Is there a single underlying factor for the metabolic syndrome in adolescents? A confirmatory factor analysis

Development and validation of a continuous metabolic syndrome severity score in the Tehran Lipid and Glucose Study

Metabolic syndrome (MetS), defined as the coexistence of interrelated cardiometabolic risk factors, is limited by ignoring the severity of the disease and individuals with a pre-metabolic state. We aimed to develop the first age- and sex-specific continuous MetS severity score in the adult population using confirmatory factor analysis (CFA) based on the MetS components in the Middle East. Using data from the population-based Tehran Lipid and Glucose Study (TLGS) I and II datasets, we conducted CFA of the single factor MetS on 8933 adults (20-60 years old) totally, and in age and sex subgroups. We allowed for different factor loadings across the subgroups to formulate age- and sex-specific continuous MetS severity score equations. Thereafter, we validated these equations in the dataset of TLGS III participants. Triglyceride had the highest factor loading across age and sex subgroups, indicating the most correlation with MetS. Except for women aged 40-60 years, waist circumference was the second most significant factor contributing to MetS. Systolic blood pressure was more closely related to MetS in women than in men. Systolic blood pressure and fasting plasma glucose had the weakest correlation with MetS among the 40-60 age group. Moreover, as women age, the contribution of fasting plasma glucose to MetS tended to decline, while it remained relatively constant in men. The resulting MetS severity score was correlated with age and homeostasis model assessment of insulin resistance. Furthermore, the continuous MetS severity score well predicted the traditional MetS according to receiver operating characteristic analysis in the validation dataset. The age- and sex-specific continuous MetS severity score for the West Asian adult population provides a tangible quantitative measure of MetS enabling clinicians to screen and monitor the individuals at risk and assess their metabolic trends.

Longitudinal association between caesarean section birth and cardio-vascular risk profiles among adolescents in Australia

OBJECTIVE

To examine the association of cesarean section (C-section) with cardiovascular disease (CVD) risk biomarkers among Australian children.

METHODS

The Longitudinal Study of Australian Children (LSAC) birth cohort was prospectively followed for body mass index (BMI) trajectory, and then linked with CVD risk indicators of children; waist circumference (WC), systolic blood pressure (SBP), blood glucose, high-density lipoprotein (HDL), triglyceride (TG), fat mass index (FMI) and composite metabolic syndrome (CMetS) score. Multivariable linear regression analysis was done to assess the association of C-sections with CVD risk biomarkers.

RESULTS

Of 1,874 study children, 30% had C-sections; the mean age (SD) was 11.50 (0.50) years, and 49% were female. Against the vaginally-born cohort, Caesarean-born children showed a higher Z- score for five of the seven CVD risk indicators in regression analysis; WC (0.15; p=0.003), SBP (0.16; p=0.003), inverse HDL (0.15; p=0.003), FMI (0.12; p=0.004), and CMetS (0.45; p=0.004) score. Children with accelerated BMI trajectory had higher CMetS scores for both the delivery types while the C-section cohort showed statistical association only (1.69; p=0.006) Conclusion: C-section was independently associated with increased CVD risk profiles of children, further increased with high BMI trajectory. Implication for public health: The chronic disease risk of C-sections should be discussed with families to reduce clinically unrequired C-sections.

Constructing a metabolic integral score model for the quantification of metabolic dysfunction and tendency

BACKGROUND AND AIMS

The binary nature of metabolic syndrome (MetS) cannot quantitatively describe the severity of metabolic abnormalities. We aim to establish a metabolic integral score (MIS) model to quantify the severity and polarity of metabolic disorders and their relationship with insulin sensitivity and secretion.

METHODS AND RESULTS

We performed factor analysis on 9950 participants from a cross-sectional study conducted in China. The MIS model was established using 10 variables including body mass index (BMI), waist circumference, hip circumference, glycosylated hemoglobin (HbA1c), fasting and 2-h plasma glucose (FPG, 2h-PG), systolic blood pressure (SBP), diastolic blood pressure (DBP), high-density lipoprotein (HDL) and triglyceride (TG) levels. Four common factors were identified as "glucose factor," "obesity factor," "blood pressure factor," and "lipid factor," respectively, in MIS model (KMO = 0.755, P < 0.001). MIS = 0.433 × Factor 1 + 0.267 × Factor 2 + 0.172 × Factor 3 + 0.128 × Factor 4. Insulin sensitivity and β-cell function decreased with the increase of MIS (P < 0.001). We classified four metabolic tendencies according to factor quartiles. Individuals in Tendency 1 (severe hyperglycemia) had the worst β-cell function. Tendency 3 (severe hypertension) had the best insulin sensitivity. Tendency 4 (severe dyslipidemia) had preferable β-cell function (P < 0.05).

CONCLUSIONS

Our MIS model provides a quantitative scoring system to assess various patterns of metabolic abnormality that indicate different underlying pathophysiology.

TG: HDL-C Ratio as Insulin Resistance Marker for Metabolic Syndrome in Children With Obesity

Insulin resistance (IR) is an important variable in the diagnosis of metabolic syndrome (MetS). Currently, IR is not part of the existing pediatric definition of MetS, instead elevated fasting blood glucose (FBG) is measured as an indicator of hyperglycemia. Arguably, many obese children with severe IR are still able to regulate their FBG well. Hence, this study aimed to assess the utility of triglyceride-to-high-density lipoprotein cholesterol (TG : HDL-C) ratio as an IR marker in the modeling of pediatric MetS among children with obesity using structural equation modeling (SEM). A total of 524 blood samples from children with obesity (age 10-16 years old) were analyzed for FBG, lipids, insulin, leptin, and adiponectin. Both exploratory (EFA) and confirmatory factor analysis (CFA) were used to examine TG : HDL-C ratio as an IR marker in pediatric MetS. EFA shows that TG: HDL-C ratio (standardized factor loading = 0.904) groups together with homeostasis model assessment-estimated insulin resistance (HOMA-IR) (standardized factor loading = 0.664), indicating a strong correlation to the IR factor. Replacing FBG with TG: HDL-C ratio improved the modeling of MetS structure in children with obesity. Our MetS model of TG: HDL-C ratio as IR component shows comparable model fitness indices (goodness of fit, Akaike's information criterion, and Bayesian information criterion) with leptin:adiponectin ratio (platinum standard for adiposity:IR marker) model. The least model fit was seen when using FBG as an IR surrogate. TG : HDL-C ratio performed better as IR surrogate in MetS structures (standardized factor loading = 0.39) compared to FBG (standardized factor loading = 0.27). TG: HDL-C ratio may be considered as an IR component in pediatric MetS.

Definition and early diagnosis of metabolic syndrome in children

With this review, we aim to focus the attention on some established as well as new concepts for the metabolic syndrome (MetS) in children and adolescents spanning from definition to recommendations for the diagnostic approach. Even though there is no international commonly used definition of the metabolic syndrome in children and adolescents, all definitions include obesity as precondition for the development of MetS even in children. Obesity is one of the major cardiometabolic risk factors and it is strongly linked to other metabolic diseases like hyperlipidemia, hyperinsulinemia as well as hypertension. The metabolic syndrome is commonly known as a constellation of the mentioned morbidities. Pediatricians and researchers agree that early diagnosis and early interventions of the MetS are important to improve the prevention of cardiovascular disease and type 2 diabetes in adulthood. However, this requires appropriate screening tools for children and adolescents at risk for the MetS and its comorbidities. Due to controversies regarding the definition of MetS and the lack of consensus thresholds for the single components in children and adolescents, there is no internationally accepted diagnostic pathway for MetS available. However, several consensus statements and national guidelines for the assessment of obesity and its comorbidities in children and adolescents are available. Obesity seems to be the driving factor for the development of the other risk factors of MetS. In order to avoid conflicts concerning the definition of overweight and obesity, we recommend using the WHO definition of overweight (one standard deviation body mass index for age and sex and obesity; two standard deviations body mass index for age and sex) in children and adolescents.

