Cumulative exposure to impaired fasting glucose and future risk of type 2 diabetes mellitus

Unraveling the pesticide-diabetes connection: A case-cohort study integrating Mendelian randomization analysis with a focus on physical activity's mitigating effect

BACKGROUND AND AIMS

There is no evidence on the longitudinal and causal associations between multiple pesticides and the incidence of type 2 diabetes mellitus (T2DM) in the Chinese rural population, and whether physical activity (PA) modified these associations remains unclear. Here, we aimed to investigate the longitudinal and causal associations between pesticides mixture and T2DM, and determine whether PA modified these associations.

METHODS

A total of 925 subjects with normal glucose and 925 subjects with impaired fasting glucose (IFG) were enrolled in this case-cohort study. A total of 51 targeted pesticides were quantified at baseline. Logistic regression, quantile g-computation, and Bayesian kernel machine regression (BKMR) were used to assess the individual and combined effects of pesticides on IFG and T2DM. Mendelian randomization (MR) analysis was employed to obtain the causal association between pesticides and T2DM.

RESULTS

After 3-year follow-up, one-unit increment in ln-isofenphos, ln-malathion, and ln-deltamethrin were associated with an increase conversion of IFG to T2DM (FDR-P<0.05). One quartile increment in organochlorine pesticides (OCPs), organophosphorus pesticides (OPs), herbicides and pyrethroids mixtures were related to a higher incidence of T2DM among IFG patients (P<0.05). The BKMR results showed a positive trend between exposure to pesticides mixture and T2DM. The MR analysis indicated a positive association between exposure to pesticides and T2DM risk (P<0.05). No any significant association was found between pesticides and IFG. In addition, compared to subjects with high levels of PA, those with low levels of PA were related to increased risk of T2DM with the increased levels of pesticides among IFG patients.

CONCLUSIONS

Individual and combined exposure to pesticides increased the incidence of T2DM among IFG patients. MR analysis further supported the causal association of pesticides exposure with T2DM risk. Our study furtherly indicated that high levels of PA attenuated the diabetogenic effect of pesticides exposure.

Triglyceride-glucose index is associated with the risk of impaired fasting glucose in Chinese elderly individuals

The association between the triglyceride-glucose (TyG) index and impaired fasting glucose (IFG) in elderly individuals remains uncertain. Our study aimed to explore the association between the TyG index and the risk of future IFG in this population. This retrospective cohort study included 17,746 elderly individuals over 60. In this population, Cox regression models proportional to hazards, along with smooth curve fitting and cubic spline functions, were employed to examine the association between the baseline TyG index and the risk of IFG. Subgroup analyses and sensitivity were also performed to ensure the robustness of the study findings. After adjusting for covariates, a positive association between the TyG index and the risk of IFG was found (HR = 1.43, 95% CI 1.27-1.60, P < 0.0001). The likelihood of IFG rose steadily as the TyG index quartiles (from Q1 to Q4) increased, with Q4 demonstrating a 62% elevated risk compared to Q1 (adjusted HR = 1.62, 95% CI 1.37-1.90). Additionally, we found the association between TyG index and risk of IFG was a linear. Sensitivity and subgroup analyses confirmed the stability of the results. Our study observed a linear association between the TyG index and the development of IFG in elderly Chinese individuals. Recognizing this association can help clinicians identify high-risk individuals and implement targeted interventions to reduce their risk of progressing to diabetes.

Long-term impact of type 2 diabetes onset on dementia incidence rate among New Zealanders with impaired glucose tolerance: A tapered-matched landmark analysis over 25 years

INTRODUCTION

We aimed to investigate the association between the onset of type 2 diabetes (T2D) and dementia incidence rates (IR) in the population with impaired glucose tolerance (IGT) identified in primary care in New Zealand (NZ) over 25 years.

METHODS

Tapered matching and landmark analysis (accounting for immortal bias) were used to control for potential effects of known confounders. The association between T2D onset and 5- and 10-year IR of dementia was estimated by weighted Cox models.

RESULTS

The onset of T2D was significantly associated with the 10-year IR of dementia, especially in the socioeconomically deprived, those of non-NZ European ethnicity, those currently smoking, and patients with higher metabolic measures.

DISCUSSION

Our findings suggest that the onset of T2D is a significant risk factor for dementia in individuals with IGT. Dementia screening and structured diabetes prevention are vital in the population with IGT, particularly those from deprived or ethnic minority backgrounds.

