modest-to-weak association between a diet that induces a high glucose response and DRC risks.

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Malavolti, Marcella, Carlotta Malagoli, Catherine M. Crespi, Furio Brighenti, Claudia Agnoli, Sabina Sieri, Vittorio Krogh, et al. "Glycaemic index, glycaemic load and risk of cutaneous melanoma in a population-based, case–control study." British Journal of Nutrition 117, no. 3 (February 14, 2017): 432–38. http://dx.doi.org/10.1017/s000711451700006x.

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AbstractGlycaemic index (GI) and glycaemic load (GL) are indicators of dietary carbohydrate quantity and quality and have been associated with increased risk of certain cancers and type 2 diabetes. Insulin resistance has been associated with increased melanoma risk. However, GI and GL have not been investigated for melanoma. We present the first study to examine the possible association of GI and GL with melanoma risk. We carried out a population-based, case–control study involving 380 incident cases of cutaneous melanoma and 719 age- and sex-matched controls in a northern Italian region. Dietary GI and GL were computed for each subject using data from a self-administered, semi-quantitative food frequency questionnaire. We computed the odds ratio (OR) for melanoma according to quintiles of distribution of GL and GL among controls. A direct association between melanoma risk and GL emerged in females (OR 2·38; 95 % CI 1·25, 4·52 for the highest v. the lowest quintile of GL score, Pfor trend 0·070) but not in males. The association in females persisted in the multivariable analysis after adjusting for several potential confounders. There was no evidence of an association between GI and melanoma risk. GL might be associated with melanoma risk in females.

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Henry, C. Jeya K., Helen J. Lightowler, Lis M. Dodwell, and Jacqueline M. Wynne. "Glycaemic index and glycaemic load values of cereal products and weight-management meals available in the UK." British Journal of Nutrition 98, no. 1 (July 2007): 147–53. http://dx.doi.org/10.1017/s000711450769179x.

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There is currently an increased global interest in the published glycaemic index (GI) values of foods. The aim of the present work was to supplement a previous study on the glycaemic response of 140 foods available in the UK by studying a further forty-four foods. One hundred and twenty-two healthy subjects, with a mean age of 32·4 (sd 11·4) years and a mean BMI of 23·6 (sd 3·6) kg/m2, were recruited to the study. Subjects were served equivalent available carbohydrate amounts (50 or 30 g) of test foods (cereal products and weight-management meals) and a standard food (glucose) on separate occasions. Capillary blood glucose was measured from finger-prick samples in fasted subjects (0 min) and at 15, 30, 45, 60, 90 and 120 min after starting to eat each test food. For each test food, the GI value was determined, and the glycaemic load was calculated as the product of the GI and the amount of available carbohydrate in a reference serving size. The GI values of the foods tested ranged from 23 to 83. Of the forty-four foods tested, thirty-three were classified as low-GI, eight as medium-GI and three as high-GI foods. Most GI values of the foods tested compared well with previously published values for similar foods. In summary, this study provides reliable GI and glycaemic load values for a range of foods, further advancing our understanding of the glycaemic response of different foods. The data reported here make an important addition to published GI values.

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Aveyard, Paul. "Sample of Aboriginal Australians, 2-hour post-load insulin concentrations are greatest between fasting plasma glucose values of 6.7-7.3 mmol/l." Diabetes and Islet Biology 1, no. 2 (September 6, 2018): 01–05. http://dx.doi.org/10.31579/2641-8975/009.

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Background: Prevention of diabetic complications requires good glycaemic control. This study aimed to provide type 2 diabetes patients with remote active care and glycaemic control through the use of videophone technology without the need for them to attend hospital. The literature recommends additional research to study the impact of technical innovations on improved disease self-management and medical outcome. This is the only study to be conducted in Turkey concerning patient monitoring using videophone technology. The aim of the study was to establish the effectiveness of the use of videophone technology in the glycaemic control of patients with diabetes living in remote areas. Methods: This is a prospective, randomized control study using the systematic sampling method (using half ratio), in which 24 patients were chosen for the Experimental Group (EG) and another 24 for the Control Group (CG). All of the patients agreed to participate in the study. Patients in the CG received routine care, while the glycaemic control and consultations for patients in the EG were conducted using videophone technology. The patients were monitored by videophone for a total of 6 months. The HbA1c and blood glucose values recorded over the 6 month monitoring period were analyzed to determine the effectiveness of using a videophone. Results: The mean age of the individuals in the EG was 54.41 ± 8.54 years (Min=43 Max=78) and in the CG it was 57.25 ± 9.61 (Min=40 Max=77). In both groups, 50% of the individuals were men and 50% were women. When the two groups were compared, it was was found that the preprandial blood glucose levels of the diabetic patients in the EG (mean 159.48 ± 40.71mg/dl) were lower by 13.55 ± 52.89 mg / dl than the preprandial blood glucose levels of the diabetic patients in the CG (mean 173.03 ± 65.07 mg/dl). It was determined at the end of the six-month monitoring that the A1c levels of the individuals in the EG were significinatly lowered by 0.49% in total, and that the A1c levels of the individuals in the CG were higher by 0.17 % in total. Conclusions: It was shown that videophone technology can be useful in the glycaemic control of diabetic patients in Turkey.

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Livesey, Geoffrey. "Low-glycaemic diets and health: implications for obesity." Proceedings of the Nutrition Society 64, no. 1 (February 2005): 105–13. http://dx.doi.org/10.1079/pns2004400.

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The present review considers the background to terminology that relates foods, glycaemia and health, including ‘available carbohydrate’, ‘glycaemic index’ (GI), 'glycaemic glucose equivalent', 'glycaemic response index' and 'net carbohydrate', and concludes that central to each of these terms is 'glycaemic load' (GL). GL represents the acute increase in exposure of tissue to glucose determined by foods; it is expressed in ingested glucose equivalents (per 100 g fresh weight or per serving), and is regarded as independent of the state of glucose metabolism from normal to type 2 diabetes mellitus (T2DM). Ad libitum studies in overweight or obese adults and children show that low-GL diets are associated with marked weight benefits, loss of adiposity and reduced food intake. Weight benefits appear on low-glycaemic v. high-glycaemic available carbohydrates, unavailable v. available carbohydrates and protein v. available carbohydrate. Energy intake immediately after lowering of meal GL via carbohydrate exchanges is apparent only after a threshold cumulative intake of >2000 MJ. Various epidemiological and interventional studies are discussed. A relationship between GL and the development of T2DM and CHD is evident. Studies that at first seem conflicting are actually consistent when data are overlaid, such that diets with a GL of >120 glucose equivalents/d would appear to be inadvisable. Whereas certain studies might place GI as being slightly stronger than GL in relationto T2DM risk, this situation appears to be associated with observations in a lower range of GL or when the range of GI is too narrow for accuracy; nevertheless, authors emphasise the importance of GL. Among the studies reviewed, GL offers a better or stronger explanation than GI in various observations including body weight, T2DM in nurses, CHD, plasma triacylglycerols, HDL-cholesterol, high-sensitivity C-reactive protein and protein glycation. Where information is available, the associations between risk factors and GL are either similar or stronger in the overweight or obese, as judged by BMI, and apply to both body weight and blood risk factors. The implications tend to favour a long-term benefit of reducing GL, for which further study is necessary to eliminate any possibility of publication bias and to establish results in clinical trials with overweight and obese patients.

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Journal articles on the topic 'Glycaemic load'

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