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Abstract Background Adolescent obesity is considered as a major health concern worldwide which is closely linked to the quality of diet. The purpose of the present study was to assess the carbohydrate quality and quantity in relation to odds of overweight and obesity in adolescents. Methods This case-control study with a 1:1 ratio was conducted on 406 adolescents (14 to 18 years old) matched for age and gender. Participants were selected by multistage cluster random sampling method from March to October 2019 in Shiraz, Iran. Dietary intakes of the study population were assessed by a validated semi-quantitative food frequency questionnaire. Also anthropometric indices were measured using standard methods and demographic information was recorded via face to face interview. The relation between low carbohydrate diet score (LCDS) and carbohydrate quality index (CQI), and odds of obesity was evaluated by multiple Logistic regression. Results After adjusting the role of potential confounders, the participants in the third tertiles of LCDS (OR = 0.443, 95% CI = (0.260 to 0.755)) and CQI (OR = 0.005, 95% CI = (0.001 to 0.025)) had less odds of being overweight and obese compared to the first tertile. Conclusion The present study found an inverse relationship between dietary quantity and quality of carbohydrate intake and the odds of overweight and obesity in a sample of Iranian adolescents.

Abstract Background/aim Evidence from recent studies suggested that the quality of dietary macronutrients can play a possible role in predicting the risk of metabolic disorders. In the current study, we aimed to assess the association of carbohydrate quality index (CQI) and protein score with the risk of metabolic syndrome (MetS) in Iranian adults. Methods This prospective study was conducted within the framework of the Tehran Lipid and Glucose Study on 1738 individuals aged between 40 and 70 years old, who were followed up for a mean of 6.1 years. A food frequency questionnaire was used to determine CQI and protein scores. The multivariable adjusted Cox regression model was used to calculate the hazard ratio (HR) of MetS across quartiles of protein score and CQI, and its components. Results The mean ± standard deviation (SD) age and body mass index of the study population (42.5% men) were 49.3 ± 7.5 years and 27.0 ± 4.0 kg/m2, respectively. Mean ± SD scores of CQI and protein for all participants were 12.6 ± 2.4 and 10.3 ± 3.5, respectively. During the study follow-up, 834(48.0%) new cases of MetS were ascertained. In the multivariable-adjusted model, the risk of MetS was decreased across quartiles of CQI (HR = 0.83;95%CI:0.69–1.00, Ptrend=0.025) and protein score (HR = 0.75; 95% CI:0.60–0.94, Ptrend=0.041). Also, Of CQI components, the whole grain/total grains ratio showed a significant inverse association with the risk of MetS (HR = 0.75;95%CI:0.60–0.94, Ptrend=0.012). Conclusion Our findings revealed that a dietary pattern with higher CQI and protein score may be related to a reduced risk of MetS in adults.

Abstract Background This study aimed to investigate the association between the intake of different dietary carbohydrate components and the long-term outcomes of non-alcoholic fatty liver disease (NAFLD). Methods We used prospective data from 26,729 NAFLD participants from the UK Biobank cohort study. Dietary information was recorded by online 24-hour questionnaires (Oxford WebQ). Consumption of different carbohydrate components was calculated by the UK Nutrient Databank Food Composition Table. Cox proportional hazards models were used to estimate the adjusted hazard ratio (HR) and 95% confidence interval (CI). A substitution model was used to estimate the associations of hypothetical substitution for free sugars. Results During a median of 10.5 (IQR: 10.2–11.2) years and a total of 280,135 person-years of follow-up, 310 incident end-stage liver disease (ESLD) and 1750 deaths were recorded. Compared with the lowest quartile, the multi-adjusted HRs (95% CI) of incident ESLD in the highest quartile were 1.65 (1.14–2.39) for free sugars, 0.51 (0.35–0.74) for non-free sugars, and 0.55 (0.36–0.83) for fiber. For overall mortality, the multi-adjusted HRs (95% CI) in the highest quartile were 1.21 (1.04–1.39) for free sugars, 0.79 (0.68–0.92) for non-free sugars, and 0.79 (0.67–0.94) for fiber. Substituting free sugars with equal amounts of non-free sugars, starch or fiber was associated with a lower risk of incident ESLD and overall mortality. Conclusions A lower intake of free sugars and a higher intake of fiber are associated with a lower incidence of ESLD and overall mortality in NAFLD patients. These findings support the important role of the quality of dietary carbohydrates in preventing ESLD and overall mortality in NAFLD patients.

