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Aims/hypothesis: Both short and long sleep durations have been linked to higher diabetes risk. However, sleep duration may vary over time, and there has been limited research focusing on individual sleep trajectories and diabetes risk. There are substantial racial disparities in both sleep health and diabetes risk in the USA. Thus, it is important to understand the role of suboptimal sleep patterns in diabetes risk in different racial groups. Methods: We assessed long-term trajectories of sleep duration and incident diabetes in 22,285 Black adults (mean age ± SD, 51.1 ± 8.2 years; 64.8% women) and 13,737 White adults (mean age ± SD, 54.4 ± 9.0 years; 63.8% women) enrolled in the Southern Community Cohort Study. Nine sleep trajectories were derived based on self-reported sleep duration at baseline and after a mean of 5 years of follow-up: normal–normal (reference), short–normal, normal–short, short–short, long–normal, normal–long, long–long, long–short and short–long. Diabetes was reported using a validated questionnaire. Multivariable-adjusted logistic regression was used to determine relationships between sleep trajectories and incident diabetes. Results: When compared with the normal–normal trajectory, suboptimal sleep trajectories were associated with higher likelihoods of developing diabetes (OR; 95% CI: short–normal 1.19; 1.09, 1.31; normal–short 1.14; 1.02, 1.27; short–short 1.17; 1.07, 1.28; long–normal 1.13; 0.98, 1.30; normal–long 1.16; 1.00, 1.34; long–long 1.23; 1.02, 1.48; long–short 1.45; 1.19, 1.77; short–long 1.51; 1.28, 1.77). Stratified analyses by race and socioeconomic status (i.e. education and household income) showed that most suboptimal sleep trajectories were consistently associated with incident diabetes in all sociodemographic subgroups. We also noted potential interaction with race and education for several sleep trajectories (i.e. short–long and normal–short with race; long–long and short–short with education). Conclusions/interpretation: Adults with suboptimal sleep duration trajectories are more likely to develop incident diabetes. Future research is needed to study how sociodemographic factors modulate this relationship. [ABSTRACT FROM AUTHOR]

Abstract Background The molecular pathways linking short and long sleep duration with incident diabetes mellitus (iDM) and incident coronary heart disease (iCHD) are not known. We aimed to identify circulating protein patterns associated with sleep duration and test their impact on incident cardiometabolic disease. Methods We assessed sleep duration and measured 78 plasma proteins among 3336 participants aged 46–68 years, free from DM and CHD at baseline, and identified cases of iDM and iCHD using national registers. Incident events occurring in the first 3 years of follow-up were excluded from analyses. Tenfold cross-fit partialing-out lasso logistic regression adjusted for age and sex was used to identify proteins that significantly predicted sleep duration quintiles when compared with the referent quintile 3 (Q3). Predictive proteins were weighted and combined into proteomic scores (PS) for sleep duration Q1, Q2, Q4, and Q5. Combinations of PS were included in a linear regression model to identify the best predictors of habitual sleep duration. Cox proportional hazards regression models with sleep duration quintiles and sleep-predictive PS as the main exposures were related to iDM and iCHD after adjustment for known covariates. Results Sixteen unique proteomic markers, predominantly reflecting inflammation and apoptosis, predicted sleep duration quintiles. The combination of PSQ1 and PSQ5 best predicted sleep duration. Mean follow-up times for iDM (n = 522) and iCHD (n = 411) were 21.8 and 22.4 years, respectively. Compared with sleep duration Q3, all sleep duration quintiles were positively and significantly associated with iDM. Only sleep duration Q1 was positively and significantly associated with iCHD. Inclusion of PSQ1 and PSQ5 abrogated the association between sleep duration Q1 and iDM. Moreover, PSQ1 was significantly associated with iDM (HR = 1.27, 95% CI: 1.06–1.53). PSQ1 and PSQ5 were not associated with iCHD and did not markedly attenuate the association between sleep duration Q1 with iCHD. Conclusions We here identify plasma proteomic fingerprints of sleep duration and suggest that PSQ1 could explain the association between very short sleep duration and incident DM.

Background: The molecular pathways linking short and long sleep duration with incident diabetes mellitus (iDM) and incident coronary heart disease (iCHD) are not known. We aimed to identify circulating protein patterns associated with sleep duration and test their impact on incident cardiometabolic disease. Methods: We assessed sleep duration and measured 78 plasma proteins among 3336 participants aged 46–68 years, free from DM and CHD at baseline, and identified cases of iDM and iCHD using national registers. Incident events occurring in the first 3 years of follow-up were excluded from analyses. Tenfold cross-fit partialing-out lasso logistic regression adjusted for age and sex was used to identify proteins that significantly predicted sleep duration quintiles when compared with the referent quintile 3 (Q3). Predictive proteins were weighted and combined into proteomic scores (PS) for sleep duration Q1, Q2, Q4, and Q5. Combinations of PS were included in a linear regression model to identify the best predictors of habitual sleep duration. Cox proportional hazards regression models with sleep duration quintiles and sleep-predictive PS as the main exposures were related to iDM and iCHD after adjustment for known covariates. Results: Sixteen unique proteomic markers, predominantly reflecting inflammation and apoptosis, predicted sleep duration quintiles. The combination of PSQ1 and PSQ5 best predicted sleep duration. Mean follow-up times for iDM (n = 522) and iCHD (n = 411) were 21.8 and 22.4 years, respectively. Compared with sleep duration Q3, all sleep duration quintiles were positively and significantly associated with iDM. Only sleep duration Q1 was positively and significantly associated with iCHD. Inclusion of PSQ1 and PSQ5 abrogated the association between sleep duration Q1 and iDM. Moreover, PSQ1 was significantly associated with iDM (HR = 1.27, 95% CI: 1.06–1.53). PSQ1 and PSQ5 were not associated with iCHD and did not markedly attenuate the association between sleep duration Q1 with iCHD. Conclusions: We here identify plasma proteomic fingerprints of sleep duration and suggest that PSQ1 could explain the association between very short sleep duration and incident DM. [ABSTRACT FROM AUTHOR]

Summary: Background: Evidence suggests an increased risk of new-onset diabetes following COVID-19 infection. American Indian/Alaska Native (AI/AN) people were disparately impacted by the COVID-19 pandemic and historically have had higher diabetes incidence than other racial/ethnic groups in the US. We measured the association between COVID-19 infection and incident diabetes in AI/AN people. Methods: We conducted a retrospective cohort study using de-identified patient data from the Indian Health Service's (IHS) National Patient Information Reporting System. We estimated age-adjusted diabetes incidence rates, incidence rate ratios, and adjusted hazard ratios among three cohorts spanning pre-pandemic (1/1/2018–2/28/2020) and pandemic (3/1/2020–12/31/2021) timeframes: 1) pre-pandemic cohort (1,503,085 individuals); 2) no-COVID-19 pandemic cohort (1,344,339 individuals); and 3) COVID-19 cohort (176,483 individuals). Findings: The COVID-19 cohort had an increased hazard of diabetes compared to the no-COVID-19 group (adjusted hazard ratio (aHR) = 1.56; 95% CI: 1.50–1.62) and the pre-pandemic group (aHR = 1.27; 95% CI: 1.22–1.32). The association between COVID-19 infection and new-onset diabetes was stronger in those with severe COVID-19 illness. A sensitivity analysis comparing the COVID-19 cohort to members of other cohorts that had acute upper respiratory infections showed an attenuated but higher risk of new-onset diabetes in those with COVID-19. Interpretation: AI/AN people diagnosed with COVID-19 had an elevated risk of a new diabetes diagnosis when compared to the no-COVID-19 group and the pre-pandemic group. The increased diabetes risk in the COVID-19 group remained in a sensitivity analysis that limited the comparator groups to individuals with an AURI diagnosis. Funding: US National Institute of Diabetes and Digestive and Kidney Diseases.

