Search

Hepatic steatosis is associated with poor cardiometabolic health, with de novo lipogenesis (DNL) contributing to hepatic steatosis and subsequent insulin resistance. Hepatic saturated fatty acids (SFA) may be a marker of DNL and are suggested to be most detrimental in contributing to insulin resistance. Here, we show in a cross-sectional study design (ClinicalTrials.gov ID: NCT03211299) that we are able to distinguish the fractions of hepatic SFA, mono- and polyunsaturated fatty acids in healthy and metabolically compromised volunteers using proton magnetic resonance spectroscopy (1H-MRS). DNL is positively associated with SFA fraction and is elevated in patients with non-alcoholic fatty liver and type 2 diabetes. Intriguingly, SFA fraction shows a strong, negative correlation with hepatic insulin sensitivity. Our results show that the hepatic lipid composition, as determined by our 1H-MRS methodology, is a measure of DNL and suggest that specifically the SFA fraction may hamper hepatic insulin sensitivity., Hepatic steatosis is associated with poor cardiometabolic health, with de novo lipogenesis (DNL) contributing to hepatic steatosis and subsequent insulin resistance. Here, the authors use 1H-MRS methodology to show hepatic SFA fraction is a measure of DNL and specifically may hamper hepatic insulin sensitivity.

Varying the macronutrient composition of meals alters acute postprandial responses, but the effect sizes for specific macronutrient exchanges have not been quantified by systematic reviews. Therefore the aim is to quantify the effect size of exchanging fat for carbohydrates in mixed meals on postprandial glucose (PPG), insulin (PPI), triglycerides (PPTG), and free fatty acids (PPFFA) responses by performing a systematic review and meta-analysis of randomized controlled trials. A systematic literature search was undertaken on randomized controlled trials comparing isocaloric high fat with high carbohydrate meals, with comparable protein contents and at least one postprandial glycemic- and one lipid outcome. The outcome data were extracted and expressed as mean postprandial levels over 2 h. Ten studies involving 14 comparisons met the eligibility criteria. Data were available for meta-analysis from 347 participants, consuming mixed meals containing 250-1003 kcal, and total fat contents of 33.3-75.6 percentage of energy (en%) (intervention) versus 0-31.7 en% (control). Each 10en% increase in fat, replacing carbohydrates produced a mean reduction in PPG of 0.32 mmol/l (95% CI -0.64 to -0.00, p = 0.047), a reduction in PPI of 18.2 pmol/l (95% CI -24.86 to -11.54), an increase in PPTG of 0.06 mmol/l (95% CI 0.02 to 0.09, p = 0.004), with no statistically significant effect on PPFFA. Modest exchange of carbohydrates for fats in mixed meals significantly reduces PPG and PPI and increases PPTG responses. The quantitative relationships derived here may be applied to predict responses, and to design and optimize meal macronutrient compositions in dietary intervention studies.

Background It is often assumed that lower postprandial glucose (PPG) and insulin (PPI) responses are induced by slower glucose influx from the gut (e.g., by delayed carbohydrate digestion). However, changes in the rate of appearance of glucose in the peripheral circulation [rate of appearance of exogenous glucose (RaE)] may be accompanied by changes in endogenous glucose production (EGP) and the rate of disappearance of total glucose into tissues (RdT). The quantitative relationships between reductions in RaE and PPG/PPI levels are unclear. Objectives The objective was to perform a meta-analysis to quantify the effect of changes in RaE on changes in PPG and PPI levels (primary) and EGP and RdT (secondary). Methods We systematically searched the Scopus, Medline, and Cochrane library databases through 10 January 2019 for randomized, controlled, carbohydrate-rich interventions that aimed to reduce RaE in humans, measured using dual or triple stable isotope methods. The 2-h net incremental AUCs for all variables were extracted or calculated. Relationships between RaE and outcomes were quantified by weighted regression analyses. Results There were 12 articles, including 17 comparisons, that satisfied the inclusion criteria. The subjects were mainly men (60%), with age and BMI ranges of 18-40 y and 20.0-27.5 kg/m2, respectively. A 10% reduction in RaE was associated with reductions in PPG levels, PPI levels, and the RdT of 7% (95% CI: 2%, 12%; P = 0.010), 8% (95% CI: 2%, 13%; P = 0.012), and 11% (95% CI: 4%, 17%; P = 0.005), respectively, but was not significantly associated with a change in EGP (13%; 95% CI: -7%, 33%; P = 0.176). All fluxes together explained 70% and 26% of the variances in PPG and PPI levels, respectively. Conclusions In adults, reducing glucose RaE by diet is associated with significant reductions in PPG levels, PPI levels, and the rate of glucose disposal. This trial was registered in the PROSPERO database with identifier CRD42018084824.

OBJECTIVE To investigate the association between intakes of n-6 polyunsaturated fatty acids (PUFAs) and type 2 diabetes risk in three prospective cohort studies of U.S. men and women. RESEARCH DESIGN AND METHODS We followed 83,648 women from the Nurses’ Health Study (NHS) (1980–2012), 88,610 women from NHSII (1991–2013), and 41,771 men from the Health Professionals Follow-Up Study (HPFS) (1986–2012). Dietary data were collected every 2–4 years by using validated food-frequency questionnaires. Self-reported incident diabetes, identified biennially, was confirmed by using a validated supplementary questionnaire. RESULTS During 4.93 million person-years of follow-up, 18,442 type 2 diabetes cases were documented. Dietary n-6 PUFAs accounted for 4.4–6.8% of total energy, on average, and consisted primarily of linoleic acid (LA) (≥98%). In multivariate-adjusted models, hazard ratios (95% CIs) of type 2 diabetes risk comparing extreme n-6 PUFA quintiles (highest vs. lowest) were 0.91 (0.85, 0.96) (Ptrend = 0.002) for total n-6 PUFAs and 0.92 (0.87, 0.98) (Ptrend = 0.01) for LA. In an isocaloric substitution model, diabetes risk was 14% (95% CI 5%, 21%) (P = 0.002) lower when LA isocalorically replaced saturated fats (5% of energy), 17% (95% CI 9%, 24%) (P < 0.001) lower for trans fats (2% of energy), or 9% (95% CI 17%, 0.1%) (P = 0.047) lower for carbohydrates (5% of energy). Replacing n-3 PUFAs or monounsaturated fats with LA was not significantly associated with type 2 diabetes risk. CONCLUSIONS Our study provides additional evidence that LA intake is inversely associated with risk of type 2 diabetes, especially when replacing saturated fatty acids, trans fats, or carbohydrates.

Dietary macronutrient composition may affect hepatic liver content and its associated diseases, but the results from human intervention trials have been equivocal or underpowered. We aimed to assess the effects of dietary macronutrient composition on liver fat content by conducting a systematic review and meta-analysis of randomized controlled trials in adults. Four databases (PubMed, Embase, Web of Science, and COCHRANE Library) were systematically searched for trials with isocaloric diets evaluating the effect of dietary macronutrient composition (energy percentages of fat, carbohydrates, and protein, and their specific types) on liver fat content as assessed by magnetic resonance techniques, computed tomography or liver biopsy. Data on change in liver fat content were pooled by random or fixed-effects meta-analyses and expressed as standardized mean difference (SMD). We included 26 randomized controlled trials providing data for 32 comparisons on dietary macronutrient composition. Replacing dietary fat with carbohydrates did not result in changes in liver fat (12 comparisons, SMD 0.01 (95% CI -0.36; 0.37)). Unsaturated fat as compared with saturated fat reduced liver fat content (4 comparisons, SMD -0.80 (95% CI -1.09; -0.51)). Replacing carbohydrates with protein reduced liver fat content (5 comparisons, SMD -0.33 (95% CI -0.54; -0.12)). Our meta-analyses showed that replacing carbohydrates with total fat on liver fat content was not effective, while replacing carbohydrates with proteins and saturated fat with unsaturated fat was. More well-performed and well-described studies on the effect of types of carbohydrates and proteins on liver fat content are needed, especially studies comparing proteins with fats.

