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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.

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.

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.

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 <1 g free sugars, (3) ≥1 g fiber and <2 g free sugars, and (4) ≥1 g fiber, and <2 g free sugars per 1 g of fiber. Outcomes included GI, GL, and inclusion of warning labels proposed by the Brazilian National Health Surveillance Agency (ANVISA), the Chilean Ministry of Health (1st and 3rd stages), and the Pan American Health Organization (PAHO). Metrics identified products with lower mean GI (-12.8 to -9.0 [ 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.

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.

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.