The consumption of ultra-processed foods (UPFs) has surged globally, raising significant public health concerns due to their associations with a range of adverse health outcomes. This review aims to elucidate potential health impacts of UPF intake and underscore the importance of considering diet quality when interpreting study findings. UPF group, as classified by the Nova system based on the extent of industrial processing, contains numerous individual food items with a wide spectrum of nutrient profiles, as well as differential quality as reflected by their potential health effects. The quality of a given food may well misalign with the processing levels so that a UPF food can be nutritious and healthful whereas a non-UPF food can be of low quality and excess intake of which may lead to adverse health consequences. The current review argues that it is critical to focus on the nutritional content and quality of foods and their role within the overall dietary pattern rather than only the level of processing. Further research should dissect health effects of diet quality and food processing, investigate the health impacts of ingredients that render the UPF categorization, understand roles of metabolomics and the gut microbiome in mediating and modulating the health effects of food processing, and consider environmental sustainability in UPF studies. Emphasizing nutrient-dense healthful foods and dietary patterns shall remain the pivotal strategy for promoting overall health and preventing chronic diseases.
Background This study aimed to develop a diabetic kidney disease (DKD) prediction model using long short term memory (LSTM) neural network and evaluate its performance using accuracy, precision, recall, and area under the curve (AUC) of the receiver operating characteristic (ROC) curve.
Methods The study identified DKD risk factors through literature review and physician focus group, and collected 7 years of data from 6,040 type 2 diabetes mellitus patients based on the risk factors. Pytorch was used to build the LSTM neural network, with 70% of the data used for training and the other 30% for testing. Three models were established to examine the impact of glycosylated hemoglobin (HbA1c), systolic blood pressure (SBP), and pulse pressure (PP) variabilities on the model’s performance.
Results The developed model achieved an accuracy of 83% and an AUC of 0.83. When the risk factor of HbA1c variability, SBP variability, or PP variability was removed one by one, the accuracy of each model was significantly lower than that of the optimal model, with an accuracy of 78% (P<0.001), 79% (P<0.001), and 81% (P<0.001), respectively. The AUC of ROC was also significantly lower for each model, with values of 0.72 (P<0.001), 0.75 (P<0.001), and 0.77 (P<0.05).
Conclusion The developed DKD risk predictive model using LSTM neural networks demonstrated high accuracy and AUC value. When HbA1c, SBP, and PP variabilities were added to the model as featured characteristics, the model’s performance was greatly improved.
Jannica S. Selenius, Patricia P. Silveira, Mikaela von Bonsdorff, Jari Lahti, Hannu Koistinen, Riitta Koistinen, Markku Seppälä, Johan G. Eriksson, Niko S. Wasenius
Diabetes Metab J. 2024;48(5):960-970. Published online March 25, 2024
Background To investigate associations between variations in the co-expression-based brain insulin receptor polygenic score and cardiometabolic risk factors and diabetes mellitus.
Methods This cross-sectional study included 1,573 participants from the Helsinki Birth Cohort Study. Biologically informed expression-based polygenic risk scores for the insulin receptor gene network were calculated for the hippocampal (hePRS-IR) and the mesocorticolimbic (mePRS-IR) regions. Cardiometabolic markers included body composition, waist circumference, circulating lipids, insulin-like growth factor 1 (IGF-1), and insulin-like growth factor-binding protein 1 and 3 (IGFBP-1 and -3). Glucose and insulin levels were measured during a standardized 2-hour 75 g oral glucose tolerance test and impaired glucose regulation status was defined by the World Health Organization 2019 criteria. Analyzes were adjusted for population stratification, age, smoking, alcohol consumption, socioeconomic status, chronic diseases, birth weight, and leisure-time physical activity.
Results Multinomial logistic regression indicated that one standard deviation increase in hePRS-IR was associated with increased risk of diabetes mellitus in all participants (adjusted relative risk ratio, 1.17; 95% confidence interval, 1.01 to 1.35). In women, higher hePRS-IR was associated with greater waist circumference and higher body fat percentage, levels of glucose, insulin, total cholesterol, low-density lipoprotein cholesterol, triglycerides, apolipoprotein B, insulin, and IGFBP-1 (all P≤0.02). The mePRS-IR was associated with decreased IGF-1 level in women (P=0.02). No associations were detected in men and studied outcomes.
Conclusion hePRS-IR is associated with sex-specific differences in cardiometabolic risk factor profiles including impaired glucose regulation, abnormal metabolic markers, and unfavorable body composition in women.
