Waist circumference is an independent predictor of insulin resistance in black and white youths

Article Outline

• Abstract
• Methods
  • Subjects
  • Anthropometric Measurements
  • Body Composition
  • Insulin Sensitivity
  • Biochemical Measurements
  • Statistical Analysis
• Results
  • Subject Characteristics
• Discussion
• Acknowledgment
• References
• Copyright

Objectives

We examined how well waist circumference (WC) reflects total and abdominal fat and whether WC predicts insulin resistance independent of body mass index (BMI) percentile in youths.

Study design

Body composition was measured by dual-energy x-ray absorptiometry and abdominal adiposity by computed tomography. Insulin sensitivity was measured by the hyperinsulinemic-euglycemic clamp.

Results

Both BMI percentile and WC were significantly associated (P < .01) with total and abdominal fat and insulin sensitivity. WC remained a significant (P < .01) correlate of total and abdominal fat and insulin sensitivity after controlling for BMI percentile. By contrast, BMI percentile did not remain a significant correlate of visceral fat and markers of insulin resistance after controlling for WC. Without exception, WC explained a greater variance in abdominal fat and metabolic profiles than did BMI percentile.

Conclusions

Our findings suggest that the prediction of health risks associated with obesity in youths is improved by the additional inclusion of WC measure to the BMI percentile. Such observations would reinforce the importance of including WC in the assessment of childhood obesity to identify those at increased metabolic risk due to excess abdominal fat.

Abbreviations:  BMI, Body mass index , DEXA, Dual-energy x-ray absorptiometry , WC, Waist circumference

Abdominal adiposity as assessed by waist circumference (WC) is a significant predictor of cardiovascular disease and type 2 diabetes independent of overall adiposity in adults.¹, ² Several epidemiological studies indicate that WC in conjunction with body mass index (BMI) is a better predictor of metabolic risk than either measure alone.³, ⁴, ⁵ However, recent evidence ⁶ suggests that WC and not BMI explains obesity-related health risk in a representative sample of adult population. Although the mechanisms that explain the increased metabolic risk associated with WC are unclear, it is reported that WC is a strong predictor of abdominal fat,⁷ a well-known predictor of metabolic dysfunction. The ability of WC to predict abdominal fat and related comorbid conditions in youths is currently unknown.

Despite the strong association between BMI and total fat,⁸ the use of BMI as an indicator of adiposity in youths has an important limitation due to an individual’s variation in growth rates and maturity levels.⁹ Indeed, it has been reported that increases in BMI during childhood is largely determined by increases in lean body mass rather than fat mass.¹⁰ Previous studies have examined the utility of WC as an index of health risk in youths.¹¹, ¹² Maffeis et al¹² demonstrated that WC is associated with fasting insulin, blood pressure, and insulin resistance index in obese girls. Whether WC is independently related to insulin sensitivity and β-cell function in children and adolescents is currently unknown.

Waist circumference during the past 10 to 20 years in youths has increased much faster than BMI over the same time period.¹³ This is of great concern because abdominal fat conveys substantial health risk for cardiovascular and metabolic disease.¹⁴ Given the escalation in the prevalence of childhood obesity and its related metabolic disorders,¹⁵ identification of youths at high risk is important because these are antecedents of adulthood morbidities.¹⁶, ¹⁷ Thus, the purpose of this study was twofold: first, to determine how well WC reflects total, abdominal subcutaneous, and visceral fat in youths, and, second, to examine whether WC predicts insulin resistance independent of BMI percentiles.

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Methods 

Subjects 

Subjects consisted of healthy black (n = 56) and white (n = 89) youths who participated in various body composition and metabolic studies, some of whom have been reported previously.¹⁸, ¹⁹ The subjects varied in age (8 to 17 years) and BMI (14 to 50 kg/m²). Study participants were recruited through newspaper advertisements in the greater Pittsburgh area, flyers posted in the city public transportation, and posters placed on campus. The investigation was approved by the Institutional Review Board and performed in the General Clinical Research Center. Parental informed consent and child assent were obtained from all participants before participation, in accordance with the ethical guidelines of Children’s Hospital of Pittsburgh. All participants were in good health, on the basis of clinical history, physical examination, and routine hematological and biochemical tests. None of the subjects were taking medications known to affect the primary outcome variables. Pubertal development was assessed by physical examination according to Tanner criteria and was confirmed by measurement of plasma testosterone in male subjects, estradiol in female subjects, and dehydroepiandrosterone sulfate in both.

