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Figure 1. 
Odds ratios (ORs; adjusted for age and race) and 95% confidence intervals (CIs) of having metabolic syndrome with increasing visceral adipose tissue (VAT) and subcutaneous abdominal adipose tissue (SAT) by 50 cm2 in normal-weight, overweight, and obese men and women. The dashed line represents an OR of 1. Asterisk denotes significant (P<.05) OR. Note the different scales for VAT and SAT.

Odds ratios (ORs; adjusted for age and race) and 95% confidence intervals (CIs) of having metabolic syndrome with increasing visceral adipose tissue (VAT) and subcutaneous abdominal adipose tissue (SAT) by 50 cm2 in normal-weight, overweight, and obese men and women. The dashed line represents an OR of 1. Asterisk denotes significant (P<.05) OR. Note the different scales for VAT and SAT.

Figure 2. 
Odds ratio (ORs; adjusted for age and race) and 95% confidence intervals (CIs) of having metabolic syndrome with increasing intermuscular adipose tissue (IMAT) (4 cm2) and subcutaneous thigh adipose tissue (STAT) (10 cm2) in normal-weight, overweight, and obese men and women. The dashed line represents an OR of 1. Asterisk denotes significant (P<.05) OR. Note the different scales for IMAT and STAT.

Odds ratio (ORs; adjusted for age and race) and 95% confidence intervals (CIs) of having metabolic syndrome with increasing intermuscular adipose tissue (IMAT) (4 cm2) and subcutaneous thigh adipose tissue (STAT) (10 cm2) in normal-weight, overweight, and obese men and women. The dashed line represents an OR of 1. Asterisk denotes significant (P<.05) OR. Note the different scales for IMAT and STAT.

