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Departments of Pediatric Endocrinology (M.E.S., A.M.M., L.S.L., A.R.M., S.E.O.) and Medicine (D.J.M.), Columbia University, New York, New York 10032
Address all correspondence and requests for reprints to: Sharon E. Oberfield, M.D., 630 West 168th Street, PH-5E-522, New York, New York 10032. E-mail: seo8{at}columbia.edu
Abstract
Insulin resistance is a strong predictor of the development of type 2 diabetes mellitus and cardiovascular disease. Girls with premature adrenarche (PA) or obesity may be at an increased risk for the development of insulin resistance. Recently, in prepubertal girls with PA, a fasting glucose to insulin ratio (FGIR) of less than 7 was found to be predictive of insulin resistance as determined by the frequently sampled iv glucose tolerance test. We sought to compare the FGIR with 2 insulin sensitivity measures, SiM (an adjusted mean measure of insulin sensitivity based on fasting and 2 h post glucose load insulin sensitivity measures) and the composite whole body insulin sensitivity index, ISI(comp), both derived from the 2-h oral glucose tolerance test in 2 groups of children at risk: girls with PA and obese girls. We studied 25 prepubertal girls with PA and/or obesity and further classified them as insulin resistant (IR) or insulin sensitive (IS) based on the FGIR. Four simple measures of insulin sensitivity [FGIR, quantitative insulin sensitivity check index (QUICKI), fasting insulin resistance index, and fasting insulin] were compared with SiM and ISI(comp). Additionally, we characterized the subjects in terms of risk factors associated with insulin resistance according to their insulin resistance status based on the FGIR.
In our subjects the strongest correlations overall appeared to be between FGIR and SiM, FGIR and ISI(comp), QUICKI and SiM, and QUICKI and ISI(comp) [correlations (r) ranged from 0.81–0.84]. Furthermore, the IR group had higher body mass index and body mass index z-scores and triglyceride levels than the IS group and were over 3 times more likely to have triglycerides greater than the 95th percentile compared with national norms.
We conclude that the FGIR and QUICKI are highly correlated with oral glucose tolerance test measures of insulin sensitivity. An FGIR less than 7 in young girls with PA or obesity may be helpful in the early identification of children at risk for complications of insulin resistance.
INSULIN RESISTANCE is known to be a risk factor for the development of type 2 diabetes mellitus and cardiovascular disease and is associated with dyslipidemia, especially hypertriglyceridemia, and obesity (1, 2, 3). Standard methods of assessing insulin sensitivity include the euglycemic-insulin clamp and the frequently sampled iv glucose tolerance test (FSIVGTT). These tests are cumbersome and difficult to perform in children as well as impractical for the screening of large populations at risk for insulin resistance. Others have sought to define simpler measures of insulin sensitivity. Legro et al. determined that a fasting glucose to insulin ratio (FGIR) correlated strongly (r = 0.73) with insulin sensitivity using the FSIVGTT and calculated by the minimal model (4). An FGIR less than 4.5 was predictive of insulin resistance in obese Caucasian women with polycystic ovarian syndrome (PCOS) over the age of 18 yr, and thus was offered as a useful screening test for insulin resistance in this group. DiMartino-Nardi found a strong correlation (r = 0.76) between the FGIR and insulin sensitivity by the FSIVGTT in prepubertal girls with premature adrenarche (PA), another population at risk, and found that a value of less than 7 identified girls with insulin resistance (5).
Recently, Katz et al. defined the quantitative insulin sensitivity check index (QUICKI), a novel and simple method of assessing insulin sensitivity using the inverse of the sum of the logs of fasting glucose and insulin levels; there was a very strong correlation between the QUICKI and the glucose clamp method in a group of obese (r = 0.89) and nonobese (r = 0.49) adults as well as diabetic subjects (r = 0.70) (6). The fasting insulin resistance index (FIRI), based on the product of basal insulin and glucose levels, has been shown to correlate strongly (r = 0.79) with insulin sensitivity according to the Bergman minimal model (7, 8). There is near-perfect correlation between FIRI and the homeostasis model assessment (7, 9).
