scholarly journals The effects of macronutrient self‐selection and sucrose form on energy intake, body composition, and aspects of the metabolic syndrome in rats

2010 ◽  
Vol 24 (S1) ◽  
Author(s):  
John W. Apolzan ◽  
Ruth B.S. Harris
Keyword(s):  
Metabolic Syndrome ◽  
Body Composition ◽  
Energy Intake ◽  
The Metabolic Syndrome ◽  
Self Selection

scholarly journals Appetite Control Might not Be Improved after Weight Loss in Adolescents with Obesity, Despite Non-Persistent Metabolic Syndrome

Nutrients ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3885
Author(s):  
Valérie Julian ◽  
Laurie Isacco ◽  
Marwa Khammassi ◽  
Alicia Fillon ◽  
Maud Miguet ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Weight Loss ◽  
Body Composition ◽  
Energy Intake ◽  
Weight Loss Intervention ◽  
Appetite Control ◽  
Post Intervention ◽  
The Metabolic Syndrome ◽  
Daily Energy ◽  
Before And After

The aim of this study was to evaluate the effect of a multidisciplinary weight loss intervention on energy intake and appetite sensations in adolescents with obesity, depending on the initial diagnosis or persistence of the metabolic syndrome. Ninety-two adolescents with obesity (12–15 years) followed a 16-week multidisciplinary weight loss intervention. Anthropometric and body composition characteristics, metabolic profile, ad libitum daily energy intake, and appetite sensations were assessed before and after the intervention. The presence of metabolic syndrome (MS) was determined at baseline (MS vs. non-MS) and after the program (persistent vs. non-persistent). While the intervention was effective in inducing weight loss (body weight T0: 87.1 ± 14.9 vs. T1: 81.2 ± 13.0 kg; p < 0.001) and body composition improvements in both adolescents with and without MS, energy intake (p = 0.07), hunger (p = 0.008), and prospective food consumption (p = 0.03) increased, while fullness decreased (p = 0.04) in both groups. Energy intake and appetite were not improved in non-persistent MS after the program and remained significantly higher among non-persistent adolescents compared with initially non-MS adolescents. To conclude, appetite control seems impaired in obese adolescents, irrespective of being affected by MS or not, whereas the treatment of MS in this population might fail to effectively preclude the adolescents from potential post-intervention compensatory food intake and subsequent weight regain.

scholarly journals Population studies of diet and obesity

2000 ◽  
Vol 83 (S1) ◽  
pp. S21-S24 ◽  
Author(s):  
Lauren Lissner ◽  
Berit L. Heitmann ◽  
Calle Bengtsson
Keyword(s):  
Metabolic Syndrome ◽  
Epidemiological Studies ◽  
Population Based ◽  
Nutritional Epidemiology ◽  
Nutritional Risk ◽  
Reporting Bias ◽  
The Metabolic Syndrome ◽  
Self Selection ◽  
Obese Subjects ◽  
Regional Adiposity

Population-based research on diet, obesity and the metabolic syndrome is faced with accumulating evidence of biases that may profoundly affect results. One potential source of bias, which is often neglected in nutritional epidemiology, arises from self-selected study populations. Subjects who agree to participate in surveys may be at less risk of metabolic syndrome than those who refuse. Analogous to observations in adult populations, studies of schoolchildren have also yielded clear evidence of self-selection. Whether such selection patterns influence analytical results depends on how the biases relate to the dependent and independent variables being studied. Systematic dietary reporting error is another source of bias in studies of nutritional risk factors for disease. While obesity-related under-reporting bias is now well documented, less is known about whether specific foods and nutrients are disproportionately affected. However, two studies employing biomarkers for protein have suggested that obese subjects under-reported the proportion of energy from fat plus carbohydrate. This should alert epidemiologists to the possibility that a dual reporting bias may be present in studies of diet and disease: general under-reporting among obese subjects compounded by food-specific errors. In summary, biases due to self-selection and selective dietary under-reporting may produce consequences in epidemiological studies that are both unpredictable and complex. We conclude this review with recent findings involving dietary fat intake and regional adiposity in a population-based study of women. These preliminary results may have etiological relevance to the development of metabolic syndrome, but multiple biases of the type described previously may also be operating.

scholarly journals Irregularity of energy intake at meals: prospective associations with the metabolic syndrome in adults of the 1946 British birth cohort

2015 ◽  
Vol 115 (2) ◽  
pp. 315-323 ◽  
Author(s):  
Gerda K. Pot ◽  
Rebecca Hardy ◽  
Alison M. Stephen
Keyword(s):  
Risk Factors ◽  
Metabolic Syndrome ◽  
Waist Circumference ◽  
Energy Intake ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors ◽  
Logistic Regression Models ◽  
The Metabolic Syndrome ◽  
Increased Risk ◽  
Health And Development

