Lipid accumulation product (LAP) as a criterion for the identification of the healthy obesity phenotype in postmenopausal women

Characteristics of the metabolically unhealthy phenotype in menopausal resistance training practitioners

Introduction

Objective: to evaluate clinical, metabolic and body characteristics related to the metabolically unhealthy phenotype (MUH) in menopausal women who practice resistance training (RT). Methods: cross-sectional study with a sample of 31 women. Clinical and metabolic variables were measured. Body adiposity was assessed by body mass index, waist circumference, visceral adiposity index (VAI) and lipid accumulation product (LAP). Body composition analysis was performed by DEXA. Results: the prevalence of the MH phenotype was 74.2 %. Metabolically healthy (MH) women were younger, had more years of RT practice, higher HDL-c levels and lower VAI and android/gynoid ratio (A/G) than the MUH women. Women with inadequacy of HDL-c, TG, A/G and VAI had 12.50 (95 % CI: 3.30-47.23), 4.83 (95 % CI: 2.37-9.85), 5.20 (95 % CI: 1.90-14.16) and 3.12 (95 % CI: 1.07-9.04) times greater prevalence of the MUH phenotype, respectively, than those with adequacy of these parameters. Binary logistic regression analysis demonstrated that age is a predictor of the MUH phenotype (OR = 1.254; 95 % CI: 1.00-1.56) and this variable showed correlation with TG, VAI and A/G. There was no association between thyrotropin and MUH phenotype in the present sample. Conclusion: age and visceral adiposity are predictors for the MUH phenotype in RT practitioners in menopause, which may initially be characterized by alterations in serum lipid profile.

Dose-Response Relationship of Resistance Training on Metabolic Phenotypes, Body Composition and Lipid Profile in Menopausal Women

The relationship between volume training of resistance training (RT), body composition and cardiometabolic profile in menopausal women is poorly understand. This study aimed to evaluate the dose−response relationship of RT on lipid profile, body composition and metabolic phenotypes in menopausal women. A total of 31 women were categorized according to different volume of RT. Body composition was evaluated by DEXA and the cardiometabolic risk by metabolic phenotypes and lipid profile. There was a higher frequency of metabolically unhealthy phenotype in women who practiced RT for less than two years and had a weekly frequency lower than three days a week (p > 0.05). Women with more than two years and a higher weekly frequency of RT had lower trunk fat mass than their counterparties (15.33 ± 7.56 versus 10.57 ± 4.87, p = 0.04; 16.31 ± 7.46 versus 10.98 ± 5.49, p = 0.03, respectively). There was an association between HDL-c and time of RT in years. A moderate correlation was identified between variables of body adiposity, time in years and weekly frequency of RT. The present study concludes that more time in years and weekly frequency of RT practice are associated with lower body adiposity in menopausal women, the first also being associated with HDL-c.

Polycystic ovary syndrome: clinical and laboratory variables related to new phenotypes using machine-learning models

PURPOSE

Polycystic Ovary Syndrome (PCOS) is the most frequent endocrinopathy in women of reproductive age. Machine learning (ML) is the area of artificial intelligence with a focus on predictive computing algorithms. We aimed to define the most relevant clinical and laboratory variables related to PCOS diagnosis, and to stratify patients into different phenotypic groups (clusters) using ML algorithms.

METHODS

Variables from a database comparing 72 patients with PCOS and 73 healthy women were included. The BorutaShap method, followed by the Random Forest algorithm, was applied to prediction and clustering of PCOS.

RESULTS

Among the 58 variables investigated, the algorithm selected in decreasing order of importance: lipid accumulation product (LAP); abdominal circumference; thrombin activatable fibrinolysis inhibitor (TAFI) levels; body mass index (BMI); C-reactive protein (CRP), high-density lipoprotein cholesterol (HDL-c), follicle-stimulating hormone (FSH) and insulin levels; HOMA-IR value; age; prolactin, 17-OH progesterone and triglycerides levels; and family history of diabetes mellitus in first-degree relative as the variables associated to PCOS diagnosis. The combined use of these variables by the algorithm showed an accuracy of 86% and area under the ROC curve of 97%. Next, PCOS patients were gathered into two clusters in the first, the patients had higher BMI, abdominal circumference, LAP and HOMA-IR index, as well as CRP and insulin levels compared to the other cluster.

