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Department of Medicine (A.D.C., A.D.), Feinberg School of Medicine, Northwestern University, Chicago, Illinois 60611; and Department of Obstetrics and Gynecology (R.S.L.), Pennsylvania State University College of Medicine, Hershey, Pennsylvania 17033
Address all correspondence and requests for reprints to: Andrea Dunaif, M.D., Division of Endocrinology, Metabolism, and Molecular Medicine, Northwestern University Feinberg School of Medicine, 303 East Chicago Avenue, Tarry Building 15-709, Chicago, Illinois 60611-3008. E-mail: a-dunaif{at}northwestern.edu
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Abstract |
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Objective: Our objective was to test the hypothesis that the prevalence of MBS is increased in adolescent girls with PCOS compared with the general population and to determine the factors associated with an increased risk of the MBS in PCOS.
Design and Setting: We conducted a cross-sectional case-control study at academic medical centers with general clinical research centers.
Participants: Participants included 49 adolescent girls with PCOS and 165 girls from the Third National Health and Nutrition Examination Survey (NHANES III) adolescent population of similar age and ethnic background.
Main Outcome Measure: We assessed the prevalence of MBS according to currently proposed adolescent MBS criteria.
Results: Thirty-seven percent of adolescent girls with PCOS had MBS compared with 5% of NHANES III girls (P < 0.0001). None of the girls of normal body mass index (BMI) had MBS, whereas 11% of overweight and 63% of obese girls with PCOS had MBS compared with 0 and 32% of NHANES III girls, respectively. Girls with PCOS were 4.5 times more likely to have MBS than age-matched NHANES III girls after adjusting for BMI (odds ratio, 4.5; 95% confidence interval, 1.1–17.7; P = 0.03). The odds of having the MBS were 3.8 times higher for every quartile increase in bioavailable testosterone in girls with PCOS after adjusting for BMI and insulin resistance (odds ratio, 3.8; 95% confidence interval, 1.4–10.2; P = 0.008).
Conclusions: Adolescent girls with PCOS have a higher prevalence of MBS than the general adolescent population. Hyperandrogenemia is a risk factor for MBS independent of obesity and insulin resistance.
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Introduction |
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Pediatricians are increasingly concerned about the long-term health effects of childhood and adolescent MBS and believe that it may be associated with early cardiovascular disease in adulthood (14). Progress in defining the nature of the long-term cardiovascular risk is hampered by the lack of consensus on criteria for the diagnosis of the MBS in adolescents (15) as well as the lack of longitudinal studies with cardiovascular endpoints as opposed to surrogate markers. Cardiovascular event endpoints are difficult to target because of the long latency period between the onset of atherosclerosis and the first cardiovascular event. However, there is evidence from autopsy studies that atherosclerosis starts in childhood (14). Furthermore, cardiovascular risk factors in childhood and adolescence have been shown to track with cardiovascular risk factors in adulthood (14, 16). Because PCOS is a common disorder, an increase in MBS among affected adolescents could have substantial public health implications.
We performed this study to investigate whether adolescent girls with PCOS had an increased prevalence of MBS compared with the general U.S. population of comparable age and to test the hypothesis that androgen excess was an independent risk factor for MBS in affected girls. In addition, we compared two sets of diagnostic criteria for MBS as part of this study.
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Subjects and Methods |
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Height and weight were measured on the morning of testing. Body mass index (BMI) was calculated. BMI percentiles adjusted for age and gender were calculated using EpiInfo, version 3.3, provided by the Centers for Disease Control (Atlanta, GA). Waist and hip circumferences were measured as previously reported (5). Blood pressure was measured in the seated position in the right arm after a 30-min rest period. The average of three measurements taken 2 min apart was the reported blood pressure. A morning blood sample was taken after an overnight fast for measurement of glucose, insulin, T, SHBG, non-SHBG-bound or uT, dehydroepiandrosterone sulfate (DHEAS), lipid, and lipoprotein levels.
