Multivariate analysis of the insulin resistance syndrome in women

The metabolic syndrome: an emerging risk state for cardiovascular disease

The common clustering of glucose intolerance, insulin resistance, abdominal adiposity, elevated blood pressure, and low HDL cholesterol is referred to as metabolic syndrome. Individuals with this syndrome have an increased risk of developing cardiovascular disease (CVD). The World Health Organisation and the National Cholesterol Education Programme’s Adult Treatment Panel III (NCEP-ATP III) have outlined specific diagnostic criteria for the diagnosis of the metabolic syndrome to help in the Identification of this syndrome in clinical practice. While the WHO criteria were specifically developed for use in research, the NCEP criteria are useful in clinical diagnosis of the metabolic syndrome. The metabolic syndrome is amenable to lifestyle modifications such as increased physical activity, weight loss, and possibly intake of low-glycemic foods. Drug therapy may be used to treat individual components of the syndrome such as elevated blood pressure and dyslipidemia. To control elevated glucose levels (when there is failure of lifestyle modification), medications such as metformin, thiazolidinedione derivatives and alpha glucosidase inhibitors may be used.

Factor analysis of metabolic syndrome components and predicting type 2 diabetes: Results of 10-year follow-up in a Middle Eastern population

BACKGROUND

The relationship among components of metabolic syndrome (MetS) and their association with diabetes is unclear in West Asia. The aim of the present study was to conduct factor analysis of MetS components and the effect these factors have on the incidence of type 2 diabetes (T2D) in a population-based cohort study of the Tehran Lipid and Glucose Study (TLGS).

METHODS

The present study enrolled 1861 men and 2706 women (20-60 years of age), from Tehran (Iran) who were free of diabetes at baseline and followed them for 10 years. A principal component analysis was performed to extract standardized factors from MetS components. Logistic regression was used to detect associations between the extracted factors and the incidence of diabetes. A propensity score was used to correct differential selection bias resulting from loss to follow-up.

RESULTS

Factor analysis identified three factors (blood pressure, lipids and glycemia). Waist circumference was shared in three all factors. Blood pressure, lipids and glycemia were related to the incidence of diabetes with odds ratios (95% confidence intervals) of 2.23 (1.31-3.78), 1.89 (1.27-3.67), and 7.54 (4.09-13.91), respectively, in men and 2.13 (1.34-3.40), 2.06 (1.35-3.15), and 13.91 (7.29-26.51), respectively, in women for the third versus the first tertile of these standardized factors.

CONCLUSIONS

Central adiposity may have a pivotal role in MetS linking other risk factors together. Glycemia had a high impact on the incidence of diabetes, whereas blood pressure and lipid had a similar moderate effect on the incidence of diabetes.

Pathophysiological domains underlying the metabolic syndrome: an alternative factor analytic strategy

PURPOSE

Factor analysis (FA) has become part and parcel in metabolic syndrome (MBS) research. Both exploration- and confirmation-driven factor analyzes are rampant. However, factor analytic results on MBS differ widely. A situation that is at least in part attributable to misapplication of FA. Here, our purpose was (i) to review factor analytic efforts in the study of MBS with emphasis on misusage of the FA model and (ii) to propose an alternative factor analytic strategy.

METHODS

The proposed factor analytic strategy consists of four steps and confronts weaknesses in application of the FA model. At its heart lies the explicit separation of dimensionality and pattern selection and the direct evaluation of competing inequality-constrained loading patterns. A high-profile MBS data set with anthropometric measurements on overweight children and adolescents is reanalyzed using this strategy.

RESULTS

The reanalysis implied a more parsimonious constellation of pathophysiological domains underlying phenotypic expressions of MBS than the original analysis (and many other analyses). The results emphasize correlated factors of impaired glucose metabolism and impaired lipid metabolism.

CONCLUSIONS

Pathophysiological domains underlying phenotypic expressions of MBS included in the analysis are driven by multiple interrelated metabolic impairments. These findings indirectly point to the possible existence of a multifactorial etiology.

Biomarker patterns of inflammatory and metabolic pathways are associated with risk of colorectal cancer: results from the European Prospective Investigation into Cancer and Nutrition (EPIC)

A number of biomarkers of inflammatory and metabolic pathways are individually related to higher risk of colorectal cancer (CRC); however, the association between biomarker patterns and CRC incidence has not been previously evaluated. Our study investigates the association of biomarker patterns with CRC in a prospective nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC). During median follow-up time of 7.0 (3.7-9.4) years, 1,260 incident CRC cases occurred and were matched to 1,260 controls using risk-set sampling. Pre-diagnostic measurements of C-peptide, glycated hemoglobin, triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), C-reactive protein (CRP), reactive oxygen metabolites (ROM), insulin-like growth factor 1, adiponectin, leptin and soluble leptin receptor (sOB-R) were used to derive biomarker patterns from principal component analysis (PCA). The relation with CRC incidence was assessed using conditional logistic regression models. We identified four biomarker patterns 'HDL-C/Adiponectin fractions', 'ROM/CRP', 'TG/C-peptide' and 'leptin/sOB-R' to explain 60 % of the overall biomarker variance. In multivariable-adjusted logistic regression, the 'HDL-C/Adiponectin fractions', 'ROM/CRP' and 'leptin/sOB-R' patterns were associated with CRC risk [for the highest quartile vs the lowest, incidence rate ratio (IRR) = 0.69, 95 % CI 0.51-0.93, P-trend = 0.01; IRR = 1.70, 95 % CI 1.30-2.23, P-trend = 0.002; and IRR = 0.79, 95 % CI 0.58-1.07; P-trend = 0.05, respectively]. In contrast, the 'TG/C-peptide' pattern was not associated with CRC risk (IRR = 0.75, 95 % CI 0.56-1.00, P-trend = 0.24). After cases within the first 2 follow-up years were excluded, the 'ROM/CRP' pattern was no longer associated with CRC risk, suggesting potential influence of preclinical disease on these associations. By application of PCA, the study identified 'HDL-C/Adiponectin fractions', 'ROM/CRP' and 'leptin/sOB-R' as biomarker patterns representing potentially important pathways for CRC development.

Gender differences in the association between metabolic syndrome and periodontal disease: the Hisayama Study

Aims: Periodontal disease and metabolic syndrome (MS) are more prevalent in males than in females. However, whether there is a gender difference in the association between these health conditions has not yet been investigated. This study examined the gender difference in this association, considering the definition of periodontal disease.

Materials and Methods: We recruited 1040 males and 1330 females, aged ≥40 years, with at least ten teeth from subjects of the 2007 Hisayama health examination. We performed a logistic regression analysis with various definitions of periodontal disease the dependent variable and MS as the independent variable. Following the analysis, the data were reanalysed with the structural equations model.

Results: The logistic regression analysis suggested a stronger association between periodontal disease and MS in females than that in males when periodontal disease was more severely defined. When we constructed the structural equations model in each gender, the model showed a good fit to the data of females, suggesting the association between periodontal disease and MS in females, but not in males.

Conclusions: Gender differences seem to exist in the association between periodontal disease and MS; MS might show a stronger association with periodontal disease in females than in males.

Furuta M, Shimazaki Y, Takeshita T, Shibata Y, Akifusa S, Eshima N, Kiyohara Y, Ninomiya T, Hirakawa Y, Mukai N, Nagata M, Yamashita Y. Gender differences in the association between metabolic syndrome and periodontal disease: the Hisayama Study. J Clin Periodontol 2013; 40: 743–752. doi: 10.1111/jcpe.12119.

Risk is not flat. Comprehensive approach to multidimensional risk management in ST-elevation myocardial infarction treated with primary angioplasty (ANIN STEMI Registry)

Introduction

Current risk assessment concepts in ST-elevation myocardial infarction (STEMI) are suboptimal for guiding clinical management.