Abstract Background and aims Excess energy intake can lead to metabolic dysfunction-associated steatotic liver disease (MASLD), but the relationship between dietary carbohydrate intake and liver fat content remains unclear. This study aimed to examine the associations between types and sources of dietary carbohydrates and liver fat content. Methods UK Biobank participants with no pre-existing diabetes, liver disease or cardiovascular disease reported dietary intake of types and sources of carbohydrates (total carbohydrates, free sugars, non-free sugars, starch from whole grains, starch from refined grains, and fibre) on at least two 24-h dietary assessments. In cross-sectional analyses, (n = 22,973), odds ratios (OR) of high liver fat content (defined as a score of ≥ 36 in the hepatic steatosis index) by quintiles of carbohydrate intakes were estimated using multivariable logistic regression models. In prospective analyses, a second sample (n = 9268) had liver proton density fat fraction (PDFF) measured by magnetic resonance imaging (2014–2020). Multivariable linear regression models estimated geometric means of PDFF (%) by quintiles of carbohydrate intakes. Models were adjusted for demographic and lifestyle confounders, including total energy intake. Results In the cross-sectional analyses, 6894 cases of high liver fat content were identified. Inverse associations between intakes of fibre (OR of highest vs. lowest quintile 0.46 [95% CI: 0.41–0.52]), non-free sugars (0.63 [0.57–0.70]) and starch from whole grains (0.52 [0.47–0.57]) with liver fat were observed. There were positive associations between starch from refined grains and liver fat (1.33 [1.21–1.46]), but no association with free sugars (p=0.61). In prospective analyses, inverse associations with PDFF (%) were observed for intakes of fibre (− 0.48 geometric mean difference between highest and lowest quintile of intake [− 0.60 to − 0.35]), non-free sugars (− 0.37 [− 0.49 to − 0.25]) and starch from whole grains (− 0.31 [− 0.42 to − 0.19]). Free sugars, but not starch from refined grains, were positively associated with PDFF (0.17 [0.05 to 0.28]). Conclusion This study suggests that different carbohydrate types and sources have varying associations with liver fat, which may be important for MASLD prevention. Non-free sugars, fibre, and starch from whole grains could be protective, while associations with free sugars and starch from refined grains are less clear.

Carbohydrates play a crucial role in the development of chronic diseases, and although research in this area is expanding, the precise definition of carbohydrate quality remains unclear. Currently, commonly utilized indicators encompass dietary fiber content, whole grain intake, free sugars intake and the glycemic index (GI). High-quality carbohydrate foods typically exhibit high dietary fiber content, consist of whole grain components, contain low levels of free sugars, and possess a low GI. The GI, in particular, directly influences the human blood sugar response and serves as a vital measure for describing carbohydrate quality. This article provides a comprehensive overview of the factors that influence the GI, focusing on three aspects: digestion and absorption, processing methods, and starch composition and structure. It further examines the GI values of various food sources. The rate of digestion and absorption, as well as diverse processing methods, can influence the GI. Additionally, the composition and structure of starch directly affect the GI. Amylose and amylopectin exhibit dissimilar structural compositions, with amylopectin containing more amylase binding sites than amylose, leading to a higher digestion rate. Consequently, foods with elevated amylose content tend to have relatively low GI values. Additionally, starch can be categorized into three types (A-type, B-type, and C-type) based on the crystal form of amylopectin present in the starch. Among these types, A-type starch is the most readily digestible, while B-type and C-type starch exhibit low GI characteristics due to their reduced digestibility. By studying the microstructure of starch, researchers can gain valuable insights into the influencing factors of the GI, thereby introducing a fresh perspective to the assessment of food carbohydrate quality.

