Waist circumference shows the highest predictive value for metabolic syndrome, and waist-to-hip ratio for its components, in Spanish adolescents

Predictive modeling the probability of suffering from metabolic syndrome using machine learning: A population-based study

Background

There is an increasing trend of Metabolic syndrome (MetS) prevalence, which has been considered as an important contributor for cardiovascular disease (CVD), cancers and diabetes. However, there is often a long asymptomatic phase of MetS, resulting in not diagnosed and intervened so timely as needed. It would be very helpful to explore tools to predict the probability of suffering from MetS in daily life or routinely clinical practice.

Objective

To develop models that predict individuals' probability of suffering from MetS timely with high efficacy in general population.

Methods

The present study enrolled 8964 individuals aged 40-75 years without severe diseases, which was a part of the REACTION study from October 2011 to February 2012. We developed three prediction models for different scenarios in hospital (Model 1, 2) or at home (Model 3) based on LightGBM (LGBM) technique and corresponding logistic regression (LR) models were also constructed for comparison. Model 1 included variables of laboratory tests, lifestyles and anthropometric measurements while model 2 was built with components of MetS excluded based on model 1, and model 3 was constructed with blood biochemical indexes removed based on model 2. Additionally, we also investigated the strength of association between the predictive factors and MetS, as well as that between the predictors and each component of MetS.

Results

In this study, 2714 (30.3%) participants suffer from MetS accordingly. The performances of the LGBM models in predicting the probability of suffering from MetS produced good results and were presented as follows: model 1 had an area under the curve (AUC) value of 0.993 while model 2 indicated an AUC value of 0.885. Model 3 had an AUC value of 0.859, which is close to that of model 2. The AUC values of LR model 1 and 2 for the scenario in hospital and model 3 at home were 0.938, 0.839 and 0.820 respectively, which seemed lower than that of their corresponding machine learning models, respectively. In both LGBM and logistic models, gender, height and resting pulse rate (RPR) were predictors for MetS. Women had higher risk of MetS than men (OR 8.84, CI: 6.70-11.66), and each 1-cm increase in height indicated 3.8% higher risk of suffering from MetS in people over 58 years, whereas each 1- Beat Per Minute (bpm) increase in RPR showed 1.0% higher risk in individuals younger than 62 years.

Conclusion

The present study showed that the prediction models developed by machine learning demonstrated effective in evaluating the probability of suffering from MetS, and presented prominent predicting efficacies and accuracies. Additionally, we found that women showed a higher risk of MetS than men, and height in individuals over 58 years was important factor in predicting the probability of suffering from MetS while RPR was of vital importance in people aged 40-62 years.

Diagnostic test accuracy of waist-to-height ratio as a screening tool for cardiovascular risk in children and adolescents: a meta-analysis

CONTEXT

Waist-to-height ratio (WHtR) is a controversial evaluation index of cardiovascular risk factors (CVRFs) in children and adolescents.

OBJECTIVE

To assess the accuracy of WHtR as a measure to screen for clusters of at least one CVRF (CVRF₁), two CVRFs (CVRF₂), and three CVRFs (CVRF₃) in different ages, sexes, regions and cut-offs.

METHODS

The PubMed, Web of Science, EBSCOhost, Springer, Taylor & Francis Online, Wiley Online Library, Wanfang, and CNKI databases were searched for eligible publications up to June 2021. The QUADAS-2 checklist was used to assess the methodology of the included studies.

RESULTS

Twenty-two studies that evaluated 85281 children and adolescents aged 5-19 years were included in the meta-analysis. The AUSROC values were 0.56 (95% CI: 0.54-0.57), 0.82 (95% CI: 0.81-0.83), and 0.89 (95% CI: 0.89-0.90) for CVRF₁, CVRF₂, and CVRF₃, respectively. Higher AUSROC values were found for adolescents (12-19 years), that is, 0.91 (95% CI: 0.88-0.93), 0.90 (95% CI: 0.87-0.92) for males, and 0.91 (95% CI: 0.90-0.91) for a cut-off of ≥ 0.51 in the identification of CVRF₃.

CONCLUSION

WHtR can be used as an accurate screening tool for CVRF₃ and CVRF₂ in children and adolescents, and it is recommended to select different cut-offs according to different ages, sexes, and regions.

