Diabetes Care 24:245-249, 2001
© 2001 by the American Diabetes Association, Inc.
Clinical Care/Education/Nutrition Original Article |
Limited Value of the Homeostasis Model Assessment to Predict Insulin Resistance in Older Men With Impaired Glucose Tolerance
Cynthia M. Ferrara, PHD and
Andrew P. Goldberg, MD
From the Division of Gerontology, School of Medicine, University of
Maryland at Baltimore; and the Geriatric Research Education Clinical Center
(GRECC), Baltimore Veterans Affairs Medical Center, Baltimore, Maryland.
Address correspondence and reprint requests to Cynthia M. Ferrara, PhD,
Division of Gerontology, School of Medicine, University of Maryland, Baltimore
Veterans Affairs Medical Center, 10 N. Greene St., GRECC (BT/18/GR),
Baltimore, MD 21201-1524. E-mail:
cindy{at}grecc.umaryland.edu
.
 |
ABSTRACT
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OBJECTIVE Insulin resistance (IR) in older individuals is
associated with risk factors for coronary artery disease. The glucose clamp
measures IR directly, but the homeostasis model assessment (HOMA) of IR,
referred to here as HOMA-IR, is based on fasting glucose and insulin and is
less invasive and labor intensive. This method requires validation in the
elderly.
RESEARCH DESIGN AND METHODS We assessed the validity of
HOMA-IR as an index of IR by comparing it to glucose infusion rates (GIRs)
measured by a glucose clamp (600 pmol · m-2 ·
min-1) in 45 obese men (61 ± 8 years of age, mean ±
SD) with normal glucose tolerance (NGT) (n = 21) or impaired glucose
tolerance (IGT) (n = 24). We also evaluated relationships between
body composition, exercise capacity, and IR.
RESULTS Subjects with NGT had lower BMI (28 ± 3 vs. 31
± 3 kg/m2), waist circumference (97 ± 9 vs. 105
± 9 cm), waist-to-hip ratio (WHR) (0.93 ± 0.06 vs. 0.97 ±
0.05), and percent body fat (25 ± 6 vs. 30 ± 6) than subjects
with IGT. Subjects with NGT also had lower areas above basal during the 2-h
oral glucose tolerance test for glucose (274 ± 95 vs. 419 ± 124
mmol · min/l) and insulin (38,142 ± 18,206 vs. 58,383 ±
34,408 pmol · min/l) and lower HOMA-IR values (2.2 ± 0.8 vs. 4.2
± 2.6) than subjects with IGT. GIR (µmol · kg-1
FFM · min-1) was higher in subjects with NGT than in
subjects with IGT (53 ± 11 vs. 43 ± 14). HOMA-IR correlated with
GIR in subjects with NGT (r = -0.59), but not in subjects with IGT
(r = -0.13). GIR correlated with Vo2max in subjects with
NGT (r = 0.58) and IGT (r = 0.42), but with WHR only in
subjects with NGT (r = -0.53). HOMA-IR correlated with
Vo2max (r = -0.57) and waist circumference (r =
0.54) in subjects with NGT, but with percent body fat in subjects with IGT
(r = 0.54).
CONCLUSIONS These findings indicate that HOMA-IR should not
be used as an index of IR in older individuals who may be at risk for IGT, and
suggest that lifestyle changes that increase Vo2max and decrease
body fat may reduce IR in older people.
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INTRODUCTION
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Aging is associated with obesity and physical inactivity, both of which
increase the risk of insulin resistance (IR), coronary artery disease, and
type 2 diabetes
(1,2,3).
The diagnosis of IR in older individuals is clinically relevant, because
effective treatment through weight loss and regular exercise may reduce the
risk of cardiovascular disease complications associated with the IR syndrome.
Although the hyperinsulinemic-euglycemic clamp measures IR directly and is the
"gold standard"
(4), the homeostasis model
assessment (HOMA) requires only fasting glucose and insulin concentrations
(5,6).
This mathematical model is based on the theory of a negative feedback loop
between the liver and ß-cells that regulates both fasting glucose and
insulin concentrations and can be used to estimate pancreatic ß-cell
function and degree of IR. Therefore, it may be a useful noninvasive tool for
clinicians to diagnose IR in older populations.
