Visit-to-visit variability in the measurements of metabolic syndrome components and the risk of all-cause mortality, cardiovascular disease, and arterial stiffness

Screen Time and Hours of Sleep Influence the Estimate Risk of Diabetes Mellitus and Metabolic Syndrome in Healthy Young Males

Objective: Screen time (ST) has shown negative effects on physical and mental health, with an increase in the prevalence of overweight, metabolic syndrome (MetS), and obesity. The time spent in front of the screens was also associated with higher odds of selecting indicators of cardiometabolic disease in adulthood. In view of this, the aim of this study was to identify the risk of MetS and type 2 diabetes mellitus (T2DM) in healthy young males and relate it to ST and sleep time. Methods: We evaluated physical and laboratory characteristics, dichotomous diagnosis criteria, and continuous scores to assess MetS and Finnish Diabetes Risk Score questionnaire to measure the T2DM risk. Results: The means of MetS dichotomous and continuous severity criteria, among individuals with <7 hr of sleep, were higher than those with adequate sleep. We did not observe a direct impact of ST on the risk of MetS; nevertheless, >8 hr of ST increased 1.22 points in the T2DM risk. Conclusion: Excessive ST increased the risk of T2DM, but not of MetS. Moreover, sleeping <7 hr was associated with a higher mean of dichotomous and continuous severity criteria for MetS.

Metabolic syndrome parameters' variability and stroke incidence in hypertensive patients: evidence from a functional community cohort

BACKGROUND

Stroke is a common complication of hypertension, but the predictive value of metabolic syndrome parameters' variability on stroke risk in individuals with hypertension remains unclear. Therefore, our objective was to investigate the relationship between metabolic syndrome parameters' variability and the risk of total stroke and its subtypes in hypertensive patients.

METHODS

This prospective cohort study included 17,789 individuals with hypertension from the Kailuan study since 2006. Metabolic syndrome parameters, including waist circumference (WC), fasting blood glucose (FBG), systolic blood pressure (SBP), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG), were collected at three follow-up visits in the 2006, 2008, and 2010 surveys. We assess the variability utilizing the coefficient of variation (CV), standard deviation (SD), average real variation (ARV), and variability independent of the mean (VIM), with CV initially assessed. Participants were categorized based on the number of high-variability metabolic syndrome parameters (0, 1, 2, ≥ 3). Stroke cases were identified by reviewing medical records. The associations between variability in metabolic syndrome parameters and the risk of total stroke and its subtypes were analyzed using Cox proportional hazard regression models.

RESULTS

During a median follow-up of 9.32 years, 1223 cases of stroke were recorded. Participants with ≥ 3 high-variability metabolic syndrome parameters had an increased risk of total stroke (HR: 1.29, 95%CI 1.09-1.52), as well as an increased risk of ischemic stroke (HR: 1.31, 95%CI 1.05-1.63) compared to those without high-variability parameters. The study also examined variability in each metabolic syndrome parameter, and significant associations with an increased risk of total stroke were observed for variability in SBP (HR: 1.24, 95%CI 1.05-1.46) and HDL-C (HR: 1.34, 95%CI 1.09-1.64).

CONCLUSIONS

Long-term fluctuations in metabolic syndrome parameters significantly increase the risk of total stroke, especially ischemic stroke. Maintaining low variability in metabolic syndrome parameters could benefit health, and hypertensive individuals must be regularly monitored.

Visit-to-visit variability in multiple biological measurements and cognitive performance and risk of cardiovascular disease: A cohort study

Background

Visit-to-visit variability in single biological measurements has been associated with cognitive decline and an elevated risk of cardiovascular diseases (CVD). However, the effect of visit-to-visit variability in multiple biological measures is underexplored. We investigated the effect of visit-to-visit variability in blood pressure (BP), heart rate (HR), weight, fasting plasma glucose, cholesterol, and triglycerides on cognitive performance and CVD.

Methods

Data on BP, HR, weight, glucose, cholesterol, and triglycerides from study visits in the Outcome Reduction with Initial Glargine Intervention (ORIGIN) trial were used to estimate the association between visit-to-visit variability, cognitive performance (Mini Mental State Examination (MMSE) score) and CVD (non-fatal stroke, non-fatal myocardial infarction, or cardiovascular death). Visit-to-visit variation for each measurement was estimated by calculating each individuals visit-to-visit standard deviation for that measurement. Participants whose standard deviation was in the highest quarter were classified as having high variation. Participants were grouped into those having 0, 1, 2, 3, or ≥ 4 high variation measurements. Regression and survival models were used to estimate the association between biological measures with MMSE and CVD with adjustment for confounders and mean measurement value.

