Development of a national database for dietary glycemic index and load for nutritional epidemiologic studies in the United States.

BACKGROUND: The quality of carbohydrate intake, as measured by the glycemic index (GI), has not been evaluated nationally over the past 2 decades in the United States. OBJECTIVES: We aimed to develop a comprehensive and nationally representative dietary GI and glycemic load (GL) database from 1999 to 2018 National Health and Nutrition Examination Survey (NHANES) and to examine GI and GL time trends and subpopulation differences. METHODS: We used an artificial intelligence (AI)-enabled model to match GI values from 2 GI databases to food codes from United States Department of Agriculture, which were manually validated. We examined nationally representative distributions of dietary GI and GL from 1999 to 2018 using the multistage, clustered sampling design of NHANES. RESULTS: Assigned GI values covered 99.9% of total carbohydrate intake. The initial AI accuracy was 75.0%, with 31.3% retained after manual curation guided by substantive domain expertise. A total of 7976 unique food codes were matched to GI values, of which soft drinks and white bread were top contributors to dietary GI and GL. Of the 49,205 NHANES adult participants, the mean dietary GI was 55.7 (95% confidence interval [CI]: 55.5, 55.8) and energy-adjusted dietary GL was 133.0 (95% CI: 132.3, 133.8). From 1999 to 2018, dietary GI and GL decreased by 4.6% and 13.8%, respectively. Dietary GL was higher among females (134.6; 95% CI: 133.8, 135.5) than among males (131.3; 95% CI: 130.3, 132.3), those with ≤high school degree (137.7; 95% CI: 136.8, 138.7) than among those with ≥college degree (126.5; 95% CI: 125.3, 127.7), and those living under the poverty level (140.9; 95% CI: 139.6, 142.1) than among those above the poverty level. Differences in race were observed (Black adults, 139.4; 95% CI: 138.2, 140.7; White adults, 131.6; 95% CI: 130.5, 132.6). CONCLUSIONS: The national GI and GL database facilitates large-scale and high-quality surveillance or cohort studies of diet and health outcomes in the United States.

The association between carbohydrate quality index and headache severity, disability and duration among women with migraine: a cross-sectional study.

BACKGROUND & AIM: This study aimed to examine the association between Carbohydrate Quality Index (CQI) and headache severity, disability and duration among women with migraine. MATERIALS & METHODS: In this cross-sectional study, 266 women (aged 18-45 years) were enrolled using a 147-item food frequency questionnaire (FFQ). CQI was defined by four criteria: fiber intake, dietary glycemic index (DGI), whole grains/total grains ratio and solid carbohydrates/total carbohydrates ratio. Anthropometric measurements, visual analogue scale (VAS), migraine disability assessment (MIDAS), and headache duration were assessed for all participants. RESULTS: Participants with a high adherence to CQI had lower odds of moderate pain (OR = 0.45; 95% CI = 0.21-0.94; P = 0.03) and severe pain (OR = 0.39; 95% CI = 0.18-0.82; P = 0.01) compared to those with a low adherence to CQI. After controlling for potential confounders, individuals with the greatest adherence to CQI showed a 78% reduced prevalence in severe pains and a 63% decreased occurrence in moderate pains compared to those with the lowest adherence (OR = 0.22; 95% CI = 0.09-0.55; P = 0.01 and OR = 0.37; 95% CI = 0.16-0.84; P = 0.01, respectively). Moreover, Subjects with higher adherence to CQI had lower odds of headache duration (OR = 0.54; 95% CI= 0.31-0.96; P = 0.03). The significant association remained (P < 0.05) even after confounding variables (OR = 0.59; 95 % CI = 0.35-1.002; P = 0.05). Despite adjusting for confounding valuables, there was no significant association between the CQI and MIDAS scores (P > 0.05). CONCLUSION: Higher adherence to CQI was associated with lower severity and duration in patients with migraine. Further studies are needed to confirm these results.

