Visceral Adiposity Index Research Articles

TCT-13 Chinese Visceral Adiposity Index Is Associated With the Occurrence of Cardiovascular Disease Among Middle-Aged and Older People in China: Evidence From the China Health and Retirement Longitudinal Study

TCT-13 Chinese Visceral Adiposity Index Is Associated With the Occurrence of Cardiovascular Disease Among Middle-Aged and Older People in China: Evidence From the China Health and Retirement Longitudinal Study

Association of visceral adiposity index and lipid accumulation products with prediabetes in US adults from NHANES 2007-2020: A cross-sectional study.

The lipid accumulation product (LAP) and the visceral adiposity index (VAI) are suggested as dependable measures for assessing visceral fat levels. Prediabetes is recognized as a condition that precedes the potential onset of diabetes. The objective of this research is to investigate how VAI and LAP are related to prediabetes among the adult population in the United States. Information from the 2007-2020 National Health and Nutrition Examination Survey (NHANES) was scrutinized in a cross-sectional study. To evaluate the connection between VAI or LAP and the presence of prediabetes, both univariate analysis and multivariate logistic regression were utilized. Threshold effect analysis and fitted smoothing curves were used to delve into the non-linear association between VAI or LAP and prediabetes. Additional analyses were performed on specific subgroups, along with tests to explore potential interactions. In general, 12,564 American adults were included. After full adjustment, prediabetes with VAI (OR: 1.128, 95% CI: 1.073-1.185) or LAP (OR: 1.006, 95% CI: 1.004-1.008) showed a positive correlation. Individuals in the 4th VAI quartile group faced a significant 61.9% elevated risk for prediabetes (OR: 1.619, 95% CI: 1.354-1.937) when contrasted to those in the 1st VAI quartile. Participants in the 4th LAP quartile group had a significant 116.4% elevated risk for prediabetes (OR: 2.164, 95% CI: 1.747-2.681) when contrasted to individuals of the 1st LAP quartile. Smooth curve fitting analysis revealed a nonlinear correlation of VAI or LAP and prediabetes, and threshold effect analysis was used to determine an inflection point of 4.090 for VAI and 68.168 for LAP. The values of VAI and LAP are positively associated with the prevalence of prediabetes. The VAI and LAP indices may be used as predictors of prediabetes.

HTLV1 infection and long term association with liver function and lipid indices; 10 years’ follow-up

BackgroundHuman T-cell leukemia virus type 1 (HTLV-1) is a well-known retrovirus, particularly prevalent in northeastern Iran, where it is associated with a range of disorders, including liver dysfunction. Previous studies have demonstrated that HTLV-1 infection can alter lipid profiles, yet no research has examined lipid indices and liver function tests in these patients in the long term.MethodsThis data is part of the Mashhad stroke and heart atherosclerotic disorder (MASHAD) study. A total of 1116 participants were randomly selected, including 837 healthy individuals and 279 HTLV-1-infected patients. Following a 10-year follow-up period, Serum levels of liver enzymes were measured. Lipid indices such as the Atherogenic Index of Plasma (AIP), Body Adiposity Index (BAC), Castelli risk index (CRI-I, CRI-II), Lipid Accumulation Product (LAP), Visceral Adiposity Index (VAI), Triglyceride-glucose index (TyG), and Triglyceride and HDL-C Ratio (THR) were calculated.ResultsMultivariable-adjusted regression analysis demonstrated a significant coefficient for the Visceral Adiposity Index (VAI) in HTLV-infected patients compared to healthy controls (B: -0.014, 95% CI: -0.02, 0.00, p = 0.046). However, no significant differences were observed in other lipid indices between HTLV-infected patients and healthy individuals. Regarding liver enzymes, significant variations were noted in HTLV-infected patients compared to healthy controls: Aspartate Aminotransferase (AST) (B: 2.978, 95% CI: 1.34, 4.61, p < 0.001), Alanine Aminotransferase (ALT) (B: 3.687, 95% CI: 1.59, 5.78, p = 0.001), Alkaline Phosphatase (ALP) (B: 18.232, 95% CI: 6.81, 29.65, p = 0.002), and Gamma-Glutamyl Transferase (GGT) (B: 3.714, 95% CI: 0.18, 7.24, p = 0.039).ConclusionIndividuals with HTLV-1 infection exhibit reduced VAI but elevated levels of liver enzymes such as AST, ALT, ALP, and GGT, indicating liver damage. These findings emphasize the virus’s involvement in liver pathology. Also, HTLV-I is associated with reduced visceral fat tissue.