AIM: To investigate the relative contribution of phenotypic and lifestyle factors to HbA1c, independent of fasting plasma glucose (FPG) and 2h post-load glucose (2hPG), in the general population. METHODS: The study populations included 2309 participants without known diabetes from the first wave of the Hoorn Study (1989) and 2619 from the second wave (2006). Multivariate linear regression models were used to analyze the relationship between potential determinants and HbA1c in addition to FPG and 2hPG. The multivariate model was derived in the first wave of the Hoorn Study, and replicated in the second wave. RESULTS: In both cohorts, independent of FPG and 2hPG, higher age, female sex, larger waist circumference, and smoking were associated with a higher HbA1c level. Larger hip circumference, higher BMI, higher alcohol consumption and vitamin C intake were associated with a lower HbA1c level. FPG and 2hPG together explained 41.0% (first wave) and 53.0% (second wave) of the total variance in HbA1c. The combination of phenotypic and lifestyle determinants additionally explained 5.7% (first wave) and 3.9% (second wave). CONCLUSIONS: This study suggests that, independent of glucose, phenotypic and lifestyle factors are associated with HbA1c, but the contribution is relatively small. These findings contribute to a better understanding of the low correlation between glucose levels and HbA1c in the general population.

Background: It is unclear to what extent adherence to dietary guidelines may specifically affect visceral fat and liver fat. We aimed to study the association between the Dutch Healthy Diet Index (DHD-index) and total body fat, visceral adipose tissue (VAT) and hepatic triglyceride content (HTGC) in middle-aged men and women. Design: In this cross-sectional study, VAT was assessed by magnetic resonance imaging (MRI) in 2580 participants, and HTGC by proton-MR spectroscopy in 2083 participants. Habitual dietary intake and physical activity were estimated by questionnaire. Adherence to the current Dutch dietary guidelines was estimated by the 2015 DHD-index score based on the thirteen components (vegetables, fruit, wholegrain products, legumes, nuts, dairy, fish, tea, liquid fats, red meat, processed meat, sweetened beverages, and alcohol). The DHD-index ranges between 0 and 130 with a higher score indicating a healthier diet. We used linear regression to examine associations of the DHD-index with VAT and HTGC, adjusted for age, smoking, education, ethnicity, basal metabolic rate, energy restricted diet, menopausal state, physical activity, total energy intake, and total body fat. We additionally excluded the components one by one to examine individual contributions to the associations. Results: Included participants (43% men) had a mean (SD) age of 56 (6) years and DHD-index score of 71 (15). A 10-point higher DHD-index score was associated with 2.3 cm2 less visceral fat (95% CI; −3.5; −1.0 cm2) and less liver fat (0.94 times, 95% CI; 0.90; 0.98). Of all components, exclusion of dairy attenuated the associations with TBF and VAT. Conclusions: Adherence to the dietary guidelines as estimated by the DHD-index was associated with less total body fat, and with less visceral and liver fat after adjustment for total body fat. These findings might contribute to better understanding of the mechanisms underlying associations between dietary habits and cardiometabolic diseases.

Dietary macronutrient composition may affect hepatic liver content and its associated diseases, but the results from human intervention trials have been equivocal or underpowered. We aimed to assess the effects of dietary macronutrient composition on liver fat content by conducting a systematic review and meta-analysis of randomized controlled trials in adults. Four databases (PubMed, Embase, Web of Science, and COCHRANE Library) were systematically searched for trials with isocaloric diets evaluating the effect of dietary macronutrient composition (energy percentages of fat, carbohydrates, and protein, and their specific types) on liver fat content as assessed by magnetic resonance techniques, computed tomography or liver biopsy. Data on change in liver fat content were pooled by random or fixed-effects meta-analyses and expressed as standardized mean difference (SMD). We included 26 randomized controlled trials providing data for 32 comparisons on dietary macronutrient composition. Replacing dietary fat with carbohydrates did not result in changes in liver fat (12 comparisons, SMD 0.01 (95% CI -0.36; 0.37)). Unsaturated fat as compared with saturated fat reduced liver fat content (4 comparisons, SMD -0.80 (95% CI -1.09; -0.51)). Replacing carbohydrates with protein reduced liver fat content (5 comparisons, SMD -0.33 (95% CI -0.54; -0.12)). Our meta-analyses showed that replacing carbohydrates with total fat on liver fat content was not effective, while replacing carbohydrates with proteins and saturated fat with unsaturated fat was. More well-performed and well-described studies on the effect of types of carbohydrates and proteins on liver fat content are needed, especially studies comparing proteins with fats.

BACKGROUND: Monounsaturated fatty acids (MUFAs) improve blood lipid profiles in intervention studies, but prospective evidence with regard to MUFA intake and coronary heart disease (CHD) risk is limited and controversial. OBJECTIVE: We investigated the associations of cis MUFA intake from plant (MUFA-P) and animal (MUFA-A) sources with CHD risk separately among 63,442 women from the Nurses’ Health Study (1990–2012) and 29,942 men from the Health Professionals Follow-Up Study (1990–2012). DESIGN: Intakes of MUFA-Ps and MUFA-As were calculated by using validated food-frequency questionnaires collected every 4 y. Incident nonfatal myocardial infarction and fatal CHD cases (n = 4419) were confirmed by medical record review. RESULTS: During follow-up, MUFA-Ps and MUFA-As contributed 5.8–7.9% and 4.2–5.4% of energy on average, respectively. When MUFA-Ps were modeled to isocalorically replace other macronutrients, HRs (95% CIs) of CHD were 0.83 (0.68, 1.00) for saturated fatty acids (SFAs; 5% of energy), 0.86 (0.76, 0.97) for refined carbohydrates (5% of energy), and 0.80 (0.70, 0.91) for trans fats (2% of energy) (P = 0.05, 0.01, and 0.001, respectively). For MUFA-As, corresponding HRs (95% CIs) for the same isocaloric substitutions were 1.04 (0.79, 1.38) for SFAs, 1.11 (0.91, 1.35) for refined carbohydrates, and 0.88 (0.77, 1.01) for trans fats (P = 0.76, 0.31, and 0.08, respectively). Given the common food sources of SFAs and MUFA-As (Spearman correlation coefficients of 0.81–0.83 between these groups of fatty acids), we further estimated CHD risk when the sum of MUFA-As and SFAs (5% of energy) was replaced by MUFA-Ps, and found that the HR was 0.81 (95% CI: 0.73, 0.90; P < 0.001) for this replacement. CONCLUSIONS: The largely different associations of MUFA-Ps and MUFA-As with CHD risk suggest that plant-based foods are the preferable sources of MUFAs for CHD prevention. These findings are observational and warrant confirmation in intervention settings. This study was registered at clinicaltrials.gov as NCT00005152 and NCT00005182.

Aims/hypothesis: Glycaemic markers and fasting insulin are frequently measured outcomes of intervention studies. To extrapolate accurately the impact of interventions on the risk of diabetes incidence, we investigated the size and shape of the associations of fasting plasma glucose (FPG), 2 h post-load glucose (2hPG), HbA1c, fasting insulin and HOMA-IR with incident type 2 diabetes mellitus. Methods: The study population included 1349 participants aged 50–75 years without diabetes at baseline (1989) from a population-based cohort in Hoorn, the Netherlands. Incident type 2 diabetes was defined by the WHO 2011 criteria or known diabetes at follow-up. Logistic regression models were used to determine the associations of the glycaemic markers, fasting insulin and HOMA-IR with incident type 2 diabetes. Restricted cubic spline logistic regressions were conducted to investigate the shape of the associations. Results: After a mean follow-up duration of 6.4 (SD 0.5) years, 152 participants developed diabetes (11.3%); the majority were screen detected by high FPG. In multivariate adjusted models, ORs (95% CI) for incident type 2 diabetes for the highest quintile in comparison with the lowest quintile were 9.0 (4.4, 18.5) for FPG, 6.1 (2.9, 12.7) for 2hPG, 3.8 (2.0, 7.2) for HbA1c, 1.9 (0.9, 3.6) for fasting insulin and 2.8 (1.4, 5.6) for HOMA-IR. The associations of FPG and HbA1c with incident diabetes were non-linear, rising more steeply at higher values. Conclusions/interpretation: FPG was most strongly associated with incident diabetes, followed by 2hPG, HbA1c, HOMA-IR and fasting insulin. The strong association with FPG is probably because FPG is the most frequent marker for diabetes diagnosis. Non-linearity of associations between glycaemic markers and incident type 2 diabetes should be taken into account when estimating future risk of type 2 diabetes based on glycaemic markers.

