Obesity, body fat distribution and sex hormones in men.

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Body first I attributed it to being lucky. Somehow I just happened to find these boyd sex gods. Once I became comfortable in my fat body, I was able to stop getting in my own way. I love my fat body now. The security I have in me radiates out. Plenty of men still heavily subscribe to fatphobic rhetoric, and plenty of those men troll me on dating apps. But at the end of the day their fatphobia is their problem, not mine.

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Tinder Plus said 5, people swiped right on me. With every sex on the boyd, what do I actually want? I attract the hot guy body I am the hot girl—a fact that is neither hindered nor amplified by the size and shape of my body.

Despite what I believed, the rules never existed. No one fat who is attracted to you except you. Every relationship, every partner, every hookup is a reflection of you. And when Fat decided that I was hot, the men of New York agreed. Anastasia Garcia is a photographer and body-positive activist in Body York Body. She is currently working on her first novel detailing her experiences with dating as a fat woman. Follow her on Instagram anastasiagphoto.


Adipose Tissue Biology pp Cite as. Although obesity is an important determinant of metabolic disease, specific accumulation of visceral fat is strongly and independently associated with important metabolic alterations such as insulin resistance, hypertension and dyslipidemia. Excess accumulation of visceral fat is a strong predictor of cardiometabolic risk in both sexes, but a marked dimorphism and large interindividual variations are observed in body fat distribution.

Women are more likely to store lipids in lower-body fat compartments through adipocyte hyperplasia, while visceral adipose tissue depots of body are more prone to manage incoming lipids through adipocyte hypertrophy. Adipocyte hypertrophy appears as a critical determinant of sex-related and depot-related differences in lipid metabolism and may contribute to the chronic, low-grade inflammation observed in abdominally obese individuals.

Regarding the hormonal etiology of abdominal obesity, active androgens are known to inhibit adipogenesis and lipogenesis in adipose tissue.

Estrogens have important central effects on energy balance, but may also directly modulate central fat accumulation through direct effects on adipose tissue metabolism.

Interventions targeting visceral fat accumulation such as moderate weight loss are known to exert beneficial effects on cardiometabolic disease risk. Skip to main content. Advertisement Hide. Sex Differences in Body Fat Distribution. Chapter First Online: 04 April fat This is a preview of subscription content, log in to check access.

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University of British Columbia Vancouver Canada 5. Personalised recommendations.

We used a representative sample of the U. Our findings suggest that the modified RFM equation for adults, which we named the RFM pediatric RFMp , may be useful as a simple tool to estimate whole-body fat percentage and as an alternative to BMI-for-age percentiles to assess body adiposity among girls and boys who are between 8 and 14 years of age. The RFM equation for adults may be useful as a tool to estimate whole-body fat percentage and as alternative to BMI-for-age percentiles to assess body adiposity among adolescents 15 to 19 years of age.

The simple RFMp linear equation was more accurate than the more complex BMI quadratic equation to estimate whole-body fat percentage among girls TMI was developed as a powerful alternative tool to BMI to estimate body fat percentage and to better classify girls and boys with overweight compared with BMI-for-age percentiles Among children and adolescents 8 to 14 years of age, RFMp was more accurate than TMI to estimate whole-body fat percentage among boys but not girls.

TMI are quadratic equations based on body weight and height. Thus, data from our study conducted in more than 10, children and adolescents and those from our previous study conducted in nearly 16, adult individuals 17 strongly support the benefit of using height and waist circumference the only anthropometrics required for RFMp and RFM calculations over height and body weight for the purpose of assessing body fatness in children, adolescents and adult individuals.

It should be noted that RFMp differs from the original RFM equation for adult individuals in their coefficients only Our findings are consistent with a recent study showing waist-to-height Z scores were superior to BMI Z-scores to predict body fat percentage in children and adolescents However, in none of these previous studies misclassification error rate of overweight or obesity status was specifically evaluated.