Association between severe headache or migraine and lipid accumulation product and visceral adiposity index in adults: a cross-sectional study from NHANES

BackgroundExisting literature on the impact of lipid accumulation product (LAP) and visceral adiposity index (VAI) on severe headache or migraine is limited. This study aims to elucidate the association between LAP and VAI and the prevalence of migraine.MethodsData for this study were sourced from the 1999–2004 National Health and Nutrition Examination Survey (NHANES). A database-self-administered questionnaire was used to assess severe headache or migraine. A weighted logistic regression model was employed to assess the relationship between LAP and VAI with migraine prevalence. Complementary analytical approaches included subgroup analysis, restricted cubic spline (RCS), and threshold effect analysis to validate the findings.ResultsIn the end, 4572 people were recruited for the research, including 880 with migraine and 3692 without migraine. Following adjustment for the relevant covariables, weighted logistic regression analysis (OR = 1.409, 95% CI: 1.054, 1.883, P = 0.022; OR = 1.288, 95% CI: 1.010, 1.642, P = 0.042) revealed significantly elevated odds of migraine prevalence in participants within the highest tertile (T3) of LAP and VAI than those in the lowest tertile (T1). The nonlinear association between migraine prevalence and both VAI and LAP was further elucidated through a restricted cubic spline. The threshold analysis pinpointed 2.142 (log-likelihood ratio = 0.016) as the critical inflection point for VAI. Subgroup analysis and interaction testing revealed the significant association was independent in different subgroup factors.ConclusionsThe data indicate a robust association between higher levels of LAP and VAI and an increased prevalence of migraine.

Associations between body fat anthropometric indices and mortality among individuals with metabolic syndrome

BackgroundThe distribution of body fat and metabolic health may contribute to the onset of metabolic syndrome (MetS), but the associations between body fat anthropometric indices (AIs) and mortality in individuals with MetS remain unclear.MethodsParticipants aged 18 years or older with MetS were recruited from the NHANES 1999–2018. The body fat anthropometric indices included the a body shape index (ABSI), body roundness index (BRI), cardiometabolic index (CMI), visceral adiposity index (VAI), waist triglyceride index (WTI), lipid accumulation product (LAP), atherogenic index of plasma (AIP), and triglyceride‒glucose (TyG) index. MetS was defined according to the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATPIII) criteria. Mortality data were obtained from the National Death Index through December 31, 2019.ResultsData were collected from 8,379 individuals with MetS, with a median follow-up of 8.5 years, of whom 1,698 died from all causes and 568 from the CCD. The random survival forest (RSF) analysis indicated that the ABSI had the strongest predictive power for both all-cause mortality and CCD mortality among the eight body fat AIs. After adjusting for multiple variables, the ABSI was found to be linearly and positively associated with all-cause and CCD mortality in individuals with MetS. Participants in the highest quartile of ABSI had an increased risk of all-cause (HR = 1.773 [1.419–2.215]) and CCD (HR = 1.735 [1.267–2.375]) mortality compared with those in the lowest quartile. Furthermore, the ABSI predicted areas under the curve (AUCs) of 0.735, 0.723, 0.718, and 0.725 for all-cause mortality at 3, 5, 10, and 15 years, respectively, and 0.774, 0.758, 0.725, and 0.715 for CCD mortality, respectively.ConclusionAmong eight body fat AIs, the ABSI exhibited the strongest predictive power for mortality in individuals with MetS. Higher ABSI values significantly increased all-cause mortality and CCD mortality in participants with MetS.

Association between the age-adjusted visceral adiposity index (AVAI) and female infertility status: a cross-sectional analysis of the NHANES 2013–2018

