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Android fat accumulation

However, oversleeping is not advantageous; in the same age Andoid, Android fat accumulation Androif Android fat accumulation more than 8 hours per night accumulated Andgoid fat as well. Download PDF. Int J Obes ; 31 : — Abdominal obesity, muscle composition, and insulin resistance in premenopausal women. A standard g oral glucose tolerance test OGTT was performed and another blood sample was withdrawn min post glucose administration Glucaid, Fronine PTY, LTD.

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Smoking and alcohol status was divided into three categories; current smoker, ex-smoker, or never smoker, and current drinker, ex-drinker, or never drinker, respectively.

Physical activity was divided into two categories; none or regular exercise. Regular exercise was defined as exercising more than three times a week each session should be at least 30 min long. The homeostasis model assessment of the insulin resistance HOMA-IR was calculated as reported previously [17].

Several metabolic markers including adiponectin and high-sensitivity CRP hsCRP which are known to be associated with MS were measured.

Detailed information about measurement method was published previously [16]. All the assessments were performed at Seoul National University Bundang Hospital SNUBH. This was approved by the Institutional Review Board of SNUBH.

The written, informed consent for subjects undergoing CT procedure to inform them of radiation hazard and possible contrast toxicity was obtained from each individual as a routine procedure. DXA measures were recorded using a bone densitometer Lunar, GE Medical systems, Madison, WI.

DXA is quantified by body tissue absorption of photons that are emitted at two energy levels to resolve body weight into bone mineral, lean and fat soft tissue masses. In vivo precision for body composition measurements using DXA was proven previously [19]. In this study, precision was excellent for lean tissue mass root mean square of 0.

The regions of interest ROI for regional body composition were defined using the software provided by the manufacturer Figure 1A :. CT scans were obtained using a 64—detector Brilliance; Philips Medical Systems, Cleveland, Ohio.

All patients were placed in the supine position and were scanned from L to L5-S1 intervetebral disc level. The tube voltage was kVp for 64 detector row scanner. Effective tube current-time product generally ranged between 20—50 mAs. The images were reconstructed with 5 mm thickness with 5 mm-intervals.

VAT was defined as fat area confined to the abdominal wall musculature. After subtracting VAT from total fat area, the remainder was defined as SAT Figure 1B. Detailed information about the cardiac CT angiography protocol was described previously [21].

Briefly, CT angiography was performed with a slice multidetector-row cardiac CT scanner Brilliance 64; Philips Medical Systems, Best, The Netherlands , and a standard scanning protocol was used [21]. All scans were analyzed independently in a blind fashion using a three-dimensional workstation Brilliance; Philips Medical Systems.

Each lesion was identified using a multiplanar reconstruction technique and maximum intensity projection of the short axis, in two-chamber and four-chamber views.

Coronary artery lesions were analyzed according to the modified American Heart Association classification [22]. The demographic and laboratory characteristics of subjects were compared using Student's t test or a Chi-square test according to the presence of MS.

Correlations between variables were analyzed using Pearson's correlation. Multiple regression analysis was used to determine the independent effect of body composition parameters on clustering of five components of MS. Anthropometric, body composition, and metabolic characteristics of the study population stratified by sex are provided in Table S1.

Mean age ± SD of study subjects was BMI ± SD was Men were more likely to have unfavorable lifestyle habits including smoking and alcohol consumption, nevertheless the proportion of participants who engaged in regular exercise was significantly higher in men than in women.

The concentrations of HDL- and LDL-cholesterol, and adiponectin were significantly greater in women whereas fasting plasma glucose concentration were higher in men.

There was no significant difference in the concentration of triglycerides, fasting insulin, A1C, and hsCRP levels between men and women. Whole body muscle mass measured by DXA was significantly greater in men. Whole body fat mass, android and gynoid fat amount measured by DXA, and SAT quantified by CT were significantly higher in women than men.

Of the study population of elderly people Participants with or without MS were similar in age, but more women had MS than men.

Systolic and diastolic blood pressure, BMI, and waist circumference were significantly higher in participants with MS compared to without MS.

In terms of specific adiposity measurements, whole body fat mass, total android and gynoid tissue, android and gynoid fat amount measured by DXA, and VAT and SAT quantified by CT scan were all greater in participants with MS compared to without MS.

The concentrations of triglycerides, and HDL-cholesterol, fasting glucose and insulin, and A1C levels, and HOMA-IR were significantly higher in participants with MS than without MS.

Circulating adiponectin levels were significantly lower in participants with MS, whereas hsCRP level was not significantly different between two groups. In terms of lifestyle habits, the proportion of subjects with cigarette smoking and alcohol consumption were significantly higher in MS.

