HDL-Cholesterol, Its Variability, and the Risk of Diabetes: A Nationwide Population-Based Study

Key biomarkers in type 2 diabetes patients: A systematic review

Type 2 diabetes mellitus (T2DM) is not just a local health issue but a significant global health burden, affecting patient outcomes and clinical management worldwide. Despite the wealth of studies reporting T2DM biomarkers, there is an urgent need for a comparative review. This review aims to provide a comprehensive analysis based on the reported T2DM biomarkers and how these are linked with other conditions, such as inflammation and wound healing. A comparative review was conducted on 24 001 study participants, including 10 024 T2DM patients and 13 977 controls (CTL; age 30-90 years). Four main profiles were extracted and analysed from the clinical reports over the past 11 years: haematological (1084 cases vs. 1458 CTL), protein (6753 cases vs. 9613 CTL), cytokine (975 cases vs. 1350 CTL) and lipid (1212 cases vs. 1556 CTL). This review provides a detailed analysis of the haematological profile in T2DM patients, highlighting fundamental changes such as increased white blood cells and platelet counts, accompanied by decreases in red blood cell counts and iron absorption. In the serum protein profile, a reduction in albumin and anti-inflammatory cytokines was noted along with an increase in globulin levels and pro-inflammatory cytokines. Furthermore, changes in lipid profiles were discussed, specifically the decreases in high-density lipoprotein (HDL) and the increases in low-density lipoprotein (LDL) and triglycerides. Understanding the changes in these four biomarker profiles is essential for developing innovative strategies to create diagnostic and prognostic tools for diabetes management.

Greater variability in HDL-C was associated with an increased risk of cognitive decline in the middle- and elderly Chinese: A cohort study

BACKGROUND

Previous studies into relationship between high-density lipoprotein cholesterol (HDL-C) and cognitive decline were constrained to a single measurement, leaving the association between HDL-C variability and risk of cognitive decline unclear.

METHODS

We identified 5930 participants from the China Health and Retirement Longitudinal Study (CHARLS) who were devoid for stroke, dementia, and memory-related diseases at baseline and underwent a minimum of 2 sequential health examinations during 2011-2015. Variability in HDL-C was defined as (1) variability independent of the mean (VIM), (2) average real variability (ARV), and (3) standard deviation (SD) of HDL-C change from baseline and follow-up visits. Cognitive function was evaluated in 2018 by Mini-mental state examination (MMSE) in the Chinese version. Logistic regression was employed to explore the association between HDL-C variability and cognitive decline. Odd ratios (OR) and 95 % confidence intervals (CI) were reported.

RESULTS

The study included participants from CHARLS, mean age of 57.84±8.44 years and 44 % male. After adjustment for covariates, the highest quartile of VIM was associated with an increased risk of cognitive decline [OR:1.049, 95 %CI: 1.014-1.086] compared to the lowest quartile. For each SD increment of VIM, the OR was 1.015 (95 %CI:1.003-1.027). Strong dose-response relationships were identified (P for trend: 0.005). Consistent results were obtained for other measures of HDL-C variability (ARV and SD). Similar patterns were identified in different dimensions of cognition.

CONCLUSIONS

Elevated HDL-C variability was associated with increased cognitive decline risk. Strategies to reducing HDL-C variability may lower the risks of cognitive decline among the general population.

Analysis of the Association Between Changes in the GGT/HDL-C Ratio and the Risk of Diabetes Mellitus Based on a Latent Class Growth Mixed Modeling: A Longitudinal Cohort Study of Adults in China

Objective

Longitudinal cohort analysis was performed to identify the association between changes in the gamma-glutamyl transferase (GGT)/high-density lipoprotein cholesterol (HDL-C) ratio trajectory and the risk of developing diabetes mellitus.

Methods

This was a retrospective cohort study. We analyzed the latent trajectory classes of changes in the GGT/HDL-C ratio by applying a latent class mixture model with healthy individuals who underwent medical checkups from January 2017 to December 2021 as the study subjects. To analyze the effect of the GGT/HDL-C ratio trajectory classes on new-onset diabetes mellitus, we then applied a multivariate Cox proportional risk regression model. Statistical analysis was performed using the R-software with the LCMM package.

Results

The study cohort comprised 3410 participants. All participants were followed up for 5 years, and 95 developed diabetes (4-year incidence of 2.78%). By applying the latent class mixed model, we categorized participants into three trajectory groups: low-stability group (n = 2253), medium-increase group (n = 941), and high-increase group (n = 216). The Cox proportional risk regression model analysis showed that the hazard ratio (95% confidence interval) for the incidence of diabetes mellitus was 1.73 (1.04-2.87) in the medium-increase group and 3.96 (2.11-7.44) in the high-increase group. Moreover, we calculated the estimated model-based levels and linear slopes of the GGT/HDL-C ratios for each age group between 26 and 85 years at 10-year intervals, respectively. The results indicated the strongest correlation between the GGT/HDL-C ratio slope and diabetes in the 46-55 year age group, with an odds ratio of 1.51 (1.25-1.83).

Conclusion

A large increase in the GGT/HDL-C ratio was highly associated with the risk of developing diabetes mellitus. This result suggests that vigilance for changes in the GGT/HDL-C ratio trajectory during community health screening can help identify potential patients with diabetes, enabling early intervention and treatment.

Association between blood lipids and diabetes mellitus in older Chinese adults aged 65 years or older: a cross-sectional analysis of residents' electronic health records

AIM

This study aimed to investigate how blood lipids are associated with diabetes among older Chinese adults.

METHODS

3,268,928 older Chinese adults without known diabetes were included. Logistic regression and restricted cubic spline (RCS) models were conducted to study associations between blood lipids (total cholesterol [TC], triglycerides [TG], low-density lipoprotein cholesterol [LDL-C], and high-density lipoprotein cholesterol [HDL-C]) and diabetes.

