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From the Clinical Research Centers |
Divisions of Clinical Pharmacology and Metabolic Research (M.B., R.D.S., A.T., D.E.M., E.G.-R., E.T.P.) and Cardiology (M.B.), Department of Medicine, University of Vermont College of Medicine, Burlington, Vermont 05405
Address all correspondence and requests for reprints to: Eric T. Poehlman, Ph.D., Given Building, B-247, Department of Medicine, University of Vermont, Burlington, Vermont 05405. E-mail: epoehlma{at}zoo.uvm.edu
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Abstract |
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We studied 44 healthy obese postmenopausal women between 50 and 71 yr of age (mean ± SD, 56.5 ± 5.3 yr). The rate of glucose disposal was measured using the euglycemic/hyperinsulinemic clamp technique. Visceral and sc adipose tissue areas and midthigh muscle attenuation were measured from computed tomography. Fat mass and lean body mass were estimated from dual energy x-ray absorptiometry. Peak VO2 was measured from a treadmill test to volitional fatigue. Physical activity energy expenditure was measured from indirect calorimetry and doubly labeled water.
Pearson correlations indicated that glucose disposal was inversely related to visceral adipose tissue area (r = -0.40; P < 0.01), but not to sc adipose tissue area (r = 0.17), total fat mass (r = 0.05), midthigh muscle attenuation (r = 0.01), peak VO2 (r = -0.22), or physical activity energy expenditure (r = -0.01). The significant association persisted after adjusting visceral adipose tissue for fat mass and abdominal sc adipose tissue levels (r = -0.45; P < 0.005; in both cases). Additional analyses matched two groups of women for fat mass, but with different visceral adipose tissue levels. Results showed that obese women with high visceral adipose tissue levels (283 ± 59 vs. 137 ± 24 cm2; P < 0.0001) had a lower glucose disposal per kg lean body mass compared to those with low visceral adipose tissue levels (0.44 ± 0.14 vs. 0.66 ± 0.28 mmol/kg·min; P < 0.05).
Visceral adipose tissue is an important and independent predictor of glucose disposal, whereas markers of skeletal muscle fat content or physical activity exhibit little association in obese postmenopausal women.
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Introduction |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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There are several issues that may contribute to this controversy. Differences in techniques to measure abdominal fat deposition may partially contribute to discrepant findings among investigators (13, 14, 15, 16). Moreover, the failure to metabolically stabilize volunteers (i.e. weight stability and standardization of diet) may also introduce spurious results among investigators (7, 9, 12). Lastly, studies have been plagued by small (7, 12) and/or heterogeneous sample sizes (8, 9), have combined men and women (10, 11), and have not considered other potential modifiers of insulin sensitivity (i.e. physical activity levels and skeletal muscle properties), which may have rendered the data difficult to interpret. To this end, we examined the relationship between body fat distribution and glucose disposal using criterion methods for body composition, body fat distribution, and physical activity levels in a cohort of older obese postmenopausal women.
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Subjects and Methods |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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The study population consisted of 44 obese (mean ± SD, 35.4 ± 5.0 kg/m2) postmenopausal women between 50 and 71 yr old (mean ± SD, 56.5 ± 5.3 yr). The subjects were recruited by solicitation through the media between 1996 and 1998 for a study of genetics in weight loss. Individuals were included if their body mass index was 27 kg/m2 or greater, they had stopped menstruating for more than 1 yr, and they had a FSH level above 30 U/L. Participants also had to be sedentary (<2 periods a week of exercise participation), nonsmokers, and low to moderate alcohol consumers. All participants were apparently healthy and had no history or evidence on physical examination of 1) cardiovascular disease, peripheral vascular disease, or stroke; 2) diabetes; 3) moderate to severe hypertension (resting blood pressure, >170/100 mm Hg); 4) orthopedic limitations or history of pathological fracture; 5) body weight fluctuation of more than 5 kg in the previous 6 months; 6) thyroid or pituitary disease; and 7) medication that could affect cardiovascular function or metabolism. Sixteen women of 45 were taking hormone replacement therapy (HRT; duration of menopause, 7.5 ± 5.2 yr; duration of HRT, 4.7 ± 2.9 yr (mean ± SD)]. The duration of menopause was similar for women without HRT (7.0 ± 5.0 yr; P = NS between groups). All participants were asked to sign an informed consent document. The University of Vermont medical sciences committee on human research approved this study.
