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Objective: Food frequency questionnaires (FFQs) assess habitual dietary intake and are relatively inexpensive to process, but may take up to 60 minutes to complete. This article describes the validation of the Flower-FFQ, which consists of four short FFQs measuring the intake of energy and macronutrients or specific (micro)nutrients/foods that can be merged into one complete daily assessment using predefined algorithms. Design: Participants completed the Flower-FFQ and validated regular-FFQ (n=401). Urinary nitrogen (n=242) and potassium excretions (n=361) were measured. We evaluated: 1) group-level bias, 2) correlations, and 3) cross-classification. Setting: Observational study. Participants: Dutch adults, 54±11(mean±SD) years. Results: Flower-FFQ1, Flower-FFQ2, Flower-FFQ3, and Flower-FFQ4 were completed in ±24, 9, 8 and 9 minutes (±50 minutes total), respectively. The regular-FFQ was completed in ±43 minutes. Mean energy (flower vs. regular: 7953 vs. 8718 kJ/day) and macronutrient intakes (carbohydrates: 204 vs. 222 g/day; protein: 75 vs. 76 g/day; fat: 74 vs. 83 g/day; ethanol: 8 vs. 12 g/day) were comparatively similar. Spearman correlations between Flower-FFQ and regular-FFQ ranged from 0.60-0.80 for macronutrients and from 0.40-0.80 for micronutrients and foods. For all micronutrients and foods, ≥78% of the participants classified in the same/adjacent quartile. The flower-FFQ underestimated urinary nitrogen and potassium excretions by 24% and 18%; 75% and 73% of the participants ranked in the same/adjacent quartile. Conclusion: Completing the Flower-FFQ required 50 minutes with a maximum of 25 minutes per short FFQ. The Flower-FFQ has a moderate to good ranking ability for most nutrients and foods and performs sufficiently to study diet-disease associations.

Dietary glycaemic index (GI) and glycaemic load (GL) are indices used to quantify the effect of carbohydrate quality and quantity on postprandial glycaemia. GI/GL-health associations are widely studied but data on the validity of integrated GI/GL measurements are scarce. We evaluated the performance of a food-frequency questionnaire (FFQ) specifically developed to assess GI/GL. In total, 263 Dutch men and 212 women (aged 55 ± 11 years) completed a 58-item GI-FFQ, an 183-item general-FFQ and a 2-day 24 h-recall and donated blood for glycated haemoglobin (HbA1c) determination. The level of agreement between these methods was evaluated by (1) crossclassification, (2) correlations and (3) Bland and Altman plots. The three dietary assessment methods provided comparable mean intake estimates for total carbohydrates (range: 214–237 g/day), mono/disaccharides (100–107 g/day), polysaccharides (114–132 g/day), as well as bread, breakfast cereals, potatoes, pasta, rice, fruit, dairy, cakes/cookies and sweets. Mean (±SD) GI estimates were also comparable between the GI-FFQ (54 ± 3), general-FFQ (53 ± 4) and 24 h-recalls (53 ± 5). Mean (±SD) GI-FFQ GL (117 ± 37) was slightly lower than the general-FFQ GL (126 ± 38) and 24 h-recalls GL (127 ± 37). Classification of GI in quartiles was identical for the GI-FFQ and general-FFQ for 43% of the population (r = 0.58) and with 24 h-recalls for 35% of the population (de-attenuated r = 0.64). For GL, this was 48% (r = 0.65) and 44% (de-attenuated r = 0.74). Correlations between GI and HbA1c were low (r = −0.09 for GI-FFQ, r = −0.04 for general-FFQ and r = 0.07 for 24 h-recalls). In conclusion, compared to a general-FFQ and 24 h-recalls, the GI-FFQ showed a moderate to good relative validity for carbohydrates, carbohydrate-rich foods and GI/GL. No metric predicted HbA1c.

