Insulin-like growth factor I, binding proteins -1 and -3, risk of type 2 diabetes and macronutrient intakes in men.

The insulin-like growth factor (IGF) axis may be involved in the development of type 2 diabetes. We examined the associations of IGF-I and IGF binding proteins (IGFBP)-1 and -3 with diabetes risk and evaluated macronutrient intakes related to the observed associations. In a nested case-control study of the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study of Finnish male smokers aged 50-69 years, the IGF variables were measured from baseline serum samples for a random sample of 310 men with diabetes diagnosed during a 12-year follow-up and for 310 controls matched by age, recruitment day and intervention group. Diet at baseline was assessed using a validated FFQ. The associations of IGF proteins with diabetes risk were estimated using conditional logistic regression and the associations with macronutrient intakes using linear regression. IGF-I and IGFBP-3 were not associated with the incidence of diabetes. Higher IGFBP-1 was associated with lower diabetes risk in an unadjusted crude model (OR 0·25; 95 % CI 0·15, 0·42 in the highest quartile compared with the lowest), but not after adjustment for BMI (corresponding OR 0·76; 95 % CI 0·41, 1·40). Intakes of carbohydrates, plant protein and milk protein associated positively and intake of meat protein and fat negatively with IGFBP-1 (P<0·005). IGFBP-1 was inversely associated with diabetes risk, but the association was substantially dependent on BMI. The associations between macronutrient intakes and IGFBP-1 may reflect influences of nutrients or foods on insulin concentrations.

Coffee does not modify postprandial glycaemic and insulinaemic responses induced by carbohydrates.

BACKGROUND: Strong epidemiological evidence suggests that coffee consumption is associated with lower risk of type 2 diabetes. In postprandial studies, however, caffeine consumption has been associated with impaired glucose regulation. AIM OF THE STUDY: To study the acute effects of coffee and caffeine-containing soft drinks on glycaemic and insulinaemic responses. DESIGN: Twelve healthy volunteers were served each test food once and the reference glucose solution twice, containing 50 g of available carbohydrates, after an overnight fast at 1-week intervals in a random order. Capillary blood samples were drawn at 15-30 min intervals for 2 h after each study meal. The incremental areas under the curve (IAUC), glycaemic index (GI) and insulinaemic index (II), were calculated to estimate the glycaemic and insulinaemic responses. RESULTS: Glucose and insulin responses of coffees with glucose containing 150 or 300 mg of caffeine did not differ from responses of pure glucose solution; the GIs were 104 and 103, and the IIs were 89 and 92, respectively. When a bun or sucrose and milk were consumed together with coffee, lower GI values and insulin responses were observed, reflecting the carbohydrate quality and protein content of the accompaniments. Sucrose-sweetened cola produced a high GI value of 90 and an II of 61. CONCLUSIONS: Coffee does not modify glycaemic and insulinaemic responses when ingested with a carbohydrate source. Therefore, there is no need to avoid coffee as a choice of beverage in GI testing.

Associations of quantity and quality of carbohydrate sources with subjective appetite sensations during 3-year weight-loss maintenance: Results from the PREVIEW intervention study.

