Separate and combined associations of obesity and metabolic health with coronary heart disease: a pan-European case-cohort analysis.

Aims: The hypothesis of 'metabolically healthy obesity' implies that, in the absence of metabolic dysfunction, individuals with excess adiposity are not at greater cardiovascular risk. We tested this hypothesis in a large pan-European prospective study. Methods and results: We conducted a case-cohort analysis in the 520 000-person European Prospective Investigation into Cancer and Nutrition study ('EPIC-CVD'). During a median follow-up of 12.2 years, we recorded 7637 incident coronary heart disease (CHD) cases. Using cut-offs recommended by guidelines, we defined obesity and overweight using body mass index (BMI), and metabolic dysfunction ('unhealthy') as ≥ 3 of elevated blood pressure, hypertriglyceridaemia, low HDL-cholesterol, hyperglycaemia, and elevated waist circumference. We calculated hazard ratios (HRs) and 95% confidence intervals (95% CI) within each country using Prentice-weighted Cox proportional hazard regressions, accounting for age, sex, centre, education, smoking, diet, and physical activity. Compared with metabolically healthy normal weight people (reference), HRs were 2.15 (95% CI: 1.79; 2.57) for unhealthy normal weight, 2.33 (1.97; 2.76) for unhealthy overweight, and 2.54 (2.21; 2.92) for unhealthy obese people. Compared with the reference group, HRs were 1.26 (1.14; 1.40) and 1.28 (1.03; 1.58) for metabolically healthy overweight and obese people, respectively. These results were robust to various sensitivity analyses. Conclusion: Irrespective of BMI, metabolically unhealthy individuals had higher CHD risk than their healthy counterparts. Conversely, irrespective of metabolic health, overweight and obese people had higher CHD risk than lean people. These findings challenge the concept of 'metabolically healthy obesity', encouraging population-wide strategies to tackle obesity.

A four-domain approach of frailty explored in the Doetinchem Cohort Study.

BACKGROUND: Accumulation of problems in physical, psychological, cognitive, or social functioning is characteristic for frail individuals. Using a four-domain approach of frailty, this study explored how sociodemographic and lifestyle factors, life events and health are associated with frailty. METHODS: The study sample included 4019 men and women (aged 40-81 years) examined during the fifth round (2008-2012) of the Doetinchem Cohort Study. Four domains of frailty were considered: physical (≥4 of 8 criteria: unintentional weight loss, exhaustion, strength, perceived health, walking, balance, hearing and vision impairments), psychological (2 criteria: depressive symptoms, mental health), cognitive (<10th percentile on global cognitive functioning), and social frailty (≥2 of 3 criteria: loneliness, social support, social participation). Logistic regression was used to study the cross-sectional association of sociodemographic factors, lifestyle, life events and chronic diseases with frailty domains. RESULTS: About 17% of the population was frail on one or more domains. Overlap between the frailty domains was limited since 82% of the frail population was frail on one domain only. Low educated respondents were at higher risk of being psychologically and socially frail. Having multiple diseases was associated with a higher risk of being physically and psychologically frail. Being physically active was consistently associated with a lower risk of frailty on each of the four domains. Short or long sleep duration was associated with a higher risk of being physically, psychologically, and socially frail. CONCLUSIONS: Sociodemographic factors, lifestyle and multimorbidity contributed differently to the four frailty domains. It is important to consider multiple frailty domains since this helps to identify different groups of frail people, and as such to provide tailored care and support. Lifestyle factors including physical activity, smoking and sleep duration were associated with multiple domains of frailty.

Salt Reductions in Some Foods in The Netherlands: Monitoring of Food Composition and Salt Intake.

