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American Journal of Clinical Nutrition, Vol. 83, No. 1, 36-46, January 2006
© 2006 American Society for Clinical Nutrition

ORIGINAL RESEARCH COMMUNICATION

Clustering of metabolic abnormalities in adolescents with the hypertriglyceridemic waist phenotype1,2,3

Ahmad Esmaillzadeh, Parvin Mirmiran and Fereidoun Azizi

1 From the Endocrine Research Center, Shaheed Beheshti University of Medical Sciences, Tehran, Iran

See corresponding editorial on page 3.

See corresponding CME exam on page 183.

2 Supported by grant no. 121 from the National Research Council of the Islamic Republic of Iran and by the combined support of the National Research Council of Islamic Republic of Iran and the Endocrine Research Center of Shaheed Beheshti University of Medical Sciences.

3 Reprints not available. Address correspondence to F Azizi, Endocrine Research Center, Shaheed Beheshti University of Medical Sciences, PO Box 19395-4763, Tehran, Iran. E-mail: azizi{at}erc.ac.ir.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background: It remains unknown whether the hypertriglyceridemic waist (HW) phenotype, an appropriate screening tool in adults, can also be used to screen for metabolic abnormalities in adolescents.

Objective: We aimed to evaluate metabolic risk factors identified by the HW phenotype in adolescents.

Design: Anthropometric and biochemical measurements were assessed in a population-based cross-sectional study of 1413 male and 1623 female Iranian adolescents aged 10–19 y. The HW phenotype was defined as serum triacylglycerol concentrations ≥110 mg/dL and concurrent waist circumference ≥90th percentile for age and sex. Elevated fasting glucose (≥110 mg/dL), high LDL (≥130 mg/dL) and low HDL (≤40 mg/dL) cholesterol, hypercholesterolemia (total cholesterol ≥200 mg/dL), and hypertension (systolic or diastolic blood pressure ≥ 95th percentile for age, sex, and height) were considered as risk factors.

Results: Adolescents with the HW phenotype had significantly higher prevalences of all metabolic risk factors except elevated fasting glucose than did those without the HW phenotype. After control for potential confounding variables, adolescents with the HW phenotype were significantly more likely to have high LDL cholesterol (odds ratio: 1.8; 95% CI: 1.3, 2.7), low HDL cholesterol (1.6; 1.3, 2.0), hypercholesterolemia (2.9; 2.0, 4.2), and ≥1 (1.4; 1.1, 1.7) and ≥2 (2.2; 1.6, 3.0) risk factors than were those without the HW phenotype. The HW phenotype had a significantly higher percentage of correct prediction of metabolic abnormalities than did overweight, elevated triacylglycerol concentration, or enlarged waist circumference.

Conclusion: This study shows a clustering of metabolic abnormalities in adolescents with the HW phenotype and suggests this phenotype as a simple marker for identifying adolescents at risk of metabolic syndrome and other metabolic abnormalities.

Key Words: Hypertriglyceridemic waist • metabolic syndrome • adolescents • cardiovascular risk factors • overweight


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Cardiovascular diseases (CVDs) are one of the major causes of mortality in Iran (1), and the prevalence of these disturbances continues to rise (2). Persons with metabolic syndrome are at greater risk of CVD. The metabolic syndrome is defined as a constellation of laboratory and physical findings such as central obesity, insulin resistance, hyperglycemia, dyslipidemia, and hypertension (3). The third report of the National Cholesterol Education Program Adult Treatment Panel III recognized the metabolic syndrome as a secondary target of risk-reduction therapy (4). A recent study in Tehran showed that the metabolic syndrome is highly prevalent in Tehranian adults; the estimated prevalence is >30% (5), which is higher than that in most developed countries, such as the United States (6).