ABSTRACTThe impact of carbohydrate quality, measured by the carbohydrate quality index (CQI), on gut microbiota and health has been scarcely investigated. The aim of this study was to cross-sectionally and longitudinally explore the relationships between CQI, fecal microbiota, and cardiometabolic risk factors in an elderly Mediterranean population at high cardiovascular risk. At baseline and 1-year, CQI was assessed from food frequency questionnaires data, cardiometabolic risk factors were measured, and fecal microbiota profiled from 16S sequencing. Multivariable-adjusted linear regression models were fitted to assess the associations between tertiles of baseline CQI, fecal microbiota, and cardiometabolic risk factors at baseline, and between tertiles of 1-year change in CQI, 1-year change in fecal microbiota and cardiometabolic risk factors. Cross-sectionally, higher CQI was positively associated with Shannon alpha diversity index, and abundance of genera Faecalibacterium and Christensenellaceae R7 group, and negatively associated with the abundance of Odoribacter, and uncultured Rhodospirillales genera. Some of these genera were associated with higher glycated hemoglobin and lower body mass index. In addition, we observed a positive association between CQI, and some pathways related with the metabolism of butyrate precursors and plants-origin molecules. Longitudinally, 1-year improvement in CQI was associated with a concurrent increase in the abundance of genera Butyrivibrio. Increased abundance of this genera was associated with 1-year improvement in insulin status. These observations suggest that a better quality of carbohydrate intake is associated with improved metabolic health, and this improvement could be modulated by greater alpha diversity and abundance of specific genera linked to beneficial metabolic outcomes.

The challenges in the characterization of the nutritional quality of grain foods comprise obstacles to public health actions toward promotion of healthier grain-based foods. The present study investigated how carbohydrate metrics related to glycemic index (GI), glycemic load (GL), and warning labels of grain foods consumed by individuals living in São Paulo, Brazil. Information on intake of grain foods at individual level was obtained using 24 h recalls within a cross-sectional population-based survey conducted in 2015. There were 244 unique grain products reported by individuals in the survey, assessed through four metrics of carbohydrate quality, considering contents per 10 g of total carbohydrate: (1) ≥1 g fiber, (2) ≥1 g fiber and p-values < 0.001]), and GL (−12.5 to −10.3 [p-values < 0.001]). Warning systems showed a certain degree of discrimination between products according to the metrics (p-value < 0.01 each); however, >50% of products with good nutritional quality according to the carbohydrate metrics still would receive warnings. Findings suggest that carbohydrate metrics identified products with lower GI and GL, and current warning labels may not adequately capture overall nutritional quality of grain foods.

The 2025–2030 United States Dietary Guidelines process is currently underway, and the 2025 Dietary Guidelines Advisory Committee is examining and evaluating a list of prioritized scientific questions identified by the United States Department of Health and Human Services and the United States Department of Agriculture. One of the questions that will be evaluated is if changes should be made to USDA Dietary Patterns based on whether starchy vegetables and grains are, or can be, consumed interchangeably. These foods have historically been classified in distinct food groups. Menu modeling analyses evaluating the impact of replacing starchy vegetables with grains result in declines in key nutrients of concern. Given their unique nutrient contributions and the fact that many cultural foodways within the United States population include both starchy vegetables and grains, it is important for dietary recommendations to continue to categorize starchy vegetables and grains separately.

Abstract Low‐carbohydrate diets (LCDs) are popular among people attempting weight loss and recommended for pregnant women with gestational diabetes (GDM), but they may increase health risks if nutritionally inadequate. We aimed to describe the dietary intake of post‐partum women according to their relative carbohydrate intake, overall, and among women attempting weight loss or diagnosed with GDM in their recent pregnancy. This cross‐sectional population‐based cohort study included 2093 post‐partum women aged 25–36 years who participated in the Australian Longitudinal Study on Women's Health. Dietary intake was assessed using a validated food frequency questionnaire. Relative carbohydrate intake was determined using a previously developed LCD score. Data were weighted to account for oversampling of women from rural/remote areas. More than half of women (n[weighted] = 1362, 66.3%) were trying to lose weight, and 4.6% (n[weighted]=88) had GDM in their recent pregnancy. Women with the lowest relative carbohydrate intake (LCD score quartile 4) consumed 36.8% of total energy intake from carbohydrates, and had a lower intake of refined grains, whole grains, fruit and fruit juice, and a higher intake of red and processed meat, compared with women with the highest relative carbohydrate intake (quartile 1). Different food groups, both healthy and unhealthy, were restricted depending on whether women were attempting weight loss and had recent GDM. These findings may reflect a lack of knowledge among post‐partum women on carbohydrates and dietary guidelines. Health professionals may have an important role in providing advice and support for post‐partum women who wish to restrict their carbohydrate intake, to ensure optimal diet quality.

