Metabolic syndrome and related disorders最新文献

Background and Aims: Visceral adipose tissue (VAT) is a key cardiometabolic risk factor. This study evaluates the association between VAT and adiposity indices and identifies reliable predictors of increased VAT. Methods: This cross-sectional study utilized data from 4696 participants in the National Health and Nutrition Examination Survey 2011-2018. VAT was measured via dual-energy X-ray absorptiometry. Adiposity indices included body mass index (BMI), waist circumference (WC), lipid accumulation product, visceral adiposity index, body shape index, body roundness index, and metabolic score for visceral fat (METS-VF). Correlation analysis, receiver operating characteristic curve analysis, and multivariate adaptive regression splines (MARS) modeling evaluated the performance of indices and identified key predictors of VAT. Results: All adiposity indices were significantly correlated with VAT (P < 0.001). Among them, METS-VF demonstrated the highest predictive performance for increased VAT (>130 cm²) followed by WC. Optimal cutoff values for METS-VF were 7.1 [areas under the curve (AUC): 0.887, 95% confidence interval (CI): 0.873-0.899] in men and 7.5 (AUC: 0.904, 95% CI: 0.891-0.916) in women. For WC, the cutoff values were 99.5 cm (AUC: 0.866, 95% CI: 0.851-0.879) in men and 96 cm (AUC: 0.883, 95% CI: 0.869-0.896) in women. MARS modeling identified race, age, WC, BMI, glucose, high-density lipoprotein cholesterol, and triglycerides as significant predictors of VAT, achieving an R² of 75.2%. Conclusion: METS-VF demonstrated the highest predictive value among the indices evaluated for predicting increased VAT. It may serve as a valuable tool in assessing visceral obesity and associated cardiometabolic risks.

Aims: Identifying participants with type 2 diabetes (T2D) based only on electronic health record (EHR) or self-reported data has limited accuracy. Therefore, the objective of the study was to develop an algorithm using EHR and self-reported data to identify participants with and without T2D. Methods: We included participants enrolled in the Mayo Clinic Biobank. At enrollment, participants completed a baseline questionnaire on health conditions, including T2D, and provided access to their EHR data. T2D status was based on self-report and EHR data (International Classification of Diseases codes, hemoglobin A1c [HbA1c], plasma glucose, and glucose-regulating medications) within 5 years prior to and 2 months after enrollment. Participants who self-reported T2D but lacked corroborating EHR data were categorized separately ("only self-reported T2D"). After identifying participants with T2D, we identified participants without T2D based on normal HbA1c and plasma glucose. Participants who self-reported the absence of T2D but lacked corroborating EHR data were categorized separately ("only self-reported no T2D"). Using manual chart reviews (gold standard), we calculated the positive and negative predictive values (NPV) to identify T2D. Results: Of 57,000 participants, the algorithm classified participants as having T2D (n = 6,238), no T2D (n = 38,883), "only self-reported T2D" (n = 757), and "only self-reported no-T2D" (n = 9,759). The algorithm had a high positive predictive value (96.0% [91.5%-98.5%]), NPV (100% [98.0%-100%]), and accuracy (99.5% [98.3%-99.8%]). Participant age (median [range]) ranged from 52 (18-98) years (only self-reported T2D) to 67 (19-99) years (T2D) (P < 0.0001), and the proportion of women ranged from 45.3% (T2D) to 69.6% (only self-reported no T2D) (P < 0.0001). Most participants were of the White race (84.0%-92.7%) and non-Hispanic ethnicity (97.6%-98.6%). Conclusions: In this study, we developed an algorithm to accurately identify participants with and without T2D, which may be generalizable to cohorts with linked EHR data.

Introduction: Severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) has been associated with the development of COVID-19. COVID-19 may cause endothelial cell dysfunction (ECD), which can lead to cardiometabolic diseases and podocytopathy. In this study, we explored whether presence of hyperglycemia predisposes to SARS-CoV-2 infection, in vitro, and whether COVID-19 can put an individual at a higher risk of persistent renal damage in the long-term following acute COVID infection. To estimate renal damage, we evaluated albuminuria and podocytopathy. Podocytopathy was estimated by measuring podocyte-specific protein levels in urine-derived exosomes from patients who were admitted with acute COVID-19 at 10 days, 6 months, and 12 months post-acute SARS-CoV-2 infection. Methods: Blood and urine samples from patients with SARS-CoV-2 post-infection were procured from the George Washington University COVID repository. Peripheral blood mononuclear cells and urine exosomes were isolated. Podocyte-specific proteins Podocalyxin (PODXL) and Nephrin (NEPH) were identified from urine exosomes. Results: Urine exosomal podocalyxin levels were significantly high at 10 week (n = 18; P = 0.001), 6 month (n = 25; P = 0.003) and 12 month (n = 14; P = 0.0001) time points. Nephrin levels were also noted to be high at 10 week (n = 18; P = 0.001) and 12 month (n = 14; P = 0.007) time points, compared with urine samples obtained from type 2 diabetes subjects who never had COVID-19. Though urinary podocyte-specific proteins were high, compared to control, there were no significant differences noted on urine albumin:creatinine ratios (UACR) between the groups. Conclusion: Persistent high levels of podocyte-specific proteins noted in urinary exosomes even at 12 months post-Covid may lead to the development of chronic kidney disease.

