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Application of glycemic index to mixed meals
Abstract
Plasma glucose and insulin responses to six different meals were determined and compared with values predicted by published glycemic indices of the component foods. The test meals were of different ethnic origins: Indian (lentil curry with rice), Italian (spaghetti bolognaise), Chinese (stir-fried vegetables and chicken with rice), Greek (lentil stew), Western (sirloin chop and vegetables); and Lebanese (sandwich with unleavened bread and hummos). Eight healthy volunteers were given 50 g carbohydrate portions of the above meals after an overnight fast. The glycemic and insulin indices were highest for the Lebanese meal and lowest for the Greek with significant differences among the meals (ANOVA, p less than 0.05). The observed glycemic indices correlated well with the predicted glycemic indices (r = 0.88, p less than 0.01) and insulin responses parallelled the glycemic responses (r = 0.83, p less than 0.05). These results suggest that the glycemic index approach will be useful in planning diets for diabetic people.
... The m ain carbohydrate component in SG L is rice. Rice, as an individual food, has been tested extensively and the GIs varied widely between laboratories when compared to glucose and when compared to white bread [9,21]. M ixing the carbohydrate foods with a meal decreases their individual GI by 20% [12]. ...
... Consequently, the GI for rice decreased to 45 6 2% when incorporated in a m ixed meal. Chew et al. [9] studied the physiological responses to two different m ixed dishes containing riceÐ an Indian meal and a Chinese m ealÐ and obtained GIs of 60% and 73% , respectively. In the present study a lower GI value was obtained for SG L, possibly because the SGL m eal had a higher fat content than both m eals studied by Chew et al. [9]. ...
... Chew et al. [9] studied the physiological responses to two different m ixed dishes containing riceÐ an Indian meal and a Chinese m ealÐ and obtained GIs of 60% and 73% , respectively. In the present study a lower GI value was obtained for SG L, possibly because the SGL m eal had a higher fat content than both m eals studied by Chew et al. [9]. This fat content may also explain the lower GI of SG L as compared to KS in this study. ...
... The GI value of whole diets can be estimated in the same way. Although this approach does not adjust for the potential influence of fat or protein on slowing the digestion of the carbohydrates, the calculated GI values of meals are consistent with the ranking of observed glycemic responses in experimental studies (Chew et al. 1988, Wolever and Bolognesi 1996a, Wolever et al. 2006). ...
... A mixed meal containing a higher-GI starchy carbohydrate will have a greater glycemic response than a similar meal containing a Downloaded by [Taylor and Francis/CRC Press] at 06:01 17 November 2016 lower-GI carbohydrate, so the relative hierarchy of individual foods is maintained in the context of a meal. In addition, the glycemic response of a mixed meal can be reliably predicted from the GI values of the component foods (Chew et al. 1988, Wolever et al. 2006). ...
IntroductionDefinitionEvidence of Clinical BenefitsThe Practicalities of Using Low GI Foods in DiabetesFood IndustryGlycemic Index Tested ProgramConclusions
References
... Ahora bien, si se parte de la concepción de que la inmensa (Chew, Brand, Thorburn & Truswel, 1988). Hecho que determina aceptar el valor práctico del concepto carga glicémica (CG). ...
... En tal sentido, la CG se considera como el producto del IG, por la cantidad de hidratos de carbono asimilables contenidos en la porción de alimento que se utilice. Es decir, la carga glicémica cuantifica el impacto sobre la glucemia de una porción o ración habitual de un alimento con determinado IG. (Chew et al., 1988;Ludwig, 2002 Las proteínas constituyen sólo una fuente de energía menor durante el ejercicio aeróbico. Así, los adultos que realizan frecuentemente ejercicios intensos se pueden beneficiar de una ingesta superior a la recomendada para la población general, pero no existen datos similares para los niños y adolescentes, y desde un punto de vista práctico, no está claro cuándo y hasta qué punto las diferencias relacionadas con la edad deben ser consideradas cuando se planifica la dieta de un adolescente deportista ya que este ha sido un campo poco investigado hasta el momento (Grandjean, 1989;Hernández-Gallardo & Arencibia, 2002a Limitando la degradación proteica, la leucina puede permitir una nueva síntesis proteica post-ejercicio con sobrecarga, llevando a una mayor hipertrofia muscular. ...
... Both high (>100 g) and low (<100 g) lentil serving sizes had a favorable postprandial blood glucose and insulin lowering effect, making it difficult to identify the optimal lentils' serving size for beneficial dose response effects [34]. Results of the current investigation are consistent with another study that reported the lowest GI and glycemic responses after consumption of lentil soup with bread roll compared to five other starchy mixed meals [35]. Another study found a 71% reduction in glycemic responses after lentils with butter and tomatoes consumption compared to two wholemeal bread meals [36], similar to the 73% reduction observed in the current investigation. ...
Low glycemic index (GI) diets have been associated with decreased chronic disease risk. In a randomized, cross-over study we investigated the GI and glycemic response to three traditional Greek mixed meals: Lentils, Trahana, and Halva. Twelve healthy, fasting individuals received isoglucidic test meals (25 g available carbohydrate) and 25 g glucose reference, in random order. GI was calculated and capillary blood glucose (BG) samples were collected at 0–120 min after meal consumption. Subjective appetite ratings were assessed. All three tested meals provided low GI values. Lentils GI was 27 ± 5, Trahana GI was 42 ± 6, and Halva GI was 52 ± 7 on glucose scale. Peak BG values were lowest for Lentils, followed by Trahana and then by Halva (p for all <0.05). Compared to the reference food, BG concentrations were significantly lower for all meals at all time-points (p for all <0.05). Lentils provided lower glucose concentrations at 30 and 45 min compared to Trahana (p for all <0.05) and at 30, 45, and 60 min compared to Halva (p for all <0.05). BG concentrations did not differ between Trahana and Halva at all time points. No differences were observed for fasting BG, time to peak rise for BG, and subjective appetite ratings. In conclusion, all three mixed meals attenuated postprandial glycemic response in comparison to glucose, which may offer advantages to glycemic control.
... Other concerns related to dietary GI/GL estimation are whether foods consumed together may have an impact on each other to alter the GI/GL of the whole meal [16,68,69]. While some authors suggest that the GI of a meal can be calculated by adding the carbohydrate contributions of each constituent food multiplied by its published GI [13,70], another school of thought argues that a food is more than just the sum of its nutrients due to several chemical and physical interactions that may occur. Combining macronutrients was found to influence GI, the latter being positively associated with carbohydrate content and negatively associated with protein and fat content, which can significantly reduce the glycemic response [71]. ...
High dietary glycemic index (GI) and glycemic load (GL) were suggested to increase the risk of metabolic syndrome (MetS). This study aims to estimate dietary GI and GL in a sample of healthy Lebanese adults and examine their association with MetS and its individual abnormalities. The study uses data from a community-based survey of 501 Lebanese urban adults. Dietary intake was assessed using a food frequency questionnaire. Biochemical, anthropometric, and blood pressure measurements were obtained. Subjects with previous diagnosis of chronic disease, metabolic abnormalities, or with incomplete data or implausible energy intakes were excluded, yielding a sample of 283. Participants were grouped into quartiles of GI and GL. Multivariate logistic regression analyses were performed. Average dietary GI and GL were estimated at 59.9 ± 8 and 209.7 ± 100.3. Participants belonging to the highest GI quartile were at increased risk of having MetS (odds ratio (OR) = 2.251, 95% CI:1.120–4.525) but this association lost significance with further adjustments. Those belonging to the second quartile of GI had significantly lower odds of having hyperglycemia (OR: 0.380, 95% CI:0.174–0.833). No associations were detected between GL and MetS. The study contributes to the body of evidence discussing the relationship between GI, GL, and MetS, in a nutrition transition context.
