fat distribution and health in obesity

491

Fat Distribution and Health in Obesity

JEANINE B. ALBU,a ALBERT J. KOVERA, AND JULIA A. JOHNSON

Obesity Research Center, St. Luke’s-Roosevelt Hospital Center,New York, New York 10025,USA

ABSTRACT: Although independent associations of visceral fat with the insulinresistance syndrome were previously reported in obese women, the importanceof truncal subcutaneous fat in this syndrome is controversial. The method bywhich the various fat depots are measured may be the reason for the underly-ing controversy. In the past five years, we have used various methods to mea-sure visceral versus subcutaneous fat distribution in Caucasian (C) andAfrican- American (AA) women and have related it to insulin sensitivity (SI)and to blood lipids, particularly fasting serum triglyceride levels (TG). Elevat-ed TG levels in obese women were best predicted by an increased amount ofvisceral fat, whereas the amounts of truncal and peripheral subcutaneous fatdid not have an impact on them. These results were confirmed, regardless ofthe method used to measure the fat depots. Insulin resistance (low SI) in obesewomen was predicted by both an increase of visceral and of upper-body (trun-cal) subcutaneous fat. However, measurements of the entire visceral and trun-cal subcutaneous fat volumes may be needed to confirm this latter association.

INTRODUCTION

Previous reports demonstrated that women with a greater proportion of upper-body (truncal/abdominal) fat tend to be more insulin resistant, hyperinsulinemic,glucose intolerant, and dyslipidemic than women with a greater proportion of lower-body (gluteal/femoral) fat.1–4 When imaging techniques, such as magnetic reso-nance imaging (MRI) and computed tomography (CT), were used, visceral fat accu-mulation was found to be specifically associated with the metabolic alterations ofobesity, both in men and women (TABLE 1). By contrast, the contribution of subcu-taneous fat patterning (upper-body vs. lower-body, or truncal vs. peripheral) to themetabolic disturbances of upper-body obesity still is controversial. Population-based studies demonstrated trends toward greater accumulation of truncal subcuta-neous fat, measured as the sum of truncal skinfolds, in hyperglycemic and hyperin-sulinemic people compared to normals.2–4 Moreover, women with a greaterproportion of upper-body (truncal/abdominal) fat have increased systemic free fattyacid (FFA) flux and higher rates of lipolysis in upper-body subcutaneous adipocytesthan do women with a greater proportion of lower-body (gluteal/femoral) fat.5–6

Still, associations between the amount of subcutaneous fat on the trunk and metabol-ic disturbances, specifically insulin sensitivity, have been reported only in men,7–9

aAddress for correspondence: Jeanine B. Albu, M.D., Obesity Research Center, St. Luke’s-Roosevelt Hospital Center, 1111 Amsterdam Avenue, New York, NY 10025. Voice: 212-523-4183; fax: 212-523-4830.

[email protected]

492 ANNALS NEW YORK ACADEMY OF SCIENCES

and these results were inconsistent.10 We measured the distribution of visceral ver-sus subcutaneous fat in Caucasian (C) and African-American (AA) women by vari-ous techniques and examined the relationship of adipose tissue distribution to insulinsensitivity (SI) and to blood lipids, particularly fasting serum triglyceride levels(TG). The findings are summarized here.

METHODS

In this paper, data from two studies are presented.

Participants/Study I

In the first study,11–12 we recruited 20- to 49-year-old Caucasian or African-American healthy premenopausal women with a body mass index (BMI) of between27 and 45 kg/m2. They were eligible if all four grandparents were of either Cauca-sian or African ancestry, by self-report. The AA women had the same age and BMIrange as the Caucasian women; then, across the entire range of BMI, AA womenwere chosen who had waist circumferences similar to those of the C women. The fol-lowing measurements were determined:

TABLE 1. Independent associations between visceral adipose tissue area and themetabolic syndrome after adjusting for overall adiposity

Study Subjects Independently Associated Variables

Sparrow19 41 lean and obese men 2-h glucose value

Fujioka20 46 obese men and womenglucose area, TG, LDL-cholesterol

Despres21 52 obese women glucose area

Seidell22 23 lean and obese men glucose area, insulin area

Zamboni23 57 obese women glucose area, insulin, TG, SBP

Zamboni24 63 obese women glucose, insulin, TG, LDL-cholesterol, SBP, DBP

Pouliot25 58 obese men fasting insulin, glucose and insulin area, HDL-cholesterol, HDL2-cholesterol

