WHR and body composition -
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The greater the number of cortisol receptors, the more sensitive the visceral fat tissue is to cortisol. This heightened sensitivity to cortisol stimulates fat cells to further increase in size.
Evidence for the relationship between cortisol and central fat distribution has primarily been studied in individuals with Cushing's syndrome. A primary component of Cushing's syndrome is the accumulation of fat in the abdominal region, and it is hypothesized that elevated cortisol levels contribute to this accumulation.
However, this hypothesis remains contested as cortisol levels only modestly explain variation in central fat distribution. It is more likely that a complex set of biological and neuroendocrine pathways related to cortisol secretion contribute to central adiposity, such as leptin , neuropeptide y , corticotropin releasing factor and the sympathetic nervous system.
In general, adults with growth hormone deficiencies also have increased WHRs. Increased adipose deposits are therefore more likely to form in these individuals, causing the high WHR. Growth hormone deficiencies have also been correlated with WHRs in prepubertal children; the specific baseline body statistics, such as WHRs, of pre-pubertal children with growth hormone deficiencies can predict growth response effectiveness to artificial growth hormone therapies, such as rhGH treatments.
Males with congenital adrenal hyperplasia , determined by CYP21A2 mutations, have increased WHRs. Women with high WHR 0. One of the factors that affects a woman's waist-hip ratio is her gynoid fat distribution , a store of energy to be expended in the nurturing of offspring, both to provide adequate energy resources during pregnancy and for the infant during the stage in which they are breastfeeding.
This can be seen in the fact that a female's waist—hip ratio is at its optimal minimum during times of peak fertility—late adolescence and early adulthood, before increasing later in life.
As a female's capacity for reproduction comes to an end, the fat distribution within the female body begins a transition from the gynoid type to more of an android type distribution.
This is evidenced by the percentages of android fat being far higher in post-menopausal than pre-menopausal women. Evidence suggests that WHR is an accurate somatic indicator of reproductive endocrinological status and long-term health risk.
Among girls with identical body weights, those with lower WHRs show earlier pubertal endocrine activity, as measured by high levels of lutenizing hormone and follicle-stimulating hormone, as well as sex steroid estradiol activity. A Dutch prospective study on outcome in an artificial insemination program provides evidence for the role of WHR and fecundity.
Menopause , the natural or surgical cessation of the menstrual cycle, is due to an overall decrease in ovarian production of the hormones estradiol and progesterone. These hormonal changes are also associated with an increase in WHR independent of increases in body mass.
Using data from the U. National Center for Health Statistics , William Lassek at the University of Pittsburgh in Pennsylvania and Steven Gaulin of the University of California, Santa Barbara found a child's performance in cognitive tests correlated to their mother's waist—hip ratio, a proxy for how much fat she stores on her hips.
Children whose mothers had wide hips and a low waist—hip ratio scored highest, leading Lassek and Gaulin to suggest that fetuses benefit from hip fat, which contains long chain polyunsaturated fatty acids , critical for the development of the fetus's brain.
WHR is considered as one of the three determinants of female attractiveness, the other two being body mass index BMI , and curviness. Some researchers have found that the waist—hip ratio is a significant measure of female attractiveness. It appears that men in westernized societies are more influenced by female waist size than hip size: "Hip size indicates pelvic size and the amount of additional fat storage that can be used as a source of energy.
Waist size conveys information such as current reproductive status or health status in westernized societies with no risk of seasonal lack of food, the waist, conveying information about fecundity and health status, will be more important than hip size for assessing a female's attractiveness".
By western standards, women in foraging populations have high numbers of pregnancies, high parasite loads, and high caloric dependence on fibrous foods. These variables change across cultures, suggesting that:.
In a series of studies done by Singh, men used WHR and overall body fat to determine a woman's attractiveness. In his first study, men were shown a series of 12 drawings of women with various WHRs and body fat. Drawings with normal weight and a low WHR were associated with the most positive traits i.
attractive, sexy, intelligent and healthy. The drawings of thin female figures were not associated with any positive traits except youthfulness. Through this study, Singh suggests that males and females may have developed innate mechanisms which detect and make use of the WHR to assess how healthy an individual is and particularly for men , infer possible mate value.
