OBJECTIVE: The obesity rate among middle-aged and young adults in China is increasing annually, and the incidence of cardiovascular diseases is becoming more prevalent in younger populations. However, it has not yet been reported whether obesity is associated with early vascular aging (EVA). This study aims to explore the correlation between obesity and EVA in middle-aged and young adult health check-up populations, providing a reference for the prevention of cardiovascular diseases.
METHODS: A total of 15 464 middle-aged and young adults aged 18-59 who completed brachial-ankle pulse wave velocity (baPWV) test in the Third Xiangya Hospital of Central South University from January to December 2020 were included. Among them, 1 965 individuals with normal blood pressure and no cardiovascular risk factors were selected as the healthy population. The baPWV thresholds for determining EVA in each age group for males and females were calculated based on the baPWV values of the healthy population. The number and percentage of individuals meeting the EVA criteria in the middle-aged and young adult health check-up populations were statistically analyzed by age and gender. The differences in obesity indicators [visceral adiposity index (VAI), body mass index (BMI), waist circumference (WC)] between the EVA and non-EVA groups for males and females were compared. Using EVA as the dependent variable, VAI, BMI, and WC were included as independent variables in a Logistic model to analyze the correlation between each obesity indicator and EVA before and after adjusting for other influencing factors. Furthermore, the correlation between each obesity indicator and EVA in each age group was analyzed.
RESULTS: In the health check-up populations, the detection rate of EVA in different age groups was 1.65%-10.92% for males, and 1.16%-10.50% for females, the detection rate of EVA increased with age in both males and females. Except for the 40-<50 age group, the EVA detection rate was higher in males than in females in all other age groups. Regardless of gender, obesity indicators VAI, BMI, and WC were significantly higher in the EVA group than in the non-EVA group (all P<0.01). Before and after adjusting for other influencing factors, VAI and WC were both correlated with EVA (both P<0.05). BMI was a risk factor for EVA before adjusting for other influencing factors (P<0.01), but after adjustment, the correlation between BMI and EVA was not statistically significant (P=0.05). After adjusting for other influencing factors, the correlation between VAI and EVA was statistically significant in the 18-<40 and 50-<60 age groups (both P<0.05), while the correlation between BMI and WC with EVA was not statistically significant (both P>0.05). In the 40-<50 age group, the correlation between VAI and BMI with EVA was not statistically significant (both P>0.05), but the correlation between WC and EVA was statistically significant (P<0.01).
CONCLUSIONS: VAI is closely related to the occurrence of EVA in middle-aged and young adults aged 18-<40 and 50-<60 years, while WC is closely related to the occurrence of EVA in those aged 40-<50 years.
目的: 中国中青年肥胖率逐年升高，心血管疾病的发生呈年轻化趋势。然而，肥胖是否与早发血管老化(early vascular aging，EVA)相关目前尚未见报道。本研究旨在分析中青年健康体检人群肥胖与EVA的相关性，为心血管疾病的预防提供参考。方法: 纳入2020年1至12月在中南大学湘雅三医院完成臂踝脉搏波传导速度(brachial-ankle pulse wave velocity，baPWV)测量的15 464名18~59岁中青年健康体检者，并选择其中血压正常且无心血管风险因素的1 965名受检者作为健康人群。根据健康人群各年龄段男性和女性的baPWV值，计算得到用于判断各年龄段男性和女性EVA的baPWV界值。按照年龄和性别进行分组，统计中青年健康体检人群中符合EVA标准的人数，并计算所占百分比。分别比较男性/女性EVA组和非EVA组之间肥胖指标[内脏脂肪指数(visceral adiposity index，VAI)、体重指数(body mass index，BMI)、腰围(waist circumference，WC)]的差异。以EVA作为因变量，分别将VAI、BMI、WC作为自变量纳入Logistic模型，分别分析校正其他影响因素前后各肥胖指标与EVA的相关性；并进一步分析各年龄段各肥胖指标与EVA的相关性。结果: 在健康体检人群中，不同年龄组男性EVA检出率1.65%~10.92%，女性EVA检出率1.16%~10.50%；随年龄增加，男性、女性EVA检出率均呈上升趋势；且除40~<50岁年龄组，其他年龄组男性EVA检出率均高于女性。不管是男性或女性，EVA组肥胖指标VAI、BMI、WC均明显高于非EVA组(均P<0.01)。在对其他影响因素进行校正前后，VAI、WC均与EVA相关(均P<0.05)。在未校正其他影响因素时，BMI为EVA的危险因素(P<0.01)，而在校正其他影响因素后，BMI与EVA的相关性不具有统计学意义(P=0.05)。校正其他影响因素后，18~<40岁、50~<60岁年龄组VAI与EVA的相关性均具有统计学意义(均P<0.05)，BMI、WC与EVA的相关性均无统计学意义(均P>0.05)；而在40~<50岁年龄组，VAI、BMI与EVA的相关性均无统计学意义(均P>0.05)，WC与EVA的相关性有统计学意义(P<0.01)。结论: 18~<40岁、50~<60岁中青年人群VAI与EVA的发生密切相关，40~<50岁中青年人群WC与EVA的发生密切相关。.