HIGHLIGHTS

Increased dementia incidence rate links with T2D onset in people with IGT. Significant incidence varied by ethnicity, socioeconomic status, and health factors. Results emphasize the diabetes manage and socioeconomic factors on dementia risk. Secondary analysis highlights the key role of vascular health in dementia prevention.

Cumulative exposure to impaired fasting glucose and gastrointestinal cancer risk: A nationwide cohort study

BACKGROUND

Impaired fasting glucose (IFG) is associated with the risk of various cancers, but the cumulative effect of IFG on gastrointestinal cancer risk remains unclear. This study evaluated the association between the cumulative exposure to IFG and gastrointestinal cancer risk.

METHODS

The authors extracted data from the Korean National Health Insurance Service and health examination data sets. Among individuals ≥40 years old who were free of diabetes or cancer, 1,430,054 who underwent national health examinations over 4 consecutive years from 2009 to 2012 were selected and followed up until gastrointestinal cancer diagnosis, death, or December 31, 2019. The IFG exposure score (range, 0-4) was based on the number of IFG diagnoses over 4 years.

RESULTS

The median follow-up duration was 6.4 years. Consistent normoglycemia for 4 years was found in 44.3% of the population, whereas 5.0% had persistent IFG and 50.7% had intermittent IFG. Compared to the group with an IFG exposure score of 0, groups with IFG exposure scores of 1, 2, 3, and 4 had a 5%, 8%, 9%, and 12% increased risk of gastrointestinal cancer, respectively (score 1: adjusted hazard ratio [aHR], 1.05; 95% confidence interval [CI], 1.01-1.08; score 2: aHR, 1.08; 95% CI, 1.04-1.12; score 3: aHR, 1.09; 95% CI, 1.05-1.14; score 4: aHR, 1.12; 95% CI, 1.06-1.19). Persistent IFG exposure was also associated with higher risks of individual cancer types (colorectum, stomach, pancreas, biliary tract, and esophagus).

CONCLUSIONS

Cumulative exposure to IFG is associated with an increased risk of developing gastrointestinal cancer, in a dose-dependent manner.

PLAIN LANGUAGE SUMMARY

Hyperglycemia, including both diabetes and prediabetes, has been associated with an increased risk of various cancers. However, the cumulative effect of impaired fasting glucose on the risk of developing gastrointestinal cancer remains unclear. A frequent diagnosis of impaired fasting glucose was dose-dependently associated with a higher risk of developing overall gastrointestinal cancer. Furthermore, risks of individual cancer types increased with persistent impaired fasting glucose. Early detection of hyperglycemia and strict glycemic control can lower the risk of gastrointestinal cancer by reducing hyperglycemic burden. Additionally, for some individuals, lifestyle changes such as managing metabolic syndrome or abstaining from alcohol may also be helpful.

Prediabetes, intervening diabetes and subsequent risk of dementia: the Atherosclerosis Risk in Communities (ARIC) study

AIMS/HYPOTHESIS

The aim of this work was to evaluate whether the association of prediabetes with dementia is explained by the intervening onset of diabetes.

METHODS

Among participants of the Atherosclerosis Risk in Communities (ARIC) study we defined baseline prediabetes as HbA1c 39-46 mmol/mol (5.7-6.4%) and subsequent incident diabetes as a self-reported physician diagnosis or use of diabetes medication. Incident dementia was ascertained via active surveillance and adjudicated. We quantified the association of prediabetes with dementia risk before and after accounting for the subsequent development of diabetes among ARIC participants without diabetes at baseline (1990-1992; participants aged 46-70 years). We also evaluated whether age at diabetes diagnosis modified the risk of dementia.

RESULTS

Among 11,656 participants without diabetes at baseline, 2330 (20.0%) had prediabetes. Before accounting for incident diabetes, prediabetes was significantly associated with the risk of dementia (HR 1.12 [95% CI 1.01, 1.24]). After accounting for incident diabetes, the association was attenuated and non-significant (HR 1.05 [95% CI 0.94, 1.16]). Earlier age of onset of diabetes had the strongest association with dementia: HR 2.92 (95% CI 2.06, 4.14) for onset before 60 years; HR 1.73 (95% CI 1.47, 2.04) for onset at 60-69 years; and HR 1.23 (95% CI 1.08, 1.40) for onset at 70-79 years.

