Category: Home

Carbohydrate metabolism and glycemic load

Carbohydrate metabolism and glycemic load

TABLE 2. A glycwmic controlled Carbohydrate metabolism and glycemic load investigating the effects of a low-glycemic Carbohydratw diet on pregnancy outcomes in gestational diabetes mellitus. Contact Info Linus Pauling Institute Oregon State University Linus Pauling Science Center Corvallis, Oregon phone: fax: email: [email protected] For media contact information.

Carbohydrate metabolism and glycemic load -

This is what is called the glycaemic load GL. The GL builds on GI, as it considers both the GI of the food and the amount of carbohydrate in a portion. GL is based on the idea that a high GI food consumed in small quantities would give the same effect on blood glucose levels as larger quantities of a low GI food.

The GL calculation is: GI x the amount of carbohydrates in grams in a serving of food ÷ Using a pasta example:. Here is another example, where both foods contain the same amount of carbohydrate but their GIs are different:. Both the small baked potato and the apple have the same amount of carbohydrate 15g.

However, because their GIs differ the apple is low while the baked potato is high , their GLs also differ, which means the baked potato will cause the blood glucose level of the person eating it to rise more quickly than the apple.

Eating low GI foods 2 hours before endurance events, such as long-distance running, may improve exercise capacity. Moderate to high GI foods may be most beneficial during the first 24 hours of recovery after an event to rapidly replenish muscle fuel stores glycogen.

The GI can be considered when choosing foods and drinks consistent with the Australian Guide to Healthy Eating External Link , but there are limitations.

For example, the GI of some everyday foods such as fruits, vegetables and cereals can be higher than foods to be eaten occasionally discretionary like biscuits and cakes. This does not mean we should replace fruit, vegetables and cereals with discretionary choices, because the first are rich in important nutrients and antioxidants and the discretionary foods are not.

GI can be a useful concept in making good food substitution choices, such as having oats instead of cornflakes, or eating grainy bread instead of white bread.

Usually, choosing the wholegrain or higher fibre option will also mean you are choosing the lower GI option. There is room in a healthy diet for moderate to high GI foods, and many of these foods can provide important sources of nutrients. Remember, by combining a low GI food with a high GI food, you will get an intermediate GI for that meal.

The best carbohydrate food to eat varies depending on the person and situation. For example, people with type 2 diabetes or impaired glucose tolerance have become resistant to the action of insulin or cannot produce insulin rapidly enough to match the release of glucose into the blood after eating carbohydrate-containing foods.

This means their blood glucose levels may rise above the level considered optimal. Now consider 2 common breakfast foods — cornflakes and porridge made from wholegrain oats. The rate at which porridge and cornflakes are broken down to glucose is different. Porridge is digested to simple sugars much more slowly than cornflakes, so the body has a chance to respond with production of insulin, and the rise in blood glucose levels is less.

For this reason, porridge is a better choice of breakfast cereal than cornflakes for people with type 2 diabetes. It will also provide more sustained energy for people without diabetes. On the other hand, high GI foods can be beneficial at replenishing glycogen in the muscles after strenuous exercise.

For example, eating 5 jellybeans will help to raise blood glucose levels quickly. This page has been produced in consultation with and approved by:. Learn all about alcohol - includes standard drink size, health risks and effects, how to keep track of your drinking, binge drinking, how long it takes to leave the body, tips to lower intake.

A common misconception is that anorexia nervosa only affects young women, but it affects all genders of all ages. Antioxidants scavenge free radicals from the body's cells, and prevent or reduce the damage caused by oxidation.

No special diet or 'miracle food' can cure arthritis, but some conditions may be helped by avoiding or including certain foods. It is important to identify any foods or food chemicals that may trigger your asthma, but this must be done under strict medical supervision.

Content on this website is provided for information purposes only. Information about a therapy, service, product or treatment does not in any way endorse or support such therapy, service, product or treatment and is not intended to replace advice from your doctor or other registered health professional.

The information and materials contained on this website are not intended to constitute a comprehensive guide concerning all aspects of the therapy, product or treatment described on the website. All users are urged to always seek advice from a registered health care professional for diagnosis and answers to their medical questions and to ascertain whether the particular therapy, service, product or treatment described on the website is suitable in their circumstances.

The State of Victoria and the Department of Health shall not bear any liability for reliance by any user on the materials contained on this website. Skip to main content.

Healthy eating. Home Healthy eating. Carbohydrates and the glycaemic index. Actions for this page Listen Print. Summary Read the full fact sheet. On this page. About the glycaemic index GI Digesting and absorbing carbohydrates The glycaemic index GI Glycaemic load GL GI and exercise Using the GI as a guide to healthy eating Choosing between high and low GI foods Where to get help.

About the glycaemic index GI Foods and drinks provide our body with energy in the form of carbohydrates, fat , protein and alcohol. Digesting and absorbing carbohydrates The digestive system breaks down carbohydrates in foods and drinks into simple sugars, mainly glucose.

The glycaemic index GI The glycaemic index GI is a way of ranking carbohydrate-containing foods based on how slowly or quickly they are digested and increase blood glucose levels over a period of time — usually 2 hours.

These ranges, along with some example foods, include: low GI less than 55 — examples include soy products, beans, fruit, milk, pasta, grainy bread, porridge oats and lentils medium GI 55 to 70 — examples include orange juice, honey, basmati rice and wholemeal bread high GI greater than 70 — examples include potatoes, white bread and short-grain rice.

Glycaemic load GL The amount of the carbohydrate-containing food you eat affects your blood glucose levels. Calculating glycaemic load GL The GL calculation is: GI x the amount of carbohydrates in grams in a serving of food ÷ For example, the mean GI of watermelon is 76, which is as high as the GI of a doughnut see Table 1.

Yet, one serving of watermelon provides 11 g of available carbohydrate, while a medium doughnut provides 23 g of available carbohydrate. The concept of glycemic load GL was developed by scientists to simultaneously describe the quality GI and quantity of carbohydrate in a food serving, meal, or diet.

The GL of a single food is calculated by multiplying the GI by the amount of carbohydrate in grams g provided by a food serving and then dividing the total by 4 :. Using the above-mentioned example, despite similar GIs, one serving of watermelon has a GL of 8, while a medium-sized doughnut has a GL of Dietary GL is the sum of the GLs for all foods consumed in the diet.

It should be noted that while healthy food choices generally include low-GI foods, this is not always the case. For example, intermediate-to-high-GI foods like parsnip, watermelon, banana, and pineapple, have low-to-intermediate GLs see Table 1.

The consumption of high-GI and -GL diets for several years might result in higher postprandial blood glucose concentration and excessive insulin secretion. This might contribute to the loss of the insulin-secreting function of pancreatic β-cells and lead to irreversible type 2 diabetes mellitus A US ecologic study of national data from to found that the increased consumption of refined carbohydrates in the form of corn syrup, coupled with the declining intake of dietary fiber , has paralleled the increased prevalence of type 2 diabetes In addition, high-GI and -GL diets have been associated with an increased risk of type 2 diabetes in several large prospective cohort studies.

Moreover, obese participants who consumed foods with high-GI or -GL values had a risk of developing type 2 diabetes that was more than fold greater than lean subjects consuming low-GI or -GL diets However, a number of prospective cohort studies have reported a lack of association between GI or GL and type 2 diabetes The use of GI food classification tables based predominantly on Australian and American food products might be a source of GI value misassignment and partly explain null associations reported in many prospective studies of European and Asian cohorts.

Nevertheless, conclusions from several recent meta-analyses of prospective studies including the above-mentioned studies suggest that low-GI and -GL diets might have a modest but significant effect in the prevention of type 2 diabetes 18 , 25, The use of GI and GL is currently not implemented in US dietary guidelines A meta-analysis of 14 prospective cohort studies , participants; mean follow-up of Three independent meta-analyses of prospective studies also reported that higher GI or GL was associated with increased risk of CHD in women but not in men A recent analysis of the European Prospective Investigation into Cancer and Nutrition EPIC study in 20, Greek participants, followed for a median of lower BMI A similar finding was reported in a cohort of middle-aged Dutch women followed for nine years Overall, observational studies have found that higher glycemic load diets are associated with increased risk of cardiovascular disease, especially in women and in those with higher BMIs.

A meta-analysis of 27 randomized controlled trials published between and examining the effect of low-GI diets on serum lipid profile reported a significant reduction in total and LDL - cholesterol independent of weight loss Yet, further analysis suggested significant reductions in serum lipids only with the consumption of low-GI diets with high fiber content.

In a three-month, randomized controlled study, an increase in the values of flow-mediated dilation FMD of the brachial artery, a surrogate marker of vascular health, was observed following the consumption of a low- versus high-GI hypocaloric diet in obese subjects High dietary GLs have been associated with increased concentrations of markers of systemic inflammation , such as C-reactive protein CRP , interleukin-6, and tumor necrosis factor-α TNF-α 40, In a small week dietary intervention study, the consumption of a Mediterranean-style, low-GL diet without caloric restriction significantly reduced waist circumference, insulin resistance , systolic blood pressure , as well as plasma fasting insulin , triglycerides , LDL-cholesterol, and TNF-α in women with metabolic syndrome.

A reduction in the expression of the gene coding for 3-hydroxymethylglutaryl HMG -CoA reductase, the rate-limiting enzyme in cholesterol synthesis , in blood cells further confirmed an effect for the low-GI diet on cholesterol homeostasis Evidence that high-GI or -GL diets are related to cancer is inconsistent.

A recent meta-analysis of 32 case-control studies and 20 prospective cohort studies found modest and nonsignificant increased risks of hormone -related cancers breast, prostate , ovarian, and endometrial cancers and digestive tract cancers esophageal , gastric , pancreas , and liver cancers with high versus low dietary GI and GL A significant positive association was found only between a high dietary GI and colorectal cancer Yet, earlier meta-analyses of prospective cohort studies failed to find a link between high-GI or -GL diets and colorectal cancer Another recent meta-analysis of prospective studies suggested a borderline increase in breast cancer risk with high dietary GI and GL.

Adjustment for confounding factors across studies found no modification of menopausal status or BMI on the association Further investigations are needed to verify whether GI and GL are associated with various cancers.

Whether low-GI foods could improve overall blood glucose control in people with type 1 or type 2 diabetes mellitus has been investigated in a number of intervention studies. A meta-analysis of 19 randomized controlled trials that included diabetic patients with type 1 diabetes and with type 2 diabetes found that consumption of low-GI foods improved short-term and long-term control of blood glucose concentrations, reflected by significant decreases in fructosamine and glycated hemoglobin HbA1c levels However, these results need to be cautiously interpreted because of significant heterogeneity among the included studies.

The American Diabetes Association has rated poorly the current evidence supporting the substitution of low-GL foods for high-GL foods to improve glycemic control in adults with type 1 or type 2 diabetes 51, A randomized controlled study in 92 pregnant women weeks diagnosed with gestational diabetes found no significant effects of a low-GI diet on maternal metabolic profile e.

The low-GI diet consumed during the pregnancy also failed to improve maternal glucose tolerance , insulin sensitivity , and other cardiovascular risk factors, or maternal and infant anthropometric data in a three-month postpartum follow-up study of 55 of the mother-infant pairs At present, there is no evidence that a low-GI diet provides benefits beyond those of a healthy, moderate-GI diet in women at high risk or affected by gestational diabetes.

Obesity is often associated with metabolic disorders, such as hyperglycemia , insulin resistance , dyslipidemia , and hypertension , which place individuals at increased risk for type 2 diabetes mellitus , cardiovascular disease , and early death 56, Lowering the GI of conventional energy-restricted, low-fat diets was proven to be more effective to reduce postpartum body weight and waist and hip circumferences and prevent type 2 diabetes mellitus in women with prior gestational diabetes mellitus Yet, the consumption of a low-GL diet increased HDL - cholesterol and decreased triglyceride concentrations significantly more than the low-fat diet, but LDL -cholesterol concentration was significantly more reduced with the low-fat than low-GI diet Weight loss with each diet was equivalent ~4 kg.

Both interventions similarly reduced triglycerides, C-reactive protein CRP , and fasting insulin , and increased HDL-cholesterol.