Bonora26 18 obese women insulin resistance (by clamp)

Fujimoto27 115 women fasting insulin, glucose and insulin area, TG, HDL-cholesterol, LDL-cholesterol, apoB, apoA1

115 men fasting insulin, glucose and insulin area, C-peptide, HDL-cholesterol, apoB

Caprio28 14 obese girls insulin resistance (by clamp)

Cefalu29 60 lean and obese men and women

insulin resistance (by minimal model)

Chowdhury30 20 lean and obese men insulin, TG

Ross31 40 obese women glucose and insulin area, fasting insulin

ABBREVIATIONS: TG = triglycerides, SBP = systolic blood pressure, DBP = diastolic bloodpressure.

493ALBU et al.: FAT DISTRIBUTION AND HEALTH IN OBESITY

Anthropometric and Skinfolds Measurements

Minimum waist circumference (minimum circumference between the lower-ribmargin and the iliac crest, midwaist) and maximum hip circumference (with womenviewed from the front) were measured while the women were standing with theirheels together. Skinfold thickness was measured to ± 2 mm with a Lange caliper(Cambridge Scientific Industries, Cambridge, MD) at five sites on the thorax (sub-scapular, midaxillary, suprailiac, umbilicus, and abdomen [between umbilicus andpubic rami]) and at four sites on the extremities (triceps, biceps, thigh and calf) ac-cording to Harrison et al.13 Calculations of the sums of truncal (TrSUM) and periph-eral (PerSUM) skinfolds were available in 38 women.

Hydrodensitometry

Total body fat mass (FM) and fat-free mass (FFM = weight [kg] − FM) were de-termined by hydrodensitometry using the Siri equation, and different densities of theFFM were used for AA (1.106 g/cm3) and C (1.100 g/cm3) women.14

MRI Measurements

The areas of visceral (VAT), subcutaneous (AbdSAT), and total (TAT) adiposetissue at midwaist, and the area of subcutaneous adipose tissue at the greater tro-chanter (HipSAT), were measured by MRI (scans by G.E. System Signa Advantage5.3 scanner, G.E. Medical Systems, Milwaukee, WI). Four 1.5-mm-thick axial im-ages, 5 mm apart, were obtained at each of two locations, above and below the mid-waist (L2-L3 spine level) and above and below the greater trochanter. The imageswere analyzed as described previously11 on a G.E. independent display console, us-ing an “automatic boundary detection program” (5.3 software, G.E. Medical Sys-tems), by an image-masking technique. The reported values represent the average ofthree readings for each image. The intraclass correlation for repeated VAT determi-nations in our laboratory is 0.99.

DXA Measurements

Dual X-ray absorptiometry (DXA) (Lunar Corporation, Madison, WI, softwareversion 3.6) measurements of central fat mass in the abdomen (AbdFMDXA, all tis-sue below L1-L2 and above L4-L5, as described previously15) were obtained fromwhole body scans. Using calculations similar to those of Jensen,16 the absolute quan-tities of visceral and subcutaneous abdominal fat masses (VFM and AbdScFM) werecalculated from the total central abdominal fat mass (AbdFMDXA) measured byDXA, based on the relative proportions of visceral and subcutaneous fat areas (VAT,SAT and TAT) as measured by MRI, respectively:

VFM (g) = [VAT (cm2)]/[TAT (cm2)] × AbdFMDXA (g),

AbdScFM (g) = [AbdSAT (cm2)/TAT (cm2)] × AbdFMDXA (g).

Frequently Sampled Intravenous Glucose Tolerance (FSIGT)

For all women, this measurement was made within 10 days of the onset of themenstrual cycle. Glucose (0.3 g/kg; 50% dextrose injection; Abbott, North Chicago,IL) was administered intravenously at time 0, followed by an injection of tolbuta-


mide (Orinase Diagnostic, Upjohn, Kalamazoo, MI) at 20 minutes. Plasma glucoseand insulin were measured on frequently collected samples (total of 30) over 180min, and the insulin sensitivity index (SI) was calculated from them with the nonlin-ear mathematical model of glucose disappearance (MINMOD program, copyrightR.N. Bergman, 1986).

Fasting Serum Triglycerides

Fasting blood samples were taken to measure total triglyceride level (TG) (assaykit 210, Diagnostic Chemicals, Monroe, CT).

