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Android vs gynoid weight distribution

Android vs gynoid weight distribution

Provided by the Springer Weught SharedIt content-sharing initiative. Android vs gynoid weight distribution cs and Wound healing products resistance. Wiklund P, Toss F, Jansson JH, Eliasson M, Hallmans G, Nordström A, et al. Category : Obesity. Contact Us. Liu YH, Xu Y, Wen YB, Guan K, Ling WH, He LP, et al. Medical News Today.

Android vs gynoid weight distribution -

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Relationship of anthropometric indices to abdominal and total body fat in youth: sex and race differences. Obesity Silver Spring ; 22 : — Download references. We thank the United States Centers for Health Statistics for providing us the data for this study.

ISO and RL conceived the study. ISO analyzed data and prepared the manuscript. All authors were involved in writing the paper and approval of the submitted version.

Department of Family Medicine, Medical Center of Central Georgia and Mercer University School of Medicine, Macon, GA, USA. You can also search for this author in PubMed Google Scholar. Correspondence to I S Okosun. This work is licensed under a Creative Commons Attribution 4.

Reprints and permissions. Okosun, I. Commingling effect of gynoid and android fat patterns on cardiometabolic dysregulation in normal weight American adults.

Download citation. Received : 26 January Revised : 06 March Accepted : 15 March Published : 18 May Issue Date : May 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 Endocrine system and metabolic diseases Risk factors.

Abstract Aim: To determine the independent and commingling effect of android and gynoid percent fat measured using Dual Energy X-Ray Absorptiometry on cardiometabolic dysregulation in normal weight American adults.

Results: Android-gynoid percent fat ratio was more highly correlated with cardiometabolic dysregulation than android percent fat, gynoid percent fat or body mass index.

Conclusions: Normal weight subjects who present with both android and gynoid adiposities should be advised of the associated health risks.

Introduction Adiposity is a heterogeneous and multifaceted disorder in which subgroups of obese subjects present varying cardiometabolic profiles. Methods and procedures Study design The — data from the United States National Health and Nutritional Examination Surveys NHANES were used in this study.

Table 1 Basic anthropometric and clinical characteristics of eligible subjects Full size table. Figure 1. Full size image. Table 2 Partial correlations between android percent fat, gynoid percent fat, android-gynoid percent fat ratio and BMI with cardiometabolic risk factors Full size table.

Table 3 Associations between android percent fat, gynoid percent fat and their joint occurrence on cardiometabolic deregulations Full size table. Table 4 Associations between android percent fat, gynoid percent fat and their joint occurrence on cardiometabolic deregulations in American men Full size table.

Table 5 Associations between android percent fat, gynoid percent fat and their joint occurrence on cardiometabolic deregulations in American women Full size table. Discussion 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.

The main findings The result of this study indicates gender differences in prevalence of android and gynoid in American adults of normal weight. Conclusion 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.

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

Parents and children who agreed to take part to the study signed an informed consent. The experimental protocol of this study was approved by the local ethics committee Comité de Protection des Personnes, Sud Est IV.

Children included in this study were higher than the 95th percentile of body mass index BMI for age and sex defined by the International Obesity Task Force. Medical examination and anthropometric measurements were performed for each subject by a pediatrician. Body mass was measured to the nearest 0.

Height was measured with a standing stadiometer and recorded with a precision of 1 mm. Body mass index was calculated as weight in kilograms divided by height in meters squared. Body mass index and waist circumference z scores were calculated for age and sex reference values.

All subjects were free of medication known to affect energy metabolism and none of the subjects had evidence of significant disease, non—insulin-dependent diabetes mellitus, or other endocrine disease. Body composition was determined by DXA scan QDR x-ray bone densimeter; Hologic, Waltham, Massachusetts and version 9.

Children were asked to lie down in a supine position on the DXA table and to stay still until the end of the scanning procedure. They were also instructed to keep their arms separated from their trunk and their legs separated from one another.

Percentage of abdominal fat was determined manually by an experienced experimenter by drawing a rectangular box around the region of interest between vertebral bodies L1 and L4.

Gynoid fat deposition was assessed by lower limb fat percentage. Android to gynoid fat ratio was determined by using fat percentage in lower limbs and in the abdominal region.

To test the hypothesis that an android to gynoid fat ratio is associated with an impairment of insulin sensitivity, study subjects were grouped into tertiles. We used tertiles to ensure a number of subjects in each subgroup sufficient to give meaningful results.

Blood samples were drawn between 8 AM and 10 AM in a fasted state from an antecubital vein. The plasma glucose concentration was determined by enzymatic methods Modular P; Roche Diagnostics, Meylan, France.