BackgroundObesity stands as an essential factor contributing to infertility in women. Early identification of obese individuals leads to favorable results for female infertility. The objective of this research is to assess the association between the age-adjusted visceral adiposity index (AVAI) and female infertility.MethodsThis study was conducted using NHANES data from 2013 to 2018, in which 1,231 women aged 20–45 were selected. Infertility was defined by survey questions. AVAI was calculated using anthropometric and serum data. Covariates included demographics and lifestyle factors. Statistical analysis with R, adjusting for covariates, and assessing nonlinearity and cutoff effects.ResultsThe study of 1,231 women from the NHANES database revealed that 11.94% were diagnosed with infertility. Individuals with higher AVAI scores showed increased age, WC, BMI, and reduced HDL levels, with a positive correlation between AVAI and female infertility (OR = 1.42, 95%CI: 1.26–1.60). AVAI quartiles showed a pronounced relationship with female infertility risk, with the highest quartile showing the greatest risk(OR = 9.35,95% CI: 2.96–29.55). Nonlinear and threshold effects in the relationship between AVAI and female infertility were identified, with an inflection point at -9.70. Subgroup analyses indicated significant interactions between AVAI and educational status and BMI, particularly in women with a BMI below 25 kg/m2, where a high AVAI level was closely related to increased infertility risk(OR = 1.92, 95%CI: 1.44–2.58).ConclusionThe study identifies a strong association between elevated AVAI scores and female infertility risk, especially in women with a BMI under 25 kg/m2. This suggests that AVAI could be a valuable predictor in female fertility assessments.

Identifying reliable obesity indices for hyperuricemia among middle-aged and elderly populations: a longitudinal study

BackgroundGiven the established link between obesity and hyperuricemia (HUA), the research want to investigate the relationship between different obesity indices and HUA, and further analyze which obesity index can better predict HUA.MethodsThe data were obtained from a longitudinal study involving middle-aged and elderly populations in Dalian, China. The research encompassed individuals who exhibited typical uric acid levels initially and tracked their progress over a three-year period. 8 obesity indices were evaluated retrospectively. Subgroup analyses were conducted to identify susceptible populations. Restricted cubic splines (RCS) were utilized to model the dose-response relationships between obesity indices and HUA. Receiver operating characteristic (ROC) curves were applied to visualize and compare the predictive value of both traditional and new obesity indices for HUA.ResultsAmong 4,112 individuals with normal baseline uric acid levels, 950 developed HUA. Significant associations with HUA were observed for body mass index (BMI), waist circumference (WC), body roundness index (BRI), cardiometabolic index (CMI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), and abdominal volume index (AVI). Subgroup analysis indicated that all obesity indices proved more effective in assessing the onset of HUA in women without Metabolic Syndrome (MetS). Further analysis using RCS revealed non-linear dose-response relationships between LAP, CMI, VAI, and HUA in males, with similar non-linear relationships observed for all indices in females. The results from the ROC curves indicate that LAP may serve as a better predictor of HUA in males, and CVAI may serve as a better predictor in females.ConclusionHUA is closely associated with obesity indices. Among females, CVAI emerges as the preferred predictive index for HUA. In males, LAP emerges as the preferred predictive index for HUA.

Association between Visceral Adiposity Index and Hyperuricemia among Steelworkers: The Moderating Effects of Drinking Tea.

Steelworkers are more likely to have a higher prevalence of hyperuricemia due to their exposure to special occupational factors and dietary habits. The interrelationships of visceral adiposity index (VAI), hyperuricemia, and drinking tea remain uncertain. This study aimed to assess the association between VAI and hyperuricemia among steelworkers, and if drinking tea modified this association. A total of 9928 steelworkers from Hunan Hualing Xiangtan Iron and Steel Company participated in this cross-sectional study. All participants completed a questionnaire, received anthropometric measurements, and provided blood samples for biochemical testing. Three logistic regression models were used to analyze the association between VAI and hyperuricemia. In this study, the prevalence of hyperuricemia was approximately 23.74% (males: 24.41%; females: 20.63%), and a positive correlation between VAI and hyperuricemia risk was observed. In multivariate logistic regression analysis, the risk of hyperuricemia increased 1.76 times (95% CI: 1.64-1.89) and 2.13 times (95% CI: 1.76-2.57) with the increase of ln VAI in males and females, respectively. For males, compared to quartile 1, the risk of hyperuricemia in the second, third, and fourth quartile of VAI were 1.75 (95% CI: 1.11-2.71), 2.56 (95% CI: 1.67-3.93) and 4.89 (95% CI: 3.22-7.43). For females, compared to quartile 1, the risk of hyperuricemia in the second, third, and fourth quartile of VAI were 1.99 (95% CI: 1.40-2.82), 2.92 (95% CI: 1.96-4.34) and 4.51 (95% CI: 2.89-7.02). Additionally, our study found that, compared with not consuming tea, drinking tea could reduce uric acid levels by 0.014 in male steelworkers (t = -2.051, p = 0.040), 0.020 in workers consuming smoked food (t = -2.569, p = 0.010), and 0.022 in workers consuming pickled food (t = -2.764, p = 0.006). In conclusion, VAI is positively correlated with hyperuricemia in steelworkers. Drinking tea may lower uric acid levels in male steelworkers and steelworkers who prefer smoked and pickled foods.

