The utility of visceral fat level measured by bioelectrical impedance analysis in predicting metabolic syndrome

Evaluation for Performance of Body Composition Index Based on Quantitative Computed Tomography in the Prediction of Metabolic Syndrome

Objective: We aimed to evaluate the performance of predicting metabolic syndrome (MS) using body composition indices obtained by quantitative computed tomography (QCT). Methods: In this cross-sectional study, data were collected from 4745 adults who underwent QCT examinations at a Chongqing teaching hospital between July 2020 and March 2022. Visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), total abdominal fat (TAT), abdominal muscle tissue (AMT), and liver fat content (LFC) were measured at the L2-L3 disc level using specialized software, and the skeletal muscle index (SMI) were calculated. The correlations between body composition indicators were analyzed using the Pearson correlation analysis. Receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) were used to assess these indicators' predictive potential for MS. Results: VAT and TAT exhibited the best predictive ability for MS, with AUCs of 0.797 [95% confidence interval (CI): 0.779-0.815] and 0.794 (95% CI: 0.775-0.812) in males, and 0.811 (95% CI: 0.785-0.836) and 0.802 (95% CI: 0.774-0.830) in females. The AUCs for VAT and TAT were the same but significantly higher than body mass index and other body composition measures. SAT also demonstrated good predictive power in females [AUC = 0.725 (95%CI: 0.692-0.759)] but fair power in males [AUC = 0.6673 (95%CI: 0.650-0.696)]. LFC showed average predictive ability, AMT showed average predictive ability in males but poor ability in females, and SMI had no predictive ability. Correlation analysis revealed a strong correlation between VAT and TAT (males: r = 0.95, females: r = 0.89). SAT was strongly correlated with TAT only in females (r = 0.89). In the male group, the optimal thresholds for VAT and TAT were 207.6 and 318.7 cm2, respectively; in the female group, the optimal thresholds for VAT and TAT were 128.0 and 269.4 cm2, respectively. Conclusions: VAT and TAT are the best predictors of MS. SAT and LFC can also be acceptable to make predictions, whereas AMT can only make predictions of MS in males.

Energy expenditure related biomarkers following bariatric surgery: a prospective six-month cohort study

BACKGROUND

Mitochondria dysfunction is one of the major causes of insulin resistance, and other countless complications of obesity. PGC-1α, and UCP-2 play key roles in energy expenditure regulation in the mitochondrial thermogenesis. However, the effects of bariatric surgery on the level of PGC-1α and UCP-2 and their relationships are unclear.

OBJECTIVE

This study aimed to investigate the effect of bariatric surgery on key pathways in energy, and to assess the potential predictive role of body composition and metabolic parameters in this regard.

SETTINGS

Hazrat-e Rasool General Hospital, Center of Excellence of International Federation for Surgery of Obesity.

METHODS

This prospective cohort study was carried out on 45 patients with morbid obesity who underwent Roux-en-Y gastric bypass surgery. The patients have evaluated three-time points at baseline, three, and six months after the surgery. Body composition components, the levels of PGC-1α, UCP-2, and metabolic parameters were measured three times during this study.

RESULTS

Significant changes in TWL%, EBMIL%, and metabolic lab tests were observed at three- and six months post-surgery (P < 0.001). The PGC-1α and UCP-2 had a significant increase three and then six-month post-operation compared with the baseline (P < 0.001). Moreover, multivariate linear regression analysis identified that the changing trend of PGC-1α was associated with insulin, uric Acid, HOMA-IR, fat mass and trunk fat mass. UCP-2 was associated with TSH, AST, fat mass and FFM.

CONCLUSIONS

Bariatric surgery has been shown to have a positive effect on UCP-2 and PGC-1α levels, as well as body composition and metabolic parameters. As a result, it is believed that bariatric surgery could improve thermogenesis and energy expenditure by enhancing mitochondrial biogenesis and function. However, further studies are needed to fully understand the precise mechanisms and possible causal relationship.

Relationships between body composition, anthropometrics, and standard lipid panels in a normative population

Introduction

More than one third of adults in the United States (US) meet the clinical criteria for a diagnosis of metabolic syndrome, but often diagnosis is challenging due to healthcare access, costs and discomfort with the process and invasiveness associated with a standard medical examination. Less invasive and more accessible approaches to collecting biometric data may have utility in identifying individuals at risk of diagnoses, such as metabolic syndrome or dyslipidemia diagnoses. Body composition is one such source of biometric data that can be non-invasively acquired in a home or community setting that may provide insight into an individual's propensity for a metabolic syndrome diagnosis. Here we investigate possible associations between body composition, anthropometrics and lipid panels in a normative population.