Background: Data on the relationship between protein intake and the risk of type 2 diabetes are conflicting.Objective: We studied prospective associations between the intake of total, plant-based, and animal protein and the risk of pre-diabetes and diabetes in 4 population-based studies included in the PREVIEW project.Methods: Analyses were conducted with the use of data from 3 European cohorts and 1 Canadian cohort, including 78,851 participants. Protein intake was assessed through the use of harmonized data from food-frequency questionnaires or 3-d dietary records. Cohort-specific incidence ratios (IRs) were estimated for pre-diabetes and diabetes, adjusting for general characteristics, lifestyle and dietary factors, disease history, and body mass index (BMI) and waist circumference; results were pooled based on a random-effects meta-analysis.Results: Higher total protein intake (g · kg-1 · d-1) was associated with lower incidences of pre-diabetes and diabetes (pooled IRs: 0.84; 95% CI: 0.82, 0.87 and 0.49; 95% CI: 0.28, 0.83, respectively); plant-based protein intake was the main determinant (pooled IRs: 0.83; 95% CI: 0.81, 0.86 and 0.53; 95% CI: 0.36, 0.76, respectively). Substituting 2 energy percentage (E%) protein at the expense of carbohydrates revealed increased risks of pre-diabetes and diabetes (pooled IRs: 1.04; 95% CI: 1.01, 1.07 and 1.09; 95% CI: 1.01, 1.18, respectively). Except for the associations between intakes of total protein and plant-based protein (g · kg-1 · d-1) and diabetes, all other associations became nonsignificant after adjustment for BMI and waist circumference.Conclusions: Higher protein intake (g · kg-1 · d-1) was associated with a lower risk of pre-diabetes and diabetes. Associations were substantially attenuated after adjustments for BMI and waist circumference, which demonstrates a crucial role for adiposity and may

OBJECTIVE The aim of the present cross-sectional study was to examine the association among physical activity (PA), sedentary time (ST), and cardiometabolic risk in adults with prediabetes. RESEARCH DESIGN AND METHODS Participants (n = 2,326; 25-70 years old, 67% female) from eight countries, with a BMI >25 kg · m22 and impaired fasting glucose (5.6-6.9 mmol · L21) or impaired glucose tolerance (7.8-11.0 mmol · L21 at 2 h), participated. Seven-day accelerometry objectively assessed PA levels and ST. RESULTS Multiple linear regression revealed that moderate-To-vigorous PA (MVPA) was negatively associated withHOMAof insulin resistance (HOMA-IR) (standardizedb =20.078 [95% CI20.128,20.027]), waist circumference (WC) (b =20.177 [20.122,20.134]), fasting insulin (b = 20.115 [20.158, 20.072]), 2-h glucose (b = 20.069 [20.112, 20.025]), triglycerides (b = 20.091 [20.138, 20.044]), and CRP (b = 20.086 [20.127, 20.045]). ST was positively associated with HOMA-IR (b = 0.175 [0.114, 0.236]), WC (b = 0.215 [0.026, 0.131]), fasting insulin (b = 0.155 [0.092, 0.219]), triglycerides (b = 0.106 [0.052, 0.16]), CRP (b = 0.106 [0.39, 0.172]), systolic blood pressure (BP) (b = 0.078 [0.026, 0.131]), and diastolic BP (b = 0.106 [0.39, 20.172]). Associations reported between total PA (counts · min21), and all risk factors were comparable or stronger than for MVPA: HOMA-IR (b = 20.151 [20.194, 20.107]), WC (b = 20.179 [20.224, 20.134]), fasting insulin (b = 20.139 [20.183, 20.096]), 2-h glucose (b = 20.088 [20.131, 20.045]), triglycerides (b = 20.117 [20.162, 20.071]), and CRP (b = 20.104 [20.146, 20.062]). CONCLUSIONS In adults with prediabetes, objectively measured PA and ST were associated with cardiometabolic risk markers. Total PA was at least as strongly associated with cardiometabolic risk markers as MVPA, which may imply that the accumulation of total PA over the day is as important as achieving the intensity of MVPA.

PurposeDuring the past decades, the number of people with cardiometabolic conditions substantially increased. To identify dietary factors that may be responsible for this increase in cardiometabolic conditions, the Nutrition Questionnaires plus (NQplus) study was initiated. The aim of this article is to provide an overview of the study design and baseline characteristics of the NQplus population.ParticipantsThe NQplus study is a prospective cohort study among 2048 Dutch men (52%) and women (48%) aged 20–70 years. Findings to date At baseline, we assessed habitual dietary intake, conducted physical examinations (measuring, eg, anthropometrics, body composition, blood pressure, pulse wave velocity, advanced glycation end product accumulation, cognitive performance), collected blood and 24-hour urine and administered a variety of validated demographic, health and lifestyle questionnaires. Participants had a mean BMI of 26.0±4.2 kg/m2, were mostly highly educated (63%), married or having a registered partnership (72%) and having a paid job (72%). Estimated daily energy and macronutrient intakes (mean±SD) were 8581±2531 kJ, 15±2energy (en%) of protein, 43±6 en% of carbohydrates, 36±5 en% of fat and 11±13 g of alcohol. Mean systolic blood pressure was 126±15 mm Hg, total cholesterol 5.3±1.1 mmol/L and haemoglobin A1c 36±5 mmol/mol. A total of 24% of the participants reported to be diagnosed with hypertension, 18% with hypercholesterolaemia and 4% with diabetes mellitus. All measurements were repeated after 1 and 2 years of follow-up.Future plansWe endeavour to continue measurements on the long-term. Moreover, dietary assessment methods used in the NQplus study will be extensively validated, that is, Food Frequency Questionnaires, 24-hour recalls and urinary and blood biomarkers of exposure. As such, the NQplus study will provide a unique opportunity to study many cross-sectional and longitudinal associations between diet and cardiometabolic health outcomes using the best

