Dietary glycaemic index and glycaemic load in a rural elderly population (60–74 years of age) and their relationship with cardiovascular risk factors

Glycemic index, glycemic load, dietary insulin index, and dietary insulin load in relation to cardiometabolic risk factors among participants with atherosclerosis: a cross-sectional study

BACKGROUND

We examined the cross-sectional associations of dietary Glycemic Index (GI), Glycemic Load (GL), Dietary Insulin Index (DII), and Dietary Insulin Load (DIL) with cardiovascular disease (CVD) factors in subjects with atherosclerosis.

METHODS

The present cross-sectional study was conducted on subjects with atherosclerosis. Regular dietary intake was assessed using a 168-item semi-quantitative food frequency questionnaire (FFQ) and GI, GL, DIL, and DII were also calculated. Odds Ratio (OR) and 95% Confidence Intervals (CIs) were estimated for general and central obesity according to the GI, GL, DII, and DIL.

RESULTS

According to the continuous score of GL, there was a significant positive association between GL and central obesity for women in all models. Regarding the association between DIL score and biochemical variables, there was a significant positive association between Na and Aspartate transaminase (AST) with DII. Moreover, there was a significant positive association between LDL-c(p = 0.03) and AST (p = 0.04)with DIL score in all 3 models.

CONCLUSION

In this study, GL was associated with greater odds of central obesity in women, but not in men. Neither dietary DII nor DIL was associated with BMI and central obesity. GI, GL, DII, and DIL were significantly associated with some CVD risk biomarkers in subjects with atherosclerosis.

Dietary glycemic load and its association with glucose metabolism and lipid profile in young adults

BACKGROUND AND AIM

To evaluate the association of Glycemic Load (GL) with glucose metabolism and blood lipids among young adults.

METHODS AND RESULTS

This study included 1538 participants (51% females), evaluated at 21 years of age as part of the EPITeen cohort. The GL of each individual was obtained from the assessment of their dietary intake by using a 86-item semi-quantitative food frequency questionnaire. The evaluation included anthropometric measurements and a fasting blood sample was used to measure glucose, insulin, triglycerides, total cholesterol, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C). Insulin resistance was calculated based on the homeostasis model method (HOMA-IR). The association between the GL and the biochemical parameters was evaluated by linear regression models using β and 95% confidence intervals (95% CI), stratified by sex and adjusted for body mass index (BMI), energy and fiber intake, and self-perceived social class. No association was found between GL and the glucose metabolism parameters after adjustment. Regarding blood lipids, a positive association was found with LDL-C (β = 1.507, 95% CI 0.454; 2.561 for females; β = 0.216, 95% CI -0.587; 1.020 for males) and a negative association with HDL-C (β = -0.647, 95% CI -1.112; -0.181 for females; β = -0.131, 95% CI -0.422; 0.160 for males).

CONCLUSIONS

Our results suggest that, in healthy young subjects, a high GL diet may have a negative impact on lipid profile.

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.

An optimal glycemic load range is better for reducing obesity and diabetes risk among middle-aged and elderly adults

Background

Due to the lack of evidence, advice pertaining to glycemic load (GL) can be misleading. Does the excessive restriction of GL, mostly through an extreme reduction in carbohydrate intake, result in a relatively high intake of fat and protein and result in overweight and obesity? This study was performed to initially explore the optimal GL range.

Methods

A cross-sectional study involving 2029 participants aged 40 years or older in Guangzhou, China was conducted. Participants were divided into four groups according to cluster analysis. Dietary data were assessed using a previously validated 3-day food record.

Results

Instead of participants with the highest [cluster 1, median (interquartile ranges) GL was 112(107–119)/1000 kcal] and the lowest GL intake [cluster 4, 90(82–96)/1000 kcal], those with moderate GL intakes [clusters 2 and 3, 93(85–102) and 93(85–99)/1000 kcal, respectively] had a lower prevalence of overweight, obesity and diabetes. In addition, clusters 2 and 3 were more consistent with the macronutrient intake reference with adequate micronutrient intake. Therefore, the optimal GL range was determined to be (85–100)/1000 kcal, rather than “lower is better”.

Conclusions

Reducing the GL intake to prevent diabetes deserves more attention in the context of a balanced diet. An appropriate GL may be better than excessive restriction.

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.

Dietary glycemic index and glycemic load and their relationship to cardiovascular risk factors in Chinese children

The purpose of this study was to examine the cross-sectional associations between dietary glycemic index (GI) and glycemic load (GL) and cardiovascular disease (CVD) risk factors in Chinese children. A total of 234 Chinese schoolchildren aged 8-11 years in Guangdong participated in the study. Dietary intake was assessed via a 3-day dietary record. Seven established cardiovascular indicators were analyzed in this study: fasting plasma glucose (FPG), fasting triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), systolic blood pressure, and diastolic blood pressure. Higher dietary GI was significantly associated with higher TG levels (P = 0.037) and lower HDL-C levels (P = 0.005) after adjusting for age, sex, nutritional intake, physical activity, and body mass index z score. LDL-C was found to differ across tertiles of dietary GL. The middle tertile tended to show the highest level of LDL-C. TC, FPG, and blood pressure were independent of both dietary GI and GL. Our findings suggest that higher dietary GI is differentially associated with some CVD risk factors, including lower HDL-C and higher TG, in school-aged children from south China.