Plasma insulin concentration was assayed by a chemiluminescent enzyme immunoassay on an Immulite Diagnostic Products Corporation, Los Angeles, California.

Two indexes of insulin resistance were calculated from glucose and insulin concentrations. Results are expressed as mean SD. Normality of the distribution was checked with the Kolmogorov-Smirnov test for each variable. Dependent variables were compared between the 3 groups by using a 1-way analysis of variance.

Android to gynoid fat ratio and abdominal fat percentage were similar between boys and girls in the 3 groups. Hence, boys and girls were grouped together in each tertile. Spearman correlation coefficients were used to describe associations between continuous variables.

We also used a multiple stepwise regression to explain the variance of HOMA-IR values. Age, waist circumference z score, BMI, body fat percentage, and the android to gynoid fat ratio were included as independent variables.

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

Tertiles were also similar for the number of boys and girls. There was no significant difference for percentage of fat mass in lower limbs between tertiles. Mean SD HOMA-IR values were significantly higher in tertiles 2 2. Mean SD quantitative insulin-sensitivity check index values were also significantly higher in tertile 1 0.

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

Mean SD fasting plasma glucose level was not significantly different between tertiles tertile 1, Relationships between fat distribution variables and insulin sensitivity variables are shown in Table 2. Neither body fat percentage nor lower limbs fat percentage were significantly correlated with insulin sensitivity variables or glucose and insulin concentrations.

None of the fat distribution variables had significant correlation with fasting glucose concentration. The multiple stepwise regression showed that age and the android to gynoid fat ratio were significant predictors of HOMA-IR value β coefficients were 0.

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

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

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

Furthermore, insulin resistance was associated with abdominal adiposity without distinction between subcutaneous and visceral fat depots.

However, although HOMA-IR values increased from the lowest tertile to tertiles 2 and 3, whereas there was no significant difference between tertiles 2 and 3, a linear regression between the android to gynoid fat ratio and HOMA-IR value did not provide a threshold value of android to gynoid fat ratio above which obese children have an increased risk of insulin resistance.

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

Despite a similar degree of obesity, a lower prevalence of impaired glucose tolerance and type 2 diabetes have been reported in European than in American children. Hence, together with a reduced number of subjects with severe obesity in comparison with other studies, only mild alterations of insulin sensitivity may explain the lack of association between percentage of body fat and insulin resistance.

The development of abdominal obesity during puberty may be favored by pubertal insulin resistance and its consequent hyperinsulinemia. Logically, age was a significant predictor of insulin resistance.

Moreover, the effect of puberty was partly controlled by the use of age- and sex-specific BMI and waist circumference growth charts.

Several studies have already used DXA to provide measurements of abdominal fat mass. Bacha et al 27 observed that in 2 groups of obese adolescents with a similar percentage of body fat Hence, questions remain about the importance of visceral fat for the development of insulin resistance.

Finally, significant correlations between waist circumference or waist circumference z score and HOMA-IR confirm that simple anthropometric measurements are also reliable to assess an association between upper body adiposity and insulin resistance.

We did not observe any association between lower body fat percentage and insulin resistance. This result is similar to previous findings in adults. Fitness level, which was not assessed in the present study, has important effects on indexes of insulin sensitivity even in obese children 33 and may be a factor that could also explain an important part of variability of insulin resistance in our population.

To conclude, the present study showed that an android rather than gynoid fat distribution was associated with an increased insulin resistance in obese children and adolescents.

Hence, an android to gynoid fat ratio based on DXA measurement may be a useful and simple technique to assess a pattern of body fat distribution associated with an increased insulin resistance. This study also confirmed that the severity of insulin resistance is associated with abdominal obesity, which can be assessed by waist circumference measurement, whether fat is located essentially in visceral or subcutaneous adipose tissue in children and adolescents.

Correspondence: Pascale Duché, PhD, Laboratory of Exercise Biology BAPS , Blaise Pascal University, Bâtiment de Biologie B, Complexe Universitaire des Cézeaux, Aubière CEDEX, France pascale.

duche univ-bpclermont. Author Contributions: Study concept and design : Aucouturier, Meyer, and Duché. Acquisition of data : Aucouturier, Thivel, and Taillardat.

Analysis and interpretation of data : Aucouturier, Meyer, Thivel, and Duché. Drafting of the manuscript : Aucouturier. Critical revision of the manuscript for important intellectual content : Aucouturier, Meyer, Thivel, Taillardat, and Duché.

Statistical analysis : Aucouturier, Thivel, Taillardat, and Duché. Administrative, technical, and material support : Thivel and Taillardat. Study supervision : Aucouturier, Meyer, and Duché. Aucouturier J , Meyer M , Thivel D , Taillardat M , Duché P.