The Chinese visceral adiposity index: a novel indicator more closely related to cardiovascular disease than other abdominal obesity indices among postmenopausal women

BackgroundSeveral abdominal obesity indices including waist circumference (WC), waist–hip ratio (WHR), visceral adiposity index (VAI), lipid accumulation product (LAP), and Chinese visceral adiposity index (CVAI) were considered effective and useful predictive markers for cardiovascular disease (CVD) in general populations or diabetic populations. However, studies investigating the associations between these indices among postmenopausal women are limited. Our study aimed to investigate the associations of the five indices with incident CVD and compare the predictive performance of CVAI with other abdominal obesity indices among postmenopausal women.MethodsA total of 1252 postmenopausal women without CVD at baseline were analyzed in our investigation based on a 10-year follow-up prospective cohort study. Link of each abdominal obesity index with CVD were assessed by the Cox regression analysis and the Kaplan–Meier curve. The receiver operating characteristic (ROC) curves were drawn to compare the predictive ability for CVD.ResultsDuring the median follow-up of 120.53 months, 121 participants newly developed CVD. Compared to quartile 1 of LAP and CVAI, quartile 4 had increased risk to develop CVD after fully adjusted among postmenopausal women. When WC, VAI and CVAI considered as continuous variables, significant increased hazard ratios (HRs) for developing CVD were observed. The areas under the curve (AUC) of CVAI (0.632) was greatly higher than other indices (WC: 0.580, WHR: 0.538, LAP: 0.573, VAI: 0.540 respectively).ConclusionsThis study suggested that the abdominal obesity indices were associated with the risk of CVD excluded WHR and highlighted that CVAI might be the most valuable abdominal obesity indicator for identifying the high risk of CVD in Chinese postmenopausal women.

Type 2 diabetes mellitus modifies and mediates the association between the visceral adiposity index and depression: A cross-sectional study using NHANES 2005–2018 data

BackgroundThe objective of this investigation was to explore the correlation between the visceral adiposity index (VAI) and depression, and to analyze how type 2 diabetes mellitus (T2DM) may influence this relationship. MethodsThis study included data of 12,378 participants sourced from the National Health and Nutrition Examination Survey (NHANES) 2005–2018. Utilizing multivariate logistic regression and restricted cubic spline (RCS) regression, we examined the correlation between VAI and depression. Additionally, we investigated the interactive and mediating effects of T2DM on the association between VAI and depression. ResultsControlling for all potential confounders, the Ln logarithmic transformation of VAI showed a significant positive correlation with depression [odds ratio (OR) = 1.16, 95 % confidence interval (CI): 1.01–1.35, P = 0.041]. T2DM exhibited a notable interaction effect on the relationship connecting lnVAI and depression (P for interaction = 0.013). Specifically, the T2DM group exhibited a notable positive correlation between lnVAI and depression (OR = 1.46, 95 % CI: 1.17–1.82, P < 0.001), whereas such correlation didn't reach statistical significance within the non-T2DM group. The RCS model revealed a J-shaped nonlinear link between lnVAI and depression, with an inflection point value of 0.052. Mediation analysis indicated that diabetes accounted for 8.0 % of the correlation between lnVAI and depression. Furthermore, sensitivity analysis confirmed the consistency of these findings. ConclusionsA J-shaped nonlinear dose-response relationship was observed between lnVAI and depression among American adults, with a threshold of 0.052. T2DM not only served as a mediator between the two variables but also modified their association.

Relationship between Body Adiposity Indices and Reversal of Metabolically Unhealthy Obesity 6 Months after Roux-en-Y Gastric Bypass.