Aim

To elaborate a composite risk management concept for STEMI, enhancing clinical decision making.

Material and methods

1995 unselected, registry patients with STEMI treated with primary percutaneous coronary intervention (pPCI) (mean age 60.1 years, 72.1% men) were included in the study. The independent risk markers were grouped by means of factor analysis, and the appropriate hazards were identified.

Results

In-hospital death was the primary outcome, observed in 95 (4.7%) patients. Independent predictors of mortality included age, leukocytosis, hyperglycemia, tachycardia, low blood pressure, impaired renal function, Killip > 1, anemia, and history of coronary disease. The factor analysis identified two significant clusters of risk markers: 1. age-anemia- impaired renal function, interpreted as the patient-related hazard; and 2. tachycardia-Killip > 1-hyperglycemia-leukocytosis, interpreted as the event-related (hemodynamic) hazard. The hazard levels (from low to high) were defined based on the number of respective risk markers. Patient-related hazard determined outcomes most significantly within the low hemodynamic hazard group.

Conclusions

The dissection of the global risk into the combination of patient- and event-related (hemodynamic) hazards allows comprehensive assessment and management of several, often contradictory sources of risk in STEMI. The cohort of high-risk STEMI patients despite hemodynamically trivial infarction face the most suboptimal outcomes under the current invasive management strategy.

The factor structure of the metabolic syndrome in obese individuals with binge eating disorder

OBJECTIVE

Metabolic syndrome (MetS) is strongly linked with cardiovascular disease and type-II diabetes, but there has been debate over which metabolic measures constitute MetS. Obese individuals with binge eating disorder (BED) are one of the high risk populations for developing MetS due to their excess weight and maladaptive eating patterns, yet, the clustering patterns of metabolic measures have not been examined in this patient group.

METHODS

347 adults (71.8% women) were recruited for treatment studies for obese individuals with BED. We used the VARCLUS procedure in the Statistical Analysis System (SAS) to investigate the clustering pattern of metabolic risk measures.

RESULTS

The analysis yielded four factors: obesity (body-mass-index [BMI] and waist circumference), lipids (HDL and triglycerides), blood pressure (systolic and diastolic blood pressure), and glucose regulation (fasting serum glucose and Hb1Ac). The four factors accounted for 84% of the total variances, and variances explained by each factor were not substantially different. There was no inter-correlation between the four factors. Subgroup analyses by sex and by race (Caucasian vs. African American) yielded the same four-factor structure.

CONCLUSION

The factor structure of MetS in obese individuals with BED is not different from those found in normative population studies. This factor structure may be applicable to the diverse population.

Identification of cardiovascular risk components in urban Chinese with metabolic syndrome and application to coronary heart disease prediction: a longitudinal study

Background

Metabolic syndrome (MetS) is proposed as a predictor for cardiovascular disease (CVD). It involves the mechanisms of insulin resistance, obesity, inflammation process of atherosclerosis, and their complex relationship in the metabolic network. Therefore, more cardiovascular risk-related biomarkers within this network should be considered as components of MetS in order to improve the prediction of CVD.

Methods

Factor analysis was performed in 5311 (4574 males and 737 females) Han Chinese subjects with MetS to extract CVD-related factors with specific clinical significance from 16 biomarkers tested in routine health check-up. Logistic regression model, based on an extreme case-control design with 445 coronary heart disease (CHD) patients and 890 controls, was performed to evaluate the extracted factors used to identify CHD. Then, Cox model, based on a cohort design with 1923 subjects followed up for 5 years, was conducted to validate their predictive effects. Finally, a synthetic predictor (SP) was created by weighting each factor with their risks for CHD to develop a risk matrix to predicting CHD.

Results

Eight factors were obtained from both males and females with a similar pattern. The AUC to classify CHD under the extreme case-control suggested that SP might serve as a useful tool in identifying CHD with 0.994 (95%CI 0.984-0.998) for males and 0.998 (95%CI 0.982-1.000) for females respectively. In the cohort study, the AUC to predict CHD was 0.871 (95%CI 0.851-0.889) for males and 0.899 (95%CI 0.873-0.921) for females, highlighting that SP was a powerful predictor for CHD. The SP-based 5-year CHD risk matrix provided as convenient tool for CHD risk appraisal.

Conclusions

Eight factors were extracted from sixteen biomarkers in subjects with MetS and the SP adds to new insights into studies of prediction of CHD risk using data from routine health check-up.

Insulin resistance is not necessarily an essential element of metabolic syndrome

Type 2 diabetes is frequently associated with metabolic syndrome (MetS). Insulin resistance (IR) is thought to be the underlying pathophysiology of MetS. The purpose of this study is to examine the association of MetS with IR and beta cell function. This is a cross-sectional study in NHANES 1999-2000 participants who were at least 18 years old, including 911 non-Hispanic whites (NHW), 398 non-Hispanic blacks (NHB), and 595 Mexican-Americans (MA). MetS was defined based on the revised ATP III. IR and beta cell function were calculated using homeostasis model assessment (HOMA-IR and HOMA-B). The high-risk tertile was defined as the highest HOMA-IR and lowest HOMA-B. The odds ratio (OR) was calculated against the other two tertiles. The relationship of HOAM-IR and HOMA-B with the components of MetS was also examined. IR was a risk factor of MetS in all three ethnic groups (OR 4.17-12.01, P < 0.0001). Fasting glucose, triglycerides, and HDL cholesterol were associated with IR (P < 0.001) and correlated with HOMA-IR (P < 0.001), while inconsistent results were noted in blood pressure and waist circumference among three racial/ethnic groups. However, in the MetS subjects, 32 % of NHW, 28 % of NHB, and 44 % of MA were not in the IR tertile and in the IR subjects, 25 % of NHW, 36 % NHB, and 30 % of MA did not have MetS. No relationship was found between beta cell function and MetS. Although IR is a risk factor for MetS, IR is neither necessary nor required for MetS.

The structure of metabolic syndrome components across follow-up survey from childhood to adolescence

BACKGROUND

The choice of what parameters are needed for the diagnosis of Metabolic syndrome (MetS) has been criticized due to the lack of an actual "gold standard" diagnostic test even in adults. This problem seems to be greater in children and adolescents.

OBJECTIVES

Stability assessment of factor structure underlying metabolic syndrome (MetS) components from childhood to adolescence in a panel study.

PATIENTS AND METHODS

A total number of 643 (305 boys and 338 girls) children (from 1999 to 2001), aged 6-10 years, with a complete median follow-up of 6.7 years (from 2006 to 2008) were selected among participants of Tehran Lipid and Glucose Study. We proposed 6 measured variables based on risk factors defined in Adult Treatment Panel III guidelines to describe clustering of MetS components.

RESULTS

The Goodness of fit of the two-factor model, extracted from exploratory factor analysis, was appropriate for boys and girls in both stages of the study using confirmatory factor analysis. Systolic blood pressure (SBP) and triglycerides (TGs), with parameter estimates (PE) of 1 and 0.75, respectively, were the greatest risk factors at baseline in boys and girls. Waist circumference with PE of 0.88 and 0.62, and SBP with PE of 0.99 and 0.86 in adolescent boys and girls, respectively, were important risk factors.

CONCLUSIONS

Our panel study supports the stability of the two-factor six-variable model across two developmental stages from childhood to adolescence, among which adiposity, SBP, and TG were the predominant risk factors.