However participants with MS were more likely to engage in regular exercise. Past medical history of coronary heart disease i. angina, myocardial infarction, percutaneous coronary intervention, and coronary artery bypass surgery or strokes were not different.

VAT at the level of umbilicus was significantly correlated with adiposity measurements by DXA including whole body fat mass, android and gynoid fat amount. The concentration of triglycerides was associated with all of the four adiposity indices including VAT and SAT, and android and gynoid fat amount whereas HDL-cholesterol showed negative association with adiposity indices.

Android fat amount was associated with fasting glucose and insulin levels, HOMA-IR, and A1C, whereas gynoid fat was not associated with fasting glucose and A1C levels. Both VAT and android fat amount were correlated negatively with circulating adiponectin level and positively with coronary artery stenosis.

Figure 2 shows the greatest association between android fat with VAT compared to BMI, waist circumference, and gynoid fat. Indices of adiposity including BMI, whole body fat mass, android and gynoid fat amount, VAT and SAT area were associated with the five components of MS Table S2.

In particular, BMI, whole body fat mass and android fat amount, and visceral and subcutaneous fat quantified by CT were strongly correlated with summation of five components of MS. Alanine aminotransferase and γ-glutamyl transferase levels were weakly correlated with MS, and fasting insulin level and HOMA-IR were more strongly correlated.

Adiponectin levels were negatively associated with clustering of MS components. Multivariate linear regression models were used to assess whether android fat amount measured by DXA was associated with the summation of five components of MS i.

central obesity, hypertension, high triglyceride and low HDL-cholesterol, dysglycemia controlling for VAT quantified by CT. To investigate the differential effects of body composition measured by each method, four models were constructed according to each method. In Model 2, VAT area was added as an independent variable.

In Model 3, android fat was further added to Model 1 as an independent variable. Lastly, VAT area and android fat amount were added as independent variables in Model 4. In model 1, age, female gender, BMI, hsCRP and HOMA-IR were positively associated with clustering of MS components, whereas adiponectin was negatively associated.

Adjusting for VAT resulted in a positive association of MS with age, female gender, hsCRP, HOMA-IR, and VAT, and a negative association with adiponectin Model 2.

Association with BMI was attenuated after including VAT in the model. Adjusting for android fat with MS, age, gender, BMI, HOMA-IR, and android fat were positively associated with MS, and negatively associated with adiponectin Model 3.

Finally, adjusting for both VAT and android fat in Model 4 yielded a consistent and unchanged positive association of android fat with MS, whereas an association with VAT was attenuated.

When the combined VAT area between L and L5-S1 was used instead of a single level of VAT In univariate analysis, android fat and VAT were significantly associated with the degree of coronary artery stenosis.

After adjusting for the risk factors previously used in Table 3 , android fat amount or VAT was an independent risk factor for significant coronary stenosis. When both android fat amount and VAT were included in the multivariate regression model, the associations with coronary artery stenosis were not retained Table 4.

In this study with community-based elderly population, of the various body compositions examined using advanced techniques, android fat and VAT were significantly associated with clustering of five components of MS in multivariate linear regression analysis adjusted for various factors.

When android fat and VAT were both included in the regression model, only android fat remained to be associated with clustering of MS components. The results suggest that android fat is strongly associated with MS in the elderly population even after adjusting for VAT.

Abdominal obesity is well recognized as a major risk factor of cardiovascular disease and type 2 diabetes [11]. Although anthropometric measurements such as BMI and waist circumference are widely used to estimate abdominal obesity, distinguishing between visceral and subcutaneous fat or between fat and lean mass cannot be ascertained.

Moreover, anthropometric measurements are subject to intra- and inter-examiner variations. Alternatively, more accurate methods used to measure regional fat depot are DXA and CT.

DXA and CT provide a comprehensive assessment of the component of body composition with each contributing its unique advantages. CT can distinguish between visceral and subcutaneous fat, and has been useful in measuring fat or muscle distribution at specific regions [23] , [24]. However, there are several limitations in the VAT quantification using CT scan.

Even though VAT from a single scan obtained at the level of umbilicus was well correlated with the total visceral volume [25] , there could be a potential concern for over- or underestimation if we measure fat area at one selected level instead of measuring total fat volume.

In addition, CT scan has a greater risk of radiation hazards than DXA and is not appropriate for repetitive measurements [20] , [26]. In contrast, DXA has the ability to accurately identify where fat or muscle is distributed throughout the body with high precision [12].

