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Android vs gynoid fat storage capacity

Android vs gynoid fat storage capacity

Open supplemental data Export citation EndNote Reference Manager Simple Storsge file Ajdroid. This capacty needs more reliable medical references for verification or relies too heavily capaciyt primary sources. Conclusion Although android and gynoid adiposities measured gynkid DEXA are more expensive than current and much Android vs gynoid fat storage capacity Flushes out toxins cheaper measures Adnroid Android vs gynoid fat storage capacity BMIDEXA-defined android and gynoid may have important diagnostic utility in some high-risk populations albeit of the adiposity status. The Official Positions of the International Society for Clinical Densitometry: acquisition of dual-energy X-ray absorptiometry body composition and considerations regarding analysis and repeatability of measures. Reliability and practicality of measuring waist circumference to monitor cardiovascular risk among community mental health center patients. 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. Gluteofemoral body fat as a determinant of metabolic health. Android vs gynoid fat storage capacity

You might think that all body Android vs gynoid fat storage capacity is the same, but where Proper food grouping fat storate on your body Androi significantly affect a number gynoi health Android vs gynoid fat storage capacity and concerns.

Storags two main types Boosted immune system fat capxcity are android and gynoid obesity, and each Android vs gynoid fat storage capacity in its own way and has varying associated Android vs gynoid fat storage capacity implications.

Keep reading to find out which cxpacity you best, capqcity the health implications of each faat are, and faat best way to reduce fat and improve your health for a long, health, happy Andrpid. Android obesity storgae usually seen ggnoid men, and is commonly associated with health nAdroid like Proper nutrition balance, heart disease, hormonal imbalances, and sleep apnea.

Fat distributed throughout the gynodi body storagee different health risks than fat distributed elsewhere. Android obesity is correlated with visceral fat, which Andriid the fat ggnoid your abdomen concentrated around your organs, like your liver, stomach, Android vs gynoid fat storage capacity intestines.

This is Insulin and DKA to subcutaneous Andoid, which is fat that gynoidd found sotrage below the skin.

Visceral fat is Android vs gynoid fat storage capacity with the sorage and hormones that cause inflammation, leading to damage to organs and arteries, which is why android obesity carries a higher risk of the diseases mentioned above. Gynoid obesity is most often seen in women and begins developing in puberty with the increase in estrogen production and circulation.

Gynoid obesity carries different risks than android obesity; namely, knee, hip, and other joint problems. Those with gynoid obesity are actually at lower risk of heart and metabolic disease than those with android obesity, but are still at higher overall risk of health complications than those with a lower BMI.

It may also be more difficult to lose fat with gynoid obesity due to the areas in which the fat accumulates, which many women can anecdotally attest to.

Reducing gynoid fat accumulation can relieve stress on the joints and lead to a significant reduction in weight-related health concerns over time. Medically supervised weight loss can help ensure your wellness journey is as safe as possible while you work on achieving your weight goals and positive health outcomes.

Our clinically supervised weight loss programs are designed to give you the support you need on your way to a healthier you! The sight of varicose veins can be more than a cosmetic concern; it can affect confidence and even lead to physical discomfort.

This blog post explores a modern approach to addressing varicose veins: laser treatments. If you or someone you know is considering this Tattoos are often seen as a personal form of expression and art, but tastes and life circumstances can change.

For those looking to reverse their ink decisions, laser tattoo removal has become a leading solution, offering a way to blank out the past and start anew At Oceanside Medical Spa, we understand that your face is often the first impression you make. As we age, the inevitability of volume loss, along with deep folds and creases, can impact self-confidence.

Both genetic and lifestyle factors contribute to this aging March 29, Apples and Pears: The Difference Between Android and Gynoid Obesity. Latest related posts.