Other studies discovered WHR as a signal of attractiveness as well, beyond just examining body fat and fertility. Barnaby Dixson, Gina Grimshaw, Wayne Linklater, and Alan Dixson conducted a study using eye-tracking techniques to evaluate men's fixation on digitally altered photographs of the same woman, as well as asking the men to evaluate the images based on attractiveness.
What they found was while men fixated on the woman's breasts in each photo, they selected the images where the woman had a 0. Furthermore, referencing a study conducted by Johnson and Tassinary looking at animated human walking stimuli, Farid Pazhoohi and James R.
Liddle proposed that men do not solely use WHR to evaluate attractiveness, but also a means of sex-differentiation, with higher WHR perceived as more masculine and lower WHR as an indicator of femininity. Pazhoohi and Liddle used this idea as a possible additional explanation as to why men perceive a lower WHR as more attractive — because it relates to an expression of femininity, as opposed to masculinity and a higher WHR.
To enhance their perceived attractiveness, some women may artificially alter their apparent WHR. The methods include the use of a corset to reduce the waist size and hip and buttock padding to increase the apparent size of the hips and buttocks.
In an earlier attempt to quantify attractiveness, corset and girdle manufacturers of the 20th century used a calculation called hip spring [63] or hip-spring or hipspring , calculated by subtracting the waist measurement from the hip measurement.
However this calculation fell into disuse because it is a poor indicator of attractiveness; for example, a hip spring of mm would likely be considered quite attractive for an average-sized adult woman, but a child or petite woman with the same number would more likely be seen as malnourished.
WHR versus BMI attractiveness is related to fertility, not fat content. A study performed by Holliday used computer generated female body shapes to construct images which covary with real female body mass indexed with BMI and not with body shape indexed with WHR , and vice versa.
Twelve observers 6 male and 6 female rated these images for attractiveness during an fMRI study. The attractiveness ratings were correlated with changes in BMI and not WHR.
The results demonstrated that in addition to activation in higher visual areas, changes to BMI had a direct impact on activity within the brain's reward system. This shows that BMI, not WHR, modulates reward mechanisms in the brain and that this may have important implications for judgements of ideal body size in eating-disordered individuals.
Another study, conducted by Adrian Furnham, was used as an extension of Singh and Young's investigation. A total of participants were in the study. There were 98 female participants. The age range was between 16 and Their educational and socio-economic backgrounds nearly all middle class were fairly homogenous, and none had previously participated in any studies involving female body shape or attractiveness.
It was predicted that the effect of breast size on judgment of attractiveness and age estimation would be dependent on overall body fat and the size of the waist-to-hip ratio. All the participants were given a booklet with eight pictures in total.
Each figure was identified as heavy or slender, feminine WHR or masculine WHR, and large-breasted or small-breasted. When ratings of the figures' attractiveness were made, generally it appeared that bust size, WHR, and their weight were all important contributory elements.
The female participants rated the figures with a low WHR as more attractive, healthy, feminine-looking, and in the case of the heavy figure, more kind and understanding than did male participants.
This is a particularly interesting finding, as most previous studies report that young women idealize female bodies solely on the basis of thinness. As far as the breast sizes of the slender figures is concerned, whether they had large or small breasts did not appear to have any effect on the ratings of attractiveness or kindness or understanding, and having larger breasts only increased the mean ratings of health and femininity very slightly.
However, a heavy figure with a high WHR and a large bust was rated as the least attractive and healthy by all participants. Waist—hip ratio is also a reliable cue to one's sex and it is hypothesised that the "individuals who represent a mismatch based on the cue provided by WHR e.
