Relationship of glycaemic index with cardiovascular risk factors: analysis of the National Diet and Nutrition Survey for people aged 65 and older

Perspective: Does Glycemic Index Matter for Weight Loss and Obesity Prevention? Examination of the Evidence on "Fast" Compared with "Slow" Carbs

High-glycemic index (high-GI) foods (so-called fast carbs) have been hypothesized to promote fat storage and increase risk of obesity. To clarify whether dietary GI impacts body weight, we searched PubMed and the Cochrane Database of Systematic Reviews for observational studies reporting associations between BMI and dietary GI, and for meta-analyses of randomized controlled trials (RCTs) comparing low-GI and high-GI diets for weight loss. Data on 43 cohorts from 34 publications, totaling 1,940,968 adults, revealed no consistent differences in BMI when comparing the highest with the lowest dietary GI groups. In the 27 cohort studies that reported results of statistical comparisons, 70% showed that BMI was either not different between the highest and lowest dietary GI groups (12 of 27 cohorts) or that BMI was lower in the highest dietary GI group (7 of 27 cohorts). Results of 30 meta-analyses of RCTs from 8 publications demonstrated that low-GI diets were generally no better than high-GI diets for reducing body weight or body fat. One notable exception is that low-GI diets with a dietary GI at least 20 units lower than the comparison diet resulted in greater weight loss in adults with normal glucose tolerance but not in adults with impaired glucose tolerance. While carbohydrate quality, including GI, impacts many health outcomes, GI as a measure of carbohydrate quality appears to be relatively unimportant as a determinant of BMI or diet-induced weight loss. Based on results from observational cohort studies and meta-analyses of RCTs, we conclude that there is scant scientific evidence that low-GI diets are superior to high-GI diets for weight loss and obesity prevention.

Macronutrient Determinants of Obesity, Insulin Resistance and Metabolic Health

Obesity caused by the overconsumption of calories has increased to epidemic proportions. Insulin resistance is often associated with an increased adiposity and is a precipitating factor in the development of cardiovascular disease, type 2 diabetes, and altered metabolic health. Of the various factors contributing to metabolic impairments, nutrition is the major modifiable factor that can be targeted to counter the rising prevalence of obesity and metabolic diseases. However, the macronutrient composition of a nutritionally balanced "healthy diet" are unclear, and so far, no tested dietary intervention has been successful in achieving long-term compliance and reductions in body weight and associated beneficial health outcomes. In the current review, we briefly describe the role of the three major macronutrients, carbohydrates, fats, and proteins, and their role in metabolic health, and provide mechanistic insights. We also discuss how an integrated multi-dimensional approach to nutritional science could help in reconciling apparently conflicting findings.

The Impact of Dietary Glycemic Index and Glycemic Load on Postprandial Lipid Kinetics, Dyslipidemia and Cardiovascular Risk

Many recent studies have acknowledged postprandial hypetriglyceridemia as a distinct risk factor for cardiovascular disease. This dysmetabolic state is the result of the hepatic overproduction of very low-density lipoproteins (VLDLs) and intestinal secretion of chylomicrons (CMs), which leads to highly atherogenic particles and endothelial inflammation. Postprandial lipid metabolism does not only depend on consumed fat but also on the other classes of nutrients that a meal contains. Various mechanisms through which carbohydrates exacerbate lipidemia have been identified, especially for fructose, which stimulates de novo lipogenesis. Glycemic index and glycemic load, despite their intrinsic limitations, have been used as markers of the postprandial glucose and insulin response, and their association with metabolic health and cardiovascular events has been extensively studied with contradictory results. This review aims to discuss the importance and pathogenesis of postprandial hypertriglyceridemia and its association with cardiovascular disease. Then, we describe the mechanisms through which carbohydrates influence lipidemia and, through a brief presentation of the available clinical studies on glycemic index/glycemic load, we discuss the association of these indices with atherogenic dyslipidemia and address possible concerns and implications for everyday practice.

The association of glycemic index and glycemic load with elevated blood pressure in Iranian women

Introduction: Dietary intake is a risk factor related to elevated blood pressure (EBP). Few studies have investigated an association of dietary glycemic index (GI) and glycemic load (GL) with the EBP. The aim of the current study was to examine the association of dietary GI and GL with the EBP among a group of healthy women.

Methods: This population-based cross-sectional study was conducted on 306 healthy women. Dietary GI and GL were measured using a validated semi-quantitative food frequency questionnaire (FFQ). Blood pressure (BP) was measured twice by a mercury sphygmomanometer from the right arm. Anthropometric measurements were also assessed according to the standard protocols.

