Introduction: While the relationship between obesity and caloric intake is widely accepted, the role of glycemic index (GI) and glycemic load (GL) to body mass index (BMI) remains equivocal. This study seeks to determine the daily glycemic index (GI) and glycemic load (GL) of usual diet of rural-dwelling Filipinos, and their relationship with body mass index (BMI). Methods: This is a cross-sectional study reviewing the data of 139 adults from San Juan, Batangas. Average daily GI and GL were calculated from two-day food recall questionnaires. Spearman’s rank test was used to determine correlation of daily GI and GL with BMI; the mean BMI was compared among GI and GL tertiles using one-way ANOVA. Partial least squares regression was used to determine the contribution of food items to daily GI and GL. Results: No overall correlation was observed between daily GI or GL and BMI using Spearman’s rank. However, BMI was higher with increasing GI tertiles (p<0.0001) and GL tertiles (p=0.0108) among the males, but not females. Bread, coffeemix and sweets were major contributors to daily GI, while rice, bread/pastries and sweetened beverages were to daily GL. Leafy vegetables negatively contributed to both. Conclusion There is a positive relationship observed between daily GI and BMI, and daily GL and BMI among the men, but not women, in this population. Staple food with high GI like bread/pastries and sweetened beverages contributed most to both daily GI and GL, with the addition of rice for daily GL. Among Filipinos with marginal daily caloric intake, optimizing carbohydrate quality (low GI or GL) rather than limiting its quantity may be more appropriate. Future studies of prospective design and using objective methods of food intake reporting are recommended.
Glycemic Index ; Glycemic Load

BACKGROUND/OBJECTIVES: The glycemic index (GI) is a measure of the postprandial glucose response (PPGR) to food items, and glycemic load (GL) is a measure of the PPGR to the diet. For those who need to maintain a healthy diet, it is beneficial to regulate appropriate levels of blood glucose. In reality, what influences the meal GI or GL depends on the macronutrient composition and the physical chemistry reactions in vivo. Thus, we investigated whether different macronutrients in a meal significantly affect the PPGR and the validity of calculated GI and GL values for mixed meals. SUBJECTS/METHODS: 12 healthy subjects (6 male, 6 female) were recruited at a campus setting, and subjects consumed a total of 6 test meals one by one, each morning between 8:00 and 8:30 am after 12 h of fasting. PPGR was measured after each consumed meal and serial finger pricks were performed at indicated times. Test meals included 1) 68 g oral glucose, 2) 210 g rice, 3) rice plus 170 g egg white (RE), 4) rice plus 200 g bean sprouts (RS), 5) rice plus 10 g oil (RO), and 6) rice plus, egg white, bean sprouts, and oil (RESO). The incremental area under the curve (iAUC) was calculated to assess the PPGR. Mixed meal GI and GL values were calculated based on the nutrients the subjects consumed in each of the test meals. RESULTS: The iAUC for all meals containing two macronutrients (RS, RO, or RE) were not significantly different from the rice iAUC, whereas, the RESO iAUC (2,237.5 ± 264.9) was significantly lower (P < 0.05). The RESO meal's calculated GI and GL values were different from the actual GI and GL values measured from the study subjects (P < 0.05). CONCLUSIONS: The mixed meal containing three macronutrients (RESO) decreased the PPGR in healthy individuals, leading to significantly lower actual GI and GL values than those derived by nutrient-based calculations. Thus, consuming various macronutrient containing meals is beneficial in regulating PPGR.
Blood Glucose ; Chemistry, Physical ; Diet ; Egg White ; Fasting ; Fingers ; Glucose ; Glycemic Index ; Glycemic Load ; Healthy Volunteers ; Humans ; Male ; Meals

OBJECTIVES: Previous studies have obtained conflicting findings regarding possible associations between indices measuring carbohydrate intake and dyslipidemia, which is an established risk factor of coronary heart disease. In the present study, we examined cross-sectional associations between carbohydrate indices, including the dietary glycemic index (GI), glycemic load (GL), total amount of carbohydrates, and the percentage of energy from carbohydrates, and a range of blood lipid parameters. METHODS: This study included 1530 participants (554 men and 976 women) from 246 families within the Healthy Twin Study. We analyzed the associations using a generalized linear mixed model to control for familial relationships. RESULTS: Levels of the Apo B were inversely associated with dietary GI, GL, and the amount of carbohydrate intake for men, but these relationships were not significant when fat-adjusted values of the carbohydrate indices were used. Triglyceride levels were positively associated with dietary GI and GL in women, and this pattern was more notable in overweight participants (body mass index [BMI] ≥25 kg/m2). However, total, low-density lipoprotein and high-density lipoprotein cholesterol levels were not significantly related with carbohydrate intake overall. CONCLUSIONS: Of the blood lipid parameters we investigated, only triglyceride levels were positively related with dietary carbohydrate indices among women participants in the Healthy Twin Study, with an interactive role observed for BMI. However, these associations were not observed in men, suggesting that the association between blood lipid levels and carbohydrate intake depends on the type of lipid, specific carbohydrate indices, gender, and BMI.
Apolipoproteins B ; Carbohydrates ; Cholesterol ; Coronary Disease ; Dietary Carbohydrates* ; Dyslipidemias ; Female ; Glycemic Index ; Glycemic Load ; Humans ; Lipoproteins ; Male ; Overweight ; Risk Factors ; Triglycerides*