Insulin sensitivity measures derived from the standard 2-h oral glucose tolerance test (OGTT) also correlate very well with insulin sensitivity as determined by clamp studies and the FSIVGTT (10, 11). Avignon et al. showed that SiM, an adjusted mean measure of insulin sensitivity calculated using the basal and 2-h insulin and glucose values, was very highly correlated (r = 0.90) with insulin sensitivity assessed by minimal model analysis of an insulin-modified FSIVGTT across a wide range of glucose tolerance (8, 10). A composite whole body insulin sensitivity index, ISI(comp), has been proposed and validated (r = 0.73) against the euglycemic insulin clamp by Matsuda and DeFronzo (11).
In adults it is well known that acanthosis nigricans (AN) is associated with insulin resistance and an increased risk for the long-term complications of insulin resistance such as diabetes (12). AN has also been proposed as a marker for insulin resistance in children (13, 14). However, AN has also been reported in healthy nonobese children (15). It is unclear whether children with AN have the same metabolic complications as adults.
The primary purpose of the present study was to compare several simple measures of insulin sensitivity (FGIR, QUICKI, FIRI, and fasting insulin) with insulin sensitivity based on the OGTT [SiM and ISI(comp)] in two groups of prepubertal girls at risk for insulin resistance: girls with premature adrenarche and obese girls (13, 16, 17, 18). The secondary aim was to further characterize the subjects in terms of risk factors for diabetes and cardiovascular disease according to their insulin resistance status based on the FGIR.
Experimental Subjects
Twenty-five prepubertal girls (22 Hispanic, 2 black, and 1 white) were enrolled in the study: 18 with premature adrenarche and 7 with obesity. Informed consent from a legal guardian of each subject and assent from subjects over the age of 7 yr were obtained before participation in the study. The study was approved by the institutional review board of Columbia-Presbyterian Medical Center.
The criteria for entry into the study in the PA group included the appearance of pubic hair before 8 yr of age, adrenal androgens in the Tanner stage 2 range, no breast development on physical examination, and no evidence of an adrenal enzyme defect or other endocrine disorder (19). Body mass index (BMI) and BMI z-scores were calculated for all subjects; obesity was defined as a BMI z-score greater than 2 for age and sex, based on 1 SD reference data for obesity developed from National Health and Nutrition Examination Survey (NHANES) I (20). The entry criteria for the obese group also included the absence of breasts and pubic hair on physical examination and no evidence of hypothyroidism or other endocrine disorder. The subjects were further divided into subgroups based on FGIR: insulin resistant (IR), with an FGIR less than 7, and insulin sensitive (IS), with an FGIR greater than or equal to 7 (5). All subjects were examined for the presence of AN.
Materials and Methods
OGTT
Twenty-one of the 25 subjects (16 PA and 5 obese) underwent a 3-h 1.75 g/kg BW (maximum, 75 g) OGTT after an overnight fast. Before and 30, 60, 90, 120, and 180 min after the ingestion of oral glucose, blood was sampled for plasma glucose and serum insulin measurements. In addition, all subjects had fasting levels of lipids, androgens, and sex hormone-binding globulin (SHBG) measured.
Measures of insulin sensitivity
FGIR was calculated as fasting plasma glucose (G0) divided by fasting serum insulin (I0) levels (4). QUICKI was calculated as 1/(logG0 + logI0) (6). FIRI was calculated as the product of fasting insulin (in microunits per mL) and glucose (in millimoles per L) divided by 25 (7). SiM was calculated according to the following formula: SiM = [(0.137)(108)/(I0)(G0)(VD) + (108)/(I2 h)(G2 h)(VD)]/2, where I2 h is insulin at 2 h during the OGTT, G2 h is glucose at 2 h during the OGTT, and VD is the volume of distribution (150 mL/kg BW) (10). ISI(comp) was calculated as: 10,000 ÷ square root of (G0)(I0)(MSI)(MBG), where MSI is mean serum insulin, and MBG is mean blood glucose (11).