Abstract Background According to research, the fatty liver index (FLI) is associated with diabetes. However, few studies have been conducted to investigate the relationship between FLI and diabetes risk from various perspectives. This study comprehensively investigated the relationship between FLI and incident diabetes in a large Japanese population. Methods This retrospective cohort study included 14,280 participants from Murakami Memorial Hospital in Japan from 2004 to 2015. The independent and dependent variables are FLI and risk of type 2 diabetes mellitus (T2DM), respectively. To examine the link between FLI and incident T2DM, Cox proportional-hazards regression was employed. In addition, we performed a number of sensitivity studies to guarantee the validity of the results. Moreover, we conducted subgroup analyses. Results After adjusting covariates, the results showed that FLI was positively associated with the risk of T2DM (HR = 1.019, 95%CI: 1.012, 1.025). Additionally, the sensitivity analysis showed how reliable the outcomes were. And a stronger association between FLI and incident T2DM was observed in the regular exercisers (HR = 1.036, 95%CI: 1.019–1.053, P

Purpose of Review: Multiple studies report an increased incidence of diabetes following SARS-CoV-2 infection. Given the potential increased global burden of diabetes, understanding the effect of SARS-CoV-2 in the epidemiology of diabetes is important. Our aim was to review the evidence pertaining to the risk of incident diabetes after COVID-19 infection. Recent Findings: Incident diabetes risk increased by approximately 60% compared to patients without SARS-CoV-2 infection. Risk also increased compared to non-COVID-19 respiratory infections, suggesting SARS-CoV-2-mediated mechanisms rather than general morbidity after respiratory illness. Evidence is mixed regarding the association between SARS-CoV-2 infection and T1D. SARS-CoV-2 infection is associated with an elevated risk of T2D, but it is unclear whether the incident diabetes is persistent over time or differs in severity over time. Summary: SARS-CoV-2 infection is associated with an increased risk of incident diabetes. Future studies should evaluate vaccination, viral variant, and patient- and treatment-related factors that influence risk. [ABSTRACT FROM AUTHOR]

IntroductionMarijuana use is common among persons living with HIV, but whether it's use increases the risk of type 2 diabetes in this population has not been explored.ObjectiveTo determine whether self-reported marijuana use is associated with incident type 2 diabetes in women and men living with and at risk for HIV.MethodsWe analyzed data from the Women's Interagency HIV Study (WIHS) and Multicenter AIDS Cohort Study (MACS), between 2000-2017 (WIHS) and 1999-2017 MACS. The association between self-reported marijuana use and incident type 2 diabetes was analyzed using time-dependent Cox regression models among 3578 and 2682 participants in the WIHS and MACS respectively.ResultsOver the follow-up period, 452 (WIHS) and 326 (MACS) incident type 2 diabetes cases occurred. In multivariable models, the hazard ratios, collectively indicate a reduced risk of type 2 diabetes, in marijuana users compared to none users, although all associations were not statistically significant. The results were similar for HIV-positive and HIV-negative participants in both cohorts.ConclusionsIn this prospective analysis of nearly 20 years of data for women and men with and at risk for HIV in the WIHS and MACS, although we found a pattern of reduced risk of type 2 diabetes among self-reported marijuana users, the associations were not statistically significant. To better inform clinical decisions and legal policy regarding marijuana use in this population, further longitudinal investigations that biologically quantify marijuana use to assess risk for incident diabetes is warranted.

Abstract Background Diabetes Mellitus (DM) is a fast-growing health problem that imposes an enormous economic burden. Several studies demonstrated the association between physical inactivity and predicting the incidence of diabetes. However, these prediction models have limited validation locally. Therefore, we aim to explore the predictive value of exercise capacity in the incidence of diabetes within a high diabetes prevalence population. Methodology A retrospective cohort study including consecutive patients free of diabetes who underwent clinically indicated treadmill stress testing. Diabetic patients at baseline or patients younger than 18 years of age were excluded. Incident diabetes was defined as an established clinical diagnosis post-exercise testing date. The predictive value of exercise capacity was examined using Harrell’s c-index, net reclassification index (NRI), and integrated discrimination index (IDI). Results A total of 8,722 participants (mean age 46 ± 12 years, 66.3% were men) were free of diabetes at baseline. Over a median follow-up period of 5.24 (2.17–8.78) years, there were 2,280 (≈ 26%) new cases of diabetes. In a multivariate model adjusted for conventional risk factors, we found a 12% reduction in the risk of incident diabetes for each METs achieved (HR, 0.9; 95% CI, 0.88–0.92; P

Abstract Background The endocrine disruption of perfluorinated compounds is an emerging issue. We aimed to examine the association of serum perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) levels with incident diabetes and fasting serum glucose concentration. Methods This prospective cohort study was based on an urban-based cohort subpopulation from the Korean Genome and Epidemiology Study. Serum samples (600 µL) were received from 100 participants in the normoglycemic baseline survey (2004–2013), and concentrations of PFOA and PFOS were measured using mass spectrometry. The incidence of diabetes was tracked in the follow-up survey (2012–2016). Results The mean age was 56.4 years (men, 59%). The median serum PFOA and PFOS concentrations were 4.29 ng/mL and 9.44 ng/mL, respectively. PFOA and PFOS concentrations differed according to age, sex, and residential area. After 60 months, 23 patients had diabetes. Log-transformed PFOA (lnPFOA) and log-transformed PFOS (lnPFOS) were significantly higher in those who transitioned to diabetes than in those who did not (both p

Background & aims: The effect of change in non-alcoholic fatty liver disease (NAFLD) status on incident diabetes has not been well studied. We aimed to investigate the association of NAFLD development and remission with the risk of incident diabetes during a median of 3.5-year follow-up. Methods: A total of 2690 participants without diabetes were recruited in 2011-2012 and assessed for incident diabetes in 2014. Abdominal ultrasonography was used to determine the change of NAFLD. 75 g oral glucose tolerance test (OGTT) was performed to determine diabetes. NAFLD severity was assessed using Gholam's model. The odds ratios (ORs) for incident diabetes were estimated by logistic regression models. Results: NAFLD was developed in 580 (33.2%) participants and NAFLD remission occurred in 150 (15.9%) participants during a median of 3.5-year follow-up. A total of 484 participants developed diabetes during follow-up, including 170 (14.6%) in consistent non-NAFLD group, 111 (19.1%) in NAFLD developed group, 19 (12.7%) in NAFLD remission group, and 184 (23.2%) in sustained NAFLD group. The development of NAFLD increased the risk of incident diabetes by 43% (OR, 1.43; 95%CI, 1.10-1.86) after adjustment for multiple confounders. Compared with sustained NAFLD group, remission of NAFLD reduced the risk of incident diabetes by 52% (OR, 0.48; 95%CI, 0.29-0.80). The effect of NAFLD alteration on incident diabetes was not changed after adjustment for body mass index or waist circumference, change of body mass index or waist circumference. In NAFLD remission group, participants with non-alcoholic steatohepatitis (NASH) at baseline were more likely to develop diabetes (OR, 3.03; 95%CI, 1.01-9.12). Conclusions: NAFLD development increases the risk of incident diabetes, whereas NAFLD remission reduces the risk of incident diabetes. Moreover, presence of NASH at baseline could attenuate the protective effect of NAFLD remission on incident diabetes. Our study suggests that early intervention of NAFLD and maintenance of non-NAFLD are important for prevention of diabetes. [ABSTRACT FROM AUTHOR]

Background: According to research, the fatty liver index (FLI) is associated with diabetes. However, few studies have been conducted to investigate the relationship between FLI and diabetes risk from various perspectives. This study comprehensively investigated the relationship between FLI and incident diabetes in a large Japanese population. Methods: This retrospective cohort study included 14,280 participants from Murakami Memorial Hospital in Japan from 2004 to 2015. The independent and dependent variables are FLI and risk of type 2 diabetes mellitus (T2DM), respectively. To examine the link between FLI and incident T2DM, Cox proportional-hazards regression was employed. In addition, we performed a number of sensitivity studies to guarantee the validity of the results. Moreover, we conducted subgroup analyses. Results: After adjusting covariates, the results showed that FLI was positively associated with the risk of T2DM (HR = 1.019, 95%CI: 1.012, 1.025). Additionally, the sensitivity analysis showed how reliable the outcomes were. And a stronger association between FLI and incident T2DM was observed in the regular exercisers (HR = 1.036, 95%CI: 1.019–1.053, P < 0.0001) and the population without ethanol consumption (HR = 1.028, 95%CI: 1.017–1.039, P < 0.0001). Besides, receiver operating characteristic (ROC) curve analysis showed that FLI was better than waist circumference, triglycerides, body mass index, and gamma-glutamyl transferase in predicting incident T2DM. Conclusion: FLI is positively associated with incident T2DM. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

BackgroundThe Metabolic score of insulin resistance (METS-IR) has recently been accepted as a reliable alternative to insulin resistance (IR), which was demonstrated to be consistent with the hyperinsulinemic-euglycemic clamp. Few pieces of research have focused on the relationship between METS-IR and diabetes in Chinese. The purpose of this research was to explore the effect of METS-IR on new-onset diabetes in a large multicenter Chinese study.MethodsAt the baseline of this retrospective longitudinal research, 116855 participators were included in the Chinese cohort study administered from 2010 to 2016. The subjects were stratified by quartiles of METS-IR. To assess the effect of METS-IR on incident diabetes, the Cox regression model was constructed in this study. Stratification analysis and interaction tests were applied to detect the potential effect of METS-IR and incident diabetes among multiple subgroups. To verify whether there was a dose-response relationship between METS-IR and diabetes, a smooth curve fitting was performed. In addition, to further determine the performance of METS -IR in predicting incident diabetes, the receiver operating characteristic curve (ROC) was conducted.ResultsThe average age of the research participators was 44.08 ± 12.93 years, and 62868 (53.8%) were men. METS-IR were significant relationship with new-onset diabetes after adjusting for possible variables (Hazard ratio [HR]: 1.077; 95% confidence interval [CI]: 1.073-1.082, P < 0.0001), the onset risk for diabetes in Quartile 4 group was 6.261-fold higher than those in Quartile 1 group. Moreover, stratified analyses and interaction tests showed that interaction was detected in the subgroup of age, body mass index, systolic blood pressure, diastolic blood pressure, and fasting plasma glucose, there was no significant interaction between males and females. Furthermore, a dose-response correlation was detected between METS-IR and incident diabetes, the nonlinear relationship was revealed and the inflection point of METS-IR was calculated to be 44.43. When METS-IR≥44.43, compared with METS-IR < 44.43, the trend was gradually saturated, with log-likelihood ratio test P < 0.001. Additionally, the area under receiver operating characteristic of the METS-IR in predicting incident diabetes was 0.729, 0.718, and 0.720 at 3, 4, and 5 years, respectively.ConclusionsMETS-IR was correlated with incident diabetes significantly, and showed a nonlinear relationship. This study also found that METS-IR had good discrimination of diabetes.