Over the years, obesity has become more commonplace and has had a substantial impact on several medical specialties, including reproductive medicine. The potential correlation between the visceral adiposity index (VAI) and infertility has yet to be determined. Women between the ages of 18 and 45 were included in this cross-sectional study, which was conducted as part of the National Health and Nutrition Examination Survey (NHANES) between 2015 and 2020. Three tertiles were used to group VAI levels. Subgroup analysis and weighted binary logistic regression were employed to investigate the independent relationship between VAI and infertility. Smooth curve fitting was used to explore nonlinear relationships. This cross-sectional study followed the criteria of the STROBE guidelines. Of the 1231 participants, 127 were infertile women aged 18-45 years. A higher VAI was associated with a higher prevalence of infertility (OR = 1.22, 95% CI:1.03-1.45), which remained consistent across all subgroups (p > 0.05 for all interactions). We demonstrated a positive nonlinear association between VAI and infertility using a smooth curve fit. A higher visceral adiposity index level is positively correlated with a higher incidence of infertility among women in the United States. Women who are infertile can be identified using the visceral obesity index, and controlling visceral obesity may help lower the chances of becoming infertile.

OBJECTIVE: Many factors influence male sexual function, including metabolic disorders such as metabolic syndrome (MetS). We aimed to investigate the effects of two metabolic indices, the triglyceride-glucose (TyG) index and the visceral adiposity index (VAI), on male sexual function.
METHODS: A total of 400 men having sexual dysfunction were included. Anthropological data, comorbidities were recorded. Serum total testosterone, prolactin, and estradiol levels were recorded. Sex-specific VAI was calculated using the [(WC/39.68) + (1.88xMI)] × (TG/1.03) × (1.31/HDL) formula and using Ln (fasting triglycerides) × (fasting glucose)/2] formula, TyG index was calculated. Turkish-validated 15-item long-form of the International Index of Erectile Dysfunction (IIEF) questionnaire and male sexual health questionnaire (MSHQ) were used for erectile function and ejaculatory function, respectively. The ROC analysis was used to evaluate the predictive abilities of TyG and VAI cut-off values for ED risk.
RESULTS: A higher TyG index and VAI were associated with an increased risk of ED. The presence of MetS further worsened sexual function, with lower scores in sexual satisfaction, orgasm, desire, and general satisfaction. The TyG index and VAI showed similar predictive abilities for ED. Patients with MetS had worse ejaculation quality compared to those without MetS.
CONCLUSIONS: These findings highlight the potential of the TyG index and VAI as convenient tools for predicting and assessing sexual dysfunction in men, particularly in the context of metabolic disorders. Early detection and intervention for metabolic syndrome and insulin resistance may help to mitigate their negative impact on male sexual function.

