Changes in dietary glycemic index and glycemic load in Australian adults from 1995 to 2012

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 effect of steamed potato-wheat bread intake on weight, lipids, glucose, and urinary Na+/K+: A randomized controlled trial in Chinese adults

Steamed potato bread has received much attention from nutritionists and agriculturalists since it became a staple food of China in 2015. Epidemiological studies have indicated that potatoes may cause diabetes and hypertension, but few trials have evaluated this effect. Through a clinical trial, we evaluated the effect of steamed potato bread intake on adults. In total, 49 and 30 individuals were assigned to the intervention and control groups, respectively. Potato-wheat bread (raw wheat flour and cooked potato flour in the ratio 3:7) and steamed wheat bread (100% raw wheat flour) were provided to the intervention and control groups, respectively, once a day for 4 weeks. Compared with the control group, the intervention group showed significant net changes in weight (−0.6 kg; 95% confidence interval [CI]: −1.2, −0.1; p = 0.016), body mass index (BMI, −0.2 kg/m²; 95% CI: −0.4, −0.1; p = 0.020), low-density lipoprotein cholesterol (LDL-c, −0.22 mmol/L; 95% CI: −0.49, −0.01; p = 0.035), and the urinary level of Na⁺/K⁺ (−2.4; 95% CI: −4.1, −0.7; p = 0.007). In conclusion, the steamed potato-wheat bread intake for 4 weeks resulted in decreases in weight, BMI, LDL-c, and the urinary Na⁺/K⁺ level among Chinese adults.

Dietary Glycaemic Index Labelling: A Global Perspective

The glycaemic index (GI) is a food metric that ranks the acute impact of available (digestible) carbohydrates on blood glucose. At present, few countries regulate the inclusion of GI on food labels even though the information may assist consumers to manage blood glucose levels. Australia and New Zealand regulate GI claims as nutrition content claims and also recognize the GI Foundation’s certified Low GI trademark as an endorsement. The GI Foundation of South Africa endorses foods with low, medium and high GI symbols. In Asia, Singapore’s Healthier Choice Symbol has specific provisions for low GI claims. Low GI claims are also permitted on food labels in India. In China, there are no national regulations specific to GI; however, voluntary claims are permitted. In the USA, GI claims are not specifically regulated but are permitted, as they are deemed to fall under general food-labelling provisions. In Canada and the European Union, GI claims are not legal under current food law. Inconsistences in food regulation around the world undermine consumer and health professional confidence and call for harmonization. Global provisions for GI claims/endorsements in food standard codes would be in the best interests of people with diabetes and those at risk.

Destigmatizing Carbohydrate with Food Labeling: The Use of Non-Mandatory Labelling to Highlight Quality Carbohydrate Foods

Dietary carbohydrates are components of healthy foods, but many carbohydrate foods have recently been stigmatized as primary causes of diet-related risk factors for chronic disease. There is an opportunity to enhance efforts within the food landscape to encourage the consumption of higher quality carbohydrate foods. The use of labelling is one strategy that permits consumers to identify healthy carbohydrate foods at the point-of-purchase. This review discusses the regulatory frameworks and examples of associated non-mandatory food labelling claims that are currently employed to highlight healthy carbohydrate foods to consumers. The existing labelling frameworks discussed here align with established measures of carbohydrate quality, such as 1. dietary fibre nutrient content claims and associated dietary fibre-based health claims; 2. the presence of whole carbohydrate foods and ingredients that are intact or reconstituted, such as whole grains; and 3. low glycemic index and glycemic response claims. Standards from Codex Alimentarius, and regulations from Australia and New Zealand, Canada, Europe, and the United States will be used to illustrate the means by which food labelling can be used by consumers to identify quality carbohydrate foods.