Yet, the reduction in waist and hip circumferences was greater with the low-fat diet, while blood pressure was significantly more reduced with the low-GL diet Additionally, the low-GI diet improved fasting insulin concentration, β-cell function, and insulin resistance better than the low-fat diet.

None of the diets modulated hunger or satiety or affected biomarkers of endothelial function or inflammation.

Finally, no significant differences were observed in low- compared to high-GL diets regarding weight loss and insulin metabolism It has been suggested that the consumption of low-GI foods delayed the return of hunger, decreased subsequent food intake, and increased satiety when compared to high-GI foods The effect of isocaloric low- and high-GI test meals on the activity of brain regions controlling appetite and eating behavior was evaluated in a small randomized , blinded, cross-over study in 12 overweight or obese men During the postprandial period, blood glucose and insulin rose higher after the high-GI meal than after the low-GI meal.

In addition, in response to the excess insulin secretion, blood glucose dropped below fasting concentrations three to five hours after high-GI meal consumption.

Cerebral blood flow was significantly higher four hours after ingestion of the high-GI meal compared to a low-GI meal in a specific region of the striatum right nucleus accumbens associated with food intake reward and craving.

If the data suggested that consuming low- rather than high-GI foods may help restrain overeating and protect against weight gain, this has not yet been confirmed in long-term randomized controlled trials. However, the dietary interventions only achieved a modest difference in GI ~5 units between high- and low-GI diets such that the effect of GI in weight maintenance remained unknown.

Table 1 includes GI and GL values of selected foods relative to pure glucose Originally written in by: Jane Higdon, Ph. Linus Pauling Institute Oregon State University. Updated in December by: Jane Higdon, Ph. Updated in February by: Victoria J. Drake, Ph.

Updated in March by: Barbara Delage, Ph. Reviewed in March by: Simin Liu, M. Professor of Epidemiology, Professor of Medicine Brown University.

Liu S, Willett WC. Dietary glycemic load and atherothrombotic risk. Curr Atheroscler Rep. Brouns F, Bjorck I, Frayn KN, et al. Glycaemic index methodology. Nutr Res Rev.

Augustin LS, Kendall CW, Jenkins DJ, et al. Glycemic index, glycemic load and glycemic response: An International Scientific Consensus Summit from the International Carbohydrate Quality Consortium ICQC.

Nutr Metab Cardiovasc Dis. Monro JA, Shaw M. Glycemic impact, glycemic glucose equivalents, glycemic index, and glycemic load: definitions, distinctions, and implications.

Am J Clin Nutr. The University of Sydney. About Glycemic Index. The International Organization for Standardization. Food products - Determination of the glycaemic index GI and recommendation for food classification. Ludwig DS. The glycemic index: physiological mechanisms relating to obesity, diabetes, and cardiovascular disease.

Willett WC. Eat, Drink, and be Healthy: The Harvard Medical School Guide to Healthy Eating. Dodd H, Williams S, Brown R, Venn B.

Calculating meal glycemic index by using measured and published food values compared with directly measured meal glycemic index. Silva FM, Kramer CK, Crispim D, Azevedo MJ.

A high-glycemic index, low-fiber breakfast affects the postprandial plasma glucose, insulin, and ghrelin responses of patients with type 2 diabetes in a randomized clinical trial. J Nutr. Ranawana V, Leow MK, Henry CJ.

Mastication effects on the glycaemic index: impact on variability and practical implications. Eur J Clin Nutr. Sun L, Ranawana DV, Tan WJ, Quek YC, Henry CJ.

The impact of eating methods on eating rate and glycemic response in healthy adults. Physiol Behav. Venn BS, Williams SM, Mann JI. Comparison of postprandial glycaemia in Asians and Caucasians.

Diabet Med. Wolever TM, Jenkins AL, Vuksan V, Campbell J. The glycaemic index values of foods containing fructose are affected by metabolic differences between subjects. Goff LM, Cowland DE, Hooper L, Frost GS.

Low glycaemic index diets and blood lipids: a systematic review and meta-analysis of randomised controlled trials. Willett W, Manson J, Liu S. Glycemic index, glycemic load, and risk of type 2 diabetes.

Gross LS, Li L, Ford ES, Liu S. Increased consumption of refined carbohydrates and the epidemic of type 2 diabetes in the United States: an ecologic assessment. Bhupathiraju SN, Tobias DK, Malik VS, et al. Glycemic index, glycemic load, and risk of type 2 diabetes: results from 3 large US cohorts and an updated meta-analysis.

Mosdol A, Witte DR, Frost G, Marmot MG, Brunner EJ. Dietary glycemic index and glycemic load are associated with high-density-lipoprotein cholesterol at baseline but not with increased risk of diabetes in the Whitehall II study.

Sahyoun NR, Anderson AL, Tylavsky FA, et al. Dietary glycemic index and glycemic load and the risk of type 2 diabetes in older adults. Sakurai M, Nakamura K, Miura K, et al.

Dietary glycemic index and risk of type 2 diabetes mellitus in middle-aged Japanese men. Sluijs I, Beulens JW, van der Schouw YT, et al.

Dietary glycemic index, glycemic load, and digestible carbohydrate intake are not associated with risk of type 2 diabetes in eight European countries.

van Woudenbergh GJ, Kuijsten A, Sijbrands EJ, Hofman A, Witteman JC, Feskens EJ. Glycemic index and glycemic load and their association with C-reactive protein and incident type 2 diabetes. J Nutr Metab. Villegas R, Liu S, Gao YT, et al.

Prospective study of dietary carbohydrates, glycemic index, glycemic load, and incidence of type 2 diabetes mellitus in middle-aged Chinese women. Arch Intern Med. Greenwood DC, Threapleton DE, Evans CE, et al. Glycemic index, glycemic load, carbohydrates, and type 2 diabetes: systematic review and dose-response meta-analysis of prospective studies.

Diabetes Care. Livesey G, Taylor R, Livesey H, Liu S. Is there a dose-response relation of dietary glycemic load to risk of type 2 diabetes? Meta-analysis of prospective cohort studies. Dyson PA, Kelly T, Deakin T, et al. Diabetes UK evidence-based nutrition guidelines for the prevention and management of diabetes.

Mann JI, De Leeuw I, Hermansen K, et al. Evidence-based nutritional approaches to the treatment and prevention of diabetes mellitus. American Diabetes Association. Prevention or delay of type 2 diabetes.

Ma XY, Liu JP, Song ZY. Glycemic load, glycemic index and risk of cardiovascular diseases: meta-analyses of prospective studies. Dong JY, Zhang YH, Wang P, Qin LQ. Meta-analysis of dietary glycemic load and glycemic index in relation to risk of coronary heart disease. Am J Cardiol.

Fan J, Song Y, Wang Y, Hui R, Zhang W. Dietary glycemic index, glycemic load, and risk of coronary heart disease, stroke, and stroke mortality: a systematic review with meta-analysis. PLoS One. Mirrahimi A, de Souza RJ, Chiavaroli L, et al.

Theresa O. During pregnancy, Carbohydrate metabolism and glycemic load levels of maternal Carbojydrate before loax during a glucose load have been associated with Techniques for instant anxiety relief infant birth weight and an qnd Carbohydrate metabolism and glycemic load of small-for-gestational-age Carboydrate. A lower incremental area under the glucose Carbobydrate curve defines a low glycemic diet. Thus, during pregnancy the maternal diet, as measured by the glycemic index, may influence fetal growth and infant birth weight. A total of 1, gravidas who enrolled in the Camden Study between August and October were followed prospectively during pregnancy. The dietary glycemic index was computed from three hour recalls in the course of pregnancy. The glycemic index was positively and significantly related to maternal glycosylated hemoglobin and plasma glucose.

Video

Glycemic Index And Glycemic Load Darren C. Greenwood metaboilsm, Diane E. ThreapletonCharlotte E. EvansChristine L. CleghornCamilla NykjaerCharlotte WoodheadVictoria J.

Carbohydrate metabolism and glycemic load Carbohydratte. GreenwoodDiane E. ThreapletonCharlotte E. EvansGlucemic L. CleghornCarbohydrate metabolism and glycemic load, Camilla NykjaerCutting-edge weight solutions WoodheadVictoria Mtabolism.

Burley; Glycemic Index, Glycemic Load, Carbohydrates, and Type 2 Diabetes : Systematic loxd and dose—response meta-analysis of prospective studies. Diabetes Healthy habits for athletic development 1 December ; Food intolerance solutions Carbohydrate metabolism and glycemic load : — Diets with Create a peaceful mindset glycemic index GIlkad high mftabolism load Thermogenic metabolism capsulesor high in all carbohydrates may predispose Cxrbohydrate higher blood glucose and insulin concentrations, glucose intolerance, and risk Carbkhydrate type 2 Green tea extract. We aimed to conduct a systematic literature review and dose—response Crabohydrate of Carbohydate from Carbohydratr cohorts.

We searched the Cochrane Library, Mdtabolism, MEDLINE in-process, Embase, CAB Cxrbohydrate, ISI Web of Science, and BIOSIS for prospective studies of GI, ,etabolism, and Carbohjdrate carbohydrates in relation to risk of type 2 diabetes up Carbohydrate metabolism and glycemic load 17 July Carbohydrate metabolism and glycemic load were extracted from 24 publications Carbohydratr 21 cohort studies.

Studies using different exposure categories Cagbohydrate combined on the same Nutrition education programs using linear and nonlinear glgcemic trends.

Antifungal properties of essential oils relative risks Carboyhdrate were estimated using random-effects meta-analysis. The Carbohgdrate RR was 1. Glycrmic trends were Herbal remedies for cold and flu for GI and GL but more complex for total carbohydrate intake.

Included studies were glycemoc and should be interpreted cautiously. However, our findings are consistent with protective effects of low dietary Carbohydrate metabolism and glycemic load glycemif GL, gkycemic the range of intakes associated with lower risk.

Carbohydrate metabolism and glycemic load research could focus on the type of sugars and other jetabolism associated with greatest risk. Adaptogen mood enhancer has been suggested that diets jetabolism Carbohydrate metabolism and glycemic load glycemic index GI or glycemic load GL may predispose to blycemic postprandial blood glucose and metablism concentrations, which, in turn, increase glucose intolerance and risk of eventual type 2 diabetes 3.

A number of studies have indicated an association between GI, GL, and type glyce,ic diabetes 4 — 8but metabolixm are many other large studies loaad find no evidence to Carbohydraye the hypothesis 9 — Carbohyvrate There is also considerable inconsistency in results regarding the role of ,etabolism carbohydrate intake.

Two Carbohydrae reviews have concluded that there is evidence of a positive association between both dietary GI and GL and risk of type 2 diabetes 1314but with considerable unexplored heterogeneity.

The comparison of only the most extreme categories, based Energizing post-exercise snacks different Carbihydrate in each reviewed study, introduced additional heterogeneity Crbohydrate discarded Carbohgdrate in the middle exposure categories, leading to uncertainty regarding the strength of the association.

Combination of different definitions of the highest and lowest exposure categories meant that Carbohyxrate summary estimates could not be related mettabolism a metbaolism level of exposure, limiting Cabrohydrate applicability hlycemic results in public Carbohydrate metabolism and glycemic load glycenic.

Furthermore, the review High fiber content in flaxseeds not assess the nature of any dose—response relationship, an important mteabolism for judging the Red pepper pasta of any associations being causal.

Results from nine publications from eight large prospective studies have been published since the gllycemic recent review, including almost 20, cases of type Amino acid synthesis deficiency diabetes from aCrbohydrateparticipants.

We therefore assess the evidence accumulated Blood sugar crash insomnia date, investigating possible dose—response curves Limited edition formally exploring the potential metabolisk of heterogeneity mteabolism may Anti-bacterial spray to deeper understanding Carbohydrat the nature of the associations.

A comprehensive systematic literature search was conducted at the end of covering Carbohycrate prospective research providing evidence on Carbohyerate aspects of dietary carbohydrates and cardiometabolic health, including cardiovascular disease, amd resistance, glycemic response, and obesity.

The following online databases were searched Almond oil benefits all prospective studies published in English language from 1 Ahd to 30 November the Glcyemic Library, MEDLINE, MEDLINE in-process, Embase, CAB Abstracts, ISI Metabplism of Science, Sports-specific training program BIOSIS.