The factors determining the reversal of metabolically unhealthy obesity (MUO) to metabolically healthy obesity (MHO) after Roux-en-Y gastric bypass (RYGB) are not completely elucidated. The present study aims to evaluate body adiposity and distribution, through different indices, according to metabolic phenotypes before and 6 months after RYGB, and the relationship between these indices and transition from MUO to MHO. This study reports a prospective longitudinal study on adults with obesity who were evaluated before (T0) and 6 months (T1) after RYGB. Bodyweight, height, waist circumference (WC), BMI, waist-to-height ratio (WHR), total cholesterol (TC), HDL-c, LDL-c, triglycerides, insulin, glucose, HbA1c and HOMA-IR were evaluated. The visceral adiposity index (VAI), the conicity index (CI), the lipid accumulation product (LAP), CUN-BAE and body shape index (ABSI) were calculated. MUO was classified based on insulin resistance. MUO at T0 with transition to MHO at T1 formed the MHO-t group MHO and MUO at both T0 and T1 formed the MHO-m and MUO-m groups, respectively. At T0, 37.3% of the 62 individuals were classified as MHO and 62.7% as MUO. Individuals in the MUO-T0 group had higher blood glucose, HbA1c, HOMA-IR, insulin, TC and LDL-c compared to those in the MHO-T0 group. Both groups showed significant improvement in biochemical and body variables at T1. After RYGB, 89.2% of MUO-T0 became MHO (MHO-t). The MUO-m group presented higher HOMA-IR, insulin and VAI, compared to the MHO-m and MHO-t groups. CI and ABSI at T0 correlated with HOMA-IR at T1 in the MHO-t and MHO-m groups. CI and ABSI, indicators of visceral fat, are promising for predicting post-RYGB metabolic improvement. Additional studies are needed to confirm the sustainability of MUO reversion and its relationship with these indices.

Relationship between four visceral obesity indices and prediabetes and diabetes: a cross-sectional study in Dalian, China

BackgroundIn recent times, a number of new indices for measuring visceral obesity have been developed. This research sought to investigate the relationship between four visceral obesity indices and prediabetes and diabetes.MethodsConducted in 2011 as a cross-sectional analysis in Dalian, China, this study utilized logistic regression models to explore the relationships between four visceral obesity indices and prediabetes and diabetes. It also assessed the dose-response relationships using restricted cubic splines (RCS), performed subgroup analyses, and conducted interaction tests. The predictive values of four visceral obesity indices were evaluated using receiver operating characteristic (ROC) curves.ResultsThe study enrolled 10,090 participants, with prediabetes and diabetes prevalence at 80.53%. Multifactorial logistic regression revealed positive relationships between the four visceral obesity indices and prediabetes and diabetes. The results of the RCS analysis revealed a linear relationship between the body roundness index (BRI), cardiometabolic index (CMI) and prediabetes and diabetes. Conversely, a non-linear relationship was observed between Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP) and prediabetes and diabetes. Subgroup analyses demonstrated stronger relationships of CMI, CVAI, and LAP with prediabetes and diabetes among females. ROC curves suggested that LAP could be an effective predictor of these conditions.ConclusionThis research confirmed that four visceral obesity indices are linked with a higher risk of prediabetes and diabetes in middle-aged and elderly individuals in Dalian. Importantly, LAP could be an effective predictor of prediabetes and diabetes. Effective weight management significantly reduces the risk of both prediabetes and diabetes.

Association of different obesity indexes with diabetic kidney disease in patients with type 2 diabetes mellitus: a cross-sectional study

The objective of this study is to investigate the association between diabetic kidney disease (DKD) and various adiposity indexes, including the visceral adiposity index (VAI), lipid accumulation product index (LAPI), visceral fat area (VFA), and subcutaneous fat area (SFA) in type 2 diabetes mellitus (T2DM) patients. 1176 T2DM patients was stratified into normoalbuminuria (NO), microalbuminuria (MI), and macroalbuminuria (MA) groups based on their urinary albumin-creatinine ratio (UACR) levels. To analyse the correlation between DKD and VAI, LAPI, VFA, and SFA. Multiple linear, restricted cubic spline (RCS), subgroup analyses, and multinomial logistic regression were employed. After adjusting for confounding variables, UACR levels were positively associated with VAI, LAPI, and VFA. RCS curves demonstrated a J-shaped dose-response relationship between VAI and LAPI levels with UACR levels, while a linear correlation was observed between UACR levels and VFA. Using the NO and MI as reference groups, the MA group was analysed as the observational group. DKD severity was positively associated with VAI, LAPI and VFA. When evaluating DKD prognostic risk, with the low-risk and medium-risk groups serving as reference categories, a significant positive correlation was identified with prognostic risk and VAI, LAPI, and VFA in the high-risk or very high-risk groups. In patients with T2DM, DKD severity and prognostic risk were positively correlated with VAI, LAPI, and VFA levels.