Participants/Study II

In the second study, we recruited 89 healthy AA and C women volunteers with awide range of BMI and age. Fasting serum triglycerides were measured (as describedabove), and regional fat depots were assessed by the whole body MRI technique.

Regional Fat by the Whole Body MRI Technique

The entire VAT and AbdSAT volumes were measured by MRI while the womenwere lying supine on their abdomen, with arms elevated above the head, as describedby Ross et al.17 The entire body was visualized on a scout coronal image (scans byG.E. System Signa Advantage 5.3 Scanner, G.E. Medical Systems, Milwaukee, WI),and the axial level of L4-L5 was identified. Scans were obtained using contiguousaxial 10-mm slices below this level to the toes, and above this level to the tip of thefingers (usually about 40–50 images for women of average height). Using the scoutwhole body coronal image, slices included in the subcutaneous adipose tissue (AT)of the trunk (from the neck to L4-L5), arms (from the neck level to the tip of the fin-gers), and lower body (from L4-L5 to the toes) were identified. The images were an-alyzed by a single investigator using “sliceOmatic” 3.1 2D for the SGI Workstation(Tomovision, Montreal, Quebec, CA). The AT area was measured in each image(slice) by an image masking technique, and its volume between two contiguous slic-es was then extrapolated from the area measurements. AT weight was obtained as-suming a density of 0.9196. The measurements of contiguous fat masses were placedin a data file under a designated number, and total intraperitoneal (visceral, VFM)and extraperitoneal (subcutaneous, ScFM) fat masses were calculated. ScFM alsowas calculated separately for the trunk, arms, and lower body.

RESULTS

Measurements of Regional Fat Area: Relationships with SI and TG

Fifty women had measurements taken of AbdSAT and VAT areas. Age, BMI, orbody composition did not differ between the AA and C groups, as discussed before(TABLE 2). AA women had lower hip circumference and higher WHR than the Cwomen. The relationship between AbdSAT and VAT areas and SI did not differ be-tween the AA and C groups (FIGS. 1 and 2), and the same was true for TG (notshown). Therefore, the groups were combined for multiple regression analysis. BothVAT and AbdSAT were negatively correlated with SI (TABLE 3), but these relation-


ships were not significant after adjusting for total fat mass (FM). In multiple regres-sion analysis, FM was a better predictor of low SI than either VAT or AbdSAT (partialr = −0.45, p < 0.01). VAT was the only independent predictor of TG (TABLE 3).

Thirty-nine women had measurements taken of HipSAT, from which the ratio ofAbdSAT to HipSAT area (AHR) also was calculated. The measurements of the re-gional subcutaneous fat area (AbdSAT, HipSAT, and AHR) did not differ significant-ly between the AA and C groups (396 ± 100 vs. 417 ± 105 cm2, 517 ± 79 vs. 563 ±106 cm2, and 0.76 ± 0.15 vs. 0.74 ± 0.15, respectively, mean ± SD). TABLE 4 showsthe univariate relationships of AbdSAT, HipSAT, and AHR with SI and TG. In re-gression analysis, none of the relationships had slopes that were significantly differ-ent between the two groups. Neither AbdSAT nor HipSAT predicted SI or TGindependently of FM (not shown).

TABLE 2. Participants’ characteristicsa

Caucasian Women African-American Women

Mean ± SD Range Mean ± SD Range

Age 34 ± 1 26 – 44 36 ± 1 26 – 49

BMI 36 ± 1 28 – 44 36 ± 1 29 – 42

Percent fat 45 ± 1 37 – 52 46 ± 1 35 – 56

Fat mass (kg) 44 ± 2 26 – 60 45 ± 2 27 – 60

Fat-free mass (kg) 53 ± 1 38 – 66 52 ± 1 40 – 65

Waist (cm) 101 ± 3 78 – 126 101 ± 2 85 – 115

Hip (cm) 125 ± 2* 105 – 140 119 ± 2* 103 – 134

WHR 0.81 ± 0.01* 0.7 – 0.9 0.85 ± 0.01* 0.69 – 0.95

aAdapted from Albu et al.11

ABBREVIATIONS: BMI = body mass index; WHR = waist-to-hip ratio.* p < 0.05.

