Derivation and validation of a new visceral adiposity index for predicting visceral obesity and cardiometabolic risk in a Korean population

Association between visceral obesity and 10-year risk of first atherosclerotic cardiovascular diseases events among American adults: National Health and Nutrition Examination Survey

Background

In the United States, the relationship between visceral obesity and the risk of developing atherosclerosis cardiovascular disease (ASCVD) for the first time in 10 years is unclear.

Methods

Data for this cross-sectional study came from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2020. We collected variable information related to 10-year ASCVD risk and visceral obesity reliable indicators [Visceral obesity index (VAI) and Lipid accumulation product (LAP)]. And we used multiple logistic regression to analyze the correlation of visceral obesity indicators (VAI and LAP) with 10-year ASCVD risk. In addition, we assessed the linear relationship between VAI or LAP and 10-year ASCVD risk by smoothing curve fitting. Finally, we conducted subgroup analysis and sensitivity analysis after excluding participants with extreme VAI and LAP values to ensure that we obtained accurate and reliable results.

Results

Our study included a total of 1,547 participants (mean age: 56.5 ± 10.1, 60% of males). The results of the multiple logistic regression showed that compared with participants with the lowest VAI in the 1st Quartile (≤0.79), the adjusted OR values for VAI and elevated 10-year ASCVD risk in Q3 (1.30-2.14), and Q4 (≥2.15) were 2.58 (95% CI: 1.24-5.36, P = 0.011), 15.14 (95% CI: 6.93-33.05, P < 0.001), respectively. Compared with participants with the lowest LAP in the 1st Quartile (≤28.29), the adjusted OR values for VAI and elevated 10-year ASCVD risk in Q3 (46.52-77.00), and Q4 (≥77.01) were 4.63 (95% CI: 2.18-9.82, P < 0.001), 16.94 (95% CI: 6.74-42.57, P < 0.001), respectively. Stratified analysis showed that the association between VAI or LAP and the first ASCVD event was more pronounced in males.

Conclusion

Higher VAI or LAP scores are significantly associated with elevated 10-year ASCVD risk in adults aged 40 to 79 in the USA, which suggested that monitoring visceral obesity is crucial to reduce the risk of a first ASCVD event.

The Visceral Adiposity Index Is a Better Predictor of Excess Visceral Fat in Military Pilots: A Cross-sectional Observational Study

INTRODUCTION

Visceral adipose tissue (VAT) is related to cardiometabolic risk. Estimating it using the visceral adiposity index (VAI) could identify this risk in the Brazilian Air Force (BAF) aviator population. The aim here is to verify the predictive capacity of the VAI for identifying visceral fat areas compared to traditional obesity indicators in BAF pilots.

MATERIALS AND METHODS

Forty male BAF pilots were recruited. The study was conducted in two stages: the first applied a structured questionnaire to characterize the sample and identify sedentary behavior and the second obtained nutritional, anthropometric, and body composition data, carrying out biochemical and magnetic resonance imaging tests and investigating physical activity level in this stage. The comparison of the predictive capacity of the VAI with that of other adiposity indicators (body mass index [BMI], waist circumference, waist-height ratio, waist-hip ratio, and neck circumference) for detecting increased VAT and the determination of the optimal cutoff points for the different adiposity indicators were carried out using receiving operating characteristic (ROC) curves. An association was verified between the adiposity indicators and excess visceral fat using Poisson regression analysis with robust variance.

RESULTS

The VAI presented a better predictive capacity for VAT (area under the ROC curve = 0.941), while the BMI did not present diagnostic accuracy (95% CI < 0.5). The strength of the association with high visceral fat was also greater for the VAI than for the other indicators evaluated.

CONCLUSIONS

The VAI was shown to be a better predictor of excess VAT in relation to the other indicators studied. As it is a more easy-access and lower-cost technique than resonance, it enables greater applicability in tracing and monitoring the visceral obesity of a large contingent of military personnel.

Novel Asian-Specific Visceral Adiposity Indices Are Associated with Chronic Kidney Disease in Korean Adults

BACKGROUND

The Chinese visceral adiposity index (CVAI) and new visceral adiposity index (NVAI) are novel indices of visceral adiposity used to predict metabolic and cardiovascular diseases in Asian populations. However, the relationships of CVAI and NVAI with chronic kidney disease (CKD) have not been investigated. We aimed to characterize the relationships of CVAI and NVAI with the prevalence of CKD in Korean adults.

