Metabolic Syndrome Severity Score Research Articles

Evaluating the Potential of a Novel Metabolic Syndrome Severity Score to Inform Exercise Interventions for People with Complex Chronic Conditions.

Aims: Exercise interventions positively affect numerous cardiometabolic risk factors. To better evaluate the health effects of exercise training, it may be more appropriate to evaluate risk factors together. The Metabolic Syndrome Severity Score (MetSSS) is a composite score representing cardiometabolic risk. Purpose: To evaluate the relationships between physical activity, neuromuscular fitness, exercise capacity, and the MetSSS in a heterogenous sample of people with complex chronic disease. Material and Methods: Fifty-three people with kidney or liver disease and at least one feature of the metabolic syndrome (MetS) were included. Pearson correlations were conducted between physical activity, neuromuscular fitness, exercise capacity, and the MetSSS. Linear regressions were performed for multi-level categorical variables. Independent variables with an association with MetSSS (P ≤ 0.2) were included in a multiple regression analysis. Results: The 6-minute walk test (6MWT) distance was inversely and independently associated with MetSSS [standardized beta coefficient (β) = -0.31, P = 0.04]. No relationship was found between MetSSS and physical activity or neuromuscular fitness. Mean 6MWT in the highest tertile was 550 m (range: 505-620 m) and 346 m (range: 233-408 m) in the lowest. The analysis showed a medium-large between-group effect for the difference in MetSSS for the lowest and highest tertile of 6MWT [Eta squared (η2) = 0.16, P = 0.01]. Conclusions: Exercise capacity was inversely and independently associated with MetSSS in people with complex chronic disease. Clinical trials with exercise interventions are needed to further investigate if improvements in exercise capacity result in clinically significant changes in the MetSSS.

Association between metabolic syndrome severity score and cardiovascular disease: results from a longitudinal cohort study on Chinese adults.

This study aimed to quantify the severity of metabolic syndrome(MetS) and investigate its association with cardiovascular disease(CVD) risk on Chinese adults. 13,500 participants from the Zhejiang Adult Chronic Disease Study were followed up between 2010 and 2021.A continuous MetS severity score derived from the five components of MetS was used to quantify MetS severity, and the association between MetS severity and the risk of incident CVD was assessed using Cox proportional hazard and restricted cubic spline regression. Both the presence and severity of MetS were strongly associated with CVD risk. MetS was related to an increased risk of CVD (hazard ratio(HR):1.700, 95% confidence interval(CI): 1.380-2.094). Compared with the hazard ratio for CVD in the lowest quartile of the MetS severity score, that in the second, third, and highest quartiles were 1.812 (1.329-2.470), 1.746 (1.265-2.410), and 2.817 (2.015-3.938), respectively. A linear and positive dose-response relationship was observed between the MetS severity and CVD risk (P for non-linearity = 0.437). Similar results were found in various sensitivity analyses. The MetS severity score was significantly associated with CVD risk. Assessing MetS severity and further ensuring intervention measures according to the different severities of MetS may be more useful in preventing CVD.

He Rourou Whai Painga, an Aotearoa New Zealand Dietary Pattern for Metabolic Health and Whānau Wellbeing: Protocol for a randomised controlled trial

Cardiometabolic diseases are highly prevalent in Aotearoa New Zealand(1). Dietary intake is a modifiable risk factor for such diseases and certain dietary patterns, specifically the Mediterranean diet (MedDiet), are associated with improved metabolic health(2). This study aims to test whether an intervention of a Mediterranean dietary pattern incorporating high quality New Zealand foods (NZMedDiet pattern) using behaviour change science can improve the metabolic health of participants and their household/whānau. This is a multi-centre, three-stage trial, with two randomised controlled trials (RCTs), both parallel groups, superiority trials, and a longitudinal cohort study. The first RCT (RCT1) is a comparison of the NZMedDiet pattern implemented using behaviour science compared to usual diet for 12 weeks, and the second (RCT2) is a behaviour-change intervention compared to no intervention for 12 weeks, administered after participants have been exposed to the intervention in RCT1. The third stage is a longitudinal cohort study where all participants are followed for up to a year. The primary outcome measure for each stage is the metabolic syndrome severity score (MetSSS). Two hundred index participants and their household/whānau have been recruited and randomised into the trial. Participants are from four centres, two of which are University research units (University of Auckland (n = 57) and University of Otago, Christchurch (n = 60)), one a community-based traditional meeting place (Tu¯ Kotahi Māori Asthma and Research Trust at Ko¯kiri Marae in Lower Hutt, Wellington (n = 19)), and the other based at a hospital-based research unit (the Centre for Endocrine Diabetes and Obesity Research (CEDOR) in Wellington (n = 64). The trial will test whether the NZMedDiet pattern and behaviour change support improves the cardiometabolic health of people in New Zealand.