Introduction: To determine whether dietary carbohydrates quality index (CQI), glycemic index, and glycemic load is associated with general and abdominal obesity. Methods: 850 participants, 20 to 59 years old, were enrolled in a cross-sectional study from five Tehran districts through health houses. The 168 items in the semi--quantitative food frequency questionnaire were used to assess dietary intake. The CQI was calculated by using the following four components: glycemic index, total fiber, solid carbohydrate to total carbohydrate ratio, and whole grains: total grains ratio. Results: After adjusting for confounding factors, the chance of obesity in men (OR=0.38, 95% CI 0.15to 0.95; P=0.04) measured by waist circumference (WC) was significantly lower in the fourth quintile of CQI in comparison with the first quintile. In addition, OR for obesity in men (OR=2.53, 95% CI0.52 to 1.37; P=0.04) was significantly 2.5 times higher among those in the fourth quintile of glycemic index compared with those in the lowest quintile. There was no significant association between dietary carbohydrates with general obesity in men and women. Conclusion: In summary, dietary CQI is significantly inversely related to central obesity in men,according to this study. Additionally, adherence to a diet with a higher glycemic index in men is positively associated with central obesity.

Background/AimThis study aimed to examine the associations between dietary protein score and carbohydrate quality index (CQI) and the risk of chronic kidney disease (CKD) in Iranian adults.MethodsThis population-based cohort study was performed within the Tehran Lipid and Glucose Study framework on 6,044 subjects aged ≥18 years old, who were followed up for a mean of 7.7 years. Dietary protein score and CQI were determined using a food frequency questionnaire. CKD was defined as an estimated glomerular filtration rate

ObjectivesIn utero glycemia is an important determinant of fetal growth. Women with gestational diabetes are more likely to deliver large-for-gestational age babies that are at increased risk for obesity. The maternal nutritional state modulates the development of offspring biological systems during the critical periods of gestation and lactation. Carbohydrate typically contributes most of the dietary energy, however, there are very few mechanistic studies investigating the effects of maternal dietary carbohydrate quality on fetal and offspring outcomes. Therefore, we sought to investigate the direct effects of maternal carbohydrate quality on sex-specific offspring metabolic programming.MethodsFemale C57BL/6 mice were fed one of five isocaloric diets: four high-sugar diets based on glucose, sucrose, isomaltulose or fructose (all containing 60% energy as carbohydrate), or a standard, minimally processed, chow diet, and were mated with chow-fed males. Half of the dams were sacrificed for fetus dissection and placental collection, with the remaining giving live birth. All dams were metabolically profiled before and during pregnancy, and pups were similarly profiled at 12 weeks of age.ResultsOverall, glucose-fed dams were heavier and fatter than chow or isomaltulose-fed dams. Female fetuses from glucose and isomaltulose-fed mothers weighed less and had smaller livers, than those from chow-fed mothers, with isomaltulose-fed female fetuses also having decreased placental mass. In contrast, male fetuses responded differently to the maternal diets, with heart mass being significantly increased when their mothers were fed fructose-containing diets, that is, sucrose, isomaltulose and fructose. High-sugar fed female offspring weighed the same, but were significantly fatter, than chow-fed offspring at 12 weeks of age, while glucose and isomaltulose-fed male pups displayed a similar phenotype to their mothers’.ConclusionWhile both glucose and isomaltulose diets constrained fetal growth in females, only placentas from isomaltulose-fed dams were significantly smaller than those from chow-fed mothers, suggesting the mechanisms through which fetal growth is reduced may be different. Female fetuses of isomaltulose-fed mothers were also lighter than sucrose-fed fetuses suggesting the glycemic index, or rate of glucose digestion and absorption, may be an important factor in determining nutrient availability to the growing fetus.

Carbohydrate foods (≥40% energy from carbohydrates) are the main source of energy in the US diet. In contrast to national-level dietary guidance, many regularly consumed carbohydrate foods are low in fiber and whole grains but high in added sugar, sodium, and/or saturated fat. Given the important contribution of higher-quality carbohydrate foods to affordable healthy diets, new metrics are needed to convey the concept of carbohydrate quality to policymakers, food industry stakeholders, health professionals, and consumers. The recently developed Carbohydrate Food Quality Scoring System is well aligned with multiple key healthy messages on nutrients of public health concern from the 2020–2025 Dietary Guidelines for Americans. Two models are described in a previously published paper: one for all non-grain carbohydrate-rich foods (e.g., fruits, vegetables, legumes) known as the Carbohydrate Food Quality Score-4 (CFQS-4), and one for grain foods only known as the Carbohydrate Food Quality Score-5 (CFQS-5). These CFQS models provide a new tool that can guide policy, programs, and people towards improved carbohydrate food choices. Specifically, the CFQS models represent a way to unify and reconcile diverse ways to describe different types of carbohydrate-rich foods (e.g., refined vs. whole, starchy vs. non-starchy, dark green vs. red/orange) and make for more useful and informative messaging that better aligns with a food’s nutritional and/or health contributions. The present paper’s aims are to show that the CFQS models can inform future dietary guidelines and help support carbohydrate food recommendations with other health messages aimed at promoting foods that are nutrient-dense, fiber-rich, and low in added sugar.