BACKGROUND & AIMS: The association of quantity and quality of carbohydrate sources with appetite during long-term weight-loss maintenance (WLM) after intentional weight loss (WL) is unclear. We aimed to investigate longitudinal associations of quantity and quality of carbohydrate sources with changes in subjective appetite sensations during WLM. METHODS: This secondary analysis evaluated longitudinal data from the 3-year WLM phase of the PREVIEW study, a 2 × 2 factorial (diet-physical activity arms), multi-center, randomized trial. 1279 individuals with overweight or obesity and prediabetes (25-70 years; BMI≥25 kg m-2) were included. Individuals were merged into 1 group to assess longitudinal associations of yearly changes in appetite sensations. Quantity and quality of carbohydrate sources including total carbohydrate, glycemic index (GI), glycemic load (GL), and total dietary fiber were assessed via 4-day food diaries at 4 timepoints (26, 52, 104, and 156 weeks) during WLM. Visual analog scales were used to assess appetite sensations in the previous week. RESULTS: During WLM, participants consumed on average 160.6 (25th, 75th percentiles 131.1, 195.8) g·day-1 of total carbohydrate, with GI 53.8 (48.7, 58.8) and GL 85.3 (67.2, 108.9) g day-1, and 22.3 (17.6, 27.3) g·day-1 of dietary fiber. In the available-case analysis, multivariable-adjusted linear mixed models with repeated measures showed that each 30-g increment in total carbohydrate was associated with increases in hunger (1.36 mm year-1, 95% CI 0.77, 1.95, P < 0.001), desire to eat (1.10 mm year-1, 0.59, 1.60, P < 0.001), desire to eat something sweet (0.99 mm year-1, 0.30, 1.68, P = 0.005), and weight regain (0.20%·year-1, 0.03, 0.36, P = 0.022). Increasing GI was associated with weight regain, but not associated with increases in appetite sensations. Each 20-unit increment in GL was associated with increases in hunger (0.92 mm year-1, 0.33, 1.51, P = 0.002), desire to eat (1.12 mm year-1, 0.62, 1.62, P < 0.001), desire to eat something sweet (1.13 mm year-1, 0.44, 1.81, P < 0.001), and weight regain (0.35%·year-1, 0.18, 0.52, P < 0.001). Surprisingly, dietary fiber was also associated with increases in desire to eat, after adjustment for carbohydrate or GL. CONCLUSIONS: In participants with moderate carbohydrate and dietary fiber intake, and low to moderate GI, we found that higher total carbohydrate, GL, and total fiber, but not GI, were associated with increases in subjective desire to eat or hunger over 3 years. This study was registered as ClinicalTrials.gov, NCT01777893.

Protein and fat modify the glycaemic and insulinaemic responses to a mashed potato-based meal.

Potatoes, especially mashed potatoes, are known to result in high glycaemic and insulinaemic responses. However, in most meals, potatoes are accompanied by other foods. The objective of the present study was to investigate how glycaemic and insulinaemic responses to a mashed potato meal changed when a high-fat food (rapeseed oil), a high-protein food (chicken breast) and/or salad were added to the meal. Healthy subjects (n 11) ingested the test meals once and the reference food (glucose solution) twice in a random order at 1-week intervals. Capillary blood samples were then drawn for 2 h, and glucose and insulin were analysed. The 2 h glycaemic responses to six mashed potato-containing meals varied more than twofold. The glycaemic index (GI) of pure mashed potato was 108, whereas combined with chicken breast, rapeseed oil and salad, it was only 54. The latter GI also differed considerably from its predicted value of 103, which was based on the individual GI of the components of the meal. The insulinaemic indices of the mashed potato-based meals varied between 94 and 148. Chicken breast in the meal increased the insulinaemic response, and rapeseed oil diminished it. However, the insulinaemic response to mashed potato with chicken breast and rapeseed oil was lower than that to mashed potato alone. In conclusion, the protein, fat and salad contents of a meal exert considerable influence on the glycaemic and insulinaemic responses to mashed potatoes. Furthermore, the estimation of the GI of a mixed meal by calculation is imprecise.

Impact of overweight and glucose tolerance on postprandial responses to high- and low-glycaemic index meals.

The beneficial effects of a low-glycaemic index (GI) meal on postprandial glucose and insulin levels have been demonstrated. However, limited data are available on the impact of overweight and glucose tolerance on postprandial responses to different GI meals. Our aim was to study the effects of physiological characteristics on postprandial glucose, insulin and lipid responses and the relative glycaemic response (RGR) of a low-GI (LGI) and a high-GI (HGI) meal. We recruited twenty-four normal-weight and twenty-four overweight subjects, twelve with normal glucose tolerance (NGT) and twelve with impaired glucose tolerance (IGT) in each group. Both test meals were consumed once and the glucose reference twice. Blood glucose and insulin were measured in the fasting state and over a 2 h period after each study meal, and TAG and NEFA were measured in the fasting state and over a 5 h period. The glucose responses of subjects with IGT differed significantly from those of subjects with NGT. The highest insulin responses to both meals were observed in overweight subjects with IGT. Physiological characteristics did not influence TAG or NEFA responses or the RGR of the meals. The LGI meal resulted in lower glucose (P < 0·001) and insulin (P < 0·001) responses, but higher TAG responses (P < 0·001), compared with the HGI meal. The GI of the meals did not affect the NEFA responses. In conclusion, the LGI meal causes lower glucose and insulin responses, but higher TAG responses, than the HGI meal. The RGR of the meals does not differ between normal-weight and overweight subjects with NGT or IGT.