Background: Metabolic syndrome (MetS) is a clinical construct that conglomerates risk factors interconnected with cardiovascular diseases and type 2 diabetes. More than a thousand million individuals in the world were diagnosed with MetS in 2018. Objective: Our objective was to examine the prevalence of MetS and its components among Mexican adults. Methods: Data from 1733 adults aged ≥20 years who participated in the Mexican National Health and Nutrition Survey 2021. Sociodemographic, and clinical factors were gathered and analyzed. To define MetS, we used the harmonized diagnosis criteria. Results: The prevalence of MetS in Mexican adults was 45.3% (43.7% in men and 46.8% in women). This was mainly driven by increased abdominal obesity (AO) 79.8% and dyslipidemia (low high-density lipoprotein [HDL]-cholesterol and hypertriglyceridemia) 77.1%. The proportion of subjects with a least one MetS component was 90.5% and with any combination of two components was 25.2% and for three was 28.9%. The most frequent combination of MetS components was the cluster of AO, low HDL-cholesterol, and hypertriglyceridemia (15.6%). Conclusions: A high prevalence of MetS was registered in Mexico in 2021. Women and adults aged 40 years or older were the groups with the highest prevalence of MetS and its components. The health system in Mexico must promote strategies for the prevention and control of MetS and its components in adults.

Background: The role of the triglyceride-glucose (TyG) index in determining the effect of obesity on blood pressure (BP) in patients without diabetes remains unclear. We examined the association between body mass index (BMI), the TyG index, resting BP, and hypertension in Korean adults. Methods: We used the baseline data (4206 males and 4724 females aged 40-69 years) from the Korean Genome and Epidemiology Study conducted from 2001 to 2002. The primary outcomes were the TyG index, BMI, resting BP, and hypertension. The demographic characteristics, health behaviors, levels of fasting blood glucose, insulin resistance (IR) markers, lipoprotein lipids, and liver enzymes were included as covariates. Results: The TyG index was significantly associated with higher IR marker levels, poor lipoprotein-lipid profiles, elevated hepatic liver enzyme levels, elevated BP, and hypertension. Logistic regression analysis showed that individuals living with obesity had a higher risk of hypertension compared to individuals with underweight. Individuals in the second, third, and fourth quartiles of the TyG index had a higher risk of hypertension compared with those in the first quartile (odds ratio = 1). Mediation analysis showed that BMI has an indirect effect on diastolic and systolic BP through the TyG index. Conclusion: Our study findings indicate that the TyG index plays a pathological intermediary role between obesity and increased BP in individuals without diabetes, implying its clinical value in assessing the impact of obesity on hypertension risk.

Background: Household food insecurity (HFI) refers to the lack of access to safe and nutritious food, and this condition may be associated with the occurrence of metabolic syndrome (MetS). Thus, this study aimed to conduct a quantitative synthesis (meta-analysis) to summarize the evidence from epidemiological studies on the association between HFI and MetS. Methods: A systematic search was conducted in the PubMed, Embase, Web of Science, and Latin American and Caribbean Health Sciences Information Center databases to retrieve epidemiological studies published until October 2023. The entire process of selection, data extraction, and assessment of article quality was independently performed by two reviewers. The quality of the studies was evaluated using the criteria proposed by the National Institutes of Health instrument. The random-effects model was used to report the quantitative synthesis of combined data. The Q-test and I² index were used to assess heterogeneity. Egger's and Begg's tests were employed to evaluate publication bias. Results: A total of 10 articles meeting the eligibility criteria were selected and included in this meta-analysis. High heterogeneity was observed among the studies (I² > 70), along with a low risk of publication bias. Considering all ten included studies, no statistically significant association was found between HFI and MetS (odds ratio = 1.17; 95% confidence interval: 0.89-1.55; I² = 79.9%). Conclusions: The findings of this meta-analysis did not reveal a statistically significant association between HFI and MetS, indicating the need for further studies aimed at exploring and expanding the scientific evidence on this relationship.