The association of changes in the Chinese visceral adiposity index and cardiometabolic diseases: a cohort study

ObjectiveThe relationship between changes in Chinese visceral adiposity index (CVAI) and cardiometabolic diseases (CMD) in middle-aged and elderly individuals remains unclear. This study aimed to explore whether changes in the CVAI were associated with CMD incidence.MethodsThis study included 3,243 individuals aged over 45 years from the China Health and Retirement Longitudinal Study. The exposures were changes in the CVAI and cumulative CVAI from 2012 to 2015. Changes in the CVAI were classified using K-means clustering analysis, and the cumulative CVAI was calculated as follows: (CVAI2012 + CVAI2015)/2 × time (2015–2012). Multivariable logistic regression models were used to assess the relationship between different CVAI change classes and CMD incidence. Restricted cubic splines regression was used to assess the dose–response relationship between cumulative CVAI and CMD incidence. To investigate the relationship between combined exposure to each component of CAVI and CMD incidence, a weighted quantile sum regression analysis was employed.ResultsDuring the 5 years of follow-up, 776 (24%) incident CMD cases were identified. Changes in CVAI and cumulative CVAI were independently and positively associated with CMD. After adjusting for potential confounders, compared with Class 1, the adjusted ORs (95% CIs) for incident CMD were 1.18 (0.90–1.57) for Class 2, 1.40 (1.03–1.92) for Class 3, and 1.56 (1.04–2.34) for Class 4. When cumulative CVAI was categorized into quartiles, compared with Q1, the adjusted ORs (95% CIs) for incident CMD were 1.30 (1.00–1.70) for Q2, 1.34 (1.01–1.79) for Q3, and 1.63 (1.15–2.31) for Q4. In addition, cumulative CVAI in the overall population exhibited a linear association with CMD (Poverall = 0.012, Pnon-linearity = 0.287), diabetes (Poverall = 0.022, Pnon-linearity = 0.188), and stroke (Poverall = 0.002, Pnon-linearity = 0.978), but showed no significant association with heart disease (Poverall = 0.619, Pnon-linearity = 0.442).ConclusionParticipants with higher baseline CVAI level and a change of elevating CVAI level may suffer an increased incidence of CMD. Furthermore, our findings elucidate the underlying mechanisms of the CVAI by highlighting TG as the primary contributor to the observed associations. Long-term CVAI monitoring is of significant importance for early identification and prevention of CMD, with significant implications for clinical practice.

Evaluating the Association of Anthropometric Indices With Total Cholesterol in a Large Population Using Data Mining Algorithms.

Unbalanced levels of serum total cholesterol (TC) and its subgroups are called dyslipidemia. Several anthropometric indices have been developed to provide a more accurate assessment of body shape and the health risks associated with obesity. In this study, we used the random forest model (RF), decision tree (DT), and logistic regression (LR) to predict total cholesterol based on new anthropometric indices in a sex-stratified analysis. Our sample size was 9639 people in which anthropometric parameters were measured for the participants and data regarding the demographic and laboratory data were obtained. Aiding the machine learning, DT, LR, and RF were drawn to build a measurement prediction model. Anthropometric and other related variables were compared between both TC <200 and TC ≥200 groups. In both males and females, Lipid Accumulation Product (LAP) had the greatest effect on the risk of TC increase. According to results of the RF model, LAP and Visceral Adiposity Index (VAI) were significant variables for men. VAI also had a stronger correlation with HDL-C and triglyceride. We identified specific anthropometric thresholds based on DT analysis that could be used to classify individuals at high or low risk of elevated TC levels. The RF model determined that the most important variables for both genders were VAI and LAP. We tend to present a picture of the Persian population's anthropometric factors and their association with TC level and possible risk factors. Various anthropometric indices indicated different predictive power for TC levels in the Persian population.