Results

After adjustment for covariates, higher visit-to-visit variability in BP, HR, weight, and FPG were associated with poorer MMSE and a higher risk of CVD. Effect sizes did not vary greatly by measurement. The effects of high visit-to-visit variability were additive; compared to participants who had no measurements with high visit-to-visit variability, those who had high visit-to-visit variability in ≥4 measurements had poorer MMSE scores (-0.63 (95 % CI -0.96 to -0·31). Participants with ≥4 measurements with high visit-to-visit variability compared to participants with none had higher risk of CVD (hazard ratio 2.46 (95 % CI 1.63 to 3.70).

Conclusion

Visit-to-visit variability in several measurements were associated with cumulatively poorer cognitive performance and a greater risk of CVD.

Metabolic Syndrome and Biotherapeutic Activity of Dairy (Cow and Buffalo) Milk Proteins and Peptides: Fast Food-Induced Obesity Perspective-A Narrative Review

Metabolic syndrome (MS) is defined by the outcome of interconnected metabolic factors that directly increase the prevalence of obesity and other metabolic diseases. Currently, obesity is considered one of the most relevant topics of discussion because an epidemic heave of the incidence of obesity in both developing and underdeveloped countries has been reached. According to the World Obesity Atlas 2023 report, 38% of the world population are presently either obese or overweight. One of the causes of obesity is an imbalance of energy intake and energy expenditure, where nutritional imbalance due to consumption of high-calorie fast foods play a pivotal role. The dynamic interactions among different risk factors of obesity are highly complex; however, the underpinnings of hyperglycemia and dyslipidemia for obesity incidence are recognized. Fast foods, primarily composed of soluble carbohydrates, non-nutritive artificial sweeteners, saturated fats, and complexes of macronutrients (protein-carbohydrate, starch-lipid, starch-lipid-protein) provide high metabolic calories. Several experimental studies have pointed out that dairy proteins and peptides may modulate the activities of risk factors of obesity. To justify the results precisely, peptides from dairy milk proteins were synthesized under in vitro conditions and their contributions to biomarkers of obesity were assessed. Comprehensive information about the impact of proteins and peptides from dairy milks on fast food-induced obesity is presented in this narrative review article.

Higher metabolic variability increases the risk of depressive disorder in type 2 diabetes mellitus: a longitudinal nationwide cohort study

BACKGROUND AND OBJECTIVES

While variabilities in metabolic parameters (METv) have been linked to adverse health outcomes in type 2 DM, their association with depression is yet to be studied. This research aimed to investigate the association between METv and depressive disorder in patients with type 2 DM.

METHODS

The study involved a nationwide cohort of 1,119,631 type 2 DM patients who had undergone three or more serial health examinations between 2005 and 2012. At each visit, body mass index (BMI), fasting glucose (FG), systolic blood pressure (BP), and total cholesterol (TC) were measured and stratified into quartiles, with Q4 being the highest and Q1 the lowest. The risk of depressive disorder was evaluated using Cox proportional hazard regression models, which accounted for METs in the indexes, after adjusting for sex, income status, lifestyle habits, medical comorbidities, DM severity, and baseline levels of BMI, FG, BP, and TC.

RESULTS

During a mean follow-up period of 6.00 ± 2.42 years, 239,477 (21.4%) cases of type 2 DM patients developed depressive disorder. The risk of developing depressive disorder was gradually increased as the number of METv increased (HR 1.18; 95% CI 1.13, 1.23 for the group with the highest METv in all parameters compared to those with the lowest METv in all parameters). In the subgroup analysis, the risk of developing depressive disorder was 43% higher in men (HR 1.43; 95% CI 1.34, 1.51), and 31% higher in those younger than 65 years of age (HR 1.31; 95% CI 1.23, 1.39) in the group with the highest number of METv compared to the group with the lowest number of METv.

CONCLUSION

In type 2 DM, higher METv was an independent risk factor for depressive disorder. This risk is notably elevated in men and individuals under the age of 65 years.

Separate and combined effect of visit-to-visit glycaemic variability and mean fasting blood glucose level on all-cause mortality in patients with type 2 diabetes: A population-based cohort study

AIMS

To assess the independent and combined impacts of visit-to-visit fasting blood glucose variability (VVV-FBG) and mean fasting blood glucose level (M-FBG) on all-cause mortality.