Prospects for predictive modeling of transition cow diseases

Transition cow diseases can negatively impact animal welfare and reduce dairy herd profitability. Transition cow disease incidence has remained relatively stable over time despite monitoring and management efforts aimed to reduce the risk of developing diseases. Dairy cattle disease risk is monitored by assessing multiple factors, including certain biomarker test results, health records, feed intake, body condition score, and milk production. However, these factors, which are used to make herd management decisions, are often reviewed separately without considering the correlation between them. In addition, the biomarkers that are currently used for monitoring may not be representative of the complex physiological changes that occur during the transition period. Predictive modeling, which uses data to predict future or current outcomes, is a method that can be used to combine the most predictive variables and their interactions efficiently. The use of an effective predictive model with relevant predictors for transition cow diseases will result in better targeted interventions, and therefore lower disease incidence. This review will discuss predictive modeling methods and candidate variables in the context of transition cow diseases. The next step is to investigate novel biomarkers and statistical methods that are best suited for the prediction of transition cow diseases.

Validation of a single factor representing the indicators of metabolic syndrome as a continuous measure of metabolic load and its association with health and cognitive function

The metabolic syndrome (MetS) is a cluster of risk factors for cardiovascular disease associated with reduced physical fitness, higher disease burden, and impaired cognitive functions. Little is known about the operation of these risk factors in older adults when considered comprehensively without relying on the cut-off values of the single MetS components. The three main aims of the current study were to: (i) establish a latent metabolic load factor (MetL), using confirmatory factor analysis (CFA), and representing a continuous measure of MetL, defined by indicators that are commonly used to separate MetS groups from healthy individuals; (ii) examine the associations of this MetL factor with objective health, and cognitive function in men and women; (iii) compare the magnitude of these associations to those observed for the individual indicators used to define the MetL factor as well to the classical categorized MetS vs. non-MetS groups. The current analysis is based on cross-sectional data from 1,609 participants of the Berlin Aging Study II (mean age = 68.5 years, SD (3.7); 50.1% female). We applied structural equation modeling (SEM) to establish a latent MetL factor defined by the five indicators commonly used to diagnose MetS. The latent MetL factor was associated with physician-assessed morbidity and kidney function (estimated glomerular filtration rate, eGFR) in both men and women, but not with hand grip strength and lung function (Forced Expiratory Volume in 1 Second (FEV1)). In addition, we found a negative association between MetL and fluid intelligence among men. A continuous latent variable approach representing the common variance of MetS indicators is well suited to foster our understanding of human aging as a systemic phenomenon in which risk factors are operating on either side of the normal versus pathological divide.

Use of BMI as the marker of adiposity in a metabolic syndrome severity score: Derivation and validation in predicting long-term disease outcomes

BACKGROUND

Estimates of adiposity in evaluating the metabolic syndrome (MetS) have traditionally utilized measures of waist circumference (WC), whereas body mass index (BMI) is more commonly used clinically. Our objective was to determine if a MetS severity Z-score employing BMI as its measure of adiposity (MetS-Z-BMI) would perform similarly to a WC-based score (MetS-Z-WC) in predicting future disease.

METHODS

To formulate the MetS-Z-BMI, we performed confirmatory factor analysis on a sex- and race/ethnicity-specific basis on MetS-related data for 6870 adult participants of the National Health and Nutrition Survey 1999-2010. We then validated this score and compared it to MetS-Z-WC in assessing correlations with future coronary heart disease (CHD) and Type 2 diabetes mellitus (T2DM) using Cox proportional hazard analysis of 13,094 participants of the Atherosclerosis Risk in Communities study and Jackson Heart Study.

RESULTS

Loading factors, which represent the relative contribution of each component to the latent MetS factor, were lower for BMI than for WC in formulating the two respective scores (MetS-Z-BMI and MetS-Z-WC). Nevertheless, MetS-Z-BMI and MetS-Z-WC exhibited similar hazard ratios (HR) toward future disease. For each one standard-deviation-unit increase in MetS-Z-BMI, HR for CHD was 1.76 (95% confidence interval [CI]: 1.65, 1.88) and HR for T2DM was 3.39 (CI 3.16, 3.63) (both p < 0.0001). There were no meaningful differences between the MetS-Z-WC and MetS-Z-BMI scores in their associations with future CHD and T2DM.

CONCLUSIONS

A MetS severity Z-score utilizing BMI as its measure of adiposity operated similarly to a WC-based score in predicting future CHD and T2DM, suggesting overall similarity in MetS-based risk as estimated by both measures of adiposity. This indicates potential clinical usefulness of MetS-Z-BMI in assessing and following MetS-related risk over time.

National Prevalence of Self-Reported Coronary Heart Disease and Chronic Stable Angina Pectoris: Factor Analysis of the Underlying Cardiometabolic Risk Factors in the SuRFNCD-2011

BACKGROUND

Coronary heart disease (CHD) is one of the most common causes of mortality worldwide. The national prevalence remains unclear in most of the developing countries.

OBJECTIVE

This study sought to estimate national prevalence of self-reported CHD and chronic stable angina pectoris in the general adult population of Iran using data from the fourth round of the Surveillance of Risk Factors of Non-Communicable Diseases (SuRFNCD-2011) survey.

METHODS

The analysis comprised data of 11,867 civilian, nonhospitalized and noninstitutionalized residents ages 6 to 70 years of age. The calculated prevalence of self-reported CHD and chronic stable angina pectoris were extrapolated to the Iranian adult population who were >20 years old using the complex sample analysis. The factor analysis was performed for clustering of the associated cardiometabolic risk factors among people ages >40 years of age.

RESULTS

The estimated national prevalence of self-reported CHD and chronic stable angina pectoris were 5.3% (95% confidence interval: 4.6 to 5.9) and 7.7% (95% confidence interval: 4.6 to 8.7), respectively. Higher prevalence of these conditions were observed among the older people, urban residents, and women. Factor analysis generated 4 distinct factors that were mainly indicators of dyslipidemia, hypertension, central obesity, hyperglycemia, and tobacco smoking. The factor incorporating hypertension was a significant correlate of self-reported CHD.

CONCLUSIONS

We report concerning prevalence of self-reported CHD and chronic stable angina pectoris in the adult population of Iran. The constellation of raised systolic and diastolic blood pressures was significantly predictive of the presence of self-reported CHD.

Pediatric siMS score: A new, simple and accurate continuous metabolic syndrome score for everyday use in pediatrics

BACKGROUND

The dichotomous nature of the current definition of metabolic syndrome (MS) in youth results in loss of information. On the other hand, the calculation of continuous MS scores using standardized residuals in linear regression (Z scores) or factor scores of principal component analysis (PCA) is highly impractical for clinical use. Recently, a novel, easily calculated continuous MS score called siMS score was developed based on the IDF MS criteria for the adult population.

OBJECTIVE

To develop a Pediatric siMS score (PsiMS), a modified continuous MS score for use in the obese youth, based on the original siMS score, while keeping the score as simple as possible and retaining high correlation with more complex scores.

SUBJECTS AND METHODS

The database consisted of clinical data on 153 obese (BMI ≥95th percentile) children and adolescents. Continuous MS scores were calculated using Z scores and PCA, as well as the original siMS score. Four variants of PsiMS score were developed in accordance with IDF criteria for MS in youth and correlation of these scores with PCA and Z score derived MS continuous scores was assessed.

RESULTS

PsiMS score calculated using formula: (2xWaist/Height) + (Glucose(mmol/l)/5.6) + (triglycerides(mmol/l)/1.7) + (Systolic BP/130)-(HDL(mmol/l)/1.02) showed the highest correlation with most of the complex continuous scores (0.792-0.901). The original siMS score also showed high correlation with continuous MS scores.

CONCLUSION

PsiMS score represents a practical and accurate score for the evaluation of MS in the obese youth. The original siMS score should be used when evaluating large cohorts consisting of both adults and children.