Purpose Data on the relation between linoleic acid (LA) and alpha-linolenic acid (ALA) and type 2 diabetes mellitus (T2DM) risk are scarce and inconsistent. The aim of this study was to investigate the association of serum LA and ALA with fasting and 2 h post-load plasma glucose and glycated hemoglobin (HbA1c). Method This study included 667 participants from third examination (2000) of the population-based Hoorn study in which individuals with glucose intolerance were overrepresented. Fatty acid profiles in serum total lipids were measured at baseline, in 2000. Diabetes risk markers were measured at baseline and follow-up in 2008. Linear regression models were used in cross-sectional and prospective analyses. Results In cross-sectional analyses (n = 667), serum LA was inversely associated with plasma glucose, both in fasting conditions (B = −0.024 [−0.045, −0.002]) and 2 h after glucose tolerance test (B = −0.099 [−0.158, −0.039]), but not with HbA1c (B = 0.000 [−0.014, 0.013]), after adjustment for relevant factors. In prospective analyses (n = 257), serum LA was not associated with fasting (B = 0.003 [−0.019, 0.025]) or post-load glucose (B = −0.026 [−0.100, 0.049]). Furthermore, no significant associations were found between serum ALA and glucose metabolism in cross-sectional or prospective analyses. Conclusions In this study, serum LA was inversely associated with fasting and post-load glucose in cross-sectional, but not in prospective analyses. Further studies are needed to elucidate the exact role of serum LA and ALA levels and dietary polyunsaturated fatty acids in glucose metabolism. Electronic supplementary material The online version of this article (doi:10.1007/s00394-016-1261-6) contains supplementary material, which is available to authorized users.

Objective: The aim of this study was to examine the relations between intakes of total, saturated, mono-unsaturated, poly-unsaturated and trans fatty acids (SFA, MUFA, PUFA and TFA), and their dietary sources (dairy, meat and plant) with markers of type 2 diabetes risk. Subjects/Methods: This was a cross-sectional analysis of baseline data of 5675 non-diabetic, middle-aged participants of the Netherlands Epidemiology of Obesity (NEO) study. Associations between habitual dietary intake and fasting and postprandial blood glucose and insulin, Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), HOMA of β-cell function (HOMA-B) and Disposition Index were assessed through multivariable linear regression models with adjustments for demographic, lifestyle and dietary factors. Results: Mean (s.d.) intakes in percent of energy (En%) were 34.4 (5.8) for total fatty acids, 12.4 (2.9) for SFA, 12.2 (2.4) for MUFA, 6.9 (1.9) for PUFA and 0.6 (0.2) for TFA. As compared with carbohydrates, only SFA was weakly inversely associated with fasting insulin, HOMA-IR and HOMA-B. When stratified by dietary source, all fatty acids from meat were positively associated with fasting insulin-total fatty acidsmeat (per 5 En%: 10.0%; 95% confidence interval: 4.0, 16.3), SFAmeat (per 1 En%: 3.7%; 0.4, 7.2), MUFAmeat (per 1 En%: 5.0%; 2.0, 8.1), PUFAmeat (per 1 En%: 17.3%; 6.0, 29.7) and TFAmeat (per 0.1 En%: 10.5%; 3.2, 18.3). Similarly, all fatty acids from meat were positively associated with HOMA-IR and HOMA-B and inversely with Disposition Index. Conclusions: Our study suggests that the relations between fatty acid intakes and markers of type 2 diabetes risk may depend on the dietary sources of the fatty acids. More epidemiological studies on diet and cardiometabolic disease are needed, addressing possible interactions between nutrients and their dietary sources.

Varying the macronutrient composition of meals alters acute postprandial responses, but the effect sizes for specific macronutrient exchanges have not been quantified by systematic reviews. Therefore the aim is to quantify the effect size of exchanging fat for carbohydrates in mixed meals on postprandial glucose (PPG), insulin (PPI), triglycerides (PPTG), and free fatty acids (PPFFA) responses by performing a systematic review and meta-analysis of randomized controlled trials. A systematic literature search was undertaken on randomized controlled trials comparing isocaloric high fat with high carbohydrate meals, with comparable protein contents and at least one postprandial glycemic- and one lipid outcome. The outcome data were extracted and expressed as mean postprandial levels over 2 h. Ten studies involving 14 comparisons met the eligibility criteria. Data were available for meta-analysis from 347 participants, consuming mixed meals containing 250-1003 kcal, and total fat contents of 33.3-75.6 percentage of energy (en%) (intervention) versus 0-31.7 en% (control). Each 10en% increase in fat, replacing carbohydrates produced a mean reduction in PPG of 0.32 mmol/l (95% CI -0.64 to -0.00, p = 0.047), a reduction in PPI of 18.2 pmol/l (95% CI -24.86 to -11.54), an increase in PPTG of 0.06 mmol/l (95% CI 0.02 to 0.09, p = 0.004), with no statistically significant effect on PPFFA. Modest exchange of carbohydrates for fats in mixed meals significantly reduces PPG and PPI and increases PPTG responses. The quantitative relationships derived here may be applied to predict responses, and to design and optimize meal macronutrient compositions in dietary intervention studies.

Visceral adipose tissue (VAT) and hepatic triglyceride content (HTGC) are major risk factors for cardiometabolic diseases. Objective: We aimed to investigate the association of dietary intake of the main food groups with VAT and HTGC in middle-aged men and women. Methods: We used data from the Netherlands Epidemiology of Obesity study, a population-based study including 6671 participants aged 45-65 y at baseline. In this cross-sectional analysis, VAT and HTGC were assessed by magnetic resonance imaging and spectroscopy, respectively, as the primary outcomes. Habitual intake of main food groups (dairy, meat, fish, fruits and vegetables, sweet snacks, and fats and oils) was estimated through the use of a food-frequency questionnaire. We examined associations of intake of different food groups with VAT and HTGC by linear regression analysis stratified by sex and adjusted for age, smoking, education, ethnicity, physical activity, basal metabolic rate, energy-restricted diet, menopausal state, and total energy intake. Results: In women, a 100-g/d higher intake of dairy was associated with 2.0 cm2 less VAT (95% CI: -3.4, -0.7 cm2) and a 0.95-fold lower HTGC (95% CI: 0.90-, 0.99-fold). Moreover, a 100-g/d higher intake of fruit and vegetables was associated with 1.6 cm2 less VAT (95% CI: -2.9, -0.2 cm2) in women. Fruit and vegetables were negatively associated (0.95; 95% CI: 0.91, 1.00) with HTGC, and sweet snacks were positively associated (1.29; 95% CI: 1.03, 1.63). Patterns were weaker but similar in men. Fish intake was not associated with VAT or HTGC and plant-based fat and oil intake were only associated with VAT after adjustment for total body fat. Conclusions: Despite some variation in the strength of the associations between men and women, dietary intake of sweet snacks was positively associated with HTGC, and fruit and vegetable intake were negatively associated with visceral and liver fat content. Prospective studies are needed to confirm these results. The Netherlands Epidemiology of Obesity study is registered at clinicaltrials.gov with identifier NCT03410316. J Nutr 2019;149:304-313.

The objective of this meta-analysis was to investigate the effects of plant-derived polyunsaturated fatty acids (PUFAs) on glucose metabolism and insulin resistance. Scopus and PubMed databases were searched until January 2018. Eligible studies were randomized controlled feeding trials that investigated the effects of a diet high in plant-derived PUFA as compared with saturated fatty acids (SFA) or carbohydrates and measured markers of glucose metabolism and insulin resistance as outcomes. Data from 13 relevant studies (19 comparisons of plant-derived PUFA with control) were retrieved. Plant-derived PUFA did not significantly affect fasting glucose (−0.01 mmol/L (95 % CI − 0.06 to 0.03 mmol/L)), but lowered fasting insulin by 2.6 pmol/L (−4.9 to −0.2 pmol/L) and homeostatic model assessment-insulin resistance (HOMA-IR) by 0.12 units (-0.23 to − 0.01 units). In dose–response analyses, a 5% increase in energy (En%) from PUFA significantly reduced insulin by 5.8 pmol/L (95% CI −10.2 to −1.3 pmol/L), but not glucose (change −0.07, 95% CI −0.17 to 0.04 mmol/L) and HOMA-IR (change − 0.24, 95% CI −0.56 to 0.07 units). In subgroup analyses, studies with higher PUFA dose (upper tertiles) reduced insulin (-6.7, –10.5 to −2.9 pmol/L) and HOMA-IR (-0.28, –0.45 to −0.12 units), but not glucose (−0.09, 95% CI −0.18 to 0.01 mmol/L), as compared with an isocaloric control. Subgroup analyses showed no differences in effects between SFA and carbohydrates as replacement nutrients (p interaction ≥0.05). Evidence from randomized controlled trials indicated that plant-derived PUFA as an isocaloric replacement for SFA or carbohydrates probably reduces fasting insulin and HOMA-IR in populations without diabetes.