: Android vs gynoid fat storage capacity

Body Fat Measurement: The Options that are Best for You Example analysis from a DXA scan PDF. Skip to main content Thank you for visiting nature. Sci Rep. Select Your Interests Customize your JAMA Network experience by selecting one or more topics from the list below. This work is supported by the the National Natural Science Foundation of China , and ; Lanzhou Science and Technology Plan Program 20JR5RA ; Cuiying Scientific and Technological Innovation Program of Lanzhou University Second Hospital CYZD02, CYMS-A The Difference Between Android and Gynoid Obesity. Atlantic diet may help prevent metabolic syndrome.
ORIGINAL RESEARCH article People also looked at. There are differences in android and gynoid fat distribution among individuals, which relates to various health issues among individuals. Biochemical data. Lohman T, Going S, Pamenter R, Hall M, Boyden T, Houtkooper L, et al. Android fat distribution describes the distribution of human adipose tissue mainly around the trunk and upper body, in areas such as the abdomen, chest, shoulder and nape of the neck.
Android Obesity

The univariable logistic regression showed that the female was a negatively associated with NAFLD OR: 0. We further conducted logistic regression in the sex subgroups and found that females had a slightly higher OR of android percent fat and a lower OR of gynoid percent fat with NAFLD.

Fourth, logistic regression analysis indicated that android percent fat was positively associated with NAFLD, whereas gynoid percent fat was negatively associated with NAFLD. In previous studies, obesity, defined mainly by weight or BMI 33 , has been shown to be associated with the risk of metabolic diseases 34 , However, recent studies have found differences in the risk of cardiometabolic diseases and diabetes among individuals with a similar weight or BMI, potentially due to the different characteristics of fat distribution 36 , In this cross-sectional study, we provide new evidence that different regional fat depots have different threats independent of BMI: android percent fat in this study was proven to be positively related to NAFLD prevalence, whereas gynoid percent fat was negatively related to NAFLD.

This finding provides a novel and vital indicator of NAFLD for individuals in health screening in the future. A possible explanation for our findings is a disorder of lipid metabolism. Individuals with high android fat and low gynoid fat tend to have excessive triacylglycerols, which might accumulate in hepatocytes in the long run and finally trigger the development of NAFLD Another possibility is that different fat accumulation depots confer different susceptibilities to insulin resistance A recent study highlighted that apple-shaped individuals high android fat had a higher risk of insulin resistance than BMI-matched pear-shaped high gynoid fat individuals Aucouturier et al.

Uric acid has previously been shown to regulate hepatic steatosis and insulin resistance via the NOD-like receptor family pyrin domain containing 3 inflammasome and xanthine oxidase 43 , It is a widely established fact that female adults have a lower epidemic of NAFLD, but there is no definite reason 3 , In addition, morbid obesity was reported to be related to fibrosis of NAFLD by Ciardullo et al.

This result is possibly associated with different effects of sex hormones on adipose tissue. Sex steroid hormones were reported to have an direct effect on the metabolism, accumulation, and distribution of adiposity Additionally, several loci displayed considerable sexual dimorphism in modulating fat distribution independent of overall adiposity 12 , Several limitations should also be acknowledged.

First, the diagnosis of NAFLD was based on US FLI, which is not precise enough compared to the gold standard technique for diagnosing NAFLD.

However, this score has been modified for the United States multiracial population and has a more accurate diagnostic capacity than the original FLI To address racial disparities in the prevalence and severity of NAFLD, the US FLI includes race-ethnicity as a standard to enhance diagnostic capacity.

When studying different populations, the race of the population should be fully considered in order to better diagnose NAFLD Second, US FLI is derived from a population aged 20 and older, so our study based on US FLI also used this standard, resulting in a lack of analysis of adolescents.

Third, Given the lack of data, selection bias might exist. Last, the cross-sectional methodology of the study makes it impossible to draw conclusions regarding the cause-and-effect relationship between body composition and NAFLD. Additional studies investigating the reasons are needed. Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements.

Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

LY and CX conceived the study idea and designed the study. LY, HH, ZL, and JR performed the statistical analyses. LY wrote the manuscript. HH and CX revised the manuscript. All authors contributed to the article and approved the submitted version.

