OBJECTIVE—To validate fasting indices of insulin sensitivity and secretion in a diverse pediatric population against gold standard estimates from euglycemic and hyperglycemic clamps.

RESEARCH DESIGN AND METHODS—A total of 31 children (mean BMI 25.1 ± 4.9 kg/m2, mean age 8.7 ± 1.4 years, 15 girls and 16 boys, 12 black and 19 white) underwent euglycemic and hyperglycemic clamps 2–6 weeks apart to derive insulin sensitivity indices (SI Eug clamp and SI Hyper clamp). Fasting samples were used to derive the homeostasis model assessment of insulin resistance index (HOMA-IR), HOMA of percent β-cell function (HOMA-B%), quantitative insulin sensitivity check index (QUICKI), insulinogenic index, antilipolytic insulin sensitivity index (ISI-FFA), and C-peptide–to–insulin ratio.

RESULTS—The QUICKI correlated best with SI Eug clamp (r = 0.69, P < 0.05) and had greater correlations to SI Eug clamp than did either SI Hyper clamp (r = 0.45, P < 0.05) or the HOMA-IR (r = −0.51, P < 0.05). Both fasting insulin and the insulinogenic index correlated well with first- and steady-phase insulin secretion (r’s from 0.79 to 0.86, P < 0.05). HOMA-B% was not as highly correlated (r = 0.69–0.72, P < 0.05). Fasting C-peptide–to–insulin ratio was not significantly correlated with clamp-derived metabolic clearance rate of insulin. ISI-FFA was not correlated with the degree of free fatty acid suppression obtained from the clamps.

CONCLUSIONS—The QUICKI, fasting insulin, and the insulinogenic index all closely correlate with corresponding clamp-derived indices of insulin sensitivity and secretion in this diverse pediatric cohort. These results, if replicated in similarly diverse populations, suggest that estimates based on fasting samples can be used to rank order insulin secretion and sensitivity in pediatric cohorts.

Obesity and type 2 diabetes are diseases that have assumed considerable public health importance in the 21st century in both developed and developing countries (13). The increased prevalence of both these conditions in children adds an added dimension of seriousness to these modern day epidemics (4). Since insulin resistance appears central to the development of the metabolic syndrome X (1,5), accurate quantification of insulin’s in vivo action, secretion, and disposal is necessary. While a combination of hyperglycemic and euglycemic-hyperinsulinemic clamp studies supplies the gold standard for quantifying these parameters (6), clamp studies are expensive and difficult tests to perform and require highly trained personnel. The difficulties with obtaining sequential clamp studies are even more pronounced for young children who may have more difficulty with clamp procedure requirements.

For the purpose of epidemiologic studies, several indices based on fasting blood that estimate insulin sensitivity, secretion, and disposal have been developed for adults. The homeostasis model assessment of insulin resistance index (HOMA-IR), the HOMA of percent β-cell function (HOMA-B%), the insulinogenic index, and the QUICKI are among the best validated and most widely used (79). Validation for these indices in pediatric populations using gold standard clamp studies is largely lacking. Therefore, to examine the relationships between fasting indices of insulin sensitivity and secretion to clamp-derived estimates, we recruited a diverse population of children, obtained euglycemic and hyperglycemic clamps, and compared the insulin profile indices from clamp studies with those derived from fasting blood.

Subjects

Overweight and nonoverweight children were recruited for metabolic studies through mailed notices to 6- to 12-year-old children in the Montgomery and Prince George’s Counties, Maryland school districts, as well as in the Washington D.C. area, and through local physician referrals and advertisements in local newspapers. All subjects had normal history and physical examinations, as well as normal baseline blood chemistry, hepatic, and thyroid function. None of the subjects had any significant medical illness and none were taking medications known to impact insulin sensitivity. All of the nonobese children had two overweight parents, because such children are considered to have a condition, namely a predisposition to develop obesity, that can justify studying them with procedures that may constitute a minor increment over minimal risk. The clinical protocol was approved by the National Institute of Child Health and Human Development (NICHD) institutional review board. Informed consent and assent were obtained from parents and children.

Clinical protocol

Subjects were studied at the Warren Grant Magnuson Clinical Center of the National Institutes of Health. Each subject had a full history and physical examination. BMI was calculated and BMI SD score (BMI SDS) was computed for each subject by using the formula BMI SDS = (actual BMI − mean BMI for age, race, and sex)/BMI SD for age, race, and sex based on established standards and norms (10). Breast development was recorded according to Tanner stages, and testicular volumes were measured according to methods of Prader (11). Weight was measured to the nearest 0.1 kg using a calibrated digital scale (Scale-Tronix, Wheaton, IL). Height was measured in triplicate to the nearest 1 mm using a stadiometer calibrated before each set of measurements (Holtain Crymych, Wales, U.K.).

A hyperglycemic clamp study was subsequently performed, and 2–6 weeks later, subjects underwent a euglycemic clamp study. Hyperglycemic and euglycemic clamp studies were carried out using a modification of the methods described by DeFronzo et al. (6) with serial measures of insulin, glucose, C-peptide and free fatty acids (FFAs) (12). Fasting glucose, insulin, C-peptide, and FFAs were obtained at the beginning of each of these studies in triplicates and the means were used for the derived indices.

