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Aims/hypothesis: Existing evidence on the relationship between intake of monounsaturated fatty acids (MUFAs) and type 2 diabetes is conflicting. Few studies have examined whether MUFAs from plant or animal sources (MUFA-Ps and MUFA-As, respectively) exhibit differential associations with type 2 diabetes. We examined associations of intakes of total MUFAs, MUFA-Ps and MUFA-As with type 2 diabetes risk., Methods: We used data from 51,290 women in the Nurses' Health Study (1990-2016), 61,703 women in the Nurses' Health Study II (1991-2017) and 29,497 men in the Health Professionals Follow-up Study (1990-2016). Using food frequency questionnaires and food composition tables, we calculated MUFA-P and MUFA-A intakes every 4 years and modelled their associations with type 2 diabetes using Cox regression models., Results: During 3,268,512 person-years of follow-up, we documented 13,211 incident type 2 diabetes cases. After multivariate adjustment, total MUFA intake was associated with higher type 2 diabetes risk, with HR for Q5 vs Q1 of 1.10 (95% CI 1.01, 1.22). MUFA-Ps and MUFA-As demonstrated divergent associations, with HRs of 0.87 (95% CI 0.81, 0.94) and 1.34 (1.23, 1.45), respectively. In substitution analyses, HRs were 0.92 (95% CI 0.86, 0.99) for replacing 2% of energy from trans fatty acids or 0.72 (0.66, 0.78) and 0.82 (0.77, 0.88) for replacing 5% from MUFA-As and 5% from the sum of saturated fatty acids and MUFA-As with MUFA-Ps, respectively. Substituting MUFA-As for saturated fatty acids and refined carbohydrates was associated with a 43% and 33% higher risk, respectively., Conclusions/interpretation: Higher intake of MUFA-Ps was associated with lower type 2 diabetes risk, whereas increased intake of MUFA-As was associated with higher risk. Replacing saturated fatty acids, trans fatty acids and MUFA-As with MUFA-Ps may be beneficial for type 2 diabetes prevention., Competing Interests: Acknowledgements: The authors thank the participants and staff of the NHS, NHSII and HPFS for their valuable contributions. Data availability: The datasets generated and analysed during the current study are available from the corresponding author on request. Funding: The NHS and HPFS studies and the current analysis are supported by National Institutes of Health grants UM1 CA186107, CA167552, DK120870, DK082486, DK126698, DK119268, DK129670, HL035464, HL060712, HL088521, DK058845, U01 CA176726, CA167552, ES022981, ES036206 and HL034594. The funding sources did not play a role in the design or conduct of the study; collection, management, analyses or interpretation of the data; or preparation, review or approval of the manuscript. Some of the data were presented as an abstract at the American Heart Association’s Epidemiology and Prevention/Lifestyle and Cardiometabolic Health meeting in 2019. Authors' relationships and activities: The authors declare that there are no relationships or activities that might bias, or be perceived to bias, their work. Contribution statement: QS, FQ and ZC conceived the study. QS and FBH were involved in data collection. FQ and ZC analysed the data. QS and YL provided statistical expertise. FQ and ZC wrote the first draft of the paper. All authors contributed to the interpretation of the results and revision of the manuscript for important intellectual content and approved the final version of the manuscript. The results of the study are presented clearly, honestly and without fabrication, falsification or inappropriate data manipulation. The authors assume full responsibility for analyses and interpretation of these data. QS and ZC are the guarantors. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted., (© 2025. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Aims/hypothesis: A positive association between sugar-sweetened beverages (SSBs) and diabetes risk has been shown, with inconsistent evidence between artificially sweetened beverages (ASBs) and diabetes. Moreover, it is uncertain if physical activity can mitigate the negative effects of these beverages on diabetes development. Therefore, we aimed to evaluate the independent and joint associations between SSB or ASB consumption and physical activity on the risk of type 2 diabetes., Methods: We followed 64,029 women in the Nurses' Health Study (1980-2016), 88,340 women in the Nurses' Health Study II (1991-2017) and 39,436 men in the Health Professionals Follow-up Study (1986-2016). SSB and ASB consumption was calculated from food-frequency questionnaires administered every 4 years, while physical activity data were collected biennially. A validated supplementary questionnaire on diabetes symptoms, diagnostic tests and treatment confirmed type 2 diabetes cases. Multivariable Cox proportional hazards regression models were used to calculate HRs and 95% CIs for developing type 2 diabetes., Results: During 5,105,351 person-years of follow-up, we recorded 19,940 new cases of type 2 diabetes. Compared with those who never or rarely consumed SSBs or ASBs, those who consumed ≥2 servings/day had a 41% (HR 1.41 [95% CI 1.33, 1.50]) and 11% (HR 1.11 [95% CI 1.07, 1.16]) higher risk of type 2 diabetes, respectively. For participants meeting physical activity guidelines (≥7.5 metabolic equivalent of task [MET] h/week) and consuming ≥2 servings/week of SSBs or ASBs, the risk was 22% (HR 1.22 [95% CI 1.15, 1.29]) and 7% (HR 1.07 [95% CI 1.02, 1.12]) higher, respectively, compared with those who met physical activity guidelines and never or rarely (<1 serving/month) consumed these beverages. For participants meeting the physical activity guidelines and consuming 1-4 servings/month of SSBs, there was a 9% (HR 1.09 [95% CI 1.02, 1.15]) higher risk of type 2 diabetes. Compared with the reference group (those who met physical activity guidelines and consumed <1 SSB serving/month), adults who did not meet physical activity guidelines (<7.5 MET h/week) and who never or rarely (<1 serving/month) consumed SSBs, had 1-4 SSB servings/month, or had ≥2 SSB servings/week, the HRs (95% CIs) were 1.22 (1.13, 1.31), 1.28 (1.20, 1.37), and 1.51 (1.43, 1.61), respectively. Similarly, for ASB consumption, adults who did not meet physical activity guidelines and who never or rarely (<1 serving/month) consumed ASBs, had 1-4 servings/month, or had ≥2 servings/week, the HRs (95% CIs) were 1.21 (1.14, 1.28), 1.21 (1.13, 1.30), and 1.30 (1.23, 1.37) compared with the reference group (who met physical activity guidelines and consumed <1 ASB serving/month)., Conclusions/interpretation: Even when individuals were physically active, a higher consumption of SSBs or ASBs was associated with a higher risk of type 2 diabetes. Meeting physical activity guidelines reduced the impact of SSB and ASB consumption on diabetes risk, underscoring the need to promote physical activity as part of lifestyle modifications to lower diabetes incidence., Competing Interests: Acknowledgements: The authors thank the participants and staff of the NHS, NHSII and HPFS for their valuable contributions. Some of the data were presented as an abstract at the American Heart Association's Epidemiology and Prevention/Lifestyle and Cardiometabolic Health 2023 Scientific Sessions. Data availability: The datasets analysed during the current study are available from the corresponding author on request. Funding: The research reported in this manuscript was supported by National Institutes of Health grants UM1 CA186107, U01 CA167552 and U01 CA176726. Additionally, this work was supported by grant T32 DK007703-26 (LSP), K01HL169414 (LSP) from the National Heart, Lung, and Blood Institute and K01 DK136968 (DEH) from the National Institute of Diabetes and Digestive and Kidney Diseases. Other funding sources include R01DK125803 (DKT), R01DK131753 (SNB), R01DK120560 (SNB) and R01DK125273 (CBE) from the National Institutes of Health, the Thrasher Research Fund (CBE), the New Balance Foundation (CBE), the Arnold Ventures (CBE) and Dairy Farmers of Canada (J-PD-C), and the Novo Nordisk Foundation grant NNF18CC0034900 (MG-F). Authors’ relationships and activities: LSP has been supported by grants T32 DK007703-26 from the NIH; DKT has been supported by grant R01DK125803 from the NIH and is currently a member of the 2025 US Dietary Guidelines Scientific Advisory Committee, reviewing beverages and cardiovascular disease; SNB has been supported by grants R01DK131753 and R01DK120560 from the NIH and discloses a pending patent entitled ‘system and methods for conducting nutritional health risk assessments and adapting risk analyses based on actual health outcomes’ (provisional application filed on 20 May 2022; US Application No. 63/344,293); WCW is part of the EAT Foundation Advisory Board (unpaid position) and receives royalties for the textbook Nutritional Epidemiology, Oxford University Press; DSL discloses royalties for a book that recommends a carbohydrate-modified diet; CBE has been supported by grant R01DK125273 from the NIH, as well as grants from the Thrasher Research Fund, New Balance Foundation, and Arnold Ventures, and honoraria from the Columbia Cornell Obesity course and the University of Arkansas for Medical Sciences (speaker); J-PD-C has been supported by grants and received payments (research grant review committee) from the Dairy Farmers of Canada. MG-F is supported by a Novo Nordisk Foundation grant NNF18CC0034900. MG-F is the PI of a grant from the International Nut Council (INC). All other authors declare that there are no relationships or activities that might bias, or be perceived to bias, their work. Contribution statement: LSP formulated the study question and design, performed the statistical analyses, interpreted the results and wrote the complete first draft of the manuscript. DKT, YL, SNB, DEH, J-PD-C, DSL, CBE and WCW revised and edited the manuscript and made substantial contributions to the interpretation of data. FBH and MG-F formulated the study question and design, interpreted the results and edited the manuscript. FBH and WCW obtained funding. YL assisted in statistical analyses and interpretation of data. All authors participated in critical revision of the manuscript and approved the final version of the manuscript. The corresponding author (LSP) and senior author (MG-F) take full responsibility for the work and/or the conduct of the study, had access to the data and controlled the decision to publish., (© 2025. The Author(s).)