RESULTS

202,832 diabetes cases were included. Compared with the lowest quintiles, TC, TG, and LDL-C in the highest quintiles showed a higher diabetes prevalence risk and HDL-C presented a lower risk in multivariate-adjusted logistic regression models. Odds ratios (ORs) and 95% confidence intervals (95% CIs) for the highest quintiles of TC, TG, and HDL-C were 1.39 (1.37-1.41), 2.56 (2.52-2.60), and 0.73 (0.72-0.74), respectively. For LDL-C, 3-5% lower risk was found in the second and third quintiles, and 4-23% higher risk was found in the fourth and fifth quintiles. RCS curves showed a non-linear relationship between each blood lipid parameters and diabetes (P-non-linear < 0.001). TG and HDL-C curves presented monotonically increasing and L-shaped patterns, respectively, whereas TC and LDL-C curves exhibited a J-shaped pattern. When TC < 4.04 mmol/L or LDL-C < 2.33 mmol/L, ORs of diabetes increased with the decrease of corresponding indexes. However, after excluding participants with lower LDL-C, the J-shaped association with TC disappeared.

CONCLUSIONS

This study demonstrates non-linear associations between lipids and diabetes. Low cholesterol levels are associated with a high risk of diabetes. The cholesterol paradox should be considered during lipid-lowering treatments.

Metabolic dysfunction-associated fatty liver disease increases the risk of type 2 diabetes mellitus in young Korean adults

AIMS

To investigate the impact of Metabolic Dysfunction-Associated Fatty Liver Disease (MAFLD) on the risk of type 2 diabetes mellitus in young Korean adults.

METHODS

Data were sourced from the Korean National Health Insurance Service-Health Screening Cohort, comprising adults aged 20-39 who underwent health examinations between 2009 and 2012. Participants were grouped based on the presence of MAFLD and nonalcoholic fatty liver disease (NAFLD), both individually and in combination. The categorizations included Neither-FLD, NAFLD-only, MAFLD-only, or Both-FLD. Incident diabetes was identified through claims data during the follow-up period.

RESULTS

Among 6,232,656 participants, 676,747 (10.8 %) had MAFLD. During a median follow-up of 9.5 years, 182,291 incident diabetes cases were identified. Multivariate analysis revealed a significantly higher diabetes risk in the MAFLD group compared to those in the Non-MAFLD group (HR = 6.148, 95 % CI, 6.084-6.212). Notably, diabetes incidence was highest in FLI ≥ 60 subgroup with BMI ≥ 23 and metabolic syndrome.

CONCLUSIONS

MAFLD is associated with a 6.1-fold increased diabetes risk in young adults, underscoring the urgent need for early intervention to mitigate this risk.

Candida albicans skin infection in diabetic patients: An updated review of pathogenesis and management

Candida species, commensal residents of human skin, are recognized as the cause of cutaneous candidiasis across various body surfaces. Individuals with weakened immune systems, particularly those with immunosuppressive conditions, are significantly more susceptible to this infection. Diabetes mellitus, a major metabolic disorder, has emerged as a critical factor inducing immunosuppression, thereby facilitating Candida colonization and subsequent skin infections. This comprehensive review examines the prevalence of different types of Candida albicans-induced cutaneous candidiasis in diabetic patients. It explores the underlying mechanisms of pathogenicity and offers insights into recommended preventive measures and treatment strategies. Diabetes notably increases vulnerability to oral and oesophageal candidiasis. Additionally, it can precipitate vulvovaginal candidiasis in females, Candida balanitis in males, and diaper candidiasis in young children with diabetes. Diabetic individuals may also experience candidal infections on their nails, hands and feet. Notably, diabetes appears to be a risk factor for intertrigo syndrome in obese individuals and periodontal disorders in denture wearers. In conclusion, the intricate relationship between diabetes and cutaneous candidiasis necessitates a comprehensive understanding to strategize effective management planning. Further investigation and interdisciplinary collaborative efforts are crucial to address this multifaceted challenge and uncover novel approaches for the treatment, management and prevention of both health conditions, including the development of safer and more effective antifungal agents.

Progression from Prediabetes to Diabetes in a Diverse U.S. Population: A Machine Learning Model

Objective: To date, there are no widely implemented machine learning (ML) models that predict progression from prediabetes to diabetes. Addressing this knowledge gap would aid in identifying at-risk patients within this heterogeneous population who may benefit from targeted treatment and management in order to preserve glucose metabolism and prevent adverse outcomes. The objective of this study was to utilize readily available laboratory data to train and test the performance of ML-based predictive risk models for progression from prediabetes to diabetes. Methods: The study population was composed of laboratory information services data procured from a large U.S. outpatient laboratory network. The retrospective dataset was composed of 15,029 adults over a 5-year period with initial hemoglobin A1C (A1C) values between 5.0% and 6.4%. ML models were developed using random forest survival methods. The ground truth outcome was progression to A1C values indicative of diabetes (i.e., ≥6.5%) within 5 years. Results: The prediabetes risk classifier model accurately predicted A1C ≥6.5% within 5 years and achieved an area under the receiver-operator characteristic curve of 0.87. The most important predictors of progression from prediabetes to diabetes were initial A1C, initial serum glucose, A1C slope, serum glucose slope, initial HDL, HDL slope, age, and sex. Conclusions: Leveraging readily obtainable laboratory data, our ML risk classifier accurately predicts elevation in A1C associated with progression from prediabetes to diabetes. Although prospective studies are warranted, the results support the clinical utility of the model to improve timely recognition, risk stratification, and optimal management for patients with prediabetes.

The association of ALT to HDL-C ratio with type 2 diabetes in 50-74 years old adults: a population-based study

There is limited information about the relationship between diabetes mellitus (DM) and ALT to HDL-C ratio. This study aims to investigate this relationship for the first time in Iran. The data of this study were taken from the third phase of the Shahroud Eye Cohort Study, which was conducted in 2019 with the participation of 4394 people aged 50-74. ALT and HDL-C levels were measured using a BT-1500 autoanalyzer. The mean ALT/HDL-C ratio was reported along with 95% confidence intervals (CI). The multiple logistic regression was used to examine the association between this ratio and DM, while controlling for the effects of other independent variables. The mean and standard deviation of the ALT/HDL-C ratio in all participants were 16.62 ± 11.22 (95% CI 16.28-16.96). The prevalence of DM was 34.7% and individuals with DM had a mean ALT/HDL-C ratio that was 1.80 units higher than those without diabetes (P < 0.001). Also, in individuals with DM, the HDL-C was found to be 0.035 (mmol/L) lower (P < 0.001), while ALT was 1.13 (IU/L) higher (P < 0.001) compared to those without diabetes. Additionally, after controlling for confounding factors, the odds of developing DM increased in a non-linear manner with an increase in the ALT/HDL-C ratio. Abdominal obesity, advanced age, female gender, and hypertension were also found to be associated with increased odds of DM. In conclusion, an increase in the ALT/ HDL-C ratiowas associated with higher odds of DM. This ratio can serve as an important predictor for diabetes mellitus.