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Background This study aimed to investigate the association between type 2 diabetes mellitus (T2DM) and shoulder adhesive capsulitis (AC) using a large-scale, nationwide, population-based cohort in the Republic of Korea.
Methods A total of 3,471,745 subjects aged over 20 years who underwent a National Health Insurance Service medical checkup between 2009 and 2010 were included in this study, and followed from the date of their medical checkup to the end of 2018. Subjects were classified into the following four groups based on the presence of dysglycemia and history of diabetes medication: normal, prediabetes, newly diagnosed T2DM (new-T2DM), and T2DM (claim history for antidiabetic medication). The endpoint was new-onset AC during follow-up. The incidence rates (IRs) in 1,000 person-years and hazard ratios (HRs) of AC for each group were analyzed using Cox proportional hazard regression models.
Results The IRs of AC were 9.453 (normal), 11.912 (prediabetes), 14.933 (new-T2DM), and 24.3761 (T2DM). The adjusted HRs of AC in the prediabetes, new-T2DM, and T2DM groups were 1.084 (95% confidence interval [CI], 1.075 to 1.094), 1.312 (95% CI, 1.287 to 1.337), and 1.473 (95% CI, 1.452 to 1.494) compared to the normal group, respectively. This secular trend of the HRs of AC according to T2DM status was statistically significant (P<0.0001).
Conclusion This large-scale, longitudinal, nationwide, population-based cohort study of 3,471,745 subjects confirmed that the risk of AC increases in prediabetic subjects and is associated with T2DM status.
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Background A substantial cardiovascular disease risk remains even after optimal statin therapy. Comparative predictiveness of major lipid and lipoprotein parameters for cardiovascular events in patients with type 2 diabetes mellitus (T2DM) who are treated with statins is not well documented.
Methods From the Korean Nationwide Cohort, 11,900 patients with T2DM (≥40 years of age) without a history of cardiovascular disease and receiving moderate- or high-intensity statins were included. The primary outcome was the first occurrence of major adverse cardiovascular events (MACE) including ischemic heart disease, ischemic stroke, and cardiovascular death. The risk of MACE was estimated according to on-statin levels of low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), highdensity lipoprotein cholesterol (HDL-C), and non-HDL-C.
Results MACE occurred in 712 patients during a median follow-up period of 37.9 months (interquartile range, 21.7 to 54.9). Among patients achieving LDL-C levels less than 100 mg/dL, the hazard ratios for MACE per 1-standard deviation change in ontreatment values were 1.25 (95% confidence interval [CI], 1.07 to 1.47) for LDL-C, 1.31 (95% CI, 1.09 to 1.57) for non-HDL-C, 1.05 (95% CI, 0.91 to 1.21) for TG, and 1.16 (95% CI, 0.98 to 1.37) for HDL-C, after adjusting for potential confounders and lipid parameters mutually. The predictive ability of on-statin LDL-C and non-HDL-C for MACE was prominent in patients at high cardiovascular risk or those with LDL-C ≥70 mg/dL.
Conclusion On-statin LDL-C and non-HDL-C levels are better predictors of the first cardiovascular event than TG or HDL-C in patients with T2DM.
Background Although obesity is a well-known risk factor of type 2 diabetes mellitus (T2DM), there is scant data on discriminating the contribution of previous obesity and recent weight gain on developing T2DM.
Methods We analyzed the Korean National Health Insurance Service-Health Screening Cohort data from 2002 to 2015 where Korean residents underwent biennial health checkups. Participants were classified into four groups according to their obesity status (body mass index [BMI] ≥25 kg/m2) before and after turning 50 years old: maintaining normal (MN), becoming obese (BO), becoming normal (BN), and maintaining obese (MO). Cox proportional hazards regression model was used to estimate the risk of T2DM factoring in the covariates age, sex, BMI, presence of impaired fasting glucose or hypertension, family history of diabetes, and smoking status.
Results A total of 118,438 participants (mean age, 52.5±1.1 years; men, 45.2%) were prospectively evaluated for incident T2DM. A total of 7,339 (6.2%) participants were diagnosed with T2DM during a follow-up period of 4.8±2.6 years. Incidence rates of T2DM per 1,000 person-year were 9.20 in MN, 14.81 in BO, 14.42 in BN, 21.38 in MO. After factoring in covariates, participants in the groups BN (adjusted hazard ratio [aHR], 1.15; 95% confidence interval [CI], 1.04 to 1.27) and MO (aHR, 1.14; 95% CI, 1.06 to 1.24) were at increased risk of developing T2DM compared to MN, whereas BO (hazard ratio, 1.06; 95% CI, 0.96 to 1.17) was not.