The HOMA for IRreferred to here simply as HOMA-IRcorrelates
highly and significantly with whole-body insulin action in nondiabetic and
type 2 diabetic individuals
(6,7).
However, it appears that HOMA-IR does not adequately predict IR in all
individuals. Indeed, several investigators report that HOMA-IR and insulin
action do not correlate highly or significantly, particularly in individuals
with impaired glucose tolerance (IGT)
(8,9,10).
These previous studies do not specifically examine the relationships between
HOMA-IR and direct measures of insulin action using the euglycemic clamp in
older individuals with IGT. This is particularly important, because 20% of
individuals >50 years of age have IGT and 10% have type 2 diabetes
(11). This study determines
whether HOMA-IR is a good predictor of IR in middle-aged and older men with
either normal glucose tolerance (NGT) or IGT. In addition, a secondary purpose
of this study is to examine the relationships between indexes of IR, body
composition, and exercise capacity.
 |
RESEARCH DESIGN AND METHODS
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Subjects
We recruited 45 healthy Caucasian nonsmoking sedentary obese (BMI >25
kg/m2) men (47-74 years of age) from the community for
participation. Written informed consent was obtained from all individuals
according to the guidelines of the institutional review boards for human
studies at Bayview Johns Hopkins and the School of Medicine at the University
of Maryland at Baltimore. All subjects underwent a thorough medical screening,
including a history and physical examination, fasting blood profile, and a
graded exercise treadmill test before entering the study. All of the clamp
data have been previously reported in other publications
(12,13,14).
Body composition
BMI was calculated by dividing the weight of the subject by the height
squared (kilograms divided by meters squared). Body density was determined by
hydrostatic weighing, and percent body fat was calculated
(15) after correction for
residual lung volume. Fat-free mass (FFM) was calculated as body mass minus
fat mass. The waist-to-hip ratio (WHR), an index of the pattern of regional
body fat distribution, was calculated by dividing the waist measurement
(minimum circumference of the abdomen) by the circumference of the buttocks at
the maximal gluteal protuberance (hip measurement).
Measurement of Vo2max
A treadmill Vo2max test was performed on each subject on at
least 2 separate days, as previously described
(12). A true Vo2max
was considered to be attained if two of the following three criteria were met:
1) respiratory exchange ratio at maximal exercise >1.10,
2) maximal heart rate >90% of age-predicted maximum (220 - age),
and 3) a plateau in Vo2 (<200 ml/min change in the
Vo2) during the last stages of exercise. Usually, a true
Vo2max was attained on the second test, but if the results for the
two exercise tests differed by >200 ml/min, an additional Vo2max
test was performed to meet these criteria.
Metabolic testing
For 3 days before each metabolic test and during testing, subjects were
provided with an American Heart Association weight-maintaining phase 1 diet
(16). If body weight varied by
>0.25 kg during periods of testing, research tests were delayed for 48 h,
and subjects were provided with additional days of food until weight stability
was achieved. All metabolic tests were performed in the morning after a 12-h
overnight fast.
Oral glucose tolerance test
Blood samples were drawn for the measurement of plasma glucose and insulin
before and at 30-min intervals for 2 h after the ingestion of 40 g
glucose/m2 body surface area
(17). The areas under the
curves for the glucose and insulin responses during the 2-h oral glucose
tolerance test (OGTT) were calculated above the basal level using a
trapezoidal model.
Hyperinsulinemic-euglycemic glucose clamp
Whole-body insulin action was measured using the one-step
hyperinsulinemic-euglycemic glucose clamp technique
(4). Briefly, an intravenous
catheter was inserted into an antecubital vein for infusion of insulin and
glucose, and a second catheter was inserted into a dorsal hand vein for blood
sampling. The hand was then placed in a warming box thermostatically
controlled at 70°C to arterialize the blood and allowed to equilibrate for
30 min before baseline samples for glucose and insulin were obtained. After a
priming dose of insulin, Humulin insulin (Eli Lilly, Indianapolis, IN) was
infused at a constant rate of 600 pmol · m-2 ·
min-1. Plasma glucose levels were measured at 5-min intervals using
the glucose oxidase method (Beckman Instruments, Fullerton, CA) and maintained
at basal levels with a variable infusion of 20% glucose, which was adjusted
according to a computerized algorithm. Samples were obtained at 10-min
intervals during the clamp for subsequent measurement of plasma insulin levels
by radioimmunoassay (18).
