Estimation of deep-abdominal-adipose-tissue (DAAT) accumulation from simple anthropometric measurements in Indian men and women

Lymphocyte to High-density Lipoprotein Cholesterol Ratio is Positively Associated with Pre-diabetes, Metabolic Syndrome, and Non-traditional Cardiometabolic Risk Markers: A Cross-sectional Study at Secondary Health Care

High scores of lymphocyte-to-high-density lipoprotein cholesterol ratio (lymphocyte-to-HDL-c) may be a new indicator of inflammation and metabolic syndrome. Here, we investigated the associations of the lymphocyte-to-HDL-c with traditional and non-traditional cardiometabolic risk markers in subjects at high cardiovascular risk. This study is a cross-sectional analysis with subjects assisted in a Secondary Health Care (n = 581, age = 63.06 ± 13.86 years; 52.3% women). Lymphocyte-to-HDL-c ratio were assessed by routine laboratory tests. Anthropometric and/or biochemical variables were used to calculate traditional (body mass index - BMI, and waist-to-height ratio - WHtR) and non-traditional (lipid accumulation product index-LAP, visceral adiposity index-VAI, deep-abdominal-adipose-tissue index-DAAT, atherogenic index of plasma-AIP, and waist-hypertriglyceridemic phenotype-HTGW) cardiometabolic risk markers. Furthermore, anthropometric measurement waist circumference (WC), blood pressure, metabolic syndrome (MS), and biochemical markers (lipid and glycemic profile) were considered traditional markers of cardiometabolic risk. Pearson's chi-square test, Poisson regression with robust variance, or multinomial logistic regression were performed (α = 0.05). Individuals with a high lymphocyte-HDL-c ratio (> 0.84, 3rd tertile) were associated with the HTGW phenotype, high VAI, high LAP, hypertriglyceridemia, high AIP, high very low-density lipoprotein-cholesterol (VLDL-c), pre-diabetes, and 3 and 4 MS components compared with individuals in the first tertile, independent of confounders. Our findings supported the lymphocyte-to-HDL-c ratio as a potential biomarker during the screening of subjects at high cardiovascular risk.

New sagittal abdominal diameter and transverse abdominal diameter based equations to estimate visceral fat area in type 2 diabetes patients

OBJECTIVE

Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) are considered gold standards for measuring visceral fat area (VFA). However, their relatively high prices and potential radiation exposure limit their widespread use in clinical practice and everyday life. Therefore, our study aims to develop a VFA estimated equation based on sagittal abdominal diameter (SAD) and transverse abdominal diameter (TAD) using anthropometric indexes. To the best of our knowledge, there have been limited studies investigating this aspect thus far.

METHODS

This study was designed as a cross-sectional, retrospective cohort survey. A total of 288 patients (167 males and 121 females) aged 18-80 with type 2 diabetes (T2D) were consecutively collected from a multicenter hospital, and VFA was measured by CT. Subsequently, variables highly correlated with VFA were screened through general linear correlation analysis. A stepwise regression analysis was then conducted to develop a VFA estimated equation. Discrepancies between the estimated and actual VFA values were assessed using the Bland-Altman method to validate the accuracy of the equation.

RESULTS

In the female T2D population, triglyceride (TG), SAD, TAD were found to be independently correlated with VFA; in the male T2D population, BMI, TG, SAD and TAD showed independent correlations with VFA. Among these variables, SAD exhibited the strongest correlation with VFA (r = 0.83 for females, r = 0.88 for males), followed by TAD (r = 0.69 for females, r = 0.79 for males). Based on these findings, a VFA estimated equation was developed for the T2D population: VFA (male) =-364.16 + 15.36*SAD + 0.77*TG + 9.41*TAD - 5.00*BMI (R2 = 0.75, adjusted R2 = 0.74); VFA(female)=-170.87 + 9.72*SAD-24.29*(TG^-1) + 3.93*TAD (R2 = 0.69, adjusted R2 = 0.68). Both models demonstrated a good fit. The Bland-Altman plot indicated a strong agreement between the actual VFA values and the estimated values, the mean differences were close to 0, and the majority of differences fell within the 95% confidence interval.

CONCLUSIONS

In the T2D population, a VFA estimated equation is developed by incorporating SAD and TAD along with other measurement indices. This equation demonstrates a favorable estimated performance, suggesting to the development of novel and practical VFA estimation models in the future study.

Anthropometric measures, predicted visceral adipose tissue and biomarkers of chronic inflammation

BACKGROUND

Evidence has linked low-grade systemic inflammation and visceral adipose tissue (VAT) with development of chronic conditions. Cytokines and select proteins released by VAT may promote a low-grade inflammatory response. A number of equations have been developed to estimate VAT levels. In this study, we compared predicted VAT equation relationships with biomarkers of inflammation.

METHODS

This was a cross-sectional study of 2038 men and women aged 46-73 years. Correlation and linear regression analyses were performed to examine inflammatory biomarker relationships with four commonly assessed anthropometric measures and 10 predicted VAT equations.

RESULTS

Compared with anthropometric measures, predicted VAT equations were found to explain a greater proportion of variance in CRP (R2  = .075, p = .001), IL-6 (R2  = .060, p = .001), TNF-α (R2  = .017, p = .005), resistin (R2  = .011, p = .012), monocyte (R2  = .027, p = .001), eosinophil (R2  = .012, p = .01) and basophil (R2  = .015, p = .002) levels in males, and a greater variance in concentrations of C3 (R2  = .175, p = .001), IL-6 (R2  = .090, p = .001), TNF-α (R2  = .036, p = .001), adiponectin (R2  = .121, p = .001), the adiponectin-to-leptin ratio (R2  = .444, p = .001), resistin (R2  = .025, p = .001), white blood cell count (R2  = .057, p = .001), neutrophils (R2  = .061, p = .001) and lymphocytes (R2  = .020, p = .001) in females.

CONCLUSION

Equations for assessing VAT levels might be useful to characterise metabolic health. Further studies that examine predicted VAT relationships with disease and mortality outcomes are warranted.

Central obesity is detrimental to anti-inflammatory, phenotype, and exhaustion markers in mononuclear cells - A cross-sectional study

OBJECTIVE

To investigate the role of central obesity on immunometabolic response in peripheral blood mononuclear cells (PBMCs) from normal weight and overweight/obese young men.

