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

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.

Factor analysis for the clustering of cardiometabolic risk factors and sedentary behavior, a cross-sectional study

Background

Few studies have reported on the clustering pattern of CVD risk factors, including sedentary behavior, systemic inflammation, and cadiometabolic components in the general population.

Objective

We aimed to explore the clustering pattern of CVD risk factors using exploratory factor analysis to investigate the underlying relationships between various CVD risk factors.

Methods

A total of 5606 subjects (3157 male, 51.5±11.7 y/o) were enrolled, and 14 cardiovascular risk factors were analyzed in an exploratory group (n = 3926) and a validation group (n = 1676), including sedentary behaviors.

Results

Five factor clusters were identified to explain 69.4% of the total variance, including adiposity (BMI, TG, HDL, UA, and HsCRP; 21.3%), lipids (total cholesterol and LDL-cholesterol; 14.0%), blood pressure (SBP and DBP; 13.3%), glucose (HbA1C, fasting glucose; 12.9%), and sedentary behavior (MET and sitting time; 8.0%). The inflammation biomarker HsCRP was clustered with only adiposity factors and not with other cardiometabolic risk factors, and the clustering pattern was verified in the validation group.

Conclusion

This study confirmed the clustering structure of cardiometabolic risk factors in the general population, including sedentary behavior. HsCRP was clustered with adiposity factors, while physical inactivity and sedentary behavior were clustered with each other.

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.

Physical fitness and plasma leptin in women with recent gestational diabetes

Aims/Hypothesis

Low physical fitness (PF) is a risk factor for type 2 diabetes mellitus (T2D). Women with a history of gestational diabetes (GDM) are at risk for T2D at a young age, but the role of PF in this population is not clear. PF has also been found to correlate inversely with plasma leptin in previous studies. Here, we examine whether women who had GDM have lower PF than women after a normoglycemic pregnancy and, second, whether PF is associated with plasma leptin, independently of body fat mass.

Methods

Cross-sectional analysis of 236 participants in the PPSDiab Study (cohort study of women 3–16 months after delivery, 152 after gestational diabetes (pGDM), 84 after normoglycemic pregnancy (control subjects); consecutively recruited 2011–16); medical history, physical examination with bioelectrical impedance analysis (BIA), whole body magnetic resonance imaging (MRI) (n = 154), 5-point oral glucose tolerance test, cardiopulmonary exercise testing, clinical chemistry including fasting plasma leptin; statistical analysis with Mann–Whitney U and t -test, Spearman correlation coefficient, multiple linear regression.

Results

Women pGDM had lower maximally achieved oxygen uptake (VO_2peak/kg: 25.7(21.3–29.9) vs. 30.0(26.6–34.1)ml/min/kg; total VO_2peak: 1733(1552–2005) vs. 1970(1767–2238)ml/min; p<0.0001 for both), and maximum workload (122.5(105.5–136.5) vs. 141.0(128.5–159.5)W; p<0.0001). Fasting plasma leptin correlated inversely with PF (VO_2peak/kg ρ = -0.72 p<0.0001; VO_2peak ρ = -0.16 p = 0.015; max. load ρ = -0.35 p<0.0001). These associations remained significant with adjustment for body mass index, or for body fat mass (BIA and MRI).

Conclusions/Interpretation

Women with a recent history of GDM were less fit than control subjects. Low PF may therefore contribute to the risk for T2D after GDM. This should be tested in intervention studies. Low PF also associated with increased leptin levels–independently of body fat. PF may therefore influence leptin levels and signaling. This hypothesis requires further investigation.

The relationship between physical activity, restless legs syndrome, and health-related quality of life in type 2 diabetes

To evaluate the relationship between physical activity with co morbidities and health-related quality of life in type 2 diabetic patients with and without restless legs syndrome (RLS). This is an observational study, set at tertiary care diabetic outpatient clinic, where 200 consecutive type 2 diabetic patients and 47 controls participated. Physical activity level was established by the International Physical Activity Questionnaire (IPAQ) and RLS diagnosis and RLS severity were established using the criteria defined by the International Restless Legs Syndrome Study Group; excessive daytime sleepiness was evaluated by the Epworth Sleepiness Scale, quality of sleep by the Pittsburgh Sleep Quality Index and Health-Related Quality of Life by the Short-Form Health Survey (SF-36). Depressive symptoms were investigated by Beck Depression Inventory (BDI- II). Among all diabetic patients (58 % women, mean age 52.7 ± 5.7), disease duration varied from 1 to 30 years (11.7 ± 7.5). Diabetic patients had more hypertension (76 %), peripheral neuropathy (65 %), and depressive symptoms (31 %) than controls; no gender differences were found between cases with and without depressive symptoms. RLS patients (72 % female) had worse quality of sleep. With regards to the quality of life domains, more active RLS diabetic patients had better perception of functional capacity, physical limitation, pain, and general health state (p < 0.05). RLS symptom severity did not vary according to physical activity (IPAQ level). This study shows that the physical activity is associated with a better perception of functional capacity, physical limitation, and pain in diabetic patients with RLS; thus a more active lifestyle should be encouraged.

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.