CONCLUSIONS/INTERPRETATION

Prediabetes is associated with dementia risk but this risk is explained by the subsequent development of diabetes. Earlier age of onset of diabetes substantially increases dementia risk. Preventing or delaying progression of prediabetes to diabetes will reduce dementia burden.

Prevalence and influencing factors of suicide in first-episode and drug-naive young major depressive disorder patients with impaired fasting glucose: a cross-sectional study

Background

An association exists between major depression disorder (MDD), suicide attempts, and glucose metabolism, but suicide attempts in young MDD patients with comorbid impaired fasting glucose (IFG) have been less well studied. The purpose of this study was to examine the prevalence and risk factors for suicide attempts in young, first-episode, drug-naive (FEDN) MDD patients with comorbid IFG.

Methods

We recruited 917 young patients with FEDN MDD, 116 of whom were judged to have combined IFG because their blood glucose was >6.0. We collected anthropological and clinical data on all of them. The Hamilton Depression Scale (HAMD) score, the Hamilton Anxiety Scale (HAMA) score and the Positive and Negative Syndrome Scale (PANSS) positive subscale score were used to assess their clinical symptoms. Blood glucose, plasma thyroid function and lipid indicators were measured.

Results

The prevalence of suicide attempts in young MDD patients with IFG was 32.8% (38/116). Furthermore, among young MDD patients with comorbid IFG, suicide attempters had more severe depression and anxiety symptoms, more comorbid psychotic symptom, higher levels of antibody of thyroid stimulating hormone and thyroid peroxidases (TPOAb), and more severe lipid metabolism disorders than those without suicide attempts. In addition, HAMA scores and TPOAb were independently associated with suicide attempts in young patients with FEDN MDD.

Conclusion

Our study suggests that young MDD patients with IFG have a high rate of suicide attempts. Some clinical symptoms and thyroid function parameters may be the risk factor for suicide attempts in young MDD patients with impaired glucose metabolism.

Cumulative exposure to metabolic syndrome in a national population-based cohort of young adults and sex-specific risk for type 2 diabetes

BACKGROUND

Metabolic syndrome is associated with type 2 diabetes and its prevalence is increasing worldwide in young adults. We aimed to determine whether cumulative exposure to metabolic syndrome is associated with type 2 diabetes risk in young adults.

METHODS

Data of 1,376,540 participants aged 20-39 years without a history of type 2 diabetes and who underwent four annual health check-ups were collected. In this large-scale prospective cohort study, we evaluated the incidence rates and hazard ratios (HRs) of diabetes according to cumulative frequencies of metabolic syndrome over 4 years of consecutive annual health check-ups (burden score 0-4). Subgroup analyses were performed by sex and age.

RESULTS

During 5.18 years of follow-up, 18,155 young adults developed type 2 diabetes. The incidence of type 2 diabetes increased with burden score (P < 0.0001). The multivariable-adjusted HRs for type 2 diabetes were 4.757, 10.511, 18.288, and 31.749 in participants with a burden score of 1 to 4, respectively, compared to those with 0. In subgroup analyses, the risk of incident diabetes was greater in women than men and in the 20-29 years age group than the 30-39 years age group. The HRs were 47.473 in women and 27.852 in men with four burden scores.

CONCLUSION

The risk of type 2 diabetes significantly increased with an increase in the cumulative burden of metabolic syndrome in young adults. Additionally, the association between cumulative burden and diabetes risk was stronger in women and the 20s age group.

Yolk-shell structured nanoreactor Au@Co3O4/CeO2@mSiO2 with superior peroxidase-like activity as nanozyme for ultra-sensitive colorimetric biosensing