Although studies indicated that the process of atherosclerosis starts at an early age and is linked even in childhood to obesity and other components of the metabolic syndrome (7), few studies have reported the prevalence of the metabolic syndrome phenotype in children and adolescents (8-11). Moreover, at present, there is no globally accepted definition for the metabolic syndrome in children and adolescents. Research is needed to ascertain whether the precursors of the metabolic syndrome in children and adolescents differ from those in adults, but many investigators assume that insulin resistance is the fundamental metabolic defect underlying the metabolic syndrome (3, 4, 12, 13). The concurrent presence of insulin resistance, increased serum apolipoprotein B concentrations, and high serum concentrations of small, dense LDL cholesterol has been referred to as a metabolic triad (14) that could be identified by using the inexpensive screening tool of the hypertriglyceridemic waist (HW) phenotype (15).

Some investigators have reported that HW, or waist-triacylglycerol syndrome, predicts the presence of the metabolic syndrome (16). Others recommended this index for the identification of a syndrome of lipid overaccumulation (17). Subjects with the HW phenotype were nearly 4 times as likely to have angiographically defined coronary artery disease (CAD) as were subjects who did not have the HW phenotype (15). Our previous studies showed that the HW phenotype is highly prevalent in the adult population of Tehran; the estimated prevalence is 19% in men (18) and 32% in women (19). Although the prevalence (15-20) and correlates (21-23) of the HW phenotype have been investigated in adults, comparatively little emphasis was placed on its prevalence and correlates in children and adolescents, and there is no report in the current literature regarding the prevalence of this phenotype in adolescents. It also remains unknown whether, as seen in adults, the HW phenotype is associated with a similar clustering of metabolic risk factors in adolescents. We found in our previous investigation (24) that the HW phenotype is highly prevalent in Tehranian adolescents; ie, the estimated prevalence is 6.5%. In the current study, we aimed to evaluate whether the HW phenotype could be used as a screening tool for metabolic abnormalities in adolescents.


   SUBJECTS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Subjects
This study was conducted within the framework of the Tehran Lipid and Glucose Study (TLGS), a prospective study performed in a representative sample of residents of one district of Tehran with the aims of ascertaining the prevalence of noncommunicable disease risk factors and developing a healthy lifestyle to curtail these risk factors (25). The TLGS provides a representative sample of the population of the city of Tehran (25): >15 000 people aged ≥3 y who were living in a district of Tehran and were selected by multistage cluster random-sampling method, including 3265 adolescents aged 10–19 y. In the current population-based cross-sectional study, after the exclusion of subjects taking medications that affect serum lipids, blood pressure, and carbohydrate metabolism (n = 23), 3036 adolescents (1413 male and 1623 female) with full relevant data (206 adolescents had incomplete relevant data) were included in the study.

Written informed consent was obtained from each subject. This study was approved by the research council of the Endocrine Research Center of the Shaheed Beheshti University of Medical Sciences.

Methods
Details of the TLGS protocol and all laboratory procedures were published elsewhere (2, 26, 27). In brief, weight was measured with the use of digital scales while subjects were minimally clothed and not wearing shoes, and it was recorded to the nearest 100 g. Height was measured with the use of a tape measure while subjects were in a standing position and not wearing shoes and while the shoulders were in a normal position. Body mass index (BMI) was calculated as weight (in kg) divided by height (in m2). Waist circumference (WC) was measured at the narrowest level, and hip circumference was measured at the maximum level over light clothing with the use of an unstretched tape measure and without any pressure to body surface; measurements were recorded to the nearest 0.1 cm. Because the measurements were to be made over light clothing, participants were asked to remove belts and any tight or loose garments that may alter the shape of the body, and the person measuring was asked to ensure that the tape had the proper tension around the subject's body—ie, neither too loose nor too tight. Although the narrowest waist is easy to identify in most subjects, for some subjects there is no single narrowest waist because of either a large amount of abdominal fat or extreme thinness (28). In the current study, when the narrowest point of waist was difficult to identify (particularly in obese subjects), we measured the WC immediately below the end of the lowest rib, because in most subjects the narrowest waist is at the lowest rib (28). To reduce subjective error, all measurements in all males were taken by the same male technician, and those in all females were taken by the same female technician. There were significant correlations between both the test and retest measurements taken by male and female technicians (r > 0.75, P < 0.01 for both). Data on family history of diabetes were collected as the subjects' oral responses to the previously tested questionnaire. The criterion for family history of diabetes was having ≥1 first-degree relative with a diagnosis of diabetes after 30 y of age. Data on physical activity, which were reported previously (29), were obtained by using subjects' oral responses to a previously tested questionnaire, and subjects were categorized into 3 physical activity groups—light, moderate, and heavy.