Results: Before controlling for potential confounders, no significant association was seen between dietary GI/GL and SBP/DBP. Also after controlling for potential confounders, the associations did not change between dietary GI and SBP (odds ratio [OR]: 0.96; 95% CI: 0.42-2.17, P = 0.87), between GI and DBP (OR: 0.72; 95% CI: 0.35-1.45, P = 0.37), as well as between GL and SBP (OR: 1.04; 95% CI: 0.43-2.49, P = 1.00) and between GL and DBP (OR: 1.20; 95% CI: 0.56-2.00, P = 0.61). In a stratified analysis by obesity and overweight, differences between tertiles of GI were not significant (OR: 0.75; 95% CI: 0.42-1.31, P = 0.31), even after adjustment for the potential confounders (OR: 1.54; 95% CI: 0.70-3.40, P = 0.26).

Conclusion: This study did not show a significant association between dietary GI/GL and the risk of high SBP/DBP. In addition, no significant association was found between dietary GI/GL and odds of overweight or obesity in adult women.

Relevance of the Glycemic Index and Glycemic Load for Body Weight, Diabetes, and Cardiovascular Disease

Despite initial enthusiasm, the relationship between glycemic index (GI) and glycemic response (GR) and disease prevention remains unclear. This review examines evidence from randomized, controlled trials and observational studies in humans for short-term (e.g., satiety) and long-term (e.g., weight, cardiovascular disease, and type 2 diabetes) health effects associated with different types of GI diets. A systematic PubMed search was conducted of studies published between 2006 and 2018 with key words glycemic index, glycemic load, diabetes, cardiovascular disease, body weight, satiety, and obesity. Criteria for inclusion for observational studies and randomized intervention studies were set. The search yielded 445 articles, of which 73 met inclusion criteria. Results suggest an equivocal relationship between GI/GR and disease outcome. The strongest intervention studies typically find little relationship among GI/GR and physiological measures of disease risk. Even for observational studies, the relationship between GI/GR and disease outcomes is limited. Thus, it is unlikely that the GI of a food or diet is linked to disease risk or health outcomes. Other measures of dietary quality, such as fiber or whole grains may be more likely to predict health outcomes. Interest in food patterns as predictors of health benefits may be more fruitful for research to inform dietary guidance.

Associations of dietary glycaemic index and glycaemic load with food and nutrient intake and general and central obesity in British adults

Inconsistent associations between dietary glycaemic index (GI) and glycaemic load (GL) and body fatness may be partly due to differences in the underlying dietary patterns or energy under-reporting. In the present study, we examined the cross-sectional associations of dietary GI and GL with food and nutrient intake and general and central obesity, accounting for energy under-reporting. The subjects were 1487 British adults aged 19-64 years. Dietary intake was assessed using a 7 d weighed dietary record. Breads and potatoes were the positive predictive foods for dietary GI, while fruit, other cereals and dairy products were the negative predictors. These foods were similarly identified in the analysis of only acceptable reporters (AR; ratio of reported energy intake:estimated energy requirement within 0·665-1·335) and under-reporters (UR; ratio < 0·665). Dietary GL was closely correlated with carbohydrate intake. Multiple linear regression analyses showed that dietary GI was independently associated with a higher risk of general obesity (BMI ≥ 30 kg/m²) and central obesity (waist circumference ≥ 102 cm in men and ≥ 88 cm in women). Dietary GL was also associated with general (only women) and central obesity. Similarly, in the analysis of AR, the GI showed positive associations with general and central obesity, and, only in women, the GL showed positive associations with general and central obesity. Conversely, in the analysis of UR, the associations were generally weaker and many of them failed to reach statistical significance. In conclusion, we found independent positive associations of dietary GI and GL with general and central obesity in British adults.

Association of glycemic load with cardiovascular disease risk factors: the Women's Health Initiative Observational Study

OBJECTIVE

Associations between dietary glycemic load (GL) and cardiovascular disease risk factors, including plasma lipoprotein/lipid levels, blood pressure, and glucose metabolism factors, in the Women's Health Initiative Observational Study were examined.

METHODS

A random sample of 878 Observational Study participants (postmenopausal women 50-79 y of age) with baseline blood measurements (647 white, 104 black, 127 Hispanic) was included. Dietary GL was estimated from baseline food-frequency questionnaires, which assessed dietary intake over the previous 3 mo. At the baseline visit, participants completed demographic and health habit questionnaires, fasting blood samples were collected, anthropometric measurements were completed, and blood pressure was assessed.