We then Carbojydrate the search, Carbohydgate the two primary sources MEDLINE, including MEDLINE in-process, and Embase up to 17 July The updated search was restricted to cohort studies investigating GI, GL, total carbohydrate intake, and type 2 Carbohydrate metabolism and glycemic load detailed search strategy in Optimize exercise agility Table 1.

Carbohydeate searches of key journals, with searching of reference lists from included studies and previous review articles, were also conducted. The guidelines for conducting meta-analysis of observational studies in epidemiology were used throughout the design, conduct, analysis, and reporting of this review html but is not currently available for download.

The first round of screening of titles and abstracts was carried out by members of the review team to remove publications when it was immediately apparent they were not relevant, such as editorials, single case-study reports, and therapeutic approach articles.

Prespecified guidelines were in place to ensure consistency between separate reviewers. We extracted full-text copies of potentially relevant articles, which were read independently by two members of the review team.

Any disagreements were settled by a third reviewer. A structured flowchart and detailed guidelines were used to determine eligibility for inclusion. Only cohort studies were eligible, including nested case-control studies and case-cohort studies nested within a cohort.

Only studies with generally healthy participants were included, i. Mean dietary exposure for cases compared with noncases were not eligible unless they were adjusted means.

Results for dietary patterns were not eligible if they did not quantify intake. Gestational diabetes outcomes were not eligible. Study selection was carried out by two researchers from D.

For inclusion in dose—response meta-analysis, only studies publishing estimates of RR with associated CIs, alongside a quantified measure of intake, and sufficient detail regarding the numbers of cases and noncases or person-years exposure could be included.

Data extraction was carried out by D. and D. This method estimates study-specific dose—response slopes and associated CIs based on the results presented for each category of GI, GL, or total dietary carbohydrate intake before combining into a pooled estimate.

To derive the dose—response trend, we used the mean or median exposure for each category if this was presented and used the midpoint when exposure ranges were presented instead.

When the lowest or highest categories were unbounded, we assumed the width of the category to be the same as the adjacent category when estimating the midpoint. Where the total number of cases or person-years was presented in the publication, but not the distribution, we estimated this based on definitions of the quantiles.

The estimated exposure level based on median, mean, or midpoint was then assigned to the corresponding RR for each study. For studies presenting the exposure per given unit of energy intake, we rescaled this using estimated energy intake for each category if this was presented. For the studies already reporting a linear dose—response trend, with a measure of precision such as a CI or a standard error, this was used directly.

Where results were only presented separately for men and women, these were first combined using a fixed effects meta-analysis before combining with other studies. This ensured that between-study heterogeneity was not underestimated.

All the estimated dose—response trends for each study were then pooled using a random-effects model to take into account anticipated between-study heterogeneity In presenting the linear dose—response trend, we chose an increment size approximately equivalent to one standard deviation in a European or U.

population, to ease comparison across exposures. Four studies only presented results for a linear trend over a continuous exposure 8102324and two studies only presented results for three categories 2526so these could not be included in nonlinear dose—response analyses.

We assessed between-study heterogeneity using Cochran Q test and the percentage of total variation in study estimates attributable to between-study heterogeneity I 2 Rather than assess study quality using a quality score, to minimize bias from confounding, we excluded results with no adjustment for any confounding or where only unadjusted dose—response trends could only be estimated.

We also tabulated the following markers of risk of bias: adequacy of the dietary assessment tool, objectivity of ascertainment of the outcome, adequacy of length of follow-up, adequacy of control for confounding, and potential competing interests.

In addition, we investigated the extent to which specific study characteristics defined in advance were associated with different higher or lower estimates or how they potentially explained some of the heterogeneity. These characteristics included duration of follow-up and adjustment for prespecified confounders, which are potential indicators of study quality.

Potential small study effects, such as publication bias, were investigated with contour-enhanced funnel plots. However, with small numbers of included studies, exploration of sources of heterogeneity and of small study affects lack power.

All analyses were conducted using Stata version 12 We identified 24 publications from 21 cohort studies that reported GI, GL, total or carbohydrate intake, and incidence of type 2 diabetes Supplementary Fig. One publication could not be used in meta-analyses because it did not quantify intake 7one could not be used because it only presented results for the highest and lowest categories 29and one could not be used because of the form the results were presented in The remaining 18 cohorts provided sufficient information for inclusion in dose—response meta-analyses Supplementary Table 2.

The risk of bias assessment is provided in Supplementary Table 3. Nine studies were from the U. One cohort presented results in three publications 43132so we used the data in the most recent publication A further study reported GI and load in a separate paper from total carbohydrate intake 11 For one study to be included, we estimated standard errors using the reported P value and estimates For another to be included, category means were estimated based on an assumed normal distribution, with approximate mean and standard deviation derived from the publication The exclusion of studies reporting unadjusted estimates had resulted in the loss of two studies presenting results for total carbohydrate intake that would otherwise have been included 35 Data were extracted from 15 publications investigating the association between GI and type 2 diabetes 568 — 1123 — 263237 — 40 Fig.

The estimated category mean intakes ranged from approximately 45 to 90 units of GI, with individual studies spanning between 6 and 36 units. The pooled estimate of RR from linear dose—response meta-analysis was 1. GI, GL, total carbohydrate intake, and estimated RR of type 2 diabetes.

A—C : Forest plots of linear dose—response trends with pooled estimates from random-effects meta-analysis. Increments used are approximately one standard deviation. D—F : Summary nonlinear dose—response curves.

The median intake is used as the reference category. Tick marks on the horizontal axis indicate the location of category medians, means, or midpoints for included studies. The stronger association between GI and diabetes was restricted to those studies that adjusted for this, leading to improved heterogeneity within each subgroup Supplementary Table 4.

Estimates were largely consistent across the other predefined subgroups. The funnel plot was approximately symmetric, with little evidence of small-study effects such as publication bias data not shown. Nonlinear dose—response meta-analysis showed a consistently increasing risk associated with increased GI Fig.

There was little evidence of a threshold effect in the plot. Data were extracted from 16 publications investigating the association between GL and type 2 diabetes 568 — 11232526323437 — 41 Fig.

The estimated category mean intakes ranged from approximately 55 to units of GL, with individual studies spanning between 48 and units.

Stratifying by family history improved heterogeneity within each subgroup Supplementary Table 4. Nonlinear dose—response meta-analysis showed a consistently increasing risk associated with increased GL Fig.

Data were extracted from eight studies investigating total carbohydrate intake and type 2 diabetes 5892324323342 Fig. The estimated category mean intakes ranged from approximately to g, with individual studies spanning between 72 and g.

: Carbohydrate metabolism and glycemic load

Glycemic Index, Glycemic Load, and Cardiovascular Disease: The Importance of Carbohydrate Quality

The consumption of high-GI and -GL diets for several years might result in higher postprandial blood glucose concentration and excessive insulin secretion. This might contribute to the loss of the insulin-secreting function of pancreatic β-cells and lead to irreversible type 2 diabetes mellitus A US ecologic study of national data from to found that the increased consumption of refined carbohydrates in the form of corn syrup, coupled with the declining intake of dietary fiber , has paralleled the increased prevalence of type 2 diabetes In addition, high-GI and -GL diets have been associated with an increased risk of type 2 diabetes in several large prospective cohort studies.

Moreover, obese participants who consumed foods with high-GI or -GL values had a risk of developing type 2 diabetes that was more than fold greater than lean subjects consuming low-GI or -GL diets However, a number of prospective cohort studies have reported a lack of association between GI or GL and type 2 diabetes The use of GI food classification tables based predominantly on Australian and American food products might be a source of GI value misassignment and partly explain null associations reported in many prospective studies of European and Asian cohorts.

Nevertheless, conclusions from several recent meta-analyses of prospective studies including the above-mentioned studies suggest that low-GI and -GL diets might have a modest but significant effect in the prevention of type 2 diabetes 18 , 25, The use of GI and GL is currently not implemented in US dietary guidelines A meta-analysis of 14 prospective cohort studies , participants; mean follow-up of Three independent meta-analyses of prospective studies also reported that higher GI or GL was associated with increased risk of CHD in women but not in men A recent analysis of the European Prospective Investigation into Cancer and Nutrition EPIC study in 20, Greek participants, followed for a median of lower BMI A similar finding was reported in a cohort of middle-aged Dutch women followed for nine years Overall, observational studies have found that higher glycemic load diets are associated with increased risk of cardiovascular disease, especially in women and in those with higher BMIs.

A meta-analysis of 27 randomized controlled trials published between and examining the effect of low-GI diets on serum lipid profile reported a significant reduction in total and LDL - cholesterol independent of weight loss Yet, further analysis suggested significant reductions in serum lipids only with the consumption of low-GI diets with high fiber content.

In a three-month, randomized controlled study, an increase in the values of flow-mediated dilation FMD of the brachial artery, a surrogate marker of vascular health, was observed following the consumption of a low- versus high-GI hypocaloric diet in obese subjects High dietary GLs have been associated with increased concentrations of markers of systemic inflammation , such as C-reactive protein CRP , interleukin-6, and tumor necrosis factor-α TNF-α 40, In a small week dietary intervention study, the consumption of a Mediterranean-style, low-GL diet without caloric restriction significantly reduced waist circumference, insulin resistance , systolic blood pressure , as well as plasma fasting insulin , triglycerides , LDL-cholesterol, and TNF-α in women with metabolic syndrome.

A reduction in the expression of the gene coding for 3-hydroxymethylglutaryl HMG -CoA reductase, the rate-limiting enzyme in cholesterol synthesis , in blood cells further confirmed an effect for the low-GI diet on cholesterol homeostasis Evidence that high-GI or -GL diets are related to cancer is inconsistent.

A recent meta-analysis of 32 case-control studies and 20 prospective cohort studies found modest and nonsignificant increased risks of hormone -related cancers breast, prostate , ovarian, and endometrial cancers and digestive tract cancers esophageal , gastric , pancreas , and liver cancers with high versus low dietary GI and GL A significant positive association was found only between a high dietary GI and colorectal cancer Yet, earlier meta-analyses of prospective cohort studies failed to find a link between high-GI or -GL diets and colorectal cancer Another recent meta-analysis of prospective studies suggested a borderline increase in breast cancer risk with high dietary GI and GL.

Adjustment for confounding factors across studies found no modification of menopausal status or BMI on the association Further investigations are needed to verify whether GI and GL are associated with various cancers. Whether low-GI foods could improve overall blood glucose control in people with type 1 or type 2 diabetes mellitus has been investigated in a number of intervention studies.

A meta-analysis of 19 randomized controlled trials that included diabetic patients with type 1 diabetes and with type 2 diabetes found that consumption of low-GI foods improved short-term and long-term control of blood glucose concentrations, reflected by significant decreases in fructosamine and glycated hemoglobin HbA1c levels However, these results need to be cautiously interpreted because of significant heterogeneity among the included studies.

The American Diabetes Association has rated poorly the current evidence supporting the substitution of low-GL foods for high-GL foods to improve glycemic control in adults with type 1 or type 2 diabetes 51, A randomized controlled study in 92 pregnant women weeks diagnosed with gestational diabetes found no significant effects of a low-GI diet on maternal metabolic profile e.

The low-GI diet consumed during the pregnancy also failed to improve maternal glucose tolerance , insulin sensitivity , and other cardiovascular risk factors, or maternal and infant anthropometric data in a three-month postpartum follow-up study of 55 of the mother-infant pairs At present, there is no evidence that a low-GI diet provides benefits beyond those of a healthy, moderate-GI diet in women at high risk or affected by gestational diabetes.

Obesity is often associated with metabolic disorders, such as hyperglycemia , insulin resistance , dyslipidemia , and hypertension , which place individuals at increased risk for type 2 diabetes mellitus , cardiovascular disease , and early death 56, Lowering the GI of conventional energy-restricted, low-fat diets was proven to be more effective to reduce postpartum body weight and waist and hip circumferences and prevent type 2 diabetes mellitus in women with prior gestational diabetes mellitus Yet, the consumption of a low-GL diet increased HDL - cholesterol and decreased triglyceride concentrations significantly more than the low-fat diet, but LDL -cholesterol concentration was significantly more reduced with the low-fat than low-GI diet Weight loss with each diet was equivalent ~4 kg.