Association of visceral adiposity index with sarcopenia based on NHANES data

The Visceral Adiposity Index (VAI) assesses visceral fat and related metabolic risks. However, its precise correlation with sarcopenia is unclear. This study aimed to examine this correlation. A cross-sectional analysis was conducted using NHANES data from 2011 to 2018. To correct VAI skewness, a logarithmic transformation was applied. Multiple covariates were included, and logistic regression was employed to explore the relationship between VAI and sarcopenia. Restricted cubic spline (RCS) and threshold saturation analyses were used to investigate the nonlinear relationship. Subgroup analyses evaluated the effects of various stratification factors. Sensitivity and additive analyses tested the robustness of the findings. The study included 4688 individuals. Participants with sarcopenia had significantly higher VAI values. Logistic regression revealed a significant positive connection between Log VAI and sarcopenia (OR 2.09, 95% CI 1.80–2.43) after adjusting for variables. RCS analysis showed a nonlinear correlation, identifying a breakpoint at VAI = 1.51. To the left of this breakpoint, each unit increase in VAI significantly correlated with a higher likelihood of sarcopenia (OR 2.54, 95% CI 1.74–3.79); to the right, increases in VAI did not significantly affect prevalence. Subgroup analyses suggested VAI as an independent risk factor. Sensitivity and additive analyses confirmed the main findings’ robustness. Among American adults, the VAI is significantly associated with sarcopenia, with higher VAI values potentially increasing the prevalence of sarcopenia. Monitoring VAI is critical for early identification of high-risk individuals and interventions to delay or minimize the onset and progression of sarcopenia.

Gender Differences in the Predictive Value of Obesity Indices for Insulin Resistance in Adult Mexican Individuals.

Obesity-linked insulin resistance (IR) is an important risk factor for metabolic diseases, and anthropometric indices are commonly used for risk assessment. The study aimed to assess possible differences between women and men in the predictive value and association of nine obesity indices with IR, as assessed by HOMA-IR, in a nondiabetic adult population. The cross-sectional study included individuals recruited from a hospital in Mexico City. Indices evaluated were waist circumference (WC), hip circumference (HC), body mass index (BMI), waist-to-hip ratio, waist-to-height ratio, visceral adiposity index, body adiposity index (BAI), relative fat mass (RFM), and conicity index (CI). Fasting plasma glucose and insulin were measured to calculate HOMA-IR. Correlation analysis was performed between obesity indices and HOMA-IR. Receiver operating characteristics curve analyses were performed to determine predictive accuracy and cut-off values of obesity indices for IR. A binary logistic regression (BLR) analysis with OR calculation was performed to determine the strength of association with HOMA-IR. We included 378 individuals (59% females, mean age 46.38 ±12.25 years). The highest Pearson coefficient value was observed for BMI among women, while among men, the highest values were found for BMI and BAI. WC among women, and BAI and RFM among men showed the highest sensitivity, while the highest specificity was observed for WHR among women and WC among men with respect to insulin prediction. In the adjusted BLR model, BMI, WC, and WHR among women and WC and RFM and BAI among men were independently associated with IR, showing the highest odds ratio (OR). In Mexican adults, WC, WHR, RFM and BAI could be complementary tools for BMI in screening for IR.

Selenoprotein-p and insulin resistance in children and adolescents with obesity.

Insulin resistance and obesity present significant challenges in pediatric populations. Selenoprotein P1 (SEPP1) serves as a biomarker for assessing selenium levels in the body. While its association with metabolic syndrome is established in adults, its relevance in children remains underexplored. To ascertain SEPP1 blood levels in children and adolescents diagnosed with obesity and to assess its correlation with insulin resistance and adiposity indices. 170 children participated in this study, including 85 diagnosed with obesity and an equal number of healthy counterparts matched for age and sex. Each participant underwent a comprehensive medical evaluation, encompassing a detailed medical history, clinical examination, and anthropometric measurements like waist circumference and waist-to-height ratio. Furthermore, routine blood tests were conducted, including serum SEPP1, visceral adiposity index (VAI), and Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) level. Our findings revealed significantly lower serum SEPP1 levels in children with obesity compared to their healthy peers. Moreover, notable negative correlations were observed between serum SEPP1 levels and body mass index, VAI, and HOMA-IR. The study suggests that SEPP1 could serve as a valuable predictor for insulin resistance among children and adolescents diagnosed with obesity. This highlights the potential utility of SEPP1 in pediatric metabolic health assessment and warrants further investigation.