METHODS

A total of 14,068 participants in the 7th Korea National Health and Nutrition Examination Survey (6,182 men and 7,886 women) were included. Receiver operating characteristic (ROC) analyses were employed to compare the associations between indices of adiposity and CKD, and a logistic regression model was used to characterize the relationships of CVAI and NVAI with CKD prevalence.

RESULTS

The areas under the ROC curves for CVAI and NVAI were significantly larger than for the other indices, including the visceral adiposity index and lipid accumulation product, in both men and women (all P<0.001). In addition, high CVAI or NVAI was significantly associated with a high CKD prevalence in both men (odds ratio [OR], 2.14; 95% confidence interval [CI], 1.31 to 3.48 in CVAI and OR, 6.47; 95% CI, 2.91 to 14.38 in NVAI, P<0.05) and women (OR, 4.87; 95% CI, 1.85 to 12.79 in CVAI and OR, 3.03; 95% CI, 1.35 to 6.82 in NVAI, P<0.05); this association remained significant after adjustment for multiple confounding factors in men and women.

CONCLUSION

CVAI and NVAI are positively associated with CKD prevalence in a Korean population. CVAI and NVAI may be useful for the identification of CKD in Asian populations, including in Korea.

The new visceral adiposity index outperforms traditional obesity indices as a predictor of subclinical renal damage in Chinese individuals: a cross-sectional study

BACKGROUND

The new visceral adiposity index (NVAI) was superior to previous obesity indices in predicting cardiovascular diseases among Asians. Nevertheless, the utility of the NVAI for predicting chronic kidney disease is still unclear. The objective of this research was to explore the relationship between the NVAI and subclinical renal damage (SRD) and to investigate whether the NVAI outperforms other common obesity indices in predicting SRD in the Chinese population.

METHODS

Participants in this cross-sectional study were from the Hanzhong Adolescent Hypertension Cohort. The NVAI and seven other common obesity indices were calculated, including body mass index, waist circumference, lipid accumulation product, visceral adiposity index, Chinese visceral adiposity index, a body shape index and metabolic score for visceral fat. Logistic regression models revealed the association between NVAI and SRD. The odds ratio (OR) and the 95% confidence interval (CI) were calculated to show the association between the two variables. The predictive power of eight obesity indices for SRD was evaluated through the receiver operating characteristic curve and area under the curve (AUC). In addition, the net reclassification index (NRI) and integrated discrimination improvement (IDI) were also applied to compare the incremental predictive value for SRD of different obesity indices.

RESULTS

The median age of the 2358 subjects was 42.00 years. Across NVAI tertiles, the prevalence of SRD was 7.25%, 11.21%, and 21.60%, respectively. After adjusting for confounders, a high level of NVAI remained a risk factor for SRD. The ORs of the middle and top NVAI tertiles for SRD were 1.920 (95% CI: 1.322, 2.787) and 4.129 (95% CI: 2.750, 6.202), respectively. The AUC of the NVAI was 0.666 (95% CI: 0.647, 0.685), which was significantly larger than the AUC of any of the other obesity indicators. Moreover, the NRI and IDI were significantly improved when NVAI was added to the basic model for predicting SRD. Among eight obesity indices, NVAI had the highest NRI (0.392; 95% CI: 0.280, 0.503), and its IDI (0.021; 95% CI: 0.014, 0.027) was second only to that of the body mass index (0.023; 95% CI: 0.014, 0.032).

CONCLUSIONS

NVAI is independently and positively associated with SRD. Among the eight obesity indices, the NVAI shows the strongest predictive power for SRD in the Chinese population. The NVAI may be useful as an effective warning indicator of chronic kidney disease in Chinese adults.