Exposure to per- and polyfluoroalkyl substance and metabolic syndrome: A nationally representative cross-sectional study from NHANES, 2003–2018

Per- and polyfluoroalkyl substances(PFAS) are widespread organic pollutants with endocrine-disrupting effects on human health, but the association of PFAS exposure with metabolic syndrome remains conflicting. National Health and Nutrition Examination Survey(NHANES) program was utilized to evaluate the association of individual PFAS exposure and metabolic disorders and further determined the joint effect of PFAS co-exposures. 13921 participants and five PFAS exposures(PFHxS, MPAH, PFDE, PFNA, and PFUA) were included for analysis. The association between individual PFAS and metabolic syndrome varied in the specific PFAS and the specific metabolic disorder examined. PFHxS was negatively associated with obesity(Q4; OR = 0.75; P < 0.001), but positively associated with hyperlipidemia (Q3; OR = 1.2; P = 0.013). PFUA was negatively associated with obesity (Q4; OR = 0.6; P < 0.001), hyperlipidemia (Q3; OR = 0.85; P = 0.03), and non-alcoholic fatty liver disease (NAFLD, Q4; OR = 0.64; P = 0.015), but positively associated with hyperglycemia(Q3; OR = 1.27; P = 0.004). Furthermore, PFAS co-exposures were negatively associated with obesity(OR = 0.63; P < 0.001) and NAFLD(OR = 0.85; P = 0.021), and positively associated with hyperlipidemia(OR = 1.05; P = 0.022), but not significantly associated with hyperglycemia or hypertension. Overall, there was a negative association between PFAS co-exposures and metabolic severity score(β = −0.15; P < 0.001). Subgroup analysis stratified by gender and obesity consistently showed the negative association of PFAS co-exposures with metabolic severity score, and the positive association with hyperlipidemia. However, subgroup analysis showed a negative association with NAFLD in females but not in males, and a negative association with hyperglycemia in the obesity group, but not in the non-obesity group. Collectively, our study showed a negative association of PFAS co-exposures with metabolic syndrome severity score, but did not support a consistent association between PFAS co-exposures and individual components of metabolic syndrome. Additionally, there were gender-specific as well as BMI-specific differences in these associations. Further studies are needed to rule out the reverse causality and clarify the relationship of PFAS co-exposures with the specific metabolic disorder.

Harnessing Metabolic Indices as a Predictive Tool for Cardiovascular Disease in a Korean Population without Known Major Cardiovascular Event.

This study evaluated the usefulness of indices for metabolic syndrome, non-alcoholic fatty liver disease (NAFLD), and insulin resistance (IR), as predictive tools for cardiovascular disease in middle-aged Korean adults. The prospective data obtained from the Ansan-Ansung cohort database, excluding patients with major adverse cardiac and cerebrovascular events (MACCE). The primary outcome was the incidence of MACCE during the follow-up period. A total of 9,337 patients were included in the analysis, of whom 1,130 (12.1%) experienced MACCE during a median follow-up period of 15.5 years. The metabolic syndrome severity Z-score, metabolic syndrome severity score, hepatic steatosis index, and NAFLD liver fat score were found to significantly predict MACCE at values above the cut-off point and in the second and third tertiles. Among these indices, the hazard ratios of the metabolic syndrome severity score and metabolic syndrome severity Z-score were the highest after adjusting for confounding factors. The area under the receiver operating characteristic curve (AUC) of the 10-year atherosclerotic cardiovascular disease (ASCVD) score for predicting MACCE was 0.716, and the metabolic syndrome severity Z-score had an AUC of 0.619. The metabolic syndrome severity score is a highly reliable indicator and was closely associated with the 10-year ASCVD risk score in predicting MACCE in the general population. Given the specific characteristics and limitations of metabolic syndrome severity scores as well as the indices of NAFLD and IR, a more practical scoring system that considers these factors is essential to achieve greater accuracy in forecasting cardiovascular outcomes.