Table 1. 
Characteristics of Men and Women With and Without Metabolic Syndrome
Characteristics of Men and Women With and Without Metabolic Syndrome
Table 2. 
Prevalence of the 5 Criteria Defining the Metabolic Syndrome Stratified by Sex and Race*
Prevalence of the 5 Criteria Defining the Metabolic Syndrome Stratified by Sex and Race*
Table 3. 
Regional Fat Distribution According to Metabolic Syndrome Status
Regional Fat Distribution According to Metabolic Syndrome Status
Table 4. 
Abdominal AT in Men and Women With and Without Metabolic Syndrome According to a Revised Definition Omitting Waist Circumference
Abdominal AT in Men and Women With and Without Metabolic Syndrome According to a Revised Definition Omitting Waist Circumference
1.
Haffner  SValdez  RHazuda  HMitchell  BMorales  PStern  M Prospective analysis of the insulin resistance syndrome (syndrome X).  Diabetes 1992;41715- 722PubMedGoogle ScholarCrossref
2.
Isomaa  BAlmgren  PTuomi  T  et al.  Cardiovascular morbidity and mortality associated with the metabolic syndrome.  Diabetes Care 2001;24683- 689PubMedGoogle ScholarCrossref
3.
National Institutes of Health, Third Report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation and Treatment of High Cholesterol in Adults (Adult Treatment Panel III).  Bethesda, Md National Institutes of Health2001;NIH publication 01-3670
4.
Ford  EGiles  WDietz  W Prevalence of the metabolic syndrome among US adults.  JAMA 2002;287356- 359PubMedGoogle ScholarCrossref
5.
Grundy  SMHansen  BSmith  SC  Jr  et al.  Clinical management of metabolic syndrome: report of the American Heart Association/National Heart, Lung, and Blood Institute/American Diabetes Association conference on scientific issues related to management.  Circulation 2004;109551- 556PubMedGoogle ScholarCrossref
6.
Harris  MIFlegal  KMCowie  CC  et al.  Prevalence of diabetes, impaired fasting glucose, and impaired glucose tolerance in U.S. adults: the Third National Health and Nutrition Examination Survey, 1988-1994.  Diabetes Care 1998;21518- 524PubMedGoogle ScholarCrossref
7.
Resnick  HEHarris  MIBrock  DBHarris  TB American Diabetes Association diabetes diagnostic criteria, advancing age, and cardiovascular disease risk profiles: results from the Third National Health and Nutrition Examination Survey.  Diabetes Care 2000;23176- 180PubMedGoogle ScholarCrossref
8.
Wilson  PWEvans  JC Coronary artery disease prediction.  Am J Hypertens 1993;6309S- 313SPubMedGoogle ScholarCrossref
9.
Mokdad  AHBowman  BAFord  ESVinicor  FMarks  JSKoplan  JP The continuing epidemics of obesity and diabetes in the United States.  JAMA 2001;2861195- 1200PubMedGoogle ScholarCrossref
10.
Després  JNadeau  ATremblay  A  et al.  Role of deep abdominal fat in the association between regional adipose tissue distribution and glucose tolerance in obese women.  Diabetes 1989;38304- 309PubMedGoogle ScholarCrossref
11.
Goodpaster  BHThaete  FLSimoneau  J-AKelley  DE Subcutaneous abdominal fat and thigh muscle composition predict insulin sensitivity independently of visceral fat.  Diabetes 1997;461579- 1585PubMedGoogle ScholarCrossref
12.
Kelley  DEThaete  FLTroost  FHuwe  TGoodpaster  BH Subdivisions of subcutaneous abdominal adipose tissue and insulin resistance.  Am J Physiol Endocrinol Metab 2000;278E941- E948PubMedGoogle Scholar
13.
Goodpaster  BKrishnaswami  SResnick  H  et al.  Association between regional adipose tissue distribution and both type 2 diabetes and impaired glucose tolerance in elderly men and women.  Diabetes Care 2003;26372- 379PubMedGoogle ScholarCrossref
14.
Seidell  JCOosterlee  AThijssen  MA  et al.  Assessment of intra-abdominal and subcutaneous abdominal fat: relation between anthropometry and computed tomography.  Am J Clin Nutr 1987;457- 13PubMedGoogle Scholar
15.
Goodpaster  BHKelley  DEThaete  FLHe  JRoss  R Skeletal muscle attenuation determined by computed tomography is associated with skeletal muscle lipid content.  J Appl Physiol 2000;89104- 110PubMedGoogle Scholar
16.
