Influence of the Metabolic Syndrome Versus the Sum of Its Individual Components on Left Ventricular Geometry in Young Adults (from the Bogalusa Heart Study)

Influence of the Metabolic Syndrome Versus the Sum of Its Individual Components on Left Ventricular Geometry in Young Adults (from the Bogalusa Heart Study) Dharmendrakumar A. Patel, MD, MPHa,*, Sathanur R. Srinivasan, PhDb, Wei Chen, MD, PhDb, and Gerald S. Berenson, MDb Current preventive cardiology guidelines strongly recommend identification of metabolic syndrome (MS), a constellation of cardiovascular risk factors, in clinical practice. These MS risk factors, individually or in a cluster, adversely alter left ventricular (LV) geometry. However, it is still unclear whether MS predicts risk, above and beyond its individual risk factors, for abnormal LV geometry. This aspect was examined in 830 asymptomatic patients (mean age 37 years, 69% whites, 41% men) as a part of the Bogalusa Heart Study. Patients with MS (as defined by the National Cholesterol Education Program Adult Treatment Panel III) showed adverse levels of echocardiographic parameters compared with patients without MS. With respect to MS components, patients with eccentric hypertrophy (EH) or concentric hypertrophy (CH) showed higher values of MS risk factors compared with patients with normal geometric pattern but no differences were noted between patients with normal and concentric remodeling. Of note, patients with concentric remodeling versus EH showed significantly higher systolic and diastolic blood pressure and fasting glucose levels. A model including only MS strongly predicted risk of EH (odds ratio [OR] 4.16, p <0.0001) and CH (OR 13.6, p <0.0001) compared with normal LV geometry. In a model including only individual MS risk factors, obesity (EH vs normal OR 14.4, p <0.0001), high blood pressure (CH vs normal OR 19.38, p <0.0001), and high fasting glucose levels (CH vs normal OR 4.02, p ⴝ 0.001) were significant predictors of abnormal LV geometry. However, the likelihood ratio test and comparisons of C-statistics for models including only individual MS risk factors versus models also including the MS variable were not significant. In conclusion, MS and its individual risk factors were strongly associated with LV geometry. However, MS did not predict risk of abnormal LV geometry independent of its individual components. © 2009 Elsevier Inc. (Am J Cardiol 2009;104: 69 –73)

As a part of the Bogalusa Heart Study, a communitybased investigation of the early natural history of cardiovascular (CV) disease,1 the present study examined (1) the influence of metabolic syndrome (MS) versus its individual risk factor components on different left ventricular (LV) geometries and (2) whether MS predicts LV geometry better than the sum of its individual components in asymptomatic young adults. Methods The Bogalusa Heart Study is a long-term epidemiologic study of the natural history of CV disease in children and young adults from the semirural, biracial (65% white, 35% black) community of Bogalusa, Louisiana. The population a Ochsner Clinic Foundation, and bTulane University, New Orleans, Louisiana. Manuscript received October 21, 2008; revised manuscript received and accepted February 23, 2009. This work was supported by Grant AG-16592 from the National Institute of Aging and Grant HL-38844 from the National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland. *Corresponding author: Tel: 504-988-7197; fax: 504-988-7194. E-mail address: [email protected].

0002-9149/09/$ – see front matter © 2009 Elsevier Inc. doi:10.1016/j.amjcard.2009.02.063

and study design of the Bogalusa Heart Study have been previously described.2,3 Subjects (n ⫽ 1,203) 24 to 43 years of age were examined in 2000 to 2001 as part of a long-term follow-up study. Of these, 830 fasting subjects (mean age 36.5 years, 69% white, 41% men) who had data on echocardiographic examinations of the heart and other variables of MS formed the study sample. This study was approved by the institutional review board of the Tulane University Health Sciences Center (New Orleans, Louisiana). All participants gave their informed consent. Standardized protocols were used by trained observers in all examinations.3 Subjects were instructed to fast for 12 hours before screening, with compliance ascertained by an interview on the day of examination. Height and weight were measured 2 times to ⫾0.1 cm and to ⫾0.1 kg, respectively, and average values were used to calculate body mass index as a measurement of overall adiposity. Waist circumference was measured midway between the lower rib cage and the iliac crest as an indicator of visceral fatness.4 Replicate blood pressure measurements were obtained by trained observers in the right arm of the subjects in a relaxed, sitting position. Systolic and diastolic blood pressure levels were recorded as the first and fifth Korotkoff phases, respectively, using a mercury sphygmomanometer. www.AJConline.org

