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  • 1
    Keywords: CANCER ; COHORT ; INTERVENTION ; DIETARY-INTAKE ; OLDER WOMEN ; POSTMENOPAUSAL WOMEN ; PHYSICAL-ACTIVITY ; RANDOMIZED CONTROLLED-TRIAL ; INSULIN SENSITIVITY ; DRINKING PATTERNS
    Abstract: Abstract. Beulens JWJ, van der Schouw YT, Bergmann MM, Rohrmann S, B Schulze M, Buijsse B, Grobbee DE, Arriola L, Cauchi S, Tormo M-J, Allen NE, van der A DL, Balkau B, Boeing H, Clavel-Chapelon F, de Lauzon-Guillan B, Franks P, Froguel P, Gonzales C, Halkjaer J, Huerta JM, Kaaks R, Key TJ, Khaw KT, Krogh V, Molina-Montes E, Nilsson P, Overvad K, Palli D, Panico S, Ramon Quiros J, Ronaldsson O, Romieu I, Romaguera D, Sacerdote C, Sanchez M-J, Spijkerman AMW, Teucher B, Tjonneland A, Tumino R, Sharp S, Forouhi NG, Langenberg C, Feskens EJM, Riboli E, Wareham NJ (University Medical Center Utrecht, The Netherlands; German Institute of Human Nutrition, Potsdam-Rehbrucke, Germany; German Cancer Research Centre, Heidelberg, Germany; Basque Government, San Sebastian, CIBERESP, Spain; Institut de Biologie de Lille, Lille, France; Murcia Regional Health Council, Murcia, Spain; CIBER Epidemiologia y Salud Publica (CIBERESP), Spain; University of Oxford, Oxford, UK; National Institute of Public Health and the Environment, Bilthoven, The Netherlands; Inserm, CESP Centre for Research in Epidemiology and Population Health, Villejuif Cedex, France; Lund University, Malmo, Sweden; Imperial College, London, UK; Department of Epidemiology, Barcelona, Spain; Danish Cancer Society, Copenhagen, Denmark; University of Cambridge, Cambridge, UK; Fondazione IRCCS Istituto Nazionale Tumori Milan, Milan, Italy; Andalusian School of Public Health, Granada, Spain; School of Public Health, Aarhus, Denmark; Cancer Research and Prevention Institute (ISPO), Florence, Italy; Universita Federico II, Napoli, Italy; Consejeria de Salud y Servicios Sanitarios, Oviedo-Asturias, Spain; Umea University, Umea, Sweden; International Agency for Research of Cancer, Lyon, France; Center for Cancer Prevention (CPO-Piemonte), Torino, Italy; "Civile - M.P. Arezzo" Hospital, Ragusa, Italy; Addenbrooke's Hospital, Cambridge, UK; and Wageningen University, Wageningen, The Netherlands). Alcohol consumption and risk of type 2 diabetes in European men and women: influence of beverage type and body size. The EPIC-InterAct study. J Intern Med 2012; 272: 358-370. Objective: To investigate the association between alcohol consumption and type 2 diabetes, and determine whether this is modified by sex, body mass index (BMI) and beverage type. Design: Multicentre prospective case-cohort study. Setting: Eight countries from the European Prospective Investigation into Cancer and Nutrition cohort. Subjects: A representative baseline sample of 16 154 participants and 12 403 incident cases of type 2 diabetes. Interventions: Alcohol consumption assessed using validated dietary questionnaires. Main outcome measures: Occurrence of type 2 diabetes based on multiple sources (mainly self-reports), verified against medical information. Results: Amongst men, moderate alcohol consumption was nonsignificantly associated with a lower incidence of diabetes with a hazard ratio (HR) of 0.90 (95% CI: 0.78-1.05) for 6.1-12.0 versus 0.1-6.0 g day(-1) , adjusted for dietary and diabetes risk factors. However, the lowest risk was observed at higher intakes of 24.1-96.0 g day(-1) with an HR of 0.86 (95% CI: 0.75-0.98). Amongst women, moderate alcohol consumption was associated with a lower incidence of diabetes with a hazard ratio of 0.82 (95% CI: 0.72-0.92) for 6.1-12.0 g day(-1) (P interaction gender 〈0.01). The inverse association between alcohol consumption and diabetes was more pronounced amongst overweight (BMI 〉/= 25 kg m(-2) ) than normal-weight men and women (P interaction 〈 0.05). Adjusting for waist and hip circumference did not alter the results for men, but attenuated the association for women (HR=0.90, 95% CI: 0.79-1.03 for 6.1-12.0 g day(-1) ). Wine consumption for men and fortified wine consumption for women were most strongly associated with a reduced risk of diabetes. Conclusions: The results of this study show that moderate alcohol consumption is associated with a lower risk
