Factor analysis of metabolic syndrome components in obese women

Factor Analysis of Metabolic Syndrome Components in a Population-Based Study in the South of Iran (PERSIAN Kharameh Cohort Study)

Background:

We aimed to estimate the exploratory factor analysis (EFA) of metabolic syndrome components based on variables including gender, BMI, and age groups in a population-based study with large sample size.

Methods:

This study was conducted on 10663 individuals 40-70 yr old in Phase 1 of the Persian Kharameh cohort study conducted in 2014–2017. EFA of the metabolic syndrome components, including waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), triglyceride (TG), high-density lipoprotein (HDL) and fasting blood sugar (FBS), was performed on all participants by gender, BMI (Body Mass Index), and age groups.

Results:

EFA results in the whole population based on eigenvalues greater than one showed two factors explaining 56.06% of the total variance. Considering factor loadings higher than 0.3, the first factor included: DBP, SBP, and WC, named as hypertension factor. The second factor also included TG, negative-loaded HDL, FBS, and WC, named as lipid factor. Almost similar patterns were extracted based on subgroups.

Conclusion:

MetS is a multi-factorial syndrome. Both blood pressure and lipid had a central role in this study and obesity was an important factor in both ones. Hypertension, having the highest factor loading, can generally be a valuable screening parameter for cardiovascular and metabolic risk assessment.

Analysis of Risk Factors in Patients with Subclinical Atherosclerosis and Increased Cardiovascular Risk Using Factor Analysis

Today, there are many parameters used for cardiovascular risk quantification and to identify many of the high-risk subjects; however, many of them do not reflect reality. Modern personalized medicine is the key to fast and effective diagnostics and treatment of cardiovascular diseases. One step towards this goal is a better understanding of connections between numerous risk factors. We used Factor analysis to identify a suitable number of factors on observed data about patients hospitalized in the East Slovak Institute of Cardiovascular Diseases in Košice. The data describes 808 participants cross-identifying symptomatic and coronarography resulting characteristics. We created several clusters of factors. The most significant cluster of factors identified six factors: basic characteristics of the patient; renal parameters and fibrinogen; family predisposition to CVD; personal history of CVD; lifestyle of the patient; and echo and ECG examination results. The factor analysis results confirmed the known findings and recommendations related to CVD. The derivation of new facts concerning the risk factors of CVD will be of interest to further research, focusing, among other things, on explanatory methods.

Partial Clinical Remission Reduces Lipid-Based Cardiovascular Risk in Adult Patients With Type 1 Diabetes

IMPORTANCE

Risk factors for atherosclerotic cardiovascular disease (ASCVD) are well established in type 2 diabetes (T2D), but not in type 1 diabetes (T1D). The impact of partial clinical remission (PR) on short-term ASCVD risk in T1D is unclear.

AIM

To investigate the impact of PR on the earliest ASCVD risk phenotype in adult T1D using factor analysis to compare the lipid phenotypes of T1D, T2D and controls after stratifying the T1D cohort into remitters and non-remitters.

SUBJECTS AND METHODS

A study of 203 adults subjects consisting of 86 T2D subjects, and 77 T1D subjects stratified into remitters (n=49), and non-remitters (n=28). PR was defined as insulin-dose adjusted HbA1c of ≤9, and obesity as a BMI ≥30 kg/m². Factor analysis was used to stratify the groups by ASCVD risk by factorizing seven lipid parameters (TC, LDL, HDL, non-HDL, TC/HDL, TG, TG/HDL) into 2 orthogonal factors (factor 1: TC*LDL; factor 2: HDL*TG) that explained 90% of the variance in the original seven parameters.