Methods

Healthy participants visited the Lab100 clinic location at a hospital setting in New York City and engaged in a wellness visit led by a nurse practitioner. Blood was analyzed at point-of-care using the Abbott Piccolo Xpress portable diagnostic analyzer (Abbott Laboratories, IL, USA) and produced direct measures of total cholesterol (TC), high density lipoprotein (HDL-C), low density lipoprotein (LDL-C), very-low density lipoprotein (VLDL-C), and triglycerides (TG). Body composition and anthropometric data were collected using two separate pieces of equipment during the same visit (Fit3D and InBody570). Regression analysis was performed to evaluate associations between all variables, after adjusting for age, sex, race, AUDIT-C total score (alcohol use), and current smoking status.

Results

Data from 199 participants were included in the analysis. After adjusting for variables, percentage body fat (%BF) and visceral fat levels were significantly associated with every laboratory lipid value, while waist-to-hip ratio also showed some significant associations. The strongest associations were detected between %BF and VLDL-C cholesterol levels (t = 4.53, p = 0.0001) and Triglyceride levels (t = 4.51, p = 0.0001).

Discussion

This initial, exploratory analysis shows early feasibility in using body composition and anthropometric data, that can easily be acquired in community settings, to identify people with dyslipidemia in a normative population.

Adiponectin-leptin ratio for the early detection of lean non-alcoholic fatty liver disease independent of insulin resistance

BACKGROUND

Lean Non-alcoholic Fatty Liver Disease (NAFLD) shares a similar disease burden to those of their overweight counterparts and should be detected early. We hypothesized that the adiponectin-leptin ratio (AL ratio) could be a good marker for early detection of lean NAFLD independent of insulin resistance.

MATERIALS AND METHODS

A total of 575 adults without diabetes were enrolled in a community-based study. The subjects were stratified into the lean controls, lean NAFLD, simple overweight/obesity and overweight/obesity NAFLD groups according to body mass index (BMI) and ultrasonographic fatty liver indicators. Serum adiponectin and leptin levels were measured by enzyme-linked immunosorbent assay. Multivariate logistic regression analyses were performed to estimate the odds ratio of having NAFLD in relation to the tertiles of serum AL concentration after adjustment. Receiver operating characteristic (ROC) analyses were applied to evaluate the diagnostic performance of the AL ratio for NAFLD.

RESULTS

The mean age of the participants was 42.8 ± 11.5 years. Comparing with the lean controls, the odds of having lean NAFLD for the highest versus the lowest tertile of AL ratio was 0.28(95%CI: 0.12-0.69) after adjustment. Putting AL ratio, BMI, triglyceride, AST/ALT ratio to the diagnosis performance of NAFLD, the ROC was 0.85 (95% CI: 0.82-0.88), 0.83 (95% CI 0.78-0.87) and 0.86 (95% CI 081-0.91) for all NAFLD, NAFLD in women and NAFLD in men, respectively. (p < .001).

CONCLUSIONS

The study revealed that the AL ratio could be a good biomarker to early distinguish lean NAFLD patients from lean controls independent of insulin resistance. [AQ3]Key messagesThe prevalence of non-alcoholic fatty liver disease (NAFLD) increases globally and is related to liver diseases and metabolic dysfunctions. Lean subset of NAFLD shares a similar disease burden to those of their overweight counterparts and should be detected early.Adiponectin-leptin ratio were associated with the severity of steatosis and was a predictor of obese NAFLD better than each single adipokine. To date, there is no investigation that explores specifically for the relationship between lean NAFLD and AL ratio.Our study found that adiponectin-leptin ratio is a sole independent marker regardless of insulin resistance in lean NAFLD. Having lean NAFLD for the highest versus the lowest tertile of adiponectin-leptin ratio was 0.28(95%CI: 0.12-0.69) after adjustment of age, sex, current smoking, exercise habits, HOMA-IR and AST/ALT. ROC for the NAFLD performance is good for the early detection (0.85; 95% CI: 0.82-0.88). Further rigorous investigation is necessary and should be promptly performed.

Association of visceral fat area with pre-frailty in Japanese community-dwelling older adults: a cross-sectional study

Background

Screening and intervention in pre-frailty can help prevent or delay frailty among older adults. Being overweight has shown associated with pre-frailty, and overweight is highly prevalent among community-dwelling older adults during COVID-19. However, the impact of visceral fat accumulation remains unclear. This study aimed to explore the association between visceral fat area and pre-frailty in community-dwelling older adults.

Methods

The participants of this study included community-dwelling older adults from three elderly welfare centers. The frailty phenotype was assessed using the frailty screening index. The body composition was measured using bioelectrical impedance analysis.

Results

A total of 214 community-dwelling older adults completed the questionnaire and measurements. After excluding 16 frail participants, 149 (75.3%) were pre-frailty. The mean age of participants was 75.4 ± 5.4 years, and 69.7% (138) of participants were women. There were 54 (27.3%) participants with high visceral fat area. The multivariable model showed that participants with high visceral fat area were at increased risk for pre-frailty (adjusted OR, 3.15; 95% CI, 1.26 − 7.87; P = 0.014), even after adjusted for age, sex, health status, and impact of COVID-19 pandemic.