Lipid variability and risk of microvascular complications in patients with diabetes: a systematic review and meta-analysis

BACKGROUND AND AIMS

The current systematic review aimed to elucidate the effects of lipid variability on microvascular complication risk in diabetic patients. The lipid components studied were as follows: High-density lipoprotein (HDL), High-density lipoprotein (LDL), Triglyceride (TG), Total Cholesterol (TC), and Remnant Cholesterol (RC).

METHOD

We carried out a systematic search in multiple databases, including PubMed, Web of Science, and SCOPUS, up to October 2nd, 2023. After omitting the duplicates, we screened the title and abstract of the studies. Next, we retrieved and reviewed the full text of the remaining articles and included the ones that met our inclusion criteria in the study.

RESULT

In this research, we examined seven studies, comprising six cohort studies and one cross-sectional study. This research was conducted in Hong Kong, China, Japan, Taiwan, Finland, and Italy. The publication years of these articles ranged from 2012 to 2022, and the duration of each study ranged from 5 to 14.3 years. The study group consisted of patients with type 2 diabetes aged between 45 and 84 years, with a diabetes history of 7 to 12 years. These studies have demonstrated that higher levels of LDL, HDL, and TG variability can have adverse effects on microvascular complications, especially nephropathy and neuropathic complications. TG and LDL variability were associated with the development of albuminuria and GFR decline. Additionally, reducing HDL levels showed a protective effect against microalbuminuria. However, other studies did not reveal an apparent relationship between lipid variations and microvascular complications, such as retinopathy. Current research lacks geographic and demographic diversity. Increased HDL, TG, and RC variability have been associated with several microvascular difficulties. Still, the pathogenic mechanism is not entirely known, and understanding how lipid variability affects microvascular disorders may lead to novel treatments. Furthermore, the current body of this research is restricted in its coverage. This field's lack of thorough investigations required a more extensive study and comprehensive effort.

CONCLUSION

The relationship between lipid variation (LDL, HDL, and TG) (adverse effects) on microvascular complications, especially nephropathy and neuropathic (and maybe not retinopathy), is proven. Physicians and health policymakers should be highly vigilant to lipid variation in a general population.

HDL Function across the Lifespan: From Childhood, to Pregnancy, to Old Age

The function of high-density lipoprotein (HDL) particles has emerged as a promising therapeutic target and the measurement of HDL function is a promising diagnostic across several disease states. The vast majority of research on HDL functional biology has focused on adult participants with underlying chronic diseases, whereas limited research has investigated the role of HDL in childhood, pregnancy, and old age. Yet, it is apparent that functional HDL is essential at all life stages for maintaining health. In this review, we discuss current data regarding the role of HDL during childhood, pregnancy and in the elderly, how disturbances in HDL may lead to adverse health outcomes, and knowledge gaps in the role of HDL across these life stages.

Structural characterization of Euglena gracilis polysaccharide and its in vitro hypoglycemic effects by alleviating insulin resistance

Diabetes mellitus, characterized by hyperglycemia and insulin resistance, is a disorder of the endocrine metabolic system which has emerged as a common chronic disease worldwide. Euglena gracilis polysaccharides have ideal development potential in the treatment of diabetes. However, their structure and bioactivity are largely unclear. A novel purified water-soluble polysaccharide (EGP-2A-2A) from E. gracilis with a molecular weight of 130.8 kDa consisted of xylose, rhamnose, galactose, fucose, glucose, arabinose, and glucosamine hydrochloride. The SEM image for EGP-2A-2A suggested a rough surface with the presence of globule-like protrusions. Methylation and NMR spectral analyses revealed that EGP-2A-2A was mainly composed of →6)-β-D-Galp-(1 → 2)-α-D-Glcp-(1 → 2)-α-L-Rhap-(1 → 3)-α-L-Araf-(1 → 6)-β-D-Galp-(1 → 3)-α-D-Araf-(1 → 3)-α-L-Rhap-(1 → 4)-β-D-Xylp-(1 → 6)-β-D-Galp-(1 → with complex branching structure. EGP-2A-2A significantly increased glucose consumption and glycogen content in IR-HeoG2 cells and modulates glucose metabolism disorders by regulating PI3K, AKT, and GLUT4 signaling pathways. EGP-2A-2A significantly suppressed TC, TG, and LDL-c levels, and enhanced that of HDL-c. EGP-2A-2A ameliorated abnormalities caused by disorders of glucose metabolism and the hypoglycemic activity of EGP-2A-2A may be mainly positively related to its high glucose content and the β-configuration in the main chain. These results suggested that EGP-2A-2A played an important role in alleviating disorders of glucose metabolism through insulin resistance and has the potential for development as a novel functional food with nutritional and health benefits.

Nomogram model and risk score to predict 5-year risk of progression from prediabetes to diabetes in Chinese adults: Development and validation of a novel model

AIM

To develop a personalized nomogram and risk score to predict the 5-year risk of diabetes among Chinese adults with prediabetes.

METHODS

There were 26 018 participants with prediabetes at baseline in this retrospective cohort study. We randomly stratified participants into two cohorts for training (n = 12 947) and validation (n = 13 071). The least absolute shrinkage and selection operator (LASSO) model was applied to select the most significant variables among candidate variables. And we further established a stepwise Cox proportional hazards model to screen out the risk factors based on the predictors chosen by the LASSO model. We presented the model with a nomogram. The model's discrimination, clinical use and calibration were assessed using the area under the receiver operating characteristic (ROC) curve, decision curve and calibration analysis. The associated risk factors were also categorized according to clinical cut-points or tertials to create the diabetes risk score model. Based on the total score, we divided it into four risk categories: low, middle, high and extremely high. We also evaluated our diabetes risk score model's performance.