Calculations
Mean glucose infusion rates (GIRs), normalized for FFM (µmol ·
kg-1 FFM · min-1), were calculated at 10-min
intervals and averaged over the last 30 min of the clamp. Steady-state plasma
insulin levels were averaged over the same interval. HOMA-IR was calculated as
previously described (19):
[(fasting insulin (µU/ml) x fasting glucose [mmol/l])/22.5].
Statistical analyses
Data were analyzed using standard statistical software packages
(20). Plasma insulin
concentrations and HOMA-IR values were logtransformed to yield a normal
distribution before analyses. Differences between groups were determined by
t tests. Pearson correlation coefficients were calculated between
selected variables and GIR and HOMA-IR. When multiple independent variables
correlated with GIR and HOMA-IR, variables with statistically significant
correlations were entered into stepwise multiple regression analysis to
determine the best predictors of GIR and HOMA-IR. P values <0.05
were considered statistically significant. All data are presented as the means
± SD.
 |
RESULTS
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Subject characteristics
The 45 subjects were grouped according to glucose tolerance status, as
determined by the OGTT (21).
There were no differences in age, body weight, or Vo2max between
the 21 men with NGT compared with the 24 men with IGT
(Table 1). The group with NGT had
significantly lower percent body fat, waist circumference, WHR, and BMI in
comparison with the group with IGT (Table
1).
Metabolic differences also were observed between the two groups. The NGT
group had significantly lower fasting glucose and insulin concentrations and
2-h OGTT glucose and insulin areas (above basal) in comparison with the IGT
group (Table 2). During the
hyperinsulinemic-euglycemic clamp, the NGT group had a significantly higher
GIR than the IGT group, despite no difference in the insulin concentrations
during the 600 pmol · m-2 · min-1 insulin
infusion (Table 2). HOMA-IR was
significantly lower in the NGT group than in the IGT group
(Table 2).
Relationships among indexes of IR, subject characteristics, and
glucose tolerance
There was a significant relationship between HOMA-IR and GIR when both
groups were combined (r = -0.39, P < 0.05;
Fig. 1). However, when the
analysis was performed separately on each group, HOMA-IR and GIR correlated
highly and significantly in the NGT group (r = -0.59, P <
0.01; Fig. 1) but not in the
IGT group (r = -0.13, NS), indicating that the significant
correlation in the entire group was due to the NGT group. One subject in the
NGT group had a high GIR (72.7 µmol · kg-1 FFM ·
min-1) and a low HOMA-IR (0.64, log value -0.19), indicating high
sensitivity to insulin. In Fig.
1, this subject appears as an outlier, with a negative value for
the log transformation of HOMA-IR (-0.19). When this subject is removed from
the analysis, the relationship between HOMA-IR and GIR for the entire
population (r = -0.31, P < 0.05) and the NGT group alone
(r = -0.46, P < 0.05) remains significant.

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Figure 1 Relationship of HOMA-IR to GIR in subjects with NGT
( and solid line; r = -0.59, P < 0.01) and in
subjects with IGT ( and dashed line; r = -0.13).
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The relationship between GIR and Vo2max was statistically
significant in both the NGT and IGT groups, whereas the correlation between
GIR and WHR was significant in the NGT group only
(Table 3). There was no
significant relationship between GIR and percent body fat, BMI, or waist
circumference in either group. In a stepwise multiple regression with both
groups combined, only Vo2max predicted GIR (r2
= 0.14, P < 0.05).
There were significant correlations between HOMA-IR and waist circumference
and Vo2max only in the NGT group
(Table 3). The relationship
between HOMA-IR and percent body fat was significant in the IGT group and
approached statistical significance in the NGT group
(Table 3, P = 0.09).
There was no significant relationship between HOMA-IR and BMI or WHR in either
group. In a stepwise multiple regression with both groups combined, HOMA-IR
was predicted only by percent body fat (r2 = 0.25,
P < 0.05). For the NGT group only, both Vo2max
(r2 = 0.29, P < 0.05) and waist circumference
(r2 = 0.12, P < 0.05) predicted HOMA-IR
(r2total = 0.41, P < 0.05).