Aims/hypothesis: Many studies have examined the relationship between plasma metabolites and type 2 diabetes progression, but few have explored saliva and multi-fluid metabolites., Methods: We used LC/MS to measure plasma (n=1051) and saliva (n=635) metabolites among Puerto Rican adults from the San Juan Overweight Adults Longitudinal Study. We used elastic net regression to identify plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting baseline HOMA-IR in a training set (n=509) and validated these scores in a testing set (n=340). We used multivariable Cox proportional hazards models to estimate HRs for the association of baseline metabolomic scores predicting insulin resistance with incident type 2 diabetes (n=54) and prediabetes (characterised by impaired glucose tolerance, impaired fasting glucose and/or high HbA 1c ) (n=130) at 3 years, along with regression from prediabetes to normoglycaemia (n=122), adjusting for traditional diabetes-related risk factors., Results: Plasma, saliva and multi-fluid plasma-saliva metabolomic scores predicting insulin resistance included highly weighted metabolites from fructose, tyrosine, lipid and amino acid metabolism. Each SD increase in the plasma (HR 1.99 [95% CI 1.18, 3.38]; p=0.01) and multi-fluid (1.80 [1.06, 3.07]; p=0.03) metabolomic scores was associated with higher risk of type 2 diabetes. The saliva metabolomic score was associated with incident prediabetes (1.48 [1.17, 1.86]; p=0.001). All three metabolomic scores were significantly associated with lower likelihood of regressing from prediabetes to normoglycaemia in models adjusting for adiposity (HRs 0.72 for plasma, 0.78 for saliva and 0.72 for multi-fluid), but associations were attenuated when adjusting for lipid and glycaemic measures., Conclusions/interpretation: The plasma metabolomic score predicting insulin resistance was more strongly associated with incident type 2 diabetes than the saliva metabolomic score. Only the saliva metabolomic score was associated with incident prediabetes., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Aims/hypothesis: Diets with higher inflammatory and insulinaemic potential have been associated with an increased risk of type 2 diabetes. However, it remains unknown whether plasma metabolomic profiles related to proinflammatory/hyperinsulinaemic diets and to inflammatory/insulin biomarkers are associated with type 2 diabetes risk., Methods: We analysed 6840 participants from the Nurses' Health Study and Health Professionals Follow-up Study to identify the plasma metabolome related to empirical dietary inflammatory pattern (EDIP), empirical dietary index for hyperinsulinemia (EDIH), four circulating inflammatory biomarkers and C-peptide. Dietary intakes were assessed using validated food frequency questionnaires. Plasma metabolomic profiling was conducted by LC-MS/MS. Metabolomic signatures were derived using elastic net regression. Multivariable Cox regression was used to examine associations of the metabolomic profiles with type 2 diabetes risk., Results: We identified 27 metabolites commonly associated with both EDIP and inflammatory biomarker z score and 21 commonly associated with both EDIH and C-peptide. Higher metabolomic dietary inflammatory potential (MDIP), reflecting higher metabolic potential of both an inflammatory dietary pattern and circulating inflammatory biomarkers, was associated with higher type 2 diabetes risk. The HR comparing highest vs lowest quartiles of MDIP was 3.26 (95% CI 2.39, 4.44). We observed a strong positive association with type 2 diabetes risk for the metabolomic signature associated with EDIP-only (HR 3.75; 95% CI 2.71, 5.17) or inflammatory biomarkers-only (HR 4.07; 95% CI 2.91, 5.69). In addition, higher metabolomic dietary index for hyperinsulinaemia (MDIH), reflecting higher metabolic potential of both an insulinaemic dietary pattern and circulating C-peptide, was associated with greater type 2 diabetes risk (HR 3.00; 95% CI 2.22, 4.06); further associations with type 2 diabetes were HR 2.79 (95% CI 2.07, 3.76) for EDIH-only signature and HR 3.89 (95% CI 2.82, 5.35) for C-peptide-only signature. The diet scores were significantly associated with risk, although adjustment for the corresponding metabolomic signature scores attenuated the associations with type 2 diabetes, these remained significant., Conclusions/interpretation: The metabolomic signatures reflecting proinflammatory or hyperinsulinaemic diets and related biomarkers were positively associated with type 2 diabetes risk, supporting that these dietary patterns may influence type 2 diabetes risk via the regulation of metabolism., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Aims/hypothesis: Plant-based diets, especially when rich in healthy plant foods, have been associated with a lower risk of type 2 diabetes. However, whether plasma metabolite profiles related to plant-based diets reflect this association was unknown. The aim of this study was to identify the plasma metabolite profiles related to plant-based diets, and to evaluate the associations between the identified metabolite profiles and the risk of type 2 diabetes., Methods: Within three prospective cohorts (Nurses' Health Study, Nurses' Health Study II and Health Professionals Follow-up Study), we measured plasma metabolites from 10,684 participants using high-throughput LC MS. Adherence to plant-based diets was assessed by three indices derived from the food frequency questionnaire: an overall Plant-based Diet Index (PDI), a Healthy Plant-based Diet Index (hPDI), and an Unhealthy Plant-based Diet Index (uPDI). Multi-metabolite profiles related to plant-based diet were identified using elastic net regression with a training/testing approach. The prospective associations between metabolite profiles and incident type 2 diabetes were evaluated using multivariable Cox proportional hazards regression. Metabolites potentially mediating the association between plant-based diets and type 2 diabetes risk were further identified., Results: We identified multi-metabolite profiles comprising 55 metabolites for PDI, 93 metabolites for hPDI and 75 metabolites for uPDI. Metabolite profile scores based on the identified metabolite profiles were correlated with the corresponding diet index (Pearson r = 0.33-0.35 for PDI, 0.41-0.45 for hPDI, and 0.37-0.38 for uPDI, all p<0.001). Metabolite profile scores of PDI (HR per 1 SD higher = 0.81 [95% CI 0.75, 0.88]) and hPDI (HR per 1 SD higher = 0.77 [95% CI 0.71, 0.84]) showed an inverse association with incident type 2 diabetes, whereas the metabolite profile score for uPDI was not associated with the risk. Mutual adjustment for metabolites selected in the metabolite profiles, including trigonelline, hippurate, isoleucine and a subset of triacylglycerols, attenuated the associations of diet indices PDI and hPDI with lower type 2 diabetes risk. The explainable proportion of PDI/hPDI-related diabetes risk by these metabolites ranged between 8.5% and 37.2% (all p<0.05)., Conclusions/interpretation: Plasma metabolite profiles related to plant-based diets, especially a healthy plant-based diet, were associated with a lower risk of type 2 diabetes among a generally healthy population. Our findings support the beneficial role of healthy plant-based diets in diabetes prevention and provide new insights for future investigation., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Aims/hypothesis: We aimed to evaluate associations of multiple recommended dietary patterns (i.e. the alternate Mediterranean diet [aMED], the Healthy Eating Index [HEI]-2015 and the healthful Plant-based Diet Index [hPDI]) with serum metabolite profile, and to examine dietary-pattern-associated metabolites in relation to incident diabetes., Methods: We included 2842 adult participants free from diabetes, CVD and cancer during baseline recruitment of the Hispanic Community Health Study/Study of Latinos. Metabolomics profiling of fasting serum was performed using an untargeted approach. Dietary pattern scores were derived using information collected by two 24 h dietary recalls. Dietary-pattern-associated metabolites were identified using multivariable survey linear regressions and their associations with incident diabetes were assessed using multivariable survey Poisson regressions with adjustment for traditional risk factors., Results: We identified eight metabolites (mannose, γ/β-tocopherol, N1-methylinosine, pyrraline and four amino acids) that were inversely associated with all dietary scores. These metabolites were detrimentally associated with various cardiometabolic risk traits, especially insulin resistance. A score comprised of these metabolites was associated with elevated risk of diabetes (RR per SD 1.54 [95% CI 1.29, 1.83]), and this detrimental association appeared to be attenuated or eliminated by having a higher score for aMED (p interaction  = 0.0001), HEI-2015 (p interaction  = 0.020) or hPDI (p interaction  = 0.023). For example, RR (95% CI) of diabetes for each SD increment in the metabolite score was 1.99 (1.44, 2.37), 1.67 (1.17, 2.38) and 1.08 (0.86, 1.34) across the lowest to the highest tertile of aMED score, respectively., Conclusions/interpretation: Various recommended dietary patterns were inversely related to a group of metabolites that were associated with elevated risk of diabetes. Adhering to a healthful eating pattern may attenuate or eliminate the detrimental association between metabolically unhealthy serum metabolites and risk of diabetes., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Aims/hypothesis: Prolactin, a multifunctional hormone, is involved in regulating insulin sensitivity and glucose homeostasis in experimental studies. However, whether circulating concentrations of prolactin are associated with risk of type 2 diabetes remains uncertain., Methods: We analysed the prospective relationship between circulating prolactin concentrations and type 2 diabetes risk in the Nurses' Health Study (NHS) and NHSII with up to 22 years of follow-up. Total plasma prolactin was measured using immunoassay in 8615 women free of type 2 diabetes and cardiovascular disease at baseline blood collection (NHS 1989-1990; NHSII 1996-1999) and a subset of 998 NHS women providing a second blood sample during 2000-2002. Baseline bioactive prolactin was measured in a subset of 2478 women using the Nb2 bioassay. HRs were estimated using Cox regression., Results: A total of 699 incident type 2 diabetes cases were documented during 156,140 person-years of follow-up. Total plasma prolactin levels were inversely associated with type 2 diabetes risk; the multivariable HR comparing the highest with the lowest quartile was 0.73 (95% CI 0.55, 0.95; p trend  = 0.02). The associations were similar by menopausal status and other risk factors (p interaction  > 0.70). Additional adjustment for sex and growth hormones, adiponectin, and inflammatory and insulin markers did not significantly alter the results. The association of plasma bioactive prolactin with type 2 diabetes risk was non-significantly stronger than that of total prolactin (HR comparing extreme quartiles, 0.53 vs 0.81 among the subset of 2478 women, p difference  = 0.11). The inverse association of total prolactin with type 2 diabetes was significant during the first 9 years after blood draw but waned linearly with time, whereas for bioactive prolactin, the inverse relationship persisted for a longer follow-up time after blood draw., Conclusions/interpretation: A normally high circulating total prolactin concentration was associated with a lower type 2 diabetes risk within 9-10 years of follow-up since blood draw in US women. Our findings are consistent with experimental evidence, suggesting that among healthy women, prolactin within the biologically normal range may play a protective role in the pathogenesis of type 2 diabetes.