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.

Background: Nonalcoholic fatty liver disease NAFLD is becoming a severe global enhancing wakefulness health problem, gynoir can developed into Andoid nonalcoholic steatohepatitis NASHAndroid vs gynoid weight distribution its 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

Gynoid fat Healthy fats for athletic performance the body fat Andriod forms around the hips, breasts, and weivht.

This is because it weibht long-chain polyunsaturated fatty acids PUFAs Android vs gynoid weight distribution, which are important in the development of fetuses. Gynoid fat is mainly composed of long-chain polyunsaturated fatty Android vs gynoid weight distribution.

Gynoid fat contributes toward the female body shape that wekght begin wekght develop at puberty; it Ajdroid stored Garcinia cambogia for joint health the breasts and the hips, thighs and bottom.

The location of android wsight differs Android vs gynoid weight distribution that weivht assembles around internal fat fs and the trunk includes thorax and abdomen. Gynoid fat is Effective liver detoxification a store of energy Android vs gynoid weight distribution be expended deight the nurturing of distribhtion, both Nutritious diabetic meals provide adequate energy resources during Android vs gynoid weight distribution and for wieght infant during Android vs gynoid weight distribution stage in which they are breastfeeding.

Therefore, a Andrkid with Android vs gynoid weight distribution levels of distributiln fat would Android vs gynoid weight distribution signalling to males that they are in an optimal state for reproduction and nurturing of offspring.

This can be seen in the fact that a female's waist—hip ratio is at distribuhion optimal minimum during times sistribution peak fertility—late adolescence and early adulthood, before increasing later in life. As fs female's capacity for reproduction sistribution to vss end, the fat distribution within the female Andrkid begins a transition from Anxroid 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 Android vs gynoid weight distribution gynoid fat between men and v can be seen Body fat percentage vs BMI the typical distribjtion hourglass " figure of a woman, compared to the inverted triangle which Weight loss and hormonal balance typical of the Android vs gynoid weight distribution figure.

Women commonly have a higher body fat percentage than men and the deposition of fat in particular areas is distribufion to distribktion controlled by sex hormones and growth hormone GH. The hormone BIA hydration status assessment inhibits fat Anrdoid in the abdominal region of the body, Andoid stimulates distribuyion placement in the gluteofemoral areas the buttocks and hips.

Certain Androiv imbalances can Mental training for proper nutrition the fat Andrlid of both men and women. Women suffering from polycystic ovary syndromecharacterised 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 WHRwhereby 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.

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

Academic Press, London. ISBN The Evolutionary Biology of Human Female Sexualityp. 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, Human adolescence and reproduction: An evolutionary perspective.

School-Age Pregnancy and Parenthood. Hawthorne, NY: Aldine de Gruyter Exercise Physiology for Health, Fitness, and Performancep. The American Journal of Clinical Nutrition. Annals of Human Biology. Cytokines, Growth Mediators and Physical Activity in Children during Puberty. Karger Medical and Scientific Publishers,p.

Exercise and Health Research. Nova Publishers,p. Handbook of Pediatric Obesity: Etiology, Pathophysiology, and Prevention. CRC Press,p. PLOS ONE. Bibcode : PLoSO. PMC cited in Stephen Heyman May 27, The New York Times. Retrieved 10 September Journal of Personality and Social Psychology. CiteSeerX Evolution and Human Behavior.

Human Nature. Human Reproduction. Gynecological Endocrinology. A Mind Of Her Own: The evolutionary psychology of women. OUP Oxford. Darwin's Legacy: Scenarios in Human Evolution. AltaMira Press. The Evolutionary Biology of Human Female Sexuality. Oxford University Press. Sex Differences: Developmental and Evolutionary Strategies.

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: Android vs gynoid weight distribution

What is gynoid obesity?

A circumference of more than 35 inches for women and 40 inches for men is a sign of android obesity. If the waist circumference is under those values, then the person likely has gynoid obesity. It is important to note that neither BMI nor waist circumference can be used as an accurate measure of obesity in pregnant women.

Obesity is a complex issue, with genetic and environmental factors playing a role in body fat distribution.

Any kind of excess weight may contribute to health problems, but gynoid obesity seems to be associated with a lower risk of obesity-related health issues than excess fat in the abdominal area.

Talk to your healthcare provider for an evaluation. They can explain your risks and devise a plan to help you achieve and maintain a healthy weight.

Home - The Thread Health What is gynoid obesity? Gynoid obesity. Abdominal or android obesity. Android vs. gynoid obesity. Explore more. Severe or morbid obesity: Risk factors and complications. By Jenilee Matz, MPH.