BMI-based metabolic syndrome severity score and arterial stiffness in a cohort Chinese study

Background and aimsTo investigate the relationship between metabolic syndrome severity z score(MetS-Z) and arterial stiffness(AS). Methods and resultsA total of 7621 participants who took three physical examination and brachial-ankle pulse wave velocity(ba-pwv) test from 2006 were enrolled. Cumulative MetS-Z(cMetS-Z) was calculated by using blood pressure, triglycerides, HDL cholesterol, blood glucose and BMI. AS was assessed by ba-pwv. Cox regression model was used to evaluate the risk of AS. All participants were divided into four groups according to cMetS-Z(Q1-Q4). The average age of the participants was 43.06 ± 8.91 years old. During a median follow-up of 6.27 years, 1831cases of AS were identified. The incident rate of AS increased gradually from group Q1 to Q4. Compared with the lowest cMetS-Z(group Q1), the adjusted hazard ratio (HR) and 95% confidence interval (CI) of group Q2-Q4 for AS were 1.27 (1.09–1.47),1.28(1.10–1.48) and 1.45 (1.24–1.69) respectively. The cubic spline model indicated cMetS-Z had a liner relationship with AS and the cut-off value was lower than zero. Sub-group analysis suggested cMetS-Z was related to AS especially among participants who were younger and without obesity or hypertension or diabetes. ConclusionHigher cMetS-Z was associated with an increased risk of AS in this cohort community study, and this relationship seemed to be stronger among normal healthy subjects. Registration numberChiCTR-TNC-11001489. Clinical trialJanuary 1st 2006, ChiCTR-TNC-11001489 and 2011.

Metabolic syndrome risk among adolescents in the Deep South and the relationships with behavioral health, food insecurity, and physical activity.

A combination of physical and psychosocial risk factors put adolescents at risk for poor cardiometabolic health and chronic disease burden, often recognized as metabolic syndrome. The purposes of this study were to (1) identify the prevalence of metabolic syndrome risk among adolescents, utilizing the metabolic syndrome severity index, and (2) determine the relationship between metabolic syndrome risk and behavioral health, food insecurity, and physical inactivity among adolescents. A cross-sectional, descriptive, correlational design was deployed in an inner-city high school in the Deep South. An 8-month recruitment and enrollment period yielded a sample of 55 adolescents. A battery of measures included assessment of demographic data, anthropometric, cardiovascular, and psychosocial data. Utilizing these data elements, a progressive methodological approach was used to identify metabolic severity risk as a continuous variable for use in the adolescent population. All participants identified as African American/Black. Among them, 71% (N = 39) were female and an average age of 16 (SD = 1.3) years old, with 67.3% (N = 37) of the sample at risk for metabolic syndrome. There was not a statistically significant relationship between metabolic syndrome severity score and behavioral health risk, food insecurity, and physical inactivity in this sample. Future use of the continuous metabolic syndrome severity score may guide practice by utilizing longitudinal data to assess the trends of metabolic syndrome severity scores in relation to disease outcomes in adolescents. This may promote the identification of psychosocial and physical interrelationships with metabolic syndrome, thus improving overall health through the development of age-appropriate interventions.

He Rourou Whai Painga, an Aotearoa New Zealand dietary pattern for metabolic health and whānau wellbeing: protocol for a randomized controlled trial.

Cardiometabolic diseases are highly prevalent in Aotearoa New Zealand. Dietary intake is a modifiable risk factor for such diseases and certain dietary patterns, specifically the Mediterranean diet (MedDiet), are associated with improved metabolic health. This study aims to test whether an intervention including a Mediterranean dietary pattern incorporating high quality New Zealand foods (NZMedDiet pattern) and behavior change science can improve the metabolic health of participants and their household/whānau. This is a multi-center, three-stage trial with two parallel group superiority randomized controlled trials (RCTs), and a longitudinal cohort study embedded within the trial design. The first RCT (RCT 1) is a comparison of the NZMedDiet pattern compared to usual diet for 12 weeks. The Behavior Change Wheel was used to select and implement strategies to support participant adherence to the NZMedDiet, such as web-based nutrition education on healthy shopping and cooking. The second (RCT 2) compares online social support to no online social support for 12 weeks, administered to participants immediately following RCT 1. The third stage is a longitudinal cohort study where all participants are followed from the beginning of their start of the active intervention for 12 months in total. The primary outcome measure for each stage is the metabolic syndrome severity score (MetSSS). The duration of enrolment is 12-15 months. The total recruitment target is 200 index participants and their household/whānau members who participate with them, and the primary analyses will be intention to treat on index participants. The trial will test whether the NZMedDiet pattern and behavior change support improves the cardiometabolic health of people in Aotearoa New Zealand. https://www.anzctr.org.au/Default.aspx, identifier ACTRN12622000906752 and https://www.isrctn.com/, identifier ISRCTN89011056 (Spirit 2).