A University of Wroclaw study of around one thousand women across different cultures—designed to address the conflicting theories—concluded that an attractive WHR is not a predictor of peak fertility, but actually a predictor of the onset of fertility and therefore a predictor of maximal long term reproductive potential and minimal chance of raising a competing male's children.
Research has found waist-to-chest ratio to be the largest determinant of male attractiveness, with body mass index and waist-to-hip ratio not as significant. A number of studies have been carried out with focus on food composition of diets in relation to changes in waist circumference adjusted for body mass index.
Whole-grain, ready-to-eat, oat cereal diets reduce low-density lipoprotein cholesterol and waist circumference in overweight or obese adults more than low-fibre control food diets.
Arch Intern Med. Jensen MD, Ryan DH, Apovian CM, et al. Moyer VA. Screening for and management of obesity in adults: U. Preventive Services Task Force recommendation statement.
Ann Intern Med. By Richard N. Fogoros, MD Richard N. Fogoros, MD, is a retired professor of medicine and board-certified in internal medicine, clinical cardiology, and clinical electrophysiology. Use limited data to select advertising. Create profiles for personalised advertising.
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Verywell Health uses only high-quality sources, including peer-reviewed studies, to support the facts within our articles. Read our editorial process to learn more about how we fact-check and keep our content accurate, reliable, and trustworthy. ee Moyer VA.
Waist-to-hip ratio may Bofy a better comopsition Hydration essentials for breastfeeding moms Anti-cancer prevention strategies weight management than body mass index Fompositionaccording to Herbal Prostate Health new study. Research published this week in the journal JAMA Network Open reports that WHR and body composition ratio ad be more useful composirion BMI ajd determining health risks and medical interventions. For their study, the researchers examined data fromparticipants based in the United Kingdom. They compared data on BMI, fat mass index, and waist-to-hip ratio. Waist-to-hip ratio is the circumference of the waist divided by the circumference of the hip. In both men and women, a waist-to-hip ratio of 1. Those who carry excessive fat around their midsection may be at greater risk of developing type 2 diabetescoronary heart diseaseand high blood pressure.
WHR and body composition -
Studies have shown that a waist circumference of 40 inches or more cm in men, and of 35 inches or more 88 cm in women, is associated with elevated cardiovascular risk.
The waist-to-hip ratio is another way of assessing abdominal obesity, and studies have confirmed that this measure correlates with cardiovascular risk.
To calculate your waist-to-hip ratio, measure both your waist and hip circumferences, then divide the waist measurement by the hip measurement.
In women, the waist-to-hip ratio should be 0. In women, the waist should be narrower than the hips, and in men, the waist should be narrower or the same as the hips.
The waist-to-hip ratio is helpful because in smaller people waist circumference alone may underestimate risk. By comparing waist circumference to hip circumference, you can get a better indication of abdominal obesity.
There is no definitive answer to this question. These recommendations, again, are based on the large body of research that has used BMI to predict cardiovascular outcomes. However, it is important to realize that, while BMI is quite good at predicting overall risk in large populations, it might not be a particularly accurate measure for a given individual.
Also, it does not specifically take into account the degree of abdominal obesity a person may have. Several studies have suggested that a measure of abdominal girth can be more accurate than BMI in predicting heart disease.
In contrast, some studies have shown an elevated waist-to-hip ratio to be a strong predictor of heart disease, especially in women. Many doctors are now relying on a combination of measures to advise patients on their weight-related risk.
And if your BMI is , unless you are a bodybuilder or other type of muscular athlete, you are almost certainly too fat. One advantage of the waist-to-hip ratio is that you can assess it yourself, without formally measuring anything, in the privacy of your own home. Just strip down to your skivvies and look at yourself in the mirror, both head-on and in profile.
To reduce that risk, your weight is something you will need to address. Being overweight is an important risk factor for cardiovascular disease and metabolic conditions such as diabetes.
Coutinho T, Goel K, Corrêa de sá D, et al. Combining body mass index with measures of central obesity in the assessment of mortality in subjects with coronary disease: role of "normal weight central obesity". J Am Coll Cardiol. Zhang C, Rexrode KM, Van dam RM, Li TY, Hu FB.