Conclusions

This study suggests that the association between visceral fat accumulation and pre-frailty may help to identify a new target for prevention. Further longitudinal studies are needed to determine their mechanisms in older adults.

Three-dimensional optical body shape and features improve prediction of metabolic disease risk in a diverse sample of adults

OBJECTIVE

This study examined whether body shape and composition obtained by three-dimensional optical (3DO) scanning improved the prediction of metabolic syndrome (MetS) prevalence compared with BMI and demographics.

METHODS

A diverse ambulatory adult population underwent whole-body 3DO scanning, blood tests, manual anthropometrics, and blood pressure assessment in the Shape Up! Adults study. MetS prevalence was evaluated based on 2005 National Cholesterol Education Program criteria, and prediction of MetS involved logistic regression to assess (1) BMI, (2) demographics-adjusted BMI, (3) 85 3DO anthropometry and body composition measures, and (4) BMI + 3DO + demographics models. Receiver operating characteristic area under the curve (AUC) values were generated for each predictive model.

RESULTS

A total of 501 participants (280 female) were recruited, with 87 meeting the criteria for MetS. Compared with the BMI model (AUC = 0.819), inclusion of age, sex, and race increased the AUC to 0.861, and inclusion of 3DO measures further increased the AUC to 0.917. The overall integrated discrimination improvement between the 3DO + demographics and the BMI model was 0.290 (p < 0.0001) with a net reclassification improvement of 0.214 (p < 0.0001).

CONCLUSIONS

Body shape measures from an accessible 3DO scan, adjusted for demographics, predicted MetS better than demographics and/or BMI alone. Risk classification in this population increased by 29% when using 3DO scanning.

Excessive weight loss after bariatric surgery: a prediction model retrospective cohort study

Bariatric surgery has been recognized as the most effective long-term treatment for morbid obesity. Despite the considerable positive results, adverse consequence can develop. Excessive Weight Loss (EXWL), a rare consequence of bariatric surgery, can lead to a broad adverse consequence. The aim of this study was determining of prevalence and the predicting model of EXWL in patient underwent bariatric surgery until 24 months after surgery. Data have been extracted from the National Obesity Surgery Database in obesity clinic of Iran University of Medical Sciences. The subjects of this retrospective cohort study were morbid obese individuals who underwent three various types of bariatric surgery [One Anastomosis Gastric Bypass (OAGB), Roux-en-Y Gastric Bypass (RYGB), or Sleeve Gastrectomy (SG)] in period of 24 months ago. EXWL has been defined as reaching to less than or equal to BMI 18.5 at any time until 24 months after surgery. SPSS was used in data analysis. Among 4214 subjects of this study, most excess weight loss after surgery has taken place in 18 months after surgery. 11.4% (n = 495) of patients experienced EXWL with highest percentage among OAGB patients (15.1%) at time of 24 months after surgery. The females (20.4% vs.9.9%) and younger persons (35.45 ± 10.25 vs. 39.06 ± 10.76) were more susceptible to EXWL. Patients with EXWL had significantly lower BMI (body mass index) (41.11 ± 4.51 vs. 46.73 ± 6.26) (Kg/m²), and were less probable to had emotional eating. Visceral fat level, fat percentage, and BMI were the best predictor of EXWL (P value for all < 0.05). So that per level increase in visceral fat, decreases the probability of EXWL as 47% and 61% in SG and OAGB. Moreover, each unit lower BMI leads to 25% higher susceptibility to experience EXWL. Surgery should be adjusted in younger females with a lower BMI and healthy metabolic status who are more prone to EXWL. In such a way that minimize weight loss speed/value. It may be possible by selection of other surgery procedures, rather than OAGB, tighter follow-ups, and consultations of patients after surgery is emphasized for more EXWL vulnerable patients.

Non-linear Associations Between Visceral Adiposity Index and Cardiovascular and Cerebrovascular Diseases: Results From the NHANES (1999–2018)

Objective

To investigate associations between visceral adiposity index (VAI) and cardiovascular and cerebrovascular diseases (CCDs) in the American population from 1999 to 2018.

Methods

Data from the National Health and Nutrition Examination Survey (1998–2018) were analyzed in this study. Specifically, VAI scores were calculated using sex-specific equations that incorporate body mass index, waist circumference (WC), high-density lipoprotein (HDL), triglycerides (TG), and cholesterol. Weighted logistic regression analysis was conducted to assess the relationship between VAI tertile and increased risk of CCDs. Restricted cubic splines were used to evaluate the non-linear relationship between VAI and CCDs, such as heart failure, angina, heart attack, stroke, hypertension, and coronary heart disease. Sensitivity analysis was conducted, using VAI quartiles as independent variables.