Brach  JSSimonsick  EMKritchevsky  SYaffe  KNewman  AB The association between physical function and lifestyle activity and exercise in the Health, Aging and Body Composition Study.  J Am Geriatr Soc 2004;52502- 509PubMedGoogle ScholarCrossref
17.
Van Pelt  REEvans  EMSchechtman  KBEhsani  AAKohrt  WM Contributions of total and regional fat mass to risk for cardiovascular disease in older women.  Am J Physiol Endocrinol Metab 2002;282E1023- E1028PubMedGoogle Scholar
18.
Albu  JBMurphy  LFrager  DHJohnson  JAPi-Sunyer  FX Visceral fat and race-dependent health risks in obese nondiabetic premenopausal women.  Diabetes 1997;46456- 462PubMedGoogle ScholarCrossref
19.
Mandavilli  ACyranoski  D Asia's big problem.  Nat Med 2004;10325- 327PubMedGoogle ScholarCrossref
20.
DeNino  WFTchernof  ADionne  IJ  et al.  Contribution of abdominal adiposity to age-related differences in insulin sensitivity and plasma lipids in healthy nonobese women.  Diabetes Care 2001;24925- 932PubMedGoogle ScholarCrossref
21.
Després  J-P Abdominal obesity as important component of insulin resistance syndrome.  Nutrition 1993;9452- 459PubMedGoogle Scholar
22.
Gabriely  IMa  XHYang  XM  et al.  Removal of visceral fat prevents insulin resistance and glucose intolerance of aging: an adipokine-mediated process?  Diabetes 2002;512951- 2958PubMedGoogle ScholarCrossref
23.
Haffner  SMKarhapaa  PMykkanen  LLaakso  M Insulin resistance, body fat distribution, and sex hormones in men.  Diabetes 1994;43212- 219PubMedGoogle ScholarCrossref
24.
Kohrt  WMKirwan  JPStaten  MABourey  REKing  DSHolloszy  JO Insulin resistance in aging is related to abdominal obesity.  Diabetes 1993;42273- 281PubMedGoogle ScholarCrossref
25.
Wajchenberg  BL Subcutaneous and visceral adipose tissue: their relation to the metabolic syndrome.  Endocr Rev 2000;21697- 738PubMedGoogle ScholarCrossref
26.
Lakka  TALaaksonen  DELakka  HM  et al.  Sedentary lifestyle, poor cardiorespiratory fitness, and the metabolic syndrome.  Med Sci Sports Exerc 2003;351279- 1286PubMedGoogle ScholarCrossref
27.
Bergman  RNVan Citters  GWMittelman  SD  et al.  Central role of the adipocyte in the metabolic syndrome.  J Investig Med 2001;49119- 126PubMedGoogle ScholarCrossref
28.
Ravussin  ESmith  SR Increased fat intake, impaired fat oxidation, and failure of fat cell proliferation result in ectopic fat storage, insulin resistance, and type 2 diabetes mellitus.  Ann N Y Acad Sci 2002;967363- 378PubMedGoogle ScholarCrossref
29.
Greco  AVMingrone  GGiancaterini  A  et al.  Insulin resistance in morbid obesity: reversal with intramyocellular fat depletion.  Diabetes 2002;51144- 151PubMedGoogle ScholarCrossref
30.
Krssak  MFalk Petersen  KDresner  A  et al.  Intramyocellular lipid concentrations are correlated with insulin sensitivity in humans: a 1H NMR spectroscopy study.  Diabetologia 1999;42113- 115PubMedGoogle ScholarCrossref
31.
Perseghin  GScifo  PDeCobelli  F  et al.  Intramyocellular triglyceride content is a determinant of in vivo insulin resistance in humans: a 1H-13C nuclear magnetic resonance spectroscopy assessment in offspring of type 2 diabetic patients.  Diabetes 1999;481600- 1606PubMedGoogle ScholarCrossref
32.
Yu  CChen  YCline  GW  et al.  Mechanism by which fatty acids inhibit insulin activation of insulin receptor substrate-1 (IRS-1)-associated phosphatidylinositol 3-kinase activity in muscle.  J Biol Chem 2002;27750230- 50236PubMedGoogle ScholarCrossref
33.
Marchesini  GBrizi  MBianchi  G  et al.  Nonalcoholic fatty liver disease: a feature of the metabolic syndrome.  Diabetes 2001;501844- 1850PubMedGoogle ScholarCrossref
34.
Oral  EASimha  VRuiz  E  et al.  Leptin-replacement therapy for lipodystrophy.  N Engl J Med 2002;346570- 578PubMedGoogle ScholarCrossref
35.
Reitman  MLMason  MMMoitra  J  et al.  Transgenic mice lacking white fat: models for understanding human lipoatrophic diabetes.  Ann N Y Acad Sci 1999;892289- 296PubMedGoogle ScholarCrossref
36.
Fried  SKBunkin  DAGreenberg  AS Omental and subcutaneous adipose tissues of obese subjects release interleukin-6: depot difference and regulation by glucocorticoid.  J Clin Endocrinol Metab 1998;83847- 850PubMedGoogle Scholar
Original Investigation
April 11, 2005