Weight and diet stabilization period
Subjects were weight stable for 1 month before metabolic
testing. Volunteers consulted with the dietitian at the Clinical
Research Center regarding energy and macronutrient composition. Daily
energy needs were then estimated from standardized equations developed
in our laboratory (17). During the weight stabilization period, the
diet consumed was approximately 30% energy as fat, 58% as
carbohydrate, and 12% as protein. Weight stability was verified by
having subjects weighed twice per week at the Clinical Research Center.
Macronutrient composition was estimated by having subjects record their
food intake for 3 days (2 week days and 1 weekend day). Three days
before testing, dietary intake was provided and standardized for all
subjects (
30% energy as fat, 58% as carbohydrate, and 12% as
protein) by the metabolic kitchen of the General Clinical Research
Center.
Body composition
Body weight was measured to the nearest 0.1 kg on a calibrated balance. Determination of fat mass, lean body mass, and percentage of body fat were assessed using dual-energy x-ray absorptiometry (DEXA; model DPX-L, Lunar Corp., Madison, WI) as previously described (18, 19). The subjects were asked to wear only a standard hospital gown and to maintain their supine position during the scan procedure.
Computed tomography (CT)
VAT and sc adipose tissue were measured by CT as previously described (20) using a GE High Speed Advantage CT scanner (General Electric Medical Systems, Milwaukee, WI). The subjects were examined in the supine position with both arms stretched above the head. The position of the scan was established at the L4–L5 level using a scout image of the body. VAT area was quantified by delineating the intraabdominal cavity at the internal-most aspect of the abdominal and oblique muscle walls surrounding the cavity and the posterior aspect of the vertebral body. Adipose tissue was highlighted and computed using an attenuation range of -190 to -30 Hounsfield units. The sc adipose tissue area was quantified by highlighting adipose tissue located between the skin and the external-most aspect of the abdominal muscle wall.
CT was also used to measure midthigh cross-sectional skeletal muscle and adipose tissue areas and muscle attenuation, the latter representing an estimate of muscle fat content (21, 22). Areas of skeletal muscle, adipose tissue, and muscle attenuation were calculated by delineating the regions of interest and then computing the surface areas using an attenuation range of -190 to -30 Hounsfield units for adipose tissue and 0–100 Hounsfield units for skeletal muscle. Test-retest measures of the different body fat distribution compartments on 10 CT scans yielded a mean absolute difference of 1%.
Measures of energy expenditure
Total daily energy expenditure (TEE). TEE was determined from the doubly labeled water over a 10-day period. During that period, subjects were asked to maintain their normal daily physical activity routines. These individuals, however, were not participating in any structured exercise training program. Specific details about the doubly labeled water have been described extensively by our laboratory (18, 19).
Resting metabolic rate (RMR). The RMR was measured by indirect calorimetry using the ventilated hood technique (23) after an overnight, 12-h fast at the General Clinical Research Center. Respiratory gas analysis was performed using a Deltatrac metabolic cart (Sensormedics, Yorba Linda, CA). RMR (kilocalories per day) was calculated from the equation of Weir (24). The test-retest correlation coefficient within 1 week has been shown to be 0.90 for RMR in our laboratory.
Daily physical activity energy expenditure (PAEE). Doubly labeled water in conjunction with indirect calorimetry was used to measure PAEE. PAEE was calculated as the difference between TEE and RMR, and the thermic effect of a meal using the equation: PAEE (kilocalories per day) = [TEE (Cal/day) x 0.9] - RMR (Cal/day), as previously described (18, 19). This approach assumes that the thermic effect of feeding is 10% of the TEE in the elderly (25).
Peak VO2
Subjects performed a graded exercise test on treadmill to voluntary exhaustion to measure peak oxygen consumption, as previously described (26). Standard 12-lead electrocardiograms were performed at the end of each 2-min stage. Peak VO2 (liters per min) was considered to be the highest value obtained during the test. Expired gas was analyzed during the exercise protocol using a Sensormedics Horizon metabolic cart (Yorba Linda, CA). Data collection included oxygen consumption (VO2) and respiratory equivalent ratio (CO2 production/O2 consumption).
Oral glucose tolerance test (OGTT)
During an out-patient visit to the General Clinical Research Center, a 2-h 75-g OGTT was performed after 3 days of a standardized diet (>250 g carbohydrate consumption) according to the guidelines of the American Diabetes Association (27). Insulin and glucose levels were measured at 0, 60, 90, and 120 min during the OGTT. The total area under the curve were determined with the trapezoid method.