... Meal patterns may affect the absolute glycemic response but do not affect the relative differences between foods (3)(4)(5). Metabolic studies using standardized methods indicated that the correlation between the glycemic index of mixed meals and the average glycemic indexes of individual component foods ranges from 0.84 to 0.99 (5)(6)(7). Even though the total quantity of the glycemic and insulinemic effects of foods may not be fully captured by dietary glycemic load, these measurement errors were likely to have been modest and unrelated to CHD because diets were assessed before disease occurred. ...
... In practice, most meals contain much greater amounts of fat and protein than were fed here. Nonetheless, differences in GI have been found to predict the glycemic response to realistic mixed meals and daylong glycemia (29,30). In persons with diabetes, low-GI diets have been found to lower glycated hemoglobin, a measure of the average blood glucose concentration over the previous 2-3 mo (31). ...
Background: Growth in normal and malignant tissues has been linked to hyperinsulinemia and insulin-like growth factors (IGFs). We hypothesized that IGF and IGF-binding protein (IGFBP) responses may be acutely affected by differences in the glycemic index (GI) of foods.
Objective: We compared the postprandial responses of IGFs and IGFBP to 2 foods of similar macronutrient composition but with greatly different GIs—pearled barley (GI: 25) and instant mashed potato (GI: 85).
Design: Ten young lean subjects consumed 50-g carbohydrate portions of the 2 foods or water (extended fast) in random order after an overnight fast. Capillary blood was collected at regular intervals over 4 h for measurement of blood glucose, insulin, and components of the IGF system.
Results: Serum IGFBP-1 declined markedly after both meals, but the mean (±SEM) change at 4 h was significantly (P < 0.01) more prolonged after the low-GI meal (−55 ± 20 ng/mL) than after the high-GI meal (−13 ± 15 ng/mL). Conversely, the change in serum IGFBP-3 concentration at 4 h was significantly (P < 0.05) higher after the low-GI meal (251 ± 102 ng/mL) than after the high-GI meal (−110 ± 96 ng/mL); the same pattern was observed at 2 h. Changes in IGFBP-2, free IGF-1, and total IGF-1 responses were minimal and did not differ significantly from those during the 4-h fast.
Conclusion: Acute changes in IGFBP-3 after low-GI and high-GI foods may provide a biologic mechanism linking cell multiplication with greater consumption of high-GI carbohydrates.
... The prediction of glycemic response to meals containing fat and protein also can successfully be predicted by GI 21 . This demonstrates that GI can be applicable into mixed meals 22 . Having said that , integrating information about the GI of foods into Malaysian diet need more data. ...
Acne vulgaris is one of the most common skin diseases seen by physicians. It has been postulated that the high glycemic index (GI) foods play an important role in the pathogenesis as well as recovery of acne vulgaris. Furthermore, the multicultural diversity gives rise to a variety of food preferences amongst Malaysians. Thus, this study was aimed to retrospectively identify the clinical impacts of low glycemic index diet in treatment of severe acne vulgaris among Malaysian youths residing in Malacca. The cases were retrieved from medical reports in SkiMed Clinic located in Malacca. A total of 20 patient records were reviewed based on the inclusion and exclusion criteria. Out of the 20 patients, 10 received dietary counseling for low GI foods (study group) and the other 10 had no dietary counseling (control group). Data analysed included demographic factors, anthropometric measurements, HbA1c, fasting sugar and global acne assessment score (GAAS) which were collected on the first and 4th visit at week 12 of the follow up. Patients’ age group were 20-25 years old, predominantly Chinese (19 individuals) with mean BMI of 23.62 to 24.21. Majority of patients have Fitzpatrick skin type III (16 individuals) followed by type IV (4 individuals). In the first visit the GAAS was 43.4 and 41.4 whilst in the 4th visit it was 15.8 and 28.4 in the study and control groups respectively. The mean serum HbA1c level was 5.1 in both groups in the first visit; however, in the 4th visit it dropped to 4.9 in the study group and increased to 5.4 in control group. There was a drop of mean fasting sugar from 5.3mg/dL on the first visit to 4.96mg/dL at the 4th visit in the study group. In conclusion, adopting a low glycemic index diet in these patients revealed a greater improvement in the recovery of severe acne vulgaris than the regular Malaysian diet.
... This process moves the sugar from the bloodstream so it can be used as energy, thereby increasing subsequent overall hunger and decreasing satiety levels (Ludwig, 2002;Page et al., 2011;Pittas et al., 2005). Indeed, high-glycemic foods, such as sugar-laden beverages, are absorbed rapidly in the gastrointestinal tract, leading to a sharp increase in glucose (Benelam, 2009;Chew, Brand, Thorburn, & Truswell, 1988;Granfeldt, Bj€ orck, & Hagander, 1991). Several studies have shown that foods with a high (vs. ...
In this research, we examine the interplay between physiological and psychological factors that determine whether the sugar level of a preload increases or decreases consumption on a subsequent snack-eating task. In study 1, participants who drank a high-sugar protein shake (which they believed to be healthy) consumed more subsequent snacks than participants who drank a low-sugar protein shake. Study 2 replicated these findings, but only when the shake was labeled as "healthy." When the shake was labeled as "indulgent," the effect was mitigated.
... Methodik). Inwieweit sich der GI einer Mahlzeit aus den GIs der Zutaten prognostizieren lässt, ist jedoch umstritten: Einige Autoren berichten nur einen niedrigen prognostischen Wert [9,14], andere fanden hingegen eine hohe Korrelation von errechneten und gemessenen Werten und eine gleichbleibende Hierarchie der Blutzuckerwirksamkeit von Lebensmitteln, unabhängig von der Zusammensetzung oder Zubereitung der Kost [1,5,31]. Darüber hinaus liegen für viele in Deutschland üblicherweise verzehrte Lebensmittel keine GI-Daten vor (z. ...
This study determined the dietary glycaemic index (GI) and the dietary glycaemic load (GL) of an optimized mixed diet (optimiX®), developed for children and adolescents by the Research Institute of Child Nutrition. OptimiX® is composed of a 7-day menu plan. Mean GI and GL values were calculated for all 35 (5 × 7) meals on the basis of published GI values. These were evaluated according to the following classification: low GI ≤55%, high GI ≥70%; low GL ≤74 g/1000 kcal, high GL ≥95 g/1 000 kcal. The complete 7-day menu yielded an average GI of 55% and average GL of 74 g/1 000 kcal for both boys and girls in the age groups considered (4-6 and 13-14 year olds). Very high GI or GL values were obtained in 5 of the 35 meals. Cornflakes (GI: 81) served for breakfast and jelly beans (GI: 78) in a snack resulted in GL values of 144 g and 157 g/1000 kcal respectively. Substituting these high GI food items with similar foods with a lower GI (e.g. substituting plain cornflakes with wholemeal cornflakes containing dried fruit), considerably lowered GL values. In the 3 other meals, wholemeal wheat bread (GI: 71) and French fries (GI: 78) produced mean GI and GL values at the upper limits of the acceptable range. OptimiX®, a practical implementation of the current dietary reference values for children and adolescents as published by the German Nutrition Society, is characterised by a low dietary GI and GL.
... The glycaemic index (Jenkins et al. 1981) has been used to take these and other factors into account and tables of glycaemic index for many food items and mixed meals are available (Parillo and Riccardi 1995, Le Floch et al. 1992, Chew et al. 1988. Several variations (Thorburn et aI., 1986) of the glycaemic index have been used, but they all attempt to quantify the increase in blood glucose for a period of several hours following a meal. ...