We aimed to examine heterogeneity in glucose response curves during an oral glucose tolerance test with multiple measurements and to compare cardiometabolic risk profiles between identified glucose response curve groups.We analyzed data from 1,267 individuals without diabetes from five studies in Denmark, the Netherlands and the USA. Each study included between 5 and 11 measurements at different time points during a 2-h oral glucose tolerance test,resulting in 9,602 plasma glucose measurements. Latent class trajectories with a cubic specification for time were fitted to identify different patterns of plasma glucose change during the oral glucose tolerance test. Cardiometabolic riskfactor profiles were compared between the identified groups. Using latent class trajectory analysis, five glucose response curves were identified. Despite similar fasting and 2-h values, glucose peaks and peak times varied greatly between groups, ranging from 7–12 mmol/L, and 35–70 min. The group with the lowest and earliest plasma glucose peak had the lowest estimated cardiovascular risk, while the group with the most delayed plasma glucose peak and the highest 2-h value had the highest estimated risk. One group, with normal fasting and 2-h values, exhibited an unusual profile, with the highest glucose peak and the highest proportion of smokers and men. The heterogeneity in glucose response curves and the distinct cardiometabolic risk profiles may reflect different underlying physiologies. Our results warrant more detailed studies to identify the source of the heterogeneity across the different phenotypes and whether these differences play a role in the development of type 2 diabetes and cardiovascular disease.

Introduction: Recent studies reported inverse associations between circulating levels of n-6 polyunsaturated fatty acids (PUFAs) and type 2 diabetes (T2D) risk, although whether intake of these fatty acids is associated T2D risk remains to be elucidated. Hypothesis: We examined the hypothesis that long-term intake of n-6 PUFAs, especially linoleic acid (LA), is associated with lower T2D risk. Methods: Diet was assessed using validated food-frequency questionnaires every 4 years in women participating in Nurses' Health Study (NHS, n=83,648) and NHSII (n=88,610), and men participating in the Health Professionals Follow-Up Study (n=41,771). Incident T2D was identified by self-report and confirmed by a supplemental questionnaire. Results: N-6 PUFAs accounted for 4.7-6.8% total energy on average, and 98% of n-6 PUFA intake was from LA. We identified 18,442 T2D cases during 4.93 million person-years of follow-up. In multivariate-adjusted models, HRs (95%CIs) of T2D comparing extreme quintiles (high vs low) were 0.92 (0.88, 0.97; P trend =0.01) for LA intake, and 1.14 (1.08, 1.20; P trend table below). For each 2% energy from LA intake, T2D risk was 17% lower for iso-calorically replacing trans fats, and 4% lower for iso-calorically replacing total carbohydrates, and refined carbohydrates (All P values Conclusion: Higher LA consumption is associated with a lower T2D risk, especially when substituting for SFAs, trans fats, or refined carbohydrates. AA mainly comes from poultry and meats, and is associated with higher T2D risk.

BACKGROUND: Chronic cardiometabolic diseases, including cardiovascular disease (CVD), type 2 diabetes (T2D) and chronic kidney disease (CKD), share many modifiable risk factors and can be prevented using combined prevention programs. Valid risk prediction tools are needed to accurately identify individuals at risk.OBJECTIVE: We aimed to validate a previously developed non-invasive risk prediction tool for predicting the combined 7-year-risk for chronic cardiometabolic diseases.DESIGN: The previously developed tool is stratified for sex and contains the predictors age, BMI, waist circumference, use of antihypertensives, smoking, family history of myocardial infarction/stroke, and family history of diabetes. This tool was externally validated, evaluating model performance using area under the receiver operating characteristic curve (AUC)-assessing discrimination-and Hosmer-Lemeshow goodness-of-fit (HL) statistics-assessing calibration. The intercept was recalibrated to improve calibration performance.PARTICIPANTS: The risk prediction tool was validated in 3544 participants from the Australian Diabetes, Obesity and Lifestyle Study (AusDiab).KEY RESULTS: Discrimination was acceptable, with an AUC of 0.78 (95% CI 0.75-0.81) in men and 0.78 (95% CI 0.74-0.81) in women. Calibration was poor (HL statistic: p CONCLUSIONS: Validation of our previously developed tool showed robust discriminative performance across populations. Model recalibration is recommended to account for different disease rates. Our risk prediction tool can be useful in large-scale prevention programs for identifying those in need of further risk profiling because of their increased risk for chronic cardiometabolic diseases.

We conducted the first prospective observational study in which we examined the association between incretin responses to an oral glucose tolerance test (OGTT) and mixed meal test (MMT) at baseline and changes in fasting glucose levels 7 years later, in individuals who were non-diabetic at baseline. We used data from the Hoorn Meal Study; a population-based cohort study among 121 subjects, aged 61.0±6.7y. GIP and GLP-1 responses were determined at baseline and expressed as total and incremental area under the curve (tAUC and iAUC). The association between incretin response at baseline and changes in fasting glucose levels was assessed using linear regression. The average change in glucose over 7 years was 0.43 ± 0.5 mmol/l. For GIP, no significant associations were observed with changes in fasting glucose levels. In contrast, participants within the middle and highest tertile of GLP-1 iAUC responses to OGTT had significantly smaller increases (actually decreases) in fasting glucose levels; -0.28 (95% confidence interval: -0.54;-0.01) mmol/l and -0.39 (-0.67;-0.10) mmol/l, respectively, compared to those in the lowest tertile. The same trend was observed for tAUC GLP-1 following OGTT (highest tertile: -0.32 (0.61;-0.04) mmol/l as compared to the lowest tertile). No significant associations were observed for GLP-1 responses following MMT. In conclusion, within our non-diabetic population-based cohort, a low GLP-1 response to OGTT was associated with a steeper increase in fasting glucose levels during 7 years of follow-up. This suggests that a reduced GLP-1 response precedes glucose deterioration and may play a role in the etiology of type 2 diabetes mellitus.

Aims: To evaluate whether participant characteristics and way of expressing circulating fatty acids (FA) influence the strengths of associations between self-reported intake and circulating levels of linoleic acid (LA), alpha-linolenic acid (ALA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA). Methods: Cross-sectional analyses were performed in pooled data from the CODAM (n = 469) and Hoorn (n = 702) studies. Circulating FA were measured by gas liquid chromatography and expressed as proportions (% of total FA) and concentrations (µg/mL). Dietary intakes were calculated from a validated food frequency questionnaire. Effects of participant characteristics on associations between dietary and circulating FA were calculated using interaction analyses. Results: Standardized regression coefficients between dietary FA and proportions of circulating FA (% of total FA) were LA β = 0.28, ALA β = 0.13, EPA β = 0.34, and DHA β = 0.45. Body mass index (BMI), waist circumference, and presence of CVD influenced associations for LA; gender influenced LA, EPA, and DHA; alcohol intake influenced LA and DHA; and glucose tolerance status influenced ALA (p values interaction Conclusions: This study suggests that characteristics such as BMI, alcohol intake, and expressing circulating FA as proportions or concentrations, influence associations between dietary and circulating FA.