Aims/hypothesis: We investigated the association between gluten intake and long-term type 2 diabetes risk among Americans., Methods: We followed women from the Nurses' Health Study (NHS, n = 71,602, 1984-2012) and NHS II (n = 88,604, 1991-2013) and men from the Health Professionals Follow-Up Study (HPFS, n = 41,908, 1986-2012). Gluten intake was estimated using a validated food frequency questionnaire every 2-4 years. Incident type 2 diabetes was defined as self-reported physician-diagnosed diabetes confirmed using a supplementary questionnaire., Result: Gluten intake was strongly correlated with intakes of carbohydrate components, especially refined grains, starch and cereal fibre (Spearman correlation coefficients >0.6). During 4.24 million years of follow-up, 15,947 people were confirmed to have type 2 diabetes. After multivariate adjustment, pooled HRs and 95% CIs for type 2 diabetes, from low to high gluten quintiles, were (p trend  < 0.001): 1 (reference); 0.89 (0.85, 0.93); 0.84 (0.80, 0.88); 0.78 (0.74, 0.82) and 0.80 (0.76, 0.84). The association was slightly weakened after further adjusting for cereal fibre, with pooled HRs (95% CIs) of (p trend  < 0.001): 1 (reference); 0.91 (0.87, 0.96); 0.88 (0.83, 0.93); 0.83 (0.78, 0.88) and 0.87 (0.81, 0.93). Dose-response analysis supported a largely linear inverse relationship between gluten intake up to 12 g/day and type 2 diabetes. The association between gluten intake and type 2 diabetes was stronger when intake of added bran was also higher (p interaction  = 0.02)., Conclusions/interpretation: Gluten intake is inversely associated with type 2 diabetes risk among largely healthy US men and women. Limiting gluten in the diet is associated with lower intake of cereal fibre and possibly other beneficial nutrients that contribute to good health.

Aims/hypothesis: Gestational diabetes mellitus (GDM) is a common complication of pregnancy that has substantial short- and long-term adverse health implications for women and their children. However, large-scale studies on genetic risk loci for GDM remain sparse., Methods: We conducted a case-control study among 2636 women with GDM and 6086 non-GDM control women from the Nurses' Health Study II and the Danish National Birth Cohort. A total of 112 susceptibility genetic variants confirmed by genome-wide association studies for type 2 diabetes were selected and measured. A weighted genetic risk score (GRS) was created based on variants that were significantly associated with risk of GDM after correcting for the false discovery rate., Results: For the first time, we identified eight variants associated with GDM, namely rs7957197 (HNF1A), rs10814916 (GLIS3), rs3802177 (SLC30A8), rs9379084 (RREB1), rs34872471 (TCF7L2), rs7903146 (TCF7L2), rs11787792 (GPSM1) and rs7041847 (GLIS3). In addition, we confirmed three variants, rs10830963 (MTNR1B), rs1387153 (MTNR1B) and rs4506565 (TCF7L2), that had previously been significantly associated with GDM risk. Furthermore, compared with participants in the first (lowest) quartile of weighted GRS based on these 11 SNPs, the ORs for GDM were 1.07 (95% CI 0.93, 1.22), 1.23 (95% CI 1.07, 1.41) and 1.53 (95% CI 1.34, 1.74) for participants in the second, third and fourth (highest) quartiles, respectively. The significant positive associations between the weighted GRS and risk of GDM persisted across most of the strata of major risk factors for GDM, including family history of type 2 diabetes, smoking status, BMI and age., Conclusions/interpretation: In this large-scale case-control study with women from two independent populations, eight novel GDM SNPs were identified. These findings offer the potential to improve our understanding of the aetiology of GDM, and particularly of biological mechanisms related to beta cell function.

Aims/hypothesis: Branched-chain amino acids (BCAAs) and aromatic amino acids (AAAs) are associated with type 2 diabetes. However, repeated measurements of BCAA/AAA and their interactions with dietary interventions have not been evaluated. We investigated the associations between baseline and changes at 1 year in BCAA/AAA with type 2 diabetes in the context of a Mediterranean diet (MedDiet) trial., Methods: We included 251 participants with incident type 2 diabetes and a random sample of 694 participants (641 participants without type 2 diabetes and 53 overlapping cases) in a case-cohort study nested within the PREvención con DIeta MEDiterránea (PREDIMED) trial. Participants were randomised to a MedDiet+extra-virgin olive oil (n = 273), a MedDiet+nuts (n = 324) or a control diet (n = 295). We used LC-MS/MS to measure plasma levels of amino acids. Type 2 diabetes was a pre-specified secondary outcome of the PREDIMED trial., Results: Elevated plasma levels of individual BCAAs/AAAs were associated with higher type 2 diabetes risk after a median follow-up of 3.8 years: multivariable HR for the highest vs lowest quartile ranged from 1.32 for phenylalanine ([95% CI 0.90, 1.92], p for trend = 0.015) to 3.29 for leucine ([95% CI 2.03, 5.34], p for trend<0.001). Increases in BCAA score at 1 year were associated with higher type 2 diabetes risk in the control group with HR per SD = 1.61 (95% CI 1.02, 2.54), but not in the MedDiet groups (p for interaction <0.001). The MedDiet+extra-virgin olive oil significantly reduced BCAA levels after 1 year of intervention (p = 0.005 vs the control group)., Conclusions/interpretation: Our results support that higher baseline BCAAs and their increases at 1 year were associated with higher type 2 diabetes risk. A Mediterranean diet rich in extra-virgin olive oil significantly reduced the levels of BCAA and attenuated the positive association between plasma BCAA levels and type 2 diabetes incidence. Clinical trial number: SRCTN35739639 ( www.controlled-trials.com ).