Both interventions similarly reduced triglycerides, C-reactive protein CRP , and fasting insulin , and increased HDL-cholesterol. Yet, the reduction in waist and hip circumferences was greater with the low-fat diet, while blood pressure was significantly more reduced with the low-GL diet Additionally, the low-GI diet improved fasting insulin concentration, β-cell function, and insulin resistance better than the low-fat diet.

None of the diets modulated hunger or satiety or affected biomarkers of endothelial function or inflammation. Finally, no significant differences were observed in low- compared to high-GL diets regarding weight loss and insulin metabolism It has been suggested that the consumption of low-GI foods delayed the return of hunger, decreased subsequent food intake, and increased satiety when compared to high-GI foods The effect of isocaloric low- and high-GI test meals on the activity of brain regions controlling appetite and eating behavior was evaluated in a small randomized , blinded, cross-over study in 12 overweight or obese men During the postprandial period, blood glucose and insulin rose higher after the high-GI meal than after the low-GI meal.

In addition, in response to the excess insulin secretion, blood glucose dropped below fasting concentrations three to five hours after high-GI meal consumption. Cerebral blood flow was significantly higher four hours after ingestion of the high-GI meal compared to a low-GI meal in a specific region of the striatum right nucleus accumbens associated with food intake reward and craving.

If the data suggested that consuming low- rather than high-GI foods may help restrain overeating and protect against weight gain, this has not yet been confirmed in long-term randomized controlled trials. However, the dietary interventions only achieved a modest difference in GI ~5 units between high- and low-GI diets such that the effect of GI in weight maintenance remained unknown.

Table 1 includes GI and GL values of selected foods relative to pure glucose Originally written in by: Jane Higdon, Ph. Linus Pauling Institute Oregon State University.

Updated in December by: Jane Higdon, Ph. Updated in February by: Victoria J. Drake, Ph. Updated in March by: Barbara Delage, Ph. Reviewed in March by: Simin Liu, M. Professor of Epidemiology, Professor of Medicine Brown University.

Liu S, Willett WC. Dietary glycemic load and atherothrombotic risk. Curr Atheroscler Rep. Brouns F, Bjorck I, Frayn KN, et al. Glycaemic index methodology. Nutr Res Rev. Augustin LS, Kendall CW, Jenkins DJ, et al. Glycemic index, glycemic load and glycemic response: An International Scientific Consensus Summit from the International Carbohydrate Quality Consortium ICQC.

Nutr Metab Cardiovasc Dis. Monro JA, Shaw M. Glycemic impact, glycemic glucose equivalents, glycemic index, and glycemic load: definitions, distinctions, and implications.

Am J Clin Nutr. The University of Sydney. About Glycemic Index. The International Organization for Standardization. Food products - Determination of the glycaemic index GI and recommendation for food classification.

Ludwig DS. The glycemic index: physiological mechanisms relating to obesity, diabetes, and cardiovascular disease. Willett WC. Eat, Drink, and be Healthy: The Harvard Medical School Guide to Healthy Eating. Dodd H, Williams S, Brown R, Venn B. Calculating meal glycemic index by using measured and published food values compared with directly measured meal glycemic index.

Silva FM, Kramer CK, Crispim D, Azevedo MJ. A high-glycemic index, low-fiber breakfast affects the postprandial plasma glucose, insulin, and ghrelin responses of patients with type 2 diabetes in a randomized clinical trial. J Nutr. Ranawana V, Leow MK, Henry CJ.

Mastication effects on the glycaemic index: impact on variability and practical implications. Eur J Clin Nutr. Sun L, Ranawana DV, Tan WJ, Quek YC, Henry CJ. The impact of eating methods on eating rate and glycemic response in healthy adults.

Physiol Behav. Venn BS, Williams SM, Mann JI. Comparison of postprandial glycaemia in Asians and Caucasians. Diabet Med.

Wolever TM, Jenkins AL, Vuksan V, Campbell J. The glycaemic index values of foods containing fructose are affected by metabolic differences between subjects. Goff LM, Cowland DE, Hooper L, Frost GS.

Low glycaemic index diets and blood lipids: a systematic review and meta-analysis of randomised controlled trials. Willett W, Manson J, Liu S. Glycemic index, glycemic load, and risk of type 2 diabetes. Gross LS, Li L, Ford ES, Liu S.

Increased consumption of refined carbohydrates and the epidemic of type 2 diabetes in the United States: an ecologic assessment.

Bhupathiraju SN, Tobias DK, Malik VS, et al. Glycemic index, glycemic load, and risk of type 2 diabetes: results from 3 large US cohorts and an updated meta-analysis. Mosdol A, Witte DR, Frost G, Marmot MG, Brunner EJ. Dietary glycemic index and glycemic load are associated with high-density-lipoprotein cholesterol at baseline but not with increased risk of diabetes in the Whitehall II study.

Sahyoun NR, Anderson AL, Tylavsky FA, et al. Dietary glycemic index and glycemic load and the risk of type 2 diabetes in older adults. Sakurai M, Nakamura K, Miura K, et al.

Dietary glycemic index and risk of type 2 diabetes mellitus in middle-aged Japanese men. Sluijs I, Beulens JW, van der Schouw YT, et al. Dietary glycemic index, glycemic load, and digestible carbohydrate intake are not associated with risk of type 2 diabetes in eight European countries.

van Woudenbergh GJ, Kuijsten A, Sijbrands EJ, Hofman A, Witteman JC, Feskens EJ. Glycemic index and glycemic load and their association with C-reactive protein and incident type 2 diabetes.

J Nutr Metab. Villegas R, Liu S, Gao YT, et al. Prospective study of dietary carbohydrates, glycemic index, glycemic load, and incidence of type 2 diabetes mellitus in middle-aged Chinese women.

Arch Intern Med. Greenwood DC, Threapleton DE, Evans CE, et al. Glycemic index, glycemic load, carbohydrates, and type 2 diabetes: systematic review and dose-response meta-analysis of prospective studies.

Diabetes Care. Livesey G, Taylor R, Livesey H, Liu S. Is there a dose-response relation of dietary glycemic load to risk of type 2 diabetes? Meta-analysis of prospective cohort studies. Dyson PA, Kelly T, Deakin T, et al. Diabetes UK evidence-based nutrition guidelines for the prevention and management of diabetes.

Mann JI, De Leeuw I, Hermansen K, et al. Evidence-based nutritional approaches to the treatment and prevention of diabetes mellitus. American Diabetes Association. Prevention or delay of type 2 diabetes. Ma XY, Liu JP, Song ZY.

Glycemic load, glycemic index and risk of cardiovascular diseases: meta-analyses of prospective studies. Dong JY, Zhang YH, Wang P, Qin LQ.

Meta-analysis of dietary glycemic load and glycemic index in relation to risk of coronary heart disease. Am J Cardiol. Fan J, Song Y, Wang Y, Hui R, Zhang W. Dietary glycemic index, glycemic load, and risk of coronary heart disease, stroke, and stroke mortality: a systematic review with meta-analysis.

PLoS One. Mirrahimi A, de Souza RJ, Chiavaroli L, et al. Associations of glycemic index and load with coronary heart disease events: a systematic review and meta-analysis of prospective cohorts. J Am Heart Assoc. Turati F, Dilis V, Rossi M, et al.

Glycemic load and coronary heart disease in a Mediterranean population: the EPIC Greek cohort study. Liu S, Willett WC, Stampfer MJ, et al. A prospective study of dietary glycemic load, carbohydrate intake, and risk of coronary heart disease in US women. Beulens JW, de Bruijne LM, Stolk RP, et al.

High dietary glycemic load and glycemic index increase risk of cardiovascular disease among middle-aged women: a population-based follow-up study. A prospective study of dietary carbohydrate quantity and quality in relation to risk of ovulatory infertility. Eur J Clin Nutr.

Higginbotham S, Zhang ZF, Lee IM, et al. J Natl Cancer Inst. Liu S, Willett WC. Dietary glycemic load and atherothrombotic risk. Curr Atheroscler Rep. Willett W, Manson J, Liu S. Glycemic index, glycemic load, and risk of type 2 diabetes.

Livesey G, Taylor R, Livesey H, Liu S. Is there a dose-response relation of dietary glycemic load to risk of type 2 diabetes? Meta-analysis of prospective cohort studies. Mirrahimi A, de Souza RJ, Chiavaroli L, et al.

Associations of glycemic index and load with coronary heart disease events: a systematic review and meta-analysis of prospective cohorts. J Am Heart Assoc. Foster-Powell K, Holt SH, Brand-Miller JC. International table of glycemic index and glycemic load values: Buyken, AE, Goletzke, J, Joslowski, G, Felbick, A, Cheng, G, Herder, C, Brand-Miller, JC.

Association between carbohydrate quality and inflammatory markers: systematic review of observational and interventional studies.

The American Journal of Clinical Nutrition Am J Clin Nutr. AlEssa H, Bupathiraju S, Malik V, Wedick N, Campos H, Rosner B, Willett W, Hu FB. Carbohydrate quality measured using multiple quality metrics is negatively associated with type 2 diabetes.

The contents of this website are for educational purposes and are not intended to offer personal medical advice. You should seek the advice of your physician or other qualified health provider with any questions you may have regarding a medical condition.

Never disregard professional medical advice or delay in seeking it because of something you have read on this website. The Nutrition Source does not recommend or endorse any products.

Skip to content The Nutrition Source. The Nutrition Source Menu. Search for:. Home Nutrition News What Should I Eat?

As blood sugar levels rise, the pancreas produces insulin, a hormone that prompts cells to absorb blood sugar for energy or storage. As cells absorb blood sugar, levels in the bloodstream begin to fall. When this happens, the pancreas start making glucagon, a hormone that signals the liver to start releasing stored sugar.

This interplay of insulin and glucagon ensure that cells throughout the body, and especially in the brain, have a steady supply of blood sugar. Type 2 diabetes usually develops gradually over a number of years, beginning when muscle and other cells stop responding to insulin.

This condition, known as insulin resistance, causes blood sugar and insulin levels to stay high long after eating. Over time, the heavy demands made on the insulin-making cells wears them out, and insulin production eventually stops. Complex carbohydrates: These carbohydrates have more complex chemical structures, with three or more sugars linked together known as oligosaccharides and polysaccharides.

Low-glycemic foods have a rating of 55 or less, and foods rated are considered high-glycemic foods. Medium-level foods have a glycemic index of Eating many high-glycemic-index foods — which cause powerful spikes in blood sugar — can lead to an increased risk for type 2 diabetes, 2 heart disease, 3 , 4 and overweight, 5 , 6 7.

There is also preliminary work linking high-glycemic diets to age-related macular degeneration, 8 ovulatory infertility, 9 and colorectal cancer. A review of studies researching carbohydrate quality and chronic disease risk showed that low-glycemic-index diets may offer anti-inflammatory benefits.

Carbohydrates and Blood Sugar | The Nutrition Source | Harvard T.H. Chan School of Public Health

Curr Opin Obstet Gynecol ; 14 : — Lee PA, Chernausek SD, Hokken-Koelega AC, et al. International Small for Gestational Age Advisory Board consensus development conference statement: management of short children born small for gestational age, April 24—October 1, Pediatrics ; : — McCowan LM, Pryor J, Harding JE.

Perinatal predictors of neurodevelopmental outcome in small-for-gestational-age children at 18 months. Barker DJP. Fetal and infant origins of adult disease. London, United Kingdom: BMJ Publishing, Chen X, Scholl TO. J Clin Endocrinol Metab ; 87 : —6. Scholl TO, Stein TP, Smith WK.

Leptin and maternal growth during adolescent pregnancy. Am J Clin Nutr ; 72 : —7. Foster-Powell K, Brand-Miller JC. International table of glycemic index. Am J Clin Nutr ; 62 : S —93S. Foster-Powell K, Holt SH, Brand-Miller JC. International table of glycemic index and glycemic load values.

Am J Clin Nutr ; 76 : 5 — Lock DR, Bar-Eyal A, Voet H, et al. Glycemic indices of various foods given to pregnant diabetic subjects.

Obstet Gynecol ; 71 : —3. Wolever TM, Nguyen PM, Chiasson JL, et al. Determinants of diet glycemic index calculated retrospectively from diet records of individuals with non-insulin-dependent diabetes mellitus.