Background/objective There is substantial interest in dietary approaches to reducing postprandial glucose (PPG) responses, but the quantitative contribution of PPG to longer-term glycemic control (reflected in glycated hemoglobin, HbA1c) in the general population is not known. This study quantified the associations of preprandial glucose exposure, PPG exposure, and glycemic variability with HbA1c and estimated the explained variance in HbA1c in individuals with and without type 2 diabetes (T2D). Subjects/methods Participants in the A1c-Derived Average Glucose (ADAG) study without T2D (n = 77) or with non-insulin-treated T2D and HbA1cHbA1c , n = 63) or HbA1c ≥ 6.5% (T2DHbA1c ≥ 6.5%, n = 34) were included in this analysis. Indices of preprandial glucose, PPG, and glycemic variability were calculated from continuous glucose monitoring during four periods over 12 weeks prior to HbA1c measurement. In linear regression models, we estimated the associations of the glycemic exposures with HbA1c and calculated the proportion of variance in HbA1c explained by glycemic and non-glycemic factors (age, sex, body mass index, and ethnicity). Results The factors in the analysis explained 35% of the variance in HbA1c in non-diabetic individuals, 49% in T2DHbA1c , and 78% in T2DHbA1c ≥ 6.5%. In non-diabetic individuals PPG exposure was associated with HbA1c in confounder-adjusted analyses (P HbA1c group, all glycemic measures were associated with HbA1c (P HbA1c ≥ 6.5%, these glycemic exposures accounted for more than 50% of the variation in HbA1c and with equal relative contributions. Conclusions Among the glycemic exposures, PPG exposure was most strongly predictive of HbA1c in non-diabetic individuals, suggesting that interventions targeting lowering of the PPG response may be beneficial for long-term glycemic maintenance. In T2D, preprandial glucose and PPG exposure contributed equally to HbA1c.

Consumption of carbohydrate-containing foods leads to transient postprandial rises in blood glucose concentrations that vary between food types. Higher postprandial glycaemic exposures have particularly been implicated in the development of chronic cardiometabolic diseases. Reducing such diet-related exposures may be beneficial not only for diabetic patients but also for the general population. A variety of markers have been used to track different aspects of glycaemic exposures, with most of the relevant knowledge derived from diabetic patients. The assessment of glycaemic exposures among the non-diabetic population may require other, more sensitive markers. The present report summarises key messages of presentations and related discussions from a workshop organised by Unilever intended to consider currently applied markers of glycaemic exposure. The particular focus of the meeting was to identify the potential applicability of glycaemic exposure markers for studying dietary effects in the non-diabetic population. Workshop participants concluded that markers of glycaemic exposures are sparsely used in intervention studies among non-diabetic populations. Continuous glucose monitoring remains the optimal approach to directly assess glycaemic exposure. Markers of glycaemic exposure such as glycated Hb, fructosamine, glycated albumin, 1,5-anhydroglucitol and advanced glycation end products can be preferred dependent on the aspect of interest (period of exposure and glucose variability). For all the markers of glycaemia, the responsiveness to interventions will probably be smaller among the non-diabetic than among the diabetic population. Further validation and acceptance of existing glycaemic exposure markers applied among the non-diabetic population would aid food innovation and better design of dietary interventions targeting glycaemic exposure.

ObjectiveTo i) compare incretin responses to oral glucose and mixed meal of diabetic patients with the normoglycaemic population and ii) to investigate whether incretin responses are associated with hypertriglyceridaemia and alanine aminotransferase (ALT) as liver fat marker.DesignA population-based study.MethodsA total of 163 persons with normal glucose metabolism (NGM), 20 with intermediate hyperglycaemia and 20 with type 2 diabetes aged 40–65 years participated. Participants received a mixed meal and oral glucose load on separate occasions. Glucagon-like peptide 1 (GLP-1), glucose-dependent insulinotropic polypeptide (GIP) and glucagon profiles were analysed as total area under the curve (tAUC) and incremental area under the curve.ResultsIn diabetic patients compared with persons with NGM, we found increased GLP-1 secretion (tAUC per hour) following oral glucose (23.2 pmol/l (95% CI 17.7–28.7) vs 18.0 (95% CI 16.9–19.1), PPConclusionThis study confirms that in type 2 diabetes, GLP-1 secretion is generally preserved and that GIP secretion is exaggerated. The mechanism underlying the divergent associations of GLP-1 and GIP metabolism with fat metabolism and liver fat accumulation warrants further study.

Aim: To systematically review data from different countries on population intakes of total fat, saturated fatty acids (SFA) and polyunsaturated fatty acids (PUFA), and to compare these to recommendations from the Food and Agriculture Organization of the United Nations/the World Health Organization (FAO/WHO). Methods: Data from national dietary surveys or population studies published from 1995 were searched via MEDLINE, Web of Science and websites of national public health institutes. Results: Fatty acid intake data from 40 countries were included. Total fat intake ranged from 11.1 to 46.2 percent of energy intake (% E), SFA from 2.9 to 20.9% E and PUFA from 2.8 to 11.3% E. The mean intakes met the recommendation for total fat (20-35% E), SFA (10% E and in 13 of 27 countries, the majority of the population had PUFA intakes Conclusions: In many countries, the fatty acids intake of adults does not meet the levels that are recommended to prevent chronic diseases. The relation between SFA and PUFA intakes shows that lower intakes of SFA in the populations are not accompanied by higher intakes of PUFA, as is recommended for preventing coronary heart disease.

Numerous studies have examined relationships between disease biomarkers (such as blood lipids) and levels of circulating or cellular fatty acids. In such association studies, fatty acids have typically been expressed as the percentage of a particular fatty acid relative to the total fatty acids in a sample. Using two human cohorts, this study examined relationships between blood lipids (TAG, and LDL, HDL or total cholesterol) and circulating fatty acids expressed either as a percentage of total or as concentration in serum. The direction of the correlation between stearic acid, linoleic acid, dihomo-γ-linolenic acid, arachidonic acid and DHA and circulating TAG reversed when fatty acids were expressed as concentrations v. a percentage of total. Similar reversals were observed for these fatty acids when examining their associations with the ratio of total cholesterol:HDL-cholesterol. This reversal pattern was replicated in serum samples from both human cohorts. The correlations between blood lipids and fatty acids expressed as a percentage of total could be mathematically modelled from the concentration data. These data reveal that the different methods of expressing fatty acids lead to dissimilar correlations between blood lipids and certain fatty acids. This study raises important questions about how such reversals in association patterns impact the interpretation of numerous association studies evaluating fatty acids and their relationships with disease biomarkers or risk.

Objective: To increase the understanding of circulating fatty acids (FA) as biomarkers of FA intake, we investigated (1) determinants of circulating proportions of linoleic acid (LA), alpha-linolenic acid (ALA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA); and (2) the effect of demographic, lifestyle, and health factors on the relation between circulating and self-reported intake of LA, ALA, EPA, and DHA. Hypothesis: We hypothesized that demographic, lifestyle, and health factors influence the relation between circulating and self-reported intake of FA. Methods: Cross-sectional analysis in combined data from the CoDAM (n=472) and Hoorn study (n=708). Dietary FA intakes (% of total FA) were calculated from a validated 79-item semi-quantitative food frequency questionnaire. Fasting total fatty acids (% of total FA) in plasma (CoDAM) or serum (Hoorn) were measured by gas liquid chromatography. The variation in circulating proportions of FA explained by demographic, lifestyle and health factors was calculated by multivariable linear regression analysis. Correlation coefficients between circulating proportions of FA and self-reported FA intakes were calculated by standardized multivariable linear regression analysis adjusted for demographic, lifestyle, and health factors. To assess the influence of specific factors on correlations, stratified analyses were performed and interactions were calculated. Results: Self-reported intakes were the primary determinants of circulating proportions of LA (partial R2: 7%), ALA (2%), EPA (9%) and DHA (16%). Standardized regression coefficients between circulating and self-reported FA were: LA β=0.280 (95% Confidence Interval: 0.227-0.333), ALA β=0.130 (0.071-0.188), EPA β=0.338 (0.281-0.395), and DHA β=0.450 (0.397-0.503). Other determinants of circulating FA were the use of lipid lowering drugs, waist circumference and sex for LA; prevalence of type 2 diabetes mellitus, age, sex, and alcohol intake for EPA; and age for DHA. The correlation between circulating and dietary LA was stronger among people with a lower vs higher waist circumference and higher vs lower alcohol intake (interaction: p Conclusion: Self-reported intake of FA is the primary, but not the only determinant of circulating proportions of LA, ALA, EPA and DHA. This analysis indicates that demographic, lifestyle, and health characteristics may influence the relation between circulating proportions and self-reported intake of FA. Improved understanding is needed of factors determining circulating FA and the implication for their use as biomarkers of dietary intake in different subgroups.