Obesity, Regional Body Fat Distribution, and the Metabolic Syndrome in Older Men and Women

Author Affiliations

Author Affiliations: Department of Medicine, University of Pittsburgh Medical Center, Pittsburgh, Pa (Drs Goodpaster, Katsiaras, and Newman); Graduate School of Public Health, University of Pittsburgh (Drs Krishnaswami and Newman); Intramural Research Program, National Institute on Aging, Baltimore, Md (Drs Harris and Simonsick); Sticht Center on Aging, Wake Forest University School of Medicine, Winston-Salem, NC (Dr Kritchevsky), Prevention Sciences Group, University of California at San Francisco (Dr Nevitt), and Center for Experimental Surgery and Anesthesiology, Catholic University, Louvain, Belgium (Dr Holvoet).

Arch Intern Med. 2005;165(7):777-783. doi:10.1001/archinte.165.7.777
Abstract

Background  The metabolic syndrome is a disorder that includes dyslipidemia, insulin resistance, and hypertension and is associated with an increased risk of diabetes and cardiovascular disease. We determined whether patterns of regional fat deposition are associated with metabolic syndrome in older adults.

Methods  A cross-sectional study was performed that included a random, population-based, volunteer sample of Medicare-eligible adults within the general communities of Pittsburgh, Pa, and Memphis, Tenn. The subjects consisted of 3035 men and women aged 70 to 79 years, of whom 41.7% were black. Metabolic syndrome was defined by Adult Treatment Panel III criteria, including serum triglyceride level, high-density lipoprotein cholesterol level, glucose level, blood pressure, and waist circumference. Visceral, subcutaneous abdominal, intermuscular, and subcutaneous thigh adipose tissue was measured by computed tomography.

Results  Visceral adipose tissue was associated with the metabolic syndrome in men who were of normal weight (odds ratio, 95% confidence interval: 2.1, 1.6-2.9), overweight (1.8, 1.5-2.1), and obese (1.2, 1.0-1.5), and in women who were of normal weight (3.3, 2.4-4.6), overweight (2.4, 2.0-3.0), and obese (1.7, 1.4-2.1), adjusting for race. Subcutaneous abdominal adipose tissue was associated with the metabolic syndrome only in normal-weight men (1.3, 1.1-1.7). Intermuscular adipose tissue was associated with the metabolic syndrome in normal-weight (2.3, 1.6-3.5) and overweight (1.2, 1.1-1.4) men. In contrast, subcutaneous thigh adipose tissue was inversely associated with the metabolic syndrome in obese men (0.9, 0.8-1.0) and women (0.9, 0.9-1.0).

Conclusion  In addition to general obesity, the distribution of body fat is independently associated with the metabolic syndrome in older men and women, particularly among those of normal body weight.

The metabolic syndrome is a complex disorder unifying dyslipidemia, insulin resistance, and hypertension. It is a primary risk factor for diabetes1 and cardiovascular disease.2 The overall prevalence of metabolic syndrome as defined by Adult Treatment Panel III guidelines3 in US adults is high (22%), and even higher among older men and women (42%).4 Physical inactivity, obesity, and diet composition all appear to be risk factors for the development of the metabolic syndrome.5 However, little is known concerning risk factors of the metabolic syndrome specific to older adults, who have a higher incidence of type 2 diabetes6,7 and cardiovascular disease8 than younger adults.