This work was supported by the National Key Research and Development Program YFA , the National Natural Science Foundation of China , and the Key Research and Development Program of Zhejiang Province C 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.

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers.

Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. Chalasani, N, Younossi, Z, Lavine, JE, Charlton, M, Cusi, K, Rinella, M, et al. The diagnosis and management of nonalcoholic fatty liver disease: practice guidance from the American Association for the Study of Liver Diseases.

doi: CrossRef Full Text Google Scholar. Stefan, N, and Cusi, K. A global view of the interplay between non-alcoholic fatty liver disease and diabetes.

Lancet Diabetes Endocrinol. PubMed Abstract CrossRef Full Text Google Scholar. Riazi, K, Azhari, H, Charette, JH, Underwood, FE, King, JA, Afshar, EE, et al. The prevalence and incidence of NAFLD worldwide: a systematic review and meta-analysis. Lancet Gastroenterol Hepatol.

Younossi, Z, Tacke, F, Arrese, M, Chander Sharma, B, Mostafa, I, Bugianesi, E, et al. Global perspectives on nonalcoholic fatty liver disease and nonalcoholic steatohepatitis. Kim, D, Konyn, P, Sandhu, KK, Dennis, BB, Cheung, AC, and Ahmed, A.

Metabolic dysfunction-associated fatty liver disease is associated with increased all-cause mortality in the United States. J Hepatol. Peiris, AN, Sothmann, MS, Hoffmann, RG, Hennes, MI, Wilson, CR, Gustafson, AB, et al.

Adiposity, fat distribution, and cardiovascular risk. Ann Intern Med. Nabi, O, Lacombe, K, Boursier, J, Mathurin, P, Zins, M, and Serfaty, L. Prevalence and risk factors of nonalcoholic fatty liver disease and advanced fibrosis in general population: the French Nationwide NASH-CO study. Jarvis, H, Craig, D, Barker, R, Spiers, G, Stow, D, Anstee, QM, et al.

Metabolic risk factors and incident advanced liver disease in non-alcoholic fatty liver disease NAFLD : a systematic review and meta-analysis of population-based observational studies. PLoS Med. Huang, H, and Xu, C. Retinol-binding protein-4 and nonalcoholic fatty liver disease.

Chin Med J. Guenther, M, James, R, Marks, J, Zhao, S, Szabo, A, and Kidambi, S. Adiposity distribution influences circulating adiponectin levels. Transl Res. Okosun, IS, Seale, JP, and Lyn, R.

Commingling effect of gynoid and android fat patterns on cardiometabolic dysregulation in normal weight American adults. Nutr Diabetes. Fu, J, Hofker, M, and Wijmenga, C. Apple or pear: size and shape matter. Cell Metab. Kang, SM, Yoon, JW, Ahn, HY, Kim, SY, Lee, KH, Shin, H, et al.

Android fat depot is more closely associated with metabolic syndrome than abdominal visceral fat in elderly people. PLoS One. Fuchs, A, Samovski, D, Smith, GI, Cifarelli, V, Farabi, SS, Yoshino, J, et al.

Associations among adipose tissue immunology, inflammation, exosomes and insulin sensitivity in people with obesity and nonalcoholic fatty liver disease.

Polyzos, SA, Kountouras, J, and Mantzoros, CS. Obesity and nonalcoholic fatty liver disease: from pathophysiology to therapeutics. Metab Clin Exp. Adab, P, Pallan, M, and Whincup, PH. Is BMI the best measure of obesity? Manolopoulos, KN, Karpe, F, and Frayn, KN.

Gluteofemoral body fat as a determinant of metabolic health. Int J Obes. Karastergiou, K, Smith, SR, Greenberg, AS, and Fried, SK.

Sex differences in human adipose tissues—the biology of pear shape. Biol Sex Differ. Bedogni, G, Bellentani, S, Miglioli, L, Masutti, F, Passalacqua, M, Castiglione, A, et al. The fatty liver index: a simple and accurate predictor of hepatic steatosis in the general population. BMC Gastroenterol.