Background: Diabetes Mellitus (DM) is a fast-growing health problem that imposes an enormous economic burden. Several studies demonstrated the association between physical inactivity and predicting the incidence of diabetes. However, these prediction models have limited validation locally. Therefore, we aim to explore the predictive value of exercise capacity in the incidence of diabetes within a high diabetes prevalence population. Methodology: A retrospective cohort study including consecutive patients free of diabetes who underwent clinically indicated treadmill stress testing. Diabetic patients at baseline or patients younger than 18 years of age were excluded. Incident diabetes was defined as an established clinical diagnosis post-exercise testing date. The predictive value of exercise capacity was examined using Harrell's c-index, net reclassification index (NRI), and integrated discrimination index (IDI). Results: A total of 8,722 participants (mean age 46 ± 12 years, 66.3% were men) were free of diabetes at baseline. Over a median follow-up period of 5.24 (2.17–8.78) years, there were 2,280 (≈ 26%) new cases of diabetes. In a multivariate model adjusted for conventional risk factors, we found a 12% reduction in the risk of incident diabetes for each METs achieved (HR, 0.9; 95% CI, 0.88–0.92; P < 0.001). Using Cox regression, exercise capacity improved the prediction ability beyond the conventional risk factors (AUC = 0.62 to 0.66 and c-index = 0.62 to 0.68). Conclusion: Exercise capacity improved the overall predictability of diabetes. Patients with reduced exercise capacity are at high risk for developing incidence diabetes. Improvement of both physical activity and functional capacity represents a preventive measure for the general population. [ABSTRACT FROM AUTHOR]

Low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, and LDL/HDL ratio have been associated with new-onset diabetes; however, their cut-off levels have not been determined. We clarified the association between dyslipidemia and the incidence of diabetes. People who underwent a health checkup under a program conducted by Panasonic Corporation from 2008 to 2018 were included. In total, 87,570 participants were included, of whom 5,110 developed type 2 diabetes. Cox regression analyses and time-dependent receiver operating characteristic (ROC) curves were used to evaluate the association between LDL cholesterol, HDL cholesterol, or LDL/HDL ratio and incident diabetes and to identify the cut-off values for incident diabetes. Multivariate analysis showed that LDL cholesterol, HDL cholesterol, and LDL/HDL ratio were significantly associated with the risk of incident type 2 diabetes. Further, the area under the ROC curve and optimized cut-off values for LDL cholesterol, HDL cholesterol, and LDL/HDL ratio for incident type 2 diabetes at 10 years were 0.613 and 124 mg/dl, 0.640 and 54 mg/dl, and 0.662 and 2.4 mg/dl, respectively. The LDL/HDL ratio with a cut-off value of 2.4 was a better predictor of incident diabetes within 10 years than LDL and HDL cholesterol. [ABSTRACT FROM AUTHOR]

• We have developed a simple model for T2DM prediction based on basic parameters. • Higher FPG levels represent greater risk of incident T2DM in the next years. In intermediate FPG values, age determines T2DM risk and BMI in a second step. • In individuals with lower FPG, higher FTGs increases risk of developing T2DM. The present model correctly classified 93.5% of individuals. To develop a simple multivariate predictor model of incident type 2 diabetes in general population. Participants were recruited from the Spanish Di@bet.es cohort study with 2570 subjects meeting all criteria to be included in the at-risk sample studied here. Information was collected using an interviewer-administered structured questionnaire, followed by physical and clinical examination. CHAID algorithm, which collects the information of individuals with and without type 2 diabetes, was used to develop a decision tree based type 2 diabetes prediction model. 156 individuals were identified as having developed type 2 diabetes (6.5% incidence). Fasting plasma glucose (FPG) at the beginning of the study was the main predictive variable for incident type 2 diabetes: FPG ≤ 92 mg/dL (ref.), 92–106 mg/dL (OR = 3.76, 95%CI = 2.36–6.00), > 106 mg/dL (OR = 13.21; 8.26–21.12). More than 25% of subjects starting follow-up with FPG levels > 106 mg/dL developed type 2 diabetes. When FPG <106 mg/dL, other variables (fasting triglycerides (FTGs), BMI or age) were needed. For levels ≤ 92 mg/dL, higher FTGs levels increased risk of incident type 2 diabetes (FTGs > 180 mg/dL, OR = 14.57; 4.89–43.40) compared with the group of FTGs ≤ 97 mg/dL (FTGs = 97–180 mg/dL, OR = 3.12; 1.05–9.24). This model correctly classified 93.5% of individuals. The type 2 diabetes prediction model is based on FTGs, FPG, age, gender, and BMI values. Utilizing commonly available clinical data and a simple blood test, a simple tree diagram helps identify subjects at risk of developing type 2 diabetes, even in apparently low risk subjects with normal FPG. [ABSTRACT FROM AUTHOR]

Identifying people with a high risk of developing diabetes among those with prediabetes may facilitate the implementation of a targeted lifestyle and pharmacological interventions. We aimed to establish machine learning models based on demographic and clinical characteristics to predict the risk of incident diabetes. We used data from the free medical examination service project for elderly people who were 65 years or older to develop logistic regression (LR), decision tree (DT), random forest (RF), and extreme gradient boosting (XGBoost) machine learning models for the follow-up results of 2019 and 2020 and performed internal validation. The receiver operating characteristic (ROC), sensitivity, specificity, accuracy, and F1 score were used to select the model with better performance. The average annual progression rate to diabetes in prediabetic elderly people was 14.21%. Each model was trained using eight features and one outcome variable from 9607 prediabetic individuals, and the performance of the models was assessed in 2402 prediabetes patients. The predictive ability of four models in the first year was better than in the second year. The XGBoost model performed relatively efficiently (ROC: 0.6742 for 2019 and 0.6707 for 2020). We established and compared four machine learning models to predict the risk of progression from prediabetes to diabetes. Although there was little difference in the performance of the four models, the XGBoost model had a relatively good ROC value, which might perform well in future exploration in this field. [ABSTRACT FROM AUTHOR]

We assessed the nearly 1-year health consequences following discharge and related risk factors of COVID-19 infection and further explored the long-term effect of COVID-19 disease severity on the risk of diabetes incidence. This prospective study included 248 COVID-19 patients discharged from Wuhan Hospital of Traditional Chinese Medicine who were followed up between 1 March and 10 June 2021. Logistic regression models were used to evaluate risk factors. The top ten symptoms were shortness of breath (30.3%), sore or dry throat (25.7%), cough (23.2%), expectoration (23.2%), body pain (22.3%), chest tightness (20.8%), palpitations (17.8%), sleep difficulties (17.0%), fatigue (16.6%), and anxiety (15.3%). Hypertension was associated with fatigue (OR = 2.51, 95% CI: 1.08, 5.80), shortness of breath (OR = 2.34, 95% CI: 1.16, 4.69), palpitations (OR = 2.82, 95% CI: 1.26, 6.31), expectoration (OR = 2.08, 95% CI: 1.01, 4.30), and sore or dry throat (OR = 2.71, 95% CI: 1.30, 5.65). Diabetes was associated with palpitations (OR = 3.22, 95% CI: 1.18, 8.81). Critical illness was associated with an increased risk of diabetes incidence after discharge (OR = 2.90, 95% CI: 1.07, 7.88), which seemed more evident in males. Long COVID-19 symptoms were common at 1-year postdischarge; hypertension and diabetes could be projected as potential risk factors. We are among the first researchers to find that critical illness is associated with incident diabetes after discharge. [ABSTRACT FROM AUTHOR]

