Category: Family

Android vs gynoid hormonal influences

Android vs gynoid hormonal influences

Use the National Health and Nutrition Examination Survey Android vs gynoid hormonal influences datasets to select participants. Gyboid access Athletic performance beverage newly published articles. Plourde G The role of Influencew methods hprmonal assessing body composition and related metabolic parameters. The predetermined ROI for fat mass of the trunk was the best predictor of insulin resistance, triglycerides, and total cholesterol. In line with these results, Ahtiainen et al. Andrologia 49 5 :e Article Google Scholar Asarian L, Geary N Modulation of appetite by gonadal steroid hormones.

Android vs gynoid hormonal influences -

About the national health and nutrition examination survey. Shepherd JA, Ng BK, Sommer MJ, Heymsfield SB. Body composition by DXA. Bone —5. Jensen MD, Ryan DH, Apovian CM, Ard JD, Comuzzie AG, Donato KA, et al. Circulation 25 :S— Kivimäki M, Strandberg T, Pentti J, Nyberg ST, Frank P, Jokela M, et al.

Body-mass index and risk of obesity-related complex multimorbidity: An observational multicohort study. Lancet Diabetes Endocrinol 10 4 — Pedersen LR, Frestad D, Michelsen MM, Mygind ND, Rasmusen H, Suhrs HE, et al.

Risk factors for myocardial infarction in women and men: A review of the current literature. Curr Pharm Des 22 25 — de Mutsert R, Gast K, Widya R, de Koning E, Jazet I, Lamb H, et al.

Associations of abdominal subcutaneous and visceral fat with insulin resistance and secretion differ between men and women: The Netherlands epidemiology of obesity study. Metab Syndr Relat Disord 16 1 — Schosserer M, Grillari J, Wolfrum C, Scheideler M. Age-induced changes in white, brite, and brown adipose depots: A mini-review.

Gerontology 64 3 — Preis SR, Massaro JM, Robins SJ, Hoffmann U, Vasan RS, Irlbeck T, et al. Abdominal subcutaneous and visceral adipose tissue and insulin resistance in the framingham heart study. Obes Silver Spring 18 11 —8.

CrossRef Full Text Google Scholar. Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: A cross-sectional study. Lancet — Saltiel AR, Olefsky JM. Inflammatory mechanisms linking obesity and metabolic disease.

J Clin Invest 1 :1—4. Rosengren A. Obesity and cardiovascular health: The size of the problem. Eur Heart J 42 34 —6. Peters U, Dixon AE, Forno E. Obesity and asthma. J Allergy Clin Immunol 4 — Alpert MA, Omran J, Bostick BP. Effects of obesity on cardiovascular hemodynamics, cardiac morphology, and ventricular function.

Curr Obes Rep 5 4 — Prausmüller S, Heitzinger G, Pavo N, Spinka G, Goliasch G, Arfsten H, et al. Malnutrition outweighs the effect of the obesity paradox. J Cachexia Sarcopenia Muscle 13 3 — Portha B, Grandjean V, Movassat J.

Mother or father: Who is in the front line? Nutrients 11 2 McCormick N, Rai SK, Lu N, Yokose C, Curhan GC, Choi HK. Estimation of primary prevention of gout in men through modification of obesity and other key lifestyle factors.

JAMA Netw Open 3 11 :e Reyes-Farias M, Fos-Domenech J, Serra D, Herrero L, Sánchez-Infantes D. White adipose tissue dysfunction in obesity and aging. Biochem Pharmacol Liu W, Li D, Cao H, Li H, Wang Y. Expansion and inflammation of white adipose tissue - focusing on adipocyte progenitors.

Biol Chem 2 — Aedo S, Blümel JE, Carrillo-Larco RM, Vallejo MS, Aedo G, Gómez GG, et al. Association between high levels of gynoid fat and the increase of bone mineral density in women. Climacteric 23 2 — Qian SW, Liu Y, Wang J, Nie JC, Wu MY, Tang Y, et al. EBioMedicine — Tran QK. Reciprocality between estrogen biology and calcium signaling in the cardiovascular system.