RESULTS

We developed a simple nomogram and risk score that predicts the risk of prediabetes by using the variables age, triglyceride, fasting blood glucose, body mass index, alanine aminotransferase, high-density lipoprotein cholesterol and family history of diabetes. The area under the ROC curve of the nomogram was 0.8146 (95% CI 0.8035-0.8258) and 0.8147 (95% CI 0.8035-0.8259) for the training and validation cohort, respectively. The calibration curve showed a perfect fit between predicted and observed diabetes risks at 5 years. Decision curve analysis presented the clinical use of the nomogram, and there was a wide range of alternative threshold probability spectrums. A total risk score of 0 to 2.5, 3 to 4.5, 5 to 7.5 and 8 to 13.5 is associated with low, middle, high and extremely high diabetes risk status, respectively.

CONCLUSIONS

We developed and validated a personalized prediction nomogram and risk score for 5-year diabetes risk among Chinese adults with prediabetes, identifying individuals at a high risk of developing diabetes. Doctors and other healthcare professionals can easily and quickly use our diabetes score model to assess the diabetes risk status in patients with prediabetes. In addition, the nomogram model and risk score we developed need to be validated in a prospective cohort study.

Associations between the HDL-C/ApoA-I ratio and fasting glucose levels differ by glucose deciles, HDL-C/ApoA-I ratio ranges and sex

AIMS

To learn how high-density lipoprotein cholesterol (HDL-C) and apolipoprotein A-I (ApoA-I) are associated with fasting blood glucose (FBG).

METHODS

A cross-sectional study was performed in 97,801 males and 70,773 females without known disease.

RESULTS

The ratio of HDL-C/ApoA-I is more stable for predicting fasting glucose levels than HDL-C or ApoA-I alone. In subjects with HDL-C/ApoA-I ≤ 0.9, HDL-C/ApoA-I ratios were negatively associated with FBG levels, with similar patterns between sexes, and the associations gradually strengthened along with the deciles of FBG increase. In subjects with HDL-C/ApoA-I > 0.9, FBG remained at relatively lower levels in both sexes, while the associations between the FBG level and the HDL-C/ApoA-I ratio turned from negative in the lowest five deciles to positive in the highest two deciles of FBG levels in males. Adjustment for known confounders only slightly attenuated the above association patterns. Subpopulations with HDL-C/ApoA-I ≤ 0.9 were distributed in the higher ranges of triglyceride (TG), non-HDL-C, total cholesterol (TC) and ApoA-I levels and lower ranges of HDL-C levels.

CONCLUSIONS

The HDL-C/ApoA-I ratio sorted TG, non-HDL-C, TC, ApoA-I and HDL-C levels and hence might combine more coordinating metabolic characteristics of these lipids in association with blood glucose homeostasis.

Risk for Behçet's disease gauged via high-density lipoprotein cholesterol: a nationwide population-based study in Korea

Behçet’s disease (BD) is a chronic inflammatory disease. Low levels of plasma high-density lipoprotein cholesterol (HDL-C) are associated with Crohn’s disease, another chronic inflammatory disease. However, the effects of low HDL-C levels on BD are unclear. We investigated the effects of HDL-C levels, and variability therein, on the risk for BD. We used the Korean National Health Insurance System database to identify 5,587,754 adults without a history of BD who underwent ≥ 3 medical examinations between 2010 and 2013. Mean HDL-C levels at each visit were used to calculate variability independent of the mean (VIM) and the coefficient of variation (CV). There were 676 new cases of BD (0.012%). The risk for BD was increased in participants with highly variable and low mean HDL-C levels. In a multivariate-adjusted model, the hazard ratios (95% confidence intervals) for BD incidence were 1.335 (1.058–1.684) in a high mean/high VIM group, 1.527 (1.211–1.925) in a low mean/low VIM group, and 2.096 (1.67–2.63) in a low mean/high VIM group compared to a high mean/low VIM group. Low mean HDL-C levels, and high variability therein, are independent risk factors for BD.

Non-linear relationship between high-density lipoprotein cholesterol and incident diabetes mellitus: a secondary retrospective analysis based on a Japanese cohort study

BACKGROUND AND OBJECTIVE

High-density lipoprotein cholesterol (HDL-C) may be directly involved in glucose metabolism by enhancing insulin sensitivity and insulin secretion. This current study aimed to explore the association between HDL-C and the risk of diabetes mellitus (DM) in Japanese population.

METHODS

This retrospective cohort study was based on a publicly available DRYAD dataset. We enrolled 15,388 Japanese participants who received medical examinations from 2004 to 2015 at Murakami Memorial Hospital. Our study selected HDL-C at baseline and incident DM during follow-up as the target independent variable and the dependent variable, respectively. Cox proportional-hazards regression was used to investigate the association between HDL-C and DM, generalized additive models to identify non-linear relationships.

RESULTS

After adjusting for the demographic and clinical covariates, the result showed low HDL-C levels were associated with increased risk for diabetes (HR = 0.54, 95%CI (0.35, 0.82)). The results remained robust in a series of sensitive analysis. A non-linear relationship was detected between HDL-C and incident DM with an inflection point of HDL-C at 1.72 mmol/L (Log-likelihood ratio test P = 0.005). Subgroup analysis showed that a stronger association could be found in ex-smokers and current-smokers. The same trend was also seen in the community with hypertension (P for interaction = 0.010, HR = 1.324).

CONCLUSION

This study demonstrates a negative and non-linear relationship between HDL-C and diabetes in the Japanese population. There is a threshold effect between HDL-C and diabetes. When HDL-C is lower than 1.72 mmol/L, the decreased HDL-C levels were associated with an increased risk for diabetes.