A two-compartment model of the carbohydrate absorption is proposed. The model keeps track of the amounts of proteins, lipids, sugar and four types of starch in the stomach and of the five types of carbohydrates in the intestine. The model is tested on various meals and it is shown that the model at least in a qualitative correct way can reproduce the reductions in glucose absorption rates caused by the admixture of proteins and lipids or by the ingestion of carbohydrates with low glycaemic index.
... There is great controversy about the utility of using glycemic index in the management diabetes and certainly obesity. Although glycemic index presents some drawbacks, it may be useful in dietary prescription [21] as some studies have shown the efficiency of the consumption of low glycemic index meals in the management of diabetes, obesity and related diseases [11,22,23]. Indeed, there is evidence that low glycemic index diets are effective in improving glucose metabolism and insulin sensitivity as well as various markers of cardiovascular risk in people with diabetes and obesity and can be considered in the overall strategy of diabetes management [24][25][26][27]. ...
... At present there is an epidemic of obesity and type 2 diabetes in both the developed and developing countries (Hossain et al., 2007). The increasing prevalence of diabetes throughout the world is partly related to fast-release nature of the staple carbohydrate foods which are more refined (Chew et al., 1988). High and rapid blood sugar levels following consumption of above mentioned foods increase oxidative stress (Hsu et al., 2007), protein glycation and the risk of development of type 2 diabetes (Hannah et al., 1994;Gavin et al., 2001). ...
Incorporation of foods with low and medium glycemic indices (GI) in diets indicates a therapeutic potential in reducing insulin resistance and diabetes. Glucometers are convenient in measuring the postprandial blood glucose concentrations and calculation of GI. The aim of this study was to compare an enzymatic kit method and a glucometer in evaluating fasting, postprandial glucose concentrations and GI of different foods. The Accu-Check Active glucometer and glucose oxidase kit (GOD-PAP) were used to analyze the glycemic response of 16 foods. Healthy individuals (age:20-30 yrs, BMI:24±3 kg/m2) participated in the study. GI values were calculated using bread as the standard. Fasting glucose concentrations measured by the two methods were significantly different (p<0.05). Mean glucometer glucose concentrations (n=10) at each time point for all foods were higher than the enzymatic kit values except for one which was not significant. Peak blood glucose concentrations obtained from the two methods and the GI values of the 15 foods were not significantly different (p>0.05). Thus the Accu-Check Active glucometer can be used to determine the GI values of foods.
... In Table 2 the results of the analyses relating the glycemic with the insulinemic response of food products are presented [14,18,19,21,24,[26][27][28][30][31][32][33]36,. A proper relation is observed between the GlyS and InsS for a large variety of fresh and processed food products with the glycemic response being the only relevant regression factor for the insulinemic response. ...
... P<0.01) in subjects with type 2 diabetes. Similar results have indicated that the relative glycemic effect of a mixed meal can be predicted from the GI of its carbohydrate constituent [58][59][60][61][62][63]. ...
Background: Recent epidemiological studies predict that the worldwide incidence of type 2 diabetes, atherosclerosis, and cardiovascular diseases are increasing at an alarming rate. Currently, limited cures are available to prevent or cure diabetes and related postprandial glycemia, atherosclerosis and cardiovascular diseases. Insufficiency of current therapies for the treatment of type 2 diabetes and atherosclerosis, combined with both the lack of patient trust in conventional medical treatment and inability of the economy to absorb the cost of synthetic pharmaceuticals, have created a growing public interest in the use of Complementary and Alternative Medicines (CAM). Especially dietary and herbal remedies have become more popular because of their therapeutic effectiveness, relatively lesser or no side effects and low cost. Methods: Our publications, internet search of research articles from Pub Med and University of Toronto library, as well as discussions with nutritional scientists and basic researchers. Results: Unfortunately, the vast majority of herbal remedies lack quality control, standardization, and clinical scrutiny for treatment of ailments. Thus patients continue self-medicating with herbal products with little or no evidence of their safety and efficacy. WHO study groups strongly emphasize the optimal and rational uses of traditional medicines. Regulatory agencies like Food Trade Commission, Food & Drug Administration of USA, and Health Canada are deeply concerned about the effectiveness and safety of natural health products and alternative therapies. The increasingly high demand of CAM, in the absence of evidence-based safety and efficacy, adequate regulatory standards, patient disclosures to physicians and physician education, have prompted a unified call from the medical and scientific community for randomized controlled clinical trials of herbal medicines, dietary supplements and functional foods, in order to understand their therapeutic potential and to provide a valid basis for legitimate health promotion claims. Several researchers have developed and standardized scientific models (randomized, double blind, crossover, placebo-controlled clinical trials) for faster and cost-effective clinical validation of medicinal herbs and functional foods for their application in the management of type 2 diabetes using 2-hour oral glucose tolerance test. This scientific approach has been strongly recommended in this communication. The management and prevention of atherosclerosis, diabetes-linked cardiovascular diseases, and metabolic syndrome should be done by following healthy life styles, dietary interventions, nutraceutical therapies, and alternative medicines as discussed in this review. Conclusion: The reviewed information may not only provide the rationale of proposing the scientific models for clinical testing of CAM therapies, but would also be beneficial in managing type 2 diabetes and atherosclerosis effectively.
... At present there is an epidemic of obesity and type 2 diabetes in both the developed and developing countries (Hossain et al., 2007). The increasing prevalence of diabetes throughout the world is partly related to fast-release nature of the staple carbohydrate foods which are more refined (Chew et al., 1988). High and rapid blood sugar levels following consumption of above mentioned foods increase oxidative stress (Hsu et al., 2007), protein glycation and the risk of development of type 2 diabetes (Hannah et al., 1994;Gavin et al., 2001). ...
Incorporation of foods with low and medium glycemic indices (GI) in diets indicates a therapeutic potential in reducing insulin resistance and diabetes. Glucometers are convenient in measuring the postprandial blood glucose concentrations and calculation of GI. The aim of this study was to compare an enzymatic kit method and a glucometer in evaluating fasting, postprandial glucose concentrations and GI of different foods. The Accu-Check Active glucometer and glucose oxidase kit (GOD-PAP) were used to analyze the glycemic response of 16 foods. Healthy individuals (age:20-30 yrs, BMI:24±3 kg/m 2) participated in the study. GI values were calculated using bread as the standard. Fasting glucose concentrations measured by the two methods were significantly different (p<0.05). Mean glucometer glucose concentrations (n=10) at each time point for all foods were higher than the enzymatic kit values except for one which was not significant. Peak blood glucose concentrations obtained from the two methods and the GI values of the 15 foods were not significantly different (p>0.05). Thus the Accu-Check Active glucometer can be used to determine the GI values of foods.
... There is great controversy about the utility of using glycemic index in the management diabetes and certainly obesity. Although glycemic index presents some drawbacks, it may be useful in dietary prescription [21] as some studies have shown the efficiency of the consumption of low glycemic index meals in the management of diabetes, obesity and related diseases [11,22,23]. Indeed, there is evidence that low glycemic index diets are effective in improving glucose metabolism and insulin sensitivity as well as various markers of cardiovascular risk in people with diabetes and obesity and can be considered in the overall strategy of diabetes management [24][25][26][27]. ...
Background
Little data to guide diet prescription exists about the foods most frequently consumed in Africa. Moreover, the sauce accompanying a meal can significantly alter the metabolic effects of food. Our work was to study the influence of sauces on the metabolic effects of foofoo corn (Zea mays), one of the most commonly consumed foods in several countries in sub-Saharan Africa with a wide range of sauces.