METHODS

Eighteen individuals were classified as normal weight (NW; n = 9 - age: 25 ± 5 and BMI: 21.4 ± 1.7) and overweight/obese (OW; n = 9 - age: 29 ± 7 and BMI: 29.2 ± 2.7). The body composition was evaluated by dual-energy x-ray absorptiometry (DXA), waist circumference, and visceral and subcutaneous fat depots by ultrasound. Physical activity levels, metabolic parameters, immune phenotypic characterization, cytokine production by lipopolysaccharide (LPS) -stimulated whole blood cells and LPS or phorbol 12-myristate 13-acetate (PMA)-stimulated PBMC, and mitochondrial respiration in PBMCs were evaluated. Expression of AMP-activated protein kinase (AMPK), peroxisome proliferator-activated receptor gamma (PPAR-γ), nuclear factor-kappa B (NF-κB), toll-like receptor 4 (TLR-4), hypoxia-inducible factor-1 alpha (HIF-1α), and adrenergic receptor beta 1 and 2 (AR-β1 and β2) genes were evaluated in cultured PBMC using quantitative real-time polymerase chain reaction (qRT-PCR).

RESULTS

Individuals with overweight/obese (OW) presented higher glucose (P = 0.009) and leptin (P = 0.010) than individuals with normal weight (NW). PBMCs of OW under stimulation with LPS presented a lower production of interleukin-10 (IL-10) (P = 0.011) and macrophage inflammatory protein-1alpha (MIP-1α) (P = 0.048) than NW. Mitochondrial respiration rates were not different between NW and OW subjects. Cultured PBMCs in LPS-stimulated condition indicated higher gene expression of AR-β2 in OW, while PMA-stimulated PBMCs presented lower expression of AMPK (P = 0.002) and higher expression of NF-κB (P=<0.0001) than NW. OW presented higher numbers of CD3+CD4+ T cells (P = 0.009) and higher expression of programmed cell death protein 1 (PD-1) in CD8+ T cells (P = 0.001) than NW.

CONCLUSION

Central obesity promoted reductions in interleukin 10 production response and increase in AR-β2 expressions in mitogen-stimulated PBMCs. Furthermore, central obesity altered the phenotype of PBMCs, also increasing the expression of PD-1 exhaustion markers in young adults.

Sex and race/ethnicity specific reference predictive equations for abdominal adiposity indices using anthropometry in US adults

BACKGROUND AND AIMS

Abdominal adiposity indices have stronger associations with cardiometabolic risk factors compared to anthropometric measures but are rarely used in large scale studies due to the cost and efficiency. The aim of this study is to establish sex and race/ethnicity specific reference equations using anthropometric measures.

METHODS AND RESULTS

A secondary data analysis (n = 6589) of healthy adults was conducted using data from National Health and Nutrition Examination Survey 2011-2018. Variables included in the analyses were anthropometric measures (height; weight; waist circumference, WC) and abdominal adiposity indices (android percent fat; android to gynoid ratio, A/G ratio; visceral adipose tissue area, VATA; visceral to subcutaneous adipose area ratio, VSR). Multivariable prediction models were developed using quantile regression. Bland-Altman was used for external validation of prediction models. Reference equations to estimate android percent fat, A/G ratio, VATA and VSR from anthropometric measurements were developed using a randomly selected subsample of 4613. These reference equations for four abdominal adiposity indices were then cross-validated in the remaining subsample of 1976. The measured and predicted android percent fat, A/G ratio, VATA and VSR were not statistically different (p > 0.05) except for the A/G ratio in Asian males and VSR in White females. The results of Bland-Altman further revealed that ≥93% of predicted abdominal adiposity indices fell within the limits of agreement (±1.96 standard deviation).

CONCLUSION

The sex and race/ethnicity specific reference equations for abdominal adiposity indices established using anthropometrics in the present study have strong predictive ability in US healthy adults.

Metabolic Score for Visceral Fat: a novel predictor for the risk of type 2 diabetes mellitus

To investigate the association between the Metabolic Score for Visceral Fat (METS-VF) and risk of type 2 diabetes mellitus (T2DM) and compare the predictive value of the METS-VF for T2DM incidence with other obesity indices in Chinese people. A total of 12 237 non-T2DM participants aged over 18 years from the Rural Chinese Cohort Study of 2007-2008 were included at baseline and followed up during 2013-2014. The cox proportional hazards regression was used to calculate hazard ratios (HR) and 95 % CI for the association between baseline METS-VF and T2DM risk. Restricted cubic splines were used to model the association between METS-VF and T2DM risk. Area under the receiver operating characteristic curve (AUC) analysis was used to evaluate the ability of METS-VF to predict T2DM incidence. During a median follow-up of 6·01 (95 % CI 5·09, 6·06) years, 837 cases developed T2DM. After adjusting for potential confounding factors, the adjusted HR for the highest v. lowest METS-VF quartile was 5·97 (95 % CI 4·28, 8·32), with a per 1-sd increase in METS-VF positively associated with T2DM risk. Positive associations were also found in the sensitivity and subgroup analyses, respectively. A significant nonlinear dose-response association was observed between METS-VF and T2DM risk for all participants (P_nonlinearity = 0·0347). Finally, the AUC value of METS-VF for predicting T2DM was largest among six indices. The METS-VF may be a reliable and applicable predictor of T2DM incidence in Chinese people regardless of sex, age or BMI.

Estimation of visceral fat area using criteria for metabolic syndrome: A cross-sectional study

BACKGROUND AND AIMS

The aim of this study was to calculate the visceral fat area (VFA) based on the criteria for metabolic syndrome (MetS).

METHODS

A multiple regression analysis was performed to determine the estimated VFA using data from Japanese participants (2315 men and 1684 women). Receiver operating characteristic curve (ROC) analyses were performed to determine the optimal estimated VFA cutoff for the diagnosis of central obesity. The cutoff was also applied to a second cohort to validate the model.