Higher-protein diets have been advocated for body-weight regulation for the past few decades. However, the potential health risks of these diets are still uncertain. We aimed to develop a protein score based on the quantity and source of protein, and to examine the association of the score with glycated haemoglobin (HbA1c) and estimated glomerular filtration rate (eGFR). Analyses were based on three population studies included in the PREVIEW project (PREVention of diabetes through lifestyle Intervention and population studies in Europe and around the World): NQplus, Lifelines, and the Young Finns Study. Cross-sectional data from food-frequency questionnaires (n = 76,777 subjects) were used to develop a protein score consisting of two components: 1) percentage of energy from total protein, and 2) plant to animal protein ratio. An inverse association between protein score and HbA1c (slope -0.02 ± 0.01 mmol/mol, p < 0.001) was seen in Lifelines. We found a positive association between the protein score and eGFR in Lifelines (slope 0.17 ± 0.02 mL/min/1.73 m², p < 0.0001). Protein scoring might be a useful tool to assess both the effect of quantity and source of protein on health parameters. Further studies are needed to validate this newly developed protein score.

Public health policies, including in Europe, are considering measures and recommendations to limit the intake of added or free sugars. For such policies to be efficient and monitored, a precise knowledge of the current situation regarding sugar intake in Europe is needed. This review summarizes published or re-analyzed data from 11 representative surveys in Belgium, France, Denmark, Hungary, Ireland, Italy, Norway, The Netherlands, Spain and the UK. Relative intakes were higher in children than in adults: total sugars ranged between 15 and 21% of energy intake in adults and between 16 and 26% in children. Added sugars (or non-milk extrinsic sugars (NMES), in the UK) contributed 7 to 11% of total energy intake in adults and represented a higher proportion of children's energy intake (11 to 17%). Educational level did not significantly affect intakes of total or added sugars in France and the Netherlands. Sweet products (e.g. confectionery, chocolates, cakes and biscuits, sugar, and jam) were major contributors to total sugars intake in all countries, genders and age groups, followed by fruits, beverages and dairy products. Fruits contributed more and beverages contributed less to adults' total sugars intakes than to children's. Added sugars were provided mostly by sweet products (36 to 61% in adults and 40 to 50% in children), followed by beverages (12 to 31% in adults and 20 to 34% in children, fruit juices excluded), then by dairy products (4 to 15% in adults and 6 to 18% in children). Caution is needed, however, as survey methodologies differ on important items such as dietary data collection, food composition tables or estimation of added sugars. Cross-country comparisons are thus not meaningful and overall information might thus not be robust enough to provide a solid basis for implementation of policy measures. Data nevertheless confirm that intakes of total and added sugars are high in the European countries considered, especially in children, and point to swe

Introduction: The differential associations of beer, wine, and spirit consumption on cardiovascular risk found in observational studies may be confounded by diet. We described and compared dietary intake and diet quality according to alcoholic beverage preference in European elderly. Methods: From the Consortium on Health and Ageing: Network of Cohorts in Europe and the United States (CHANCES), seven European cohorts were included, i.e. four sub-cohorts from EPIC-Elderly, the SENECA Study, the Zutphen Elderly Study, and the Rotterdam Study. Harmonized data of 29,423 elderly participants from 14 European countries were analyzed. Baseline data on consumption of beer, wine, and spirits, and dietary intake were collected with questionnaires. Diet quality was assessed using the Healthy Diet Indicator (HDI). Intakes and scores across categories of alcoholic beverage preference (beer, wine, spirit, no preference, non-consumers) were adjusted for age, sex, socio-economic status, self-reported prevalent diseases, and lifestyle factors. Cohort-specific mean intakes and scores were calculated as well as weighted means combining all cohorts. Results: In 5 of 7 cohorts, persons with a wine preference formed the largest group. After multivariate adjustment, persons with a wine preference tended to have a higher HDI score and intake of healthy foods in most cohorts, but differences were small. The weighted estimates of all cohorts combined revealed that non-consumers had the highest fruit and vegetable intake, followed by wine consumers. Non-consumers and persons with no specific preference had a higher HDI score, spirit consumers the lowest. However, overall diet quality as measured by HDI did not differ greatly across alcoholic beverage preference categories. Discussion: This study using harmonized data from ~30,000 elderly from 14 European countries showed that, after multivariate adjustment, dietary habits and diet quality did not differ greatly according to alcoholic beverage