The Effect of Obesity on the Waist Circumference Cut-Point Used for the Diagnosis of the Metabolic Syndrome in African Women: Results from the SWEET Study

Waist circumference (WC) is one of the diagnostic criteria for metabolic syndrome (MetS). However, studies have shown that the waist cut-point may be influenced by BMI. The aim of this study was to, therefore, determine whether the presence of obesity influences the WC cut-point used to diagnose MetS in sub-Saharan African women. The second aim was to determine whether calculated cut-points of other waist-related and dual-energy X-ray absorptiometry (DXA)-determined anthropometric measures used for the diagnosis of MetS were also influenced by BMI. Biochemical, simple anthropometric and dual-energy X-ray absorptiometry-derived anthropometric data were collected in 702 black South African women from the Study of Women Entering and in Endocrine Transition (SWEET). A receiver operating characteristic curve analysis was used to determine waist, waist-to-hip (WHR) and waist-to-height ratios, body shape index (ABSI), total body fat, trunk fat, and peripheral (arm + leg) fat cut-points for MetS (without waist) in subjects with BMI above or below the median value. The estimated WC cut-points (107 cm, 93.5 cm) for women with high BMI and low BMI, respectively, and the cut-points for the other anthropometric variables for the diagnosis of MetS were greater in high BMI women compared to low BMI women. The exceptions were WHR and ABSI, for which the cut-points were very similar in both BMI groups, and peripheral fat, where the cut-point was lower in the high BMI group. Logistic regression analysis demonstrated that WC was associated with a higher risk (odds ratio [95% CIs]: 1.07 [1.04, 1.10]; p < 0.0001), whilst hip was associated with a lower risk (0.97 [0.94, 0.99]; p = 0.02) for MetS. These data suggest that with increasing BMI, the higher levels of protective gluteofemoral fat lead to the requirement for higher WC cut-points for MetS diagnosis. The opposing associations of waist and hip with MetS risk make WHR a more appropriate variable for diagnosing MetS among African women as the WHR cut-point is less influenced by increasing BMI than is WC, which was also observed for ABSI.

Assessment of insulin resistance and metabolic syndrome in young reproductive aged women with polycystic ovarian syndrome: analogy of surrogate indices

BACKGROUND

Polycystic ovarian syndrome has emerged as a cardiometabolic disorder and aim of this study was to evaluate various surrogate indices and their diagnostic potential to determine the most convenient and cost-effective marker of IR, CVD, and MetS in these women.

MATERIALS AND METHODS

Ninety-five PCOS women and 45 age matched healthy women were enrolled. Measures included anthropometric and biochemical parameters, BMI, WHR, WHtR, BAI, VAI, LAP, HOMA-IR, and lipid profile.

RESULTS

LAP has highest AUC value 0.781 with cut-off value = 39.73 (sensitivity = 75% and specificity = 79.5%) for predicting IR and AUC value 0.83 with cut-off value = 35.63 (sensitivity = 94.4% and specificity = 77.3%) for predicting MetS in women with PCOS. LAP had statistically strong positive correlation with WC, BMI, WHR, fasting glucose, fasting insulin, HOMA-IR, TC, TG, and SBP.

CONCLUSIONS

LAP is a powerful and reliable marker for assessment of IR, CVD, and MetS risk in young Indian women with PCOS.

Body impedance analyzer and anthropometric indicators; predictors of metabolic syndrome

Aim

Metabolic syndrome is one of the outcomes of a sedentary lifestyle in the modern world. In this study, we want to introduce the predictors of metabolic syndrome using anthropometric indices and Bio-Electrical Impedance Analysis (BIA) test values.

Method

This cross-sectional study was performed on 2284 employees of Tehran University of Medical Sciences in different job categories. Metabolic syndrome was determined according to IDF criteria. Anthropometric dimensions, para-clinical tests, basic information were collected from the participants. Also, the body analysis of the participants was performed using a BIA method.

Result

The prevalence of metabolic syndrome in this study was 23.2% based on IDF criteria, which was 21% and 26.6% in men and women, respectively. The most important factor among the components of IDF criteria was HDL deficiency. In this study, neck circumference, fat mass, visceral fat, muscle mass percentage and waist to height ratio were observed as predictors of metabolic syndrome.