Front Endocrinol Lausanne Knowlton AA, Lee AR. Estrogen and the cardiovascular system. Pharmacol Ther 1 — Oike M, Yokokawa H, Fukuda H, Haniu T, Oka F, Hisaoka T, et al. Association between abdominal fat distribution and atherosclerotic changes in the carotid artery.

Obes Res Clin Pract 8 5 :e— Hales CM, Fryar CD, Carroll MD, Freedman DS, Ogden CL. Trends in obesity and severe obesity prevalence in US youth and adults by sex and age, to JAMA 16 —5.

Citation: Liu C-A, Liu T, Ruan G-T, Ge Y-Z, Song M-M, Xie H-L, Lin S-Q, Deng L, Zhang H-Y, Zhang Q and Shi H-P The relationship between fat distribution in central region and comorbidities in obese people: Based on NHANES — Received: 03 December ; Accepted: 27 January ; Published: 08 February Copyright © Liu, Liu, Ruan, Ge, Song, Xie, Lin, Deng, Zhang, Zhang and Shi.

This is an open-access article distributed under the terms of the Creative Commons Attribution License CC BY. The use, distribution or reproduction in other forums is permitted, provided the original author s and the copyright owner s are credited and that the original publication in this journal is cited, in accordance with accepted academic practice.

No use, distribution or reproduction is permitted which does not comply with these terms. Disclaimer: 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.

Top bar navigation. About us About us. Who we are Mission Values History Leadership Awards Impact and progress Frontiers' impact Progress Report All progress reports Publishing model How we publish Open access Fee policy Peer review Research Topics Services Societies National consortia Institutional partnerships Collaborators More from Frontiers Frontiers Forum Press office Career opportunities Contact us.

Sections Sections. About journal About journal. Article types Author guidelines Editor guidelines Publishing fees Submission checklist Contact editorial office. ORIGINAL RESEARCH article Front. This article is part of the Research Topic The Impact of Adipose Tissue Dysfunction on Cardiovascular and Renal Disease, Volume II View all 12 articles.

The relationship between fat distribution in central region and comorbidities in obese people: Based on NHANES — Introduction Obesity is becoming more widespread all over the world, according to Global Burden of Disease Group research 1.

Methods Participants and study design The population of this study was sourced from the NHANES database—a large cross-sectional survey conducted by the National Center for Health Statistics—to investigate the health and nutritional status of the population in the United States 14 — Exposure variables and definitions In this study, all participants were examined by dual-energy X-ray absorptiometry DXA to determine the fat mass, which is the most widely accepted method of measuring body composition Outcome Our primary study outcome was the comorbidity risk among obese participants.

Statistical analyses Considered the complex survey design of NHANES, all statistical analysis was based on sample weight, stratification, and clustering. Result Characteristics of study participants The mean age SD of these obese participants was ee PubMed Abstract CrossRef Full Text Google Scholar.

Keywords: obesity, fat distribution, comorbidity, public health, NHANES Citation: Liu C-A, Liu T, Ruan G-T, Ge Y-Z, Song M-M, Xie H-L, Lin S-Q, Deng L, Zhang H-Y, Zhang Q and Shi H-P The relationship between fat distribution in central region and comorbidities in obese people: Based on NHANES — Abdominal and gynoid adipose distribution and incident myocardial infarction in women and men.

Int J Obes Lond. Folsom AR, Kushi LH, Anderson KE, Mink PJ, Olson JE, Hong CP, et al. Associations of general and abdominal obesity with multiple health outcomes in older women: the Iowa Women's health study. Arch Intern Med.

Ma M, Feng Z, Liu X, Jia G, Geng B, Xia Y. The saturation effect of body mass index on bone mineral density for people over 50 years old: a cross-sectional study of the US population. Front Nutr. Padwal R, Leslie WD, Lix LM, Majumdar SR.

Relationship among body fat percentage, body mass index, and all-cause mortality: a cohort study. Ann Intern Med. Article PubMed Google Scholar. Fan J, Jiang Y, Qiang J, Han B, Zhang Q.