Factor structure underlying components of allostatic load

Allostatic load is a commonly used metric of health risk based on the hypothesis that recurrent exposure to environmental demands (e.g., stress) engenders a progressive dysregulation of multiple physiological systems. Prominent indicators of response to environmental challenges, such as stress-related hormones, sympatho-vagal balance, or inflammatory cytokines, comprise primary allostatic mediators. Secondary mediators reflect ensuing biological alterations that accumulate over time and confer risk for clinical disease but overlap substantially with a second metric of health risk, the metabolic syndrome. Whether allostatic load mediators covary and thus warrant treatment as a unitary construct remains to be established and, in particular, the relation of allostatic load parameters to the metabolic syndrome requires elucidation. Here, we employ confirmatory factor analysis to test: 1) whether a single common factor underlies variation in physiological systems associated with allostatic load; and 2) whether allostatic load parameters continue to load on a single common factor if a second factor representing the metabolic syndrome is also modeled. Participants were 645 adults from Allegheny County, PA (30–54 years old, 82% non-Hispanic white, 52% female) who were free of confounding medications. Model fitting supported a single, second-order factor underlying variance in the allostatic load components available in this study (metabolic, inflammatory and vagal measures). Further, this common factor reflecting covariation among allostatic load components persisted when a latent factor representing metabolic syndrome facets was conjointly modeled. Overall, this study provides novel evidence that the modeled allostatic load components do share common variance as hypothesized. Moreover, the common variance suggests the existence of statistical coherence above and beyond that attributable to the metabolic syndrome.

Ambulatory blood pressure and the metabolic syndrome in normotensive and untreated hypertensive men

BACKGROUND

Components of the metabolic syndrome are typically intercorrelated in epidemiologic studies and, when combined, predict type 2 diabetes and cardiovascular diseases. However, it remains unclear whether a single construct underlies the various components and which of the components are most closely associated with the underlying syndrome. Here, we use our confirmatory factor analytic model of the metabolic syndrome to examine the extent to which measures of ambulatory blood pressure, reflecting blood pressure variability throughout the day and night, may strengthen the association between blood pressure and the other components of the syndrome.

METHODS

Participants were a community sample of 358 men (248 with hypertension), ages 40-70, not receiving antihypertensive medications. Confirmatory factor analysis was employed to examine model fit and the strength of association between clinic and ambulatory blood pressure and the metabolic syndrome.

RESULTS

The blood pressure factor loaded significantly on the underlying metabolic syndrome but the strength of association was not as great (loading = 0.34, p < 0.01) as those observed for the obesity, insulin resistance and lipid factors. The factor loadings for the ambulatory measures (awake loading = 0.19; sleep loading = 0.16, p values < 0.01) were significant but smaller in magnitude than the loadings for clinic blood pressure.

CONCLUSIONS

Both clinic and ambulatory measures of blood pressure are significantly associated with the underlying metabolic syndrome using confirmatory factor analytic methods. However, the strength of association appears greater for the clinic measures relative to the ambulatory measures in this study.

Validating metabolic syndrome through principal component analysis in a medically diverse, realistic cohort

BACKGROUND

The concept of metabolic syndrome has been subject to etiological and clinical controversies in recent years. Associations among the five risk factors (obesity, hypertension, hyperglycemia, high triglyceride levels, and low high-density lipoprotein cholesterol) may help establish the validity of the concept, especially in a cohort representative of an actual population.

METHODS

We used principal component analysis (PCA) to analyze the structure of the physiological components of metabolic syndrome in 7213 patients contained in an administrative database for the Centre Hospitalier Universitaire de Sherbrooke in Sherbrooke, Quebec, a realistic cohort with diverse medical histories. We validated the results by repeating the analysis on stratified and random subgroups of patients, and on different combinations of risk factors. The first axis of the PCA was used to predict coronary heart disease (CHD) and diabetes.

RESULTS

The two first axes explained 53% of the variance. The first axis (33%) was associated in the expected direction with all five predictor variables, consistent with its interpretation as metabolic syndrome. The first axis was more predictive of subsequent CHD and diabetes than the formal definition of metabolic syndrome.

CONCLUSIONS

These results suggest that the concept of metabolic syndrome accurately captures an existing underlying physiological process. A continuous indicator could be constructed to identify metabolic syndrome more accurately, thus improving risk assessment for CHD and diabetes mellitus. Metabolic syndrome can be measured well even without all five predictors. However, discrepancies with other studies suggest that our results may not be generalizable, perhaps because our cohort tends to be sicker.

Linkage Analysis of Factors Underlying Insulin Resistance: Strong Heart Family Study

In previous work in non-diabetic participants of the Strong Heart Family Study, we identified three heritable principal components of nine insulin resistance (IR) phenotypes: 1) a glucose/insulin/obesity factor, 2) a blood pressure factor, and 3) a dyslipidemia factor. To localize quantitative trait loci (QTL) potentially influencing these factors, we conducted a genome scan of factor scores in Strong Heart Family Study participants. Approximately 599 men and women, >or=18 years of age, in 32 extended families at three centers (in Arizona, Oklahoma, and North and South Dakota), were examined between 1997 and 1999. We used variance components linkage analysis to identify QTLs for the IR factors. With age, sex, and study center as covariates, we detected linkage of the glucose/insulin/obesity factor to chromosome 4 (robust logarithm of the odds (LOD) = 2.2), the dyslipidemia factor to chromosome 12 (robust LOD = 2.7), and the blood pressure factor to chromosome 1 (robust LOD = 1.6). The peak linkage signals identified for these IR factors support several positive findings from other studies and occur in regions harboring interesting candidate genes. The corroboration of existing QTLs will bring us closer to the identification of the functional genes that predispose to IR.

Lipoprotein Candidate Genes for Multivariate Factors of the Insulin Resistance Syndrome: A Sib-pair Linkage Analysis in Women Twins

The insulin resistance syndrome (IRS) is characterized by a combination of interrelated coronary heart disease risk factors, including low high-density lipoprotein cholesterol (HDLC) levels, obesity and increases in triglyceride (TG), systolic and diastolic blood pressure (BP), small low-density lipoprotein particles (LDL-size), and fasting and postload plasma insulin and glucose. Using factor analysis, we previously identified multivariate factors based on data from women participating in the Kaiser Permanente Women Twins Study: 1) Weight/Fat, 2) Insulin/Glucose, 3) Lipids, and 4) BP. The purpose of this study is to evaluate evidence for genetic linkage between the multivariate factors and candidate genes. Quantitative sib-pair analysis based on the factor scores with markers for 9 candidate genes was carried out based on data from 126 pairs of dizygotic (DZ) women twins from the second exam of the Kaiser Permanente Women Twins study. Suggestive evidence for linkage was found for the Weight/fat factor and the Apo E gene (p= 0.01), and stronger evidence for linkage with the Lipid factor and the cholesterol ester transfer protein (p= 0.002) gene. Therefore, the CETP gene appears to influence covariation in LDL size, TG, and HDL, and may account for a portion of the well-established statistical and metabolic associations observed between these risk factors.

Twins of Mistaken Zygosity (TOMZ): Evidence for Genetic Contributions to Dietary Patterns and Physiologic Traits

Twin designs, comparing correlations in monozygotic (MZ) versus dizygotic (DZ) twins, have an extensive history. One major confounder in such studies is that MZ twins may share postnatal environmental influences more so than do DZ twins. To avoid such confounding, twins separated at or soon after birth have been studied, but their scarcity often makes this approach impractical. Another method has been to measure the degree of contact twins have maintained over time, and adjust the observed correlations. Here, we remove confounding by utilizing the discrepancy between biological and self-perceived zygosity to separate environmental from genetic sources of twin similarity. We analyzed dietary patterns and physiologic traits in 350 female twin pairs of the 1988 Kaiser Permanente Twin Registry. Among twin pairs, 175 were MZ by self-report and genetic testing (MZC), 136 were DZ by self-report and genetic testing (DZC), 30 were MZ by genetic testing but not by self-report (MZW), and 9 were DZ by genetic testing but not by self-report (DZW) but were excluded due to small sample size. For healthy food patterns, MZC and MZW intraclass correlations were similar and greater than for DZC, yielding positive and significant heritability estimates. For unhealthy food patterns, the MZC, MZW and DZC correlations were similar with no significant heritability. For physiologic traits, MZC and MZW correlations were similar and higher than those for DZC, indicating significant heritability, except for insulin for which MZW and DZC were similar and which showed modest heritability. Twins of mistaken zygosity (TOMZ) provides a useful approach to robust determination of heritability.