BACKGROUND AND OBJECTIVES: High salt intake increases blood pressure and thereby the risk of chronic diseases. Food reformulation (or food product improvement) may lower the dietary intake of salt. This study describes the changes in salt contents of foods in the Dutch market over a five-year period (2011-2016) and differences in estimated salt intake over a 10-year period (2006-2015). METHODS: To assess the salt contents of foods; we obtained recent data from chemical analyses and from food labels. Salt content of these foods in 2016 was compared to salt contents in the 2011 version Dutch Food Composition Database (NEVO, version 2011), and statistically tested with General Linear Models. To estimate the daily dietary salt intake in 2006, 2010, and 2015, men and women aged 19 to 70 years were recruited through random population sampling in Doetinchem, a small town located in a rural area in the eastern part of the Netherlands. The characteristics of the study population were in 2006: n = 317, mean age 49 years, 43% men, in 2010: n = 342, mean age 46 years, 45% men, and in 2015: n = 289, mean age 46 years, 47% men. Sodium and potassium excretion was measured in a single 24-h urine sample. All estimates were converted to a common metric: salt intake in grams per day by multiplication of sodium with a factor of 2.54. RESULTS: In 2016 compared to 2011, the salt content in certain types of bread was on average 19 percent lower and certain types of sauce, soup, canned vegetables and legumes, and crisps had a 12 to 26 percent lower salt content. Salt content in other types of foods had not changed significantly. Between 2006, 2010 and 2015 the estimated salt intake among adults in Doetinchem remained unchanged. In 2015, the median estimated salt intake was 9.7 g per day for men and 7.4 g per day for women. As in 2006 and 2010, the estimated salt intake in 2015 exceeded the recommended maximum intake of 6 g per day set by the Dutch Health Council. CONCLUSION: In the Netherlands, the salt content of bread, certain sauces, soups, potato crisps, and processed legumes and vegetables have been reduced over the period 2011-2016. However, median salt intake in 2006 and 2015 remained well above the recommended intake of 6 g.

Association Between Low-Density Lipoprotein Cholesterol-Lowering Genetic Variants and Risk of Type 2 Diabetes: A Meta-analysis.

Importance: Low-density lipoprotein cholesterol (LDL-C)-lowering alleles in or near NPC1L1 or HMGCR, encoding the respective molecular targets of ezetimibe and statins, have previously been used as proxies to study the efficacy of these lipid-lowering drugs. Alleles near HMGCR are associated with a higher risk of type 2 diabetes, similar to the increased incidence of new-onset diabetes associated with statin treatment in randomized clinical trials. It is unknown whether alleles near NPC1L1 are associated with the risk of type 2 diabetes. Objective: To investigate whether LDL-C-lowering alleles in or near NPC1L1 and other genes encoding current or prospective molecular targets of lipid-lowering therapy (ie, HMGCR, PCSK9, ABCG5/G8, LDLR) are associated with the risk of type 2 diabetes. Design, Setting, and Participants: The associations with type 2 diabetes and coronary artery disease of LDL-C-lowering genetic variants were investigated in meta-analyses of genetic association studies. Meta-analyses included 50 775 individuals with type 2 diabetes and 270 269 controls and 60 801 individuals with coronary artery disease and 123 504 controls. Data collection took place in Europe and the United States between 1991 and 2016. Exposures: Low-density lipoprotein cholesterol-lowering alleles in or near NPC1L1, HMGCR, PCSK9, ABCG5/G8, and LDLR. Main Outcomes and Measures: Odds ratios (ORs) for type 2 diabetes and coronary artery disease. Results: Low-density lipoprotein cholesterol-lowering genetic variants at NPC1L1 were inversely associated with coronary artery disease (OR for a genetically predicted 1-mmol/L [38.7-mg/dL] reduction in LDL-C of 0.61 [95% CI, 0.42-0.88]; P = .008) and directly associated with type 2 diabetes (OR for a genetically predicted 1-mmol/L reduction in LDL-C of 2.42 [95% CI, 1.70-3.43]; P < .001). For PCSK9 genetic variants, the OR for type 2 diabetes per 1-mmol/L genetically predicted reduction in LDL-C was 1.19 (95% CI, 1.02-1.38; P = .03). For a given reduction in LDL-C, genetic variants were associated with a similar reduction in coronary artery disease risk (I2 = 0% for heterogeneity in genetic associations; P = .93). However, associations with type 2 diabetes were heterogeneous (I2 = 77.2%; P = .002), indicating gene-specific associations with metabolic risk of LDL-C-lowering alleles. Conclusions and Relevance: In this meta-analysis, exposure to LDL-C-lowering genetic variants in or near NPC1L1 and other genes was associated with a higher risk of type 2 diabetes. These data provide insights into potential adverse effects of LDL-C-lowering therapy.