OBJECTIVE Heart failure is common in individuals with type 2 diabetes, and early detection of individuals at risk may offer opportunities for prevention. We aimed to explore 1) prospective associations of B-type natriuretic peptide (BNP) levels in a non–heart failure range with changes in markers of left ventricular (LV) function and 2) possible effect modification by type 2 diabetes in a population-based cohort. RESEARCH DESIGN AND METHODS Echocardiographic measurements were performed at baseline (2000–2001) and follow-up (2007–2009), together with standardized physical examinations and BNP measurements on 300 individuals (mean age 66 years, 32% with type 2 diabetes) of the longitudinal Hoorn Study. Multivariate linear regression analyses were performed to investigate associations of baseline BNP ( RESULTS In all individuals, higher BNP was associated with 8-year increases in left atrial volume index. Higher BNP was also associated with increasing LV mass index and E/e′. These associations were significantly stronger in individuals with type 2 diabetes compared with the nonsignificant associations in individuals without type 2 diabetes. CONCLUSIONS This 8-year follow-up study shows that higher BNP levels in a non–heart failure range were associated with an increased LV mass and deteriorated LV diastolic function, particularly in individuals with type 2 diabetes. This implies that the presence or absence of type 2 diabetes should be taken into account if BNP levels are used to assess future heart failure risk.

OBJECTIVE To investigate relative contributions of glucose status and arterial stiffness to markers of left ventricular (LV) systolic and diastolic dysfunction after 8 years of follow-up. RESEARCH DESIGN AND METHODS In the population-based prospective Hoorn Study, 394 individuals with preserved LV systolic and diastolic function participated, of whom 87 had impaired glucose metabolism and 128 had type 2 diabetes. Measurements including arterial ultrasound and echocardiography were performed according to standardized protocols. RESULTS The presence of type 2 diabetes was associated with more severe LV systolic and diastolic dysfunction 8 years later: LV ejection fraction was 2.98% (95% CI 0.46–5.51) lower, and left atrial (LA) volume index, LV mass index, and tissue Doppler-derived E/e′ were 3.71 mL/m2 (1.20–6.22), 5.86 g/m2.7 (2.94–8.78), and 1.64 units (0.95–2.33) higher, respectively. Furthermore, presence of impaired glucose metabolism or type 2 diabetes was associated with 8-year increases in LV mass index. More arterial stiffness (measured as a lower distensibility) was associated with LV diastolic dysfunction 8 years later: LA volume index, LV mass index, and E/e′ at follow-up were higher. Subsequent adjustments for baseline mean arterial pressure and/or LV diastolic dysfunction did not eliminate these associations. Associations of type 2 diabetes and arterial stiffness with markers of LV diastolic dysfunction were largely independent of each other. CONCLUSIONS Both glucose status and arterial distensibility are independently associated with more severe LV diastolic dysfunction 8 years later and with deterioration of LV diastolic dysfunction. Therefore, type 2 diabetes and arterial stiffness may relate to LV diastolic dysfunction through different pathways.

OBJECTIVE Individuals at high risk for chronic cardiometabolic disease (cardiovascular disease [CVD], type 2 diabetes, and chronic kidney disease [CKD]) share many risk factors and would benefit from early intervention. We developed a nonlaboratory-based risk-assessment tool for identification of people at high cardiometabolic disease risk. RESEARCH DESIGN AND METHODS Data of three population-based cohorts from different regions of the Netherlands were merged. Participants were 2,840 men and 3,940 women, white, aged 28–85 years, free from CVD, type 2 diabetes, and CKD diagnosis at baseline. The outcome was developing cardiometabolic disease during 7 years follow-up. RESULTS Age, BMI, waist circumference, antihypertensive treatment, smoking, family history of myocardial infarction or stroke, and family history of diabetes were significant predictors, whereas former smoking, history of gestational diabetes, and use of lipid-lowering medication were not. The models showed acceptable calibration (Hosmer and Lemeshow statistics, P > 0.05) and discrimination (area under the receiver operating characteristic [ROC] curve 0.82 [95% CI 0.81–0.83] for women and 0.80 [0.78–0.82] for men). Discrimination of individual outcomes was lowest for diabetes (area under the ROC curve 0.70 for men and 0.73 for women) and highest for CVD mortality (0.83 for men and 0.85 for women). CONCLUSIONS We demonstrate that a single risk stratification tool can identify people at high risk for future CVD, type 2 diabetes, and/or CKD. The present risk-assessment tool can be used for referring the highest risk individuals to health care for further (multivariable) risk assessment and may as such serve as an important part of prevention programs targeting chronic cardiometabolic disease.

Diabet. Med. 28, 1078–1081 (2011) Abstract Aims The Finnish Diabetes Risk Score (FINDRISC) is widely used for risk stratification in Type 2 diabetes prevention programmes. Estimates of β-cell function vary widely in people without diabetes and reduced insulin secretion has been described in people at risk for diabetes. The aim of this analysis was to evaluate FINDRISC as a tool to characterize reduced β-cell function in individuals without known diabetes. Methods In this population-based cohort from the Hoorn municipal registry, subjects received an oral glucose tolerance test and a meal tolerance test on separate days, in random order, within 2 weeks. One hundred and eighty-six subjects, age 41–66 years, with no known Type 2 diabetes were included. Of those, 163 (87.6%) had normal glucose metabolism and 23 (12.4%) had abnormal glucose metabolism (19 with impaired glucose metabolism; four with newly diagnosed Type 2 diabetes based on study results). Insulin sensitivity and β-cell function (classical: insulinogenic index; ratio of areas under insulin/glucose curves; model-based: glucose sensitivity; rate sensitivity; potentiation) estimates were calculated from oral glucose tolerance test and meal tolerance test data. Results FINDRISC was associated with insulin sensitivity (r = −0.41, P

OBJECTIVE To identify distinct developmental patterns of diabetic retinopathy (DR) and assess the risk factor levels of patients in these clusters. RESEARCH DESIGN AND METHODS A cohort of 3,343 patients with type 2 diabetes mellitus (T2DM) monitored and treated in the Diabetes Care System West-Friesland, the Netherlands, was followed from 2 to 6 years. Risk factors were measured, and two-field fundus photographs were taken annually and graded according to the EURODIAB study group. Latent class growth modeling was used to identify distinct developmental patterns of DR over time. RESULTS Five clusters of patients with distinct developmental patterns of DR were identified: A, patients without any signs of DR (88.9%); B, patients with a slow regression from minimal background to no DR (4.9%); C, patients with a slow progression from minimal background to moderate nonproliferative DR (4.0%); D, patients with a fast progression from minimal or moderate nonproliferative to (pre)proliferative or treated DR (1.4%); and E, patients with persistent proliferative DR (0.8%). Patients in clusters A and B were characterized by lower risk factor levels, such as diabetes duration, HbA1c, and systolic blood pressure compared with patients in progressive clusters (C–E). CONCLUSIONS Clusters of patients with T2DM with markedly different patterns of DR development were identified, including a cluster with regression of DR. These clusters enable a more detailed examination of the influence of various risk factors on DR.

Aims/hypothesis: The Finnish diabetes risk questionnaire is a widely used, simple tool for identification of those at risk for drug-treated type 2 diabetes. We updated the risk questionnaire by using clinically diagnosed and screen-detected type 2 diabetes instead of drug-treated diabetes as an endpoint and by considering additional predictors.Methods: Data from 18,301 participants in studies of the Evaluation of Screening and Early Detection Strategies for Type 2 Diabetes and Impaired Glucose Tolerance (DETECT-2) project with baseline and follow-up information on oral glucose tolerance status were included. Incidence of type 2 diabetes within 5 years was used as the outcome variable. Improvement in discrimination and classification of the logistic regression model was assessed by the area under the receiver-operating characteristic (ROC) curve and by the net reclassification improvement. Internal validation was by bootstrapping techniques.Results: Of the 18,301 participants, 844 developed type 2 diabetes in a period of 5 years (4.6%). The Finnish risk score had an area under the ROC curve of 0.742 (95% CI 0.726–0.758). Re-estimation of the regression coefficients improved the area under the ROC curve to 0.766 (95% CI 0.750–0.783). Additional items such as male sex, smoking and family history of diabetes (parent, sibling or both) improved the area under the ROC curve and net reclassification. Bootstrapping showed good internal validity.Conclusions/interpretation: The predictive value of the original Finnish risk questionnaire could be improved by adding information on sex, smoking and family history of diabetes. The DETECT-2 update of the Finnish diabetes risk questionnaire is an adequate and robust predictor for future screen-detected and clinically diagnosed type 2 diabetes in Europid populations.

