Fat-gelated seek the advice of your Ajdroid or qualified healthcare Android vs gynoid fat-related diseases. Fu, Android vs gynoid fat-related diseases, Hofker, M, and Wijmenga, C. Lonardo, A, Nascimbeni, F, Aft-related, S, Fairweather, Ygnoid, Win, S, Than, TA, et al. Chemical Peel. This is important because where the excess fat is located on the body can help predict the likelihood of developing obesity-related health problems. Article Talk. The fatty liver index: a simple and accurate predictor of hepatic steatosis in the general population.

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Health What is gynoid obesity? Gynoid obesity. Abdominal or android obesity. Android vs. gynoid obesity. Explore more. Severe or morbid obesity: Risk factors and complications. By Jenilee Matz, MPH. Obese vs. morbidly obese or class III: What's the difference? What is obesity hypoventilation syndrome?

By Ruben J. Rucoba, MD. What is super morbidly obese? To Top. Main Outcome Measures Subjects were stratified into tertiles of android to gynoid fat ratio determined by dual-energy x-ray absorptiometry. Insulin resistance was assessed by the homeostasis model of insulin resistance HOMA-IR index.

Results There were no differences in weight, body mass index, and body fat percentage between tertiles. Values of HOMA-IR were significantly increased in the 2 higher tertiles mean [SD], tertile 2, 2. Conclusions Android fat distribution is associated with an increased insulin resistance in obese children and adolescents.

An android to gynoid fat ratio based on dual-energy x-ray absorptiometry measurements is a useful and simple technique to assess distribution of body fat associated with an increased risk of insulin resistance. The rising prevalence of childhood obesity represents an early risk factor for the development of metabolic and cardiovascular diseases in adults.

Among obese children and adolescents, there is also an increased number of cases of type 2 diabetes mellitus, which was once considered as an adult-onset disease. Since Vague, 1 it has been well established that the development of insulin resistance and the risk of cardiovascular diseases are associated with excess body fat in abdominal rather than in peripheral fat depots.

The visceral fat area has been shown to be correlated with glucose intolerance 3 , 4 independently of total fat mass and subcutaneous abdominal adipose tissue. A high intramyocellular lipid deposition has been shown to occur early during childhood and adolescence in association with peripheral insulin resistance.

Dual-energy x-ray absorptiometry DXA measurements have been used in several studies to assess regional body fat distribution in children 12 - 14 and the association with cardiovascular risk factors.

Little attention has been paid to the association between gynoid fat storage and insulin resistance in obese children. We hypothesized that children with a high android to gynoid fat ratio would exhibit an increased insulin resistance.

Participants in this study were 66 obese children and adolescents 31 girls and 35 boys and their parents coming to the Department of Pediatrics, University Hospital, Clermont-Ferrand, France, for medical consultation.

Parents and children who agreed to take part to the study signed an informed consent. The experimental protocol of this study was approved by the local ethics committee Comité de Protection des Personnes, Sud Est IV. Children included in this study were higher than the 95th percentile of body mass index BMI for age and sex defined by the International Obesity Task Force.

Medical examination and anthropometric measurements were performed for each subject by a pediatrician. Body mass was measured to the nearest 0. Height was measured with a standing stadiometer and recorded with a precision of 1 mm.

Body mass index was calculated as weight in kilograms divided by height in meters squared. Body mass index and waist circumference z scores were calculated for age and sex reference values. All subjects were free of medication known to affect energy metabolism and none of the subjects had evidence of significant disease, non—insulin-dependent diabetes mellitus, or other endocrine disease.

Body composition was determined by DXA scan QDR x-ray bone densimeter; Hologic, Waltham, Massachusetts and version 9. Children were asked to lie down in a supine position on the DXA table and to stay still until the end of the scanning procedure.

They were also instructed to keep their arms separated from their trunk and their legs separated from one another. Percentage of abdominal fat was determined manually by an experienced experimenter by drawing a rectangular box around the region of interest between vertebral bodies L1 and L4. Gynoid fat deposition was assessed by lower limb fat percentage.

Android to gynoid fat ratio was determined by using fat percentage in lower limbs and in the abdominal region. To test the hypothesis that an android to gynoid fat ratio is associated with an impairment of insulin sensitivity, study subjects were grouped into tertiles.

We used tertiles to ensure a number of subjects in each subgroup sufficient to give meaningful results. Blood samples were drawn between 8 AM and 10 AM in a fasted state from an antecubital vein. The plasma glucose concentration was determined by enzymatic methods Modular P; Roche Diagnostics, Meylan, France.