    Type of Publication: Journal article published
    PubMed ID: 22353562
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  • 2
    Keywords: CANCER ; COHORT ; DISEASE ; prevention ; WOMEN ; nutrition ; LIFE-STYLE ; MELLITUS ; ENERGY-INTAKE ; FIBER INTAKE
    Abstract: The association of glycemic index (GI) and glycemic load (GL) with the risk of type 2 diabetes remains unclear. We investigated associations of dietary GI, GL, and digestible carbohydrate with incident type 2 diabetes. We performed a case-cohort study nested within the European Prospective Investigation into Cancer and Nutrition Study, including a random subcohort (n = 16,835) and incident type 2 diabetes cases (n = 12,403). The median follow-up time was 12 y. Baseline dietary intakes were assessed using country-specific dietary questionnaires. Country-specific HR were calculated and pooled using random effects meta-analysis. Dietary GI, GL, and digestible carbohydrate in the subcohort were (mean +/- SD) 56 +/- 4, 127 +/- 23, and 226 +/- 36 g/d, respectively. After adjustment for confounders, GI and GL were not associated with incident diabetes [HR highest vs. lowest quartile (HR(Q4)) for GI: 1.05 (95% CI = 0.96, 1.16); HR(Q4) for GL: 1.07 (95% CI = 0.95, 1.20)]. Digestible carbohydrate intake was not associated with incident diabetes [HR(Q4): 0.98 (95% CI = 0.86, 1.10)]. In additional analyses, we found that discrepancies in the GI value assignment to foods possibly explain differences in GI associations with diabetes within the same study population. In conclusion, an expansion of the GI tables and systematic GI value assignment to foods may be needed to improve the validity of GI values derived in such studies, after which GI associations may need reevaluation. Our study shows that digestible carbohydrate intake is not associated with diabetes risk and suggests that diabetes risk with high-GI and -GL diets may be more modest than initial studies suggested.
    Type of Publication: Journal article published
    PubMed ID: 23190759
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  • 3
    Keywords: RECEPTOR ; EXPRESSION ; RISK ; CALCIUM ; inflammation ; METAANALYSIS ; GENOME-WIDE ASSOCIATION ; INSULIN-SECRETION ; VITAMIN-D SUPPLEMENTATION ; GLUCOSE-TOLERANCE
    Abstract: It is unclear whether vitamin D lowers risk of type 2 diabetes (T2D). In an observational study, we assessed the prospective association between plasma 25-hydroxyvitamin D (25(OH)D) and incident T2D, and evaluated whether it holds up for genetically determined elevated 25(OH)D. We used a case-cohort study nested within the German arm of the European Prospective Investigation into Cancer. From a total cohort of 53,088 participants with a mean follow-up of 6.6 years, we identified a random subcohort of 2,121 participants (57 % women) and 1,572 incident cases of T2D. 25(OH)D was measured in baseline plasma samples retrieved from frozen storage. Mean plasma 25(OH)D in the subcohort was 47.1 (5th-95th percentile 19.6-80.7) nmol/L. After controlling for age, sex, center, season of blood draw, education, and lifestyle, the hazard of T2D decreased across increasing plasma concentrations of 25(OH)D (P linear trend 〈 0.0001). The association became non-linear after adjustment for BMI and waist circumference (P non-linearity 〈 0.0001), with the inverse association being restricted to participants with 25(OH)D concentrations below similar to 45 nmol/L (hazard ratio per 5 nmol/L higher 25(OH)D 0.91, 95 % CI 0.84-0.98). A score predicting genetically determined plasma 25(OH)D by weighting four independent single-nucleotide polymorphisms by their effect on 25(OH)D, explained 3.7 % of the variance in 25(OH)D. The hazard ratio (95 % CI) per 5 nmol/L higher genetically predicted 25(OH)D was 0.98 (0.89-1.08) in the entire study sample and 1.06 (0.93-1.21) in the sub-sample with 25(OH)D 〈 45 nmol/L. This latter finding casts doubt on a strong causal association of 25(OH)D with T2D, but further research in large-scale consortia is needed.