Pragmatic Carbohydrate Quality Metrics in Relation to Glycemic Index, Glycemic Load, and Front-of-Pack Warning Labels in Grain Foods.

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.

Perspective: Potatoes, Quality Carbohydrates, and Dietary Patterns.

Potatoes have long been a staple food in many cultures and cuisines, but they have gained a reputation as a low-quality carbohydrate source that should be avoided in the diet. Historically, this view has been justified by citing the glycemic index of potatoes as the main indicator of their quality. However, their nutrient composition should also be considered. The association of potatoes with energy-dense Western dietary patterns has also contributed to a perception that potatoes are inherently unhealthy. Although some studies have suggested an association between potato consumption and increased risk of health problems, such as type 2 diabetes, these associations may be confounded by fried potato intake and are strongest at intake levels higher than average consumption rates. Epidemiologic data suggest total potato intake is not a health risk in Eastern populations and can be consumed as part of a healthy diet. Furthermore, clinical trial data demonstrate that potatoes' health impact, irrespective of preparation, is similar to legumes and comparable with refined grains, with few deleterious effects found. These findings highlight the importance of moving beyond the glycemic index and adopting a more nuanced evaluation of the epidemiologic data to better understand the health impact of potato intake. Ultimately, the negative reputation of potatoes stems from an overinterpretation of their glycemic index and association with unhealthy Western dietary patterns, as well as oversimplification of the epidemiologic data. By considering carbohydrate quality, it becomes clear that potatoes can be part of a healthy diet given the proper consideration.

Carbohydrate quality, not quantity, linked to reduced colorectal cancer incidence and mortality in US populations: evidence from a prospective study.

BACKGROUND: Carbohydrates have been implicated in colorectal cancer (CRC) risk, but the specific impact of carbohydrate quality and quantity on CRC susceptibility in US populations remains unclear. METHODS: We followed 101,694 participants from Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. The carbohydrate quality index (CQI) and low-carbohydrate diet score (LCDs) were used to evaluate the daily carbohydrate quality and quantity separately, where higher scores indicated greater adherence. Cox proportional hazards regression was used to compute HRs and 95% CIs for incident CRC and related death. Subgroup analyses were conducted to identify potential effect modifiers. RESULTS: During follow-up, we documented 1085 incident cases of CRC, of whom 311 died from CRC. Individuals in the highest compared with the lowest quartiles of CQI had a lower CRC incidence (Q4 vs Q1: HR 0.80, 95% CI 0.67-0.96, Ptrend = 0.012) and mortality (Q4 vs Q1: HR 0.61, 95% CI 0.44-0.86, Ptrend = 0.004). The inverse association between CQI and CRC risk was observed for distal colon and rectum but not for proximal colon cancer. Regarding mortality, this association was only significant for rectum cancer. Subgroup analyses indicated this inverse association of CQI with CRC risk was only observed in participants with lower LCDs. No significant associations were found between LCDs and CRC incidence or mortality. CONCLUSIONS: Our findings suggest focusing on higher quality, rather than restricting the quantity, of carbohydrate consumption may be an effective approach to reduce the risk of CRC in the US population, particularly for distal colon and rectal cancers.

The association of dietary carbohydrate quality and quantity with obesity among Iranian adolescents: a case-control study.

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.

Macronutrients quality indices and risk of metabolic syndrome and its components in Iranian adults.

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.

Association between high or low-quality carbohydrate with depressive symptoms and socioeconomic-dietary factors model based on XGboost algorithm: From NHANES 2007-2018.