Dynamic physical examination indicators of cardiovascular health: A single-center study in Shanghai, China

Dynamic physical examination data can provide both cross-sectional and time-series characteristics of cardiovascular health. However, most physical examination databases containing health and disease information have not been fully utilized in China. Hence, this study aimed to analyze dynamic physical examination indicators for cardiovascular health to provide evidence for precise prevention and control of cardiovascular diseases in the primary prevention domain among healthy population with different demographic characteristics in Shanghai. Three-year continuous data were collected from the physical examination center of a hospital in Shanghai from 2018 to 2020, which included a total of 14,044 participants with an average age of 46.51±15.57 years. The cardiovascular status of overall healthy individuals may have a decreasing trend, which is manifested as a significant year-on-year decrease in high-density lipoprotein cholesterol; a significant year-on-year increase in total cholesterol, low-density lipoprotein cholesterol, and blood glucose levels; and a possible increasing trend of diastolic blood pressure, body mass index, and triglycerides. Healthy population with different sex and age groups have various sensitives to cardiovascular physical examination indicators. To conduct more accurate cardiovascular health management and health promotion for key populations in primary prevention, focusing on the dynamic trends of blood pressure, blood lipids, blood glucose, and body mass index in men and changes in total cholesterol in women over time is especially important. The age group of 50–69 years is key for better prevention and control of cardiovascular health.

Variability, Mean, and Baseline Values of Metabolic Parameters in Predicting Risk of Type 2 Diabetes

CONTEXT

The effect of baseline (B) and alteration of metabolic parameters (MPs), including plasma glucose (PG) testing, insulin resistance surrogates, and lipid profile and their mutual interactions on the development of type 2 diabetes mellitus (T2DM), has not been investigated systematically.

OBJECTIVE

To access the association of the past variability (V), past mean (M), and B values of various MPs and their mutual interaction with the risk of T2DM.

METHODS

A community-based, longitudinal analysis was conducted using the Korean Genome and Epidemiology Study comprising 3829 nondiabetic participants with completed MPs measurements during 3 biannually visits who were followed over the next 10 years. Outcomes included the incidence of T2DM during follow-up.

RESULTS

Among predictors, PG concentrations measured during the oral glucose tolerance test were the most prominent T2DM determinants, in which the M of the average value of fasting PG (FPG), 1-hour, and 2-hour PGs had the strongest discriminative power (hazard ratios and 95% CI for an increment of SD: 3.00 (2.5-3.26), AUC: 0.82). The M values of MPs were superior to their B and V values in predicting T2DM, especially among postload PGs. Various mutual interactions between indices and among MPs were found. The most consistent interactants were the M values of high-density lipoprotein cholesterol and the M and V values of FPG. The findings were similar in normal glucose tolerance participants and were confirmed by sensitivity analyses.

CONCLUSION

Postload PG, past alteration of measurements, and mutual interactions among indices of MPs are important risk factors for T2DM development.

Plasma lipid levels and risk of retinal vascular occlusion: A genetic study using Mendelian randomization

The causal effects of plasma lipid levels and the risk of retinal vascular occlusion (RVO) have not been clearly identified, especially for high-density lipoprotein-cholesterol (HDL-C) and low-density lipoprotein-cholesterol (LDL-C). Here, we try to identify these causal risk factors using a two-sample Mendelian randomization (MR) analysis. Single nucleotide polymorphisms (SNPs) were chosen as instrumental variables (IVs). We obtained genetic variants associated with lipid exposure at the genome-wide significance (P<5×10^-8) level from a meta-analysis of GWAS from the Global Lipids Genetics Consortium (GLGC) based on 188,577 individuals of mostly European ancestry for MR analyses. Meanwhile, we used lipid GWAS from UK Biobank (UKB) with a sample size of 115,078 individuals as a supplement. We obtained genetic predictors of RVO from a FinnGen biobank study. We conducted both univariable and multivariable MR (MVMR) analyses to identify the causal effects of RVO. Although inverse variance weighted (IVW) was the primary method used for MR analyses, MR-Egger and weighted-median methods were used as supplements to IVW. We determined the heterogeneity of IVs using Cochrane's Q test and I² , and used the MR-Egger intercept and MR-PRESSO Global test to detect horizontal pleiotropy. A leave-one-out sensitivity analysis was conducted by removing a single variant from the analysis. Genetically predicted increased HDL-C level was associated with decreased risk of RVO from GLGC [OR=0.806; 95% CI=(0.659, 0.986); P=0.036], which was consistent with UKB results [OR=0.766; 95% CI=(0.635, 0.925); P=0.005]. MVMR analysis for plasma lipids [adjusted OR=0.639; 95% CI=(0.411, 0.992); P=0.046] or diabetes [adjusted OR=0.81; 95% CI=(0.67, 0.979); P=0.029] suggested that low HDL-C may be an independent risk factor for RVO. However, there was no evidence to support a causal association between LDL-C {GLGC [adjusted OR=1.015; 95% CI=(0.408, 2.523); P=0.975], UKB [OR=1.115; 95% CI=(0.884, 1.407); P=0.359]}, total cholesterol {GLGC [adjusted OR=0.904; 95% CI=(0.307, 2.659); P=0.854], UKB [OR=1.047; 95% CI=(0.816, 1.344); P=0.716]} or triglycerides {GLGC [OR=1.103; 95% CI=(0.883, 1.378); P=0.385], UKB [OR=1.003; 95% CI=(0.827, 1.217); P=0.098]} and RVO. Using two-sample MR analysis, our study suggested that dyslipidemia was a risk factor for RVO. Furthermore, our results indicated that a low HDL-C level may be an independent risk factor for RVO, suggesting that controlling HDL-C level may be effective in RVO development.

Associations of visit-to-visit variabilities and trajectories of serum lipids with the future probability of type 2 diabetes mellitus

Background

Serum lipid abnormalities are generally considered as a major risk factor for type 2 diabetes mellitus (T2DM). However, evidence for the effect of long-term serum lipid fluctuations on future T2DM probability remains limited.

Methods

A total of 4475 nondiabetic participants who underwent annual health examinations between 2010 and 2013 were followed for the subsequent 5-year risk of T2DM. The Cox proportional hazards model was performed to evaluate the associations of visit-to-visit variabilities and trajectories of triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-c) and low-density lipoprotein cholesterol (LDL-c) with T2DM probability.