Abstract Background Diet quality is generally poor in persons with diabetes and it is unknown whether this is associated with worse glycaemic control and atherogenic lipid profile. The aim was to examine diet quality in relation to important markers of metabolic control in adults with type 1 diabetes (T1D) and type 2 diabetes (T2D). Methods The study was cross-sectional and included 423 (49% females) persons with T1D and 339 (29% females) persons with T2D recruited from an outpatient diabetes clinic in Denmark. Data were collected from July 2014 to January 2015. Diet quality was assessed with a food frequency questionnaire to examine eight key dietary components (carbohydrates, saturated fatty acids, monounsaturated fatty acids, polyunsaturated fatty acids, added sugar, dietary fibre, fruit and vegetables). Clinical data assessing metabolic control (haemoglobin A1c (HbA1c), total cholesterol (total C), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), systolic and diastolic blood pressure and body mass index were extracted from the electronic medical records. Results In T1D, higher intake of carbohydrates and added sugar was associated with higher HbA1c; higher fruit intake was associated with lower total C and LDL-C; and higher intake of carbohydrates and dietary fibre was associated with lower HDL-C. In T2D, higher intake of saturated fat was associated with higher total C; higher intake of added sugar was associated with higher LDL-C; and higher intake of polyunsaturated fat was associated with higher diastolic blood pressure. Conclusions In Danish adults with T1D and T2D, both the total intake and the quality of carbohydrates and fat were associated with an unfavourable glucose regulation and lipid profile. Thus, our findings support a constant focus on diet and emphasise the need for dietary support in people with diabetes to improve diet quality, metabolic control and possibly reduce cardiovascular risk.

Dietary glycemic index (GI), carbohydrate to fiber ratio (CF) and carbohydrate quality index (CQI) are conventional and emerging indicators for carbohydrate quality. We aimed to investigate the associations between these indicators and new-onset type 2 diabetes mellitus (T2DM) risk among Chinese adults. This prospective cohort study included 14,590 adults from the China Health and Nutrition Survey without cardiometabolic diseases at baseline. The associations between dietary GI, CF and CQI and T2DM risk were assessed using Cox proportional hazard regression analysis and dose–response relationships were explored using restricted cubic spline and threshold analysis. After a mean follow-up duration of 10 years, a total of 1053 new-onset T2DM cases occurred. There were U-shaped associations between dietary GI and CF and T2DM risk (both P-nonlinear < 0.0001), and T2DM risk was lowest when dietary GI was 72.85 (71.40, 74.05) and CF was 20.55 (17.92, 21.91), respectively (both P-log likelihood ratio < 0.0001). Inverse associations between CQI and T2DM risk specifically existed in participants < 60 y or attended middle school or above (both P-trend < 0.05). These findings indicated that moderate dietary GI and CF range and a higher dietary CQI score may be suggested for T2DM prevention in Chinese adults.

Carbohydrate-containing crops provide the bulk of dietary energy worldwide. In addition to their various carbohydrate forms (sugars, starches, fibers) and ratios, these foods may also contain varying amounts and combinations of proteins, fats, vitamins, minerals, phytochemicals, prebiotics, and anti-nutritional factors that may impact diet quality and health. Currently, there is no standardized or unified way to assess the quality of carbohydrate foods for the overall purpose of improving diet quality and health outcomes, creating an urgent need for the development of metrics and tools to better define and classify high-quality carbohydrate foods. The present report is based on a series of expert panel meetings and a scoping review of the literature focused on carbohydrate quality indicators and metrics produced over the last 10 years. The report outlines various approaches to assessing food quality, and proposes next steps and principles for developing improved metrics for assessing carbohydrate food quality. The expert panel concluded that a composite metric based on nutrient profiling methods featuring inputs such as carbohydrate–fiber–sugar ratios, micronutrients, and/or food group classification could provide useful and informative measures for guiding researchers, policymakers, industry, and consumers towards a better understanding of carbohydrate food quality and overall healthier diets. The identification of higher quality carbohydrate foods could improve evidence-based public health policies and programming—such as the 2025–2030 Dietary Guidelines for Americans.