The euglycemic clamp studies involved a continuous infusion of regular insulin (Humulin S; Eli Lily, Indianapolis, IN) at a rate greater than 40 mU · m−2 body surface area · min−1 during the 180-min duration of the test. This rate was chosen to achieve sustained plasma insulin levels above 1,500 pmol/l in order to completely suppress endogenous hepatic glucose output. Plasma glucose during the studies were maintained within the “normal” range of 5.3–5.8 mmol/l using a continuous infusion of variable amounts of 20% dextrose as previously described. (6). Infusion adjustments were made every 5 min and steady-state hyperinsulinemia (plasma insulin >1,500 pmol/l) with coincident euglycemia (plasma glucose between 5.3 and 5.8 mmol/l) was achieved for all subjects in the study between the 120- to 180-min periods of the test, which was the designated steady-state period. The procedure for the hyperglycemic clamp studies has been published previously (12).

Plasma FFAs were measured during the clamps using an enzymatic colorimetric assay (Wako Laboratories, Richmond, VA). Plasma glucose was concurrently measured using a glucose analyzer (Yellow Springs Instrument, Yellow Springs, OH), calibrated to within 5% of multiple glucose standards (50, 100, 125, 150, 250, and 500 mg/dl) before each study and using a Hitachi 736-30 analyzer (Boehringer Mannheim, Indianapolis, IN). Plasma insulin was measured by the TOSOH two-site immunoenzymometric assay (Covance, Vienna, VA). The cross-reactivity of the assay with proinsulin and C-peptide are both <1% while the mean inter- and intra-assay coefficients of variation are 5.8 and 3.6%, respectively. Serum C-peptide was assayed during the same time points of the studies using the analyte-specific reagents immunochemiluminometric assay (ICMA) method (Mayo Medical Laboratories, Rochester, MN).

All subjects also had an oral glucose tolerance test (OGTT) performed. This involved administration of 1.75 g/kg body wt of glucose (as a cola syrup called glucola) at the initiation of the test. The maximum dose administered was 75 g, and the samples for plasma glucose and insulin were obtained at baseline and 2 h later. The details of the methodology are as previously described (12). The definitions for normal, impaired fasting glucose, impaired glucose tolerance, and diabetes based on the OGTT were based on the established American Diabetes Association criteria (13).

Derived indices from clamp studies

Whole-body glucose uptake from the hyperglycemic clamp studies was estimated as the metabolic rate (M), defined as the infusion rate of exogenous glucose administered, corrected for urinary glucose losses and the glucose space correction (6,14). As a measure of insulin sensitivity (SI Hyper clamp), the ratio of metabolic rate to steady-state insulin (M/I) was calculated (6,14). Whole-body glucose uptake from the euglycemic clamp studies was estimated as the metabolic rate (M), defined as the infusion rate of exogenous glucose administered, corrected for urinary glucose losses and the glucose space correction (6,14). The metabolic clearance rate (MCR) for insulin was computed as the insulin infusion rate divided by the increase in plasma insulin concentration above baseline (6). As a measure of insulin sensitivity (SI Eug clamp), the ratio of metabolic rate to steady-state insulin (M/I) was calculated (6,14). The first-phase and steady-state insulin and C-peptide levels were derived from the hyperglycemic clamp study as indices of pancreatic β-cell secretory capacity (6,15). The C-peptide–to–insulin molar ratios for the first-phase and steady-state phase of the hyperglycemic clamp study were derived as indices of dynamic hepatic insulin clearance, respectively (15,16). The degree of FFA suppression from baseline during the clamp studies was utilized as an index of insulin’s sensitivity as an antilipolytic (17,18).

Derived indices from fasting blood samples

The HOMA-IR, QUICKI index, and fasting glucose–to–insulin ratios were derived as estimates of insulin sensitivity (7,8). HOMA-IR was computed using the following formula: (fasting insulin in μU/ml × fasting glucose in mmol/l)/22.5, while QUICKI was computed as 1/(log fasting insulin in μU/ml + log glucose in mg/dl). In addition to the fasting C-peptide and insulin levels, the insulinogenic index and the HOMA-B% were derived as indices of pancreatic β-cell function (7,9). The insulinogenic index was computed as the ratio of fasting insulin in μU/ml and fasting glucose in mg/dl, while the HOMA-B% was computed as 20 × fasting insulin in mU/l/(fasting glucose in mmol/l − 3.5). The fasting C-peptide–to–insulin molar ratio was considered an index of hepatic insulin clearance. Estimates of insulin’s antilipolytic effect based on fasting insulin and FFA levels were obtained using the nomogram reported by Belfiore et al. (19,20).