Results

During the five-year follow-up, 223 newly developed T2DM cases were identified. Compared with the “Low” TG trajectory, “Moderate” and “Moderate-High” TG trajectories were significantly associated with T2DM incidence, with adjusted hazard ratios (HRs) and 95 % confidence intervals (CIs) of 1.51 (1.12-2.03) and 2.55 (1.62-4.03), respectively. Additionally, participants in the third and fourth quartiles of TG/standard deviation (SD) were associated with increased T2DM probability when compared with those in the lowest quartile. After excluding individuals with prediabetes, participants with “Moderate-High” TG trajectory still had a 2.43-fold greater risk of T2DM compared with those with “Low” TG trajectory (95 % CI: 1.28-4.63). In addition, compared with participants in “Low” HDL-c trajectory, the future T2DM probability was significantly reduced in those with “Moderate” and “High” HDL-c trajectories, with HR (95 % CI) of 0.52 (0.37-0.72) and 0.38 (0.18-0.80), respectively. After excluding individuals with prediabetes, the “Moderate” HDL-c trajectory remained associated with decreased T2DM probability when compared with “Low” HDL-c trajectory (HR: 0.55, 95 % CI: 0.35-0.88). However, the incidence of T2DM was not associated with the long-term fluctuations of TC and LDL-c.

Conclusions

Long-term visit-to-visit variability of TG, and the change trajectories of TG and HDL-c were significantly associated with future T2DM probability. Moreover, these associations were not affected after excluding individuals with prediabetes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12944-021-01592-9.

Increased Visit-to-Visit Liver Enzyme Variability Is Associated with Incident Diabetes: A Community-Based 12-Year Prospective Cohort Study

BACKGROUND

Fatty liver and/or increased liver enzyme values have been reported to be associated with incident diabetes. We sought to determine whether increased visit-to-visit liver enzyme variability is associated with incident diabetes.

METHODS

Study participants were recruited from the Korean Genome and Epidemiologic Study (KoGES). A total of 4,151 people aged 40 to 69 years was recruited and tested every 2 years for up to 12 years. Visit-to-visit aspartate aminotransferase (AST) and alanine aminotransferase (ALT) variability was evaluated in first the 6-year period through the use of various variability measurements: standard deviation (SD), average successive variability, coefficient of variation (CV), and variation independent of mean (VIM). Oral glucose tolerance test was performed at every visit.

RESULTS

During the 6-year follow-up appointments, 13.0% (538/4,151) of people developed incident diabetes. Visit-to-visit AST variability was associated with an increased risk of diabetes independent of conventional risk factors for diabetes (hazard ratio per 1-SD increment [95% confidence interval]: 1.06 [1.00 to 1.11], 1.12 [1.04 to 1.21], and 1.13 [1.04 to 1.22] for SD, CV, and VIM, respectively; all P<0.05); however, no such associations were observed in the visit-to-visit ALT variability. According to alcohol consumption status, both AST and ALT variability were independent predictors for incident diabetes in subjects with heavy alcohol consumption; however, neither AST nor ALT variability was associated with diabetes risk in subjects who did not drink alcohol heavily.

CONCLUSION

Visit-to-visit liver enzyme variability is an independent predictor of incident diabetes. Such association was more evident in those who consumed significant amounts of alcohol.

The association between triglyceride-glucose index and the incidence of type 2 diabetes mellitus-a systematic review and dose-response meta-analysis of cohort studies

ABSTARCT

AIMS: We aimed to assess the dose-response relationship between triglyceride-glucose (TyG) index and the incidence of type 2 diabetes mellitus (T2DM).

METHODS

We performed a comprehensive systematic literature search using PubMed, Scopus, and Embase for records published from inception until 9 February 2021. The effect estimates were reported as relative risks (RRs).

RESULTS

270,229 subjects from 14 studies were included in this systematic review and meta-analysis. The pooled incidence of T2DM was 9%. Meta-regression analysis indicates that baseline age (coefficient: 0.67, p = 0.026), drinking (coefficient: 0.03, p = 0.035), and HDL (coefficient: -0.89, p = 0.035) affected the incidence of T2DM in future. High TyG index was associated with increased incidence of T2DM in pooled unadjusted (RR 4.68 [3.01, 7.29], p < 0.001; I²: 96.6%) and adjusted model (adjusted RR 3.54 [2.75, 4.54], p < 0.001; I²: 83.7%). Dose-response meta-analysis for the adjusted RR showed that the linear association analysis was not significant per 0.1 increase in TyG index (RR 1.01 [0.99, 1.03], p = 0.223). There is a non-linear trend (p < 0.001) for the association between TyG index and incidence of T2DM. The dose-response curve became increasingly steeper at TyG index above 8.6.

CONCLUSIONS

TyG index was associated with the incidence of T2DM in a non-linear fashion.

The relationship between high-density lipoprotein cholesterol (HDL-C) and glycosylated hemoglobin in diabetic patients aged 20 or above: a cross-sectional study

AIM

The incidence rate of diabetes is increasing year by year, seriously threatening human health. As a predictor of glycemic control, glycated hemoglobin is reported to be related to various complications and prognoses of diabetes. Besides, HDL-C dyslipidemia is a component of metabolic syndrome and may be related to various cardiovascular and cerebrovascular diseases. The principal objective of this project was to investigate the relationship between HDL-C and glycosylated hemoglobin in adult diabetic patients.

METHODS

A total of 3171 adult diabetic patients aged 20 years and above were included in the present study from the National Health and Nutrition Examination Survey (NHANES). HDL-C and glycosylated hemoglobin were regarded as independent and dependent variables, respectively. EmpowerStats software and R (version 3.4.3) were used to examine the association between HDL-C and glycosylated hemoglobin.

RESULTS

HDL-C was inversely associated with glycohemoglobin after adjusting for other covariates (β = - 0.004, 95% CI:- 0.008 to - 0.000, p = 0.044). Race/ethnicity and age were considered the most prominent interactive factors that affect the relationship between HDL and glycosylated hemoglobin by the interaction analysis. A U-shaped association was detected between HDL-C and glycosylated hemoglobin for people of other race/ethnicity or aged 60 and above, which had an inflection point of HDL-C at 60 mg/dL. In contrast, we observed an inverted U-shaped distribution between HDL-C and glycosylated hemoglobin in people under 40 with point of inflection located at 60 mg/dL as well.

CONCLUSIONS

HDL-C in diabetic patients is inversely associated with glycosylated hemoglobin and may be relevant to glycemic control. However, a U-shaped relationship was also observed in a certain kind of people, which implied that, though HDL-C is considered as metabolism and anti-atherogenic property, for diabetics, it is not the higher, the better.

