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American Journal of Clinical Nutrition, Vol. 84, No. 5, 1193-1199, November 2006
© 2006 American Society for Nutrition

ORIGINAL RESEARCH COMMUNICATION

Interrelations between fat distribution, muscle lipid content, adipocytokines, and insulin resistance: effect of moderate weight loss in older women1,2,3

Gloria Mazzali, Vincenzo Di Francesco, Elena Zoico, Francesco Fantin, Giulia Zamboni, Claudia Benati, Valentina Bambara, Mauro Negri, Ottavio Bosello and Mauro Zamboni

1 From Geriatric Medicine (GM, VDF, EZ, FF, CB, VB, OB, and MZ) and the Radiology Institute (GZ), University of Verona, Verona, Italy, and the Clinical Chemistry and Haematology Laboraory, Hopital of Verona, Verona, Italy (MN)

2 Supported by grants from the MIUR project "Aging effects on adipose tissue production of inflammatory peptides" 2005063885_005.

3 Address reprint requests to M Zamboni, Cattedra di Geriatria, University of Verona, Ospedale Maggiore-Piazzale Stefani 1, 37126 Verona, Italy. E-mail: mauro.zamboni{at}univr.it.

See corresponding editorial on page 957.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background: Interrelations between fat distribution, muscle lipid infiltration, adipocytokines, insulin resistance, and moderate weight loss have not been investigated in obese older subjects.

Objective: The objective was to evaluate relations between fat distribution, muscle lipid content, adipocytokines, and insulin resistance in older women and the effects of moderate weight loss.

Design: In 35 healthy women aged 58–83 y, body mass index, waist circumference, sagittal abdominal diameter (SAD), and body composition measured by dual-energy X-ray absorptiometry were evaluated. A midthigh single computed tomography scan was performed to determine subcutaneous adipose tissue (AT), intermuscular AT (IAT), muscular tissue, and muscle lipid infiltration, evaluated as low-density lean tissue. Metabolic variables, insulin resistance measured by homeostasis model assessment, adiponectin, leptin, and high-sensitivity C-reactive protein were measured in all subjects and after weight loss in a subgroup of 15 obese women.

Results: Waist circumference and SAD were positively correlated with leptin and insulin resistance and negatively correlated with adiponectin. Adiponectin was associated negatively with insulin resistance and positively with HDL cholesterol, whereas leptin was positively associated with insulin resistance and triacylglycerols. Midthigh subcutaneous AT was associated with insulin resistance and leptin, whereas IAT was associated with triacylglycerols. Stepwise regression with insulin resistance as the dependent variable and body mass index, SAD, triacylglycerols, HDL cholesterol, adiponectin, leptin, high-sensitivity C-reactive protein, and midthigh subcutaneous AT as independent variables showed that SAD entered the regression first (R2 = 0.492) followed by adiponectin (R2 = 0.63). After moderate weight loss, midthigh subcutaneous AT, IAT, low-density lean tissue, leptin, and insulin resistance decreased significantly; no significant changes in adiponectin were observed.

Conclusions: Fat distribution indexes and adiponectin are independently associated with insulin resistance. Even in older women, moderate weight loss improves body fat distribution, muscle lipid infiltration, and insulin resistance. Moderate weight loss results in a significant decrease in leptin but no changes in adiponectin.

Key Words: Fat distribution • muscle lipid content • obesity • insulin resistance • adipocytokines • weight loss


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The interest in obesity in the elderly is growing (1, 2). With aging, both visceral fat and muscle lipid content increase (1, 2). High amounts of visceral fat and muscle lipid have been shown to be associated with metabolic disorders, particularly with insulin resistance in obese subjects (1-4). Additionally, adipocytokines have been shown to be associated with insulin resistance; some studies have shown that adipocytokines decrease and others that it increases insulin sensitivity (5, 6).

Furthermore, weight loss reverts the metabolic complications of obesity (7, 8). This effect may be due to a higher decrease in visceral than in subcutaneous fat (9, 10) or may be due to a reduction in the lipid content within muscles (10). However, only a few studies have evaluated the effects of weight loss on the amount of lipid within muscles, with discrepant findings (10-15). Computed tomography (CT) has been validated as a method to evaluate the amount of adipose tissue (AT) within muscles (16). Using CT at the midthigh level, Goodpaster et al (10, 11) reported a significant decrease in muscle fat content after a weight loss of about 13% in obese sedentary subjects. These findings were confirmed after greater weight loss in muscle biopsy samples used to determine intramuscular lipid content (13, 15) but not after moderate weight loss (14, 15).