RESULTS

The analysis of individual lipid parameters showed that TC/HDL was similar between the controls and remitters (p=NS) but was significantly higher in the non-remitters compared to the remitters (p=0.026). TG/HDL was equally similar between the controls and remitters (p=NS) but was lower in the remitters compared to the non-remitters (p=0.007). TG was significantly lower in the remitters compared to T2D subjects (p<0.0001) but was similar between T2D subjects and non-remitters (p=NS). Non-HDL was significantly lower in the controls versus non-remitters (p=0.0003) but was similar between the controls and remitters (p=NS). Factor analysis showed that the means of factor 1 and factor 2 composite scores for dyslipidemia increased linearly from the controls, remitters, non-remitters to T2D, p value 0.0042 for factor 1, and <0.0001 for factor 2, with remitters having similar lipid phenotype as controls, while non-remitters were similar to T2D.

CONCLUSIONS

Partial clinical remission of T1D is associated with a favorable early lipid phenotype which could translate to reduced long-term CVD risk in adults.

Exploratory factor analysis of gender-based metabolic syndrome components: Results from the PERSIAN Guilan cohort study (PGCS)

BACKGROUND

One of the important issues related to metabolic syndrome is the underlying factor that remains controversial. The purpose of this study was estimating exploratory factor analysis (EFA) to reveal underlying factors that may explain the observed variants of metabolic syndrome (MetS) components in a population-based study.

METHODS

In this cross-sectional study, the target population consisted of 10,520 individuals aged 35-70 years from Phase 1 of the PERSIAN Guilan cohort study conducted between 2014 and 2017. Exploratory factor analysis (EFA) of components of the metabolic syndrome, including waist circumference (WC), systolic (SBP) and diastolic (DBP) blood pressure, triglyceride (TG), high-density lipoprotein (HDL) and fasting blood glucose (f-Glc) was performed across the population as well as by gender.

RESULTS

EFA results in the whole population based on eigen values > 1 showed two factors that explain 55.46% of the total variance. Taking factor loadings above 0.3, the first factor included systolic blood pressure, diastolic blood pressure, and waist circumference - called the blood pressure factor. Also, the second factor included triglycerides, negative-loaded HDL, and fasting blood glucose, which was named as lipid factor. In terms of gender, the first factor was similar to the whole population pattern, but in the second factor, in addition to the two components of blood lipids, waist size for men and in fasting blood glucose for women was launched.

CONCLUSION

Hypertension and lipids were substantial factors, and obesity is an important factor in this study. Hypertension, having the highest factor load, can generally be a valuable screening parameter for cardiovascular and metabolic risk assessment.

Metabolic syndrome, adherence to the Mediterranean diet and 10-year cardiovascular disease incidence: The ATTICA study

BACKGROUND AND AIMS

To better understand the metabolic syndrome (MS) spectrum through principal components analysis and further evaluate the role of the Mediterranean diet on MS presence.

METHODS

During 2001-2002, 1514 men and 1528 women (>18 y) without any clinical evidence of CVD or any other chronic disease, at baseline, living in greater Athens area, Greece, were enrolled. In 2011-2012, the 10-year follow-up was performed in 2583 participants (15% of the participants were lost to follow-up). Incidence of fatal or non-fatal CVD was defined according to WHO-ICD-10 criteria. MS was defined by the National Cholesterol Education Program Adult Treatment panel III (revised NCEP ATP III) definition. Adherence to the Mediterranean diet was assessed using the MedDietScore (range 0-55).

RESULTS

Five principal components were derived, explaining 73.8% of the total variation, characterized by the: a) body weight and lipid profile, b) blood pressure, c) lipid profile, d) glucose profile, e) inflammatory factors. All components were associated with higher likelihood of CVD incidence. After adjusting for various potential confounding factors, adherence to the Mediterranean dietary pattern for each 10% increase in the MedDietScore, was associated with 15% lower odds of CVD incidence (95%CI: 0.71-1.06). For the participants with low adherence to the Mediterranean diet all five components were significantly associated with increased likelihood of CVD incidence. However, for the ones following closely the Mediterranean pattern positive, yet not significant associations were observed.