CONCLUSION

The developed algorithm could be applied to select more important clinical and biochemical variables related to PCOS and to classify into phenotypically different clusters. These results could guide more personalized and effective approaches to the treatment of PCOS.

Metabolically healthy obesity: Is it really healthy for type 2 diabetes mellitus?

Metabolically healthy obese (MHO) individuals are reported to have a lower risk of developing cardiovascular diseases in comparison with individuals with metabolic syndrome. However, the association between MHO and type 2 diabetes (T2DM) is still controversial. Some studies indicated that MHO is a favorable phenotype for T2DM, but more studies showed that MHO individuals have an increased risk of developing T2DM compared with metabolically healthy normal-weight individuals, especially among those who would acquire metabolically unhealthy obesity. This has been supported by finding insulin resistance and low-grade inflammatory responses in MHO individuals with a tendency for impaired beta-cell dysfunction. Studies also showed that liver fat accumulation increased the risk of incidence of T2DM in MHO. Here, we reviewed current literature on the relationship between MHO and T2DM, discussed the determinants for the development of diabetes in MHO, and summarized the measures for the prevention of T2DM in MHO.

Children's Lipid Accumulation Product Combining Visceral Adiposity Index is a Novel Indicator for Predicting Unhealthy Metabolic Phenotype Among Chinese Children and Adolescents

PURPOSE

The predictive capacity between children's lipid accumulation product (CLAP) combining visceral adiposity index (VAI), CLAP, and VAI with metabolically unhealthy phenotype remained unclear. This study aimed to compare the ability of CLAP combining VAI, CLAP, VAI and traditional adiposity indicators (body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR) and waist-to-hip ratio (WHR)) to predict metabolically unhealthy phenotype among Chinese children and adolescents.

PATIENTS AND METHODS

In the cross-sectional study, 1714 children and adolescents aged 12 to 18 were selected by random cluster sampling, underwent a questionnaire survey, physical examination, biochemical tests and body composition was measured by bioelectrical impedance analysis (BIA). Participants were divided into four phenotypes according to BMI and metabolic syndrome components. The logarithmic CLAP (LnCLAP), VAI, BMI, WC, WHtR and WHR were standardized for sex and age using the z-score method (standardized variables: LnCLAP-z, VAI-z, BMI-z, WC-z, WHtR-z and WHR-z).

RESULTS

LnCLAP-z ≥ 1, VAI-z ≥ 1, WC-z ≥ 1, and WHR-z ≥ 1 increased the risk of metabolically unhealthy normal-weight phenotype (the OR and 95% CI were 4.18 (1.75-10.02), 24.05 (12.79-45.21), 6.17 (1.14-33.51), 2.69 (1.07-6.72), respectively), LnCLAP-z ≥ 1, VAI-z ≥ 1 and WC-z ≥ 1 increased the risk of metabolically unhealthy overweight or obese phenotype (the OR and 95% CI were 2.67 (1.40-5.09), 10.30 (3.03-35.03), 2.19 (1.18-4.09), respectively). The area under the ROC curve (AUC) for CLAP combining VAI in the prediction of the metabolically unhealthy phenotype were 0.837 (0.776-0.899) and 0.876 (0.834-0.918) for boys and girls with normal-weight, 0.853 (0.803-0.903) and 0.794 (0.711-0.878) for boys and girls with overweight and obese (all P < 0.001), which were higher than CLAP, VAI, BMI, WC, WHtR and WHR.

CONCLUSION

Among Chinese children and adolescents, CLAP combining VAI was a more effective indicator than CLAP, VAI and traditional adiposity indicators in predicting unhealthy metabolic phenotype.

Obesity and low levels of physical activity are associated with a decreased health-related quality of life in postmenopausal women: a Wroclaw pilot study