Conclusion

This study realized that there is association between fat mass, fat-free mass, visceral fat and muscle mass which all are some elements of body composition analysis and metabolic syndrome as a major health issue.

Effects of Lifestyle Intervention on Inflammatory Markers and Waist Circumference in Overweight/Obese Adults With Metabolic Syndrome: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

BACKGROUND

Physical inactivity and an imbalanced diet could lead to some cardio metabolic risk factors.

OBJECTIVE

The objective of this meta-analysis was to investigate the effects of lifestyle modification on inflammatory indicators and waist circumference (WC) in overweight/obese subjects with metabolic syndrome (MS).

DATA SOURCES

A systematic search was conducted in PubMed, CINAHL, MEDLINE, Cochrane, Google Scholar, and Web of Science.

STUDY SELECTION

The selection criteria were randomized controlled trials (RCTs) investigating the effects of lifestyle interventions on inflammation and WC from inception to 20 December 2020. The weighted mean difference (WMD) and 95% confidence interval (CI) between interventions were computed using a random or fixed-effects model.

RESULTS

Six RCTs (including 1246 MS patients who had, on average, overweight/obesity) met all inclusion criteria. Interventions lasted 6 to 12 months (2-5 sessions per week). Lifestyle intervention significantly reduced C-reactive protein (WMD: -0.52 mg/ml, 95% CI: -0.72, -0.33), IL-6 (WMD: -0.50 pg/ml, 95% CI: -0.56, -0.45), and increased adiponectin (WMD: 0.81 µg/ml, 95% CI, 0.64, 0.98). Moreover, lifestyle modification significantly decreased WC (WMD: -3.12 cm, 95% CI, -4.61, -1.62).

CONCLUSION

Our findings provide evidence that lifestyle alterations, including physical activity and diet, can lead to significant improvement in abdominal obesity, measured by WC and some inflammation markers among overweight/obese individuals with MS. Further high-quality research is needed to clarify the mechanisms underlying the effect of such interventions on this population's inflammatory markers.

Significance and agreement between obesity anthropometric measurements and indices in adults: a population-based study from the United Arab Emirates

BACKGROUND

The rates of overweight and obese adults in the United Arab Emirates (UAE) have increased dramatically in recent decades. Several anthropometric measurements are used to assess body weight status. Some anthropometric measurements might not be convenient to use in certain communities and settings. The objective of this study was to assess the agreement of four anthropometric measurements and indices of weight status and to investigate their associations with cardiometabolic risks.

METHODS

The study design was a cross-section population-based study. Adults living in the Northern Emirates were surveyed. Fasting blood samples, blood pressure readings and anthropometric measurements were also collected.

RESULTS

A total of 3531 subjects were included in this study. The prevalence of obesity/overweight was 66.4% based on body mass index (BMI), 61.7% based on waist circumference (WC), 64.6% based on waist-hip ratio (WHR) and 71% based on neck circumference (NC). There were moderate agreements between BMI and WC and between WC and WHR, with kappa (k) ranging from 0.41 to 0.60. NC showed poor agreement with BMI, WC and WHR, with k ranging from 0 to 0.2. Overweight and obesity based on BMI, WC and WHR were significantly associated with cardiometabolic risks.

CONCLUSION

Overall, there was a moderate to a poor agreement between BMI, WC, WHR and NC. Particularly, NC showed poor agreement with BMI, WC and WHR. BMI and WC showed better performance for identifying cardiometabolic risks than WHR and NC.

Performance of waist-to-height ratio as a screening tool for identifying cardiometabolic risk in children: a meta-analysis

OBJECTIVE

To provide the latest evidence of performance and robustness of waist-to-height ratio (WHtR) in discriminating clusters of cardiometabolic risk factors (CMRs) and promote WHtR in routine primary health care practice in children, a meta-analysis was used.

METHODS

Searches was performed in eight databases from inception to July 03, 2020. Inclusion criteria were: (1) observational study, (2) children and adolescents, (3) provided WHtR measurements, (4) had CMRs as outcomes, and (5) diagnostic studies. Exclusion criteria were: (1) non-original articles, (2) unable to extract 2 × 2 contingency tables, (3) not in English or Chinese language, (4) populations comprising clinical patients, or (5) duplicate articles. WHtR cutoff points, 2 × 2 contingency tables were extracted from published reports. Outcomes included: CMR clusters of at least three CMRs (CMR₃), two (CMR₂), one (CMR₁), and CMR components. Bivariate mixed-effects models were performed to estimate the summarised area under the curves (AUSROC) with 95% CIs and related indexes. We conducted subgroup analyses by sex and East Asian ethnicity.