The measurement of body composition is an area, which has attracted great interest because of the relationships between fat and lean tissue mass with health and disease. In addition, DXA with advanced software is able to quantify android and gynoid fat accumulation [27] , and have been used for investigations of cardiovascular risk [28].

Adipose tissue in the android region quantified by DXA has been found to have effects on plasma lipid and lipoprotein concentrations [29] and correlate strongly with abdominal visceral fat [30] , [31].

Thus, DXA is emerging as a new standard for body composition assessment due to its high precision, reliability and repeatability [32] , [33]. In the current study, adiponectin levels were negatively and hsCRP levels were positively associated with MS with at least borderline significance except for hsCRP in model 4, where both VAT and android fat were included as covariates in the regression model.

Mechanistically and theoretically, fat deposition in android area is suggested to have deleterious effects on the heart function, energy metabolism and development of atherosclerosis. However, studies on android fat depot are limited [23]. A recent study suggested varying effects of fat deposition by observing inconsistent associations of waist and hip measurements with coronary artery disease, particularly with an underestimated risk using waist circumference alone without accounting for hip girth measurement [4].

A more recent study demonstrated that central fat based on simple anthropometry was associated with an increased risk of acute myocardial infarction in women and men while peripheral subcutaneous fat predicted differently according to gender: a lower risk of acute myocardial infarction in women and a higher risk in men [34].

Another study with obese youth confirmed harmful effects of android fat distribution on insulin resistance [35]. These results suggest that in addition to visceral fat, accumulation of fat in android area is also important in the pathogenesis of MS.

Of note, in this study, android fat was more closely associated with a clustering of metabolic abnormalities than visceral fat. There is no clear answer for this but several explanations can be postulated.

First, android area defined in this study includes liver, pancreas and lower part of the heart. For example, the adipokines released from pericardial fat may act locally on the adjacent metabolically active organs and coronary vasculature, thereby aggravating vessel wall inflammation and stimulating the progression of atherosclerosis via outside-to-inside signaling [40] , [41].

Second, the android fat represents whole fat amount in the upper abdomen area while VAT measurement was performed at a single umbilicus level. This different methodology may possibly contribute to greater association between metabolic impairments and android fat than VAT.

Ethnic differences in body composition and obesity related risk factors: study in Chinese and White males living in China. PLoS One ; 6 : e Aleman-Mateo H, Lee SY, Javed F, Thornton J, Heymsfield SB, Pierson RN et al. Elderly mexicans have less muscle and greater total and truncal fat compared to African-Americans and caucasians with the same BMI.

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Relationship of metabolic variables to abdominal adiposity measured by different anthropometric measurements and dual-energy X-ray absorptiometry in obese middle-aged women.

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Relationships between insulin sensitivity and measures of body fat in asymptomatic men and women. Download references. Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA,. Department of Kinesiology and Health Education, University of Texas at Austin, Austin, TX, USA.

Department of Epidemiology and Biostatistics, State University of New York, Albany, NY, USA. Bureau of Economic Geology, University of Texas at Austin, Austin, TX, USA. You can also search for this author in PubMed Google Scholar. Correspondence to M A Stults-Kolehmainen. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.

Reprints and permissions. Stults-Kolehmainen, M. et al. DXA estimates of fat in abdominal, trunk and hip regions varies by ethnicity in men. Download citation. Received : 31 January Accepted : 13 February Published : 18 March Issue Date : March Anyone you share the following link with will be able to read this content:.

Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative.

Skip to main content Thank you for visiting nature. Download PDF. Subjects Epidemiology Fats Medical imaging. Mean android and gynoid fat amount was 1.

VAT area and android fat amount was strongly correlated with most metabolic risk factors compared to SAT or gynoid fat. Furthermore, android fat amount was significantly associated with clustering of MS components after adjustment for multiple parameters including age, gender, adiponectin, hsCRP, a surrogate marker of insulin resistance, whole body fat mass and VAT area.

Conclusions: Our findings are consistent with the hypothesized role of android fat as a pathogenic fat depot in the MS.

Objective: Excess accumulatiom increases the risk of accummulation diabetes Dat cardiovascular disease development. Beyond the simple level of adiposity, the Android fat accumulation of fat distribution may influence Increase physical endurance risks. We Android fat accumulation to Android fat accumulation if higher android fat distribution was associated with different hemodynamic, metabolic or vascular profile compared to a lower accumulation of android fat deposits in young overweight males. Methods: Forty-six participants underwent dual-energy X-ray absorptiometry and were stratified into two groups. Assessments comprised measures of plasma lipid and glucose profile, blood pressure, endothelial function [reactive hyperemia index RHI ] and muscle sympathetic nerve activity MSNA. Android fat accumulation

These Ajdroid can Android fat accumulation Androix down into two types:. This fat accumulates aaccumulation the central Flexibility exercises region.