Anthropometric Measurements 

Body weight and height were measured to the nearest 0.1 kg and 0.1 cm, respectively, by using standardized equipment. WC was obtained at the midpoint between the lowest rib and the iliac crest. BMI was calculated as weight (kg) divided by the square of height (m²). The Centers for Disease Control and Prevention Growth Charts were used to calculate sex-and age-specific BMI percentiles.²⁰

Body Composition 

Total fat was assessed by dual-energy x-ray absorptiometry (DEXA). DEXA was not performed on 9 subjects whose body weight exceeded the DEXA weight limit. A single axial image of the abdomen (L4-L5) was obtained by means of computed tomography to measure abdominal subcutaneous and visceral fat. Both measures are described in detail elsewhere.²¹

Insulin Sensitivity 

All participants, except for one black boy, underwent a 3-hour hyperinsulinemic-euglycemic clamp after 10 to 12 hours of overnight fasting. Briefly, intravenous crystalline insulin (Humulin; Lilly, Indianapolis, IN) was infused at a constant rate of 40 mU/m⁻² per · minute in normal-weight subjects and 80 mU/m⁻² per · minute in obese subjects, as previously described by us.²², ²³ Plasma glucose was clamped at 5.6 mmol/L, with a variable-rate infusion of 20% dextrose, based on arterialized plasma glucose determinations every 5 minutes. The insulin-stimulated glucose disposal rate was calculated by using the average exogenous glucose infusion rate during the final 30 minutes of the clamp. Insulin sensitivity was calculated by dividing insulin-stimulated glucose disposal rate by the steady-state insulin levels during the last 30 minutes of the clamp, as described previously.¹⁸ Insulin sensitivity is expressed per metabolically active fat-free mass (mg/min per kg fat-free mass per μU/mL).

Biochemical Measurements 

Plasma glucose was measured by the glucose oxidase method, with a glucose analyzer (YSI, Inc, Yellow Springs, OH), and the insulin concentration was determined by radioimmunoassay.¹⁸ Proinsulin was measured at the Esoterix Endocrinology Laboratory (Calabasas Hills, CA) by immunochemiluminescent assays. Proinsulin was not measured in three subjects because of insufficient serum sample.

Statistical Analysis 

Statistical procedures were performed with the use of SPSS (Version 13.0; SPSS, Inc, Chicago, IL). Mann-Whitney U tests were used to evaluate racial differences in subject characteristics. Log transformations were performed to normalize the distribution for all analyses. Pearson and partial correlation coefficients were used to determine the associations among BMI percentiles, WC, total and abdominal fat, and metabolic profiles. Multiple regression analyses were used to quantify the independent contribution of BMI percentiles and WC to total and abdominal fat and metabolic profiles. Although BMI percentile and WC were significantly correlated (r = 0.72), the colinearity diagnostics indicated that BMI percentile and WC could be used in the same regression model. To further investigate the contributions of WC and BMI percentile to the markers of insulin resistance, subjects were divided into low (<75^th), moderate (75^th to 90^th), and high WC (>90^th) groups²⁴ and normal weight (<85^th), at risk for overweight (85^th to 95^th) and overweight (>95^th) groups.²⁵ General linear models were used to determine the influence of WC or BMI group on the markers of insulin resistance.

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Results 

Subject Characteristics 

Black and white youths did not differ with respect to age, BMI, and all measures of body composition (Table I).