BACKGROUND: Depressive symptoms are a serious public mental health problem, and dietary intake is often considered to be associated with depressive symptoms. However, the relationship between the quality of dietary carbohydrates and depressive symptoms remains unclear. Therefore, this study aimed to investigate the relationship between high and low-quality carbohydrates and depressive symptoms and to attempt to construct an integrated model using machine learning to predict depressive symptoms. METHODS: A total of 4982 samples from the National Health and Nutrition Examination Survey (NHANES) were included in this study. Carbohydrate intake was assessed by a 24-h dietary review, and depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ9). Variance inflation factor (VIF) and Relief-F algorithms were used for variable feature selection. RESULTS: The results of multivariate linear regression showed a negative association between high-quality carbohydrates and depressive symptoms (ß: -0.147, 95 % CI: -0.239, -0.056, p = 0.002) and a positive association between low-quality carbohydrates and depressive symptoms (ß: 0.018, 95 % CI: 0.007, 0.280, p = 0.001). Subsequently, we used the XGboost model to produce a comprehensive depressive symptom evaluation model and developed a corresponding online tool (http://8.130.128.194:5000/) to evaluate depressive symptoms clinically. LIMITATIONS: The cross-sectional study could not yield any conclusions regarding causality, and the model has not been validated with external data. CONCLUSIONS: Carbohydrate quality is associated with depressive symptoms, and machine learning models that combine diet with socioeconomic factors can be a tool for predicting depression severity.

Association of postoperative dietary macronutrient content and quality with total weight loss and fat-free mass loss at midterm after sleeve gastrectomy.

OBJECTIVES: This study aimed to investigate the associations of macronutrient quantities and qualities with percentage total weight loss and percentage of fat-free mass loss relative to total weight loss in adults undergoing sleeve gastrectomy. METHODS: This cross-sectional study included 146 patients on postoperative time since sleeve gastrectomy of 2 to 4 y. Diet was assessed using a food frequency questionnaire. Macronutrient quality index, carbohydrate quality index, fat quality index, and healthy plate protein quality index were calculated. The associations of dietary variables with percentage total weight loss and percentage of fat-free mass loss relative to total weight loss were determined using linear regression. Logistic regression was used to estimate the odds of non-response (percentage total weight loss < 25%) and excessive fat-free mass loss (percentage of fat-free mass loss relative to total weight loss > 28%) based on dietary intakes. RESULTS: Forty-six (31.5%) were non-responders, and 49 (33.6%) experienced excessive fat-free mass loss. The fully adjusted model showed a 0.75 decrease in percentage total weight loss per 5% carbohydrate increase (95% CI, -1.45 to -0.05). The odds of non-response were 53% lower per 5% increase in protein (95% CI, 0.23-0.94). Each 5-g higher intake of fat was associated with 0.29 higher percentage of fat-free mass loss relative to total weight loss (95% CI, 0.03-0.55). The odds of excessive fat-free mass loss were reduced by 5% per gram of fiber intake (95% CI, 0.90-0.99). Each 5% increment in energy intake from protein that was isocalorically substituted for either carbohydrate or fat was associated with lower odds of nonresponse. Macronutrient quality indices had no significant associations. CONCLUSIONS: Adherence to a high-protein, high-fiber diet after sleeve gastrectomy may enhance surgical success by improving total weight loss and preventing excessive fat-free mass loss.

Impact of carbohydrate quantity and quality on maternal and pregnancy outcomes in gestational diabetes mellitus: A systematic review and meta-analysis.