    Type of Publication: Journal article published
    PubMed ID: 24002339
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  • 4
    Abstract: OBJECTIVE: The aims of this study were to investigate the association between smoking and incident type 2 diabetes, accounting for a large number of potential confounding factors, and to explore potential effect modifiers and intermediate factors. RESEARCH DESIGN AND METHODS: The European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct is a prospective case-cohort study within eight European countries, including 12,403 cases of incident type 2 diabetes and a random subcohort of 16,835 individuals. After exclusion of individuals with missing data, the analyses included 10,327 cases and 13,863 subcohort individuals. Smoking status was used (never, former, current), with never smokers as the reference. Country-specific Prentice-weighted Cox regression models and random-effects meta-analysis were used to estimate hazard ratios (HRs) for type 2 diabetes. RESULTS: In men, the HRs (95% CI) of type 2 diabetes were 1.40 (1.26, 1.55) for former smokers and 1.43 (1.27, 1.61) for current smokers, independent of age, education, center, physical activity, and alcohol, coffee, and meat consumption. In women, associations were weaker, with HRs (95% CI) of 1.18 (1.07, 1.30) and 1.13 (1.03, 1.25) for former and current smokers, respectively. There was some evidence of effect modification by BMI. The association tended to be slightly stronger in normal weight men compared with those with overall adiposity. CONCLUSIONS: Former and current smoking was associated with a higher risk of incident type 2 diabetes compared with never smoking in men and women, independent of educational level, physical activity, alcohol consumption, and diet. Smoking may be regarded as a modifiable risk factor for type 2 diabetes, and smoking cessation should be encouraged for diabetes prevention.
    Type of Publication: Journal article published
    PubMed ID: 25336749
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  • 5
    Abstract: OBJECTIVE: Observational studies show an association between ferritin and type 2 diabetes (T2D), suggesting a role of high iron stores in T2D development. However, ferritin is influenced by factors other than iron stores, which is less the case for other biomarkers of iron metabolism. We investigated associations of ferritin, transferrin saturation (TSAT), serum iron, and transferrin with T2D incidence to clarify the role of iron in the pathogenesis of T2D. RESEARCH DESIGN AND METHODS: The European Prospective Investigation into Cancer and Nutrition-InterAct study includes 12,403 incident T2D cases and a representative subcohort of 16,154 individuals from a European cohort with 3.99 million person-years of follow-up. We studied the prospective association of ferritin, TSAT, serum iron, and transferrin with incident T2D in 11,052 cases and a random subcohort of 15,182 individuals and assessed whether these associations differed by subgroups of the population. RESULTS: Higher levels of ferritin and transferrin were associated with a higher risk of T2D (hazard ratio [HR] [95% CI] in men and women, respectively: 1.07 [1.01-1.12] and 1.12 [1.05-1.19] per 100 mug/L higher ferritin level; 1.11 [1.00-1.24] and 1.22 [1.12-1.33] per 0.5 g/L higher transferrin level) after adjustment for age, center, BMI, physical activity, smoking status, education, hs-CRP, alanine aminotransferase, and gamma-glutamyl transferase. Elevated TSAT (〉/=45% vs. 〈45%) was associated with a lower risk of T2D in women (0.68 [0.54-0.86]) but was not statistically significantly associated in men (0.90 [0.75-1.08]). Serum iron was not associated with T2D. The association of ferritin with T2D was stronger among leaner individuals (Pinteraction 〈 0.01). CONCLUSIONS: The pattern of association of TSAT and transferrin with T2D suggests that the underlying relationship between iron stores and T2D is more complex than the simple link suggested by the association of ferritin with T2D.