CONCLUSION

Results of the present work propose a wider MS definition, while highlighting the beneficial role of the Mediterranean dietary pattern.

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.

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.

Apolipoproteins a-I and B as components of metabolic syndrome with respect to diabetes status: a factor analysis

BACKGROUND

The aim of the current study was to elucidate the clustering pattern of metabolic syndrome components along with apolipoproteins (Apo) A-I and B in diabetic and nondiabetic subjects.

METHODS

Factor analysis of conventional variables of metabolic syndrome [i.e., waist circumference, homeostasis model assessment of insulin resistance (HOMA-IR), triglycerides (TG), high-density lipoprotein-cholesterol (HDL-C), and systolic blood pressure (SBP)] with or without addition of Apo A-I and B was performed on 567 and 327 diabetic and nondiabetic subjects, respectively. Thereafter, analyses were repeated after substitution of TG and HDL-C by the TG-to-HDL-C ratio (TG/HDL-C).

RESULTS

Regarding conventional variables of metabolic syndrome, one or two underlying factors were identified, depending on whether lipid measures were entered as two distinct variables or as a composite measure. Apolipoproteins were consistent with a one-factor structure model of metabolic syndrome and did not change the loading pattern remarkably in nondiabetics. TG and HDL-C tended to cluster with Apo B and A-I, respectively, in different models.

CONCLUSION

The current study confirms that addition of Apo A-I and B is consistent with the one-factor model of metabolic syndrome and does not modify the loading pattern remarkably in nondiabetic subjects.

A comparison of different approaches to unravel the latent structure within metabolic syndrome

BACKGROUND

Exploratory factor analysis is a commonly used statistical technique in metabolic syndrome research to uncover latent structure amongst metabolic variables. The application of factor analysis requires methodological decisions that reflect the hypothesis of the metabolic syndrome construct. These decisions often raise the complexity of the interpretation from the output. We propose two alternative techniques developed from cluster analysis which can achieve a clinically relevant structure, whilst maintaining intuitive advantages of clustering methodology.

METHODS

Two advanced techniques of clustering in the VARCLUS and matroid methods are discussed and implemented on a metabolic syndrome data set to analyze the structure of ten metabolic risk factors. The subjects were selected from the normative aging study based in Boston, Massachusetts. The sample included a total of 847 men aged between 21 and 81 years who provided complete data on selected risk factors during the period 1987 to 1991.

RESULTS

Four core components were identified by the clustering methods. These are labelled obesity, lipids, insulin resistance and blood pressure. The exploratory factor analysis with oblique rotation suggested an overlap of the loadings identified on the insulin resistance and obesity factors. The VARCLUS and matroid analyses separated these components and were able to demonstrate associations between individual risk factors.

CONCLUSIONS

An oblique rotation can be selected to reflect the clinical concept of a single underlying syndrome, however the results are often difficult to interpret. Factor loadings must be considered along with correlations between the factors. The correlated components produced by the VARCLUS and matroid analyses are not overlapped, which allows for a simpler application of the methodologies and interpretation of the results. These techniques encourage consistency in the interpretation whilst remaining faithful to the construct under study.

Prevalence of the metabolic syndrome and its components among obese men and women in Italy

OBJECTIVE

Assessment of the prevalence of the metabolic syndrome (MetS) and its components in Italian obese individuals.

METHODS

Cross-sectional estimate of MetS prevalence using the IDF definition in 635 obese (BMI ≥ 35 kg/m(2)) individuals (286 men, 349 women) aged 19-78 years hospitalised for mass excess treatment.

RESULTS

MetS prevalence was significantly (p < 0.001) higher in males (75.9%) than in females (61.9%), due to the increased prevalence of 4/5 involved abnormalities. A multivariate binary logistic regression analysis disclosed a contributory independent effect of ageing (p < 0.01-0.001), but not of BMI, whereas large waist circumference (p < 0.01) and high waist-to-hip ratio (p < 0.01) contributed to MetS prevalence only in women. Affected individuals were significantly older (males p = 0.022; females p < 0.001), affected men being younger than affected women (p < 0.01). The prevailing clinical picture included all abnormalities (21.2% in men, 22.2% in women); in minimal trait MetS (3/5 abnormalities), the prevailing combination was, beside central obesity, hypertension-hyperglycaemia in men (12.4%), and hypertension-dyslipidemia in women (19.4%).