Glycaemic index database for the epidemiological Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study.

Interest in the dietary glycaemic index (GI) and glycaemic load (GL) as risk factors for chronic diseases has grown in recent years but findings have been controversial. We describe the compilation of the GI database for the cohort studies within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study and the main characteristics associating with diet GI and GL. The ATBC Study enrolled 29 133 male smokers aged 50-69 years who filled in a dietary history questionnaire upon study entry. The dietary data included 1097 foods, of which 195 foods with no or a negligible amount of available carbohydrates were assigned a GI of zero. Based on preset methodological criteria for published GI studies, the GI value of a similar food was available for 130 foods, and the GI of related food was assigned to 360 foods. The GI values of these foods served in the GI calculation of 412 composite foods. The median diet GI among the ATBC Study participants was 67.3 (interquartile range 64.8-70.0), and the median diet GL was 175 (interquartile range 158-192). The intakes of carbohydrates, protein and fat decreased, and the intake of fibre increased, with increasing GI. The GL showed a positive correlation with intakes of carbohydrates and dietary fibre and a negative correlation with intakes of protein and fat. The GI studies available that fulfilled the minimum methodological requirements cover a sufficient amount of foods to form a meaningful GI database for epidemiological study. This, however, requires the availability of GI values for relevant local carbohydrate-containing foods.

Measuring the glycemic index of foods: interlaboratory study.

BACKGROUND: Many laboratories offer glycemic index (GI) services. OBJECTIVE: We assessed the performance of the method used to measure GI. DESIGN: The GI of cheese-puffs and fruit-leather (centrally provided) was measured in 28 laboratories (n=311 subjects) by using the FAO/WHO method. The laboratories reported the results of their calculations and sent the raw data for recalculation centrally. RESULTS: Values for the incremental area under the curve (AUC) reported by 54% of the laboratories differed from central calculations. Because of this and other differences in data analysis, 19% of reported food GI values differed by >5 units from those calculated centrally. GI values in individual subjects were unrelated to age, sex, ethnicity, body mass index, or AUC but were negatively related to within-individual variation (P=0.033) expressed as the CV of the AUC for repeated reference food tests (refCV). The between-laboratory GI values (mean+/-SD) for cheese-puffs and fruit-leather were 74.3+/-10.5 and 33.2+/-7.2, respectively. The mean laboratory GI was related to refCV (P=0.003) and the type of restrictions on alcohol consumption before the test (P=0.006, r2=0.509 for model). The within-laboratory SD of GI was related to refCV (P<0.001), the glucose analysis method (P=0.010), whether glucose measures were duplicated (P=0.008), and restrictions on dinner the night before (P=0.013, r2=0.810 for model). CONCLUSIONS: The between-laboratory SD of the GI values is approximately 9. Standardized data analysis and low within-subject variation (refCV<30%) are required for accuracy. The results suggest that common misconceptions exist about which factors do and do not need to be controlled to improve precision. Controlled studies and cost-benefit analyses are needed to optimize GI methodology. The trial was registered at clinicaltrials.gov as NCT00260858.

Methodologic considerations in the measurement of glycemic index: glycemic response to rye bread, oatmeal porridge, and mashed potato.

BACKGROUND: Methodologic choices affect measures of the glycemic index (GI). The effects on GI values of blood sampling site, reference food type, and the number of repeat tests have been insufficiently determined. OBJECTIVE: The objective was to study the effect of methodologic choices on GI values. Comparisons were made between venous and capillary blood sampling and between glucose and white bread as the reference food. The number of tests needed for the reference food was assessed. Rye bread, oatmeal porridge, and instant mashed potato were used as the test foods. DESIGN: Twelve healthy volunteers were served each test food once and both reference foods 3 times at 1-wk intervals in a random order after they had fasted overnight. Capillary and venous blood samples were drawn at intervals for 3 h after each study meal. RESULTS: GIs and their CVs based on capillary samples were lower than those based on venous samples. Two tests of glucose solution as the reference provided stable capillary GIs for the test foods. The capillary GIs did not differ significantly when white bread was used as the reference 1, 2, or 3 times, but the variation was lower when tests were performed 2 and 3 times. Capillary GIs with white bread as the reference were 1.3 times as high as those with glucose as the reference. The capillary GIs of rye bread, oatmeal porridge, and mashed potato were 77, 74, and 80, respectively, with glucose as the reference. CONCLUSIONS: Capillary blood sampling should be used in the measurement of GI, and reference tests with glucose or white bread should be performed at least twice.