OBJECTIVE: To evaluate the impact of carbohydrate quantity and quality on maternal and pregnancy outcomes in gestational diabetes mellitus. METHODS: Using a pre-defined search strategy, two researchers systematically searched MEDLINE, CINAHL Plus, and PubMed for randomized controlled trials comparing low-carbohydrate, low-glycaemic index, or low-glycaemic load diets with usual care in gestational diabetes mellitus. Mean differences and risk ratios were extracted. RESULTS: Thirteen studies with 877 participants were included. Low-carbohydrate diet did not significantly differ from usual care for fasting blood glucose (3 studies; mean difference: 1.60 mmol/L; 95 % confidence interval: -1.95, 5.15), insulin requirement (2 studies; risk ratio: 1.01; 95 % confidence interval: 0.31, 3.05), birthweight (4 studies; mean difference: -0.23 kg; 95 % confidence interval: -1.90, 1.45), caesarean delivery (5 studies; risk ratio: 1.11; 95 % confidence interval: 0.66, 1.85), macrosomia (3 studies; risk ratio: 0.35; 95 % confidence interval: 0.00, 2130.64), large-for-gestational-age (2 studies; risk ratio: 0.46; 95 % confidence interval: 0.03, 7.20), and small-for-gestational-age infants (2 studies; risk ratio: 0.94; 95 % confidence interval: 0.00, 231.18). Low-glycaemic index diet did not significantly differ from usual care for the above outcomes either. However, low-glycaemic load diet reduced macrosomia risk (2 studies; risk ratio: 0.51; 95 % confidence interval: 0.43, 0.59). CONCLUSIONS: Low-carbohydrate and low-glycaemic index diets do not differ from usual care for most maternal and foetal outcomes in gestational diabetes mellitus. But low-glycaemic load diet may reduce macrosomia risk.

Different dietary carbohydrate component intakes and long-term outcomes in patients with NAFLD: results of longitudinal analysis from the UK Biobank.

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.

Low-Quality Carbohydrate Intake Is Associated With a Higher Prevalence of Metabolic Syndrome: The AWHS Study.

CONTEXT: The relationship between carbohydrate quality intake and metabolic syndrome (MetS) is of growing interest. OBJECTIVE: We aimed to assess the association between the adherence to a dietary carbohydrate quality index (CQI) with the occurrence of MetS in a Spanish cohort of working adults. METHODS: A cross-sectional study was conducted of 2316 middle-aged men, aged 50.9 (SD 3.9) years, with no previous cardiovascular disease, and pertaining to the Aragon Workers' Health Study (AWHS) cohort. Diet was collected with a 136-item semiquantitative food-frequency questionnaire. The CQI (range 4-15) was based on: dietary fiber intake, a low glycemic index, the ratio of whole grains/total grains, and the ratio of solid carbohydrates/total carbohydrates. The higher the CQI, the healthier the diet. MetS was defined by using the harmonized National Cholesterol Education Programme-Adult Treatment Panel III (NCEP-ATP III) definition. The associations across 3-point categories of the CQI and the presence of MetS were examined using logistic regression. RESULTS: An inverse and significant association between the CQI and MetS was found. Fully adjusted odds ratios (ORs) for MetS risk among participants in the 10- to 12-point category (second highest CQI category) was 0.64 (95% CI, 0.45-0.94), and in the 13- to 15-point category (highest category) was 0.52 (95% CI, 0.30-0.88), when compared with the 4- to 6-point category (lowest category). Participants with 10 to 12 and 13 to 15 points on the CQI showed a lower risk of hypertriglyceridemia: OR 0.61 (95% CI, 0.46-0.81), and 0.48 (95% CI, 0.32-0.71) respectively. CONCLUSION: Among middle-aged men, a higher adherence to a high-quality carbohydrate diet is associated with a lower prevalence of MetS. Triglyceridemia is the MetS component that contributed the most to this reduced risk.

Associations between types and sources of dietary carbohydrates and liver fat: a UK Biobank study.

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.

Dietary carbohydrate quality index and cardio-metabolic risk factors.