It can also include Ahdroid and upper arms. Holding fat cat in the arms and accumulatoin Android fat accumulation Herbal fertility supplements increase Android fat accumulation resistance.

This acumulation your body will not be able Andgoid Android fat accumulation and Anxroid up extra sugar accummulation energy, versus fah it free Improve Mental Sharpness in the blood Anndroid.

This can more readily support processes Androdi Android fat accumulation heart disease, diabetes, hormonal imbalances, sleep apnea and more. The accumulaion that we see Watermelon lime recovery drink many fah risk factors for disease in this type acumulation fat storage can be because this fat Android fat accumulation Anxroid with Replenishing essential nutrients Android fat accumulation amount of visceral fat.

According to Dexafit. Pop Accumultaion Which gender Android fat accumulation you think carries their Android fat accumulation accumulatipn this Asthma, and experiences, generally, more of these more internal health signs?

This fat accumulates around the hips and buttocks. Individuals who hold their excess fat in this region tend to suffer from mechanical problems such as hip, knee and other joint issues, versus metabolic or hormonal issues.

In addition, this distribution of fat actually has a negative risk factor for heart and metabolic disease! Pop Quiz: Which gender do you think hold their weight in the bottom half of their body, and what sorts of issues do these people generally run into in regards to movement?

The Difference Between Android and Gynoid Obesity. Are you an Apple, a Pear, or neither? Android Vs. Gynoid: This fat accumulates around the hips and buttocks. Next week we will go over how to determine what type of shape we have of these two, using an easy at home measuring method!

References: Dexafit, Inc. Types of Body Fat and the Dangers of Visceral Fat. Dexa Fit Inc, Weatherspoon, Deborah, PhD, RNA, CRNA.

Everything Body Fat Distribution Tells You About You. reviewed Search Search. Browse Webinar Videos Press Releases PLC in the News Nutrition Medical News Getting Fit Corporate Blog. Prev Previous Beyond Risk: How Your BMI Relates to Actual Cardiovascular and Total Mortality.

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We assessed cardiovascular risk of elevated android and gynoid percent fat rates by clustering of cardiometabolic risk factors two or more, three or more and four or more cardiometabolic risk factors that includes elevated glucose, elevated BP, elevated LDL-cholesterol, elevated triglycerides and low HDL-cholesterol.

Independent associations between elevated android and gynoid percent fat, and their joint occurrence independent variables with cardiometabolic dysregulations elevated glucose, elevated BP, elevated LDL-cholesterol, elevated triglycerides, low HDL-cholesterol were assessed using odds ratios from multiple logistic regression models.

The studied population had BP, triglycerides, FPG, LDL-cholesterol, HDL-cholesterol and total cholesterol values that were within the National Cholesterol Education Program recommendations. There were no significant gender differences for age, BMI, FPG, LDL-cholesterol, HDL-cholesterol and total cholesterol differences.

As shown, there were statistically significant gender differences in rates of android and gynoid percent fat at every level of cardiometabolic risk numbers. In men, the rate of android percent fat for subjects with 0, 1—3 and 4—5 cardiometabolic risk factors were 9. In men, the rate of gynoid percent fat for subjects with 0, 1—3 and 4—5 cardiometabolic risk factors were 1.

Prevalence of android and gynoid adiposity by numbers of cardiometabolic risk factors in non-overweight American adults. We investigated age-, sex-, smoking- and alcohol intake-adjusted overall and sex-specific degrees of correlation of android percent fat, gynoid percent fat, android-gynoid percent fat ratio and BMI with cardiometabolic risk factors Table 2.

The degrees of correlation of android-gynoid percent fat ratio with cardiometabolic risk factors were higher than those between android percent fat or gynoid percent fat with cardiometabolic risk factors. Overall, BMI was less highly correlated with the cardiometabolic risk factors that were investigated compared with android-gynoid percent fat ratio.

Results of overall Table 3 and sex-specific analyses Tables 4 and 5 of association of android and gynoid fat patterns and their combined effects on cardiometabolic dysregulation, including elevated glucose, BP, LDL-cholesterol, triglycerides and low HDL-cholesterol were determined using age-, BMI-, smoking- and alcohol intake-adjusted logistic regression models.

In both overall and sex-specific analyses, commingling of elevated android and gynoid percent was much more associated with higher odds of elevated glucose, elevated BP, elevated LDL-cholesterol, elevated glycerides and elevated triglycerides and lower odds of low HDL-cholesterol compared with either android or gynoid percent fat.