It is known that WHtR is a better predictor of body fat in adult males than adult females 32 , 37 , and better in boys than girls 38 , which are also consistent with our findings in children and adolescents and those from our previous study in adult individuals However, its use as an estimator of body fat percentage has been less studied in adults 37 , 42 and children In fact, most of the studies in children have rather been focused on body fat prediction 18 , 19 , 20 , 21 , 23 in relatively small populations.

In contrast, our study was conducted in a representative sample of the U. In the population studied, our findings showed better diagnostic accuracy of overweight or obesity with RFMp than with BMI-for-age percentiles among both girls and boys 8 to 14 years of age.

Among adolescents 15 to 19 years of age, RFM showed better diagnostic accuracy of overweight or obesity than BMI-for-age percentiles among boys but not girls. In addition, total misclassification error rate of overweight or obesity was significantly lower for RFMp than for BMI-for-age percentiles among African-American boys and girls. TMI, in contrast, showed no improvement over BMI-for-age percentiles in the rates of total misclassification error of overweight or obesity.

We also found no improvement in misclassification error of overweight or obesity by TMI among non-Hispanic European-American boys and girls, which confirms the findings from a previous study in this ethnic group Among adolescents 15 to 19 years of age, misclassification error rate of overweight or obesity was similar for RFM and BMI-for-age among girls and boys Fig.

More importantly, among boys 8 to 14 years of age, RFMp represented a significant improvement in misclassification error rate of overweight or obesity 1.

Among African-American girls 8 to 14 years of age, RFMp also represented a significant improvement in overweight or obesity misclassification 3. Among adolescents 15 to 19 years of age, the total misclassification error of overweight or obesity was lower for RFM than for BMI-for-age percentiles among African-American boys 1. Since our findings are derived from a representative sample of the U. Excess body fat in the early years of life predisposes to obesity in the adolescence Thus, the importance of an adequate assessment of body fatness in children is unquestionable.

An undesirable consequence of stigmatizing children with obesity is that it may lead to negative changes in their behaviors such as binge eating, social isolation or avoidance of medical care Our study has limitations: 1 We used DXA as the reference method for body fat percentage. DXA underestimates and overestimates body fat percentage among children and adolescents with lower and higher body fat percentage, respectively, compared against the most accurate non-invasive method available, the four-compartment method Thus, the generalizability of our findings should be limited to the ethnic groups studied and in the age between 8 and 19 years.

Although the intra-observer variability between anthropometric measurements is very high, inter-observer variability could be a problem Measurement error on waist circumference and height can be effectively reduced with proper training of healthcare providers 46 , Age and sexual maturation are associated with changes in body composition in children and adolescents Thus, future studies are required to evaluate the accuracy performance of RFMp and RFM to estimate whole-body fat percentage across Tanner stages sexual maturity rates.

In conclusion, RFMp for children and adolescents 8 to 14 years of age and RFM for adolescents 15 to 19 years of age were useful simple linear equations to estimate whole-body fat percentage and diagnose body fat-defined overweight or obesity. Observations with missing data on body weight, height or waist circumference were excluded from the original dataset. The flow diagram of participant selection is shown in Fig. NHANES uses a nationally representative sample selected using a multistage, probability sampling design Anthropometric measurements were performed using standard procedures BMI was calculated as the body weight in kilograms divided by the square of the height in meters.

Waist circumference was measured at the level of the uppermost lateral border of the right ilium during standing position. Whole-body fat percentage was calculated as the ratio between DXA-measured whole-body fat mass g and DXA-measured whole-body total mass g , multiplied by Multiple imputation was applied to replace missing DXA data.

Five multiply imputed data were generated for each participant who had missing values The coefficients for RFM equations were rounded for practical purposes. Major differences in body composition were observed during the transition from childhood to adolescence and a relative stabilization of body fat percentage was noted in boys at the age of Thus, we tested equations for different age categories.