The growing prevalence of overweight and obesity9 are established risk factors for the metabolic syndrome. Patterns of fat distribution in middle-aged adults may confer additional risk for metabolic syndrome.10-12 Moreover, we have recently found in the Health, Aging, and Body Composition (Health ABC) Study that visceral abdominal adipose tissue (AT) and muscle-associated AT are related to insulin resistance in older subjects, particularly in those who are of normal weight, and that accumulation of these regional AT depots is characteristic of older people with type 2 diabetes and impaired glucose tolerance.13 However, it is not known whether these regional AT depots are associated with the metabolic syndrome in older adults. Furthermore, although waist circumference is included in the definition for metabolic syndrome as a surrogate for total abdominal AT, waist circumference does not distinguish visceral from subcutaneous abdominal AT. Patterns of regional fat distribution may be a more critical feature in older adults who may experience health decline–related weight loss composed of skeletal muscle and subcutaneous AT. Thus, normal-weight individuals may still be at risk for the metabolic syndrome and its consequences.

The Health ABC cohort includes approximately an equal proportion of older men and women and, importantly, an oversampling (41.7%) of blacks. We examined whether the specific criteria developed by the Adult Treatment Panel III to define the metabolic syndrome differ between older men and women and between blacks and whites. Using baseline data from this longitudinal study, we examined the primary hypothesis that visceral abdominal AT and AT infiltrating skeletal muscle are associated with the metabolic syndrome in older men and women, and also examined whether these associations differ by level of body weight or race.

Methods
Subjects

The study population consisted of men and women who participated in baseline evaluations in the Health ABC Study, a longitudinal investigation of 3075 nondisabled men and women aged 70 to 79 years, recruited primarily from a random sample of Medicare-eligible adults residing in designated ZIP code areas in Pittsburgh, Pa, and Memphis, Tenn, with an oversampling of blacks (41.7%). Detailed exclusion criteria for this cohort have been reported previously.13 Briefly, subjects were ineligible if they reported difficulty getting around without assistive devices, reported difficulty in performing basic activities of daily living, reported difficulty walking one-quarter mile or climbing 10 steps without resting, reported life-threatening cancers, or were participating in any research study involving medications or modification of eating or exercise habits. This analysis included 3035 subjects of this cohort who had complete data on body composition as well as criteria defining the metabolic syndrome. The institutions’ review boards approved the study, and written informed consent was obtained from each volunteer.

Criteria for metabolic syndrome

On the basis of recently defined criteria,3 persons were characterized as having the metabolic syndrome if they had at least 3 of the following conditions: (1) waist circumference greater than 102 cm in men and 88 cm in women; (2) serum triglyceride level of 150 mg/dL (1.7 mmol/L) or greater; (3) high-density lipoprotein (HDL) cholesterol level less than 40 mg/dL (1.0 mmol/L) in men and 50 mg/dL (1.3 mmol/L) in women; (4) blood pressure of 130/85 mm Hg or greater; and (5) serum glucose level of 110 mg/dL (6.1 mmol/L) or more. In addition, individuals who reported currently using antihypertensive or antidiabetic medication were counted as meeting the high blood pressure or glucose criterion, respectively.

Age of participants was determined to the nearest year. Standing height and weight were measured in stocking feet and with light clothing, and body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters, to characterize men and women who were of normal weight (BMI, <25.0), overweight (BMI, 25.0-29.9), and obese (BMI, >29.9). Total body fat was determined by means of dual-energy x-ray absorptiometry (QDR 4500; Hologic Inc, Waltham, Mass). Waist circumference was determined to the nearest centimeter. Blood was drawn after an overnight fast and analyzed for serum triglycerides, HDL cholesterol, and glucose determinations. Serum triglycerides and HDL cholesterol were measured on a chemistry analyzer (Vitros 950; Johnson & Johnson, Raritan, NJ). Plasma glucose was measured by means of an automated glucose oxidase reaction (YSI 2300 Glucose Analyzer; Yellow Springs Instruments, Yellow Springs, Ohio). A conventional mercury sphygmomanometer was used for the measurement of blood pressure. The participant rested quietly in a seated position with the back supported and feet flat on the ground for at least 5 minutes before the blood pressure measurement. Systolic and diastolic blood pressures were defined as the average of 2 measures.

Computed tomography of abdominal at

Computed tomographic (CT) images were acquired in Pittsburgh (9800 Advantage, General Electric Co, Milwaukee, Wis) and Memphis (Somatom Plus; Siemens, Iselin, NJ; or PQ 2000S; Picker, Cleveland, Ohio). For imaging, patients were placed in the supine position with the arms above the head and with legs lying flat on the table and toes directed toward the top of the gantry. To quantify abdominal AT, a single axial image at the L4-5 vertebral disk space was obtained as previously described.13 Visceral AT was separated from subcutaneous AT by manually drawing a line around the interior of the abdominal muscles along the fascial plane, which separates the 2 AT compartments. The intrareader and interreader variability (coefficient of variation) in visceral AT (n = 41) is less than 1%.