Evaluation of the Value of Waist Circumference and Metabolomics in the Estimation of Visceral Adipose Tissue

Visceral adipose tissue (VAT) is a strong prognostic factor for cardiovascular disease and a potential target for cardiovascular risk stratification. Because VAT is difficult to measure in clinical practice, we estimated prediction models with predictors routinely measured in general practice and VAT as outcome using ridge regression in 2,501 middle-aged participants from the Netherlands Epidemiology of Obesity study, 2008-2012. Adding waist circumference and other anthropometric measurements on top of the routinely measured variables improved the optimism-adjusted R2 from 0.50 to 0.58 with a decrease in the root-mean-square error (RMSE) from 45.6 to 41.5 cm2 and with overall good calibration. Further addition of predominantly lipoprotein-related metabolites from the Nightingale platform did not improve the optimism-corrected R2 and RMSE. The models were externally validated in 370 participants from the Prospective Investigation of Vasculature in Uppsala Seniors (PIVUS, 2006-2009) and 1,901 participants from the Multi-Ethnic Study of Atherosclerosis (MESA, 2000-2007). Performance was comparable to the development setting in PIVUS (R2 = 0.63, RMSE = 42.4 cm2, calibration slope = 0.94) but lower in MESA (R2 = 0.44, RMSE = 60.7 cm2, calibration slope = 0.75). Our findings indicate that the estimation of VAT with routine clinical measurements can be substantially improved by incorporating waist circumference but not by metabolite measurements.

Negative associations of morning serum cortisol levels with obesity: the Henan rural cohort study

AIMS

To evaluate the associations of morning serum cortisol levels with obesity defined by different indices in Chinese rural populations.

MATERIALS AND METHODS

A cross-sectional study was performed including 6198 participants (2566 males and 3632 females). Serum cortisol was collected in morning and quantified by liquid chromatography-tandem mass spectrometry. Obesity was defined by body mass index (BMI), body fat percentage (BFP), waist-to-height ratio (WHtR), waist circumference (WC), visceral fat index (VFI) and waist-to-hip ratio (WHR). Both multivariable liner regression, logistic regression and restrictive cubic splines models were used to estimate the gender-specific relationships between cortisol levels and obesity defined by different indices, respectively.

RESULTS

After adjusting for potential confounders, serum cortisol was negatively associated with different obesity measures, except obese females defined by BFP (for instance, overall obesity defined by BMI, Quartile 4 vs. Quartile 1, odds ratio (OR) = 0.25, 95% confidence interval (CI):0.15, 0.41 in males, and OR = 0.58, 95% CI: 0.42,0.80 in females, central obesity defined by WC, OR = 0.52, 95% CI:0.39,0.69 in males and OR = 0.63, 95% CI:0.51,0.77 in females). Similarly, restrictive cubic splines showed the nonlinear relationship between high levels of cortisol and different obesity indices. Furthermore, ROC curve analysis indicated that cortisol could improve the discrimination of model with common biomarkers.

CONCLUSION

Morning serum cortisol were negatively related to obesity defined by different indices in Chinese rural populations. In addition, cortisol could be as a biomarker for prediction of obesity in males.

Dysfunctional adiposity index as a marker of adipose tissue morpho-functional abnormalities and metabolic disorders in apparently healthy subjects

Compared to body mass index, waist circumference (WC), and adiposity measurements, adipose tissue (AT) morpho-functionality evaluations are better predictors of cardiometabolic abnormalities (CA). The present study establishes a dysfunctional adiposity index (DAI) as an early marker of CA based on adipocytes morpho-functional abnormalities. DAI was established in 340 subjects without cardiovascular risk factors selected from a cross-sectional study (n=1600). Then, DAI was calculated in 36 healthy subjects who underwent subcutaneous AT biopsy. The correlation of DAI with adipocyte morphology (size/number) and functionality (adiponectin/leptin ratio) was analyzed. The DAI cut-off point was identified and its independent association with CA was determined in 1418 subjects from the cross-sectional study. The constant parameters to calculate the DAI were [WC/[22.79+[2.68*BMI]]]*[triglycerides (TG, mmol/L)/1.37]*[1.19/high density lipoprotein-cholesterol (HDL-C, mmol/L)] for males, and [WC/[24.02+[2.37*BMI]]]*[TG(mmol/L)/1.32]*[1.43/HDL-C(mmol/L)] for females. DAI correlated with adipocytes mean area, adipocyte number and adiponectin/leptin ratio. DAI ≥1.065 was independently associated with diabetes, non-alcoholic fatty liver disease, subclinical atherosclerosis, and hypertension. The present study highlights that DAI is associated with early CA independently of adiposity and other risk factors. Since DAI is obtained using accessible parameters, it can be easily incorporated into clinical practice for early identification of AT abnormalities in apparently healthy subjects.