Between 0700 and 0900, a blood sample was drawn into evacuated tubes from all study participants after overnight (ie, > 10 h) fasting. Blood samples were taken while the subjects were in a sitting position, according to the standard protocol, and were centrifuged within 30–45 min. All blood lipid analyses were done at the TLGS research laboratory on the day of blood collection. The analysis of samples was performed by using a Selectra 2 autoanalyzer (Vital Scientific, Spankeren, Netherlands). Fasting plasma glucose was measured on the day of blood collection by using the enzymatic colorimetric method with glucose oxidase. Serum total cholesterol (TC) and triacylglycerol concentrations were measured by commercially available enzymatic reagents (Pars Azmoon Inc, Tehran, Iran) adapted to the Selectra autoanalyzer. HDL cholesterol was measured after precipitation of the apolipoprotein B–containing lipoproteins with phosphotungistic acid. LDL cholesterol was calculated from serum TC, triacylglycerol, and HDL cholesterol concentrations, except when the triacylglycerol concentration was > 400 mg/dL. Assay performance was monitored once every 20 tests by using the lipid control serum Percinorm (normal range) and by using Percipath (pathologic range) whenever applicable [Cat. no. 1446070 (Percinorm) and 171778 (Percipath); Boehringer Mannheim, Mannheim, Germany]. Lipid standard (calibrated for automated systems) (Cat. No. 759350; Boehringer Mannheim) was used to calibrate the Selectra 2 autoanalyzer on each day of laboratory analyses. All samples were analyzed when internal quality control met the acceptable criteria. Interassay and intraassay CVs were 2% and 0.5% for TC and 1.6% and 0.6% for TAG, respectively (26).

Participants were made to rest for 15 min before their blood pressure was measured. A qualified physician then measured the blood pressure of the seated subject twice by using a standard mercury sphygmomanometer, and thereafter the mean of 2 measurements was considered as the participant's blood pressure. The systolic blood pressure was defined as the appearance of the first sound (Korotkoff phase 1), and the diastolic blood pressure was defined as the disappearance of the sound (Korotkoff phase 5) during deflation of the cuff at a decrement rate of 2–3 mm/s of the mercury column (30).

Definition of terms
Because no reference values for WC exist for children and adolescents, we established the enlarged WC criteria by analyzing all adolescents in the current dataset whose WCs were recorded. Subjects with a value ≥90th percentile for age and sex from this sample population were classified as having enlarged WC. The choice of the 90th percentile was based on the association between truncal fat and WC according to Taylor et al (31). Other investigators also showed that clustering of risk factors was significantly higher in subjects with a WC > 90th percentile than in subjects with a WC < 90th percentile (32).

In developing a definition for elevated serum triacylglycerol concentration in adolescents, we considered reference values from the National Cholesterol Education Program's Pediatric Panel Report (32). In children aged 10–19 y, a borderline high range for triacylglycerol concentrations is given as 90–129 mg/dL (1.02–1.46 mmol/L). Therefore, the midpoint value for triacylglycerol concentrations (≥110 mg/dL = 1.24 mmol/L) was taken as the 90th percentile value for age. Subjects were categorized in 4 phenotype groups on the basis of the mentioned cutoffs: normal WC (<90th percentile for age and sex) and normal serum triacylglycerol concentrations (<110 mg/dL); normal WC (<90th percentile for age and sex) and elevated serum triacylglycerol concentrations (≥110 mg/dL); enlarged WC (≥90th percentile for age and sex) and normal serum triacylglycerol concentrations (<110 mg/dL); and enlarged WC (≥90th percentile for age and sex) and elevated serum triacylglycerol concentrations (≥110 mg/dL).