UNASSIGNED: Polycystic ovary syndrome (PCOS) women are at risk of developing diabetes, cardiovascular disease and metabolic syndrome (MetS) due to insulin resistance (IR) and hyperandrogenism (HA). Both visceral adiposity index (VAI) and lipid accumulation product (LAP) are simple outpatient department-based metric tools that have been introduced to screen PCOS women who are metabolically unhealthy and are at risk of development of MetS.
UNASSIGNED: The aim of the study was to evaluate VAI and LAP in women with PCOS and to correlate them with metabolic and endocrine markers. The study also assessed these parameters amongst different PCOS phenotypes and determined their usefulness to define metabolically healthy PCOS (MH-PCOS) and metabolically unhealthy PCOS (MU-PCOS).
UNASSIGNED: The design of the study was a cross-sectional study.
UNASSIGNED: Two hundred PCOS women were included in the study, and all the clinical, anthropometric, hormonal, biochemical and metabolic markers were assessed. The cohort was divided into MH-PCOS and MU-PCOS by the modified National Cholesterol Education Programme criteria. VAI and LAP were calculated and correlated with clinical, endocrine and metabolic parameters.
UNASSIGNED: Univariate and multivariate logistic regression analysis was used to study the independent role of VAI and LAP to predict MetS. Adjusted and unadjusted odds ratios were calculated. Receiver-operating characteristic (ROC) analysis was done to define cut-offs in Asian Indian women.
UNASSIGNED: VAI and LAP had good ability to correctly discriminate MU-PCOS from MH-PCOS (area under the curve [AUC] [95% confidence interval (CI)]: 0.89 [0.82-0.95]) and (AUC [95% CI [0.81-0.92] =0.86) using ROC, respectively. The sensitivity of VAI and LAP corresponding to the optimal cut-off of ≥2.76 and ≥48.06 (Youden) was 84.09% and 79.55%, respectively. Similarly, the specificity of VAI and LAP was 85.26% and 79.49%, respectively. VAI has a positive predictive value of 61.7% (95% CI [23.7%-40.3%]) and a negative predictive value of 95% (95% CI [88%-99.1%]). LAP has a positive predictive value of 53% (95% CI [40.3%-65.4%]) and a negative predictive value of 93.3% (95% CI [87.6%-96.9%]). PCOS women having VAI ≥ 2.76 had 19.3 times ([95% CI: 6.50-57.70]) more chance of developing MetS. PCOS women having LAP (≥48.06) have 3.7 times ([95% CI: 1.35-10.60]) more odds. There was no difference between ROC curves of VAI and LAP (P = 0.32).
UNASSIGNED: VAI cut-off ≥ 2.76 and LAP with a cut-off of ≥ 48.06 may be used as markers for predicting MetS amongst PCOS women.

BACKGROUND: This study aimed to compare anthropometric indices to predict type 2 diabetes mellitus (T2DM) among first-degree relatives of diabetic patients in the Iranian community.
METHODS: In this study, information on 3483 first-degree relatives (FDRs) of diabetic patients was extracted from the database of the Endocrinology and Metabolism Research Center of Isfahan University of Medical Sciences. Overall, 2082 FDRs were included in the analyses. A logistic regression model was used to evaluate the association between anthropometric indices and the odds of having diabetes. Furthermore, a receiver operating characteristic (ROC) curve was applied to estimate the optimal cutoff point based on the sensitivity and specificity of each index. In addition, the indices were compared based on the area under the curve (AUC).
RESULTS: The overall prevalence of diabetes was 15.3%. The optimal cutoff points for anthropometric measures among men were 25.09 for body mass index (BMI) (AUC = 0.573), 0.52 for waist-to-height ratio (WHtR) (AUC = 0.648), 0.91 for waist-to-hip ratio (WHR) (AUC = 0.654), 0.08 for a body shape index (ABSI) (AUC = 0.599), 3.92 for body roundness index (BRI) (AUC = 0.648), 27.27 for body adiposity index (BAI) (AUC = 0.590), and 8 for visceral adiposity index (VAI) (AUC = 0.596). The optimal cutoff points for anthropometric indices were 28.75 for BMI (AUC = 0.610), 0.55 for the WHtR (AUC = 0.685), 0.80 for the WHR (AUC = 0.687), 0.07 for the ABSI (AUC = 0.669), 4.34 for the BRI (AUC = 0.685), 39.95 for the BAI (AUC = 0.583), and 6.15 for the VAI (AUC = 0.658). The WHR, WHTR, and BRI were revealed to have fair AUC values and were relatively greater than the other indices for both men and women. Furthermore, in women, the ABSI and VAI also had fair AUCs. However, BMI and the BAI had the lowest AUC values among the indices in both sexes.
CONCLUSIONS: The WHtR, BRI, VAI, and WHR outperformed other anthropometric indices in predicting T2DM in first-degree relatives (FDRs) of diabetic patients. However, further investigations in different populations may need to be implemented to justify their widespread adoption in clinical practice.