Results

A total of 22,622 subjects aged over 20 years were included. In the fully adjusted model after controlling for covariates, the third VAI tertile was more strongly associated with CCDs than the first VAI tertile, with odds ratio (OR) and 95% confidence interval (95% CI) values for angina of 2.86, 1.68–4.85; heart attack, 1.75, 1.14–2.69; stroke, 2.01, 1.23–3.26; hypertension, 2.28, 1.86–2.78; and coronary heart disease, 1.78, 1.32–2.41; but there was no significant association with heart failure (p &gt; 0.05). Restricted cubic splines revealed parabolic relationships between VAI score and angina (p for non-linear = 0.03), coronary heart disease (p for non-linear = 0.01), and hypertension (p for non-linear &lt; 0.001). Sensitivity analysis indicated that the fourth VAI quartile was more strongly associated with an increased risk of angina (OR = 2.92, 95% CI, 1.49–5.69), hypertension (OR = 2.37, 95% CI, 1.90–2.97), heart attack (OR = 1.77, 95% CI, 1.09–2.88), and coronary heart disease (OR = 1.89, 95% CI, 1.24–2.86) than the first VAI quartile. VAI had superior predictive power for prevalent CCDs than other independent indicators (p &lt; 0.05).

Conclusion

Visceral adiposity index score is positively correlated with angina, heart attack, stroke, hypertension, and coronary heart disease, but not heart failure, and the relationships between VAI score and angina, hypertension, and coronary heart disease are non-linear.

Joint Effect of Beer, Spirits Intake, and Excess Adiposity on Hyperuricemia Among Chinese Male Adults: Evidence From the China National Health Survey

Alcohol intake and excess adiposity are associated with serum uric acid (SUA), but their interaction effect on hyperuricemia (HUA) remains unclear. Using data from the China National Health Survey (CNHS) (2012-2017), we analyzed the additive interaction of beer, spirits intake, excess adiposity [measured by body mass index (BMI), body fat percentage (BFP), and visceral fat index (VFI)] with HUA among male participants aged 20-80 from mainland China. The relative excess risk due to interaction (RERI), the attributable proportion due to interaction (AP), and the synergy index (SI) were calculated to assess the interaction effect on the additive scale. Both RERI and AP larger than 0 and SI larger than 1 indicate a positive additive interaction. Among 12,592 male participants, the mean SUA level was 367.1 ± 85.5 μmol/L and 24.1% were HUA. Overweight/obese men who were presently drinking spirits had an odds ratio (OR) of 3.20 (95%CI: 2.71-3.79) than the never drink group, with RERI, AP, and SI of 0.45 (95%CI: 0.08-0.81), 0.14 (95%CI: 0.03-0.25), and 1.25 (95%CI: 1.02-1.54), respectively. However, although combined exposures on beer intake and excess adiposity had the highest OR compared with no beer intake and nonobese participants, there was no additive interaction, with RERI, AP, and SI in the overweight/obesity and the beer intake group of 0.58 (-0.41-1.57), 0.17 (-0.08-0.41), and 1.30 (0.85-1.97), respectively. Other excess adiposity indexes revealed similar estimates. Our findings suggested that the exposures of both excess adiposity and alcohol drink could result in an additive interaction effect on HUA: the combined risk of excess adiposity with spirits intake but not with beer was greater than the sum of the effects among Chinese male adults.

Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Association of Body Composition with Type 2 Diabetes: A Retrospective Chart Review Study

This study analyzed the body composition of individuals with type 2 diabetes (T2DM). In this retrospective chart review study, body composition was measured through multifrequency bioelectrical impedance analysis (InBody 770). Body composition assessments were conducted in individuals with T2DM, who were aged ≥18 years. The parameters included body mass index (BMI), body fat mass (BFM), fat-free mass (FFM), visceral fat area, percent body fat (PBF), appendicular skeletal muscle mass (ASM), and skeletal muscle index (SMI). One-way ANOVA and independent t-tests were used to calculate differences in body composition distribution by age and sex. A total of 2404 participants were recruited. The prevalence of overall low muscle mass and sarcopenic obesity was 28.0% and 18.7%, respectively, which increased with age. The overall prevalence of obesity when PBF was used was 71.5%, which was higher than that when BMI was applied (32.4%). The normal BMI group exhibited a prevalence of low muscle mass of 55.6% and sarcopenic obesity of 34.8%. For both men and women, bodyweight, BFM, FFM, ASM, and SMI all decreased with age. The prevalence of low muscle mass and sarcopenic obesity was high in older adults and people with normal BMI. Using BMI to assess obesity and determine insufficient muscle mass underestimates the prevalence of obesity and neglects the problems of sarcopenia and high body fat in people with normal BMI.