RESULTS

The estimated VFA was calculated using the MetS criteria, age, and body mass index (adjusted coefficient of determination = 0.682 for men and 0.726 for women). The area under the ROC curve for waist circumference, VFA, and estimated VFA were 0.669, 0.741, and 0.749, respectively, for men and 0.711, 0.787, and 0.803, respectively, for women. The optimal cutoffs for estimated VFA were 128.1 cm² for men and 82.2 cm² for women. Multivariate logistic regression for heart disease revealed that estimated VFA, rather than waist circumference, was associated with a high risk of heart disease.

CONCLUSION

The estimated VFA is a better index of central obesity than waist circumference and VFA for the diagnosis of MetS.

Equations for predicting DXA-measured visceral adipose tissue mass based on BMI or weight in adults

Background

Obesity, especially presenting with excessive amounts of visceral adipose tissue (VAT), is strongly associated with insulin resistance (IR), atherosclerosis, metabolic syndrome, and cardiovascular diseases (CVDs).

Aims

To construct a predication equation for estimating VAT mass using anthropometric parameters and validate the models with a validation group.

Methods

Five hundred fifteen subjects (366 for the derivation group and 149 for the validation group) were enrolled in the study. The anthropometric parameters, blood lipid profile, and VAT mass were accessed from medical records. Stepwise regression was applied to develop prediction models based on the dual X–ray absorptiometry (DXA)-measured VAT mass in the derivation group. Bland–Altman plots and correlation analysis were performed to validate the agreements in the validation group. The performance of the prediction equations was evaluated with the Hosmer–Lemeshow test and area under the curve (AUC).

Results

Model 1, which included age, sex, body mass index (BMI), triglyceride (TG), high-density lipoprotein (HDL), and the grade of hepatic steatosis, had a variance of 70%, and model 2, which included age, sex, weight, height, TG, HDL, and the grade of hepatic steatosis, had a variance of 74%. The VAT mass measured by DXA was correlated with age, sex, height, weight, BMI, TG, HDL, and grade of hepatic steatosis. In the validation group, the VAT mass calculated by the prediction equations was strongly correlated with the DXA–VAT mass (r = 0.870, r = 0.875, respectively). The AUC, sensitivity, and specificity of the two prediction equations were not significantly different (both P = 0.933).

Conclusion

The study suggests that prediction equations including age, sex, height, BMI, weight, TG, HDL, and the grade of hepatic steatosis could be useful tools for predicting VAT mass when DXA is not available.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12944-022-01652-8.

A Reliable Estimate of Visceral Fat Area From Simple Anthropometric Measurements in Chinese Overweight and Obese Individuals

OBJECTIVE

Visceral obesity, reflected by the amount of visceral adipose tissue (VAT), is associated with multiple chronic diseases and metabolic disorders. The visceral fat area (VFA), measured by MRI, is the 'gold standard' for diagnosis of visceral obesity. In this study, a simple model to predict VFA was constructed to facilitate the identification and monitoring of patients who are at high risk of visceral obesity.

METHODS

The 721 overweight and obese participants were divided into two groups according to sex, then randomly assigned to derivation and validation cohorts in a 1:2 ratio. Data from the derivation group were used to construct a multiple linear regression model; data from the validation group were used to verify the validity of the model.

RESULTS

The following prediction equations, applicable to both sexes, were developed based on age, waist circumference (WC) and neck circumference (NC) that exhibited strong correlations with the VFA: VFA=3.7×age+2.4×WC+5.5×NC-443.6 (R² = 0.511, adjusted R² = 0.481, for men) and VFA=2.8×age+1.7×WC+6.5×NC-367.3 (R² = 0.442, adjusted R² = 0.433, for women). The data demonstrated good fit for both sexes. A comparison of the predicted and actual VFA in the verification group confirmed the accuracy of the equations: for men, R² = 0.489, adjusted R² = 0.484 and intra-class correlation coefficient (ICC) = 0.653 (p < 0.001) and for women: R² = 0.538, adjusted R²= 0.536 and ICC = 0.672 (p < 0.001). The actual and predicted VFAs also showed good agreement in a Bland-Altman plot, indicating the significant correlations of both equations with the actual VFA.

CONCLUSIONS

Based on readily available anthropometric data, VFA prediction equations consisting of age, WC and NC were developed. The equations are robust, with good predictive power in both sexes; they provide ideal tools for the early detection of visceral obesity in Chinese overweight and obese individuals.

Effect of pecan nuts and extra-virgin olive oil on glycemic profile and nontraditional anthropometric indexes in patients with coronary artery disease: a randomized clinical trial

BACKGROUND/OBJECTIVES

The influence of cardioprotective foods on nontraditional indexes related to dysglycemia and body fat distribution is unknown in individuals with coronary artery disease (CAD). This study aimed to evaluate the effect of a healthy diet supplemented with pecan nuts or extra-virgin olive oil on glycemic profile and adipose tissue dysfunction assessed by anthropometric indexes in patients with stable CAD.

SUBJECTS/METHODS

In a randomized, pragmatic, parallel clinical trial lasting 12 weeks, 204 individuals were allocated to three interventions: a healthy diet (control group [CG], n = 67), a healthy diet plus 30 g/day of pecan nuts (pecan nut group [PNG], n = 68), or a healthy diet plus 30 mL/day of extra-virgin olive oil (olive oil group [OOG], n = 69). Triglyceride-glucose (TyG) index (primary outcome) and other markers of glycemic profile were evaluated, and nontraditional anthropometric indexes as well. Diet quality was assessed according to the Alternate Healthy Eating Index (mAHEI).

RESULTS

After adjustment for baseline values, use of antidiabetic drugs and insulin, there were no differences in both glycemic and anthropometric profiles according to groups at the end of the study. PNG improved the quality of the diet in comparison to other groups (final mAHEI scores: CG: 19 ± 7.5; PNG: 26 ± 8; OOG: 18.9 ± 6; P < 0.001).

CONCLUSIONS

There was no difference regarding glycemic and anthropometric parameters according to interventions in patients with stable CAD. However, adding pecan nuts to a healthy diet may improve its quality. Further studies must be conducted considering dietary interventions on secondary cardiovascular prevention setting.

CLINICAL TRIALS IDENTIFIER NUMBER

NCT02202265. First Posted: July 2014; Last Update: September 2020.