Am J Clin Nutr ; 59 : —9. Perry GS, Byers TE, Mikdad AH, et al. The validity of self-reports of past body weights by U. Epidemiology ; 6 : 61 —6. Casey VA, Dwyer JT, Berkey CS, et al. Long-term memory of body weight and past weight satisfaction: a longitudinal follow-up study.

Am J Clin Nutr ; 53 : —8. Steven-Simon C, McAnarney ER, Coulter MP. How accurately do pregnant adolescents estimate their weight prior to pregnancy? J Adolesc Health Care ; 7 : —4. Butman M, ed. Prenatal nutrition: a clinical manual. Boston, MA: WIC Program, Massachusetts Department of Public Health, Zhang J, Bowes WA.

Birth-weight-for-gestational-age patterns by race, sex and parity in the United States population. Obstet Gynecol ; 86 : —8.

Willett W. Nutritional epidemiology. Oxford, United Kingdom: Oxford University Press, Kleinbaum DG, Kupper LL, Morgenstern H. Epidemiologic research. Belmont, CA: Lifetime Learning Publications, Baumann MU, Deborde S, Illsley NP. Placental glucose transfer and fetal growth.

Endocrine ; 19 : 13 — Wolever TMS, Vorster HH, Bjorck I, et al. Detemination of the glycaemic index of foods: interlaboratory study. Eur J Clin Nutr ; 57 : — Wolever TMS, Mehling C.

Long-term effect of varying the source or amount of dietary carbohydrate on postprandial plasma glucose, insulin, triacylglycerol, and free fatty acid concentrations in subjects with impaired glucose tolerance. Am J Clin Nutr ; 77 : — Clapp JF 3rd.

Effect of dietary carbohydrate on the glucose and insulin response to mixed caloric intake and exercise in both nonpregnant and pregnant women. Diabetes Care ; 21 suppl 2 : B — Willett W, Manson J, Liu S.

Glycemic index, glycemic load, and risk of type 2 diabetes. Am J Clin Nutr ; 76 : S —80S. Wolever TM, Miller JB. Sugars and blood glucose control. Am J Clin Nutr ; 62 suppl 1 : S —21S.

Moore TR. Maternal adaptation to pregnancy. In: Moore TR, Reiter RC, Rebar RW, et al, eds. A longitudinal approach. New York, NY: Churchill Livingstone, — Mathews F, Yudkin P, Neil A.

Influence of maternal nutrition on outcome of pregnancy: prospective cohort study. BMJ ; : — Ludwig D. The glycemic index. Physiological mechanisms relating obesity, diabetes, and cardiovascular disease. JAMA ; : — Svec F, Nastasi K, Hilton C, et al.

Black-white contrasts in insulin concentrations during pubertal development. Diabetes ; 41 : — Radhakrishnamurthy B, Srinivasan SR, Webber LS, et al. Relationship of carbohydrate intolerance to serum lipoprotein profiles in childhood. The Bogalusa Heart Study. Metabolism ; 34 : — Rosetti L, Giaccari A, De Fronzo RA.

Glucose toxicity. Diabetes Care ; 13 : — Lenders CM, Hediger ML, Scholl TO, et al. Effect of high-sugar intake by low-income pregnant adolescents on infant birth weight. J Adolesc Health ; 15 : — Diet, exercise and feto-placental growth. Arch Gynecol Obstet ; : —8. Clapp JF 3rd, Kim H, Burciu B, et al.

Continuing regular exercise during pregnancy: effect of exercise volume in fetoplacental growth. Am J Obstet Gynecol ; : —7. Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide.

Sign In or Create an Account. Navbar Search Filter American Journal of Epidemiology This issue Public Health and Epidemiology Books Journals Oxford Academic Mobile Enter search term Search. Issues More Content Advance articles Editor's Choice years of the AJE Collections Submit Author Guidelines Submission Site Open Access Options Purchase Alerts About About American Journal of Epidemiology About the Johns Hopkins Bloomberg School of Public Health Journals Career Network Editorial Board Advertising and Corporate Services Self-Archiving Policy Dispatch Dates Journals on Oxford Academic Books on Oxford Academic.

Issues More Content Advance articles Editor's Choice years of the AJE Collections Submit Author Guidelines Submission Site Open Access Options Purchase Alerts About About American Journal of Epidemiology About the Johns Hopkins Bloomberg School of Public Health Journals Career Network Editorial Board Advertising and Corporate Services Self-Archiving Policy Dispatch Dates Close Navbar Search Filter American Journal of Epidemiology This issue Public Health and Epidemiology Books Journals Oxford Academic Enter search term Search.

Advanced Search. Search Menu. Article Navigation. Close mobile search navigation Article Navigation. Volume Article Contents Abstract. MATERIALS AND METHODS. Journal Article. The Dietary Glycemic Index during Pregnancy: Influence on Infant Birth Weight, Fetal Growth, and Biomarkers of Carbohydrate Metabolism.

Scholl , Theresa O. Oxford Academic. Google Scholar. Xinhua Chen. Chor San Khoo. Carine Lenders. PDF Split View Views. Cite Cite Theresa O. Select Format Select format. ris Mendeley, Papers, Zotero. enw EndNote. bibtex BibTex. txt Medlars, RefWorks Download citation.

Permissions Icon Permissions. Close Navbar Search Filter American Journal of Epidemiology This issue Public Health and Epidemiology Books Journals Oxford Academic Enter search term Search.

Abstract During pregnancy, lower levels of maternal glucose before and during a glucose load have been associated with reduced infant birth weight and an increased risk of small-for-gestational-age births. birth weight; diet; glycemic index; hemoglobin A, glycosylated; infant, small for gestational age.

Abbreviation: OR, odds ratio. For instance, watermelon has a high GI, but a typical serving of watermelon does not contain many carbohydrates, so the glycemic load of eating it is low. Whereas glycemic index is defined for each type of food, glycemic load can be calculated for any size serving of a food, an entire meal, or an entire day's meals.

Glycemic load of a g serving of food can be calculated as its carbohydrate content measured in grams g , multiplied by the food's GI, and divided by For example, watermelon has a GI of A food with a GI of 90 and 8 g of available carbohydrates has a GL of 7. For one serving of a food, a GL greater than 20 is considered high, a GL of 11—19 is considered medium, and a GL of 10 or less is considered low.

Foods that have a low GL in a typical serving size almost always have a low GI. Foods with an intermediate or high GL in a typical serving size range from a very low to very high GI. One study has questioned the value of using glycemic load as a basis for weight-loss programmes.

Das et al. conducted a study on 36 healthy, overweight adults, using a randomised test to measure the efficacy of two diets, one with a high glycemic load and one with a low GL.

The study concluded that there is no statistically significant difference between the outcome of the two diets. Glycemic load appears to be a significant factor in dietary programs targeting metabolic syndrome, insulin resistance , and weight loss; studies have shown that sustained spikes in blood sugar and insulin levels may lead to increased diabetes risk.

The data on GI and GL listed in this article is from the University of Sydney Human Nutrition Unit GI database.

The GI was invented in by Dr Thomas Wolever and Dr David Jenkins at the University of Toronto and is a measure of how quickly a food containing 25 or 50 g of carbohydrate raises blood-glucose levels. Because some foods typically have a low carbohydrate content, Harvard researchers created the GL, which takes into account the amount of carbohydrates in a given serving of a food and so provides a more useful measure.

Liu et al. were the first to show that based on their calculation, the glycemic load of a specific food—calculated as the product of that food's carbohydrate content and its glycemic index value—has direct physiologic meaning in that each unit can be interpreted as the equivalent of 1 g carbohydrate from white bread or glucose depending on the reference used in determining the glycemic index.

Contents move to sidebar hide. Article Talk. Read Edit View history. Tools Tools. What links here Related changes Upload file Special pages Permanent link Page information Cite this page Get shortened URL Download QR code Wikidata item. Download as PDF Printable version. Results for dietary patterns were not eligible if they did not quantify intake.

Gestational diabetes outcomes were not eligible. Study selection was carried out by two researchers from D. For inclusion in dose—response meta-analysis, only studies publishing estimates of RR with associated CIs, alongside a quantified measure of intake, and sufficient detail regarding the numbers of cases and noncases or person-years exposure could be included.

Data extraction was carried out by D. and D. This method estimates study-specific dose—response slopes and associated CIs based on the results presented for each category of GI, GL, or total dietary carbohydrate intake before combining into a pooled estimate.

To derive the dose—response trend, we used the mean or median exposure for each category if this was presented and used the midpoint when exposure ranges were presented instead.

When the lowest or highest categories were unbounded, we assumed the width of the category to be the same as the adjacent category when estimating the midpoint. Where the total number of cases or person-years was presented in the publication, but not the distribution, we estimated this based on definitions of the quantiles.

The estimated exposure level based on median, mean, or midpoint was then assigned to the corresponding RR for each study. For studies presenting the exposure per given unit of energy intake, we rescaled this using estimated energy intake for each category if this was presented. For the studies already reporting a linear dose—response trend, with a measure of precision such as a CI or a standard error, this was used directly.

Where results were only presented separately for men and women, these were first combined using a fixed effects meta-analysis before combining with other studies.

This ensured that between-study heterogeneity was not underestimated. All the estimated dose—response trends for each study were then pooled using a random-effects model to take into account anticipated between-study heterogeneity In presenting the linear dose—response trend, we chose an increment size approximately equivalent to one standard deviation in a European or U.

population, to ease comparison across exposures. Four studies only presented results for a linear trend over a continuous exposure 8 , 10 , 23 , 24 , and two studies only presented results for three categories 25 , 26 , so these could not be included in nonlinear dose—response analyses.

We assessed between-study heterogeneity using Cochran Q test and the percentage of total variation in study estimates attributable to between-study heterogeneity I 2 Rather than assess study quality using a quality score, to minimize bias from confounding, we excluded results with no adjustment for any confounding or where only unadjusted dose—response trends could only be estimated.

We also tabulated the following markers of risk of bias: adequacy of the dietary assessment tool, objectivity of ascertainment of the outcome, adequacy of length of follow-up, adequacy of control for confounding, and potential competing interests. In addition, we investigated the extent to which specific study characteristics defined in advance were associated with different higher or lower estimates or how they potentially explained some of the heterogeneity.

These characteristics included duration of follow-up and adjustment for prespecified confounders, which are potential indicators of study quality. Potential small study effects, such as publication bias, were investigated with contour-enhanced funnel plots.

However, with small numbers of included studies, exploration of sources of heterogeneity and of small study affects lack power. All analyses were conducted using Stata version 12 We identified 24 publications from 21 cohort studies that reported GI, GL, total or carbohydrate intake, and incidence of type 2 diabetes Supplementary Fig.

One publication could not be used in meta-analyses because it did not quantify intake 7 , one could not be used because it only presented results for the highest and lowest categories 29 , and one could not be used because of the form the results were presented in The remaining 18 cohorts provided sufficient information for inclusion in dose—response meta-analyses Supplementary Table 2.

The risk of bias assessment is provided in Supplementary Table 3. Nine studies were from the U. One cohort presented results in three publications 4 , 31 , 32 , so we used the data in the most recent publication A further study reported GI and load in a separate paper from total carbohydrate intake 11 , For one study to be included, we estimated standard errors using the reported P value and estimates For another to be included, category means were estimated based on an assumed normal distribution, with approximate mean and standard deviation derived from the publication The exclusion of studies reporting unadjusted estimates had resulted in the loss of two studies presenting results for total carbohydrate intake that would otherwise have been included 35 , Data were extracted from 15 publications investigating the association between GI and type 2 diabetes 5 , 6 , 8 — 11 , 23 — 26 , 32 , 37 — 40 Fig.

The estimated category mean intakes ranged from approximately 45 to 90 units of GI, with individual studies spanning between 6 and 36 units. The pooled estimate of RR from linear dose—response meta-analysis was 1.

GI, GL, total carbohydrate intake, and estimated RR of type 2 diabetes. A—C : Forest plots of linear dose—response trends with pooled estimates from random-effects meta-analysis. Increments used are approximately one standard deviation.