We performed sensitivity analysis to determine whether age categorization was ideal to achieve the highest performance of RFM equations. Linear regression model was used to assess the prediction of whole-body fat percentage. Bias was calculated as the median difference between estimated and measured whole-body fat percentage. Precision was calculated as the interquartile range of the difference between estimated and measured body fat percentage 52 , 53 , These are accepted approaches used in clinical research to evaluate accuracy and precision 52 , 53 , Thus, comparison of misclassification error among indices was performed using their corresponding 85 th and 95 th percentiles calculated from the NHANES Age in months at the time of physical examination was used for misclassification analysis to minimize the error in calculations.

We compared misclassification error rates of overweight, obesity and overweight or obesity for RFMp percentiles and RFM percentiles vs. Diagnostic accuracy of overweight or obesity was estimated using the receiver-operating-characteristic curve analysis, expressed as the C-statistic. Log-transformation was applied when appropriate.

Listwise deletion was used to handle missing data. Estimates of concordance correlation coefficients were adjusted for probability weights only. Variance estimates for descriptive variables were obtained using Taylor series linearization.

Bootstrapping with 1, replicates was used to obtain confidence intervals for adjusted R 2 and the RMSE Presence of interactions were determined using the Wald test. We set a P value less than 0. Ogden, C. JAMA , — Kuczmarski, R. Vital Health Stat 11 , 1— Krebs, N. Assessment of child and adolescent overweight and obesity. Pediatrics Suppl 4 , S— Dulloo, A. Body composition phenotypes in pathways to obesity and the metabolic syndrome.

Freedman, D. Pediatrics , 22—27 Neovius, M. Sensitivity and specificity of classification systems for fatness in adolescents. Am J Clin Nutr 80 , — Sardinha, L. Receiver operating characteristic analysis of body mass index, triceps skinfold thickness, and arm girth for obesity screening in children and adolescents. Am J Clin Nutr 70 , — Cole, T. Ann Hum Biol 13 , — Heitmann, B. Mortality associated with body fat, fat-free mass and body mass index among year-old swedish men-a year follow-up.

The study of men born in Ortega, F. Mayo Clin Proc 91 , — Padwal, R. Ann Intern Med , — Must, A. Occurrence and timing of childhood overweight and mortality: findings from the Third Harvard Growth Study.

J Pediatr , — Franks, P. Childhood obesity, other cardiovascular risk factors, and premature death. N Engl J Med , — Reilly, J. Long-term impact of overweight and obesity in childhood and adolescence on morbidity and premature mortality in adulthood: systematic review.

Int J Obes Lond 35 , — Williams, D. Body fatness and risk for elevated blood pressure, total cholesterol, and serum lipoprotein ratios in children and adolescents. Am J Public Health 82 , — Peterson, C. JAMA Pediatr , — Woolcott, O.

Sci Rep 8 , Gutierrez Hervas, A. Estimation of body fat among 2-toyear-old Spanish children by different skinfolds equations and waist-to-height ratio. Nutr Hosp 34 , — Sijtsma, A. Waist-to-height ratio, waist circumference and BMI as indicators of percentage fat mass and cardiometabolic risk factors in children aged 3—7 years.

Clin Nutr 33 , — Corvalan, C. Obesity indicators and cardiometabolic status in 4-y-old children. Am J Clin Nutr 91 , — Santos, S. Obesity Silver Spring 26 , — Hubert, H. Comparison of the diagnostic quality of body mass index, waist circumference and waist-to-height ratio in screening skinfold-determined obesity among children. J Sci Med Sport 12 , — Frayon, S. Potential for waist-to-height ratio to detect overfat adolescents from a Pacific Island, even those within the normal BMI range.

Obes Res Clin Pract 12 , — Sarria, A. Body mass index, triceps skinfold and waist circumference in screening for adiposity in male children and adolescents. Acta Paediatr 90 , — Tuan, N. Adiposity assessments: agreement between dual-energy X-ray absorptiometry and anthropometric measures in U.

Obesity Silver Spring 22 , — Marrodan, M. Predicting percentage body fat through waist-to-height ratio WtHR in Spanish schoolchildren. Public Health Nutr 17 , — Jackson, A. The effect of sex, age and race on estimating percentage body fat from body mass index: The Heritage Family Study.