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Blood pressure levels were reported as the mean of 6 replicate readings taken by each of 2 randomly assigned observers. Cholesterol and triglyceride levels in serum were assayed using enzymatic procedures on a Hitachi 902 automatic analyzer (Roche Diagnostics, Indianapolis, Indiana). Serum lipoprotein cholesterol levels were analyzed by a combination of heparin-calcium precipitation and agar-agarose gel electrophoresis procedures.5 The laboratory is monitored for precision and accuracy of lipid measurements by the Lipid Standardization and Surveillance Program of the Centers for Disease Control and Prevention (Atlanta, Georgia). A commercial radioimmunoassay kit was used for measuring plasma immunoreactive insulin levels (Phadebas; Pharmacia Diagnostics, Piscataway, New Jersey). Glucose levels were measured as part of a multiple chemistry profile (SMA20) by enzymatic procedures with a multichannel Olympus Au-5000 analyzer (Olympus, Lake Success, New York). LV dimensions were assessed by 2-dimensional M-mode echocardiography with 2.25- and 3.5-MHz transducers according to American Society of Echocardiography recommendations.6 Images were recorded on standard VHS videocassette tapes by trained technicians, and repeated observations were obtained in a randomized 6% sample of subjects selected for repeat measurements 10 to 12 days apart. Measurement errors were consistent with those found in other epidemiologic studies. The coefficient of variation for inter- and intrareader variabilities for all measures of cardiac anatomy was ⬍10%. All echocardiograms were digitized and measured on TomTec/Freeland Cardiology Workstation Digitizing Systems (TomTec/Freeland Systems, Broomfield, Colorado). Parasternal long- and short-axis views were used for measuring LV end-diastolic and end-systolic measurements in duplicate, which were then averaged. LV mass was calculated from a necropsy-validated formula,7 based on a thick-wall prolate ellipsoidal geometry.8 To take body size into account, LV mass was normalized for body height to power 2.7, an indexation that has been reported to detection from normal, also in obese subjects.9,10 LV relative wall thickness was also calculated, as septal wall thickness plus posterior wall thickness divided by LV end-diastolic diameter.11 The presence of LV hypertrophy was defined by LV mass indexes ⬎47 g/m2.7 in women and ⬎50 g/m2.7 in men.9 LV geometry was considered concentric when relative wall thickness was ⬎0.42.12 Patterns of LV geometry were defined as normal LV geometry (normal relative wall thickness with no LV hypertrophy), concentric LV remodeling (concentric remodeling defined as increased relative wall thickness but no LV hypertrophy), eccentric LV hypertrophy (EH; normal relative wall thickness with LV hypertrophy), and concentric LV hypertrophy (CH; increased relative wall thickness with LV hypertrophy).13 All statistical analyses were performed with SAS 9.1 (SAS Institute, Cary, North Carolina). Echocardiographic variables were compared between subjects with and without MS (ⱖ3 risk factors defined by the National Cholesterol Education Program Adult Treatment Panel III14) using Student’s t test, chi-square test, and analysis of covariance. Similarly, concentric remodeling, EH, and CH were com-

Table 1 Echocardiographic parameters by metabolic syndrome status: the Bogalusa Heart Study Echocardiographic Parameters

MS Absent (n ⫽ 696)

MS Present (n ⫽ 134)

p Value

LV mass (g) LV mass index (g/m2.7) LV posterior wall thickness (cm) Septal wall thickness (mm) Relative wall thickness (mm) LV end-diastolic diameter (cm) Fractional shortening E/A ratio

133 ⫾ 42 32 ⫾ 9 0.76 ⫾ 0.15 0.78 ⫾ 0.16 0.31 ⫾ 0.10 5.01 ⫾ 0.57 5.36 ⫾ 2.84 2.60 ⫾ 1.31