Statistical analysis

The derived data were analyzed using JMP IN version 3.2.1 software for Windows (1989–1997; SAS Institute, Cary, NC) and StatView version 5.0.1 for Windows (1992–1998; SAS Institute). Standard tests of data symmetry using skewness and kurtosis were performed on all data, and normality was tested using the Shapiro-Wilkes test. Nonnormal data were transformed by common log or other transformation procedures to achieve data symmetry and normality before use of parametric tests. Data that could not be normalized by transformation procedures were analyzed using equivalent nonparametric tests. Unless otherwise indicated, data are reported as mean ± SD. Correlations between parameters were evaluated using Spearman correlation coefficients. Comparisons between groups of data were done using unpaired Student’s t tests, ANOVA, or ANCOVA. P < 0.05 was considered significant for all the data analyses.

A total of 31 children (12 black and 19 white) were studied (Table 1). Of the study subjects, 81% were obese, having a BMI percentile ≥95th percentile for age, sex, and race (4).

All the children had normal OGTTs. There were no children with diabetes, impaired fasting glucose, or impaired glucose tolerance. The mean fasting glucose and insulin levels are as shown in Table 2 while the corresponding mean 2-h glucose and insulin values are 5.98 ± 0.87 mmol/l and 536.2 ± 578.5 pmol/l.

The mean fasting data obtained at the baseline for each of the two clamp studies (based on triplicates) were found to be concordant based on correlation coefficients (all >0.85 with P values all <0.01) and Bland-Altman concordance plots (data not shown). The means of these fasting data are presented in Table 2. No subject had impaired fasting glucose. The mean HOMA-IR was at the upper limit of adult-established norms, while the QUICKI index was comparable to norms established for nonobese adults (7,8). The mean ISI-FFA was below the adult established norms for nonobese subjects, which is consistent with the fact that this was a predominantly obese cohort of children (20). Both QUICKI and HOMA-IR were significantly related to the BMI SDS (Fig. 1).

Table 3 shows the mean insulin sensitivity, secretion, and clearance parameters derived from the clamp studies and demonstrates the wide range of values observed. Spearman correlation coefficients between the fasting and clamp estimates (Table 4 and Fig. 2) demonstrate that the best fasting indices of pancreatic β-cell secretory capacity were the fasting insulin and insulinogenic index, rather than the HOMA-B%. The correlation coefficient between SI Eug clamp and the QUICKI (r = 0.69) was greater than that between SI Eug clamp and SI Hyper clamp (r = 0.45, P < 0.05) or between SI Eug clamp and HOMA-IR (r = −0.51, P < 0.05). The fasting measures of insulin’s lipid-modulating effect, however, were not significantly correlated with the degree of FFA suppression during the clamp studies. The fasting C-peptide–to–insulin ratio (an index of hepatic insulin clearance) was not significantly correlated with either the MCR of insulin (from the euglycemic clamp) or the steady-phase C-peptide–to–insulin ratio (from the hyperglycemic clamp), although it was correlated with the first-phase C-peptide–to–insulin ratio (from the hyperglycemic clamp).

We found in a diverse cohort of children (n = 31) aged 6.2–11.3 years that fasting indices of insulin sensitivity correlated well with estimates obtained from the gold standard method, the euglycemic-hyperinsulinemic clamp. In addition, the fasting insulin and insulinogenic indices were found to correlate well with the gold standard method for estimating pancreatic β-cell secretion, the hyperglycemic clamp. Although the hyperglycemic clamp is being increasingly used to estimate insulin sensitivity, it is crucial to note that this has significant limitations and potential caveats (14,21) and that the euglycemic clamp remains the most robust method for quantifying glycemic insulin sensitivity (14,21). Fasting estimates of insulin’s ability to modulate FFAs did not, however, correlate with the degree of FFA suppression from either clamp study. The fasting C-peptide–to–insulin molar ratio did not correlate with the MCR from the euglycemic clamp or with the steady-phase C-peptide–to–insulin ratio, but it did correlate with the first-phase C-peptide–to–insulin ratio, suggesting that this index may possibly be a useful surrogate of hepatic insulin clearance but not of total insulin clearance.

Although they clearly yield the most robust measures of insulin sensitivity, pancreatic β-cell secretion, and total insulin clearance (6), the combined clamp studies are difficult to perform, require sophisticated equipment and highly trained staff, and carry the potential risks of hypoglycemia if intravenous access is lost during the hyperinsulinemic clamp.

Since its initial description (7), the HOMA-IR has been validated in diverse adult populations (2228). There are, however, few data on its utility in pediatric populations (29) and, to our knowledge, no pediatric information on its validation against clamps. Our cohort showed a significant correlation between the HOMA-IR and the SI estimates from both the euglycemic and hyperglycemic clamps (−0.51 and −0.56, respectively). These correlation coefficients were comparable to that between the SI Hyper clamp and the SI Eug clamp. However, the more recently developed QUICKI index, which has been suggested to have excellent correlation with clamp-derived insulin sensitivity estimates in adults (8,30,31), had a significantly greater correlation with SI Eug clamp. As with the HOMA-IR, there are to our knowledge no validation data of the QUICKI with clamp indices in children (29). However, a recent report in abstract form documents similar trends in a large cohort of children on whom fasting data and euglycemic clamps were obtained (32). Silfen et al. (33) have, however, previously found that in a cohort of preubertal girls with premature adrenarche and/or obesity, QUICKI correlated well with OGTT-derived estimates of insulin sensitivity.