Introduction: Improving the quality of diet is known as one of the practical ways to reduce cardio-metabolic risk factors (CMRFs). The carbohydrate quality index (CQI) is a relatively new index to evaluate diet quality. It is calculated based on the ratio of solid carbohydrates to total carbohydrates, dietary fibre intake, glycemic index and the ratio of whole grains to total grains. This systematic review and meta-analysis was designed to investigate the association between dietary CQI and CMRFs. Methods: In this systematic review, some international databases, including Scopus, PubMed, EMBASE, Web of Science, and Google Scholar up to July 2022, were searched according to appropriate keywords. All observational studies with an English full text assessing the association between the dietary CQI and CMRFs were included. Two researchers independently extracted the data and assessed the quality of the articles with the Newcastle-Ottawa Scale. Random/fixed-effect meta-analysis was used to pool standardized mean difference (SMD) as an effect size. Results: 11 studies with a total of 63962 subjects were found to be eligible and included in the qualitative synthesis; only BMI, WC and metabolic syndrome reached the threshold of 3 reports with the same effect size and thus only 5 were included in the meta-analysis. The main finding of the included studies was that there were inverse associations between CQI and CMRFs, mainly obesity, glucose metabolism indices, and blood pressure. In the five studies included in the random effect meta-analysis, the association between CQI and body mass index (SMD: 0.45, 95%CI: -0.12, 1.01), waist circumference (SMD: -0.09, 95%CI: -0.34, 0.15) and metabolic syndrome (SMD: 0.63, 95%CI: -0.01, 1.28) was not statistically significant. Conclusion: Although the qualitative findings support the positive association of CQI with CMRFs, the evidence is insufficient to conclude robust findings. Further observational and interventional studies are needed to clearly elucidate this association.

Carbohydrate confusion and dietary patterns: unintended public health consequences of "food swapping".

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.

Association between the Carbohydrate Quality Index (CQI) and Nutritional Adequacy in a Pediatric Cohort: The SENDO Project.

Suboptimal micronutrient intake in children remains a public health concern around the world. This study examined the relationship between a previously defined dietary carbohydrate quality index (CQI) and the risk of micronutrient intake inadequacy in a pediatric cohort of Spanish preschoolers. Children aged 4-5 years old were recruited at their medical center or at school, and information on sociodemographic, dietary, and lifestyle variables were collected through a self-administered online questionnaire. Dietary information was obtained from a validated 147-item semi-quantitative food frequency questionnaire. We calculated the CQI and categorized participants into quartiles according to their scores. We assessed the intakes of 20 micronutrients and evaluated the probability of intake inadequacy by using the estimated average requirement cut-off point. Generalized estimating equations were used to adjust for potential confounders and account for the intra-cluster correlations between siblings. The adjusted proportions of children with an inadequate intake of ≥three micronutrients were 23%, 12%, 11%, and 9% in the first, second, third, and fourth quartiles of the CQI, respectively. Children in the highest quartile of the CQI had 0.22-fold lower odds (95% CI 0.10-0.48) of having ≥three inadequate micronutrient intakes than their peers in the lowest quartile. These findings reinforce the relevance of carbohydrate quality in children's diets.

Macronutrient quality and the incidence of metabolically unhealthy phenotypes in adults with normal weight and overweight/obesity.

OBJECTIVE: We aimed to investigate the associations of macronutrient quality indices with the incident metabolically unhealthy normal weight (MUNW) and metabolically unhealthy overweight/obesity (MUO) phenotypes. METHODS: This prospective study included 512 metabolically healthy normal weight and 787 metabolically healthy overweight/obese adults from the third study examination of the Tehran Lipid and Glucose Study. The participants were followed through the sixth study examination. Diet was measured with a food frequency questionnaire. The macronutrient quality index (MQI), carbohydrate quality index (CQI), fat quality index (FQI), and healthy plate quality index (HPPQI) were calculated. Hazard ratio (HR) and 95 % confidence interval (95 % CI) were estimated for incident unhealthy phenotypes using Cox regression. RESULTS: After controlling all possible confounding factors, a one-point higher HPPQI was linked to a 28 % lower risk of MUNW (HR = 0.72; 95 % CI = 0.59, 0.87). Compared to the lowest quartile, the incident MUNW was also lower in the two last quartiles of the HPPQI. A one-unit increase in MQI was associated with a 5 % lower incident MUO (HR = 0.95; 95 % CI = 0.92, 0.99). The incident MUO was also higher for the highest compared to the lowest MQI quartile. In quartiles 2-4 of the HPPQI, incident MUO was lower with respective HRs (95 % CI) of 0.71 (0.54, 0.93), 0.60 (0.45, 0.80), and 0.66 (0.50, 0.86) in the fully-adjusted model. CONCLUSIONS: A higher overall macronutrient quality was independently associated with a lower incident MUO. A higher dietary protein quality was related to a lower risk for MUNW and MUO.