Diets high in glycaemic index (GI) and glycaemic load (GL) have been associated with a higher diabetes risk. Beer explained a large proportion of variation in GI in a Finnish and an American study. However, few beers have been tested according to International Organization for Standardization (ISO) methodology. We tested the GI of beer and estimated its contribution to dietary GI and GL in the Netherlands. GI testing of pilsner beer (Pilsner Urquell) was conducted at The University of Sydney according to ISO international standards with glucose as the reference food. Subsequently, GI and GL values were assigned to 2556 food items in the 2011 Dutch food composition table using a six-step methodology and consulting four databases. This table was linked to dietary data from 2106 adults in the Dutch National Food Consumption Survey 2007-2010. Stepwise linear regression identified contribution to inter-individual variation in dietary GI and GL. The GI of pilsner beer was 89 (sd 5). Beer consumption contributed to 9·6 and 5·3 % inter-individual variation in GI and GL, respectively. Other foods that contributed to the inter-individual variation in GI and GL included potatoes, bread, soft drinks, sugar, candy, wine, coffee and tea. The results were more pronounced in men than in women. In conclusion, beer is a high-GI food. Despite its relatively low carbohydrate content (approximately 4-5 g/100 ml), it still made a contribution to dietary GL, especially in men. Next to potatoes, bread, sugar and sugar-sweetened beverages, beer captured a considerable proportion of between-person variability in GI and GL in the Dutch diet.

Background: The health impact of dietary replacement of carbohydrates with protein for patients with type 2 diabetes is still debated. This study aimed to investigate the association between dietary substitution of carbohydrates with (animal and plant) protein and 5-year weight change, and all-cause and cardiovascular (CVD) mortality risk in patients with type 2 diabetes. Methods: The study included 6,107 diabetes patients from 15 European cohorts. Patients with type 1 diabetes were excluded. At recruitment, validated country-specific food-frequency questionnaires were used to estimate dietary intake. Multivariable adjusted linear regression was used to examine the associations between dietary carbohydrate substitution with protein and 5-year weight change, and Cox regression to estimate hazard ratios (HRs) for (CVD) mortality. Results: Annual weight loss of patients with type 2 diabetes was 0.17 (SD 1.24) kg. After a mean follow-up of 9.2 (SD 2.3)y, 787 (13%) participants had died, of which 266 (4%) deaths were due to CVD. Substitution of 10 gram dietary carbohydrate with total (ß = 187 [75;299]g) and animal (ß = 196 [137;254]g) protein was associated with mean 5-year weight gain. Substitution for plant protein was not significantly associated with weight change (β = 82 [−421;584]g). Substitution with plant protein was associated with lower all-cause mortality risk (HR = 0.79 [0.64;0.97]), whereas substitution with total or animal protein was not associated with (CVD) mortality risk. Conclusions: In diabetes patients, substitution with plant protein was beneficial with respect to weight change and all-cause mortality as opposed to substitution with animal protein. Therefore, future research is needed whether dietary guidelines should not actively promote substitution of carbohydrates by total protein, but rather focus on substitution of carbohydrates with plant protein.

The health impact of dietary replacement of carbohydrates with protein for patients with type 2 diabetes is still debated. This study aimed to investigate the association between dietary substitution of carbohydrates with (animal and plant) protein and 5-year weight change, and all-cause and cardiovascular (CVD) mortality risk in patients with type 2 diabetes.