Association of Plasma Phospholipid n-3 and n-6 Polyunsaturated Fatty Acids with Type 2 Diabetes: The EPIC-InterAct Case-Cohort Study.

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, α-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 γ-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.

Association of Multiple Biomarkers of Iron Metabolism and Type 2 Diabetes: The EPIC-InterAct Study.

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 µg/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 γ-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.

Intake of Total and Subgroups of Fat Minimally Affect the Associations between Selected Single Nucleotide Polymorphisms in the PPARγ Pathway and Changes in Anthropometry among European Adults from Cohorts of the DiOGenes Study.

BACKGROUND: Although the peroxisome proliferator-activated receptor γ (PPARγ) pathway is central in adipogenesis, it remains unknown whether it influences change in body weight (BW) and whether dietary fat has a modifying effect on the association. OBJECTIVES: We examined whether 27 single nucleotide polymorphisms (SNPs) within 4 genes in the PPARγ pathway are associated with the OR of being a BW gainer or with annual changes in anthropometry and whether intake of total fat, monounsaturated fat, polyunsaturated fat, or saturated fat has a modifying effect on these associations. METHODS: A case-noncase study included 11,048 men and women from cohorts in the European Diet, Obesity and Genes study; 5552 were cases, defined as individuals with the greatest BW gain during follow-up, and 6548 were randomly selected, including 5496 noncases. We selected 4 genes [CCAAT/enhancer binding protein ß (CEBPB), phosphoenolpyruvate carboxykinase 2, PPARγ gene (PPARG), and sterol regulatory element binding transcription factor 1] according to evidence about biologic plausibility for interactions with dietary fat in weight regulation. Diet was assessed at baseline, and anthropometry was followed for 7 y. RESULTS: The ORs for being a BW gainer for the 27 genetic variants ranged from 0.87 (95% CI: 0.79, 1.03) to 1.12 (95% CI: 0.96, 1.22) per additional minor allele. Uncorrected, CEBPB rs4253449 had a significant interaction with the intake of total fat and subgroups of fat. The OR for being a BW gainer for each additional rs4253449 minor allele per 100 kcal higher total fat intake was 1.07 (95% CI: 1.02, 1.12; P = 0.008), and similar associations were found for subgroups of fat. CONCLUSIONS: Among European men and women, the influence of dietary fat on associations between SNPs in the PPARγ pathway and anthropometry is likely to be absent or marginal. The observed interaction between rs4253449 and dietary fat needs confirmation.

Osteocalcin Is Not Associated with the Risk of Type 2 Diabetes: Findings from the EPIC-NL Study.

OBJECTIVE: To investigate whether total osteocalcin (tOC), uncarboxylated osteocalcin (ucOC) and percentage of uncarboxylated osteocalcin (%ucOC) are associated with the risk of type 2 diabetes. METHODS: This nested case control study included 1,635 participants, 833 incident diabetes cases and 802 non-diabetic control participants, aged 21-70 years from the EPIC-NL cohort. Baseline concentrations of tOC, ucOC and %ucOC were assessed. During 10 years of follow-up, diabetes cases were self-reported and verified against information from general practitioners or pharmacists. The association between the different forms of osteocalcin and diabetes risk was assessed with logistic regression adjusted for diabetes risk factors (waist circumference, age, sex, cohort, smoking status, family history of diabetes, hypertension, alcohol intake, physical activity and education) and dietary factors (total energy intake and energy adjusted intake of fat, fiber, protein and calcium). RESULTS: TOC concentration was not associated with diabetes risk, with an odds ratio (OR) of 0.97 (0.91-1.03) for each ng/ml increment after adjustment for diabetes risk factors and dietary factors. No association between ucOC and %ucOC and the risk of diabetes was observed either. In sex stratified analyses (P interaction = 0.07), higher %ucOC tended to be associated with an increased risk of type 2 diabetes in a multivariable model in women (OR 1.05 for each increment of 5% ucOC (1.00-1.11), Ptrend = 0.08), but not in men (OR 0.96 for each increment of 5% ucOC (0.88-1.04)). When waist circumference was replaced by body mass index, none of the osteocalcin forms were associated with the risk of type 2 diabetes in the final model among both women and men. CONCLUSIONS: Available evidence suggests that tOC, ucOC and %ucOC are each not associated with the risk of type 2 diabetes. However, more large-scale cohort studies are needed to clarify the presence of any association between the different forms of osteocalcin and the risk of type 2 diabetes.