A high quality Aotearoa New Zealand dietary pattern adapting a Mediterranean diet for metabolic health: a feasibility study

AimTo assess the feasibility of a family-based dietary intervention study using a meal kit home delivery service, in people at risk of cardio-metabolic disease.MethodsA 12-week dietary intervention feasibility study of adults (termed the index participants) at increased risk of metabolic and cardiovascular disease, enriched for Māori who are indigenous New Zealanders. The study sample also included the household/whānau members living with the index participant. All participants received a 12 week intervention using weekly home delivery of meal kits and groceries consistent with a Mediterranean dietary pattern. Outcomes were the metabolic syndrome severity score (MetSSS); feasibility and acceptability of the intervention; dietary intake; and other clinical and anthropometric measures.ResultsThere were 29 index participants recruited and in addition, 50 household/whānau members took part in the feasibility study. The mean (SD) household/whānau size was 3.45 (1.4) people, and the mean (SD) number of people in each household/whānau who participated in the study was 2.84 (1.2). The feasibility of intervention to households/whānau was proven in this context. The mean (SD) change in MetSSS was 0.03 (0.33), N = 27, P = 0.69 and there was a statistically significant decrease in body weight of 1.37 kg (95% CI 0.11 to 2.62), p = 0.034. The food deliveries were well received, the dinner kits more so than the grocery items.ConclusionIt is feasible to recruit individuals and households/whānau to a family-based dietary intervention. Use of a meal kit home delivery service to provide food which is consistent with the intervention dietary pattern was well received. This feasibility study identified improvements to be made such as nutrition behaviour change support, more variety in food provided, more recipes, and better matching of food quantity to family size.Trial registrationANZCTR—ACTRN12621000856819p registered 2.JUN.2021 https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=382021&isReview=true

A Preliminary Investigation into the Frequency Dose Effects of High-Intensity Functional Training on Cardiometabolic Health.

The objective of this study was to explore the effects of three weekly frequency doses of high-intensity functional training (HIFT) on an array of cardiometabolic markers in adults with metabolic syndrome (MetS). Twenty-one men and women, randomized into one (HIFT1), two (HIFT2), or three (HIFT3) days per week of HIFT, completed 3-weeks of familiarization plus a 12-week progressive training program. Pre- and post-intervention, several cardiometabolic, body composition, oxygen consumption, metabolic syndrome severity, and perceptions of fitness measurements were assessed. Additionally, an exercise enjoyment survey was administered post-intervention. A Cohen's d was used to demonstrate within-group change effect size. Although this study was not fully powered, a one-way and two-way ANOVA were used to compare the dose groups to provide provisional insights. No differences were found when frequency dose groups were compared. Many cardiometabolic, body composition, and fitness improvements were seen within each group, with clinically meaningful improvements in the metabolic syndrome severity score (MSSS) (HIFT1: -0.105, d = 0.28; HIFT2: -0.382, d = 1.20; HIFT3: -0.467, d = 1.07), waist circumference (HIFT1: -4.1cm, d = 3.33; HIFT2: -5.4cm, d = 0.89; HIFT3: -0.7cm, d = 0.20), and blood glucose (HIFT1: -9.5mg/dL, d = 0.98; HIFT2: -4.9mg/dL, d = 1.00; HIFT3: -1.7mg/dL, d = 0.23). All three groups similarly reported high exercise enjoyment and likeliness to continue after the intervention. In conclusion, HIFT performed once, twice, or thrice a week elicits improvements in MetS and is considered enjoyable. HIFT, even at a low weekly dose, therefore represents a potential strategy to reduce the global MetS burden.

