scholarly journals Effects of Extreme Weight Loss on Cardiometabolic Health in Children With Metabolic Syndrome: A Metabolomic Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Jingxin Liu ◽  
Lin Zhu ◽  
Jing Liao ◽  
Xiaoguang Liu
Keyword(s):  
Risk Factors ◽  
Metabolic Syndrome ◽  
Weight Loss ◽  
Body Composition ◽  
Organic Acids ◽  
Cardiometabolic Risk ◽  
The Body ◽  
Cardiometabolic Risk Factors ◽  
Plasma Metabolites ◽  
Cardiometabolic Health

Objectives: To evaluate the effect of extreme weight loss programs on circulating metabolites and their relationship with cardiometabolic health in children with metabolic syndrome.Methods: This study was a quasi-experimental design with a pretest and post-test. Thirty children with metabolic syndrome and aged 10–17years were recruited to an extreme weight loss program (i.e., exercise combined with diet control). The primary outcomes included plasma metabolites, body composition, and cardiometabolic risk factors. A total of 324 metabolites were quantitatively detected by an ultra-performance liquid chromatography coupled to tandem mass spectrometry system, and the variable importance in the projection (VIP) value of each metabolite was calculated by the orthogonal projection to latent structures discriminant analysis. The fold change (FC) and p value of each metabolite were used to screen differential metabolites with the following values: VIP>1, p value<0.05, and |log2FC|>0.25. Pathway enrichment and correlation analyses between metabolites and cardiometabolic risk factors were also performed.Result: A large effect size was observed, presenting a weight loss of −8.9kg (Cohen’s d=1.00, p<0.001), body mass index reduction of −3.3kg/m2 (Cohen’s d=1.47, p<0.001), and body fat percent reduction of −4.1 (%) (Cohen’s d=1.22, p<0.001) after the intervention. Similar improvements were found in total cholesterol (Cohen’s d=2.65, p<0.001), triglycerides (Cohen’s d=2.59, p<0.001), low-density lipoprotein cholesterol (Cohen’s d=2.81, p<0.001), glucose metabolism, and blood pressure. A total of 59 metabolites were changed after the intervention (e.g., aminoacyl-tRNA biosynthesis, glycine, serine, and threonine metabolism; nitrogen metabolism, tricarboxylic acid cycle, and phenylalanine, tyrosine, and tryptophan biosynthesis). The changes in metabolites (e.g., amino acids, fatty acids, organic acids, and carnitine) were related to lipid metabolism improvement (p<0.05). Organic acids and carnitines were associated with changes in the body composition (p<0.05).Conclusion: Exercise combined with dietary control improved the body composition and cardiometabolic health in children with metabolic syndrome, and these changes may be related to plasma metabolites.

scholarly journals Examining the Interaction of the Gut Microbiome with Host Metabolism and Cardiometabolic Health in Metabolic Syndrome

Nutrients ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 4318
Author(s):  
Serena Galié ◽  
Christopher Papandreou ◽  
Pierre Arcelin ◽  
David Garcia ◽  
Antoni Palau-Galindo ◽  
...  
Keyword(s):  
Risk Factors ◽  
Metabolic Syndrome ◽  
Cardiometabolic Risk ◽  
Adult Population ◽  
Cardiometabolic Risk Factors ◽  
Plasma Metabolites ◽  
Cardiometabolic Health ◽  
Cross Sectional ◽  
Generalized Canonical Correlation Analysis ◽  
Positive Correlations

(1) Background: The microbiota-host cross-talk has been previously investigated, while its role in health is not yet clear. This study aimed to unravel the network of microbial-host interactions and correlate it with cardiometabolic risk factors. (2) Methods: A total of 47 adults with overweight/obesity and metabolic syndrome from the METADIET study were included in this cross-sectional analysis. Microbiota composition (151 genera) was assessed by 16S rRNA sequencing, fecal (m = 203) and plasma (m = 373) metabolites were profiled. An unsupervised sparse generalized canonical correlation analysis was used to construct a network of microbiota-metabolite interactions. A multi-omics score was derived for each cluster of the network and associated with cardiometabolic risk factors. (3) Results: Five multi-omics clusters were identified. Thirty-one fecal metabolites formed these clusters and were correlated with plasma sphingomyelins, lysophospholipids and medium to long-chain acylcarnitines. Seven genera from Ruminococcaceae and a member from the Desulfovibrionaceae family were correlated with fecal and plasma metabolites. Positive correlations were found between the multi-omics scores from two clusters with cholesterol and triglycerides levels. (4) Conclusions: We identified a correlated network between specific microbial genera and fecal/plasma metabolites in an adult population with metabolic syndrome, suggesting an interplay between gut microbiota and host lipid metabolism on cardiometabolic health.