DEVELOPMENT AND VALIDATION OF EQUATIONS TO ESTIMATE VISCERAL ADIPOSE TISSUE IN MILITARY MEN

ABSTRACT Introduction It has been suggested that visceral adipose tissue (VAT) is associated with several non-communicable chronic diseases, but measuring it is difficult. Thus, anthropometry could be used because is easily applied in clinical practice. Objectives The present study aimed to develop and validate VAT estimation equations (Eq) in military men. Methods The sample consisted of 409 (mean age, 36.5 ± 6.7 years) military men in the Brazilian Army (BA) divided into an equation group (EG) ( n = 270; mean age, 37.0 ± 6.3 years) and a validation group (VG) ( n =139; mean age, 36.0 ± 7.2 years). Anthropometric, hemodynamic and DXA body composition evaluations ( GE iLunar ) were performed. The Student’s t test, Pearson’s correlation, and stepwise general linear regression were applied. Bland-Altman graphics were used to assess the concordance between VAT by Eq and by DXA. The level of significance was 95% ( p < 0.05). Results Age, waist circumference (WC), hip circumference and body mass index presented the main significant positive correlations with the VAT-DXA. Four Eq were created Eq1 ( r 2 = 0.793), Eq2 ( r 2 = 0.810), Eq3 ( r 2 = 0.817), and Eq 4 ( r 2 = 0.823) ( p < 0.05). No differences were observed between VAT by DXA and VAT by Eq ( p = 0.982, p = 0.970, p = 0.495 and p = 0.698). Bland-Altman analysis also presented good concordance as the bias was close to zero and was not statistically significant. Conclusion Eq2 (age*13.0 + WC*60.0 - 4975,.5) was more suitable because it is easier to apply, has a higher predictive power (81.0%), less bias (1.86) and validation yielded average VAT values close to those found in DXA. It may still be considered a valuable tool for other extensive epidemiological studies in military men in the BA and can be used in adult men. Evidence Level I: Development of diagnostic criteria on consecutive patients (with universally applied reference ‘‘gold’’ standard).

Metabolic Score for Visceral Fat (METS-VF) Estimation - A Novel Cost-Effective Obesity Indicator for Visceral Adipose Tissue Estimation

BACKGROUND

Visceral adipose tissue (VAT) assessment is limited in clinical practice due to expensive, time consuming and limited availability of MRI and DXA machines. We explored the utility of a recently developed Metabolic Score for Visceral Fat (METS-VF) to assess VAT in south Asian individuals with morbid obesity.

PATIENTS AND METHODS

Individuals with BMI ≥35 kg/m2 aged between 30 and 60 years were randomly selected from a database of individuals with morbid obesity, attending a multi-disciplinary bariatric clinic in a tertiary care teaching hospital in southern India. Body composition was assessed by using a Hologic Discovery A dual-energy X-ray absorptiometry (DXA) machine. METS-VF was used to estimate VAT by using a previously published algorithm.

RESULTS

The mean age and body mass index of the study subjects (N=350) were 38.2 years and 40.1 kg/m2. The MET-VF score performed satisfactorily (AUC of 0.78 (95% CI 0.72-0.85)) for predicting an increased visceral adipose tissue (VAT area ≥ 163 cm2) as detected by DXA. A METS-VF value of 7.3 was found to have a good sensitivity and reasonable specificity in predicting elevated VAT in this population.

CONCLUSION

This is the first study to validate the utility of METS-VF as a surrogate measure of visceral adiposity in south Indian individuals with morbid obesity. Given the simplicity, easy availability, reliability and inexpensive nature of this obesity indicator, it may find its widespread use in lower middle-income countries.

Metabolic Score for Visceral Fat (METS-VF), a novel estimator of intra-abdominal fat content and cardio-metabolic health

BACKGROUND & AIMS

Intra-abdominal and visceral fat (VAT) are risk factors for the development of cardio-metabolic comorbidities; however its clinical assessment is limited by technology and required expertise for its assessment. We aimed to develop a novel score (METS-VF) to estimate VAT by combining the non-insulin-based METS-IR index, waist-height ratio (WHtr), age and sex.

METHODS

We developed METS-VF in a sample of 366 individuals with Dual X-ray absorptiometry (DXA). METS-VF was modeled using non-linear regression and validated in two replication cohorts with DXA (n = 184, with n = 118 who also had MRI) and bio-electrical impedance (n = 991). We also assessed METS-VF to predict incident type 2 diabetes (T2D) and arterial hypertension independent of body-mass index (BMI) in our Metabolic Syndrome Cohort (n = 6144).

RESULTS

We defined METS-VF as: 4.466 + 0.011*(Ln(METS-IR))³ + 3.239*(Ln(WHtr))³ + 0.319*(Sex) + 0.594*(Ln(Age)). METS-VF showed better performance compared to other VAT surrogates using either DXA (AUC 0.896 95% CI 0.847-0.945) or MRI (AUC 0.842 95% CI 0.771-0.913) as gold standards. We identified a METS-VF cut-off point >7.18 in healthy patients which has 100% sensitivity (95% CI 76.8-100) and 87.2% specificity (95% CI 79.1-93.0) to identify increased VAT (>100 cm²). METS-VF also had adequate performance in subjects with metabolically-healthy obesity. Finally, in our metabolic syndrome cohort, subjects in the upper quintiles of METS-VF (>7.2) had 3.8 and 2.0-fold higher risk of incident T2D and hypertension, respectively (p < 0.001). This effect was independent of BMI for both outcomes.

CONCLUSION

METS-VF is a novel surrogate to estimate VAT, which has better performance compared to other surrogate VAT indexes and is predictive of incident T2D and hypertension. METS-VF could be a useful tool to assess cardio-metabolic risk in primary care practice and research settings.

Correlations between Traditional and Nontraditional Indicators of Adiposity, Inflammation, and Monocyte Subtypes in Patients with Stable Coronary Artery Disease

BACKGROUND

Recruitment of monocytes and low-grade inflammation process are both involved in obesity and in atherosclerosis. Thus, the aim of this study was to evaluate the correlation among indicators of adiposity, monocyte subtypes, and inflammatory markers in patients with stable coronary artery disease (CAD).