Hyperinsulinemic/euglycemic clamp
Basal and insulin-stimulated glucose kinetics were measured by the hyperinsulinemic-euglycemic clamp technique as described by DeFronzo et al. (28) and implemented in our laboratory (29). All subjects were tested after a 12-h overnight fast at the General Clinical Research Center and 3 days of standardized meals. An iv catheter was placed in an antecubital vein at 0600 h for infusion of insulin, 20% dextrose, and [6,6–2H2]glucose (99% 2H; Cambridge Isotope Laboratories, Andover, MA) tracer. A second catheter was placed retrograde in the contralateral hand for blood sampling. The hand was warmed in a box by a gentle stream of heated air (50–55 C) to produce arterialized venous blood. At 0700 h, a primed, infusion of [6,6–2H2]glucose (4 mg/min) was begun and continued for 2 h. Blood samples were taken before the start and during the second hour of the infusion for determination of plasma [6,6–2H2]glucose enrichment. At 0900 h, the insulin infusion was begun and continued for an additional 2 h. Insulin was infused at a rate of 240 pmol/m2·min to attain postprandial peripheral insulin levels and suppress hepatic glucose output. Blood glucose was monitored every 5 min during the insulin infusion, and euglycemia was maintained throughout the clamp by infusing 20% dextrose at a variable rate. The rate of infused glucose reached a constant value by the second hour of the clamp. Blood samples were also taken during the last 30 min of the clamp for determination of [6,6–2H2]glucose enrichment. To maintain a constant enrichment of [6,6–2H2]glucose tracer in blood during the clamp, [6,6–2H2]glucose was added to 20% dextrose before the start of the study to produce an enrichment of 1 molar percent excess (mpe) of [6,6–2H2]glucose in the dextrose. Aliquots of blood were placed in heparinized tubes and stored on ice until the plasma was prepared by centrifugation at 4 C, frozen, and stored at -60 C for later analysis.
Analytical methods
For measuring plasma [6,6–2H2]glucose enrichments, 0.1-mL aliquots of plasma were deproteinized with ice-cold (4 C) acetone, the supernatants were decanted and placed into screw-cap vials, and the samples were evaporated to dryness under a gentle stream of dry nitrogen. After adding 50 µL 2% butyl boron dihydroxide (Sigma, St. Louis, MO) in pyridine, the samples were allowed to sit for 24 h at room temperature. Acetic anhydride (50 µL) was added just before measurement to complete formation of the butyl butylboronate glucose derivatization formation.
The butylboronate glucose derivatives were measured by gas chromatography-mass spectrometry using electron impact ionization (model 5971, Hewlett-Packard Co., Palo Alto, CA). The [M-57]+ ions at m/z = 297 and 299 were monitored for unlabeled glucose and [6,6–2H2]glucose, respectively. The peak area ratios of 299/297 were determined by selected ion monitoring, as performed previously. From these ratios, the background corrected amino acid enrichments, as mpe, were calculated.
Calculations
The purpose of the hyperinsulinemic/euglycemic clamp was to provide measurements of basal hepatic glucose output or appearance and a measure of hepatic glucose output during the clamp.
The rate of glucose output (HGO) was calculated from the mean [6,6–2H2]glucose enrichment in plasma during the basal state: HGO = I (Ei/Ep - 1), where I is the rate of [6,6–2H2]glucose infusion (milligrams per min), Ei is the enrichment of the tracer enrichment in mpe, and Ep is the mean enrichment (mpe) of [6,6–2H2]glucose in plasma during the basal state.
During the hyperinsulinemic/euglycemic clamp, total glucose disposal (TGD) was also calculated from the plasma [2H2]glucose enrichment taken from blood samples during the last 30 min of the insulin infusion: TGD = (I x Ei + M x Em)/Ep(cl) - I, where M is the rate of exogenous dextrose infusion (milligrams per min), Em is the enrichment of [6,6–2H2]glucose in the infused dextrose (mpe), and Ep(cl) is the mean [2H2]glucose enrichment in the blood samples taken during the last 30 min of the clamp.
The residual hepatic glucose output during the clamp (HGOcl) was taken as the difference between TGD measured using the [2H2]glucose and the mean rate of dextrose infusion during the last 30 min of the insulin infusion (M): HGOcl = TGD - M.
Analyses of the clamp procedure indicated a coefficient of variation of 9% among subjects and 4% within subjects for plasma glucose levels during the clamp.
Biochemical analyses
Plasma glucose concentrations were determined using a YSI, Inc., glucose analyzer (Yellow Springs, OH). Plasma insulin levels were determined with a double antibody RIA (Diagnostic Products, Los Angeles, CA).