Identifying cardiovascular risk factor-related dietary patterns with reduced rank regression and random forest in the EPIC-NL cohort.

BACKGROUND: Several methods are used to determine dietary patterns. Hybrid methods incorporate information on nutrient intake or biological factors to extract patterns relevant to disease etiology. OBJECTIVE: We explore differences between patterns derived with 2 hybrid methods with those obtained by a posteriori methods and compare associations of these patterns with coronary artery disease (CAD) and stroke risk. DESIGN: Food-frequency questionnaires were used to estimate dietary intake in 34,644 participants of European Prospective Investigation into Cancer-Netherlands at baseline (1993-1997). Follow-up was complete until 31 December 2007. Hybrid methods to determine dietary patterns were reduced rank regression (RRR) and random forest with classification tree analysis (RF-CTA). Included risk factors were body mass index, total:high-density lipoprotein cholesterol ratio, and systolic blood pressure. Results were compared with those from principal component analysis (PCA) and k-means cluster analysis (KCA), respectively. RESULTS: Both RRR and PCA derived a "Western," "prudent," and "traditional pattern." All RRR patterns were significantly associated with CAD risk [highest vs. lowest quartile factor score; HR: 1.45 (95% CI: 1.25, 1.69), 0.86 (0.74, 0.99), and 1.25 (1.07, 1.47), respectively]. Only the prudent RRR factor was statistically significant associated with stroke (HR: 0.76; 95% CI: 0.59, 0.97). From the PCA patterns, only the traditional pattern was associated with CAD (HR: 1.29; 95% CI: 1.11, 1.50). RF-CTA derived 7 dietary patterns that could be categorized as "Western-like," "prudent-like," and "traditional-like." KCA established a prudent and Western cluster. Compared with the RF-CTA "prudent-like 1" pattern, only the "traditional-like 1" pattern was associated with CAD (HR: 1.36; 955 CI: 1.12, 1.65). None of the RF-CTA groups were associated with stroke. Compared with the Western KCA cluster, the prudent cluster was not associated with CAD or stroke. CONCLUSION: Including risk factors in RRR and RF-CTA resulted in small differences in food groups, contributing to similar patterns that showed in general stronger associations with CAD than PCA and KCA, respectively.

A Mendelian Randomization Study of Circulating Uric Acid and Type 2 Diabetes.

We aimed to investigate the causal effect of circulating uric acid concentrations on type 2 diabetes risk. A Mendelian randomization study was performed using a genetic score with 24 uric acid-associated loci. We used data of the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct case-cohort study, comprising 24,265 individuals of European ancestry from eight European countries. During a mean (SD) follow-up of 10 (4) years, 10,576 verified incident case subjects with type 2 diabetes were ascertained. Higher uric acid was associated with a higher diabetes risk after adjustment for confounders, with a hazard ratio (HR) of 1.20 (95% CI 1.11, 1.30) per 59.48 µmol/L (1 mg/dL) uric acid. The genetic score raised uric acid by 17 µmol/L (95% CI 15, 18) per SD increase and explained 4% of uric acid variation. By using the genetic score to estimate the unconfounded effect, we found that a 59.48 µmol/L higher uric acid concentration did not have a causal effect on diabetes (HR 1.01 [95% CI 0.87, 1.16]). Including data from the Diabetes Genetics Replication And Meta-analysis (DIAGRAM) consortium, increasing our dataset to 41,508 case subjects with diabetes, the summary odds ratio estimate was 0.99 (95% CI 0.92, 1.06). In conclusion, our study does not support a causal effect of circulating uric acid on diabetes risk. Uric acid-lowering therapies may therefore not be beneficial in reducing diabetes risk.

HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials.