METHODS

This was a cross-sectional study including 97 patients with stable CAD aged >40 years. Traditional anthropometric indicators of adiposity (body mass index (BMI); waist, hip, and neck circumferences; and waist-hip ratio) and nontraditional anthropometric indicators of adiposity (lipid accumulation product index (LAP), visceral adiposity index (VAI), and deep-abdominal-adipose-tissue index (DAAT)) were determined. Immunoprecipitation, turbidimetry, coagulometric method, and CBA were used for the evaluation of inflammatory markers (hs-CRP, IL-2, IL-4, IL-6, IL-10, and INF-γ). Monocyte subtypes were identified by flow cytometry and defined as CD14++ CD16- (Mon1), CD14++ CD16+ (Mon2), and CD14+ CD16++ (Mon3). Pearson's correlation coefficient and adjusted partial correlation were calculated.

RESULTS

Monocyte subtypes were correlated with inflammation regardless of nutritional status according to BMI. In overweight individuals, LAP was correlated with IL-4 and fibrinogen (P < 0.01 and P < 0.05, respectively) and VAI with IL-4 (P < 0.05). In obese patients, the BMI, waist, neck, and hip circumferences, and DAAT were correlated with IL-6 (P < 0.05), regardless of age and sex. The hip circumference was correlated positively with Mon1 (r = 0.40, P = 0.007) and negatively with Mon3 (r = -0.35, P = 0.02) in obese subjects.

CONCLUSION

Monocyte subtypes are correlated with inflammation in patients with stable CAD independently of BMI, whereas traditional and nontraditional indicators of adiposity are correlated differently with inflammatory markers and monocytes, according to the nutritional status.

Design and validation of a novel estimator of visceral adipose tissue area and comparison to existing adiposity surrogates

AIMS

Visceral adiposity measured by computed tomography (CT) as intra-abdominal fat area (IAFA) predicts metabolic diseases. Existing adiposity surrogates have not been systematically compared to a regression-based model derived in individuals of Japanese ancestry. We developed and validated a method to estimate IAFA in individuals of Japanese ancestry and compared it to existing adiposity surrogates.

METHODS

We assessed age, BMI, waist circumference (WC), fasting lipids, glucose, smoking status, grip strength, mid-thigh circumference (MTC), humeral length, leg length, and IAFA by single-slice CT at the umbilicus for 622 Japanese Americans. We used stepwise linear regression to predict IAFA and termed the predicted value the Estimate of Visceral Adipose Tissue Area (EVA). For men, the final model included age, BMI, WC, high-density lipoprotein cholesterol (HDLc), glucose, and MTC; for women, age, BMI, WC, HDLc, low-density lipoprotein cholesterol, glucose, and MTC. We compared goodness-of-fit (R2) from linear regression models and mean-squared errors (MSE) from k-fold cross-validation to compare the ability of EVA to estimate IAFA compared to an estimate by Després et al., waist-to-height ratio, WC, deep abdominal adipose tissue index, BMI, lipid accumulation product, and visceral adiposity index (VAI). We classified low/high IAFA using area under receiver-operating characteristic curves (AUROC) for IAFA dichotomized at the 75th percentile.

RESULTS

EVA gave the least MSE and greatest R2 (men: 1244, 0.61; women: 581, 0.72). VAI gave the greatest MSE and smallest R2 (mean 2888, 0.08; women 1734, 0.14).

CONCLUSIONS

EVA better predicts IAFA in Japanese-American men and women compared to existing surrogates for adiposity.

Interactions between general and central obesity in predicting gestational diabetes mellitus in Chinese pregnant women: A prospective population-based study in Tianjin, China

BACKGROUND

The aim of the present study was to define cut-off points of body mass index (BMI) and waist circumference (WC) for gestational diabetes mellitus (GDM) and to investigate any interactions between high BMI and high WC on the risk of GDM in pregnant Chinese women.

METHODS

From 2010 to 2012, 17 803 women in Tianjin, China, who were at 4-12 weeks gestation were recruited to the study. Gestational diabetes mellitus was diagnosed according to the criteria of the International Association of Diabetes and Pregnancy Study Group at 24-28 weeks gestation. Binary logistic regression was used to obtain odds ratios (ORs) and 95% confidence intervals (CIs) while controlling for the confounding effects of traditional risk factors. Restricted cubic spline was used to identify cut-off points of WC and BMI, if any, for GDM.

RESULTS

Gestational diabetes mellitus developed in 1383 (7.8%) women. The risk of GDM increased steeply with increasing WC from ≥78.5 cm and BMI ≥22.5 kg/m² . If BMI <22.5 kg/m² and WC <78.5 cm were used as the reference, BMI between ≥22.5 and <24.0 kg/m² (multivariable OR 1.76; 95%CI 1.47-2.10) and WC between ≥78.5 and <85.0 cm (multivariable OR 1.53; 95%CI 1.31-1.78) were independently associated with increased risks of GDM. In addition, the presence of both BMI ≥22.5 kg/m² and WC ≥78.5 cm further increased the OR to 2.83 (95% CI 2.44-3.28), with significant additive interaction.

CONCLUSIONS

Body mass index ≥22.5 kg/m² and WC ≥78.5 cm measured up to 12 weeks of gestation were independently and synergistically associated with increased risks of GDM in Chinese pregnant women.

Equation to estimate visceral adipose tissue volume based on anthropometry for workplace health checkup in Japanese abdominally obese men

The purpose of this study was to develop a new equation model for predicting abdominal visceral adipose tissue (VAT) volume using anthropometric values for workplace health checkup and to clarify the association between metabolic risk factors and measured and predicted VAT volumes. Two hundred sixty male workers (200 for derivation group and 60 for validation group) participated in the cross-sectional study. The anthropometric variables and VAT volume were measured with 24 consecutive magnetic resonance images. Measurements in the validation group also included metabolic risk factors, i.e. blood pressure, HDL cholesterol, triglyceride, fasting glucose and HbA1c. Using multiple regression analyses for the derivation group, we determined the best prediction equation for abdominal VAT volume with a variance of 47% as follows: 47.03 age+117.79 BMI+74.18 waist circumference -8,792.7. In our validation group, the correlation coefficient between the measured and predicted VAT volumes was 0.74 (p<0.01). Furthermore, blood pressure, fasting glucose and HbA1c correlated with both measured and predicted VAT volumes. This study suggests that the equation model has potential to assess VAT accumulation levels in workers health checkup where CT and MRI are not available.