Systems genetics of the nuclear factor-κB signal transduction network. I. Detection of several quantitative trait loci potentially relevant to aging

A theory of aging holds that senescence is caused by a dysregulated nuclear factor kappa B (NF-κB) signal transduction network (STN). We adopted a systems genetics approach in our study of the NF-κB STN. Ingenuity Pathways Analysis (IPA) was used to identify gene/gene product interactions between NF-κB and the genes in our transcriptional profiling array. Principal components factor analysis (PCFA) was performed on a sub-network of 19 genes, including two initiators of the toll-like receptor (TLR) pathway, myeloid differentiation primary response gene (88) (MyD88) and TIR (Toll/interleukin-1 receptor)-domain-containing adapter-inducing interferon-β (TRIF). TLR pathways are either MyD88-dependent or TRIF-dependent. Therefore, we also performed PCFA on a subset excluding the MyD88 transcript, and on another subset excluding two TRIF transcripts. Using linkage analysis we found that each set gave rise to at least one factor with a logarithm of the odds (LOD) score greater than 3, two on chromosome 15 at 15q12 and 15q22.2, and another two on chromosome 17 at 17p13.3 and 17q25.3. We also found several suggestive signals (2<LOD score<3) at 1q32.1, 1q41, 2q34, 3q23, and 7p15.3. We are currently examining potential associations with single nucleotide polymorphisms within the 1-LOD intervals of our linkage signals.

Genome-wide linkage scan for factors of metabolic syndrome in a Chinese population

BACKGROUND

Shared genetic factors may contribute to the phenotypic clustering of different components of the metabolic syndrome (MES). This study aims to identify genetic loci that contribute to individual or multiple factors related to MES.

RESULTS

We studied 478 normoglycemic subjects ascertained through 163 families participating in the Hong Kong Family Diabetes Study. Factor analysis on 15 MES-related traits yielded 6 factors including adiposity factor (body mass index, waist and hip circumferences), insulin factor (fasting insulin and insulin AUC during OGTT), glucose factor (fasting glucose and glucose AUC during OGTT), TC-LDLC factor (total cholesterol and LDL-cholesterol), blood pressure factor (systolic and diastolic blood pressure) and TG-HDLC factor (triglycerides and HDL-cholesterol). Genome-wide linkage analyses were performed on these factors using variance component approach. Suggestive evidence for linkage (LOD = 1.24 - 2.46) were observed for adiposity factor (chromosome 1 at 187 cM, chromosome 9 at 34 cM and chromosome 17 at 10 cM), insulin factor (chromosome 2 at 128 cM, chromosome 5 at 21 cM and chromosome 12 at 7 cM), glucose factor (chromosome 7 at 155 cM), TC-LDLC factor (chromosome 7 at 151 cM and chromosome 13 at 15 cM) and TG-HDLC factor (chromosome 7 at 155 cM).

CONCLUSIONS

In summary, our findings suggest the presence of susceptibility loci that influence either single (chromosomes 1, 2, 5, 9, 12, 13 and 17) or multiple factors (chromosome 7) for MES in Hong Kong Chinese without diabetes.

Factor analysis of metabolic syndrome components in severely obese girls and boys

AIMS AND METHODS

Factor analysis is a multivariate correlation technique frequently employed to characterise the aggregation of abnormalities underlying the metabolic syndrome (MS), but scarcely used in obese adolescents. Aim of the study was to investigate the clustering of anthropometric and metabolic variables related to the MS in 487 obese pubertal adolescents (140 boys, 347 girls) in the range of age 11-18 yr employing the factor analysis with exploratory approach.

RESULTS

Principal component analysis reduced 11 correlated physiological variables to 4 uncorrelated factors that explained 68.7% of the variance in the original parameters in boys, and 68.4% in girls. In boys, these factors were: obesity/ hypertension, insulin resistance, dyslipidemia, and hyperglycemia, with elements related to obesity and fat distribution loaded also in dyslipidemia and insulin resistance. In girls no commonalities were detected, but elements of dyslipidemia and insulin resistance were loaded in a single factor, whereas elements of obesity and hypertension were loaded in separate factors.

CONCLUSIONS

The identification of 4 independent factors suggests a multiple physiological origin of the MS also in youngsters. The measures of adiposity were correlated with development of hypertension, insulin resistance, and dyslipidemic phenomena in boys only, whereas in girls anthropometric measures were not correlated with any tested component of the MS, possibly disclosing the protective effect of female sex hormones in the juvenile age span.

Uma exploração multidimensional dos componentes da síndrome metabólica

O objetivo deste estudo foi verificar os padrões de agrupamento das variáveis antropométricas e metabólicas relacionadas com a síndrome metabólica, de acordo com o sexo. Foram coletados dados de 579 moradores de duas comunidades rurais brasileiras, com idades entre 18 e 94 anos. A análise fatorial foi realizada utilizando-se o método de extração de componentes principais e rotação ortogonal varimax. Este estudo reduziu um grupo complexo de fatores de risco cardiovascular que caracterizam a síndrome metabólica em três fatores independentes, cada um refletindo um aspecto diferente da síndrome metabólica. Em ambos os sexos, o fator 1 esteve relacionado à obesidade e dislipidemia, o fator 2 à obesidade e pressão arterial e o fator 3 à obesidade e resistência à insulina. As variâncias totais explicadas para os sexos masculino e feminino foram, respectivamente, 66,61% e 68,98%. Esses achados corroboram com a hipótese de que pelo menos três processos fisiopatológicos atuam no agrupamento dos fatores de risco cardiovasculares na população rural estudada.

Sociodemographic risk factors associated with metabolic syndrome in a Mediterranean population

OBJECTIVE

To investigate the sociodemographic risk factors associated with metabolic syndrome (MetS) in the Mediterranean population of Catalonia, Spain.

DESIGN AND SETTING

Data from the cross-sectional, population-based 2002-2003 Health Survey of Catalonia were analysed. The survey used a structured questionnaire to collect information on demographics, lifestyle and medical history. In a sub-sample of the original survey population anthropometrics and blood pressure were measured and blood samples were taken to determine HDL cholesterol, TAG and fasting glucose.

SUBJECTS

The analysis included the 1,104 individuals aged 18-74 years from this sub-sample who had complete information on all variables necessary to define MetS using the National Cholesterol Education Program's Adult Treatment Panel III (ATP III) and the International Diabetes Federation (IDF) criteria.

RESULTS

MetS prevalence was 28.5 % and 24.8 % according to IDF and ATP III criteria, respectively. MetS was significantly (P = 0.05) more common in males than females. MetS prevalence increased significantly (P<0.001) with age and degree of adiposity and as social class decreased. In general, MetS prevalence decreased as physical activity increased, which was significant (P = 0.0253) when applying ATP III criteria. After taking into account important confounders, MetS prevalence was significantly positively associated with male gender, age, BMI, physical inactivity and lower social class. Smoking status, marital status and working situation were not independently associated with MetS.

CONCLUSIONS

Age, sex, degree of adiposity, physical activity and social class are the sociodemographic risk factors independently associated with MetS in this Mediterranean population. Understanding which factors predict MetS is important considering likely increasing MetS trends, and is useful for determining public health strategies.