Methods
Our study population consisted of ten healthy volunteers (five men, five women), aged from 21 to 28 years, with mean BMI of 23.9 (SD 1.9) kg/m². The study involved seven visits of three hours each, conducted every 2 days, including one devoted to the oral glucose tolerance test (OGTT) and six visits to the consumption of each of 6 meals tested, standardized to 75 g of carbohydrate intake. Blood samples were collected at 0, 15, 30, 60, 90, 120 and 180 min after consumption of meals for blood glucose and triglycerides levels. The glucose area under the curve of each tested meal, was used to calculate its glycemic index, using the OGTT as the reference. The accompanying sauces tested with foofoo corn were: okra sauce (Abelmoschus esculentus), the so-called yellow sauce (Elaeis guinensis), the pistachio sauce (Pistacia vera), the nkui (Triumpheta pentandra), ndolé (Vernonia amygdalima) and cabbage (Brassica oleracea).
Results
All meals had generally a low glycemic index, with a maximum of 22.59 % for okra and cabbage, followed by ndolè (20.18 %), the yellow sauce (13.10 %), pistachio sauce (11.60 %), and nkui (5.27 %). There was a difference in the effects of the diets on triglyceride levels only at 180 min (p = 0.03).
Conclusion
Whatever the accompanying sauce, foofoo corn has a low glycemic index. Some sauces, such as nkui give it a very low glycemic index and may be of great interest in diet prescription for patients with various metabolic disorders such as diabetes and obesity.
... It is therefore unrealistic to analytically determine the GI for all possible combinations of foods. However, previous studies have tested the GI for a sample of mixed foods and determined that a calculated GI using a weighted average of the GI values of each individual ingredient gives a reasonable approximation of the GI of the mixture (Chew et al., 1988; Wolever and Jenkins, 1986). Mixed foods or recipes carried on the FCT were calculated in this manner. ...
The glycemic index (GI) provides an indication of a food's carbohydrate quality by measuring the blood glucose response to consuming the food. The glycemic load (GL) is calculated as the GI times the available carbohydrate in a fixed amount of the food. GI and GL are currently of interest for the study of associations of diet and chronic disease including diabetes, cardiovascular disease, cancer and obesity. An international table of GI values is available and provides a compilation of currently available data. The purpose of this project was to use these data, as well as other available references, to expand the Cancer Research Center of Hawaii Food Composition Table (FCT) to include GI and GL values. All of the individual foods in the FCT (n=1592) were assigned GI values as a direct match (n=181), imputation (n=948), calculated value (n=208), or assigned a zero value (n=255). GL per 100 g was then calculated using the assigned GI and available carbohydrate per 100 g of food. The addition of GI and GL values to the FCT will allow researchers to estimate the effect of dietary carbohydrate quality on various health outcomes.
... The daily GI was calculated as a continuous value as the product of the carbohydrate content of each food per serving, the average daily servings of the food, and the GI, as described by Salmerón et al. (14). In a validation study of the foodfrequency questionnaire, high correlations were reported for foods from which GI was calculated; furthermore, calculated and measured GIs for mixed meals have been reported to correlate well (15). GL was calculated as the daily GI times the total carbohydrate content per day of the diet. ...
Dietary guidelines recommend interchanging protein foods (e.g., chicken for red meat), but they may be exchanged for carbohydrate-rich foods varying in quality [glycemic load (GL)]. Whether such exchanges occur and how they influence long-term weight gain are not established.
Our objective was to determine how changes in intake of protein foods, GL, and their interrelationship influence long-term weight gain.
We investigated the association between 4-y changes in consumption of protein foods, GL, and their interaction with 4-y weight change over a 16- to 24-y follow-up, adjusted for other lifestyle changes (smoking, physical activity, television watching, sleep duration), body mass index, and all dietary factors simultaneously in 3 prospective US cohorts (Nurses' Health Study, Nurses' Health Study II, and Health Professionals Follow-Up Study) comprising 120,784 men and women free of chronic disease or obesity at baseline.
Protein foods were not interchanged with each other (intercorrelations typically <|0.05|) but with carbohydrate (negative correlation as low as -0.39). Protein foods had different relations with long-term weight gain, with positive associations for meats, chicken with skin, and regular cheese (per increased serving/d, 0.13-1.17 kg; P = 0.02 to P < 0.001); no association for milk, legumes, peanuts, or eggs (P > 0.40 for each); and relative weight loss for yogurt, peanut butter, walnuts, other nuts, chicken without skin, low-fat cheese, and seafood (-0.14 to -0.71 kg; P = 0.01 to P < 0.001). Increases in GL were independently associated with a 0.42-kg greater weight gain per 50-unit increase (P < 0.001). Significant interactions (P-interaction < 0.05) between changes in protein foods and GL were identified; for example, increased cheese intake was associated with weight gain when GL increased, with weight stability when GL did not change, and with weight loss when exchanged for GL (i.e., decrease in GL).
Protein foods were commonly interchanged with carbohydrate, and changes in protein foods and GL interacted to influence long-term weight gain.
© 2015 American Society for Nutrition.
... Although the GI has gained popularity over the years, conflicting views remain around the reliability and application of this measure in clinical and public health settings. Many GI skeptics continue to question its usefulness for a number of different reasons (Flint et al., 2004;Venn & Green, 2007;Williams et al., 2008;Vega-López et al., 2007;Coulston et al., 1984), even though most if not all of these issues have been addressed elsewhere (Wolever et al.,1991b;Wolever et al., 2008;Chew et al., 1988). ...
... Chaturvedi et al. (1997) reported the results obtained for tomato rice curry and chapatti with curry in Pakistan using recipes that included the addition of tomato (25 g), oil (10 g) and bottle gourd (100 g), which are different from our recipes. Chew et al. (1988) measured the glycaemic responses to Indian rice served with lentils and cauliflower curry in Australia (no ingredients specified). Hettiaratchi et al. (2009) determined the GIs of Sri Lankan wheat bread served with lentil curry and Pirasath et al. (2010) measured the GI of parboiled rice and different types of curry (green leaf, soya meat gravy and a combination of both); however, the exact fat content that was mainly derived from coconut milk was not reported. ...
Background
The glycaemic responses of staples differ when eaten as mixed meals. We determined the glycaemic responses and glycaemic index (GI) values for common South Asian carbohydrate rich foods and the effect of adding curried chicken to them as mixed meals.Methods
The GI and glycaemic response to staples (basmati rice, pilau rice and chapatti) and mixed meals (pilau rice with chicken curry and chapatti with chicken curry) were measured in healthy volunteers. Paired comparisons in each subject were carried out for staples and their equivalent mixed meals (n = 9).ResultsGI values for the mixed meals were significantly lower than the staples alone (41 and 60 for pilau rice with chicken curry and pilau rice alone, P = 0.001; 45 and 68 for chapatti with chicken curry and chapatti alone, P = 0.004). Both, pilau rice and chapatti with chicken curry had a significantly lower glycaemic response than their equivalent staples alone: incremental area under the blood glucose response curves (IAUC) 111.9 mmol min−1 L−1 for pilau rice with curry versus 162.4 mmol min−1 L−1 for pilau rice alone (P = 0.001) and IAUC 110.1 mmol min−1 L−1 for chapatti with chicken curry versus 183.6 mmol min−1 L−1 for chapatti alone (P = 0.002).Conclusions
Adding fat and protein-containing curries as part of a mixed meal to carbohydrate rich staple foods reduced glycaemic responses, and also changed the GI category.