Objective:The general public recognizes the connections between obesity, family history of diabetes (FHD), and diabetes, but remains unaware of synergistic effects that occur due to their combination. In this study, we investigate the synergistic effects of event diabetes between snoring, FHD, and obesity.Materials and Methods:Study subjects were selected among participants in the Korean Genome and Epidemiology Study Ansan- Ansung cohort, an ongoing prospective population-based study. Ansan-Ansung cohort initiated in 2001 and 2002 and has been followed biennially. At baseline, the initial cohort of 10.030 subjects, aged 40 to 69 years. A total of 5.759 participants were included in this study. The relationships between diabetes and snoring, FHD, and obesity were estimated using Cox hazard regression models after adjusting for confounding factors. Snoring, obesity and FHD were significantly associated with diabetes in both males and females after adjustments for covariates. However, males were significantly more likely to have FHD and obesity.Results:A synergistic effect between these two risk factors showed that being female was associated with the all group after adjustment for covariates. Moreover, there was a high risk of having two risk factors among female patients, while males showed no such tendency. A significant synergistic effect between these three risk factors was seen in females. An exposure group with these three factors had higher diabetes risk than other groups [hazard ratio (HR): 6.27 (95% confidence interval (CI): 2.93-13.41] p

Abstract Background Reliable quantification of the relationship between hypertension and diabetes risk is limited, especially among Chinese people. We aimed to investigate the association between hypertension and the risk of diabetes in a large cohort of the Chinese population. Methods This was a retrospective propensity score-matched cohort study among 211,809 Chinese adults without diabetes at baseline between 2010 and 2016. The target independent and dependent variable were hypertension at baseline and incident diabetes during follow-up respectively. The propensity score matching using a non-parsimonious multivariable logistic regression was conducted to balance the confounders between 28,711 hypertensive patients and 28,711 non-hypertensive participants. The doubly robust estimation method was used to investigate the association between hypertension and diabetes. Results In the propensity-score matching cohort, diabetes risk increased by 11.0% among hypertensive patients (HR = 1.110, 95% confidence interval (CI): 1.031–1.195, P = 0.00539). And diabetes risk dropped to 8.3% among hypertensive subjects after adjusting for the propensity score (HR = 1.083, 95%CI: 1.006–1.166, P = 0.03367). Compared to non-hypertensive participants with low propensity score, the risk of incident diabetes increased by 2.646 times among hypertensive patients with high propensity score (HR = 3.646, 95%CI: 2.635–5.045, P

Background: Studies have reported an association between prevalent cardiovascular disease (CVD) and risk of diabetes mellitus (DM). However, factors that may explain the association remain unclear. We examined the association of prevalent CVD with incident DM and assessed whether weight gain and medication use may explain the association. Methods: Data from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) Visit 1 (2008‐2011) and Visit 2 (2014‐2017) were used to compare incidence of DM among individuals with and without self‐reported CVD at Visit 1. A total of 1899 individuals with self‐reported CVD were matched to controls free of self‐reported CVD at Visit 1 using 1:1 propensity score matching. Covariates included in the propensity model were sociodemographic characteristics, lifestyle factors, comorbid conditions, and study site. The effect of self‐reported CVD on incident DM was examined using a generalized estimating equation. The mediating effects of weight gain and use of cardiovascular medications were evaluated. Results: Covariate distributions were similar among individuals with and without self‐reported CVD. The incidence of DM among persons with self‐reported CVD was 15.3% vs 12.7% among those without self‐reported CVD. Compared to individuals without self‐reported CVD, individuals with self‐reported CVD had a 24% increased risk for incident DM (odds ratio = 1.24, 95% confidence interval = 1.01, 1.51). The association between self‐reported CVD and DM was mediated by the use of beta‐blockers (proportion explained = 25.4%), statins (proportion explained = 18%), and diuretics (proportion explained = 8%). We found that weight gain did not explain the observed association. Conclusions: Prevalent cardiovascular disease was associated with a significant increased risk of incident diabetes. The observed association was partially explained by some medications used to manage CVD. [ABSTRACT FROM AUTHOR]

Type 2 diabetes (T2D) is associated with reduced gut microbiome diversity, although the cause is unclear. Metabolites generated by gut microbes also appear to be causative factors in T2D. We therefore searched for serum metabolites predictive of gut microbiome diversity in 1018 females from TwinsUK with concurrent metabolomic profiling and microbiome composition. We generated a Microbial Metabolites Diversity (MMD) score of six circulating metabolites that explained over 18% of the variance in microbiome alpha diversity. Moreover, the MMD score was associated with a significantly lower odds of prevalent (OR[95%CI] = 0.22[0.07;0.70], P = .01) and incident T2D (HR[95%CI] = 0.31[0.11,0.90], P = .03). We replicated our results in 1522 individuals from the ARIC study (prevalent T2D: OR[95%CI] = 0.79[0.64,0.96], P = .02, incident T2D: HR[95%CI] = 0.87[0.79,0.95], P = .003). The MMD score mediated 28%[15%,94%] of the total effect of gut microbiome on T2D after adjusting for confounders. Metabolites predicting higher microbiome diversity included 3-phenylpropionate(hydrocinnamate), indolepropionate, cinnamoylglycine and 5-alpha-pregnan-3beta,20 alpha-diol monosulfate(2) of which indolepropionate and phenylpropionate have already been linked to lower incidence of T2D. Metabolites correlating with lower microbial diversity included glutarate and imidazole propionate, of which the latter has been implicated in insulin resistance. Our results suggest that the effect of gut microbiome diversity on T2D is largely mediated by microbial metabolites, which might be modifiable by diet.

Abstract Background Recent studies have suggested the triglyceride-glucose index (TyG index) may serve as a suitable substitute for insulin resistance. However, evidence for the relationship between TyG index and risk of diabetes remains limited. This study sought to explore the association of baseline TyG index with risk of developing diabetes in Chinese adults. Methods This retrospective cohort study was conducted using data from the health screening program in China. A total of 201,298 non-diabetic individuals were included. TyG index was calculated as Ln [fasting plasma glucose (mg/dL) × fasting triglyceride level (mg/dL) / 2]. Diabetes was defined as fasting plasma glucose ≥126 mg/dL and/or self-reported diabetes. Cox proportion-hazard model was employed to evaluate the independent impact of baseline TyG index on future diabetes risk. Sensitivity and subgroup analyses were implemented to verify the reliability of results. Notably, data were downloaded from the DATADRYAD website, and used only for secondary analyses. Results During an average follow-up of 3.12 years, among 201,298 individuals aged ≥20 years, 3389 subjects developed diabetes. After adjusting for potential confounders, elevated TyG index were independently correlated with greater risk of incident diabetes (hazard ratio (HR), 3.34; 95% confidence interval (CI), 3.11–3.60). Compared with the lowest quartile (Q1), increasing TyG index (Q2, Q3, and Q4) was related to increased HR estimates of incident diabetes [HR (95% CI), 1.83 (1.49–2.26); 3.29 (2.70–4.01), and 6.26 (5.15–7.60), respectively]. Moreover, a nonlinear relationship was observed between TyG index and risk of diabetes and the slope of the curve increased accompanying the rise of TyG index. Subgroup analysis revealed the positive association was stronger among subjects with age

Abstract Background Previous studies have revealed that triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C) is one of major risk factors of insulin resistance and diabetes. However, study on the association between TG/HDL-C and diabetes mellitus (DM) risk is limited, especially in Chinese people. This study was undertaken to investigate the relationship between TG/HDL-C and incident of diabetes in a large cohort in Chinese population. Methods The present study was a retrospective cohort study. A total of 114,787 adults from Rich Healthcare Group in China, which includes all medical records for participants who received a health check from 2010 to 2016. The target independent variable and the dependent variable were triglyceride to high-density lipoprotein cholesterol ratio measured at baseline and incident of diabetes mellitus appeared during follow-up respectively. Covariates involved in this study included age, gender, body mass index, diastolic blood pressure, systolic blood pressure, fasting plasma glucose, total cholesterol, low density lipoprotein cholesterol, serum creatinine, smoking and drinking status and family history of diabetes. Cox proportional-hazards regression was used to investigate the association of TG/HDL-C and diabetes. Generalized additive models was used to identify non-linear relationships. Additionally, we also performed a subgroup analysis. It was stated that the data had been uploaded to the DATADRYAD website. Result After adjusting age, gender, body mass index, systolic blood pressure, diastolic blood pressure, fasting blood glucose, total cholesterol, low density lipoprotein cholesterol, serum creatinine, smoking and drinking status and family history of diabetes, result showed TG/HDL-C was positively associated with incident of diabetes mellitus (HR = 1.159, 95%CI (1.104, 1.215)). A non-linear relationship was detected between TG/HDL-C and incident of diabetes, which had an inflection point of TG/HDL-C was 1.186. The effect sizes and the confidence intervals on the left and right sides of the inflection point were 1.718(1.433,2.060) and 1.049(0.981,1.120), respectively. Subgroup analysis showed, the stronger association can be found in the population with fasting plasma glucose (FPG)