Among the measures of pancreatic β-cell–secretory capacity, the first-phase and steady-state insulin secretion from the hyperglycemic clamp studies are believed to give the most robust estimates (6). The HOMA-B% first described by Matthews et al. (7) correlated reasonably well with these measures; however, the simpler insulinogenic index and fasting insulin levels had even higher correlations (r = 0.79–0.86). This finding has also been described in several adult studies (9,3436).

Based on known secretion and kinetics patterns of C-peptide and insulin, (15,37,38) the molar C-peptide–to–insulin ratio has been suggested as a good surrogate of hepatic insulin clearance. Our data did not show a significant correlation between the fasting C-peptide–to–glucose ratio and MCR from the euglycemic clamp. Thus, the C-peptide–to–insulin ratio cannot be recommended as a surrogate for the euglycemic clamp MCR. Similarly, the ISI-FFA, which has been validated in adults (20), did not correlate with the degree of FFA suppression during clamp studies and thus appears to be an inadequate substitute for the clamp-derived measures.

Overall, our study results suggest that the fasting-derived QUICKI index and insulinogenic index have significant predictive value for estimating both insulin sensitivity and pancreatic β-cell secretion in children and could thus be used in large epidemiologic studies of pediatric populations. However, there are some important caveats to mention in interpreting these findings. First, there is biological variability in fasting glucose and insulin levels, and some have expressed concerns regarding the degree of repeatability of the fasting data upon which these indices are dependent (39). In the current study, we found no statistically significant differences between measures obtained from the two clamp studies (performed 2–6 weeks apart). Second, reports in adult cohorts suggest limitations in the utility of the HOMA-IR in men with impaired glucose tolerance (40) and in the QUICKI’s ability to detect changes in insulin sensitivity brought about by exercise training (41). As no pediatric subjects with impaired glucose tolerance were studied, and given that no data were obtained in relation to exercise training, we do not know if these limitations will also apply to these indices in children. Third, the relatively small sample size of our cohort makes it insufficiently powered to perform subgroup analyses of the potential confounding effects of sex, pubertal status, obesity versus leanness, and ethnicity on these findings. Finally, it is known that by measuring only the fasting glucose concentration (which is largely dependent on baseline hepatic glucose output), one cannot identify patients who may have impaired glucose tolerance and/or diabetes despite having normal fasting glucose (42,43). There is a similar discordance between fasting and postprandial insulin levels, which could thus result in fasting-based indices that underestimate insulin resistance (44). Based on these important caveats, it seems that indices based exclusively on fasting data rather than dynamic data are best restricted to use in large epidemiologic studies rather than smaller intervention and/or screening metabolic studies.

In summary, for a diverse group of lean and overweight children, the QUICKI correlated most closely with the SI Eug clamp and the insulinogenic index, and fasting insulin correlated closely with both first-phase and steady-phase hyperglycemic clamp insulin secretion. Fasting estimates of hepatic insulin clearance did not, however, correlate with MCR of insulin, nor did fasting estimates of insulin’s antilipolytic effect correlate with the degree of FFA suppression from clamp studies. If these findings are replicated in larger, similarly diverse pediatric cohorts, it would suggest a place for the use of these fasting indices in large epidemiological surveys. However, while these fasting indices of insulin sensitivity and secretory capacity might be suitable for large epidemiological studies of pediatric populations, their use cannot fully substitute for more accurate measures of insulin sensitivity and secretory capacity.

Figure 1—

Correlation plot of fasting insulin sensitivity indices and BMI SDS. A: Correlation between QUICKI and BMI SDS. B: Correlation between HOMA-IR and BMI SDS.

Figure 1—

Correlation plot of fasting insulin sensitivity indices and BMI SDS. A: Correlation between QUICKI and BMI SDS. B: Correlation between HOMA-IR and BMI SDS.

Close modal
Figure 2—

Correlation plots of fasting and clamp-derived indices of insulin secretion, sensitivity, and clearance. A: Fasting insulin to first-phase insulin. B: Insulinogenic index to first-phase insulin. C: QUICKI to SI from euglycemic clamp (SI Eugly.). D: Fasting C-peptide-to-insulin to MCR for insulin. All r values in correlation plots are Pearson’s correlation coefficients.

Figure 2—

Correlation plots of fasting and clamp-derived indices of insulin secretion, sensitivity, and clearance. A: Fasting insulin to first-phase insulin. B: Insulinogenic index to first-phase insulin. C: QUICKI to SI from euglycemic clamp (SI Eugly.). D: Fasting C-peptide-to-insulin to MCR for insulin. All r values in correlation plots are Pearson’s correlation coefficients.