BACKGROUND: Obesity and hypertension are major risk factors for cardiovascular diseases that affect millions of people worldwide. Both conditions are associated with chronic low-grade inflammation, which is mediated by adipokines such as adiponectin. Adiponectin is the most abundant adipokine that has a beneficial impact on metabolic and vascular biology, while high serum concentrations are associated with some syndromes. This \"adiponectin paradox\" still needs to be clarified in obesity-associated hypertension. The aim of this study was to investigate how adiponectin affects blood pressure, inflammation, and metabolic function in obesity hypertension using a Chinese adult case-control study.
METHODS: A case-control study that had finished recruiting 153 subjects divided as four characteristic groups. Adiponectin serum levels were tested by ELISA in these subjects among these four characteristic Chinese adult physical examination groups. Waist circumference (WC), body mass index (BMI), systolic blood pressure (SB), diastolic blood pressure (DB), and other clinical laboratory data were collected. Analyzation of correlations between the research index and differences between groups was done by SPSS.
RESULTS: Serum adiponectin levels in the| normal healthy group (NH group) were significantly higher than those in the newly diagnosed untreated just-obesity group (JO group), and negatively correlated with the visceral adiposity index. With multiple linear egression analysis, it was found that, for serum adiponectin, gender, serum albumin (ALB), alanine aminotransferase (ALT) and high-density lipoprotein cholesterol (HDLC) were the significant independent correlates, and for SB, age and HDLC were the significant independent correlates, and for DB, alkaline phosphatase (ALP) was the significant independent correlate. The other variables did not reach significance in the model.
CONCLUSIONS: Our study reveals that adiponectin\'s role in obesity-hypertension is multifaceted and is influenced by the systemic metabolic homeostasis signaling axis. In obesity-related hypertension, compensatory effects, adiponectin resistance, and reduced adiponectin clearance from impaired kidneys and liver all contribute to the \"adiponectin paradox\".

BACKGROUND: Obesity refers to a significant contributor to the development of obstructive sleep apnea (OSA). Early prediction of OSA usually leads to better treatment outcomes, and this study aims to employ novel metabolic markers, visceral adiposity index (VAI), and lipid accumulation product (LAP) to evaluate the relationship to OSA.
METHODS: The data used in the current cross-sectional investigation are from the National Health and Nutrition Examination Survey (NHANES), which was carried out between 2015 and 2018. To examine the correlation between LAP and VAI levels and OSA, multivariate logistic regression analysis was adopted. In addition, various analytical methods were applied, including subgroup analysis, smooth curve fitting, and threshold effect analysis.
RESULTS: Among totally 3932 participants, 1934 were included in the OSA group. The median (Q1-Q3) values of LAP and VAI for the participants were 40.25 (21.51-68.26) and 1.27 (0.75-2.21), respectively. Logistic regression studies indicated a positive correlation between LAP, VAI, and OSA risk after adjusting for potential confounding variables. Subgroup analysis revealed a stronger correlation between LAP, VAI levels, and OSA among individuals aged < 60 years. Through smooth curve fitting, specific saturation effects of LAP, VAI, and BMD were identified, with inflection points at 65.684 and 0.428, respectively.
CONCLUSIONS: This study demonstrates that elevated levels of LAP and VAI increase the risk of OSA, suggesting their potential as predictive markers for OSA and advocating for dietary and exercise interventions to mitigate OSA risk in individuals with high LAP and VAI levels.