    Type of Publication: Journal article published
    PubMed ID: 26861925
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  • 6
    Abstract: BACKGROUND: Whether and how n-3 and n-6 polyunsaturated fatty acids (PUFAs) are related to type 2 diabetes (T2D) is debated. Objectively measured plasma PUFAs can help to clarify these associations. METHODS AND FINDINGS: Plasma phospholipid PUFAs were measured by gas chromatography among 12,132 incident T2D cases and 15,919 subcohort participants in the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct study across eight European countries. Country-specific hazard ratios (HRs) were estimated using Prentice-weighted Cox regression and pooled by random-effects meta-analysis. We also systematically reviewed published prospective studies on circulating PUFAs and T2D risk and pooled the quantitative evidence for comparison with results from EPIC-InterAct. In EPIC-InterAct, among long-chain n-3 PUFAs, alpha-linolenic acid (ALA) was inversely associated with T2D (HR per standard deviation [SD] 0.93; 95% CI 0.88-0.98), but eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) were not significantly associated. Among n-6 PUFAs, linoleic acid (LA) (0.80; 95% CI 0.77-0.83) and eicosadienoic acid (EDA) (0.89; 95% CI 0.85-0.94) were inversely related, and arachidonic acid (AA) was not significantly associated, while significant positive associations were observed with gamma-linolenic acid (GLA), dihomo-GLA, docosatetraenoic acid (DTA), and docosapentaenoic acid (n6-DPA), with HRs between 1.13 to 1.46 per SD. These findings from EPIC-InterAct were broadly similar to comparative findings from summary estimates from up to nine studies including between 71 to 2,499 T2D cases. Limitations included potential residual confounding and the inability to distinguish between dietary and metabolic influences on plasma phospholipid PUFAs. CONCLUSIONS: These large-scale findings suggest an important inverse association of circulating plant-origin n-3 PUFA (ALA) but no convincing association of marine-derived n3 PUFAs (EPA and DHA) with T2D. Moreover, they highlight that the most abundant n6-PUFA (LA) is inversely associated with T2D. The detection of associations with previously less well-investigated PUFAs points to the importance of considering individual fatty acids rather than focusing on fatty acid class.
    Type of Publication: Journal article published
    PubMed ID: 27434045
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  • 7
    Abstract: Background: Gene-diet interactions have been reported to contribute to the development of type 2 diabetes (T2D). However, to our knowledge, few examples have been consistently replicated to date.Objective: We aimed to identify existing evidence for gene-macronutrient interactions and T2D and to examine the reported interactions in a large-scale study.Design: We systematically reviewed studies reporting gene-macronutrient interactions and T2D. We searched the MEDLINE, Human Genome Epidemiology Network, and WHO International Clinical Trials Registry Platform electronic databases to identify studies published up to October 2015. Eligibility criteria included assessment of macronutrient quantity (e.g., total carbohydrate) or indicators of quality (e.g., dietary fiber) by use of self-report or objective biomarkers of intake. Interactions identified in the review were subsequently examined in the EPIC (European Prospective Investigation into Cancer)-InterAct case-cohort study (n = 21,148, with 9403 T2D cases; 8 European countries). Prentice-weighted Cox regression was used to estimate country-specific HRs, 95% CIs, and P-interaction values, which were then pooled by random-effects meta-analysis. A primary model was fitted by using the same covariates as reported in the published studies, and a second model adjusted for additional covariates and estimated the effects of isocaloric macronutrient substitution.Results: Thirteen observational studies met the eligibility criteria (n 〈 1700 cases). Eight unique interactions were reported to be significant between macronutrients [carbohydrate, fat, saturated fat, dietary fiber, and glycemic load derived from self-report of dietary intake and circulating n-3 (omega-3) polyunsaturated fatty acids] and genetic variants in or near transcription factor 7-like 2 (TCF7L2), gastric inhibitory polypeptide receptor (GIPR), caveolin 2 (CAV2), and peptidase D (PEPD) (P-interaction 〈 0.05). We found no evidence of interaction when we tried to replicate previously reported interactions. In addition, no interactions were detected in models with additional covariates.Conclusions: Eight gene-macronutrient interactions were identified for the risk of T2D from the literature. These interactions were not replicated in the EPIC-InterAct study, which mirrored the analyses undertaken in the original reports. Our findings highlight the importance of independent replication of reported interactions.