Aims/hypothesis: Studies suggest a potential link between low-grade metabolic acidosis and type 2 diabetes. A western dietary pattern increases daily acid load but the association between diet-dependent acid load and type 2 diabetes is still unclear. This study aimed to assess whether diet-dependent acid load is associated with the risk of type 2 diabetes., Methods: We examined the association between energy-adjusted net endogenous acid production (NEAP), potential renal acid load (PRAL) and animal protein-to-potassium ratio (A:P) on incident type 2 diabetes in 67,433 women from the Nurses' Health Study, 84,310 women from the Nurses' Health Study II and 35,743 men from the Health Professionals' Follow-up Study who were free from type 2 diabetes, cardiovascular disease and cancer at baseline. Study-specific HRs were estimated using Cox proportional hazards models with time-varying covariates and were pooled using a random effects meta-analysis., Results: We documented 15,305 cases of type 2 diabetes during 4,025,131 person-years of follow-up. After adjustment for diabetes risk factors, dietary NEAP, PRAL and A:P were positively associated with type 2 diabetes (pooled HR [95% CI] for highest (Q5) vs lowest quintile (Q1): 1.29 [1.22, 1.37], p trend <0.0001; 1.29 [1.22, 1.36], p trend <0.0001 and 1.32 [1.24, 1.40], p trend <0.0001 for NEAP, PRAL and A:P, respectively). These results were not fully explained by other dietary factors including glycaemic load and dietary quality (HR [95% CI] for Q5 vs Q1: 1.21 [1.09, 1.33], p trend <0.0001; 1.19 [1.08, 1.30] and 1.26 [1.17, 1.36], p trend <0.0001 for NEAP, PRAL and A:P, respectively)., Conclusions/interpretation: This study suggests that higher diet-dependent acid load is associated with an increased risk of type 2 diabetes. This association is not fully explained by diabetes risk factors and overall diet quality.

Aims/hypothesis: Low birthweight has been associated with a high risk of type 2 diabetes mellitus in observational studies. However, it remains unclear whether this relation is causal., Methods: The present study included 3627 individuals with type 2 diabetes and 12,974 control participants of European ancestry from the Nurses' Health Study and the Health Professionals Follow-Up Study. A genetic risk score (GRS) was calculated based on five low-birthweight-related single nucleotide polymorphisms (SNPs). We assessed the evidence for causality first by examining the association of the GRS and the individual SNPs with type 2 diabetes, and second by performing a Mendelian randomisation analysis to estimate the potentially causal effect size of low birthweight on type 2 diabetes., Results: In a meta-analysis of the two studies, each 1 point increment in the GRS was associated with a 6% (95% CI 3%, 9%) higher risk of type 2 diabetes. CCNL1 rs900400 and 5q11.2 rs4432842 showed dose-response associations with risk of type 2 diabetes; the corresponding ORs and 95% CIs were 1.09 (1.03, 1.16) and 1.09 (1.02, 1.16), respectively. Furthermore, we observed an overall Mendelian randomisation OR of 2.94 (95% CI 1.70, 5.16; p < 0.001) for type 2 diabetes per 1 SD lower genetically determined birthweight., Conclusions/interpretation: A genetically lowered birthweight was associated with increased susceptibility to type 2 diabetes. Our findings support a potential causal relation between birthweight and risk of type 2 diabetes, providing new evidence to support the role of intrauterine exposures in the pathogenesis of type 2 diabetes.

Aims/hypothesis: Sleeping difficulty has been associated with type 2 diabetes in some prior studies. Whether the observed associations are independent of health behaviours, other cardiovascular risk factors or other sleep disorders is unclear., Methods: We analysed data from 133,353 women without diabetes, cardiovascular disease and cancer at baseline in the Nurses' Health Study (NHS, 2000-2010) and the NHSII (2001-2011). Sleeping difficulty was assessed as having difficulty falling or staying asleep 'all of the time' or 'most of the time' at baseline (2000 in NHS and 2001 in NHSII)., Results: We documented 6,407 incident cases of type 2 diabetes during up to 10 years of follow-up. After adjustment for lifestyle factors at baseline, comparing women with and without sleeping difficulty, the multivariate-adjusted HR (95% CI) for type 2 diabetes was 1.45 (95% CI 1.33, 1.58), which changed to 1.22 (95% CI 1.12, 1.34) after further adjustment for hypertension, depression and BMI based on the updated repeated measurements. Women who reported all four sleep conditions (sleeping difficulty, frequent snoring, sleep duration ≤6 h and sleep apnoea in NHS or rotating shift work in NHSII) had more than a fourfold increased likelihood of type 2 diabetes (HR 4.17, 95% CI 2.93, 5.91)., Conclusions/interpretation: Sleeping difficulty was significantly associated with type 2 diabetes. This association was partially explained by associations with hypertension, BMI and depression symptoms, and was particularly strong when combined with other sleep disorders. Our findings highlight the importance of sleep disturbance in the development and prevention of type 2 diabetes., Competing Interests: the authors declare that there is no duality of interest associated with this manuscript. JWW has received research grant and lecture/other fees from NeuroMetrix (grant only), UCB and Xenoport and SR has received research grant from Jazz Pharmaceuticals. All have non conflict of interest with the current study.

Aims/hypothesis: Baseline sleep duration has a U-shaped relationship with type 2 diabetes, but little research examines the associated changes. We examined long-term changes in sleep duration and concomitant changes in diet, physical activity, weight and subsequent diabetes., Methods: The cohort includes 59,031 women aged 55-83 years in the Nurses' Health Study without diabetes in 2000. Change in sleep duration is the difference between self-reported 24 h sleep duration in 1986 and 2000. Diet, physical activity and covariates were updated every 2-4 years. Self-reported diabetes was confirmed via validated questionnaires. Cox regression models were adjusted for 1986 sleep duration and 1986 values of diabetes risk factors, including BMI, and subsequently for change in covariates from 1986 to 2000., Results: We documented 3,513 incident diabetes cases through to 2012. Compared with no change, decreases in sleep duration were adversely associated with changes in diet quality and physical activity, while increases were associated with greater weight gain. After adjustment for 1986 covariates, HRs (95% CI) for ≤ -2, > -2 to < 0, > 0 to < 2 and ≥ 2 h/day changes in sleep duration (vs no change) were 1.09 (0.93, 1.28), 1.10 (1.001, 1.12), 1.09 (1.00, 1.18) and 1.30 (1.14, 1.46), respectively. Additional adjustment for diet and physical activity did not appreciably alter the results. Increases in sleep duration ≥ 2 h/day remained adversely associated with diabetes (HR [95% CI]: 1.15 [1.01, 1.30]) after adjustment for change in covariates, including BMI., Conclusions/interpretation: Increases in sleep duration among middle-aged and older women were modestly associated with risk of diabetes; changes in diet, physical activity and BMI did not explain associations.

Aims/hypothesis: Women with a history of gestational diabetes mellitus (GDM) are advised to control their weight after pregnancy. We aimed to examine how adiposity and weight change influence the long-term risk of developing type 2 diabetes after GDM., Methods: We included 1,695 women who had incident GDM between 1991 and 2001, as part of the Diabetes & Women's Health study, and followed them until the return of the 2009 questionnaire. Body weight and incident type 2 diabetic cases were reported biennially. We defined baseline as the questionnaire period when women reported an incident GDM pregnancy. We estimated HRs and 95% CIs using Cox proportional hazards models., Results: We documented 259 incident cases of type 2 diabetes during up to 18 years of follow-up. The adjusted HRs of type 2 diabetes associated with each 1 kg/m(2) increase in BMI were 1.16 (95% CI 1.12, 1.19) for baseline BMI and 1.16 (95% CI 1.13, 1.20) for most recent BMI. Moreover, each 5 kg increment of weight gain after GDM development was associated with a 27% higher risk of type 2 diabetes (adjusted HR 1.27; 95% CI 1.04, 1.54). Jointly, women who had a BMI ≥30.0 kg/m(2) at baseline and gained ≥5 kg after GDM had an adjusted HR of 43.19 (95% CI 13.60, 137.11), compared with women who had a BMI <25.0 kg/m(2) at baseline and gained <5 kg after GDM., Conclusions/interpretation: Baseline BMI, most recent BMI and weight gain after GDM were significantly and positively associated with risk of progression from GDM to type 2 diabetes.