Cardiometabolic Risk Variables in Preadolescent Children: A Factor Analysis

BACKGROUND

Atherosclerosis begins during preadolescence and is occurring at an accelerated rate. This acceleration has been linked to poor lifestyle behaviors and subsequent cardiometabolic complications. Although the clustering of cardiometabolic risk factors has been recognized for over 2 decades, previous studies in children have predominantly examined the relationships between atherosclerosis and individual cardiometabolic risk factors or have grouped together preadolescent and adolescent children. Further, no known studies have included glycated hemoglobin or central hemodynamic measures such as central systolic blood pressure and augmentation index.

METHODS AND RESULTS

Principal component analysis was performed on a cross-sectional sample of 392 children (aged 9.5 years, 50% girls) from 3 representative sample sites across New Zealand. Four factors explained 60% of the variance in the measured variables. In order of variance explained, the factors were: blood pressure (central systolic blood pressure and peripheral systolic and diastolic blood pressure), adiposity (waist circumference, body mass index, and glycated hemoglobin), lipids (total cholesterol, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol), and vascular (augmentation index, heart rate, and fasting blood glucose).

CONCLUSIONS

In accordance with previous findings in adults and adolescents, one common factor is unlikely to define cardiometabolic health in preadolescent children. Each of the factors, except vascular, which was predominantly explained by augmentation index, are in agreement with previous findings in adolescents. An additional novel finding was that glycated hemoglobin and fasting blood glucose loaded onto different factors, supporting previous work suggesting that fasting blood glucose indicates short-term glycemic control, whereas glycated hemoglobin reflects chronic glycemic control.

CLINICAL TRIAL REGISTRATION

URL: www.anzctr.org.au/. ID: ACTRN12614000433606.

Metabolic Syndrome in Hispanic Youth: Results from the Hispanic Community Children's Health Study/Study of Latino Youth

BACKGROUND

Metabolic syndrome (MetS), a cluster of cardiovascular risk factors, is being diagnosed in youth. Specific diagnostic criteria used to define MetS influence prevalence estimates and populations considered at risk for cardiovascular disease. The National Cholesterol Education Program's Adult Treatment Panel III (ATP), the World Health Organization (WHO), and the International Diabetes Federation (IDF) provide three MetS definitions used in medical research. This study examined concordance among these definitions in 1137 children 10-16 years of age, who participated in the Hispanic Community Children's Health Study/Study of Latino Youth.

METHODS

Prevalence of MetS and of individual components was estimated using SAS. Mplus was used to test a single-factor model of MetS components (triglycerides, high-density lipoprotein cholesterol, systolic and diastolic blood pressure, waist circumference, and fasting glucose).

RESULTS

The ATP definition identified most MetS cases in 10-15 (N = 19, 4.7%) and 16-year-old girls (N = 3, 7.3%). The IDF definition identified most cases of MetS in 10-15 (N = 16, 3.1%) and 16-year-old boys (N = 2, 2.8%). Fewest cases of MetS were identified with the WHO definition across age and sex groups.

CONCLUSION

Only one participant was classified as having MetS across all three definitions. Confirmatory factor analysis indicated fasting glucose and systolic blood pressure did not reliably cluster with other risk factors that define MetS in Hispanic/Latino adolescents. We conclude that prevalence estimates of MetS in youth are unstable across current criteria, calling into question the accuracy of defining and diagnosing MetS in youth.

A red yeast rice-olive extract supplement reduces biomarkers of oxidative stress, OxLDL and Lp-PLA2, in subjects with metabolic syndrome: a randomised, double-blind, placebo-controlled trial

BACKGROUND

Metabolic syndrome (MetS) refers to clustered cardiovascular risk factors (abdominal obesity, pre-diabetes, high blood pressure, dyslipidaemia). Therapies targeting oxidative stress may delay progression to atherosclerosis and diabetes. We investigated the anti-oxidative effect of a supplement combining red yeast rice and olive extract in patients with MetS.

METHODS

A double-blind, placebo-controlled, randomised trial was conducted with 50 patients with MetS as defined by National Cholesterol Education Program Adult Treatment Panel III criteria. Forty-nine subjects randomly assigned to red yeast rice-olive extract (RYR-olive extract; 10.82 mg of monacolins and 9.32 mg of hydroxytyrosol per Cholesfytolplus capsule) or placebo completed the 8-week trial. Whereas effects on cardiovascular risk parameters of MetS have been reported recently, the observed significant 20% increase in oxidised low-density lipoprotein (OxLDL) prompted us to investigate other oxidative stress-related parameters: malondialdehyde (MDA), lipoprotein-associated phospholipase A₂ (Lp-PLA₂) and 8-hydroxy-2'-deoxyguanosine (8-OHdG). Statistical calculations included univariate quantitative analysis, multivariate linear regression and correlation analysis.

RESULTS

The updated results indicate that an RYR-olive extract supplement significantly reduced Lp-PLA₂ by 7% (p < 0.001), but it failed to show a significant decrease in plasma MDA and 8-OHdG (p > 0.05). Reductions in OxLDL (20%) and Lp-PLA₂ (7%) were associated with each other (r = 0.740, p < 0.001).

CONCLUSIONS

RYR-olive extract significantly reduced Lp-PLA₂ in correlation with the marked reduction in plasma OxLDL, which may lead to a reduced risk for cardiovascular disease in patients with MetS.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT02065180 . Registered on 13 February 2014.

siMS Score: Simple Method for Quantifying Metabolic Syndrome

Objective

To evaluate siMS score and siMS risk score, novel continuous metabolic syndrome scores as methods for quantification of metabolic status and risk.

Materials and Methods

Developed siMS score was calculated using formula: siMS score = 2*Waist/Height + Gly/5.6 + Tg/1.7 + TA_systolic/130—HDL/1.02 or 1.28 (for male or female subjects, respectively). siMS risk score was calculated using formula: siMS risk score = siMS score * age/45 or 50 (for male or female subjects, respectively) * family history of cardio/cerebro-vascular events (event = 1.2, no event = 1). A sample of 528 obese and non-obese participants was used to validate siMS score and siMS risk score. Scores calculated as sum of z-scores (each component of metabolic syndrome regressed with age and gender) and sum of scores derived from principal component analysis (PCA) were used for evaluation of siMS score. Variants were made by replacing glucose with HOMA in calculations. Framingham score was used for evaluation of siMS risk score.

Results

Correlation between siMS score with sum of z-scores and weighted sum of factors of PCA was high (r = 0.866 and r = 0.822, respectively). Correlation between siMS risk score and log transformed Framingham score was medium to high for age groups 18+,30+ and 35+ (0.835, 0.707 and 0.667, respectively).

Conclusions

siMS score and siMS risk score showed high correlation with more complex scores. Demonstrated accuracy together with superior simplicity and the ability to evaluate and follow-up individual patients makes siMS and siMS risk scores very convenient for use in clinical practice and research as well.

Three clustering patterns among metabolic syndrome risk factors and their associations with dietary factors in Korean adolescents: based on the Korea National Health and Nutrition Examination Survey of 2007-2010

BACKGROUND/OBJECTIVE

Even though the prevalence of metabolic syndrome in adolescents is increasing, little is presently known about this syndrome in adolescents. This study aimed to cluster metabolic risk factors as well as examine the associations between identified patterns and nutrient intake using data from the Korean National Health Examination and Nutritional Assessment (KNHANES).

SUBJECTS/METHODS

A total of 2,958 subjects aged 10 to 18 years along with both biochemical and dietary data information were obtained from KNHANES 2007-2010. Six components of metabolic syndrome were used to identify any patterns via factor analysis. Individuals were categorized into quartile groups according to their pattern score.

RESULTS

Three clustering patterns with high loadings were identified and named as follows: 1) high blood pressure, 2) dyslipidemia, and 3) glucose abnormality patterns. The high blood pressure pattern showed high loadings of systolic and diastolic blood pressures, the dyslipidemia pattern showed high loadings of triglyceride and HDL-cholesterol levels, and the glucose abnormality pattern showed high loadings of fasting blood glucose levels. Intakes of fat and riboflavin were significantly decreased, whereas those of sodium and niacin were significantly increased across the quartiles in the dyslipidemia pattern. No nutrient intake except that of thiamin was significantly associated with the high blood pressure or glucose abnormality pattern.