RESULTS

Fifty-three observational studies were included. The AUSROC reached 0.91 (95% CI: 0.88-0.93), 0.85 (95% CI: 0.81, 0.88) and 0.75 (95% CI: 0.71, 0.79) for CMR₃, CMR₂, and CMR₁, respectively. The pooled sensitivity and specificity for CMR₃ reached 0.84 and exceeded 0.75 for CMR₂. For CMR₁, the sensitivity achieved 0.55 with 0.84 for specificity. We had similar findings for our subgroup and sensitivity analyses.

CONCLUSIONS

WHtR shows good and robust performance in identifying CMRs clustering across racial populations, suggesting its promising utility in public health practice globally.

Comparison of visceral, general and central obesity indices in the prediction of metabolic syndrome in maintenance hemodialysis patients

PURPOSE

We aimed to compare the predictive ability of the anthropometric indices reflecting general, central and visceral obesity for identification of metabolic syndrome (MetS) in maintenance hemodialysis (MHD) patients.

METHODS

A multicenter, cross-sectional study that consisted of 1603 adult MHD patients (54.6 ± 16 years) was conducted in Guizhou Province, Southwest China. Eight anthropometric obesity indexes including body mass index (BMI), waist circumference (WC), waist-height ratio (WHtR), conicity index (Ci) and visceral adiposity index (VAI), lipid accumulation product (LAP), a body shape index (ABSI) and body roundness index (BRI) were recorded. MetS was defined based on the criteria of the International Diabetes Federation. Participants were categorized into four groups according to quartiles of different obesity indices. Binary logistic regression analyses were used to evaluate the associations between the eight obesity parameters and MetS. Receiver operator curve (ROC) analyses were used to identify the best predictor of MetS.

RESULTS

The eight anthropometric obesity indexes were independently associated with MetS risk, even after adjustment for age, sex, educational status and history of smoking. The ROC analysis revealed that all the eight obesity indices included in the study were able to discriminate MetS [all area under the ROC curves (AUCs) > 0.6, P < 0.05]. LAP showed the highest AUC and according to the maximum Youden indexes, the cut off values for men and women were 27.29 and 36.45, respectively. The AUCs of LAP, VAI, ABSI, BRI, WC, WHtR, Ci and BMI were 0.88, 0.87, 0.60, 0.78, 0.79, 0.78, 0.69 and 0.76 for men, and 0.87, 0.85, 0.65, 0.79, 0.81, 0.79, 0.73 and 0.76 for women, respectively. There was no significant difference in the AUC value between LAP and VAI, BRI/WHtR and BMI in men and between BRI/WHtR and BMI in women. The AUC value for WHtR was equal to that for BRI in identifying MetS.

CONCLUSIONS

Visceral obesity marker LAP followed by VAI was the most effective predictor of MetS while ABSI followed by CI was the weakest indicator for the screening of MetS in MHD patients. BRI could be an alternative obesity measure to WHtR in assessment of MetS. LAP may be a simple and useful screening tool to identify individuals at high risk of MetS particularly in middle-aged and elderly Chinese MHD patients.

LEVEL OF EVIDENCE

Level V, descriptive study.

Prediction modelling of 1-year outcomes to a personalized lifestyle intervention for Canadians with metabolic syndrome