Trajectory patterns of metabolic syndrome severity score and risk of type 2 diabetes

BackgroundThe available evidence indicates that the severity of metabolic syndrome tends to worsen progressively over time. We assessed the trajectory of age and sex-specific continuous MetS severity score (cMetS-S) and its association with the development of diabetes during an 18-year follow-up.MethodsIn a prospective population-based Tehran Lipid and Glucose Study, 3931 eligible participants free of diabetes, aged 20–60 years, were followed at three-year intervals. We examined the trajectories of cMetS-S over nine years using latent growth mixture modeling (LGMM) and subsequent risks of incident diabetes eight years later. The prospective association of identified trajectories with diabetes was examined using the Cox proportional hazard model adjusting for age, sex, education, and family history of diabetes, physical activity, obesity (BMI ≥ 30 kg/m2), antihypertensive and lipid-lowering medication, and baseline fasting plasma glucose in a stepwise manner.ResultsAmong 3931 participants, three cMetS-S trajectory groups of low (24.1%), medium (46.8%), and high (29.1%) were identified during the exposure period. Participants in the medium and high cMetS-S trajectory classes had HRs of 2.44 (95% CI: 1.56–3.81) and 6.81 (95% CI: 4.07–10.01) for future diabetes in fully adjusted models, respectively. Normoglycemic individuals within the high cMetS-S class had an over seven-fold increased risk of diabetes (HR: 7.12; 95% CI: 6.05–12.52).ConclusionAlthough most adults exhibit an unhealthy metabolic score, its severity usually remains stable throughout adulthood over ten years of follow-up. The severity score of metabolic syndrome has the potential to be utilized as a comprehensive and easily measurable indicator of cardiometabolic dysfunction. It can be employed in clinical settings to detect and track individuals at a heightened risk of developing T2DM, even if their glucose levels are normal.

The Prevalence and Risk Factors of Metabolic Syndrome in Patients with Hemodialysis.

Metabolic syndrome is a common disorder that puts patients at high risk for cardiovascular disease (CVD) and mortality. To our knowledge, there is no published study in Pub Med which evaluated both lifestyle and metabolic syndrome in hemodialysis patients. This study aimed to estimate the prevalence of metabolic syndrome and investigate the potential risk factors in hemodialysis patients. This was a cross-sectional study conducted on 204 patients enrolled conveniently. National Cholesterol Education Program Adult Treatment Panel III criteria considered for Metabolic Syndrome. Demographics, lifestyle, and disease characteristics were gathered. The relationship between metabolic syndrome and its severity with independent variables was investigated through multivariable multivariate logistic and linear regressions. The mean (SD) age was 55 (14) years and 42% were women. 42.6% had metabolic syndrome. Low high-density lipoprotein (HDL), high fasting blood sugar, high blood pressure (BP), increased waist circumference (WC), and high triglyceride were observed in decreasing order of frequency in 54.4%, 44.1%, 38.7%, 33.3% 28.9% of patients, respectively. The logistic regression model revealed significant associations between metabolic syndrome and physical activity (OR=0.85, 95% CI : 0.74-0.97), mood (OR=1.04, 95% CI : 1.002-1.078), age (OR=1.023, 95% CI : 1.001-1.046), and missed work (OR=0.86, 95% CI : 0.76-0.97). The linear regression model revealed significant associations between metabolic syndrome severity score and physical activity (B=-0.12, 95% CI : -0.21-0.02) and sleep quality (B=0.017, 95% CI : 0.001-0.033). Poorer sleep quality, lower physical activity, lower mood status, and older age were associated with higher odds of metabolic syndrome/metabolic syndrome severity score in hemodialysis patients.

The nurse-led GILL eHealth intervention for improving physical health and lifestyle behaviours in clients with severe mental illness: design of a cluster-randomised controlled trial