UNASSIGNED: Cardiometabolic multimorbidity (CMM) has emerged as a prominent public health concern. Hypertensive patients are prone to develop comorbidities. Moreover, the accumulation of visceral adipose tissue is the main cause for the development of cardiometabolic diseases. The cardiometabolic index (CMI), lipid accumulation product (LAP), visceral adiposity index (VAI), and Chinese visceral adiposity index (CVAI) not only assess adipose tissue mass but also reflect adipose tissue dysfunction. So far, no study has been reported to evaluate the association of CMI, LAP, VAI, and CVAI with CMM risk in hypertensive patients. Therefore, this study aimed to assess the association between these adiposity indicators and the risk of CMM among Chinese hypertensive patients.
UNASSIGNED: In this cross-sectional study, a total of 229,287 hypertensive patients aged 35 years and older were included from the National Basic Public Health Service Project. All participants underwent a face-to-face questionnaire survey, physical examination, and the collection of fasting venous blood samples. Multivariable logistic regression models were performed to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Receiver operating characteristic curve was utilized to evaluate the identification ability for CMM.
UNASSIGNED: After adjusting for confounders, each 1-standard deviation increase in CMI, LAP, VAI, and CVAI was associated with a 14%, 8%, 12%, and 54% increased risk of CMM, respectively. When comparing the highest quartile of these indicators with the lowest quartile, individuals in the highest quartile of CMM, LAP, VAI, and CVAI had a 1.39-fold (95% CI 1.30, 1.48), 1.28-fold (95% CI 1.19, 1.37), 1.37-fold (95% CI 1.29, 1.46), and 2.56-fold (95% CI 2.34, 2.79) increased risk of CMM after adjusting for potential confounders. Notably, a nonlinear association was observed for CMI, LAP, and VAI with the risk of CMM (all P nonlinearity < 0.001). CVAI exhibited the highest area under the receiver operating characteristic curve (AUC) among all the included adiposity indices in this analysis.
UNASSIGNED: This study indicated the significant positive association of CMI, LAP, VAI, and CVAI with the risk of CMM in hypertensive patients. Among these indicators, CVAI demonstrated the most robust performance in predicting CMM risk and may serve as a valuable tool for identifying CMM risk in Chinese hypertensive patients.

OBJECTIVE: Visceral obesity and the lifetime risk of cardiovascular disease (CVD) have received increasing attention. However, the relationship between dynamic changes in visceral obesity and CVD has not been studied. We aimed to determine the association of visceral adiposity index (VAI) transition with CVD risk.
METHODS: A total of 5395 participants were recruited in 2011-2012 and followed up until 2018 from the China Health and Retirement Longitudinal Study. The cut-off value of the VAI was obtained by the receiver-operating characteristic curve. Participants were grouped based on VAI change patterns during the follow-up period (2011-2015): the low-low group, low-high group, high-low group, and high-high group. CVD was defined as a medical diagnosis of heart disease and/or stroke. A Cox proportional hazards model was used to evaluate the correlation between VAI transition and CVD.
RESULTS: Over a median follow-up period of 7 years, 969 participants (17.9 %) developed CVD. VAI change patterns were significantly associated with CVD risk after adjustment for demographic characteristics and risk factors. The high-high group (hazard ratio (HR): 1.65, 95 % confidence interval (CI): 1.39-1.97) and the low-high group (HR: 1.29, 95 % CI: 1.04-1.61) were associated with a higher risk of CVD after adjusting for demographic characteristics and traditional risk factors compared to the low-low group, while the effect in the high-low group was not significant.
CONCLUSIONS: VAI transition was significantly associated with the risk of CVD. Monitoring the dynamics of the VAI in public health practice would help prevent CVD.

OBJECTIVE: Considering the positive association between visceral adiposity index (VAI) and type 2 diabetes mellitus (T2DM), no comprehensive assessment on the summarized and dose-response relationship between VAI and T2DM has yet been reported. Therefore, we performed a meta-analysis, including dose-response analysis, to quantitively elucidate this association.
RESULTS: MEDLINE via PubMed and Embase databases were searched for relevant articles up to December 14, 2021. Random-effects generalized least squares regression models were used to assess the quantitative association between VAI and T2DM risk across studies. Restricted cubic splines were used to model the dose-response association. A total of 9 prospective cohort studies and 5 cross sectional studies were included in our review. Based on the meta-analysis, the pooled RR of T2DM was 2.05 (95% CI 1.74-2.41) for the highest versus reference VAI category. We found that the risk of T2DM was increased by 44% (RR, 1.44; 95% CI, 1.23-1.68) with each 1-unit increment of VAI. While, we found no evidence of a nonlinear dose-response association of VAI and T2DM (Pnon-linearity = 0.428). With the linear cubic spline model, when compared to population with VAI at 0.6, for those with VAI at 2.0, the risk of T2DM was increased by 81% (RR, 1.81; 95% CI 1.55-2.12).
CONCLUSIONS: Our meta-analysis provides quantitative data suggesting that VAI is associated with an increased risk of T2DM. Public health strategies focusing on weight loss among obesity, especially the people characterized by the thin-on-the-outside--fat-on-the-inside phenotype could possibly reduce a substantial risk of T2DM.
BACKGROUND: PROSPERO CRD42022372666.