BACKGROUND AND PURPOSE: Elevated postprandial blood glucose is a critical risk factor for stroke. The dietary glycemic load (GL) and glycemic index (GI) are frequently used as markers of the postprandial blood glucose response to estimate the overall glycemic effect of diets. We hypothesized that high dietary GL, GI, or total carbohydrate intake is associated with a poor functional outcome in patients with acute ischemic stroke. METHODS: We prospectively included 263 first-ever ischemic stroke patients who completed a semiquantitative food-frequency questionnaire. The dietary GL, GI, and total carbohydrate intake were investigated by examining the average frequency of intake during the previous year based on reference amounts for various food items. Poor functional outcome was defined as a score on the modified Rankin Scale (mRS) of ≥3 at 3 months after stroke. RESULTS: The patients were aged 65.4±11.7 years (mean±standard deviation), and 58.2% of them were male. A multivariate analysis adjusted for age, sex, marital status, prestroke mRS score, diabetes mellitus, hyperlipidemia, body mass index, triglycerides, low-density lipoprotein, hemoglobin A1c, stroke classification, and National Institutes of Health Stroke Scale score, early neurological deterioration, and high-grade white-matter hyperintensities revealed that the dietary GL and total carbohydrate intake were associated with a poor functional outcome, with odds ratios for the top quartile relative to the bottom quartile of 28.93 (95% confidence interval=2.82–296.04) and 36.84 (95% confidence interval=2.99–453.42), respectively (p for trend=0.002 and 0.002, respectively). In contrast, high dietary GI was not associated with a poor functional outcome (p for trend=0.481). CONCLUSIONS: Increased dietary GL and carbohydrate intake were associated with a poor short-term functional outcome after an acute ischemic stroke.
Blood Glucose ; Body Mass Index ; Cerebral Infarction* ; Classification ; Diabetes Mellitus ; Diet ; Glycemic Index ; Glycemic Load* ; Humans ; Hyperlipidemias ; Lipoproteins ; Male ; Marital Status ; Multivariate Analysis ; National Institutes of Health (U.S.) ; Odds Ratio ; Prospective Studies ; Risk Factors ; Stroke ; Triglycerides

PURPOSE: This study evaluated the glycemic response of diets using estimated glycemic load (eGL), which had been developed for mixed meals for Korean adults, and examined its associations with cardiometabolic risk factors among Korean adults. METHODS: A total of 4,655 men and 6,760 women aged 19 years and above were included from the 2013 ~ 2016 Korea National Health and Nutrition Examination Survey. eGL was calculated by each meal (breakfast, lunch, dinner, and snack) and then summed to give daily total eGL. A multiple logistic regression analysis was used to examine the association. RESULTS: Mean daily total eGL was 112.6 in men and 99.3 in women. Daily total eGL was positively associated with carbohydrate and fiber intakes, but negatively associated with protein and fat intakes in both men and women (p < 0.05 for all). Daily total eGL showed an inverse association with HDL-cholesterol level in both men and women (p = 0.0036 for men and p = 0.0008 for women). Men in the highest quintile of daily total eGL showed a 66% increased risk of hypercholesterolemia (OR, 1.66; 95% CI, 1.10 ~ 2.50; p for trend = 0.0447) compared with those in the lowest quintile. CONCLUSION: These findings suggest that eGL based on carbohydrate, protein, fat and fiber intakes can reflect glycemic response and therefore can be used as an index for dietary planning, nutrition education and in the food industry.
Adult ; Asian Continental Ancestry Group ; Diet ; Dyslipidemias ; Education ; Female ; Food Industry ; Glycemic Load ; Humans ; Hypercholesterolemia ; Korea ; Logistic Models ; Lunch ; Male ; Meals ; Nutrition Surveys ; Risk Factors

Animals ; Chemical and Drug Induced Liver Injury ; drug therapy ; Diabetes Mellitus, Experimental ; drug therapy ; Diabetes Mellitus, Type 2 ; drug therapy ; Dyslipidemias ; drug therapy ; Glycemic Load ; drug effects ; Male ; Protective Agents ; pharmacology ; Rats ; Rats, Sprague-Dawley ; Specific Pathogen-Free Organisms ; Stilbenes ; pharmacology

Objective: To our knowledge, no definitive conclusion has been reached regarding the relationship between glucocorticoids and hypertension. Here, we aimed to explore the characteristics of glucocorticoids in participants with dysglycemia and hypertension, and to analyze their association with blood pressure indicators. Methods: The participants of this study were from the Henan Rural Cohort study. A total of 1,688 patients 18-79 years of age were included in the matched case control study after application of the inclusion and exclusion criteria. Statistical methods were used to analyze the association between glucocorticoids and various indices of blood pressure, through approaches such as logistic regression analysis, trend tests, linear regression, and restricted cubic regression. Results: The study population consisted of 552 patients with dysglycemia and hypertension (32.7%). The patients with co-morbidities had higher levels of serum cortisol ( Conclusions Serum deoxycortisol was positively correlated with systolic blood pressure, pulse pressure, mean arterial pressure, mean blood pressure, and mean proportional arterial pressure. Glucocorticoids (deoxycortisol and cortisol) increase the risk of hypertension in people with dysglycemia, particularly in those with T2DM.
Adult ; Aged ; Aged, 80 and over ; Blood Pressure ; Case-Control Studies ; China/epidemiology* ; Cohort Studies ; Female ; Glucocorticoids/blood* ; Glycemic Load ; Humans ; Hydrocortisone/blood* ; Hypertension/etiology* ; Male ; Middle Aged ; Prevalence ; Risk Factors ; Rural Population ; Young Adult