Conclusion Having been obese before 50 years old increased the risk of developing T2DM in the future, but becoming obese after 50 did not. Therefore, it is important to maintain normal weight from early adulthood to prevent future metabolic perturbations.
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Methods This study is a nationwide population-based cohort study that included all people with T2DM (n=2,746,078) who received the National Screening Program during 2009–2012. According to the anatomical location of the fracture, the incidence rate and hazard ratio (HR) were analyzed by dividing it into four categories: vertebra, hip, limbs, and total fracture.
Results The total fracture had higher HR in the underweight group (HR, 1.268; 95% CI, 1.228 to 1.309) and lower HR in the obese group (HR, 0.891; 95% CI, 0.882 to 0.901) and the morbidly obese group (HR, 0.873; 95% CI, 0.857 to 0.89), compared to reference (normal BMI group). Similar trends were observed for HR of vertebra fracture. The risk of hip fracture was most prominent, the risk of hip fracture increased in the underweight group (HR, 1.896; 95% CI, 1.178 to 2.021) and decreased in the obesity (HR, 0.643; 95% CI, 0.624 to 0.663) and morbidly obesity group (HR, 0.627; 95% CI, 0.591 to 0.665). Lastly, fracture risk was least affected by BMI for limbs.
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Diabetes Metab J. 2022;46(6):819-826. Published online November 24, 2022
Diabetes screening serves to identify individuals at high-risk for diabetes who have not yet developed symptoms and to diagnose diabetes at an early stage. Globally, the prevalence of diabetes is rapidly increasing. Furthermore, obesity and/or abdominal obesity, which are major risk factors for type 2 diabetes mellitus (T2DM), are progressively increasing, particularly among young adults. Many patients with T2DM are asymptomatic and can accompany various complications at the time of diagnosis, as well as chronic complications develop as the duration of diabetes increases. Thus, proper screening and early diagnosis are essential for diabetes care. Based on reports on the changing epidemiology of diabetes and obesity in Korea, as well as growing evidence from new national cohort studies on diabetes screening, the Korean Diabetes Association has updated its clinical practice recommendations regarding T2DM screening. Diabetes screening is now recommended in adults aged ≥35 years regardless of the presence of risk factors, and in all adults (aged ≥19) with any of the risk factors. Abdominal obesity based on waist circumference (men ≥90 cm, women ≥85 cm) was added to the list of risk factors.
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Background This study aimed to investigate the prevalence and management of diabetes mellitus, risk-factor control, and comorbidities among Korean adults.
Methods We conducted a cross-sectional analysis of data from the Korea National Health and Nutrition Examination Survey to assess the prevalence, treatment, risk factors, comorbidities, and self-management behaviors of diabetes mellitus from 2019 to 2020. We also analyzed data from the Korean National Health Insurance Service to evaluate the use of antidiabetic medications in people with diabetes mellitus from 2002 through 2018.
Results Among Korean adults aged 30 years or older, the estimated prevalence of diabetes mellitus was 16.7% in 2020. From 2019 through 2020, 65.8% of adults with diabetes mellitus were aware of the disease and treated with antidiabetic medications. The percentage of adults with diabetes mellitus who achieved glycosylated hemoglobin (HbA1c) <6.5% was 24.5% despite the increased use of new antidiabetic medications. We found that adults with diabetes mellitus who achieved all three goals of HbA1c <6.5%, blood pressure (BP) <140/85 mm Hg, and low-density lipoprotein cholesterol <100 mg/dL were 9.7%. The percentage of self-management behaviors was lower in men than women. Excess energy intake was observed in 16.7% of adults with diabetes mellitus.
Conclusion The prevalence of diabetes mellitus among Korean adults remained high. Only 9.7% of adults with diabetes mellitus achieved all glycemic, BP, and lipid controls from 2019 to 2020. Continuous evaluation of national diabetes statistics and a national effort to increase awareness of diabetes mellitus and improve comprehensive diabetes care are needed.
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Background Insulin-treated patients with long duration of type 2 diabetes mellitus (T2DM) are at increased risk of ketoacidosis related to sodium-glucose co-transporter 2 inhibitor (SGLT2i). The extent of circulating ketone elevation in these patients remains unknown. We conducted this study to compare the serum ketone response between dapagliflozin, an SGLT2i, and sitagliptin, a dipeptidyl peptidase-4 inhibitor, among insulin-treated T2DM patients.