Subjects with ≥3 of the 5 characteristics described in this paragraph were categorized as having the metabolic syndrome. The first characteristic was an enlarged WC (≥90th percentile for age and sex), and the second characteristic was an elevated systolic or diastolic blood pressure, which was defined as a value ≥90th percentile for age, sex, and height based on published reference data (34). Because the updated report of the Task Force on the Diagnosis and Management of Hypertension does not include adolescents aged 18 and 19 y, we used cutoffs of ≥130 and ≥85 mm Hg for systolic and diastolic blood pressure, respectively, in those age categories, on the basis of the recommendations of the Joint National Committee on Prevention, Detection, Evaluation and Treatment of High Blood Pressure (35). The third characteristic was a borderline low HDL cholesterol concentration, in the range of 35–45 mg/dL (0.91–1.16 mmol/L), as ascertained for all sexes and ages by the National Cholesterol Education Program's Report of the Expert Panel on Blood Cholesterol Levels in Children and Adolescents (33). Therefore, the midpoint value for HDL cholesterol (≤40 mg/dL = 1.03 mmol/L) was used as a 10th percentile value. The fourth characteristic was an elevated serum triacylglycerol concentration (≥110 mg/dL). The fifth characteristic was a reference value of ≥110 mg/dL (≥6.1 mmol/L) for elevated fasting plasma glucose, which was taken from the American Diabetes Association guideline (36).

Hypercholestrolemia was defined as TC ≥200 mg/dL and high LDL cholesterol as ≥130mg/dL (33). Hypertension was defined as systolic or diastolic blood pressure of ≥95th percentile for sex, age, and height (34) and, in adolescents aged 18 and 19 y, as a systolic blood pressure ≥140 mm Hg or a diastolic blood pressure ≥ 90 mm Hg (35). The presence of ≥1 and ≥2 of the 5 major risk factors for CVD (ie, elevated fasting glucose, high LDL cholesterol, low HDL cholesterol, hypercholesterolemia, and hypertension) was also evaluated.

On the basis of the standardized percentile curves of BMI suggested for Iranian children and adolescents, overweight was defined as ≥95th percentile of BMI for age and sex (37). Risk of overweight was defined as ≥85th to <95th percentile of BMI for age and sex, and normal weight was defined as <85th percentile of BMI for age and sex.

Statistical analysis
We used SPSS software (version 9.05; SPSS Inc, Chicago IL) for all statistical analyses. The prevalence of the HW phenotype and its 95% CI was calculated overall, by sex, by sex and family history of diabetes, and by sex and BMI status. There was a significant interaction between sex and age with regard to the prevalence of HW (P < 0.05). Therefore, the prevalences of the HW phenotype in boys and girls were examined by age. Prevalence values were compared by using the chi-square test. Significant differences in general characteristics across different phenotypes of serum triacylglycerol concentrations and WC were searched by using 2-factor (enlarged WC versus normal WC and elevated triacylglycerol versus normal triacylglycerol) analysis of variance (ANOVA), and the main effects of WC and triacylglycerol concentrations and the WC x triacylglycerol concentration interaction were tested. We also used 2-factor ANOVA to detect significant differences in the distribution of subjects across different phenotypes of serum triacylglycerol concentration and WC with regard to the prevalence of metabolic abnormalities. We ascertained age- and sex-adjusted means of metabolic risk factors across different phenotypes of serum triacylglycerol concentrations and WC by using general linear models. These models were further adjusted for BMI. Analysis of covariance was used to compare these means. To determine the association of the HW phenotype with metabolic abnormalities, we used logistic regression models. Because the ORs estimated from logistic regression models in cross-sectional studies are not valid estimators of the rate ratios when the binary outcome variable has a higher prevalence (38, 39), we used the formula suggested by Zhang and Yu (39) to correct the adjusted ORs obtained from logistic regression so that we could derive an estimate of association that better represents the true relative risk. All models were controlled for age (y), sex, and physical activity level (light, moderate, and heavy). When a significant association with the HW phenotype was observed, we further examined whether overweight associated with the HW phenotype would explain the associations by adjusting for BMI. In all multivariate models, subjects with normal serum triacylglycerol concentrations and normal WCs were considered as a reference. McNemar's chi-square statistic was used to ascertain whether significant differences were present between the HW phenotype and overweight with respect to accuracy in classifying individuals according to the presence or absence of risk factors. Such analyses were also repeated by comparing the HW phenotype with the metabolic syndrome, enlarged WC, or elevated triacylglycerol concentration alone. The frequency of subjects with and without CVD risk factors in established cutoffs of the screening measures (HW phenotype, overweight, and the metabolic syndrome) was ascertained by cross-tabulation, and sensitivity and specificity were calculated. The sensitivity of each screening measure was defined as the proportion of the total number of subjects with a given risk factor who were identified correctly by the same indicator. The specificity of each screening measure was defined as the proportion of the total subjects without the risk factor who were correctly identified by the same measure.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Of the 3036 adolescents, 358 (11.8%) had a family history of diabetes, 382 (12.5%) were overweight, and 399 (13.1%) were at risk of overweight. The prevalence of the HW phenotype was 6.4% (95% CI: 5.5, 7.2) among Tehranian adolescents. The syndrome was significantly (P = 0.02) more common in males (7.3%; 5.9, 8.7) than in females (5.6%; 4.4, 6.7). There was no significant difference in the prevalence of the HW phenotype between adolescents with (8.1%; 5.2, 10.9) and without (6.2%; 5.2, 7.1) a family history of diabetes. When the subjects were examined by BMI category, 38.7% of overweight adolescents had the HW phenotype as compared with 7.7% of adolescents at risk of overweight and 0.7% of adolescents with normal weight (P = 0.001).