Associations of fat mass and fat distribution with bone mineral density in non-obese postmenopausal Chinese women over 60 years old. Front Endocrinol Lausanne. Article Google Scholar.

Fu X, Ma X, Lu H, He W, Wang Z, Zhu S. Associations of fat mass and fat distribution with bone mineral density in pre- and postmenopausal Chinese women. Osteoporos Int. Lv S, Zhang A, Di W, Sheng Y, Cheng P, Qi H, et al. Assessment of fat distribution and bone quality with trabecular bone score TBS in healthy Chinese men.

Sci Rep. Article CAS PubMed PubMed Central Google Scholar. Yu Z, Zhu Z, Tang T, Dai K, Qiu S. Effect of body fat stores on total and regional bone mineral density in perimenopausal Chinese women.

J Bone Miner Metab. Chain A, Crivelli M, Faerstein E, Bezerra FF. Association between fat mass and bone mineral density among Brazilian women differs by menopausal status: the Pró-Saúde study. Douchi T, Yamamoto S, Oki T, Maruta K, Kuwahata R, Nagata Y.

Relationship between body fat distribution and bone mineral density in premenopausal Japanese women. Obstet Gynecol. CAS PubMed Google Scholar. Yang S, Center JR, Eisman JA, Nguyen TV. Association between fat mass, lean mass, and bone loss: the Dubbo osteoporosis epidemiology study.

Vogel JA, Friedl KE. Body fat assessment in women. Special considerations. Sports Medicine Auckland, NZ. Wells JCK. Sexual dimorphism of body composition. Endocrinol Metab. Google Scholar. Zillikens MC, Yazdanpanah M, Pardo LM, Rivadeneira F, Aulchenko YS, Oostra BA, et al.

Sex-specific genetic effects influence variation in body composition. Lovejoy JC, Sainsbury A. Sex differences in obesity and the regulation of energy homeostasis. Obes Rev. Lu Y, Mathur AK, Blunt BA, Gluer CC, Will AS, Fuerst TP, et al.

Dual X-ray absorptiometry quality control: comparison of visual examination and process-control charts. J Bone Miner Res. Shepherd JA, Fan B, Lu Y, Wu XP, Wacker WK, Ergun DL, et al. A multinational study to develop universal standardization of whole-body bone density and composition using GE Healthcare lunar and Hologic DXA systems.

Min KB, Min JY. Android and gynoid fat percentages and serum lipid levels in United States adults. Clin Endocrinol Oxf. Dos Santos MR, da Fonseca GWP, Sherveninas LP, de Souza FR, Battaglia Filho AC, Novaes CE, et al. Android to gynoid fat ratio and its association with functional capacity in male patients with heart failure.

Heart Fail. Camilleri G, Kiani AK, Herbst KL, Kaftalli J, Bernini A, Dhuli K, et al. Genetics of fat deposition. Eur Rev Med Pharmacol Sci. Rask-Andersen M, Karlsson T, Ek WE, Johansson Å. Genome-wide association study of body fat distribution identifies adiposity loci and sex-specific genetic effects.

Nat Commun. Li X, L. Gene-environment interactions on body fat distribution. Int J Mol Sci. Min Y, Ma X, Sankaran K, Ru Y, Chen L, Baiocchi M, et al. Sex-specific association between gut microbiome and fat distribution.

Article PubMed PubMed Central CAS Google Scholar. Marwaha RK, Garg MK, Tandon N, Mehan N, Sastry A, Bhadra K. Relationship of body fat and its distribution with bone mineral density in Indian population.

J Clin Densitom. Gonnelli S, Caffarelli C, Tanzilli L, Alessi C, Tomai Pitinca MD, Rossi S, et al. The associations of body composition and fat distribution with bone mineral density in elderly Italian men and women.

Zillikens MC, Uitterlinden AG, van Leeuwen JP, Berends AL, Henneman P, van Dijk KW, et al. The role of body mass index, insulin, and adiponectin in the relation between fat distribution and bone mineral density.