BackgroundClients with severe mental illness (SMI) have overall poor physical health. SMI reduces life expectancy by 5–17 years, primarily due to physical comorbidity linked to cardiometabolic risks that are mainly driven by unhealthy lifestyle behaviours. To improve physical health in clients with SMI, key elements are systematic somatic screening and lifestyle promotion. The nurse-led GILL eHealth was developed for somatic screening and the implementation of lifestyle activities in clients with SMI. Aims of this study are to evaluate the effectiveness of the GILL eHealth intervention in clients with SMI compared to usual care, and to evaluate the implementation process, and the experiences of clients and healthcare providers with GILL eHealth.MethodsThe GILL study encompasses a cluster-randomised controlled trial in approximately 20 mental health care facilities in the Netherlands. The randomisation takes place at the team level, assigning clients to the eHealth intervention or the usual care group. The GILL eHealth intervention consists of two complementary modules for somatic screening and lifestyle promotion, resulting in personalised somatic treatment and lifestyle plans. Trained mental health nurses and nurse practitioners will implement the intervention within the multidisciplinary treatment context, and will guide and support the participants in promoting their physical health, including cardiometabolic risk management. Usual care includes treatment as currently delivered, with national guidelines as frame of reference. We aim to include 258 clients with SMI and a BMI of 27 or higher. Primary outcome is the metabolic syndrome severity score. Secondary outcomes are physical health measurements and participants’ reports on physical activity, perceived lifestyle behaviours, quality of life, recovery, psychosocial functioning, and health-related self-efficacy. Measurements will be completed at baseline and at 6 and 12 months. A qualitative process evaluation will be conducted alongside, to evaluate the process of implementation and the experiences of clients and healthcare professionals with GILL eHealth.DiscussionThe GILL eHealth intervention is expected to be more effective than usual care in improving physical health and lifestyle behaviours among clients with SMI. It will also provide important information on implementation of GILL eHealth in mental health care. If proven effective, GILL eHealth offers a clinically useful tool to improve physical health and lifestyle behaviours.Trial registrationClinical trial registration NCT05533749, registration date: 8 September 2022.

Independent association between age- and sex-specific metabolic syndrome severity score and cardiovascular disease and mortality

Traditional metabolic syndrome (MetS) criteria have several limitations, which hinder its use in clinical practice. To overcome the limitations, we investigated the association between age- and sex-specific continuous MetS severity score (cMetS-S) and cardiovascular disease (CVD) and mortality beyond MetS components in the framework of the Tehran Lipid and Glucose Study. Participants aged 20–60 years at baseline were included in the study. We excluded participants with CVD, cancer, use of corticosteroids, estimated glomerular filtration rate < 30 ml/min/1.73 m2, and those who were pregnant. We evaluated the association between cMetS-S with CVD and mortality over 18 years of follow-up among 8500 participants with continuous and quantile approaches using the Cox proportional hazard regression model. In addition, the model performance of cMetS-S for predicting CVD events was compared to the conventional MetS criteria. Participants with higher cMetS-S had a significantly increased risk for CVD, coronary (CHD) and non-coronary heart disease (non-CHD), and all-cause, cardiovascular, and sudden cardiac death. Independent of the confounders and MetS components, the cMetS-S had the HRs of 1.67 (95% CI 1.47–1.89), 1.60 (95% CI 1.37–1.86), and 1.88 (95% CI 1.50, 2.35) for CVD, CHD, and non-CHD events upon 1-SD increment, respectively. The risk of mortality was increased for 1-SD of cMetS-S (all-cause mortality, HR 1.24; 95% CI 1.09–1.41; CVD mortality, HR 1.72; 95% CI 1.20–2.45; sudden cardiac death, HR 1.60; 95% CI 1.03–2.49). The model fitness of cMetS-S was superior to the conventional MetS criteria in predicting CVD and mortality. The cMetS-S provided an additional risk for CVD and mortality beyond the individual MetS components. Standardized cMetS-S could be a potential universal measure to define MetS severity while considering the weighted contribution of MetS components and their variations by age, sex, and ethnicity.

Systemic Lupus, Metabolic Syndrome, Cardiac Disease, and Peripheral Artery Disease

Systemic Lupus, Metabolic Syndrome, Cardiac Disease, and Peripheral Artery Disease

Associations of metabolic syndrome, its severity with cognitive impairment among hemodialysis patients