Mean (±SEM) prevalence of the HW phenotype by age is shown in Figure 1Go. In the subjects at age 10 y, the mean prevalence of the HW phenotype was 5.0 ± 1.0% in the males; this was the lowest prevalence among all age groups. This estimate rose to its highest value (9.2 ± 1.2%) in the males aged 12 y. Females aged 10 y had the highest prevalence of the HW phenotype (9.5 ± 1.3%), and the lowest prevalence of this phenotype was seen in females aged 19 y (3.4 ± 0.6%). At age 10 y, the prevalence was significantly higher in females than in males, but at ages 12, 15, and 17–19 y, the prevalence was significantly higher in males than in females.



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  		FIGURE 1.. Mean (±SEM) prevalence of the hypertriglyceridemic waist (HW) phenotype by age. The HW phenotype was defined as a serum triacylglycerol concentration ≥110 mg/dL and concurrent waist circumference ≥90th percentile for age and sex. n = 115-176 males and 126-197 females in each category. At age 10 y, the prevalence in females was significantly higher than that in males, but, at ages 12, 15, and 17–19 y, the prevalence was significantly higher in males than in females. There was a significant sex x age interaction for the prevalence of HW, P < 0.05. *Significantly different from females (chi-square analysis), P < 0.01.

 
Characteristics of adolescents by different categories of serum triacylglycerol concentration and WC are shown in Table 1Go. Adolescents in different categories of serum triacylglycerol concentrations had significantly different age (triacylglycerol main effect: P = 0.029), WC (P = 0.001), waist-to-hip ratio (P = 0.001), and BMI (P = 0.001; all, 2-way ANOVA), whereas no significant difference was found for hip circumference (P = 0.193). There was a significant difference in WC (WC main effect: P = 0.001), hip circumference (P = 0.001), waist-to-hip ratio (P = 0.001), and BMI (P = 0.001; all: 2-way ANOVA) between the categories of WC, whereas no significant difference was found for age (P = 0.703). The interaction term between WC and triacylglycerol was significant only for hip circumference. There was no significant difference in the distribution of adolescents with family history of diabetes across different categories of serum triacylglycerol concentration and WC. Most adolescents with the HW phenotype were overweight (75.9%), but only 3.9% of adolescents with normal serum triacylglycerol and normal WC were overweight. Conversely, most adolescents with normal serum triacylglycerol and normal WC had normal weight (86.1%), whereas only 8.2% of adolescents with the HW phenotype had normal weight (data not shown).