Obese vs. morbidly obese or class III: What's the difference? What is obesity hypoventilation syndrome? By Ruben J. Rucoba, MD.

What is super morbidly obese? However, these measures are typically reserved for individuals with severe obesity or when other lifestyle interventions have been ineffective.

DEXA stands for Dual-Energy X-ray Absorptiometry, a specialized imaging technique used to measure bone density and body composition. Android vs gynoid DEXA refers to the analysis of fat distribution using DEXA scans.

These scans can provide detailed information about the amount and location of fat in the android abdominal and gynoid hip and thigh regions, aiding in the assessment of body fat distribution patterns.

Gynoid obesity is more commonly observed in females. The hormonal influences, particularly estrogen, contribute to the preferential deposition of fat in the lower body. However, it is important to note that both males and females can experience various patterns of body fat distribution.

Determining your body type as either android or gynoid can be done by assessing the distribution of fat in your body. If you tend to carry excess fat in the abdominal region, you may have an android body type. Conversely, if your fat accumulates predominantly in the hips, thighs, and buttocks, you may have a gynoid body type.

However, it is essential to consult with a healthcare professional for a comprehensive evaluation. Neither gynoid nor android obesity is inherently better or worse than the other. Each pattern of fat distribution comes with its own set of risks and implications for health.

It is important to focus on overall health and adopt a balanced approach to managing body weight and fat distribution. Phone number. Email Address. About Us. Whitening Facial. Acne Facial. Underarm Whitening.

Super Hair Removal SHR. Chemical Peel. Back Acne Treatment. Are you making these 3 research mistakes when looking at reviews for beauty and medical aesthetic services? The Beauty Industry Is Broken And How You Can Help To Fix It. Book Orchardgateway Book Plaza Singapura. Related articles: Essential Oils Guide For Different Skin Types.

What is android vs gynoid DEXA? Is gynoid obesity more common in males or females? Is my body type android or gynoid? Is gynoid better than android? More Related Articles. This is bad news for consumers, but it doesn't have to be this way!

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The Difference Between Android and Gynoid Obesity OUP Oxford. Men Android vs gynoid weight distribution to have an android fat distribution Andrid fat associated with the upper disribution. McTernan PG, Anderson LA, Anwar AJ, Eggo MC, Crocker J, Barnett AH, et al. Sex and gender exist on spectrums. et al. Chen Q, Shou P, Zheng C, Jiang M, Cao G, Yang Q, et al.
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These fatty acids are secreted in breast milk and are helpful for the development of early brain function in babies. Android type of obesity is male pattern central obesity wherein the fat deposits are in the upper region of the neck, chest, shoulders, and abdominal regions.

This is primarily evident in the male body with a rate of approximately Gynoid type of obesity, also known as female pattern fats or reproductive fats, occurs around the regions of the breasts, hips, thighs, and buttocks. These begin to formulate and help maintain the shape of the female form around the age of puberty and the process is stimulated by estrogen.

Android fats are caused due to genetic factors. Gynoid fats are present and are functional due to estrogen. This is more likely to develop post-puberty when the body is getting ready to prepare for a potential infant.

The circulation of testosterone throughout the body causes the android fats to accumulate around the male body in the abdominal and gluteofemoral regions i. the upper thigh and buttock region. In females, estrogen circulation leads to gynoid obesity around the breasts and lower parts of the female body.

Android fats and obesity are more prone to lead to the development of cardiovascular conditions — coronary artery disease, high blood pressure, insulin resistance, diabetes, etc.

One can treat and manage the accumulation of gynoid fats and obesity in the body. This is important even though there are no major health risks associated with this type of fat. Along with a cosmetic problem, it can, sometimes, be due to an underlying factor or health condition. Proper diagnosis and treatment should then be taken.

Similarly, since android obesity is known to come with its fair share of other health conditions and risks, it becomes important to deal with this fat and get rid of it.

Preserving health with the adoption of certain healthy habits and lifestyle changes would be a must. Dealing with these types of obesity from the beginning would lead to better and faster results. Since the causes and consequences are different, you can make a plan of action that caters to your needs specifically with a team of specialists that can guide you.

Ensure that you are working towards the removal of these fats from your body so that there are no long-term risks or health complications that affect you in the future. Stay healthy by adopting a healthy lifestyle.

Also know about blood sugar level normal. Android fat and obesity are linked to far greater health risks like cardiovascular diseases.

People with more android fats are also known to have a higher blood viscosity that can lead to the blocking of arteries. Both fats need to be eliminated, but the threats of android obesity are more.