Ct of the midthigh

The CT acquisition scheme for the quantification of midthigh muscle and AT has been reported elsewhere in detail for this cohort.13 Briefly, a single, 10-mm-thick, axial image was obtained at the femoral midpoint, with the entire circumference of both thighs included in the field of view. Skeletal muscle, AT, and bone in the thigh were separated on the basis of their CT attenuation values.14 Mean muscle attenuation values were determined by averaging the CT number (pixel intensity) values of the regions outlined on the images. Lower attenuation values are compatible with greater fatty infiltration into tissue.15 Intermuscular AT was distinguished from the subcutaneous AT by manually drawing a line along the deep fascial plane surrounding the thigh muscles, ensuring that no bone density pixels were included in the muscle. The intrareader and interreader coefficient of variation in subcutaneous thigh AT (n = 30) is less than 1% and 4.3%, respectively.

For all calculations, CT numbers were defined on a Hounsfield unit scale where 0 equals the Hounsfield units of water and –1000 equals the Hounsfield units of air. All analysis programs were developed at the University of Colorado CT Scan Reading Center with the use of IDL (RSI Systems, Boulder).

Statistical analysis

Prevalence of metabolic syndrome, demographics, body composition, and regional AT variables were described, and the differences in continuous variables between those with and without metabolic syndrome were evaluated by either t tests or the Wilcoxon rank-sum test. Categorical differences between persons with and without the metabolic syndrome were evaluated with the χ2 test. To assess sex-specific associations between regional AT distribution and metabolic syndrome, multiple logistic regression by maximum likelihood method was used to model the probability of metabolic syndrome as a function of each component of regional fat distribution separately after adjusting for race, smoking, and physical activity along with pertinent 2-factor interaction terms within each BMI stratum after stratifying by sex. Point estimates and the associated confidence interval for all the independent variables were obtained, multicollinearity was tested by variance inflation factor, and the model evaluation was done by Hosmer-Lemeshow statistic. Since the results were similar for BMI and total body fat strata, we present findings for only BMI strata. Current smoking status and physical activity were assessed by questionnaire.16 All analyses were performed with SAS 6.12 for Windows (SAS Institute Inc, Cary, NC).

Results
Prevalence and characteristics of metabolic syndrome

The overall prevalence of metabolic syndrome in this older cohort was 39%, with women having higher rates than men (Table 1). Prevalence of metabolic syndrome was higher (P<.01) in obese (63% and 61%) than overweight (37% and 46%) and normal-weight (12% and 22%) men and women, respectively. Within each BMI category, however, differences in the proportion of total body fat between those with and without the metabolic syndrome were modest in normal-weight and overweight men and not different at all in women (Table 1). In fact, obese women without metabolic syndrome had a significantly higher proportion of body fat than obese women with metabolic syndrome. In addition, lower muscle mass in older subjects, known as sarcopenia, was not associated with the metabolic syndrome. Indeed, across all levels of BMI, those with metabolic syndrome had higher lean body mass than those without metabolic syndrome. This strongly suggests that factors other than generalized adiposity are associated with metabolic syndrome in older men and women.

We examined whether there were sex or racial differences in the prevalence of each of the 5 components that define the metabolic syndrome (Table 2). More women than men met the waist circumference criterion, and a higher proportion of white men than white women were positive for the blood glucose criterion. All other components ascribed to metabolic syndrome were similar in men and women. Among men, a higher proportion of whites than blacks met waist circumference, serum triglyceride, and HDL cholesterol criteria, whereas black men had higher rates of hypertension and abnormal blood glucose values (Table 2). Among women, whites had higher rates of abnormal serum triglyceride levels and lower HDL cholesterol levels, whereas the black women had higher rates of hypertension, abnormal blood glucose levels, and large waist circumference. Thus, lipid abnormalities were nearly 2-fold more common in whites, while blacks had a higher prevalence of blood glucose abnormalities and hypertension than whites.

Regional fat distribution in the metabolic syndrome

As shown in Table 1, although overweight and obesity were associated with a higher prevalence of the metabolic syndrome, differences in regional fat distribution were even more distinct (Table 3). Among those with metabolic syndrome, 77% of women and 44% of men met the waist circumference criterion. Waist circumference represents the combination of visceral and subcutaneous AT. When we examined whether these specific fat depots were associated with metabolic syndrome, we found in both men and women that differences in visceral AT were more prominent, being nearly 50% higher in both men and women with metabolic syndrome than in those without. Differences in subcutaneous AT were more modest, with men and women having 29% and 18% more subcutaneous AT, respectively, than their counterparts without metabolic syndrome. Moreover, the proportion of abdominal AT as visceral AT remained higher in both men (42% vs 39%) and women (31% vs 26%), even when waist circumference was omitted from the defining criteria for metabolic syndrome (Table 4). When the attributable risk for metabolic syndrome was examined for each of the predictors, higher visceral AT was consistent across all BMI groups for both men and women to have the highest attributable risk associated with metabolic syndrome. Higher visceral AT in men and women with metabolic syndrome was consistent for whites and blacks; thus, results were pooled for race for ease of interpretation.