Close modal
Table 1—

Subject demographics

n 
Sex (F/M) 15/16 
Race (W/B) 19/12 
Girls’ breast Tanner stage 9 Tanner 1, 5 Tanner 2, 1 Tanner 3 (range 1–3) 
Boys’ Tanner pubic hair stage 14 Tanner 1, 2 Tanner 2 (range 1–2) 
Girls’ Tanner pubic hair stage 9 Tanner 1, 4 Tanner 2, 2 Tanner 3 (range 1–3) 
Boys’ testicular volume 2.0 ± 0.8 (1–4) 
Age (years) 8.7 ± 1.4 (6.2–11.3) 
Weight (kg) 48.5 ± 14.5 (26.5–73.9) 
BMI (kg/m225.1 ± 4.9 (17.5–35.0) 
BMI SDS +3.3 ± +2.4 (+0.3 to +9.8) 
Waist circumference (cm) 73.8 ± 10.5 (54.2–90.8) 
Hip circumference (cm) 84.8 ± 11.7 (64–105) 
n 
Sex (F/M) 15/16 
Race (W/B) 19/12 
Girls’ breast Tanner stage 9 Tanner 1, 5 Tanner 2, 1 Tanner 3 (range 1–3) 
Boys’ Tanner pubic hair stage 14 Tanner 1, 2 Tanner 2 (range 1–2) 
Girls’ Tanner pubic hair stage 9 Tanner 1, 4 Tanner 2, 2 Tanner 3 (range 1–3) 
Boys’ testicular volume 2.0 ± 0.8 (1–4) 
Age (years) 8.7 ± 1.4 (6.2–11.3) 
Weight (kg) 48.5 ± 14.5 (26.5–73.9) 
BMI (kg/m225.1 ± 4.9 (17.5–35.0) 
BMI SDS +3.3 ± +2.4 (+0.3 to +9.8) 
Waist circumference (cm) 73.8 ± 10.5 (54.2–90.8) 
Hip circumference (cm) 84.8 ± 11.7 (64–105) 

Data are n or means ± SD (range).

Table 2—

Fasting indices of insulin secretory capacity, sensitivity, and hepatic insulin clearance

Mean ± SDRange
Fasting glucose (mmol/l) 4.86 ± 0.60 2.90–5.70 
Fasting insulin (pmol/l) 82.50 ± 63.10 13.6–253.30 
Fasting C-peptide (nmol/l) 0.70 ± 0.36 0.29–1.70 
Insulinogenic index 0.13 ± 0.09 0.02–0.40 
HOMA-B% 183 ± 120 24–523 
Glucose/insulin ratio (in conventional units) 12.30 ± 9.30 2.50–47.90 
HOMA-IR 2.50 ± 2.00 0.4–7.6 
QUICKI 0.354 ± 0.042 0.288–0.463 
ISI FFA 0.64 ± 0.31 0.20–1.36 
C-peptide/insulin molar ratio 10.80 ± 5.40 4.0–31.2 
Mean ± SDRange
Fasting glucose (mmol/l) 4.86 ± 0.60 2.90–5.70 
Fasting insulin (pmol/l) 82.50 ± 63.10 13.6–253.30 
Fasting C-peptide (nmol/l) 0.70 ± 0.36 0.29–1.70 
Insulinogenic index 0.13 ± 0.09 0.02–0.40 
HOMA-B% 183 ± 120 24–523 
Glucose/insulin ratio (in conventional units) 12.30 ± 9.30 2.50–47.90 
HOMA-IR 2.50 ± 2.00 0.4–7.6 
QUICKI 0.354 ± 0.042 0.288–0.463 
ISI FFA 0.64 ± 0.31 0.20–1.36 
C-peptide/insulin molar ratio 10.80 ± 5.40 4.0–31.2 
Table 3—

Clamp-derived measures of insulin sensitivity and β-cell secretory capacity and clearance

Hyperglycemic clampEuglycemic clamp
M (mg · kg−1 · min114.1 ± 6.5 14.7 ± 8.2 
SIClamp (mg · kg−1 · min−1 per μU/ml) 16.7 ± 14.3 3.5 ± 3.5 
First-phase insulin (pmol/l) 648.6 ± 658.7  
Steady-phase insulin (pmol/l) 974.4 ± 663.7  
First-phase C-peptide (nmol/l) 2.2 ± 1.2  
Steady-phase C-peptide (nmol/l) 3.7 ± 1.2  
MCR of insulin (mg · kg−1 · min−1 per μU/ml)  0.106 ± 0.033 
First-phase C-peptide/insulin molar ratio 4.8 ± 2.0  
Steady-phase C-peptide/insulin molar ratio 4.8 ± 1.8  
Total % FFA suppression  77.6 ± 16.0 
First-phase FFA suppression 4.9 ± 23.1  
Steady-phase % FFA suppression 54.7 ± 18.0  
Hyperglycemic clampEuglycemic clamp
M (mg · kg−1 · min114.1 ± 6.5 14.7 ± 8.2 
SIClamp (mg · kg−1 · min−1 per μU/ml) 16.7 ± 14.3 3.5 ± 3.5 
First-phase insulin (pmol/l) 648.6 ± 658.7  
Steady-phase insulin (pmol/l) 974.4 ± 663.7  
First-phase C-peptide (nmol/l) 2.2 ± 1.2  
Steady-phase C-peptide (nmol/l) 3.7 ± 1.2  
MCR of insulin (mg · kg−1 · min−1 per μU/ml)  0.106 ± 0.033 
First-phase C-peptide/insulin molar ratio 4.8 ± 2.0  
Steady-phase C-peptide/insulin molar ratio 4.8 ± 1.8  
Total % FFA suppression  77.6 ± 16.0 
First-phase FFA suppression 4.9 ± 23.1  
Steady-phase % FFA suppression 54.7 ± 18.0  

Data are means ± SD.