... Importantly, we found a strong correlation between the GI and corresponding insulin response (r ϭ 0.76, p Ͻ 0.0001). In general these two physiological measures of glucose metabolism have correlated well, showing correlation coefficients in the range of 0.70 to 0.88 [23][24][25]15]. Dairy products and chocolate-flavoured products, however, appear to be exceptions to the rule, tending to give significantly higher insulin responses than predicted by their GI [26,27]. ...
Objective:
Technological processes may influence the release of glucose in starch. The aim of this study was to compare the metabolic response and the kinetics of appearance of exogenous glucose from 2 cereal products consumed at breakfast.
Methods:
Twenty-five healthy men were submitted to a randomized, open, crossover study that was divided into 2 parts: 12 of the 25 subjects were included in the "isotope part," and the 13 other subjects were included in the "glycemic part." On test days, subjects received biscuits (low glycemic index [GI], high slowly available glucose [SAG]) or extruded cereals (medium GI, low SAG) as part of a breakfast similar in terms of caloric and macronutrient content. The postprandial phase lasted 270 minutes.
Results:
The rate of appearance (RaE) of exogenous glucose was significantly lower after consumption of biscuits in the first part of the morning (90-150 minutes) than after consumption of extruded cereals (p ≤ 0.05). Conversely, at 210 minutes, it was significantly higher with biscuits (p ≤ 0.01). For the first 2 hours, plasma glucose and insulin were significantly lower after biscuits during the glycemic part. C-peptide plasma concentrations were significantly lower at 90, 120, and 150 minutes after ingestion of the biscuits (p ≤ 0.05).
Conclusion:
The consumption of biscuits with a high content of slowly digestible starch reduces the appearance rate of glucose in the first part of the morning and prolongs this release in the late phase of the morning (210 minutes). Our results also emphasize that modulation of glucose availability at breakfast is an important factor for metabolic control throughout the morning in healthy subjects due to the lowering of blood glucose and insulin excursions.
... There are many studies demonstrating that the glycemic index of individual foods predicts a response to mixed meals when appropriate methodology is utilized (5)(6)(7). With regard to the authors' description of our study, two of the test meals did have identical macronutrient composition and solid food components, and the measured glycemic response corresponded closely with prediction (8). ...
In their recent article, Alfenas and Mattes (1) conclude that the glycemic index values of individual foods do not predict glycemic response to mixed meals, nor influence measures of hunger. Because the observed glycemic response did not differ between diets, the lack of effect on appetite is not surprising. Thus, the potentially important aspect of the study pertains to the prediction of glycemic index in mixed meals.
The authors’ approach was to validate published glycemic index values in a pretest, selecting 48 of 79 foods with consistent glycemic responses. However, their …
... The daily GI was calculated by summing the weighted GI values for each food item. The GL was calculated as the product of the daily GI and total carbohydrate and adjusted for energy intake (33). Dietary compliance with the assigned diet-treatment group was determined by assessing the change of meal GI, meal GL, and the percentage of energy from fat with the intervention. ...
Background:
In Hispanic children and adolescents, the prevalence of obesity and insulin resistance is considerably greater than in non-Hispanic white children. A low-glycemic load diet (LGD) has been proposed as an effective dietary intervention for pediatric obesity, but to our knowledge, no published study has examined the effects of an LGD in obese Hispanic children.
Objective:
We compared the effects of an LGD and a low-fat diet (LFD) on body composition and components of metabolic syndrome in obese Hispanic youth.
Design:
Obese Hispanic children (7-15 y of age) were randomly assigned to consume an LGD or an LFD in a 2-y intervention program. Body composition and laboratory assessments were obtained at baseline and 3, 12, and 24 mo after intervention.
Results:
In 113 children who were randomly assigned, 79% of both groups completed 3 mo of treatment; 58% of LGD and 55% of LFD subjects attended 24-mo follow-up. Compared with the LFD, the LGD decreased the glycemic load per kilocalories of reported food intakes in participants at 3 mo (P = 0.02). Both groups had a decreased BMI z score (P < 0.003), which was expressed as a standard z score relative to CDC age- and sex-specific norms, and improved waist circumference and systolic blood pressure (P < 0.05) at 3, 12, and 24 mo after intervention. However, there were no significant differences between groups for changes in BMI, insulin resistance, or components of metabolic syndrome (all P > 0.5).
Conclusions:
We showed no evidence that an LGD and an LFD differ in efficacy for the reduction of BMI or aspects of metabolic syndrome in obese Hispanic youth. Both diets decreased the BMI z score when prescribed in the context of a culturally adapted, comprehensive weight-reduction program.
... The dietary GI was calculated by multiplying the amount of available carbohydrates of each food item by the food's GI, and the sum of these products was then divided by the total carbohydrate intake. Glucose was used as the reference (GI for glucose = 100) [27,28]. GL was then calculated as follows: GL = (total available carbohydrate intake 9 dietary GI)/100 [14]. ...
Background
Depression is a very common disorder in elderly, especially in those institutionalized. Nutrition could play an important role in the onset and/or progression of depression, since the intake of carbohydrates with a high glycaemic index (GI) or diets with a high glycaemic load (GL) may increase the insulin-induced brain serotonin secretion.
Objective
The aim of our study was to analyse the association between dietary GI and GL and the odds of suffering depression in institutionalized elderly people without antidepressant treatment.
Methods
This cross-sectional study included 140 institutionalized elderly people from the Madrid region (Spain) (65–90 years of age) whose diets were recorded using a precise weighing method over seven consecutive days. Energy and nutrient intakes were recorded and the GI and GL calculated. The participants’ affective capacity was assessed using the Geriatric Depression Scale (GDS). Subjects were grouped into non-depressed (GDS ≤ 5) and depressed (GDS > 5). Since GDS scores and gender were statistically associated (p < 0.01), the data were grouped considering this association.
Results
Dietary GI (51.09 ± 3.80) and GL (97.54 ± 13.46) were considered as medium. The dietary GL was significantly higher in the non-depressed (100.00 ± 12.13) compared with the depressed group (93.97 ± 14.04, p < 0.01). However, a similar GI was observed between non-depressed (51.50 ± 3.29) and depressed groups (50.52 ± 4.46). Additionally, participants with a dietary GL placed in the second and third tertiles had a 67.4 % and 65.3 %, respectively, less odds of suffering depression than those in the first tertile. GDS scores and dietary GL were inversely related; therefore, an increase in one unit in the dietary GL scale decreased the GDS score by 0.058 units.
Conclusions
Glyaemic load is associated with a lower odd of depression.
In this article, the authors develop and analyze a linear programming model to obtain an ideal diet for individuals with diabetes by setting the glycemic load as the objective function. Additionally, a standardized system is used in order to facilitate the substitutability of foods present in a diet since those are classified according to their macronutrient content (proteins, lipids, and carbohydrates) and these values are, on average, very similar. Finally, the diet glycemic index is calculated with the model's outcome to corroborate that it is indeed a diet with low glycemic index and that, at the same time, it complies with the nutrient restrictions, which proves that the model can be a useful tool both to generate low glycemic index diets and to restrict certain nutrients from the diet.
This chapter will review the relationship between gastrointestinal events and carbohydrate metabolism in the short and long terms, beginning with the effects of dietary fiber and including the extension of this to more recent work on the glycemic index of foods where fiber, food form, and the so-called “antinutrients” all combine to produce the glycemic response typical of the whole food.
Background:
Obesity and metabolic abnormalities are important risk factors for knee osteoarthritis (KOA). Recent epidemiologic studies have found that a high glycemic index (GI) and glycemic load (GL) diet are associated with a higher risk for metabolic complications and cardiovascular mortality.