Methods This was a randomized, open-label, active comparator-controlled study involving 60 insulin-treated T2DM patients. Participants were randomized 1:1 for 24-week of dapagliflozin 10 mg daily or sitagliptin 100 mg daily. Serum β-hydroxybutyrate (BHB) levels were measured at baseline, 12 and 24 weeks after intervention. Comprehensive cardiometabolic assessments were performed with measurements of high-density lipoprotein cholesterol (HDL-C) cholesterol efflux capacity (CEC), vibration-controlled transient elastography and echocardiography.
Results Among these 60 insulin-treated participants (mean age 58.8 years, diabetes duration 18.2 years, glycosylated hemoglobin 8.87%), as compared with sitagliptin, serum BHB levels increased significantly after 24 weeks of dapagliflozin (P=0.045), with a median of 27% increase from baseline. Change in serum BHB levels correlated significantly with change in free fatty acid levels. Despite similar glucose lowering, dapagliflozin led to significant improvements in body weight (P=0.006), waist circumference (P=0.028), HDL-C (P=0.041), CEC (P=0.045), controlled attenuation parameter (P=0.007), and liver stiffness (P=0.022). Average E/e’, an echocardiographic index of left ventricular diastolic dysfunction, was also significantly lower at 24 weeks in participants treated with dapagliflozin (P=0.037).
Conclusion Among insulin-treated T2DM patients with long diabetes duration, compared to sitagliptin, dapagliflozin modestly increased ketone levels and was associated with cardiometabolic benefits.
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Background Risky health decisions and impulse control profiles may impact on metabolic control in type 1 diabetes mellitus (T1DM). We hypothesize that the neural correlates of cognitive impulsivity and decision-making in T1DM relate to metabolic control trajectories.
Methods We combined functional magnetic resonance imaging (fMRI), measures of metabolic trajectories (glycosylated hemoglobin [HbA1c] over multiple time points) and behavioral assessment using a cognitive impulsivity paradigm, the Balloon Analogue Risk Task (BART), in 50 participants (25 T1DM and 25 controls).
Results Behavioral results showed that T1DM participants followed a rigid conservative risk strategy along the iterative game. Imaging group comparisons showed that patients showed larger activation of reward related, limbic regions (nucleus accumbens, amygdala) and insula (interoceptive saliency network) in initial game stages. Upon game completion differences emerged in relation to error monitoring (anterior cingulate cortex [ACC]) and inhibitory control (inferior frontal gyrus). Importantly, activity in the saliency network (ACC and insula), which monitors interoceptive states, was related with metabolic trajectories, which was also found for limbic/reward networks. Parietal and posterior cingulate regions activated both in controls and patients with adaptive decision-making, and positively associated with metabolic trajectories.
Conclusion We found triple converging evidence when comparing metabolic trajectories, patients versus controls or risk averse (non-learners) versus patients who learned by trial and error. Dopaminergic reward and saliency (interoceptive and error monitoring) circuits show a tight link with impaired metabolic trajectories and cognitive impulsivity in T1DM. Activity in parietal and posterior cingulate are associated with adaptive trajectories. This link between reward-saliency-inhibition circuits suggests novel strategies for patient management.
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Background Metabolic syndrome (MetS) is reportedly a crucial risk factor for coronavirus disease 2019 (COVID-19). Since the epidemiological studies that examine this association are few and include small samples, we investigated the relationship between MetS and COVID-19 severity and death using a larger sample in the Republic of Korea.
Methods We analyzed 66,321 patients, 4,066 of whom had COVID-19. We used chi-square tests to examine patients’ characteristics. We performed logistic regression analysis to analyze differences in COVID-19 infection and clinical outcomes according to the presence of MetS.
Results Although MetS was not significantly associated with COVID-19 risk, acquiring MetS was significantly associated with the risk of severe COVID-19 outcomes (odds ratio [OR], 1.97; 95% confidence interval [CI], 1.34 to 2.91; P=0.001). The mortality risk was significantly higher in COVID-19 patients with MetS (OR, 1.74; 95% CI, 1.17 to 2.59; P=0.006). Patients with abnormal waist circumference were approximately 2.07 times more likely to develop severe COVID-19 (P<0.001), and high-density lipoprotein cholesterol (HDL-C) levels were significantly associated with COVID-19; the mortality risk due to COVID-19 was 1.74 times higher in men with an HDL-C level of <40 mg/dL and in women with an HDL-C level of <50 mg/dL (P=0.012).