Table 4—

Correlation of fasting to clamp-derived indices of insulin secretion, sensitivity, and clearance.

Spearman coefficient (r)P
Indices of pancreatic β-cell secretion   
 Fasting insulin: first-phase insulin 0.85 <0.05 
 Fasting insulin: steady-phase insulin 0.79 <0.05 
 Fasting C-peptide: first-phase insulin 0.59 <0.05 
 Fasting C-peptide: steady-phase insulin 0.72 <0.05 
 Fasting C-peptide: first-phase C-peptide 0.59 <0.05 
 Fasting C-peptide: steady-phase C-peptide 0.70 <0.05 
 Insulinogenic index: first-phase insulin 0.86 <0.05 
 Insulinogenic index: steady-phase insulin 0.80 <0.05 
 HOMA-B%: first-phase insulin 0.69 <0.05 
 HOMA-B%: steady-phase insulin 0.72 <0.05 
Indices of glycemic insulin sensitivity and resistance   
 HOMA-IR: SIEug clamp −0.51 <0.05 
 HOMA-IR: SIHyper clamp −0.56 <0.05 
 Quicki: SIEug clamp 0.69 <0.05 
 Quicki: SIHyper clamp 0.67 <0.05 
 Glucose/insulin: SIEug clamp 0.37 <0.05 
 Glucose/insulin: SIHyper clamp 0.42 <0.05 
Indices of insulin sensitivity as an antilipolytic   
 ISI FFA: % FFA suppression (first phase) 0.008 0.16 
 ISI FFA: % FFA suppression (steady phase) −0.04 0.14 
 ISI FFA: % total FFA suppression (euglycemic clamp) 0.22 0.09 
Indices of insulin clearance   
 Fasting C-peptide/insulin: MCR insulin 0.09 0.80 
 Fasting C-peptide/insulin: first-phase C-peptide/insulin 0.52 <0.05 
 Fasting C-peptide/insulin: steady-phase C-peptide/insulin 0.30 0.07 
Spearman coefficient (r)P
Indices of pancreatic β-cell secretion   
 Fasting insulin: first-phase insulin 0.85 <0.05 
 Fasting insulin: steady-phase insulin 0.79 <0.05 
 Fasting C-peptide: first-phase insulin 0.59 <0.05 
 Fasting C-peptide: steady-phase insulin 0.72 <0.05 
 Fasting C-peptide: first-phase C-peptide 0.59 <0.05 
 Fasting C-peptide: steady-phase C-peptide 0.70 <0.05 
 Insulinogenic index: first-phase insulin 0.86 <0.05 
 Insulinogenic index: steady-phase insulin 0.80 <0.05 
 HOMA-B%: first-phase insulin 0.69 <0.05 
 HOMA-B%: steady-phase insulin 0.72 <0.05 
Indices of glycemic insulin sensitivity and resistance   
 HOMA-IR: SIEug clamp −0.51 <0.05 
 HOMA-IR: SIHyper clamp −0.56 <0.05 
 Quicki: SIEug clamp 0.69 <0.05 
 Quicki: SIHyper clamp 0.67 <0.05 
 Glucose/insulin: SIEug clamp 0.37 <0.05 
 Glucose/insulin: SIHyper clamp 0.42 <0.05 
Indices of insulin sensitivity as an antilipolytic   
 ISI FFA: % FFA suppression (first phase) 0.008 0.16 
 ISI FFA: % FFA suppression (steady phase) −0.04 0.14 
 ISI FFA: % total FFA suppression (euglycemic clamp) 0.22 0.09 
Indices of insulin clearance   
 Fasting C-peptide/insulin: MCR insulin 0.09 0.80 
 Fasting C-peptide/insulin: first-phase C-peptide/insulin 0.52 <0.05 
 Fasting C-peptide/insulin: steady-phase C-peptide/insulin 0.30 0.07 

This research project was funded by an intramural research grant from the National Institute of Child Health and Human Development, National Institutes of Health, HD-000641 (to J.A.Y.). J.A.Y. is also supported by the National Center on Minority Health and Health Disparities, National Institutes of Health.

We acknowledge the efforts of all the nursing staff of the 9 West ward of the Warren Grant Magnuson Clinical Center, the clinical fellows who were involved in the clinical care of the subjects during their inpatient visits, and especially the children and parents who participated in these studies.