Abstract Aims/Introduction Dyslipidemia is commonly present in type 2 diabetes mellitus patients. Recently, the triglyceride : high‐density lipoprotein cholesterol (TG/HDL‐C) ratio, a novel parameter of lipid abnormality, has been seen as an independent predictor for incident diabetes. However, the correlation of the TG/HDL‐C ratio with incident diabetes in the Chinese population and how this relationship is impacted by sex have been rarely studied. In the present study, the correlation of the TG/HDL‐C ratio with incident diabetes is investigated between different sexes of the Chinese population. Materials and Methods A total of 116,855 participants who were free of diabetes at baseline were enrolled in the study. The participants were grouped by the median value (0.82) of the TG/HDL‐C ratio. Then, participants were further analyzed according to their sex. Cumulative incidence and person‐years incidence were used to express the incidence rate. The predictive value of the TG/HDL‐C ratio for incident diabetes was probed by the Cox regression proportional hazards model. Results The mean age of the participants was 44.1 ± 12.9 years, and 53% of participants (n = 62,868) were the men. A total of 2,685 incident diabetes cases occurred during the 3.1 years of the median follow‐up period. The cumulative incidence in total incident diabetes patients, men and women was 2.30% (2.21–2.38%), 3.01% (2.87–3.14%) and 1.47% (1.37–1.57%), respectively. After the adjustment of multivariate factors, the multivariate Cox regression analysis results showed that a higher TG/HDL‐C ratio was the independent predictive factor of incident diabetes in men (hazard ratio 1.30, 95% confidence interval 1.03–1.64), compared with women (hazard ratio 0.85, 95% confidence interval 0.53–1.38). Conclusions Among the Chinese population, the TG/HDL‐C ratio is an independent predictor for incident diabetes in male patients.

BackgroundPrevious studies have revealed that chronic kidney disease (CKD) is a significant risk factor for insulin resistance and diabetes. However, few studies are on the association between estimated glomerular filtration rate (eGFR) and incident diabetes, especially in the Chinese population with eGFR>60 mL/min·1.73 m2. This study explored the relationship between eGFR and incident diabetes in a large cohort in the Chinese community.MethodsThis study was a retrospective cohort study. A total of 1,99,435 adults from Rich Healthcare Group in China were studied, including all medical records for participants who received a health check from 2010 to 2016. The target-independent and target-dependent variables were eGFR measured at baseline, and incident diabetes mellitus appeared during the follow-up. After testing the proportion hypothesis, Cox proportional hazards regression was used to investigate the association between eGFR and incident diabetes. A Cox proportional hazards regression with cubic spline functions and smooth curve fitting (the cubic spline smoothing) was used to identify non-linear relationships between eGFR and the risk of diabetes. Additionally, we also performed subgroup analysis and a series sensitivity analysis. It was stated that the data had been uploaded to the DATADRYAD website.ResultAfter adjusting gender, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting plasma glucose (FPG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglyceride (TG), alanine aminotransferase (ALT), aspartate aminotransferase (AST), smoking and drinking status, and family history of diabetes, the result showed that eGFR was negatively associated with incident diabetes [HR = 0.986, 95% CI (0.984, 0.988)]. A non-linear relationship was detected between eGFR and incident diabetes, with an inflection point of eGFR of 98.034 mL/min·1.73 m2. The effect sizes and the confidence intervals (Cis) on the left and right sides of the inflection point were 0.998 (0.993, 1.003) and 0.976 (0.972, 0.980), respectively. Subgroup analysis showed a stronger association in the population with FPG

Purpose: We aimed to establish and validate a risk assessment system that combines demographic and clinical variables to predict the 3-year risk of incident diabetes in Chinese adults.Methods: A 3-year cohort study was performed on 15,928 Chinese adults without diabetes at baseline. All participants were randomly divided into a training set (n = 7,940) and a validation set (n = 7,988). XGBoost method is an effective machine learning technique used to select the most important variables from candidate variables. And we further established a stepwise model based on the predictors chosen by the XGBoost model. The area under the receiver operating characteristic curve (AUC), decision curve and calibration analysis were used to assess discrimination, clinical use and calibration of the model, respectively. The external validation was performed on a cohort of 11,113 Japanese participants.Result: In the training and validation sets, 148 and 145 incident diabetes cases occurred. XGBoost methods selected the 10 most important variables from 15 candidate variables. Fasting plasma glucose (FPG), body mass index (BMI) and age were the top 3 important variables. And we further established a stepwise model and a prediction nomogram. The AUCs of the stepwise model were 0.933 and 0.910 in the training and validation sets, respectively. The Hosmer-Lemeshow test showed a perfect fit between the predicted diabetes risk and the observed diabetes risk (p = 0.068 for the training set, p = 0.165 for the validation set). Decision curve analysis presented the clinical use of the stepwise model and there was a wide range of alternative threshold probability spectrum. And there were almost no the interactions between these predictors (most P-values for interaction >0.05). Furthermore, the AUC for the external validation set was 0.830, and the Hosmer-Lemeshow test for the external validation set showed no statistically significant difference between the predicted diabetes risk and observed diabetes risk (P = 0.824).Conclusion: We established and validated a risk assessment system for characterizing the 3-year risk of incident diabetes.

Objective: The general public recognizes the connections between obesity, family history of diabetes (FHD), and diabetes, but remains unaware of synergistic effects that occur due to their combination. In this study, we investigate the synergistic effects of event diabetes between snoring, FHD, and obesity. Materials and Methods: Study subjects were selected among participants in the Korean Genome and Epidemiology Study Ansan-Ansung cohort, an ongoing prospective population-based study. Ansan-Ansung cohort initiated in 2001 and 2002 and has been followed biennially. At baseline, the initial cohort of 10.030 subjects, aged 40 to 69 years. A total of 5.759 participants were included in this study. The relationships between diabetes and snoring, FHD, and obesity were estimated using Cox hazard regression models after adjusting for confounding factors. Snoring, obesity and FHD were significantly associated with diabetes in both males and females after adjustments for covariates. However, males were significantly more likely to have FHD and obesity. Results: A synergistic effect between these two risk factors showed that being female was associated with the all group after adjustment for covariates. Moreover, there was a high risk of having two risk factors among female patients, while males showed no such tendency. A significant synergistic effect between these three risk factors was seen in females. An exposure group with these three factors had higher diabetes risk than other groups [hazard ratio (HR): 6.27 (95% confidence interval (CI): 2.93-13.41] p<0.01, but this was not seen in males. Especially, premenopausal women was showed significant with FHD, obese, habitual snorer [HR=5.69 (95% CI: 2.31-14.02) p<0.01]. But postmenopausal women was showed significant with FHD and habitual snorer both non-obese and obese [HR=7.22 (95% CI: 1.68-30.99) p=0.01 and HR=7.85 (95% CI: 1.88-32.82) p<0.01, respectively]. Conclusion: The combination of obesity, FHD, and habitual snoring was associated with greater susceptibility to diabetes in female patients, while obesity and habitual snoring was associated with greater susceptibility to diabetes in males. [ABSTRACT FROM AUTHOR]

The aim was to examine the effects of replacing self‐reported leisure‐time sedentary behavior with sleep, light‐to‐moderate physical activity, or vigorous physical activity on incident diabetes among Danish adults using isotemporal substitution modeling. Participants ≥25 years from the Danish Capital Region Health Survey 2007 (N = 69 800, response rate 52.3%), 2010 (N = 95 150, response rate 52.3%), and 2013 (N = 95 150, response rate 43.5%) were included. Information on daily sleep duration, leisure‐time sedentary behavior, and movement behaviors was collected by questionnaire. Information on incident diabetes was obtained from National registers. Analyses included Cox proportional hazards regression models and isotemporal substitution analyses, with time (in years) from baseline to incident diabetes or censoring December 31, 2017. Potential confounders, sex, age, BMI, ethnicity, education, smoking, inflammatory joint disease, perceived stress, physical and mental component scale and work status, were included. Out of N = 87 339 in the final study sample, n = 3007 had incident diabetes during a mean follow‐up time of 7.4 years. Adults with incident diabetes included more men, higher mean age, and higher BMI, compared to respondents without incident diabetes. Theoretically substituting 30 minutes of leisure‐time sedentary behavior with light‐to‐moderate PA (HR: 0.96; 95% CI: 0.94; 0.98) or with vigorous PA (HR: 0.82; 95% CI: 0.72; 0.94) decreased the risk of incident diabetes. We found no change in incident diabetes risk of substituting sedentary time with sleep (HR: 1.00; 95% CI: 0.97; 1.02). Substituting 30 minutes per day of leisure‐time sedentary behavior with light‐to‐moderate or vigorous PA may significantly reduce the risk of incident diabetes among adults. [ABSTRACT FROM AUTHOR]