Genome-wide linkage scan for the metabolic syndrome: the GENNID study

In the United States, the metabolic syndrome (MetS) constitutes a major public health problem with over 47 million persons meeting clinical criteria for MetS. Numerous studies have suggested genetic susceptibility to MetS. The goals of this study were (i) to identify susceptibility loci for MetS in well-characterized families with type 2 diabetes (T2D) in four ethnic groups and (ii) to determine whether evidence for linkage varies across the four groups. The GENNID study (Genetics of NIDDM) is a multicenter study established by the American Diabetes Association in 1993 and comprises a comprehensive, well-characterized resource of T2D families from four ethnic groups (whites, Mexican Americans, African Americans, and Japanese Americans). Principal component factor analysis (PCFA) was used to define quantitative phenotypes of the MetS. Variance components linkage analysis was conducted using microsatellite markers from a 10-cM genome-wide linkage scan, separately in each of the four ethnic groups. Three quantitative MetS factors were identified by PCFA and used as phenotypes for MetS: (i) a weight/waist factor, (ii) a blood pressure factor, and (iii) a lipid factor. Evidence for linkage to each of these factors was observed. For each ethnic group, our results suggest that several regions harbor susceptibility genes for the MetS. The strongest evidence for linkage for MetS phenotypes was observed on chromosome 2 (2q12.1-2q13) in the white sample and on chromosome 3 (3q26.1-3q29) in the Mexican-American sample. In conclusion, the results suggest that several regions harbor MetS susceptibility genes and that heterogeneity may exist across groups.

Factor analysis of metabolic syndrome components in obese women

BACKGROUND AND AIM

Factor analysis is a multivariate correlation technique that is frequently employed to characterise the clustering of intercorrelated abnormalities, which underlie the metabolic syndrome in cohorts of individuals with different characteristics. To our knowledge, it has never been used to identify the components of this syndrome in obese subjects. The purpose of this study was to use factor analysis to investigate the clustering of features, which characterise the metabolic syndrome, in a cohort of 552 obese women aged 18-83 years (mean body mass index: 43.0 kg/m(2)+/-5.7 SD).

METHODS AND RESULTS

Principal component analysis reduced ten correlated physiological variables, to four uncorrelated factors that explained 72.2% of the variance in the original parameters. These factors were interpreted as: (1) an insulin resistance factor, with positive loading of fasting serum insulin and homeostatic model assessment of insulin resistance; (2) a metabolic glucose/lipid factor, with positive loading of fasting plasma glucose, triglycerides, waist-to-hip ratio, and inverse loading of high density lipoprotein cholesterol; (3) a body mass factor, with positive loading of body mass and waist circumference; and (4) a blood pressure factor, with positive loading of systolic and diastolic blood pressure.

CONCLUSION

The identification of four independent factors is consistent with previous findings among samples of different populations and may also support, in obese women, the hypothesis that multiple physiological determinants are responsible for the abnormalities underlying the metabolic syndrome. Nonetheless, findings in this cohort of obese women suggest that the absolute degree of adiposity is not correlated with any tested component of the metabolic syndrome, but that the relative fat distribution is highly correlated with the development of hyperglycaemic and dyslipidaemic phenomena. Furthermore, insulin resistance appears to be a major factor in obese individuals, independent of other metabolic and anthropometic abnormalities.

Severity of metabolic syndrome unfavorably influences oxidative stress and fatty acid metabolism in men

Metabolic syndrome (MS) is defined by the clustering of several components (MSC), which include abdominal fat accumulation, impaired glucose homeostasis, hypertriglyceridemia, lowered high-density lipoprotein cholesterol, increased blood pressure, and hyperuricemia. Metabolic syndrome is also accompanied by increased oxidative stress and inflammation as well as by altered composition of esterified fatty acids (FA). Therefore, we have investigated 210 men (categorized into six groups with increasing number of MSC) to find trends in the extent of oxidative stress, FA pattern and frequency of pathological alleles of the selected candidate genes for lipid metabolism. Increasing number of MSC was connected with the raised serum glucose and insulin, increased concentrations of conjugated dienes in low-density lipoprotein (all p < 0.0001), and high frequency of e2 and e4 alleles of the apolipoprotein E gene (p < 0.005). However, the last significance was lost after the adjustment for age. The incidence of 54Thr allele for intestinal isoform of the fatty acid-binding protein (FABP-2) gene was comparable in all groups. The most important findings were the raised content of saturated FA and the increased activities of Delta9 and Delta6 desaturases (all p < 0.0001), and the decreased content of polyunsaturated FA n-6 family and the decreased activity of Delta5 desaturase (both p < 0.001) in connection with increasing number of MSC. In conclusion, the severity of MS is connected with the progression of oxidative stress and the unfavorable changes in the FA composition. These changes are independent of the studied gene polymorphisms.

Evidence for distinct effects of GH and IGF-I in the metabolic syndrome

AIMS

The metabolic syndrome is a cluster of cardiovascular risk factors which include central obesity, dyslipidaemia, glucose intolerance and hypertension. These risk factors are common in patients with growth hormone (GH) deficiency, suggesting a role for the somatotropic axis in the development of metabolic syndrome.

METHODS

We used factor analysis to investigate the relationships linking serum levels of GH and insulin-like growth factor I (IGF-I) to metabolic syndrome variables (high-density lipoprotein cholesterol, triglycerides, fasting glucose, blood pressure and waist circumference). We studied 359 men and 388 women from the Data from an Epidemiological Study on the Insulin Resistance syndrome (DESIR). Their age range was 30-64 years.

RESULTS

Three independent latent factors explained 61% of the total variance in women and four factors explained 73% in men. In both men and women, IGF-I showed a strong positive correlation with the lipid factor and a negative correlation with the obesity/glucose factor. In women, GH showed a strong negative correlation with the obesity/glucose factor but not the lipid factor. In men, GH was unrelated to the lipid and obesity/glucose factors. The blood pressure factor was not related to GH or IGF-I. In contrast with IGF-I, GH was significantly lower in women with metabolic syndrome (1575 +/- 449 pg/ml) than in the other women (2121 +/- 520 pg/ml, P = 0.002). No significant difference was observed in men for GH or IGF-I.

CONCLUSION

Our results support a link between the somatotropic axis and several features of the metabolic syndrome, and suggest distinct effects of GH and IGF-I on these parameters.

In addition to obesity and insulin resistance, microalbuminuria and diminished insulin secretion are linked with the metabolic syndrome in community-dwelling nondiabetic Taiwanese subjects

Although insulin resistance and obesity are currently considered primary factors underlying development of the metabolic syndrome, microalbuminuria and inadequate insulin secretion may also be involved. The present study is the first to examine intercorrelations among these factors in a community-based Taiwanese population. An epidemiological survey of chronic diseases conducted in 1996 was utilized to evaluate 1340 community-dwelling, nondiabetic adults. Principal component factor analyses involving varimax orthogonal rotation of transformed continuously distributed variables were performed. Sex-specific factor analyses yielded four separate factors in women (obesity/insulin resistance, lipid, blood pressure and insulin resistance/secretion factors) and three in men (obesity/insulin resistance/secretion, lipid and blood pressure factors). For men the corrected insulin response clustered with obesity, and insulin resistance loaded on the same factor, explaining 31% of variance; however, microalbuminuria was closely linked with blood pressure variables, and the corrected insulin response loaded on the same factor, explaining 13.2% of variance. Obesity and insulin resistance were confirmed as central anomalies of all features of the metabolic syndrome. The observed linkage of impaired beta-cell function and microalbuminuria with the metabolic syndrome should facilitate prediction of the onset of cardio-vasculo-metabolic disorders. Inadequate beta-cell function and microalbuminuria are plausible components of the metabolic syndrome in Taiwanese subjects.

