Dietary Imbalance between Natural and Added Nutrient Sources Is Associated with Higher Fat Mass in Young Non-Obese Individuals

Increased energy intake from carbohydrates and sugars has been associated with overweight and obesity, risk factors for type 2 diabetes. However, such an association is higher with westernised diets with higher amounts of processed foods. Our aim was to correlate the dietary intake of sugars and lipids from naturally present and added sources with fat mass in young individuals. We performed an observational study in 80 young non-obese individuals, who completed food frequency and nutritional knowledge (NK) questionnaires, as well as an anthropometric evaluation. Foods were divided into naturally or added sources of sugars and lipids, and the intake from both sources was calculated separately. Individuals with a higher fat mass percentage had lower NK and lower consumption of lipids and sugars from naturally present sources. Moreover, consumption of lipids and sugars from naturally present sources was negatively correlated with nutritional knowledge and anthropometric markers of overweight, especially body weight and waist circumference. In non-obese young adults, lower consumption of sugars and lipids from naturally present sources instead of added ones is higher in individuals with excessive fat mass percentage and correlated with anthropometric markers of fat mass. Such dietary imbalance is associated with lower nutritional knowledge, suggesting that it could be a strategy to strengthen the prevention of obesity and associated pathologies later in life.

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DIABETES OR OBESITY; MAJOR EFFECTOR OF ALTERED LEVELS OF GHRELIN AND LEPTIN

10.36106/ijsr/2604593 ◽

2021 ◽

pp. 55-59

Author(s):

Lakshmi G.L ◽

Shruti Dasgupta ◽

Mohammed Salman ◽

Sanjay K. R

Keyword(s):

Type 2 Diabetes ◽

Lean Body Mass ◽

Body Mass ◽

Fat Mass ◽

Postprandial Glucose ◽

Independent Effect ◽

Mass Percentage ◽

Obesity And Diabetes ◽

Obese Subjects

Background: Ghrelin and leptin are the key hormones involved in the energy homeostasis and plays a relevant role in regulating hunger and satiety stimuli afferent to the brain. Abnormalities in the levels of ghrelin and leptin are often associated with the obesity and type 2 diabetes complications. However, there are no studies clarifying whether ghrelin and leptin levels have stronger association with obesity or Type 2 diabetes (T2DM). Aims:To evaluate and compare the independent effect of major dening factors of obesity and diabetes on ghrelin and leptin concentrations. Materials And Methods: Anthropometric measures such as height, weight, waist (WC) and hip circumference (HC), Body mass index (BMI), Basal metabolic rate (BMR), fat percentage, lean body mass, were taken. Assessed daily physical activity and energy intake. Biochemical parameters such as fasting glucose, postprandial glucose, HBA1c, ghrelin, leptin and insulin levels were measured. Statistical Analysis: One-way analysis of variance (ANOVA), Chi-square (χ2) test Pearson's correlation coefcients, Multiple stepwise linear regression model analysis were performed. Result: The diabetic subjects irrespective of obesity showed signicantly higher waist to hip ratio, HOMAIR levels of fasting blood glucose, postprandial glucose and signicantly lower levels of Ghrelin than non-diabetics. Similarly, obese subjects irrespective of diabetes have signicantly higher BMR and higher levels of Leptin than non-diabetics. Asignicantly higher BMI, fat mass percentage and lower lean body mass percentage were observed in obese subjects irrespective of diabetes than non-obese subjects. Among non-obese, diabetics have higher BMI, Fat mass percentage and lower lean body mass percentage. The levels of insulin were signicantly higher in diabetic obese subjects. HOMAIR (P≤0.0001) and Postprandial glucose (P≤0.05) showed negative independent effect and QUICKI (P≤0.0001) showed positive independent effect on the levels of ghrelin. BMI (P≤0.05) showed a positive effect and lean body mass percentage (P≤0.0001) showed an inverse effect on levels of leptin. Conclusion: It is evident from the study that low levels of ghrelin are predominantly associated with diabetes parameters when compared to parameters of obesity and on the contrary increased leptin levels have much stronger association with measures of obesity than diabetes. Evidence of altered leptin and ghrelin levels in these disorders infers vice versa, their respective roles in obesity and lean diabetes.

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Overweight and obesity risk factors in children aged 3–7 years: a prospective study in the city of Kraków

Annals of Human Biology ◽

10.1080/03014460.2017.1380226 ◽

2017 ◽

Vol 44 (8) ◽

pp. 693-703

Author(s):

Małgorzata Kowal ◽

Stanisław Matusik ◽

Maciej Wojciech Pilecki ◽

Łukasz Kryst ◽

Jan Sobiecki ◽

...

Keyword(s):

Risk Factors ◽

Prospective Study ◽

Overweight And Obesity ◽

Obesity Risk ◽

Obesity Risk Factors ◽

A Prospective Study ◽

The City

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Childhood Obesity: Risk Factors and Preventive Measures

Medical & Clinical Research ◽

10.33140/mcr.04.05.02 ◽

2019 ◽

Vol 4 (5) ◽

Keyword(s):

Risk Factors ◽

Childhood Obesity ◽

Cultural Practice ◽

Overweight And Obesity ◽

Obesity Risk ◽

Common People ◽

Obesity Epidemic ◽

Hormonal Imbalance ◽

The Future ◽

Obesity Risk Factors

The obesity epidemic has grown worldwide in both the developed and developing countries. We are the “present” of the era with ever increasing growth of obesity; the coming generation is our “future”. Future of obesity largely depends on how we are handling it in present. Overweight and obesity prevailing in children has multiple causes from genetic factor, hormonal imbalance to environmental factors, lifestyle preferences and cultural practice. Keeping apart the hormonal, genetic and any physiological causes of obesity which are not in direct control, the remaining factors such as lifestyle, environment and cultural background which can be modulate to help eliminating percentage of existing and future obesity. Evidences have suggested that the major cause of obesity is imbalance between food habits and physical activity. Additional factors as per the recent researches show that excessive use of smart phones has increased the overweight issues and also increases the anxiety among the user. Childhood obesity has maximum chances to develop into adulthood obesity. Therefore, to eradicate the future obesity, there is need to increase the awareness of do's & don'ts to prevent obesity and also the educate common people to know about the pros & cons of obesity. This paper is inclined towards the various risk factors of childhood obesity, and also pointing some preventive and educational measure to avoid obesity in the future.

