Visceral adiposity index (VAI) is a reliable indicator of visceral adiposity. However, no stu-dies have evaluated the association between VAI and DKD in US adults with diabetes. Theref-ore, this study aimed to explore the relationship between them and whether VAI is a good pr-edictor of DKD in US adults with diabetes. Our cross-sectional study included 2508 participan-ts with diabetes who were eligible for the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2018. Univariate and multivariate logistic regression were used to an-alyze the association between VAI level and DKD. Three models were used to control for pot-ential confounding factors, and subgroup analysis was performed for further verification. A tot-al of 2508 diabetic patients were enrolled, of whom 945 (37.68%) were diagnosed with DKD. Overall, the VAI was 3.36 ± 0.18 in the DKD group and 2.76 ± 0.11 in the control group. VAI was positively correlated with DKD (OR = 1.050, 95% CI 1.049, 1.050) after fully adjusting for co-nfounding factors. Compared with participants in the lowest tertile of VAI, participants in the highest tertile of VAI had a significantly increased risk of DKD by 35.9% (OR = 1.359, 95% CI 1.355, 1.362). Through subgroup analysis, we found that VAI was positively correlated with the occurrence of DKD in all age subgroups, male(OR = 1.043, 95% CI 1.010, 1.080), participants wit-hout cardiovascular disease(OR = 1.038, 95% CI 1.011, 1.069), hypertension (OR = 1.054, 95% CI 1.021, 1.090), unmarried participants (OR = 1.153, 95% CI 1.036, 1.294), PIR < 1.30(OR = 1.049, 95% CI 1.010, 1.094), PIR ≧ 3 (OR = 1.085, 95% CI 1.021, 1.160), BMI ≧ 30 kg/m2 (OR = 1.050, 95% CI 1.016, 1.091), former smokers (OR = 1.060, 95% CI 1.011, 1.117), never exercised (OR = 1.033, 95% CI 1.004, 1.067), non-Hispanic white population (OR = 1.055, 95% CI 1.010, 1.106) and non-Hipanic black population (OR = 1.129, 95% CI 1.033, 1.258). Our results suggest that elevated VAI levels are closely associated with the development of DKD in diabetic patients. VAI may be a simpl-e and cost-effective index to predict the occurrence of DKD. This needs to be verified in furt-her prospective investigations.

BACKGROUND: Obesity correlates with accelerated aging. This study aims to investigate the association between the visceral adiposity index (VAI) and accelerated aging.
METHODS: Biological aging was evaluated by phenotypic age acceleration (PhenoAgeAccel). Utilizing data from the National Health and Nutrition Examination Survey (NHANES) conducted between 1999 and 2010, we employed weighted multivariable logistic regression models, along with subgroup analysis, to examine the association between VAI and PhenoAgeAccel. Moreover, smooth curve fitting was utilized to identify potential nonlinear association, complemented by a two-piece linear regression model to investigate threshold effects.
RESULTS: Of the included 11,340 participants aged 20 years and older, the mean (95% CI) age was 46.569 (45.946, 47.191) years, and 49.189% were male. The mean (95% CI) VAI for all participants was 2.176 (2.114, 2.238), and the mean (95% CI) PhenoAgeAccel was -6.306 (-6.618, -5.994) years. In the fully adjusted model, each incremental unit increase of VAI was associated with a 0.312-year increase in PhenoAgeAccel (β = 0.312, 95% CI: 0.217, 0.408). This positive association was more statistically significant among individuals with cancer. Furthermore, a segmented association was observed between VAI and PhenoAgeAccel, with a turning point identified at 10.543. Below this threshold, VAI exhibited a positive correlation with PhenoAgeAccel (β = 0.617, 95% CI: 0.499, 0.735), while beyond it, the association became nonsignificant.
CONCLUSIONS: This study demonstrated a positive association between VAI and accelerated aging within a nationally representative population. The findings suggest that controlling adiposity may exert anti-aging effects and help prevent aging-related diseases.

The visceral adiposity index (VAI) and handgrip strength (HGS) are identified as important objectives for the prevention of illness. Nevertheless, there is limited understanding regarding the impact of the VAI and HGS on cardiometabolic multimorbidity (CMM). We aimed to ascertain the impact of the VAI and HGS on CMM among middle-aged and older people. Data spanning from 2011 to 2020 were derived from the China Health and Retirement Longitudinal Study (CHARLS). In total, 7909 individuals aged 45 years and older were included. Cox proportional hazard regression was utilized to examine the correlation among the VAI, HGS, and CMM. Throughout the 10-year follow-up, we determined that both the VAI (HR = 1.330; 95%CI = 1.179-1.500) and HGS (HR = 0.745, 95%CI = 0.645-0.861) exhibited significant associations with CMM risk. Individuals exposed to both a high VAI and low HGS were found to have higher hazards of CMM (HR = 1.377, 95%CI = 1.120-1.694) in contrast to participants exposed to one or none of these conditions. The older (HR = 1.414; 95%CI = 1.053-1.899) and male (HR = 1.586; 95%CI = 1.114-2.256) groups are more likely to experience CMM risk. Our findings suggest that both the VAI and HGS have significant effects on CMM risk. Appropriate interventions focused on vulnerable groups are recommended to prevent the incidence of CMM.

Kidney stones represent a serious medical problem, resulting from several factors such as diet, genetics, and certain medical conditions. Visceral adipose tissue has been shown in recent research to play a significant role in kidney stone formation, making it a more precise indicator than traditional obesity indicators such as body mass index. The main aim of this review is to summarize studies on visceral obesity as a predictive marker for nephrolithiasis and to highlight new mechanistic pathways such as adipokine-mediated inflammation and its impact on kidney stone formation. This review emphasizes the importance of considering visceral fat in the prevention and management of kidney stones, suggesting that targeted strategies to reduce visceral fat could decrease the incidence of kidney stones and their management costs. Further prospective studies are needed to validate these findings and propose preventive strategies based on visceral adiposity assessments.

OBJECTIVE: Previous research shows conflicting views on the relationship between obesity and osteoporosis, partly due to variations in obesity classification and the nonlinear nature of these relationships. This study investigated the association between adiposity indices and osteoporosis, diagnosed using dual-energy X-ray absorptiometry (DXA), employing nonlinear models and offering optimal thresholds to prevent further bone mineral density decline.
METHODS: In 2019, a prospective study enrolled males over 50 years and postmenopausal women. Anthropometric measurements, blood biochemistry, and osteoporosis measured by DXA were collected. Associations between adiposity indices and osteoporosis were analyzed using a generalized additive model and segmented regression model.
RESULTS: The study included 872 women and 1321 men. Indices such as abdominal volume index (AVI), visceral adiposity index (VAI), waist circumference (WC), hip circumference, body mass index (BMI), waist-to-hip ratio, and waist-to-height ratio (WHtR) were inversely associated with osteoporosis. In women, the relationship between the risk of osteoporosis and the adiposity indices was U-shaped, with thresholds of WC = 94 cm, AVI = 17.67 cm2, BMI = 25.74 kg/m2, VAI = 4.29, and WHtR = 0.61, considering changes in bone mineral density. Conversely, men exhibited a linear patterns for the inverse association.
CONCLUSIONS: The impact of obesity and adiposity on osteoporosis varies significantly between women and men. In postmenopausal women, the relationship is nonlinear (U-shaped), with both very low and very high adiposity linked to higher osteoporosis risk. In men over 50, the relationship is linear, with higher adiposity associated with lower osteoporosis risk. The study suggests that maintaining specific levels of adiposity could help prevent osteoporosis in postmenopausal women.

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.