230: Changes of plasma leptin levels and cardiometabolic risk factors during the weight loss with orlistat in combination with hypocaloric diet

2008 ◽  
Vol 2 (5) ◽  
pp. S107
Keyword(s):  
Risk Factors ◽  
Weight Loss ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors ◽  
Hypocaloric Diet ◽  
Plasma Leptin

scholarly journals Effect of a high-egg diet on cardiometabolic risk factors in people with type 2 diabetes: the Diabetes and Egg (DIABEGG) Study—randomized weight-loss and follow-up phase

2018 ◽  
Vol 107 (6) ◽  
pp. 921-931 ◽  
Author(s):  
Nicholas R Fuller ◽  
Amanda Sainsbury ◽  
Ian D Caterson ◽  
Gareth Denyer ◽  
Mackenzie Fong ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Weight Loss ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors

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 Effects of whole and refined grains on cardiometabolic risk factors in a controlled‐feeding, weight loss study: Preliminary findings

2012 ◽  
Vol 26 (S1) ◽  
Author(s):  
Kristina Arline Harris ◽  
Shiela West ◽  
Jack Vanden Heuvel ◽  
Satya Jonnalagadda ◽  
Penny Kris-Etherton
Keyword(s):  
Risk Factors ◽  
Weight Loss ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors ◽  
Refined Grains ◽  
Weight Loss Study

scholarly journals Relationship among physical activity, sedentary behaviors, and cardiometabolic risk factors during gastric bypass surgery–induced weight loss

2017 ◽  
Vol 13 (2) ◽  
pp. 210-219 ◽  
Author(s):  
Jakob F. Wefers ◽  
Tracey L. Woodlief ◽  
Elvis A. Carnero ◽  
Nicole L. Helbling ◽  
Steven J. Anthony ◽  
...  
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
Weight Loss ◽  
Gastric Bypass ◽  
Bypass Surgery ◽  
Cardiometabolic Risk ◽  
Gastric Bypass Surgery ◽  
Cardiometabolic Risk Factors ◽  
Sedentary Behaviors

scholarly journals Weight loss, exercise or both and cardiometabolic risk factors in obese older adults: results of a randomized controlled trial

2013 ◽  
Vol 38 (3) ◽  
pp. 423-431 ◽  
Author(s):  
M Bouchonville ◽  
R Armamento-Villareal ◽  
K Shah ◽  
N Napoli ◽  
D R Sinacore ◽  
...  
Keyword(s):  
Risk Factors ◽  
Older Adults ◽  
Weight Loss ◽  
Randomized Controlled Trial ◽  
Cardiometabolic Risk ◽  
Controlled Trial ◽  
Cardiometabolic Risk Factors ◽  
Randomized Controlled

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.

scholarly journals Predictors of Improvement in Cardiometabolic Risk Factors With Weight Loss in Women

2013 ◽  
Vol 2 (6) ◽  
Author(s):  
Caitlin A. Dow ◽  
Cynthia A. Thomson ◽  
Shirley W. Flatt ◽  
Nancy E. Sherwood ◽  
Bilge Pakiz ◽  
...  
Keyword(s):  
Risk Factors ◽  
Weight Loss ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors

The Visceral Adiposity Index: Relationship with cardiometabolic risk factors in obese and overweight postmenopausal women – A MONET group study

2013 ◽  
Vol 38 (8) ◽  
pp. 892-899 ◽  
Author(s):  
Belinda Elisha ◽  
Virginie Messier ◽  
Antony Karelis ◽  
Lise Coderre ◽  
Sophie Bernard ◽  
...  
Keyword(s):  
Risk Factors ◽  
Weight Loss ◽  
Adipose Tissue ◽  
Postmenopausal Women ◽  
Cardiometabolic Risk ◽  
Area Under The Curve ◽  
Weight Loss Program ◽  
Cardiometabolic Risk Factors ◽  
Visceral Adiposity Index ◽  
Visceral Adipose

A recent study suggested visceral adipose index (VAI) as an indicator of adipose tissue distribution and function associated with cardiometabolic risk. We aim to examine the association between VAI and visceral adipose tissue (VAT), insulin sensitivity, and a large panel of associated cardiometabolic risk factors, and to determine if changes in VAI after weight loss intervention will reflect changes in VAT. We performed a secondary analysis using the data of 99 overweight and postmenopausal women that completed a 6-month weight loss program (Montreal Ottawa New Emerging Team Study). VAI was calculated according to the equation by Amato et al. (2010; Diabetes Care, 33(4):920–922). At baseline, VAI was associated with VAT (r = 0.284, p < 0.01) but not with subcutaneous adipose tissue (SAT) while body mass index (BMI) and waist circumference (WC) were significantly related to both. BMI and WC demonstrated significantly stronger predictive value of VAT accumulation (area under the curve = 0.84 and 0.86, respectively) than VAI (area under the curve = 0.61; p < 0.01). However, VAT, BMI, WC, and VAI were similarly related to fasting insulin and glucose disposal rates. After a 6-month weight loss program, VAI decreased significantly and similarly in both intervention groups (p < 0.01). In addition, the percentage of change in VAI showed the significantly weakest correlation (r = 0.25) with the percentage of change in VAT than BMI (r = 0.56; p < 0.01 for r comparisons) and was not a significant predictor of interindividual percentage of change in VAT while BMI accounted for 33.7%. VAI is a weak indicator of VAT function and did not predict changes in VAT after weight loss. Furthermore, this index was not superior to BMI or WC. However, VAI is a good indicator of metabolic syndrome.