Impact of clinical characteristics of individual metabolic syndrome on the severity of insulin resistance in Chinese adults

The impact the metabolic syndrome (MetS) components on the severity of insulin resistance (IR) has not been reported. We enrolled 564 subjects with MetS and they were divided into quartiles according to the level of each component; and an insulin suppression test was performed to measure IR. In males, steady state plasma glucose (SSPG) levels in the highest quartiles, corresponding to body mass index (BMI) and fasting plasma glucose (FPG), were higher than the other three quartiles and the highest quartiles, corresponding to the diastolic blood pressure and triglycerides, were higher than in the lowest two quartiles. In females, SSPG levels in the highest quartiles, corresponding to the BMI and triglycerides, were higher than in all other quartiles. No significant differences existed between genders, other than the mean SSPG levels in males were greater in the highest quartile corresponding to BMI than that in the highest quartile corresponding to HDL-cholesterol levels. The factor analysis identified two underlying factors (IR and blood pressure factors) among the MetS variables. The clustering of the SSPG, BMI, triglyceride and HDLcholesterol was noted. Our data suggest that adiposity, higher FPG and triglyceride levels have stronger correlation with IR and subjects with the highest BMI have the highest IR.

Comparative evaluation of anthropometric measures to predict cardiovascular risk factors in Tehranian adult women

Objective

To compare the ability of waist circumference (WC), body mass index (BMI), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR) to predict cardiovascular risk factors in an urban adult population of Tehranian women.

Design

Population-based cross-sectional study.

Setting

Tehran, the capital of Iran.

Subjects

This study was conducted on 5073 women aged 18–74 years, participants of the Tehran Lipid and Glucose Study. Demographic data were collected. Anthropometric indices were measured according to standard protocols. Cut-off points of BMI, WC, WHR and WHtR were considered as 25 kg m−2, 80 cm, 0.8 and 0.5, respectively. Blood pressure was measured and hypertension was defined based on the sixth report of the Joint National Committee on Prevention, Detection, Evaluation and Treatment of High Blood Pressure. Biochemical analyses were conducted on fasting blood samples. Diabetes was defined as fasting plasma glucose ≥126 mg dl−1or 2-hour plasma glucose ≥200 mg dl−1and dyslipidaemia based on the third report of the National Cholesterol Education Program Expert Panel. The presence of ‘at least one risk factor’ from the three major cardiovascular risk factors (hypertension, dyslipidaemia and diabetes) was also evaluated.

Results

Mean (±standard deviation) age of women was 39.9 ± 14.6 years; mean BMI, WC, WHR and WHtR were 27.1 ± 1.5 kg m−2, 86.5 ± 13.5 cm and 0.83 ± 0.08 and 0.55 ± 0.08, respectively. Of the four anthropometric measures, WC had the highest sensitivity and specificity to identify subjects with risk factors in both the 18–39 year and the 40–74 year age categories. WC was seen to have a higher percentage of correct prediction than BMI, WHR and WHtR.

Conclusion

It is concluded that WC is the best screening measure for cardiovascular risk factors, compared with BMI, WHR and WHtR, in Tehranian adult women.

Impaired Glucose Tolerance and Impaired Fasting Glucose Share Similar Underlying Pathophysiologies

Both impaired glucose tolerance (IGT) and impaired fasting glucose (IFG) are pre-diabetic states. IGT was defined as having normal fasting plasma glucose (< 6.1 mmol/l) and abnormal 2-hr post-challenge plasma glucose. IFG was defined as having abnormal fasting plasma and normal 2-hr post-challenge plasma glucose (< 7.8 mmol/l). To explore whether these two abnormalities share similar underlying pathophysiologies, we evaluated risk factors of IGT and IFT using the models of factor analysis. The present study included 107 subjects with IGT and 52 with IFG. An oral glucose tolerance test and insulin suppression test, which could quantify insulin resistance, were performed on separate days. The risk factors include waist-to-hip ratio (WHR), triglycerides, high-density lipoprotein (HDL)-cholesterol, blood pressure, and fasting plasma glucose, which are associated with metabolic syndrome and insulin resistance. Factor analysis is a commonly used statistical method that could reduce a large number of risk factors into smaller numbers of groups, also called dimension. Accordingly, the complicated data could be interpreted more easily, since the related risk factors are grouped in one dimension. The results showed that the risk factors of IGT and IFG have similar grouping patterns. Triglyceride, insulin resistance, and HDL-cholesterol were grouped in one dimension (the lipid dimension), while WHR, mean blood pressure and fasting plasma glucose were grouped in another dimension (the metabolic dimension). In conclusion, except for WHR, the grouping patterns of the components in both IGT and IFG were nearly identical. These results suggest that IGT and IFG may share similar pathophysiologies.

Metabolic syndrome and progression of atherosclerosis among middle-aged US adults

Metabolic syndrome, indicated by insulin resistance/hyperinsulinemia, obesity, central obesity, atherogenic dyslipidemia, and hypertension, contributes to atherosclerotic cardiovascular disease. However, it is controversial whether the indicators of metabolic syndrome are related to subclinical atherosclerosis collectively or individually. Whether there is any gender-based difference in the mechanisms of metabolic syndrome-induced atherosclerosis progression is also unknown. Two models were compared in this study. Model 1 assumes that a latent factor, metabolic syndrome per se, impacts subclinical atherosclerosis (collective effects model); Model 2 assumes the effect of the syndrome is mediated through its indicators (individual effects model). Data were obtained from the Los Angeles Atherosclerosis Study. The cohort consists of 573 adults (age, 40-60 years) who were asymptomatic for cardiovascular disease. Subclinical atherosclerosis was assessed by measuring common carotid artery intima-media thickness (CCA-IMT) using B-mode ultrasound. Three examinations were completed at 1.5-year intervals from 1995-1999. The analyses were performed with SAS 8.2 and AMOS 4.0. The results showed that atherogenic effects of metabolic syndrome were mediated through its indicators; there were gender-based differences in the mechanisms of metabolic syndrome-induced atherosclerosis. Central obesity was significantly associated with the baseline IMT for men only, whereas triglycerides were significantly associated with the progression of IMT for women only. Systolic blood pressure was significantly associated with the baseline and progression for both men and women. However, fasting insulin was not found to be significantly associated with the baseline and progression of IMT in the multivariate model, although it was significantly associated with other components of metabolic syndrome.

A pathophysiological approach to metabolic syndrome using factor analysis in an adult Romanian population

The aim of the study was to examine the role of insulin resistance in etiopathogenesis of metabolic syndrome in an adult Romanian population using exploratory factor analysis. We analyzed 228 non-diabetic subjects randomized in respect to the age and sex distribution of the general population. For each patient, age, sex, body mass index (BMI), systolic and diastolic blood pressure (SBP, DBP), HDL-cholesterol (HDL), plasma triglycerides (TG), fasting plasma glucose (FPG) and fasting insulin were obtained. Factor analysis was performed using principal component analysis, with Varimax rotation of the major determinants of metabolic syndrome. Mean age was 48.9 +/- 12.7 years; 107 (46.9%) were men and 121 (53.1%) women. We found three major factors, which are correlated with metabolic syndrome and may explain its variance. Factor 1 comprises SBP and DBP in men and SBP, DBP and BMI in women. Factor 2 comprises BMI, HDL, TG and FPG in men and BMI, TG and FPG in women. Factor 3 comprises fasting insulin in men and fasting insulin, TG and HDL in women. The finding of more than one factor suggests that insulin resistance is not the only pathophysiological mechanism involved. These factors appear to work independently of each other in men, but they intersect in women, suggesting that the pathophysiology of metabolic syndrome may be different in women compared with men.