Conclusion COVID-19 is likely associated with severity and death in patients with MetS or in patients with MetS risk factors. Therefore, patients with MetS or those with abnormal waist circumference and HDL-C levels need to be treated with caution.
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Background Risk assessment tools have been actively studied, and they summarize key predictors with relative weights/importance for a disease. Currently, standardized screening scores for type 2 diabetes mellitus (DM) and chronic kidney disease (CKD)—two key global health problems—are available in United States and Korea. We aimed to compare and evaluate screening scores for DM (or combined with prediabetes) and CKD, and assess the risk in contemporary United States and Korean populations.
Methods Four (2×2) models were evaluated in the United States-National Health and Nutrition Examination Survey (NHANES 2015–2018) and Korea-NHANES (2016–2018)—8,928 and 16,209 adults. Weighted statistics were used to describe population characteristics. We used logistic regression for predictors in the models to assess associations with study outcomes (undiagnosed DM and CKD) and diagnostic measures for temporal and cross-validation.
Results Korean adult population (mean age 47.5 years) appeared to be healthier than United States counterpart, in terms of DM and CKD risks and associated factors, with exceptions of undiagnosed DM, prediabetes and prehypertension. Models performed well in own country and external populations regarding predictor-outcome association and discrimination. Risk tests (high vs. low) showed area under the curve >0.75, sensitivity >84%, specificity >45%, positive predictive value >8%, and negative predictive value >99%. Discrimination was better for DM, compared to the combined outcome of DM and prediabetes, and excellent for CKD due to age.
Conclusion Four easy-to-use screening scores for DM and CKD are well-validated in contemporary United States and Korean populations. Prevention of DM and CKD may serve as first-step in public health, with these self-assessment tools as basic tools to help health education and disparity.
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Cardiovascular disease is the primary cause of mortality in women and men with diabetes. Due to age and worsening of risk factors over the menopausal transition, risk of coronary heart disease events increases in postmenopausal women with diabetes. Randomized studies have conflicted regarding the beneficial impact of estrogen therapy upon intermediate cardiovascular disease markers and events. Therefore, estrogen therapy is not currently recommended for indications other than symptom management. However, for women at low risk of adverse events, estrogen therapy can be used to minimize menopausal symptoms. The risk of adverse events can be estimated using risk engines for the calculation of cardiovascular risk and breast cancer risk in conjunction with screening tools such as mammography. Use of estrogen therapy, statins, and anti-platelet agents can be guided by such calculators particularly for younger women with diabetes. Risk management remains focused upon lifestyle behaviors and achieving optimal levels of cardiovascular risk factors, including lipids, glucose, and blood pressure. Use of pharmacologic therapies to address these risk factors, particularly specific hypoglycemic agents, may provide some additional benefit for risk prevention. The minimal benefit for women with limited life expectancy and risk of complications with intensive therapy should also be considered.
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Background The influencing factors of diabetic kidney disease (DKD) in Chinese patients with type 2 diabetes mellitus (T2DM) were explored to develop and validate a DKD diagnostic tool based on nomogram approach for patients with T2DM.
Methods A total of 2,163 in-hospital patients with diabetes diagnosed from March 2015 to March 2017 were enrolled. Specified logistic regression models were used to screen the factors and establish four different diagnostic tools based on nomogram according to the final included variables. Discrimination and calibration were used to assess the performance of screening tools.
Results Among the 2,163 participants with diabetes (1,227 men and 949 women), 313 patients (194 men and 120 women) were diagnosed with DKD. Four different screening equations (full model, laboratory-based model 1 [LBM1], laboratory-based model 2 [LBM2], and simplified model) showed good discriminations and calibrations. The C-indexes were 0.8450 (95% confidence interval [CI], 0.8202 to 0.8690) for full model, 0.8149 (95% CI, 0.7892 to 0.8405) for LBM1, 0.8171 (95% CI, 0.7912 to 0.8430) for LBM2, and 0.8083 (95% CI, 0.7824 to 0.8342) for simplified model. According to Hosmer-Lemeshow goodness-of-fit test, good agreement between the predicted and observed DKD events in patients with diabetes was observed for full model (χ2=3.2756, P=0.9159), LBM1 (χ2=7.749, P=0.4584), LBM2 (χ2=10.023, P=0.2634), and simplified model (χ2=12.294, P=0.1387).
Conclusion LBM1, LBM2, and simplified model exhibited excellent predictive performance and availability and could be recommended for screening DKD cases among Chinese patients with diabetes.
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