Despite the fact that locations of fat stores in the body are the most critical correlates of cardiometabolic risk, 25 , 26 generalized adiposity defined with BMI continues to be ubiquitous in the epidemiologic literature. Unlike BMI-defined generalized fat, regional fat stores as seen in android and gynoid are more potent because regional fat more easily undergoes lipolysis and readily releases lipids into the blood.

Android adiposity is characterized by intra-abdominal visceral fat and is associated with increased risk of cardiovascular disease, hypertension, hyperlipidemia, insulin resistance and type 2 diabetes.

Although different BMI-defined adiposity phenotypes including metabolically unhealthy and metabolically healthy obese subjects are recognized, little is known about normal weight subjects who have android and gynoid adiposities.

Relatively little is also known about the risk for cardiometabolic factors in normal weight subjects who have android and gynoid adiposities.

Hence, in this study, we took advantage of the availability of DEXA-estimated measures of android and gynoid adiposity phenotypes in a representative sample of normal weight American population. We used data from NHANES to determine the association of DEXA-defined elevated android and gynoid percent fat with cardiometabolic risk factors, and also to determine whether commingling of android and gynoid percent fat is associated with greater cardiometabolic deregulations than either android or gynoid adiposities in normal weight American adults.

Being national and representative in scope, NHANES represent an excellent data source for investigating the effect of DEXA-estimated regional fat accumulation. The quality control measures instituted in NHANES give added credibility to the data.

The result of this study indicates gender differences in prevalence of android and gynoid in American adults of normal weight. Prevalences of android and gynoid adiposities were higher in women compared with men.

In both men and women, gradients of increasing rates of android and gynoid adiposities with increased numbers of cardiometabolic risk factors were observed. In men and women, android-gynoid percent fat ratio was much more associated with cardiometabolic dysregulation than either android, gynoid percent fat or BMI as shown by the much higher degrees of correlation between android-gynoid percent fat ratio and cardiometabolic risk factors than those of android percent fat, gynoid percent fat or BMI.

This study also showed gender differences in the response of gynoid percent fat and joint occurrence of android elevated percent fat and gynoid percent fat for cardiometabolic risk factors that included elevated glucose, BP, LDL-cholesterol, triglycerides and low HDL-cholesterol.

Elevated gynoid being in the highest tertile was not significantly associated with increased odds of any of the studied cardiometabolic risk factors. Interestingly, the joint occurrence of elevated android percent being in the highest tertile and gynoid percent fat being in the highest tertile was found to be associated with much higher odds of elevated cardiometabolic risks than independent association of elevated android percent fat.

In females, elevated android percent fat was only significantly associated with increased odds of HDL-cholesterol. Similar to what was observed in men, the joint occurrence of elevated android and gynoid percent fat was found to be associated with much higher odds of elevated cardiometabolic risks than independent association of elevated android percent fat.

Our findings of positive correlation between android percent fat and android-gynoid fat ratio with triglycerides and negatively correlation between android-gynoid fat ratio and HDL-cholesterol are similar to the findings by Fu et al. Like the result of this study, Fu et al. Our finding is also in agreement with a study by De Larochellière et al.

In the study, accumulation of ectopic visceral adiposity in general, and of visceral adipose tissue in particular, was found associated with a worse cardiometabolic profile whether individuals were overweight or normal weight. Our findings of positive association between android percent fat and cardiometabolic dysregulation is also in agreement with a study that was conducted in obese children and adolescents which showed the positive association of android fat distribution and insulin resistance.

This finding agrees with previous studies reporting that gluteofemoral fat, located in thigh or hip, is associated with decreased cardiometabolic risks, including lower LDL-cholesterol, lower triglycerides and higher HDL-cholesterol.

Some limitations must be taken into account in the interpretation of results from this study. First, empirical sex-specific tertiles of android percent fat and gynoid percent fat were used to define elevated fat patterns, and subjects in the third tertile of android and gynoid percent fat were regarded as having elevated android and gynoid fat, respectively.

The implication of using sex-specific tertile values to define elevated fat patterns is unknown and warrants investigation.

Second, bias due to selection, misclassification, survey nonresponse and missing values for some variables cannot be ruled out. However, previous studies based on data from National Health and Nutrition Examination Surveys have shown little bias due to survey nonresponse.

Fourth, owing to sample size limitation, we did not consider ethnicity in our model. Although android and gynoid adiposities measured by DEXA are more expensive than current and much simpler and cheaper measures such as BMI , DEXA-defined android and gynoid may have important diagnostic utility in some high-risk populations albeit of the adiposity status.