Background: Menopause is associated with numerous somatic dysfunctions, an increased risk of chronic diseases, and complications in the mental and social components of health that lower the quality of life (QoL). Obesity and related comorbidities affect over 60% of postmenopausal women in Poland. A significant role for systematic physical activity (PA) in the prevention of dysfunctions and chronic diseases, including obesity and mental disorders, has been observed previously. A low level of PA is observed across the Polish population, especially in postmenopausal women. Aim of the study: To examine QoL in postmenopausal women participating in a community health promotion program as it relates to obesity and levels of PA. Material and methods: The study sample consisted of 76 postmenopausal women (aged 65.75±5.14 years) participating in the Active Wrocław 55+ program. Before starting the program, anthropometric measurements were taken, and QoL and PA were assessed using the 36-Item Short Form Health Survey (SF-36) and the International Physical Activity Questionnaire-Short Form (IPAQ-SF), respectively. Results: Most women had a PA level above 600 MET -min/week (78.95%), and were overweight or obese (86.84%). A waist circumference over 80 cm, indicating an increased risk for metabolic syndrome, was observed in 85.89% of the participants. BMI and waist circumference negatively correlated with the level of PA (p=0.001 and p=0.017, respectively). Women exhibiting low levels of PA and higher BMIs showed a significantly lower QoL compared to those with higher PA and lower BMIs, particularly with regard to the physical domains of QoL. Conclusions: Obesity and a low level of PA are associated with a significant decline in the health-related QoL (especially in the PF and PCS domains) of postmenopausal women an urban setting.

Anthropometric indices obesity and cardiometabolic risk: is there a link?

Adipose tissue is currently regarded as a key organ for excess dietary lipids, which determine whether the body will maintain normal homeostasis or whether inflammation and insulin resistance will develop. In recent years, there is more information about novel prognostic models — the visceral adiposity index and the lipid accumulation product. The aim of this review was to analyze the results of studies examining the relationship between various indices of obesity and cardiometabolic risk. We analyzed 105 literature sources, 53 of which were ruled out, becausethe processes of interest were not described in detail or included anassessment of the relationship of various obesity indices with metabolic parameters. The results obtained indicate the advisability of using novel obesity indices, which have a good predictive ability and are simple and convenient to use. It is necessary to use additional methods of anthropometric and clinical examination in order to assess the metabolic phenotype of obesity, which will make it possible to stratify patients by the level of cardiometabolic risk.

Vitamin D and selected cytokine concentrations in postmenopausal women in relation to metabolic disorders and physical activity

Obesity and metabolic disturbances constitute significant health problems in elderly women. Due to the multifactorial background of these disorders, assessing the interaction between risk factors remains a significant part of prevention and health promotion. Studies have illustrated a relationship between low physical activity and vitamin D deficiency with obesity and its complications. Furthermore, vitamin D affects the production of adipokines and the inflammatory response in adipose tissue. The aim of our study was to determine the association between selected adipokines, vitamin D concentrations, physical activity (PA), and visceral adiposity index (VAI) in postmenopausal women. The study sample consisted of 318 ethnically homogenous postmenopausal women aged 50-60. Both anthropometric measurements (BMI, WC, WHR) and biochemical measurements (TC, HDL, LDL, TG, AIP, glucose, insulin, IL-6, TNF-α, adiponectin, leptin) were made, and PA by IPAQ were recorded. Body mass index (BMI), waist-to-hip ratio (WHR), HOMA, atherogenic index of plasma (AIP), and VAI were calculated using the standard formulas. We observed a negative correlation between BMI, WC, insulin, HOMA, and PA. We determined that there is a negative association between leptin and vitamin 25(OH)D concentrations (P = 0.007) and a positive association with adiponectin (P = 0.014). The results of the multiple linear regression analysis indicate that vitamin D and HOMA are independent factors that significantly affect leptin and adiponectin levels, contrary to VAI.

DXA-measured visceral fat mass and lean body mass reflect abnormal metabolic phenotypes among some obese and nonobese Chinese children and adolescents

BACKGROUND AND AIM

The exact constellation of body composition characteristics among metabolically unhealthy obese (MUO) and nonobese (MUNO) children and adolescents remains unclear. The purpose of this study was to identify the major body composition determinants of metabolically unhealthy phenotypes among Chinese children and adolescents.

METHODS AND RESULTS

We used data from a cross-sectional survey in 2015 that included 1983 children and adolescents aged 6-18 years. Subjects were classified into two phenotypes based on a combination of body mass index (BMI) and metabolic syndrome components. Body composition was measured by dual-energy X-ray absorptiometry (DXA). Among all boys and among adolescent boys, those with MUNO phenotypes displayed significantly higher indices of body composition except for fat mass (FM) percentage and trunk-to-legs FM ratio compared with the metabolically healthy nonobese phenotype (all P < 0.05). MUO individuals had higher arm FM, lean body mass (LBM), and trunk lean mass compared to metabolically healthy obese individuals (all P < 0.05). Visceral fat mass (VFM) and BMI were the major independent determinants of MUNO (VFM, 6- to 9-year-old boys, OR = 1.02, 95% CI = 1.00-1.03, P = 0.021; BMI, 6- to 9-year-old girls, OR = 1.90, 95% CI = 1.31-2.84, P = 0.001; and adolescent boys, OR = 1.34, 95% CI = 1.23-1.44, P < 0.001). LBM was the major independent predictor of MUO among adolescent boys (OR = 1.90, 95% CI = 1.03-1.17, P = 0.003).