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  		TABLE 1. Characteristics of adolescents by phenotypes of serum triacylglycerol (TG) concentration and waist circumference (WC)1

 
Multivariate-adjusted means of metabolic risk factors across different phenotypes of serum triacylglycerol concentration and WC are given in Table 2Go. After control for age and sex, adolescents in different categories of serum triacylglycerol concentrations had significantly different degrees of metabolic abnormalities (triacylglycerol main effect: P = 0.001 for all, 2-way ANOVA). When the models were further adjusted for BMI, the difference in diastolic blood pressure ceased to be significant and that of systolic blood pressure weakened between different categories of serum triacylglycerol concentrations, which indicated that the differences were mediated by BMI. But even after control for BMI, there was a significant difference in other metabolic abnormalities between different categories of serum triacylglycerol concentration. Significant differences in serum TC (WC main effect: P = 0.001), HDL cholesterol (P = 0.002), LDL cholesterol (P = 0.001), triacylglycerol concentration (P = 0.001), and systolic (P = 0.001) and diastolic (P = 0.001; 2-way ANOVA for all) blood pressure were found between categories of WC after control for age and sex. All of these differences ceased to be significant after further control for BMI. There was a significant interaction between WC and triacylglycerol with regard to serum TC and triacylglycerol. A significant interaction was also found for LDL cholesterol when the model was controlled for age and sex, but not after further control for BMI.


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  		TABLE 2. Multivariate-adjusted means for metabolic risk factors across phenotypes of serum triacylglycerol (TG) concentration and waist circumference (WC)1

 
The prevalence of metabolic risk factors across different phenotypes of serum triacylglycerol concentration and WC is shown in Table 3Go. Adolescents in different categories of serum triacylglycerol concentrations (triacylglycerol main effect: P < 0.01, 2-way ANOVA) and WC (WC main effect: P < 0.01, 2-way ANOVA) had significantly different prevalences of all metabolic abnormalities except elevated fasting glucose (triacylglycerol main effect: P > 0.05; WC main effect: P > 0.05; 2-way ANOVA for all). There was a significant interaction between WC and triacylglycerol concentrations with regard to the prevalence of elevated fasting glucose, high LDL cholesterol, hypercholesterolemia, ≥2 risk factors, and the metabolic syndrome. Adolescents with the HW phenotype had significantly higher prevalences of all metabolic risk factors except elevated fasting glucose than did the other phenotypes. Approximately 4 of 5 adolescents with the HW phenotype met the criteria for the metabolic syndrome. Adolescents with elevated WC and normal serum triacylglycerol concentrations had significantly higher prevalences of elevated fasting glucose than did other groups.


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  		TABLE 3. Prevalence of metabolic abnormalities across phenotypes of serum triacylglycerol (TG) concentration and waist circumference (WC)1

 
Multivariate-adjusted ORs (and 95% CIs) for metabolic risk factors across different phenotypes of serum triacylglycerol concentration and WC are shown in Table 4Go. After control for age, sex, and physical activity, adolescents with the HW phenotype were more likely to have elevated blood pressure (2.1; 1.7, 2.7), high LDL cholesterol (3.3; 2.5, 4.4), low HDL cholesterol (2.1; 1.7, 2.5), hypercholesterolemia (5.1; 3.9, 6.7), hypertension (2.8; 2.0, 3.8), and ≥1 (1.9; 1.6, 2.2) and ≥2 (4.6; 3.7, 5.9) risk factors than were adolescents with normal WC and triacylglycerol concentrations. When the models were further controlled for BMI, the association of elevated blood pressure and hypertension with the HW phenotype was no longer significant, whereas the association of other metabolic abnormalities with the HW phenotype remained significant. Elevated fasting glucose was not associated with the HW phenotype in either model.