OBJECTIVE To investigate the relationship among A1C, fasting plasma glucose (FPG), and 2-h postload plasma glucose in the Dutch general population and to evaluate the results of using A1C for screening and diagnosis of diabetes. RESEARCH DESIGN AND METHODS In 2006–2007, 2,753 participants of the New Hoorn Study, aged 40–65 years, who were randomly selected from the population of Hoorn, the Netherlands, underwent an oral glucose tolerance test (OGTT). Glucose status (normal glucose metabolism [NGM], intermediate hyperglycemia, newly diagnosed diabetes, and known diabetes) was defined by the 2006 World Health Organization criteria. Spearman correlations were used to investigate the agreement between markers of hyperglycemia, and a receiver operating characteristic (ROC) curve was calculated to evaluate the use of A1C to identify newly diagnosed diabetes. RESULTS In the total population, the correlations between fasting plasma glucose and A1C and between 2-h postload plasma glucose and A1C were 0.46 and 0.33, respectively. In patients with known diabetes, these correlations were 0.71 and 0.79. An A1C level of ≥5.8%, representing 12% of the population, had the highest combination of sensitivity (72%) and specificity (91%) for identifying newly diagnosed diabetes. This cutoff point would identify 72% of the patients with newly diagnosed diabetes and include 30% of the individuals with intermediate hyperglycemia. CONCLUSIONS In patients with known diabetes, correlations between glucose and A1C are strong; however, moderate correlations were found in the general population. In addition, based on the diagnostic properties of A1C defined by ROC curve analysis, the advantage of A1C compared with OGTT for the diagnosis of diabetes is limited.

Early insulin secretion following a meal is representative for normal physiology and may depend on meal composition. To compare the effects of a fat-rich and a carbohydrate-rich mixed meal on insulinogenic index as a measure of early insulin secretion in normoglycemic women (NGM) and in women with type 2 diabetes mellitus (DM2), and to assess the relationship of anthropometric and metabolic factors with insulinogenic index.Postmenopausal women, 76 with NGM and 64 with DM2, received a fat-rich meal and a carbohydrate-rich meal on separate occasions. Early insulin response was estimated as insulinogenic index ( big up tri, Deltainsulin(0-30 min)/ big up tri, Deltaglucose(0-30 min)) for each meal. Associations of fasting and postprandial triglycerides, body mass index, waist and hip circumference and alanine aminotransferase with insulinogenic indices were determined.Women with NGM present with higher insulinogenic index than women with DM2. The insulinogenic index following the fat-rich meal ( big up tri, DeltaI(30)/ big up tri, DeltaG(30) (fat)) was higher than the index following the carbohydrate-rich meal (big up tri, DeltaI(30)/ big up tri, DeltaG(30) (CH)) (P0.05 in women with DM2, and not significant in women with NGM). In women with DM2, homeostasis model assessment for insulin resistance was positively associated with big up tri, DeltaI(30)/ big up tri, DeltaG(30) (CH). In women with NGM, waist circumference was independently and inversely associated with big up tri, DeltaI(30)/ big up tri, DeltaG(30) (fat) and with big up tri, DeltaI(30)/ big up tri, DeltaG(30) (CH); hip circumference was positively associated with big up tri, DeltaI(30)/ big up tri, DeltaG(30) (fat).The insulinogenic index following the fat-rich meal was higher than following the isocaloric carbohydrate-rich meal, which might favorably affect postprandial glucose excursions, especially in women with DM2. The association between a larger waist circumference and a lower meal-induced insulinogenic index in women with NGM requires further mechanistic studies.

The present study aimed to compare the associations of postprandial glucose (ppGL) and postprandial triglycerides (ppTG) with carotid intima media thickness (cIMT) in women with normal glucose metabolism (NGM) and type 2 diabetes (DM2). Post-menopausal women (76 with NGM, 78 with DM2), received two consecutive fat-rich and two consecutive carbohydrate-rich meals on separate occasions. Blood samples were taken before and 1, 2, 4, 6 and 8h following breakfast; lunch was given at t=4. Ultrasound imaging of the carotid artery was performed to measure cIMT. In women with NGM, an increase of 1.0 mmol/l glucose following the fat-rich meals was associated with a 50 microm cIMT increase (p=0.04), and following the carbohydrate meals, an increase of 1.8 mmol/l glucose was associated with a 50 microm larger cIMT (p=0.08). These associations were not explained by classical cardiovascular risk factors. However, no association between ppGL and cIMT was found in women with DM2 and ppTG were not associated with cIMT. The association between ppGL and cIMT in normoglycaemic women suggests that ppGL in the normal range is a marker or a risk factor for atherosclerosis. Postprandial glucose levels might be a better indicator of risk than post-OGTT glucose levels or triglyceride levels.

Patients with type 2 diabetes mellitus (DM2) have an increased risk of cardiovascular disease (CVD). Myeloperoxidase (MPO), expressed in leukocytes and released upon activation, is associated with CVD and endothelial dysfunction. Postprandial leukocyte recruitment and activation with subsequent MPO release may contribute to atherosclerosis and CVD. We hypothesized that MPO may increase in the postprandial state because of postprandial leukocyte recruitment and/or activation, especially in subjects with DM2. One hundred postmenopausal women, aged 50 to 65 years (66 with normal glucose metabolism [NGM] and 34 with DM2), received 2 consecutive fat-rich meals and 2 consecutive carbohydrate-rich meals on separate occasions. Blood samples were taken before (t = 0) and at 2, 4, and 8 hours after breakfast; lunch was given at t = 4. Plasma MPO concentration was measured by sandwich enzyme-linked immunosorbent assay. The number of leukocytes in fasting blood samples was higher in DM2 compared with NGM (6.1 +/- 1.4 and 5.4 +/- 1.2 x 10(9)/L, respectively; P.05). Baseline MPO concentration did not significantly differ between NGM and DM2 (51.4 +/- 12.9 and 54.5 +/- 18.4 mug/L, respectively; P = .39). Baseline MPO was positively associated with leukocytes (r = 0.20, P.05) and inversely associated with high-density lipoprotein cholesterol (r = -0.22, P.05). Leukocytes increased from 5.0 +/- 1.5 to 6.1 +/- 1.5 x 10(9)/L and from 5.8 +/- 1.4 to 6.6 +/- 1.4 x 10(9)/L in NGM and DM2, respectively (both P.01), after the fat-rich meals. In contrast to our hypothesized increase in MPO, we found a significant decrease in MPO in NGM (both meal types) and DM2 (fat-rich meals only). Our findings provide no support to our initial hypothesis that meal-induced release of MPO might be a mechanism that contributes to CVD risk.

Both postprandial hyperglycemia and hypertriglyceridemia have been identified as risk markers for cardiovascular disease, but parameters associated with these postprandial responses are largely unknown. The objective was to assess whether usually measured clinical and biochemical parameters can predict postprandial glucose and triglyceride responses and whether these responses are associated with each other. Postmenopausal women, 76 with normal glucose metabolism (NGM) and 41 with type 2 diabetes mellitus (T2DM), received 2 consecutive fat-rich meals and carbohydrate-rich meals on separate occasions. Blood samples were taken before and at t = 1, 2, 4, 6, and 8 hours after breakfast; lunch was given at t = 4 hours. Regression analysis was performed with incremental area under the postprandial triglyceride curve (triglyceride-iAUC) and glucose curve (glucose-iAUC) after fat-rich and carbohydrate-rich meals, respectively. In women with NGM, fasting triglycerides, hemoglobin A(1c), total cholesterol, and, inversely, high-density lipoprotein cholesterol were independently associated with triglyceride-iAUC; and age and fasting triglycerides were independently associated with glucose-iAUC. In women with T2DM, fasting triglycerides were independently associated with triglyceride-iAUC, whereas hemoglobin A(1c) and fasting glucose were stronger than fasting triglycerides associated with glucose-iAUC. Glucose-iAUC and triglyceride-iAUC were associated with each other in women with T2DM, but not in those with NGM. The association between glucose-iAUC and triglyceride-iAUC in women with T2DM and the association of fasting triglycerides with both glucose-iAUC and triglyceride-iAUC in NGM and T2DM suggest a common underlying mechanism for postprandial increments in glucose and triglycerides, especially in T2DM. Commonly measured clinical and biochemical parameters can only partly explain postprandial glucose and triglyceride excursions.