Aims/hypothesis: The association of single nucleotide polymorphisms (SNPs) proximal to CRY2 and MTNR1B with fasting glucose is well established. CRY1/2 and MTNR1B encode proteins that regulate circadian rhythmicity and influence energy metabolism. Here we tested whether season modified the relationship of these loci with blood glucose concentration., Methods: SNPs rs8192440 (CRY1), rs11605924 (CRY2) and rs10830963 (MTNR1B) were genotyped in a prospective cohort study from northern Sweden (n = 16,499). The number of hours of daylight exposure during the year ranged from 4.5 to 22 h daily. Owing to the non-linear distribution of daylight throughout the year, season was dichotomised based on the vernal and autumnal equinoxes. Effect modification was assessed using linear regression models fitted with a SNP × season interaction term, marginal effect terms and putative confounding variables, with fasting or 2 h glucose concentrations as outcomes., Results: The rs8192440 (CRY1) variant was only associated with fasting glucose among participants (n = 2,318) examined during the light season (β = -0.04 mmol/l per A allele, 95% CI -0.08, -0.01, p = 0.02, p interaction = 0.01). In addition to the established association with fasting glucose, the rs11605924 (CRY2) and rs10830963 (MTNR1B) loci were associated with 2 h glucose concentrations (β = 0.07 mmol/l per A allele, 95% CI 0.03, 0.12, p = 0.0008, n = 9,605, and β = -0.11 mmol/l per G allele, 95% CI -0.15, -0.06, p < 0.0001, n = 9,517, respectively), but only in participants examined during the dark season (p interaction = 0.006 and 0.04, respectively). Repeated measures analyses including data collected 10 years after baseline (n = 3,500) confirmed the results for the CRY1 locus (p interaction = 0.01)., Conclusions/interpretation: In summary, these observations suggest a biologically plausible season-dependent association between SNPs at CRY1, CRY2 and MTNR1B and glucose homeostasis.

Aims/hypothesis: We sought to evaluate the relationship between delayed conception and type 2 diabetes risk, given that there are plausible underlying mechanisms linking the two, including inflammation and insulin resistance., Methods: Participants of the Nurses' Health Study II prospective cohort were included if they were free of chronic disease (cardiovascular disease, type 2 diabetes, cancer) at baseline. Biennial questionnaires updated information on infertility status (>12 months attempted pregnancy), lifestyle characteristics and several health-related outcomes. Self-reported cases of diabetes were confirmed using a follow-up questionnaire. Multivariable Cox proportional hazards models were used to compute the HRs and 95% CIs., Results: Incident type 2 diabetes occurred in 5,993 of the 112,106 participants over 24 years of follow-up (1989-2013). A history of infertility was reported in 27,774 (24.8%) women and was associated with a 20% greater risk of developing diabetes, compared with those never reporting infertility (HR 1.20 [95% CI 1.14, 1.28]), after adjusting for age, lifestyle factors, marital status, oral contraceptive use, family history of diabetes and BMI. Compared with women without a history of infertility, the causes of infertility associated with a higher diabetes risk were ovulation disorders (HR 1.43 [95% CI 1.29, 1.58]) and tubal factor (HR 1.34 [95% CI 1.13, 1.58]). Cervical factor (HR 1.06 [95% CI 0.81, 1.40]) and endometriosis (HR 1.06 [95% CI 0.89, 1.27]) were not associated, while male factor infertility was associated with a modestly higher diabetes risk (HR 1.15 [95% CI 1.00, 1.33])., Conclusions/interpretation: These novel findings suggest a history of infertility, particularly that related to ovulation disorders and tubal blockage, is significantly associated with a higher risk of type 2 diabetes.

Aims/hypothesis: Although microbiota-derived endotoxaemia has previously been shown to induce metabolic disorders, data from population-based longitudinal studies are scarce. This study therefore investigated the associations between lipopolysaccharide binding protein (LBP) levels and 6 year incident metabolic syndrome (MetS), as well as the potentially modifying effects of obesity status in middle-aged and older Chinese men and women., Methods: A total of 2,529 men and women aged 50-70 years from Beijing and Shanghai, China, were followed for 6 years. Those free of MetS at baseline (1,312) were included in the analyses for the risk of developing MetS. Baseline plasma LBP was measured using an ELISA kit., Results: During the 6 year follow-up, 449 (34.2%) participants developed MetS. Baseline LBP was significantly associated with BMI, waist circumference, blood lipid profile and C-reactive protein (CRP) both at baseline and during follow-up (all p < 0.05). The RR for incident MetS comparing extreme quartiles of LBP was 1.28 (95% CI 1.04, 1.58), after multivariate adjustment including BMI and CRP. In stratified analysis, LBP was positively associated with incident MetS only in normal-weight participants (RR, comparing extreme tertiles, 1.59; 95% CI 1.18, 2.15; p(trend)= 0.002), but not in their overweight/obese counterparts (RR, comparing extreme tertiles, 0.99; 95% CI 0.80, 1.22; p(trend) = 0.880). A significant interaction was observed between LBP and obesity status (p(interaction) = 0.013)., Conclusions/interpretation: Our study suggested that elevated plasma LBP was associated with an increased risk of developing MetS among middle-aged and older Chinese, especially in normal-weight individuals.

Aims/hypothesis: Coffee and tea consumption has been associated with a lower type 2 diabetes risk but little is known about how changes in coffee and tea consumption influence subsequent type 2 diabetes risk. We examined the associations between 4 year changes in coffee and tea consumption and risk of type 2 diabetes in the subsequent 4 years., Methods: We prospectively followed 48,464 women in the Nurses' Health Study (NHS; 1986-2006), 47,510 women in NHS II (1991-2007) and 27,759 men in the Health Professionals Follow-up Study (HPFS; 1986-2006). Diet was assessed every 4 years using a validated food-frequency questionnaire. Self-reported cases of incident type 2 diabetes were validated by supplementary questionnaires., Results: During 1,663,319 person-years of follow-up, we documented 7,269 cases of incident type 2 diabetes. Participants who increased their coffee consumption by more than 1 cup/day (median change = 1.69 cups/day) over a 4 year period had an 11% (95% CI 3%, 18%) lower risk of type 2 diabetes in the subsequent 4 years compared with those who made no changes in consumption. Participants who decreased their coffee intake by more than 1 cup/day (median change = -2 cups/day) had a 17% (95% CI 8%, 26%) higher risk for type 2 diabetes. Changes in tea consumption were not associated with type 2 diabetes risk., Conclusions/interpretation: Our data provide novel evidence that increasing coffee consumption over a 4 year period is associated with a lower risk of type 2 diabetes, while decreasing coffee consumption is associated with a higher risk of type 2 diabetes in subsequent years.

Aims/hypothesis: The benefits of moderate alcohol consumption for type 2 diabetes have been postulated to involve a mechanism of improved insulin sensitivity. Fetuin-A, which is known to inhibit insulin signalling, has emerged as a biomarker for diabetes risk. Alcohol consumption may influence circulating fetuin-A concentrations and subsequently diabetes risk by altering the insulin signal. We therefore hypothesised that moderate alcohol consumption would be associated with lower fetuin-A concentration and that fetuin-A would partly explain the association between alcohol consumption and incident type 2 diabetes., Methods: Among diabetes-free female participants in the Nurses' Health Study (n = 1,331), multiple linear regression was conducted to assess the association between alcohol consumption and plasma fetuin-A. Least-squares means (lsmeans) of fetuin-A were estimated in categories of alcohol consumption (0, 0.1-4.9, 5-14.9 and ≥ 15 g/day). The proportion of alcohol consumption and diabetes association explained by baseline fetuin-A was assessed in 470 matched incident diabetes case-control pairs with follow-up 2000-2006., Results: Higher alcohol consumption was associated with lower plasma fetuin-A (p for trend = 0.009): lsmean ± SE 476.5 ± 5.9 μg/ml for abstainers, 468.9 ± 5.2 μg/ml for 0.1-4.9 g/day consumers, 455.9 ± 7.0 μg/ml for 5.0-14.9 g/day consumers, and 450.0 ± 9.4 μg/ml for ≥ 15.0 g/day consumers. Fetuin-A and fasting insulin explained 18.4% and 54.8%, respectively, of the inverse association between alcohol consumption and diabetes after multiple adjustment (both p for contribution <0.04)., Conclusions/interpretation: Moderate alcohol consumption is associated with lower plasma fetuin-A in diabetes-free women. Fetuin-A and insulin explain a significant proportion of the association between alcohol consumption and incident type 2 diabetes. Further studies are needed to examine potential biological mechanisms underlying this association.