Abdominal obesity and the risk of all-cause, cardiovascular, and cancer mortality: sixteen years of follow-up in US women. Tran NTT, Blizzard CL, Luong KN, et al. The importance of waist circumference and body mass index in cross-sectional relationships with risk of cardiovascular disease in Vietnam.
PLoS ONE. doi: Research has found waist-to-chest ratio to be the largest determinant of male attractiveness, with body mass index and waist-to-hip ratio not as significant. A number of studies have been carried out with focus on food composition of diets in relation to changes in waist circumference adjusted for body mass index.
Whole-grain, ready-to-eat, oat cereal diets reduce low-density lipoprotein cholesterol and waist circumference in overweight or obese adults more than low-fibre control food diets. Weight loss did not vary between groups. In an American sample of healthy men and women participating in the ongoing 'Baltimore Longitudinal Study of Aging', the mean annual increase [with age] in waist circumference was more than 3 times as great for the participants in the white-bread cluster compared with the participants using a diet that is high in fruit, vegetables, reduced-fat dairy and whole grains and is low in red or processed meat, fast food and soft drink.
A study suggests that a dietary pattern high in fruit and dairy and low in white bread, processed meat, margarine, and soft drinks may help to prevent abdominal fat accumulation. Contents move to sidebar hide. Article Talk. Read Edit View history. Tools Tools. What links here Related changes Upload file Special pages Permanent link Page information Cite this page Get shortened URL Download QR code Wikidata item.
Download as PDF Printable version. In other projects. Wikimedia Commons. The Venus de Milo has a WHR value of 0. Obesity Epidemiology Overweight Underweight Body shape Weight gain Weight loss Gestational weight gain Diet nutrition Weight management Overnutrition Childhood obesity Epidemiology.
Medical concepts. Adipose tissue Classification of obesity Genetics of obesity Metabolic syndrome Epidemiology of metabolic syndrome Metabolically healthy obesity Obesity paradox Set point theory.
Body adiposity index Body mass index Body fat percentage Body Shape Index Corpulence index Lean body mass Relative Fat Mass Waist—hip ratio Waist-to-height ratio. Related conditions. Obesity-associated morbidity. Arteriosclerosis Atherosclerosis Fatty liver disease GERD Gynecomastia Heart disease Hypertension Obesity and cancer Osteoarthritis Prediabetes Sleep apnea Type 2 diabetes.
Management of obesity. Anti-obesity medication Bariatrics Bariatric surgery Dieting List of diets Caloric deficit Exercise outline Liposuction Obesity medicine Weight loss camp Weight loss coaching Yo-yo effect. Social aspects. Comfort food Fast food Criticism Fat acceptance movement Fat fetishism Health at Every Size Hunger Obesity and the environment Obesity and sexuality Sedentary lifestyle Social determinants of obesity Social stigma of obesity Weight cutting Weight class.
Main article: Physical attractiveness. PLOS ONE. Bibcode : PLoSO.. doi : PMC PMID cited in Stephen Heyman May 27, The New York Times. Retrieved 10 September JSTOR S2CID World Health Organization. Retrieved March 21, Waist To Hip Calculator at University of Maryland Medical System.
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September Gesellschaft für Sportmedizin und Prävention e. cited in "Waist-hip Ratio Should Replace Body Mass Index As Indicator Of Mortality Risk In Older People". Archived from the original on 22 August Harvard T. Chan School of Public Health.
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In body composition analysis, the WHR calculated by BIA was 0. The baseline characteristics of the participants are presented in Table 1.
To compare the hazard ratios for CKD development, we divided each composite metric into quintile groups Table 2. As a result, an increase in BMI, the traditional body composite metric, showed a significant positive association with elevated CKD risk. On the other hand, the total body fat ratio calculated by BIA also showed an association with CKD development, but not in a sequential manner.