Background: The association between saturated fatty acid (SFA) intake and ischemic heart disease (IHD) risk is debated. Objective: We sought to investigate whether dietary SFAs were associated with IHD risk and whether associations depended on 1) the substituting macronutrient, 2) the carbon chain length of SFAs, and 3) the SFA food source. Design: Baseline (1993-1997) SFA intake was measured with a foodfrequency questionnaire among 35,597 participants from the European Prospective Investigation into Cancer and Nutrition-Netherlands cohort. IHD risks were estimated with multivariable Cox regression for the substitution of SFAs with other macronutrients and for higher intakes of total SFAs, individual SFAs, and SFAs from different food sources. Results: During 12 y of follow-up, 1807 IHD events occurred. Total SFA intake was associated with a lower IHD risk (HR per 5% of energy: 0.83; 95% CI: 0.74, 0.93). Substituting SFAs with animal protein, cis monounsaturated fatty acids, polyunsaturated fatty acids (PUFAs), or carbohydrates was significantly associated with higher IHD risks (HR per 5% of energy: 1.27-1.37). Slightly lower IHD risks were observed for higher intakes of the sum of butyric (4:0) through capric (10:0) acid (HRSD: 0.93; 95% CI: 0.89, 0.99), myristic acid (14:0) (HRSD: 0.90; 95% CI: 0.83, 0.97), the sum of pentadecylic (15:0) and margaric (17:0) acid (HRSD: 0.91: 95% CI: 0.83, 0.99), and for SFAs from dairy sources, including butter (HRSD: 0.94; 95% CI: 0.90, 0.99), cheese (HRSD: 0.91; 95% CI: 0.86, 0.97), and milk and milk products (HRSD: 0.92; 95% CI: 0.86, 0.97). Conclusions: In this Dutch population, higher SFA intake was not associated with higher IHD risks. The lower IHD risk observed did not depend on the substituting macronutrient but appeared to be driven mainly by the sums of butyric through capric acid, the sum of pentadecylic and margaric acid, myristic acid, and SFAs from dairy sources. Residual confounding by cholesterol-lowering therapy and trans fat or limited variation in SFA and PUFA intake may explain our findings. Analyses need to be repeated in populations with larger differences in SFA intake and different SFA food sources.

OBJECTIVE—High proinsulin concentration may be a better predictor for cardiovascular disease (CVD) mortality than insulin concentration. Previous observations may have been confounded by glucose tolerance status or lack of precision because of high intraindividual variability. We investigated the longitudinal relation of means of duplicate measurements of insulin and proinsulin with all-cause and CVD mortality in a population-based cohort taking glucose tolerance status into account. RESEARCH DESIGN AND METHODS—Fasting and post–75-g glucose-load (2-h) glucose, insulin, and proinsulin values were determined in duplicate on separate days in 277 participants with normal glucose metabolism, 208 participants with impaired glucose metabolism, and 119 newly detected patients with type 2 diabetes of the Hoorn Study. Insulin resistance and β-cell function were estimated by homeostasis model assessment (HOMA-IR and HOMA-B, respectively), and the fasting proinsulin-to-insulin ratio was calculated. Subjects were followed with respect to mortality until January 2003. RESULTS—Fasting proinsulin levels were significantly associated with all-cause and CVD mortality. The hazard ratios (HRs) per increase in interquartile range adjusted for age and sex were 1.21 (95% CI 1.04–1.42) for all-cause mortality and 1.33 (1.06–1.66) for CVD mortality. Adjustment for glucose tolerance status and HOMA-IR did not substantially change the associations. CONCLUSIONS—Fasting proinsulin was associated with all-cause and CVD mortality, independent of glucose tolerance status and insulin resistance and largely independent of other CVD risk factors. Proinsulin might play a role in the relationship between insulin resistance and CVD.

Keywords Epidemiology.Prediction.Risk scores.Type 2 diabetesAbbreviationADDITION Anglo–Danish–Dutch Study of IntensiveTreatment in People with Screen DetectedDiabetes in Primary CareTo the Editor: In a recent commentary related to our paperon the performance of a risk score questionnaire forpredicting future diabetes [1], Wareham and Griffin makean interesting point about the effect of real life responserates on the true performance of a risk assessment [2]. Inour paper we evaluated the performance of the originalFinnish diabetes risk questionnaire to predict future

Background: A high consumption of the polyunsaturated fatty acids linoleic acid (LA) and alpha-linolenic acid (ALA) instead of saturated fatty acids is known to reduce CHD risk, but data on the relation between LA and ALA intake and Type 2 Diabetes Mellitus (T2DM) risk are limited and inconsistent. Plasma levels of LA and ALA provide a relatively accurate reflection of the intake over several weeks or months, because of the essential nature of these fatty acids. Objective: To investigate the association of the percentage of LA and ALA in plasma lipids with fasting plasma glucose (FPG), post-load glucose (PLG) and glycated hemoglobin (HbA1c) as markers of T2DM risk. Methods: The study population included 667 Dutch men and women, aged 50-75 years from the population-based Hoorn Study. Baseline data for the current study were collected between 2000 and 2001, with follow-up in 2008. Linear regression models were used in cross-sectional and prospective analyses. Results: In cross-sectional analyses, plasma LA (per %) was significantly and inversely associated with FPG ( B = -0.022 [-0.044, 0.000]) and PLG ( B = -0.096 [-0.155, -0.036]), but not with HbA1c ( B = 0.000 [-0.014, 0.014]), after adjustment for age, gender, total energy intake, BMI, waist-to-hip ratio, physical activity, fiber, dietary saturated fat intake, alcohol intake and education level. In prospective analyses, plasma LA was not significantly associated with FPG, PLG or HbA1c after adjustments for baseline glucose. In addition, no significant associations were found between plasma ALA and markers of T2DM risk in cross-sectional or prospective analyses. Conclusion: Plasma LA, but not ALA, was inversely associated with fasting and post-load glucose levels in cross-sectional, but not in prospective analyses. Further studies are needed to elucidate the exact role of plasma LA and ALA levels and dietary polyunsaturated fatty acids in glucose metabolism.

The incretin hormone glucagon-like peptide 1 (GLP-1) promotes glucose homeostasis and enhances β-cell function. GLP-1 receptor agonists (GLP-1 RAs) and dipeptidyl peptidase-4 (DPP-4) inhibitors, which inhibit the physiological inactivation of endogenous GLP-1, are used for the treatment of type 2 diabetes. Using the Metabochip, we identified three novel genetic loci with large effects (30–40%) on GLP-1–stimulated insulin secretion during hyperglycemic clamps in nondiabetic Caucasian individuals (TMEM114; CHST3 and CTRB1/2; n = 232; all P ≤ 8.8 × 10−7). rs7202877 near CTRB1/2, a known diabetes risk locus, also associated with an absolute 0.51 ± 0.16% (5.6 ± 1.7 mmol/mol) lower A1C response to DPP-4 inhibitor treatment in G-allele carriers, but there was no effect on GLP-1 RA treatment in type 2 diabetic patients (n = 527). Furthermore, in pancreatic tissue, we show that rs7202877 acts as expression quantitative trait locus for CTRB1 and CTRB2, encoding chymotrypsinogen, and increases fecal chymotrypsin activity in healthy carriers. Chymotrypsin is one of the most abundant digestive enzymes in the gut where it cleaves food proteins into smaller peptide fragments. Our data identify chymotrypsin in the regulation of the incretin pathway, development of diabetes, and response to DPP-4 inhibitor treatment.