Statistical analyses
Data are presented as the mean ± SD. Pearson
product-moment correlations were used to determine the relationship
between dependent and independent variables. Because abdominal sc fat
and/or total adipose tissue levels may influence the association
between VAT levels and glucose disposal, the relationship between these
variables was examined after statistical adjustment using analysis of
covariance. Unpaired t tests were used to examine
differences between groups. Log transformation was used to normalize
the distribution for variables of interest that had an abnormal
distribution (age, body mass index, VAT, basal hepatic glucose output,
hepatic glucose output during the clamp, total glucose disposal, and
total glucose disposal expressed by kilograms of lean body mass).
Because users and nonusers of hormone replacement showed similar
responses during the clamp and the oral glucose tolerance test and
displayed similar associations between glucose disposal and body
composition and body fat distribution measures, both groups were pooled
for statistical analyses. 
2 analysis showed no
difference in the number of users and nonusers of HRT for the paired
approach. P < 0.05 was accepted as significant.
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Results |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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shows that our population of
obese, but otherwise healthy, postmenopausal women were characterized
by a broad range of physical activity indices (peak
VO2 and physical activity energy expenditure) and
of body composition (body weight, body mass index, percent body fat,
fat mass, and lean body mass) and of body fat distribution measures
(abdominal and midthigh sc adipose tissue, VAT, and skeletal muscle
attenuation). Responses during the OGTT and clamp are presented in
Table 2. The concentration of insulin
achieved during the clamp was 615 + 117 pmol/L for the entire group
(results not shown).
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. Pearson product-moment correlation
analysis indicated that VAT area was the only variable significantly
related to total glucose disposal per kg lean body mass (r =
-0.40; P < 0.01; Table 3). Nonsignificant
correlations were observed between glucose disposal and the other
independent variables (r = -0.22 to 0.20). Because body fat may
influence the association between VAT and glucose disposal, this
relationship was examined after statistical adjustment. The
relationship between glucose disposal and VAT levels slightly improved
after adjusting for fat mass as well as for abdominal sc adipose tissue
levels (r = -0.45; P < 0.005 in both cases; Fig. 1).
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and 5).
By design, the 2 subgroups were different on the basis of VAT areas
(283 ± 59 vs. 137 ± 24
cm2; P < 0.0001), but were
similar for body composition (body weight, body mass index, percent
body fat, fat mass, and lean body mass) and body fat distribution
measures (abdominal and midthigh sc adipose tissue, and skeletal muscle
attenuation; Table 4). Women with high VAT accumulation had lower
midthigh sc adipose tissue area (184 ± 36 vs. 228
± 53 cm2; P < 0.02) and higher
leg muscle area (118 ± 16 vs. 105 ± 15
cm2; P < 0.05).
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. Women
who displayed high levels of VAT showed higher insulin (121.1 ±
73.3 vs. 59.3 ± 39.3 pmol/L x
10-3; P <
0.05) and glucose (0.93 ± 0.16 vs. 0.78 ± 0.17
mmol/L x 10-3;
P < 0.05) areas under the curve during the OGTT as
well as lower exogenous glucose infusion (17.8 ± 6.2
vs. 26.9 ± 8.6 mmol/min; P < 0.01)
and lower total glucose disposal per kg lean body mass levels
(0.44 ± 0.14 vs. 0.66 ± 0.28 mmol/kg·min;
P < 0.05) during the clamp compared to women with low
VAT (Table 5). No difference was observed for the other variables of
interest. |
Discussion |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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There is considerable controversy regarding the relative importance of the compartments of body fat on glucose disposal (30). This question, however, has not been assessed in older, obese, postmenopausal women. Potential confounders, such as differences in body composition techniques, physical activity levels, as well as mixed gender and age groups, may contribute to discrepant results. We attempted to overcome these potential confounders by studying an older group of obese postmenopausal women and by using criterion methodologies (CT scan, DEXA, hyperinsulinemic/euglycemic clamp, and doubly labeled water).
We weight stabilized all subjects 1 month before metabolic assessment and standardized dietary intake 3 days before testing. This is not a trivial experimental issue, as fluctuations in body weight (31, 32, 33) and the macronutrient content of the diet impact on glucose disposal (34, 35, 36). We also studied sedentary postmenopausal obese women displaying a broad range of obesity, which helps control for potential confounders such as physical activity, gender, and age (i.e. all women were inactive). Finally, we used regression-based and matching approaches to explore the association of VAT, independently of the confounding influence of fat mass and/or sc adipose tissue levels, on glucose disposal (30). We believe that these approaches help reduce the physiological noise that may have rendered other studies difficult to interpret, with respect to the contribution of regional and total adiposity to glucose disposal.