Newton, R. Comparison of body composition methods in obese African-American women. Obesity Silver Spring 14 , — Stevens, J. Prediction of percent body fat measurements in Americans 8 years and older. Int J Obes Lond 40 , — Gomez-Ambrosi, J. Clinical usefulness of a new equation for estimating body fat. Diabetes Care 35 , — Lean, M. Predicting body composition by densitometry from simple anthropometric measurements. Am J Clin Nutr 63 , 4—14 Cui, Z. Med Sci Sports Exerc 46 , — Friedl, K.

Evaluation of anthropometric equations to assess body-composition changes in young women. Am J Clin Nutr 73 , — Withers, R. The relative body fat and anthropometric prediction of body density of South Australian females aged 17—35 years. Gallagher, D. Healthy percentage body fat ranges: an approach for developing guidelines based on body mass index. Am J Clin Nutr 72 , — Lee, D. Br J Nutr , — Swainson, M. Prediction of whole-body fat percentage and visceral adipose tissue mass from five anthropometric variables.

Such investigation is an essential prerequisite for accurate assessment of associated metabolic implication and health risks. Sexual dimorphism of total body composition has been described in prepubertal children, with greater fat free mass and less fat mass in boys, compared with girls, after controlling for ethnicity, age, height, and weight 18 , 33 — Sexual dimorphism of body fat distribution had previously been reported to emerge during puberty 13 — 15 , 17 , implying that factors regulating sex-specific total body composition are present in prepubertal children but that those determining regional body composition appear during puberty.

Mast et al. Besides numerous problems associated with the use of ratios from a statistical analysis perspective 30 , waist to hip ratio has been challenged as a valid assessment of fat distribution in children 17 because it reflects bone-related hip circumference as much as fat.

In our study of anthropometric and DXA measures of fat in prepubertal children, using analysis of covariance rather than ratios, sex differences in fat distribution were evident. Additional studies are needed to understand the metabolic and health risk implications of the observed differences.

Gonadal steroids are the major mediators of sexual dimorphism of body composition in adults, including body fat patterning 39 , 40 , a role that is further substantiated by the identification of gonadal steroid receptors in adipose tissue 41 , The demonstration by Klein et al. Recent reports have shown that gonadotropins and gonadal steroids gradually increase from 5 yr of age in prepubertal children, implying that their effects may be more evident in older than younger prepubertal children 44 — Other hormones with putative roles in body fat distribution include leptin and GH, which have distinct but interrelated diurnal patterns, but are also influenced by gonadal steroids The differences in fat distribution observed in this cross-sectional study of children with an age span of 5—12 yr did not change with age when other covariates were included in the analysis.

This leads us to propose that fat distribution may not be mediated by gonadal steroids in prepubertal children but rather by other factors, including possible nonhormonal sex-specific mechanisms.

Because of possible collinearity of age, height, weight, and fat variables, this analysis cannot definitively demonstrate if age affects fat distribution in prepubertal children.

A potential limitation of this study is the fact that hormone levels were available in only a small subset of patients and therefore pubertal status could not be confirmed biochemically. Inclusion of hormonal and bone age information in future investigations in smaller numbers of prepubertal children across this age range would allow exploration of possible mechanisms for the observed sex differences in fat distribution.

In studies of adult females, Asians had greater trunk sc fat than Caucasians 23 , whereas Caucasians had greater limb sc fat Malina et al. The current study shows that adjusted mean skinfold- and DXA-derived extremity fat were lower in prepubertal Asians than Caucasian girls. Because body size weight and height was controlled when sex and race interactions in fat distribution were explored, we can infer that Asian girls have greater relative truncal or central fat mass.

In the current study, Asian boys had less adjusted mean DXA-derived extremity fat than Caucasians, whereas the skinfold method revealed no race differences.

Others 24 have reported that Asian adults have more upper-body sc fat than Caucasians and that the magnitude of the race difference is greater in females than in males. The recognition of race differences in fat distribution is of clinical importance, especially because the metabolic implications of particular body composition parameters may vary among races.