For yolk-shell structured nanoreactors, multiple active components can be precisely positioned on core and/or shell that can afford more exposed accessible active sites, and the internal voids can guarantee sufficient contact of reactants and catalysts. In this work, a unique yolk-shell structured nanoreactor Au@Co₃O₄/CeO₂@mSiO₂ was fabricated and applied as nanozyme for biosensing. The Au@Co₃O₄/CeO₂@mSiO₂ exhibited superior peroxidase-like activity with a lower Michaelis constant (K_m) and a higher affinity to H₂O₂. The enhanced peroxidase-like activity was attributed to the unique structure and the synergistic effects between the multiple active components. Colorimetric essays were developed based on Au@Co₃O₄/CeO₂@mSiO₂ for the ultra-sensitive sensing of glucose in the range of 3.9 nM-1.03 mM with the limit of detection as low as 3.2 nM. In the detection of glucose-6-phosphate dehydrogenase (G6PD), the cooperation between G6PD and Au@Co₃O₄/CeO₂@mSiO₂ triggered the redox cycling between NAD⁺ and NADH, thereby achieving the amplification of the signal and enhancing the sensitivity of the assay. The assay showed superior performance as compared to other methods with linear response of 5.0 × 10^-3-15 mU mL^-1 and lower detection limit of 3.6 × 10^-3 mU mL^-1. The fabricated novel multi-enzyme catalytical cascade reaction system allowed rapid and sensitive biodetection, demonstrating its potential in biosensors and biomedical applications.

Development and validation of risk prediction models for new-onset type 2 diabetes in adults with impaired fasting glucose

AIMS

To develop and validate sex-specific risk prediction models based on easily obtainable clinical data for predicting 5-year risk of type 2 diabetes (T2D) among individuals with impaired fasting glucose (IFG), and generate practical tools for public use.

METHODS

The data used for model training and internal validation came from a large prospective cohort (N = 18,384). Two independent cohorts were used for external validation. A two-step approach was applied to screen variables. Coefficient-based models were constructed by multivariate Cox regression analyses, and score-based models were subsequently generated. The predictive power was evaluated by the area under the curve (AUC).

RESULTS

During a median follow-up of 7.55 years, 5697 new-onset T2D cases were identified. Predictor variables included age, body mass index, waist circumference, diastolic blood pressure, triglycerides, fasting plasma glucose, and fatty liver. The proposed models outperformed five existing models. In internal validation, the AUCs of the coefficient-based models were 0.741 (95% CI 0.723-0.760) for men and 0.762 (95% CI 0.720-0.802) for women. External validation yielded comparable prediction performance. We finally constructed a risk scoring system and a web calculator.

CONCLUSIONS

The risk prediction models and derived tools had well-validated performance to predict the 5-year risk of T2D in IFG adults.

Visceral adiposity index is positively associated with fasting plasma glucose: a cross-sectional study from National Health and Nutrition Examination Survey 2017-2020

BACKGROUND

Visceral adiposity index (VAI) has been recognized as a reliable indicator for visceral adiposity. However, it remains largely unexplored on its association with fasting plasma glucose (FPG). The current study aims to explore the association between VAI and FPG using a representative dataset.

METHODS

A cross-sectional study was carried out based on the dataset from National Health and Nutrition Examination Survey (NHANES) 2017-2020. Univariate and Multiple linear regression analysis were performed to explore the relationship between VAI and FPG. Generalized additive model (GAM) and smooth curve fitting analysis were performed to explore the nonlinear relationship between VAI and FPG. Receiver operating characteristic (ROC) analysis was used to evaluate the predictive value of VAI for FPG elevation.

RESULTS

A total of 4437 participants with complete data were finally included in the research. Individuals were divided into 4 quartiles according to the calculated VAI value: Q1 (VAI<0.69), Q2 (0.69 ≤ VAI < 1.18), Q3 (1.18 ≤ VAI < 2.02) and Q4 (VAI ≥ 2.02). FPG significantly increased with the increasing VAI quartile. Multiple linear regression analysis showed VAI was independently positively associated with FPG after adjusting confounding factors. As a continuous variable, an increase of one unit in VAI was correlated with 0.52 mmol/L (95% CI: 0.41-0.63, p < 0.0001) higher FPG level. As a categorical variable, 4th VAI quartile group was related to 0.71 mmol/L (95% CI: 0.47-0.95, p < 0.001) higher FPG level compared with 1st VAI group. GAM and smooth curve fitting analysis identified the non-linear relationship between VAI and FPG, and 4.02 was identified as the inflection point using two-piecewise linear regression. The positive association between VAI and FPG existed when VAI was lower (β = 0.73, p < 0.0001) and higher than 4.02 (β = 0.23, p = 0.0063). ROC analysis indicated VAI has a good predictive value for FPG elevation (AUC = 0.7169, 95% CI: 0.6948-0.7389), and the best threshold of VAI was 1.4315.