CONCLUSION

Our findings show that metabolic syndrome risk factors in the Korean adolescent population are characterized by three distinct patterns, which are differentially associated with dietary factors. Characterizing metabolic risk factors and providing specific dietary guidelines for target groups are important.

[Metabolic syndrome risk assessment in children: use of a single score]

OBJECTIVE

To calculate a score of metabolic syndrome (MetS) in children and set a cutoff point of this score for the prediction of MetS risk.

METHODS

The study included a random sample of 348 children aged 8 and 9 years of Viçosa, Southeast Brazil. Factor analysis by principal components (PCA) was used to determine, among various risk factors, those with higher degrees of intercorrelation. The chosen variables were: waist circumference (PC), homeostatic model assessment of insulin resistance (HOMA), high density lipoprotein (HDL), triglycerides (TAG) and mean arterial pressure (MAP). Z-scores were created for each one of these parameters and the sum of these z-scores constituted the MetS score. The receiver operating characteristic (ROC) curve was used to identify the cutoff of MetS score, using as gold standard the presence or absence of MetS determined according to criteria age-modified.

RESULTS

The prevalence of MetS in the sample was 8.9% by adopting specific criteria for age, and 24% when considering the cutoff of MetS score. The selected cutoff point of 1.86 was accurate to predict the MetS risk in this sample due to its high sensitivity (96.7%), specificity (82.7%) and AUC of 0.96.

CONCLUSIONS

This original Brazilian study presents the MetS score as a suitable alternative for the study of Metabolic Syndrome in children, given the lack of consensus for the definition of this syndrome in childhood.

Metabolic syndrome related health inequalities in Korean elderly: Korean National Health and Nutrition Examination Survey (KNHAES)

While the prevalence of metabolic syndrome is increasing, little is presently known about this syndrome in Korean elderly. This study aimed to group metabolic risk factors and to examine the associations between groups of health living conditions and metabolic syndrome using data from the Korean National Health Examination and Nutritional Assessment (KNHANES). A total of 1,435 subjects aged over 65 years old with both biochemical and dietary data information were obtained from the 4th and 5th KNHANES (2007–2012). Using stratified and multistage probability sample data, five components of metabolic syndrome were adopted to identify health inequalities. Our findings show that groups of health living conditions such as dietary pattern, body image, muscle mass, and fat mass were differentially associated with metabolic syndrome risk factors. Future studies are necessary to examine the underlying mechanisms of individual health living conditions to better understand the role of metabolic risk factors in metabolic syndrome in elderly.

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.

Validation of metabolic syndrome score by confirmatory factor analysis in children and adults and prediction of cardiometabolic outcomes in adults

AIMS/HYPOTHESIS

We validated the metabolic syndrome (MetS) score by confirmatory factor analysis (CFA) in children, middle-aged men, and older women and men and by investigating the relationships of the MetS score to incident type 2 diabetes, myocardial infarction, and cardiovascular and overall death in middle-aged men.

METHODS

We assessed the core features of MetS, calculated the MetS score using z scores for waist circumference, insulin, glucose, triacylglycerols, HDL-cholesterol and blood pressure, and carried out CFA to investigate whether MetS represents a single entity in population samples of 491 children, 1,900 middle-aged men, 614 older women and 555 older men from Finland. We also followed-up incident type 2 diabetes for 11 years and other outcomes for 17-18 years in middle-aged men.

RESULTS

We carried out second-order CFAs in which the MetS was represented by a second-order latent variable underlying four latent variables characterised by abdominal obesity, insulin resistance, dyslipidaemia and raised blood pressure in different age groups. These second-order factors and factors derived from first-order CFA using previously proposed models were strongly associated with a composite MetS score in all age groups (r = 0.84-0.94) and similarly predicted type 2 diabetes, cardiovascular outcomes and mortality in middle-aged men. The risk of type 2 diabetes, myocardial infarction, cardiovascular death and overall death increased 3.67-, 1.38-, 1.56- and 1.44-fold, respectively, for a 1 SD increase in the MetS score.

CONCLUSIONS

The MetS can be described as a single entity in all age groups. The MetS score is a valid tool for research evaluating cardiometabolic risk in different age groups. Further research is needed to define cut-off points for risk estimation in clinical practice.

Sleep quality and the metabolic syndrome: the role of sleep duration and lifestyle

BACKGROUND

This study examined the association between sleep quality and the metabolic syndrome and whether if it is independent of sleep duration and if it can be explained by lifestyles linked to sleep quality.

METHODS

Cross-sectional study conducted from 2008 to 2010 with 10 342 individuals representative of the population aged ≥18 years in Spain. Poor sleep quality was ascertained through self-reported difficulty falling asleep, difficulty maintaining sleep and sleeping pill consumption. Metabolic syndrome was defined according to the recent harmonized definition. Analyses were conducted with logistic regression and adjusted for the main confounders.

RESULTS

Difficulty falling asleep was associated with higher frequency of metabolic syndrome after adjustment for sociodemographic variables, lifestyle and diagnosed morbidity [odds ratio (OR) = 1.25; 95% confidence interval (CI) = 1.06-1.47]. The association was slightly attenuated after further adjusting for sleep duration (OR = 1.23; 95% CI = 1.04-1.46) and held after additional adjustment for energy intake, adherence to a Mediterranean dietary pattern, energy spent in physical activity and time watching TV (OR = 1.20; 95% CI = 1.01-1.42). No associations were found between metabolic syndrome and other sleep quality indicators. Difficulty falling asleep was associated with high blood pressure in the fully adjusted analyses (OR = 1.17; 95% CI = 1.00-1.37) but not with the rest of components of metabolic syndrome.

CONCLUSIONS

Difficulty falling asleep is associated with metabolic syndrome and, in particular, with high blood pressure. This association is independent of sleep duration and is not due to lifestyles related to poor sleep. This finding should be replicated in prospective studies using objective sleep measures; also, the influence of antihypertensive and lipid-lowering drug treatment on this association should be further studied.

An examination of sex and racial/ethnic differences in the metabolic syndrome among adults: a confirmatory factor analysis and a resulting continuous severity score

OBJECTIVE

The metabolic syndrome (MetS) is typically diagnosed based on abnormalities in specific clustered clinical measures that are associated with increased risk for coronary heart disease (CHD) and Type 2 diabetes mellitus (T2DM). However, current MetS criteria result in racial/ethnic discrepancies. Our goals were to use confirmatory factor analysis (CFA) to delineate differential contributions to MetS by sub-group, and if contributions were discovered, develop sex and racial/ethnic-specific equations to calculate MetS severity.

RESEARCH DESIGN AND METHODS

Using data on adults from the National Health and Nutrition Examination Survey 1999-2010, we performed a CFA of a single MetS factor that allowed differential loadings across groups, resulting in a sex and race/ethnicity-specific continuous MetS severity score.

RESULTS

Loadings to the single MetS factor differed by sub-group for each MetS component (p<0.001), with lower factor loadings among non-Hispanic-blacks for triglycerides and among Hispanics for waist circumference. Systolic blood pressure exhibited low factor loadings among all groups. MetS severity scores were correlated with biomarkers of future disease (high-sensitivity C-reactive-protein, uric acid, insulin resistance). Non-Hispanic-black-males with diabetics had a low prevalence of MetS but high MetS severity scores that were not significantly different from other racial/ethnic groups.

CONCLUSIONS

This analysis among adults uniquely demonstrated differences between sexes and racial/ethnic groups regarding contributions of traditional MetS components to an assumed single factor. The resulting equations provide a clinically-accessible and interpretable continuous measure of MetS for potential use in identifying adults at higher risk for MetS-related diseases and following changes within individuals over time. These equations hold potential to be a powerful new outcome for use in MetS-focused research and interventions.