scholarly journals Late eating is associated with cardiometabolic risk traits, obesogenic behaviors, and impaired weight loss

2020 ◽  
Vol 113 (1) ◽  
pp. 154-161 ◽  
Author(s):  
Hassan S Dashti ◽  
Puri Gómez-Abellán ◽  
Jingyi Qian ◽  
Alberto Esteban ◽  
Eva Morales ◽  
...  
Keyword(s):  
Risk Factors ◽  
Weight Loss ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors ◽  
Cardiometabolic Health ◽  
Activity Levels ◽  
Weight Loss Intervention ◽  
Meal Intake ◽  
Intervention Protocol ◽  
Obesogenic Behaviors

ABSTRACT Background There is a paucity of evidence regarding the role of food timing on cardiometabolic health and weight loss in adults. Objectives To determine whether late eating is cross-sectionally associated with obesity and cardiometabolic risk factors at baseline; and whether late eating is associated with weight loss rate and success following a weight loss intervention protocol. Also, to identify obesogenic behaviors and weight loss barriers associated with late eating. Methods Participants were recruited from a weight-loss program in Spain. Upon recruitment, the midpoint of meal intake was determined by calculating the midway point between breakfast and dinner times, and dietary composition was determined from diet recall. Population median for the midpoint of meal intake was used to stratify participants into early (before 14:54) and late (after 14:54) eaters. Cardiometabolic and satiety hormonal profiles were determined from fasting blood samples collected prior to intervention. Weekly weight loss and barriers were evaluated during the ∼19-wk program. Linear and logistic regression models were used to assess differences between late and early eaters in cardiometabolic traits, satiety hormones, obesogenic behaviors, and weight loss, adjusted for age, sex, clinic site, year of recruitment, and baseline BMI. Results A total of 3362 adults [mean (SD): age: 41 (14) y; 79.2% women, BMI: 31.05 (5.58) kg/m2] were enrolled. At baseline, no differences were observed in energy intake or physical activity levels between early and late eaters (P >0.05). Late eaters had higher BMI, higher concentrations of triglycerides, and lower insulin sensitivity compared with early eaters (all P <0.05) prior to intervention. In addition, late eaters had higher concentrations of the satiety hormone leptin in the morning (P = 0.001). On average, late eaters had an average 80 g lower weekly rate of weight loss [early, 585 (667) g/wk; late, 505 (467) g/wk; P = 0.008], higher odds of having weight-loss barriers [OR (95% CI): 1.22 (1.03, 1.46); P = 0.025], and lower odds of motivation for weight loss [0.81 (0.66, 0.99); P = 0.044] compared with early eaters. Conclusion Our results suggest that late eating is associated with cardiometabolic risk factors and reduced efficacy of a weight-loss intervention. Insights into the characteristics and behaviors related to late eating may be useful in the development of future interventions aimed at advancing the timing of food intake.

Intermittent Fasting Improves Cardiometabolic Risk Factors and Alters Gut Microbiota in Metabolic Syndrome Patients

2020 ◽  
Vol 106 (1) ◽  
pp. 64-79
Author(s):  
Yi Guo ◽  
Shiyun Luo ◽  
Yongxin Ye ◽  
Songping Yin ◽  
Jiahua Fan ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Risk Factors ◽  
Metabolic Syndrome ◽  
Gut Microbiota ◽  
Inflammatory Cytokines ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors ◽  
Cardiometabolic Health ◽  
Intermittent Fasting ◽  
Functional Pathways

Abstract Context Intermittent fasting (IF) is an effective strategy to improve cardiometabolic health. Objective The objective of this work is to examine the effects of IF on cardiometabolic risk factors and the gut microbiota in patients with metabolic syndrome (MS). Design and Setting A randomized clinical trial was conducted at a community health service center. Patients Participants included adults with MS, age 30 to 50 years. Intervention Intervention consisted of 8 weeks of “2-day” modified IF. Main Outcome Measure Cardiometabolic risk factors including body composition, oxidative stress, inflammatory cytokines, and endothelial function were assessed at baseline and at 8 weeks. The diversity, composition, and functional pathways of the gut microbiota, as well as circulating gut-derived metabolites, were measured. Results Thirty-nine patients with MS were included: 21 in the IF group and 18 in the control group. On fasting days, participants in the IF group reduced 69% of their calorie intake compared to nonfasting days. The 8-week IF significantly reduced fat mass, ameliorated oxidative stress, modulated inflammatory cytokines, and improved vasodilatory parameters. Furthermore, IF induced significant changes in gut microbiota communities, increased the production of short-chain fatty acids, and decreased the circulating levels of lipopolysaccharides. The gut microbiota alteration attributed to the IF was significantly associated with cardiovascular risk factors and resulted in distinct genetic shifts of carbohydrate metabolism in the gut community. Conclusion IF induces a significant alteration of the gut microbial community and functional pathways in a manner closely associated with the mitigation of cardiometabolic risk factors. The study provides potential mechanistic insights into the prevention of adverse outcomes associated with MS.

