Influence of body variables in the development of metabolic syndrome-A long term follow-up study

Lipoprotein profiles of fat distribution and its association with insulin sensitivity

BACKGROUND

Fat deposition is associated with adverse outcomes. Waist-to-hip (WHR) ratio is a simple feasible index to assess fat distribution. Lipoprotein particle composition in relation to WHR and to what extent their association is mediated by insulin sensitivity are less investigated.

METHODS

In 504 randomly recruited Flemish (mean age: 48.9 years; women: 51.6%), we analyzed the lipoprotein particle constitutions using nuclear magnetic resonance spectroscopy. WHR obesity described a WHR of ≥ 0.85 for women or 0.9 for men. Insulin sensitivity was evaluated by the homeostasis model assessment-estimated insulin resistance (HOMA-IR). SCORE-2 risk algorithm was applied to estimate 10-year cardiovascular risk. Statistical methods included multivariable-adjusted linear regression analysis, logistic regression analysis, and mediation analysis.

RESULTS

The prevalence of WHR obesity was 54.6%, approximately 3 times of BMI-determined obesity (19.1%). Individuals with WHR obesity had significantly higher metabolic complications, such as hypertension (57.1%), dyslipidemia (61.8%), and insulin resistance (14.2%). WHR and WHR obesity were positively associated with total very-low-density lipoprotein (VLDL) particle concentration, remnant cholesterol, and triglycerides, but were negatively associated with VLDL particle size (P ≤ 0.027), independent of body mass index and other covariates. WHR was inversely associated with total high-density lipoprotein (HDL) particle concentration, whereas WHR obesity was inversely associated with HDL cholesterol (P ≤ 0.039). Neither WHR nor WHR obesity was associated with the concentration of total low-density lipoprotein (LDL) particles, LDL particle size, and LDL cholesterol (P ≥ 0.089). In the mediation analysis, insulin sensitivity significantly mediated the effect of WHR on total VLDL particle concentration (mediation percentage: 37.0%), remnant cholesterol (47.7%), and HDL cholesterol (41.1%). Individuals with WHR obesity were at increased cardiovascular risk, regardless of LDL cholesterol (P ≤0.028). In WHR obesity, higher total VLDL particle concent36ration and remnant cholesterol, and lower HDL cholesterol were associated with an increased cardiovascular risk (P≤ 0.002).

CONCLUSIONS

Upper-body fat deposition was independently associated with an unfavorable lipoprotein profile, and insulin sensitivity significantly mediated this association. LDL cholesterol might underestimate lipid abnormality for people with upper-body obesity and lowering VLDL particles and remnant cholesterol might potentially reduce the residual cardiovascular risk.

Usefulness of the waist-to-height ratio for predicting cardiometabolic risk in children and its suggested boundary values

BACKGROUND & AIMS

Only limited information is available on the usefulness of the waist-to-height ratio (WHtR) as an abdominal obesity marker in children. Our aim was to compare the ability of a WHtR >90th percentile, a WHtR ≥0.50, a WHtR ≥0.55 and a BMI z-score ≥2 SD to predict cardiometabolic risk in children followed-up at different ages.

METHODS

We evaluated data from 660 children at 5, 8 and 11 years of age who participated in the Childhood Obesity Project trial in 5 European countries. We classified children with or without cardiometabolic (CMet) risk (yes vs. no) according to the presence of ≥2 parameters (blood pressure, HOMA-IR, triglyceride levels and high-density lipoprotein (HDL) cholesterol levels) ≥90th percentile.

RESULTS

The odds ratio for CMet risk in children at all followed-up ages was statistically significant for all measures. The OR for the WHtR≥0.55 cut-off was 29.1 (5.6, 151.7) at 5 years of age, 11.8 (4.1, 33.8) at 8 year of age and 3.6 (1.7, 7.7) at 11 years of age, compared to the WHtR<0.55 cut-off. The WHtR≥0.55 cut-off showed a higher OR at younger ages than the BMI z-score ≥2SD, WHtR ≥90th percentile and WHtR≥0.50 cut-offs and a higher positive predictive value (82% at 5 years of age compared to 55%, 36% and 41%, respectively).

CONCLUSION

A WHtR≥0.55 is a suitable cut-off for screening children at high cardiometabolic risk in the general young European population.

Prediction of Metabolic Syndrome in a Mexican Population Applying Machine Learning Algorithms

Metabolic syndrome is a health condition that increases the risk of heart diseases, diabetes, and stroke. The prognostic variables that identify this syndrome have already been defined by the World Health Organization (WHO), the National Cholesterol Education Program Third Adult Treatment Panel (ATP III) as well as by the International Diabetes Federation. According to these guides, there is some symmetry among anthropometric prognostic variables to classify abdominal obesity in people with metabolic syndrome. However, some appear to be more sensitive than others, nevertheless, these proposed definitions have failed to appropriately classify a specific population or ethnic group. In this work, we used the ATP III criteria as the framework with the purpose to rank the health parameters (clinical and anthropometric measurements, lifestyle data, and blood tests) from a data set of 2942 participants of Mexico City Tlalpan 2020 cohort, applying machine learning algorithms. We aimed to find the most appropriate prognostic variables to classify Mexicans with metabolic syndrome. The criteria of sensitivity, specificity, and balanced accuracy were used for validation. The ATP III using Waist-to-Height-Ratio (WHtR) as an anthropometric index for the diagnosis of abdominal obesity achieved better performance in classification than waist or body mass index. Further work is needed to assess its precision as a classification tool for Metabolic Syndrome in a Mexican population.

Cyclic nucleotide phosphodiesterases: New targets in the metabolic syndrome?