173 ⫾ 49 41 ⫾ 11 0.87 ⫾ 0.19 0.89 ⫾ 0.18 0.34 ⫾ 0.09 5.34 ⫾ 0.65 4.77 ⫾ 2.71 2.14 ⫾ 0.84

⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 0.0004 ⬍0.0001 0.03 0.0004

pared with normal LV geometry with respect to MS risk variables. Effect of multiple risk factors of MS, as defined by National Cholesterol Education Program Adult Treatment Panel III14 on LV mass index and relative wall thickness, variables used to define LV geometric patterns, were examined by comparing mean values of subjects with 0, 1, 2, and ⱖ3 risk factors. Multiple regression models containing the MS variable and/or individual MS components were used to calculate odds ratios (ORs) with 95% confidence intervals. Likelihood ratio tests were used to compare models including individual MS components with and without the MS variable. Areas under the receiver operating characteristics curve (C-statistics) were calculated for models including individual MS components with and without the MS variable. The hypothesis that MS influences LV geometric patterns above and beyond the impact of its individual components was tested by comparing C-statistics and using likelihood ratio tests. Results Of 830 subjects, 134 (16%) met the MS criteria as defined by National Cholesterol Education Program Adult Treatment Panel III. Of note, 31% of subjects (normal 96%, concentric remodeling 4%, EH 0%, CH 0%) had “0” MS risk factor. Similarly, 53% of subjects (normal 91%, concentric remodeling 5%, EH 3%, CH 1%) had “0 or 1” risk factor, and 16% (normal 74%, concentric remodeling 6%, EH 11%, CH 9%) had “ⱖ3” risk factors of MS. Echocardiographic characteristics of subjects with and without MS are listed in Table 1. Subjects with MS showed significantly higher (p ⬍0.0001) values for LV mass, LV mass index, end-diastolic posterior wall thickness, septal wall thickness, relative wall thickness, and LV end-diastolic diameter and lower values for fractional shortening (p ⫽ 0.03) and E/A ratio (p ⫽ 0.0004) than subjects without MS. With respect to MS components, subjects with EH or CH showed higher values of MS risk factors compared with subjects with normal geometric pattern but no differences were noted between subjects with normal and concentric remodeling patterns of LV geometry (Table 2). Also, the prevalence of subjects with MS and its individual risk factors was significantly different among different LV geometries. Of note, subjects with CH versus EH showed significantly higher systolic and diastolic blood pressure and fasting glucose levels and had a higher prevalence of hypertension and

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Table 2 Prevalence and mean levels of risk factor variables by left ventricular geometry: the Bogalusa Heart Study Risk Factors

Men Whites MS Obesity Hypertension Dyslipidemia Hyperglycemia Age (yrs) Waist circumference (cm) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) HDL cholesterol (mg/dl) Triglyceride (mg/dl) Glucose (mg/dl)

Normal (n ⫽ 727)

CR (n ⫽ 46)

EH (n ⫽ 39)

CH (n ⫽ 18)

40% 70% 14% 32% 20% 52% 4% 36 ⫾ 4 89 ⫾ 15 115 ⫾ 13 78 ⫾ 9 49 ⫾ 14 124 ⫾ 96 85 ⫾ 22

63% 78% 17% 39% 13% 67% 2% 37 ⫾ 4 94 ⫾ 15 114 ⫾ 10 78 ⫾ 7 43 ⫾ 10 153 ⫾ 150 88 ⫾ 34

36% 54% 39% 90% 44% 72% 13% 37 ⫾ 5 110 ⫾ 15 123 ⫾ 17 83 ⫾ 11 43 ⫾ 12 163 ⫾ 97 97 ⫾ 39

22% 33% 67% 89% 83% 67% 39% 37 ⫾ 5 108 ⫾ 16 138 ⫾ 17 91 ⫾ 10 46 ⫾ 11 159 ⫾ 128 125 ⫾ 69

p Value Normal vs CR

Normal vs EH

Normal vs CH

⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 NS NS NS NS NS NS NS

⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 NS ⬍0.0001 0.001 0.002 0.01 0.02 0.04

⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 NS ⬍0.0001 ⬍0.0001 ⬍0.0001 NS NS ⬍0.0001

Obesity was defined as a body mass index ⬎30 kg/m2; hypertension as systolic blood pressure ⬎140 mm Hg or diastolic blood pressure ⬎90 mm Hg or being treated for the condition; dyslipidemia as total cholesterol level ⬎240 mg/dl, low-density lipoprotein cholesterol level ⬎160 mg/dl, HDL cholesterol ⬍40 mg/dl, triglyceride level ⬎150 mg/dl, or being treated for the condition; and hyperglycemia as fasting glucose level ⱖ126 mg/dl. CR ⫽ concentric remodeling; HDL ⫽ high-density lipoprotein.