Metabolic syndrome between two ethnic minority groups (Circassians and Chechens) and the original inhabitants of Jordan

The prevalence of metabolic syndrome is increasing worldwide and exhibits variation among ethnic groups. The objective of this study was to estimate and compare the prevalence of metabolic syndrome and its components between two ethnic groups (Circassians and Chechens) in Jordan and the original inhabitants of Jordan. Data were collected from a cross-sectional study of Circassian (n = 436), Chechen (n = 355), and Jordanian (n = 3234) population aged 18 years and older. Metabolic syndrome was defined according to International Diabetes Federation criteria. Age-standardized prevalence rate of metabolic syndrome was Jordanians 38.0 %, Circassians 32.0 %, and Chechens 33.7 %. Compared to Jordanians, both minority groups had lower means of body mass index, total cholesterol, fasting blood glucose, and triglycerides. The means of high-density lipoprotein and low-density lipoprotein were significantly higher among Circassians compared to Jordanians and Chechens. The odds of BMI defined by overweight and obesity and diabetes were less common among Circassians and Chechens compared to Jordanians. The prevalence of the metabolic syndrome and its individual components is relatively high in the three ethnic groups compared to world. Variation in components between groups may relate to ethnicity. Therefore, a community-based integrated approach is needed that would include behavioral, social changes that would lead to the prevention and treatment of the metabolic syndrome.

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 hypertriglyceridemic state increases high sensitivity C-reactive protein of Japanese men with normal glucose tolerance

Both fasting and postprandial hypertriglyceridemia have been identified as risk markers for cardiovascular disease. High-sensitivity C-reactive protein (hs-CRP), known to independently predict future cardiovascular disease, has also been reported to be a direct participant in the progression of atherosclerosis. We evaluated whether or not fasting and/or postprandial hypertriglyceridemia influence hs-CRP of men with normal glucose tolerance. According to the triglyceride (TG) level, measured before and 1 and 2 h after a meal tolerance test, subjects were classified into a normotriglyceridemic (NTG) group (n = 86), a postprandial hypertriglyceridemia (PHTG) group (n = 50), or a fasting hypertriglyceridemia (FHTG) group (n = 53). Hs-CRP and HOMA-R were significantly higher in the FHTG group than in the other groups (P < 0.01). The PHTG group had higher hs-CRP than the NTG group (P < 0.05). No significant differences in age, BMI, LDL cholesterol, or carotid intima-media thickness were found in comparison of the three groups. Multivariate linear regression analysis showed that the area under the TG curve (AUC-TG), HbA1c, and BMI were independently correlated with hs-CRP (P < 0.001, P = 0.016, P = 0.032, respectively). Our data suggests that a hypertriglyceridemic state is associated with hs-CRP irrespective of BMI, LDL-C, and HDL-C, indicating that hs-CRP might represent chronic inflammation induced by hypertriglyceridemia in Japanese men with normal glucose tolerance.

The underlying factor structure of National Institutes of Health Stroke scale: an exploratory factor analysis

The underlying structure of National Institutes of Health Stroke Scale (NIHSS) as the most widely used scale in clinical trials has been the focus of little attention. The aim of the current study was to elucidate the clustering pattern of NIHSS items in ischemic stroke patients. A series of 152 consecutive patients with first-ever ischemic strokes admitted to a university affiliated hospital were enrolled. NIHSS score was estimated on admission and correlation coefficients between its items were calculated. Further, exploratory factor analysis was used to study the clustering pattern of NIHSS items. Extinction neglect, visual field, and facial palsy were weakly associated with other NIHSS items. Factor analysis led to a four-factor structure. Factors 1 and 3 were determined by left brain function as items of right arm and leg motor, language and dysarthria loaded on both of them. By contrast, factor 2 reflected right brain involvement. Since visual field and ataxia loaded on factor 4, this factor was primarily associated with posterior strokes. Our study shows that a four-factor structure model is plausible for NIHSS. Further, for the first time, a single distinct factor is identified for posterior strokes.

Leptin cut-off values for determination of metabolic syndrome: third national surveillance of risk factors of non-communicable diseases in Iran (SuRFNCD-2007)

Leptin is strongly contributed to the clustering of metabolic syndrome (MetS) components and potentially can be regarded as a single predictor of MetS. This population-based study, for the first time, reports the diagnostic accuracy of different leptin cut-points for determining MetS. Further, the current study compares the predictive ability of the appropriate threshold of leptin with insulin resistance. Data of the individuals without history of known diabetes mellitus, aged 25-64 years, from the third national surveillance of risk factors of non-communicable diseases (SuRFNCD-2007) were analyzed. MetS was defined due to either adult treatment panel III (ATPIII) or the modified international diabetes federation (IDF) criteria. Receiver-operating characteristic (ROC) curves were depicted to define cut-off of serum leptin, using the maximum Youden index and the shortest distance methods. Further, the values of leptin cut-offs in prediction of MetS were compared with those of insulin resistance (defined as homeostasis model assessment of insulin resistance >1.775). In men, the optimal cut-offs of leptin for IDF- and ATPIII-defined MetS were 3.6 ng/ml (positive predictive value, PPV: 56.5%; negative predictive value, NPV: 72.7%) and 4.1 ng/ml (PPV: 49.6%; NPV: 78.1%), respectively. In women, the optimal threshold was equal to 11.0 ng/ml (PPV: 53.8%; NPV: 73.0% for IDF criteria and PPV: 60.1%; NPV: 64.9% for ATPIII criteria). The diagnostic accuracy of these values in identifying MetS was similar to that of insulin resistance. Therefore, leptin is comparable to insulin resistance in identifying MetS and can be used as single predictor of MetS.