BackgroundIn the general population, metabolic syndrome (MetS) is associated with increased risk of cognitive impairment, including global and specific cognitive domains. These associations are not well studied in patients undergoing hemodialysis and were the focus of the current investigation.MethodsIn this multicenter cross-sectional study, 5492 adult hemodialysis patients (3351 men; mean age: 54.4 ± 15.2 years) treated in twenty-two dialysis centers of Guizhou, China were included. The Mini-Mental State Examination (MMSE) was utilized to assess mild cognitive impairment (MCI). MetS was diagnosed with abdominal obesity, hypertension, hyperglycemia, and dyslipidemia. Multivariate logistic and linear regression models were used to examine the associations of MetS, its components, and metabolic scores with the risk of MCI. Restricted cubic spline analyses were performed to explore the dose–response associations.ResultsHemodialysis patients had a high prevalence of MetS (62.3%) and MCI (34.3%). MetS was positively associated with MCI risk with adjusted ORs of 1.22 [95% confidence interval (CI) 1.08–1.37, P = 0.001]. Compared to no MetS, adjusted ORs for MCI were 2.03 (95% CI 1.04–3.98) for 22.51 (95% CI 1.28–4.90) for 3, 2.35 (95% CI 1.20–4.62) for 4, and 2.94 (95% CI 1.48–5.84) for 5 components. Metabolic syndrome score, cardiometabolic index, and metabolic syndrome severity score were associated with increased risk of MCI. Further analysis showed that MetS was negatively associated with MMSE score, orientation, registration, recall and language (P < 0.05). Significant interaction effect of sex (P for interaction = 0.012) on the MetS-MCI was observed.ConclusionMetabolic syndrome was associated with MCI in hemodialysis patients in a positive dose–response effect.

The Relationship between Sleep Duration and Metabolic Syndrome Severity Scores in Emerging Adults.

Research suggests sleep duration can influence metabolic systems including glucose homeostasis, blood pressure, hormone regulation, nervous system activity, and total energy expenditure (TEE), all of which are related to cardiometabolic disease risk, even in young adults. The purpose of this study was to examine the relationship between sleep duration and metabolic syndrome severity scores (MSSS) in a sample of emerging adults (18-24 y/o). Data were collected between 2012 and 2021 from the College Health and Nutrition Assessment Survey, an ongoing, cross-sectional study conducted at a midsized northeastern university. Anthropometric, biochemical, and clinical measures were obtained following an overnight fast and used to assess the prevalence of metabolic syndrome (MetS). MetS severity scores (MSSS) were calculated using race- and sex-specific formulas. Sleep duration was calculated from the difference in self-reported bedtime and wake time acquired through an online survey. ANCOVA was used to examine the relationship between sleep duration and MetS severity score while adjusting for covariates (age, sex, BMI, physical activity level, smoking status, alcohol consumption, and academic major). In the final sample (n = 3816), MetS (≥3 criteria) was present in 3.3% of students, while 15.4% of students presented with ≥2 MetS criteria. Mean MSSS was -0.65 ± 0.56, and the reported sleep duration was 8.2 ± 1.3 h/day. MSSS was higher among low sleepers (<7 h/day) and long sleepers (>9 h/day) compared to the reference sleepers (7-8 h/day) (-0.61 ± 0.02 and -0.63 ± 0.01 vs. -0.7 ± 0.02, respectively, p < 0.01). Our findings suggest short (<7 h/day) and long (>9 h/day) sleep durations raise the risk of MetS in a sample of emerging adults. Further research is needed to elucidate the impact of improving sleep habits on future disease risk.

Metabolic syndrome severity score in the middle-aged and elderly Iranian population: A cross-sectional survey of Bandare-Kong Cohort Study (the findings of PERSIAN Cohort Study).

Metabolic syndrome (MetS) is defined as the presence of several metabolic risk factors. The traditional MetS criteria have been considered insufficient for evaluating individuals at risk. MetS has always been categorized using binary criteria, which deny that the risk associated with MetS is likely to exist as a continuum. Also, MetS may present differently depending on age, sex, race, or ethnicity. We aimed to derive age-sex-specific equations for MetS severity scores within a southern Iranian population. This study used first-phase data from the Bandare-Kong Non-Communicable Diseases (BKNCD) Cohort Study as part of the Prospective Epidemiological Research Studies in IrAN (PERSIAN). After exclusion of the pregnant women, diabetic patients, and individuals taking antihypertensive, antihyperlipidemic, and antidiabetic medications, 2,735 individuals aged 35 to 70 years were selected for analysis. The diagnosis of MetS was based on the National Cholesterol Education Program (NCEP) criteria for the Iranian population. Confirmatory factor analysis (CFA) was performed to formulate MetS severity scores. The receiver operating characteristic (ROC) analysis was performed to validate MetS severity score equations for age-sex-specific categories. Triglyceride had the highest factor loading range in all age-sex categories for determining the MetS severity score. Conversely, systolic blood pressure and fasting plasma glucose (FPG) exhibited the lowest factor loadings across all age-sex groups. In both sexes, when age was considered, systolic blood pressure and FPG factor loadings were less significant among subjects aged ≥45 and 35-44 years, respectively. MetS severity scores might be more applicable than the current criteria of MetS. Prospective population-based studies should be conducted to assess the accuracy and validity of the MetS severity score for predicting cardiometabolic diseases.