Reference population
The prevalence of MBS in this group of adolescent girls with PCOS was compared with the prevalence in the female adolescent Third National Health and Nutrition Examination Survey (NHANES III) population. The NHANES III population was sampled from all U.S. households between 1988 and 1994 (19). All non-Hispanic white females aged 12–19 yr with complete information for determining the diagnosis of MBS were included in the study to match the profile of our adolescent PCOS population. Participants who fasted 8 or more hours before their blood draw were included. A total of 165 girls were identified in the NHANES III population who underwent physical and laboratory evaluations and met the above criteria. BMI percentiles adjusted for age and gender were calculated using EpiInfo (Centers for Disease Control, Atlanta, GA).
Laboratory assays
All laboratory assays were done at the endocrine research lab of The Pennsylvania State University College of Medicine, the central research laboratory for this study. T, uT, DHEAS, SHBG, and insulin were assayed as previously reported (18). The T assay had intra- and interassay coefficients of variation (CV) of 4 and 12%, respectively, and the uT assay had intra- and interassay CV of 3 and 6%, respectively, at a low-pool range. The DHEAS assay had intra- and interassay CV of 5 and 8%, respectively. The SHBG assay had intra- and interassay CV of 6 and 8%, respectively. Plasma glucose was determined by the glucose oxidase technique (20). Fasting total cholesterol, HDLc, and TG were assayed as previously reported (21). Low-density lipoprotein cholesterol (LDLc) was calculated using the Friedewald equation (22).
Diagnostic criteria for MBS in adolescents
Waist circumference percentiles adjusted for age, gender, and race were determined using distributions in 9713 children and adolescents in NHANES III (23). Blood pressure percentiles were calculated adjusted for age, gender, and height. The diagnosis of elevated blood pressure in adolescents was a blood pressure equal to or greater than the 90th percentile and hypertension as blood pressure greater than the 95th percentile as defined by the National High Blood Pressure Education Program for Children and Adolescents (24). The diagnosis of MBS was determined using two different proposed sets of criteria for adolescents.
The first diagnostic criteria were those outlined by Cook et al. (2). Adolescents meeting three or more of the following criteria were diagnosed with MBS: waist circumference of at least 90th percentile for age and gender; systolic or diastolic blood pressure at least 90th percentile for age, height, and gender; fasting TG at least 110 mg/dl (90th percentile for age) and fasting HDLc no more than 40 mg/dl (10th percentile for age); and fasting glucose at least 110 mg/dl.
The second diagnostic criteria were proposed by de Ferranti et al. (3). Subjects meeting three or more of the following criteria were diagnosed with MBS: waist circumference more than the 75th percentile for age and gender; elevated blood pressure defined by either systolic or diastolic blood pressure greater than the 90th percentile for age, gender, and height; fasting TG at least 97.3 mg/dl and fasting HDLc less than 50.2 mg/dl; and fasting glucose at least 110 mg/dl.
Statistical analyses
Log transformation was used as necessary to approximate the normal distribution for parametric analyses. Comparisons between groups were done with t test after testing for equality of variance and ANCOVA for adjusted comparisons. When assumptions for parametric tests were not met, the two-sample Wilcoxon rank-sum/Mann-Whitney test was used. Prevalence rates across subgroups were compared with 
2 analysis including Cochran-Mantel-Haenszel statistics for composite odds ratios. The homeostatic index of IR (HOMA-IR) was calculated as follows: HOMA-IR = [fasting insulin (µU/ml) x fasting glucose (mmol/liter)]/22.5 (25).
Logistic regression was used to examine predictors of MBS and to adjust for IR, BMI, and SHBG. Adjustment for IR was done by stratification by HOMA-IR quartile. Stratification by BMI was done by percentile grouping adjusted for age: 1) normal, less than the 85th percentile; 2) overweight, 85–94th percentile; 3) obese, 95–97th percentile; and 4) severely obese, more than the 97th percentile. Relationships between lipids, androgens, and metabolic parameters were examined with Pearson correlation and Spearman-Rank correlation coefficients. Linear regression was used to examine predictors of uT, and 
was set at 0.05 for the purpose of determining statistical significance for all analyses. Statistical analyses were done with Stata 6.0 (StataCorp, College Station, TX) and SAS 9.12 (SAS Institute, Inc., Cary, NC). Data are presented as the untransformed mean ± SD or proportion ± SE.