TABLE 3. Correlation of insulin sensitivity and triglyceride level (TG) withmeasurements of regional adipose tissue before and after adjusting for fat mass (FM)a

DependentVariables

IndependentVariables

Univariate CorrelationPartial Correlation after

Adjusting for FM

r p r p

SI VAT -0.50 <0.01 −0.24 NS

AbdSAT -0.39 <0.05 0.15 NS

TG VAT 0.62 <0.01 0.56 < 0.05

AbdSAT 0.17 NS 0.01 NS

aAdapted from Albu et al.11

ABBREVIATIONS: FM = fat mass; SI = insulin sensitivity; VAT = visceral adipose tissue; Abd-SAT = abdominal subcutaneous adipose tissue; TG = triglyceride level.


Measurements of Regional Fat Mass by DXA and MRI and Sum of Skinfolds:Relationships with SI and TG

Thirty-eight women had complete measurements of the sum of skinfolds, and 26women also had complete DXA measurements. TrSUM, PerSUM, AbdFMDXA,and the calculated values for VFM and AbdScFM did not differ between the AA andC groups. TABLE 5 shows the univariate and partial (controlling for FM) correlationcoefficients between these measurements and SI. FM, AbdFMDXA, VFM, TrSUM,and PerSUM were negatively correlated with SI (all p ≤ 0.022), whereas AbdScFMwas not correlated (p = 0.23). After controlling for FM, only VFM (p = 0.035) and

FIGURE 2. The relationship between abdominal subcutaneous adipose tissue area(AbdSAT) and SI in African-American (�) and Caucasian (�) women. There are no signif-icant differences between the slopes of the regression lines.

FIGURE 1. The relationship between visceral adipose tissue area (VAT) and SI inAfrican-American (�) and Caucasian (�) women. There are no significant differences be-tween the slopes of the regression lines.


TrSUM (p = 0.002) were significantly related to SI. In multiple regression analysiswith backward elimination, only the relation between SI and TrSUM remained sig-nificant after modeling in FM, VFM, and PerSUM (p < 0.001).

A similar analysis was performed for TG (TABLE 6). FM, AbdFMDXA, VFM, andTrSUM were positively correlated with TG (all p ≤ 0.011), whereas AbdScFM wasnot correlated with it (p = 0.38). After controlling for FM, only AbdFMDXA(p = 0.013) and VFM (p < 0.001) were significantly related to TG. In multiple re-gression analysis with backward elimination, only the relationship to VFM remainedsignificant after modeling in FM, TrSUM, and PerSUM (p < 0.001).

TABLE 4. Univariate correlations of insulin sensitivity and triglyceride level withmeasurements of subcutaneous adipose tissue area

All womenCaucasian

womenAfrican-American

Women

r P r P r P

SI

AbdSAT (cm2) -0.47 < 0.05 −0.36 NS -0.61 < 0.01

HipSAT (cm2) −0.30 NS −0.29 NS −0.38 NS

AHR (n = 39) -0.37 < 0.05 −0.19 NS -0.56 < 0.05

TG

AbdSAT (cm2) 0.20 NS 0.32 NS 0.02 NS

HipSAT (cm2) −0.06 NS −0.12 NS −0.19 NS

AHR (n = 39) 0.32 < 0.05 0.48 < 0.05 0.23 NS

ABBREVIATIONS: SI = insulin sensitivity;AbdSAT = abdominal subcutaneous adipose tissuearea at midwaist; HipSAT = subcutaneous adipose tissue area at greater trochanter; AHR = Abd-SAT/HipSAT ratio; TG = triglyceride level.

TABLE 5. Univariate and partial (controlling for total body fat mass) correlationsbetween selected measurements of body composition and insulin sensitivitya

n


Adjusting for FM

r P r P

FM (kg) 38 –0.56 < 0.001 — —

TrSUM (mm) 38 –0.62 < 0.001 –0.41 < 0.05

PerSUM (mm) 38 –0.37 < 0.05 −0.11 NS

AbdFMDXA 26 –0.49 < 0.05 −0.26 NS

VFM (g) 26 –0.51 < 0.01 –0.42 < 0.05

AbdScFM (g) 26 −0.25 NS 0.014 NS

aAdapted from Marcus et al.12

ABBREVIATIONS: FM = total body fat mass; TrSUM = sum of trunk skinfolds; PerSUM = sumof peripheral skinfolds; AbdFMDXA = abdominal fat mass by DXA; VFM = visceral fat mass;AbdScFM = abdominal subcutaneous fat mass.