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.

Triglyceride to high-density lipoprotein cholesterol ratio variability and incident diabetes: A 7-year prospective study in a Chinese population

AIMS/INTRODUCTION

The correlation between triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio variability and incident diabetes has not been fully elucidated. We aimed to characterize the relationship between TG/HDL-C ratio variability and new-onset diabetes in Chinese adults.

MATERIALS AND METHODS

A total of 45,911 patients with three TG and HDL measurements between 2006 and 2011 were enrolled. Average real variability (ARV) were used to evaluate variability, and participants were grouped according to tertiles of TG/HDL-ARV.

RESULTS

There were 3,724 cases of incident diabetes mellitus during the observation period (6.24 ± 1.2 years). The 7-year cumulative incidences of diabetes mellitus in tertiles 1, 2 and 3 were 6.13%, 8.09% and 11.77%, respectively. New-onset diabetes increased with the tertiles of TG/HDL-ARV. This association was further confirmed after adjustment for mean TG/HDL-C ratio, TG/HDL-C ratio change slope, fasting plasma glucose variability (ARV) and other traditional risk factors for diabetes, the hazard ratio value for incident diabetes was 1.38 (1.25-1.50) for the highest tertile, and risk of diabetes increases by 4% with a one standard deviation increase in TG/HDL-C ratio variability. Restricted cubic splines showed a dose-response relationship between TG/HDL-C ratio variability and incident diabetes. Similar results were obtained in various subgroup and sensitivity analyses.

CONCLUSIONS

High TG/HDL-C variability was associated with a higher risk of diabetes in Chinese adults, independent of the direction of TG/HDL-C variability.

Nonalcoholic fatty liver disease increases the risk of diabetes in young adults: A nationwide population-based study in Korea

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) is associated with an increased risk of diabetes but has been rarely investigated in young adults. In this study, we investigated the relationship between NAFLD and incident diabetes risk in young adults using nationwide Korean population data.

METHODS

This population-based cohort study from the Korean National Health Insurance Service included adults aged 20 through 39 years who underwent a health examination from 2009 to 2012. NAFLD was defined as a fatty liver index (FLI) ≥60 in the absence of alcohol consumption of ≥30 g/day. Newly diagnosed diabetes during follow-up was identified using claims data. Cox regression was used to calculate the hazard ratio for incident diabetes after adjusting for classical confounders.

FINDINGS

Among the 5,254,786 participants, 9.3% had an FLI ≥60. During the median follow-up of 8.6 years, 91,885 cases of incident diabetes occurred. In multivariable analysis, the risk of incident diabetes was significantly higher in the NAFLD group than the control group (adjusted hazard ratio = 4.97, 95% confidence interval, 4.90-5.05). Stratified analyses showed higher associations in those who were ≥30 years, male, obese, smokers, alcohol consumers, and did not regularly exercise (all P < 0.001).

CONCLUSIONS

NAFLD is associated with a five-fold increased risk of incident diabetes in young adults. These results suggest an independent high risk for incident diabetes in young adults and underscore the importance of paying early attention to patients who develop NAFLD before middle age.

High Density Lipoproteins and Diabetes

Epidemiological studies have established that a high plasma high density lipoprotein cholesterol (HDL-C) level is associated with reduced cardiovascular risk. However, recent randomised clinical trials of interventions that increase HDL-C levels have failed to establish a causal basis for this relationship. This has led to a shift in HDL research efforts towards developing strategies that improve the cardioprotective functions of HDLs, rather than simply increasing HDL-C levels. These efforts are also leading to the discovery of novel HDL functions that are unrelated to cardiovascular disease. One of the most recently identified functions of HDLs is their potent antidiabetic properties. The antidiabetic functions of HDLs, and recent key advances in this area are the subject of this review. Given that all forms of diabetes are increasing at an alarming rate globally, there is a clear unmet need to identify and develop new approaches that will complement existing therapies and reduce disease progression as well as reverse established disease. Exploration of a potential role for HDLs and their constituent lipids and apolipoproteins in this area is clearly warranted. This review highlights focus areas that have yet to be investigated and potential strategies for exploiting the antidiabetic functions of HDLs.

Gender differences of relationship between serum lipid indices and type 2 diabetes mellitus: a cross-sectional survey in Chinese elderly adults

Background

To investigate the gender differences of the relationships between clinical serum lipid indices and type 2 diabetes mellitus (T2DM) in Chinese elderly adults.

Methods

Between 2014 and 2016, participants selected from three communities in an urban district of Shanghai were measured for serum lipid indices of low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), total cholesterol (TC), and triglyceride (TG). Age and multivariate adjusted logistic regression models were utilized to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) of serum lipid indices on T2DM prevalence.

Results

In total, 4,023 male and 3,862 female participants were included in this study, with the T2DM prevalence proportions of 13.03% and 11.73%, respectively. In association analysis, the serum levels of LDL-c, HDL-c, TC were significant between non-T2DM individuals and T2DM patients in men, but the HDL-c and TG in women. LDL-c/HDL-c, TG/HDL-c, and TC/HDL-c ratios were associated with the T2DM prevalence only in women. In the multivariate analysis, a higher serum LDL-c level was positively associated with a reduced risk of T2DM prevalence in men with OR (95% CI) of 0.57 (0.39–0.85) (P=0.006). Higher ratios of LDL-c/HDL-c, TG/HDL-c, and TC/HDL-c were all more likely associated with the decreased risks of T2DM prevalence with the ORs ranging from 0.45 to 0.62 in men (all P<0.05), but not in women.

Conclusions

High LDL-c concentration was significantly associated with a lower T2DM prevalence in men. A gender difference of the associations between the lipid ratios and T2DM prevalence was observed for LDL-c/HDL-c and TC/HDL-c ratios, which might be validated in female T2DM prevalence in the future.

Effect of Variability in Blood Pressure, Glucose and Cholesterol Concentrations, and Body Weight on Emergency Hospitalization and 30-Day Mortality in the General Population

Background

Variability in blood pressure, glucose concentration, cholesterol concentration, or body weight is associated with a wide range of health outcomes. We hypothesized that high variability in metabolic parameters is associated with an increased risk of emergency hospitalization and mortality.