MATERIALS AND METHODS

This prospective cohort study included 48 843 Chinese patients with type 2 diabetes. Cox proportional hazards regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) to evaluate the association of VVV-FBG and M-FBG with all-cause mortality. The potential nonlinear associations were examined using restricted cubic splines, and additive interaction was evaluated using relative excess risk due to interaction (RERI). Cox generalized additive models (CGAMs) and bivariate response surface models were further used to assess the combined effects of VVV-FBG and M-FBG.

RESULTS

A total of 4087 deaths were observed during a median follow-up of 6.99 years. Compared with patients with values at the 5th percentile of average real variability (ARV) and M-FBG, we observed a 23% and 38% increased risk of premature deaths among those with values at the 95th percentile of ARV (HR 1.23, 95% CI 1.10, 1.37) and M-FBG (HR 1.38, 95% CI 1.26, 1.51), respectively. The interaction between glycaemic variability (ARV) and M-FBG was significant on both the additive scale (RERI 0.80 [0.29, 1.32]) and the multiplicative scale (HR 1.90 [1.10, 3.28]). High VVV-FBG and high M-FBG conferred the highest risk of all-cause mortality (HR 1.89, 95% CI 1.64, 2.17), compared to low VVV-FBG and low M-FBG. The CGAMs showed significant synergistic effects between glycaemic variability and M-FBG (P < 0.05). Moreover, a bivariate surface plot showed that risk of death increased more rapidly in type 2 diabetes patients with lower M-FBG combined with lower VVV-FBG.

CONCLUSIONS

The coexistence of high glycaemic variability and high glucose level might exacerbate the independent risk of premature mortality in type 2 diabetes patients, highlighting the importance of achieving normal and stable glucose levels simultaneously in the management of glucose.

Changes in Arterial Stiffness in Response to Various Types of Exercise Modalities: A Narrative Review on Physiological and Endothelial Senescence Perspectives

Arterial stiffness is a reliable independent predictor of cardiovascular events. Exercise training might enhance arterial compliance through improved metabolic health status. Different modes of exercise may have different effects on arterial stiffness. However, the interactions among different modes of exercise on endothelial senescence, the development of arterial vascular stiffness, and the associated molecular mechanisms are not completely understood. In this narrative review, we evaluate the current evidence focusing on the effects of various exercise modes on arterial stiffness and vascular health, and the known underlying physiological mechanisms are discussed as well. Here, we discuss the most recent evidence of aerobic exercise, high-intensity interval training (HIIT), and resistance exercise (RE) on arterial stiffness and endothelial senescence in physiological and cellular studies. Indeed, aerobic, HIIT, and progression RE-induced arterial compliance may reduce arterial stiffness by effectively promoting nitric oxide (NO) bioavailability and reducing endothelial senescence. However, the transient increase in inflammation and sympathetic activation may contribute to the temporary elevation in arterial stiffness following whole-body high-intensity acute resistance exercise.

Elevated levels of body mass index and waist circumference, but not high variability, are associated with an increased risk of atrial fibrillation

BACKGROUND

Although obesity has been associated with risk of atrial fibrillation (AF), the associations of variability of obesity measures with AF risk are uncertain, and longitudinal studies among Chinese population are still lacking. We aimed to evaluate the impacts of obesity and variability of body mass index (BMI) and waist circumference (WC) on the risk of atrial fibrillation (AF) in a large Chinese cohort study.

METHODS

A total of 44,135 participants of the Kailuan Study who were free of cancer and cardiovascular disease and underwent three consecutive surveys from 2006 to 2010 were followed for incident AF until 2020. Average BMI and WC over time and variability were calculated. Cox proportional hazards regression models were used to assess hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations of obesity and variability in BMI and WC with AF risk.

RESULTS

During a mean follow-up of 9.68 years, there were 410 cases of incident AF. In multivariable-adjusted models, compared with normal BMI/WC, individuals with general obesity and abdominal obesity had increased risk of AF, with corresponding HRs of 1.73 (95% CI: 1.31-2.30) and 1.38 (95% CI: 1.11-1.60), respectively. The short-term elevation in AF risk persisted for the obese even after adjustment for updated biologic intermediaries and weight. Variability in BMI and WC were not associated with the risk of AF. The restricted cubic spline models indicated significant linear relationships between levels of WC and BMI and risk of AF.