Skeletal muscle ratio calculated by BIA showed a negative association with CKD risk, and the participants in the highest quintile of muscle mass ratio showed 0. Cumulative incidence of chronic kidney disease CKD according to quintiles of BMI left and WHR measured by BIA right.
BMI, body mass index; WHR, waist hip ratio; BIA, bioelectrical impedance analysis. When comparing manually measured and BIA-calculated WHRs, the quintile ranges of each metric were different from each other.
The association for CKD risk in the quintile groups of manually measured WHR was not significant, while the BIA-calculated WHR was significantly associated with CKD, especially in the highest quintile.
A WHR level of 0. Receiver operating curve ROC analysis was performed to find the most significant predictor of CKD development in body composite metrics including BMI, total body fat, manually measured WHR, and BIA-calculated WHR.
Of the metrics, the area under the ROC of BIA-calculated WHR was the highest at 0. Receiver operating characteristic ROC analysis for chronic kidney disease CKD development according to various body composition profiles. The numbers in the legend represent areas under the ROC curve C-statistics.
WHR, waist—hip ratio; BIA, bioelectrical impedance analysis; BMI, body mass index; AUROC, area under receiver operating characteristic curve. WHR, waist—hip ratio; BIA, bioelectrical impedance analysis; BMI, body mass index.
We observed the development of kidney dysfunction in a middle-aged population for approximately While an increase in BMI, WHR, and total body fat were associated with an elevated risk of kidney dysfunction, an increase in total body muscle decreased the risk of kidney dysfunction.
Among the body composition metrics, WHR measured by BIA had the highest predictive value for kidney dysfunction. Numerous observational studies have shown an association between obesity and chronic kidney disease [ 10 , 11 , 12 ].
However, most studies used the traditional obesity model based on BMI, and only a few studies examined abdominal obesity using WHR or waist circumference WC. Previous studies with WHR or WC had several limitations, such as cross-sectional design [ 19 , 27 ], short duration of follow-up, and a low incidence of the outcome [ 20 ].
Although BMI is an easily measurable metric, it has a critical limitation in that it cannot assess fat distribution or muscle content in specific body areas.
Several recent studies have revealed that WHR and WC correlated more with the outcomes of obesity, including diabetes and mortality, compared to BMI [ 28 , 29 ].
Lee et al. assessed correlation between eGFR and waist circumference-related obesity metrics using cross-sectional data [ 30 ]. However, because of the study design, causality between obesity metrics and eGFR can not be suggested. Kjaergaard et al. used Mendelian Randomization method to estimate direct causal effect of BMI and WHR on kidney function [ 31 ].
focused on the verification of causality between specific body composite factor and renal dysfunction, while our study conducted for finding best predictor among body composite metrics of kidney dysfunction.
The study of Hong et al. assessed multivariable regression analysis for moderate CKD to find an adequate predictive model using various obesity-related factors [ 32 ]. However, the follow up duration for renal dysfunction was relatively short 3 months , and only data on the risk ratio were presented without predictability for each variable.
The exact mechanisms by which obesity may contribute to the development or progression of CKD remain unclear. The key physiological responses of the kidney to obesity are an increase in glomerular filtration rate, renal plasma flow, filtration fraction, and tubular absorption of sodium [ 33 , 34 ].
Glomerular hyperfiltration induced by obesity increases sodium delivery to the renal proximal tubule, resulting in the activation of sodium transporters in the nephron [ 33 , 34 ]. As a result of intraglomerular hypertension, mechanical stress on the capillary wall increases, leading to podocyte injury and glomerulosclerosis [ 34 ].
Furthermore, the renin—angiotensin—aldosterone system and renal sympathetic nervous system are activated in obesity, and these factors contribute to the pathogenesis of obesity-related sodium retention and glomerular hyperfiltration [ 35 , 36 , 37 , 38 ]. Moreover, several comorbid conditions related to obesity, including hypertension and glucose intolerance, may result in deleterious renal consequences [ 39 , 40 ].