Metabolic syndrome and its association with ischemic cerebrovascular disease

Metabolic syndrome (MS) is the term that encompasses metabolic risk factors that may lead to atherosclerotic cardiovascular disease. This study was undertaken to investigate the prevalence of MS in patients with ischemic cerebrovascular disease (CVD), according to National Cholesterol Education Program/Adult Treatment Panel III (ATP III) criteria. A total of 40 patients who were referred to the emergency department and given a diagnosis of CVD were included in this study. Detailed medical histories, physical examination findings, heights, weights, and waist circumferences of patients were recorded. Fasting blood glucose levels and lipid profiles of patients were evaluated. Those with hypertension, diabetes, or hyperlipidemia were regarded as meeting at least 1 of the ATP III criteria. Study results were compared, especially between females and males. In all, 55% of patients were female, and 70% were older than 65 y. Blood pressure over 130/85 mm Hg was assessed in 60% of patients. Among female patients, 81.8% had a waist circumference greater than 88 cm; 50% of male patients had a waist circumference over 102 cm. A fasting blood glucose level above 110 mg/dL was identified in 57.5% of patients. Serum triglyceride levels in 30% of patients were above 150 mg/L. It was noted that 33.3% of male patients had a high-density lipoprotein (HDL) level below 40 mg/L, and in 68.2% of female patients, an HDL level below 50 mg/dL was recorded. According to these findings, 14 of 22 female patients (64%) and 13 of 18 male patients (72%) were identified as having MS. High rates of stroke associated with MS reveal the importance of forthcoming preventive approaches.

Is the factor structure of the metabolic syndrome comparable between men and women and across three ethnic groups: the Miami Community Health Study

PURPOSE

The metabolic syndrome (MS) is conceived as a cluster of disorders that increase risk for coronary heart disease and type 2 diabetes. Studies examining its structure primarily have used an exploratory factor analytic technique, but yielded discrepant results. There also is a lack of research that investigates whether the clustering pattern is similar across sex and ethnic groups. This study uses confirmatory factor analysis to evaluate the factor structure of the MS and examines its similarity between men and women and across three ethnic groups (Caucasian, African, and Cuban Americans).

METHOD

A hierarchical four-factor model with an overarching MS factor uniting insulin resistance, obesity, lipid, and blood pressure factors was tested with 517 individuals from the Miami Community Health Study.

RESULTS

Findings show that the proposed structure was well supported (comparative fit index=0.97) and similar between men and women and across ethnic groups. The MS was represented strongly by insulin resistance, followed by obesity, lipid factors, and, to a lesser extent, a blood pressure factor.

CONCLUSIONS

This study provides empirical support for identifying and diagnosing the MS by its component factors in a diverse population.

Longitudinal analyses among overweight, insulin resistance, and cardiovascular risk factors in children

OBJECTIVE

It has been questioned whether insulin resistance or obesity is the central abnormality contributing to the cardiovascular risk factors dyslipidemia and hypertension in obesity.

RESEARCH METHODS AND PROCEDURES

We studied weight status [SD score (SDS)-BMI], lipids (triglycerides, low-density lipoprotein- and high-density lipoprotein-cholesterol), blood pressure, and insulin resistance index [as homeostasis model assessment (HOMA) model] over a 1-year period in 229 obese white children (median age 12 years).

RESULTS

Any degree of decrease in HOMA was associated with significant decreases in triglycerides (p < 0.001), systolic blood pressure (p < 0.001), and diastolic blood pressure (p < 0.001), whereas the children with different changes in HOMA did not differ significantly in their weight changes. Only the children in the highest quartile of weight reduction (decrease in SDS-BMI > 0.5) demonstrated a significant decrease in systolic blood pressure (p < 0.001), diastolic blood pressure (p < 0.001), and triglycerides (p = 0.012), and an increase in high-density lipoprotein-cholesterol (p = 0.023), whereas with a lower degree of weight loss, there were no significant changes in cardiovascular risk factors. In contrast with a lower degree of weight loss, a reduction of >0.5 SDS-BMI was associated with a significant decrease in HOMA (p < 0.001).

DISCUSSION

Because blood pressure and triglycerides decreased with any degree of decrease in HOMA, independently of changes in weight status, these findings support the hypothesis that insulin resistance is the central abnormality contributing to these cardiovascular risk factors. Therefore, improving insulin resistance seems more important than reducing overweight to prevent or treat hypertension and dyslipidemia in obese children.

Arterial Stiffness in HIV-Infected Patients Receiving Highly Active Antiretroviral Therapy

HIV-infected patients receiving highly active antiretroviral therapy (HAART) are at increased risk of cardiovascular events. Reported non-invasive techniques for assessment of blood pressure in this population have been limited to sphygmomanometry. The present cross-sectional study investigated the impact of antiretroviral therapy and the HAART-associated lipodystrophy on aortic blood pressure conditions and arterial stiffness in HAART-treated lipodystrophic ( n=42) and non-lipodys-trophic ( n=17) patients. Pulse wave analysis, novel to this population, was used to evaluate measures of arterial stiffness, including the heart rate corrected augmentation index, AgIHR. Results indicated no significant difference between the study groups in peripheral or aortic blood pressure and AgIHR. Significant correlates of AgIHR included age ( P=0.003), duration of antiretroviral therapy ( P=0.020), lamivudine therapy ( P=0.015) and ritonavir therapy ( P=0.016) as well as cumulative exposure to protease inhibitors ( P=0.030). Time since HIV diagnosis, severity of immunodeficiency or presence of HAART-associated lipodystrophy bore no relationship to AgIHR. In multivariate analysis, duration of antiretroviral therapy ( P=0.046), cumulative exposure to nucleoside reverse transcriptase inhibitors ( P=0.032) and to protease inhibitors ( P=0.011) were identified as independent factors predicting AgIHR. Prolonged antiretroviral treatment, thus, delineates as a risk factor for systemic arterial stiffness and the associated cardiovascular mortality.

Factor analysis of lifestyle-related factors in 12,525 urban Japanese subjects

This study describes the clustering patterns of several lifestyle-related factors in urban Japanese subjects. The effect of aging on these patterns was also investigated. Data of 8 factors that included body mass index (BMI), blood pressure (BP), fasting plasma glucose (FPG), serum total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDLc), gamma-glutamyl-transferase (GGT), and cigarette smoking were analyzed for 12,525 individuals (4,591 men and 7,934 women) aged either 40, 50, or 60 years. Factor analysis showed eight factors clustered into 3 unrelated groups. BMI and BP were excluded in subjects aged 60 years. Our data showed that the effect of obesity on the prevalence of type 2 diabetes mellitus was age dependent. In spite of the established inverse relationship between TG and HDLc, we found that TG had an association with GGT. These results indicated that aging may have a major influence on the expression of multiple risk factors. The influence of BMI on the lifestyle-related factors appeared to be mostly expressed in younger people, while these factors appeared to be independent of BMI at age 60.

The metabolic syndrome in older individuals: prevalence and prediction of cardiovascular events: the Cardiovascular Health Study

OBJECTIVE

The prevalence of the metabolic syndrome, a potent risk factor for cardiovascular diseases (CVDs), has not been adequately explored in older individuals. Moreover, two sets of criteria have been proposed for the definition of metabolic syndrome, one by the World Health Organization (WHO) and one by the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATPIII). We therefore investigated the prevalence of this syndrome in a subgroup of older participants from the Cardiovascular Health Study (CHS) who were free of CVD at baseline. We also compared the prognostic significance of the two definitions of the metabolic syndrome.

RESEARCH DESIGN AND METHODS

A total of 2,175 subjects from the CHS who were free of CVD at baseline and not taking antihypertensive or lipid-lowering medications were studied. Prevalence of the metabolic syndrome was assessed with both the WHO and ATPIII criteria. The incidence of coronary or cerebrovascular disease was ascertained during a median follow-up time of 4.1 years.

RESULTS

Prevalence of the metabolic syndrome was 28.1% by ATPIII criteria and 21.0% by WHO criteria. The two sets of criteria provided concordant classification for 80.6% of participants. Multivariate Cox propotional hazard models showed that the metabolic syndrome defined with the ATPIII criteria, but not with the WHO criteria, was an independent predictor of coronary or cerebrovascular events and was associated with a 38% increased risk (hazard ratio 1.38 [95% CI 1.06-1.79], P < 0.01).