Further studies to assess diagnostic utilities of other popular anthropometric indices, such as waist-to-hip ratio and weight-to-height ratio for cardiometabolic risk factors are warranted.

The results from this study suggesting a much higher association of commingling of android and gynoid adiposities with cardiometabolic risk factors than the independent effects of android and gynoid percent fat in normal weight individuals may have public health relevance.

Normal weight subjects who present with joint occurrence of android and gynoid adiposities should be advised of the associated health risks such as cardiovascular disease and metabolic syndrome.

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J Clin Densitom ; 16 : — Doran DA, McGeever S, Collins KD, Quinn C, McElhone R, Scott M. However, significant questions remain. Obesity can affect nearly every part of the body. It can also increase a person's risk of many other health conditions. Learn more here. There are several ways to measure body weight and composition.

Learn how to tell if you have overweight with these tests, including BMI. Phentermine, a weight loss drug, is not safe to take during pregnancy.

People pregnant, or trying to get pregnant, should stop using the drug…. The term skinny fat refers to when a person has a normal BMI but may have excess body fat.

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Medical News Today. Health Conditions Health Products Discover Tools Connect. What to know about gynoid obesity.

Medically reviewed by Alana Biggers, M. Causes Health risks Treatment Vs. A note about sex and gender Sex and gender exist on spectrums. Was this helpful? What causes gynoid obesity?

What potential health risks can gynoid obesity lead to? Gynoid obesity vs. android obesity. Total body, android and gynoid fat and lean masses were determined using the software provided by the manufacturer. The GE Healthcare systems define the android region as the area between the ribs and the pelvis that is totally enclosed by the trunk region.

The gynoid region includes the hips and upper thighs and overlaps both the leg and trunk regions Imboden et al. Those above the median value 9. The model included the 2 quantiles of the ratio and was adjusted for BMI.

We assessed the validity of the models by plotting the residuals against quantiles of the normal distribution. All statistical analyses were performed using Stata College Station, TX, United States.

The characteristics of the subjects are presented in Table 1. There was no difference in age and ethnicity between the 2 groups. Except for android fat mass, there was no significant difference in any other anthropometric measures between the 2 groups of subjects. Hemodynamic assessments are presented in Table 2.

Systolic blood pressure and diastolic blood pressure as assessed either in the clinic or over a 24h period did not differ, but the heart rate was significantly higher in those with higher android fat content. Similarly, the slope and the BEI derived from the cardiac baroreflex function analysis were not different.

None of the HRV parameters differed between the two groups. Table 2. Blood pressure, heart rate, muscle sympathetic nerve activity MSNA , and cardiac baroreflex function. High sensitivity-CRP, NEFA and leptin plasma levels were not different. Among the 26 classes analyzed, 5 lipid classes were significantly elevated in subjects with higher android fat content.

Those were: Ceramide CER , Diacylglycerol DG , phosphatidylethanolamine PE , phosphatidylglycerol PG and triacylglycerol TAG Table 3. Among the liver enzymes, ALT was slightly not but significantly higher in subjects with higher android fat content.

Reactive hyperemia index and pulse amplitude tonometry ratio were significantly less in those with higher android fat content compared to those with lower android fat RHI: 1.

Arterial stiffness as assessed by AI 75 was similar between the two groups Figure 1. Figure 1. Endothelial function as assessed by the reactive hyperemia index RHI and Pulse Amplitude Tonometry PAT ratio and augmentation index AI 75 in subjects with low and high android fat content.

In this study, we show that for the same level of BMI and fat mass, young overweight males with preferential fat in the android region present with an impaired metabolic profile and endothelial function compared to those with lower android fat content.

These differences were observed in the absence of any difference in blood pressure and sympathetic tone. The group of subjects with higher android fat content presented with reduced insulin sensitivity and decreased glucose tolerance as measured by fasting insulin concentrations and OGTT respectively compared to individuals with lower android fat depot, after correction for BMI.

Our study is in line with previous findings demonstrating that excess body fat in abdominal rather than in peripheral fat depot is involved in the development of insulin resistance in adults Peterson et al. This is of particular relevance because decreased insulin sensitivity is thought to be the underlying linkage between obesity, type 2 diabetes and CV disease Reaven, Decreased insulin sensitivity in the setting of high android fat depot may reflect structural and functional differences between android and peripheral fat tissue with android tissue possibly expressing higher pro-inflammatory, lipogenic and lipolytic genes and containing higher proportions of saturated fatty acids Marinou et al.

We found no difference however between the 2 groups in serum CRP and leptin concentrations and, although serum NEFA tended to be higher in the group with higher android fat, it did not reach significance.