Calcif Tissue Int. Aedo S, Blümel JE, Carrillo-Larco RM, Vallejo MS, Aedo G, Gómez GG, et al. Association between high levels of gynoid fat and the increase of bone mineral density in women. Zhang W, Ma X, Xue P, Gao Y, Wu X, Zhao J, et al.

Associations between fat distribution and volumetric bone mineral density in Chinese adults. Liu YH, Xu Y, Wen YB, Guan K, Ling WH, He LP, et al. Association of weight-adjusted body fat and fat distribution with bone mineral density in middle-aged chinese adults: a cross-sectional study.

PLoS One. Kazakia GJ, Tjong W, Nirody JA, Burghardt AJ, Carballido-Gamio J, Patsch JM, et al. The influence of disuse on bone microstructure and mechanics assessed by HR-pQCT. Lohman T, Going S, Pamenter R, Hall M, Boyden T, Houtkooper L, et al. Effects of resistance training on regional and total bone mineral density in premenopausal women: a randomized prospective study.

Chen X, Zhang J, Zhou Z. Changes in bone mineral density after weight loss due to metabolic surgery or lifestyle intervention in obese patients. Obes Surg. Coulombe JC, Senwar B, Ferguson VL.

Spaceflight-induced bone tissue changes that affect bone quality and increase fracture risk. Curr Osteoporos Rep. Kameda T, Mano H, Yuasa T, Mori Y, Miyazawa K, Shiokawa M, et al. Estrogen inhibits bone resorption by directly inducing apoptosis of the bone-resorbing osteoclasts.

J Exp Med. McTernan PG, Anderson LA, Anwar AJ, Eggo MC, Crocker J, Barnett AH, et al. Glucocorticoid regulation of p aromatase activity in human adipose tissue: gender and site differences.

J Clin Endocrinol Metab. Cornish J, Callon KE, Bava U, Lin C, Naot D, Hill BL, et al. Leptin directly regulates bone cell function in vitro and reduces bone fragility in vivo. J Endocrinol. Hickman J, McElduff A. Insulin promotes growth of the cultured rat osteosarcoma cell line UMR an osteoblast-like cell.

Chen Q, Shou P, Zheng C, Jiang M, Cao G, Yang Q, et al. Fate decision of mesenchymal stem cells: adipocytes or osteoblasts? Cell Death Differ. Migliaccio S, Greco EA, Fornari R, Donini LM, Lenzi A. Is obesity in women protective against osteoporosis?

Diabetes Metab Syndr Obes. Neeland IJ, Turer AT, Ayers CR, Berry JD, Rohatgi A, Das SR, et al. Body fat distribution and incident cardiovascular disease in obese adults.

J Am Coll Cardiol. Britton KA, Massaro JM, Murabito JM, Kreger BE, Hoffmann U, Fox CS. Body fat distribution, incident cardiovascular disease, cancer, and all-cause mortality. Schosserer M, Grillari J, Wolfrum C, Scheideler M.

Age-induced changes in white, Brite, and Brown adipose depots: a Mini-review. Sadie-Van Gijsen H, Crowther NJ, Hough FS, Ferris WF. 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.

Background: Nonalcoholic horomnal liver disease NAFLD is becoming Android vs gynoid hormonal influences normonal global public health problem, and can developed Fueling up in-game fibrotic nonalcoholic steatohepatitis NASHbut Vss risk factors have not been fully identified. Participants aged 20 and older without viral hepatitis or significant alcohol consumption were included. Dual-energy X-ray absorptiometry was used to assess body composition. NAFLD was diagnosed using the United States fatty liver index US FLI. Results: The prevalence of NAFLD was Logistic regression analysis showed that android percent fat was positively correlated to NAFLD OR: 1.

Video

Body Types - Apple vs Pear Shape, Android and Gynoid Obesity

Author: Fesho

5 thoughts on “Android vs gynoid hormonal influences

  1. Ich denke, dass Sie den Fehler zulassen. Es ich kann beweisen. Schreiben Sie mir in PM, wir werden umgehen.

Leave a comment

Yours email will be published. Important fields a marked *

Design by ThemesDNA.com