A cross-sectional study of Jamaican adolescents' risk for type 2 diabetes and cardiovascular diseases

OBJECTIVES

To compare obese versus non-obese Jamaican adolescents' risk for type 2 diabetes (T2D) and cardiovascular diseases (CVDs); and to explore a suitable and economical method of screening for these risk factors in the school settings.

DESIGN

A descriptive cross-sectional study of adolescents' risk for T2D and CVD. All the participants were examined at their respective schools.

SETTING

Jamaica, West Indies.

POPULATION

276 Jamaican adolescents aged 14-19 years, randomly selected from grades 9 to 12 from 10 high schools on the island and included both boys and girls. All ethnicities on the island were represented.

MAIN OUTCOME MEASURES

High fasting blood glucose, total cholesterol, glycated haemoglobin (HbA1c), blood pressure, body mass index (BMI), waist circumference, waist-to-hip ratio, family history of obesity, T2D and CVDs, low physical activity, and presence of Acanthosis Nigricans. All blood measures were analysed using the finger prick procedure.

RESULTS

Waist circumference, waist-to-hip ratio, Acanthosis Nigricans, total cholesterol, family history of T2D and blood pressure were the strongest predictors of BMI (p=0.001). Over one-third of the participants were overweight. Jamaican adolescent females had a significantly higher number of risk factors and were less physically active than males (p<0.05). Over 80% of participants reported ≥3 risk factors for T2D and CVD. Participants with BMI ≥25 reported five or more risk factors. One-third of the overweight participants were classified with metabolic syndrome.

CONCLUSIONS

Jamaican adolescents are at risk of T2D and CVD. Family history of disease and anthropometric measures identified more participants at risk than did the blood measures. Jamaican adolescent females reported more risk factors for T2D and CVD as compared to males. Collection of this type of data was feasible within the school settings. All data were collected in 1 day per school. Intervention measures are needed to educate Jamaican adolescents to reduce overweight and subsequently the risk factors.

Evaluation of two single-factor models of metabolic syndrome: a confirmatory factor analysis for an adult population in Beijing

Background

Prevalence of metabolic syndrome is high and increasing in China. The causation of this disorder is, yet, to be fully understood. Several studies with confirmatory factor analysis have been performed to investigate the core of the disease in some races other than Chinese, and amongst the other studies, they have yielded a sound model fit. This study was to evaluate and compare two single-factor models of the underlying factor structure of metabolic syndrome in a Chinese population using confirmatory factor analysis.

Results

Findings showed that in a Chinese sample of 7,472 individuals, Model 1 (with waist circumference, triglycerides/HDL-C ratio, fasting plasma glucose and mean artery pressure) yielded good level of fitness (SRMR < 0.08, CFI > 0.96 and RMSEA < 0.10) in men and women of all age groups; and Model 2 (with waist circumference, triglycerides, fasting plasma glucose and systolic blood pressure) fitted well in men aged 18–34 and over 60 and in all women, except in men of 35–59 (RMSEA = 0.142). In comparison, Model 2 were shown to be better fit (with relative larger GFI and smaller AIC, BIC, CAIC, and EVIC) in women of all age groups and in men of 18–34 and over 60 years old; Model 1 had a better fit in men between 35 and 59.

Conclusions

This study suggests that the single-factor model of metabolic syndrome with waist circumference, triglycerides, fasting plasma glucose and systolic blood pressure are plausible in women of all age groups and young and senior men in Beijing. The model with waist circumference, triglycerides/HDL-C ratio, fasting plasma glucose and mean artery pressure fits middle-aged men.

Prevalence of metabolic syndrome in a cohort of Chinese schoolchildren: comparison of two definitions and assessment of adipokines as components by factor analysis

BACKGROUND

Although attention to metabolic syndrome (MetS) in children has increased, there is still no universally accepted definition and its pathogenesis remains unclear. Our aim was to compare the current definitions of childhood MetS in a Chinese cohort and to examine the clustering pattern of MetS risk factors, particularly inclusion of leptin and adiponectin as additional components.

METHODS

3373 schoolchildren aged 6 to 18 years were recruited. Anthropometric and biochemical parameters and adipokines were measured. MetS was identified using both the International Diabetes Federation (IDF) and a modified Adult Treatment Panel III (ATP III) definitions. Exploratory factor analysis was performed to establish grouping of metabolic characteristics.

RESULTS

For children ≥ 10 years, the prevalence of MetS was 14.3% in the obese group and 3.7% in the overweight group according to the new IDF definition, and 32.3% in the obese group and 8.4% in the overweight group according to the modified ATPIII definition. Frequency of hypertriglyceridemia, low high-density lipoprotein cholesterol (HDL-C), impaired fasting glucose, elevated blood pressure, and central obesity according to the new IDF definition was 16.7%, 20.7%, 15.8%, 25.5% and 75.5% in obese boys and 14.7%, 24.0%, 12.0%, 11.0% and 89.0% in obese girls, respectively. Metabolic abnormalities in children under 10 years of age were also noted. Using factor analysis on eight conventional variables led to the extraction of 3 factors. Waist circumference (WC) provided a connection between two factors in boys and all three factors in girls, suggesting its central role in the clustering of metabolic risk factors. Addition of leptin and adiponectin also led to the extraction of 3 factors, with leptin providing a connection between two factors in girls. When using WC, mean arterial pressure, triglyceride/HDL-C ratio, HOMA-IR and leptin/adiponectin ratio as variables, a single-factor model was extracted. WC had the biggest factor loading, followed by leptin/adiponectin ratio.

CONCLUSIONS

MetS was highly prevalent amongst obese children and adolescents in this cohort, regardless of the definition used. Central obesity is the key player in the clustering of metabolic risk factors in children, supporting the new IDF definition. Moreover, our findings suggest that a common factor may underlie MetS. Leptin/adiponectin ratio as a possible component of MetS deserves further consideration.

Characteristics of metabolic syndrome based on clustering pattern among Korean adolescents: findings from the Korean National Health and Nutrition Examination Survey, 2007-2008

To define the factors that influence the development of metabolic syndrome (MetS) characteristics in adolescents, this study assessed the clustering pattern for MetS using confirmatory factor analysis (CFA). Components of metabolic syndrome, including abdominal obesity, insulin resistance, high blood pressure, and dyslipidemia, were analyzed in 1,514 Korean adolescents aged 10 to 18 years. The validities of one-factor models underlying a unifying etiology and a four-factor model based on more than one physiologic process for MetS across sex and age groups were assessed using the CFA method. The one-factor model, which incorporated waist circumference (WC), homeostasis model assessment-insulin resistance (HOMA-IR), systolic blood pressure (SBP), and high-density lipoprotein (HDL) values, had the best goodness-of-fit indices among the models (comparative fit index 0.99, root mean square error of approximation 0.04), with stability over sex and age groups. MetS was mainly defined by WC, SBP, HOMA-IR, and HDL values, with factor loadings of 0.78, 0.47, 0.44, and -0.37, respectively. WC contributed the most to MetS, with the highest factor loading value across sex and age groups. In conclusion, a single underlying factor representing the common pathway linking abdominal obesity, SBP, HOMA-IR, and HDL may explain MetS in Korean adolescents with stability across sex and age groups.

Metabolic syndrome model definitions predicting type 2 diabetes and cardiovascular disease

OBJECTIVE

Metabolic syndrome (MetS) is a cluster of abdominal obesity, hyperglycemia, hypertension, and dyslipidemia, which increases the risk for type 2 diabetes and cardiovascular diseases (CVDs). Some argue that MetS is not a single disorder because the traditional MetS features do not represent one entity, and they would like to exclude features from MetS. Others would like to add additional features in order to increase predictive ability of MetS. The aim of this study was to identify a MetS model that optimally predicts type 2 diabetes and CVD while still representing a single entity.

RESEARCH DESIGN AND METHODS

In a random sample (n = 1,928) of the EPIC-NL cohort and a subset of the EPIC-NL MORGEN study (n = 1,333), we tested the model fit of several one-factor MetS models using confirmatory factor analysis. We compared predictive ability for type 2 diabetes and CVD of these models within the EPIC-NL case-cohort study of 545 incident type 2 diabetic subjects, 1,312 incident CVD case subjects, and the random sample, using survival analyses and reclassification.