Novel Body Shape Descriptors for Abdominal Adiposity Prediction Using Magnetic Resonance Images and Stereovision Body Images

OBJECTIVE

The purpose of this study was to design novel shape descriptors based on three-dimensional (3D) body images and to use these parameters to establish prediction models for abdominal adiposity.

METHODS

Sixty-six men and fifty-five women were recruited for abdominal magnetic resonance imaging (MRI) and 3D whole-body imaging. Volumes of abdominal visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) were measured from MRI sequences by using a fully automated algorithm. The shape descriptors were measured on the 3D body images by using the software developed in this study. Multiple regression analysis was employed on the training data set (70% of the total participants) to develop predictive models for VAT and SAT, with potential predictors selected from age, BMI, and the body shape descriptors. The validation data set (30%) was used for the validation of the predictive models.

RESULTS

Thirteen body shape descriptors exhibited high correlations (P < 0.01) with abdominal adiposity. The optimal predictive equations for VAT and SAT were determined separately for men and women.

CONCLUSIONS

Novel body shape descriptors defined on 3D body images can effectively predict abdominal adiposity quantified by MRI.

Anthropometric dimensions provide reliable estimates of abdominal adiposity: A validation study

Abdominal fat accumulation is a major risk factor for cardiometabolic morbidity and mortality. The purpose of the study is to assess the possibility of developing accurate estimation equations based on body measurements to determine total abdominal (TFA), subcutaneous (SFA) and visceral fat area (VFA). Hungarian volunteers (n=198) aged between 20 and 81 years were enrolled in the study, which was conducted between July and November 2014. All persons underwent anthropometric measurements and computer tomographic (CT) scanning. Sex-specific multiple linear regression analyses were conducted in a subgroup of 98 participants to generate estimation models, then Bland-Altman's analyses were applied in the cross-validation group to compare their predictive efficiency. The variables best predicting VFA were hip circumference, calf circumference and waist-to-hip ratio (WHR) for males (R²=0.713; SEE=5602.1mm²) and sagittal abdominal diameter (SAD), WHR, thigh circumference and triceps skinfold for females (R²=0.845; SEE=3835.6mm²). The SFA prediction equation included SAD, thigh circumference and abdominal skinfold for males (R²=0.848; SEE=4124.1mm²), body mass index and thigh circumference for females (R²=0.861; SEE=5049.7mm²). Prediction accuracy was the highest in the case of TFA: hip circumference and WHR for males (R²=0.910; SEE=5637.2mm²), SAD, thigh circumference and abdominal skinfold for females (R²=0.915; SEE=6197.5mm²) were used in the equations. The results suggested that deviations in the predictions were independent of the amount of adipose tissue. Estimation of abdominal fat depots based on anthropometric traits could provide a cheap, reliable method in epidemiologic research and public health screening to evaluate the risk of cardiometabolic events.

Predictive models for estimating visceral fat: The contribution from anthropometric parameters

Background

Excessive adipose visceral tissue (AVT) represents an independent risk factor for cardiometabolic alterations. The search continues for a highly valid marker for estimating visceral adiposity that is a simple and low cost tool able to screen individuals who are highly at risk of being viscerally obese. The aim of this study was to develop a predictive model for estimating AVT volume using anthropometric parameters.

Objective

Excessive adipose visceral tissue (AVT) represents an independent risk factor for cardiometabolic alterations. The search continues for a highly valid marker for estimating visceral adiposity that is a simple and low cost tool able to screen individuals who are highly at risk of being viscerally obese. The aim of this study was to develop a predictive model for estimating AVT volume using anthropometric parameters.

Methods

A cross-sectional study involving overweight individuals whose AVT was evaluated (using computed tomography–CT), along with the following anthropometric parameters: body mass index (BMI), abdominal circumference (AC), waist-to-hip ratio (WHpR), waist-to-height ratio (WHtR), sagittal diameter (SD), conicity index (CI), neck circumference (NC), neck-to-thigh ratio (NTR), waist-to-thigh ratio (WTR), and body adiposity index (BAI).

Results

109 individuals with an average age of 50.3±12.2 were evaluated. The predictive equation developed to estimate AVT in men was AVT = -1647.75 +2.43(AC) +594.74(WHpR) +883.40(CI) (R² adjusted: 64.1%). For women, the model chosen was: AVT = -634.73 +1.49(Age) +8.34(SD) + 291.51(CI) + 6.92(NC) (R² adjusted: 40.4%). The predictive ability of the equations developed in relation to AVT volume determined by CT was 66.9% and 46.2% for males and females, respectively (p<0.001).

Conclusions

A quick and precise AVT estimate, especially for men, can be obtained using only AC, WHpR, and CI for men, and age, SD, CI, and NC for women. These equations can be used as a clinical and epidemiological tool for overweight individuals.

Correlation between the percentage of body fat and surrogate indices of obesity among adult population in rural block of Haryana

INTRODUCTION

The increasing prevalence of overweight and obesity has raised concerns regarding the importance of different techniques, which are used to assess body growth composition that can be used at the level of primary health care settings with minimal knowledge. The purpose of this study was to evaluate the relationship between different surrogate indices of fatness (body mass index [BMI], waist circumference [WC], waist-to-hip ratio [WHR], waist-to-height ratio [WHtR], and body fat percentage [BF%]) with the percentage of body fat and their usefulness as a predictor of obesity among adult population.

MATERIALS AND METHODS

The community-based cross-sectional study done over a period of 1-year involved 1080 adult participants from a rural area in Haryana. Anthropometry, along with BF% (using hand held analyzer) were recorded using standard procedures.

RESULTS

The prevalence of overweight and obesity as per the modified criteria of BMI for the Asian Indians was found to be 15.0% and 34.6%, respectively. Positive correlation was seen among all the indices except between the WHR and body adiposity index (BAI) using Pearson's correlation analysis. Maximum correlation was seen between WHtR and WC (r = 0.923), whereas WHtR depicted maximum correlation (r = 0.810) with BF%. Receiver operating characteristic curve analysis revealed that the WHtR was the most sensitive and specific indicator for the study population to predict overweight and obesity comparable to that calculated by body fat analyser followed by BAI, BMI, and WHR.