In obese subjects, weight loss also determines a significant decrease in leptin concentrations (10, 17). Some, but not all, studies reported an increase in adiponectin after weight loss (17-22). However, improvement in metabolic disorders after weight loss may be due both to the decrease in leptin and to the increase in adiponectin. No studies of the effects of weight loss on fat distribution, muscle lipid content, or adipocytokines have been performed in elderly women.

The aim of our study was to investigate the joint and separate effects of fat distribution, muscle lipid content, and adipocytokines (leptin and adiponectin) on insulin resistance as well as to test the effect of moderate weight loss (nearly 5%) on body composition, regional fat distribution, muscle lipid content, adiponectin and leptin concentrations, and insulin sensitivity in older age.


   SUBJECTS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Subjects
A total of 35 women aged 58–83 y and with a body mass index (BMI; kg/m2) ranging from 21.7 to 43.8 were studied. All subjects underwent a careful initial clinical assessment. All subjects were weight-stable in the previous 6 mo and had no evidence of diabetes, cancer, or liver, renal, or thyroid disease. None of the subjects received insulin, thiazolidinediones, or hypoglycemic or lipid-lowering therapy. All women were postmenopausal and were not receiving hormone replacement therapy. The participants were not engaged in regular physical exercise before the study and were asked not to modify their physical activity during the study period. Smokers and obese subjects outside the dual-energy X-ray absorptiometry (DXA) field of view were excluded.

A subgroup of 15 patients with BMIs ranging from 29.6 to 43.8 and ranging in age from 58 to 73 y consumed a hypoenergetic diet and were evaluated before and after treatment. All participants gave their informed consent, and the experimental protocol was approved by the ethical committee of our university.

Anthropometric measurements
While the subjects were wearing light indoor clothes and no shoes, body weight was measured to the nearest 0.1 kg (Salus, Milan, Italy) and height to the nearest 0.5 cm with a stadiometer (Salus). BMI was calculated as body weight adjusted by stature squared (kg/m2). Waist circumference was obtained with a measuring tape at the narrowest circumference of the abdomen. Sagittal abdominal diameter (SAD) was measured with a portable, sliding beam, abdominal caliper as the largest anteroposterior diameter between the xyphoid process and the umbilicus while the subjects were in a supine position (23).

Body-composition assessment
Body composition was measured by using DXA (QDR 4500, Hologic, Waltham, MA) array beam system software version 11.1. The characteristics and physics concepts of DXA measurement were described elsewhere (24). Daily quality-assurance tests were performed according to the manufacturer's directions.

All of the subjects included in this study were within the maximum weight supported by our DXA scanner (130 kg). The subjects who were near the limits of DXA field of view (195.6 x 65–67 cm) were positioned with their hands parallel to their thighs and arms as near as possible to the body.

All of the scans were subsequently analyzed by a single trained investigator. Total body fat was expressed in kg (FM) and as a percentage of body weight (%FM). Lean soft tissue mass was calculated as total body mass minus the sum of total body fat and bone mass and expressed in kilograms. Appendicular fat-free mass (AFFM) was calculated as the sum of arm and leg fat-free soft tissue. The CVs for double determination in 11 subjects (men and women aged 66–77 y) were 1% for FM and 2.3% for %FM.

Midthigh computed tomography
CT was used to measure the cross-sectional area of midthigh muscle and AT and to measure muscle attenuation (16). A 10-mm axial scan was acquired at the midpoint between the anterior iliac crest and the patella while the subject was supine. Areas of AT and skeletal muscle were measured by manually tracing regions of interest defined by attenuation values [Hounsfield units (HU)]: 0 to –190 HU for AT, and 0 to 100 HU for muscle. Intermuscular AT (IAT) area was obtained by manual tracing. In particular, one tracing was drawn around the outermost edge of the thigh skeletal muscle to distinguish intermuscular AT. Subcutaneous AT area corresponded to the difference between total AT area and IAT area. Muscle area was further characterized as normal-density muscle (cross-sectional area of muscle displaying attenuation values of 31 to 100 HU), and low-density muscle (cross-sectional area of muscle displaying attenuation values of 0 to 30 HU) (11, 25).

Biochemical analyses
Venous blood samples for all metabolic assessments were obtained after the subjects fasted overnight. Plasma glucose was measured with a glucose analyzer (Beckman Instruments Inc, Palo Alto, CA). The intraassay CV was 1.5%.

Plasma immune-reactive insulin underwent duplicate measurements by double-antibody radioimmunoassay with the use of a commercial kit (Diagnostic Products Corp, Los Angeles, CA). Sensitivity was 6 pmol/L, and the intraassay CV was 4.9%.