Endotoxemia, nutrition, and cardiometabolic disorders.

AIMS: Circulating lipopolysaccharides (LPSs), associated with both infection and inflammation, may arise from the gastrointestinal tract microbiota, and the levels may be affected by daily nutrition. We investigated whether nutrient intake affects the association of serum LPS activity with prevalent obesity, metabolic syndrome (MetS), diabetes, and coronary heart disease (CHD) and with the risk of incident CHD events. METHODS: The nutrition cohort (n = 2,452, mean age ± SD, 52.2 ± 10.1 years) of the FINRISK 1997 Study was followed up for 10 years. Information on macronutrient intake at baseline was collected from 24-h dietary recall. Serum endotoxin activities were determined by the Limulus amebocyte lysate assay. RESULTS: LPS activity was associated directly with the total energy intake and indirectly with carbohydrate intake in lean, healthy subjects. High LPS was significantly associated with prevalent obesity, MetS, diabetes, and CHD events, independently of established risk factors, CRP, and total energy or nutrient intake. The ORs (95 % CI) were 1.49 (1.21-1.85, p < 0.001, Q2-4 vs. Q1) for obesity, 2.56 (1.97-3.32, p < 0.001, Q2-4 vs. Q1) for MetS, 1.94 (1.06-3.52, p = 0.031, Q2-4 vs. Q1) for CHD, and 1.01 (1.00-1.01, p = 0.032, LPS unit) for diabetes. In the follow-up, high LPS was significantly associated with the risk of CHD events with a hazard ratio of 1.88 (1.13-3.12, p = 0.013, Q2-4 vs. Q1). This association was independent of baseline established risk factors, diet, obesity, MetS, and diabetes. CONCLUSION: A high serum LPS activity is strongly associated with cardiometabolic disorders, which supports the role of bacterial infections and immune response in their etiology.

Modifying effects of alcohol on the postprandial glucose and insulin responses in healthy subjects.

BACKGROUND: Moderate alcohol consumption associates with lower risk of type 2 diabetes, but in postprandial studies, alcohol induced impaired insulin sensitivity. The measurement of the glycemic index (GI) for beer has been considered challenging because of its low carbohydrate content. Therefore, imputed GI values from 36 to 95 on the basis of carbohydrate-rich beverages have been used for beer in epidemiologic studies. OBJECTIVES: We investigated the acute effects of alcohol on glucose and insulin responses and measured GIs and insulinemic indexes (IIs) of nonalcoholic and alcoholic beers. DESIGN: In a crossover design, 10 healthy volunteers were served beer with 4.5% alcohol by volume, nonalcoholic beer, and a glucose solution with alcohol once and the reference glucose solution twice. Each portion contained 25 g available carbohydrate, and the beer and glucose solution with alcohol contained 21 g alcohol. Capillary blood samples were collected up to 2 h after ingestion, and the incremental AUCs (IAUCs), GIs, and IIs were calculated. RESULTS: Compared with the reference glucose solution, the glucose solution with alcohol produced an 18% higher postprandial glucose IAUC (P = 0.03) and had no significant effect on the insulin IAUC. Compared with the reference glucose solution, beer had no significant effect on glucose or insulin IAUCs, and nonalcoholic beer tended to reduce the glucose IAUC (P = 0.06) but not the insulin IAUC. GIs of beer and nonalcoholic beer were 119 and 80, and IIs were 130 and 88, respectively. CONCLUSIONS: Alcohol increases the postprandial glucose response, probably through impaired insulin sensitivity. GI values published for alcohol-containing beers have underestimated the true glycemic effects.