BACKGROUND: Statins increase the risk of new-onset type 2 diabetes mellitus. We aimed to assess whether this increase in risk is a consequence of inhibition of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), the intended drug target. METHODS: We used single nucleotide polymorphisms in the HMGCR gene, rs17238484 (for the main analysis) and rs12916 (for a subsidiary analysis) as proxies for HMGCR inhibition by statins. We examined associations of these variants with plasma lipid, glucose, and insulin concentrations; bodyweight; waist circumference; and prevalent and incident type 2 diabetes. Study-specific effect estimates per copy of each LDL-lowering allele were pooled by meta-analysis. These findings were compared with a meta-analysis of new-onset type 2 diabetes and bodyweight change data from randomised trials of statin drugs. The effects of statins in each randomised trial were assessed using meta-analysis. FINDINGS: Data were available for up to 223 463 individuals from 43 genetic studies. Each additional rs17238484-G allele was associated with a mean 0·06 mmol/L (95% CI 0·05-0·07) lower LDL cholesterol and higher body weight (0·30 kg, 0·18-0·43), waist circumference (0·32 cm, 0·16-0·47), plasma insulin concentration (1·62%, 0·53-2·72), and plasma glucose concentration (0·23%, 0·02-0·44). The rs12916 SNP had similar effects on LDL cholesterol, bodyweight, and waist circumference. The rs17238484-G allele seemed to be associated with higher risk of type 2 diabetes (odds ratio [OR] per allele 1·02, 95% CI 1·00-1·05); the rs12916-T allele association was consistent (1·06, 1·03-1·09). In 129 170 individuals in randomised trials, statins lowered LDL cholesterol by 0·92 mmol/L (95% CI 0·18-1·67) at 1-year of follow-up, increased bodyweight by 0·24 kg (95% CI 0·10-0·38 in all trials; 0·33 kg, 95% CI 0·24-0·42 in placebo or standard care controlled trials and -0·15 kg, 95% CI -0·39 to 0·08 in intensive-dose vs moderate-dose trials) at a mean of 4·2 years (range 1·9-6·7) of follow-up, and increased the odds of new-onset type 2 diabetes (OR 1·12, 95% CI 1·06-1·18 in all trials; 1·11, 95% CI 1·03-1·20 in placebo or standard care controlled trials and 1·12, 95% CI 1·04-1·22 in intensive-dose vs moderate dose trials). INTERPRETATION: The increased risk of type 2 diabetes noted with statins is at least partially explained by HMGCR inhibition. FUNDING: The funding sources are cited at the end of the paper.

Plasma advanced glycation end products are associated with incident cardiovascular events in individuals with type 2 diabetes: a case-cohort study with a median follow-up of 10 years (EPIC-NL).

Experimental data suggest a role for advanced glycation end products (AGEs) in cardiovascular disease (CVD), particularly in type 2 diabetes (T2DM). However, epidemiological evidence of an association between high plasma AGEs and increased cardiovascular risk remains inconclusive. Therefore, in a case-cohort study comprising 134 cardiovascular case subjects and a random subcohort of 218 individuals (including 65 cardiovascular case subjects), all with T2DM and nested in the European Prospective Investigation into Cancer and Nutrition in the Netherlands (EPIC-NL) study, plasma levels of protein-bound Nε-(carboxymethyl)lysine, Nε-(carboxyethyl)lysine, and pentosidine were measured with liquid chromatography. AGEs were loge-transformed, combined in a z-score, and the association with incident cardiovascular events was analyzed with Cox proportional hazard regression, adapted for case-cohort design (Prentice method). After multivariable adjustment (sex, age, cohort status, diabetes duration, total cholesterol to HDL-cholesterol ratio, smoking, systolic blood pressure, BMI, blood pressure-, cholesterol- and glucose-lowering treatment, prior cardiovascular events, and triglycerides), higher plasma AGE z-scores were associated with higher risk of incident cardiovascular events in individuals without prior cardiovascular events (hazard ratio 1.31 [95% CI: 1.06-1.61]). A similar trend was observed in individuals with prior cardiovascular events (1.37 [0.63-2.98]). In conclusion, high plasma AGEs were associated with incident cardiovascular events in individuals with T2DM. These results underline the potential importance of AGEs in development of CVD.

Smoking and long-term risk of type 2 diabetes: the EPIC-InterAct study in European populations.

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.

Association between Mediterranean and Nordic diet scores and changes in weight and waist circumference: influence of FTO and TCF7L2 loci.