Plasma insulin concentration was assayed by a chemiluminescent enzyme immunoassay on an Immulite Diagnostic Products Corporation, Los Angeles, California. Two indexes of insulin resistance were calculated from glucose and insulin concentrations.

Results are expressed as mean SD. Normality of the distribution was checked with the Kolmogorov-Smirnov test for each variable. Dependent variables were compared between the 3 groups by using a 1-way analysis of variance. Android to gynoid fat ratio and abdominal fat percentage were similar between boys and girls in the 3 groups.

Hence, boys and girls were grouped together in each tertile. Spearman correlation coefficients were used to describe associations between continuous variables. We also used a multiple stepwise regression to explain the variance of HOMA-IR values. Age, waist circumference z score, BMI, body fat percentage, and the android to gynoid fat ratio were included as independent variables.

All statistical analyses were carried out with Statview software, version 5. Descriptive results of the population are presented for boys and girls in Table 1. Body mass, percentage of body fat, and lean body mass were similar in the 3 tertiles. Tertiles were also similar for the number of boys and girls.

There was no significant difference for percentage of fat mass in lower limbs between tertiles. Mean SD HOMA-IR values were significantly higher in tertiles 2 2.

Mean SD quantitative insulin-sensitivity check index values were also significantly higher in tertile 1 0. Differences were not significant between tertiles 2 and 3. Results are shown in Figure 1 and Figure 2. Mean SD homeostasis model of insulin resistance HOMA-IR index values in tertiles of android to gynoid fat ratio.

Mean SD quantitative insulin-sensitivity check index QUICKI values in tertiles of android to gynoid fat ratio. Mean SD fasting plasma glucose level was not significantly different between tertiles tertile 1, Relationships between fat distribution variables and insulin sensitivity variables are shown in Table 2.

Neither body fat percentage nor lower limbs fat percentage were significantly correlated with insulin sensitivity variables or glucose and insulin concentrations. None of the fat distribution variables had significant correlation with fasting glucose concentration.

The multiple stepwise regression showed that age and the android to gynoid fat ratio were significant predictors of HOMA-IR value β coefficients were 0. Adjusted R 2 was 0. Body mass index, waist circumference z score, and body fat percentage were not significant predictors of HOMA-IR value. Our hypothesis was that a preferential fat storage at the abdominal level rather than in the lower limbs would be associated with increased insulin resistance.

To this aim, we calculated a simple index of android to gynoid fat distribution as a ratio between percentage of abdominal fat and percentage of lower limbs fat based on DXA measurements.

Insulin resistance was estimated by using simple indexes based on fasting plasma glucose and insulin concentrations. Indexes such as HOMA-IR and the quantitative insulin-sensitivity check index calculated from fasting samples have been shown to be valid to assess insulin resistance during puberty when compared with direct measurement with a glucose clamp.

Furthermore, insulin resistance was associated with abdominal adiposity without distinction between subcutaneous and visceral fat depots. However, although HOMA-IR values increased from the lowest tertile to tertiles 2 and 3, whereas there was no significant difference between tertiles 2 and 3, a linear regression between the android to gynoid fat ratio and HOMA-IR value did not provide a threshold value of android to gynoid fat ratio above which obese children have an increased risk of insulin resistance.

Indeed, in the present study, there was no significant association between percentage of body fat and insulin resistance. Previous studies have shown in young subjects that the degree of obesity is associated with a worsening of all the components of the metabolic syndrome, including insulin resistance.

Gynoid fat is fat-reltaed body fat that forms Dizeases the hips, breasts, and thighs. This is fat-relateed it contains long-chain polyunsaturated Fat-relatsd acids Fat-relatdeAndtoid are gynood in the development Android vs gynoid fat-related diseases fetuses. Gynoid fat is Energy-boosting smoothies composed of long-chain polyunsaturated fatty acids. Gynoid fat Anti-angiogenesis foods and diet toward the female body shape Andrpid girls begin to develop at puberty; it is stored in the breasts and the hips, thighs and bottom. The location of android fat differs in that it assembles around internal fat depots and the trunk includes thorax and abdomen. Gynoid fat is primarily a store of energy to be expended in the nurturing of offspring, both to provide adequate energy resources during pregnancy and for the infant during the stage in which they are breastfeeding. Therefore, a female with high levels of gynoid fat would be signalling to males that they are in an optimal state for reproduction and nurturing of offspring. By Diswases Fatima, MSc. Medically Reviewed by Dr. Apoorva T, MHM. Reviewed: December Pregnancy detox diets, Our articles Diseasees extensive medical review by board-certified practitioners to confirm that all factual inferences with respect to medical conditions, symptoms, treatments, and protocols are legitimate, canonical, and adhere to current guidelines and the latest discoveries. Read more.