Dietary Glycemic Index and Glycemic Load Are Not Associated with the Metabolic Syndrome in Lebanese Healthy Adults: A Cross-Sectional Study

High dietary glycemic index (GI) and glycemic load (GL) were suggested to increase the risk of metabolic syndrome (MetS). This study aims to estimate dietary GI and GL in a sample of healthy Lebanese adults and examine their association with MetS and its individual abnormalities. The study uses data from a community-based survey of 501 Lebanese urban adults. Dietary intake was assessed using a food frequency questionnaire. Biochemical, anthropometric, and blood pressure measurements were obtained. Subjects with previous diagnosis of chronic disease, metabolic abnormalities, or with incomplete data or implausible energy intakes were excluded, yielding a sample of 283. Participants were grouped into quartiles of GI and GL. Multivariate logistic regression analyses were performed. Average dietary GI and GL were estimated at 59.9 ± 8 and 209.7 ± 100.3. Participants belonging to the highest GI quartile were at increased risk of having MetS (odds ratio (OR) = 2.251, 95% CI:1.120–4.525) but this association lost significance with further adjustments. Those belonging to the second quartile of GI had significantly lower odds of having hyperglycemia (OR: 0.380, 95% CI:0.174–0.833). No associations were detected between GL and MetS. The study contributes to the body of evidence discussing the relationship between GI, GL, and MetS, in a nutrition transition context.

Carbohydrate restriction in midlife is associated with higher risk of type 2 diabetes among Australian women: A cohort study

BACKGROUND AND AIMS

Low-carbohydrate diets (LCDs) are increasingly popular but may be nutritionally inadequate. We aimed to examine if carbohydrate restriction in midlife is associated with risk of developing type 2 diabetes (T2DM), and if this association differs by previous gestational diabetes (GDM) diagnosis.

METHODS AND RESULTS

Dietary intake was assessed for 9689 women from the Australian Longitudinal Study on Women's Health in 2001 (aged 50-55) and 2013 (aged 62-67) via validated food frequency questionnaires. Average long-term carbohydrate restriction was assessed using a low-carbohydrate diet score (highest quartile (Q4) indicating lowest proportion of energy from carbohydrates). Incidence of T2DM between 2001 and 2016 was self-reported at 3-yearly surveys. Log-binomial regression was used to estimate relative risks (RR) and 95% CIs. During 15 years of follow-up, 959 women (9.9%) developed T2DM. Carbohydrate restriction was associated with T2DM after adjustment for sociodemographic factors, history of GDM diagnosis and physical activity (Q4 vs Q1: RR 1.27 [95% CI 1.10, 1.48]), and this was attenuated when additionally adjusted for BMI (1.10 [0.95, 1.27]). Carbohydrate restriction was associated with lower consumption of fruit, cereals and high-fibre bread, and lower intakes of these food groups were associated with higher T2DM risk. Associations did not differ by history of GDM (P for interaction >0.15).

CONCLUSION

Carbohydrate restriction was associated with higher T2DM incidence in middle-aged women, regardless of GDM history. Health professionals should advise women to avoid LCDs that are low in fruit and grains, and to consume a diet in line with current dietary recommendations.

Rice and Prevention of Type 2 Diabetes: Narrative Review of Epidemiologic Evidene

Inspite that rice is a main staple and heaviliy consumed in most of Asian populations, health effect of rice has been less examined in nutritional epidemiologic studies compared to those of foods such as fruits, vegetables, meats and fish. Some recent meta-analyses that collected prospective cohort studies reported the associations between rice intake and incidence of and mortality from some chronic diseases especially type 2 diabetes. Concerning type 2 diabetes, the results are remarkably different between white (polished) rice and brown (unpolished) rice: the former increased and the latter decreased the risk. This difference may partly be explained by the different types and amounts of dietary fiber and different scores of dietary glycemic index. However, the results on dietary fiber and dietary glycemic index were not necessarily consistent. Indirect effect of rice intake has been examined through the studies on association of dietary patterns and breakfast skipping to type 2 diabetes. However, most of the results were inconclusive. Simple and straightforward judgement on the effect of rice to type 2 diabete should be avoided, and more nutritional epidemiologic studies with high research quality, including basic studies on dietary assessment, are needed, especially in Asian populations.

Maternal Dietary Glycemic and Insulinemic Indexes Are Not Associated with Birth Outcomes or Childhood Adiposity at 5 Years of Age in an Irish Cohort Study

BACKGROUND

High maternal dietary glycemic index (GI) and glycemic load (GL) may be associated with adverse offspring birth and postnatal adiposity outcomes through metabolic programming, but the evidence thus far, mainly from studies conducted in high-risk pregnant populations, has been inconclusive. No study has examined the influence of maternal insulin demand [measured by food insulinemic index (II) and insulinemic load (IL)] on offspring outcomes.