Metabolic syndrome (MetS) comprises a cluster of risk factors that includes central obesity, hypertension, dyslipidemia, and impaired glucose homeostasis. Although lifestyle interventions reduce MetS risk, not everyone responds to the same extent. The primary objective of this study was to identify variables that could predict 1-year changes in MetS risk in individuals participating in the Canadian Health Advanced by Nutrition and Graded Exercise (CHANGE) program. Participants were allocated into training (n = 157) and test (n = 29) datasets by availability of genetic data. A linear mixed-effect model revealed that age, medication, fasting glucose, triglycerides, high-density lipoprotein cholesterol, waist circumference, systolic blood pressure, and fibre intake were associated with continuous MetS (cMetS) score across all time points. Multiple linear regressions were then used to build 2 prediction models using 1-year cMetS score as the outcome variable. Model 1 included only baseline variables and was 38% accurate for predicting cMetS score. Model 2 included both baseline variables and the 3-month change in cMetS score and was 86% accurate. As a secondary objective, we also examined if we could build a model to predict a person's categorical response bin (i.e., positive responder, nonresponder, or adverse responder) at 1 year using the same variables. We found 72% concordance between predicted and observed outcomes. These various prediction models need to be further tested in independent cohorts but provide a potentially promising new tool to project patient outcomes during lifestyle interventions for MetS. Novelty Short-term changes in cMetS score improve prediction model performance compared with only baseline variables. Predictive models could potentially facilitate clinical decision-making for personalized treatment plans.

Association of anthropometric indicators to evaluate nutritional status and cardiometabolic risk in Mexican teenagers

Introduction

Introduction: anthropometric indicators (AIs) such as waist circumference (WC), body mass index (BMI), waist/hip index (WHpI), waist/height index (WHtI) and body fat percentage (BFP) are useful tools for the diagnosis of nutritional status (NS) in adolescents. Each of these parameters has advantages and disadvantages. The purpose of the present study was to analyze the association of these AIs (WC, BMI, WHpI, WHtI, and BFP) to evaluate nutritional status and estimate the cardiometabolic risk (CMR) in Mexican adolescents. Material and method: in a cross-sectional descriptive study, the NS was analyzed through various AIs and CMR with the WHtI criteria. Nine hundred and seventeen adolescents between 15 and 17 years old participated in the study, of whom 488 (52.9%) were female and 429 (47.1%) male, all students of middle school in Tuxtla Gutiérrez, Chiapas, Mexico. Results and conclusion: women presented a higher prevalence of obesity according to most indicators. The WHtI was the parameter that detected the highest prevalence of obesity (31%), correlating with the BMI and the BFP. Moreover, there was evidence of a significant relation between NS (assessed by all the anthropometric indicators) and CMR. The WHtI could be considered as an adequate tool for the diagnosis of obesity associated with CMR in adolescents.

Value of appendicular skeletal muscle mass to total body fat ratio in predicting obesity in elderly people: a 2.2-year longitudinal study

BACKGROUND

Obesity is a disease characterized by much fat accumulation and abnormal distribution, which was related to cardiovascular diseases, diabetes mellitus (DM) and muscular skeletal diseases. The aim of this study was to evaluate the usefulness of appendicular skeletal muscle mass to total body fat ratio (ASM/TBF) in screening for the risk of obesity in elderly people.

METHODS

A prospective study was carried out with 446 participants (non-obese elderly people with body mass index (BMI) < 28 kg/m²) who underwent baseline and an average around 2.2-year follow-up health check-up examinations.

RESULTS

The mean age at baseline was 63.6 years. The incidence of new obesity was 5.4% during follow-up. Linear regression demonstrated that baseline ASM/TBFs were negatively correlated with follow-up BMIs in both men and women (β = - 1.147 (- 1.463--0.831) for men and - 4.727 (- 5.761--3.692) for women). The cut-off points of baseline ASM/TBF in elderly people for obesity were 1.24 in men and 0.90 in women which were identified by Classification and Regression Tree (CART). Logistic regression showed that both men and women with decreased ASM/TBF had higher risks of obesity over the follow-up period (Relative Risk (RRs) = 5.664 (1.879-17.074) for men and 34.856 (3.930-309.153) for women).

CONCLUSIONS

Elderly people with a low ASM/TBF had a higher risk of new obesity, which suggested that ASM/TBF should be considered in obesity management in the elderly.