CONCLUSION

VAI was an independently risk indicator for FPG, and VAI was nonlinearly positively associated with FPG. VAI had a good predictive value for elevated FPG. VAI might become a useful indicator for risk assessment and treatment of hyperglycemia in clinical practice.

Predicting the Risk of Insulin-Requiring Gestational Diabetes before Pregnancy: A Model Generated from a Nationwide Population-Based Cohort Study in Korea

BACKGRUOUND

The severity of gestational diabetes mellitus (GDM) is associated with adverse pregnancy outcomes. We aimed to generate a risk model for predicting insulin-requiring GDM before pregnancy in Korean women.

METHODS

A total of 417,210 women who received a health examination within 52 weeks before pregnancy and delivered between 2011 and 2015 were recruited from the Korean National Health Insurance database. The risk prediction model was created using a sample of 70% of the participants, while the remaining 30% were used for internal validation. Risk scores were assigned based on the hazard ratios for each risk factor in the multivariable Cox proportional hazards regression model. Six risk variables were selected, and a risk nomogram was created to estimate the risk of insulin-requiring GDM.

RESULTS

A total of 2,891 (0.69%) women developed insulin-requiring GDM. Age, body mass index (BMI), current smoking, fasting blood glucose (FBG), total cholesterol, and γ-glutamyl transferase were significant risk factors for insulin-requiring GDM and were incorporated into the risk model. Among the variables, old age, high BMI, and high FBG level were the main contributors to an increased risk of insulin-requiring GDM. The concordance index of the risk model for predicting insulin-requiring GDM was 0.783 (95% confidence interval, 0.766 to 0.799). The validation cohort's incidence rates for insulin-requiring GDM were consistent with the risk model's predictions.

CONCLUSION

A novel risk engine was generated to predict insulin-requiring GDM among Korean women. This model may provide helpful information for identifying high-risk women and enhancing prepregnancy care.

Effect of high density lipoprotein cholesterol (HDL-C) on renal outcome in patients with nephrotic syndrome complicated with steroid-induced diabetes mellitus(SIDM)

OBJECTIVE

We aimed to investigate the renal prognosis of patients with idiopathic nephrotic syndrome (INS) complicated with steroid-induced diabetes mellitus (SIDM), the association of high-density lipoprotein cholesterol (HDL-C) before glucocorticoid treatment with renal prognosis, and the risk for persistent diabetes among patients with INS who had withdrawn from steroid therapy.

MATERIALS AND METHODS

We retrospectively analyzed 239 patients with INS complicated with SIDM at the National Clinical Research Center of Kidney Diseases, Jinling Hospital, from January 2008 to December 2019. The primary endpoint was the composite renal outcome defined as the development of end-stage renal disease (ESRD) or a 50% decrease in estimated glomerular filtration rate (eGFR) for more than 24 months after glucocorticoid withdrawal. The secondary endpoint was persistent diabetes, defined as fulfilling the criteria for diagnosing diabetes or using antidiabetic medications for at least 24 months after glucocorticoid withdrawal.

RESULTS

After glucocorticoid withdrawal for over 24 months, 35 (14.6%) patients reached the composite renal endpoint: end-stage renal disease (n = 14) or a 50% decrease in eGFR (n = 21). Before glucocorticoid therapy, a level of HDL-C greater than 1.45 mmol/L worsened renal survival in patients with INS complicated with SIDM. The log₁₀ the level of HDL-C before glucocorticoid treatment was an independent risk factor for the renal outcome. A prediction model was generated: Hazard ratio (renal outcome) = 0.94 * hypertension before glucocorticoid therapy + 2.29 * log₁₀ level of HDL-C before glucocorticoid treatment + 0.90 * the grade of interstitial tubule injury (AUROC, 0.75; 95% CI, 0.63 to 0.87; P < 0.01). Meanwhile, a level of fasting plasma glucose (FPG) before glucocorticoid treatment greater than 5.2 mmol/L enhanced the likelihood of persistent diabetes for at least 24 months after glucocorticoid withdrawal.

CONCLUSIONS

Increased level of HDL-C before glucocorticoid therapy was independently associated with a higher risk for renal outcome and thus may be useful in the renal prognosis of patients with INS complicated with SIDM.

Construction and Validation of a Model for Predicting Impaired Fasting Glucose Based on More Than 4000 General Population

Purpose

Impaired fasting glucose (IFG) is associated with an increased risk of multiple diseases. Therefore, the early identification and intervention of IFG are particularly significant. Our study aims to construct and validate a clinical and laboratory-based nomogram (CLN) model for predicting IFG risk.