CONCLUSIONS

MetS is a highly prevalent condition among Italian obese individuals. Prevalence and combinations of involved abnormalities differ considerably between genders and suggest a different pathophysiology of the MetS in men and women, with possible relevance for prevention and treatment of the condition.

Clustering of leptin and physical activity with components of metabolic syndrome in Iranian population: an exploratory factor analysis

Metabolic syndrome (MetS), manifested by insulin resistance, dyslipidemia, central obesity, and hypertension, is conceived to be associated with hyperleptinemia and physical activity. The aim of this study was to elucidate the factors underlying components of MetS and also to test the suitability of leptin and physical activity as additional components of this syndrome. Data of the individuals without history of diabetes mellitus, aged 25-64 years, from third national surveillance of risk factors of non-communicable diseases (SuRFNCD-2007), were analyzed. Performing factor analysis on waist circumference, homeostasis model assessment of insulin resistance, systolic blood pressure, triglycerides (TG) and high-density lipoprotein cholesterol (HDL-C) led to extraction of two factors which explained around 59.0% of the total variance in both genders. When TG and HDL-C were replaced by TG to HDL-C ratio, a single factor was obtained. In contrast to physical activity, addition of leptin was consistent with one-factor structure of MetS and improved the ability of suggested models to identify obesity (BMI≥30 kg/m2, P<0.01), using receiver-operator characteristics curve analysis. In general, physical activity loaded on the first identified factor. Our study shows that one underlying factor structure of MetS is also plausible and the inclusion of leptin does not interfere with this structure. Further, this study suggests that physical activity influences MetS components via modulation of the main underlying pathophysiologic pathway of this syndrome.

Clustering of metabolic syndrome components in a Middle Eastern diabetic and non-diabetic population

BACKGROUND

Metabolic syndrome (MetS) encompasses a cluster of coronary heart disease and diabetes mellitus risk factors. In this study, we aimed to elucidate the factors underlying the clustering of MetS components in diabetic and non-diabetic individuals.

METHODS

Factor analysis was performed on 2978 (1652 non-diabetic and 1326 diabetic) participants. Entering waist circumference, homeostasis model assessment of insulin resistance (HOMA-IR), triglycerides, high-density lipoprotein-cholesterol (HDL-C) and systolic blood pressure (SBP), we performed exploratory factor analysis in diabetic and non-diabetic individuals separately. The analysis was repeated after replacing triglycerides and HDL-C with triglycerides to HDL-C ratio (triglycerides/HDL-C). MetS was defined by either adult treatment panel III (ATPIII), international diabetes federation (IDF) criteria, or by the modified form of IDF using waist circumference cut-off points for Iranian population.

RESULTS

The selection of triglycerides and HDL-C as two distinct variables led to identifying two factors explaining 61.3% and 55.4% of the total variance in non-diabetic and diabetic participants, respectively. In both diabetic and non-diabetic subjects, waist circumference, HOMA-IR and SBP loaded on factor 1. Factor 2 was mainly determined by triglycerides and HDL-C. Factor 1 and 2 were directly and inversely associated with MetS, respectively. When triglycerides and HDL-C were replaced by triglycerides/HDL-C, one factor was extracted, which explained 47.6% and 38.8% of the total variance in non-diabetic and diabetic participants, respectively.

CONCLUSION

This study confirms that in both diabetic and non-diabetic participants the concept of a single underlying factor representing MetS is plausible.