Laboratory data
Insulin (by immunochemiluminometric assay), androgens, and SHBG were measured by Endocrine Sciences, Inc. (Calabasas Hills, CA). Plasma glucose levels were measured by the glucose hexokinase method. Plasma total and high density lipoprotein (HDL) cholesterol, and triglycerides were measured using the Hitachi analyzer in the Core Laboratory of the General Clinical Research Center at Columbia-Presbyterian Medical Center. Low density lipoprotein (LDL) was calculated using the Friedewald formula (21).
Statistical analysis
Descriptive statistics were calculated for all variables and distributions visually examined. Comparisons between groups on continuous measures used Student’s t test with Saitherwaite correction in the event of statistically unequal variances. For intragroup analysis, the PA group was further divided into obese and nonobese subgroups. The Pearson r correlation was computed as a measure of the strength of association between continuous measures. The proportion of cases exceeding the 95th percentile on total cholesterol, triglycerides, and LDL and less than the 5th percentile on HDL was expressed as an odds ratio (with 95% confidence limits) calculated from the age-specific normative data published by the Lipid Research Clinics Prevalence Study (North America) (22). No adjustment for multiple comparisons was made.
Results
Clinical and laboratory data (Table 1
)
Clinical and laboratory characteristics are given in Table 1. The
mean ages of the PA and obese groups were 6.9 and 8.4 yr, respectively.
The mean BMI and BMI z-score were 21.3 and 3.2 in the PA group and 31.0
and 6.0 in the obese group, respectively. Two subjects (1 PA obese and
1 obese) were found to have impaired glucose tolerance. Seven of the 18
PA girls and 5 of the 7 obese girls were insulin resistant, as defined
by an FGIR less than 7. All of the insulin-resistant PA subjects were
obese. However, 4 of the 11 obese PA girls were insulin sensitive. All
nonobese PA girls were insulin sensitive. AN and a positive family
history for diabetes mellitus and coronary heart disease were common in
all groups.
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)
Correlations of simple insulin sensitivity measures with SiM and
ISI(comp) for PA group are shown in Table 2. In the 21 patients
considered as a whole, FGIR was highly correlated with SiM (r =
0.84) and ISI(comp) (r = 0.81). QUICKI also correlated strongly
with both SiM and ISI(comp) (r = 0.82). The relationships between
FIRI and SiM, FIRI and ISI(comp), I0 and SiM, and
I0 and ISI(comp) did not appear to be as strong
[correlations (r) ranged from -0.57 to -0.67]. These
correlations did not reach statistical significance in the obese group,
except for I0 with SiM. FGIR and QUICKI were
similarly strongly correlated with SiM and ISI(comp) in the PA group as
a whole and in the PA obese subgroup. BMI and BMI z-score were
significantly correlated [range of correlations (r) =
|0.60–0.81|] with all insulin sensitivity measures examined. Age
did not correlate significantly with any insulin sensitivity measure.
Additionally, we compared insulin resistance status defined by FGIR
(<7 IR, 
7 IS) to insulin levels during the OGTT, defining insulin
resistance by OGTT as 2 or more insulin levels greater than 120 µU/mL
or greater than the 90th percentile for children (23, 24, 25, 26).
Eight of the 10 girls classified as IR by FGIR and only 2 of the 11
classified as IS by FGIR were insulin resistant by OGTT, suggesting
positive and negative predictive values of 80% and 82%, respectively,
for the FGIR compared with insulin levels obtained during the OGTT.
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There was a modest correlation in the PA group between SHBG and all six measures of insulin sensitivity [range of correlations (r) = |0.44–0.69|] as well as between free testosterone, but not total testosterone, and SiM (r = -0.52).