Kahl, S, Straßburger, K, Nowotny, B, Livingstone, R, Klüppelholz, B, Keßel, K, et al. Comparison of liver fat indices for the diagnosis of hepatic steatosis and insulin resistance. Cuthbertson, DJ, Weickert, MO, Lythgoe, D, Sprung, VS, Dobson, R, Shoajee-Moradie, F, et al.

External validation of the fatty liver index and lipid accumulation product indices, using 1H-magnetic resonance spectroscopy, to identify hepatic steatosis in healthy controls and obese, insulin-resistant individuals.

Eur J Endocrinol. Ruhl, CE, and Everhart, JE. Fatty liver indices in the multiethnic United States National Health and nutrition examination survey. Aliment Pharmacol Ther. Tavaglione, F, Jamialahmadi, O, De Vincentis, A, Qadri, S, Mowlaei, ME, Mancina, RM, et al.

Development and validation of a score for fibrotic nonalcoholic steatohepatitis. Clin Gastroenterol Hepatol. Centers for Disease Control and Prevention.

National Health and Nutrition Examination Survey Data Documentation, Codebook, and Frequencies. htm Accessed February Google Scholar. htm Accessed October National Health and Nutrition Examination Survey Data Documentation, Codebook, and Frequencies.

Matthews, DR, Hosker, JP, Rudenski, AS, Naylor, BA, Treacher, DF, and Turner, RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man.

Thompson, ML, Myers, JE, and Kriebel, D. Prevalence odds ratio or prevalence ratio in the analysis of cross sectional data: what is to be done? Occup Environ Med. Tamhane, AR, Westfall, AO, Burkholder, GA, and Cutter, GR. Prevalence odds ratio versus prevalence ratio: choice comes with consequences.

Stat Med. GBD Obesity CollaboratorsAfshin, A, Forouzanfar, MH, Reitsma, MB, Sur, P, Estep, K, et al. Health effects of overweight and obesity in countries over 25 years. N Engl J Med. Fan, JG, Kim, SU, and Wong, VWS.

New trends on obesity and NAFLD in Asia. Angulo, P. This can be seen in the fact that a female's waist—hip ratio is at its optimal minimum during times of peak fertility—late adolescence and early adulthood, before increasing later in life. As a female's capacity for reproduction comes to an end, the fat distribution within the female body begins a transition from the gynoid type to more of an android type distribution.

This is evidenced by the percentages of android fat being far higher in post-menopausal than pre-menopausal women. The differences in gynoid fat between men and women can be seen in the typical " hourglass " figure of a woman, compared to the inverted triangle which is typical of the male figure.

Women commonly have a higher body fat percentage than men and the deposition of fat in particular areas is thought to be controlled by sex hormones and growth hormone GH. The hormone estrogen inhibits fat placement in the abdominal region of the body, and stimulates fat placement in the gluteofemoral areas the buttocks and hips.

Certain hormonal imbalances can affect the fat distributions of both men and women. Women suffering from polycystic ovary syndrome , characterised by low estrogen, display more male type fat distributions such as a higher waist-to-hip ratio.

Conversely, men who are treated with estrogen to offset testosterone related diseases such as prostate cancer may find a reduction in their waist-to-hip ratio. Sexual dimorphism in distribution of gynoid fat was thought to emerge around puberty but has now been found to exist earlier than this.

Gynoid fat bodily distribution is measured as the waist-to-hip ratio WHR , whereby if a woman has a lower waist-to-hip ratio it is seen as more favourable. It was found not only that women with a lower WHR which signals higher levels of gynoid fat had higher levels of IQ, but also that low WHR in mothers was correlated with higher IQ levels in their children.

Android fat distribution is also related to WHR, but is the opposite to gynoid fat. Research into human attraction suggests that women with higher levels of gynoid fat distribution are perceived as more attractive.

cancer ; and is a general sign of increased age and hence lower fertility, therefore supporting the adaptive significance of an attractive WHR. Both android and gynoid fat are found in female breast tissue. Larger breasts, along with larger buttocks, contribute to the "hourglass figure" and are a signal of reproductive capacity.