The relationship between 2-h OGTT insulin areas and GIR was statistically
significant for both the NGT and IGT groups. The relationship between the 2-h
OGTT insulin area and HOMA-IR was statistically significant in the IGT group
only and approached statistical significance in the NGT group (P =
0.06). In a stepwise multiple regression, the 2-h OGTT insulin area was
predicted by both HOMA-IR (r2 = 0.32, P <
0.05) and GIR (r2 = 0.09, P < 0.05).
 |
CONCLUSIONS
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The results of this study show that HOMA-IR is a
statistically significant predictor of IR in middle-aged and older men with
NGT, but not in men with IGT. Although the HOMA-IR model is a relatively
noninvasive and convenient way to estimate IR, its use and validity in older
individuals may be limited, since the prevalence of IGT increases with age. In
contrast, the insulin response during an OGTT correlated with IR measured
during the glucose clamp as well as with HOMA-IR in subjects with either NGT
or IGT. These findings indicate that HOMA-IR should not be used as an index of
IR in older obese individuals or in individuals at high risk for IGT. Rather,
the insulin response during an OGTT may be a better index of IR in older
subjects when glucose clamps cannot be performed to directly assess insulin
action.
The absence of a relationship between HOMA-IR and GIR in individuals with
IGT in this study supports the findings of Anderson et al.
(8), but differs from those of
Matsuda and DeFronzo (7). Since
both studies involved subjects with an average age of 40 years, the findings
are not applicable to the elderly. The lack of a correlation in subjects with
IGT in our study may be because the relationship between HOMA-IR and GIR is
not linear, particularly at the upper limits of HOMA-IR values, which may be
more common in older individuals with IGT. Inaccurate assumptions that may
limit the ability of HOMA-IR to accurately predict IR were recently reviewed
(22). These include the fact
that HOMA-IR is based on fasting glucose and insulin concentrations, both of
which are measures that reflect insulin sensitivity in the basal state, when
the majority of glucose uptake occurs in insulin-independent tissues. Thus, it
may not provide a good measure of insulin action in insulin-sensitive tissues,
such as muscle, in the postprandial phase. Furthermore, the fasting state does
not accurately represent both the hepatic and peripheral components of insulin
action, thus limiting its ability to assess IR. In addition, one of the
assumptions of the HOMA is that the fasting glucose and insulin concentrations
reflect the normal insulin secretory response after a glucose challenge. This
may not necessarily be true in all individuals, particularly those with IGT.
Furthermore, HOMA assumes that fasting insulin is directly related to
whole-body IR. Since few studies have examined insulin action at low insulin
concentrations, it would be difficult to extrapolate values under basal
conditions from the results of a glucose clamp normally performed at
physiological insulin levels. IR is primarily manifest in the postprandial
state and thus, may not be accurately represented by fasting models of IR such
as HOMA-IR (22). Our results
confirm that HOMA-IR is not a valid index of IR in older individuals with IGT
and suggest that insulin responses during the OGTT may be a better surrogate
measure. A similar conclusion was reached in a study by Yeni-Komshian et al.
(10), which showed
approximately two-thirds of the variability in insulin action is explained by
the total insulin area during an OGTT.
We found a significant correlation between GIR and Vo2max in
individuals with either NGT or IGT and between GIR and WHR in the individuals
with NGT. These results are similar to findings from our laboratories as well
as those of other investigators
(23,24,25).
In the present study, there was a significant correlation between HOMA-IR and
both waist circumference and Vo2max in individuals with NGT and
between HOMA-IR and percent body fat in individuals with IGT. Since these
studies were in middle-aged and older men, obesity and WHR may be related,
because older men tend to deposit excess fat centrally. This supports the
tenet that low Vo2max and central obesity are associated with IR in
older individuals and suggests that treatment modalities that increase
Vo2max and decrease body fat may reduce the risk for the
development of IR in healthy older obese men. This notion is supported by our
recent findings that highintensity aerobic exercise and weight loss increase
insulin action, thus increasing insulin sensitivity in obese hypertensive men
with the metabolic abnormalities associated with the IR syndrome
(14). In addition, other
studies have observed improved insulin sensitivity in older individuals after
a regular aerobic exercise program
(26,27).