AbstractIrregularity in eating patterns could be a potential cardiometabolic risk factor. We aimed to study the associations of irregular intake of energy at meals in relation to cardiometabolic risk factors 10 and 17 years later. Variability of energy intake data – derived from 5-d estimated diet diaries of cohort members of the National Survey for Health and Development collected at ages 36 (n1416), 43 (n1505) and 53 years (n1381) – was used as a measure for irregularity. Associations between meal irregularity scores with cardiometabolic risk factors measured 10 and 17 years later were investigated using linear mixed models and logistic regression models. The results showed that irregularity scores changed significantly over the years (P<0·05). At age 36 years, subjects with a more irregular intake of energy at lunch (OR 1·42; 95 % CI 1·05, 1·91) and between meals (OR 1·35; 95 % CI 1·01, 1·82) had an increased risk for the metabolic syndrome 17 years later; at lunch was also associated with an increased waist circumference (OR 1·58; 95 % 1·27, 1·96) and TAG levels (OR 1·33; 95 % CI 1·02, 1·72). At age 43 years, subjects with a more irregular intake at breakfast had an increased risk of the metabolic syndrome 10 years later (OR 1·53; 95 % CI 1·15, 2·04), as well as an increased BMI (OR 1·66; 95 % CI 1·31, 2·10), waist circumference (OR 1·53; 95 % CI 1·23, 1·90) and diastolic blood pressure (OR 1·42; 95 % CI 1·13, 1·78). In conclusion, subjects with a more irregular intake of energy, mostly at breakfast and lunch, appeared to have an increased cardiometabolic risk 10 and 17 years later.

scholarly journals The metabolic syndrome and body composition in childhood cancer survivors

2011 ◽  
Vol 54 (6) ◽  
pp. 253 ◽  
Author(s):  
Young Bae Sohn ◽  
Su Jin Kim ◽  
Sung Won Park ◽  
Se-Hwa Kim ◽  
Sung-Yoon Cho ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Body Composition ◽  
Cancer Survivors ◽  
Childhood Cancer ◽  
Childhood Cancer Survivors ◽  
The Metabolic Syndrome

scholarly journals Isotemporal substitution of inactive time with physical activity and time in bed: cross-sectional associations with cardiometabolic health in the PREDIMED-Plus study

2019 ◽  
Vol 16 (1) ◽  
Author(s):  
Aina M. Galmes-Panades ◽  
Veronica Varela-Mato ◽  
Jadwiga Konieczna ◽  
Julia Wärnberg ◽  
Miguel Ángel Martínez-González ◽  
...  
Keyword(s):  
Physical Activity ◽  
Blood Pressure ◽  
Older Adults ◽  
Metabolic Syndrome ◽  
Body Composition ◽  
Waist Circumference ◽  
Biochemical Parameters ◽  
Cross Sectional ◽  
The Metabolic Syndrome ◽  
Time In Bed

Abstract Background This study explored the association between inactive time and measures of adiposity, clinical parameters, obesity, type 2 diabetes and metabolic syndrome components. It further examined the impact of reallocating inactive time to time in bed, light physical activity (LPA) or moderate-to-vigorous physical activity (MVPA) on cardio-metabolic risk factors, including measures of adiposity and body composition, biochemical parameters and blood pressure in older adults. Methods This is a cross-sectional analysis of baseline data from 2189 Caucasian men and women (age 55–75 years, BMI 27–40 Kg/m2) from the PREDIMED-Plus study (http://www.predimedplus.com/). All participants had ≥3 components of the metabolic syndrome. Inactive time, physical activity and time in bed were objectively determined using triaxial accelerometers GENEActiv during 7 days (ActivInsights Ltd., Kimbolton, United Kingdom). Multiple adjusted linear and logistic regression models were used. Isotemporal substitution regression modelling was performed to assess the relationship of replacing the amount of time spent in one activity for another, on each outcome, including measures of adiposity and body composition, biochemical parameters and blood pressure in older adults. Results Inactive time was associated with indicators of obesity and the metabolic syndrome. Reallocating 30 min per day of inactive time to 30 min per day of time in bed was associated with lower BMI, waist circumference and glycated hemoglobin (HbA1c) (all p-values < 0.05). Reallocating 30 min per day of inactive time with 30 min per day of LPA or MVPA was associated with lower BMI, waist circumference, total fat, visceral adipose tissue, HbA1c, glucose, triglycerides, and higher body muscle mass and HDL cholesterol (all p-values < 0.05). Conclusions Inactive time was associated with a poor cardio-metabolic profile. Isotemporal substitution of inactive time with MVPA and LPA or time in bed could have beneficial impact on cardio-metabolic health. Trial registration The trial was registered at the International Standard Randomized Controlled Trial (ISRCTN: http://www.isrctn.com/ISRCTN89898870) with number 89898870 and registration date of 24 July 2014, retrospectively registered.