The long-term impact of carbohydrate quality on abdominal weight gain is not fully understood. We aimed to examine the prospective relation of a carbohydrate quality index (CQI; defined by four criteria: dietary fiber, glycemic index, whole grain-to-total grain ratio, and solid-to-total carbohydrate ratio), total, cereal grain, vegetable, and fruit fiber, carbohydrate-to-total fiber ratio, and carbohydrate-to-cereal fiber ratio with changes in waist circumference (WC). Subjects were middle-aged to older, mostly white, participants in the Framingham Offspring cohort (n = 3101 subjects), with mean baseline age 54.9 ± 0.2 years (mean ± SE) and body mass index (BMI) 27.2 ± 0.1 kg/m2. Food frequency questionnaire (FFQ), health, and lifestyle data were collected approximately every four years over a median total follow-up of 18 years. Repeated measure mixed models were used to estimate adjusted mean change in WC per four-year interval across quartiles of carbohydrate variables. In the most adjusted model, a higher CQI was marginally associated with a smaller increase in WC (2.0 ± 0.1 vs. 2.4 ± 0.1 cm in highest vs. lowest quartile, p-trend = 0.04). Higher ratios of carbohydrate-to-fiber and carbohydrate-to-cereal fiber were associated with greater increases in WC per four-year interval (2.6 ± 0.1 vs. 2.0 ± 0.1 cm, p-trend < 0.001, and 2.5 ± 0.1 vs. 2.1 ± 0.1 cm in highest versus lowest categories, p-trend = 0.007, respectively); whereas higher intake of total fiber (1.8 ± 0.1 vs. 2.7 ± 0.1 cm, p-trend < 0.001), cereal fiber (2.0 ± 0.1 vs. 2.5 ± 0.1 cm, p-trend = 0.001), and fruit fiber (2.0 ± 0.1 vs. 2.7 ± 0.1 cm, p-trend < 0.001) were associated with smaller increases in WC compared to lower intakes. There was a significant interaction between total fiber and total carbohydrate (as % of total energy intake). After stratification, the association between fiber intake and change in WC was not maintained in the context of a high carbohydrate diet. Better carbohydrate quality, primarily higher fiber intake and lower carbohydrate-to-fiber ratios, may help attenuate increases in abdominal adiposity over time.

To draw attention to the necessity of considering differences in the digestibility of carbohydrates, and more specifically of starch, a symposium was held at the 12th European Nutrition Conference (FENS), which took place in Berlin from October 20 to 23, 2015. The purpose of this session was to present the consolidated knowledge and recent advances regarding the relationship between slow-release carbohydrates, metabolic responses, and public health issues. Three main topics were presented: 1) the definition of, sources of, and recognised interest in the glycaemic response to slowly digestible starch (SDS); 2) clinical evidence regarding the physiological effects of slow-release carbohydrates from cereal foods; and 3) interest in reducing the postprandial glycaemic response to help prevent metabolic diseases. Foods with the highest SDS content induce the lowest glycaemic responses, as the starch is protected from gelatinisation during processing. In humans, high-SDS food consumption induces slower glucose release, lower postprandial insulinaemia, and stimulation of gut hormones. Moreover, postprandial hyperglycaemia is an independent risk factor for type two diabetes mellitus (T2DM) and cardiovascular disease (CVD). Therefore, given the plausible aetiologic mechanisms, we argue that postprandial glucose levels are relevant for health and disease and represent a meaningful target for intervention, for example, through dietary factors. This symposium was organised by Mondelez International R&D.

Carbohydrate quality is an aetiological factor of diet-related disease. Indices of carbohydrate quality featuring various ratios of carbohydrates-to-dietary fibre-to-sugar have been associated with improved product and/or diet quality in westernised countries. Carbohydrate intake is especially high in Asia Pacific. Thus, this study evaluated the ability of such carbohydrate metrics to discriminate the nutritional quality of carbohydrate-rich packaged foods and beverages in Australia, Malaysia, Singapore, Thailand and the Philippines, with an additional focus on beverages. This evaluation was conducted by comparing product nutritional composition and assessing products against three national nutrient profiling models. Results showed that Australia had the highest proportion of products meeting all metrics, compared to the Southeast Asian countries. Beverages had a low adherence to all metrics compared to solid foods. Across the five countries, both processed food and beverages meeting the metrics generally contained higher dietary fibre, protein, and certain vitamins and minerals whilst having lower energy, total sugars, free sugars, trans fat and cholesterol content compared to products not meeting the metrics. The metrics were also aligned with national nutrient profiling models to identify nutritious products. In conclusion, these metrics allowed us to discriminate product nutritional quality in the countries assessed and are applicable to beverages.