Aims/hypothesis: Few data are available about intakes and food sources of trans-fatty acids (TFAs) or their associations with cardiometabolic outcomes in Asian people who consume a prudent diet but are experiencing rapid nutritional transitions. We aimed to investigate the relationships between TFA biomarkers and type 2 diabetes and cardiovascular risk factors in Chinese individuals., Methods: Erythrocyte fatty acids were measured by gas chromatography among 3,107 men and women (50-70 years) recruited from urban and rural areas in Beijing and Shanghai, China., Results: Total trans-18:1 and two trans-18:2 isomers were detected and accounted for 0.37% of the total fatty acids in the erythrocytes. Concentrations of TFAs were higher in women than men, and in urban than rural residents. Of the TFAs, trans-18:1, but not trans-18:2, showed a modest association with dairy consumption (β = 0.27), but not with other foods. After adjustment for BMI, social-demographic, lifestyle and dietary factors and other TFAs, erythrocyte trans-18:1 was shown to be associated with a lower risk of type 2 diabetes (OR comparing extreme [first and fourth] quartiles 0.68, 95% CI 0.48, 0.97, p(trend) = 0.02), as well as 20-50% lower odds of central obesity, dyslipidaemia, hyperglycaemia, insulin resistance and chronic inflammation. In contrast, trans-18:2 fatty acids were positively associated with high triacylglycerol (p(trend) < 0.001) and LDL-cholesterol (p(trend) = 0.03) levels, but not with diabetes and other cardiometabolic risk factors., Conclusions/interpretation: Among middle-aged and older Chinese individuals with overall low erythrocyte TFAs levels, trans-18:1 might serve as a marker of dairy intake. Higher trans-18:1 levels were associated with a lower risk of type 2 diabetes, whereas higher trans-18:2 levels were associated with dyslipidaemia.

Aims/hypothesis: The results of several studies have suggested a potential positive association between use of antidepressant medication (ADM) and incident type 2 diabetes mellitus. We examined this association in three cohorts of US adults., Methods: We followed 29,776 men in the Health Professionals Follow-up Study (HPFS, 1990-2006), 61,791 women in the Nurses' Health Study I (NHS I, 1996-2008) and 76,868 women in NHS II (1993-2005), who were free of diabetes mellitus, cardiovascular disease or cancer at baseline. The mean baseline ages for participants from the HPFS and NHS I and II were 56.4, 61.3 and 38.1 years, respectively. ADM use and other covariates were assessed at baseline and updated every 2 years. A time-dependent Cox proportional hazards model was used, and HRs were pooled together across the three cohorts., Results: During 1,644,679 person-years of follow-up, we documented 6,641 new cases of type 2 diabetes. ADM use was associated with an increased risk of diabetes in all three cohorts in age-adjusted models (pooled HR 1.68 [95% CI 1.27, 2.23]). The association was attenuated after adjustment for diabetes risk factors and histories of high cholesterol and hypertension (1.30 [1.14, 1.49]), and further attenuated by controlling for updated BMI (1.17 [1.09, 1.25]). Use of selective serotonin reuptake inhibitors and other antidepressants (mainly tricyclic antidepressants) were both associated with an elevated risk of diabetes, with pooled multivariate-adjusted HRs of 1.10 (1.00, 1.22) and 1.26 (1.11, 1.42), respectively., Conclusions/interpretation: The results suggest that ADM users had a moderately elevated risk of type 2 diabetes mellitus compared with non-users, even after adjustment for BMI.

Aims/hypothesis: The recent advent of genome-wide association studies has considerably accelerated the identification of type 2 diabetes loci. We aimed to investigate the combined effects of multiple genetic variants, alone or in combination with conventional risk factors, on type 2 diabetes and diabetes-related traits in Han Chinese., Methods: We genotyped 17 variants in 17 loci in a population-based Han Chinese cohort including 3,210 unrelated individuals. A genetic risk score (GRS) was calculated on the basis of these variants. The discriminatory ability was assessed by the area under the receiver operating characteristics curve., Results: The odds ratio for type 2 diabetes and hyperglycaemia with each GRS point (per risk allele) was 1.18 (95% CI 1.12-1.23, p = 1.3 x 10(-12)) and 1.12 (95% CI 1.09-1.16, p = 7.5 x 10(-14)), respectively. Compared with participants with GRS < or =11.0 (7.63%), those with GRS > or =19.0 (8.87%) had a 4.58-fold higher risk (95% CI 2.49-8.42) of type 2 diabetes. The GRS also showed a significant association with lower beta cell function estimated by HOMA of beta cell function (p = 8.4 x 10(-10)). In addition, we observed significant interactive effects between GRS and BMI on fasting glucose and HbA(1c) levels (p = 0.04 and p = 0.03 for interaction, respectively). Discrimination of diabetes risk was improved (p < 0.001) when the GRS was added to a model including clinical risk factors. The AUCs were 0.62 and 0.77, respectively, for the GRS and conventional clinic risk factors alone, and 0.79 when the GRS was added., Conclusions/interpretation: In this Han Chinese population, the GRS of 17 combined variants modestly but significantly improved discrimination of the conventional risk factors for type 2 diabetes.

Aims/hypothesis: We prospectively determined the risk of gestational diabetes mellitus in association with life-course weight characteristics and adult abdominal adiposity., Methods: We investigated the joint and independent impact of birthweight, childhood size by somatotypes, adolescent and adult BMI, and abdominal adiposity on gestational diabetes mellitus risk among the 21,647 women in the Nurses' Health Study II who reported a singleton pregnancy between 1989 and 2001. A total of 1,386 incident cases of gestational diabetes mellitus were reported. Relative risk was estimated by pooled logistic regression adjusting for age, prematurity, race, smoking status, parental history of diabetes, age of first birth, parity and physical activity., Results: Birthweight was inversely associated with gestational diabetes mellitus risk (p = 0.02 for trend). Childhood somatotypes at ages 5 and 10 years were not associated with risk. U-shaped associations were found for BMI at age 18 years and somatotype at age 20 years. Weight gain between adolescence and adulthood, pre-gravid BMI and abdominal adiposity were positively associated with risk (p < 0.01 for all trends). Multivariate adjusted RRs for gestational diabetes from lowest to highest quintile of WHR were 1.00, 1.50, 1.51, 2.03, 2.12 (p = 0.0003 for trend). Lower birthweight (<7 lb) without adulthood overweight (BMI > 25 kg/m(2)) was associated with a 20% increased risk (95% CI 1.02-1.41). However, adulthood overweight alone was related to a 2.36 times greater risk (95% CI 2.12-3.77)., Conclusions/interpretation: Although lower birthweight is an independent risk factor for gestational diabetes mellitus, weight gain since early adulthood, and overall and central obesity in adulthood were more strongly associated with elevated risk of the condition independently of other known risk factors.

Aims/hypothesis: Potentially modifiable biomarkers may influence the decline in estimated GFR (eGFR), but few data are currently available in type 2 diabetic adults., Methods: We studied 516 women with type 2 diabetes in the Nurses' Health Study with data on lipid and inflammatory biomarkers from plasma collected in 1989 and plasma creatinine in samples collected in 1989 and 2000. An estimated GFR decline of >or=25% over 11 years was the outcome of interest., Results: Comparing the highest with the lowest quartile, soluble tumour necrosis factor receptor 2 (sTNFR-2) was independently associated with an eGFR decline of >or=25% (multivariate OR 5.81; 95% CI 2.90-11.65); this association was stronger in obese women (OR 16.76; 95% CI 4.69-59.90 for BMI >or=30 kg/m(2); OR 2.78, 95% CI 1.12-6.89 for BMI <30 kg/m(2); p for interaction = 0.02). No lipids (total cholesterol, LDL-cholesterol, HDL-cholesterol, non-HDL-cholesterol, triacylglycerols, lipoprotein(a), or apolipoprotein B) or other markers of inflammation (C-reactive protein, fibrinogen, E-selectin, intracellular cell adhesion molecule 1, leptin or adiponectin) were significantly associated with eGFR decline after multivariable adjustment., Conclusions/interpretation: Elevated sTNFR-2 levels may be an important and potentially modifiable risk factor for eGFR decline in type 2 diabetes, especially in those with a BMI of >or=30 kg/m(2).

Aims/hypothesis: The pathophysiology of type 2 diabetes involves pro-inflammatory pathways. We tested the hypothesis that IL-18 predicts future diabetes cases., Methods: We used a nested case-control design based in the Nurses' Health Study. Baseline blood samples were collected between 1989 and 1990. Questionnaires to assess body weight, lifestyle (physical activity, diet, smoking) and diabetes diagnosis were sent out and assessed biennially (follow-up until 2002). Cases (n = 1,012) were defined as women developing type 2 diabetes at least 1 year after blood sampling. Control women (n = 1,081) were matched to cases by age, date of blood draw, fasting status and race. We calculated the RR (95% CI) of type 2 diabetes in quintiles of IL-18 using conditional logistic regression with the first quintile as referent; adjustments included matching factors, diabetes risk factors, BMI, adipokine levels (adiponectin, resistin) and inflammatory proteins (C-reactive protein, tumour necrosis factor receptor 2 (TNFalpha-R2) and IL-6)., Results: Higher IL-18 levels were associated with increased risk of developing diabetes, even after adjustment for matching factors and multiple diabetes risk factors: being in the highest quintile of IL-18 was associated with a RR of 1.75 (1.41-2.18) for diabetes relative to the first quintile (p < 0.0001 for trend). Significant trends in association were still observed after adjustment for BMI (RR 1.44 [1.15-1.80], p < 0.0001 for trend) and adiponectin levels (RR 1.28 [1.02-1.60], p = 0.006 for trend). Further adjustment for inflammatory markers in a sub-sample did not significantly change the results., Conclusions/interpretation: Elevated IL-18 levels are associated with higher risk of diabetes. This association is independent of usual risk factors, including BMI and adipokine levels.