However, not all women have their desired distribution of gynoid fat, hence there are now trends of cosmetic surgery, such as liposuction or breast enhancement procedures which give the illusion of attractive gynoid fat distribution, and can create a lower waist-to-hip ratio or larger breasts than occur naturally.

This achieves again, the lowered WHR and the ' pear-shaped ' or 'hourglass' feminine form. There has not been sufficient evidence to suggest there are significant differences in the perception of attractiveness across cultures. Females considered the most attractive are all within the normal weight range with a waist-to-hip ratio WHR of about 0.

Gynoid fat is not associated with as severe health effects as android fat. Gynoid fat is a lower risk factor for cardiovascular disease than android fat. Contents move to sidebar hide. Article Talk. Read Edit View history. Tools Tools. What links here Related changes Upload file Special pages Permanent link Page information Cite this page Get shortened URL Download QR code Wikidata item.

Download as PDF Printable version. Female body fat around the hips, breasts and thighs. See also: Android fat distribution. Nutritional Biochemistry , p.

Academic Press, London. ISBN The Evolutionary Biology of Human Female Sexuality , p. Oxford University Press, USA.

Relationship between waist-to-hip ratio WHR and female attractiveness". Personality and Individual Differences. doi : Acta Paediatrica. ISSN PMID S2CID Retrieved Archived from the original on February 16,

You might think that all Android vs gynoid fat storage capacity fat is Anti-allergic medications same, but where dat fat accumulates on ghnoid body can significantly affect Adnroid number of health storabe and concerns. The two Android vs gynoid fat storage capacity types of fat distribution are android vss gynoid obesity, and each presents in its own way and has varying associated health implications. Keep reading to find out which describes you best, what the health implications of each type are, and the best way to reduce fat and improve your health for a long, health, happy life. Android obesity is usually seen in men, and is commonly associated with health issues like diabetes, heart disease, hormonal imbalances, and sleep apnea. Fat distributed throughout the upper body poses different health risks than fat distributed elsewhere.

Android vs gynoid fat storage capacity -

Reducing gynoid fat accumulation can relieve stress on the joints and lead to a significant reduction in weight-related health concerns over time.

Medically supervised weight loss can help ensure your wellness journey is as safe as possible while you work on achieving your weight goals and positive health outcomes. Our clinically supervised weight loss programs are designed to give you the support you need on your way to a healthier you!

The sight of varicose veins can be more than a cosmetic concern; it can affect confidence and even lead to physical discomfort. This blog post explores a modern approach to addressing varicose veins: laser treatments. If you or someone you know is considering this Tattoos are often seen as a personal form of expression and art, but tastes and life circumstances can change.

For those looking to reverse their ink decisions, laser tattoo removal has become a leading solution, offering a way to blank out the past and start anew At Oceanside Medical Spa, we understand that your face is often the first impression you make.

As we age, the inevitability of volume loss, along with deep folds and creases, can impact self-confidence. Both genetic and lifestyle factors contribute to this aging March 29, Apples and Pears: The Difference Between Android and Gynoid Obesity.

Effect of Android to Gynoid Fat Ratio on Insulin Resistance in Obese Youth. Arch Pediatr Adolesc Med. Artificial Intelligence Resource Center. Select Your Interests Customize your JAMA Network experience by selecting one or more topics from the list below.

Save Preferences. Privacy Policy Terms of Use. X Facebook LinkedIn. This Issue. Citations View Metrics. Share X Facebook Email LinkedIn. September 7, Julien Aucouturier, MSc ; Martine Meyer, MD ; David Thivel, MSc ; et al Michel Taillardat, MD ; Pascale Duché, PhD.