Insulin resistance was estimated with the homeostasis model assessment (HOMA) method (26). Cholesterol and triacylglycerols were measured with a Technicon Autoanalyzer (Technicon Inc, Co, Tarrytown, NY); dextran-magnesium precipitation was used for HDL separation. LDL was calculated by using the Friedewald formula (27).

Serum leptin was measured with a specific enzyme-linked immunoassay kit (DBC-Diagnostic Biochem Canada Inc, London, Canada). The sensitivity of the kit was 0.5 ng/mL, and the intraassay and interassay CVs were 7.47% and 9.6%, respectively.

Serum adiponectin was measured by using a commercially available radioimmunoassay (RIA) kit (Linco Research Inc, St Charles, MO). The sensitivity of the kit was 0.78 ng/mL, and the intraassay and interassay CVs were 7.4% and 8.4%, respectively.

High-sensitivity C-reactive protein (hs-CRP) was measured with the immunoturbidimetric method. The detection threshold was 0.5 mg/L, the reference interval was 3 mg/L, and the analytic variability was 5%.

Energy expenditure evaluation
Resting metabolic rate (RMR) was assessed by indirect calorimetry (28) with the use of an MMC Horizon System 6 (Beckman Sensormedics, Milan, Italy) that measured resting oxygen uptake and resting carbon dioxide production. The subjects were familiarized with the canopy of the calorimeter so that they did not feel suffocated during the measurement period. They were instructed to avoid hyperventilating, fidgeting, and falling asleep. Gas was measured in the morning in the supine position after the subjects had fasted 12 h. Values were considered reliable after a 20-min nonstop period when differences in consecutive values were <5%; at this point, gas measurements were continued for another 20 min, and mean values for resting oxygen uptake and resting carbon dioxide production were calculated. The CV for duplicate measurements in 12 subjects was 5%.

Hypoenergetic diet
A subgroup of 15 subjects completed a 3-mo weight-loss program designed to achieve a loss of 5% of initial weight. The caloric restriction was 500 kcal below the resting energy expenditure, evaluated by indirect calorimetry and multiplied by a physical activity level of 1.4 (29). Each subject received a diet providing 62% carbohydrates, 24% fat, 14% protein, and 20 g fiber. The subjects were advised to eat 3 meals: breakfast, lunch, and dinner. Breakfast consisted of skim milk and bread; lunch consisted of pasta or rice, vegetables, and fruit; and dinner consisted of fish or meat, bread, vegetables, and fruit.

The only beverage allowed was water. The subjects underwent monthly clinical and nutritional follow-ups. Dietary compliance was checked by a 24-h recall every 4 wk during an outpatient visit. These data were processed by using special software to calculate the mean (±SD) daily energy before and after the weight loss: 2320 ± 509.8 and 1661.5 ± 260.9 kcal/d, respectively (30).

Statistical analysis
The results are presented as means ± SDs. Log transformation has been performed for nonnormal variables. Comparisons of anthropometric, metabolic, and body-composition variables before and after weight loss were made by using an unpaired t test. Correlation and stepwise multiple regression analyses were used to test associations between variables. The level of statistical significance was P < 0.05 for all the variables. All statistical analyses were performed by using SPSS 12.1 for WINDOWS (31).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
The main characteristics of the study sample are shown in Table 1Go. Correlations between adipocytokines, hs-CRP, midthigh adipose and lean tissue, and anthropometric, body-composition, and metabolic variables in the whole study sample are shown in Table 2Go.


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  		TABLE 1 Characteristics of the study population1

 

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  		TABLE 2 Main correlations between study variables1

 
A significant association was observed between BMI, waist circumference, SAD, all metabolic variables except cholesterol, and hs-CRP. BMI, waist circumference, and SAD were positively correlated with leptin, whereas only waist circumference and SAD were negatively correlated with adiponectin. A significant association was observed between BMI, waist circumference, SAD, and subcutaneous AT, IAT and low-density lean tissue at the midthigh (measured by CT). Subcutaneous AT at the midthigh (measured by CT) was associated with HOMA and leptin, whereas IAT was associated with triacylglycerols. Adiponectin was negatively associated with insulin and HOMA and positively associated with HDL cholesterol. Leptin was positively associated with HOMA, triacylglycerols, and low-density lean tissue at the midthigh (measured by CT); hs-CRP was positively associated with HOMA and negatively associated with HDL cholesterol.