D—F : Summary nonlinear dose—response curves. The median intake is used as the reference category. Tick marks on the horizontal axis indicate the location of category medians, means, or midpoints for included studies.

The stronger association between GI and diabetes was restricted to those studies that adjusted for this, leading to improved heterogeneity within each subgroup Supplementary Table 4.

Estimates were largely consistent across the other predefined subgroups. The funnel plot was approximately symmetric, with little evidence of small-study effects such as publication bias data not shown. Nonlinear dose—response meta-analysis showed a consistently increasing risk associated with increased GI Fig.

There was little evidence of a threshold effect in the plot. Data were extracted from 16 publications investigating the association between GL and type 2 diabetes 5 , 6 , 8 — 11 , 23 , 25 , 26 , 32 , 34 , 37 — 41 Fig.

The estimated category mean intakes ranged from approximately 55 to units of GL, with individual studies spanning between 48 and units.

Stratifying by family history improved heterogeneity within each subgroup Supplementary Table 4. Nonlinear dose—response meta-analysis showed a consistently increasing risk associated with increased GL Fig.

Data were extracted from eight studies investigating total carbohydrate intake and type 2 diabetes 5 , 8 , 9 , 23 , 24 , 32 , 33 , 42 Fig. The estimated category mean intakes ranged from approximately to g, with individual studies spanning between 72 and g. The pooled estimate of RR from linear dose—response meta-analysis was 0.

Estimates were largely consistent across predefined subgroups, though there was a tendency for studies with longer follow-up to have larger estimates Supplementary Table 4. Nonlinear dose—response meta-analysis showed a relatively flat curve over a broad range of typical intakes, with a suggestion of lower risks associated with higher intakes where data are more sparse and CIs wider Fig.

We have quantified a clear positive association between both GI and GL with increasing incidence of type 2 diabetes. The association was stronger for GI than GL, with approximately one standard deviation of GI intake associated with more than twice the increased risk associated with GL. Compared with the data on dietary GI, the evidence base for GL is more inconsistent in terms of direction of association.

Despite use of linear dose—response trends to combine studies using different exposure categorizations, heterogeneity was still high for all exposures. Exploration of this heterogeneity by investigating the estimates in different predefined subgroups suggested that adjustment for family history of diabetes was potentially important, with studies that did not adjust for it having much lower estimates for the association between GI, GL, and type 2 diabetes.

While these findings are consistent with those of two previous systematic reviews 13 , 14 , our review is the first to quantify the strength of the association, the first to explore some of the heterogeneity in results, the first to remove some of this heterogeneity by combining dose—response trends, and the first to investigate possible nonlinear associations.

We have included results from nine publications from large prospective studies that have been published since the most recent review, and these include almost 20, more cases of type 2 diabetes from over , more participants, further strengthening the evidence on which our conclusions are based.

Meta-analysis of observational studies is susceptible to the same biases that the studies they contain are prone to, so the pooled estimate may still contain an element of bias to the extent that the studies reviewed are biased.

In particular, all the studies reviewed used some form of self-reported dietary exposure and were therefore susceptible to potentially large measurement error.

In addition, many adjusted for self-reported dietary covariates so may not have fully adjusted for true intake. This could bias the associations in either direction. Furthermore, we cannot conclusively prove that any associations are causal on the basis of observational studies alone, and there may be some uncorrected confounding in some or all of the studies.

However, the estimates we have found for GI and GL are strong with clear dose—response trends, and there was no evidence of any small-study effects such as publication bias. Typically, GI values for each food item in a questionnaire were taken from the international table of GI values of foods Broad groupings of foods within each FFQ item sometimes necessitates the allocation of an average GI for that item, and this has led some to express concerns about the appropriateness of using FFQ-derived GI and GL values to explore disease associations The dietary GI of a food is subject to considerable variation dependent upon the extent of processing, cooking method and duration, extent of starch gelatinization, ripeness, and storage duration Further issues concern whether foods consumed together impact on each other to alter the GI of the whole meal This exposure is therefore potentially prone to measurement error bias.

The estimation of GL requires the additional estimate of the amount of carbohydrate in the diet, providing greater scope for dilution of results through measurement error bias.

Even though the estimated absolute values of GI and GL are probably not accurate estimates of actual values in many studies, we have still used them so that the different studies can be combined on the same scale and dose—response trends and nonlinear trends can be estimated.

However, in interpreting these, the emphasis should be on the relative ranking as much as on the estimated GI and GL. A wide range of exposures were reported across the publications, though the intakes reported by individual studies generally varied by smaller amounts.

[The role of glycemic index concept in carbohydrate metabolism] Diabetes Care ; 21 suppl 2 : B — A small-for-gestational-age fetus was defined by birth weight for gestation below the 10th percentile of the same standard. New diabetes nutrition therapy recommendations: what you need to know. Opting for minimally processed foods like colorful non-starchy vegetables , lean proteins, and healthy fats, is better for your blood sugar and metabolism. Silva FM, Kramer CK, Crispim D, Azevedo MJ. For the present study, we used the NHNS subsample of adolescents aged 12—19 years evaluated by means of a validated semiquantitative food-frequency questionnaire SFFQ to assess dietary habits [ 23 ]. Processed foods Sticking to whole, unprocessed foods is another way to minimize a glycemic response.
Difference Between Glycemic Index and Glycemic Load Use limited Carbohyddrate to select advertising. However, clinical metbolism have been conducted in specific population groups: Carbohydrate metabolism and glycemic load fact—along Carbohysrate dietary intervention—could explain the differences from our results. The time wakefulness and aging takes for a Carbohydrate metabolism and glycemic load to be absorbed is measured on a scale from 0 to Effect of breakfast glycemic index on metabolic responses during rest and exercise in overweight and non-overweight adolescent girls. Eating high-GI foods or low-GI foods in large portions occasionally is OK, as the body can respond to large amounts of sugar periodically. Authoring Open access Purchasing Institutional account management Rights and permissions. Svec F, Nastasi K, Hilton C, et al.
Actions for this page

Liu S, Willett WC. Dietary glycemic load and atherothrombotic risk. Curr Atheroscler Rep. Brouns F, Bjorck I, Frayn KN, et al. Glycaemic index methodology. Nutr Res Rev. Augustin LS, Kendall CW, Jenkins DJ, et al.

Glycemic index, glycemic load and glycemic response: An International Scientific Consensus Summit from the International Carbohydrate Quality Consortium ICQC. Nutr Metab Cardiovasc Dis. Monro JA, Shaw M. Glycemic impact, glycemic glucose equivalents, glycemic index, and glycemic load: definitions, distinctions, and implications.

Am J Clin Nutr. The University of Sydney. About Glycemic Index. The International Organization for Standardization. Food products - Determination of the glycaemic index GI and recommendation for food classification.

Ludwig DS. The glycemic index: physiological mechanisms relating to obesity, diabetes, and cardiovascular disease. Willett WC. Eat, Drink, and be Healthy: The Harvard Medical School Guide to Healthy Eating. Dodd H, Williams S, Brown R, Venn B. Calculating meal glycemic index by using measured and published food values compared with directly measured meal glycemic index.

Silva FM, Kramer CK, Crispim D, Azevedo MJ. A high-glycemic index, low-fiber breakfast affects the postprandial plasma glucose, insulin, and ghrelin responses of patients with type 2 diabetes in a randomized clinical trial.

J Nutr. Ranawana V, Leow MK, Henry CJ. Mastication effects on the glycaemic index: impact on variability and practical implications. Eur J Clin Nutr. Sun L, Ranawana DV, Tan WJ, Quek YC, Henry CJ. The impact of eating methods on eating rate and glycemic response in healthy adults.

Physiol Behav. Venn BS, Williams SM, Mann JI. Comparison of postprandial glycaemia in Asians and Caucasians. Diabet Med. Wolever TM, Jenkins AL, Vuksan V, Campbell J. The glycaemic index values of foods containing fructose are affected by metabolic differences between subjects. Goff LM, Cowland DE, Hooper L, Frost GS.

Low glycaemic index diets and blood lipids: a systematic review and meta-analysis of randomised controlled trials. Willett W, Manson J, Liu S. Glycemic index, glycemic load, and risk of type 2 diabetes. Gross LS, Li L, Ford ES, Liu S. Increased consumption of refined carbohydrates and the epidemic of type 2 diabetes in the United States: an ecologic assessment.

Bhupathiraju SN, Tobias DK, Malik VS, et al. Glycemic index, glycemic load, and risk of type 2 diabetes: results from 3 large US cohorts and an updated meta-analysis. Mosdol A, Witte DR, Frost G, Marmot MG, Brunner EJ. Dietary glycemic index and glycemic load are associated with high-density-lipoprotein cholesterol at baseline but not with increased risk of diabetes in the Whitehall II study.

Sahyoun NR, Anderson AL, Tylavsky FA, et al. Dietary glycemic index and glycemic load and the risk of type 2 diabetes in older adults. Sakurai M, Nakamura K, Miura K, et al. Dietary glycemic index and risk of type 2 diabetes mellitus in middle-aged Japanese men. Sluijs I, Beulens JW, van der Schouw YT, et al.

Dietary glycemic index, glycemic load, and digestible carbohydrate intake are not associated with risk of type 2 diabetes in eight European countries. van Woudenbergh GJ, Kuijsten A, Sijbrands EJ, Hofman A, Witteman JC, Feskens EJ. Glycemic index and glycemic load and their association with C-reactive protein and incident type 2 diabetes.

J Nutr Metab. Villegas R, Liu S, Gao YT, et al. Prospective study of dietary carbohydrates, glycemic index, glycemic load, and incidence of type 2 diabetes mellitus in middle-aged Chinese women.

Arch Intern Med. Greenwood DC, Threapleton DE, Evans CE, et al. Glycemic index, glycemic load, carbohydrates, and type 2 diabetes: systematic review and dose-response meta-analysis of prospective studies. Diabetes Care. Livesey G, Taylor R, Livesey H, Liu S. Is there a dose-response relation of dietary glycemic load to risk of type 2 diabetes?

Meta-analysis of prospective cohort studies. Dyson PA, Kelly T, Deakin T, et al. Diabetes UK evidence-based nutrition guidelines for the prevention and management of diabetes. Mann JI, De Leeuw I, Hermansen K, et al.

Evidence-based nutritional approaches to the treatment and prevention of diabetes mellitus. American Diabetes Association. Prevention or delay of type 2 diabetes. Ma XY, Liu JP, Song ZY. Glycemic load, glycemic index and risk of cardiovascular diseases: meta-analyses of prospective studies.

Dong JY, Zhang YH, Wang P, Qin LQ. Meta-analysis of dietary glycemic load and glycemic index in relation to risk of coronary heart disease.

Am J Cardiol. Fan J, Song Y, Wang Y, Hui R, Zhang W. Dietary glycemic index, glycemic load, and risk of coronary heart disease, stroke, and stroke mortality: a systematic review with meta-analysis.

PLoS One. Mirrahimi A, de Souza RJ, Chiavaroli L, et al. Associations of glycemic index and load with coronary heart disease events: a systematic review and meta-analysis of prospective cohorts. J Am Heart Assoc. Turati F, Dilis V, Rossi M, et al. Glycemic load and coronary heart disease in a Mediterranean population: the EPIC Greek cohort study.

Liu S, Willett WC, Stampfer MJ, et al. A prospective study of dietary glycemic load, carbohydrate intake, and risk of coronary heart disease in US women. Beulens JW, de Bruijne LM, Stolk RP, et al.

High dietary glycemic load and glycemic index increase risk of cardiovascular disease among middle-aged women: a population-based follow-up study. J Am Coll Cardiol. Cai X, Wang C, Wang S, et al. Carbohydrate intake, glycemic index, glycemic load, and stroke: a meta-analysis of prospective cohort studies.

Asia Pac J Public Health. Rossi M, Turati F, Lagiou P, Trichopoulos D, La Vecchia C, Trichopoulou A. Relation of dietary glycemic load with ischemic and hemorrhagic stroke: a cohort study in Greece and a meta-analysis.

Eur J Nutr. Buscemi S, Cosentino L, Rosafio G, et al. Effects of hypocaloric diets with different glycemic indexes on endothelial function and glycemic variability in overweight and in obese adult patients at increased cardiovascular risk. Clin Nutr. Bullo M, Casas R, Portillo MP, et al.