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Results |
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). All 49 girls identified their ethnicity as white of non-Hispanic origin. Although three girls (6%) had a previous diagnosis of hypertension, 10 girls (20%) were newly diagnosed with hypertension using pediatric diagnostic criteria (24). None of the girls had a previous diagnosis of DM. One (2%) was newly diagnosed with type 2 DM. Over half (55%) were obese as defined by a BMI equal to or greater than the 95th percentile, and an additional 18% were overweight defined as BMI equal to or greater than the 85th but less than the 95th percentile. Nineteen girls (38%) were severely obese (BMI greater than the 97th percentile). Only four (8%) met the criteria for severe obesity defined by Weiss et al. (4) as a BMI greater than 2.5 SD above the mean (>99.4th percentile).
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). The prevalence of MBS was 47% using the de Ferranti et al. (3) criteria compared with 13% of the NHANES III girls. The de Ferranti criteria had a higher prevalence of adolescent girls who met the waist circumference and lipid profile criteria as expected given the more liberal cutoff points (Table 2). The proportion with elevated blood pressure and fasting glucose were similar with both criteria. Although only one girl with PCOS met all five MBS criteria, 4% had no features of MBS with the de Ferranti criteria, and 25% had no features of MBS with the Cook criteria.
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). Overall, the risk of MBS was higher in girls with PCOS compared with the general population after adjusting for BMI (P = 0.01).
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Because the mean age of girls with PCOS was higher, 17 ± 2 yr compared with 15 ± 2 yr in the NHANES III girls, a second analysis was done in 127 girls in NHANES III aged 14–19 yr to match the age range of girls with PCOS. The prevalence of the MBS in this subset was not appreciably different from the original group of 165 girls aged 12–19 yr. The prevalence of MBS in the NHANES III population aged 14–19 yr was 3 ± 2% using the Cook criteria (2) and 12 ± 3% using the de Ferranti criteria (3). The smaller group of NHANES III girls did result in a loss of power to allow comparison of MBS prevalence within BMI strata; however, the overall trend was the same. The overall odds of having MBS was higher in girls with PCOS compared with the NHANES III population age 14–19 yr after stratifying by BMI [odds ratio (OR), 4.5; 95% confidence interval (CI), 1.1–17.7; P = 0.03].
Hyperandrogenemia (subanalysis in girls with PCOS)
The mean uT was higher in the adolescent girls with the MBS than in adolescent girls without the MBS (40 ± 3 vs. 23 ± 2 ng/dl; P < 0.0001). The difference in uT between girls with and without the MBS was significant (P = 0.001) after adjusting for HOMA-IR and BMI with regression modeling (total model: P = 0.0002, R2 = 0.31). There was no significant difference in total T between groups (80 ± 23 vs. 72 ± 25 ng/dl; P = 0.2). SHBG was lower in the girls with MBS than those without MBS (33 ± 13 vs. 77 ± 53 nmol/liter; P < 0.01).
The relative odds of an adolescent girl with PCOS having MBS increased approximately five times for every quartile increase in uT (OR, 4.8; 95% CI, 2.1–11.2; P < 0.0001) and increased approximately four times for every quartile increase in uT after adjusting for HOMA-IR and BMI (OR, 3.8; 95% CI, 1.4–10.2; P = 0.008) (Table 3). The prevalence of MBS increased with increasing uT quartile (P < 0.001) (Fig. 2) and decreased with increasing SHBG quartile (P < 0.001). The relative odds of having MBS increased approximately four times for every quartile increase in uT after adjusting for SHBG (OR, 3.8; 95% CI,1.6–9.2; P = 0.003). Girls with uT in the highest two quartiles were approximately 14 times more likely to have MBS than girls with uT in the lowest two quartiles after adjusting for IR and obesity (OR, 14.3; 95% CI, 2.0–100.5; P = 0.007).