RESULTS

The standard model, representing the current MetS definition (EPIC-NL comparative fit index [CFI] = 0.95; MORGEN CFI = 0.98); the standard model excluding blood pressure (EPIC-NL CFI = 0.95; MORGEN CFI = 1.00); and the standard model extended with hsCRP (EPIC-NL CFI = 0.95) had an acceptable model fit. The model extended with hsCRP predicted type 2 diabetes (integral discrimination index [IDI]: 0.34) and CVD (IDI: 0.07) slightly better than did the standard model.

CONCLUSIONS

It seems valid to represent the traditional MetS features by a single entity. Extension of this entity with hsCRP slightly improves predictive ability for type 2 diabetes and CVD.

Metabolic syndrome risk profiles among African American adolescents: national health and nutrition examination survey, 2003-2010

OBJECTIVE

Although African American adolescents have the highest prevalence of obesity, they have the lowest prevalence of metabolic syndrome across all definitions used in previous research. To address this paradox, we sought to develop a model of the metabolic syndrome specific to African American adolescents.

RESEARCH DESIGN AND METHODS

Data from the National Health and Nutrition Examination Survey (2003-2010) of 822 nonpregnant, nondiabetic, African American adolescents (45% girls; aged 12 to 17 years) who underwent physical examinations and fasted at least 8 h were analyzed. We conducted a confirmatory factor analysis to model metabolic syndrome and then used latent profile analysis to identify metabolic syndrome risk groups among African American adolescents. We compared the risk groups on probability of prediabetes.

RESULTS

The best-fitting metabolic syndrome model consisted of waist circumference, fasting insulin, HDL, and systolic blood pressure. We identified three metabolic syndrome risk groups: low, moderate, and high risk (19% boys; 16% girls). Thirty-five percent of both boys and girls in the high-risk groups had prediabetes, a significantly higher prevalence compared with boys and girls in the low-risk groups. Among adolescents with BMI higher than the 85th percentile, 48 and 36% of boys and girls, respectively, were in the high-risk group.

CONCLUSIONS

Our findings provide a plausible model of the metabolic syndrome specific to African American adolescents. Based on this model, approximately 19 and 16% of African American boys and girls, respectively, are at high risk for having the metabolic syndrome.

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.

Heterogeneous behavior of lipids according to HbA1c levels undermines the plausibility of metabolic syndrome in type 1 diabetes: data from a nationwide multicenter survey

Background

Cardiovascular risk factors (CVRF) may cluster in type 1 diabetes, analogously to the metabolic syndrome described in type 2 diabetes. The threshold of HbA1_c above which lipid variables start changing behavior is unclear. This study aims to 1) assess the behavior of dyslipidemia according to HbA1_c values; 2) detect a threshold of HbA1_c beyond which lipids start to change and 3) compare the clustering of lipids and other non-lipid CVRF among strata of HbA1_c individuals with type 1 diabetes.

Methods

Effects of HbA1_c quintiles (1st: ≤7.4%; 2nd: 7.5-8.5%; 3rd: 8.6-9.6%; 4th: 9.7-11.3%; and 5th: >11.5%) and covariates (gender, BMI, blood pressure, insulin daily dose, lipids, statin use, diabetes duration) on dyslipidemia were studied in 1275 individuals from the Brazilian multi-centre type 1 diabetes study and 171 normal controls.

Results

Body size and blood pressure were not correlated to lipids and glycemic control. OR (99% CI) for high-LDL were 2.07 (1.21-3.54) and 2.51 (1.46-4.31), in the 4th and 5th HbA1_c quintiles, respectively. Hypertriglyceridemia increased in the 5th quintile of HbA1_c, OR 2.76 (1.20-6.37). OR of low-HDL-cholesterol were 0.48 (0.24-0.98) and 0.41 (0.19-0.85) in the 3rd and 4th HbA1_c quintiles, respectively. HDL-cholesterol correlated positively (0.437) with HbA1_c in the 3rd quintile. HDL-cholesterol and insulin dose correlated inversely in all levels of glycemic control.

Conclusions

Correlation of serum lipids with HbA1_c is heterogeneous across the spectrum of glycemic control in type 1 diabetes individuals. LDL-cholesterol and triglycerides worsened alongside HbA1_c with distinct thresholds. Association of lower HDL-cholesterol with higher daily insulin dose is consistent and it points out to a role of exogenous hyperinsulinemia in the pathophysiology of the CVRF clustering. These data suggest diverse pathophysiological processes depending on HbA1_c, refuting a unified explanation for cardiovascular risk in type 1 diabetes.

A principal component model of medical health: implications for cognitive deficits and decline among adults in a population-based sample

Longitudinal blood- and cognitive data from 879 adults were analyzed to extract a multidimensional health structure for prediction of cognitive change. Six health components were identified and replicated at two waves. Following, cognitive outcomes were regressed on the health components. Large proportions of cognitive age related variations were accounted for by baseline health in both cross-sectional and prospective analyses. Less variation was accounted for when health change and cognitive change were contrasted. Cardiovascular health was particularly important for prediction of cognitive change. Our study underlines causal relations between health and cognitive functions, and suggests that some effects are long term.

A confirmatory factor analysis of the metabolic syndrome in adolescents: an examination of sex and racial/ethnic differences

Objective

The metabolic syndrome (MetS) is a cluster of clinical indices that signals increased risk for cardiovascular disease and Type 2 diabetes. The diagnosis of MetS is typically based on cut-off points for various components, e.g. waist circumference and blood pressure. Because current MetS criteria result in racial/ethnic discrepancies, our goal was to use confirmatory factor analysis to delineate differential contributions to MetS by sub-group.

Research Design and Methods

Using 1999–2010 data from the National Health and Nutrition Examination Survey (NHANES), we performed a confirmatory factor analysis of a single MetS factor that allowed differential loadings across sex and race/ethnicity, resulting in a continuous MetS risk score that is sex and race/ethnicity-specific.

Results

Loadings to the MetS score differed by racial/ethnic and gender subgroup with respect to triglycerides and HDL-cholesterol. ROC-curve analysis revealed high area-under-the-curve concordance with MetS by traditional criteria (0.96), and with elevations in MetS-associated risk markers, including high-sensitivity C-reactive protein (0.71), uric acid (0.75) and fasting insulin (0.82). Using a cut off for this score derived from ROC-curve analysis, the MetS risk score exhibited increased sensitivity for predicting elevations in ≥2 of these risk markers as compared with traditional pediatric MetS criteria.

Conclusions

The equations from this sex- and race/ethnicity-specific analysis provide a clinically-accessible and interpretable continuous measure of MetS that can be used to identify children at higher risk for developing adult diseases related to MetS, who could then be targeted for intervention. These equations also provide a powerful new outcome for use in childhood obesity and MetS research.

Stability of the factorial structure of metabolic syndrome from childhood to adolescence: a 6-year follow-up study

Background

Metabolic syndrome (MS) is a clustering of cardiometabolic risk factors that is considered a predictor of cardiovascular disease, type 2 diabetes and mortality. There is no consistent evidence on whether the MS construct works in the same way in different populations and at different stages in life.

Methods

We used confirmatory factor analysis to examine if a single-factor-model including waist circumference, triglycerides/HDL-c, insulin and mean arterial pressure underlies metabolic syndrome from the childhood to adolescence in a 6-years follow-up study in 174 Swedish and 460 Estonian children aged 9 years at baseline. Indeed, we analyze the tracking of a previously validated MS index over this 6-years period.

Results

The estimates of goodness-of-fit for the single-factor-model underlying MS were acceptable both in children and adolescents. The construct stability of a new model including the differences from baseline to the end of the follow-up in the components of the proposed model displayed good fit indexes for the change, supporting the hypothesis of a single factor underlying MS component trends.

Conclusions

A single-factor-model underlying MS is stable across the puberty in both Estonian and Swedish young people. The MS index tracks acceptably from childhood to adolescence.