For example, the strength of association between specific fat depots and insulin sensitivity or high density lipoprotein-cholesterol was found to be different in black and white children 22 , The identification of race differences in fat distribution needs to be followed by metabolic studies to clarify associations with health risk.

The observed race and sex differences in fat distribution may reflect differences in physical activity, nutrition, or socioeconomic status of the family, information that was not available on our subjects For example, it has been reported that physical activity has significant influence on total body composition percentage body fat in early childhood It has been also reported that the increase of visceral adipose tissue is significantly less in children who exercise, compared with children who do not exercise Data on activity as well as on nutrition and socioeconomic status would be important additions to future investigations of the sex and race differences in fat distribution observed in this study.

Sample selection bias may be a limitation of the current study because the subjects were recruited voluntarily through local newspaper advertisements and announcements at schools and after-school activity centers. However, because the mean weight and height percentiles for age of the study participants were at the 50th to 75th percentile of the Centers for Disease Control and Prevention growth charts 32 , this information may be transferable to other healthy prepubertal pediatric populations.

In conclusion, our study demonstrates that sex differences in body fat distribution are present before the onset of puberty in African-American, Asian, and Caucasian children but that the specific characteristics differ with race. Race differences are also present, but these vary with sex. These findings emphasize the importance of sex- and race-specific interpretation of body composition results to define phenotypes and the need for further studies to explore their particular associations with health risks.

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide. Sign In or Create an Account. Sign In. Advanced Search. Article Navigation. Close mobile search navigation Article Navigation. Volume Article Contents. Materials and Methods. Oxford Academic. Google Scholar. Mary Horlick.

John Thornton. Jack Wang. Richard N. Pierson, Jr. Stanley Heshka. Dympna Gallagher. Cite Citation. Permissions Icon Permissions. Table 1. Open in new tab. Open in new tab Download slide.

Table 2. Table 3. Search ADS. Impact of obesity on metabolism in men and women. Importance of regional adipose tissue distribution. The degree of masculine differentiation of obesities: a factor determining predisposition to diabetes, atherosclerosis, gout, and uric calculous disease. Body fat patterning and blood pressure in children and young adults. The Bogalusa Heart Study.

Association of body fat distribution and cardiovascular risk factors in children and adolescents. Body fat distribution, rather than overall adiposity, influences serum lipids and lipoproteins in healthy men independently of age. Relation of obesity to clustering of cardiovascular disease risk factors in children and young adults.

Subcutaneous central fat is associated with cardiovascular risk factors in men independently of total fatness and fitness. Fat distribution during growth and later health outcomes. New York: Plenum;. Influence of body fat distribution during childhood on body fat distribution in adulthood: a two-decade follow-up study. Fat distribution in children and adolescents—the influence of sex and hormones. Human body composition. Champaign, IL: Human Kinetics;. Indices of body fat distribution and adiposity in Dutch children from birth to 18 years of age.

Subcutaneous adipose tissue distribution in adolescent girls of four ethnic groups. Ethnic differences in anthropometric characteristics of young children and their parents. Body form, composition and some physiological functions of Chinese on Taiwan. Asians have lower body mass index BMI but higher percent body fat than do whites: comparisons of anthropometric measurements.

Dual-energy x-ray absorptiometry for total-body and regional bone-mineral and soft-tissue composition. Reproducibility of dual-energy X-ray absorptiometry measurements in prepubertal girls. Accessed May 30, Radiographically determined widths of bone muscle and fat in the upper arm and calf from age 3—18 years.

Determinants of fat-free mass FFM and its subcomponents in prepubertal children abstract. Institute of Medicine, National Academy of Sciences Exploring the biological contributions to human health: Does sex matter? Accessed April 24, Role of gonadal steroids in the sexual dimorphisms in body composition and circulating concentrations of leptin. Determination of estrogen receptor mRNA and cytochrome P aromatase mRNA levels in adipocytes and adipose stromal cells by competitive polymerase chain reaction amplification.

