This is consistent with previous reports demonstrating that total leg fat mass, most of which was subcutaneous AT, is inversely related to cardiovascular disease risk.

Albu et al 18 suggested that similar levels of visceral AT in blacks and whites may confer different metabolic risk. Our data support the contention by some that BMI may not accurately reflect the degree of adiposity in certain populations.

The current results parallel our previous observation in the Health ABC cohort that visceral and intermuscular AT strongly predict insulin resistance and type 2 diabetes. These associations between regional fat deposition and metabolic dysregulation are also consistent with other previous findings in both middle-aged and older adults.

Although we included in the analysis physical activity as a potential confounder to our associations, it is possible that the self-reported estimates for physical activity were not sensitive enough to detect significant associations with metabolic syndrome demonstrated in previous studies.

However, predictors of the incidence of metabolic syndrome can be examined when data become available in this longitudinal study. There are several possible explanations for the observed association between excess visceral fat accumulation and the metabolic syndrome.

Visceral fat is thought to release fatty acids into the portal circulation, where they may cause insulin resistance in the liver and subsequently in muscle.

A parallel hypothesis is that adipose tissue is an endocrine organ that secretes a variety of endocrine hormones such as leptin, interleukin 6, angiotensin II, adiponectin, and resistin, which may have potent effects on the metabolism of peripheral tissues.

In conclusion, excess accumulation of either visceral abdominal or muscle AT is associated with a higher prevalence of metabolic syndrome in older adults, particularly in those who are of normal body weight. This suggests that practitioners should not discount the risk of metabolic syndrome in their older patients entirely on the basis of body weight or BMI.

Indeed, generalized body composition, in terms of both BMI and the proportion of body fat, does not clearly distinguish older subjects with the metabolic syndrome. Moreover, racial differences in the various components of the metabolic syndrome provide strong evidence that the cause of the syndrome likely varies in blacks and whites.

Thus, the development of a treatment for the metabolic syndrome as a unifying disorder is likely to be complex. Correspondence: Bret H. Goodpaster, PhD, Department of Medicine, North MUH, University of Pittsburgh Medical Center, Pittsburgh, PA bgood pitt. Dr Goodpaster was supported by grant KAG from the National Institute on Aging, National Institutes of Health.

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Table 1. Characteristics of Men and Women With and Without Metabolic Syndrome. Regional Fat Distribution According to Metabolic Syndrome Status. Abdominal AT in Men and Women With and Without Metabolic Syndrome According to a Revised Definition Omitting Waist Circumference.

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J Clin Endocrinol Metab ; PubMed Google Scholar. See More About Obesity. Select Your Interests 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. This Issue. Citations View Metrics. X Facebook More LinkedIn. Cite This Citation Goodpaster BH , Krishnaswami S , Harris TB, et al.

Original Investigation. April 11, Bret H. Goodpaster, PhD ; Shanthi Krishnaswami, MPH ; Tamara B. Harris, MD ; et al Andreas Katsiaras, PhD ; Steven B.

Kritchevsky, PhD ; Eleanor M. Simonsick, PhD ; Michael Nevitt, PhD ; Paul Holvoet, PhD ; Anne B. Newman, MD. Indeed, the U-shaped association between BMI and mortality that has been observed in some studies may reflect the opposite monotonous relations of lean mass beneficial and fat mass detrimental with risk of premature mortality.

Studies of body fat distribution and premature mortality have been limited to studies of anthropometric measures of body fat distribution. In several studies, larger waist circumference, larger WHR, 16 , 44 , larger iliac-to-thigh circumference, larger SAD, and smaller hip circumference 52 , 55 , were substantially associated with risk of premature mortality after adjustment for BMI.

Because BMI may also reflect variation in lean body mass, one could argue that these independent associations are owing to incomplete adjustment for overall body fatness.

However, measures of central fat distribution also remained associated with premature mortality after adjustment for overall body fatness assessed by skinfold thickness 44 , or bioelectrical impedance. It should be noted that studies of body fat distribution and mortality have mostly been conducted in white populations.

Large waist circumference was a stronger predictor of premature mortality than BMI in black men, but neither measure was clearly associated with mortality in black women possibly owing to the limited size of the study. Although the concept that obesity, in particular abdominal obesity, is an important cause of metabolic disturbances is generally accepted, the exact pathophysiological mechanisms are not completely known.