scholarly journals Drugs in the treatment of obesity: sibutramine, orlistat and rimonabant

2007 ◽  
Vol 10 (10A) ◽  
pp. 1200-1205 ◽  
Author(s):  
Miguel A Rubio ◽  
Manuel Gargallo ◽  
Ana Isabel Millán ◽  
Basilio Moreno
Keyword(s):  
Risk Factors ◽  
Weight Loss ◽  
Cardiometabolic Risk ◽  
The Body ◽  
Cardiometabolic Risk Factors ◽  
Phase Iii ◽  
Diabetic Patients ◽  
Long Term Treatment ◽  
Treatment Of Obesity

AbstractBackgroundModification of lifestyle is the main therapeutical approach in the treatment of obesity, but use to fail on long terms of time. Addition of anti-obesity drugs allows keeping the weight loss during years and improving obesity-related comorbidities.MethodsThis review is an actualisation on efficacy, safety and tolerability of the approved drugs on the long-term treatment of obesity (orlistat and sibutramine). New indications and effects of their use far beyond the weight loss are as well commented. Finally, potential benefits of the administration of CB1 antagonist rimonabant on the weight loss and cardiometabolic risk factors are analysed in detail.DiscussionA decade of experience on the use of orlistat and sibutramine has demonstrated their higher efficacy on the weight loss when compared to placebo either on adult or teenage population as well as safety and tolerability on long-term administration. Beneficial effects on the lipid profile, glycosilated haemoglobin on diabetic patients, blood pressure and levels of inflammatory cytokines, contribute to decrease the cardiovascular risk on obese patients. Phase III clinical trials using rimonabant show additional benefits to the expected weight loss, mainly reducing visceral fat and cardiometabolic risk factors.ConclusionPharmacological treatment of obesity must be considered as a therapeutical tool that has to be used together with long-term lifestyle changes, contributing to the body weight reduction as well as to the improvement of the cardiometabolic risk related to obesity.

Temporal Trend of Non-Invasive Method Capacity for Early Detection of Metabolic Syndrome in Children and Adolescents: A Bayesian Multilevel Analysis of Pseudo-Panel Data

2019 ◽  
Vol 75 (1) ◽  
pp. 55-65 ◽  
Author(s):  
Shahram Arsang-Jang ◽  
Roya Kelishadi ◽  
Mohammad Esmail Motlagh ◽  
Ramin Heshmat ◽  
Marjan Mansourian
Keyword(s):  
Risk Factors ◽  
Metabolic Syndrome ◽  
Children And Adolescents ◽  
Cardiometabolic Risk ◽  
Lipid Profiles ◽  
The Body ◽  
Cardiometabolic Risk Factors ◽  
Youden Index ◽  
Noninvasive Methods ◽  
Anthropometric Measures

Background: The aim of this study was to examine the ability of Noninvasive methods to early predictions of metabolic syndrome (MetS) among children and adolescents from 2003 to 2016. Methods: This was a repeated cross-sectional study based on 24,409 Iranian children and adolescents. The variables included anthropometric measures, serum lipid profiles, hypertension, and MetS. The receiver operating characteristic regression and Bayesian multilevel modeling conducted on data to comparison the power of anthropometric measures to early prediction of cardiometabolic risk factors. Results: The tri-ponderal body shape index (TBSI) in females and waist circumference (WC) percentile in males yielded a greater ability to predict lipid profiles and hypertension than the rest of anthropometric factors. The TBSI (β = 6.24, 95% credible interval [95% Crl] 3.9–8.7) followed by the WC percentile (β = 4.43, 95% Crl 3.5–5.4) were considered the better predictors of MetS compared with the body mass index (BMI), tri-ponderal mass index (TMI), WC, waist-to-height ratio, and WC to height5 in adolescents. The TBSI with Youden index J (JI) = 0.85 was significantly more accurate than the BMI (JI = 0.73), and TMI (JI = 0.7) for classifying individuals with MetS and in healthy groups. The predictability of early MetS was consistent for both TBSI and WC components throughout the study period. Conclusions: The TBSI including, both BMI and WC components, predicts MetS and cardiometabolic risk factors more accurately than BMI or WC alone in females. The TBSI ability was higher than other anthropometric factors for screening MetS and cardiometabolic risk factors among adolescents.

scholarly journals Impact of COVID-19 and Associated Preventive Measures on Cardiometabolic Risk Factors in South Korea: An Observational Study