Novel Adiposity and Biochemical-Anthropometric Indices to Identify Cardiometabolic Risk and Metabolic Syndrome in Mexican Adults

Although several indices used in clinical practice identify cardiometabolic risk (CR) and metabolic syndrome (MetS), it is imperative to develop indices for specific populations. Therefore, we proposed and validated sex-specific indices to identify CR associated with visceral adipose tissue (VAT) accumulation or MetS in Mexican adults. Additionally, a cut-off value for the visceral fat area (VFA) to identify CR was proposed. Clinical, anthropometric, biochemical, and body composition variables were evaluated in 904 subjects (25-45 years old) (84.4% men). Multiple and logistic regressions were used to model the indices and ROC curve analysis to determine predictive performance. An additional cohort (n = 186) was used for indices validation, and Cohen's kappa coefficient was employed for agreement analysis. The proposed sex-specific indices, called Mexican adiposity indices (MAIs) and biochemical-anthropometric indices (BAIs), were good predictors for CR and MetS. The kappa coefficients showed a moderate agreement level. The VFA cut-off value chosen to identify CR was 100.3 cm2 because it had the best combination of sensitivity (66.8%) and specificity (64.4%). MAIs and BAIs could be clinical tools to identify either CR associated to VAT accumulation or MetS, respectively. A VFA cut-off value of 100.3 cm2 could identify CR in Mexican men.

Association of the new visceral adiposity index with coronary artery calcification and arterial stiffness in Korean population

BACKGROUND AND AIMS

The new visceral adiposity index (NVAI) is an indirect marker of visceral adipose tissue recently developed using a Korean population. Here we examined the association of NVAI with coronary artery calcification and arterial stiffness in asymptomatic Korean patients.

METHODS AND RESULTS

We analyzed data from 60,938 asymptomatic Korean adults. Odds ratios and 95% confidence intervals (CIs) for coronary artery calcification score (CACS) > 100 and brachial-ankle pulse wave velocity (baPWV) ≥14 m/s were calculated across NVAI tertiles using multiple logistic regression analysis. Receiver operating characteristic (ROC) and area under the curve (AUC) analyses were used to assess the ability of NVAI to predict moderate to high risk of cardiovascular disease. The prevalence of moderate and high risk of cardiovascular disease increased significantly as the NVAI tertile increased. The odds ratio (95% CI) of the highest NVAI tertile for CACS >100 was 5.840 (5.101-6.686) for men and 18.916 (11.232-31.855) for women, after adjusting for confounders. All NVAI AUC values were significantly higher than the AUC values for other visceral adiposity markers.

CONCLUSIONS

This study provides the evidence that NVAI is independently and positively associated with coronary calcification and arterial stiffness in asymptomatic Korean adults.

Concurrent smoking and alcohol consumers had higher triglyceride glucose indices than either only smokers or alcohol consumers: a cross-sectional study in Korea

BACKGROUND

The triglyceride glucose (TyG) index is a noninsulin-based marker for insulin resistance (IR) in general practice. Although smoking and heavy drinking have been regarded as major risk factors for various chronic diseases, there is limited evidence regarding the combined effects of smoking and alcohol consumption on IR. This study aimed to investigate the relationship between the TyG index and smoking and alcohol consumption using two Korean population-based datasets.

METHODS

This study included 10,568 adults in the Korean National Health and Nutrition Examination Survey (KNHANES) and 9586 adults in the Korean Initiatives on Coronary Artery Calcification (KOICA) registry datasets. Multivariate logistic analysis was conducted to explore the relationship between smoking and alcohol consumption and the TyG index. To assess the predictive value of smoking and alcohol consumption on high TyG index, the area under the curve (AUC) were compared and net reclassification improvement (NRI) and integrated discrimination improvement (IDI) analyses were derived.

RESULTS

The combined effect of smoking and alcohol consumption was an independent risk factor of a higher TyG index in the KNHANES (adjusted odds ratio: 4.33, P < .001) and KOICA (adjusted odds ratio: 1.94, P < .001) datasets. Adding smoking and alcohol consumption to the multivariate logistic models improved the model performance for the TyG index in the KNHANES (AUC: from 0.817 to 0.829, P < .001; NRI: 0.040, P < .001; IDI: 0.017, P < .001) and KOICA (AUC: from 0.822 to 0.826, P < .001; NRI: 0.025, P = .006; IDI: 0.005, P < .001) datasets.