Prevalence of the metabolic syndrome among extremely obese adolescents in Italy and Germany

Juvenile metabolic syndrome (MetS) is a growing major medical problem in industrialised countries. We estimated its prevalence among two similar clinic-based sequentially recruited cohorts of extremely obese adolescents (age: 12-18 years) from Italy (N=665, males=271, females=394) and Germany (N=661, males=261, females=400) using the recent IDF paediatric criteria. The prevalence of the MetS was 23.3% among the Italians and 40.4% among the Germans. A multivariate logistic regression revealed an increased risk related to age (adjusted odd ratio (AOR): 2.24; 95% confidence interval (CI): 1.59-3.16; p<0.001), BMI SDS (AOR: 3.61; 95% CI: 2.33-5.60; p<0.001), male gender (AOR: 2.36; 95% CI: 1.80-3.10; p<0.001), and in German adolescents (AOR: 2.56; 95% CI: 1.98-3.31; p<0.001). Among Italian adolescents having the MetS, 83% had 3 abnormalities, 16% had 4 abnormalities while less than 1% had all the 5 abnormalities. In the German cohort, 67%, 28% and 5% of affected individuals had 3, 4 and 5 abnormalities, respectively. These results indicate that MetS is highly prevalent among extremely obese adolescents, and suggest that (besides age, obesity and gender) national sociocultural factors, as alimentary trends, could be important. Further tools should be developed to understand international epidemiological differences concerning obesity and its comorbidities in relation to lifestyles in the countries of European Union.

Defining genetic determinants of the Metabolic Syndrome in the Framingham Heart Study using association and structural equation modeling methods

The Metabolic Syndrome (MetSyn), which is a clustering of traits including insulin resistance, obesity, hypertension and dyslipidemia, is estimated to have a substantial genetic component, yet few specific genetic targets have been identified. Factor analysis, a sub-type of structural equation modeling (SEM), has been used to model the complex relationships in MetSyn. Therefore, we aimed to define the genetic determinants of MetSyn in the Framingham Heart Study (Offspring Cohort, Exam 7) using the Affymetrix 50 k Human Gene Panel and three different approaches: 1) an association-based "one-SNP-at-a-time" analysis with MetSyn as a binary trait using the World Health Organization criteria; 2) an association-based "one-SNP-at-a-time" analysis with MetSyn as a continuous trait using second-order factor scores derived from four first-order factors; and, 3) a multivariate SEM analysis with MetSyn as a continuous, second-order factor modeled with multiple putative genes, which were represented by latent constructs defined using multiple SNPs in each gene. Results were similar between approaches in that CSMD1 SNPs were associated with MetSyn in Approaches 1 and 2; however, the effects of CSMD1 diminished in Approach 3 when modeled simultaneously with six other genes, most notably CETP and STARD13, which were strongly associated with the Lipids and MetSyn factors, respectively. We conclude that modeling multiple genes as latent constructs on first-order trait factors, most proximal to the gene's function with limited paths directly from genes to the second-order MetSyn factor, using SEM is the most viable approach toward understanding overall gene variation effects in the presence of multiple putative SNPs.

Does the DASH diet lower blood pressure by altering peripheral vascular function?

We tested whether lowering of blood pressure (BP) on the dietary approaches to stop hypertension (DASH) diet was associated with changes in peripheral vascular function: endothelial function, assessed by flow-mediated vasodilatation (FMD) of the brachial artery, and subcutaneous adipose tissue blood flow (ATBF). We also assessed effects on heart rate variability (HRV) as a measure of autonomic control of the heart. We allocated 27 men and women to DASH diet and control groups. We measured FMD, ATBF and HRV on fasting and after ingestion of 75 g glucose, before and after 30 days on dietary intervention, aiming for weight maintenance. The control group did not change their diet. The DASH-diet group complied with the diet as shown by significant reductions in systolic (P<0.001) and diastolic (P=0.005) BP, and in plasma C-reactive protein (P<0.01), LDL-cholesterol (P<0.01) and apolipoprotein B (P=0.001), a novel finding. Body weight changed by <1 kg. There were no changes in the control group. We found no changes in FMD, or in ATBF, in the DASH-diet group, although heart rate fell (P<0.05). Glucose and insulin concentrations did not change. In this small-scale study, the DASH diet lowered BP independently of peripheral mechanisms.