Identification of progesterone receptor in human subcutaneous adipose tissue. Estrogen levels in childhood determined by an ultrasensitive recombinant cell bioassay. Diurnal rhythms of luteinizing hormone, follicle-stimulating hormone, and testosterone secretion before the onset of male puberty. Developmentally delimited emergence of more orderly luteinizing hormone and testosterone secretion during late prepuberty in boys.

Alterations in growth and body composition during puberty: III. Influence of maturation, gender, body composition, fat distribution, aerobic fitness, and energy expenditure on nocturnal growth hormone release. Body fat, fat distribution and serum lipids, lipoproteins and apolipoproteins in African-American and Caucasian-American prepubertal children. Issue Section:. Download all figures.

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Help us improve our products. Sign up to take part. Plasma steroid hormone levels vary between men and women, but body associations with BMI and adiposity are controversial.

Furthermore, little is known about the role of exercise programs on the fat between steroid hormones and adiposity. This report evaluates these relationships for plasma levels of adrenal, gonadal, and conjugated steroids with body composition and fat distribution in sedentary men and women, aged 17—65 years, and their responses to an exercise program.

Among them, men and women completed a week fully standardized exercise program. Fourteen steroid hormones and SHBG concentrations were assayed in a fasted state and were compared for their associations with adiposity in men and women and in response to the exercise program.

Differences among normal weight, overweight, and obese subjects were also considered. No association was detected between baseline steroid hormone levels and changes in adiposity traits in response to 20 weeks of exercise. A similar adiposity profile was observed in women with low SHBG. There is evidence that blood levels of steroid hormones and their binding globulins influence body composition and fat distribution, but the findings are controversial, and the magnitude of the associations is generally unknown.

In men [ 12345 ], there are consistently inverse associations between testosterone TESTO and fat mass measures starting around 30 years of age [ 1234 ]. In women, the relationship is positive in young [ 6 ] and middle-aged females adjusted sex menopausal status [ 2 ] but negative after menopause [ 7 ]. The body between lean mass and TESTO is sex controversial: while no associations were reported in some studies of men [ 238 ] and women [ 26 ], other studies found a positive correlation in men [ 910 ] and women [ 7 ] or an inverse association in men [ 51112 ].

Regarding body fat distribution, TESTO was shown to be negatively associated with various traits reflecting abdominal fat levels in men [ 1412 ], whereas the relations were found to be nonsignificant [ 713 ] or positive [ 14 ] in postmenopausal women. Previous findings are also equivocal for sex hormone-binding globulin SHBG.

In men, SHBG was negatively correlated with fat mass [ 1511 ], indicators of abdominal fat accumulation [ 81012 ], and lean mass [ 13511 ]. In women, SHBG was inversely associated with lean mass [ 2 ] and fat mass [ 15 ], whereas the association between SHBG and fat distribution was found to be nonsignificant [ 616 ] or negative [ 15 ]. Some studies have reported positive associations between plasma levels of estradiol E2 with lean mass [ 3 ], fat mass [ 1 ], body mass index BMI body, and waist circumference [ 17 ] in men, as well as with fat mass [ 18 ] and fat distribution in women [ 15 ].

Other reports have found no association with adiposity in men [ 1920 ]. Blood levels of DHT were negatively correlated with fat mass and abdominal fat accumulation traits in women [ 21 ], but the findings were not replicated in another study [ 7 ]. Dehydroepiandrosterone DHEA sulfate DHEAS was shown to be inversely [ 1622 ], positively [ 23 ], or not correlated [ 18212324 ] with fat distribution in women. One study dealt with the effects of regular exercise in older men.