P for trend: <0.0001

Relative Wall Thickness

Left Ventricular Mass Index

Left Ventricular Mass Index and Relative Wall Thickness by Increasing Metabolic Syndrome Components P for trend: <0.0001

Components of Metabolic Syndrome (NCEP ATP III) [ “0” (n=253), “1” (n=236), “2” (n=207), “3+” (n=134) ] Figure 1. LV mass index and relative wall thickness by 0 MS risk factor (n ⫽ 253), 1 MS risk factor (n ⫽ 236), 2 MS risk factors (n ⫽ 207), and ⱖ3 MS risk factors (n ⫽ 134): the Bogalusa Heart Study.

hyperglycemia. LV mass index and relative wall thickness, parameters used to define LV geometry, were significantly correlated to an increasing number of MS components, as shown in Figure 1. ORs and C-statistics of MS versus its components for predicting different LV geometric patterns are listed in Table 3. Regression model including only MS strongly predicted risk of EH (OR 4.16, p ⬍0.0001) and CH (OR 13.6, p ⬍0.0001) compared with normal LV geometry. In a model including only individual MS risk factors, obesity (EH vs normal OR 14.4, p ⬍0.0001; CH vs normal OR 4.92, 1.22 to 24.87, p ⫽ 0.001), high blood pressure (CH vs normal: OR ⫽ 19.38, p ⬍0.0001), and high fasting glucose levels (CH vs normal OR 4.02, p ⫽ 0.001) were significant predictors of abnormal LV geometry. However, the likeli-

hood ratio test and comparisons of C-statistics for models including only individual MS risk factors with models also including the MS variable were not significant. Discussion In the present community-based study of asymptomatic young adults, individual CV risk factors and their cluster as MS were strongly associated with presence of abnormal LV geometry. However, risk of abnormal LV geometry associated with MS was no different than that explained by the presence of its individual components. MS has an impact on LV geometry and function, which are potent bioassays of preclinical CV disease. Similarly, components of MS are independently associated with LV

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Table 3 Odds ratio (95% CI) and C-statistic (area under receiver operating characteristic curve) values of metabolic syndrome versus its components for abnormal left ventricular geometric patterns compared with normal left ventricular geometry: the Bogalusa Heart Study

OR (95% CI) MS (vs not)—unadjusted MS components—adjusted for each other Obesity (vs not) High blood pressure (vs not) High glucose (vs not) High triglyceride (vs not) Low HDL cholesterol (vs not) MS (vs not)—adjusted for its components Likelihood ratio test (p value)* C-statistic Model including only individual MS components Model including individual components plus MS variable p value for comparison of C-statistics

CR

EH

CH

1.99 (0.54–2.67)

4.16 (2.10–8.27)‡

13.60 (4.88–37.89)‡

1.52 (0.79–2.92) 0.37 (0.15–1.00) 0.40 (0.05–3.06) 1.81 (0.91–3.60) 1.30 (0.69–2.47) 0.80 (0.24–2.72) NS

14.40 (4.88–42.54)‡ 2.00 (1.00–4.21) 1.65 (0.56–4.90) 0.83 (0.37–1.88) 1.79 (0.85–3.75) 0.32 (0.08–1.21) NS

4.92 (1.22–24.87)† 19.38 (4.69–80.07)‡ 4.02 (2.41–33.78)† 0.81 (0.20–3.21) 1.87 (0.57–6.20) 0.47 (0.07–3.43) NS

0.68 0.68 NS

0.85 0.85 NS

0.92 0.92 NS

All models included age, race, and gender. * Likelihood ratio test (p values) compares models including only MS components with models also including the MS variable. † p ⫽ 0.001; ‡ p ⬍0.0001. CI ⫽ confidence interval. Other abbreviations as in Table 2.