CONCLUSIONS

Smoking and alcohol consumption were independently associated with the TyG index. Concurrent smokers and alcohol consumers were more likely to have a TyG index that was ≥8.8 and higher than the TyG indices of non-users and those who exclusively consumed alcohol or smoking tobacco.

Low socioeconomic status aggravated associations of exposure to mixture of air pollutants with obesity in rural Chinese adults: A cross-sectional study

OBJECTIVES

Socio-economic status (SES) and air pollutants are thought to play an important role in human obesity. The evidence of interactive effect between SES and long-term exposure to mixture of air pollutants on obesity is limited, thus, this study is aimed to investigate their interactive effects on obesity among a rural Chinese population.

METHODS

A total of 38,817 individuals were selected from the Henan Rural Cohort Study. Structural equation modeling (SEM) was applied to construct the latent variables of low SES (educational level, marital status, family yearly income, and number of family members), air pollution (particulate matter with aerodynamics diameters ≤ 1.0 μm, ≤ 2.5 μm or ≤ 10 μm, and nitrogen dioxide) and obesity (body mass index, waist circumference, waist-to-hip ratio, waist-to-height ratio, body fat percentage and visceral fat index). Generalized linear regression models were used to assess associations between the constructed latent variables. Interaction plots were applied to describe interactive effect of air pollution and low SES on obesity and biological interaction indicators (the relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP) and synergy index (S)) were also calculated.

RESULTS

Increased latent variables of low SES and mixture of air pollution were associated with a higher odds of latent variable of obesity (odds ratios (OR) (95% confidence interval (CI)) were 1.055 (1.049, 1.060) and 1.050 (1.045, 1.055)). The association of the mixture of air pollutants on obesity was aggravated by increased values of the latent variable of low SES (P < 0.001). Furthermore, the values of RERI, AP and S were 0.073 (0.051, 0.094), 0.057 (0.040, 0.073) and 1.340 (1.214, 1.479), respectively, indicating an additive effect of estimated latent variable of low SES and air pollution on obesity.

CONCLUSIONS

These findings suggested that low SES aggravated the negative effect of mixture of air pollutants on obesity, implying that individuals with low SES may be more susceptible to exposure to high levels of mixture of air pollutants related to increased risk of prevalent obesity.

Associations of Socioeconomic Status and Physical Activity With Obesity Measures in Rural Chinese Adults

Background: Although independent association of socioeconomic status (SES) or physical activity (PA) with obesity has been well-documented in urban settings, their independent and joint associations on obesity measures are limited in rural regions.

Methods: Almost 38,000 (n = 37,922) individuals were included from the Henan Rural Cohort Study. The International Physical Activity Questionnaire (IPAQ) was used to evaluate PA. Obesity was reflected by body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body fat percentage (BFP), and visceral fat index (VFI). The independent and interactive effects of SES and PA on obesity were analyzed by logistic regression models and generalized linear regression models, respectively.

Results: Compared with high education level, the OR (95%CI) of obesity defined by BMI with low education level was 1.466 (1.337, 1.608), 1.064 (0.924, 1.225), and 1.853 (1.625, 2.114) in total population, men and women, respectively. Besides, the OR (95%CI) of obesity defined by BMI associated with per capita monthly income were 1.089 (1.015, 1.170), 1.192 (1.055, 1.347), 1.038 (0.951, 1.133) in total population, men and women, respectively. Similar results had been observed in other obesity measures. Negative interactive association of low education level and PA on obesity measures were observed only in women (all P < 0.05).

Conclusions: This study suggests that women are more susceptible to obesity concerning low SES and that adequate PA may be a potential target for mitigating the negative effect of low SES on obesity in women.

Clinical Trial Registration: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699) http://www.chictr.org.cn/showproj.aspx?proj=11375.