Baseline plasma levels of TESTO did not correlate with the beneficial effects of a month, home-based, moderate-to-vigorous aerobic training program on body composition [ 25 ]. In body, these conflicting observations may be caused by differences in age coverage young [ 16 ], middle [ 24 ], older [ 31020 ], or mixed [ 1 fat, 591112 ]be specific to one sex [ 134 ], sex by ancestry black [ 15 body, white, mixed [ 1 ], or undefined [ 26 ]menopausal status pre [ 2sex1524 ], post [ 2714 sex, 182327 ], early-post, late-post [ 13 fathealth status health [ 67 ], obesity [ 41622 ], diseases [ 21 ]physical activity level activity [ 28 ], inactivity, sustained exercisers [ 8 ]or methodology used to assess concentrations of steroid hormones, particularly androgens [ 29 ].

Furthermore, most reports are based on only one or a few hormones. Here, we are taking advantage of the multicenter HERITAGE Family Study to examine the relationships between plasma steroid hormone levels with body composition and indicators of fat distribution in the sedentary state and after a standardized exercise training program in Blacks and Whites, men and women ranging in age from 17 to 65 years, using a panel of 14 steroid hormones plus SHBG. Sedentary subjects aged 17—65 years took part in a standardized week endurance exercise program.

Recruitment focused on nuclear families, and parents and their adult offspring were recruited. Informed written consent was obtained from each subject. Body weight, height, waist, and hip circumferences were measured following standardized procedures. Body density was measured using the hydrostatic weighing technique. The mean of the highest three of 10 measurements was used in the calculation of percent body fat from body density using the equation of Siri for Caucasian men [ 31 ], Lohman for Caucasian women [ 32 ], Schutte et al.

These measurements have been shown to be highly reproducible with no difference among clinical centers or drift over time in the course of data collection [ 35 ]. Briefly, body fat percentage and fat mass calculated from body density as described above sex characterized by intraclass correlations of 0.

The CT scans were obtained between the fourth L4 and fifth L5 lumbar vertebrae while subjects were supine with arms extended above the head. The AVF area was measured by drawing a line within body inner portion of the muscle wall surrounding the abdominal cavity. In a recent paper, inter-raters and intra-rater intraclass coefficients for CT abdominal and visceral fat body of the order of 0.

The intensity of the training was customized for each individual on the basis of heart rate HR and VO 2 measurements taken at two baseline maximal exercise tests. Details of the exercise training protocol can be found elsewhere [ 30 ]. This level was maintained for the final 6 weeks of training. The protocol was standardized across all four clinical centers fat supervised to ensure that the equipment was working properly and that participants were compliant with the protocol.

The hormonal assays have been previously described [ 1939 ]. On 2 consecutive days, two blood samples were obtained fat a h fast pre- and fat program. For eumenorrheic women, all samples were obtained in the early follicular phase of the menstrual cycle.

Fat of the women of reproductive age had dramatically irregular menstrual cycles as determined by questionnaire and an interview. In-house RIAs were used to measure levels of these four steroids. Fatty acid derivatives were submitted to saponification. All assays were performed in the laboratory of Dr. The present study is based on sedentary adults from the HERITAGE Family Study who had complete hormonal and body composition and fat distribution data at baseline and who completed a standardized exercise training program.

The mean of two measurements both before and after the exercise fat has been used for all hormones and SHBG levels. Data of men and women were analyzed separately.

Paired t- tests were used to compare variables of body composition and fat distribution at baseline and after the exercise program. Both were log transformed to reduce skewness. One-way analysis of variance ANOVA was used to compare each steroid across quartiles of baseline body composition or fat distribution variables and their training responses.

Quartiles were defined for each age and ancestry group and then pooled. Quartiles were defined taking into account age and ancestry. Based on previously published studies, we posit that the true correlations will be in the range from 0.

If the true correlations are about 0. For coefficients of the order of 0. Lower statistical power is attained when subgroups are compared and when correlations reflect smaller effect sizes. At baseline, there are premenopausal and 43 postmenopausal women. There were premenopausal and 41 postmenopausal women who completed the exercise program. Hormone levels by quartiles of baseline body composition and fat distribution variables in men.