BACKGROUND: Several studies have shown that adherence to the Mediterranean Diet measured by using the Mediterranean diet score (MDS) is associated with lower obesity risk. The newly proposed Nordic Diet could hold similar beneficial effects. Because of the increasing focus on the interaction between diet and genetic predisposition to adiposity, studies should consider both diet and genetics. OBJECTIVE: We investigated whether FTO rs9939609 and TCF7L2 rs7903146 modified the association between the MDS and Nordic diet score (NDS) and changes in weight (Δweight), waist circumference (ΔWC), and waist circumference adjusted for body mass index (BMI) (ΔWCBMI). DESIGN: We conducted a case-cohort study with a median follow-up of 6.8 y that included 11,048 participants from 5 European countries; 5552 of these subjects were cases defined as individuals with the greatest degree of unexplained weight gain during follow-up. A randomly selected subcohort included 6548 participants, including 5496 noncases. Cases and noncases were compared in analyses by using logistic regression. Continuous traits (ie, Δweight, ΔWC, and ΔWCBMI) were analyzed by using linear regression models in the random subcohort. Interactions were tested by including interaction terms in models. RESULTS: A higher MDS was significantly inversely associated with case status (OR: 0.98; 95% CI: 0.96, 1.00), ΔWC (ß = -0.010 cm/y; 95% CI: -0.020, -0.001 cm/y), and ΔWCBMI (ß = -0.008; 95% CI:-0.015, -0.001) per 1-point increment but not Δweight (P = 0.53). The NDS was not significantly associated with any outcome. There was a borderline significant interaction between the MDS and TCF7L2 rs7903146 on weight gain (P = 0.05), which suggested a beneficial effect of the MDS only in subjects who carried 1 or 2 risk alleles. FTO did not modify observed associations. CONCLUSIONS: A high MDS is associated with a lower ΔWC and ΔWCBMI, regardless of FTO and TCF7L2 risk alleles. For Δweight, findings were less clear, but the effect may depend on the TCF7L2 rs7903146 variant. The NDS was not associated with anthropometric changes during follow-up.

Differences in the prospective association between individual plasma phospholipid saturated fatty acids and incident type 2 diabetes: the EPIC-InterAct case-cohort study.

BACKGROUND: Conflicting evidence exists regarding the association between saturated fatty acids (SFAs) and type 2 diabetes. In this longitudinal case-cohort study, we aimed to investigate the prospective associations between objectively measured individual plasma phospholipid SFAs and incident type 2 diabetes in EPIC-InterAct participants. METHODS: The EPIC-InterAct case-cohort study includes 12,403 people with incident type 2 diabetes and a representative subcohort of 16,154 individuals who were selected from a cohort of 340.234 European participants with 3·99 million person-years of follow-up (the EPIC study). Incident type 2 diabetes was ascertained until Dec 31, 2007, by a review of several sources of evidence. Gas chromatography was used to measure the distribution of fatty acids in plasma phospholipids (mol%); samples from people with type 2 diabetes and subcohort participants were processed in a random order by centre, and laboratory staff were masked to participant characteristics. We estimated country-specific hazard ratios (HRs) for associations per SD of each SFA with incident type 2 diabetes using Prentice-weighted Cox regression, which is weighted for case-cohort sampling, and pooled our findings using random-effects meta-analysis. FINDINGS: SFAs accounted for 46% of total plasma phospholipid fatty acids. In adjusted analyses, different individual SFAs were associated with incident type 2 diabetes in opposing directions. Even-chain SFAs that were measured (14:0 [myristic acid], 16:0 [palmitic acid], and 18:0 [stearic acid]) were positively associated with incident type 2 diabetes (HR [95% CI] per SD difference: myristic acid 1·15 [95% CI 1·09-1·22], palmitic acid 1·26 [1·15-1·37], and stearic acid 1·06 [1·00-1·13]). By contrast, measured odd-chain SFAs (15:0 [pentadecanoic acid] and 17:0 [heptadecanoic acid]) were inversely associated with incident type 2 diabetes (HR [95% CI] per 1 SD difference: 0·79 [0·73-0·85] for pentadecanoic acid and 0·67 [0·63-0·71] for heptadecanoic acid), as were measured longer-chain SFAs (20:0 [arachidic acid], 22:0 [behenic acid], 23:0 [tricosanoic acid], and 24:0 [lignoceric acid]), with HRs ranging from 0·72 to 0·81 (95% CIs ranging between 0·61 and 0·92). Our findings were robust to a range of sensitivity analyses. INTERPRETATION: Different individual plasma phospholipid SFAs were associated with incident type 2 diabetes in opposite directions, which suggests that SFAs are not homogeneous in their effects. Our findings emphasise the importance of the recognition of subtypes of these fatty acids. An improved understanding of differences in sources of individual SFAs from dietary intake versus endogenous metabolism is needed. FUNDING: EU FP6 programme, Medical Research Council Epidemiology Unit, Medical Research Council Human Nutrition Research, and Cambridge Lipidomics Biomarker Research Initiative.