Objective:
We aimed to examine the association between dietary GI, dietary GL, and KOA among Korean adults.
Design:
This was a cross-sectional study that analyzed data obtained from the Korean National Health and Nutrition Examination Survey 2010-2012.
Participants/setting:
A total of 9,203 participants (5,275 women) aged ≥50 years were included.
Main outcome measures:
KOA was defined as the presence of radiographic features of Kellgren-Lawrence grade ≥2. Chronic knee pain was defined as the presence of knee pain for more than 30 days during the past 3 months. Dietary information was collected using a single 24-hour recall method.
Statistical analyses performed:
The association between the quintiles of dietary GI and dietary GL and knee conditions was analyzed using a multinomial logistic regression analysis adjusting for age, physical activity, obesity, hypertension and diabetes, serum low-density lipoprotein, and total energy intake.
Results:
Among the women, the association between dietary GI and symptomatic KOA was: quintile 1: 1.00 (reference); quintile 2: 1.29 (95% CI 0.87 to 1.92); quintile 3: 1.59 (95% CI 1.11 to 2.28); quintile 4: 1.74 (95% CI 1.21 to 2.51); and quintile 5: 1.77 (95% CI 1.20 to 2.60) (P=0.001). Chronic knee pain without KOA was associated with dietary GI; however, this association was not linear across quintiles. There was no significant association between dietary GI and asymptomatic KOA. Among the men, no significant association was found between dietary GI and any knee conditions. There was no significant association between dietary GL and KOA in both men and women.
Conclusions:
There was a significant positive association between dietary GI and symptomatic KOA in women.
Diet therapy, the cornerstone of gestational diabetes mellitus (GDM) management aims to promote adequate weight gain and ensure glycaemic control in the pregnant mother. Achievement of these maternal goals improves pregnancy and neonatal outcomes. The advocacy of low-GI foods is based on slower rate of carbohydrate absorption of these foods, which subsequently lowers postprandial glycaemic and insulinaemic responses. Glycaemic load (GL), a concept that merges carbohydrate quality and quantity of foods, accurately predicts postprandial glycaemia for single foods or mixed meals. Low-GI/GL diets have shown to improve management of body weight, glycaemia and cardiovascular risks, especially in hyperinsulinaemic and insulin-resistant populations. A 15% reduction in dietary GI bestows clinically significant health benefits, and this magnitude of GI reduction is made possible by substituting usual high-GI staples with lower GI alternatives, while maintaining their prescribed serving size. In this review, we assess the evidence for the treatment of GDM, a condition closely associated with hyperinsulinaemia and insulin resistance, with low-GI/GL diets.
Aims
The traditional Italian dish pasta is major food source of starch with low glycemic index (GI), and also an important low-GI component of the Mediterranean diet. This systematic review aimed at assessing comprehensively and in-depth the potential benefit of pasta on cardio-metabolic disease risk factors.
Data Synthesis
Following a standard protocol, we conducted a systematic literature search of PubMed, CINAHL, and Cochrane Central Register of Controlled Trials, for prospective cohort studies and randomized controlled dietary intervention trials that examined pasta, and pasta-related fiber and grain intake in relation to cardio-metabolic risk factors of interest. Studies evaluating postprandial glucose response to pasta compared to bread or potato were quantitatively summarized using meta-analysis of standardized mean difference. Evidence from studies with pasta as part of low-GI dietary intervention and studies investigating different types of pasta were qualitatively summarized.
Conclusions
Pasta meals have significant lower postprandial glucose response compared to bread or potato meals, but evidence was lacking in terms of how the intake of pasta can influence cardio-metabolic disease risk. More long-term randomized controlled trials are needed where investigators directly contrast the cardio-metabolic effects of pasta and bread or potato. Long-term prospective cohort studies with required data available should also be analyzed regarding the effect of pasta intake on disease endpoints.
Over the past two decades there has been a radical change in dietary guidelines for diabetes, which now stress high carbohydrate and fiber intakes. The initial impetus for the increase in carbohydrate came from early studies of Himsworth (1935–36) and, later, Stone and Connor (1965), showing improved blood lipids and glucose tolerance on a high-carbohydrate diet. Further motivation for change originated in the early 1970s from Trowell’s suggestion (1973) that the development of diabetes might be related to a lack of fiber in the diet. This spurred many new concepts about the dietary treatment of diabetes and lead to the classic studies of Anderson (Kiehm et al., 1976; Anderson and Ward, 1979) and others (Simpson et al., 1981; Rivellese et al., 1980) showing the beneficial effects of high-carbohydrate, high-fiber diets.
The glycaemic index (GI) concept is based on the difference in blood glucose response after ingestion of the same amount of carbohydrates from different foods, and possible implications of these differences for health, performance and well-being. GI is defined as the incremental blood glucose area (0_2 h) following ingestion of 50 g of available carbohydrates in the test product as a percentage of the corresponding area following an equivalent amount of carbohydrate from a reference product. A high GI is generally accompanied by a high insulin response. The glycaemic load (GL) is the GI_/the amount (g) of carbohydrate in the food/100. Many factors affect the GI of foods, and GI values in published tables are indicative only, and cannot be applied directly to individual foods. Properly determined GI values for individual foods have been used successfully to predict the glycaemic response of a meal, while table values have not. An internationally recognised method f or GI determination is available, and work is in progress to improve inter- and intra-laboratory performance. Some epidemiological studies and intervention studies indicate that low GI diets may favourably influence the risk of chronic diseases such as diabetes and coronary heart disease, although further well-controlled studies are needed for more definite conclusions. Low GI diets have been demonstrated to improve the blood glucose control, LDL-cholesterol and a risk factor for thrombosis in intervention studies with diabetes patients, but the effect in free-living conditions remains to be shown. The impact of GI in weight reduction and maintenance as well as exercise performance also needs further investigation. The GI concept should be applied only to foods providing at least 15 g and preferably 20 g of available carbohydrates per normal serving, and comparisons should be kept within the same food group. For healthy people, the significance of GI is still unclear and gen e ral labelling is therefore not recommended. If introduced, labelling should be product-specific and considered on a case-by-case basis. Keywords: body weight; carbohydrates; disease risk; starch; sugars
Abstract Rice is the principle staple and energy source for nearly half the world's population and therefore has significant nutrition and health implications. Rice is generally considered a high glycaemic index (GI) food, however this depends on varietal, compositional, processing and accompaniment factors. Being a major contributor to the glycaemic load in rice eating populations, there is increasing concern that the rising prevalence of insulin resistance is as a result of the consumption of large amounts of rice. Devising ways and means of reducing the glycaemic impact of rice is therefore imperative. This review gathers studies examining the GI of rice and rice products and provides a critical overview of the current state of the art. A table collating published GI values for rice and rice products is also included.
This paper discusses common misconceptions about the glycaemic index (GI). The rate of carbohydrate digestion is only one of the many determinants of GI and, hence, in vitro methods cannot reliably predict the GI of a food. GI has been criticized as being extremely variable between subjects and not applying in mixed meals. In fact, however, GI controls for differences in glycaemic response between individuals and apparent differences are due to within-individual, variation which does not detract from the ability of GI to predict average glycaemic responses. The conclusion that GI does not apply in mixed meals is based on flawed methodology; recent studies show that nearly 90% of the variation in glycaemic response of realistic mixed meals can be explained by differences in carbohydrate content and GI. The health benefits of low GI foods tend to be ascribed to their slow rate of digestion and reduced post-prandial insulin responses. While the former is important, it is not the only mechanism involved, since low GI sugars may have some of the same effects as slowly absorbed starch. The role of insulin is questioned because, unlike GI, the insulinaemic index (II) of foods may vary in different subjects and, hence, may not be a valid measure. It is not clear that high insulin exacerbates obesity; indeed, there is good evidence that hyperinsulinaemia is associated with reduced weight gain. The public health message about GI is usually to avoid refined foods, eat more fruits and vegetables instead of concentrated juice, and have more pasta and less potato. However, with respect to GI, all of these recommendations are wrong and will ultimately cause confusion and rejection of the concept. An alternative, more scientifically accurate message is suggested.