scholarly journals Adherence to a Plant-Based Diet and Consumption of Specific Plant Foods—Associations with 3-Year Weight-Loss Maintenance and Cardiometabolic Risk Factors: A Secondary Analysis of the PREVIEW Intervention Study

Nutrients ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 3916
Author(s):  
Ruixin Zhu ◽  
Mikael Fogelholm ◽  
Sally D. Poppitt ◽  
Marta P. Silvestre ◽  
Grith Møller ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Weight Loss ◽  
Weight Management ◽  
Cardiometabolic Risk ◽  
Ldl Cholesterol ◽  
Secondary Analysis ◽  
Weight Loss Maintenance ◽  
Cardiometabolic Risk Factors ◽  
Plant Foods

Plant-based diets are recommended by dietary guidelines. This secondary analysis aimed to assess longitudinal associations of an overall plant-based diet and specific plant foods with weight-loss maintenance and cardiometabolic risk factors. Longitudinal data on 710 participants (aged 26–70 years) with overweight or obesity and pre-diabetes from the 3-year weight-loss maintenance phase of the PREVIEW intervention were analyzed. Adherence to an overall plant-based diet was evaluated using a novel plant-based diet index, where all plant-based foods received positive scores and all animal-based foods received negative scores. After adjustment for potential confounders, linear mixed models with repeated measures showed that the plant-based diet index was inversely associated with weight regain, but not with cardiometabolic risk factors. Nut intake was inversely associated with regain of weight and fat mass and increments in total cholesterol and LDL cholesterol. Fruit intake was inversely associated with increments in diastolic blood pressure, total cholesterol, and LDL cholesterol. Vegetable intake was inversely associated with an increment in diastolic blood pressure and triglycerides and was positively associated with an increase in HDL cholesterol. All reported associations with cardiometabolic risk factors were independent of weight change. Long-term consumption of nuts, fruits, and vegetables may be beneficial for weight management and cardiometabolic health, whereas an overall plant-based diet may improve weight management only.

scholarly journals Contribution of binge eating behaviour to cardiometabolic risk factors in subjects starting a weight loss or maintenance programme

2016 ◽  
Vol 116 (11) ◽  
pp. 1984-1992 ◽  
Author(s):  
Alessandro Leone ◽  
Giorgio Bedogni ◽  
Veronica Ponissi ◽  
Alberto Battezzati ◽  
Valentina Beggio ◽  
...  
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
Weight Loss ◽  
Nutritional Status ◽  
Binge Eating ◽  
Regression Model ◽  
Cardiometabolic Risk ◽  
Smoking Status ◽  
Cardiometabolic Risk Factors ◽  
Binge Eaters

AbstractThe contribution of binge eating (BE) behaviour to cardiometabolic risk factors has been scarcely investigated so far. Previous studies have not considered the nutritional status and lifestyle of subjects suffering from BE. The aim of this study was to evaluate the contribution of BE to the metabolic syndrome (MS), its components, high total cholesterol and high LDL in a large sample of subjects, taking into account nutritional status, dietary habits, smoking status and physical activity. For this purpose, 5175 adults seeking a weight loss or maintenance programme were recruited. Anthropometrical measurements and blood parameters were measured. BE was evaluated using the Binge Eating Scale (BES). A fourteen-item questionnaire was used to evaluate the adherence to the Mediterranean diet. Smoking status and physical activity were investigated by interview. BE prevalence was 0·16 (95 % CI 0·15, 0·17). A sex- and age-adjusted Poisson regression model showed a higher prevalence of MS in binge eaters (0·33; 95 % CI 0·28, 0·37) compared with non-binge eaters (0·27; 95 % CI 0·25, 0·28, P=0·011). However, the statistical difference was lost after inclusion of BMI and lifestyle parameters in the multiple-adjusted model. We also evaluated the association between the continuous outcomes of interest and the BES score using a multivariable median regression model. We observed a positive, but clinically irrelevant, association between BES score and HDL levels (P<0·001). In conclusion, BE does not seem to be independently related to cardiometabolic risk factors. However, the screening and treatment of BE are of clinical relevance in order to reduce the risk of developing obesity.

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