OBJECTIVES

We investigated associations between maternal GI, GL, II, and IL and offspring birth outcomes and postnatal adiposity in a general pregnant population.

METHODS

The study was based on data from 842 mother-child pairs from the Lifeways prospective cohort study in Ireland. Through the use of standard methodology, maternal GI, GL, II, and IL were derived from dietary information obtained via a validated food-frequency questionnaire in early pregnancy (12-16 wk). Birth outcomes were abstracted from hospital records. At 5-y follow-up, children's body mass index (BMI) and waist circumference were measured. Associations were assessed through the use of multivariable-adjusted regression analysis.

RESULTS

Mothers had a mean ± SD age of 30.3 ± 5.7 y and a mean BMI (kg/m2) of 23.9 ± 4.2. The mean ± SD for dietary glycemic and insulinemic indexes were: GI = 58.9 ± 4.4; GL = 152 ± 49; II = 57.4 ± 14.5; IL = 673 ± 267. After adjustment for confounders, no consistent associations were observed between maternal GI, GL, II, and IL and birth outcomes including birth weight, macrosomia, gestational age, and postterm births. Similarly, no association was observed with BMI and waist circumference z scores and childhood obesity (general and central) at 5-y follow-up. There was no evidence of a nonlinear relation between the studied indexes and outcomes.

CONCLUSIONS

We observed no clear relation between maternal GI, GL, II, and IL and offspring birth outcomes and childhood obesity in a general pregnant population.

Macronutrient Composition of the Australian Population's Diet; Trends from Three National Nutrition Surveys 1983, 1995 and 2012

Although the role of individual macronutrients in the development of obesity remains controversial, changes in macronutrient composition of the diet may have played a causal role in the obesity epidemic. The aim of this analysis was to determine the percentage energy (%E) for protein, carbohydrate and fat of Australian adults' diets over time. Cross-sectional, national nutrition surveys from 1983, 1995 and 2012 assessed diet using one 24 h recall. The prevalence of obesity increased between each survey, from 9.6% to 19.7% and 27.7%. Protein (%E) differed between each survey and contributed 17.7%, 16.8% and 18.3% energy in 1983, 1995 and 2012, respectively (p < 0.001). Carbohydrate (%E) increased from 40.0% in 1983 to 44.9% in 1995 (p < 0.001), with no change in dietary fibre but declined in 2012 to 43.1%. Fat (%E) declined between each survey from 35.3%, 31.9%, to 30.9%, respectively (p < 0.001). Alcohol (%E) has declined for younger adults and men but intake increased for women aged >45 years. Prospective cohort studies with comprehensive assessment of foods consumed, together with measurements of weight and height, will advance the understanding of the relationship between macronutrients and changes in body weight and obesity.

The Carbohydrate-Insulin Model of Obesity: Beyond "Calories In, Calories Out"

Despite intensive research, the causes of the obesity epidemic remain incompletely understood and conventional calorie-restricted diets continue to lack long-term efficacy. According to the carbohydrate-insulin model (CIM) of obesity, recent increases in the consumption of processed, high-glycemic-load carbohydrates produce hormonal changes that promote calorie deposition in adipose tissue, exacerbate hunger, and lower energy expenditure. Basic and genetic research provides mechanistic evidence in support of the CIM. In animals, dietary composition has been clearly demonstrated to affect metabolism and body composition, independently of calorie intake, consistent with CIM predictions. Meta-analyses of behavioral trials report greater weight loss with reduced-glycemic load vs low-fat diets, though these studies characteristically suffer from poor long-term compliance. Feeding studies have lacked the rigor and duration to test the CIM, but the longest such studies tend to show metabolic advantages for low-glycemic load vs low-fat diets. Beyond the type and amount of carbohydrate consumed, the CIM provides a conceptual framework for understanding how many dietary and nondietary exposures might alter hormones, metabolism, and adipocyte biology in ways that could predispose to obesity. Pending definitive studies, the principles of a low-glycemic load diet offer a practical alternative to the conventional focus on dietary fat and calorie restriction.