Longitudinal factor analysis reveals a distinct clustering of cardiometabolic improvements during intensive, short-term dietary and exercise intervention in obese children and adolescents

OBJECTIVE

The aim of this study was to investigate changes in cardiometabolic clustering characteristics in response to highly significant weight loss.

BACKGROUND

Pre-post analysis of a lifestyle intervention for the treatment of obesity and the assessment of interrelated metabolic changes were analyzed using principal component analysis (PCA). A total of n=75 clinically obese boys and girls [standardized body mass index (sBMI) 3.07±0.59] aged 8-18 years were assessed after lifestyle intervention (30±12 days).

RESULTS

There were favorable improvements in BMI waist circumference, fasting insulin, triglycerides (TGs), systolic blood pressure (SBP) and diastolic blood pressure (DBP) (all P<0.001). PCA was performed using a simple conceptual model of changes in six metabolic variables: Overall and central obesity (BMI and waist circumference), dyslipidemia [TG and high-density lipoprotein cholesterol (HDL-C)], insulin resistance [fasting insulin or homeostasis model assessment of insulin resistance (HOMA-IR)], and blood pressure [SBP or mean arterial pressure (MAP)]. PCA models consistently identified two factors underlying the changes in six cardiometabolic variables. These were labeled a "metabolic" factor, typically including waist circumference, fasting triglyceride, insulin, or HOMA-IR and HDL-C (negatively) and an "obesity/blood pressure" factor, typically loading waist, BMI, SBP or MAP, and occasionally fasting insulin/HOMA-IR). The metabolic and obesity/blood pressure factors explained 26.5%-28.4% and 30.4%-31.9%, of the variance in metabolic risk factors changes, respectively. Reductions in BMI, waist circumference, and HOMA-IR (or fasting insulin) were central underlying features of cardiometabolic changes.

CONCLUSION

There were significant and favorable cardiometabolic risk factor changes to short-term weight-loss. A distinct clustering of cardiometabolic responses supports the etiological importance of both overall and central obesity and insulin resistance in the modification of cardiometabolic risk in obese youths.

Ability among adolescents for the metabolic syndrome to predict elevations in factors associated with type 2 diabetes and cardiovascular disease: data from the national health and nutrition examination survey 1999-2006

OBJECTIVE

The aim of this study was to compare currently proposed sets of pediatric metabolic syndrome criteria for the ability to predict elevations in "surrogate" factors that are associated with metabolic syndrome and with future cardiovascular disease and type 2 diabetes mellitus. These surrogate factors were fasting insulin, hemoglobin A1c (HbA1c), high-sensitivity C-reactive protein (hsCRP), and uric acid.

METHODS

Waist circumference (WC), blood pressure, triglycerides, high-density lipoprotein cholesterol (HDL-C), fasting glucose, fasting insulin, HbA1c, hsCRP, and uric acid measurements were obtained from 2,624 adolescent (12-18 years old) participants of the 1999-2006 National Health and Nutrition Examination Surveys. We identified children with metabolic syndrome as defined by six commonly used sets of pediatric metabolic syndrome criteria. We then defined elevations in the surrogate factors as values in the top 5% for the cohort and calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for each set of metabolic syndrome criteria and for each surrogate factor.

RESULTS

Current pediatric metabolic syndrome criteria exhibited variable sensitivity and specificity for surrogate predictions. Metabolic syndrome criteria had the highest sensitivity for predicting fasting insulin (40-70%), followed by uric acid (31-54%), hsCRP (13-31%), and HbA1c (7-21%). The criteria of de Ferranti (which includes children with WC >75(th) percentile, compared to all other sets including children with WC >90(th) percentile) exhibited the highest sensitivity for predicting each of the surrogates, with only modest decrease in specificity compared to the other sets of criteria. However, the de Ferranti criteria also exhibited the lowest PPV values. Conversely, the pediatric International Diabetes Federation criteria exhibited the lowest sensitivity and the highest specificity.

CONCLUSIONS

Pediatric metabolic syndrome criteria exhibit moderate sensitivity for detecting elevations in surrogate factors associated with metabolic syndrome and with risk for future disease. Inclusion of children with more modestly elevated WC improved sensitivity.

Is impaired energy regulation the core of the metabolic syndrome in various ethnic groups of the USA and Taiwan?

BACKGROUND

The metabolic syndrome (MetS) concept is widely used in public health and clinical settings without an agreed pathophysiology. We have re-examined the MetS in terms of body fuels, so as to provide a coherent cross-cultural pathogenesis.

METHODS

National Health and Nutrition Examination Survey (NHANES 2001-2) with n = 2254 and Taiwanese National Health Interview Survey (NHIS) sub-set for hypertension, hyperglycemia and hyperlipidemia assessment (TwSHHH 2002), n = 5786, were used to compare different ethnicities according to NCEP-ATPIII (NCEP-tw) criteria for METS. Exploratory factor analysis (EFA) using principal components (PC) was employed to differentiate and unify MetS components across four ethnicities, gender, age-strata, and urban-rural settings.

RESULTS

The first two factors from the PC analysis (PCA) accounted for from 55.2% (non-Hispanic white) to 63.7% (Taiwanese) of the variance. Rotated factor loadings showed that the six MetS components provided three clusters: the impaired energy regulation (IER) components (waist circumference, WC, fasting triglycerides, TG, and fasting plasma glucose, FPG), systolic and diastolic blood pressures (BPs), and HDL-cholesterol, where the IER components accounted for 25-26% of total variance of MetS components. For the three US ethnic subgroups, factor 1 was mainly determined by IER and HDL-cholesterol, and factor 2 was related to the BP components. For Taiwanese, IER was determinant for both factors, and BPs and HDL-cholesterol were related to factors 1 and 2 respectively.

CONCLUSIONS

There is a MetS core which unifies populations. It comprises WC, TG and FPG as a core, IER, which may be expressed and modulated in various second order ways.

Validity of a single-factor model underlying the metabolic syndrome in children: a confirmatory factor analysis

OBJECTIVE

We used confirmatory factor analysis to test whether a single factor might explain the clustering of the metabolic syndrome (MS) components in children.

RESEARCH DESIGN AND METHODS

We studied 1,020 children aged 10-13 years from 20 schools in Cuenca, Spain. The single-factor model included: waist circumference (WC), fasting insulin, triglyceride to HDL cholesterol ratio (Triglyl/HDL-C), and mean arterial pressure (MAP). The standardized scores of the four variables in the model were used to develop a continuous MS index.

RESULTS

Factor loadings were 0.67 for WC, 0.68 for fasting insulin, 0.57 for Triglyl/HDL-C, and 0.37 for MAP. The single-factor model also showed a good fit to the data. As compared with Adult Treatment Panel III criteria, the MS index showed strong validity in the diagnosis of MS (area under the receiver operating characteristic curve = 0.98, 95% CI 0.96-0.99).

CONCLUSIONS

A single underlying factor has acceptable validity to represent MS in children.

Underdiagnosis of Metabolic Syndrome in Non-Hispanic Black Adolescents: A Call for Ethnic-Specific Criteria

Childhood obesity is a risk factor for the development of both type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD). One marker that can be used to predict T2DM is the metabolic syndrome (MetS). MetS, a cluster of cardiovascular factors associated with insulin resistance, is defined by central obesity, impaired fasting glucose, hypertension, elevated triglycerides (TG), and low levels of high-density lipoprotein cholesterol. Some have advocated using a diagnosis of MetS to trigger increased intervention in children. However, ethnic differences in MetS may hamper identification of at-risk children. For example, non-Hispanic blacks are diagnosed with MetS less frequently than non-Hispanic whites, despite having higher rates of T2DM and CVD. These differences in MetS are predominantly due to a low frequency of hypertriglyceridemia in non-Hispanic blacks. Compared with non-Hispanic whites and Mexican Americans, non-Hispanic blacks have lower TG levels at baseline but exhibit worsening insulin resistance with increasing TG. Therefore "normal" TG levels appear to be falsely reassuring among insulin-resistant non-Hispanic blacks. Ethnic-specific tools may be needed to more accurately predict risk for T2DM and CVD in minorities.