Stepwise multiple regression analysis was performed considering HOMA as the dependent variable and all of the variables that showed a significant association with HOMA (BMI, SAD, triacylglycerols, HDL cholesterol, adiponectin, leptin, hs-CRP, and subcutaneous AT at midthigh) as independent variables. SAD entered the regression first (R2 = 0.492, P < 0.001), followed by adiponectin (R2 = 0.630, P < 0001).

Mean (±SD) values for anthropometric and body-composition variables and midthigh AT and lean tissue (measured by CT) before and after weight loss are shown in Table 3Go for 15 subjects. The mean decrease in body weight was 5.4%. Weight, BMI, waist circumference, and SAD decreased significantly after weight loss. Total body fat, appendicular fat-free mass, subcutaneous AT (P < 0.05), and IAT (P < 0.001) decreased significantly. Low-density lean tissue decreased by 8% (P < 0.05), whereas no significant difference was shown for muscular tissue.


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  		TABLE 3 Anthropometric, body-composition, and fat-distribution variables before and after moderate weight loss1

 
Mean (±SD) values for the metabolic variables, hs-CRP, and adipocytokines before and after weight loss are shown in Table 4Go. Insulin concentrations and HOMA significantly decreased after weight loss. Fasting serum leptin significantly decreased, whereas no changes were observed in adiponectin.


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  		TABLE 4 Metabolic variables and adipocytokine concentrations before and after weight loss1

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
Our study showed that indexes of body fat distribution and adiponectin are independently associated with insulin resistance. Our findings also showed that even moderate weight loss improves body fat distribution, lipid content within muscles, and insulin resistance. Leptin, but not adiponectin, was significantly affected by moderate weight loss.

Several studies have shown that the amount of visceral fat is the main determinant of insulin resistance and metabolic alterations in obese subjects (3, 32). Our data are in line with previous studies showing that adiponectin, independently of fat distribution, contributes to explain insulin resistance (1, 33-35). In fact, when we performed a stepwise multiple regression analysis using insulin resistance (measured by HOMA) as the dependent variable, only SAD and adiponectin entered the regression explaining all together 60% of the variance in insulin resistance, with adiponectin alone explaining almost 20% of the variance.

On the contrary, our data do not support a significant role for the lipid content of muscles, both intramuscular fat and low-density lean tissue, as evaluated by CT, in determining insulin resistance. The clinical relevance of lipid muscle content (as measured by CT) at the midthigh level was previously suggested and confirmed by Goodpaster et al (16), who observed that low CT attenuation values of the skeletal muscle reflect an increased lipid content within muscle fibers. It must be noted, however, that in previous studies (11, 36) the associations between the lipid content of muscle and insulin sensitivity were no longer significant after adjustment for body fat, which suggests that the effect of muscle lipid content on insulin resistance is not independent. The relation between lipid muscle content and insulin sensitivity is still not completely clear. In fact, in contrast with the previously observed negative relation between muscle lipid content and insulin sensitivity (10, 11, 13, 15), endurance-trained subjects have a lipid muscle content equivalent to that reported in sedentary obese or type 2 diabetic subjects (37). The significant association observed in our subjects between surrogate markers of visceral fat, such as waist circumference and SAD, and intermuscular fat and low-density lean tissue may also suggest that muscle lipid content is just a proxy of fat distribution. It must be noted that CT cannot directly measure the lipid content or detect the location of fat storage within or surrounding the muscle cells. Thus, it is possible to hypothesize that our finding of a lack of relation between intermuscular fat and insulin resistance could have been different if we had used a more sensitive technique for measuring the intramyocellular lipid content, such as magnetic resonance imaging (38).

Interestingly we observed a significant positive association between leptin and low-density lean tissue; this finding seems to link high concentrations of leptin, ie, a surrogate of leptin resistance, with higher amounts of lipid in the muscle, ie, a surrogate of lower oxidative muscle capacity.

In our obese subjects after moderate weight loss (5% of initial body weight), both abdominal fat and lipid muscle content significantly decreased. The effects of weight loss in regional adiposity at the midthigh were previously observed in some (10, 11, 13, 15), but not in all (14, 15), studies. Goodpaster et al (10) observed a decrease in low-density lean tissue after a weight loss of nearly 13% in 32 obese women who underwent a very-low-calorie diet. Gray et al (13) found a 30% decrease in the intramuscular lipid content, determined histochemically in 6 obese subjects after gastric bypass surgery, and a 47% reduction in BMI. Greco et al (15), after bariatric surgery with a weight loss of 33 kg, observed a 87% reduction in intramuscular fat content assessed by quantitative histochemistry in 8 morbidly obese subjects, but failed to observe any change in the intramuscular fat content of 9 subjects who underwent a hypocaloric diet with a weight loss of 14 kg. Similar results were observed by Malenfant et al (14).