1.
Ford ES, Giles WH, Dietz WH: Prevalence of the metabolic syndrome among US adults: findings from the Third National Health and Nutrition Examination Survey.
JAMA
287
:
356
–359,
2002
2.
Mokdad AH, Serdula MK, Dietz WH, Bowman BA, Marks JS, Koplan JP: The spread of the obesity epidemic in the United States, 1991–1998. JAMA
282
:
1519
–1522,
1999
3.
Pi-Sunyer FX, Laferrere B, Aronne LJ, Bray GA: Therapeutic controversy: obesity–a modern-day epidemic.
J Clin Endocrinol Metab
84
:
3
–12,
1999
4.
Must A, Dallal GE, Dietz WH: Reference data for obesity: 85th and 95th percentiles of body mass index (wt/ht2) and triceps skinfold thickness.
Am J Clin Nutr
53
:
839
–846,
1991
5.
Ezenwaka CE, Offiah NV, Davis G: Early metabolic defects for developing diabetes mellitus among offspring of patients with type 2 diabetes are independent of gender.
West Indian Med J
49
:
276
–280,
2000
6.
DeFronzo RA, Tobin JD, Andres R: Glucose clamp technique: a method for quantifying insulin secretion and resistance.
Am J Physiol
237
:
E214
–E223,
1979
7.
Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC: Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man.
Diabetologia
28
:
412
–419,
1985
8.
Katz A, Nambi SS, Mather K, Baron AD, Follmann DA, Sullivan G, Quon MJ: Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans.
J Clin Endocrinol Metab
85
:
2402
–2410,
2000
9.
Guerrero-Romero F, Rodriguez-Moran M: Glucose intolerance is predicted by the high fasting insulin-to-glucose ratio.
Diabete Metab
27
:
117
–121,
2001
10.
Frisancho AR:
Anthropometric Standards for the Assessment of Growth and Nutritional Status
. Ann Arbor, MI, University of Michigan Press,
1990
11.
Tanner JM: Growth and maturation during adolescence.
Nutr Rev
39
:
43
–55,
1981
12.
Nguyen TT, Keil MF, Russell DL, Pathomvanich A, Uwaifo GI, Sebring NG, Reynolds JC, Yanovski JA: Relation of acanthosis nigricans to hyperinsulinemia and insulin sensitivity in overweight African American and white children.
J Pediatr
138
:
474
–480,
2001
13.
American Diabetes Association: Clinical Practice Recommendations 1997.
Diabetes Care
20 (Suppl. 1)
,
1997
14.
Mitrakou A, Vuorinen-Markkola H, Raptis G, Toft I, Mokan M, Strumph P, Pimenta W, Veneman T, Bolli G: Simultaneous assessment of insulin secretion and insulin sensitivity using a hyperglycemia clamp.
J Clin Endocrinol Metab
75
:
379
–382,
1992
15.
Shapiro ET, Tillil H, Miller MA, Frank BH, Galloway JA, Rubenstein AH, Polonsky KS: Insulin secretion and clearance: comparison after oral and intravenous glucose.
Diabetes
36
:
1365
–1371,
1987
16.
Madison LL: Role of insulin in the hepatic handling of glucose.
Arch Intern Med
123
:
284
–292,
1969
17.
Sumner AE, Kushner H, Lakota CA, Falkner B, Marsh JB: Gender differences in insulin-induced free fatty acid suppression: studies in an African American population.
Lipids
31 (Suppl.)
:
S275
–S278,
1996
18.
Sumner AE, Kushner H, Sherif KD, Tulenko TN, Falkner B, Marsh JB: Sex differences in African-Americans regarding sensitivity to insulin’s glucoregulatory and antilipolytic actions.
Diabetes Care
22
:
71
–77,
1999
19.
Belfiore F, Iannello S: Insulin resistance in obesity: metabolic mechanisms and measurement methods.
Mol Genet Metab
65
:
121
–128,
1998
20.
Belfiore F, Iannello S, Volpicelli G: Insulin sensitivity indices calculated from basal and OGTT-induced insulin, glucose, and FFA levels.
Mol Genet Metab
63
:
134
–141,
1998
21.
Davis SN, Monti L, Piatti PM, Moller N, Ng L, Coppack S, May M, Brown MD, Orskov H, Alberti KG: Estimates of insulin action in normal, obese and NIDDM man: comparison of insulin and glucose infusion test, CIGMA, minimal model and glucose clamp techniques.
Diabetes Res
23
:
1
–18,
1993
22.
Shoji T, Emoto M, Nishizawa Y: HOMA index to assess insulin resistance in renal failure patients.
Nephron
89
:
348
–349,
2001
23.
Rabasa-Lhoret R, Laville M: How to measure insulin sensitivity in clinical practice?
Diabete Metab
27
:
201
–208,
2001
24.
Ikeda Y, Suehiro T, Nakamura T, Kumon Y, Hashimoto K: Clinical significance of the insulin resistance index as assessed by homeostasis model assessment.
Endocr J
48
:
81
–86,
2001
25.
Katsuki A, Sumida Y, Gabazza EC, Murashima S, Furuta M, Araki-Susaki R, Hori Y, Yano Y, Adachi Y: Homeostasis model assessment is a reliable indicator of insulin resistance during follow-up of patients with type 2 diabetes.
Diabetes Care
24
:
362
–365,
2001
26.