Background: This study aimed to explore the association of cardiometabolic index (CMI), CMI-age, visceral adiposity index (VAI), and VAI-age with heart failure (HF) and to compare those indicators for early identification of HF. Methods: Drawing from the National Health and Nutrition Examination Survey (NHANES) for 2011-2018, we enrolled 8999 participants in a cross-sectional study. The association of different visceral obesity indicators (CMI, CMI-age, VAI, and VAI-age) with HF was estimated by multivariable regression analysis. Receiver operating characteristic (ROC) curves were used to examine the predictive ability of CMI, CMI-age, VAI, and VAI-age on patients with HF. Results: CMI, CMI-age, VAI and VAI-age showed positive correlations with HF. When indicators were analyzed as continuous variables, CMI, CMI-age, VAI, and VAI-age showed positive correlations with HF in both the crude and adjusted models (all P < 0.05). When indicators were analyzed as categorical variables, it was found that in all four models, the ORs of group Q4 was significantly different compared to Q1 (all P < 0.05), suggesting the risk of HF is significantly increased with higher CMI, CMI-age, VAI, or VAI-age. The association between those indicators (CMI, CMI-age, VAI, and VAI-age) and HF was similar in all stratified populations (P for interaction >0.05).The areas under the ROC curve (AUCs) of four indicators in predicting HF were significantly different (CMI: 0.610, 95% CI, 0.578-0.643; CMI-age: 0.700, 95% CI, 0.669-0.726; VAI: 0.593, 95% CI, 0.561-0.626; VAI-age: 0.689, 95% CI, 0.661-0.718), suggesting that CMI-age was significantly better than the other three indicators in predicting HF (P < 0.001). Conclusions: CMI, CMI-age, VAI, and VAI-age were all independently correlated with the risk of HF. In four indicators, the CMI-age was significantly better than the other three indicators in predicting HF, which provides new insights into the prevention and management of HF.

Sodium-glucose cotransporter-2 (SGLT2) inhibition and lactation result in the excretion of large amounts of glucose in urine or milk and are associated with a lower risk of cardiovascular events. The respective mechanisms behind this association with cardiovascular protection are not clear. This review compares the contribution of noninsulin-mediated glucose transport during pharmacologic inhibition of SGLT2 with noninsulin-mediated glucose transport during lactation in terms of the implications for the cardiometabolic health of parous women. The search topics used to obtain information on SGLT2 inhibitors included mechanisms of action, atherosclerosis, and heart failure. The search topics used to obtain information on lactation included cardiovascular health and milk composition. Subsequent reference searches of retrieved articles were also used. Active treatment with SGLT2 inhibitors affects glucose and sodium transport in the kidneys and predominantly protects against hospitalization for heart failure soon after the onset of therapy. Active lactation stimulates glucose transport into the mammary gland and improves subclinical and clinical atherosclerotic vascular disease years after delivery. Both SGLT2 inhibitors and lactation have effects on a variety of glucose transporters. Several mechanisms have been proposed to explain the cardiometabolic benefits of SGLT2 inhibition and lactation. Learning from the similarities and differences between both processes will advance our understanding of cardiometabolic health for all people.

Background: Socioeconomic status and lifestyle factors could potentially modify the association between diet and chronic diseases such as metabolic syndrome (MetS). Objective: This study aimed to investigate the combined effect of socioeconomic status, lifestyle factors, and dietary patterns on the MetS risk. Methods: During 8.9 years of follow-up, dietary information of 1915 individuals was collected by a validated Food Frequency Questionnaire (FFQ). Dietary patterns were derived using principal component analysis. Results: Two major dietary patterns including healthy dietary and Western dietary patterns were identified. In the crude and fully adjusted models, an association was not found between Western and healthy dietary patterns and the risk of MetS. There was a significant decrease in the risk of MetS among participants with higher levels of education who adhered to a healthy dietary pattern (hazard ratio: 0.71, 95% confidence interval: 0.34-0.89). Furthermore, the risk of MetS decreased in the fourth quartile of healthy dietary pattern among nonemployed (0.78, 0.51-0.94). According to the stratification of physical activity levels, it was shown that the healthy dietary pattern had a negative association with the risk of MetS only among participants who engaged in a high level of physical activity (0.70, 0.40-0.91). About the smoking status, it was shown that among non-smoker participants, higher adherence to a healthy dietary pattern was associated with a reduction in the risk of MetS. The risk of MetS reduced by 36% (0.64, 0.51-0.97) in the third quartile and by 39% (0.61, 0.54-0.95) in the fourth quartile of the healthy dietary pattern. No association was found between Western dietary pattern with MetS in different status of socioeconomic and lifestyle factors. Conclusions: Adhering to a healthy dietary pattern, engaging in regular physical activity, and abstaining from smoking could reduce incidents of MetS. Moreover, socioeconomic status modified the association between healthy dietary pattern and MetS.