The objective of this study was to investigate whether the temperature at which the cooked food is served affects its glycemic and insulinemic indices in subjects with varied insulin sensitivity. Two potato meals containing 50 g of carbohydrates were fed to 9 subjects with varied insulin sensitivity, at mean temperatures of 83.6 ± 2.0°C for hot potato (HP) and 26.0 ± 0.6°C for cooled potato (CP). Cooled potato resulted in a significantly lower postprandial blood glucose and area under the glucose curve (glucose AUC) as compared to HP (P < .05). Postprandial triglyceride values significantly decreased from fasting levels after the CP whereas an increase was observed after the HP (P < .05). Glycemic index of CP was significantly lower than HP (P < .05). After consumption of HP, greater incremental changes in glucose and insulin were observed in hyperinsulinemic as compared to normoinsulinemic subjects. These results emphasize the importance of starch temperature at consumption as a factor that influences the glycemic index and may allow patients with hyperinsulinemia and diabetes to have a wider selection of starchy foods, if consumed at the appropriate temperature.
Carbohydrate (CHO) enriched diets can improve glucose tolerance in healthy subjects but have controversial effects in NIDDM patients. Their effects on glucose metabolism are not clearly established in obese patients with impaired glucose tolerance (IGT) and might depend on their glycemic index (GI). For that reason, we compared the metabolic responses to 2 isocaloric CHO rich breakfasts with either a low GI (LGI) or a high GI (HGI) in 10 lean healthy controls (group I) and in 9 obese subjects with IGT (group II). The LGI breakfast contained dairy products and fruits while the HGI breakfast was rich in bread. The 2 breakfasts were allocated in a random order and the metabolic and hormonal responses were evaluated both over the post-prandial periods of the breakfast and of the following lunch. Blood glucose concentrations were continuously monitored. Plasma insulin and counter regulatory hormones were measured every 30 min for 360 min. Nutrient oxidation rates were calculated from respiratory exchange data obtained for 60 min in the pre and post-prandial periods. Blood glucose responses and metabolic responses in terms of oxygen consumption and CO2 production were similar in the two groups after a LGI breakfast but became different after the HGI breakfast. In the two groups taken as a whole, changes in CHO oxidation rates observed for 1 hour following the meal, were negatively correlated with the corresponding incremental areas of plasma glucose, this effect being more marked in obese patients with IGT. Such a limitation in CHO oxidation following a HGI CHO load could impair the glycogen cycle and favour fat synthesis. Consequently, breakfasts rich in dairy products and fruits are more recommended in obesity with IGT than breakfasts rich in bread.
A number of different issues of aging affect work organizations. Workers age in the usual sense of biological, psychological, and social aging. Workers age in an organizational sense resulting in a need for training and growth. Updating may prevent or minimize obsolescence. Human factors approaches can support adult and older adult workers through designing or redesigning a work situation in a way sensitive to the physical and cognitive demands of a job. Demands on individual workers can change in middle age and older adulthood as caregiving demands of family members must be balanced with work.
There is increasing evidence that both the amount and type of carbohydrate play an important role in weight management and risk of chronic disease. Classifying carbohydrates according to their post-prandial glycemic effect (ie, the glycemic index of foods) has yielded more useful insights than the historical distinctions of simple versus complex chemical structure. Diets based on carbohydrate foods that are more slowly digested and absorbed (ie, low glycemic index diets) have been independently linked to reduced risk of type 2 diabetes, cardiovascular disease, and some types of cancer. In individuals with diabetes, intervention studies have shown improvements in insulin sensitivity and glycated hemoglobin concentration with low glycemic index diets. Research also suggests that low glycemic index diets may assist with weight management through effects on satiety and fuel partitioning. Although ongoing research is needed, the current findings, together with the fact that there are no demonstrated negative effects of a low glycemic index diet, suggest that the glycemic index should be an important consideration in the dietary management and prevention of obesity and chronic disease.
Low GI diet reduces GDM insulin need 2 Background A low glycemic index (GI) diet is effective as treatment for people with diabetes and has been shown to improve pregnancy outcomes when used from the first trimester. A low GI diet is commonly advised as treatment for women with gestational diabetes mellitus (GDM). However the efficacy and pregnancy outcomes of this advice have not been systematically examined.
Background: Recent studies have concluded that the carbohydrate content and glycemic index (GI) of individual foods do not predict the glycemic and insulinemic effects of mixed meals. We hypothesized that these conclusions may be unwarranted because of methodologic considerations.
Objective: The aim was to ascertain whether the GI and carbohydrate content of individual foods influence glucose and insulin responses elicited by realistic mixed meals in normal subjects.
Design: With the use of a crossover design, we determined the glucose and insulin responses of 6 test meals in 16 subjects in Sydney and the glucose responses of 8 test meals in 10 subjects in Toronto and then the results were pooled. The 14 different test meals varied in energy (220–450 kcal), protein (0–18 g), fat (0–18 g), and available carbohydrate (16–79 g) content and in GI (35–100; values were rounded).
Results:The glucose and insulin responses of the Sydney test meals varied over a 3-fold range (P < 0.001), and the glucose responses of the Toronto test meals varied over a 2.4-fold range (P < 0.001). The glucose responses were not related to the fat or protein content of the test meal. Carbohydrate content (P = 0.002) and GI (P = 0.022) alone were related to glucose responses; together they accounted for 88% of the variation in the glycemic response (P < 0.0001). The insulin response was significantly related to the glucose response (r = 0.94, P = 0.005).
Conclusions: When properly applied in realistic settings, GI is a significant determinant of the glycemic effect of mixed meals in normal subjects. For mixed meals within the broad range of nutrient composition that we tested, carbohydrate content and GI together explained ≈90% of the variation in the mean glycemic response, with protein and fat having negligible effects.
Abstract There is compelling evidence that carbohydrate quality has important influences on cardiovascular disease, the metabolic syndrome, type 2 diabetes, and obesity. Cohort and interventional studies indicate that dietary fiber is an important determinant of satiation, satiety, and weight gain, and also protects against cardiovascular disease. Cohort studies have shown that vegetables and fruits protect against coronary heart disease, whereas whole grains provide protection against cardiovascular disease, type 2 diabetes, and weight gain. Dietary glycemia within the range eaten by most of the population seems not to have a significant influence on body weight, although it may influence waist circumference. There is strong evidence from interventional trials that dietary glycemia does influence insulin resistance and diabetes control. Moreover, replacing saturated fat with high-glycemic carbohydrate may increase cardiovascular risk. Soft drink consumption is a proven cause of weight gain, which may relate to the lack of satiation provided by these drinks. In large amounts, dietary fructose leads to greater adverse metabolic changes than equivalent amounts of glucose, although the extent to which fructose per se is contributing to many of the metabolic changes found in the obese, as distinct from the calories it provides, is still a matter of debate.