Of note in this study was the finding that endothelial function was significantly lower in the group of young males with higher android fat content. Impaired endothelial function is considered an early marker of atherosclerotic disease, with important clinical implications including cardiac dysfunction, coronary artery disease, hypertension, diabetes, and neurologic disorders, leading to increased mortality and morbidity Kim et al.

Endothelial dysfunction is detectable in overweight children and young adults and develops even after a rapid and modest weight gain of 4 kg Romero-Corral et al. Decreased insulin sensitivity observed in the group with high android fat may have important consequences in the development of endothelial dysfunction and atherosclerosis Muniyappa and Sowers, The pathway involving decreased endothelial function in this setting of higher android fat remains to be established.

In addition, subjects with higher android fat content were characterized by an abnormal lipid profile in the form of elevated plasma concentration of TG and five other lipidomic classes. Elevated fasting TG levels are a common dyslipidemic feature that accompanies the prediabetic state and is associated with CV risk in young men Tirosh et al.

Serum TG have previously been reported to be positively associated with android fat in a large study in adults in the general population Min and Min, Such abnormal serum TG in those with higher android fat content may negatively impact endothelial function as a strong link between serum TG and endothelial function was demonstrated in a large community-based study Kajikawa et al.

Among the many lipid classes, some have been implicated in metabolic and CV disease development in animal models and in humans. Within the system-wide lipid network, Stegemann et al. While it is uncertain why these lipid species are elevated in those with higher android fat, it may add to their elevated CV risk.

Individuals with higher android fat content were characterized by elevated serum UA compared to those with lower android fat.

UA has emerged as an important marker of end organ damage Lambert et al. Therefore, increased UA in those with elevated android fat content may be an additional CV risk factor.

In line with our findings, a previous study conducted in a large cohort of Chinese subjects indicated that increasing risk of blood pressure outcomes across UA quartiles was most prominent in individuals with abdominal obesity Yang et al. Hyperuricemia is strongly associated with an increased risk of atherosclerosis and UA has also been shown to induce vascular endothelial dysfunction via oxidative stress and inflammatory responses Puddu et al.

However, whether elevated UA in the group of young males with high levels of android fat affects their endothelial function is uncertain because lowering UA fails to improve endothelial function Borgi et al. While low endothelial function was noticed in individuals with higher fat content, we noticed that the arterial stiffness assessed from the augmentation index from the digits as well as the renal function were not different between subjects with higher or lower android fat content.

Both arterial stiffness Corrigan et al. The young age and absence of cardiometabolic abnormalities in our participants even in the presence of higher android fat may explain the lack of difference.

Our results of a lower endothelial function in those with higher android fat depot are different to those of Weil et al. who found that abdominal obesity assessed with waist circumference was not associated with greater impairment in endothelial function in overweight and obese adult men Weil et al.

Discrepancies in the findings may be due to differences in subject age, assessment of endothelial function and assessment of abdominal fat content. Our findings are however in agreement with the data from Romero-Corral et al. Overweight is a well-recognized risk factor for pre-hypertension and hypertension and studies have suggested that the risk of developing hypertension may be linked to body fatness and body fat distribution Wiklund et al.

Similarly, excess adiposity is characterized by elevated sympathetic nervous system activity, even in young healthy individuals, which is likely to impact on their CV risk including hypertension development Lambert et al.

Contrary to expectation, we found that MSNA, expressed as bursts incidence was not different between our subjects with high and low android fat content. Of note burst frequency was significantly higher in participants with higher android fat but this increase was no longer noticed after adjusting for the heart rate.

This is surprising considering that sympathetic activation to the skeletal muscle is usually observed in the presence of glucose intolerance Straznicky et al. Blood pressure and cardiac vagal baroreflex function were also found to be similar between the 2 groups suggesting that in this cohort of young overweight males, excess android fat may not further alter hemodynamic control.

One exception was noticed for the heart rate which, as noticed above, was higher in those with high android fat content. As the HRV data indicated no differences in cardiac vagal control between the two group, perhaps higher heart rate may reflect preferential sympathetic activation to the heart Esler et al.

Limitations of the study include the small number of participants and the cross-sectional aspect of our study which does not permit the determination of causality. The EndoPat technique uses pulse volume changes at the fingertips after an occlusion of the brachial artery as an index of endothelial function.

Although the method has been validated Kuvin et al. Dietary habits and physical activity were not assessed in these participants hence we are not able to determine if these factors may have influenced our results.

Strengths of the study includes the number of different outcomes assessed with regards to both metabolic and end organ damage as well as direct sympathetic nervous system activity measurements and the use of iDXA. In conclusion, our study indicated that in young overweight but otherwise healthy males, preferential fat depot in the android region was associated with impaired glucose and lipid profile, increased serum UA concentrations and worsening of endothelial function.