RESULTS

In all participants combined, GL was inversely associated with high-density lipoprotein cholesterol (P for trend = 0.004) and positively associated with log(10)-transformed triacylglycerols (P = 0.008). Although there were no statistically significant interactions of race/ethnicity with associations between GL and cardiovascular disease risk factors, stratified results were suggestive, showing that GL was positively associated with total cholesterol (P = 0.018) and low-density lipoprotein cholesterol (P = 0.038) in Hispanics. In white subjects, there was a trend of reduced high-density lipoprotein cholesterol with higher GL (P = 0.003), whereas GL was positively associated with log(10)-transformed triacylglycerols (P = 0.015). Associations between GL and high-density lipoprotein cholesterol and between GL and triacylglycerols also differed by body mass index, although the interactions were not statistically significant.

CONCLUSION

Among these generally healthy postmenopausal women, GL was associated with high-density lipoprotein cholesterol and triacylglycerols. Suggestive effects of race/ethnicity and body mass index on these associations need to be confirmed in larger studies.

Consumption of sugars and body weight

The role of dietary sugars in the current obesity epidemic is much debated and opposing views can be found in the lay as well as scientific literature. Here we have reviewed the recent scientific literature on consumption of sugars and body weight. Main focus was on three questions: (i) What is the evidence that intake of dietary sugars is associated with higher body weight than intake of non-sugar carbohydrates? (ii) What is the evidence that sugars in liquid form are associated with higher body weight than sugars in solid form? (iii) What is the evidence that diets with a low glycaemic index (GI) or glycaemic load (GL) are associated with lower body weight than diets high in GI or GL? We conclude that (i) there is insufficient evidence that an exchange of sugar for non-sugar carbohydrates in the context of a reduced-fat ad libitum diet or energy-restricted diet results in lower body weights; (ii) observational studies suggest a possible relationship between consumption of sugar-sweetened beverages and body weight, but there is currently insufficient supporting evidence from randomized controlled trials of sufficient size and duration; (iii) at this moment there is insufficient evidence to support a difference between liquid and solid sugar intake in body-weight control and (iv) there is some, although not consistent, evidence for a lower body weight on diets with a lower GL, but the effect is likely to be small. There is currently no convincing evidence for a role of GI independent of GL.

Should glycemic index and glycemic load be considered in dietary recommendations?

High glycemic index (GI) and glycemic load (GL) have been proposed to be associated with increased risk of lifestyle diseases. Since protein intake varies little in humans, adherence to the common recommendation to reduce fat intake probably leads to increases in carbohydrate intake, which emphasizes the need to investigate the effects of carbohydrate on diet-related conditions and diseases. This review examines the epidemiological literature linking GI and GL to heart disease, insulin sensitivity, type 2 diabetes, dyslipidemia, and obesity among initially healthy people. The evidence for associations between GI and particularly GL and health among free-living populations is mixed. Only the positive association between GI and development of type 2 diabetes was consistent across cross-sectional and longitudinal studies for both sexes. Low GI/GL may protect against heart disease in women, and cross-sectional studies indicate low GI/GL may reduce high-density-lipoprotein cholesterol and triacylglycerol levels in both sexes. Based on the evidence found in this review, it seems premature to include GI/GL in dietary recommendations.

Glycemic index and glycemic load in relation to food and nutrient intake and metabolic risk factors in a Dutch population

BACKGROUND

Previous studies on the glycemic index (GI) and glycemic load (GL) reported inconsistent findings on their association with metabolic risk factors. This may partly have been due to differences in underlying dietary patterns.

OBJECTIVE

We aimed to examine the association of GI and GL with food and nutrient intake and with metabolic risk factors including blood glucose, insulin, lipids, and high-sensitivity C-reactive protein (CRP).

DESIGN

The study entailed cross-sectional analyses of data from 2 joint observational studies, the CoDAM Study and the Hoorn Study.

RESULTS

In total, 974 subjects aged 42-87 y were included in the study. The mean (+/-SD) GI was 57 +/- 4 and the mean GL was 130 +/- 39. Dairy products, potatoes and other tubers, cereal products, and fruit were the main predictive food groups for GI. GL was closely correlated with intake of total carbohydrates (r(s) = 0.97), which explained >95% of the variation in GL. After adjustment for potential confounders, GI was significantly inversely associated with HDL cholesterol and positively associated with fasting insulin, the homeostasis model assessment index of insulin resistance, the ratio of total to HDL cholesterol, and CRP. No association was observed between GL and any of the metabolic risk factors, except for a borderline significant positive association with CRP.

CONCLUSIONS

In this population, a low-GI diet, which is high in dairy and fruit but low in potatoes and cereals, is associated with improved insulin sensitivity and lipid metabolism and reduced chronic inflammation. GL is highly correlated with carbohydrate intake and is not clearly associated with the investigated metabolic risk factors.