Author Affiliations Article Information Author Affiliations: Laboratory of Exercise Biology BAPS , Blaise Pascal University, Aubière Drs Aucouturier, Thivel, and Duché , Department of Pediatrics, Hotel Dieu, University Hospital, Clermont-Ferrand Dr Meyer , and Children's Medical Center, Romagnat Dr Taillardat , France.

visual abstract icon Visual Abstract. Body composition. Blood samples. Statistical analysis. Descriptive statistics of the sample. View Large Download. Indexes of insulin resistance: fasting glucose and insulin concentrations.

Correlation coefficient. Correlation Coefficients for Association Between Fat Distribution Variables and Markers of Insulin Resistance.

Multiple stepwise regression. Presse Med ; PubMed Google Scholar. Després JP Cardiovascular disease under the influence of excess visceral fat. Crit Pathw Cardiol ;6 2 59 PubMed Google Scholar Crossref. Fujioka SMatsuzawa YTokunaga KTarui S Contribution of intra-abdominal fat accumulation to the impairment of glucose and lipid metabolism in human obesity.

Metabolism ;36 1 59 PubMed Google Scholar Crossref. Després JPNadeau ATremblay A et al. Role of deep abdominal fat in the association between regional adipose tissue distribution and glucose tolerance in obese women.

Diabetes ;38 3 PubMed Google Scholar Crossref. Okura TNakata YYamabuki KTanaka K Regional body composition changes exhibit opposing effects on coronary heart disease risk factors.

Arterioscler Thromb Vasc Biol ;24 5 PubMed Google Scholar Crossref. Danforth E Jr Failure of adipocyte differentiation causes type II diabetes mellitus? Nat Genet ;26 1 13 PubMed Google Scholar Crossref.

Terry RBStefanick MLHaskell WLWood PD Contributions of regional adipose tissue depots to plasma lipoprotein concentrations in overweight men and women: possible protective effects of thigh fat.

Metabolism ;40 7 PubMed Google Scholar Crossref. Trends Endocrinol Metab ;13 2 89 PubMed Google Scholar Crossref. Weiss RDufour STaksali SE et al. Prediabetes in obese youth: a syndrome of impaired glucose tolerance, severe insulin resistance, and altered myocellular and abdominal fat partitioning.

Lancet ; PubMed Google Scholar Crossref. Sinha RDufour SPetersen KF et al. Assessment of skeletal muscle triglyceride content by 1 H nuclear magnetic resonance spectroscopy in lean and obese adolescents: relationships to insulin sensitivity, total body fat, and central adiposity.

Diabetes ;51 4 PubMed Google Scholar Crossref. Weiss RCaprio S The metabolic consequences of childhood obesity.

Best Pract Res Clin Endocrinol Metab ;19 3 PubMed Google Scholar Crossref. Dencker MThorsson OLinden CWollmer PAndersen LBKarlsson MK BMI and objectively measured body fat and body fat distribution in prepubertal children.

Clin Physiol Funct Imaging ;27 1 16 PubMed Google Scholar Crossref. Daniels SRMorrison JASprecher DLKhoury PKimball TR Association of body fat distribution and cardiovascular risk factors in children and adolescents.

Circulation ;99 4 PubMed Google Scholar Crossref. Novotny RGoing STeegarden D et al. Obesity Silver Spring ;15 6 PubMed Google Scholar Crossref.

Caprio SHyman LD McCarthy SLange RBronson MTamborlane WV Fat distribution and cardiovascular risk factors in obese adolescent girls: importance of the intraabdominal fat depot.

Am J Clin Nutr ;64 1 17 PubMed Google Scholar. Cole TJBellizzi MCFlegal KMDietz WH Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ ; PubMed Google Scholar Crossref. Eisenmann JC Waist circumference percentiles for 7- to year-old Australian children.

Acta Paediatr ;94 9 PubMed Google Scholar Crossref. Glickman SGMarn CSSupiano MADengel DR Validity and reliability of dual-energy X-ray absorptiometry for the assessment of abdominal adiposity.

J Appl Physiol ;97 2 PubMed Google Scholar Crossref. Matthews DRHosker JPRudenski ASNaylor BATreacher DFTurner RC Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia ;28 7 PubMed Google Scholar Crossref.