CONCLUSIONS

Prevalence of the metabolic syndrome in older individuals is approximately 21-28% (depending on the definition used). The two sets of criteria have 80% concordance in classifying subjects. As defined by the ATPIII criteria, the metabolic syndrome yields independent prognostic information, even after adjusting for traditional cardiovascular risk factors and the individual domains of the metabolic syndrome.

The metabolic syndrome in Chinese, Malays and Asian Indians. Factor analysis of data from the 1998 Singapore National Health Survey

We used factor analysis to define and compare the manner in which the various features of the metabolic syndrome are linked or clustered in Chinese, Malays and Asian Indians. One thousand nine hundred and fifty seven men (1324 Chinese, 391 Malays and 261 Asian Indians) and 2308 women (1622 Chinese, 391 Malays and 296 Asian Indians) were examined. Anthropometry, blood pressure, serum glucose, lipid concentrations, and serum insulin were measured for all subjects. These data were then subjected to factor analysis which reduced the variables examined to three factors in all ethnic groups and both genders. The first (dyslipidemia) factor was positively loaded for obesity, insulin resistance (IR), fasting triglyceride and negatively loaded for HDL-cholesterol. The second (hyperglycemia) factor was positively loaded for IR and blood glucose. The third (hypertension) factor was positively loaded for obesity and blood pressure. IR was positively loaded in the hypertension factor in Malay women but not in others. Rather than a single entity causally associated with insulin resistance (IR), our findings support a concept in which the metabolic syndrome represents several distinct entities (dyslipidemia, hypertension and hyperglycemia). It appears that Malay females may be more prone to develop hypertension in association with IR.

A quantitative trait locus influences coordinated variation in measures of ApoB-containing lipoproteins

Lipoprotein phenotypes are known to be strongly intercorrelated. These intercorrelations are due to genetic and environmental effects on common metabolic pathways. The purpose of this study was to determine if we could localize genes that exert pleiotropic effects on multiple related lipoprotein traits in humans. Using data from the San Antonio Family Heart Study, we extracted principal components from a set of 12 intercorrelated lipoprotein traits that included phenotypes reflecting lipid and protein concentrations and size distributions for LDLs and HDLs. Five principal components were extracted from the data and all were significantly heritable (h(2) = 0.41-0.57). When subjected to linkage analyses, only one, Component 5, returned a LOD score > or = 3 (LOD score was 3.0 at 38cM on chromosome 15; genome-wide P-value = 0.039). LDL median diameter (-0.529), non-HDLC (-0.422), and ApoB (-0.403) concentrations were the only traits with loadings (absolute value) >0.4, suggesting Component 5 is related to LDL size or perhaps more generally to beta-lipoprotein metabolism. Surprisingly, none of the 12 original lipoprotein traits had a LOD >1 in this region of chromosome 15. These data provide evidence for a novel gene, influencing beta-lipoprotein phenotypes, whose effect(s) is detected only when several lipoprotein traits are considered together.

Nutritional aspects in the causation and management of the metabolic syndrome

This article emphasizes the importance of weight reduction in obese individuals as the main nutritional focus relevant to the metabolic syndrome. Although other nutrients influence insulin sensitivity, these effects are modest in comparison with the benefit achievable with weight reduction. This article therefore initially discusses the dramatic rise in the prevalence of the metabolic syndrome,especially in the Asian-Pacific region where insulin resistance and the high conversion rate to type 2 diabetes are almost certainly related to weight gain.

Estimating cardiovascular disease risk and the metabolic syndrome: a Framingham view

The metabolic syndrome as currently defined by the Adult Treatment Panel III includes multiple components. This article describes the background for these components' inclusion in the syndrome,measurement of these factors, and the appropriate interventions. The factors are highly interrelated and the true utility of this diagnostic entity is under critical evaluation as new and existing data are evaluated concerning the role of the syndrome in the development of vascular disease and other clinical outcomes.

Prevalence and factor analysis of metabolic syndrome in an urban Korean population

OBJECTIVE

The aim of this study was to explore the prevalence and pattern of the metabolic syndrome and its association with hyperinsulinemia in an urban Korean population of 269 men and 505 women.

RESEARCH DESIGN AND METHODS

The National Cholesterol Education Program Adult Treatment Panel (ATP) III guidelines were used to calculate the sex-specific prevalence of the metabolic syndrome. After excluding individuals taking medication for hypertension, diabetes, or dyslipidemia, we used factor analysis to examine the pattern of the metabolic syndrome in 206 men and 449 women.

RESULTS

The prevalence of metabolic syndrome was 16.0% in men and 10.7% in women aged 30-80 years. However, ATP III criteria for central obesity are not optimal for an Asian-Pacific population; when waist circumference is reduced from 102 to 90 cm in men and 88 to 80 cm in women, the prevalence of the metabolic syndrome increased to 29.0 and 16.8%, respectively. Sex-specific factor analysis showed four factors in men (obesity, glucose intolerance, hypertension, and dyslipidemia) and three in women (obesity-hypertension, glucose intolerance, and obesity-dyslipidemia). Insulin resistance estimated from fasting insulin levels clustered with three of the four factors in men and two of the three factors in women. By ATP III or Asian-Pacific waist circumference criteria, the prevalence of the metabolic syndrome increased with increasing tertiles of insulin resistance, which was estimated by a homeostasis model assessment.

CONCLUSIONS

The metabolic syndrome is common in an urban Korean population when using Asian-Pacific waist criteria. The prevalence of the metabolic syndrome increased with increasing tertiles of insulin resistance.

Metabolic and inflammation variable clusters and prediction of type 2 diabetes: factor analysis using directly measured insulin sensitivity

Factor analysis, a multivariate correlation technique, has been used to provide insight into the underlying structure of the metabolic syndrome. The majority of previous factor analyses, however, have used only surrogate measures of insulin sensitivity; very few have included nontraditional cardiovascular disease (CVD) risk factors such as plasminogen activator inhibitor (PAI)-1, fibrinogen, and C-reactive protein (CRP); and only a limited number have assessed the ability of factors to predict type 2 diabetes. The objective of this study was to investigate, using factor analysis, the clustering of metabolic and inflammation variables using data from 1,087 nondiabetic participants in the Insulin Resistance Atherosclerosis Study (IRAS) and to determine the association of these clusters with risk of type 2 diabetes at follow-up. This study includes information on directly measured insulin sensitivity (S(i)) from the frequently sampled intravenous glucose tolerance test among African-American, Hispanic, and non-Hispanic white subjects aged 40-69 years. Principal factor analysis of data from nondiabetic subjects at baseline (1992-1994) identified three factors, which explained 28.4, 7.4, and 6% of the total variance in the dataset, respectively. Based on factor loadings of >or= 0.40, these factors were interpreted as 1) a "metabolic" factor, with positive loadings of BMI, waist circumference, 2-h glucose, log triglyceride, and log PAI-1 and inverse loadings of log S(i) + 1 and HDL; 2) an "inflammation" factor, with positive loadings of BMI, waist circumference, fibrinogen, and log CRP and an inverse loading of log S(i) + 1; and 3) a "blood pressure" factor, with positive loadings of systolic and diastolic blood pressure. The results were similar within strata of ethnicity, and there were only subtle differences in sex-specific analyses. In a prospective analysis, each of the factors was a significant predictor of diabetes after a median follow-up period of 5.2 years, and each factor remained significant in a multivariate model that included all three factors, although this three-factor model was not significantly more predictive than models using either impaired glucose tolerance or conventional CVD risk factors. Factor analysis identified three underlying factors among a group of inflammation and metabolic syndrome variables, with insulin sensitivity loading on both the metabolic and inflammation variable clusters. Each factor significantly predicted diabetes in multivariate analysis. The findings support the emerging hypothesis that chronic subclinical inflammation is associated with insulin resistance and comprises a component of the metabolic syndrome.