It is widely acknowledged that fatty acids play an important role in the development of type 2 diabetes. The pancreas will compensate the diminished glucose uptake by increasing insulin secretion, but in many of the insulin resistant persons, the beta-cell eventually fails.

Accumulation of fat in non-adipose tissue may further promote insulin resistance and impair beta-cell function, which are the two key features in the development of type 2 diabetes. Visceral fat is more sensitive to lipolytic stimuli, and less sensitive to anti-lipolytic stimuli such as insulin , compared with subcutaneous fat.

Therefore, visceral fat is more likely to release free fatty acids into the circulation causing increased free fatty acid levels, which may lead to ectopic fat storage in muscle, liver, and pancreas. From epidemiological studies see above it is unclear whether a larger abdominal subcutaneous fat mass also contributes to an increased disease risk, independently of visceral fat.

It was demonstrated that the amount of deep subcutaneous adipose tissue had a much stronger association with insulin resistance than superficial subcutaneous fat, which may be due to differences in lipolysis.

As also described in a previous section, recent studies suggest that more peripheral subcutaneous fat in the legs, for a given amount of abdominal fat, may be associated with a more favourable cardiovascular risk profile.

The enzyme lipoprotein lipase LPL plays an important role in the uptake of free fatty acids from the circulation, and particularly in women, the femoral fat depot has a relatively high LPL activity and relatively low rate of basal and stimulated lipolysis. As a result of FFA uptake in the femoral-gluteal region, detrimental ectopic fat storage in the liver, skeletal muscle, and pancreas, may be prevented.

In line with this potential mechanism, transplantation of subcutaneous adipose tissue in lipoatrophic animals reversed elevated glucose levels and subcutaneous lipectomy caused metabolic disturbances in hamsters. The medical drugs thiazolidinediones increases insulin sensitivity in insulin resistant patients, while a considerable amount of total body fat is accumulated.

These drugs promote preadipocyte differentiation into mature adipocytes, in particular in the gluteal regions. Adipose tissue secretes many signalling proteins and cytokines with broad biological activity and critical functions.

Some of these adipokines may be involved in the development of insulin resistance in obesity. There are known differences in endocrine secretion of leptin, adiponectin, and IL-6 between abdominal subcutaneous fat and visceral fat, — whereas the existence of regional differences in the secretion of plasminogen activator inhibitor-1 PAI-1 and TNF-alpha is controversial.

In addition, there are probably many more yet undiscovered proteins, differently secreted by different fat depots, which might influence metabolic function. Clearly, more research in this area is needed.

There are several factors that may influence body fat patterning as well as the development of metabolic disturbances and may, therefore, underlie or confound the associations between these phenomena. These factors include behavioural factors smoking, physical activity, diet , hormonal factors disturbances in glucocorticoid metabolism, sex hormones, growth hormone , and demographic factors such as age and gender.

In conclusion, it is supported by mechanistic studies, studies of metabolic risk factors, and studies of cardiovascular disease and premature mortality, that body fat distribution is relevant for the risk of cardiovascular disease and mortality. Time trend studies have shown that there is a consistent increase over time in the prevalence of obesity and, particularly, abdominal obesity, which is likely to contribute to a higher incidence of type 2 diabetes, cardiovascular disease, and mortality.

Several methods are available to measure body fatness, and the choice largely depends on the purpose. For clinical applications it should be considered that usually no information on body fatness is collected at all and the health problems of being overweight are often not discussed by clinicians with their patients.

For this purpose, BMI can be an adequate measure of body fatness in adults. However, waist circumference may be a simple alternative that also captures information on abdominal fat distribution and may be less affected by variation in lean mass. The WHR is more difficult to interpret because it may reflect an effect of larger waist as well as a smaller hip circumference.

The SAD can be used instead of waist circumference but has not consistently been shown to be superior for the prediction of disease risk. For large epidemiological studies the BMI can capture most of the relevant variation in body fatness depending on the age of the study population.

However, many studies have shown that the collection of information on body fat distribution waist circumference, WHR, SAD, DXA can provide additional insights.

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