Aims/hypothesis: The GCKR rs780094 and GCK rs1799884 polymorphisms have been reported to be associated with dyslipidaemia and type 2 diabetes in white Europeans. The aim of this study was to replicate these associations in Han Chinese individuals and to identify the potential mechanisms underlying these associations., Methods: The single nucleotide polymorphisms rs780094 and rs1799884 were genotyped in a population-based sample of Han Chinese individuals (n = 3,210) and tested for association with risk of type 2 diabetes and related phenotypes., Results: The GCKR rs780094 A allele was marginally associated with reduced risk of type 2 diabetes (OR 0.85, 95% CI 0.73-1.00, p value under an additive model [p((add))] = 0.05) and significantly associated with reduced risk of impaired fasting glucose (IFG) or type 2 diabetes (OR 0.86, 95% CI 0.77-0.96, p([add]) = 0.0032). It was also significantly associated with decreased fasting glucose and increased HOMA of beta cell function (HOMA-B) and fasting triacylglycerol levels (p([add]) = 0.0169-5.3 x 10(-6)), but not with HOMA of insulin sensitivity (HOMA-S). The associations with type 2 diabetes and IFG remained significant after adjustment for BMI, while adjustment for HOMA-B abolished the associations. The GCKR rs780094 was also associated with obesity and BMI, independently of its association with type 2 diabetes. The GCK rs1799884 A allele was significantly associated with decreased HOMA-B (p([add]) = 0.0005), but not with type 2 diabetes or IFG. Individuals with increasing numbers of risk alleles for both variants had significantly lower HOMA-B (p([add]) = 5.8 x 10(-5)) in the combined analysis., Conclusions/interpretation: Consistent with observations in white Europeans, the GCKR rs780094 polymorphism contributes to the risk of type 2 diabetes and dyslipidaemia in Han Chinese individuals. In addition, we showed that the effect on type 2 diabetes is probably mediated through impaired beta cell function rather than through obesity.

Aims/hypothesis: Coffee has been linked to both beneficial and harmful health effects, but data on its relationship with cardiovascular disease and mortality in patients with type 2 diabetes are sparse., Methods: This was a prospective cohort study including 7,170 women with diagnosed type 2 diabetes but free of cardiovascular disease or cancer at baseline. Coffee consumption was assessed in 1980 and then every 2-4 years using validated questionnaires. A total of 658 incident cardiovascular events (434 coronary heart disease and 224 stroke) and 734 deaths from all causes were documented between 1980 and 2004., Results: After adjustment for age, smoking and other cardiovascular risk factors, the relative risks were 0.76 (95% CI 0.50-1.14) for cardiovascular diseases (p trend = 0.09) and 0.80 (95% CI 0.55-1.14) for all-cause mortality (p trend = 0.05) for the consumption of >or=4 cups/day of caffeinated coffee compared with non-drinkers. Similarly, multivariable RRs were 0.96 (95% CI 0.66-1.38) for cardiovascular diseases (p trend = 0.84) and 0.76 (95% CI 0.54-1.07) for all-cause mortality (p trend = 0.08) for the consumption of >or=2 cups/day of decaffeinated coffee compared with non-drinkers. Higher decaffeinated coffee consumption was associated with lower concentrations of HbA(1c) (6.2% for >or=2 cups/day versus 6.7% for <1 cup/month; p trend = 0.02)., Conclusions: These data provide evidence that habitual coffee consumption is not associated with increased risk of cardiovascular diseases or premature mortality among diabetic women.

Aims/hypothesis: A range of prediction rules for the onset of type 2 diabetes have been proposed. However, most studies have been conducted in white groups and it is not clear whether these models apply to Asian populations. The purpose of this study was to construct a simple points model for predicting incident diabetes among Chinese people., Methods: We estimated the 10 year risk of diabetes in a cohort study of middle-aged and elderly participants who were free from diabetes at baseline. Cox regression coefficients were used to construct the simple points model and the discriminatory ability of the resulting prediction rule was determined using AUC and net reclassification improvement and integrated discrimination improvement statistics. Fivefold random splitting was used to test the internal validity and obtain bootstrap estimates of the AUC., Results: Of the 2,960 participants without diabetes at the baseline examination, 548 developed type 2 diabetes during a median 10 year follow-up period. Age (four points), elevated fasting glucose (11 points), body mass index (eight points), triacylglycerol (five points), white blood cell count (four points) and a higher HDL-cholesterol (negative four points) were found to strongly predict diabetes incidence in a multivariate model. The estimated AUC for the model was 0.702 (95% CI 0.676-0.727). This model performed better than existing prediction models developed in other populations, including the Prospective Cardiovascular Münster, Cambridge, San Antonia and Framingham models for diabetes risk., Conclusions/interpretation: We have constructed a model for predicting the 10 year incidence of diabetes in Chinese people that could be useful for identifying individuals at high risk of diabetes in the Chinese population.

Aims/hypothesis: Leptin, an adipocyte-secreted hormone, plays an important role in regulating neuroendocrine and immune function as well as insulin resistance and metabolism. Our objective was to examine the relationship between leptin levels and cardiovascular morbidity and overall mortality in women with type 2 diabetes., Subjects and Methods: This prospective cohort study included 1,194 women with a confirmed diagnosis of type 2 diabetes, who provided a blood sample at baseline in 1989-1990. Participants were followed for 12 years for the development of health outcomes including cardiovascular disease (CVD) events as well as total mortality., Results: There were 218 new CVD events and 228 deaths from all causes. Cox proportional hazards analysis was used to estimate the relative risks (RRs) for each quintile level of leptin compared with the lowest quintile. Leptin levels were positively associated with several CVD risk factors including BMI and inflammatory markers, but were not independently associated with the incidence of CVD or total mortality in women with diabetes. The multivariate RRs (95% CIs) for CVD across the quintiles of leptin were 0.96 (0.61-1.53), 0.99 (0.61-1.61), 1.04 (0.63-1.71), 1.02 (0.59-1.75) (p for trend = 0.83)., Conclusions/interpretation: Although circulating leptin levels are associated with obesity and inflammatory markers, they are not significantly related to the risk of CVD or mortality in women with diabetes.

Aims/hypothesis: The aim of this study was to prospectively examine whether dietary patterns are related to risk of gestational diabetes mellitus (GDM)., Methods: This prospective cohort study included 13,110 women who were free of cardiovascular disease, cancer, type 2 diabetes and history of GDM. Subjects completed a validated semi-quantitative food frequency questionnaire in 1991, and reported at least one singleton pregnancy between 1992 and 1998 in the Nurses' Health Study II. Two major dietary patterns (i.e. 'prudent' and 'Western') were identified through factor analysis. The prudent pattern was characterised by a high intake of fruit, green leafy vegetables, poultry and fish, whereas the Western pattern was characterised by high intake of red meat, processed meat, refined grain products, sweets, French fries and pizza., Results: We documented 758 incident cases of GDM. After adjustment for age, parity, pre-pregnancy BMI and other covariates, the relative risk (RR) of GDM, comparing the highest with the lowest quintile of the Western pattern scores, was 1.63 (95% CI 1.20-2.21; p (trend)=0.001), whereas the RR comparing the lowest with the highest quintile of the prudent pattern scores was 1.39 (95% CI 1.08-1.80; p (trend)=0.018). The RR for each increment of one serving/day was 1.61 (95% CI 1.25-2.07) for red meat and 1.64 (95% CI 1.13-2.38) for processed meat., Conclusions/interpretation: These findings suggest that pre-pregnancy dietary patterns may affect women's risk of developing GDM. A diet high in red and processed meat was associated with a significantly elevated risk.