The American Journal of Clinical Nutrition Am J Clin Nutr. AlEssa H, Bupathiraju S, Malik V, Wedick N, Campos H, Rosner B, Willett W, Hu FB. Carbohydrate quality measured using multiple quality metrics is negatively associated with type 2 diabetes.

The contents of this website are for educational purposes and are not intended to offer personal medical advice. You should seek the advice of your physician or other qualified health provider with any questions you may have regarding a medical condition.

Never disregard professional medical advice or delay in seeking it because of something you have read on this website. The Nutrition Source does not recommend or endorse any products.

Skip to content The Nutrition Source. The Nutrition Source Menu. Search for:. Home Nutrition News What Should I Eat? As blood sugar levels rise, the pancreas produces insulin, a hormone that prompts cells to absorb blood sugar for energy or storage. As cells absorb blood sugar, levels in the bloodstream begin to fall.

When this happens, the pancreas start making glucagon, a hormone that signals the liver to start releasing stored sugar. This interplay of insulin and glucagon ensure that cells throughout the body, and especially in the brain, have a steady supply of blood sugar.

Type 2 diabetes usually develops gradually over a number of years, beginning when muscle and other cells stop responding to insulin. This condition, known as insulin resistance, causes blood sugar and insulin levels to stay high long after eating.

Over time, the heavy demands made on the insulin-making cells wears them out, and insulin production eventually stops. Complex carbohydrates: These carbohydrates have more complex chemical structures, with three or more sugars linked together known as oligosaccharides and polysaccharides.

Low-glycemic foods have a rating of 55 or less, and foods rated are considered high-glycemic foods. Medium-level foods have a glycemic index of Eating many high-glycemic-index foods — which cause powerful spikes in blood sugar — can lead to an increased risk for type 2 diabetes, 2 heart disease, 3 , 4 and overweight, 5 , 6 7.

There is also preliminary work linking high-glycemic diets to age-related macular degeneration, 8 ovulatory infertility, 9 and colorectal cancer. A review of studies researching carbohydrate quality and chronic disease risk showed that low-glycemic-index diets may offer anti-inflammatory benefits.

Physical form : Finely ground grain is more rapidly digested than coarsely ground grain. Fat content and acid content : Meals with fat or acid are converted more slowly into sugar.

References 2. Terms of Use The contents of this website are for educational purposes and are not intended to offer personal medical advice.

The dietary glycemic index value based upon each of the three recalls was then averaged to give a mean value for each gravida over the course of her pregnancy.

As a corollary, another measure derived from the dietary glycemic index, the glycemic load, was also calculated This involved multiplying the food glycemic index by the carbohydrate content, summing the values over all foods, and then averaging over all recalls as described above.

Pregravid weight was determined by recall at entry to prenatal care, and weight was measured at each visit using a beam balance scale. Height was measured at entry to prenatal care using a stadiometer. The total gestational weight gain was calculated as the difference between the reported pregravid weight and the weight measured within 2 weeks before delivery; the rate of gestational weight gain was computed from the total weight gain and the duration of gestation.

The adequacy of gestational weight gain was also defined to within 2 completed weeks of delivery using published criteria that adjust weight gain for the duration of gestation A large-for-gestational-age fetus was defined by a birth weight for gestation above the 90th percentile of the standard described by Zhang and Bowes 32 , which adjusts for maternal parity, ethnicity, and fetal sex.

A small-for-gestational-age fetus was defined by birth weight for gestation below the 10th percentile of the same standard.

Maternal plasma glucose and red cells for glycosylated hemoglobin were obtained by venipuncture between 24—28 weeks of gestation. Plasma glucose levels were measured 1 hour after a g glucose-screening test to detect gestational diabetes, routinely conducted in Camden gravidas.

A total of 92 percent of the women provided a fasting sample, but fasting is not a requirement for either the glucose-screening test or the glycosylated hemoglobin.

Samples were stored at —70°C until assayed. Glucose was measured with the glucose oxidase method Sigma Diagnostics, St. Louis, Missouri and with glycosylated hemoglobin by turbidimetric immune inhibition Boehringer Mannheim, Indianapolis, Indiana.

The coefficient of variation within and between assays was less than 5 percent for each method. Linear regression was used to generate a dietary glycemic index adjusted for energy intake Dietary residuals from these regressions were further categorized into quintiles.

The significance of the linear trend was assessed across categories quintiles of the glycemic index using analysis of variance with 1 df. The chi-square statistic or overall F statistic from the analysis of variance was used to assess the relation between glycemic index quintiles and maternal background characteristics.

Potential confounding variables traditionally associated with infant birth weight or risk of small-for-gestational-age births e. Separate models were fit for infant birth weight and each pregnancy outcome or bio-marker of carbohydrate metabolism using multiple logistic regression or multiple linear regression.

In models of birth weight and pregnancy outcome, the highest quintile of the dietary glycemic index was compared with quintiles 1—4, and the lowest quintile of the dietary glycemic index was compared with quintiles 2—5.

Confounding was assessed by comparing crude and adjusted odds ratios or regression coefficients. Adjusted odds ratios and their 95 percent confidence intervals were computed from the logistic regression coefficients and their corresponding covariance matrices For the biomarkers of carbohydrate metabolism, we used the regression coefficients and the mean dietary glycemic index values from the highest quintile mean, We also expressed this difference as the percentage of change by dividing it by the mean concentration of the biomarker.

Little association was found between quintiles of the dietary glycemic index and variables such as maternal pregravid body mass index and the adequacy or rate of gestational weight gain. Women in the lower quintiles of the dietary glycemic index tended to be somewhat older and were slightly more likely to be nulliparous and less likely to smoke heavily table 1.

There was an overall ethnic difference in the dietary glycemic index for the group. Energy intake was somewhat lower for women in both the highest and lowest dietary glycemic index quintiles table 2.

With adjustment for energy, the dietary glycemic index was associated with other aspects of the maternal diet. There were significant trends for gravidas in the lower quintiles of the glycemic index to eat diets richer in carbohydrate, fiber, sucrose, and folate but lower in fat table 2.

Controlling for maternal ethnicity and other potential confounding variables, we found that the dietary glycemic index was positively related to biomarkers of maternal carbohydrate metabolism during the third trimester table 3. These measures included levels of glycosylated hemoglobin mean, 5.

Both of these biomarkers increased with every unit increase in the dietary glycemic index. Using coefficients from the regression equations, we calculated expected levels of plasma glucose and glycosylated hemoglobin for gravidas in the lowest and highest quintiles of the dietary glycemic index.

The computations suggested a lower level of plasma glucose —4. Like plasma glucose, the dietary glycemic index influenced fetal growth table 4. After adjustment for the duration of gestation, a dietary glycemic index in the lowest quintile was associated with lower infant birth weight, a reduction of more than g.

After including other potential confounding variables along with gestational duration, we found that the birth weight difference increased to — g. Unlike with the low dietary glycemic index, there was no association between a diet that placed the mother in the highest quintile of the dietary glycemic index and the birth weight of her infant.

Like the relation between plasma glucose and fetal growth, women with a dietary glycemic index in the lowest quintile had approximately a twofold increased risk of bearing a growth-restricted infant table 5. This risk was not greatly altered by inclusion of other potential confounding variables maternal age, cigarettes smoked per day, prior history of low birth weight in the model.

We repeated the analyses utilizing the energy-adjusted glycemic load in lieu of the dietary glycemic index. From these data, we estimated a small difference in glycosylated hemoglobin between the highest and lowest quintiles of the glycemic load —0. Glucose, the major substrate for fetal growth, is transported across the placenta in proportion to its concentration in the maternal circulation and according to the rate of placental red blood flow.

Gluconeogenesis is virtually absent in the fetus so that the fetus obtains its glucose almost entirely from circulating levels in the mother Maternal glucose and other metabolic fuels thus provide the energy for fetal growth and facilitate the passage of nutrients from mother to fetus 1 — 4.

Circulating levels of glucose are produced by maternal metabolism from endogenous sources and also from the diet, principally from carbohydrate. Not all carbohydrates raise blood glucose levels to the same extent. The glycemic response to carbohydrate depends upon the type that is consumed.

The glycemic index is a qualitative measure that classifies the type of carbohydrate according to the metabolic response that it elicits. The reference food used by researchers to determine tabled values for the food glycemic index is white bread or glucose 11 , White bread represents a more physiologic meal than glucose, although neither is the primary source of carbohydrate in populations that have been studied In addition, the glycemic index for a food may also be influenced by the method of processing and preparation, its fat, protein, and fiber content, as well as other factors.

Carbohydrates with a higher glycemic index are absorbed quickly and can raise blood glucose concentrations rapidly, whereas carbohydrates with a lower glycemic index break down more steadily and have a gradual glucose rise Consistent with this expectation, our data showed a positive relation between the maternal dietary glycemic index and biomarkers of maternal carbohydrate metabolism during pregnancy, including glycosylated hemoglobin, a measure of average plasma glucose over the past 2—3 months, and an acute measure, third trimester postload plasma glucose.

Calculations from these data suggested that plasma glucose was about 4 percent lower and that glycosylated hemoglobin HbA1c was about 2 percent lower comparing the lowest and highest dietary glycemic index quintiles. Among patients with impaired glucose tolerance, diets with a lower dietary glycemic index lowered postprandial glucose levels by about 4 percent Pregnant women on the aboriginal diet had lower glucose areas 3 hours after a mixed meal and a lower insulin response with advancing gestation than gravidas on the cafeteria diet Data from studies on the management of type 1 or type 2 diabetes that have been incorporated into a recent review of the glycemic index suggested that glycolysated hemoglobin or fructosamine fell by about 10 percent on average with a low glycemic index diet Salmeron et al.

In the present study of pregnant women, the glycemic load had a weaker relation with glycosylated hemoglobin computed as 0. The relation between the glycemic load and the glucose response depends upon the amount of carbohydrate as well as on the type.

The diets of Camden gravidas are rich in sugar, and approximately 50 percent of the carbohydrate that they eat comes from sugar table 2. However, simple sugars, including sucrose, have a lower glycemic index and elicit a lower blood glucose response than white bread and other starchy foods It is also possible that the slowed gastric emptying and colonic transit that characterize pregnancy 41 have altered the relation among the glycemic load, maternal glucose levels, and fetal growth.

Although one small study in diabetic gravidas suggested that pregnancy did not change the glycemic index of the eight foods that were tested, it did not examine the effects of the glycemic load on blood glucose Our observations are the first from a larger-scale observational study to report an increased risk of fetal growth restriction in association with a low maternal dietary glycemic index.

This finding supports the hypothesis that reduced fetal growth is associated with the maternal diet during pregnancy. As we observed during pregnancy and as others have observed in the nonpregnant state 12 , 43 , a low dietary glycemic index diet is associated with lower concentrations of glucose, and a high dietary glycemic index is associated with higher concentrations of plasma glucose.

Consistent with our findings on maternal plasma glucose, those of Scholl et al. However, we did not observe that gravidas eating a diet with a high dietary glycemic index had concomitant increases in birth weight and other measures of fetal growth, such as a large-for-gestational-age birth.

The influence of maternal plasma glucose on excessive fetal growth has been described in women with diabetes 4 , 7. High circulating concentrations of maternal glucose are associated with increased transport of glucose and other nutrients to the fetus.

Fetal insulin secretion is stimulated in order to prevent fetal hyperglycemia. Fetal insulin increases the storage of glucose and other nutrients and also acts as a growth factor for the fetus.

With increases in the supply of nutrients and the production of growth factors, the intrauterine growth rate is higher and the infant birth weight greater 4 , 7. Although high dietary glycemic index diets have been reported to raise postprandial glucose and insulin 12 , 43 , it seems plausible that young women who are not diabetic should secrete a sufficient amount of insulin to maintain blood glucose levels in the normal range.

Thus, there would be little extra maternal glucose for increased fetal growth. Some studies have suggested that a high dietary glycemic index may increase the risk of type 2 diabetes and other chronic diseases in later life 15 — We observed ethnic differences in the glycemic index and found that African Americans were more likely to eat a high dietary glycemic index diet than were other gravidas.