Effects of Daily Consumption of an Aqueous Dispersion of Free-Phytosterols Nanoparticles on Individuals with Metabolic Syndrome: A Randomised, Double-Blind, Placebo-Controlled Clinical Trial

Metabolic syndrome (MS) affects up to 40% of the population and is associated with heart failure, stroke and diabetes. Phytosterols (PS) could help to manage one or more MS criteria. The purpose of this study was to evaluate the therapeutic effect of daily supplementation of an aqueous dispersion of 2 g of free-phytosterols nanoparticles in individuals with MS over six months of intervention, compared with placebo. This double-blind study included 202 participants with MS randomly assigned into phytosterol (n = 102) and placebo (n = 100) groups. Participants were assessed at baseline, 4, 12 and 24 weeks. General health questions, anthropometric measurements and blood parameters were analysed. At week 24, the proportion of participants with high triglycerides (≥150 mg/dL) in the phytosterol group was 15.65% lower than in the placebo group (p-value = 0.023). Similarly, half of the participants in the phytosterol group decreased their waist circumference up to 4 cm compared with 0 cm in the placebo group (p-value = 0.0001). We reported no adverse effects (diarrhoea or vitamin D reduction); nonetheless, almost 70% of participants in the phytosterol group self-reported an improvement in bowel habits. Daily intake of free-PS nanoparticles improved some MS criteria; therefore, it might be a promising adjuvant therapy for individuals with MS (NCT02969720).

Association between long-term exposure to ambient air pollution and obesity in a Chinese rural population: The Henan Rural Cohort Study

Association between long-term exposure to ambient air pollution and obesity remains inconclusive, and the evidence from rural areas was limited. Thus, this study aimed to assess the association between ambient air pollution and obesity based on different anthropometric indices in Chinese rural adults, and further to compare the effect sizes of different air pollution types. A total of 38,824 participants (aged 18-79 years) were recruited from the Henan Rural Cohort Study. Logistic and multivariable linear regression model were used to examine the association between ambient air pollution exposure (including particulate matter with aerodynamic diameters ≤ 1.0 μm (PM₁), ≤2.5 μm (PM_2.5), and ≤10 μm (PM₁₀), and nitrogen dioxide (NO₂)) and obesity as well as obese anthropometric indices (including body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body fat percentage (BFP), and visceral fat index (VFI)). The potential effect modifications were also examined. Positive associations were found between long-term exposure to PM₁, PM_2.5, PM₁₀ and NO₂ and obesity regardless of how obesity was defined (false discovery rate (FDR) < 0.05). Moreover, BMI, WC, WHR, WHtR, BFP, and VFI displayed increased trends with PM₁, PM_2.5, PM₁₀ and NO₂ concentrations increasing (all FDR<0.05). PM₁₀ had the largest effects on obesity among the four types of air pollution. The elderly, women, individuals with low level of education and income, and those who had high fat diet were more vulnerable to the adverse effects of air pollution. In addition, the results of the sensitivity analysis showed that those associations between ambient air pollution and obesity remained robust. These findings suggest that long-term exposure to ambient air pollutant (particularly PM₁₀) may be positively associated with obesity in Chinese rural adults, especially among the elderly, women, individuals with low education and income, as well as unhealthy lifestyles.

The Prediction of Human Abdominal Adiposity Based on the Combination of a Particle Swarm Algorithm and Support Vector Machine

Background: Abdominal adiposity is an important risk factor of chronic cardiovascular diseases, thus the prediction of abdominal adiposity and obesity can reduce the risks of contracting such diseases. However, the current prediction models display low accuracy and high sample size dependence. The purpose of this study is to put forward a new prediction method based on an improved support vector machine (SVM) to solve these problems. Methods: A total of 200 individuals participated in this study and were further divided into a modeling group and a test group. Their physiological parameters (height, weight, age, the four parameters of abdominal impedance and body fat mass) were measured using the body composition tester (the universal INBODY measurement device) based on BIA. Intelligent algorithms were used in the modeling group to build predictive models and the test group was used in model performance evaluation. Firstly, the optimal boundary C and parameter gamma were optimized by the particle swarm algorithm. We then developed an algorithm to classify human abdominal adiposity according to the parameter setup of the SVM algorithm and constructed the prediction model using this algorithm. Finally, we designed experiments to compare the performances of the proposed method and the other methods. Results: There are different abdominal obesity prediction models in the 1 KHz and 250 KHz frequency bands. The experimental data demonstrates that for the frequency band of 250 KHz, the proposed method can reduce the false classification rate by 10.7%, 15%, and 33% in relation to the sole SVM algorithm, the regression model, and the waistline measurement model, respectively. For the frequency band of 1 KHz, the proposed model is still more accurate. (4) Conclusions: The proposed method effectively improves the prediction accuracy and reduces the sample size dependence of the algorithm, which can provide a reference for abdominal obesity.