Generating valid estimates of dietary glycemic index (GI) and glycemic load (GL) has been a challenge in nutritional epidemiology. The methodologic issues may have contributed to the wide variation of GI/GL associations with health outcomes observed in existing literature. We describe a standardized methodology for assigning GI values to items in the National Health and Nutrition Examination Survey (NHANES) nutrient database using the new International Tables to develop research-driven, systematic procedures and strategies to estimate dietary GI/GL exposures of a nationally representative population sample. Nutrient databases for NHANES 2003-2006 contain information on 3,155 unique foods derived from the US Department of Agriculture National Nutrient Database for Standard Reference versions 18 and 20. Assignment of GI values were made to a subset of 2,078 carbohydrate-containing foods using systematic food item matching procedures applied to 2008 international GI tables and online data sources. Matching protocols indicated that 45.4% of foods had identical matches with existing data sources, 31.9% had similar matches, 2.5% derived GI values calculated with the formula for combination foods, 13.6% were assigned a default GI value based on low carbohydrate content, and 6.7% of GI values were based on data extrapolation. Most GI values were derived from international sources; 36.1% were from North American product information. To confirm data assignments, dietary GI and GL intakes of the NHANES 2003-2006 adult participants were estimated from two 24-hour recalls and compared with published studies. Among the 3,689 men and 4,112 women studied, mean dietary GI was 56.2 (men 56.9, women 55.5), mean dietary GL was 138.1 (men 162.1, women 116.4); the distribution of dietary GI was approximately normal. Estimates of population GI and GL compare favorably with other published literature. This methodology of adding GI values to an existing population nutrient database utilized systematic matching protocols and the latest comprehensive data sources on food composition. The database can be applied in clinical and survey research settings where there is interest in estimating individual and population dietary exposures and relating them to health outcomes.
The development of insulinemic indices (IIs) to foods has been reported as necessary to supplement glycemic index (GI) tables used in the dietary management of diabetes mellitus. In this study the glycemic and insulinemic responses of 12 healthy volunteers to four commonly consumed Middle Eastern dishes were measured. All meals contained 50 g of carbohydrates, fed as chickpea salad dip (CSD), stuffed grape leaves (SGL), kibbeh saynieh (KS) or Middle Eastern bread (MEB). The results showed that the CSD resulted in the lowest glycemic and insulinemic responses as compared to equivalent amounts of carbohydrates fed as glucose, MEB, SGL or KS. KS induced moderate glycemic and insulinemic responses, whereas SGL gave higher GI and II responses as compared to the other CSD and KS meals. MEB gave responses similar to glucose. Except for CSD, the GIs and IIs, as predicted by adding the published indices of the individual ingredients, showed a high correlation with the observed data. CSD is recommended as a favorable dietary item for diabetics and more data on the glycemic and insulinemic responses to combination dishes need to be collected for better dietary management of diabetes mellitus.
The long-term effects of incorporating waxy hulless barley (β-glucan = -7%) bread products in the usual dietary pattern of non-insulin-dependent diabetic (Type 2) subjects were evaluated via dietary, clinical and biochemical methods. Eleven Type 2 men (x age = 51 ± 6.5 yr), living in the community, participated in a 24-wk crossover study (two 12-wk periods). Five randomly chosen subjects ate Barley Bread products first; the remainder ate the control White Bread first. Dietary intake was assessed (four 48-h dietary recalls/period). Blood glucose and insulin (8-h profiles) were measured at 0, 12 and 24 wks. Total energy and macronutrient intakes were similar in both dietary periods. Mean total dietary fibre intake was 28 g/d in the White Bread period and 39 g/d (10 g/d from barley) in the Barley Bread period. Mean glycemic response area (AUC) was lower (NS) and insulin response area was higher (P 0.05) for the Barley Bread period than the White Bread period. In the Barley Bread period, AUC after lunch was lower for glucose (NS) and higher for insulin (P 0.05) than in the White Bread period. For the Barley Bread period, insulin/glucose ratios for peak 1 and peak 2 were 65% (P 0.05) and 113% (NS), respectively, higher than for the White Bread period. Results indicate that for the Type 2 diabetic subjects incorporation of the well accepted Barley Bread products (5 g/d β-glucan) into the diet improved their glycemic response. Insulinemic response increased; some subjects reduced their dose of oral hypoglycemics. Barley Bread products could be readily incorporated into the diet and greatly benefit the overall health of individuals with Type 2 diabetes.
Patients with diabetes are often recommended to use whole fruit rather than canned fruit or fruit juice because of a belief that the addition of sucrose to canned fruit and the removal of dietary fibre to make fruit juice may increase blood glucose responses. However, the glycaemic responses of few fruits and fruit products have been assessed in patients with diabetes. Therefore, we determined the glycaemic index (GI) values of ten fruits and fruit products in patients with diabetes, for comparison with the GI of white bread (100). The mean ± s.e.m. GI values, with number of subjects in parentheses, were: pineapple juice, 66 ± 3 (13); grapefruit juice, 69 ± 5 (13); apple juice, 59 ± 8 (6); canned peaches, 74 ± 7 (11); canned pears, 63 ± 6 (10); canned apricots, 91 ± 6 (9); fruit cocktail, 79 ± 5 (8); dried apricots, 46 ± 7 (9); fresh oranges, 69 ± 11 (10); and fresh pears, 58 ± 7 (13). It is concluded that in patients with diabetes the glycaemic responses of various fruit products vary over a two-fold range. Most canned fruits and fruit juices tested had similar glycaemic responses to fresh fruits when equivalent amounts of carbohydrate were consumed.
The glycaemic index of foods describes the hyperglycaemic effect of isolated foods. It is measured by the ratio of the area under the glycaemic curve observed after ingestion of a 50 gram carbohydrate dose of the tested food to the area observed after ingestion of the same amount of a reference food (white bread). The glycaemic index classification provides an approach of the diabetic diet based on the glucose response to foods. Widely accepted when applied to isolated foods, its clinical utility during mixed meals remains discussed. The improvement of the average metabolic control which can be expected from its use is modest. However, its major interest could be observed during snacks and meals in order to control precisely post-prandial glucose variations, in association with blood glucose self-monitoring. As it allows high sweet taste-low-glycaemic index-carbohydrate foods to be consumed, it could significantly improve the quality of life of diabetic patients.
The purpose of the study was to compare the in vitro starch digestibility and postprandial blood glucose response of conventionally-cooked versus factory-processed foods. Carbohydrate portions of three unprocessed foods (boiled rice, sweet corn, and potato) and six processed foods (instant rice, Rice Bubbles, corn chips, Cornflakes, instant potato, and potato crisps) were incubated for 3 h with human saliva and porcine pancreatin. The proportion of starch digested was significantly higher (p less than 0.05) for the processed forms of rice, corn, and potato compared with the respective conventionally cooked foods. In six healthy volunteers who ingested 50 g carbohydrate portions of the above foods the processed foods produced a higher glycemic index (p less than 0.05) in all but one instance. The exception was potato crisps which gave a similar glycemic response to boiled potato.
The determine the effect of different foods on the blood glucose, 62 commonly eaten foods and sugars were fed individually to groups of 5 to 10 healthy fasting volunteers. Blood glucose levels were measured over 2 h, and expressed as a percentage of the area under the glucose response curve when the same amount of carbohydrate was taken as glucose. The largest rises were seen with vegetables (70 +/- 5%), followed by breakfast cereals (65 +/- 5%), cereals and biscuits (60 +/- 3%), fruit (50 +/- 5%), dairy products (35 +/- 1%), and dried legumes (31 +/- 3%). A significant negative relationship was seen between fat (p less than 0.01) and protein (p less than 0.001) and postprandial glucose rise but not with fiber or sugar content.
Effects of source of dietary carbohydrate on plasma glucose, insulin and gastric inhibitory polypeptide responses to test meals in subjects with noninsulindependent diabetes mellitus
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Am J Gin Nutr 1984;40:965-70.