A All people, B male subgroup, and C female subgroup. A complex sample logistic regression was used to investigate the relationship between fat depots and the prevalence of NAFLD Table 3.

In the crude model, android percent fat was positively related to NAFLD OR: 1. We further conducted multivariable logistic regression analyses, additionally adjusting for BMI, hypertension, diabetes, ALT, AST, gamma-glutamyl-transpeptidase, total cholesterol, triglycerides, HDL, LDL, and uric acid, in which there were similar OR values resembling the two previous models.

Fat distribution and NAFLD categorized by gender are displayed in Table 5. More body fat in both the android area and gynoid areas was found in women than in men.

Overall, the NAFLD group showed a similar pattern, except for the first and second quartiles, in which the proportion of women did not decline correspondingly as in the other two groups Figure 2.

Figure 2. 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.

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Atherosclerosis ; : 23— 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 ; : — Peppa M, Koliaki C, Hadjidakis DI, Garoflos E, Papaefstathiou A, Katsilambros N et al. Regional fat distribution and cardiometabolic risk in healthy postmenopausal women.

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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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Google Scholar Barreira TV, Broyles ST, Gupta AK, Katzmarzyk PT. Article Google Scholar Download references. Treating gynoid obesity is important to reduce the risk of developing health problems that relate to excess body fat. While there is no single treatment for gynoid obesity that suits everybody, the following strategies can be effective:.

It is important to note that people should achieve weight loss through healthy and sustainable methods. Crash dieting or extreme weight loss methods can be harmful. A safe and effective rate of weight loss is typically around 1—2 pounds per week, which people can achieve through a combination of a healthy diet and regular exercise.

Consulting with a healthcare professional, such as a registered dietitian or a personal trainer, can also help a person develop a safe and effective individualized weight loss plan.

Gynoid obesity and android obesity are two different types of obesity featuring different body fat distribution patterns. Android obesity features an excess accumulation of fat in the upper part of the body, particularly in the abdomen and chest.

A article notes that females tend to be more prone to gynoid obesity due to the presence of estrogen, which promotes fat deposition in the lower body.

Males, on the other hand, tend to be more prone to android obesity due to the presence of testosterone , which promotes fat deposition in the upper body. However, doctors generally consider android obesity to be more harmful than gynoid obesity because excess abdominal fat can be more metabolically active and release hormones that increase inflammation and insulin resistance.

This may contribute to the development of health problems such as type 2 diabetes, cardiovascular disease, and certain types of cancer.

Apple-shaped obesity refers specifically to android obesity , which involves an excess accumulation of fat in the upper part of the body, particularly in the abdomen and chest.

The android-gynoid ratio is the ratio of the circumference of the waist to the circumference of the hips. Doctors use it as a measure of body fat distribution and to determine whether an individual has an apple-shaped body or a pear-shaped body.

Android obesity involves the accumulation of fat in the upper part of the body, primarily in the abdomen and chest. Both types of obesity can increase the risk of medical conditions, such as cardiovascular disease. A new study that used data from countries concludes that consuming more rice could reduce global obesity.

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.