2020 ◽  
Author(s):  
Minji Sohn ◽  
Bo Kyung Koo ◽  
Soo Lim ◽  
Ho Il Yoon ◽  
Kyoung-Ho Song ◽  
...  
Keyword(s):  
Risk Factors ◽  
South Korea ◽  
Cardiometabolic Risk ◽  
Preventive Measures ◽  
Density Lipoprotein ◽  
The Body ◽  
Cardiometabolic Risk Factors ◽  
Lipoprotein Cholesterol ◽  
Cardiometabolic Health ◽  
Number Of Patients

Abstract Background: During the COVID-19 pandemic, people have been required to follow preventive measures such as social distancing or staying at home, which can lead to an unhealthy lifestyle. We investigated the effect of these preventive measures on metabolic parameters in individuals with cardiometabolic risk factors.Methods: Using data for patients who visited a tertiary hospital in South Korea at least twice a year for the past 4 years, changes in clinical and biochemical data from the COVID-19 pandemic (2019–2020) were compared with changes in the same data at the same annual time points during the three previous seasons of 2016–2019.Results: Among 7,094 patients, data for 1,485 were included. Systolic blood pressure increased by 2.6 ± 18.2 mmHg in the COVID-19 pandemic period compared with the 2018–2019, 2017–2018, and 2016–2017 seasons: –1.4 ± 16.5 mmHg, –2.8 ± 14.3 mmHg, and –0.7 ± 14.3 mmHg, respectively; all p < 0.05. The body mass index increased by 0.09 ± 1.16 kg/m2 in the 2019–2020 pandemic season whereas it changed by –0.39 ± 3.03 kg/m2 in 2018–2019 and by –0.34 ± 2.18 kg/m2 in 2017–2018 (both p <0.05). Total cholesterol, triglycerides, high-density lipoprotein-cholesterol, and low-density lipoprotein-cholesterol levels worsened in the pandemic season compared with the previous three. Fasting glucose and glycated hemoglobin levels also showed increasing tendencies during the pandemic, but without significance. During the COVID-19 pandemic, the number of patients whose metabolic syndrome worsened increased significantly by 21% compared with the 2018–2019 season. The 10-year coronary heart disease risk calculated using the Framingham risk score also increased significantly.Conclusions: Comorbidity and mortality arising from cardiometabolic disorders as collateral damage during COVID-19 infections and preventive procedures could have major impacts on human health in the future. Nationwide strategies to reverse the aggravation of cardiometabolic health during a pandemic should be implemented in countries attempting to cope with it.

scholarly journals The Effect of Four Weeks Dietary Intervention with 8-Hour Time-Restricted Eating on Body Composition and Cardiometabolic Risk Factors in Young Adults

Nutrients ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 2164
Author(s):  
Su-Jeong Park ◽  
Jae-Won Yang ◽  
Yoon-Ju Song
Keyword(s):  
Risk Factors ◽  
Weight Loss ◽  
Young Adults ◽  
Body Composition ◽  
Body Weight ◽  
Weight Gain ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors ◽  
Meal Frequency ◽  
Weight Loss Group

Recently, intermittent fasting, also known as time-restricted eating (TRE), has become a popular diet trend. Compared to animal studies, there have been few studies and inconclusive findings investigating the effects of TRE in humans. In this study, we examined the effects of 8 h TRE on body weight and cardiometabolic risk factors in young adults who were mainly active at night. A total of 33 young adults completed the 8 h TRE for 4 weeks. Body composition was measured by bioelectrical impedance analysis at baseline and every 2 weeks, and blood samples were collected at baseline and week 4. Daily dietary records were logged throughout the intervention period. Participants experienced significant changes in body weight (−1.0 ± 1.4 kg), body mass index (−0.4 ± 0.5 kg/m2), and body fat (−0.4 ± 1.9%) after 4 weeks of TRE. When participants were divided into weight loss/gain groups based on their weight change in week 4, fat mass reduction was significantly higher in the weight loss group than in the weight gain group. Regarding cardiometabolic risk factors, levels of fasting insulin and insulin resistance improved in the weight loss group after intervention, but not in the weight gain group. All subjects showed late-shifted sleeping patterns, but no significant differences in sleep duration, sleep quality, or psychological measures between the two groups. When meal frequency and energy proportion were evaluated, the average meal frequency was 2.8 ± 0.5 and energy proportions of breakfast, lunch, dinner, and snacks were 4.5, 39.2, 37.6, and 18.5%, respectively; there were no significant differences between the two groups. However, the saturated fat intake at dinner was lower in the weight loss group (3.1 ± 3.2%, 6.0 ± 2.5% respectively). In conclusion, 8 h TRE can be applied as a lifestyle strategy to manage body weight and cardiometabolic risk factors among young adults with late chronotypes.

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