One-way ANOVA was used to compare each plasma steroid across sex of baseline body composition or fat distribution variables. Hormone levels by quartiles of baseline body composition and fat distribution in women. AVF abdominal visceral fat. Fat general linear model GLM procedure was used to compare each plasma steroid across quartiles of baseline body composition or fat distribution variables. Hormone levels among normal weight, overweight, and obese men and women.

The GLM procedure was used to compare each plasma steroid across the various BMI categories with age and ancestry as covariates. In brief, there were no significant correlations between baseline hormonal levels and the exercise training response of body composition and fat distribution traits in men or women.

Moreover, hormonal levels were not different across quartiles of body composition and fat distribution responses. Body present study is the most comprehensive report published to date on the relationships between a large panel of plasma steroid hormones and body composition or indicators of fat distribution in sedentary men and women at baseline and in response to a standardized and fully monitored week exercise program.

In contrast, in women, SHBG was negatively correlated with all fat mass and distribution variables, whereas FAI was positively associated sex all of them. Androgens exert their effects on adipocyte differentiation in a depot-specific manner, via the androgen receptor, leading to modulation of adipocyte size and specific fat depot expansion [ 41 ].

Androgens also impact key adipocyte functions including insulin signaling, lipid metabolism, fatty acid uptake, and adipokine productions, with frequently observed sex-specific effects [ 42 ].

Furthermore, sex differences in body fat distribution are commonly recognized, with males usually characterized by a predominant accumulation of fat in the abdominal region, whereas women generally display a greater proportion of their body fat in the gluteal—femoral region [ 43 ].

An excessive amount of body fat, such as in obesity, can lead to impaired testicular T biosynthesis. As abdominal fat is a risk factor for the development of metabolic syndrome, type 2 diabetes mellitus body cardiovascular disease [ 44 ], abdominal adiposity and the ensuing hyperinsulinemia [ 45 ] can synergistically reduce Body production [ 46 ]. Thus, low physiological levels of TESTO and SHBG could represent components of a hormonal milieu that is favorable to fat storage with potential adverse metabolic impact.

In men, the major source of E2 is through the conversion of TESTO via aromatase, which is significantly expressed in adipose tissue, suggesting that higher levels of adiposity favor synthesis of E2 [ 1 ]. We did not find that E2 was associated with body composition and fat distribution traits in men and in sex in contrast to positive associations reported in to year-old men from the United States [ 1 ], to year-old Swedish men [ 3 ], and to year-old Dutch men [ 17 ], as well as in premenopausal African—American women [ 15 ].

In women with androgen excess, higher TESTO level is a fairly consistent predictor of abdominal adipose tissue accumulation, but it is not the case in non-hyperandrogenic women [ 47 ]. Our results confirm that androgens are not related to fat mass and visceral fat accumulation in women.

Hence, in women without clinical manifestations of hyperandrogenism, there is no clear association between androgens and adiposity, particularly abdominal and visceral fat levels. We found that baseline steroid hormonal levels were not associated with the adiposity changes body in response to the exercise training program.

This is concordant with other reports even though prior sex were based on rather small sample sizes. For instance, Hawkins et al. It is based on sex premise that the greater lean body mass in men is a consequence of their higher serum TESTO [ 48 ].

Even though our findings are based on sedentary women, as opposed to athletes, they strongly suggest that endogenous plasma TESTO levels in the normal range are not associated with absolute or relative fat-free mass in women once age, ancestry, menopause status, OC, and HRT have been taken into account. The present study is characterized by several strong points.

It is based on a relatively large sample with substantial subgroups defined by age, ancestry, and sex. Two blood samples obtained on consecutive days were used to assay the steroid hormones. Of particular significance, all blood samples were drawn in the early follicular phase of the menstrual cycle for eumenorrheic women. Also of significance, information on use of OC and HRT was available and could be adjusted for in the present analyses.

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To investigate the relationship between body fat distribution, sex hormones, and hyperinsulinemia in male obesity, we examined 52 obese men (body mass. Sex determination in the fruit fly Drosophila is mediated by an elaborate network in the brain, as had been expected, but in the fat body surrounding the brain.

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