Clinical and biochemical features of subjects according to insulin
sensitivity status based on FGIR (Tables 1
and 3 and Fig. 1)
The PA subjects with an FGIR less than 7 (IR) had higher BMI and
BMI z-scores, fasting insulin, and free testosterone levels; lower SHBG
levels; and similar ages and total cholesterol, LDL, and HDL levels
compared with those with an FGIR of 7 or more (IS) (Tables 1 and 3).
Although not reaching statistical significance, there was a trend
toward higher triglycerides in all IR subjects compared with all IS
subjects and in PA IR compared with PA IS subjects (Table 3). Eleven of
the 12 patients classified as IR by FGIR and 9 of the 13 classified as
IS were noted to have AN. A family history of adult-onset diabetes
mellitus and/or coronary heart disease was frequently elicited and was
seen more commonly in the PA IR than in the PA IS group (Table 1). No
significant differences were seen in the birth weights of the IR and IS
groups, nor did birth weight correlate significantly with any insulin
sensitivity measure examined.
|
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, grouped according to insulin resistance status by FGIR
(22). The PA subjects were at a 7-fold increased risk of
having elevated triglycerides and low HDL compared with national norms.
The IR groups were 3–4 times more likely than the IS groups to have
triglycerides in the highest 5th percentile and almost twice as likely
overall to have an HDL in the lowest 5th percentile. Discussion
Our results indicate that FGIR and QUICKI as well as other simple measures of insulin sensitivity using only fasting glucose and insulin levels correlate strongly with two measures of insulin sensitivity based on the OGTT, SiM and ISI(comp), in this small group of prepubertal, predominantly Hispanic girls with premature adrenarche and/or obesity. Overall, of the four simple measures examined, FGIR and QUICKI appear to have the strongest relationship with the OGTT measures, although larger numbers of subjects would be needed to conclude that they are statistically significantly stronger than the other measures. In contrast to the multiple blood samples, length of time, and personnel required for the OGTT, these measures can be obtained easily from a single fasting blood sample. As expected, insulin sensitivity did not change with age in these prepubertal children (27). Although AN can be a marker of insulin resistance in many children, it also occurs in some healthy nonobese children (13, 14, 15). AN was seen in over half of the insulin-sensitive subjects, many of whom were nonobese, suggesting that it lacks specificity for insulin resistance in our young, predominantly Hispanic study population.
When we performed subgroup comparisons between FGIR or QUICKI and the OGTT measures, the correlations did not appear to be as strong for the nonobese PA group. Legro et al. predicted this for nonobese PCOS women due to the lack of basal hyperinsulinemia and normal hepatic glucose production (4). An alternative explanation in our group of subjects is the limitation of assay sensitivity at the lowest insulin levels, as is seen most often in the nonobese, insulin-sensitive subjects. Further studies with a greater number of nonobese girls are needed to clarify this relationship. One would also expect a weaker relationship between FGIR and the OGTT measures in the setting of impaired glucose tolerance or any relative insulin deficiency state, given that for a fixed degree of glucose tolerance, the product of insulin sensitivity and ß-cell function is constant (10, 28). Therefore, in the setting of relative insulin secretory insufficiency, one can have a falsely reassuring FGIR. In our study the two children who were probably misclassified as insulin sensitive by the FGIR had evidence of relative insulin deficiency on OGTT and borderline FGIR values of 7.5 and 7.8. Both subjects with glucose intolerance in our study had unfavorable FGIRs, but larger studies of glucose-intolerant children will be needed to determine whether this is in fact the case. In children, another consideration in interpreting the FGIR is significant emotional stress at the time of the blood test. In one subject identified as clearly very stressed at the beginning of the test, the fasting glucose and especially the insulin levels were elevated, resulting in a falsely abnormal (low) FGIR with an otherwise normal glucose tolerance test. The effects of insulin pulsatilily, stress, and exercise on this measure are not known and may affect its reproducibility.