    Type of Publication: Journal article published
    PubMed ID: 28592605
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  • 8
    Keywords: DIETARY ; PREVALENCE ; QUESTIONNAIRE ; TYPE-2 ; MELLITUS ; PHYSICAL-ACTIVITY ; HbA(1c) ; FASTING PLASMA-GLUCOSE ; IDENTIFYING INDIVIDUALS ; PREDICTION MODELS
    Abstract: AIM: To validate the German Diabetes Risk Score within the population-based cohort of the Cardiovascular Disease - Living and Ageing in Halle (CARLA) study. METHODS: The sample included 582 women and 719 men, aged 45-83 years, who did not have diabetes at baseline. The individual risk of every participant was calculated using the German Diabetes Risk Score, which was modified for 4 years of follow-up. Predicted probabilities and observed outcomes were compared using Hosmer-Lemeshow goodness-of-fit tests and receiver-operator characteristic analyses. Changes in prediction power were investigated by expanding the German Diabetes Risk Score to include metabolic variables and by subgroup analyses. RESULTS: We found 58 cases of incident diabetes. The median 4-year probability of developing diabetes based on the German Diabetes Risk Score was 6.5%. The observed and predicted probabilities of developing diabetes were similar, although estimation was imprecise owing to the small number of cases, and the Hosmer-Lemeshow test returned a poor correlation (chi-squared = 55.3; P = 5.8*10(-12) ). The area under the receiver-operator characteristic curve (AUC) was 0.70 (95% CI 0.64-0.77), and after excluding participants 〉/=66 years old, the AUC increased to 0.77 (95% CI 0.70-0.84). Consideration of glycaemic diagnostic variables, in addition to self-reported diabetes, reduced the AUC to 0.65 (95% CI 0.58-0.71). A new model that included the German Diabetes Risk Score and blood glucose concentration (AUC 0.81; 95% CI 0.76-0.86) or HbA1c concentration (AUC 0.84; 95% CI 0.80-0.91) was found to peform better. CONCLUSIONS: Application of the German Diabetes Risk Score in the CARLA cohort did not reproduce the findings in the European Prospective Investigation into Cancer and Nutrition (EPIC) Potsdam study, which may be explained by cohort differences and model overfit in the latter; however, a high score does provide an indication of increased risk of diabetes.