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  		TABLE 4. Multivariate-adjusted odds ratios (and 95% CIs) for metabolic risk factors across phenotypes of serum triacylglycerol (TG) concentration and waist circumference (WC)1

 
The comparison of the HW phenotype, overweight, and metabolic syndrome with respect to their ability to predict the presence or absence of risk factors is shown in Table 5Go. The HW phenotype was seen to have a significantly higher percentage of correct prediction than was overweight. There was a significant difference between the percentage of subjects whose risk factor status was correctly predicted with the use of the HW phenotype (but not with the use of overweight), and the percentage of subjects whose risk factor status was correctly predicted with the use of overweight (but not with the use of the HW phenotype). Significant differences were also seen between the HW phenotype and the metabolic syndrome. The HW phenotype alone identified more persons with high concentrations of LDL cholesterol than did the metabolic syndrome alone. However, other metabolic abnormalities were more likely to be predicted correctly by the metabolic syndrome than by the HW phenotype. The HW phenotype had also a higher percentage of correct prediction for most risk factors than did either elevated triacylglycerol concentration or enlarged WC alone (data not shown).


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  		TABLE 5. Comparison of selected screening measures for predicting metabolic abnormalities in Tehranian adolescents1

 
A comparison of the sensitivity and specificity of the HW phenotype, overweight, and the metabolic syndrome for CVD risk factors is shown in Table 6Go. In predicting most metabolic abnormalities, the HW phenotype had significantly higher sensitivity than did overweight and significantly lower sensitivity than did the metabolic syndrome. The specificity of this phenotype for predicting risk factors was found to be significantly higher than that of overweight but not significantly different from that of the metabolic syndrome. The HW phenotype had significantly higher sensitivity and specificity for all risk factors than did either elevated triacylglycerol concentration or enlarged WC (data not shown).


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  		TABLE 6. Sensitivity and specificity of hypertriglyceridemic waist (HW) phenotype, overweight, and metabolic syndrome (MS) in predicting metabolic abnormalities in adolescents

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
The current study, conducted on a population of Tehranian adolescents, showed clustering of metabolic risk factors in adolescents with the HW phenotype. This is the first study proposing the use of HW as a screening tool for identification of adolescents who are at metabolic risk; however, the use of the HW phenotype for screening metabolic risks is not new, and the current literature contains some reports of studies that used this phenotype to estimate the risk in adults. Canadian investigators showed that the HW phenotype could identify men with hyperinsulinemia, elevated apolipoprotein B, and small, dense LDL particles, and their findings indicated that CAD risk factors increase as WC and triacylglycerol concentrations increase (15). Such a finding has also been reported by LaMonte et al (20) in women enrolled in the Cross-Cultural Activity Participation Study. Kahn and Valdez (17) introduced this phenotype as a simple marker for identifying the syndrome of lipid overaccumulation in US men and women. We showed clustering of CVD risks in Iranian men (18) and women (19) with the HW phenotype. Overall, these data indicate that the HW phenotype is a simple, inexpensive, accurate measure that could be used to identify high-risk groups among both adults and adolescents. This phenotype describes a high-risk obesity subtype and provides a promising approach to evaluating CVD risk; differences, however, in visceral adipose tissue accumulation and metabolic complications attributable to age, sex, and ethnicity still need to be assessed, because cutoffs may differ for different populations. It is hoped that, in the future, WC will be routinely monitored by family physicians as a critically important vital sign because of its excellent reproducibility (28) and simplicity.

Some investigators believe that the HW phenotype predicts the occurrence of the metabolic syndrome in adults (16). Whereas elevated triacylglycerol concentrations and enlarged WC were previously associated with increased risk for CAD among adolescents, it remains unknown whether the HW phenotype is also associated with the metabolic abnormalities in adolescents. Although the prevalence of both the HW and the metabolic syndrome in adolescents has rarely been investigated (8-11), the results of the current study showed that, in Tehranian adolescents, those with the HW phenotype are more likely to have metabolic syndrome and clustering of CVD risk factors than are those without this phenotype. WC, even without triacylglycerol concentration, has been shown to be the best predictor of metabolic syndrome in children (41) and is more closely related to multiple CVD risk factors than is BMI (42). Enlarged WC reflects high intraabdominal fat in both children (43, 44) and adults (45), which results in increased delivery of lipid products to the liver, which in turn produces higher concentrations of LDL and VLDL and also increases hepatic gluconeogenesis. On the other hand, elevated serum triacylglycerol could result in lower concentrations of HDL cholesterol. High intraabdominal fat would also cause free fatty acid concentrations to increase in body tissues, which in turn could result in the development of insulin resistance and hyperinsulinemia (17), which combine to form the fundamental metabolic defect underlying the metabolic syndrome and metabolic abnormalities (3, 4, 12, 13).