We and others have reported higher insulin and lower glucose concentrations among African-American girls and young women, pregnant and nonpregnant alike 22 , 44 , Ethnic differences in insulin and glucose could reflect the influence of a higher dietary glycemic index. Regular consumption of a high glycemic index diet is thought to initiate a cycle of hyperinsulinemia acute insulin resistance followed by increases in counter regulatory hormones, the release of free fatty acids and, as observed in many studies of African Americans, lower postprandial glucose concentrations.

During pregnancy, the lower postload levels of glucose in African-American gravidas are associated with 5—7 percent of the difference in fetal growth and infant birth weight between African Americans and Whites A cycle of high blood glucose and insulin followed by episodes of reactive hypoglycemia and increased insulin resistance may eventually boost the demand for the beta cells to secrete more insulin, augment insulin resistance, impair beta-cell function, and increase risk of type 2 diabetes and other chronic diseases 39 , 43 , The observations from the present study are also consistent with those from an earlier report from Camden on adolescent pregnancy In that study, Lenders et al.

As Wolever et al. Sucrose table sugar has a glycemic index below those of white bread, rice, potatoes, and most breakfast cereals, and simple sugars such as those in milk products and fruit juices have a glycemic index below that of sucrose 24 , Consumption of a sugar-rich diet would by definition result in a lower dietary glycemic index with lower levels of maternal blood glucose 40 available for transmission to the fetus.

The effect of the dietary glycemic index on carbohydrate metabolism and fetal growth, however, is difficult to disentangle from the effect of regular exercise on the same outcomes Unlike Clapp, we found no influence of the dietary glycemic index on the maternal pregravid body mass index, rate of weight gain, or adequacy of weight gain during pregnancy in either the present study table 1 or our prior work on sugar-rich diets In summary, we found that the dietary glycemic index, a measure of the type of carbohydrate in the maternal diet, influences the outcome of pregnancy and has utility for predicting the maternal metabolic response during pregnancy.

Our results suggest that we should examine the diets of pregnant women to see if increasing the dietary glycemic index reduces the risk of small-for-gestational-age birth.

Conversely, a lower dietary glycemic index diet might also help to raise postprandial glucose levels among African Americans. In this ethnic group, lower concentrations of maternal plasma glucose possibly a reactive hypoglycemia in response to a high dietary glycemic index have been associated with lower infant birth weight.

This research was supported by grants HD and HD from the National Institutes of Health. The authors are indebted to the staffs at the Osborn Family Health Center, Our Lady of Lourdes Hospital, and St. John the Baptist Prenatal Care Center in Camden for access to patients.

Special thanks to Joan Murray for expert assistance with the nutrient and glycemic index databases, SaTonya Jones for laboratory assays, and Deborah Cruz for manuscript preparation. Correspondence to Dr. Scholl, Department of Obstetrics and Gynecology, The University of Medicine and Dentistry of New Jersey-SOM, Two Medical Center Drive, Science Center, Suite , Stratford, NJ e-mail: scholl umdnj.

Maternal background characteristics and the dietary glycemic index of gravidas who enrolled in the Camden Study between August and October Mean intake of energy and energy-adjusted macronutrients, fiber, and selected micronutrients by quintile of the dietary glycemic index in gravidas who enrolled in the Camden Study between August and October Relation between the dietary glycemic index and markers of maternal carbohydrate metabolism in gravidas who enrolled in the Camden Study between August and October Influence of the dietary glycemic index on infant birth weight in gravidas who enrolled in the Camden Study between August and October Herrera E.

Metabolic adaptations in pregnancy and their implications for the availability of substrates to the fetus. Eur J Clin Nutr ; 54 suppl 1 : S47 — Knopp RH. Hormone-mediated changes in nutrient metabolism in pregnancy: a physiological basis for normal fetal development.

Ann N Y Acad Sci ; : — Boden G. Fuel metabolism in pregnancy and in gestational diabetes mellitus. Obstet Gynecol Clin North Am ; 23 : 1 — Pedersen J. Weight and length at birth of infants of diabetic mothers. Acta Endocrinol ; 16 : — Sermer M, Naylor D, Gare DJ, et al. Impact of increasing carbohydrate intolerance on maternal-fetal outcomes in women without gestational diabetes.

Am J Obstet Gynecol ; : — Farmer G, Russell G, Hamilton-Nicol DR, et al. The influence of maternal glucose metabolism on fetal growth, development and morbidity in singleton pregnancies in nondiabetic women.

Diabetologia ; 31 : — Jovanovic-Peterson L, Peterson CM, Reed GF, et al.

Carbohydrate metabolism and glycemic load -

A healthy diet is considered one of the pillars of cardiovascular disease prevention. Multiple specialty groups provide nutrition recommendations in cardiovascular disease prevention guidelines. Carbohydrates are one of the major classes of nutrients and include sugars, starches, and fibers.

High-fiber and whole-grain foods are considered beneficial for cardiovascular disease prevention. Carbohydrates that cause a spike in blood glucose, like sugar-sweetened beverages, have a high glycemic index compared with those that lead to a less pronounced rise in glucose, such as legumes.

While glycemic index does not account for the amount of carbohydrate intake, glycemic load is the product of glycemic index and total available carbohydrate content in a given amount of food.

Glycemic Index, Glycemic Load, and Cardiovascular Disease Randomized clinical trials of low glycemic index and low glycemic load interventions demonstrated improvements in cardiometabolic factors. In a recent analysis, Jenkins, et al. examined the association of glycemic index and glycemic load with risk of cardiovascular disease among adults enrolled in the Prospective Urban Rural Epidemiology PURE study.

The glycemic index was estimated for participants based on country-specific diet questionnaires and glycemic index values for multiple carbohydrate categories. Glycemic load was determined based on the glycemic index and total carbohydrate intake.

The primary composite outcome was all-cause death or a cardiovascular disease event, including cardiovascular death, nonfatal myocardial infarction, stroke, or heart failure. The dietary patterns of , participants across five continents from the PURE study varied widely with the highest glycemic index observed in China and greatest glycemic load in South Asia.

Over 9. After adjusting for demographics, socioeconomic and cardiovascular disease risk factors, participants in the highest glycemic index quintile had higher risk of death or cardiovascular disease compared with those in the lowest quintile hazard ratio [HR], 1.

These findings were consistent among participants with HR for quintile 5 vs. In contrast, the association between greater glycemic load and higher risk of death or cardiovascular disease was only observed in the secondary prevention cohort HR for quintile 5 vs.

This analysis from the PURE study suggests that higher glycemic index and glycemic load are associated with greater risk of adverse cardiovascular disease events in adults with established cardiovascular disease.

However, this study is limited by its observational study design. This article will explore the similarities and differences between GI and GL and how your glycemic response influences your health and well-being.

The glycemic index is a system of classification in which the glycemic responses of foods are indexed against a standard white bread. It was introduced in by David Jenkins, M. GI is a numerical way of describing how carbohydrates in foods affect blood sugar levels.

The GI ranges from 0 to , with pure glucose being given a value of Processed foods made with refined sugar and flour such as candy, bread, cake, and cookies have a high GI, while whole foods such as unrefined grains, non-starchy vegetables, and fruits tend to have a lower GI.

GI is categorized as follows:. The glycemic load GL is a relatively new way to assess the impact of carbohydrate consumption on the rise of blood sugar in the body. It gives a fuller picture than GI alone. GL uses GI and the amount of total carbohydrates per serving of a specific food to estimate both how quickly a food causes blood sugar to rise and how much blood sugar levels will rise in total after eating.

By taking GI and the amount of carbohydrates per serving into account, GL highlights what nutritionists have known for a long time: High or low GI does not necessarily mean healthy or not healthy. Most fruits, for instance, have a high GI, but low GL.

Your blood sugar levels are dependent on many factors, including insulin levels , how quickly sugar is absorbed into your bloodstream, and how much sugar glucose is in a meal per serving. GI tells you something about how high your blood sugar could rise with certain foods, but it does not tell you how high your blood sugar will go when you actually eat the food.

GL gives you a more accurate picture of how food impacts your blood sugar levels by considering the following factors:. GL provides food's real-life impact on your blood sugar.

Watermelon , for example, has a high glycemic index 80 , but its low carbohydrate content per serving results in a glycemic load of only 5. Dietary GL is calculated by the amount of carbohydrate contained in a specified serving size of the food multiplied by the GI of that food and divided by GL is categorized as follows:.

GL and GI estimate the rise of blood glucose in the body after eating a specific food. Generally, foods with a low GL have a low GI, whereas foods with an intermediate or high GL can range from very low to very high GI. GI is a significant factor in GL.

The lower a food's GI, the slower blood sugar rises after eating that food. In general, foods that are higher in carbs and contain more processed ingredients have a higher GI. On the other hand, foods high in fiber or fat have lower GIs.

GL represents the quantity and quality of carbohydrates in the overall diet and their interactions in the body. This is why GL is widely regarded as a more reliable tool than the glycemic index alone. Glycemic load offers information about how foods affect blood sugar and insulin.

The lower a food's glycemic index or glycemic load, the less it affects blood sugar and insulin levels. Research shows that sticking to a low GL diet can play an important role in staving off type 2 diabetes and heart disease. Here is a GL reference list with many common foods based on their GL reference range.

Foods with a low GL of 10 or less include:. Foods with an intermediate GL of 11—19 include:. Foods with a high GL of 20 or more include:. Observational studies have yielded mixed results regarding the association of GI, GL, and adverse medical events. Studies show that carbohydrates are not bad in and of themselves.

Rather, diets that are too high or too low in carbohydrates can be problematic. Eating carbohydrates in the form of whole foods, such as whole grains, legumes, fruits, and vegetables, is better for your health than the carbohydrates contained in processed foods.

Overall, research shows that eating a low glycemic load diet, especially one that is high in fiber and whole-grain foods, is considered beneficial for cardiovascular disease prevention and several other chronic diseases, such as type 2 diabetes. One study, the PURE Prospective Urban Rural Epidemiology study, looked at how GI and GL impact cardiovascular health in nearly , people.

The PURE study found that higher GI and GL are associated with a greater risk of adverse cardiovascular disease events in adults with established cardiovascular disease.

However, the study was limited by recall bias due to its observational study design. More follow-up studies are needed to verify these results. Both of these tools are valuable in blood sugar management and diet planning.

GI is more commonly discussed than GL, but both are integral to diet planning, whether you have diabetes or not. Eating carbohydrates in moderation and exercising impact your body's ability to produce insulin and absorb glucose so those lifestyle choices must also be factored in.

If you are trying to form a personalized diet plan, you may want to discuss the role of glycemic index and glycemic load in your food choices with a nutritionist or healthcare provider.

Glycemic index does not account for the many factors that impact your blood sugar, such as the amount of carbohydrates in a specific food and how quickly they are absorbed in the body. This is why glycemic load is widely regarded as a more reliable tool than the glycemic index alone.

Chickpeas, green leafy vegetables celery, kale, and spinach , carrots, and parsnips are the vegetables with the lowest glycemic load. The GI of pasta ranges from 40 to 60, which is the intermediate range. Sticking to moderate portion sizes is as important as GI if you don't want your blood sugar to skyrocket.

Harvard Health. The lowdown on glycemic index and glycemic load. Atkinson FS, Brand-Miller JC, Foster-Powell K, Buyken AE, Goletzke J.

Foods and drinks provide our body with energy Cargohydrate the blycemic of carbohydrates, Carbohydrate metabolism and glycemic loadprotein and alcohol. Foods with carbohydrates include bread, Macronutrients and breastfeeding cereals, rice, Carbohydrate metabolism and glycemic load CCarbohydrate, legumes, corn, potato, fruit metaboliem, milkyoghurtsugarbiscuits, cakes and lollies. The digestive system breaks down carbohydrates in foods and drinks into simple sugars, mainly glucose. For example, both rice and soft drink will be broken down to simple sugars in your digestive system. The pancreas secretes a hormone called insulin, which helps the glucose to move from your blood into the cells. Our brain, muscles and nervous system all rely on glucose as their main fuel to make energy. The body converts excess glucose from food into glycogen. Carbohydrate metabolism and glycemic load

Author: Sagal

3 thoughts on “Carbohydrate metabolism and glycemic load

Leave a comment

Yours email will be published. Important fields a marked *

Design by ThemesDNA.com