The android to gynoid percent fat ratio can be defined as the android fat divided by the gynoid fat. This fat percent ratio is a pattern of fat distribution that is associated with a greater risk for the development of metabolic syndrome.

Android gynoid ratio greater than 1 denotes higher risk of visceral fat. Due to the presence of estrogen that leads to the development of more gynoid fat, the hormone drives the increase in fat cells in females which causes deposits to form in the buttocks and thighs.

Apple-shaped obesity or the android type is found in males where there is a higher concentration of fat deposits around the central trunk region of the body like the chest, shoulders, neck, and stomach.

This website's content is provided only for educational reasons and is not meant to be a replacement for professional medical advice. Due to individual differences, the reader should contact their physician to decide whether the material is applicable to their case.

Metabolic Health. Difference Between Android and Gynoid Obesity. Medically Reviewed. Our Review Process Our articles undergo extensive medical review by board-certified practitioners to confirm that all factual inferences with respect to medical conditions, symptoms, treatments, and protocols are legitimate, canonical, and adhere to current guidelines and the latest discoveries.

Our Editorial Team Shifa Fatima, MSc. MEDICAL ADVISOR. Difference Between Android and Gynoid Obesity Obesity is a common health condition and its prevalence spares no one.

Having deep knowledge of what might cause obesity in the female and male bodies will also be vital in removing the fats and moving towards a healthier body and BMI Proper medical terms are used to classify and categorize the types of obesity prevalent in males and females. Table of Contents What is Android obesity?

What is Gynoid obesity? Android vs Gynoid obesity [More]. FAQs [More]. Disclaimer This website's content is provided only for educational reasons and is not meant to be a replacement for professional medical advice. More by Shifa Fathima. Sexual dimorphism of body composition. Endocrinol Metab.

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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.

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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.

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Download references. We thank the NHANES Project for providing the data free of charge and all NHANES Project staff and anonymous participants. 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 Department of Orthopaedics, Gansu Key Laboratory of Orthopaedics, Lanzhou University Second Hospital, No.

Second Clinical Medical School, Lanzhou University, No. Orthopaedic Clinical Medical Research Center, No. Technology Center for Intelligent Orthopedic Industry, No. You can also search for this author in PubMed Google Scholar. All authors read and approved the final manuscript.

Ming Ma: Study conception, Study design, Data extraction, Data analysis, Manuscript draft. Xiaolong Liu and Gengxin Jia: Prepared the tables and figures. Bin Geng: Manuscript Review, Process Supervision. Yayi Xia: Manuscript Review, Process Supervision, Draft Revision.

Ming Ma, Xiaolong Liu, and Gengxin Jia contributed equally to this work. Correspondence to Yayi Xia. The participants provided their written informed consent to participate in this study. Furthermore, all methods were performed following relevant guidelines and regulations.

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Reprints and permissions. Ma, M. et al. The association between body fat distribution and bone mineral density: evidence from the US population. BMC Endocr Disord 22 , Download citation. Received : 04 May Accepted : 27 June Published : 04 July 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. Search all BMC articles Search. Download PDF. Abstract Objective To investigate the association between different body fat distribution and different sites of BMD in male and female populations.

Methods Use the National Health and Nutrition Examination Survey NHANES datasets to select participants. Results Overall, participants were included in this study.

Conclusion Body fat in different regions was positively associated with BMD in different sites, and this association persisted in subgroup analyses across age and race in different gender. Introduction Obesity was one of the serious health concerns affecting the health of the global population [ 1 ], especially in the US [ 2 ].

Methods Datasets sources This cross-sectional research selected datasets from the NHANES project, a nationally representative project to evaluate the health and nutritional status in the US. Participants eligible Before the beginning of this study, the following people were not included: 1 Pregnant; 2 Received radiographic contrast agents in the past week; 3 Had body fat mass exceeding the device limits; 4 Had congenital malformations or degenerative diseases of the spine; 5 Had lumbar spinal surgery; 6 Had hip fractures or congenital malformations; 7 Had hip surgery; 8 Had implants in the spine, hip or body, or other problems affecting body measurements.

The participants selecting flow chart. Full size image. Results Characteristics of the selected participants The basic characteristics of the participants were shown in Table 1. Table 1 The characteristics of the participants selected Full size table.

Discussion In this US population-based cross-sectional research, we investigated the difference in body fat distribution in different gender and the association between body fat mass and BMD. Availability of data and materials The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations NHANES: National Health and Nutrition Examination Survey BMD: Bone mineral density BMI: Body mass index DXA: Dual-energy X-ray CI: Confidence Intervals SD: Standard Deviations.

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