Metabolic syndrome severity score (MetSSS) associates with metabolic health status in multi-ethnic Aotearoa New Zealand cohorts

AimTo investigate the relationship of metabolic syndrome severity score (MetSSS) with glucose regulatory and cardiovascular disease (CVD) status in Aotearoa New Zealand. MethodsMetSSS and MetSSS component coefficients were calculated for participants from the cross-sectional Workforce Diabetes Study (WDS) (n = 5,806) and Diabetes, Heart and Health Survey (DHAH) (n = 4,010) and compared by ethnicity (European, Māori, Pacific and Asian), glucose regulatory status [impaired fasting glucose, impaired glucose tolerance and type 2 diabetes) and history of cardiovascular disease. ResultsMetSSS positively associated with impaired glucose regulatory status and history of cardiovascular disease for all ethnic groups. Ethnicity significantly affected different coefficients of the MetSSS components, however all ethnicities had an approximately normal MetSSS distribution, with Māori and Pacific curves being right-shifted compared to European. While the MetSSS thresholds that capture 80% of participant with type 2 diabetes (T2D) were higher for Māori and Pacific, the difference in MetSSS between those participants with and without type 2 diabetes within an ethnicity group was similar across ethnicities. ConclusionMetSSS may have utility as a tool to quantify an individual’s cardiometabolic disease risk within the multi-ethnic population of Aotearoa New Zealand, however ethnic-specific categories for disease risk are likely to be required.

Lifestyle Therapy Targeting Hyperinsulinemia Normalizes Hyperglycemia and Surrogate Markers of Insulin Resistance in a Large, Free-Living Population

This article reports the evaluation of a personalized, team-based comprehensive lifestyle modification program targeting known triggers of hyperinsulinemia and insulin resistance. A retrospective chart review was undertaken for 536 participants in a novel high-intensity lifestyle behavioral modification program. Surrogate markers of insulin resistance and metabolic syndrome‒related pathologies were measured before and after participation in the the program. Reversal of metabolic syndrome was present in 42% of participants who met the criteria for this syndrome. Additional changes seen in this cohort include: 36% decrease in triglyceride to high-density lipoprotein cholesterol ratio; 5% (-7.2 mm Hg) decrease in systolic blood pressure and 4% (-3.8 mm Hg) decrease in diastolic blood pressure; decreased abdominal adiposity and waist circumference (-7.6 cm); increased high-density lipoprotein cholesterol (1.3 mg/dL); and 23% (-57.1 mg/dL) decrease in serum triglycerides. Hyperglycemia was normalized in 35% of participants with prediabetes. Only 2% of those with prediabetes progressed to type 2 diabetes mellitus. Among those with type 2 diabetes mellitus, 46% experienced a reduction in HbA1c to below diabetic cut offs. Compared to baseline, the Metabolic Syndrome Severity Score decreased by 30% among those with metabolic syndrome, 11% among those with prediabetes, 26% among those with type 2 diabetes mellitus, and 38% among those with uncontrolled type 2 diabetes mellitus. Cardiorespiratory fitness, measured by the calculated Metabolic Equivalent of Task maximum, increased by 30% in the metabolic syndrome cohort, 28% in the prediabetic cohort, 29% in the type 2 diabetes mellitus cohort, 29% in the uncontrolled type 2 diabetes mellitus cohort, and 32% in the cohort with obesity. Modifying lifestyle factors that trigger hyperinsulinemia provided pleiotropic improvements to all measured surrogate markers of insulin resistance, mitigated the progressive nature of the insulin resistance and metabolic syndrome‒related chronic pathologies, reduced Metabolic Syndrome Severity Score, and improved cardiorespiratory fitness. These results suggest that earlier identification of the diagnostic criteria of metabolic syndrome and/or Metabolic Syndrome Severity Score and the prompt initiation of a comprehensive therapeutic lifestyle approach would significantly mitigate disease burden.