Measurements of Regional Fat Mass by Whole Body MRI: Relationships with TG

The 89 healthy C and AA women who underwent whole body MRI measure-ments had a wide range of BMI (mean ± SD, 24 ± 4 kg/m2, range 16–37) and age(mean ± SD, 45 ± 17, range 18–88). The relationships between regional fat measure-ments and TG did not differ between the two racial groups (FIG. 3). TG was positive-ly correlated with age and BMI, as well as with the regional fat masses—that is,VFM, ScFM, and the components of the subcutaneous fat, truncal subcutaneous fat,arm fat, and lower-body fat (p values ranging from <0.05 to <0.001). In multiple re-gression analysis, none of the subcutaneous fat masses, nor the subcutaneous fat dis-tribution (ratio of upper- vs. lower-body subcutaneous fat) predicted TGindependently of BMI and/or age. Only VFM predicted TG independently of BMIand age (p < 0.001).

TABLE 6. Univariate and partial (controlling for total body fat mass) correlationsbetween selected measurements of body composition and serum triglyceridesa

n


Adjusting for FM

r P r P

FM (kg) 38 0.41 < 0.05 — —

TrSUM (mm) 38 0.49 < 0.01 0.32 < 0.06

PerSUM (mm) 38 0.30 NS 0.11 NS

AbdFMDXA 26 0.56 < 0.01 0.49 < 0.05

VFM (g) 26 0.76 < 0.01 0.73 < 0.001

AbdScFM (g) 26 0.18 NS 0.01 NS

aAdapted from Marcus et al.12

ABBREVIATIONS: FM = total body fat mass; TrSUM = sum of trunk skinfolds; PerSUM = sumof peripheral skinfolds; AbdFMDXA = abdominal fat mass by DXA; VFM = visceral fat mass;AbdScFM = abdominal subcutaneous fat mass.

FIGURE 3. The relationship between visceral fat mass (VFM) and triglyceride (TG)levels in obese women. There are no significant differences between African-American andCaucasian women in the slopes of the regression lines.


DISCUSSION

We found that elevated TG levels in obese women were best related to an in-creased amount of visceral fat, whereas the amounts of truncal or peripheral subcu-taneous fat did not have an impact on these levels. These results were confirmed,regardless of the method used to measure the fat depots. On the other hand, insulinresistance (low SI) in obese women was best related to an overall increase in fatmass, or to an increase in truncal subcutaneous fat mass measured by the sum oftruncal skinfolds. Moreover, insulin resistance was predicted independently by in-creased visceral fat mass, as well as by an increase in truncal subcutaneous fat mass.Measurements of the abdominal subcutaneous fat mass were not sufficient to showthe relationship with insulin resistance in obese women. The total central abdominalfat mass measured by DXA (AbdFMDXA) was a good predictor of elevated TG lev-els, independently of total fat mass. However, AbdFMDXA was not as good a predic-tor of insulin resistance as was visceral fat mass (VFM), a calculated value ofvisceral fat using direct measurements by MRI.

Other previous studies using DXA methodology found strong relationships be-tween measurements of total abdominal fat mass by DXA and insulin resistance inlean and mildly obese women,15 as well as in more severely obese women.18 How-ever, in these studies visceral versus subcutaneous abdominal fat mass were notidentified separately. When we separated the two depots in obese women using theirrelative ratio by MRI, we found that only VFM, but not AbdScFM, was significantlyrelated to insulin resistance, independent of total body fat mass. Therefore, measure-ments of the entire truncal subcutaneous fat were needed to confirm an associationwith insulin resistance in obese women. This requirement may reflect the heteroge-neity of the subcutaneous fat on the trunk and, perhaps, an inherent association be-tween certain subcutaneous fat depots and visceral fat accumulation in women thatis largely independent of the quantity of abdominal subcutaneous adipose tissue.Whether there is in women lipolytic heterogeneity among truncal subcutaneous ad-ipocytes—that is, those in the upper trunk versus those in the abdominal region—isnot known. Indeed, accumulation of subcutaneous fat specifically on the chest andsubscapular regions has been associated with impaired glucose tolerance in Japa-nese-American women.4

Taken together, our results indicate that the health risks of upper body fat distri-bution in obese women may reflect the specific contributions of different compart-ments of central adipose tissue. Insulin sensitivity appears to be a function of bothvisceral and subcutaneous fat on the trunk, whereas serum triglyceride levels appearlargely dependent on the accumulation of visceral fat.