Obesity and Body Composition in Man and Woman: Associated Diseases and the New Role of Gut Microbiota

2020 ◽  
Vol 27 (2) ◽  
pp. 216-229 ◽  
Author(s):  
Ennio Avolio ◽  
Paola Gualtieri ◽  
Lorenzo Romano ◽  
Claudio Pecorella ◽  
Simona Ferraro ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Body Composition ◽  
Gut Microbiota ◽  
Disease Risk ◽  
Intestinal Flora ◽  
Disease Process ◽  
The Body ◽  
Heart Attacks ◽  
The Metabolic Syndrome ◽  
Pubmed Database

Background: Obesity is now recognized as a worldwide health issue and has reached epidemic proportions, affecting both developed and developing countries. The World Obesity Federation stated that “Obesity is a chronic relapsing disease process”: as a result, obesity has been recognized internationally as a chronic disease. : The primary cause of the metabolic syndrome and increase of the cardiovascular risk have been identified in "sick fat", a condition then defined as adiposopathy. Heart attacks, strokes and renal failures are pathologies that have mid-risk factors such as dyslipidemia, hypertension and diabetes, which in turn are caused by obesity, whose primary risk factor is represented by the diet. The aim of the present review is to consider the importance of body composition, together with chronic inflammation and a new gut microbiota data that may turn out to be crucial elements of some target treatment of human obesity. Methods: In this review, we performed research using PubMed database reviewing the evidence in the literature of evidence information regarding the link between obesity and body composition in the development of metabolic disease via inflammation markers and in particular, the new role exerted by gut microbiota. Results: Several papers were evaluated searching for differences in fat mass and disease risk. We also identified the same papers dealing with differences in body composition and metabolic syndrome. Our attention focuses also on a new frontier of gut microbiota composition in the body weight decrease and anti-inflammatory effects. Conclusion: To the saving of lean mass, for the prevention of cardiometabolic diseases, also considering the relationship with obesity, it is necessary to reduce the inflammatory state, acting on the gut-microbiota and on the intestinal permeability. To improve the health of the intestinal flora, we propose a 4P medicine and treatment with probiotics, prebiotics, postbiotics, and polyphenols.

scholarly journals Metabolic syndrome and insulin resistance in obese adolescents

2014 ◽  
Vol 32 (1) ◽  
pp. 55-59 ◽  
Author(s):  
Amanda Oliva Gobato ◽  
Ana Carolina J. Vasques ◽  
Mariana Porto Zambon ◽  
Antonio de Azevedo Barros Filho ◽  
Gabriel Hessel
Keyword(s):  
Insulin Resistance ◽  
Metabolic Syndrome ◽  
Body Composition ◽  
Subcutaneous Fat ◽  
Hdl Cholesterol ◽  
Cutoff Point ◽  
Abdominal Circumference ◽  
Model Assessment ◽  
Obese Adolescents ◽  
The Metabolic Syndrome

Objective: To verify the prevalence of metabolic syndrome and insulin resistance in obese adolescents and its relationship with different body composition indicators. Methods: A cross-sectional study comprising 79 adolescents aged ten to 18 years old. The assessed body composition indicators were: body mass index (BMI), body fat percentage, abdominal circumference, and subcutaneous fat. The metabolic syndrome was diagnosed according to the criteria proposed by Cook et al. The insulin resistance was determined by the Homeostasis Model Assessment for Insulin Resistance (HOMA-IR) index for values above 3.16. The analysis of ROC curves was used to assess the BMI and the abdominal circumference, aiming to identify the subjects with metabolic syndrome and insulin resistance. The cutoff point corresponded to the percentage above the reference value used to diagnose obesity. Results: The metabolic syndrome was diagnosed in 45.5% of the patients and insulin resistance, in 29.1%. Insulin resistance showed association with HDL-cholesterol (p=0.032) and with metabolic syndrome (p=0.006). All body composition indicators were correlated with insulin resistance (p<0.01). In relation to the cutoff point evaluation, the values of 23.5 and 36.3% above the BMI reference point allowed the identification of insulin resistance and metabolic syndrome. The best cutoff point for abdominal circumference to identify insulin resistance was 40%. Conclusions: All body composition indicators, HDL-cholesterol and metabolic syndrome showed correlation with insulin resistance. The BMI was the most effective anthropometric indicator to identify insulin resistance.

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