Screening of metabolic syndrome in obese children: a primary care concern

OBJECTIVE

To determine the prevalence of metabolic syndrome (MS) in a primary care pediatric setting and to collect clinical and biochemical data, allowing for a prediction of its presence in a supposedly healthy population.

METHODS

Belonging to a pediatric population followed by pediatricians of the Italian National Health Service, 415 subjects with obesity as a unique selection criterion were enrolled. The entire cohort was screened for MS, which was defined as the presence of at least 2 other findings out of obesity: fasting hyperglycemia, low levels of high-density lipoproteins cholesterol, hypertriglyceridemia, and hypertension.

RESULTS

The overall prevalence of MS was 30.8%. Major findings (out of obesity) were low high-density lipoproteins cholesterol levels (46.2%), hypertension (23.6%), hypertriglyceridemia (22.2%), and fasting hyperglycemia (16.6%). Waist-to-height ratio was the only clinical parameter directly related to MS, with the same predictive power of insulin resistance.

CONCLUSIONS

Metabolic syndrome can be present in a significant percentage of "healthy" obese children, and a simple clinical parameter could identify at-risk subjects. This observation justifies the development and implementation of pediatric networks for obesity screening programs.

Stability of the factor structure of the metabolic syndrome across pubertal development: confirmatory factor analyses of three alternative models

OBJECTIVE

To test the fit and stability of 3 alternative models of the metabolic syndrome's factor structure across 3 developmental stages.

STUDY DESIGN

With data from the Fels Longitudinal Study, confirmatory factor analyses tested 3 alternative models of the factor structure underlying relationships among 8 metabolic syndrome-associated risks. Models tested were a 1-factor model (A), a 4-factor model (B), and a second-order latent factor model (C). Developmental stages assessed were prepuberty (ages 8-10), puberty (ages 11-15), and postpuberty (ages 16-20).

RESULTS

Convergence was achieved for all developmental stages for model A, but the fit was poor throughout (root mean square error of approximation > 0.1). Standardized factor loadings for waist circumference and body mass index were much stronger than those for fasting insulin at all 3 time points. Although prepuberty and postpuberty models converged for models B and C, each model had problems with Heywood cases. The puberty model did not converge for either model B or C.

CONCLUSIONS

The hypothetical structures commonly used to support the metabolic syndrome concept do not provide adequate fit in a pediatric sample and may be variable by maturation stage. A components-based approach to cardiovascular risk reduction, with emphasis on obesity prevention and control, may be a more appropriate clinical strategy for children and youth than a syndromic approach.

Nitric oxide and clustering of metabolic syndrome components in pediatrics

This study was performed to determine the risk factor pattern of the metabolic syndrome (MetS) in association with serum nitric oxide metabolites (NO(x)) in children and adolescents. The study included 851 children and adolescents, aged 4-19 years. The MetS was defined according to modified Adult treatment Panel III criteria. Cluster analysis was performed using principle components analysis with varimax orthogonal rotation to examine the risk factor pattern of the MetS. The prevalence of MetS was 10.8 and 10.0% in males and females, respectively. Age-and sex-adjusted odds ratio of having MetS was significantly higher in the upper quartile of NO(x) compared to the lower quartile (2.2, 95% CI: 1.1-4.7, p = 0.029). In the whole population, three factors were identified including blood pressure/obesity, lipid/obesity, and glucose/NO(x). Stratifying for sex, again three factors were retained; however, in males NO(x) was loaded in two factors. In conclusion, serum NO( x ) was associated and loaded with other MetS components in cluster analysis of metabolic risk factors.

Use of confirmatory factor analysis for the identification of new components of the metabolic syndrome: the role of plasminogen activator inhibitor-1 and Haemoglobin A1c

BACKGROUND AND AIM

This study was aimed to identify additional components of metabolic syndrome from a set of cardiovascular risk markers.

METHODS AND RESULTS

The homeostasis model assessment of insulin resistance (HOMA-IR), C-reactive protein, fibrinogen, plasminogen activator inhibitor-1 (PAI-1), von Willebrand factor, homocysteine, Haemoglobin A1c (HbA1c), and lipoprotein(a) were assessed in a population-based sample of 902 nondiabetic adult subjects. Those biomarkers that were associated with metabolic syndrome were evaluated by multiple regression analysis, along with other traditional cardiovascular risk factors. Confirmatory factor analysis (CFA) was used to test the hypothesis that both the established components of metabolic syndrome and the novel variables identified by the regression analysis were associated with a single underlying factor. HOMA-IR, PAI-1 and HbA1c were the only biomarkers independently related to metabolic syndrome. CFA validated a one-factor model that included these variables. Moreover, the indices of goodness of fit were better for this expanded model than those obtained for a previously validated one-factor model that was restricted to the conventional elements of the syndrome.

CONCLUSIONS

These findings show that PAI-1 and HbA1c are singularly linked to metabolic syndrome. Their elevation is presumably another manifestation of the same pathophysiological mechanism that underlies the recognized traits of the syndrome.

Homeostasis model assessment of insulin resistance*body mass index interactions at ages 9 to 10 years predict metabolic syndrome risk factor aggregate score at ages 18 to 19 years: a 10-year prospective study of black and white girls

If homeostasis model assessment of insulin resistance (HOMA-IR) interactions with obesity (body mass index [BMI]) at ages 9 to 10 years predict aggregate metabolic syndrome risk factors at ages 18 to 19 years, this would identify novel avenues for primary prevention of metabolic syndrome. Our hypothesis was that HOMA-IR*BMI interactions at ages 9 to 10 years would predict aggregate metabolic syndrome risk factor z scores at ages 18 to 19 years in prospective studies of a biracial population of girls. Two centers in the National Heart, Lung, and Blood Institute Growth and Health Study measured serum insulin and glucose at ages 9 to 10 years and 5 metabolic syndrome risk factors at ages 18 to 19 years (triglyceride, high-density lipoprotein cholesterol, systolic/diastolic blood pressure, waist circumference, and glucose). Studies in Cincinnati, OH, included girls from public and parochial schools in the inner city, within-city residential neighborhoods, and suburban areas; and those in Washington, DC, included girls from a health maintenance organization. Girls (194 white, 281 black) were studied first at ages 9 to 10 years, then at ages 18 to 19 years. We assessed HOMA-IR*BMI interactions at ages 9 to 10 years with race-specific z scores for 5 metabolic syndrome risk factors at ages 18 to 19 years. The lowest summed z score (mean +/- SD) was observed for subjects in the lowest tertiles for both HOMA-IR and BMI (-1.15 +/- 2.05), and the highest z score (2.58 +/- 3.11) was for subjects in the highest tertiles for both HOMA-IR and BMI (P < .0001). For the top BMI tertile, there was a progressive increase in z score (increasing risk of metabolic syndrome) as HOMA-IR increased. Interaction of BMI with HOMA-IR at ages 9 to 10 years predicts aggregate metabolic risk score at ages 18 to 19 years, with progressive risk increments within the top BMI tertile as HOMA-IR increases, opening avenues for intervention to reduce both BMI and HOMA-IR at ages 9 to 10 years as a primary approach to prevention of metabolic syndrome at ages 18 to 19 years.

Defining the metabolic syndrome in children and adolescents: will the real definition please stand up?

OBJECTIVES

To review the use of definitions of the metabolic syndrome in studies of children and adolescents and to review results from studies that used factor analysis to examine structure among cardiometabolic variables.

STUDY DESIGN

Literature review.

RESULTS

In 27 publications, authors used 40 unique definitions of the metabolic syndrome. Most of these definitions were adaptations of the adult definition developed by the National Cholesterol Education Program. In 11 studies that used exploratory factor analysis, the number of components ranged from 5 to 19, and the number of factors identified ranged from 1 to 5.

CONCLUSIONS

The use of multiple definitions of the metabolic syndrome argues strongly for the development of a standard pediatric definition.