CONCLUSIONS

Elevated levels of BMI and WC were associated with an increased risk of AF, whereas variability in BMI and WC were not. Therefore, achieving optimal levels of BMI and WC could be valuable in AF prevention.

Incidence and long-term specific mortality trends of metabolic syndrome in the United States

PURPOSE

Metabolic syndrome (MetS) is extremely prevalent and related to severe diseases and death. This study aims to investigate the incidence and mortality trends among MetS over the past few decades. The gender and age differences of MetS are also explored.

PATIENTS AND METHODS

Adults with MetS were screened in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2014. The mortality data were also acquired. Then we assessed the incidence and mortality trends of MetS in the United States.

RESULTS

Our study included 14171 participants with a mean age of 46.8 ± 19.3 years, of whom 7354 (51.9%) were women. Among them, 4789 participants were subsequently diagnosed with MetS. From 1999 to 2014, the overall trend of MetS incidence increased (from 27.6 to 32.3%; adjusted odds ratios [aOR], 1.71; 95% confidence interval [CI], 1.42-2.05; P-value <0.001, P for trend <0.001). In more detail, the incidence of MetS rose first but subsequently plateaued and declined. Obvious downward trends were observed from 29.6 to 2.7% for all-cause mortality (aOR, 0.12; 95%CI, 0.07-0.21; P-value <0.001, P for trend <0.001) and 4.8 to 0.8% for cardio-cerebrovascular mortality (aOR, 0.17; 95%CI, 0.05-0.61; P-value =0.007, P for trend <0.001). All-cause mortality decreased yearly, whereas cardio-cerebrovascular death increased briefly before declining and stabilizing. Similarly, the temporal mortality trends in MetS patients of different ages and genders had the same results. Specifically, the incidence of MetS was higher in women than in men (adjusted P =0.003; OR, 1.14; 95%CI, 1.05-1.24), but the mortality was significantly lower after an average of 7.7 years of follow-up (all-cause mortality, adjusted P <0.001; hazard ratio [HR], 0.68; 95%CI, 0.57-0.81; cardio-cerebrovascular mortality, adjusted P =0.004; HR, 0.55; 95%CI, 0.37-0.83).

CONCLUSION

From 1999 to 2014, the incidence of MetS in U.S. adults significantly increased overall, while the mortality rate of MetS had a considerable downward trend. Both trends showed marked gender differences, being more prevalent and at lower risk in women compared with men. It is important to identify the factors that will curb the incidence of MetS and decrease mortality, especially in male patients.

Triglyceride-Glucose Index for the Diagnosis of Metabolic Syndrome: A Cross-Sectional Study of 298,652 Individuals Receiving a Health Check-Up in China

OBJECTIVE

We herein aim to explore the relationship between the triglyceride-glucose (TyG) index and metabolic syndrome (MS).

METHODS

We enrolled 298,652 individuals with an average age of 47.08 ± 12.94 years and who underwent health check-ups at the First Affiliated Hospital of Wuhu Wannan Medical College in this cross-sectional study from 2014 to 2016. We enlisted 125,025 women (41.86%) and 173,627 men (58.14%). The survey information included a questionnaire survey, a physical examination, and a laboratory examination.

RESULTS

The prevalence of MS increased gradually in the TyG-index subgroups (Q1, TyG <8.30; Q2, 8.30≤ TyG <8.83; and Q3, TyG ≥8.83). We noted significant differences in hypertension, hyperlipidemia, hyperglycemia, sex, age, body mass index (BMI), smoking and drinking habits, and estimated glomerular filtration rate between the TyG-index subgroups. Multiclass logistic regression analysis showed that the group with TyG <8.30 was the reference group, and the 8.30≤ TyG <8.83 and the TyG ≥8.83 groups exhibited a higher TyG index with MS, and a lower TyG index without MS disease. In the linear curve analysis of the TyG index and MS components, BMI, systolic blood pressure, and diastolic blood pressure showed upward trends, while high-density lipoprotein cholesterol showed no obvious trend in the TyG index at a range of 7.8-11.0. Receiver operating characteristic analysis was used to evaluate the predictive value of the TyG index, triglycerides, and fasting blood glucose for MS, and we found that the area under the TyG index curve was the largest (AUC = 0.89).

CONCLUSION

There were associations between the TyG index and MS and its components, and the TyG index is therefore of great value in the early diagnosis of MS.