hypertrophy and/or dysfunction even in the absence of coronary artery disease. Several studies have examined this relation of risk factors, individually or in a cluster, on LV geometry. Observations from the present study focus on the adverse impact of individual MS factors and their clustering on LV geometry in the same population. Individually, obesity is 1 of the strongest predictors of EH and CH, independent of other MS risk factors. Several mechanisms by which obesity can lead to alteration in LV geometry include excessive vascularity of adipose tissue, increase in total blood volume, and greater cardiac output.15–18 In addition, fat cells generate cytokines and inflammatory factors that can increase cardiac remodeling. Obesity also influences cardiac dilatation that produces additional stress and compensatory hypertrophy. Similarly, high blood pressure and diabetes have detrimental effects on LV structure and function.19 –21 Especially the concentric form of LV hypertrophy (LV hypertrophy), which is known to be associated with a worse prognosis,22–24 is related to the occurrence of diabetes and hypertension.19,21,25 Arterial hypertension results in cardiac geometric adaptation mainly by altering systemic hemodynamics and ventricular load.13 High fasting glucose levels and subsequent hyperinsulinemia and associated insulin resistance have been known to cause the altered collagen/ muscular ratio and exaggerated CV trophic effects of insulin. The present study, in agreement with other studies, also showed a strong adverse relation between MS and abnormal LV geometry. Moreover, supporting the finding that combined metabolic abnormalities exert a greater adverse influence to alter LV geometry, the present study demonstrates the burden of clustering on LV geometry by showing abnormal LV geometry with increasing MS risk factors. Among major independent predictors of abnormal LV geometry, obesity was the most prevalent in this study population and may underlie or amplify the effect of other risk factors on LV geometry. Higher prevalence of abnormal LV geometry has been noted in obese subjects with associated hypertension and diabetes compared with subjects with 1

risk factor or 2 risk factors.26 Even without obesity, joint effects of systemic hypertension and diabetes mellitus have been shown to be more detrimental on LV and function.13,25 Thus, strong coexistence of multiple MS risk factors that complement each other results in a higher risk burden. The present study did not find any additional risk information provided by MS above and beyond its individual components. Few studies have demonstrated similar findings using different CV end points.27,28 On the contrary, there are few studies showing the additional benefit of MS independent of its components in risk prediction.29 Thus the issue is still debatable and unresolved. However, if the results of this study are confirmed in other samples, MS might be viewed as a useful clinical summary of risk factors rather than as a strong biological entity and a target for pharmacologic treatment. This by no means undermines the usefulness of MS as a cluster of risk factors, which encourages clinicians to look for the presence of other CV risk factors in subjects with any major CV risk factor. 1. The Bogalusa Heart Study. 20th anniversary symposium. Am J Med Sci 1995;310(suppl):S1–S318. 2. Berenson GS, McMahan CA, Voors AW, Webber LS, Srinivasan SE, Frank GC, Foster TA, Blonde CV. Cardiovascular Risk Factors in Children—The Early Natural History of Atherosclerosis and Essential Hypertension. New York: Oxford University Press, 1980. 3. Berenson GS, ed. Causation of Cardiovascular Risk Factors in Children: Perspective on Cardiovascular Risk in Early Life. New York: Raven, 1986:408. 4. Pouliot MC, Despres JP, Lemieux S, Moorjani S, Bouchard C, Tremblay A, Nadeau A, Lupien PJ. Waist circumference and abdominal sagittal diameter: best simple anthropometric indexes of abdominal visceral adipose tissue accumulation and related cardiovascular risk in men and women. Am J Cardiol 1994;73:460 – 468. 5. Srinivasan SR, Berenson GS. Serum lipoproteins in children and methods for study. In: Lewis LA, ed. Handbook of Electrophoresis. Boca Raton, FL: CRC, 1983:185–204. 6. Sahn DJ, DeMaria A, Kisslo J, Weyman A. Recommendations regarding quantitation in M-mode echocardiography: results of a survey of echocardiographic measurements. Circulation 1978;58:1072–1083.

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