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= 0.61; P < 0.0001), waist circumference ( = 0.54; P = 0.0001), fasting insulin ( = 0.39; P = 0.005), HOMA-IR ( = 0.37; P = 0.008), fasting TG ( = 0.34; P = 0.02), and systolic ( = 0.38; P = 0.007) and diastolic ( = 0.35; P = 0.01) blood pressure. uT did not correlate with fasting glucose but was negatively correlated with HDLc ( = –0.42; P = 0.003). SHBG correlated negatively with BMI percentile ( = –0.57; P < 0.0001), waist circumference ( = –0.56; P < 0.0001), fasting insulin ( = –0.42; P = 0.003), HOMA-IR ( = –0.42; P = 0.003), and uT ( = –0.70; P < 0.0001). HOMA-IR was positively correlated with BMI percentile ( = 0.59; P < 0.0001). Lipids
There was no significant difference in the prevalence of elevated LDLc or non-HDLc between girls with PCOS and NHANES III girls. LDLc was in the borderline range (110–129 mg/dl) in 10 ± 4% of girls with PCOS compared with 8 ± 3% of NHANES III girls (26) and in the at-risk range (
130 mg/dl) in 17 ± 5% of girls with PCOS vs. 18 ± 4% of NHANES III girls (27). Non-HDLc was greater than the 90th percentile for white females aged 12–17 yr in 20 ± 6% of girls with PCOS compared with 13 ± 3% of NHANES III girls (16). LDLc and non-HDLc were significantly correlated ( = 0.93; P < 0.0001) in the PCOS population.
The lipid profiles for adolescent girls with PCOS varied with MBS status. Mean fasting LDLc was higher in the group with MBS compared with those without MBS (109 ± 22 vs. 94 ± 25 mg/dl; P = 0.03) using the Cook adolescent MBS criteria. Mean HDLc was lower (36 ± 5 vs. 45 ± 11 mg/dl; P = 0.0003) and mean TG higher (176 ± 86 vs. 90 ± 43 mg/dl; P < 0.0001) in girls with MBS than those unaffected by MBS. Mean non-HDLc was higher in the girls with MBS (142 ± 25 vs. 111 ± 30 mg/dl; P < 0.001).
Blood pressure
The prevalence of hypertension was greater in girls with PCOS compared with the NHANES III girls, 27 ± 6% vs. 1 ± 1%, respectively (P < 0.0001). Girls with PCOS were also more at risk for hypertension with a blood pressure in the 90–95th percentile than the NHANES III girls, 14 ± 5% vs. 2 ± 1%, respectively (P < 0.0001) (24).
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Discussion |
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The Cook criteria were modified from the adult National Cholesterol Education Program Adult Treatment Panel III criteria by lowering the TG and HDLc cutoff points and using the 90th percentile for age and gender for waist circumference and the 90th percentile for age, gender, and height for blood pressure as cutoff points. The de Ferranti criteria were targeted to parallel the adult percentile cutoff points more closely, resulting in more liberal criteria. The difference between the Cook and de Ferranti criteria is largely because of the decrease in the waist circumference cutoff point from the 90th to the 75th percentile and the increase in the HDLc cutoff point from no more than 40 to less than 50.2 mg/dl in the de Ferranti criteria. The prevalence of elevated TG, elevated blood pressure, and fasting hyperglycemia was similar between the two sets of criteria (Table 2
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The increasing prevalence of MBS in children and adolescents has coincided with the rise in obesity as it has in adults (2, 28). The prevalence of MBS increased with BMI in the NHANES III population with both the Cook and de Ferranti criteria (2, 3) and has been estimated to be as high as 50% in a study of severely obese adolescents (4). Both BMI and waist circumference have been shown to be predictive of metabolic cardiovascular risk factors in children and adolescents (29). The rise in childhood obesity correlates with increased waist circumference, a good marker of abdominal visceral fat (14). Visceral adiposity is associated with IR, the primary pathophysiological mechanism thought to be responsible for the metabolic disturbances of MBS (1, 30, 31). Obesity is also a common feature of PCOS, affecting approximately 50–70% of adult women, with a fat distribution characterized by increased central adiposity (32, 33). However, the high prevalence of MBS in these adolescent girls with PCOS cannot be accounted for by obesity alone. The prevalence of the MBS was similar in the obese (BMI, 95–97th percentile) and very obese (BMI, >97th percentile) girls, 62 vs. 63%, respectively (Fig. 1B).