Patients and Methods

This cross-sectional study collected information on health check-up subjects. Risk predictors were screened mainly by the LASSO regression analysis and were applied to construct the CLN model. Furthermore, we showed examples of applications. Then, the accuracy of the CLN model was evaluated by the receiver operating characteristic (ROC) curve, the area under the ROC curve (AUC) values, and the calibration curve of the CLN model in the training set and validation set, respectively. The decision curve analysis (DCA) was used to estimate the level of clinical benefit. Furthermore, the performance of the CLN model was evaluated in the independent validation dataset.

Results

In the model development dataset, 2340 subjects were randomly assigned to the training set (N = 1638) and validation set (N = 702). Six predictors significantly associated with IFG were screened and used in the construction of the CLN model, a subject was randomly selected, and the risk of developing IFG was predicted to be 83.6% by using the CLN model. The AUC values of the CLN model were 0.783 in the training set and 0.789 in the validation set. The calibration curve demonstrated good concordance. DCA showed that the CLN model has good clinical application. We further performed independent validation (N = 1875), showed an AUC of 0.801, with the good agreement and clinical diagnostic value.

Conclusion

We developed and validated the CLN model that could predict the risk of IFG in the general population. It not only facilitates the diagnosis and treatment of IFG but also helps to reduce the medical and economic burdens of IFG-related diseases.

Differences in the impact of impaired glucose status on clinical outcomes in younger and older adults: Over a decade of follow-up in the Tehran lipid and glucose study

Introduction

Studies found that the impact of dysglycemia on microvascular, macrovascular events and mortality outcomes were different between the younger vs. older population. We aimed to investigate the age-specific association of prediabetes with clinical outcomes including type 2 diabetes (T2DM), hypertension, chronic kidney disease (CKD), cardiovascular disease (CVD), and mortality.

Materials and methods

A total of 5,970 Iranians (3,829 women) aged ≥30 years, without T2DM, were included. The age-specific (<60 and ≥60 years; minimum p-value for interaction = 0.001) multivariable-adjusted Cox regression was done to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) of the impaired glucose status including impaired fasting glucose (IFG) vs. normal fasting glucose (NFG), impaired glucose tolerance (IGT) vs. normal glucose tolerance (NGT), and IFG&IGT vs. NFG/NGT with each outcome.

Results

Among individuals aged ≥60 years, the prevalence of impaired glucose status (IFG, IGT, or both) was about 2 times higher compared to those aged <60. Age-specific association between prediabetes and incident hypertension was found for those aged <60 years; [HR (95% CI); IFG: 1.38 (1.16–1.65), IGT: 1.51 (1.26–1.81), and IFG&IGT: 1.62 (1.21–2.12)]. For CVD, in all impaired glycemic states, those aged <60 were at higher significant risk [IFG: 1.39 (1.09–1.77), IGT: 1.53 (1.19–1.97), and IFG&IGT: 1.60 (1.14–2.25)]. Stratified analyses showed similar associations for IFG and IGT with non-CV mortality 1.71 (1.04–2.80) and 2.12 (1.30–3.46), respectively, and for all-cause mortality among those aged <60 years [IFG: 1.63 (1.08–2.45) and IGT: 1.82 (1.20–2.76)]. In both age groups, all glycemic status groups were significantly associated with T2DM but not with CKD and CV mortality.

Conclusions

The high prevalence of prediabetes particularly among the elderly population, limited resources, and the observed significant age differences in the impact of prediabetes states on different clinical outcomes calls for multicomponent intervention strategies by policy health makers, including lifestyle and possible pharmacological therapy, with the priority for the young Iranian population.

Development of Various Diabetes Prediction Models Using Machine Learning Techniques

BACKGROUND

There are many models for predicting diabetes mellitus (DM), but their clinical implication remains vague. Therefore, we aimed to create various DM prediction models using easily accessible health screening test parameters.

METHODS

Two sets of variables were used to develop eight DM prediction models. One set comprised 62 easily accessible examination results of commonly used variables from a tertiary university hospital. The second set comprised 27 of the 62 variables included in the national routine health checkups. Gradient boosting and random forest algorithms were used to develop the models. Internal validation was performed using the stratified 10-fold cross-validation method.