Background: Dietary fiber, carbohydrate quality and quantity are associated with mortality risk in the general population. Whether this is also the case among diabetes patients is unknown.Objective: To assess the associations of dietary fiber, glycemic load, glycemic index, carbohydrate, sugar, and starch intake with mortality risk in individuals with diabetes. Methods: This study was a prospective cohort study among 6,192 individuals with confirmed diabetes mellitus (mean age of 57.4 years, and median diabetes duration of 4.4 years at baseline) from the European Prospective Investigation into Cancer and Nutrition (EPIC). Dietary intake was assessed at baseline (1992-2000) with validated dietary questionnaires. Cox proportional hazards analysis was performed to estimate hazard ratios (HRs) for all-cause and cardiovascular mortality, while adjusting for CVD-related, diabetes-related, and nutritional factors. Results: During a median follow-up of 9.2 y, 791 deaths were recorded, 306 due to CVD. Dietary fiber was inversely associated with all-cause mortality risk (adjusted HR per SD increase, 0.83 [95% CI, 0.75-0.91]) and CVD mortality risk (0.76[0.64-0.89]). No significant associations were observed for glycemic load, glycemic index, carbohydrate, sugar, or starch. Glycemic load (1.42[1.07-1.88]), carbohydrate (1.67[1.18-2.37]) and sugar intake (1.53[1.12-2.09]) were associated with an increased total mortality risk among normal weight individuals (BMI <= 25 kg/m(2); 22% of study population) but not among overweight individuals (P interaction <= 0.04). These associations became stronger after exclusion of energy misreporters. Conclusions: High fiber intake was associated with a decreased mortality risk. High glycemic load, carbohydrate and sugar intake were associated with an increased mortality risk in normal weight individuals with diabetes.

Objectives: To investigate whether low self-rated health (SRH) is associated with increased mortality in individuals with diabetes. Design: Population-based prospective cohort study. Setting: Enrolment took place between 1992 and 2000 in four centres (Bilthoven, Heidelberg, Potsdam, Umea) in a subcohort nested in the European Prospective Investigation into Cancer and Nutrition. Participants: 3257 individuals (mean +/- SD age was 55.8 +/- 7.6 years and 42% women) with confirmed diagnosis of diabetes mellitus. Primary outcome measure: The authors used Cox proportional hazards modelling to estimate HRs for total mortality controlling for age, centre, sex, educational level, body mass index, physical inactivity, smoking, insulin treatment, hypertension, hyperlipidaemia and history of myocardial infarction, stroke or cancer. Results: During follow-up (mean follow-up +/- SD was 8.6 +/- 2.3 years), 344 deaths (241 men/103 women) occurred. In a multivariate model, individuals with low SRH were at higher risk of mortality (HR 1.38, 95% CI 1.10 to 1.73) than those with high SRH. The association was mainly driven by increased 5-year mortality and was stronger among individuals with body mass index of <25 kg/m(2) than among obese individuals. In sex-specific analyses, the association was statistically significant in men only. There was no indication of heterogeneity across centres. Conclusions: Low SRH was associated with increased mortality in individuals with diabetes after controlling for established risk factors. In patients with diabetes with low SRH, the physician should consider a more detailed consultation and intensified support.

Introduction: Observational studies have shown that glycated haemoglobin (HbA(1c)) is related to mortality, but the shape of the association is less clear. Furthermore, disease duration and medication may modify this association. This observational study explored the association between HbA(1c) measured in stored erythrocytes and mortality. Secondly, it was assessed whether disease duration and medication use influenced the estimates or were independently associated with mortality. Methods: Within the European Prospective Investigation into Cancer and Nutrition a cohort was analysed of 4,345 individuals with a confirmed diagnosis of diabetes at enrolment. HbA(1c) was measured in blood samples stored up to 19 years. Multivariable Cox proportional hazard regression models for all-cause mortality investigated HbA(1c) in quartiles as well as per 1% increment, diabetes medication in seven categories of insulin and oral hypoglycaemic agents, and disease duration in quartiles. Results: After a median follow-up of 9.3 years, 460 participants died. Higher HbA(1c) was associated with higher mortality: Hazard Ratio for 1%-increase was 1.11 (95% CI 1.06, 1.17). This association was linear (P-nonlinearity = 0.15) and persistent across categories of medication use, disease duration, and co-morbidities. Compared with metformin, other medication types were not associated with mortality. Longer disease duration was associated with mortality, but not after adjustment for HbA(1c) and medication. Conclusion: This prospective study showed that persons with lower HbA(1c) had better survival than those with higher HbA(1c). The association was linear and independent of disease duration, type of medication use, and presence of co-morbidities. Any improvement of HbA(1c) appears to be associated with reduced mortality risk.