CONCLUSION

A single value of WHtR irrespective of gender and the area of residence can be used as a universal screening tool for the identification of individuals at high risk of development of metabolic complications.

The study of anthropometric estimates in the visceral fat of healthy individuals

Background

Abdominal visceral fat affects the metabolic processes, and is an important risk factor for morbidity and mortality. The purpose of the study was to develop a quick and accurate estimate in the visceral fat area (VFA) of the L4-L5 vertebrae using anthropometric predictor variables that can be measured conveniently.

Methods

A total of 227 individuals participated in this study and were further divided into a Modeling group (MG) and a Validation group (VG). Anthropometrics measurements (height, weight, waist circumference, hip circumference, age, and subcutaneous fat thickness) and VFA_CT were measured using computer assisted tomography for all participants. Multivariate linear regression analysis was applied to the MG to construct a VFA estimator using anthropometric predictor variables and to evaluate its performance using the VG.

Results

The estimate equation obtained from the MG were VFA_ANT = -144.66 + 1.84X₁ + 1.35X₂ + 0.52X₃ (r = 0.92, SEE =14.58 cm², P < 0.001, n = 152). The X₁, X₂, and X₃ variables in the equation were denoted as waist circumference (WC), age, and abdomen subcutaneous fat thickness (AS). In addition, the correlation between VFA_ANT and VFA_CT showed a high correlation (r = 0.92).

Conclusion

A rapid and accurate VFA estimation can be achieved by using only age, WC, and AS. The approach in the present study provides an easy and reliable estimate that can be applied widely in health and epidemiology studies.

Waist height ratio: A universal screening tool for prediction of metabolic syndrome in urban and rural population of Haryana

AIMS

To compare waist circumference (WC), body mass index (BMI), waist hip ratio (WHR), and waist-to-height ratio (WHtR) and define an appropriate cut-off, which is most closely predictive of the non-adipose components of the IDF metabolic syndrome (MetS) definition.

METHODS AND RESULTS

A total of 3,042 adults (1,693 in rural area and 1,349 in urban area) were screened for the presence of MetS according to the IDF definition. Among 3,042 adults selected as subjects, 1,518 were male and 1,524 were female. The receiver operating curve (ROC) analysis was done to determine the optimal cut-off value and the best discriminatory value of each of these anthropometric parameters to predict two or more non-obese components of metabolic syndrome. The area under ROC (AURC) for WC was superior to that for other anthropometric variables. The optimal cut-off value of WC in urban and rural males was >89 cm, which is higher than that in urban and rural females at 83 cm and 79 cm, respectively; the optimal cut-off for WHtR was >0.51 in rural females, 0.52 in rural males, and 0.53 in both urban males and females. Both parameters were found to be better than BMI and WHR. ROC and AURC values for WC were better than those for WHtR in men and women in both urban and rural areas (P = 0.0054); however, when the entire study cohort was analyzed together, irrespective of gender and place of residence, then at a value of 0.52, WHtR scored over WC as a predictor of metabolic syndrome (P = 0.001).

CONCLUSION

Although the predictive value of different gender-specific WC values is clearly superior to other anthropometric measures for predicting two or more non-adipose components of MetS, a single value of WHtR irrespective of gender and the area of residence can be used as a universal screening tool for the identification of individuals at high risk of development of metabolic complications.

Predictive equations for central obesity via anthropometrics, stereovision imaging and MRI in adults

OBJECTIVE

Abdominal visceral adiposity is related to risks for insulin resistance and metabolic perturbations. Magnetic resonance imaging (MRI) and computed tomography are advanced instruments that quantify abdominal adiposity; yet field use is constrained by their bulkiness and costliness. The purpose of this study is to develop prediction equations for total abdominal, subcutaneous, and visceral adiposity via anthropometrics, stereovision body imaging (SBI), and MRI.

METHODS

Participants (67 men and 55 women) were measured for anthropometrics and abdominal adiposity volumes evaluated by MRI umbilicus scans. Body circumferences and central obesity were obtained via SBI. Prediction models were developed via multiple linear regression analysis, utilizing body measurements and demographics as independent predictors, and abdominal adiposity as a dependent variable. Cross-validation was performed by the data-splitting method.

RESULTS

The final total abdominal adiposity prediction equation was -470.28 + 7.10 waist circumference - 91.01 gender + 5.74 sagittal diameter (R2 = 89.9%), subcutaneous adiposity was -172.37 + 8.57 waist circumference - 62.65 gender - 450.16 stereovision waist-to-hip ratio (R2 =90.4%), and visceral adiposity was -96.76 + 11.48 central obesity depth - 5.09 central obesity width + 204.74 stereovision waist-to-hip ratio - 18.59 gender (R2 = 71.7%). R2 significantly improved for predicting visceral fat when SBI variables were included, but not for total abdominal or subcutaneous adiposity.

CONCLUSIONS

SBI is effective for predicting visceral adiposity and the prediction equations derived from SBI measurements can assess obesity.

Use of anthropometry for the prediction of regional body tissue distribution in adults: benefits and limitations in clinical practice

Regional body composition changes with aging. Some of the changes in composition are considered major risk factors for developing obesity related chronic diseases which in turn may lead to increased mortality in adults. The role of anthropometry is well recognized in the screening, diagnosis and follow-up of adults for risk classification, regardless of age. Regional body composition is influenced by a number of intrinsic and extrinsic factors. Therapeutic measures recommended to lower cardiovascular disease risk include lifestyle changes. The aim of this review is to systematically summarize studies that assessed the relationships between anthropometry and regional body composition. The potential benefits and limitations of anthropometry for use in clinical practice are presented and suggestions for future research given.

Estimation of CT-derived abdominal visceral and subcutaneous adipose tissue depots from anthropometry in Europeans, South Asians and African Caribbeans

BACKGROUND

South Asians and African Caribbeans experience more cardiometabolic disease than Europeans. Risk factors include visceral (VAT) and subcutaneous abdominal (SAT) adipose tissue, which vary with ethnicity and are difficult to quantify using anthropometry.

OBJECTIVE

We developed and cross-validated ethnicity and gender-specific equations using anthropometrics to predict VAT and SAT.