RESULTS

The area under the receiver operating characteristic curve (ROC-AUC) for the 62-variable DM model making 12-month predictions for subjects without diabetes was the largest (0.928) among those of the eight DM prediction models. The ROC-AUC dropped by more than 0.04 when training with the simplified 27-variable set but still showed fairly good performance with ROC-AUCs between 0.842 and 0.880. The accuracy was up to 11.5% higher (from 0.807 to 0.714) when fasting glucose was included.

CONCLUSION

We created easily applicable diabetes prediction models that deliver good performance using parameters commonly assessed during tertiary university hospital and national routine health checkups. We plan to perform prospective external validation, hoping that the developed DM prediction models will be widely used in clinical practice.

Associations Between Dietary Patterns and Incident Type 2 Diabetes: Prospective Cohort Study of 120,343 UK Biobank Participants

OBJECTIVE

To identify dietary patterns (DPs) characterized by a set of nutrients of concern and their association with incident type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

A total of 120,343 participants from the U.K. Biobank study with at least two 24 h dietary assessments were studied. Reduced rank regression was used to derive DPs explaining variability in energy density, free sugars, saturated fat, and fiber intakes. We investigated prospective associations with T2D using Cox proportional hazard models.

RESULTS

Over 8.4 years of follow-up from the latest dietary assessment, 2,878 participants developed T2D. Two DPs were identified that jointly explained a total of 63% variation in four nutrients. DP1 was characterized by high intakes of chocolate and confectionery, butter, low-fiber bread, and sugars and preserves, and low intakes of fruits and vegetables. DP1 was linearly associated with T2D in multivariable models without BMI adjustment (per z score, hazard ratio [HR] 1.11 [95% CI 1.08-1.14]) and after BMI adjustment (HR 1.09 [95% CI 1.06-1.12]). DP2 was characterized by high intakes of sugar-sweetened beverages, fruit juice, table sugars and preserves, and low intakes of high-fat cheese and butter, but showed no clear association with T2D. There were significant interactions between both DPs and age, with increased risks among younger people in DP1 (HR 1.13 [95% CI 1.09-1.18]) and DP2 (HR 1.10 [95% CI 1.05-1.15]), as well as with DP1 and BMI, with increased risks among people with obesity (HR 1.11 [95% CI 1.07-1.16]).

CONCLUSIONS

A DP characterized by high intakes of chocolate and confectionery, butter, low-fiber bread, and added sugars, and low in fresh fruits and vegetables intake is associated with a higher incidence of T2D, particularly among younger people and those with obesity.

Frequency of Exposure to Impaired Fasting Glucose and Risk of Mortality and Cardiovascular Outcomes

BACKGROUND

Metabolic abnormalities, such as impaired fasting glucose (IFG), are dynamic phenomena; however, it is unclear whether the timing of IFG exposure and cumulative exposure to IFG are related to cardiovascular disease (CVD) and mortality risk.

METHODS

Data were extracted from a nationwide population-based cohort in South Korea for adults (n=2,206,679) who were free of diabetes and had 4 years of consecutive health examination data. Fasting blood glucose levels of 100 to 125 mg/dL were defined as IFG, and the number of IFG diagnoses for each adult in the 4-year period was tabulated as the IFG exposure score (range, 0 to 4). Adults with persistent IFG for the 4-year period received a score of 4.

RESULTS

The median follow-up was 8.2 years. There were 24,820 deaths, 13,502 cases of stroke, and 13,057 cases of myocardial infarction (MI). IFG exposure scores of 1, 2, 3, and 4 were associated with all-cause mortality (multivariable-adjusted hazard ratio [aHR], 1.11; 95% confidence interval [CI], 1.08 to 1.15; aHR, 1.16; 95% CI, 1.12 to 1.20; aHR, 1.20; 95% CI, 1.15 to 1.25; aHR, 1.18; 95% CI, 1.11 to 1.25, respectively) compared with an IFG exposure score of 0. Adjusting for hypertension and dyslipidemia attenuated the slightly increased risk of MI or stroke associated with high IFG exposure scores, but significant associations for allcause mortality remained.

CONCLUSION

The intensity of IFG exposure was associated with an elevated risk of all-cause mortality, independent of cardiovascular risk factors. The association between IFG exposure and CVD risk was largely mediated by the coexistence of dyslipidemia and hypertension.