Methods and Results

Using a nationally representative database from the Korean National Health Insurance System, 8 049 228 individuals who underwent 3 or more health examinations during 2005 to 2010 were followed up until the end of 2016. Variability in fasting blood glucose and total cholesterol concentrations, systolic blood pressure, and body weight was measured using the variability independent of the mean (VIM). High variability was defined as the highest quartile of variability. Subjects were classified according to the number of high variability parameters. The end points of the study were emergency hospitalization and 30‐day mortality. There were 733 387 emergency hospitalizations (9.1%) during a median follow‐up of 5.6±1.2 years. For each metabolic parameter, an incrementally higher risk of emergency hospitalization was observed for higher VIM quartile groups than for the lowest quartile group. Compared with the group with low variability for all 4 parameters, the group with high variability for all 4 parameters had a significantly higher risk for emergency hospitalization (hazard ratio [HR], 1.58; 95% CI, 1.54–1.61) and 30‐day mortality (HR, 2.44; 95% CI, 1.62–3.69), after adjusting for possible confounding factors.

Conclusions

High variability in metabolic parameters was associated with increased risk of emergency hospitalization and short‐term mortality.

Elevated triglyceride-glucose (TyG) index predicts incidence of Prediabetes: a prospective cohort study in China

BACKGROUND

Prediabetes has become a pandemic. This study aimed to identify a better predictor for the incidence of prediabetes, which we hypothesize to be the triglyceride-glucose (TyG) index, a simplified insulin resistance index. We compared its predictive value with the other common risk factors of prediabetes.

METHODS

The participants of this analysis were derived from the Risk Evaluation of cAncers in Chinese diabeTic Individuals: a lONgitudinal (REACTION) study. A total of 4543 participants without initial prediabetes or diabetes were followed up for 3.25 years. Using multivariate logistic regression model, the associations between baseline obesity, lipid profiles and non-insulin-based insulin resistance indices with the incidence of prediabetes were analyzed. To assess which is better predictor for the incidence of prediabetes, the area under curves (AUCs) calculated from the receiver operating characteristic curve analyses were used to evaluate and compare with the predictive value of the different indices.

RESULTS

During the 3.25 years, 1071 out of the 4543 participants developed prediabetes. Using the logistic regression analysis adjusted for some potential confounders, the risk of incidence of prediabetes increased 1.38 (1.28-1.48) fold for each 1-SD increment of TyG index. The predictive ability (assessed by AUCs) of TyG index for predicting prediabetes was 0.60 (0.58-0.62), which was superior to the indices of obesity, lipid profiles and other non-insulin-based insulin resistance indices. Although the predictive ability of the TyG index was overall similar to fasting plasma glucose (FPG) (P = 0.4340), TyG index trended higher than FPG in females (0.62 (0.59-0.64) vs. 0.59 (0.57-0.61), P = 0.0872) and obese subjects (0.59 (0.57-0.62) vs. 0.57 (0.54-0.59), P = 0.1313). TyG index had superior predictive ability for the prediabetic phenotype with isolated impaired glucose tolerance compared with FPG (P <  0.05) and other indices. Furthermore, TyG index significantly improved the C statistic (0.62 (0.60-0.64)), integrated discrimination improvement (1.89% (1.44-2.33%)) and net reclassification index (28.76% (21.84-35.67%)) of conventional model in predicting prediabetes than other indices.

CONCLUSIONS

TyG could be a potential predictor to identify the high risk individuals of prediabetes.

Effects of Cardiovascular Risk Factor Variability on Health Outcomes

Innumerable studies have suggested "the lower, the better" for cardiovascular risk factors, such as body weight, lipid profile, blood pressure, and blood glucose, in terms of health outcomes. However, excessively low levels of these parameters cause health problems, as seen in cachexia, hypoglycemia, and hypotension. Body weight fluctuation is related to mortality, diabetes, obesity, cardiovascular disease, and cancer, although contradictory findings have been reported. High lipid variability is associated with increased mortality and elevated risks of cardiovascular disease, diabetes, end-stage renal disease, and dementia. High blood pressure variability is associated with increased mortality, myocardial infarction, hospitalization, and dementia, which may be caused by hypotension. Furthermore, high glucose variability, which can be measured by continuous glucose monitoring systems or self-monitoring of blood glucose levels, is associated with increased mortality, microvascular and macrovascular complications of diabetes, and hypoglycemic events, leading to hospitalization. Variability in metabolic parameters could be affected by medications, such as statins, antihypertensives, and hypoglycemic agents, and changes in lifestyle patterns. However, other mechanisms modify the relationships between biological variability and various health outcomes. In this study, we review recent evidence regarding the role of variability in metabolic parameters and discuss the clinical implications of these findings.

A nomogram for predicting 5-year incidence of type 2 diabetes in a Chinese population

PURPOSE

To develop a nomogram for predicting 5-year incidence of type 2 diabetes (T2D) in Chinese adults.

METHODS

This is a retrospective cohort study from a prospectively collected database. We included a total 32,766 adults free of T2D at baseline with a median follow-up of 3 years. Univariate and multivariate Cox regression analyses were applied to identify independent predictors. A nomogram was constructed to predict 5-year incident rate of T2D based on the multivariate analysis results. Harrell's C-indexes and calibration plots were used to evaluate the accuracy of the nomogram in both internal and external validations.

RESULTS

The overall prevalence of T2D was 2.1%. Participants were randomly divided into a training set (n = 21,844) and a validation set (n = 10,922). After multivariate analysis in the training set, age, sex, BMI, hypertension, dyslipidemia, smoking status, and family history were found as risk predictors and integrated into the nomogram. Harrell's C-indexes were 0.815 (95% CI: 0.797-0.834) and 0.779 (95% CI: 0.747-0.811) in the training and validation sets, respectively. The calibration plots demonstrated good agreement between the estimated probability and the actual observation.

CONCLUSION

Our nomogram could be a simple and reliable tool for predicting 5-year risk of developing T2D in high-risk Chinese. Through the model, early identifying high-risk individuals is helpful for timely intervention to reduce the incidence of T2D.