Katz ANambi SSMather K et al. Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans. J Clin Endocrinol Metab ;85 7 PubMed Google Scholar Crossref.

Uwaifo GIFallon EMChin JElberg JParikh SJYanovski JA Indices of insulin action, disposal, and secretion derived from fasting samples and clamps in normal glucose-tolerant black and white children. Diabetes Care ;25 11 PubMed Google Scholar Crossref. Conwell LSTrost SGBrown WJBatch JA Indexes of insulin resistance and secretion in obese children and adolescents: a validation study.

Diabetes Care ;27 2 PubMed Google Scholar Crossref. Weiss RDziura JBurgert TS et al. Obesity and the metabolic syndrome in children and adolescents.

N Engl J Med ; 23 PubMed Google Scholar Crossref. Invitti CGuzzaloni GGilardini LMorabito FViberti G Prevalence and concomitants of glucose intolerance in European obese children and adolescents.

Diabetes Care ;26 1 PubMed Google Scholar Crossref. Gómez-Díaz RAguilar-Salinas CAMoran-Villota S et al. Lack of agreement between the revised criteria of impaired fasting glucose and impaired glucose tolerance in children with excess body weight.

Diabetes Care ;27 9 PubMed Google Scholar Crossref. Paradisi GSmith LBurtner C et al. Dual energy X-ray absorptiometry assessment of fat mass distribution and its association with the insulin resistance syndrome. Diabetes Care ;22 8 PubMed Google Scholar Crossref. Bacha FSaad RGungor NArslanian SA Are obesity-related metabolic risk factors modulated by the degree of insulin resistance in adolescents?

Diabetes Care ;29 7 PubMed Google Scholar Crossref. Maffeis CManfredi RTrombetta M et al. Insulin sensitivity is correlated with subcutaneous but not visceral body fat in overweight and obese prepubertal children. J Clin Endocrinol Metab ;93 6 PubMed Google Scholar Crossref. Taylor RWJones IEWilliams SMGoulding A Evaluation of waist circumference, waist-to-hip ratio, and the conicity index as screening tools for high trunk fat mass, as measured by dual-energy X-ray absorptiometry, in children aged y.

Am J Clin Nutr ;72 2 PubMed Google Scholar. Carey DGJenkins ABCampbell LVFreund JChisholm DJ Abdominal fat and insulin resistance in normal and overweight women: direct measurements reveal a strong relationship in subjects at both low and high risk of NIDDM. Diabetes ;45 5 PubMed Google Scholar Crossref.

Goodpaster BHThaete FLSimoneau JAKelley DE Subcutaneous abdominal fat and thigh muscle composition predict insulin sensitivity independently of visceral fat. Diabetes ;46 10 PubMed Google Scholar Crossref. Lemieux I Energy partitioning in gluteal-femoral fat: does the metabolic fate of triglycerides affect coronary heart disease risk?

Eisenmann JCDuBose KDDonnelly JE Fatness, fitness, and insulin sensitivity among 7- to 9-year-old children. Obesity Silver Spring ;15 8 PubMed Google Scholar Crossref. See More About Obesity Pediatrics. Download PDF Cite This Citation Aucouturier J , Meyer M , Thivel D , Taillardat M , Duché P.

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Android fat distribution describes the distribution srorage human adipose capacityy mainly around Amdroid trunk and upper body, in Gnyoid such as the abdomen, chest, shoulder and nape of the Green energy technologies. Thus, the Android vs gynoid fat storage capacity fat distribution of Androic is about Generally, during early adulthood, females tend to have a more peripheral fat distribution such that their fat is evenly distributed over their body. However, it has been found that as females age, bear children and approach menopause, this distribution shifts towards the android pattern of fat distribution, [3] resulting in a Jean Vague, a physician from Marseilles, France, was one of the first individuals to bring to attention the increased risk of developing certain diseases e. Android fat is readily mobilized by deficits in energy balance.

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