Although the present study may be one of the first to examine the
relationships between insulin action measured by the glucose clamp and HOMA-IR
with measures of body composition and exercise capacity in middle-aged and
older individuals, it included only Caucasian men, none of whom had type 2
diabetes. Thus, the findings may apply only to nondiabetic obese older
Caucasian men, not older women, older individuals with type 2 diabetes, or
older men from other ethnic groups. Furthermore, our findings show that
Vo2max and percent body fat are the best independent predictors of
GIR and HOMA-IR. This result suggests that lifestyle changes that increase
Vo2max and decrease central obesity may prevent IR and reduce the
risk for type 2 diabetes and the cardiovascular disease complications
associated with the IR syndrome in older men.
 |
ACKNOWLEDGMENTS
|
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This work was supported by a T3200219 training grant, Teaching Nursing Home
Grants P01AG4402, R07AG00608, and R01AG07660 (National Institute on Aging,
National Institutes of Health), a Veterans Affairs Merit Review Entry Program
grant, and the Johns Hopkins Bayview General Clinical Research Center
(M01-RR-02719).
We thank all of the subjects who volunteered, the nursing staff at the
Bayview General Clinical Research Center and GRECC at the Baltimore Veterans
Affairs Medical Center for assistance with research studies, and the exercise
technicians for their exercise testing and body composition measurements.
 |
FOOTNOTES
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Abbreviations: FFM, fat-free mass; GIR, glucose infusion rate; HOMA,
homeostasis model assessment; IGT, impaired glucose tolerance; IR, insulin
resistance; NGT, normal glucose tolerance; OGTT, oral glucose tolerance test;
WHR, waist-to-hip ratio.
A table elsewhere in this issue shows conventional and
Système International (SI) units and
conversion factors for many substances.
Received for publication July 20, 2000.
Accepted for publication October 12, 2000.
 |
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L. S. Conwell, S. G. Trost, W. J. Brown, and J. A. Batch
Indexes of Insulin Resistance and Secretion in Obese Children and Adolescents: A validation study
Diabetes Care,
February 1, 2004;
27(2):
314 - 319.
[Abstract]
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J. Skrha, T. Haas, G. Sindelka, M. Prazny, J. Widimsky, D. Cibula, and S. Svacina
Comparison of the Insulin Action Parameters from Hyperinsulinemic Clamps with Homeostasis Model Assessment and QUICKI Indexes in Subjects with Different Endocrine Disorders
J. Clin. Endocrinol. Metab.,
January 1, 2004;
89(1):
135 - 141.
[Abstract]
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A. Tenerz, A. Norhammar, A. Silveira, A. Hamsten, G. Nilsson, L. Ryden, and K. Malmberg
Diabetes, Insulin Resistance, and the Metabolic Syndrome in Patients With Acute Myocardial Infarction Without Previously Known Diabetes
Diabetes Care,
October 1, 2003;
26(10):
2770 - 2776.
[Abstract]
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A. Katsuki, Y. Sumida, H. Urakawa, E. C. Gabazza, S. Murashima, K. Morioka, N. Kitagawa, T. Tanaka, R. Araki-Sasaki, Y. Hori, et al.
Neither Homeostasis Model Assessment nor Quantitative Insulin Sensitivity Check Index Can Predict Insulin Resistance in Elderly Patients with Poorly Controlled Type 2 Diabetes Mellitus
J. Clin. Endocrinol. Metab.,
November 1, 2002;
87(11):
5332 - 5335.
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G. I. Uwaifo, E. M. Fallon, J. Chin, J. Elberg, S. J. Parikh, and J. A. Yanovski
Indices of Insulin Action, Disposal, and Secretion Derived From Fasting Samples and Clamps in Normal Glucose-Tolerant Black and White Children
Diabetes Care,
November 1, 2002;
25(11):
2081 - 2087.
[Abstract]
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P. Marques-Vidal, E. Mazoyer, V. Bongard, P. Gourdy, J.-B. Ruidavets, L. Drouet, and J. Ferrieres
Prevalence of Insulin Resistance Syndrome in Southwestern France and Its Relationship With Inflammatory and Hemostatic Markers
Diabetes Care,
August 1, 2002;
25(8):
1371 - 1377.
[Abstract]
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