Table I. Subject characteristics

	Black			White
	29 M + 27 F			47 M + 42 F
	Mean ± SD	Median	Range	Mean ± SD	Median	Range
Anthropometric
Age (y)	12.5±2.0	12.6	8.5–16.8	12.9±2.1	13.1	8.0–17.2
Tanner stage
I	14			17
II–V	42			72
Weight (kg)	61.7±28.3	55.4	27.6–128.8	62.2±27.6	53.7	25.3–139.1
BMI (kg/m2)	25.1±9.1	22.2	14.7–49.6	24.2±8.0	21.8	13.9–47.1
BMI percentile	72.5±27.2	81.0	4.0–99.0	70.3±30.5	81.0	0.3–99.0
Waist circumference (cm)	77.4±17.9	73.8	52.0–109.2	80.8±20.8	76.0	51.0–139.0
Body composition
Total body AT (kg)⁎	18.1±15.4	12.9	2.7–51.0	17.1±13.2	11.6	3.2–47.7
Total abdominal AT (cm2)	270.1±269.1	139.9	26.2–957.1	277.8±249.0	182.8	31.3–930.1
Visceral AT (cm2)	34.0±29.7	19.8	3.2–108.1	41.0±36.6	27.2	5.2–161.4
ASAT (cm2)	236.1±243.2	113.8	19.6–890.1	237.9±216.8	157.2	20.8–822.6
Metabolic variables
Fasting glucose (mg/dL)	95.1±5.4	94.8	84.7–108.0	96.4±6.2	95.3	84.3–117.7
Fasting insulin (μU/mL)	24.3±18.1	17.8	8.1–91.1	24.5±14.7	19.8	6.8–95.5
Proinsulin (pmol/L)†	21.8±23.7	12.0	3.2–112.0	21.3±20.0	12.8	3.2–108.0
Insulin sensitivity‡ (mg/min per kg FFM per μU/mL)	10.7±6.3	11.4	1.1–24.2	12.6±7.2	11.5	1.9–40.1

Data are shown as mean ± SD.

AT, Adipose tissue; ASAT, abdominal subcutaneous adipose tissue.

Figure 1 indicates that both BMI and WC are significantly associated with total fat, abdominal subcutaneous, and visceral fat. Although both BMI percentile and WC were significant (P < .01) correlates of total body fat, abdominal fat, and metabolic profiles (Table II), WC remained a significant (P < .01) correlate of these variables after controlling for BMI percentile. In contrast, BMI percentile did not remain a significant correlate of visceral fat and markers of insulin resistance after controlling for WC.

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• Figure 1. 

  Association of WC (upper panel, A through C) and BMI (lower panel, D through F) with total, abdominal subcutaneous, and visceral fat. Black squares indicate blaack; white squares, white.

Table II. Relations (r) between BMI percentiles, WC, total and abdominal fat, and metabolic variables

All variables were log-transformed to normalize their distribution.

NS, not significant. All other listed correlations are significant, P < .01.

Multiple regression analyses revealed that the variance explained (R²) for total and abdominal fat and metabolic variables were significantly increased when WC was added to BMI percentile in the multiple regression models (Table III and Table IV). By contrast, BMI percentile did not add (P > .10) to the variance in visceral fat and markers of insulin resistance (eg, fasting insulin, proinsulin, and insulin sensitivity) explained by WC and only marginally (1% ∼ 3%) contributed to the variance in total body fat, abdominal subcutaneous fat, and fasting glucose. These findings suggest that the influence of BMI percentile on total and abdominal adiposity and metabolic profiles are mediated through central obesity, measured by WC, and that WC alone is an independent predictor of total and abdominal adiposity and metabolic profiles.

Table III. Multiple regression analyses examining independent contributions of BMI percentile and WC to the variance of total and abdominal adiposity

BMI percentile, WC, total body AT, and all abdominal AT measures were log-transformed to normalize their distribution.

Step 1 = Age, gender, race, and pubertal status entered together.

Step 2 = BMI percentile (left side of table) or WC (right side of table) added to step 1.

Step 3 = BMI percentile and WC together added to step 1.

Table IV. Multiple regression analyses examining independent contributions of BMI percentile and WC to the variance of metabolic profiles

BMI percentile, WC, and all metabolic variables were log-transformed to normalize their distribution.