Empirical evidence for "syndrome Z": a hierarchical 5-factor model of the metabolic syndrome incorporating sleep disturbance measures

STUDY OBJECTIVE

Sleep disturbances have been associated with individual components of the metabolic syndrome ("syndrome X"), and, although the concept has been proposed, it is not known whether sleep disturbances actually cluster with features of the metabolic syndrome to produce a unifying trait, "syndrome Z". Therefore, we evaluated a second-order factor model, whereby syndrome Z was described by 5 first-order factors--insulin resistance, obesity, hypertension, dyslipidemia, and sleep disturbance--with the sleep disturbance factor defined using the apnea-hypopnea index, arousal index, percentage of sleep time with oxygen saturation less than 90%, and percentage of slow wave sleep.

DESIGN

Observational, cross-sectional study.

SETTING

Clinical research center.

PARTICIPANTS

Five hundred thirty-three adults from the Cleveland Family Sleep Study who underwent polysomnography and were not treated by continuous positive airway pressure.

MEASUREMENTS AND RESULTS

When modeling syndrome Z as a second-order factor unifying 5 first-order factors, we observed good overall model fit (chi2/df= 3.20; CFI = 0.96; RMSEA = 0.06; SRMR = 0.05) and found that obesity was the most important determining factor (standardized loading = 0.85 +/- standard error = 0.02; P < 0.01) followed by sleep disturbance (0.82 +/- 0.03; P < 0.01), insulin resistance (0.67 +/- 0.03; P < 0.01), hypertension (0.64 +/- 0.04; P < 0.01), and dyslipidemia (0.60 +/- 0.05; P < 0.01). Simultaneous multiple group analyses revealed that this model was essentially generalizable across age, race, and sex subgroups.

CONCLUSIONS

Our results demonstrate that sleep disturbance coaggregates with other metabolic features to represent a single unifying trait, syndrome Z. Although our model awaits validation in other populations, it provides a tool for better understanding the synergistic risk of syndrome Z, compared with syndrome X, on type 2 diabetes and cardiovascular disease in future studies.

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.

Five-year alterations in BMI are associated with clustering of changes in cardiovascular risk factors in a gender-dependant way: the Stanislas study

OBJECTIVE

The purpose of the present longitudinal study was to describe the associations between the 5-year changes in body mass index (BMI) and alterations in the clusters of metabolic syndrome (MS)-related factors.

METHODS

The study population comprised 1099 middle-aged adults drawn from the Stanislas study. Individuals were stratified into four groups according to the 5-year changes in BMI (weight loss (<0 kg/m(2)), and weight gain (0-1, 1-2 and >2 kg/m(2))). Changes in various MS-related variables and clusters were compared between groups: anthropometric indices, blood pressure, lipid and inflammatory markers, liver enzymes, uric acid and the five summary factors extracted by using factor analysis ('risk lipids', 'liver enzymes', 'inflammation', 'protective lipids' and 'blood pressure').

RESULTS

There was a strong linear trend between increasing BMI and worsening of risk lipids and blood pressure factors for both men and women (P<or=0.001). In men only, liver enzymes and protective lipids factors were significantly related to the 5-year gain of BMI (P<or=0.001), whereas inflammation factor positively increased across the four BMI-change groups, in women only. Interaction terms for sex were statistically significant for inflammation and liver enzymes clusters.

CONCLUSION

In our population, there was a strong linear trend between increasing BMI and worsening of various MS-related variables. More interestingly, the identification of five factors associated with BMI changes dependent to gender, support the hypothesis that weight gain, and probably obesity, trigger metabolic mechanisms that differ between men and women.