Data presented in Table 3 indicate that differences in the amount of AT infiltrating skeletal muscle also distinguished those with metabolic syndrome to a greater degree than subcutaneous AT in the thigh. Intermuscular AT was 44% higher in men and 27% higher in women with metabolic syndrome. This is in contrast to the smaller differences in subcutaneous thigh AT for men (16%) or women (9%) with metabolic syndrome. Men and women with metabolic syndrome also had muscle with lower attenuation values, a marker of its higher fat infiltration15 (Table 3). Again, these results were similar for blacks and whites.

Metabolic syndrome in normal-weight, overweight, and obese men and women

Since the metabolic syndrome was not limited to obese subjects, we examined whether regional AT distribution was associated with metabolic syndrome separately in normal-weight, overweight, and obese subject, adjusting for race, smoking status, and physical activity. Higher visceral AT was associated with a significantly higher prevalence of metabolic syndrome, especially in normal-weight and overweight men and women but less so in the obese (Figure 1). The association between visceral AT and the metabolic syndrome was more evident at lower levels of total adiposity in both men and women independent of race (P<.001). Higher subcutaneous AT was significantly associated with metabolic syndrome in normal-weight and overweight but not in obese men. A positive interaction (P = .03) indicated that higher visceral AT and black race were both associated with the metabolic syndrome in obese women. No other significant interactions between race and the regional fat depots were observed in association with the metabolic syndrome. Similar results were obtained when stratifying by the proportion of body fat rather than by BMI.

Higher intermuscular AT was significantly associated with metabolic syndrome in normal-weight and overweight, but not in obese, men (Figure 2). There was an interaction (P<.001) between lower total body fat and higher intermuscular AT in predicting the metabolic syndrome in men independent of race. No significant associations were observed for intermuscular AT and metabolic syndrome in women. In contrast, having more subcutaneous thigh AT was associated with a lower prevalence of metabolic syndrome in obese men and in overweight and obese women.

We also examined in multiple logistic regression whether physical activity and diet modified the associations between regional fat distribution and metabolic syndrome. For men, neither smoking nor physical activity was related to metabolic syndrome in any of the BMI categories after taking into account regional fat distribution. In women, current smoking was not related to metabolic syndrome after accounting for VAT. Only in overweight women was physical inactivity associated with metabolic syndrome independent of all regional depots. Thus, adjusting results for smoking and physical activity did not appear to confound associations between regional fat depots and metabolic syndrome.

Comment

The overall prevalence of the metabolic syndrome in this older cohort was similar to that reported for older adults in the United States4 and nearly double that reported for middle-aged adults.4 This is, to our knowledge, the first large-scale investigation of predictors of the metabolic syndrome in older adults. With an oversampling of blacks, we were able to determine that, although the overall prevalence of metabolic syndrome was not different between blacks and whites, there were racial differences in the prevalence of specific criteria that define metabolic syndrome. Specifically, blacks had higher rates of hypertension and abnormal glucose metabolism, whereas whites had higher rates of dysregulated lipid metabolism. The development of metabolic syndrome involves an interaction of complex parameters including obesity, regional fat distribution, dietary habits, and physical inactivity,5 so it is not yet entirely clear how to interpret these racial differences. Nevertheless, this suggests that the cause of metabolic syndrome is different in blacks and whites.

The prevalence of metabolic syndrome, not surprisingly, was much higher among the obese. However, differences in generalized obesity by BMI or total body fat criteria in those with metabolic syndrome were at best modest. Obese women with the metabolic syndrome actually had a lower proportion of body fat than obese women without metabolic syndrome. Regional fat distribution, particularly visceral abdominal AT and intermuscular AT, clearly discriminated those with the metabolic syndrome, particularly among the nonobese. This implies that older men and women can have normal body weight, and even have relatively lower total body fat, but still have metabolic syndrome, due to the amount of AT located intra-abdominally or interspersed within the musculature. What makes this observation more remarkable is that these associations were much less robust or even nonexistent for subcutaneous AT. More subcutaneous AT in the thighs of obese men and women was actually associated with a lower prevalence of metabolic syndrome. 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.17 The relationship between altered fat distribution and metabolic syndrome is further complicated by the observation in our study that whites had higher visceral AT, while blacks had higher intermuscular AT. Albu et al18 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.19 Indeed, this suggests a complex and not fully understood relationship between metabolic syndrome, obesity, and abnormal fat distribution.

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.13 These findings are consistent with the hypothesized links among insulin resistance, type 2 diabetes, dyslipidemia, abdominal fat accumulation, and hypertension (the metabolic syndrome). These associations between regional fat deposition and metabolic dysregulation are also consistent with other previous findings in both middle-aged and older adults.20-25 The current data, however, are not without limitations. 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.26 It is also likely that diet composition is related to metabolic syndrome independent of obesity and physical activity.5 This cross-sectional analysis also does not allow us to determine whether body composition prospectively predicts future development of the syndrome. 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.27 Another emerging hypothesis is that the ability to store excess fat in AT is impaired, leading to the ectopic storage of fat into nonadipose tissue such as muscle and liver, and possibly the β cell.28 This excess accumulation of fat into these cells is associated with insulin resistance29-32 and metabolic syndrome.33 Our novel observation of higher subcutaneous AT in the thigh associated with lower prevalence of the metabolic syndrome is in accord with lipodystrophic, insulin-resistant humans34 and animals,35 which have an abundance of visceral and muscle-associated fat and concomitantly less subcutaneous fat. 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. Production of these “adipokines” may be higher in visceral AT.36 Further studies will be required to examine whether these secreted factors link either visceral or muscle AT to metabolic syndrome.