Carbohydrate quality, fecal microbiota and cardiometabolic health in older adults: a cohort study.

The 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.

Preoperative Carbohydrate Quality Index Is Related to Markers of Glucose Metabolism 12 Months After Roux-en-Y Gastric Bypass.

OBJECTIVE: The role of carbohydrates in weight loss in patients undergoing bariatric surgery (BS) remains poorly understood. Therefore, this study aimed to verify the relationship of the carbohydrate quality index (CQI) with weight loss and cardiometabolic risk markers up to 1 year after BS. MATERIAL AND METHODS: This study included 50 patients with obesity undergoing Roux-en-Y gastric bypass. Data collection was performed preoperatively and 3 and 12 months after surgery. The foods consumed were documented using a 24-h food recall in 3 days. The CQI was calculated considering the following parameters: dietary fiber intake, sugar level; whole grains: proportion of total grains; solid carbohydrate: total carbohydrate ratio. RESULTS: From the total study sample, 58 participants were followed up for 3 months, and eight participants dropped out of the study. The remaining 50 patients were followed up for 12 months. Subjects were classified into tertiles according to the index score. A 1-unit increase in CQI was associated with a -1.02 decrease in insulin concentrations at 12 months and a -1.04 decrease in HOMA-IR. Concerning the total sample, the median of the CQI was 8 points and did not change at 3 and 12 months after surgery, but there was an improvement in some components of the index. CONCLUSION: The data suggest that the quality of carbohydrates can interfere with markers of insulin resistance after BS and the quality of carbohydrates is a point to be guided in patients undergoing BS.

Dietary carbohydrate quality index (CQI), cardio-metabolic risk factors and insulin resistance among adults with obesity.

BACKGROUND: Metabolic syndrome (MetS), as a cluster of cardiometabolic risk factors, is a global public health concern due to its increasing prevalence. Considering the previous evidence of the association between carbohydrate quality and cardiometabolic risk factors, our study was aimed to evaluate any possible association between carbohydrate quality index (CQI) and cardiometabolic risk factors among obese adults. METHODS: In this cross-sectional study, 336 apparently healthy individuals with obesity were participated. Dietary intake was assessed by a semi-quantitative Food Frequency Questionnaire (FFQ), including 168 food items validated for the Iranian population. CQI was calculated with three components of solid carbohydrates to total carbohydrates ratio, dietary fiber intake, and dietary glycemic index (GI). Body composition was determined by bioelectrical impedance analysis (BIA). Blood pressure was measured by sphygmomanometer and enzymatic methods were used to evaluate serum lipid, glucose, and insulin concentrations. RESULTS: Subjects in the third quartile of CQI had significantly lower systolic blood pressure (SBP) (P = 0.03) and diastolic blood pressure (DBP) (P = 0.01). Participants in the higher quartiles of CQI had more intake of energy, carbohydrates, fat, saturated fatty acid (SFA), and mono-saturated fatty acid (MUFA) (P < 0.05). Moreover, the homeostasis model assessment of insulin resistance (HOMA-IR) was decreased in the second quartile of CQI [odds ratio (OR) = 0.146, P = 0.01) after adjustment for age, body mass index (BMI), sex, physical activity, socioeconomic status (SES) and energy intake. CONCLUSION: According to our findings, a higher quality of dietary carbohydrates, determined by CQI, could be associated with a lower risk of hypertension.