Step 1 = Age, gender, race, and pubertal status entered together.

Step 2 = BMI percentile (left side of table) or WC (right side of table) added to step 1.

Step 3 = BMI percentile and WC together added to step 1.

As shown in Figure 2, increasing WC and BMI percentile was associated with lower insulin sensitivity and higher fasting insulin and proinsulin (P for trend < .01).

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• Figure 2. 

  Insulin sensitivity, fasting insulin, and proinsulin across the WC (left panel, A through C) and BMI percentile (right panel, D through F) groups. Data are shown as mean ± SEM.

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Discussion 

We examined whether WC independently contributes to the prediction of total and abdominal fat and insulin resistance in black and white youths. Our primary finding is that although both BMI percentile and WC were significantly associated with measures of abdominal fat and insulin resistance, WC remained a significant correlate of abdominal adiposity and insulin sensitivity even after controlling for BMI percentile, independent of race. Further, we observed that WC explained a greater variance in abdominal adiposity and insulin sensitivity than did BMI percentile. These observations underscore the notion that WC should be incorporated into the assessment of childhood obesity, both in the clinical and the research setting, to identify those at increased health risks caused by excess total and abdominal fat.

In adults, it is well established that WC is a predictor of morbidity⁵, ⁶ and mortality²⁶ independent of BMI. It has been suggested that the added health risk predicted by WC is explained by its ability to act as a surrogate for abdominal fat.²⁷ Janssen et al⁷ reported that for a given BMI category, WC is an independent contributor of abdominal fat, and the use of WC in combination with BMI explained a greater variance in abdominal fat than BMI alone in adult men and women. Consistent with this, our findings in children and adolescents suggest that both BMI and WC are associated with total and abdominal subcutaneous fat. However, results from the present study indicate that in the pediatric population, WC alone is a strong predictor of visceral fat. Although it has been suggested that only small amounts of visceral fat are physiologically present before adulthood,²⁸ visceral fat is now recognized as a depot that predisposes children and adolescents to development of insulin resistance and type 2 diabetes.¹⁹, ²⁹

A growing body of evidence suggests that WC is associated with risk factors for cardiovascular disease and insulin resistance in children and adolescents.¹¹, ¹², ³⁰ Savva et al³⁰ reported that WC is a better predictor of blood pressure and dyslipidemia than BMI in 10- to 14-year-old boys and girls. Further, Moreno et al¹¹ have shown that WC is the best anthropometric tool for the screening of the metabolic syndrome in children. Our observation that in a large sample of children and adolescents, WC is an independent predictor of insulin sensitivity measured by the euglycemic clamp expands previous observations¹², ¹⁵, ³⁰, ³¹ and indicates the usefulness of WC as an indicator of abdominal obesity-related metabolic dysfunction. Together, these observations suggest the need to include this simple measure in clinical practice to evaluate childhood obesity and related metabolic profiles.

Accordingly, WC percentiles have been developed for children and adolescents in several countries.²⁴, ³², ³³ Fernandez et al²⁴ reported sex-, race-, and age-specific WC percentiles in a large representative sample of US youths. In that study, the WC cutoff at the 90^th percentile of the WC distribution for 13-year-old black girls exceeds the WC value of 88 cm, identified as the cutoff for increased metabolic dysfunction in adult women.²⁴, ²⁷ Further studies are needed to examine whether the proposed cutoffs²⁴ are related to elevated health risks in a large sample of children and adolescents.

Our findings provide compelling evidence that WC is a significant marker of total and abdominal fat independent of BMI percentiles in youths. Further, WC is a strong independent predictor of insulin resistance, elevated fasting insulin, and proinsulin levels. Combined with the observation that WC has increased much faster than BMI during the past 10 to 20 years in youths,¹³ our findings support the recommendation that WC should be included in the routine clinical assessment of childhood obesity to identify those at increased health risk for metabolic consequences caused by increased abdominal fat.

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The authors express their gratitude to the study participants and their parents and to the General Clinical Research Center staff for their assistance.

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