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, 809 North MUH, University of Pittsburgh Medical Center, Pittsburgh, PA 15213 (bgood@pitt.edu).

Accepted for Publication: November 2, 2004.

Financial Disclosure: None.

Funding/Support: This study was supported by grants N01-AG-6-2106, N01-AG-6-2102, and N01-AG-6-2103 from the National Institutes of Health, Bethesda, Md. Dr Goodpaster was supported by grant K01-AG-00851 from the National Institute on Aging, National Institutes of Health.

References
1.
Haffner  SValdez  RHazuda  HMitchell  BMorales  PStern  M Prospective analysis of the insulin resistance syndrome (syndrome X).  Diabetes 1992;41715- 722PubMedGoogle ScholarCrossref
2.
Isomaa  BAlmgren  PTuomi  T  et al.  Cardiovascular morbidity and mortality associated with the metabolic syndrome.  Diabetes Care 2001;24683- 689PubMedGoogle ScholarCrossref
3.
National Institutes of Health, Third Report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation and Treatment of High Cholesterol in Adults (Adult Treatment Panel III).  Bethesda, Md National Institutes of Health2001;NIH publication 01-3670
4.
Ford  EGiles  WDietz  W Prevalence of the metabolic syndrome among US adults.  JAMA 2002;287356- 359PubMedGoogle ScholarCrossref
5.
Grundy  SMHansen  BSmith  SC  Jr  et al.  Clinical management of metabolic syndrome: report of the American Heart Association/National Heart, Lung, and Blood Institute/American Diabetes Association conference on scientific issues related to management.  Circulation 2004;109551- 556PubMedGoogle ScholarCrossref
6.
Harris  MIFlegal  KMCowie  CC  et al.  Prevalence of diabetes, impaired fasting glucose, and impaired glucose tolerance in U.S. adults: the Third National Health and Nutrition Examination Survey, 1988-1994.  Diabetes Care 1998;21518- 524PubMedGoogle ScholarCrossref
7.
Resnick  HEHarris  MIBrock  DBHarris  TB American Diabetes Association diabetes diagnostic criteria, advancing age, and cardiovascular disease risk profiles: results from the Third National Health and Nutrition Examination Survey.  Diabetes Care 2000;23176- 180PubMedGoogle ScholarCrossref
8.
Wilson  PWEvans  JC Coronary artery disease prediction.  Am J Hypertens 1993;6309S- 313SPubMedGoogle ScholarCrossref
9.
Mokdad  AHBowman  BAFord  ESVinicor  FMarks  JSKoplan  JP The continuing epidemics of obesity and diabetes in the United States.  JAMA 2001;2861195- 1200PubMedGoogle ScholarCrossref
10.
Després  JNadeau  ATremblay  A  et al.  Role of deep abdominal fat in the association between regional adipose tissue distribution and glucose tolerance in obese women.  Diabetes 1989;38304- 309PubMedGoogle ScholarCrossref
11.
Goodpaster  BHThaete  FLSimoneau  J-AKelley  DE Subcutaneous abdominal fat and thigh muscle composition predict insulin sensitivity independently of visceral fat.  Diabetes 1997;461579- 1585PubMedGoogle ScholarCrossref
12.
Kelley  DEThaete  FLTroost  FHuwe  TGoodpaster  BH Subdivisions of subcutaneous abdominal adipose tissue and insulin resistance.  Am J Physiol Endocrinol Metab 2000;278E941- E948PubMedGoogle Scholar
13.
Goodpaster  BKrishnaswami  SResnick  H  et al.  Association between regional adipose tissue distribution and both type 2 diabetes and impaired glucose tolerance in elderly men and women.  Diabetes Care 2003;26372- 379PubMedGoogle ScholarCrossref
14.
Seidell  JCOosterlee  AThijssen  MA  et al.  Assessment of intra-abdominal and subcutaneous abdominal fat: relation between anthropometry and computed tomography.  Am J Clin Nutr 1987;457- 13PubMedGoogle Scholar
15.
Goodpaster  BHKelley  DEThaete  FLHe  JRoss  R Skeletal muscle attenuation determined by computed tomography is associated with skeletal muscle lipid content.  J Appl Physiol 2000;89104- 110PubMedGoogle Scholar
16.
Brach  JSSimonsick  EMKritchevsky  SYaffe  KNewman  AB The association between physical function and lifestyle activity and exercise in the Health, Aging and Body Composition Study.  J Am Geriatr Soc 2004;52502- 509PubMedGoogle ScholarCrossref
17.
Van Pelt  REEvans  EMSchechtman  KBEhsani  AAKohrt  WM Contributions of total and regional fat mass to risk for cardiovascular disease in older women.  Am J Physiol Endocrinol Metab 2002;282E1023- E1028PubMedGoogle Scholar
18.
Albu  JBMurphy  LFrager  DHJohnson  JAPi-Sunyer  FX Visceral fat and race-dependent health risks in obese nondiabetic premenopausal women.  Diabetes 1997;46456- 462PubMedGoogle ScholarCrossref
19.
Mandavilli  ACyranoski  D Asia's big problem.  Nat Med 2004;10325- 327PubMedGoogle ScholarCrossref
20.
DeNino  WFTchernof  ADionne  IJ  et al.  Contribution of abdominal adiposity to age-related differences in insulin sensitivity and plasma lipids in healthy nonobese women.  Diabetes Care 2001;24925- 932PubMedGoogle ScholarCrossref
21.
Després  J-P Abdominal obesity as important component of insulin resistance syndrome.  Nutrition 1993;9452- 459PubMedGoogle Scholar
22.
Gabriely  IMa  XHYang  XM  et al.  Removal of visceral fat prevents insulin resistance and glucose intolerance of aging: an adipokine-mediated process?  Diabetes 2002;512951- 2958PubMedGoogle ScholarCrossref
23.
Haffner  SMKarhapaa  PMykkanen  LLaakso  M Insulin resistance, body fat distribution, and sex hormones in men.  Diabetes 1994;43212- 219PubMedGoogle ScholarCrossref
24.
Kohrt  WMKirwan  JPStaten  MABourey  REKing  DSHolloszy  JO Insulin resistance in aging is related to abdominal obesity.  Diabetes 1993;42273- 281PubMedGoogle ScholarCrossref
25.
Wajchenberg  BL Subcutaneous and visceral adipose tissue: their relation to the metabolic syndrome.  Endocr Rev 2000;21697- 738PubMedGoogle ScholarCrossref
26.
Lakka  TALaaksonen  DELakka  HM  et al.  Sedentary lifestyle, poor cardiorespiratory fitness, and the metabolic syndrome.  Med Sci Sports Exerc 2003;351279- 1286PubMedGoogle ScholarCrossref
27.
Bergman  RNVan Citters  GWMittelman  SD  et al.  Central role of the adipocyte in the metabolic syndrome.  J Investig Med 2001;49119- 126PubMedGoogle ScholarCrossref
28.
Ravussin  ESmith  SR Increased fat intake, impaired fat oxidation, and failure of fat cell proliferation result in ectopic fat storage, insulin resistance, and type 2 diabetes mellitus.  Ann N Y Acad Sci 2002;967363- 378PubMedGoogle ScholarCrossref
29.
Greco  AVMingrone  GGiancaterini  A  et al.  Insulin resistance in morbid obesity: reversal with intramyocellular fat depletion.  Diabetes 2002;51144- 151PubMedGoogle ScholarCrossref
30.
Krssak  MFalk Petersen  KDresner  A  et al.  Intramyocellular lipid concentrations are correlated with insulin sensitivity in humans: a 1H NMR spectroscopy study.  Diabetologia 1999;42113- 115PubMedGoogle ScholarCrossref
31.
Perseghin  GScifo  PDeCobelli  F  et al.  Intramyocellular triglyceride content is a determinant of in vivo insulin resistance in humans: a 1H-13C nuclear magnetic resonance spectroscopy assessment in offspring of type 2 diabetic patients.  Diabetes 1999;481600- 1606PubMedGoogle ScholarCrossref
32.
Yu  CChen  YCline  GW  et al.  Mechanism by which fatty acids inhibit insulin activation of insulin receptor substrate-1 (IRS-1)-associated phosphatidylinositol 3-kinase activity in muscle.  J Biol Chem 2002;27750230- 50236PubMedGoogle ScholarCrossref
33.
Marchesini  GBrizi  MBianchi  G  et al.  Nonalcoholic fatty liver disease: a feature of the metabolic syndrome.  Diabetes 2001;501844- 1850PubMedGoogle ScholarCrossref
34.
Oral  EASimha  VRuiz  E  et al.  Leptin-replacement therapy for lipodystrophy.  N Engl J Med 2002;346570- 578PubMedGoogle ScholarCrossref
35.
Reitman  MLMason  MMMoitra  J  et al.  Transgenic mice lacking white fat: models for understanding human lipoatrophic diabetes.  Ann N Y Acad Sci 1999;892289- 296PubMedGoogle ScholarCrossref
36.
Fried  SKBunkin  DAGreenberg  AS Omental and subcutaneous adipose tissues of obese subjects release interleukin-6: depot difference and regulation by glucocorticoid.  J Clin Endocrinol Metab 1998;83847- 850PubMedGoogle Scholar
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