CONCLUSIONS

Among children and adolescents, the metabolically unhealthy phenotype was associated with excess of body composition, but with significant differences observed based on age and sex. VFM and LBM derived by DXA can predict the metabolically unhealthy phenotype effectively in specific sex and age groups.

Is Lipid Accumulation Product Associated with an Atherogenic Lipoprotein Profile in Brazilian Subjects?

Background

Lipid accumulation product (LAP), a simple and low-cost tool, is a novel biomarker of central lipid accumulation and represents a potential surrogate marker for atherogenic lipoprotein profile. However, its association with lipoprotein subfractions has not been described in the literature.

Objective

To determine whether LAP index could be used as a marker of low- and high-density lipoprotein (LDL and HDL) size in Brazilian individuals.

Methods

This cross-sectional study included patients (n = 351) of both sexes and age between 30-74 years. Clinical and sociodemographic data and family history of diseases were evaluated. Lipoprotein size, and levels of total cholesterol (TC), lipoproteins, apolipoprotein AI and B (APO AI/APO B), glucose, insulin, insulin resistance index (HOMA-IR) and non-esterified fatty acids (NEFA) were assessed in blood samples. LAP was calculated by the formulas [(waist circumference_[cm]-58) × (triglycerides_[mmol/L]) for women and (waist circumference _[cm]-65) × (triglycerides _[mmol/L]) for men]. The association between LAP and metabolic parameters were tested by linear trend (general linear model, GLM test) before and after multiple adjustments for potential confounders (sex, age, smoking, statin, fibrate, and hypoglycemic drugs) at significant level p < 0.05.

Results

LAP was positively associated with TC, APO B, NEFA, glucose, insulin and HOMA-IR values, and negatively associated with HDL-C. Higher central lipid accumulation was corelated with higher percentage of intermediate HDL and of small LDL and HDL and less amount of large HDL. LDL size was also reduced in greater LAP index values. The negative impact of LAP was maintained after adjustment for multiple variables.

Conclusion

LAP was robustly associated with atherogenic profile of lipoprotein subfractions, independently of multiple confounders.

Haptoglobin levels, but not Hp1-Hp2 polymorphism, are associated with polycystic ovary syndrome

PURPOSE

Proteomic studies suggest an association between haptoglobin (Hp) and polycystic ovary syndrome (PCOS). Hp is a classic inflammatory marker and binds to the intravascular hemoglobin, avoiding the oxidative damages that can be caused by free hemoglobin. Inflammation and oxidative stress are important in the pathogenesis of the PCOS, one of the most frequent metabolic diseases in women.

METHODS

To validate these proteomic studies, we developed a controlled cross-sectional study that aimed to evaluate the Hp levels and allelic and genotypic frequencies of Hp1-Hp2 polymorphism in Brazilian women with PCOS. We also investigated the correlation between Hp levels and several important parameters in PCOS as follows: body mass index (BMI), waist circumference (WC), fasting glucose, post-prandial glucose, homeostatic model assessment (HOMA), lipid accumulation product (LAP), C-reactive protein (CRP), and metabolization test of tetrazolium salts (MTTs-serum antioxidant capacity).

RESULTS

Plasma Hp levels were higher in the PCOS group than in controls [8.20 (4.04) g/L; 7.98 (3.31) g/L; p = 0.018]. No significant difference was observed in the frequency of Hp1-Hp2 genotypes under additive, recessive, or dominant model of inheritance between the PCOS and the control groups. Plasma Hp levels did not differ according to the genotype. However, plasma Hp showed a negative correlation with MTT (r = - 0.383; p = 0.028), as well as a positive correlation with CRP (r = 0.361; p = 0.014) in the PCOS group.

CONCLUSION

Hp1-Hp2 polymorphism is not associated with PCOS but plasma Hp could be a potential biomarker for PCOS and its complications.