DESIGN

669 Europeans, 514 South Asians and 227 African Caribbeans (70 ± 7 years) underwent anthropometric measurement and abdominal CT scanning. South Asian and African Caribbean participants were first-generation migrants living in London. Prediction equations were derived for CT-measured VAT and SAT using stepwise regression, then cross-validated by comparing actual and predicted means.

RESULTS

South Asians had more and African Caribbeans less VAT than Europeans. For basic VAT prediction equations (age and waist circumference), model fit was better in men (R(2) range 0.59-0.71) than women (range 0.35-0.59). Expanded equations (+ weight, height, hip and thigh circumference) improved fit for South Asian and African Caribbean women (R(2) 0.35 to 0.55, and 0.43 to 0.56 respectively). For basic SAT equations, R(2) was 0.69-0.77, and for expanded equations it was 0.72-0.86. Cross-validation showed differences between actual and estimated VAT of <7%, and SAT of <8% in all groups, apart from VAT in South Asian women which disagreed by 16%.

CONCLUSION

We provide ethnicity- and gender-specific VAT and SAT prediction equations, derived from a large tri-ethnic sample. Model fit was reasonable for SAT and VAT in men, while basic VAT models should be used cautiously in South Asian and African Caribbean women. These equations will aid studies of mechanisms of cardiometabolic disease in later life, where imaging data are not available.

Utilização de medidas antropométricas para a avaliação do acúmulo de gordura visceral

A obesidade visceral tem sido associada ao desenvolvimento de doenças cardiovasculares e a alguns tipos de câncer. Nesse sentido, é crescente o interesse na avaliação da adiposidade intra-abdominal, de forma a se analisarem o risco de doenças e alterações metabólicas, como intolerância à glicose, hiperinsulinemia, diabetes mellitus tipo 2, dislipidemias e hipertensão arterial. Técnicas de imagem, como a tomografia computadorizada e a ressonância magnética, permitem a mensuração acurada e precisa da gordura visceral..Contudo, ambas são dispendiosas e inaplicáveis na prática clínica de rotina e nos estudos epidemiológicos..Parâmetros antro-pométricos surgem como uma opção para a avaliação da gordura visceral nessas situações, por serem inócuos, de fácil aplicação e de baixo custo. À luz dessas questões, este trabalho objetivou analisar criticamente estudos que avaliaram a pertinência em empregar parâmetros antropométricos como indicadores da gordura visceral. Realizou-se um levantamento bibliográfico, no qual foram consultados periódicos nacionais e internacionais disponíveis nas seguintes bases científicas: Portal de periódicos da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Scientific Electronic Library Online, Science Direct e Pubmed, abrangendo publicações entre os anos de 1947 e 2007. Procurou-se dar ênfase aos parâmetros antropométricos, como o índice de massa corporal, a circunferência da cintura, a relação cintura-quadril e o diâmetro abdominal sagital.

Waist circumference, body mass index and waist to hip ratio for prediction of the metabolic syndrome in Chinese

BACKGROUND AND AIMS

To explore the ability of waist circumference (WC), body mass index (BMI) and waist to hip ratio (WHR) to predict two or more non-adipose components of the metabolic syndrome (MetS) among individuals aged 18-85 in North China.

METHODS AND RESULTS

This study is a cluster sample survey of 101,510 individuals, complete data are 75,788 subjects, 59,874 males and 15,914 females. Their ages were 51.9+/-12.7 years (males) and 48.7+/-11.5 years (females). Receiver operating characteristic (ROC) analysis was used to examine discrimination and find optimal cut off values of WC, BMI and WHR to predict two or more non-adipose components of MetS. The area under the ROC curve (AURC) for WC (0.694) and BMI (0.692) in females showed no difference. In males BMI (0.657) had a better discrimination than WC (0.634). WHR was weaker in both sexes. The optimal cut off value of WC in males (86.5 cm) was higher than in females (82.1cm); and that of BMI was about 24 kg/m(2) in both genders. The optimal cut off values of WC, BMI, and WHR, increased with age in both sexes.

CONCLUSIONS

BMI and WC are more useful than WHR for predicting two or more non-adipose components of MetS. Cut off values for WC in males, and those of BMI and WHR in both sexes are lower than that in present MetS criteria; WC in females is slightly higher. Cut off values of WC, BMI and WHR were increased with age in the Chinese.

Predictive equations for body fat and abdominal fat with DXA and MRI as reference in Asian Indians

OBJECTIVE

To develop accurate and reliable equations from simple anthropometric parameters that would predict percentage of total body fat (%BF), total abdominal fat (TAF), subcutaneous abdominal adipose tissue (SCAT), and intra-abdominal adipose tissue (IAAT) with a fair degree of accuracy.

METHODS AND PROCEDURES

Anthropometry, %BF by dual-energy X-ray absorptiometry (DXA) in 171 healthy subjects (95 men and 76 women) and TAF, IAAT, and SCAT by single slice magnetic resonance imaging (MRI) at L3-4 intervertebral level in 100 healthy subjects were measured. Mean age and BMI were 32.2 years and 22.9 kg/m(2), respectively. Multiple regression analysis was used on the training data set (70%) to develop equations, by taking anthropometric and demographic variables as potential predictors. Predicted equations were applied on validation data set (30%).

RESULTS

Multiple regression analysis revealed the best equation for predicting %BF to be: %BF = 42.42 + 0.003 x age (years) + 7.04 x gender (M = 1, F = 2) + 0.42 x triceps skinfold (mm) + 0.29 x waist circumference (cm) + 0.22 [corrected] x weight (kg) - 0.42 x height (cm) (R (2) = 86.4%). The most precise predictive equation for estimating IAAT was: IAAT (mm(2)) = -238.7 + 16.9 x age (years) + 934.18 x gender (M = 1, F = 2) + 578.09 x BMI (kg/m(2)) - 441.06 x hip circumference (cm) + 434.2 x waist circumference (cm) (R (2) = 52.1%). SCAT was best predicted by: SCAT (mm(2)) = -49,376.4 - 17.15 x age (years) + 1,016.5 x gender (M = 1, F = 2) +783.3 x BMI (kg/m(2)) + 466 x hip circumference (cm) (R (2) = 67.1).

DISCUSSION

We present predictive equations to quantify body fat and abdominal adipose tissue sub-compartments in healthy Asian Indians. These equations could be used for clinical and research purposes.