Tri-ponderal mass index and body mass index in prediction of pediatric metabolic syndrome: the CASPIAN-V study

Objective Body mass index (BMI) and tri-ponderal mass index (TMI) are anthropometric measures to evaluate body adiposity in the various age groups. The present study aims to compare the predictive value of TMI and BMI for metabolic syndrome (Mets) in children and adolescents of both genders. Subjects and methods A cross-sectional study conducted on 3731 Iranian children and adolescents aged 7-18 years obtained from the fifth survey of 'Childhood and Adolescence Surveillance and Prevention of Adult Non-communicable Disease' (CASPIAN-V) study. The predictive value of BMI and TMI for MetS were determined using Receiver-operator curves. Logistic regression analysis was used to assess the relationship between these indices with MetS. Results 52.6% of participants were boys. The mean (standard deviations) age for boys and girls were 12.62 (3.02) and 12.25 (3.05) years, respectively. In boys, the area under the curve (AUC) of TMI was greater than BMI for all age groups. AUC of TMI was also greater than BMI for age group of 11-14 years (AUC = 0.74; 95% CI (0.67, 0.81)) in girls. Furthermore, our findings showed that odds ratio of Mets for TMI was greater than BMI in age groups of 11-14 years (OR = 1.33 vs 1.22) and 15-18 years (1.16 vs 1.15) in girls and boys, respectively. Conclusion TMI and BMI had moderate predictive value for identifying MetS. However, TMI was a better predictor of MetS than BMI in both genders, especially in age groups of 11-14 and 15-19 years for girls and boys.

Effects of diet versus diet plus aerobic and resistance exercise on metabolic syndrome in obese young men

Background

Diet and physical activity are the most commonly recommended strategies for preventing and treating metabolic syndrome (MetS). This randomized trial aims to examine the effectiveness of a weight reduction intervention based on caloric restriction, low-impact aerobics (LIA), and a resistance-training program in improving body composition, metabolic parameters and cardiovascular disease (CVD) risk factors among obese students diagnosed with MetS.

Methods

In all, 23 male participants, aged 19–24 years, were randomly introduced to a dieting program (the diet group, or DG = 09) or to dieting associated with a supervised physical training program (the diet plus training group, or DTG = 14). Before and after the intervention, the participants’ anthropometric measures and cardiovascular disease risk factors were assessed.

Results

Following the diet-based intervention, significant improvements were noted in BMI (p = 0.39), PBF (p = 0.022) and LDL-c (p = 0.024). However, in response to the diet plus aerobic and resistance exercise intervention, obese participants had significant reductions in body weight (p = 0.018), WC (p = 0.042), BMI (p = 0.001), BFP (p < 0.001), DBP (p = 0.013), SBP (p = 0.016), TG level (p = 0.026), TC (p = 0.016), LDL-c (p = 0.001) and VLDL-c (p = 0.026). Notable differences were also observed between groups in terms of changes in WC (p = 0.003), BFP (p = 0.05), WHR (p = 0.029), FBG level (p = 0.022), TG level (p = 0.001), TC (p = 0.006), LDL-c (p = 0.014) and VLDL-c (p < 0.001).

Conclusion

Diet-based intervention could be an effective tool in reducing body composition and some MetS components. However, adding three weekly aerobic and resistance-training sessions to the dieting program may deliver better outcomes, particularly in terms of reducing WC, BFP, WHR, FBG level, TG level, TC, LDL-c, and VLDL-c.

Application of conicity index adjusted total body fat in young adults-a novel method to assess metabolic diseases risk

The aim of the study was to evaluate the usefulness of conicity index (CI) adjusted total body fat (TBF), which was defined as TBF/CI, in various metabolic diseases in young adults. A cross-sectional study was carried out in Chinese PLA General Hospital and a total of 1365 young adults (age 20–40 years) who underwent a health check-up examination were finally included in the analysis from February 2016 to 2017. Linear Regression and logistic regression were used to further examine relationship between the index and metabolic diseases. The average age was 34.5 years. Odds Ratios (ORs) for the risk of metabolic diseases increased from the lowest to highest TBF/CI quartile (all P trends < 0.001). Young adults with increased TBF/CI had higher risk of hyperhomocysteinemia (Hhcy) (OR = 1.528, 95% confidence interval = 1.057–2.209). There was a 1.407 increase in the odds of obesity, a 1.112 increase in the odds of hyperlipidemia (HLP) and a 1.094 increase in the odds of diabetes mellitus (DM) per standard deviation (SD) increase in TBF/CI (all P < 0.001). TBF/CI showed higher predictive values for obesity, HLP, DM and Hhcy than weight adjusted total body fat (all P < 0.001). Young adults with increased TBF/CI had higher ratios of metabolic diseases, which suggested that TBF/CI can be a good indicator and had a close relationship with metabolic diseases.