The present study shows that VAT accumulation, but not total body fat or sc adipose tissue levels, were associated with lower glucose disposal in obese postmenopausal women. We were somewhat surprised at the strength of the correlation between VAT and glucose disposal, whereas the other constituents of regional and total fat exhibited nonsignificant associations. One would have predicted that the high degree of covariance shared among the constituents of body composition may have yielded comparable correlations with glucose disposal and obscured the independent contribution of each component to insulin resistance. This was not the case. This finding contrasts with conclusions obtained in previous studies using similar methodologies (7, 8, 9, 10, 11, 12).
It is likely that the discordant results among studies may be explained
by our selection criteria. We tested a cohort of obese women, whereas
other investigators included both lean and obese individuals (7, 8, 9, 10, 11, 12) in
their experimental design. However, our cohort of subjects was quite
heterogeneous based on VAT areas (67–366 cm2).
Thus, it is possible that our cohort composed only of obese subjects,
but displaying a broad range of VAT levels, favors a physiological
scenario that potentially limits the contribution of total body fatness
(i.e. all subjects are obese) while highlighting the
importance of VAT accumulation as an important determinant of glucose
disposal. It has also been suggested that once a certain threshold of
obesity is achieved (30%), fat mass per se loses its
predictive power of insulin resistance (37, 38, 39). Our results would also
support this idea. That is, all of our women had greater than 30% body
fat; this possibly limited the contribution of total body fat to
variations in glucose disposal.
In addition to our regression-based approach, we used a matching strategy to examine determinants of glucose disposal. In a subgroup analysis, we analyzed differences in glucose disposal in groups of women who were matched for total fat mass, but differed in VAT. We found that total glucose disposal per kg lean body mass was 50% lower in women displaying high levels of VAT than in women matched for body fat but with low VAT accumulation. Thus, regardless of our experimental approach (regression vs. matching), our results underscore the importance of VAT levels as an independent predictor of glucose disposal.
A secondary objective of our study examined the association between total glucose disposal with markers of skeletal muscle (muscle attenuation) and physical activity. Muscle attenuation is another important aspect of body composition that is altered in obesity (25, 40) and has been linked to the expression of insulin resistance (22, 41). It has been shown that a reduced attenuation value of skeletal muscle in obesity is a strong marker of insulin resistance (10). Contrary to these results, we found no relation between mean muscle attenuation and rates of glucose disposal in our population.
We also examined the possibility that peak VO2 (a biological attribute) and physical activity energy expenditure (a behavioral characteristic), measured from doubly labeled water, may be associated with total glucose disposal. These variables were considered in our model because of previously reported positive associations between markers of exercise capacity and indexes of insulin sensitivity (10, 42). In the present study, however, no associations were found between total glucose disposal and peak VO2 or physical activity energy expenditure. It is likely that low variation in physical activity and fitness levels may contribute to minimize the association between these variables and markers of insulin sensitivity. Other factors, such as muscle fiber morphology (muscle fiber areas and number of capillaries) (43), muscle fiber type proportion (44), and metabolic properties of skeletal muscle (glycolytic and oxidative enzyme) (22), may contribute to explain variations in insulin sensitivity in obese postmenopausal women. Taken together, in a population of postmenopausal obese women, physiological variations in muscle attenuation and in markers of cardiorespiratory fitness and physical activity energy expenditure fail to explain additional biological variations in glucose disposal.
There are limitations of our study that should be noted. First, the cross-sectional design precludes firm conclusions regarding factors that may influence glucose disposal in postmenopausal obese women. Other factors could potentially explain variance in glucose disposal in this population (structure and composition of skeletal muscle, muscle enzyme activities, genetic susceptibility, etc.). Finally, statistical analyses based on a cohort composed uniquely of obese inactive subjects may have limited our capacity to detect a significant effect of these parameters on glucose disposal.
Collectively, our results and those of others support the idea that an excessive adipose tissue accumulation in the visceral cavity is an important independent factor associated with decreased rates of glucose disposal in obese postmenopausal women. Therapeutic interventions to offset accelerated central fat accumulation, lipid profile abnormalities, and decreases in insulin sensitivity associated with the menopause transition (45, 46) are needed.
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Footnotes |
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Received July 14, 1999.
Revised October 18, 1999.
Revised March 1, 2000.
Accepted April 1, 2000.
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References |
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R. Ross, J. Freeman, R. Hudson, and I. Janssen Abdominal Obesity, Muscle Composition, and Insulin Resistance in Premenopausal Women J. Clin. Endocrinol. Metab., November 1, 2002; 87(11): 5044 - 5051. [Abstract] [Full Text] [PDF]
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