Metabolic diseases have a tremendous impact on human morbidity and mortality. Numerous targets regulating adenosine monophosphate kinase (AMPK) have been identified for treating the metabolic syndrome (MetS), and many compounds are being used or developed to increase AMPK activity. In parallel, the cyclic nucleotide phosphodiesterase families (PDEs) have emerged as new therapeutic targets in cardiovascular diseases, as well as in non-resolved pathologies. Since some PDE subfamilies inactivate cAMP into 5'-AMP, while the beneficial effects in MetS are related to 5'-AMP-dependent activation of AMPK, an analysis of the various controversial relationships between PDEs and AMPK in MetS appears interesting. The present review will describe the various PDE families, AMPK and molecular mechanisms in the MetS and discuss the PDEs/PDE modulators related to the tissues involved, thus supporting the discovery of original molecules and the design of new therapeutic approaches in MetS.

Impact of PPAR-Alpha Polymorphisms-The Case of Metabolic Disorders and Atherosclerosis

Peroxisome proliferator activated receptor α (PPARα) has the most relevant biological functions among PPARs. Activation by drugs and dietary components lead to major metabolic changes, from reduced triglyceridemia to improvement in the metabolic syndrome. Polymorphisms of PPARα are of interest in order to improve our understanding of metabolic disorders associated with a raised or reduced risk of diseases. PPARα polymorphisms are mainly characterized by two sequence changes, L162V and V227A, with the latter occurring only in Eastern nations, and by numerous SNPs (Single nucleotide polymorphisms) with a less clear biological role. The minor allele of L162V associates with raised total cholesterol, LDL-C (low-density lipoprotein cholesterol), and triglycerides, reduced HDL-C (high-density lipoprotein metabolism), and elevated lipoprotein (a). An increased cardiovascular risk is not clear, whereas a raised risk of diabetes or of liver steatosis are not well supported. The minor allele of the V227A polymorphism is instead linked to a reduction of steatosis and raised γ-glutamyltranspeptidase levels in non-drinking Orientals, the latter being reduced in drinkers. Lastly, the minor allele of rs4353747 is associated with a raised high-altitude appetite loss. These and other associations indicate the predictive potential of PPARα polymorphisms for an improved understanding of human disease, which also explain variability in the clinical response to specific drug treatments or dietary approaches.

The most appropriate cut-off point of anthropometric indices in predicting the incidence of metabolic syndrome and its components

INTRODUCTION

The association of individuals' anthropometric indices with their development of metabolic syndrome (MetS) has been investigated in several studies. Taking into account the ethnic differences, this study aimed to determine the most appropriate cut-off points of anthropometric indices in predicting the incidence of MetS and its components in Ahvaz.

METHODS

This study is part of a cohort study conducted at the Diabetes Research Center of Ahvaz Jundishapur University of Medical Sciences on a population of over 20 in Ahvaz during 2009-2014. Of the 592 patients, 505 patients who were not diagnosed with MetS in 2009, were entered into this study. The data analyzed involved demographic information including age and sex, anthropometric information including height, weight, waist circumference (WC), hip circumference (HC) and the ratios between them, laboratory data including blood levels of Triglyceride (TG), Fasting plasma glucose (FPG) and High-density lipoprotein cholesterol (HDL-C), and clinical data including systolic(S) and diastolic(D)blood pressure(BP). After 5 years, the subjects were re-evaluated for MetS based on the National Cholesterol Education Program - Adult Treatment Panel III (NCEP-ATP III) criteria and the most appropriate cut-off points of anthropometric indices for the prediction of the incidence of MetS using the Receiver Operative Characteristic (ROC) curves were obtained.

RESULTS

Waist-to-Height Ratio (WHtR) index with a cut-off point of 0.53 followed by WC with a cut-off point of 87.5 cm had the highest power to predict the incidence of MetS. The cut-off points of WC and Body mass index (BMI) were respectively 89.5 cm and 26 kg/m2 for men, and 83.5 cm and 27.5 kg/m2 for women. All anthropometric indices were able to predict the components of this syndrome (with the exception of low HDL-C). The cut-off point of WC in predicting High FBS, High TG and High BP was 84.5, 84.8, and 86.5 cm, respectively.

CONCLUSION

Overall, it seems that given its ease of measurement, the WC index is preferred to other indices for predicting the incidence of MetS and its components in clinical screening.

Obesity measured as percent body fat, relationship with body mass index, and percentile curves for Mexican pediatric population

In Mexico, the increase in childhood obesity is alarming. Thus, improving the precision of its diagnosis is expected to impact on disease prevention. We estimated obesity prevalence by bioimpedance-based percent body fat (%BF) and body mass index (BMI) in 1061 girls and 1121 boys, from 3 to 17 years old. Multiple regressions and area under receiver operating curves (AUC) were used to determine the predictive value of BMI on %BF and percentile curves were constructed. Overall obesity prevalence estimated by %BF was 43.7%, and by BMI it was 20.1%; it means that the diagnosis by BMI underestimated around 50% of children diagnosed with obesity by %BF (≥30% for girls, ≥25% for boys). The fat mass excess is further underestimated in boys than in girls when using the standard BMI classification. The relationship between %BF and BMI was strong in school children and adolescents (all cases R2>0.70), but not in preschool children (girls R2 = 0.57, boys R2 = 0.23). AUCs showed greater discriminative power of BMI to detect %BF obesity in school children and adolescents (all cases AUC≥0.90) than in preschool children (girls AUC = 0.86; boys AUC = 0.70). Growth percentile charts showed that girls aged 9-17 years and boys aged 8-17 years presented fat excess from the 50th percentile and above. We suggested to change the BMI cut-off for them, considering values at the 75th percentile as overweight, and values at the 85th percentile as obesity, as previously recommended for Mexican children. Improving obesity diagnosis will allow greater efficiency when searching for comorbidities in clinical practice.