Aims/hypothesis: The -514 C to T polymorphism of the hepatic lipase gene (LIPC) has been associated with lowered LIPC activity and elevated HDL-cholesterol concentrations. Previous findings on the association of this polymorphism with the risk of CHD are inconsistent. Moreover, data on this association among diabetic patients are limited. We investigated the association of the LIPC polymorphism with CHD risk among US diabetic men and evaluated whether this association was modified by adiposity status., Subjects and Methods: The case group consisted of 220 diabetic men who were recruited from the Health Professionals Follow-up Study (years 1986-2000) and were free of cardiovascular disease at baseline, but subsequently developed CHD. A total of 641 diabetic men from the same study but without cardiovascular disease constituted the control group., Results: No overall association between the LIPC polymorphism and CHD risk was observed. However, we did observe a significant interaction between this polymorphism and BMI in association with CHD risk. Among obese men, after adjustment for age, duration of diabetes and major lifestyle factors, the CT or TT genotype was associated with an increased CHD risk compared with the CC genotype (odds ratio [OR] 2.52, 95% CI 1.08-5.90); the corresponding ORs (95% CI) were 0.99 (0.58, 1.69) for overweight men (25< or =BMI <30 kg/m(2)) and 0.37 (0.17, 0.79) for lean men (BMI <25 kg/m(2)) (p for interaction 0.001). Stratified analyses by waist circumference (tertiles) showed a similar pattern of interaction (adjusted p for interaction 0.023)., Conclusion/interpretation: These data suggest that obesity may modify the association between the LIPC C(-514)T polymorphism and CHD risk among diabetic men.

Aims: We examined the association between lipoprotein (Lp)(a) and CHD among women with type 2 diabetes., Methods: Of 32,826 women from the Nurses' Health Study who provided blood at baseline, we followed 921 who had a confirmed diagnosis of type 2 diabetes., Results: During 10 years of follow-up (6,835 person-years), we documented 122 incident cases of CHD. After adjustment for age, smoking, BMI, glycosylated HbA(1)c, triglycerides (TGs), high-density lipoprotein cholesterol, low-density lipoprotein cholesterol and other cardiovascular risk factors, the relative risk (RR) comparing extreme quintiles of Lp(a) was 1.95 (95% CI 1.07-3.56). The association was not appreciably altered after further adjustment for apolipoprotein B(100) or several inflammatory biomarkers. Increasing levels of Lp(a) were associated with lower levels of TGs. The probability of developing CHD over 10 years was higher among diabetic women with substantially higher levels of both Lp(a) (>1.07 micromol/l) and TGs (>2.26 mmol/l) than among diabetic women with lower levels (22 vs 10%, p log-rank test=0.049). Diabetic women with a higher level of only Lp(a) or TGs had a similar (14%) risk. In a multivariate model, diabetic women with higher levels of Lp(a) and TGs had an RR of 2.46 (95% CI 1.21-5.01) for developing CHD, as compared with those with lower levels of both biomarkers (p for interaction=0.413). The RRs for women with a higher level of either Lp(a) (RR=1.22, 95% CI 0.77-1.92) or TGs (RR=1.39, 95% CI 0.78-2.42) were comparable., Conclusions/interpretation: Increased levels of Lp(a) were independently associated with risk of CHD among diabetic women.

Aims/hypothesis: Non-HDL cholesterol (the sum of LDL, VLDL and IDL cholesterol) is considered to be particularly valuable in the management of dyslipidaemia in type 2 diabetes. However, it remains uncertain whether the association between non-HDL cholesterol and cardiovascular risk in type 2 diabetes depends on the status of hyperglycaemia. We aimed to determine whether non-HDL cholesterol predicts CHD events among diabetic women independently of currently established risk factors and the status of glycaemic control., Methods: We prospectively followed 921 diabetic women in the Nurses' Health Study, who were free of cardiovascular disease at the time that blood was drawn in 1989/90. During 10 years of follow-up, we identified 122 incident CHD cases., Results: After adjustment for age, BMI, smoking, alcohol consumption, and other lifestyle risk factors, the multivariate relative risks (RRs) of CHD for extreme quartiles were 1.97 (95% CI: 1.14-3.43) for non-HDL cholesterol, 1.78 (1.02-3.11) for apolipoprotein B-100, and 1.93 (1.15-3.22) for LDL cholesterol. However, the association between non-HDL cholesterol and CHD risk was only apparent among women with elevated fasting triglycerides (RR for extreme quartiles: 3.80; p=0.045). HbA(1)c was strongly associated with increased CHD risk (RR for increase by 1 unit: 1.24; 95% CI: 1.13-1.35), and both non-HDL cholesterol and HbA(1)c additively predicted CHD risk (RR for the combination of high non-HDL cholesterol and high HbA(1)c [tertiles]: 4.59)., Conclusions/interpretation: Our study suggests that non-HDL cholesterol and HbA(1)c are potent predictors of CHD risk in diabetic women. Therapies to lower CHD risk in diabetic patients should emphasise both glycaemic control and lipid lowering.

Aims/hypothesis: Type 2 diabetes mellitus is characterised by heightened inflammation and endothelial dysfunction. Moderate alcohol intake has been associated with a reduced risk of cardiovascular disease in type 2 diabetic patients. It remains to be determined whether there is an association between alcohol and inflammation in individuals with diabetes., Methods: We investigated the relationship between alcohol intake and inflammation in 726 of 18,159 men who returned blood samples in the Health Professionals Follow-up Study and had confirmed type 2 diabetes at blood draw., Results: In age-adjusted analyses, alcohol intake was associated with lower levels of HbA1c, fibrinogen, soluble tumour necrosis factor receptor-2 (sTNF-R2) and soluble vascular adhesion molecule-1 (sVCAM-1), and with higher levels of HDL cholesterol and adiponectin (p value for trends <0.05). After adjustment for age, HbA1c, insulin use, fasting status, smoking, BMI, physical activity, aspirin use, prevalence of cardiovascular disease and dietary factors, each additional drink per day was related to increased HDL cholesterol (0.053 mmol/l, p<0.0001) and adiponectin (0.8 microg/ml, p=0.01), and decreased sTNFR-2 (73 pg/ml, p=0.03), fibrinogen (0.302 micromol/l, p=0.02) and sVCAM-1 (33 ng/ml, p=0.02). The relationship between alcohol and inflammatory biomarkers persisted when subjects were stratified according to HbA1c levels., Conclusions/interpretation: Moderate alcohol intake may have a beneficial effect on markers of inflammation and endothelial dysfunction in type 2 diabetic patients.

Aim/hypothesis: The aim of this study was to investigate the association between processed and other meat intake and incidence of Type 2 diabetes in a large cohort of women., Methods: Incident cases of Type 2 diabetes were identified during 8 years of follow-up in a prospective cohort study of 91246 U.S. women aged 26 to 46 years and being free of diabetes and other major chronic diseases at baseline in 1991., Results: We identified 741 incident cases of confirmed Type 2 diabetes during 716276 person-years of follow-up. The relative risk adjusted for potential non-dietary confounders was 1.91 (95% CI: 1.42-2.57) in women consuming processed meat five times or more a week compared with those consuming processed meat less than once a week ( p<0.001 for trend). Further adjustment for intakes of magnesium, cereal fibre, glycaemic index, and caffeine or for a Western dietary pattern did not appreciably change the results and associations remained strong after further adjustment for fatty acid and cholesterol intake. Frequent consumption of bacon, hot dogs, and sausage was each associated with an increased risk of diabetes. While total red meat (beef or lamb as main dish, pork as main dish, hamburger, beef, pork or lamb as sandwich or mixed dish) intake was associated with an increased risk of diabetes, this association was attenuated after adjustment for magnesium, cereal fiber, glycaemic index, and caffeine (relative risk: 1.44; 95% CI: 0.92-2.24)., Conclusion/interpretation: Our data suggest that diets high in processed meats could increase the risk for developing Type 2 diabetes.

Although diet and nutrition are widely believed to play an important part in the development of Type II (non-insulin-dependent) diabetes mellitus, specific dietary factors have not been clearly defined. Much controversy exists about the relations between the amount and types of dietary fat and carbohydrate and the risk of diabetes. In this article, we review in detail the current evidence regarding the associations between different types of fats and carbohydrates and insulin resistance and Type II diabetes. Our findings indicate that a higher intake of polyunsaturated fat and possibly long-chain n-3 fatty acids could be beneficial, whereas a higher intake of saturated fat and trans-fat could adversely affect glucose metabolism and insulin resistance. In dietary practice, exchanging nonhydrogenated polyunsaturated fat for saturated and trans-fatty acids could appreciably reduce risk of Type II diabetes. In addition, a low-glycaemic index diet with a higher amount of fiber and minimally processed whole grain products reduces glycaemic and insulinaemic responses and lowers the risk of Type II diabetes. Dietary recommendations to prevent Type II diabetes should focus more on the quality of fat and carbohydrate in the diet than quantity alone, in addition to balancing total energy intake with expenditure to avoid overweight and obesity.