Common genetic variants highlight the role of insulin resistance and body fat distribution in type 2 diabetes, independent of obesity.

We aimed to validate genetic variants as instruments for insulin resistance and secretion, to characterize their association with intermediate phenotypes, and to investigate their role in type 2 diabetes (T2D) risk among normal-weight, overweight, and obese individuals. We investigated the association of genetic scores with euglycemic-hyperinsulinemic clamp- and oral glucose tolerance test-based measures of insulin resistance and secretion and a range of metabolic measures in up to 18,565 individuals. We also studied their association with T2D risk among normal-weight, overweight, and obese individuals in up to 8,124 incident T2D cases. The insulin resistance score was associated with lower insulin sensitivity measured by M/I value (ß in SDs per allele [95% CI], -0.03 [-0.04, -0.01]; P = 0.004). This score was associated with lower BMI (-0.01 [-0.01, -0.0]; P = 0.02) and gluteofemoral fat mass (-0.03 [-0.05, -0.02; P = 1.4 × 10(-6)) and with higher alanine transaminase (0.02 [0.01, 0.03]; P = 0.002) and γ-glutamyl transferase (0.02 [0.01, 0.03]; P = 0.001). While the secretion score had a stronger association with T2D in leaner individuals (Pinteraction = 0.001), we saw no difference in the association of the insulin resistance score with T2D among BMI or waist strata (Pinteraction > 0.31). While insulin resistance is often considered secondary to obesity, the association of the insulin resistance score with lower BMI and adiposity and with incident T2D even among individuals of normal weight highlights the role of insulin resistance and ectopic fat distribution in T2D, independently of body size.

Gene-lifestyle interaction and type 2 diabetes: the EPIC interact case-cohort study.

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  = 1.20×10-4). 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  = 1.50×10-3) and waist circumference (p for interaction  = 7.49×10-9). 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.

Dietary protein intake and incidence of type 2 diabetes in Europe: the EPIC-InterAct Case-Cohort Study.

OBJECTIVE: The long-term association between dietary protein and type 2 diabetes incidence is uncertain. We aimed to investigate the association between total, animal, and plant protein intake and the incidence of type 2 diabetes. RESEARCH DESIGN AND METHODS: The prospective European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct case-cohort study consists of 12,403 incident type 2 diabetes cases and a stratified subcohort of 16,154 individuals from eight European countries, with an average follow-up time of 12.0 years. Pooled country-specific hazard ratios (HRs) and 95% CI of prentice-weighted Cox regression analyses were used to estimate type 2 diabetes incidence according to protein intake. RESULTS: After adjustment for important diabetes risk factors and dietary factors, the incidence of type 2 diabetes was higher in those with high intake of total protein (per 10 g: HR 1.06 [95% CI 1.02-1.09], P(trend) < 0.001) and animal protein (per 10 g: 1.05 [1.02-1.08], P(trend) = 0.001). Effect modification by sex (P < 0.001) and BMI among women (P < 0.001) was observed. Compared with the overall analyses, associations were stronger in women, more specifically obese women with a BMI >30 kg/m(2) (per 10 g animal protein: 1.19 [1.09-1.32]), and nonsignificant in men. Plant protein intake was not associated with type 2 diabetes (per 10 g: 1.04 [0.93-1.16], P(trend) = 0.098). CONCLUSIONS: High total and animal protein intake was associated with a modest elevated risk of type 2 diabetes in a large cohort of European adults. In view of the rapidly increasing prevalence of type 2 diabetes, limiting iso-energetic diets high in dietary proteins, particularly from animal sources, should be considered.

Non-invasive risk scores for prediction of type 2 diabetes (EPIC-InterAct): a validation of existing models.

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.