Lansang MC, Williams GH, Carroll JS: Correlation between the glucose clamp technique and the homeostasis model assessment in hypertension.
Am J Hypertens
14
:
51
–53,
2001
27.
Bonora E, Targher G, Alberiche M, Bonadonna RC, Saggiani F, Zenere MB, Monauni T, Muggeo M: Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity: studies in subjects with various degrees of glucose tolerance and insulin sensitivity.
Diabetes Care
23
:
57
–63,
2000
28.
Haffner SM, Kennedy E, Gonzalez C, Stern MP, Miettinen H: A prospective analysis of the HOMA model. The Mexico City Diabetes Study.
Diabetes Care
19
:
1138
–1141,
1996
29.
Hrebicek J, Janout V, Malincikova J, Horakova D, Cizek L: Detection of insulin resistance by simple quantitative insulin sensitivity check index QUICKI for epidemiological assessment and prevention.
J Clin Endocrinol Metab
87
:
144
–147,
2002
30.
Abbasi F, Reaven GM: Evaluation of the quantitative insulin sensitivity check index as an estimate of insulin sensitivity in humans.
Metabolism
51
:
235
–237,
2002
31.
Kirwan JP, Huston-Presley L, Kalhan SC, Catalano PM: Clinically useful estimates of insulin sensitivity during pregnancy: validation studies in women with normal glucose tolerance and gestational diabetes mellitus.
Diabetes Care
24
:
1602
–1607,
2001
32.
Gungor N, Saad R, Arslanian S: Simple estimates of insulin sensitivity in children: comparison with gold standard of glucose clamp (Abstract).
Pediatric Research
51
:
709
,
2002
33.
Silfen ME, Manibo AM, McMahon DJ, Levine LS, Murphy AR, Oberfield SE: Comparison of simple measures of insulin sensitivity in young girls with premature adrenarche: the fasting glucose to insulin ratio may be a simple and useful measure.
J Clin Endocrinol Metab
86
:
2863
–2868,
2001
34.
Kashiwabara H, Inaba M, Maruno Y, Morita T, Awata T, Negishi K, Litaka M, Katayama S: Insulin levels during fasting and the glucose tolerance test and HOMA’s index predict subsequent development of hypertension.
J Hypertens
18
:
83
–88,
2000
35.
Kim J, Choi S, Kong B, Oh Y, Shinn S: Insulin secretion and sensitivity during oral glucose tolerance test in Korean lean elderly women.
J Korean Med Sci
16
:
592
–597,
2001
36.
Guerrer-Romer F, Rodriguez-Moran M, Gonzalez-Ortiz M, Martinez-Abundis E: Insulin action and secretion in healthy Hispanic-Mexican first-degree relatives of subjects with type 2 diabetes.
J Endocrinol Invest
24
:
580
–586,
2001
37.
Faber OK, Hagen C, Binder C, Markussen J, Naithania VK, Blix PM, Kuzuya H, Horwitz DL, Rubinstein AH, Rossing N: Kinetics of human connecting peptide in normal and diabetic subjects.
J Clin Invest
62
:
197
–203,
1978
38.
Steiner DF, Clark JL, Nolan C, Rubenstein AH, Margoliash E, Aten B, Oyer PE: Proinsulin and the biosynthesis of insulin.
Recent Prog Horm Res
25
:
207
–282,
1969
39.
Mather KJ, Hunt AE, Steinberg HO, Paradisi G, Hook G, Katz A, Quon MJ, Baron AD: Repeatability characteristics of simple indices of insulin resistance: implications for research applications.
J Clin Endocrinol Metab
86
:
5457
–5464,
2001
40.
Ferrara CM, Goldberg AP: Limited value of the homeostasis model assessment to predict insulin resistance in older men with impaired glucose tolerance.
Diabetes Care
24
:
245
–249,
2001
41.
Duncan GE, Hutson AD, Stacpoole PW: QUICKI does not accurately reflect changes in insulin sensitivity with exercise training.
J Clin Endocrinol Metab
86
:
4115
–4119,
2001
42.
de Vegt F, Dekker JM, Jager A, Hienkens E, Kosteuse PJ, Stehouwer CD, Nijpels G, Bouter LM, Heine RJ: Relation of impaired fasting and postload glucose with incident type 2 diabetes in a Dutch population: the Hoorn Study.
JAMA
285
:
2109
–2113,
2001
43.
Li CL, Tsai ST, Chou P: Comparison of metabolic risk profiles between subjects with fasting and 2-hour plasma glucose impairment: the Kinmen Study.
J Clin Epidemiol
55
:
19
–24,
2002
44.
Gutt M, Davis CL, Spitzer SB, Llabre MM, Kumar M, Czarnecki EM, Schneiderman N, Skyler JS, Marks JB: Validation of the insulin sensitivity index (ISI(0,120)): comparison with other measures.
Diabetes Res Clin Pract
47
:
177
–184,
2000
.

Address correspondence and reprint requests to Jack A. Yanovski MD, PhD, Head, Unit on Growth and Obesity, DEB, NICHD, National Institutes of Health, 10 Center Dr., Building 10, Rm. 10N262, MSC 1862, Bethesda, MD 20892-1862. E-mail: [email protected].

Received for publication 26 April 2002 and accepted in revised form 13 August 2002.

A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.