In the current study, the HW phenotype was not associated with elevated fasting glucose. Moreover, when the models were controlled for BMI, there was no significant association between the HW phenotype and hypertension or elevated blood pressure. This could indicate that overall obesity plays a more important role in elevated blood glucose and hypertension than does fat distribution. Other factors such as dietary intake might be important factors in determining blood glucose and blood pressure (46, 47).

Our findings should be interpreted along with consideration of some limitations. The major limitation of this study is the definition of the HW phenotype. We used a value of ≥90th percentile for age and sex from our sample population to define enlarged WC. The choice of the 90th percentile was based on the association between truncal fat and WC described by Taylor et al (31). Other investigators also showed that clustering of risk factors was significantly higher in subjects with a WC > 90th percentile than in subjects with a WC < 90th percentile (32). It should be kept in mind that, in the TLGS, WC was measured at the point of noticeable waist narrowing, which may have resulted in lower WC values than may be obtained by using other common sites of measurement (28). Whereas the World Health Organization Expert Committee on Physical Status recommends measurement midway between the lower rib and the iliac crest (48), the third National Health and Nutrition Examination Survey guidelines prescribe the use of a point just above the right ileum (49), and the recommendation of the North American Association for the Study of Obesity (50) and the National Heart, Lung, and Blood Institute is to use the right iliac crest (50). The lack of standard measurement for WC is unfortunate, and it makes comparison with other studies difficult. It is believed that the use of the narrowest waist measurement offers greater ease of acceptance and interpretation by the public and may facilitate self-measurement in addition to clinical use. The cross-sectional nature of our study did not allow us to make causal inferences, and prospective studies are necessary to prove whether this phenotype could predict major outcomes such as CVD events or mortality. However, most recently, Tank et al (51) showed in a prospective study that enlarged WC combined with elevated triacylglycerol is a strong predictor of accelerated atherogenesis and related CVD mortality in postmenopausal women. It should be kept in mind that serum lipid concentrations, particularly in males, are affected by puberty (52). Yet pediatric data for lipid norms are available by age, not by Tanner stage. Therefore, we may have overestimated the number of subjects with high serum triacylglycerol concentrations. Fat distribution is also affected by puberty (53). We attempted to control for this by using age- and sex-specific WC percentiles. However, it should be kept in mind that our study group was a population aged 10–19 y, which therefore included prepubertal, pubertal, and postpubertal subjects. Covariance for age alone does not adequately adjust for the influence of hormonal and body-composition differences across a population that varies widely in pubertal development. Unfortunately, in the TLGS, we did not gather data on the stage of pubertal development. However Cook et al (10) observed no difference in the prevalence of the metabolic syndrome when they examined by stage of pubertal development. Our results in the current study are based on data from the first phase of the TLGS, collected nearly 5 y ago. Because overweight is more prevalent now in children and adolescents than it was 5 y ago (54), the HW phenotype may also have a higher prevalence now than it did during the first phase of the TLGS.

Our study provides evidence of a clustering of metabolic abnormalities in adolescents with the HW phenotype and suggests this phenotype as a simple marker for identifying adolescents at risk of the metabolic syndrome and other metabolic abnormalities. Because measurements of WC and fasting serum triacylglycerol concentrations are relatively inexpensive and readily available in a clinical setting, the possibility of using these indexes to identify asymptomatic persons at high risk of CAD and diabetes has important public health implications for primary prevention and could improve the ability of general physicians and other health professionals to identify subjects with a cluster of metabolic abnormalities.


   ACKNOWLEDGMENTS
 
We thank the participants of the Tehran Lipid and Glucose Study for their enthusiastic support and the staff of the Endocrine Research Center, Tehran Lipid and Glucose Study unit, for their valuable help in conducting this study.

AE and PM designed the study, collected and analyzed the data, and wrote the manuscript. FA supervised the study. None of the authors had any personal or financial conflicts of interest.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
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Received for publication March 14, 2005. Accepted for publication August 25, 2005.


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