    Type of Publication: Journal article published
    PubMed ID: 23586438
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  • 9
    Keywords: FOLLOW-UP ; TOOL ; COHORT ; prevention ; VALIDITY ; MELLITUS ; METAANALYSIS ; EXTERNAL VALIDATION ; IDENTIFYING INDIVIDUALS ; LIFE-STYLE INTERVENTIONS
    Abstract: BACKGROUND: The comparative performance of existing models for prediction of type 2 diabetes across populations has not been investigated. We validated existing non-laboratory-based models and assessed variability in predictive performance in European populations. METHODS: We selected non-invasive prediction models for incident diabetes developed in populations of European ancestry and validated them using data from the EPIC-InterAct case-cohort sample (27,779 individuals from eight European countries, of whom 12,403 had incident diabetes). We assessed model discrimination and calibration for the first 10 years of follow-up. The models were first adjusted to the country-specific diabetes incidence. We did the main analyses for each country and for subgroups defined by sex, age (〈60 years vs 〉/=60 years), BMI (〈25 kg/m(2)vs 〉/=25 kg/m(2)), and waist circumference (men 〈102 cm vs 〉/=102 cm; women 〈88 cm vs 〉/=88 cm). FINDINGS: We validated 12 prediction models. Discrimination was acceptable to good: C statistics ranged from 0.76 (95% CI 0.72-0.80) to 0.81 (0.77-0.84) overall, from 0.73 (0.70-0.76) to 0.79 (0.74-0.83) in men, and from 0.78 (0.74-0.82) to 0.81 (0.80-0.82) in women. We noted significant heterogeneity in discrimination (pheterogeneity〈0.0001) in all but one model. Calibration was good for most models, and consistent across countries (pheterogeneity〉0.05) except for three models. However, two models overestimated risk, DPoRT by 34% (95% CI 29-39%) and Cambridge by 40% (28-52%). Discrimination was always better in individuals younger than 60 years or with a low waist circumference than in those aged at least 60 years or with a large waist circumference. Patterns were inconsistent for BMI. All models overestimated risks for individuals with a BMI of 〈25 kg/m(2). Calibration patterns were inconsistent for age and waist-circumference subgroups. INTERPRETATION: Existing diabetes prediction models can be used to identify individuals at high risk of type 2 diabetes in the general population. However, the performance of each model varies with country, age, sex, and adiposity. FUNDING: The European Union.
    Type of Publication: Journal article published
    PubMed ID: 24622666
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  • 10
    Keywords: CANCER ; RISK-FACTORS ; VARIANTS ; Mediterranean diet ; PHYSICAL-ACTIVITY ; GENOME-WIDE ASSOCIATION ; IMPAIRED GLUCOSE-TOLERANCE ; 10 EUROPEAN COUNTRIES ; ENVIRONMENT INTERACTIONS ; PREVENTION PROGRAM
    Abstract: BACKGROUND: Understanding of the genetic basis of type 2 diabetes (T2D) has progressed rapidly, but the interactions between common genetic variants and lifestyle risk factors have not been systematically investigated in studies with adequate statistical power. Therefore, we aimed to quantify the combined effects of genetic and lifestyle factors on risk of T2D in order to inform strategies for prevention. METHODS AND FINDINGS: The InterAct study includes 12,403 incident T2D cases and a representative sub-cohort of 16,154 individuals from a cohort of 340,234 European participants with 3.99 million person-years of follow-up. We studied the combined effects of an additive genetic T2D risk score and modifiable and non-modifiable risk factors using Prentice-weighted Cox regression and random effects meta-analysis methods. The effect of the genetic score was significantly greater in younger individuals (p for interaction = 1.20x10-4). Relative genetic risk (per standard deviation [4.4 risk alleles]) was also larger in participants who were leaner, both in terms of body mass index (p for interaction = 1.50x10-3) and waist circumference (p for interaction = 7.49x10-9). Examination of absolute risks by strata showed the importance of obesity for T2D risk. The 10-y cumulative incidence of T2D rose from 0.25% to 0.89% across extreme quartiles of the genetic score in normal weight individuals, compared to 4.22% to 7.99% in obese individuals. We detected no significant interactions between the genetic score and sex, diabetes family history, physical activity, or dietary habits assessed by a Mediterranean diet score. CONCLUSIONS: The relative effect of a T2D genetic risk score is greater in younger and leaner participants. However, this sub-group is at low absolute risk and would not be a logical target for preventive interventions. The high absolute risk associated with obesity at any level of genetic risk highlights the importance of universal rather than targeted approaches to lifestyle intervention.
    Type of Publication: Journal article published
    PubMed ID: 24845081
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