An FGIR cut-off for insulin resistance of below 4.5 in obese White women with PCOS and below 7 in a small group of young black and Hispanic girls with PA has been validated against an IVGTT (4, 5). The lower ratio developed for assessing insulin resistance in the adult women reflects at least in part the fact that an obese group of women was used to define the normal range (4). Other possible factors are differences in age and ethnicity. Further studies are needed in other groups of children, particularly other racial and ethnic groups, as the FGIR cut-off for insulin resistance may vary with the population studied. Additionally, further validation of our preliminary findings will be required in our young obese subjects.
The clustering of risk factors well known to be associated with insulin resistance (increased BMI and BMI z-score, hypertriglyceridemia, family history of diabetes mellitus, and low SHBG) according to insulin resistance status based on the FGIR cut-off of 7 lends further support for the usefulness of this measure in identifying children at risk for insulin resistance and its complications. Obese children are at an increased risk for insulin resistance and dyslipidemia (18, 29). Hyperinsulinemia and increased triglyceride levels, probably secondary to insulin resistance, have been reported in girls with premature adrenarche (17, 30). Clustering of metabolic markers of insulin resistance has been noted in normal children and girls with premature adrenarche (31, 32). Whether these children are at an increased risk of developing diabetes mellitus and coronary heart disease later in life remains to be seen. Our PA obese subjects were twice as likely as our small group of obese subjects to have triglyceride levels greater than the 95th percentile for age and sex, not attributable to differences in BMI or BMI z-score, suggesting that they may be the group most at risk. There is good evidence suggesting that hyperinsulinemia in women with PCOS contributes to hyperandrogenism by inhibiting hepatic SHBG production (33). Low SHBG is associated with hyperinsulinemia in girls with premature pubarche as well (30). The correlation between all measures of insulin sensitivity and SHBG in our group of PA girls supports this. Ibanez et al. reported lower birth weight SD score in nonobese girls with premature pubarche compared with normal girls (34). DiMartino-Nardi reported lower birth weights in insulin-resistant (by IVGTT), compared with insulin-sensitive, PA girls (5). A common prenatal origin has been hypothesized to explain the relationship among fetal growth, premature adrenarche, and insulin resistance (35). In our study birth weights did not differ between insulin-resistant and insulin-sensitive groups. Our findings may differ due to the method of assessing insulin sensitivity employed or differences in the study population.
Conclusions
Our results indicate that FGIR and QUICKI, easily obtained measures, are strongly correlated with more dynamic measures of insulin sensitivity in prepubertal girls with premature adrenarche and/or obesity. Further, given the epidemic of obesity and the alarming rise of type 2 diabetes mellitus in children, the FGIR, which requires minimal calculation to derive, may prove most useful in the identification of the increasing number of children at risk for insulin resistance and its complications (36). These children can then be targeted for early conservative intervention with diet, exercise, and behavioral therapy, which, we speculate, may prevent the complications of insulin resistance. The validity of these measures will need to be confirmed in other populations.
Acknowledgments
We thank members of the Pediatric Endocrine Division at Columbia-Presbyterian Medical Center and Dr. Nan Salomon for their kind referral of subjects, as well as the subjects for agreeing to participate. We also thank the nurses and staff of the Pediatric General Clinical Research Center for their outstanding help, and Thomas Toothaker for his expert data management. We gratefully acknowledge Endocrine Sciences, Inc., and the General Clinical Research Center laboratory for performing laboratory measurements. We thank Dr. S. Arslanian for initial review of our data and helpful suggestions.
Footnotes
1 This work was supported in part by grants from the NIH (Grant
RR-00645), Eli Lilly & Co., Pharmacia & Upjohn, Inc., and Genentech, Inc. Presented in part at the
Annual Meeting of The Endocrine Society, Toronto, Canada, 2000. 
2 Recipient of an Endocrine Society Travel Award.
Received November 16, 2000.
Revised January 26, 2001.
Revised February 15, 2001.
Accepted February 16, 2001.
References
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