Background: Reliable quantification of the relationship between hypertension and diabetes risk is limited, especially among Chinese people. We aimed to investigate the association between hypertension and the risk of diabetes in a large cohort of the Chinese population. Methods: This was a retrospective propensity score-matched cohort study among 211,809 Chinese adults without diabetes at baseline between 2010 and 2016. The target independent and dependent variable were hypertension at baseline and incident diabetes during follow-up respectively. The propensity score matching using a non-parsimonious multivariable logistic regression was conducted to balance the confounders between 28,711 hypertensive patients and 28,711 non-hypertensive participants. The doubly robust estimation method was used to investigate the association between hypertension and diabetes. Results: In the propensity-score matching cohort, diabetes risk increased by 11.0% among hypertensive patients (HR = 1.110, 95% confidence interval (CI): 1.031–1.195, P = 0.00539). And diabetes risk dropped to 8.3% among hypertensive subjects after adjusting for the propensity score (HR = 1.083, 95%CI: 1.006–1.166, P = 0.03367). Compared to non-hypertensive participants with low propensity score, the risk of incident diabetes increased by 2.646 times among hypertensive patients with high propensity score (HR = 3.646, 95%CI: 2.635–5.045, P < 0.0001). Conclusion: Hypertension was associated with an 11.0% increase in the risk of developing diabetes in Chinese adults. And the figure dropped to 8.3% after adjusting the propensity score. Additionally, compared to non-hypertensive participants with low propensity scores, the risk of incident diabetes increased by 2.646 times among hypertensive patients with high propensity scores. [ABSTRACT FROM AUTHOR]

Aims/Introduction: Dyslipidemia plays a critical role in the pathogenesis of metabolic syndrome and diabetes. Evidence has increasingly shown that the ratio of low‐ to high‐density lipoprotein cholesterol (LDL‐C/HDL‐C) is a novel marker for increased risk of insulin resistance and cardiovascular diseases. However, the correlation between the LDL‐C/HDL‐C ratio and diabetes risk is rarely reported. This is the first study to investigate the association between the LDL‐C/HDL‐C ratio and new‐onset diabetes in a large community‐based cohort. Materials and Methods: In this retrospective cohort study, a total of 116,661 adults without baseline diabetes were enrolled. Participants were stratified into four groups based on LDL‐C/HDL‐C ratio quartiles. The outcome of interest was new‐onset diabetes. Results: During a median follow‐up period of 2.98 years, 2,681 (2.3%) new diabetes cases were recorded. The total cumulative incidence of diabetes progressively increased alongside LDL‐C/HDL‐C ratio quartiles (0.31, 0.43, 0.68 and 0.88%, respectively, P‐value for trend <0.001). After adjusting for potential confounders, using the lowest quartile of the LDL‐C/HDL‐C ratio as the reference, the risk of diabetes increased with LDL‐C/HDL‐C ratio quartiles (P‐value for trend <0.001); in particular, from the second to fourth quartile, hazard ratios were 1.18 (95% confidence interval 0.87–1.59), 1.42 (95% confidence interval 1.07–1.90) and 1.92 (95% confidence interval 1.43–2.59), respectively. The results were also robust to challenges in multiple sensitivity analyses. Conclusions: Among the Chinese population, elevated LDL‐C/HDL‐C ratio might be an independent risk factor for new‐onset diabetes. [ABSTRACT FROM AUTHOR]

Background: Evidence suggests an increased risk of new-onset diabetes following COVID-19 infection. American Indian/Alaska Native (AI/AN) people were disparately impacted by the COVID-19 pandemic and historically have had higher diabetes incidence than other racial/ethnic groups in the US. We measured the association between COVID-19 infection and incident diabetes in AI/AN people., Methods: We conducted a retrospective cohort study using de-identified patient data from the Indian Health Service's (IHS) National Patient Information Reporting System. We estimated age-adjusted diabetes incidence rates, incidence rate ratios, and adjusted hazard ratios among three cohorts spanning pre-pandemic (1/1/2018-2/28/2020) and pandemic (3/1/2020-12/31/2021) timeframes: 1) pre-pandemic cohort (1,503,085 individuals); 2) no-COVID-19 pandemic cohort (1,344,339 individuals); and 3) COVID-19 cohort (176,483 individuals)., Findings: The COVID-19 cohort had an increased hazard of diabetes compared to the no-COVID-19 group (adjusted hazard ratio (aHR) = 1.56; 95% CI: 1.50-1.62) and the pre-pandemic group (aHR = 1.27; 95% CI: 1.22-1.32). The association between COVID-19 infection and new-onset diabetes was stronger in those with severe COVID-19 illness. A sensitivity analysis comparing the COVID-19 cohort to members of other cohorts that had acute upper respiratory infections showed an attenuated but higher risk of new-onset diabetes in those with COVID-19., Interpretation: AI/AN people diagnosed with COVID-19 had an elevated risk of a new diabetes diagnosis when compared to the no-COVID-19 group and the pre-pandemic group. The increased diabetes risk in the COVID-19 group remained in a sensitivity analysis that limited the comparator groups to individuals with an AURI diagnosis., Funding: US National Institute of Diabetes and Digestive and Kidney Diseases., Competing Interests: The authors declare no potential conflicts of interest relevant to this work., (© 2024 The Authors.)

The association between serum uric acid and the risk of incident diabetes in Chinese adults remains unknown. This study aimed to investigate this association in a community-dwelling population aged ≥ 40 years in Shanghai, China. Oral glucose tole3rance test was conducted during baseline and follow-up visits. Relative risk regression was utilized to examine the associations between baseline gender-specific serum uric acid levels and incident diabetes risk. A total of 613 (10.3%) incident diabetes cases were identified during the follow-up visit after 4.5 years. Fasting plasma glucose, postload glucose, and glycated hemoglobin A1c during the follow-up visit progressively increased across the sex-specific quartiles of serum uric acid (all Ps < 0.05). The incidence rate of diabetes increased across the quartiles of serum uric acid (7.43%, 8.77%, 11.47%, and 13.43%). Multivariate adjusted regression analysis revealed that individuals in the highest quartile had 1.36-fold increased risk of diabetes compared with those in the lowest quartile of serum uric acid (odds ratio (95% confidence interval) = 1.36 (1.06–1.73)). Stratified analysis indicated that the association was only observed in women. Accordingly, serum uric acid was associated with the increased risk of incident diabetes among middle-aged and elderly Chinese women. [ABSTRACT FROM AUTHOR]

Background: Recent studies have suggested the triglyceride-glucose index (TyG index) may serve as a suitable substitute for insulin resistance. However, evidence for the relationship between TyG index and risk of diabetes remains limited. This study sought to explore the association of baseline TyG index with risk of developing diabetes in Chinese adults. Methods: This retrospective cohort study was conducted using data from the health screening program in China. A total of 201,298 non-diabetic individuals were included. TyG index was calculated as Ln [fasting plasma glucose (mg/dL) × fasting triglyceride level (mg/dL) / 2]. Diabetes was defined as fasting plasma glucose ≥126 mg/dL and/or self-reported diabetes. Cox proportion-hazard model was employed to evaluate the independent impact of baseline TyG index on future diabetes risk. Sensitivity and subgroup analyses were implemented to verify the reliability of results. Notably, data were downloaded from the DATADRYAD website, and used only for secondary analyses. Results: During an average follow-up of 3.12 years, among 201,298 individuals aged ≥20 years, 3389 subjects developed diabetes. After adjusting for potential confounders, elevated TyG index were independently correlated with greater risk of incident diabetes (hazard ratio (HR), 3.34; 95% confidence interval (CI), 3.11–3.60). Compared with the lowest quartile (Q1), increasing TyG index (Q2, Q3, and Q4) was related to increased HR estimates of incident diabetes [HR (95% CI), 1.83 (1.49–2.26); 3.29 (2.70–4.01), and 6.26 (5.15–7.60), respectively]. Moreover, a nonlinear relationship was observed between TyG index and risk of diabetes and the slope of the curve increased accompanying the rise of TyG index. Subgroup analysis revealed the positive association was stronger among subjects with age < 40 years, body mass index ≥18.5 kg/m2 and < 24 kg/m2, or systolic blood pressure < 140 mmHg, or in females. Conclusions: Elevated TyG index is independently correlated with increased risk of incident diabetes in Chinese adults, indicating it may represent a reliable predictor of diabetes in high-risk populations. [ABSTRACT FROM AUTHOR]