These discrepancies could be justified by differences in the amount of weight loss or in the way in which weight loss was achieved. Individual variability in muscle lipid content, as well as the method used to assess inter- and intramuscular fat (biopsy or CT), may also be responsible for the discrepant results. However, our findings of a significant and prevalent decrease in intramuscular fat and low-density lean tissue after weight loss seem to add relevant information to this debate because the findings were observed after moderate weight loss and after the consumption of a low-calorie diet instead of a very-low-calorie diet (10, 11) or bariatric surgery (13, 15).

The higher percentage loss of IAT and intramuscular AT than of subcutaneous AT observed in our study and in other studies (10) suggests a parallelism with the largest loss of visceral compared with subcutaneous abdominal AT observed after weight loss by ourselves (9) and others (39). This parallelism may mean that both visceral fat, intermuscular, and low-density lean tissue are more sensitive to weight loss because of a higher lipolytic response.

Our data also confirm that, even after only moderate weight loss, muscle mass (measured by DXA) declines together with fat mass. Thus, our finding of no change in the amount of skeletal muscle within the normal range agrees with the findings of Goodpaster et al (10).

The main strength of our study was the finding that weight loss resulted in a significant improvement in body fat distribution, a loss of both intramuscular and intermuscular fat, and a decrease in insulin resistance with no loss of high-quality muscle in a group of older obese subjects. To our knowledge, ours is the first study to observe such effects. Given the steady increase in the prevalence of obesity, even in old age, studies showing the beneficial effect of moderate weight loss on these variables in old subjects are warranted.

In the present study, in line with previous reports (17), we observed that a weight loss of {approx}5% is associated with a significant decrease in leptin concentrations and an improvement in insulin sensitivity, whereas we found no significant changes in adiponectin concentrations after weight loss, despite a significant improvement in insulin resistance. These findings are in contrast with those of Yang et al (18), who observed a 46% increase in adiponectin in 22 obese patients who underwent partial gastrectomy and had an important weight loss of {approx}22% of body weight. An increase in adiponectin was also found in 120 premenopausal women after a weight loss of >10% of the initial weight (19) and after a very-low-calorie diet with a weight loss of nearly 12% (40).

It must be noted, on the other hand, that no significant changes in adiponectin were observed after moderate weight loss or after a program of physical activity, even by other researchers (17). Thus, it seems likely that only a large loss of AT will result in a significant increase in adiponectin.

Moreover, a significant increase in adiponectin has been observed after moderate weight loss in obese diabetic subjects but not in obese subjects with impaired glucose tolerance or in subjects with normal glucose tolerance (41), which suggests that even the degree of insulin resistance may influence increases in adiponectin after weight loss.

Some limitations of our study should be acknowledged. First, we did not measure visceral fat but rather surrogates such as SAD and waist circumference. However, we previously showed that SAD, measured while subjects were supine, is a reliable index of visceral fat and is useful in clinical studies (23). Second, we observed a decline in HDL cholesterol after weight loss in our subjects.

However, this apparent negative finding could be in line with previous observations (42), which showed a decrease in HDL cholesterol immediately after active weight loss, which reversed after stabilization of weight loss. Future studies of changes in HDL cholesterol after weight loss stabilization as well as after weight loss induced by both a hypocaloric diet and physical exercise are needed in elderly subjects. Finally, we cannot rule out that the composition of the diet given to our subjects may have been responsible for the observed improvement in insulin resistance. However, the fact that the decrease in abdominal fat and muscle lipid content coincided with a significant improvement in insulin resistance seems to suggest that weight loss, even if only moderate, improves insulin sensitivity via changes in fat distribution and muscle quality.

In conclusion, our study showed an independent association between indexes of body fat distribution and adiponectin with insulin resistance in a group of old women. Our findings also show that even moderate weight loss improves body fat distribution, muscle lipid content, and insulin resistance. Leptin, but not adiponectin, was significantly affected by moderate weight loss.


   ACKNOWLEDGMENTS
 
FF, GZ, VB, and CB were responsible for the data collection. MN and VDF contributed to the statistical analysis. GM, EZ, MZ, and OB interpreted the results and wrote the manuscript. None of the authors had a personal or financial conflict of interest related to this manuscript.


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 RESULTS
 DISCUSSION
 REFERENCES
 

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Received for publication February 9, 2006. Accepted for publication May 18, 2006.




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