REFERENCES

1. KISSEBAH, A.H. & A.N. PEIRIS. 1989. Biology of regional body fat distribution: relation-ship to non-insulin-dependent diabetes mellitus. Diabetes Metab. Rev. 5: 83–109.

2. FELDMAN, R., A.J. SENSER & A.B. SIEGELAUB. 1969. Differences in diabetic and nondi-abetic fat distribution patterns by skinfold measurements. Diabetes 18: 478–486.

3. FREEDMAN, D.S., D.F. WILLIAMSON, J.B. CROFT et al. 1995. Relation of body fat distribu-tion to ischemic heart disease. The National Health and Nutrition Examination SurveyI (NHANES I); Epidemiologic Follow-up Study. Am. J. Epidemiol. 142: 53–63.


4. FUJIMOTO, W.Y., R.W. BERGSTROM, E.J. BOYKO et al. 1995. Susceptibility to develop-ment of central adiposity among populations. Obesity Res. 3: 179S–186S.

5. MARTIN, M.L. & M.D. JENSEN. 1991. Effects of body fat distribution on regional lipol-ysis in obesity. J. Clin. Invest. 88: 609–613.

6. DOWLING, H.J., S.K. FRIED & F.X. PI-SUNYER. 1995. Insulin resistance in adipocytes ofobese women: effects of body fat distribution and race. Metabolism 44: 987–995.

7. ABATE, N., A. GARG, R.M. PESHOCK et al. 1995. Relationship of generalized andregional adiposity to insulin sensitivity in men. J. Clin. Invest. 96: 88–98.

8. ABATE, N., A. GARG, R.M. PESHOCK et al. 1996. Relationship of generalized and regionaladiposity to insulin sensitivity in men with NIDDM. Diabetes 45: 1684–1693.

9. GOODPASTER, B.H., F.L. THAETE, J.-A. SIMONEAU et al. 1997. Subcutaneous abdominalfat and thigh muscle composition predict insulin sensitivity independently of visceralfat. Diabetes 46: 1579–1585.

10. BANERJI, M.A., R.L. CHAIKEN, D. GORDON et al. 1995. Does intra-abdominal adiposetissue in black men determine whether NIDDM is insulin-resistant or insulin-sensi-tive? Diabetes 44: 141–146.

11. ALBU, J.B., L. MURPHY, D.H. FRAGER et al. 1997. Visceral fat and race-dependenthealth risks in obese nondiabetic premenopausal women. Diabetes 46: 456–462.

12. MARCUS, A.M., L. MURPHY, F.X. PI-SUNYER et al. 1999. Insulin sensitivity and serumtriglyceride level in obese white and black women: relationship to visceral and trun-cal subcutaneous fat. Metabolism 48: 194–199.

13. HARRISON, G.G., E.R. BUSKIRK, L.J.E. CARTER et al. 1988. Skinfold thicknesses andmeasurement technique. In Anthropometric Standardization Reference Manual. T.G.Lohman, A.F. Roche & R. Martorell, Eds.: 55–70. Human Kinetics Books. Cham-paign, IL.

14. ORTIZ, O., M. RUSSELL, T.L. DALEY et al. 1992. Differences in skeletal muscle andbone mineral mass between black and white females and their relevance to estimatesof body composition. Am. J. Clin. Nutr. 55: 8–13.

15. CAREY, D.C., A.B. JENKINS, L.V. CAMPBELL et al. 1996. Abdominal fat and insulinresistance in normal and overweight women: direct measurements reveal a strongrelationship in subjects at both low and high risk for NIDDM. Diabetes 45: 633–638.

16. JENSEN, M.D., J.A. KANALEY, J.E. REED et al. 1995. Measurement of abdominal andvisceral fat with computed tomography and dual X-ray absorptiometry. Am. J. Clin.Nutr. 61: 274–278.

17. ROSS, R., L. LEGER, D. MORRIS et al. 1992. Quantification of adipose tissue by MRI:relationship with anthropometric variables. J. Appl. Physiol. 72: 787–795.

18. PEDERSEN, S.B., J.D. BORGLUM, O. SCHMITZ et al. 1993. Abdominal obesity is associ-ated with insulin resistance and reduced glycogen synthase activity in skeletal mus-cle. Metabolism 42: 998–1005.