Background: Previous studies have revealed that triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C) is one of major risk factors of insulin resistance and diabetes. However, study on the association between TG/HDL-C and diabetes mellitus (DM) risk is limited, especially in Chinese people. This study was undertaken to investigate the relationship between TG/HDL-C and incident of diabetes in a large cohort in Chinese population. Methods: The present study was a retrospective cohort study. A total of 114,787 adults from Rich Healthcare Group in China, which includes all medical records for participants who received a health check from 2010 to 2016. The target independent variable and the dependent variable were triglyceride to high-density lipoprotein cholesterol ratio measured at baseline and incident of diabetes mellitus appeared during follow-up respectively. Covariates involved in this study included age, gender, body mass index, diastolic blood pressure, systolic blood pressure, fasting plasma glucose, total cholesterol, low density lipoprotein cholesterol, serum creatinine, smoking and drinking status and family history of diabetes. Cox proportional-hazards regression was used to investigate the association of TG/HDL-C and diabetes. Generalized additive models was used to identify non-linear relationships. Additionally, we also performed a subgroup analysis. It was stated that the data had been uploaded to the DATADRYAD website. Result: After adjusting age, gender, body mass index, systolic blood pressure, diastolic blood pressure, fasting blood glucose, total cholesterol, low density lipoprotein cholesterol, serum creatinine, smoking and drinking status and family history of diabetes, result showed TG/HDL-C was positively associated with incident of diabetes mellitus (HR = 1.159, 95%CI (1.104, 1.215)). A non-linear relationship was detected between TG/HDL-C and incident of diabetes, which had an inflection point of TG/HDL-C was 1.186. The effect sizes and the confidence intervals on the left and right sides of the inflection point were 1.718(1.433,2.060) and 1.049(0.981,1.120), respectively. Subgroup analysis showed, the stronger association can be found in the population with fasting plasma glucose (FPG) < 6.1 mmol/L (P for interaction< 0.0001; HR = 1.296 with FPG < 6.1 mmol/L vs HR = 1.051 with FPG ≥ 6.1 mmol/L).The same trend was also seen in the population with body mass index (BMI)(≥18.5, < 24 kg/m2) (P for interaction = 0.010,HR = 1.324) and family history without diabetes(P for interaction = 0.025, HR = 1.170). Conclusion: TG/HDL-C is positively associated with diabetes risk. The relationship between TG/HDL-C and incident of diabetes is also non-linear. TG/HDL-C was strong positively related to incident of diabetes when TG/HDL-C is less than 1.186. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: Type 1 and type 2 diabetes differ with respect to pathophysiological factors such as beta cell function, insulin resistance and phenotypic appearance, but there may be overlap between the two forms of diabetes. However, there are relatively few prospective studies that have characterised the relationship between autoimmunity and incident diabetes. We investigated associations of antibodies against the 65 kDa isoform of GAD (GAD65) with type 1 diabetes and type 2 diabetes genetic risk scores and incident diabetes in adults in European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct, a case-cohort study nested in the EPIC cohort. Methods: GAD65 antibodies were analysed in EPIC participants (over 40 years of age and free of known diabetes at baseline) by radioligand binding assay in a random subcohort (n = 15,802) and in incident diabetes cases (n = 11,981). Type 1 diabetes and type 2 diabetes genetic risk scores were calculated. Associations between GAD65 antibodies and incident diabetes were estimated using Prentice-weighted Cox regression. Results: GAD65 antibody positivity at baseline was associated with development of diabetes during a median follow-up time of 10.9 years (HR for GAD65 antibody positive vs negative 1.78; 95% CI 1.43, 2.20) after adjustment for sex, centre, physical activity, smoking status and education. The genetic risk score for type 1 diabetes but not type 2 diabetes was associated with GAD65 antibody positivity in both the subcohort (OR per SD genetic risk 1.24; 95% CI 1.03, 1.50) and incident cases (OR 1.97; 95% CI 1.72, 2.26) after adjusting for age and sex. The risk of incident diabetes in those in the top tertile of the type 1 diabetes genetic risk score who were also GAD65 antibody positive was 3.23 (95% CI 2.10, 4.97) compared with all other individuals, suggesting that 1.8% of incident diabetes in adults was attributable to this combination of risk factors. Conclusions/interpretation: Our study indicates that incident diabetes in adults has an element of autoimmune aetiology. Thus, there might be a reason to re-evaluate the present subclassification of diabetes in adulthood. [ABSTRACT FROM AUTHOR]

Aims/Introduction: Dyslipidemia is commonly present in type 2 diabetes mellitus patients. Recently, the triglyceride : high‐density lipoprotein cholesterol (TG/HDL‐C) ratio, a novel parameter of lipid abnormality, has been seen as an independent predictor for incident diabetes. However, the correlation of the TG/HDL‐C ratio with incident diabetes in the Chinese population and how this relationship is impacted by sex have been rarely studied. In the present study, the correlation of the TG/HDL‐C ratio with incident diabetes is investigated between different sexes of the Chinese population. Materials and Methods: A total of 116,855 participants who were free of diabetes at baseline were enrolled in the study. The participants were grouped by the median value (0.82) of the TG/HDL‐C ratio. Then, participants were further analyzed according to their sex. Cumulative incidence and person‐years incidence were used to express the incidence rate. The predictive value of the TG/HDL‐C ratio for incident diabetes was probed by the Cox regression proportional hazards model. Results: The mean age of the participants was 44.1 ± 12.9 years, and 53% of participants (n = 62,868) were the men. A total of 2,685 incident diabetes cases occurred during the 3.1 years of the median follow‐up period. The cumulative incidence in total incident diabetes patients, men and women was 2.30% (2.21–2.38%), 3.01% (2.87–3.14%) and 1.47% (1.37–1.57%), respectively. After the adjustment of multivariate factors, the multivariate Cox regression analysis results showed that a higher TG/HDL‐C ratio was the independent predictive factor of incident diabetes in men (hazard ratio 1.30, 95% confidence interval 1.03–1.64), compared with women (hazard ratio 0.85, 95% confidence interval 0.53–1.38). Conclusions: Among the Chinese population, the TG/HDL‐C ratio is an independent predictor for incident diabetes in male patients. [ABSTRACT FROM AUTHOR]

Abstract Background With the marked increase in the prevalence of diabetes mellitus, it was the purpose of our study to assess a potential association of time-cumulated exposure to systolic (CumSBP) and of diastolic blood pressure (CumDBP) with onset of impaired glucose tolerance and diabetes mellitus. Methods The prospective investigation included participants of the longitudinal Kailuan Study with three baseline examinations in 2006–2007, 2008–2009 and 2010–2011, re-examination in 2012–2013, and no diabetes mellitus at baseline. Cumulative blood pressure (BP) was calculated as cumBP = [(BP1 + BP2)/2 × time1–2] + [(BP2 + BP3)/2 × time2–3]. Based on cumSBP, the study population was stratified into four groups (cumSBP

Background: Epidemiological evidence supports an association between sugar-sweetened soda consumption and diabetes. However, evidence regarding this association is limited in countries that have recently undergone a nutritional transition.Objective: We estimated the association between sugar-sweetened soda consumption and incident diabetes. We also determined if the association between sugar-sweetened soda and diabetes differs as a result of early life factors and potential genetic susceptibility.Methods: We used data from the Mexican Teachers' Cohort including 72,667 women aged ≥25 y, free of diabetes, cardiovascular disease, and cancer at baseline. We assessed sugar-sweetened soda consumption using a validated food frequency questionnaire (FFQ) at baseline. Diabetes was self-reported. We used Cox proportional hazard regression models to estimate the association between quintiles of sugar-sweetend soda and diabetes. We also estimated the associaiton by increasing one serving per day (355 mL) of sugar-sweetened soda. We conducted prespecified subgroup analysis by potential effect modifiers, namely markers of energy balance of early life factors, family history of diabetes, and Amerindian admixture.Results: During a median follow-up of 2.16 y (IQR 0.75-4.50) we identified 3,155 incident cases of diabetes. The median consumption of sugar-sweetened soda was 1.17 servings per day (IQR 0.47- 4.00). In multivariable analyses, comparing extreme quintiles showed that higher sugar-sweetened soda consumption was associated with diabetes incidence (HR = 1.32; 95% CI: 1.17, 1.49), and each additional serving per day of sugar-sweetened soda was associated with an increase of 27% in diabetes incidence (HR = 1.27; 95% CI: 1.16, 1.38). The soda-diabetes association was stronger among women who experienced intrauterine and childhood over-nutrition (high birth weight, no short stature, higher adiposity in premenarche, and higher adiposity at age 18-20 y old).Conclusion: Sugar-sweetened soda consumption is associated with an increased risk of diabetes among Mexican women in a magnitude similar to that reported in other populations. The stronger association among individuals with markers of early life over-nutrition reinforce the need for early life interventions. [ABSTRACT FROM AUTHOR]

Abstract Background Three cross sectional studies suggest that neighbourhood greenspace may protect against incident diabetes. This study uses data from a longitudinal study with a large sample size to investigate the association between greenspace and the occurrence of incident diabetes over time. Methods Data was from the European Prospective Investigation of Cancer Norfolk, UK, cohort, recruitment 1993–2007 (N = 23,865). Neighbourhoods were defined as 800 m circular buffers around participants’ home locations, according to their home postcode (zip code). Greenspace exposure was defined as the percentage of the home neighbourhood that was woodland, grassland, arable land, mountain, heath and bog, according to the UK Land Cover Map. Cox proportional hazards regression examined the association between neighbourhood greenspace exposure and incident diabetes. The population attributable fraction assessed the proportion of diabetes cases attributable to exposure to least green neighbourhoods. Mediation analysis assessed if physical activity explained associations between greenspace and diabetes. Interaction analysis was used to test for the modifying effect of rurality and socio-economic status on the relationship between greenspace and diabetes. Models were adjusted for known and hypothesised confounders. Results The mean age of participants was 59 years at baseline and 55.1% were female. The mean follow-up time was 11.3 years. Individuals living in the greenest neighbourhood quartile had a 19% lower relative hazard of developing diabetes (HR 0.81; 95% CI 0.67, 0.99; p = 0.035; linear trend p = 0.010). The hazard ratio remained similar (HR 0.81; 95% CI 0.65, 0.99; p = 0.042) after adjusting for age, sex, BMI, whether a parent had been diagnosed with diabetes and socio-economic status at the individual and neighbourhood level. A HR of 0.97 was attributed to the pathway through physical activity in a fully adjusted model, although this was non-significant (95% CI 0.88, 1.08; p = 0.603). The incidence of diabetes in the least green neighbourhoods (with 20% greenspace on average) would fall by 10.7% (95% CI −2.1%, 25.2%; p = 0.106) if they were as green as the average neighbourhood observed across the whole cohort (59% greenspace on average). There were no significant interactions between rurality or socio-economic status and level of greenspace. Conclusions Greener home neighbourhoods may protect against risk of diabetes in older adults, although this study does not support a mediation role for physical activity. Causal mechanisms underlying the associations require further investigation.