Comparison of obesity indicators for predicting cardiovascular risk factors and multimorbidity among the Chinese population based on ROC analysis

To date, the best obesity-related indicators (ORIs) for predicting hypertension, dyslipidaemia, Type 2 diabetes mellitus (T2DM) and multimorbidity are still controversial. This study assessed the ability of 17 ORIs [body mass index (BMI), body fat percentage (BF%), c-index, Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE), a body shape index (ABSI), body adiposity index (BAI), waist circumference (WC), waist-hip ratio (WHR), waist-to-height ratio (WHtR), body roundness index (BRI), abdominal volume index (AVI), triglyceride glucose index (TYG), lipid accumulation product (LAP), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), waist triglyceride index (WTI) and cardiometabolic index (CMI)] to predict hypertension, dyslipidemia, T2DM, and multimorbidity in populations aged 40–69 years. From November 2017 to December 2022, 10,432 compliant residents participated in this study. Receiver operating characteristic curves were used to assess the ability of ORIs to predict target diseases across the whole population and genders. The DeLong test was used to analyse the heterogeneity of area under curves (AUCs). Multivariable logistic regression was used to analyse the association of ORIs with hypertension, dyslipidaemia, T2DM, and multimorbidity. The prevalence of hypertension, dyslipidaemia, T2DM, and multimorbidity was 67.46%, 39.36%, 12.54% and 63.58%, respectively. After excluding ORIs associated with the target disease components, in the whole population, CVAI (AUC = 0.656), BMI (AUC = 0.655, not significantly different from WC and AVI), CVAI (AUC = 0.645, not significantly different from LAP, CMI, WHR, and WTI), and TYG (AUC = 0.740) were the best predictor of hypertension, dyslipidemia, T2DM, and multimorbidity, respectively (all P < 0.05). In the male population, BF% (AUC = 0.677), BMI (AUC = 0.698), CMI (AUC = 0.648, not significantly different from LAP and CVAI), and TYG (AUC = 0.741) were the best predictors (all P < 0.05). In the female population, CVAI (AUC = 0.677), CUN-BAE (AUC = 0.623, not significantly different from BF%, WC, WHR, WHtR, BRI and BMI), CVAI (AUC = 0.657, not significantly different from WHR), TYG (AUC = 0.740) were the best predictors (all P < 0.05). After adjusting for all covariates, all ORIs were significantly associated with hypertension, dyslipidaemia, T2DM, and multimorbidity (all P < 0.05), except for ABSI and hypertension and BAI and T2DM, which were insignificant. Ultimately, after considering the heterogeneity of prediction of ORIs among different populations, for hypertension, BF% was the best indicator for men and CVAI for the rest of the population. The best predictors of dyslipidaemia, T2DM, and multimorbidity were BMI, CVAI and TYG, respectively. Screening for common chronic diseases in combination with these factors may help to improve the effectiveness.

Effectiveness of cardiometabolic index, lipid accumulation product, visceral adiposity index and waist-to-thigh ratio for the early diagnosis of diabetes in young females at childbearing age who were obese or non-obese

AimTo explore the effectiveness of the cardiometabolic index (CMI), lipid accumulation product (LAP), and waist-to-thigh ratio (WTR) in identifying insulin resistance (IR) in females who are clinically not having diabetes mellitus (DM). MethodsThis cross-sectional study was conducted in Sri Lanka between 2020 and 2023. A total of 282 female participants aged 18 to 35 were recruited. Their anthropometric measurements, fasting blood sugar (FBS) levels, IR by HOMA-IR, lipid profile, and blood pressure were assessed. All females with FBS levels >100 mg/dl were excluded from the study. ResultsThe study participants were divided into two groups, normal-weight controls (N = 142, BMI:18.0–22.9 kg/m2) and overweight/obese cases (N = 140, BMI:23.0–24.9 kg/m2, Obesity: >25 kg/m2), based on their BMI values. The mean values of CMI, LAP, and WTR in cases were 3.56 ± 0.63, 49.97 ± 17.75, and 1.88 ± 0.17, respectively. Significant associations were identified between all adiposity indexes, IR and lipid profile parameters (p < 0.05). In this female cohort, despite being clinically non DM, the prevalence of IR was significantly higher (52.83 %). ROC analysis results showed greater sensitivities for detecting IR with higher AUC as follows: CMI = 0.854(0.811–0.899), LAP = 0.869(0.829–0.910), and WTR = 0.828(0.779–0.877). The normal-weight controls were assessed to check the prevalence of metabolically-obese normal-weights (MONW,65.5 %) and metabolically-healthy normal-weights (MHNW,35.5 %) among the population, given the higher prevalence of IR. The detection accuracy of MONW females in the ROC assay was; CMI > LAP > WTR > VAI. ConclusionsCMI had the highest accuracy for detecting IR, with the accuracy of all four indexes ranked as follows: CMI > LAP > WTR > VAI.