Although the odds of having MBS increased significantly with both increasing HOMA-IR and BMI, the odds of having MBS increased approximately 4-fold for every quartile increase in uT independent of BMI and IR (Table 3). The increased risk of MBS associated with uT was also independent of SHBG. Treatment with flutamide, a nonsteroidal androgen receptor antagonist, has been shown to decrease central fat mass in obese women with PCOS (34) as well as in nonobese women and adolescent girls with PCOS in combination with metformin (35). There is evidence of an additive effect on the improvement of body composition, androgen levels, and IR when metformin and flutamide are used together (35, 36), suggesting an interaction between hyperandrogenemia, hyperinsulinemia, and obesity in the expression of the metabolic phenotype in PCOS. Interestingly, hyperandrogenemia has also been reported to be an independent risk factor for MBS in premenopausal women without PCOS (37) and has been associated with hyperinsulinemia, fasting hyperglycemia, and the metabolic syndrome in postmenopausal women as well (13). Androgen receptors have been identified on preadipocytes and adipocytes, and there is some evidence that intraabdominal fat development may be influenced by androgens (38). Androgens may contribute to MBS through mechanisms independent of or in synergy with central obesity and visceral adiposity.
The prevalence of hypertension was higher in the adolescent girls with PCOS compared with the NHANES III population, 27 vs. 1%, respectively (2). Adolescent girls with PCOS and abnormal glucose tolerance have a disruption of normal circadian blood pressure fluctuations that may be a precursor to the development of hypertension (9). Adolescent girls with PCOS and elevated blood pressure who meet criteria for MBS may represent a subset of girls with a more severe metabolic phenotype.
In addition to the lower HDLc and higher TG levels expected with MBS, the adolescent girls with PCOS and MBS in this study had significantly higher LDLc and non-HDLc compared with girls with PCOS without MBS. Elevated LDLc is characteristic of adult women with PCOS as well as sisters of women with PCOS who have hyperandrogenemia with normal menses (12, 21, 39). Treatment of adult women with the nonsteroidal androgen receptor antagonist flutamide has been shown to decrease fasting cholesterol and LDLc (12, 34, 40) and increase HDLc independent of obesity (40). Elevated LDLc and non-HDLc levels in adolescent girls with PCOS represent additional potential cardiovascular risk factors (16).
In summary, adolescent girls with PCOS appear to be at substantially increased risk for the MBS relative to adolescent girls in the general population. Hyperandrogenemia, in addition to obesity and IR, is an important risk factor for MBS in PCOS. These defects can be targeted with traditional therapy such as diet and exercise as well as with novel interventions with insulin sensitizers and antiandrogens. Early identification of MBS and intervention in adolescent girls with PCOS may mitigate the associated metabolic effects and reduce the risk of developing diabetes and cardiovascular disease.
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Footnotes |
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First Published Online October 25, 2005
Abbreviations: BMI, Body mass index; CI, confidence interval; CV, coefficients of variation; DHEAS, dehydroepiandrosterone sulfate; DM, diabetes mellitus; HDLc, high-density lipoprotein cholesterol; HOMA-IR, homeostatic index of insulin resistance; IR, insulin resistance; LDLc, low-density lipoprotein cholesterol; MBS, metabolic syndrome; PCOS, polycystic ovary syndrome; T, testosterone; TG, triglycerides; uT, bioavalable T.
Received July 26, 2005.
Accepted October 17, 2005.
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