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E65 Overweight and obesity – risk factors in calcium oxalate stone disease?

European Urology Supplements ◽

10.1016/s1569-9056(11)61188-3 ◽

2011 ◽

Vol 10 (7) ◽

pp. 476

Author(s):

B. Duethorn

Keyword(s):

Risk Factors ◽

Calcium Oxalate ◽

Stone Disease ◽

Overweight And Obesity ◽

Obesity Risk ◽

Calcium Oxalate Stone ◽

Obesity Risk Factors

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Are overweight and obesity risk factors for invasive mechanical ventilation in severe coronavirus disease 2019 pneumonia?

Archives of Endocrinology and Metabolism ◽

10.20945/2359-3997000000350 ◽

2021 ◽

Author(s):

Maria Fernanda Coss-Rovirosa ◽

Mercedes Aguilar-Soto ◽

Dalia Cuenca ◽

Mariana Velez-Pintado ◽

Antonio Camiro-Zuñiga ◽

...

Keyword(s):

Risk Factors ◽

Mechanical Ventilation ◽

Invasive Mechanical Ventilation ◽

Overweight And Obesity ◽

Obesity Risk ◽

Obesity Risk Factors

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A simple equation to estimate body fat percentage in children with overweightness or obesity: a retrospective study

PeerJ ◽

10.7717/peerj.3238 ◽

2017 ◽

Vol 5 ◽

pp. e3238 ◽

Cited By ~ 3

Author(s):

Ernesto Cortés-Castell ◽

Mercedes Juste ◽

Antonio Palazón-Bru ◽

Laura Monge ◽

Francisco Sánchez-Ferrer ◽

...

Keyword(s):

Correlation Coefficient ◽

Intraclass Correlation Coefficient ◽

Fat Mass ◽

Intraclass Correlation ◽

Overweight And Obesity ◽

Fat Free Mass ◽

Coefficient Of Determination ◽

Fat Percentage ◽

Mass Percentage ◽

Cross Sectional

BackgroundDual-energy X-ray absorptiometry (DXA) provides separate measurements of fat mass, fat-free mass and bone mass, and is a quick, accurate, and safe technique, yet one that is not readily available in routine clinical practice. Consequently, we aimed to develop statistical formulas to predict fat mass (%) and fat mass index (FMI) with simple parameters (age, sex, weight and height).MethodsWe conducted a retrospective observational cross-sectional study in 416 overweight or obese patients aged 4–18 years that involved assessing adiposity by DXA (fat mass percentage and FMI), body mass index (BMI), sex and age. We randomly divided the sample into two parts (construction and validation). In the construction sample, we developed formulas to predict fat mass and FMI using linear multiple regression models. The formulas were validated in the other sample, calculating the intraclass correlation coefficient via bootstrapping.ResultsThe fat mass percentage formula had a coefficient of determination of 0.65. This value was 0.86 for FMI. In the validation, the constructed formulas had an intraclass correlation coefficient of 0.77 for fat mass percentage and 0.92 for FMI.ConclusionsOur predictive formulas accurately predicted fat mass and FMI with simple parameters (BMI, sex and age) in children with overweight and obesity. The proposed methodology could be applied in other fields. Further studies are needed to externally validate these formulas.

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OVERWEIGHT AND OBESITY RISK ASSESSMENT - TWO METHODS, DIFFERENT RESULTS

Physical Education of Students ◽

10.15561/20755279.2016.0306 ◽

2016 ◽

Vol 20 (3) ◽

pp. 53-57 ◽

Cited By ~ 6

Author(s):

Cristiana Lucretia Pop

Keyword(s):

Body Fat ◽

Health Knowledge ◽

Overweight And Obesity ◽

The Body ◽

Body Fat Percentage ◽

Obesity Risk ◽

Fat Percentage ◽

Mass Percentage ◽

Significant Difference ◽

Girl Students

Purpose: the purpose of this study was to verify if there is any significant difference between body fat assessment by calculating body mass index and by using bioelectrical impedance analysis. Materials: subsequently we determined the ratio between body fat and muscular mass percentage in a sample of 156 university girl students. Results: BMI and muscle mass percentage seem to have similar variance and trends, while body fat exceeded in numbers and percents the highest levels of BMI. While by calculating BMI the found number of overweight and obese subjects was 23 from the total of 156, (14 %); by measuring body fat percentage that number increased to 67 (43%) of girl students in the sample. The t test showed significant difference between BMI values and the body fat percentage for the study sample: t (155) = 2.37, p-0.01. Conclusions: this study supports the idea that BMI results may be insufficient for correct assessment of overweight and obesity risk. Body composition adds useful information about health and fitness. A few concluding recommendations, regarding beneficial effects of exercise, have been made aiming to provide students of all body parameters with meaningful, relevant and positive physical education and health knowledge.

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