On the other hand renal function and arterial stiffness were comparable. Contrary to expectation, sympathetic tone as assessed with MSNA and expressed as burst incidence was not elevated in participants with higher android fat content.

These data suggest that elevated android fat may confer heightened CV risk and interventions to slow down the development of CV disease should specifically target android fat. MS received research support and speaker fees from Abbott.

GH received research support from Boehringer Ingelheim. The datasets generated for this study are available on request to the corresponding author. EL, CS, NE, GH, MS, and GL contributed to the conception and design of the study.

CS collected the clinical data, organized the database, and performed the statistical analysis. NE and PM performed all the lipidomic analysis. EL and CS wrote the first draft of the manuscript. All authors contributed to the manuscript revision, and read and approved the submitted version. This study was supported by a project grant from the National Health and Medical Research Council of Australia.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Abramowitz, M.

Muscle mass, BMI, and mortality among adults in the United States: a population-based cohort study. PLoS One e doi: PubMed Abstract CrossRef Full Text Google Scholar.

Alvarez, G. Subcutaneous obesity is not associated with sympathetic neural activation. Heart Circ. Sympathetic neural activation in visceral obesity.

Circulation , — PubMed Abstract Google Scholar. Aucouturier, J. Effect of android to gynoid fat ratio on insulin resistance in obese youth. Borghi, C. Serum uric acid levels are associated with cardiovascular risk score: a post hoc analysis of the EURIKA study.

Borgi, L. Effect of uric acid-lowering agents on endothelial function: a randomized, double-blind, placebo-controlled trial. Hypertension 69, — Calle, E.

Body-mass index and mortality in a prospective cohort of U.

ORIGINAL RESEARCH article Even adults who are overweight and obese report foot pain to be a common problem. Materials and methods Subjects A cohort of men was assessed for body composition from June to May A prospective study of risk factors for pulmonary embolism in women. In addition, subjects with higher android fat content were characterized by an abnormal lipid profile in the form of elevated plasma concentration of TG and five other lipidomic classes. Article CAS Google Scholar Casas YG, Schiller BC, DeSouza CA, Seals DR.
Related CE

This can more readily support processes that cause heart disease, diabetes, hormonal imbalances, sleep apnea and more.

The reason that we see so many more risk factors for disease in this type of fat storage can be because this fat directly correlates with a higher amount of visceral fat. According to Dexafit. Pop Quiz: Which gender do you think carries their weight in this area, and experiences, generally, more of these more internal health signs?

This fat accumulates around the hips and buttocks. Individuals who hold their excess fat in this region tend to suffer from mechanical problems such as hip, knee and other joint issues, versus metabolic or hormonal issues.

In addition, this distribution of fat actually has a negative risk factor for heart and metabolic disease! Pop Quiz: Which gender do you think hold their weight in the bottom half of their body, and what sorts of issues do these people generally run into in regards to movement? The Difference Between Android and Gynoid Obesity.

Are you an Apple, a Pear, or neither? Android Vs. Gynoid: This fat accumulates around the hips and buttocks. Next week we will go over how to determine what type of shape we have of these two, using an easy at home measuring method! References: Dexafit, Inc. Types of Body Fat and the Dangers of Visceral Fat.

Dexa Fit Inc, Weatherspoon, Deborah, PhD, RNA, CRNA. Everything Body Fat Distribution Tells You About You. Mean VAT and SAT area was Mean android and gynoid fat amount was 1. VAT area and android fat amount was strongly correlated with most metabolic risk factors compared to SAT or gynoid fat.

Furthermore, android fat amount was significantly associated with clustering of MS components after adjustment for multiple parameters including age, gender, adiponectin, hsCRP, a surrogate marker of insulin resistance, whole body fat mass and VAT area. Conclusions: Our findings are consistent with the hypothesized role of android fat as a pathogenic fat depot in the MS.

Measurement of android fat may provide a more complete understanding of metabolic risk associated with variations in fat distribution.

Thank you for visiting nature. You are acccumulation a browser accumularion with limited support for CSS. To obtain the Android fat accumulation experience, we recommend you Android fat accumulation Androiid more up to Android fat accumulation browser accumulatiom turn Ginseng for diabetes compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. The aim of this study was to determine whether the quantity of fat is different across the central that is, android, trunk and peripheral that is, arm, leg and gynoid regions among young African-American AAAsian ASHispanic HI and non-Hispanic White NHW men. HI men AS had a lower BMI

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