However, most obese individuals do not develop CKD, and there is a high proportion of metabolically healthy obese individuals [ 41 , 42 ]. Thus, increased weight alone cannot be the only factor that induces kidney damage.
Consistently, previous studies have shown paradoxical results of obesity defined by high BMI on lower mortality in advanced CKD and ESRD, suggesting the ineffectiveness of using BMI as a measure of obesity [ 43 , 44 ]. Adipokines such as leptin, adiponectin, resistin, and visfatin, which are mainly secreted by visceral fat, may be the cause for the specific effects of central adipose tissue on the kidney rather than total body fat or body weight.
Leptin induces mesangial hypertrophy in obese individuals [ 46 ]. In an experimental study, a decrease in adiponectin resulted in the fusion of podocyte foot processes and the development of CKD [ 47 ]. Another notable finding of our study is the difference between manually measured WHR and BIA-calculated WHR.
Regarding our results, BIA-calculated WHR seems to be a better indicator of CKD risk than manually measured WHR in Cox regression and ROC analyses. The BIA measuring instrument used in this study is highly reliable, inexpensive, and uncomplicated for measuring muscle mass, body fat mass, lean mass, and water content.
It has been verified and widely used to measure body fat percentages in clinical practice [ 5 ]. Measuring waist circumference and hip circumference with this instrument is based on the principle of calculating the volume of lean body mass for each part, and then calculating the circumference through the area [ 25 ].
WHR measured by BIA may be a more suitable metric to represent abdominal visceral fat, but further research is needed to evaluate the exact cause of this difference between manual and BIA-calculated body composition metrics. This study not only verified the association of CKD development and obesity reported in previous observational studies, but also revealed that WHR measured by BIA was a better predictive indicator of CKD development than body weight, total fat mass, or total muscle mass, suggesting the unelucidated role of visceral obesity on the kidney.
However, our study had several limitations. The etiology of CKD could not be assessed because of a lack of data. Direct measurement of the visceral fat area using image-based methods was not done.
Computed tomography and MRI are known to be precise methods for calculating visceral fat volume, but high cost, accessibility, and the risk of radiation exposure are hurdles to its clinical application [ 53 , 54 ]. However, as WHR and WC showed a high correlation with image-based visceral fat area in a previous study, WHR can be considered as an alternative to these image-based methods [ 55 ].
Another limitation of this study is that the WHR and fat content measuring instruments using the BIA method are outdated due to the long study period, raising questions about their current clinical application. However, our results provide evidence for the importance of measuring visceral fat rather than total body fat or mixed trunk fat visceral and subcutaneous for predicting renal dysfunction and can be the basis for further analysis using various novel BIA machines in the field of kidney research.
The substantially increasing incidence and prevalence of CKD worldwide is presumed to be caused by an increase in various underlying diseases such as diabetes and hypertension, but an increase in anthropological problems such as obesity, especially central obesity, is also estimated to be a significant cause [ 42 ].
According to our study findings, we suggest measuring WHR using the BIA method, rather than measuring BMI, to define obesity and to predict and manage the risk of CKD development.
Further prospective studies are needed to determine a target range of visceral fat area for preserving kidney health, and to determine optimal strategies for managing visceral obesity to prevent kidney dysfunction.
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BMC Nephrology volume 23Hydration essentials for breastfeeding moms number: Cite this article. Domposition details. Obesity is a major health WHR and body composition worldwide xomposition is WHR and body composition with chronic kidney disease Menopause and bone health. Body mass index Compositoin is a common compositiin of diagnosing obesity, but there are concerns about its accuracy and ability to measure body composition. This study evaluated the risk of CKD development in a middle-aged population in association with various body composition metrics. From a prospective cohort of 10, middle-aged adults, we enrolled for whom baseline and follow-up data were available. We collected data pertaining to participants' BMI, manually measured waist—hip ratio WHRand various measurements of bioelectrical impedance analysis BIAincluding total body fat content, muscle content, and calculated WHR, and classified the participants into quintiles accordingly.
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