Aim: To determine the risk of new‑onset diabetes mellitus in patients treated with simvastatin at primary healthcare clinics in North Central Trinidad. Materials and Methods: A retrospective descriptive case‑series study design was applied to 384 conveniently sampled patient medical records from the cluster of primary healthcare centers during the period of February 2016–May 2016. Information from the patient files were then recorded using a systematic data extraction form. The major inclusion criteria were non‑diabetic patients who were compliant with daily simvastatin for a minimum period of 1 year. The risk of incident diabetes mellitus was calculated, using SPSS version 20.0. Chi‑squared (χ²) testing was performed to determine any association between new‑onset diabetes mellitus and simvastatin use. Results: In all, 207 patients became diabetic during their treatment period translating into a 53.9% risk of incident diabetes mellitus (χ² = 2.3438, P = 0.1258). A subgroup analysis of 133 subjects was performed to eliminate the confounders of family history of diabetes and age greater than 60 years. In this subgroup, 50 incident diabetics (37%) were identified and a statistically significant association was observed (χ² = 8.118, P = 0.0042). Linear regression revealed that this association was dose‑dependent with a corresponding 32% higher risk in patients taking 40 mg (P = 0.001) of simvastatin daily compared with 20 mg of simvastatin (P = 0.094). Linear regression also revealed that there was significant statistical association between onset of diabetes mellitus and duration of statin therapy (P = 0.006). Conclusion: In this population, simvastatin use is associated with a 53.9% increased risk of development of new‑onset diabetes mellitus (χ² = 2.3438, P = 0.1258). A statistically significant association was attained after subgroup analysis involving patients less than 60 years old and without a family history of diabetes with an incident risk of 37%. The increased risk of incident diabetes mellitus conferred by higher doses of simvastatin warrants consideration by physicians considering therapies for dyslipidemia in patients with multiple risk factors for diabetes mellitus. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: This study examined the relationship between hip/knee osteoarthritis and incident diabetes. We hypothesised that hip/knee osteoarthritis would be independently related to an increased risk of incident diabetes and that this relationship would be due, at least in part, to walking difficulty. We also hypothesised a stronger relationship with incident diabetes for knee than hip osteoarthritis because of the higher prevalence in the former of obesity/the metabolic syndrome.Methods: A population cohort aged ≥55 years recruited from 1996 to 1998 was followed through provincial health administrative data to 2014. Participants with baseline diabetes were excluded. Hip/knee osteoarthritis was defined as swelling, pain or stiffness in any joint lasting 6 weeks in the past 3 months and indication on a joint homunculus that a hip/knee was ‘troublesome’. Walking limitation was defined as self-reported difficulty standing or walking in the last 3 months (yes/no). Using Cox regressions, we examined the relationship of baseline hip/knee osteoarthritis with incident diabetes as defined from health administrative data, controlling for age, sex, BMI, income, prior hypertension, cardiovascular disease and primary care exposure. We tested whether the observed effect was mediated through walking limitation.Results: In total, 16,362 participants were included: median age 68 years and 61% female. Of these, 1637 (10%) individuals met the criteria for hip osteoarthritis, 2431 (15%) for knee osteoarthritis and 3908 (24%) for walking limitation. Over a median follow-up of 13.5 years (interquartile range 7.3-17.8), 3539 individuals (22%) developed diabetes. Controlling for confounders, a significant relationship was observed between number of hip/knee joints with osteoarthritis and incident diabetes: HR for two vs no osteoarthritic hips 1.25 (95% CI 1.08, 1.44); HR for two vs no osteoarthritic knees 1.16 (95% CI 1.04, 1.29). From 37% to 46% of this relationship was explained by baseline walking limitation.Conclusions/interpretation: In a large population cohort aged ≥55 years who were free of diabetes at baseline, and controlling for confounders, the presence and burden of hip/knee osteoarthritis was a significant independent predictor of incident diabetes. This association was partially explained by walking limitation. Increased attention to osteoarthritis and osteoarthritis-related functional limitations has the potential to reduce diabetes risk. [ABSTRACT FROM AUTHOR]

Aims: The aim of this study was to develop a new risk score system to predict 5-year incident diabetes risk among middle-aged and older Chinese population. Methods: This prospective study included 17,690 individuals derived from the Dongfeng–Tongji cohort. Participants were recruited in 2008 and were followed until October 2013. Incident diabetes was defined as self-reported clinician diagnosed diabetes, fasting glucose ≥7.0 mmol/l, or the use of insulin or oral hypoglycemic agent. A total of 1390 incident diabetic cases were diagnosed during the follow-up period. β-Coefficients were derived from Cox proportional hazard regression model and were used to calculate the risk score.Results: The diabetes risk score includes BMI, fasting glucose, hypertension, hyperlipidemia, current smoking status, and family history of diabetes. The β-coefficients of these variables ranged from 0.139 to 1.914, and the optimal cutoff value was 1.5. The diabetes risk score was calculated by multiplying the β-coefficients of the significant variables by 10 and rounding to the nearest integer. The score ranges from 0 to 36. The area under the receiver operating curve of the score was 0.751. At the optimal cutoff value of 15, the sensitivity and specificity were 65.6 and 72.9%, respectively. Based upon these risk factors, this model had the highest discrimination compared with several commonly used diabetes prediction models.Conclusions: The newly established diabetes risk score with six parameters appears to be a reliable screening tool to predict 5-year risk of incident diabetes in a middle-aged and older Chinese population. [ABSTRACT FROM AUTHOR]

Aims: To evaluate whether variable fatty liver status over time influence the risk of type 2 diabetes differently.Methods: We analyzed the data from 7849 subjects without type 2 diabetes who underwent comprehensive health check-ups annually for 5 years. All subjects had an abdominal ultrasonography annually. The risk of incident diabetes was assessed in individuals with sustained non-alcoholic fatty liver disease (NAFLD), individuals with changed fatty liver status (intermittent NAFLD group), and individuals who did not have NAFLD (never NAFLD group) during the study period. A subgroup analysis was done in subjects of the intermittent NAFLD group. Incident diabetes was compared according to the number of time diagnosed as NAFLD by annual ultrasonography.Results: During the mean follow-up of 4 years, subjects in the sustained NAFLD group had a HR of 1.50 (95% CI 1.13-1.98) for the development of diabetes compared with those in the never NAFLD group, whereas the risk was not higher in the intermittent NAFLD group (HR 0.99, 95% CI 0.76-1.31). When compared with the intermittent NAFLD group, multivariable adjusted HR for incident diabetes was 1.50 (95% CI 1.20-1.89) in the sustained NAFLD group. As the number of times diagnosed as NAFLD increased, the proportion of subjects who developed diabetes also increased (p = .002).Conclusions: The presence of fatty liver was differentially associated with incident diabetes based on its duration. The persistence of fatty liver status is an important factor for an independent association between NAFLD and incident diabetes. [ABSTRACT FROM AUTHOR]

Introduction Diabetes is prospectively associated with cognitive decline. Whether lower cognitive function and worse brain structure are prospectively associated with incident diabetes is unclear. Methods We analyzed data for 10,133 individuals with cognitive function testing (1990–1992) and 1212 individuals with brain magnetic resonance imaging (1993–1994) from the Atherosclerosis Risk in Communities cohort. We estimated hazard ratios for incident diabetes through 2014 after adjustment for traditional diabetes risk factors and cohort attrition. Results Higher level of baseline cognitive function was associated with lower risk for diabetes (per 1 standard deviation, hazard ratio = 0.94; 95% confidence interval = 0.90, 0.98). This association did not persist after accounting for baseline glucose level, case ascertainment methods, and cohort attrition. No association was observed between any brain magnetic resonance imaging measure and incident diabetes. Discussion This is one of the first studies to prospectively evaluate the association between both cognitive function and brain structure and the incidence of diabetes. [ABSTRACT FROM AUTHOR]