19. SPARROW, D., G.A. BORKAN, S.G. GERZOF, C. WISNIEWSKI & C.K. SILBERT. 1986. Rela-tionship of fat distribution to glucose tolerance: results of computed tomography inmale participants of the Normative Aging Study. Diabetes 35: 411–415.

20. FUJIOKA, S., Y. MATSUZAWA, K. TOKUNAGA & S. TARUI. 1987. Contribution of intra-abdominal fat accumulation to the impairment of glucose and lipid metabolism inhuman obesity. Metabolism 36: 54–59.

21. DESPRÉS, J-P., A. NADEAU, A. TREMBLAY, M. FERLAND, S. MOORJANI, P.J. LUPIEN, G.THÉRIAULT, S. PINAULT & C. BOUCHARD. 1989. Role of deep abdominal fat in theassociation between regional adipose tissue distribution and glucose tolerance inobese women. Diabetes 38: 304–309.

22. SEIDELL, J.C., P. BJÖRNTORP, L. SJÖSTRÖM, H. KVIST & R. SANNERSTEDT. 1990. Vis-ceral fat accumulation in men is positively associated with insulin, glucose, and C-peptide levels, but negatively with testosterone levels. Metabolism 39: 897–901.

23. ZAMBONI, M., F. ARMELLINI, M.P. MILANI, M. DE MARCHI, T. TODESCO, R. ROBBI, I.A.BERGAMI-ANDREIS & O. BOSELLO. 1992. Body fat distribution in pre- and post-meno-pausal women: metabolic and anthropometric variables and their inter-relationships.Int. J. Obes. 16: 495–504.

24. ZAMBONI, M., F. ARMELLINI M.P. MILANI, T. TODESCO, M. DE MARCHI, R. ROBBI, G.MONTRESOR, A.I.A. BERGAMO & O. BOSELLO. 1992. Evaluation of regional body fat


distribution: comparison between W/H ratio and computed tomography in obesewomen. J. Intern. Med. 232: 341–347.

25. POULIOT, M-C., J.-P. DESPRÉS, A. NADEAU, S. MOORJANI, D. PRUD’HOMME, P.J. LUPLEN,A. TREMBLAY & C. BOUCHARD. 1992. Visceral obesity in men: associations with glu-cose tolerance, plasma insulin, and lipoprotein levels. Diabetes 41: 826–834.

26. BONORA, E., S. DEL PRATO, R.C. BONADONNA, G. GULLI, A. SOLINI, M.L. SHANK, A.A.GHIATAS, J.L. LANCASTER R.F. KILCOYNE, A.M. ALYASSIN & R.A. DEFRONZO. 1992.Total body fat content and fat topography are associated differently with in vivo glu-cose metabolism in nonobese and obese nondiabetic women. Diabetes 41: 1151–1159.

27. FUJIMOTO, W.Y., R.W. BERGSTROM, D.L. LEONETTI, L.L. NEWELL-MORRIS, W.P. SHU-MAN & P.W. WAHL. 1994. Metabolic and adipose risk factors for NIDDM and coro-nary disease in third-generation Japanese-American men and women with impairedglucose tolerance. Diabetologia 37: 524–532.

28. CAPRIO, S., L.D. HYMAN, C. LIMB, S. MCCARTHY, R. LANGE, R.S. SHERWIN, G. SHUL-MAN & W.V. TAMBORLANE. 1995. Central adiposity and its metabolic correlates inobese adolescent girls. Am. J. Physiol. 269: E118–E126.

29. CEFALU, W.T., Z.Q. WANG, S. WERBEL, A. BELL-FARROW, J.R. CROUSE, W.H. HINSON,J.G. TERRY & R. ANDERSON. 1995. Contribution of visceral fat mass to the insulinresistance of aging. Metabolism 44: 954–959.

30. CHOWDHURY, B., H. LANTZ & L. SJÖSTRÖM. 1996. Computed tomography-determinedbody composition in relation to cardiovascular risk factors in Indian and matchedSwedish males. Metabolism 45: 634–644.

31. ROSS, R., L. FORTIER & R. HUDSON. 1996. Separate associations between visceral andsubcutaneous adipose tissue distribution, insulin and glucose levels in obese women.Diabetes Care 19: 1404–1411.

fat distribution and health in obesity

Documents