Dietary fibre is a generic term describing non-absorbed plant carbohydrates and small amounts of associated non-carbohydrate components. The main contributors of fibre to the diet are the cell walls of plant tissues, which are supramolecular polymer networks containing variable proportions of cellulose, hemicelluloses, pectic substances, and non-carbohydrate components, such as lignin. Other contributors of fibre are the intracellular storage oligosaccharides, such as fructans. A distinction needs to be made between intrinsic sources of dietary fibre and purified forms of fibre, given that the three-dimensional matrix of the plant cell wall confers benefits beyond fibre isolates. Movement through the digestive tract modifies the cell wall structure and may affect the interactions with the colonic microbes (e.g., small intestinally non-absorbed carbohydrates are broken down by bacteria to short-chain fatty acids, absorbed by colonocytes). These aspects, combined with the fibre associated components (e.g., micronutrients, polyphenols, phytosterols, and phytoestrogens), may contribute to the health outcomes seen with the consumption of dietary fibre. Therefore, where possible, processing should minimise the degradation of the plant cell wall structures to preserve some of its benefits. Food labelling should include dietary fibre values and distinguish between intrinsic and added fibre. Labelling may also help achieve the recommended intake of 14 g/1000 kcal/day.

The objectives of this qualitative study was to: (1) understand Canadian consumers’ knowledge and perception of dietary carbohydrates, carbohydrate quality, and the glycemic index (GI); and (2) determine Canadian’s receptiveness to GI labelling to assist with identifying and consuming foods of higher carbohydrate quality. Focus groups were recruited in Vancouver, Toronto, and Montreal and grouped according to body mass index (BMI) (NBW, normal body weight; PO, previously obese; and OW/OB, overweight/obese) and diagnosis with prediabetes and diabetes (PO (Vancouver) and OW/OB (Montreal and Toronto). Subjects in all groups linked excess consumption of carbohydrate with weight gain. PO and OW/OB groups were conflicted between perceived negative consequences and feelings of pleasure associated with carbohydrate consumption. Subjects were largely unfamiliar with the term ‘carbohydrate quality’, but were often associated with classifying carbohydrates as ‘good’ or ‘bad’. The concept of the GI resonated well across groups after exposure to corresponding educational materials. However, NBW groups largely felt that the GI was irrelevant to their dietary choices as they did not have a history of diabetes. PO and OW/OB groups associated the GI with diabetes management. The concept of a GI labelling program to help facilitate healthier carbohydrate choices was well received across all groups, especially when the low GI was interpreted as giving permission to consume foods they enjoyed eating. Results suggest that the GI could be used as a consumer-facing labelling program in Canada and assist with de-stigmatizing carbohydrate foods by helping to facilitate the consumption of carbohydrate foods that align with healthy dietary patterns.

Glycaemic index (GI) is used as an indicator to guide consumers in making healthier food choices. We compared the GI, insulin index (II), and the area under the curve for blood glucose and insulin as glucose (GR) and insulin responses (IR) of a newly developed liquid nutritional formula with one commercially available liquid product with different types of carbohydrates. We then evaluated the glucose and insulin responses of two test foods with comparable energy density and protein percentage but presented in different food forms (liquid vs. solid). Fourteen healthy women participated in the study. GI, II, GR, and IR were assessed after (independent) consumption of two liquid products and a solid breakfast meal. The two liquid foods showed comparable GI, whilst the liquid form appeared to produce lower median GI (25 vs. 54), and II (52 vs. 98) values compared to the solid breakfast (p < 0.02). The median GR and IR for solid breakfast were respectively 44% and 45% higher compared to the liquid product (p < 0.02). Liquid formulas with different carbohydrate qualities produced comparable glucose responses, while foods with comparable energy density and protein percentage but different food form elicited differential effects on GI, II, GR, and IR. Nutrient quality and food form need to be taken into consideration when developing low GI products to manage glycaemic responses.